HomeMy WebLinkAboutMemo - Mail Packet - 4/6/2021 - Memorandum From Janet Freeman Re: Equity Indicators Final Report
Social Sustainability
222 Laporte Ave.
PO Box 580
Fort Collins, CO 80522
970.221.6758
MEMORANDUM
DATE: March 31, 2021
TO: Mayor Wade Troxell & City Councilmembers
THRU: Darin Atteberry, City Manager
Kyle Stannert, Deputy City Manager
Jacqueline Kozak-Thiel, Chief Sustainability Officer
Beth Sowder, Social Sustainability Department Director
FROM: Janet Freeman, on behalf of the Equity Indicator Core Team*
CC: Kelly DiMartino, Deputy City Manager
Teresa Roche, Chief Human Resource Officer
RE: Equity Indicators Final Report
The purpose of this memo is informational on the subject of the final equity indicators report (attached),
as well as next steps related to integrating the work into City processes and programs.
Background
In alignment with Council’s adopted priority of Equity and Inclusion and one of the identified deliverables
for this priority, the equity indicators report provides a baseline analysis of disparity gaps in the
community and in some aspects of the City’s service delivery. The work was funded as a midcycle offer in
2019, and the chosen vendor, the CUNY Institute for State and Local Governance (ISLG), began work in
2020 and has now completed their final report. The project was funded with $60,00 from the City and
$20,00 additional dollars donated by the Bohemian Foundation. Waterpik also donated $10,000, which is
being used for ISLG to benchmark comparison cities and develop a suite of materials to help guide
interpretation of findings.
ISLG led their work with a guiding principle of leading with racial equity, in accordance with Council’s
adopted strategic objective in Neighborhood Livability and Social Heath 1.4: Advance equity for all,
leading with race, so that a person’s identity or identities is not a predictor of outcomes.
Council has received updates and provided guidance on the project at the May 19th, 2020 and December
8, 2020 work sessions (attached), as well as during the Community Impact Ad-Hoc Committee meetings
on September 28, 2020, and on January 25, 2021. Examples of how Council feedback influenced the
report and overall project include incorporating it into the landscape disparity analysis, reviewing the
larger pool of indicators as well as providing input on deeper-dive analysis pertaining to some topic areas.
Project Objectives
The project’s objectives were to supply the City with a baseline report of equity gaps, disaggregated by
race and other historically underserved community members. This effort aligns to the Government
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Alliance on Race and Equity (GARE) framework and has been undertaken by a few cities. The report
contains both a landscape disparity analysis section and a section highlighting equity indicators prioritized
by community members.
A subset of these equity indicators—including ones prioritized by community members—will be entered
into a public-facing dashboard to support data-informed policy-making, program design, budgeting and
partnerships while also increasing transparency and accountability—all of which also align to GARE’s
logic model for cities working to advance equitable outcomes for all. The City will track these indicators
over time to assess progress and prioritize efforts.
Methodology
ISLG conducted extensive background research and a data diagnostic to establish what work had been
done in the area, and the availability and reliability of different sources of data. ISLG used this to conduct
a preliminary set of analyses. Internal staff and community partners such as Poudre School District
(PSD), Larimer County, the Health District of Northern Larimer County, Colorado State University (CSU),
and other stakeholders were included as information providers during this phase.
This analysis formed the basis for a survey that enabled community members to:
• Rank the measures they believe to be most important for the City to track
• Identify gaps and suggest new measures to fill them; and
• Provide information on potential data sets that could be used to shed light on disparities
impacting different communities.
ISLG also hosted nine focus groups where more information was sought to better understand gaps in
equity and experiences of specific underserved communities. In total, ISLG hosted 14.5 hours of listening
with 35 community members during these sessions. ISLG will ensure that all community members who
participated in listening sessions will receive information about where to find the report.
Once ISLG explored additional data sets and measures suggested through the survey responses and
focus groups, they were able to compile and analyze a final list of measures across 10 domains where
disparities could be examined (i.e., where data were disaggregated by race and ethnicity, or by one or
more other identity). Measures selected as potential indicators also met the criteria of having sufficient
data to enable tracking disparities over time (i.e., data are collected and updated on a regular basis), in
addition to being prioritized by community members. In addition, measures include topic areas that are
under direct City purview and those where the City is partnered with local institutions to address systemic
inequities.
Final Deliverable
The final deliverable for this project is the attached report that provides a more detailed explanation of
methodology and guiding frameworks, including information on how community was engaged; the
disparity landscape analysis; and a final collection of selected indicators.
City staff have also created a guide to help with interpretation of the report (attached).
Next Steps
• Q1: ISLG benchmarking comparison cities and crafting materials to help guide report interpretation
• Q1: Staff developing internal and external communication plans
• Q1 - Q2: Staff developing equity dashboard
• Q3: Beginning root cause analysis work
• Q3 – Q4: Integrate indicator work into Budgeting for Outcomes for future cycles
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• 2022 and beyond: review and revise indicators
Attachments
• Equity Indicators Report
• Interpretation Guide
• Work Session Summaries
*Equity Indicator core team members: Sierra Anderson, DeAngelo Bowden, Leo Escalante, Janet
Freeman, Nick Heimann, Angela Peña, and Victoria Shaw. Executive sponsor: Jackie Kozak-Thiel.
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EQUITY INDICATORS
The City of Fort Collins supports equity for all, leading with race. As part of its effort to advance
equitable outcomes, the City selected the CUNY Institute for State and Local Governance
(ISLG) to lead its Equity Indicators project and establish a framework for measuring and
understanding the inequities that exist in Fort Collins and how they change over time.
Equity indicators are one tool local governments can use to measure and track the experiences
of equality among community members to more proactively address systems that perpetuate
racism and/or oppression. Reducing inequities can improve opportunities for everyone.
DIFFERENT GROUPS EXPERIENCE
OUR COMMUNITY DIFFERENTLY.
HOW WERE THE CITY’S
EQUITY INDICATORS
DEVELOPED?
ISLG developed an analysis of
disparities in Fort Collins and a
final set of Equity Indicators.
The report contains more detailed
information on the steps taken
and the findings, including:
• Background research
• Data gathered from partner
institutions
• Landscape analysis
• Survey and focus groups
• Community prioritized list of
indicators
KEY INFORMATION
In this project, ISLG collected and analyzed data
disaggregated by race, ethnicity, and other demographic
factors to examine the broad landscape of disparities in
outcomes and perspectives in the Fort Collins area. ISLG
engaged with community members to identify a set of Equity
Indicators that will be used to measure and track disparities
going forward.
HOW WILL THE CITY USE THE DATA?
• While the Equity Indicators themselves cannot directly
address inequities, they will inform the City’s equity work
moving forward, providing critical information to guide
decisions about investments and policy development.
• The data provide a starting point for the City to pursue
partnerships with institutions for systems change and
deepen community engagement with communities most
impacted.
• The City will share the indicators on a public dashboard to
assess progress and prioritize efforts.
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FAQ FREQUENTLY ASKED QUESTIONS
1. IS EQUITY THE SAME AS EQUALITY?
Equity is not the same as equality. Whereas
equality as a strategy means giving everyone
the same thing, equity’s approach addresses
disparity gaps based on historical and present-
day injustices. Equity focuses on ensuring
people’s identities are no longer a predictor of
life’s outcomes.
2. WHY ARE INDICATORS IMPORTANT?
These indicators help us better understand
who is faring well in our community, and who
isn’t, compared to the overall average. And
because the community let us know which
ones are of the highest priority, the City can
better align its equity, diversity and inclusion
efforts to create more meaningful and
sustainable change.
3. I NOTICED SOME FINDINGS DO NOT
TEST FOR STATISTICAL SIGNIFICANCE,
WHY?
Throughout this project, the City sought to
support inclusion of all people in Fort Collins.
As a result, some statistical testing could not
be conducted because of smaller population
sizes or else the data source itself was pulled
from percentages versus raw numbers.
This does not discredit what the data is
demonstrating in terms of disparity gaps.
4. IS THE CITY RESPONSIBLE FOR
ALL THESE INDICATORS?
While the City is able to influence some
indicators, others are outside of city control.
These data may inform new opportunities or
potential partnerships. Both are important to
document and track in order to successfully
dismantle systems that lead to inequitable
outcomes, both locally and from a regional
perspective.
WHAT ARE THE EQUITY INDICATORS FOR FORT COLLINS?
ISLG engaged our community to prioritize which indicators the City should track, a subset of which
will be included in a public-facing equity dashboard. All fall in the following 10 categories, with
indicators for each listed in the report:
1. Housing
2. Economic Opportunity
3. Education
4. Criminal Justice & Public Safety
5. Civic Engagement
6. Environmental Justice
7. Services
8. Public Health
9. Social Inclusion
10. Transportation
This initiative evaluated a wide range of data. While some indicator data represent Fort Collins’
population specifically, data were also gathered from partner institutions such as Larimer County,
Poudre School District and Health District, and may represent varying geographic areas.
21-23094Auxiliary aids and services are available for persons with disabilities. V/TDD: 711
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CUNY Institute for State & Local Governance
Fort Collins
Equity Indicators
Final Report - March 2021
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Letter from Mayor Wade Troxell and City Manager Darin Atteberry
Fort Collins strives to be a diverse, inclusive and equitable community where all people feel a
sense of belonging regardless of who they are. We believe an equitable community means
everyone who lives here has the same opportunity to experience the joys and delights of an
accepting community. We are a community committed to equity for all.
In 2019, City Council adopted Equity and Inclusion as a Council priority and supported the
funding of the Equity Indicators Project which is aligned with the Government Alliance on Race
and Equity (GARE) roadmap. That same year, Council also adopted an updated Strategic Plan,
with an objective to advance equity for all, leading with race, so that a person’s identity or
identities is not a predictor of outcome. In 2020, the City worked to develop the Fort Collins
Equity Indicators Project to guide the way forward.
Equity indicators will inform the City’s work moving forward, providing critical information to
guide decisions about the allocation of resources and policy development. The hope is that our
community partners will find both the report and dashboard helpful as we all work toward
addressing systemic impacts needed to make Fort Collins an equitable and inclusive community
for all.
We invite you to read the report and use it in your own work as we look to strengthen our
community’s commitment to advancing justice, fairness and equity for all who live here.
Sincerely,
Wade Troxell Darin Atteberry
Mayor City Manager
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Executive Summary
Overview
The City of Fort Collins supports equity for all, leading with race. As part of its effort to advance equitable
outcomes, the City selected the CUNY Institute for State and Local Governance (ISLG) to lead its Equity
Indicators project and establish a framework for measuring and understanding the inequities that exist in
Fort Collins and how they change over time. In this project, ISLG collected and analyzed data
disaggregated by race, ethnicity, and other demographic factors to examine the broad landscape of
disparities in outcomes and perceptions in Fort Collins and worked closely with the City and community
to identify a pool of Equity Indicators that can be used to track progress in reducing key disparities
moving forward and provide a springboard for deeper exploration of root causes and potential solutions.
While Equity Indicators themselves cannot directly address inequities, they will inform the City’s equity
work moving forward, providing critical information to guide decisions about the allocation of resources
and policy development. The City will also share them on a public dashboard and update them on an
ongoing basis to enable the public to track changes in outcomes and perceptions, increasing transparency
and accountability and giving communities tools to share in successes and identify ways the City can
better support and partner with them to create change.
ISLG’s work relied on a six-phase process to develop a multi-faceted analysis of the landscape of
disparities in Fort Collins and a final pool of Equity Indicators consisting of the following:
Background research designed to understand current priorities, both in and outside of
government and some of the important inequities that have come to light in research to date;
Data diagnostic to see what local data are available, where, and of what quality;
City and County staff discussions to further understand different areas and what data might be
available to measure disparities;
Preliminary landscape analysis which used what had been learned to collect and analyze data for a
range of measures across the priority areas identified;
Community input to see whether important areas were missing, solicit suggestions for additional
measures and data sources, and obtain feedback on which measures should be selected as Equity
Indictors; and
Final landscape analysis including additional measures and analyses and identifying those selected
as potential Equity Indicators based on the feedback and suggestions received through
community and other stakeholder input.
The landscape analysis explores the presence or absence of disparities on 114 measures across 10
domains: Civic Engagement, Criminal Justice and Public Safety, Economic Opportunity, Education,
Environmental Justice, Housing, Public Health, Services, Social Inclusion, and Transportation. Given the
City’s focus on leading with race, measures were generally not included if some form of disaggregation by
race and/or ethnicity was not possible. For select measures identified as important through stakeholder
and/or community input, data were included if they did not allow disaggregation by race/ethnicity if they
disaggregated by another important characteristic (e.g., income, neighborhood). For all measures, the
presence or absence of disparities was assessed by comparing the outcome or perception for each group
to the overall outcome or perception.
It is important to note that not all of the measures included within these areas are directly under the
purview of the City. Some fall to the County, or to others, and many are complex issues that have multiple
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root causes and multiple factors that play a role in maintaining disparities. These will require multi-
faceted efforts to address them, and require partnership and coordination among multiple entities inside
and outside of government.
It is also important to note that the data included in this report were collected prior to the COVID-19
pandemic. COVID-19 has had a devastating impact on communities nationwide, particularly on
communities of color and other marginalized communities. These impacts will need to be considered in
developing solutions to the disparities reported here, as it is very possible that many have worsened, and
that new disparities have arisen.
Findings
Racial and ethnic disparities1 were found in all areas and on just over half (54%) of the measures where
racial/ethnic comparisons were possible in total, although the groups were not always consistent. ISLG
also found differences by income, gender, sexual orientation, disability status, educational attainment,
household composition, and neighborhood.
Across areas, Asians or Pacific Islanders had more positive outcomes or perceptions compared to overall
on 26% of measures where they were able to be examined, the highest percentage of the groups,
although they also had more negative outcomes or perceptions on 10% (see Table i and Figure i). Whites
had more positive outcomes or perceptions on 15% of measures, but did not have any measures with
more negative outcomes or perceptions. By contrast, Hispanics/Latinx had more negative outcomes or
perceptions compared to overall on 62% of measures where they were able to be examined, the highest
of the groups, and did not have more positive outcomes or perceptions on any of the measures examined
in the landscape analysis.
Table i. Number (percentage) of measures with more positive, equivalent, or more negative outcomes or
perceptions than the overall outcome or perception for each racial and ethnic grouping included
Racial/ethnic group
Number (%) of
measures with
positive outcomes or
perceptions
Number (%) of
measures with
equivalent outcomes
or perceptions
Number (%) of
measures with
negative outcomes
or perceptions
Non-Hispanic White 15 (16%) 81 (84%) 0 (0%)
Hispanic/Latinx 0 (0%) 17 (38%) 28 (62%)
Asian or Pacific Islander 10 (26%) 25 (64%) 4 (10%)
Black 3 (8%) 20 (50%) 17 (43%)
Native American 3 (9%) 21 (60%) 11 (31%)
Other 2 (6%) 16 (52%) 13 (42%)
Non-Hispanic, Non-White 0 (0%) 8 (100%) 0 (0%)
Hispanic and/or Other Race 1 (2%) 33 (61%) 20 (37%)
White, including Hispanic 0 (0%) 6 (86%) 1 (14%)
1 For the purposes of this report, disparities were defined as differences between the finding for a particular group
and the overall finding across groups that were either statistically significant or were larger than our pre-determined
thresholds (see Landscape Analysis Methodology).
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Figure i. Percentage of measures with more positive (positive numbers) or more negative (negative
numbers) outcomes or perceptions than the overall outcome or perception for each racial and ethnic
grouping included
The percentage of measures where racial/ethnic differences were found varied considerably by domain
from a low of 24% of measures allowing racial/ethnic comparisons for Public Health to 100% of measures
allowing racial/ethnic comparisons for Criminal Justice and Public Safety (see Table ii).
Table ii. For each domain examined, the number of measures overall, the number where racial/ethnic
comparisons could be made, and, of those, the number and percentage where racial/ethnic differences
were found.
Domain
Number of
Measures
Number Allowing Race/
Ethnicity Comparisons
Number (%) with
Racial/Ethnic Differences
Civic Engagement 7 6 4 (67%)
Criminal Justice and Public Safety 9 9 9 (100%)
Economic Opportunity 17 15 9 (60%)
Education 15 15 11 (73%)
Environmental Justice 5 5 2 (40%)
Housing 9 9 5 (55%)
Public Health 17 17 4 (24%)
Services 18 11 6 (54%)
Social Inclusion 8 7 3 (43%)
Transportation 9 9 3 (33%)
Total 114 103 56 (54%)
When looking at the domains where each racial and ethnic group fared the best, non-Hispanic whites and
Asians or Pacific Islanders did particularly well in Education, where they had more positive outcomes or
perceptions on nine of 15 and five of 13 measures, respectively (see Table iii). Interestingly, Education
was also where Asians or Pacific Islanders had the highest number of negative outcomes or perceptions,
but it should be noted that this represented only two measures, and this group had more negative
16%
0%
26%
8%9%6%
0%2%0%0%
-62%
-10%
-43%
-31%
-42%
0%
-37%
-14%
-70%
-60%
-50%
-40%
-30%
-20%
-10%
0%
10%
20%
30%
40%
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outcomes or perceptions on only four measures in total across domains. For all other racial and ethnic
group groups, there were no domains with more than one measure with a positive outcome or
perception.
In terms of where groups fared the worst, Education was a clear area of disparities for Hispanics/Latinx
and Native Americans who each had their highest number of negative outcomes or perceptions within
this domain. By contrast, Criminal Justice and Public Safety was the source of the greatest number of
disparities for Blacks who had more negative outcomes or perceptions on six of seven measures. Hispanic
and/or other race individuals (i.e., people of color) fared the worst in Services, where many of the
measures able to be included did not allow for further disaggregation by race and ethnicity so it was not
possible to obtain a more nuanced view of disparities by group. Lastly, individuals from other racial and
ethnic groups fared the worst in Economic Opportunity, where they had more negative outcomes or
perceptions on three of seven measures.
Table iii. Domains with the highest number of measures with more positive outcomes or perceptions and
more negatives outcomes and perceptions compared to the overall outcome or perception for each racial
and ethnic grouping included
Racial/ethnic group
Domain with the highest number of
more positive measures
Domain with the highest number of
more negative measures
Non-Hispanic White Education (9 of 15) n/a†
Hispanic/Latinx n/a Education (10 of 15)
Asian or Pacific Islander Education (5 of 13) Education (2 of 13)
Black Services (1 of 3), Education (1 of
14), Transportation (1 of 2) Criminal Justice (6 of 7)
Native American Criminal Justice (1 of 6), Education
(1 of 11), Transportation (1 of 2) Education (6 of 11)
Other Education (1 of 11), Housing (1 of
5) Economic Opportunity (3 of 7)
Non-Hispanic, Non-White n/a n/a
Hispanic and/or Other Race Social Inclusion (1 of 6) Services (5 of 7)
White, including Hispanic n/a Criminal Justice (1 of 4)
Equity Indicators
ISLG used community and other stakeholder input to select a pool of 72 potential Equity Indicators from
the measures included in the final landscape analysis; the City will identify final Equity Indicators from
within the larger pool. The breakdown across domains was as follows:
Civic Engagement (3 indicators)
Engagement with Government 1 indicator
Engagement with Community 2 indicators
Criminal Justice and Public Safety (8 indicators)
Law Enforcement 5 indicators
Incarceration and Community Supervision 2 indicators
Perceptions of Safety 1 indicator
Economic Opportunity (8 indicators)
Poverty and Food Security 3 indicators
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Income 2 indicators
Employment 1 indicator
Business Ownership 1 indicator
Childcare 1 indicator
Education (13 indicators)
Academic Achievement 5 indicators
Staff Representation 2 indicators
School Connections 1 indicator
Barriers to Academic Success 3 indicators
Educational Attainment 2 indicators
Environmental Justice (2 indicators)
Pollutants 2 indicators
Housing (8 indicators)
Housing Affordability 5 indicators
Homelessness 2 indicators
Neighborhood 1 indicator
Public Health (10 indicators)
Access to Care 6 indicators
Physical Health 1 indicator
Mental Health 3 indicators
Services (10 indicators)
Essential Services 8 indicators
Parks and Recreation 2 indicators
Social Inclusion (5 indicators)
Community 4 indicators
City Inclusiveness 1 indicator
Transportation (5 indicators)
Commuting 1 indicator
Personal Transportation 2 indicators
Public Transportation 2 indicators
Next Steps
This report provides baseline findings for the Fort Collins Equity Indicators project as a whole; findings for
the final Equity Indicators will also be presented on a public dashboard developed and maintained by the
City of Fort Collins. The City will update the findings for these indicators on an ongoing basis moving
forward in order to assess progress towards increasing equity within and across the 10 domains. The City
will also be using the findings from the Equity Indicators and the Landscape Analysis more broadly to
inform decision-making about policy and practice, and guide the allocation of resources by identifying
areas where there are greater opportunities for investment and growth. The City will also be beginning
the work of conducting root cause analyses to uncover the drivers behind different disparities and work
with the community and other stakeholders to develop targeted solutions. ISLG will further support the
City in its work by collecting comparison data for other jurisdictions at the local, state, or national level,
where possible.
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Contents
Letter from Mayor Wade Troxell and City Manager Darin Atteberry .............................................................. i
Executive Summary ........................................................................................................................................... ii
Overview ....................................................................................................................................................... ii
Findings ........................................................................................................................................................ iii
Equity Indicators ........................................................................................................................................... v
Next Steps .................................................................................................................................................... vi
Introduction ..................................................................................................................................................... 1
Key Terms and Definitions ............................................................................................................................... 3
What is Equity? ............................................................................................................................................ 3
What are Indicators? ................................................................................................................................... 3
What are Equity Indicators? ........................................................................................................................ 3
Process of Developing Landscape Analysis and Equity Indicators .................................................................. 4
Background Research and Data Diagnostic ................................................................................................. 4
City and County Stakeholder Discussions ................................................................................................... 4
Preliminary Landscape Analysis ................................................................................................................... 4
Community Engagement ............................................................................................................................. 5
Landscape Analysis Methodology .................................................................................................................. 11
Structure of Landscape Analysis ................................................................................................................ 11
Data and Sources ....................................................................................................................................... 12
How Information is Reported .................................................................................................................... 14
Landscape Analysis Findings Overview .......................................................................................................... 17
Overall Findings by Race and Ethnicity ...................................................................................................... 17
Racial and Ethnic Disparities by Domain ................................................................................................... 18
Civic Engagement ........................................................................................................................................... 21
Engagement with Government ................................................................................................................. 22
Engagement with Community ................................................................................................................... 25
Criminal Justice and Public Safety .................................................................................................................. 28
Law Enforcement ....................................................................................................................................... 29
Incarceration and Community Supervision ............................................................................................... 33
Perceptions of Safety ................................................................................................................................. 35
Economic Opportunity ................................................................................................................................... 36
Poverty and Food Security ......................................................................................................................... 37
Income ....................................................................................................................................................... 42
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Employment ............................................................................................................................................... 48
Business Ownership ................................................................................................................................... 53
Childcare .................................................................................................................................................... 54
Education ....................................................................................................................................................... 58
Academic Achievement ............................................................................................................................. 59
Staff Representation .................................................................................................................................. 65
School Connections ................................................................................................................................... 66
Barriers to Academic Success .................................................................................................................... 69
Educational Attainment ............................................................................................................................. 72
Environmental Justice .................................................................................................................................... 75
Pollutants ................................................................................................................................................... 76
Climate Vulnerability Factors .................................................................................................................... 78
Housing ........................................................................................................................................................... 80
Housing Affordability ................................................................................................................................. 81
Homelessness ............................................................................................................................................ 87
Neighborhood ............................................................................................................................................ 90
Public Health .................................................................................................................................................. 92
Access to Care ............................................................................................................................................ 93
Physical Health ......................................................................................................................................... 105
Mental Health .......................................................................................................................................... 110
Services ......................................................................................................................................................... 117
Essential Services ..................................................................................................................................... 118
Parks and Recreation ............................................................................................................................... 127
Social Inclusion ............................................................................................................................................. 133
Community .............................................................................................................................................. 134
City Inclusiveness ..................................................................................................................................... 138
Transportation ............................................................................................................................................. 140
Commuting .............................................................................................................................................. 141
Personal Transportation .......................................................................................................................... 141
Public Transportation .............................................................................................................................. 145
Equity Indicators .......................................................................................................................................... 151
How Indicators Were Selected ................................................................................................................ 151
Final Equity Indicators ............................................................................................................................. 151
Next Steps .................................................................................................................................................... 154
Appendix A ................................................................................................................................................... 155
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Survey Participant Details ........................................................................................................................ 155
Appendix B ................................................................................................................................................... 158
Additional Findings from Focus Groups .................................................................................................. 158
Appendix C ................................................................................................................................................... 160
List of All Measures Included in the Landscape Analysis ........................................................................ 160
About ............................................................................................................................................................ 165
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Introduction
The City of Fort Collins supports equity for all, leading with race. As part of its effort to advance equitable
outcomes, the City selected the CUNY Institute for State and Local Governance (ISLG) to lead its Equity
Indicators project and establish a framework for measuring and understanding the inequities that exist in
Fort Collins and how they change over time. In this project, ISLG collected and analyzed data
disaggregated by race, ethnicity, and other demographic factors to examine the broader landscape of
disparities in outcomes and perceptions in Fort Collins and worked closely with the City and community
to identify a pool of Equity Indicators that can be used to track progress in reducing key disparities
moving forward and provide a springboard for deeper exploration of root causes and potential solutions.
While the Equity Indicators themselves cannot directly address inequities, they will inform the City’s
equity work moving forward, providing critical information to guide decisions about the allocation of
resources and policy development. The City will also share them on a public dashboard and update them
on an ongoing basis to enable the public to track changes in outcomes and perceptions, increasing
transparency and accountability and giving communities tools to share in successes and identify ways the
City can better support and partner with them to create change.
ISLG’s work relied on a six-phase process to develop a multi-faceted analysis of the landscape of
disparities in Fort Collins and a final pool of Equity Indicators (see Figure 1). Throughout this process, ISLG
worked closely with an internal City equity team comprised of an executive sponsor and eight
representatives from different departments. The members of this team served as thought partners on
the work, and provided feedback, guidance, and support throughout the process, in addition to
connecting the research team to stakeholders from different departments and organizations.
Figure 1. ISLG Phases of Work for the Fort Collins Equity Indicators
In this report, we describe the process and methodology for developing the landscape analysis and
selecting Equity Indicators across the six phases as follows:
Background research designed to understand current priorities, both in and outside of
government and some of the important inequities that have come to light in research to date;
Data diagnostic to see what local data were available, where, and of what quality;
Background
Research
Data
Diagnostic
City and
County
Stakeholder
Discussions
Preliminary
Landscape
Analysis
Community
Input
Final
Landscape
Analysis and
Equity
Indicators
Partnership with Internal City Equity Team
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City and County staff discussions to further understand different areas and what data might be
available to measure disparities;
Preliminary landscape analysis which used what we had learned to collect and analyze data for a
range of measures across the priority areas identified;
Community input to see whether important areas were missing, solicit suggestions for additional
measures and data sources, and obtain feedback on which measures should be selected as Equity
Indictors; and
Final landscape analysis including additional measures and analyses and identifying those selected
as potential Equity Indicators based on the feedback and suggestions received through
community and other stakeholder input.
We then present findings for all measures. For the measures that are ultimately selected as Equity
Indicators, these findings can serve as the baseline against which progress will be assessed.
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Key Terms and Definitions
What is Equity?
The City of Fort Collins defines equity as when a person's identity or identities, or where they live, does
not negatively affect their outcomes in life. Achieving equity means recognizing that not everyone starts
from the same place, so leveling the playing field might involve providing different resources to different
people or communities.
What are Indicators?
Indicators are ways to assess things. They often serve as proxies for abstract, difficult-to-define concepts
that have no single definition or single way to measure them such as Justice or Economic Opportunity.
Looking at Justice, or even Criminal Justice, there is no single definition or way to establish when it has
been achieved. But some things you might look at to assess how a jurisdiction is doing in terms of
Criminal Justice are incarceration rates, arrest rates, or diversion rates. Within Economic Opportunity, you
might look at things like poverty rates, household income, or unemployment rates. All of these are social
indicators that look at how people overall are doing within each area.
What are Equity Indicators?
While social indictors in themselves are incredibly important measures for assessing overall conditions
and outcomes, equity indicators go a step further and compare how different groups are doing. So rather
than just looking at incarceration, for example, you could look at how the incarceration rate differs for
different groups, like different racial and ethnic groups, or people with and without a mental health
condition. Rather than looking just at income, you might look at income for different genders, or people
with different levels of educational attainment.
Table 1. Examples of indicators and equity indicators within three domains or concepts
Domain Sample Indicator Sample Equity Indicator
Criminal Justice Incarceration rates Disparities in incarceration rates for different racial and
ethnic groups
Economic
Opportunity
Personal income Disparities in income for men, women, and nonbinary
people
Services Sidewalk accessibility Disparities in sidewalk accessibility for people with and
without physical disabilities
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Process of Developing Landscape Analysis and Equity Indicators
Background Research and Data Diagnostic
The purpose of background research was to gain a deeper understanding of the local context, including
key inequities, the communities that are most affected by them, and the steps that the City is taking to
address them. The data diagnostic, in turn, was designed to explore the data available to measure those
key inequities, including what local data exist, where, and of what quality. In order to establish whether
potential measures drawing on the different sources identified could be tracked over time, ISLG also
examined whether data are collected on an ongoing basis and, if so, how frequently.
Background research began with gathering publicly available reports and other information on equity
research and disparity-reduction efforts in Fort Collins. This was supplemented with reports and
resources provided by the internal City equity team. Additional reports and resources referenced in these
sources were then gathered throughout the review process. Researchers took systematic notes
throughout their review of materials, and then analyzed their notes to pull out key themes and domains,
in addition to lists of potential measures to include within them. ISLG then reviewed the initial list of
domains with the internal City equity team and made revisions based on the feedback from the group.
During these conversations, the City team made additional suggestions for specific measures, and for City
and County departments, agencies, and individual staff members to reach out to in order to get more
information on domains and measures of interest.
Once the domains had been revised, ISLG began the data diagnostic. ISLG first established the types of
measures within these domains that could be obtained from annually collected federal sources that
provide local data. For example, local Fort Collins data on a range of topics can be obtained from the U.S.
Census Bureau’s American Community Survey (ACS). Next, the research team began the process of
searching for publicly available data from local sources, such as the Poudre School District, that could
shed light on the domains identified. This also included noting where data could be pulled directly from
existing reports and other materials that had been obtained as part of the background research process.
This work laid the initial foundation for the preliminary landscape analysis, which was built upon through
conversations with City and County stakeholders.
City and County Stakeholder Discussions
To gain more information about the key domains, ISLG had a series of conversations with City and County
stakeholders. To facilitate these conversations, the internal City equity team connected ISLG to individuals
within the City and County departments and agencies identified during background research discussions.
ISLG research staff then had conversations with those individuals and others within their departments to
learn more about the domains, what disparities exist within them, potential metrics to assess, and what
data might be available to measure them. In addition to providing critical contextual information about
each area and the work they are engaged in, stakeholders shared information on data sources, reports,
and resources, and in some cases were able to directly provide aggregate data. They also pointed us to
additional efforts being conducted by others working on similar issues to their own. In total, ISLG spoke
with 42 individuals across 25 departments, agencies, and institutes, including two non-governmental
institutes connected to Colorado State University.
Preliminary Landscape Analysis
ISLG incorporated what was learned during the initial phases of work into a preliminary analysis of the
disparity landscape drawing on measures identified during each phase. The preliminary landscape
analysis included raw data on the frequencies and rates of different outcomes and perceptions for
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different groups, focusing largely on different racial and ethnic groups to align with the designation of
race as the priority by the City of Fort Collins. These analyses provided descriptive comparisons of the
findings for each group to overall or average outcomes and perceptions, but did not test for statistical
significance.
The preliminary landscape analysis included 78 measures across nine domains: City Services, Criminal
Justice and Public Safety, Economic Opportunity, Education, Environmental Justice, Housing, Public
Health, Social Inclusion and Civic Engagement, and Transportation (see Landscape Disparity Analysis
Methodology). These domains were retained in later stages of the work, with the exception that Social
Inclusion and Civic Engagement were split into their own categories, and City Services was renamed
simply Services. ISLG used these domains and measures as the basis for our community engagement,
soliciting input on whether the most important areas and issues had been captured and what should be
tracked by the City moving forward. Within each of the key domains, additional measures suggested
through stakeholder and community input were added as possible based on data availability.
Community Engagement
Overview
The primary purpose of community engagement was to solicit input on big-picture domains and specific
measures that should be explored and/or selected as Equity Indicators, as well as information on where
we might find additional data. We were also interested in hearing about how disparities impact different
communities, especially those that are typically underrepresented. In order to ensure input from as many
communities as possible, and particularly to try to ensure representation from underrepresented groups,
we used a multi-method engagement strategy that included the following key components:
1. Multi-modal outreach
2. Online and hard copy surveys in multiple languages
3. Focus groups
Outreach was conducted online through email and social media, and in person through hard-copy flyers
distributed in select locations or communities where internet access or comfort using the internet was
thought to be lowest. Outreach was conducted by City of Fort Collins staff, ISLG staff, and a community
outreach specialist with deep roots in the Fort Collins community who had partnered with the City of Fort
Collins on previous outreach and engagement efforts.
As in additional mechanism for sharing information about the project to as broad an audience as possible,
a City of Fort Collins OurCity page was set up that contained background information in four languages—
English, Spanish, Mandarin, and Arabic—an informational video presentation, links to the different
versions of the surveys, and information on the focus groups. The page also included contact information
for project staff from the City and ISLG, and gave visitors the option of signing up to receive updates on
the project in future.
The primary community input methods were the surveys and focus groups, more information on which
follows below.
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Surveys
Design
In recognition of the fact that time might be limited for some people who would want to provide input,
two versions of the survey were created: one approximately 5 minutes long and the other approximately
20 minutes long. Surveys were created in English and then translated into Spanish, Mandarin, and Arabic.
The surveys were directly available online in English, Spanish, and Mandarin, from October 8th through
November 1st, 2020; those wishing a copy in Arabic were directed to contact ISLG staff, as it could not be
accommodated by the survey platform.2 The 5-minute long survey was also included on the back of all
hard-copy flyers with an address to which responses could be sent.3 All surveys asked respondents to
provide demographic information so ISLG would be able to ascertain whether input was provided by a
diverse pool that included underrepresented populations.
Five-Minute Version
The shorter version of the survey focused on obtaining feedback on the broad domains included in the
preliminary landscape analysis. Respondents were asked to do the following:
1. Rank the domains in terms of their importance to living and working in Fort Collins in general,
and then rank them specifically for increasing equity in Fort Collins (i.e., where there are large
disparities that should be a focus of the City moving forward);
2. Identify any important areas that were missing, and provide information on how those areas
ranked in terms of importance overall and importance to increasing equity; and
3. Share any information on data sources that might shed light on the domains of interest,
specific measures, or communities that experience disparities.
Twenty-Minute Version
In addition to the questions from the 5-minute version of the survey, the 20-minute version asked
respondents to do the following:
1. Identify the characteristics by which people are most likely to experience inequity within Fort
Collins (e.g., age, race, ethnicity, LGBTQIA+ status, religion) and any sources of data that might
measure them; and
2. Select the measures within each of the domains identified at that time that they thought should
be chosen as Equity Indicators for the City to track moving forward, and identify any important
measures that were missing and potential data sources that might measure them.
Participants
A total of 73 community members completed the survey. The bulk of respondents (54) completed the 5-
minute version, while 19 completed the 20-minute version. One of the goals of community outreach was
to invite participation of typically underrepresented communities, particularly among racial and ethnic
groups. The racial and ethnic breakdowns of survey respondents suggests our efforts were successful in
reaching a diverse group of Fort Collins residents: roughly two-thirds of the survey respondents identified
as non-Hispanic white (67.1%) compared to 80% of the general Fort Collins population, while roughly a
third identified as a race/ethnicity other than non-Hispanic white. The sample was diverse in numerous
other ways (see Appendix A for full details on the demographic breakdowns of survey respondents). One
in ten participants were born in a country other than the United States, and 11% speak a language other
than English at home (either alone or in addition to English). Ages ranged from 17 to 64, and roughly two
2 No requests for the Arabic-language version were received.
3 No hard copy responses were received.
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thirds of respondents identified as women (69.9%). In terms of sexual orientation and gender identity,
16.5% of survey respondents identified LGBQ+, while one respondent identified as transgender. Almost
one quarter of respondents (23.3%) identified as having a disability or chronic medical condition, with
similar percentages reporting having physical/medical conditions as cognitive/mental health conditions.
The sample was highly educated, with almost three quarters of respondents having a bachelor’s degree
or higher (71.3%) and 16.4% currently attending a college or university in Fort Collins. Average tenure in
Fort Collins was 13.5 years.
Domain Rankings
Participants ranked the domains, or broad areas, around (i) their importance to living and working in Fort
Collins in general (general importance rank), and (ii) the extent to which there are large disparities that
they thought should be a focus of the City’s equity work (unequal outcomes rank). To determine the
ranks for each area, we calculated the median rank of each broad area separately for the general
importance rank and unequal outcomes rank, and used the average rank to break any ties where the
median rank was the same. It is important to keep in mind that using forced-rank choices means that
responses represent relative importance, not necessarily importance in of itself. For example, if forced to
choose, a person might rank economic opportunity over education or criminal justice, but find all three to
be important areas of life where disparities should be addressed.
The same three broad areas were ranked in the top three for both importance of measuring the broad
area and unequal outcomes: housing, economic opportunity, and education. This suggests agreement
among respondents that housing, economic opportunity, and education are both primary in their
importance to life in Fort Collins and need the most work to be done towards increasing equity.
Public health and public safety were ranked fourth and fifth on general importance; however, in the
unequal outcomes ranks, social inclusion and criminal justice were ranked fourth and fifth, suggesting
that there is not a one-to-one correspondence in the areas that people perceive as most important and
the areas where they think disparities are greatest. Interestingly, though, we found that the general
importance ranks for social inclusion and criminal justice were bimodal, meaning that there were large
proportions of respondents who felt they were among the most important but also large proportions who
felt they were among the least important. For example, more than 50% of respondents ranked criminal
justice in the top five for general importance, but a large percentage of survey respondents also ranked it
eleventh. Similarly, roughly one in five respondents ranked social inclusion as the most important broad
area to be measured, but more than one in six ranked it tenth or lower.
City services was ranked in the middle with respect to general importance, yet eleventh with respect
unequal outcomes. On the other hand, environmental justice, transportation, and civic engagement were
ranked similarly low for both general importance and unequal outcomes, although perceptions seemed
to be split for environmental justice and civic engagement in a similar manner as for social inclusion and
criminal justice. For example, the same percentage of respondents ranked environmental justice as the
most important broad area as ranked it ninth most important.
General Importance
Domains Median Mean Rank
Housing 2 2.49 1
Economic Opportunity 2 2.61 2
Education 3 3.88 3
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Public Health 4 4.09 4
Public Safety 4 4.62 5
City Services 4 4.98 6
Social Inclusion 4 5.04 7
Criminal Justice 5 5.58 8
Environmental Justice 6 5.52 9
Transportation 6 5.64 10
Civic Engagement 7 6.27 11
Equal Outcomes
Domains Median Mean Rank
Economic Opportunity 2 2.39 1
Housing 2 2.48 2
Education 3 3.75 3
Criminal Justice 3 3.78 4
Social Inclusion 3 4.16 5
Public Health 4 4.34 6
Public Safety 5.5 5.52 7
Transportation 6 5.69 8
Environmental Justice 6 6.09 9
Civic Engagement 7 6 10
City Services 7.5 6.2 11
Survey respondents who chose to participate in the 20-minute version of the survey were also asked to
indicate on the basis of which characteristics they think people are likely to experience inequities in Fort
Collins by providing an answer of yes/no for each characteristic. All of the characteristics listed were rated
as a likely source of inequity by the majority of survey respondents. Almost all survey respondents
(94.7%) listed living in poverty as a characteristic that is a source of inequity in Fort Collins, followed
closely by race or ethnicity, immigrant status, current or former involvement with the criminal justice
system, and undocumented status.
Characteristics Associated with Inequity
Characteristic Frequency Percent
Living in poverty 18 94.7%
Race or ethnicity 17 89.5%
Immigrant status 16 84.2%
Current or former involvement with the
criminal justice system
15 78.9%
Undocumented status 15 78.9%
Low educational attainment 14 73.7%
LGBTQIA+ status 14 73.7%
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Living with disabilities or chronic health
conditions
14 73.7%
Age 11 57.9%
Single parenthood 11 57.9%
Religion 10 52.6%
Focus Groups
Design
Nine focus groups were conducted, each focusing on disparities impacting one of the following
communities (with one being mixed-race/ethnicity):
1. Asian and Pacific Islander
2. Black
3. Hispanic/Latinx
4. LGBTQIA+
5. Native American
6. People living with disabilities
7. People with undocumented status or from mixed-status families
8. Religious minorities
All focus groups were conducted virtually using Zoom and recorded with the express consent of each
community member who chose to participate. Two ISLG staff conducted the focus groups with one
primarily responsible for facilitating and the other serving in the capacity of note-taker. For two of the
focus groups, the community outreach specialist offered interpretation in Spanish for the focus groups
with Hispanic/Latinx and undocumented status or mixed-status families groups.
Each focus group followed a structured, but iterative, protocol anchored in two key questions. The first
question asked participants to share which of the broad areas identified through the preliminary
landscape analysis resonated with them and why, and whether they should all be retained moving
forward in the City’s work. The facilitator also probed for whether participants thought there were key
areas where disparities were experienced by community members that were missing and should be
added. The second question focused on going through select areas collectively chosen by participants and
seeking their input on which measures they would choose as Equity Indicators to go on the public
dashboard and why. The facilitator also probed for whether the measures in each area were appropriate
for documenting inequity and what other indicators should be considered for inclusion. For each of the
two main questions, the facilitator asked participants whether there were any data sources they would
recommend the ISLG research team examine to analyze disparities given the insights offered during the
process. Focus groups ranged from 60 to 90 minutes each, with a total listening time of approximately
14.5 hours.
Participants
Participants were identified through a purposive, snowball sampling method. Individuals who were
residents of the City of Fort Collins and demonstrated interest in participating in the focus groups focused
on the communities described above were included on a first-come, first-served basis with participation
capped at eight members per group. Participant outreach was a multi-pronged process. Members of the
core project team from the City of Fort Collins engaged in email outreach with key members of the
different communities and organizations within Fort Collins and introduced them to the ISLG research
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team. The research team then provided additional information about the focus groups and invited them
to participate. The research team also asked community members to forward the invitation and
information about other ways to provide input to all community residents in their networks. At the same
time, the community outreach specialist sent direct invitations to some of the communities typically
precluded from these types of conversations with which her ties were the strongest (e.g., mixed status
families). Lastly, information about the focus groups was also disseminated via social media and on the
project OurCity page. Focus groups were conducted from the 19th through the 29th of October. Between
one to eight community members attended each focus group with a total of 35 participants in
attendance.
Findings from Community Input
While rankings differed among domains, the responses to the survey suggested that the domains
included in the preliminary landscape were important areas and identified measures within each as
critical enough to be included as Equity Indicators. Similarly, over the course of the focus groups, all of the
domains identified in the landscape analysis were named as important by community members, as well
as many specific measures. Notably, areas that were identified by at least five of the focus groups were:
City Services, Civic Engagement, Economic Opportunity, Education, Housing, and Social Inclusion.
Survey respondents and focus group participants also named additional areas and measures that they felt
should be included in the landscape analysis or selected as Equity Indicators. In some cases, they also
provided suggestions for potential data sources for looking at specific measures and/or specific
communities. ISLG compiled all of these suggestions and sought to include as many suggestions as
possible in the final landscape analysis. Unfortunately, in many cases, measures or areas could not be
included because datasets did not exist (e.g., diversity of school syllabi), data were not disaggregated by
race/ethnicity or other characteristics (e.g., ambient temperature), data were for a larger geographic area
than Fort Collins or Larimer County (e.g., U.S. Transgender Survey), or data could not be used for the
purposes of this project (e.g., individual-level data from service providers). That being said, as the result
of the input from community engagement and other stakeholders, 35 additional measures were added to
the landscape analysis. This input was also used to select the measures to be included as Equity
Indicators.
Focus group participants also spoke about how they and others within their community have been
impacted by disparities. More information on the key themes emerging from these sessions can be found
in Appendix B.
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Landscape Analysis Methodology
Structure of Landscape Analysis
The analysis of the broad landscape of disparities looked at specific measures within 10 domains (see
Table 2). The number of measures within each domain ranged from five to 18; and there were 114
measures in total (although some measures included multiple individual comparisons, such as separate
comparisons for race/ethnicity and disability status). Measures were first identified through background
research, and then supplemented with suggestions from City and County stakeholders and community
members if data were available to measure their suggestions. Given the City’s focus on leading with race,
measures were generally not included if some form of disaggregation by race and/or ethnicity was not
possible. For select measures identified as important through stakeholder and/or community input, data
that did not allow disaggregation by race/ethnicity were included if they disaggregated by another
important characteristic (e.g., income, neighborhood). For measures where race and ethnicity were
available, disparities based on other characteristics were explored for select measures identified as
important in prior phases of the work where possible based on data availability and time constraints. For
all measures, the presence or absence of disparities was assessed by comparing the outcome or
perception (i.e., the percentage, rate, or rating) for each group to the overall outcome or perception (see
How Information is Reported below).
It is important to note that not all of the measures included within these areas are directly under the
purview of the City. Some fall to the County, or to others, and many are complex issues that have multiple
root causes and multiple factors that play a role in maintaining disparities. These will require multi-
faceted efforts to address them, and require partnership and coordination among multiple entities inside
and outside of government.
Table 2. Key domains included in landscape disparity analysis, more specific areas included within them,
the number of measures in each, and the different characteristics explored on one or more measure within
each domain
Domain Areas Included Number of
Measures
Characteristics Explored
Civic Engagement Engagement with government,
engagement with community
7 Race and ethnicity, income
Criminal Justice
and Public Safety
Law enforcement, incarceration
and community supervision,
perceptions of safety
9 Race and ethnicity
Economic
Opportunity
Poverty and food security, income,
employment, business ownership,
childcare
17 Race and ethnicity, gender,
disability status, sexual orientation,
educational attainment, household
composition, neighborhood
Education Academic achievement, staff
representation, school
connections, barriers to academic
success, educational attainment
15 Race and ethnicity, income (free or
reduced lunch status), academic
achievement (levels of support)
Environmental
Justice
Pollutants, climate vulnerability
factors
5 Race and ethnicity
Housing Housing affordability,
homelessness, neighborhood
9 Race and ethnicity, income,
neighborhood
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Public Health Access to health care, physical
health, mental health
17 Race and ethnicity, income, sexual
orientation
Services Essential services, parks and
recreation
18 Race and ethnicity, income,
disability status, neighborhood
Social Inclusion Community, City inclusiveness 8 Race and ethnicity
Transportation Commuting, personal
transportation, public
transportation
9 Race and ethnicity, sexual
orientation
Data and Sources
Data were collected and compiled from a wide range of sources (see Box 1) and included measures
assessing both outcomes and perceptions; however, it is important to keep in mind that data for many
important measures, areas, and groups were not available and could not be included in this analysis. For
most measures, data were for the City of Fort Collins, but for some, data were only available for Larimer
County as a whole. In these cases, the findings for the measure specify that they are for Larimer County.
Larimer County was the largest geography included; data sources were not used if they only allowed us to
look at the region, state, or country as a whole. In terms of other criteria for inclusion, sources from
which data were drawn were included if they were deemed to be reliable and from large enough samples
to be reported, if enough information was provided to enable us to understand what was being measured
and for whom, and if they allowed for disaggregation by race, ethnicity, or another key characteristic
linked to disparities as described above (e.g., income, neighborhood).
To create specific measures from these data sources, ISLG used the most recent timeframe available, with
a cutoff point of 2016 as the earliest year that would be considered. Given the variety of data sources
employed, the specific reference year varied metric to metric. So while data for some of these measures
were collected in 2019 or 2020, in some cases the most recent data available were from 2018 or earlier (e.g.,
American Community Survey 5-year dataset, Annual Survey of Jails); as noted above, no data from earlier than
2016 were included. The year of data is included in the findings for each measure.
It is also important to note that the data included in this report were collected prior to the COVID-19
pandemic. COVID-19 has had a devastating impact on communities nationwide, particularly on
communities of color and other marginalized communities. These impacts will need to be considered in
developing solutions to the disparities reported here, as it is very possible that many have worsened, and
that new disparities have arisen.
Population estimates were taken from the American Community Survey (ACS). In order to enable a large
enough sample size to explore breakdowns by individual racial/ethnic groups other than white, ISLG used
the 5-year combined sample, for which the most recent year available at the time of data collection was
2018. Where possible, ISLG use standard ACS tables containing margins of error to enable statistical
significance testing; however, where tables were not available (e.g., racial/ethnic breakdowns for
different age groups), ISLG directly pulled datasets from the U.S. Census Bureau’s microdata portal. For
this reason, population estimates may vary for different measures. Most estimates of the overall
population, including the ACS, include Colorado State University students within the total population, so
they are included in most population measures reported here. Table 3 provides an overview of the Fort
Collins population by race, ethnicity, and student status in order to further contextualize the findings for
each group, while Table 4 provides the same information for Larimer County as a whole.
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Table 3. Fort Collins demographics by race, ethnicity, and college enrollment
Population
Percentage of
Population
Total Population 162,511 100%
Race/Ethnicity
Hispanic/Latinx, any race 19,736 12.1%
Not Hispanic/Latinx
White 129,931 80.0%
Asian 5,445 3.4%
Black 2,343 1.4%
Native American 1,083 0.7%
Native Hawaiian or other Pacific Islander 148 0.1%
Other race 207 0.1%
Two or more races 3,618 2.2%
College and Graduate School Enrollment
Enrolled in college, undergraduate 27,703 17.1%
Enrolled in graduate or professional school 5,182 3.2%
Table 4. Larimer County demographics by race, ethnicity, and college enrollment
Population
Percentage of
Population
Total Population 338,161 100%
Race/Ethnicity
Hispanic/Latinx, any race 38,323 11.3%
Not Hispanic/Latinx
White 280,122 82.8%
Asian 7,357 2.2%
Black 3,035 0.9%
Native American 1,640 0.5%
Native Hawaiian or other Pacific Islander 290 0.1%
Other race 375 0.1%
Box 1: Four types of data sources
Existing reports (e.g., 2020 Sustainability Gaps Analysis, Larimer County Community Corrections
Annual Report)
Publicly available data or dashboards from local/state sources (e.g., Fort Collins Police Services
Transparency data, Poudre School District data from the Colorado Department of Education)
Publicly available local data from national sources (e.g., Fort Collins data from the American
Community Survey, Home Mortgage Disclosure Act data)
Data provided directly by City or County departments and agencies (e.g., Community Health
Survey, utilities burden data).
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Two or more races 7,019 2.1%
College and Graduate School Enrollment
Enrolled in college, undergraduate 34,621 10.2%
Enrolled in graduate or professional school 6,996 2.1%
It is also important to note that information on race and/or ethnicity and other groups differed in
different data sources. In general, ISLG aimed to include the racial/ethnic categories of white,
Hispanic/Latinx, Asian or Pacific Islander, Black, Native American, and other. Where one of these groups is
not included in the findings for a measure, either data were not available for that group or the sample
size was too small to be reported. For the Asian or Pacific Islander category, in some data sources they
were combined into one category and reported together. In others they were separate, but the Pacific
Islander sample was too small to be able to report and is not included in the findings for the tables.
Finally, some sources differentiated only between non-Hispanic white and Hispanic/Latinx or other race,
or between non-Hispanic white, Hispanic/Latinx, and non-Hispanic, non-white. Table 5 includes the
number of measures for which each racial/ethnic category or grouping was examined.
Table 5. Number of measures examined for racial/ethnic group or category based on data availability
Racial/ethnic group Number of measures
Non-Hispanic white 96
Hispanic/ Latinx 45
Asian or Pacific Islander 39
Black 40
Native American 35
Other 31
Non-white, non-Hispanic 8
Hispanic and/or other race 54
White, including Hispanic 7
For most measures, the Hispanic/Latinx designation includes Hispanic/Latinx individuals from all racial
groups; individuals within other categories do not include Hispanic/Latinx individuals. For some data
sources, however, this categorization was not possible. For example, with the exception of the table
reporting race and ethnicity itself, the American Community Survey (ACS) standard data tables only allow
non-Hispanic designation for white individuals; for outcomes based on ACS standard tables, then, non-
white racial groups might also include Hispanic/Latinx individuals. For these outcomes, non-Hispanic
white is specified in the outcomes table since other categories might include Hispanic/Latinx individuals.
How Information is Reported
For each domain, an overall description of findings is provided first, followed by the findings for each
specific measure. For specific measures, a brief description of findings across all characteristics or groups
examined is provided first, followed by detailed tables and disparity graphs for each group.
It is important to take population size into account in assessing disproportionate impact and disparities.
For that reason, with the exception of perception measures based on ratings (e.g., average disaster
response rating on a scale from 1 to 100), findings are presented as percentages or rates to account for
the size of the population of interest. With that being said, ISLG included raw numbers alongside
percentages and rates in the detailed tables wherever possible based on the data available; however,
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where the data source provided only percentages, for example, raw numbers could not be included. For
two of the surveys, the Fort Collins Community Survey and the Health District of Northern Larimer County
Community Health Survey, the numbers of respondents represent the total number of respondent to the
survey from each racial and ethnic group; it was not possible to provide disaggregated counts of the
respondents for each question.
Disparities were calculated by comparing the finding for each group—meaning the percentage, rate, or
rating—to the overall finding for the relevant population (e.g., Fort Collins, Larimer County, Poudre
School District). Depending on whether a higher number was more positive or more negative, the
disparity was either the group finding subtracted from the overall finding or the overall finding subtracted
from the group finding. A positive number means that the group had a more positive outcome or
perceived something more positively than the overall/average outcome or perception; a negative number
means that the group had a more negative outcome or perceived something more negatively than the
overall outcome or perception. For example, 17% of people in Fort Collins overall lived in poverty;
however, the percentage living in poverty was 16% for whites, a more positive outcome with a difference
of 1. The percentage of Native Americans living in poverty, on the other hand, was 25%, a more negative
outcome and a difference of -8.
Wherever possible, statistical testing was conducted in order to see whether differences between the
finding for the overall outcome or perception and the finding for each racial and ethnic group included in
the data were statistically significant. It should be noted that significance testing was not possible in
several circumstances: 1) raw numbers for the different groups were not provided (e.g., percentages
only), 2) measures of variance were not provided (e.g., standard error), or 3) for ACS data, standard tables
including margins of error were not available and data were pulled from the Microdata portal instead. In
keeping with the City’s focus on leading with race, ISLG tested for statistical significance for differences
based on race and ethnicity only, with the exception of a few select measures.
Where significance testing was possible, ISLG performed most tests, while the Larimer County Health
District conducted significance testing for measures from the District’s Community Health Survey.
Statistical testing was possible for 64% of measures that examined differences by race and ethnicity, but
was not possible for the remaining 36%. One thing that is important to keep in mind, however, is that
statistical significance is impacted by sample size. There was a very small sample size for a number of
measures across the landscape analysis, particularly for racial and ethnic groups that represent a smaller
proportion of the population. For that reason, it is possible that meaningful differences were not
statistically significant in the data that was able to be included here, but would have been had a larger
sample size been possible.
Where statistical testing could not be conducted, ISLG used the following criteria to establish whether or
not to call two numerical findings different based on the magnitude of differences that tended to appear
as meaningful or significant in the background research reviewed:
Type of metric Numerical criteria
Percentage Difference of 5% or more
Rating from 1 to 100 Difference of 5 or more
Rate per 100 Difference of 5 or more
Rate per 1,000 Difference of 10 or more
Rate per 10,000 Difference of 100 or more
Amount in $ Difference of $5,000 or more
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Despite the use of these criteria, caution should be used in drawing conclusions about the differences
between groups where statistical significance could not be conducted.
The detailed tables include findings for each comparison group and how they compare to the total,
overall outcome across all groups as follows:
Race/ethnicity
Population
Number living in
poverty
Percent living in
poverty
Difference
Non-Hispanic white 123,833 19,206 15.51% 1.27%
Hispanic/Latinx* 18,466 3,969 21.49% -4.72%
Asian 5,142 1,033 20.09% -3.31%
Black 2,312 519 22.45% -5.67%
Native American 1,278 315 24.65% -7.87%
Other* 2,458 723 29.41% -12.64%
Overall 154,160 25,861 16.78% -
*Statistically significant at p < .05
Basis for
comparison and
relevant groups
Number with each outcome
for each group and overall
across groups
How each group
compares to the
overall outcome
Total in population
for each group and
overall
Percent/rate with each
outcome for each
group and overall
Signifies statistically
significantly different
from the overall
outcome
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Landscape Analysis Findings Overview
As noted above, ISLG explored differences in outcomes and perceptions by race and ethnicity and, in
some cases, other characteristics in order to establish where disparities exist and identify areas for
deeper exploration and opportunities for growth and investment. A brief overview of findings across
areas is included here, followed by more detailed findings for each of the 10 areas explored: Civic
Engagement, Criminal Justice and Public Safety, Economic Opportunity, Education, Housing, Public Health,
Services, Social Inclusion, and Transportation.
Racial and ethnic disparities4 were found on just over half (54%) of the measures where racial/ethnic
comparisons were possible, although the groups were not always consistent. While differences were
found across all of the areas examined, the percentage by area varied considerably, as can be seen below.
ISLG also found differences by income, gender, sexual orientation, disability status, educational
attainment, household composition, and neighborhood. Table 6 and Figure 1 show how different racial
and ethnic groups fared across all measures included in the landscape analysis. It is important to keep in
mind that that because information on race and/or ethnicity and other groups differed in different data
sources, the number of measures for each racial/ethnic grouping is different (see Table 5 above for the
number of measures by group). For that reason, the percentage of measures for which each group had a
more positive or negative outcome or perception is used in addition to or in place of the number.
Overall Findings by Race and Ethnicity
Across areas, Asians or Pacific Islanders had more positive outcomes or perceptions compared to overall
on 26% of measures where they were able to be examined, the highest percentage of the groups,
although they also had more negative outcomes or perceptions on 10%. Whites had more positive
outcomes or perceptions on 16% of measures, but did not have any measures with more negative
outcomes or perceptions. By contrast, Hispanics/Latinx had more negative outcomes or perceptions
compared to overall on 62% of measures where they were able to be examined, the highest of the
groups; and did not have more positive outcomes or perceptions on any of the measures examined in the
landscape analysis. They were followed by Blacks, Hispanic and/or other race individuals, and individuals
from other racial groups, for whom roughly two in five measures had more negative outcomes or
perceptions, and Native Americans for whom one in three measures were more negative.
4 For the purposes of this report, disparities were defined as differences between the finding for a particular group
and the overall finding for the relevant population that were either statistically significant or were larger than our
pre-determined thresholds (see Landscape Analysis Methodology).
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Table 6. Number (percentage) of measures with more positive, equivalent, or more negative outcomes or
perceptions than the overall outcome or perception for each racial and ethnic grouping included
Racial/ethnic group
Number (%) of
measures with
positive outcomes or
perceptions
Number (%) of
measures with
equivalent outcomes
or perceptions
Number (%) of
measures with
negative outcomes
or perceptions
Non-Hispanic White 15 (16%) 81 (84%) 0 (0%)
Hispanic/Latinx 0 (0%) 17 (38%) 28 (62%)
Asian or Pacific Islander 10 (26%) 25 (64%) 4 (10%)
Black 3 (8%) 20 (50%) 17 (43%)
Native American 3 (9%) 21 (60%) 11 (31%)
Other 2 (6%) 16 (52%) 13 (42%)
Non-Hispanic, Non-White 0 (0%) 8 (100%) 0 (0%)
Hispanic and/or Other Race 1 (2%) 33 (61%) 20 (37%)
White, including Hispanic 0 (0%) 6 (86%) 1 (14%)
Figure 2. Percentage of measures with more positive (positive numbers) or more negative (negative
numbers) outcomes or perceptions than the overall outcome or perception for each racial and ethnic
grouping included
Racial and Ethnic Disparities by Domain
ISLG also explored how racial and ethnic differences varied by domain and where different groups were
particularly likely to experience more positive or more negative outcomes or perceptions compared to
the overall outcome or perception.
The percentage of measures where racial/ethnic differences were found varied considerably by domain
from a low of 24% of measures allowing racial/ethnic comparisons for Public Health to 100% of measures
allowing racial/ethnic comparisons for Criminal Justice and Public Safety (see Table 7).
16%
0%
26%
8%9%6%
0%2%0%0%
-62%
-10%
-43%
-31%
-42%
0%
-37%
-14%
-70%
-60%
-50%
-40%
-30%
-20%
-10%
0%
10%
20%
30%
40%
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Table 7. For each domain examined, the number of measures overall, the number where racial/ethnic
comparisons could be made, and, of those, the number and percentage where racial/ethnic differences
were found.
Domain
Number of
Measures
Number Allowing Race/
Ethnicity Comparisons
Number (%) with
Racial/Ethnic Differences
Civic Engagement 7 6 4 (67%)
Criminal Justice and Public Safety 9 9 9 (100%)
Economic Opportunity 17 15 9 (60%)
Education 15 15 11 (73%)
Environmental Justice 5 5 2 (40%)
Housing 9 9 5 (55%)
Public Health 17 17 4 (24%)
Services 18 11 6 (54%)
Social Inclusion 8 7 3 (43%)
Transportation 9 9 3 (33%)
Total 114 103 56 (54%)
When looking at the domains where each racial and ethnic group fared the best, non-Hispanic whites and
Asians or Pacific Islanders did particularly well in Education, where they had more positive outcomes or
perceptions on nine of 15 and five of 13 measures, respectively (see Table 8). Interestingly, Education was
also where Asians or Pacific Islanders had the highest number of negative outcomes or perceptions, but it
should be noted that this represented only two measures, and this group had more negative outcomes or
perceptions on only four measures in total across domains. Three groups fared equally well in multiple
domains—Blacks, Native Americans, and individuals from other racial and ethnic groups—but in all of
these cases, it was because the group had only three measures with more positive outcomes or
perceptions in total and these were spread evenly across domains. Hispanic and/or other race individuals
fared best in Social Inclusion, but here too, this represented only one measure.
In terms of where groups fared the worst, Education was a clear area of disparities for Hispanics/Latinx
and Native Americans who each had their highest number of negative outcomes or perceptions within
this domain. By contrast, Criminal Justice and Public Safety was the source of the greatest number of
disparities for Blacks who had more negative outcomes or perceptions on six of seven measures. Hispanic
and/or other race individuals (i.e., people of color) fared the worst in Services, where many of the
measures able to be included did not allow for further disaggregation by race and ethnicity so it was not
possible to obtain a more nuanced view of disparities by group. Lastly, individuals from other racial and
ethnic groups fared the worst in Economic Opportunity, where they had more negative outcomes or
perceptions on three of seven measures.
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Table 8. Domains with the highest number of measures with more positive outcomes or perceptions and
more negatives outcomes and perceptions compared to the overall outcome or perception for each racial
and ethnic grouping included
Racial/ethnic group
Domain with the highest number of
more positive measures
Domain with the highest number of
more negative measures
Non-Hispanic White Education (9 of 15) n/a†
Hispanic/Latinx n/a Education (10 of 15)
Asian or Pacific Islander Education (5 of 13) Education (2 of 13)
Black Services (1 of 3), Education (1 of
14), Transportation (1 of 2) Criminal Justice (6 of 7)
Native American Criminal Justice (1 of 6), Education
(1 of 11), Transportation (1 of 2) Education (6 of 11)
Other Education (1 of 11), Housing (1 of
5) Economic Opportunity (3 of 7)
Non-Hispanic, Non-White n/a n/a
Hispanic and/or Other Race Social Inclusion (1 of 6) Services (5 of 7)
White, including Hispanic n/a Criminal Justice (1 of 4)
† Indicates that there were no applicable measures
In the sections to follow detailed findings for each domain are presented. Each section begins with an
overview of findings for each racial and ethnic group across the domain that includes the number of
measures for which each group had more positive, equivalent, and more negative outcomes or
perceptions compared to the overall outcome or perception. We then give an overview of findings for
race and ethnicity in addition to any other characteristics examined, accompanied by tables and graphs
that include the detailed findings for each measure and characteristic examined.
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Civic Engagement
Within Civic Engagement, seven measures of engagement with the government and engagement with
the community were examined. Racial/ethnic and income-based disparities were found across some but
not all measures. More negative outcomes or perceptions were found for people of color in terms of their
representation in decision-making bodies or community groups and measures examining volunteering, in
addition to lower rates of reported trust in the local government. Disparities by income were found in
voter turnout, where there was lower turnout in lower-income census tracts and higher turnout in
higher-income census tracts.
Table 9. Number (percentage) of measures with more positive, equivalent, or more negative outcomes or
perceptions than the overall outcome or perception for each racial and ethnic grouping included
Racial/ethnic group
Number (%) of
measures with
positive outcomes or
perceptions
Number (%) of
measures with
equivalent outcomes
or perceptions
Number (%) of
measures with
negative outcomes
or perceptions
Non-Hispanic White 0 (0%) 6 (100%) 0 (0%)
Hispanic/Latinx 0 (0%) 1 (33%) 2 (67%)
Asian or Pacific Islander 0 (0%) 1 (100%) 0 (0%)
Black n/a n/a n/a
Native American n/a n/a n/a
Other 0 (0%) 0 (0%) 1 (100%)
Non-Hispanic, Non-White 0 (0%) 2 (100%) 0 (0%)
Hispanic and/or Other Race 0 (0%) 1 (33%) 2 (67%)
White, including Hispanic n/a n/a n/a
Data Note: Assessing Differences Between Groups
Wherever possible, statistical testing was conducted in order to see whether differences between the finding
for the overall outcome or perception and the finding for each racial and ethnic group included in the data were
statistically significant. It should be noted that significance testing was not possible in several circumstances: 1)
raw numbers for the different groups were not provided (e.g., percentages only), 2) measures of variance were
not provided (e.g., standard error), or 3) for ACS data, standard tables including margins of error were not
available and data were pulled from the Microdata portal instead. In keeping with the City’s focus on leading
with race, ISLG tested for statistical significance for differences based on race and ethnicity only, with the
exception of a few select measures.
One thing that is important to keep in mind is that statistical significance is impacted by sample size. There was
a very small sample size for a number of measures across the landscape analysis, particularly for racial and
ethnic groups that represent a smaller proportion of the population. For that reason, it is possible that
meaningful differences were not statistically significant in the data that was able to be included here, but would
have been had a larger sample size been possible.
Where statistical testing could not be conducted, ISLG used a set threshold (see How Information is Reported)
to establish whether or not to call two numerical findings different based on the magnitude of differences that
tended to appear as meaningful or significant in the background research reviewed. Despite the use of set
thresholds, caution should be used in drawing conclusions about the differences between groups where
statistical significance could not be conducted.
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Engagement with Government
Voter Turnout
Voting is essentially to democracy and one of the most important elements of civic engagement. Income-
based disparities were found in voter turnout, however, with registered voters in the bottom two income
groups significantly less likely and the top two income groups more likely to vote in the most recent
general election than residents of Fort Collins overall.
Income
Percent of registered voters in Fort Collins who voted in the general election, 2020
Source: Larimer County Elections Office Voter Registration List
Income group
by census tract
Number of
registered
voters
Number
who voted
Percent
who voted
Difference
from overall
Bottom 20%* 21,191 14,575 68.78% -9.30%
20-40%* 24,093 18,266 75.81% -2.27%
40-60% 23,348 18,422 78.90% 0.82%
60-80%* 25,948 21,223 81.79% 3.71%
Top 20%* 16,669 14,380 86.27% 8.19%
Overall 111,249 86,866 78.08% -
*Significantly different from overall at p < .05
Disparity Graph: Income differences in voter turnout
Representation on Boards and Commissions
Boards and Commissions are responsible for making numerous important decisions in the life of a City,
yet disparities by both race/ethnicity and income were found. Hispanic/Latinx and other-race individuals
were underrepresented among Boards and Commissions members. When examined by income,
representation tended to be lower for lower-income groups and higher for higher-income groups.
-9.30%
-2.27%
0.82%
3.71%
8.19%
-15.00%
-10.00%
-5.00%
0.00%
5.00%
10.00%
Bottom 20%20-40%40-60%60-80%Top 20%
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Race/ethnicity
Self-reported race and ethnicity of Boards and Commissions members, 2017
Source: City of Fort Collins Public Participation Report
Race/ethnicity† Population
Number of Boards and
Commissions members
Participation rate
per 10,000
Difference
from overall
White 134,736 116 8.61 1.00
Hispanic/Latinx 16,703 4 2.39 -5.22
Asian 4,666 2 4.29 -3.33
Multiple 3,804 2 5.26 -2.35
Other 2,990 0 0.00 -7.61
Overall 162,899 124 7.61 -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Racial/ethnic differences in Boards and Commissions representation
Income
Self-reported income of Boards and Commission members, 2017
Source: City of Fort Collins Public Participation Report
Household income Percentage of
population
Percentage of Boards
and Commission
members
Difference
from overall
Less than $10,000 13.68% 1.94% -11.74%
$15,000-$24,999 9.05% 1.94% -7.11%
$25,000-$34,999 10.62% 5.83% -4.79%
$35,000-$49,999 12.12% 4.85% -7.27%
$50,000-$74,999 16.02% 16.50% 0.48%
$75,000-$99,999 13.78% 16.50% 2.72%
$100,000-$149,999 15.36% 34.95% 19.59%
$150,000-$199,999 4.94% 8.74% 3.80%
$200,000 or more 4.43% 8.74% 4.31%
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
1.00
-5.22
-3.33 -2.35
-7.61-10.00
-8.00
-6.00
-4.00
-2.00
0.00
2.00
White Hispanic/Latinx Asian Multiple Other
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Disparity Graph: Income differences in Boards and Commissions representation
Attending Government Events
Just over a quarter of respondents overall reported having attended at least one government-organized
event in the past year, and attendance rates were similar across racial and ethnic groups.
Race/ethnicity
Percent of survey respondents who reported having attended a government-organized event in the last
12 months, 2019
Source: Fort Collins Community Survey
Race/ethnicity†
Number of
respondents
Percent who attended a
government event
Difference
from overall
White 528 28% 1%
Hispanic and/or other race 86 24% -3%
Overall 614 27% -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Racial/ethnic differences in attending government events
Trust in Local Government
Sizeable racial and ethnic differences were found in reported trust in the local government. While the
percentage of whites who reported generally trusting the local government was similar to the overall
-11.74%
-7.11%
-4.79%
-7.27%
0.48%
2.72%
19.59%
3.80%4.31%
-15.00%
-10.00%
-5.00%
0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
1%
-3%-4%
-2%
0%
2%
White Hispanic and/or other race
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percentage, the percentage was considerably lower for non-Hispanic non-white or multiple-race
respondents and for Hispanic/Latinx respondents, who reported significantly lower levels of trust—24
percentage points lower than overall.
Race/ethnicity
Percentage of individuals who report that they generally trust the local government, 2020
Source: City of Fort Collins Our Climate Future Demographic Survey†
Race/ethnicity
Number of
respondents
Number
reporting trust
Percent
reporting trust
Difference
from overall
Non-Hispanic white 253 169 67% 4.82%
Hispanic/Latinx* 37 14 38% -24.14%
Non-Hispanic non-white
or multiple 23 11 48% -14.15%
Overall 313 194 62%
*Statistically significant at p < .05
† Note that the Our Climate Future Demographic Survey was conducted as part of a larger community
engagement strategy and may not be fully representative of all segments of the population
Disparity Graph: Racial/ethnic differences in trust in local government
Engagement with Community
Community Group Membership
In addition to engagement with the government, engagement with community groups and other non-
governmental organizations is an important part of civic engagement. While almost half of respondents
overall reported that they were members of community groups, one in four Hispanic/Latinx respondents
reported membership; however, likely due to small sample size this difference was not significant.
4.82%
-24.14%
-14.15%
-30.00%
-25.00%
-20.00%
-15.00%
-10.00%
-5.00%
0.00%
5.00%
10.00%
Non-Hispanic white Hispanic/Latinx Non-Hispanic non-white or multiple
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Race/ethnicity
Percent of individuals reporting that they are members of a community group, 2020
Source: City of Fort Collins Our Climate Future Demographic Survey†
Race/ethnicity
Number of
respondents
Number who were
community group
members
Percent who were
community group
members
Difference
from overall
Non-Hispanic white 253 119 47% 1.99%
Hispanic/Latinx 37 10 27% -18.02%
Non-Hispanic non-white
or multiple 23 12 52% 7.13%
Overall 313 141 45%
† Note that the Our Climate Future Demographic Survey was conducted as part of a larger community
engagement strategy and may not be fully representative of all segments of the population
Disparity Graph: Racial/ethnic differences in community group membership
Volunteering
Overall, almost two thirds of respondents reported having volunteered in the past year. However, rates
were lower for Hispanic and/or other race respondents, among whom just over half reported having
volunteered.
Race/ethnicity
Percent of survey respondents who volunteered their time to some group/activity in Fort Collins in the
last 12 months, 2019
Source: Fort Collins Community Survey
Race/ethnicity†
Number of
respondents
Percent who
volunteered in last year
Difference
from overall
White 528 63% 3%
Hispanic and/or other race 86 52% -8%
Overall 614 60% -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
1.99%
-18.02%
7.13%
-20.00%
-15.00%
-10.00%
-5.00%
0.00%
5.00%
10.00%
Non-Hispanic white Hispanic/Latinx Non-Hispanic non-white or multiple
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Disparity Graph: Racial/ethnic differences in volunteering
Opportunities to Volunteer Ratings
Perhaps related to differences in volunteering rates, Hispanic and/or other race respondents reported
that fewer opportunities to volunteer were provided by the City of Fort Collins than respondents overall.
Race/ethnicity
Average rating of the extent to which the City of Fort Collins provides volunteer opportunities to
community members on a scale of 0 to 100, 2019
Source: Fort Collins Community Survey,
Race/ethnicity†
Number of
respondents
Volunteer
opportunity rating
Difference
from overall
White 528 71 2
Hispanic and/or other race 86 63 -6
Overall 614 69 -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Racial/ethnic differences in reported opportunities to volunteer
3%
-8%-10%
-8%
-6%
-4%
-2%
0%
2%
4%
White Hispanic and/or other race
2%
-6%-8%
-6%
-4%
-2%
0%
2%
4%
White Hispanic and/or other race
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Criminal Justice and Public Safety
Nine measures within the domain of Criminal Justice and Public Safety were explored, looking at law
enforcement, incarceration, community supervision, and perceptions of safety. Consistent with the stark
racial and ethnic disparities found in the criminal justice system nationwide, racial and ethnic disparities
were found on all measures examined. Blacks experienced the most negative outcomes at multiple points
in the criminal justice system, although disparities were also found for other racial and ethnic groups.
Despite this, ratings of police services in the Fort Collins Community Survey were moderately high for
both whites and people of color, although they were somewhat lower for the latter.
Table 10. Number (percentage) of measures with more positive, equivalent, or more negative outcomes or
perceptions than the overall outcome or perception for each racial and ethnic grouping included
Racial/ethnic group
Number (%) of
measures with
positive outcomes or
perceptions
Number (%) of
measures with
equivalent outcomes
or perceptions
Number (%) of
measures with
negative outcomes
or perceptions
Non-Hispanic White 1 (11%) 8 (89%) 0 (0%)
Hispanic/Latinx 0 (0%) 1 (25%) 3 (75%)
Asian or Pacific Islander 4 (67%) 2 (33%) 0 (0%)
Black 0 (0%) 1 (14%) 6 (86%)
Native American 1 (17%) 4 (67%) 1 (17%)
Other 1 (20%) 2 (40%) 2 (40%)
Non-Hispanic, Non-White n/a n/a n/a
Hispanic and/or Other Race 0 (0%) 0 (0%) 2 (100%)
White, including Hispanic 0 (0%) 3 (75%) 1 (25%)
Data Note: Assessing Differences Between Groups
Wherever possible, statistical testing was conducted in order to see whether differences between the finding
for the overall outcome or perception and the finding for each racial and ethnic group included in the data were
statistically significant. It should be noted that significance testing was not possible in several circumstances: 1)
raw numbers for the different groups were not provided (e.g., percentages only), 2) measures of variance were
not provided (e.g., standard error), or 3) for ACS data, standard tables including margins of error were not
available and data were pulled from the Microdata portal instead. In keeping with the City’s focus on leading
with race, ISLG tested for statistical significance for differences based on race and ethnicity only, with the
exception of a few select measures.
One thing that is important to keep in mind is that statistical significance is impacted by sample size. There was
a very small sample size for a number of measures across the landscape analysis, particularly for racial and
ethnic groups that represent a smaller proportion of the population. For that reason, it is possible that
meaningful differences were not statistically significant in the data that was able to be included here, but would
have been had a larger sample size been possible.
Where statistical testing could not be conducted, ISLG used a set threshold (see How Information is Reported)
to establish whether or not to call two numerical findings different based on the magnitude of differences that
tended to appear as meaningful or significant in the background research reviewed. Despite the use of set
thresholds, caution should be used in drawing conclusions about the differences between groups where
statistical significance could not be conducted.
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Law Enforcement
Criminal Arrest or Citation
Significant racial disparities in criminal arrests and citations were found, with arrest/citation rates for
Blacks almost five times higher than the overall rate. The rates were significantly lower than overall for
Asians or Pacific Islanders and those from other racial groups, however, although the magnitude of the
difference was smaller.
Race
Criminal arrest or citation rate per 1,000 in the population, 2019
Source: City of Fort Collins Police Services, Transparency Site
Race Population‡
Number of criminal
arrests/citations
Criminal arrest/
citation rate per 1,000
Difference
from overall
White, including Hispanic* 144,533 5,427 37.55 -1.35
Asian or Pacific Islander* 5,745 38 6.61 29.58
Black* 2,579 367 142.30 -106.11
Native American 1,383 43 31.09 5.10
Overall 162,511 5,882† 36.19 -
*Statistically significant at p < .05
‡ Population numbers are taken from the American Community Survey 5-year estimates, 2018
† There were an additional 7 criminal arrests/citations for which race was unknown
Disparity Graph: Racial/ethnic differences in adult criminal arrest/citation rate per 1,000
-1.35
29.58
-106.11
5.10
-120.00
-100.00
-80.00
-60.00
-40.00
-20.00
0.00
20.00
40.00
White Asian or Pacific Islander Black Native American
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Traffic Citation
While less extreme than for criminal arrests and citations, disparities were still considerable for traffic
citations. Blacks again had the highest citation rates—almost twice as high as overall. Asians or Pacific
Islanders and Native Americans were similarly less likely to be cited than overall.
Race
Traffic citation rate per 1,000 in the population 16 and over, 2019
Source: City of Fort Collins Police Services, Transparency Site
Race
Population 16
and over‡
Number of traffic
citations
Traffic citation
rate per 1,000
Difference
from overall
White, including Hispanic 154,956 6,988 45.10 -0.09
Asian or Pacific Islander* 5,289 55 10.40 34.61
Black* 2,225 194 87.19 -42.18
Native American* 1,188 12 10.10 34.91
Overall 170,478 7,673† 45.01 -
*Statistically significant at p < .05
‡ Population numbers are taken from the American Community Survey Public Use Microdata Sample 5-
year estimates, 2018
† There were an additional 424 traffic citations for which race was unknown
Disparity Graph: Racial/ethnic differences in trust in traffic citation rate per 1,000
Use of Force in the Population
Given the importance of use of force in current conversations around criminal justice reform, use of force
was examined in two different ways. First, use of force rates for different racial and ethnic groups in the
general population were examined. While an important measure in itself, looking at population rates
does not account for differential amounts of contact with the police—a measure that is unfortunately
extremely difficult to capture. For this reason, use of force rates for individuals who were arrested were
examined separately as a proxy for contacts.
1.79
36.49
-40.31
36.78
-50.00
-40.00
-30.00
-20.00
-10.00
0.00
10.00
20.00
30.00
40.00
50.00
White Asian or Pacific Islander Black Native American
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Racial disparities in use of force were particularly prominent when looked at for the general population,
although it should be noted that the absolute number of uses of force for some groups was low. That
being said, use of force rates for Blacks were more than seven times higher than overall.
Race/ethnicity (Population)
Use of force rate per 1,000 people in the population, 2019
Source: City of Fort Collins Police Services, Transparency Site
Race/ethnicity Population‡
Number of uses
of force
Use of force
rate per 1,000
Difference
from overall
White, including Hispanic 144,533 125 0.86 0.05
Asian or Pacific Islander 5,745 1 0.17 0.74
Black* 2,579 17 6.59 -5.68
Native American 1,383 2 1.45 -0.54
Overall 162,511 148 0.91 -
*Statistically significant at p < .05
‡ Population numbers are taken from the American Community Survey 5-year estimates, 2018
† There were an additional 3 uses of force for which race was unknown
Disparity Graph: Racial/ethnic differences in use of force rate per 1,000 in the general population
Use of Force for Arrestees
When use of force was examined for only individuals receiving a criminal arrest or citation, racial
disparities remained, although they were smaller in size than in the general population. Here, Blacks and
Native Americans both had use of force rates approximately twice as high as the overall rate, while rates
for whites and Asians or Pacific Islanders were similar to the overall rate.
Race/ethnicity (Arrests)
Use of force rate per 1,000 criminal arrests or citations, 2019
Source: City of Fort Collins Police Services, Transparency Site
Race/ethnicity
Number of criminal
arrests/citations
Number of uses of
force during arrest
Use of force
rate per 1,000
Difference
from overall
White, including Hispanic 5,427 117 21.56 2.10
Asian or Pacific Islander 38 1 26.32 -2.66
Black* 367 16 43.60 -19.94
Native American 43 2 46.51 -22.85
Overall 5,882 139‡ 23.66 -
*Statistically significant at p < .05
‡ There were an additional 3 uses of force for which race was unknown
0.05 0.74
-5.68
-0.54
-10.00
-5.00
0.00
5.00
White Asian or Pacific Islander Black Native American
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Disparity Graph: Racial/ethnic differences in use of force rate per 1,000 arrests
Representation among Police Officers
Within Fort Collins police officers, the Hispanic/Latinx community was particularly underrepresented,
with rates roughly half those of the population overall; a statistically significant difference.
Race/ethnicity
Number of police officers per 10,000 population, 2019
Source: City of Fort Collins Police Services, Transparency Site
Race/ethnicity Population‡ Sworn officers
Representation
rate per 10,000 Disparity
White 129,931 200 15.39 1.61
Hispanic/Latinx* 19,736 14 7.09 -6.69
Black 2,343 4 17.07 3.29
Other* 10,501 6 5.71 -8.07
Overall 162,511 224 13.78 -
*Statistically significant at p < .05
‡ Population numbers are taken from the American Community Survey 5-year estimates, 2018
Disparity Graph: Racial/ethnic differences in police representation rates
Police Service Quality Ratings
Overall, respondents gave moderately high ratings of the quality of police services in Fort Collins.
However, Hispanic/Latinx and/or other-race respondents rated police services less favorably than overall.
2.10
-2.66
-19.94 -22.85-25.00
-20.00
-15.00
-10.00
-5.00
0.00
5.00
White Asian or Pacific Islander Black Native American
1.14
-5.21
4.69
-5.51-8
-6
-4
-2
0
2
4
6
White Hispanic/Latinx Black Other
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Race/ethnicity
Average rating of police services overall on a scale of 0 to 100, 2019
Source: Fort Collins Community Survey
Race/ethnicity†
Number of
respondents
Average rating of
police services overall
Difference
from overall
Non-Hispanic white 528 75 1
Hispanic/Latinx and/or other race 86 69 -5
Overall 614 74 -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Racial/ethnic differences in police services quality ratings
Incarceration and Community Supervision
Jail Incarceration
Large racial and ethnic disparities in jail incarceration rates were found, with the rate for Blacks five times
the overall rate, and the rate for Hispanics/Latinx twice as high. Rates were less than half the overall rate
for Asians or Pacific Islanders, however.
Race/ethnicity (Larimer County)
Rate of jail incarceration per 10,000 population, 2018
Source: Bureau of Justice Statistics Annual Survey of Jails
Race/ethnicity
General
population‡
Jail
population
Incarceration
rate per 10,000
Difference
from overall
White* 280,122 378 13.49 3.13
Hispanic/Latinx* 38,323 139 36.27 -19.64
Asian or Pacific Islander* 7,647 5 6.54 10.09
Black* 3,035 26 85.67 -69.04
Native American 1,640 2 12.20 4.43
Overall 330,767 550 16.63 -
*Statistically significant at p < .05
‡ Population numbers are taken from the American Community Survey Public Use Microdata Sample 5-
year estimates, 2018
1
-5-6
-4
-2
0
2
White Hispanic and/or other race
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Disparity Graph: Racial/ethnic differences in jail incarceration rate per 10,000
Probation
The adult probation rate for Blacks in Larimer County was more than three times higher than the overall
rate, almost three times as high for Native Americans, and more than one-and-a-half times as high for
Hispanics/Latinx. The rate was considerably lower for Asians or Pacific Islanders, for whom only one
individual was on probation on any given day in 2019.
Race/ethnicity (Larimer County)
Percent of individuals age 18 and older who were on probation on any given day, 2019
Source: Larimer County Community Corrections 2019 Annual Report
Race/ethnicity
Population 18
and over‡
Average daily number
on probation
Probation rate
per 10,000
Difference
from overall
White 137,369 222 16.15 2.83
Hispanic/Latinx* 17,350 57 32.76 -13.79
Asian or Pacific Islander* 5,058 1 1.19 17.79
Black* 2,053 14 67.70 -48.72
Native American* 904 5 50.06 -31.08
Other* 3,242 17 53.14 -34.16
Overall 165,976 315 18.98 -
*Statistically significant at p < .05
‡ Population numbers are taken from the American Community Survey Public Use Microdata Sample 5-
year estimates, 2018
3.13
-19.64
10.09
-69.04
4.43
-80.00
-70.00
-60.00
-50.00
-40.00
-30.00
-20.00
-10.00
0.00
10.00
20.00
White Hispanic/Latinx Asian or Pacific
Islander
Black Native American
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Disparity Graph: Racial/ethnic differences in probation rate per 10,000
Perceptions of Safety
Neighborhood Safety Ratings
Racial and ethnic disparities were found in perceptions of neighborhood safety, with Hispanic and/or non-
white respondents rating their neighborhoods as less safe at night than respondents overall.
Race and Ethnicity
Average rating of personal safety in own neighborhood at night on a scale of 0 to 100, 2019
Source: Fort Collins Community Survey
Race/ethnicity†
Number of
respondents
Average neighborhood
safety rating
Difference
from overall
White 528 80 0
Hispanic and/or other race 86 75 -5
Overall 614 80 -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Racial/ethnic differences in neighborhood safety ratings
2.83
-13.79
17.79
-48.72
-31.08 -34.16
-60.00
-50.00
-40.00
-30.00
-20.00
-10.00
0.00
10.00
20.00
30.00
White Hispanic/Latinx Asian or Pacific
Islander
Black Native American Other
0
-5-6
-4
-2
0
White Hispanic and/or other race
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Economic Opportunity
Within Economic Opportunity, 17 measures exploring poverty, food security, income, employment,
business ownership, and childcare were explored. Our analysis indicated that racial and ethnic disparities
permeate numerous measures within this domain, with people of color more likely to experience a wide
range of negative outcomes from living in poverty to unemployment to lower rates of business ownership
compared to people overall in Fort Collins. We also found disparities by gender, disability status, family
composition, and level of education. For example, women were less likely to own businesses, single
mothers and those with less than a high school education more likely to live in poverty, and individuals
with disabilities earned less than those without a disability, particularly among women.
Table 11. Number (percentage) of measures with more positive, equivalent, or more negative outcomes or
perceptions than the overall outcome or perception for each racial and ethnic grouping included
Racial/ethnic group
Number (%) of
measures with
positive outcomes or
perceptions
Number (%) of
measures with
equivalent outcomes
or perceptions
Number (%) of
measures with
negative outcomes
or perceptions
Non-Hispanic White 3 (21%) 11 (79%) 0 (0%)
Hispanic/Latinx 0 (0%) 2 (22%) 7 (78%)
Asian or Pacific Islander 0 (0%) 8 (100%) 0 (0%)
Black 0 (0%) 4 (50%) 4 (50%)
Native American 0 (0%) 6 (86%) 1 (14%)
Other 0 (0%) 4 (57%) 3 (43%)
Non-Hispanic, Non-White 0 (0%) 1 (100%) 0 (0%)
Hispanic and/or Other Race 0 (0%) 4 (67%) 2 (33%)
White, including Hispanic 0 (0%) 1 (100%) 0 (0%)
Data Note: Assessing Differences Between Groups
Wherever possible, statistical testing was conducted in order to see whether differences between the finding
for the overall outcome or perception and the finding for each racial and ethnic group included in the data were
statistically significant. It should be noted that significance testing was not possible in several circumstances: 1)
raw numbers for the different groups were not provided (e.g., percentages only), 2) measures of variance were
not provided (e.g., standard error), or 3) for ACS data, standard tables including margins of error were not
available and data were pulled from the Microdata portal instead. In keeping with the City’s focus on leading
with race, ISLG tested for statistical significance for differences based on race and ethnicity only, with the
exception of a few select measures.
One thing that is important to keep in mind is that statistical significance is impacted by sample size. There was
a very small sample size for a number of measures across the landscape analysis, particularly for racial and
ethnic groups that represent a smaller proportion of the population. For that reason, it is possible that
meaningful differences were not statistically significant in the data that was able to be included here, but would
have been had a larger sample size been possible.
Where statistical testing could not be conducted, ISLG used a set threshold (see How Information is Reported)
to establish whether or not to call two numerical findings different based on the magnitude of differences that
tended to appear as meaningful or significant in the background research reviewed. Despite the use of set
thresholds, caution should be used in drawing conclusions about the differences between groups where
statistical significance could not be conducted.
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Poverty and Food Security
Poverty Status
Disparities in poverty rates were found for almost every characteristic examined, including race and
ethnicity, family composition, and educational attainment; the one exception was disability status. Within
racial and ethnic groups, poverty rates were highest for Native Americans, with almost one in four living
in poverty; followed by Blacks, Asians, and Hispanic/Latinx, roughly one in five of whom lived in poverty.
Due to small sample sizes, however, only the rates for Hispanic/Latinx and other race individuals were
statistically significantly different from overall rates. Family composition also had in impact on poverty
rates, with households led by single mothers almost four times more likely to live in poverty as
households overall, and households led by single fathers two-and-a-half times more likely to live in
poverty than households overall. Poverty rates were three times higher for adults who did not complete
high school, although they were similar to the overall rates among individuals with physical or cognitive
disabilities.
Race/ethnicity
Percent of individuals living below the Federal Poverty Level (FPL), 2018
Source: American Community Survey 5-year estimates
Race/ethnicity Population
Number living
below the FPL
Percent living
below the FPL
Difference
from overall
Non-Hispanic white 123,833 19,206 15.51% 1.27%
Hispanic/Latinx* 18,466 3,969 21.49% -4.72%
Asian 5,142 1,033 20.09% -3.31%
Black 2,312 519 22.45% -5.67%
Native American 1,278 315 24.65% -7.87%
Other* 2,458 723 29.41% -12.64%
Overall 154,160 25,861 16.78% -
*Statistically significant at p < .05
Disparity Graph: Racial/ethnic differences in poverty rates
1.27%
-4.72%
-3.31%
-5.67%
-7.87%
-12.64%-14.00%
-12.00%
-10.00%
-8.00%
-6.00%
-4.00%
-2.00%
0.00%
2.00%
Non-Hispanic
white
Hispanic/Latinx Asian Black Native American Other
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Family composition
Percent of family households living below the Federal Poverty Level (FPL), 20165
Source: American Community Survey 5-year estimates
Household type for families† Population
Number living
below the FPL
Percent living
below the FPL
Difference
from overall
Married-couple family, no children 14,485 393 2.71% 4.21%
with children 11,677 542 4.64% 2.29%
Male householder, no spouse present,
no children 914 88 9.63% -2.70%
with children 1,201 209 17.40% -10.47%
Female householder, no spouse
present, no children 1,555 167 10.74% -3.81%
with children 3,326 898 27.00% -20.07%
Overall 33,158 2,297 6.93% -
† Statistical significance testing was not possible for this measure, so caution is advised in interpreting
results
Disparity Graph: Family composition differences in poverty rates
Disability Status
Percent of individuals living below the Federal Poverty Level (FPL), 2018
Source: American Community Survey 5-year estimates
Disability status† Population
Number living
below the FPL
Percent living
below the FPL
Difference
from overall
With a disability 11,953 3,698 19.5% -1.3%
Without a disability 114,964 21,721 18.1% 0.1%
Overall 126,917 25,419 18.2% -
† Statistical significance testing was not possible for this measure, so caution is advised in interpreting
results
5 More recent data were not available for family composition estimates.
4.21%2.29%
-2.70%
-10.47%
-3.81%
-20.07%-25.00%
-20.00%
-15.00%
-10.00%
-5.00%
0.00%
5.00%
10.00%
Married-couple
family, no children
with children Male householder,
no spouse present,
no children
with children Female householder,
no spouse present,
no children
with children
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Disparity Graph: Disability status differences in poverty rates
Educational Attainment
Percent of individuals 25 years or older living below the Federal Poverty Level (FPL), 2018
Source: American Community Survey 5-year estimates
Educational attainment† Population
Number living
below the FPL
Percent living
below the FPL
Difference from
overall
Less than high school graduate 3,072 832 27.08% -18.11%
High school graduate (includes
equivalency) 13,641 1,734 12.71% -3.74%
Some college or associate degree 24,964 2,769 11.09% -2.12%
Bachelor's degree or higher 51,168 2,999 5.86% 3.12%
Overall 92,845 8,334 8.98% -
† Statistical significance testing was not possible for this measure, so caution is advised in interpreting
results
Disparity Graph: Educational attainment differences in poverty rates
Emergency Fund
Consistent with the findings for poverty rates and income, sizeable racial and ethnic differences were
found in the percentage of respondents with an emergency fund, defined as one covering three months
of expenses or more. While almost half of respondents overall reporting possessing an emergency fund,
only one in four Hispanic/Latinx respondents reported having such a fund—a difference that was
statistically significant. One in three non-Hispanic, non-white respondents had such a fund but the
difference from overall rates was not significant, likely due to small sample size.
-1.3%
0.1%
-2.0%
0.0%
2.0%
With a disability Without a disability
-18.11%
-3.74%
-2.12%
3.12%
-20.00%
-15.00%
-10.00%
-5.00%
0.00%
5.00%
Less than high school
graduate
High school graduate
(includes equivalency)
Some college or associate
degree
Bachelor's degree or higher
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Race/ethnicity
Percentage of respondents reporting having an emergency fund covering three months or more, 2020
Source: City of Fort Collins Our Climate Future Demographics Survey†
Race/ethnicity
Number of
respondents
Number with an
emergency fund
Percent with an
emergency fund
Difference
from overall
Non-Hispanic white 253 137 54.15% 5.59%
Hispanic/Latinx* 37 8 21.62% -26.94%
Non-Hispanic non-white or
multiple 23 7 30.43% -18.13%
Overall 313 152 48.56% -
*Statistically significant at p < .05
† Note that the Our Climate Future Demographic Survey was conducted as part of a larger community
engagement strategy and may not be fully representative of all segments of the population
Disparity Graph: Racial/ethnic differences in possessing emergency funds
Use of Food Assistance Programs
The differences found in receipt of Supplemental Nutrition Assistance Program (SNAP) benefits suggest
disparities in both economic circumstances and food security, as SNAP may not always be sufficient to
meet families’ needs. Compared to households overall, Native American households were 17 percentage
points more likely to receive SNAP, followed by Black and Hispanic/Latinx households who were 16 and
14 percentage points more likely to receive SNAP, respectively.
Race/ethnicity
Percent of households receiving Supplemental Nutrition Assistance Program (SNAP) benefits, 2018
Source: American Community Survey 5-year estimates
Race/ethnicity of
householder†
Total
households
Number
receiving SNAP
Percent
receiving SNAP
Difference
from overall
Non-Hispanic white 53,554 2,926 5.46% 1.8%
Hispanic/Latinx 5,351 1,112 20.78% -13.5%
Asian 1,843 108 5.86% 1.4%
Black 650 152 23.38% -16.1%
Native American 437 108 24.71% -17.4%
Other 635 143 22.52% -15.2%
Overall 62,470 4,549 7.28% -
† Statistical significance testing was not possible for this measure, so caution is advised in interpreting
results
5.59%
-26.94%
-18.13%
-30.00%
-20.00%
-10.00%
0.00%
10.00%
Non-Hispanic white Hispanic/Latinx Non-Hispanic non-white or multiple
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Disparity Graph: Racial/ethnic differences in SNAP recipiency
Worry About Affording Nutritious Meals
Overall, less than one in ten respondents reported that they were usually or always worried about having
enough money to afford nutritious meals. However, these rates differed by race and ethnicity with
Hispanic/Latinx and other race respondents significantly more likely to report worrying about affording
nutritious meals than respondents overall.
Race/ethnicity (Larimer County)
Percent of individuals reporting that they were usually or always worried or stressed about having enough
money to afford nutritious meals, 2019
Source: Health District of Northern Larimer County Community Health Survey
Race/ethnicity
Number of
respondents
Percent usually or
always worried
Difference
from overall
Non-Hispanic white 2,231 7.5% 1.0%
Hispanic/Latinx or other race*† 224 16.3% -7.8%
Hispanic/Latinx 133 17.2% -8.7%
Non-white non-Hispanic 91 14.8% -6.3%
Overall 2,455 8.5% -
*Statistically significant at p < .05
† Due to small sample size, Hispanic/Latinx and non-white non-Hispanic groups were combined for
statistical significance testing
Disparity Graph: Racial/ethnic differences in worry about affording nutritious meals
1.8%
-13.5%
1.4%
-16.1%-17.4%
-15.2%
-20.0%
-15.0%
-10.0%
-5.0%
0.0%
5.0%
Non-Hispanic white Hispanic/Latinx Asian Black Native American Other
1.0%
-8.7%
-6.3%
-10.0%
-8.0%
-6.0%
-4.0%
-2.0%
0.0%
2.0%
Non-Hispanic white Hispanic/Latinx Non-white non-Hispanic
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Problems with Unsafe Food in Grocery Stores and Restaurants
Roughly 3% of survey respondents reported that unsafe food in restaurants and grocery stores was a
major problem where they lived. There were racial/ethnic disparities in unsafe food being an issue, with
significantly more Hispanic/Latinx and other-race respondents reporting that unsafe food was a problem
for them than respondents in Larimer County overall.
Race/ethnicity (Larimer County)
Percent of individuals reporting that unsafe food in restaurants, grocery stores, etc. is a major problem
where they live, 2019
Source: Health District of Northern Larimer County Community Health Survey
Race/ethnicity
Number of
respondents
Percent reporting unsafe
food is a major problem
Difference
from overall
Non-Hispanic white 2,231 2.4% 0.4%
Hispanic/Latinx or other race* 224 5.7% -2.9%
Overall 2,455 2.8% -
*Statistically significant at p < .05
Disparity Graph: Racial/ethnic differences in unsafe food being a major problem
Income
Household Income
Median household income differed by race and ethnicity, with people of color earning less, on average,
than the population as a whole. Disparities were most pronounced for Hispanic/Latinx, Black, and Native
American households who made 80 cents, 81 cents, and 83 cents, respectively, for every dollar made by
households overall. Differences in income were smaller for Asian households, who made 94 cents on the
dollar, while non-Hispanic white households made $1.04 for each dollar made by households overall. The
differences from the overall median income were significant for non-Hispanic whites, Hispanics/Latinx,
and Blacks.
0.4%
-2.9%-4.0%
-2.0%
0.0%
2.0%
Non-Hispanic White Hispanic/Latinx or other race
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43
Race/ethnicity
Median household income, 2018
Source: American Community Survey 5-year estimates
Race/ethnicity of
householder
Total
households
Median household
income
Difference
from overall
Non-Hispanic white* 53,554 $65,061 $2,929
Hispanic/Latinx* 5,351 $49,646 -$12,486
Asian 1,843 $58,505 -$3,627
Black* 650 $50,614 -$11,518
Native American 437 $51,797 -$10,335
Other 635 $56,679 -$5,453
Overall 62,796 $62,132 -
*Statistically significant at p < .05
Disparity Graph: Racial/ethnic differences in median household income
Personal Earnings
Disparities in personal earnings were found by both sex6 and disability status. For every dollar made by
the average person in Fort Collins, females made 82 cents, while males made $1.20; this translated to
females making 68 cents for every dollar made by males. For every dollar made by individuals without a
physical or cognitive disability, individuals with a disability made 76 cents. Disparities were particularly
pronounced when these characteristics were looked at in combination, with females with a disability
making only 45 cents for every dollar made by the average person in Fort Collins.
Sex
Median personal income for population 16 years and over with earnings, 2018
Source: American Community Survey 5-year estimates
Sex†
Population 16 years and
older with earnings
Median personal
income
Difference
from overall
Male 54,543 $32,378 $5,387.00
Female 49,452 $21,997 -$4,994.00
Overall 103,995 $26,991 -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
6 Note that the American Community Survey asks about sex only, so it is not possible to establish gender.
$2,929
-$12,486
-$3,627
-$11,518 -$10,335
-$5,453
-$15,000
-$10,000
-$5,000
$0
$5,000
Non-Hispanic white Hispanic/Latinx Asian Black Native American Other
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Disparity Graph: Sex differences in personal earnings
Disability Status
Median personal earnings for individuals 16 and over
Source: American Community Survey 5-year estimates, 2018
Disability status
Population 16
years and older
Median personal
earnings
Difference
from overall
With a disability 4,917 $20,860 -$6,051.00
Without a disability 98,146 $27,295 $384.00
Overall 133,190 $26,991
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Disability status differences in personal earnings
Sex and disability status
Median personal earnings for individuals 16 and over
Source: American Community Survey 5-year estimates, 2018
Sex and disability status†
Median personal
earnings
Difference
from overall
Male with a disability $23,929 -$2,982
Male without a disability $33,522 $6,611
Female with a disability $12,209 -$14,702
Female without a disability $22,307 -$4,604
Overall $26,991 -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
$5,387.00
-$4,994.00-$6,000.00
-$4,000.00
-$2,000.00
$0.00
$2,000.00
$4,000.00
$6,000.00
Male Female
-$6,051.00
$384.00
-$8,000.00
-$6,000.00
-$4,000.00
-$2,000.00
$0.00
$2,000.00
With a disability Without a disability
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Disparity Graph: Racial/ethnic differences in median household income
High Wage Occupations
High wage occupations include those in management occupations; legal occupations; healthcare
practitioner and technical occupations; computer and mathematical occupations; architecture and
engineering occupations; life, physical, and social science occupations; and business and financial
operations occupations. Disparities were found in employment in high wage occupations by race and
ethnicity and by educational attainment; there were only minimal differences by sex7 and disability.
Within racial and ethnic groups, employment in high wage occupations was lowest for Black and
Hispanic/Latinx workers, only about one in four of whom were employed in high wage occupations—
close to one and a half times less likely than workers overall. Adult workers who did not complete high
school were more than seven times less likely to be employed in high wage occupations than workers
overall, and almost three times lower for those with a high school education of GED; the percentage was
20 points higher than overall, however, for workers with a graduate degree.
Race/Ethnicity
Percentage of workers employed in high wage occupations, 2018
Source: American Community Survey Public Use Microdata Sample 5-year estimates
Race/ethnicity† Population
Number in high
wage occupations
Percent in high
wage occupations
Difference
from overall
White 91,878 32,082 34.9% 1.7%
Hispanic/Latinx 11,979 2,683 22.4% -10.8%
Asian 3,561 1,174 33.0% -0.2%
Black 1,371 337 24.6% -8.6%
Other 2,855 823 28.8% -4.4%
Overall 111,644 37,099 33.2% -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
7 Note that the American Community Survey asks about sex only, so it is not possible to establish gender.
-$2,982
$6,611
-$14,702
-$4,604
-$20,000
-$15,000
-$10,000
-$5,000
$0
$5,000
$10,000
Male with a disability Male without a disability Female with a disability Female without a disability
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Disparity Graph: Racial/ethnic differences in high wage occupations
Sex
Percentage of workers employed in high wage occupations, 2018
Source: American Community Survey Public Use Microdata Sample 5-year estimates
Sex† Population
Number in high
wage occupations
Percent in high
wage occupations
Difference
from overall
Male 59,147 21,076 35.6% 2.40%
Female 52,497 16,023 30.5% -2.70%
Overall 111,644 37,099 33.2% -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Sex differences in high wage occupations
Disability Status
Percentage of workers employed in high wage occupations, 2018
Source: American Community Survey Public Use Microdata Sample 5-year estimates
Disability Status Population
Number in high
wage occupations
Percent in high
wage occupations
Difference
from overall
With a disability 4,646 1,347 29.0% -4.2%
Without a disability 106,998 35,752 33.4% 0.2%
Overall 111,644 37,099 33.2% -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
1.7%
-8.6%
-10.8%
-0.2%
-4.4%
-12.0%
-10.0%
-8.0%
-6.0%
-4.0%
-2.0%
0.0%
2.0%
4.0%
White Black Hispanic/Latinx Asian Other
2.40%
-2.70%-4.00%
-2.00%
0.00%
2.00%
4.00%
Male Female
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Disparity Graph: Disability status differences in high wage occupations
Educational Attainment
Percentage of workers employed in high wage occupations, 2018
Source: American Community Survey Public Use Microdata Sample 5-year estimates
Educational attainment Population
Number in high
wage occupations
Percent in high
wage occupations
Difference
from overall
Less than a high school degree 4,653 352 7.6% -25.6%
High school graduate (includes
equivalency) 15,511 1,849 11.9% -21.3%
Some college or associate degree 37,218 8,253 22.2% -11.0%
Bachelor's degree 34,448 15,396 44.7% 11.5%
Graduate degree 19,814 11,249 56.8% 23.6%
Overall 111,644 37,099 33.2% -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Educational attainment differences in high wage occupations
Low Income Status
Similar to poverty status, pronounced racial and ethnic disparities were found when examining low-
income status, defined as living below 125% of the poverty level. Overall, roughly one in four people were
low income, but rates were significantly higher for Hispanics/Latinx, Blacks—as high as almost one in
three for Blacks—, and people from other racial groups. Notably, the rate was significantly lower for non-
Hispanic whites although the difference from overall was small.
-4.2%
0.2%
-6.0%
-4.0%
-2.0%
0.0%
2.0%
With a disability Without a disability
-31.1%
-23.7%
-11.8%
10.8%
20.2%
-40.0%
-30.0%
-20.0%
-10.0%
0.0%
10.0%
20.0%
30.0%
Less than a high school
degree
High school graduate
(includes equivalency)
Some college or
associate degree
Bachelor's degree Graduate degree
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Race/ethnicity
Percent of individuals living below 125% of the Federal Poverty Level (FPL), 2018
Source: American Community Survey 5-year estimates
Race/ethnicity Population
Percent living below
125% of the FPL
Difference from
overall
Non-Hispanic white* 123,833 19.2% 1.60%
Hispanic/Latinx* 18,466 27.5% -6.70%
Asian 5,142 25.2% -4.40%
Black* 2,312 30.4% -9.60%
Native American 1278 26.5% -5.70%
Other* 2,458 32.6% -11.80%
Overall 154,160 20.8% -
*Statistically significant at p < .05
Disparity Graph: Racial/ethnic differences in low-income status
Employment
Labor Force Nonparticipation
Participation in the labor force indicates that an individual is either employed or actively seeking work.
While in some cases nonparticipation can be voluntary due to retirement or other factors, it can also
indicate chronic unemployment or inability to work for other reasons. Almost a third of Fort Collins
residents across racial and ethnic groups were not participating in the labor force, with minimal
differences across groups. Disparities were pronounced for individuals with disabilities, however, with
almost two thirds not participating, a rate more than twice the overall rate.
1.60%
-6.70%
-4.40%
-9.60%
-5.70%
-11.80%-14.00%
-12.00%
-10.00%
-8.00%
-6.00%
-4.00%
-2.00%
0.00%
2.00%
4.00%
Non-Hispanic
white
Hispanic/Latinx Asian Black Native American Other
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Race/ethnicity
Percent of individuals age 16 and older who are not in the labor force, 2018
Source: American Community Survey 5-year estimates
Race/ethnicity
Population 16
and over
Percent not in
labor force
Difference
from overall
Non-Hispanic white 110,427 29.70% 0.20%
Hispanic/Latinx 14,283 30.30% -0.40%
Asian 4,762 31.60% -1.70%
Black 2,249 28.00% 1.90%
Native American 1117 31.20% -1.30%
Other 1,896 28.30% 1.60%
Overall 135,025 29.90% -
Disparity Graph: Racial/ethnic differences in labor force nonparticipation
Disability status
Percent of individuals age 18-64 who are not in the labor force, 2018
Source: American Community Survey 5-year estimates
Disability status†
Population 16 and
over
Percent not in
labor force
Difference
from overall
With a disability 12,495 64.80% -35.80%
Without a disability 120,695 25.30% 3.70%
Overall 133,190 29.00% -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Disability status differences in labor force nonparticipation
0.20%
-0.40%
-1.70%
1.90%
-1.30%
1.60%
-2.00%
-1.00%
0.00%
1.00%
2.00%
3.00%
White Hispanic/Latinx Asian Black Native American Other
-35.80%
3.70%
-40.00%
-35.00%
-30.00%
-25.00%
-20.00%
-15.00%
-10.00%
-5.00%
0.00%
5.00%
10.00%
With a disability Without a disability
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Unemployment
While racial and ethnic differences in unemployment rates were found, these differences did not reach
statistical significance, likely due to small sample size. Unemployment rates were also higher than the
overall employment rate for individuals with disabilities.
Race/ethnicity
Percent of individuals age 16 and older in the labor force that are unemployed, 2018
Source: American Community Survey 5-year estimates, 2018
Race/ethnicity
Population 16 and
over
Percent
unemployed
Difference
from overall
Non-Hispanic white 110,427 5.70% 0.20%
Hispanic/Latinx 14,283 7.80% -1.90%
Asian 4,762 4.80% 1.10%
Black 2,249 4.20% 1.70%
Native American 1117 12.40% -6.50%
Other 1,896 14.40% -8.50%
Overall 135,025 5.90% -
Disparity Graph: Racial/ethnic differences in unemployment rates
Disability status
Percent of individuals age 18-64 in the labor force that are unemployed, 2018
Source: American Community Survey 5-year estimates
Disability status†
Population 18-64
years
Number
unemployed
Percent
unemployed
Difference
from overall
With a disability 3,770 440 11.67% -5.8%
Without a disability 86,325 4,868 5.64% 0.3%
Overall 90,095 5,308 5.89% -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
0.20%
-1.90%
1.10%1.70%
-6.50%
-8.50%-10.00%
-8.00%
-6.00%
-4.00%
-2.00%
0.00%
2.00%
4.00%
Non-Hispanic
white
Hispanic/Latinx Asian Black Native American Other
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Disparity Graph: Disability status differences in unemployment rates
Use of Work-Related or Employment Services
Four percent of respondents overall reported having needed and used work-related or employment
services, and these rates did not differ by race and ethnicity. Additionally, while a somewhat higher
percentage of LGBQ+ than respondents overall reported having needed and used services, this difference
was not significant.
Race/Ethnicity (Larimer County)
Percent of survey respondents who reported needing and using work-related or employment services
(job training or help finding work), 2019
Source: Health District of Northern Larimer County Community Health Survey
Race/ethnicity
Percent using
services
Difference
from overall
Non-Hispanic White 4.0% 0.1%
Hispanic/Latinx or other race 4.5% -0.4%
Overall 4.1%
Disparity Graph: Racial/ethnic differences in using employment services
Sexual Orientation (Larimer County)
Percent of survey respondents who reported needing and using work-related or employment services
(job training or help finding work), 2019
Source: Health District of Northern Larimer County Community Health Survey
Sexual orientation
Percent using
services
Difference
from overall
Straight 3.6% 0.5%
LGBQ+ 8.3% -4.2%
Overall 4.1% -
-5.8%
0.3%
-8.0%
-6.0%
-4.0%
-2.0%
0.0%
2.0%
With a disability Without a disability
0.1%
-0.4%-1.0%
0.0%
1.0%
Non-Hispanic White Hispanic/Latinx or other race
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Disparity Graph: Sexual orientation differences in using employment services
Needed But Did Not Use Work-Related or Employment Services
Almost an identical percentage to the percentage who needed and used work-related or employment
services reported having needed but not used such services—approximately 4%. While the percentage
was somewhat higher for Hispanic/Latinx respondents than for respondents overall, this difference was
not statistically significant. Similarly, while a higher percentage of LGBQ+ respondents than respondents
overall reported needing but not using work-related or employment services, this difference was not
statistically significant.
Race/Ethnicity (Larimer County)
Percent of survey respondents who reported needing but not using work-related or employment services
(job training or help finding work), 2019
Source: Health District of Northern Larimer County Community Health Survey
Race/ethnicity
Percent needing but
not using services
Difference
from overall
Non-Hispanic white 3.3% 1.0%
Hispanic/Latinx or other race† 9.8% -5.5%
Hispanic/Latinx 8.7% -4.4%
Non-White Non-Hispanic 11.7% -7.4%
Overall 4.3% -
† Due to small sample size, Hispanic/Latinx and non-white non-Hispanic groups were combined for
statistical significance testing
Disparity Graph: Racial/ethnic differences in needing but not using employment services
0.5%
-4.2%-6.0%
-4.0%
-2.0%
0.0%
2.0%
Straight LGBQ+
1.0%
-4.4%
-7.4%-8.0%
-6.0%
-4.0%
-2.0%
0.0%
2.0%
Non-Hispanic White Hispanic/Latinx Non-White Non-Hispanic
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Sexual Orientation (Larimer County)
Percent of survey respondents who reported needing but not using work-related or employment services
(job training or help finding work), 2019
Source: Health District of Northern Larimer County Community Health Survey
Sexual orientation
Percent needing but
not using services
Difference from
overall
Straight 3.7% 0.6%
LGBQ+ 14.5% -10.2%
Overall 4.3% -
Disparity Graph: Sexual orientation differences in needing but not using employment services
Business Ownership
Representation among Business Owners
Disparities in business ownership were found by race and ethnicity and by sex.8 Hispanics/Latinx were
underrepresented among business owners, among whom the percentage of business owners was
approximately four times less than their percentage in the population. Disparities by sex were also
pronounced, with the percentage of business owned by females 27 percentage points lower than their
representation in the population.
Race and Ethnicity
Representation among business owners, 2018
Source: Annual Business Survey
Race/ethnicity†
Percent of
population
Percent of
business owners
Difference from
population
White, including Hispanic 91.4% 95.8% 4.4%
Hispanic/Latinx 11.7% 2.9% -8.8%
Asian 2.2% 3.2% 1.0%
Black 1.0% 0.3% -0.7%
Native American 0.6% 0.7% 0.1%
Overall 100% 100% -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
8 Note that the Annual Business Survey asks about sex only, so it is not possible to establish gender.
0.6%
-10.2%-12.0%
-10.0%
-8.0%
-6.0%
-4.0%
-2.0%
0.0%
2.0%
Straight LGBQ+
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Disparity Graph: Racial/ethnic differences in representation among business owners
Sex
Representation among business owners, 2018
Source: Annual Business Survey
Sex†
Percent of
population
Percent of
business owners
Difference
from overall
Male 49.5% 59.8% 10.30%
Female 50.5% 24.0% -26.50%
Overall 100% 100%‡ -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
‡ In addition, 16.3% of businesses were equally male/female owned
Disparity Graph: Sex differences in representation among business owners
Childcare
Difficulty Finding Childcare
Roughly seven in 10 respondents across racial and ethnic groups reported having difficulty in finding
childcare or that they did not find the desired childcare program. No significant differences were found
when comparing racial and ethnic groups to respondents overall. When examined by sexual orientation,
more LGBQ+ respondents than respondents overall reported difficulty finding childcare, but this
difference was not statistically significant.
4.4%
-8.8%
1.0%
-0.7%
0.1%
-10.0%
-5.0%
0.0%
5.0%
10.0%
White Hispanic/Latinx Asian Black Native American
10.30%
-26.50%-30.00%
-25.00%
-20.00%
-15.00%
-10.00%
-5.00%
0.00%
5.00%
10.00%
15.00%
Male Female
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Race/ethnicity (Larimer County)
Percent of individuals reporting some or a lot of difficulty finding childcare, or who did not find the
desired program, 2019
Source: Health District of Northern Larimer County Community Health Survey
Race/ethnicity
Percent with difficulty
finding childcare
Difference
from overall
Non-Hispanic white 70.2% 0.1%
Hispanic/Latinx or other race† 72.0% -2.2%
Hispanic/Latinx 73.1% -2.8%
Non-white non-Hispanic 70.2% 0.1%
Overall 70.3% -
† Due to small sample size, Hispanic/Latinx and non-white non-Hispanic groups were combined for
statistical significance testing
Disparity Graph: Racial/ethnic differences in difficulty finding childcare
Sexual Orientation (Larimer County)
Percent of individuals reporting some or a lot of difficulty finding childcare, or who did not find the
desired program, 2019
Source: Health District of Northern Larimer County Community Health Survey
Sexual orientation
Percent with difficulty
finding childcare
Difference
from overall
Straight 70.0% 0.3%
LGBQ+ 86.9% -16.6%
Overall 70.3% -
Disparity Graph: Sexual orientation differences in difficulty finding childcare
0.1%
-2.8%
0.1%
-4.0%
-2.0%
0.0%
2.0%
Non-Hispanic white Hispanic/Latinx Non-white non-Hispanic
0.3%
-16.6%-20.0%
-15.0%
-10.0%
-5.0%
0.0%
5.0%
Straight LGBQ+
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Difficulty Finding Affordable Childcare
Among those with difficulty finding childcare, roughly two in five cited cost as the primary reason for the
difficulty. Interestingly, among those with difficulty finding childcare, non-white, non-Hispanic
respondents were least likely to cite cost as the primary difficulty; however, when comparing non-
Hispanic, non-white respondents as a whole to respondents overall the differences were quite small and
were not statistically significant. Additionally, while LGBQ+ respondents were more likely than
respondents overall to cite cost as the primary reason, this difference was also not statistically significant.
Race/ethnicity (Larimer County)
Percent of individuals reporting cost as the primary reason for difficulty finding childcare, 2019
Source: Health District of Northern Larimer County Community Health Survey
Race/ethnicity
Percent with difficulty
finding affordable childcare
Difference
from overall
Non-Hispanic white 42.1% 0.4%
Hispanic/Latinx or other race† 41.3% -1.20%
Hispanic/Latinx 45.3% -2.8%
Non-white non-Hispanic 25.8% 16.7%
Overall 42.5% -
† Due to small sample size, Hispanic/Latinx and non-white non-Hispanic groups were combined for
statistical significance testing
Disparity Graph: Racial/ethnic differences in difficulty finding childcare due to cost
Sexual Orientation (Larimer County)
Percent of individuals reporting cost as the primary reason for difficulty finding childcare
Source: Health District of Northern Larimer County Community Health Survey, 2019
Sexual orientation
Percent with difficulty
finding affordable childcare
Difference from
overall
Straight 42.0% 0.5%
LGBQ+ 60.5% -18.0%
Overall 42.5% -
0.4%
-2.8%
16.7%
-5.0%
0.0%
5.0%
10.0%
15.0%
20.0%
Non-Hispanic white Hispanic/Latinx Non-white non-Hispanic
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Disparity Graph: Sexual orientation differences in difficulty finding childcare due to cost
Availability of Affordable Childcare
Differences in the reported availability of affordable childcare differed considerably by neighborhood,
although no neighborhood was perceived as having widely available affordable childcare. Residents of
Northeast had the lowest ratings for affordable childcare availability, 12 points lower than the overall
rates, while residents of Southeast rated it as most available, 10 points higher than overall.
Neighborhood
Average rating of availability of affordable quality childcare on a scale of 0 to 100
Source: Fort Collins Community Survey, 2019
Neighborhood
Number of
respondents
Average rating of
affordable quality
childcare
Difference
from
overall
Northeast 78 26 -12
East Central 144 41 3
Southeast 103 37 -1
Northwest/CSU 143 40 2
West Central 131 40 2
Southwest 29 48 10
Overall 626 38 -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Neighborhood differences in availability of affordable childcare ratings
0.5%
-18.0%-20.0%
-15.0%
-10.0%
-5.0%
0.0%
5.0%
Straight LGBQ+
-12
3
-1
2 2
10
-15
-10
-5
0
5
10
15
Northeast East Central Southeast Northwest/CSU West Central Southwest
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Education
Within Education, 15 measures were examined looking at academic achievement, staff representation,
school connections, barriers to academic success, and educational attainment. Racial and ethnic
disparities were found across phases of life and of learning, from third grade reading scores to adult
educational attainment. While early education could not be included in the current analysis, the Poudre
School District is hoping data will be available in future to examine outcomes for the youngest learners.
For the measures examined, Hispanic/Latinx, Black, and/or Native American students often experienced
more negative outcomes, including lower test scores, higher levels of school discipline, and
underrepresentation among teachers and administrators. By contrast, Asian and white students often
had similar or more positive results compared to students overall. Disparities were also found by
economic status and academic performance.
Table 12. Number (percentage) of measures with more positive, equivalent, or more negative outcomes or
perceptions than the overall outcome or perception for each racial and ethnic grouping included
Racial/ethnic group
Number (%) of
measures with
positive outcomes or
perceptions
Number (%) of
measures with
equivalent outcomes
or perceptions
Number (%) of
measures with
negative outcomes
or perceptions
Non-Hispanic White 9 (60%) 6 (40%) 0 (0%)
Hispanic/Latinx 0 (0%) 5 (33%) 10 (67%)
Asian or Pacific Islander 5 (38%) 6 (46%) 2 (15%)
Black 1 (7%) 9 (64%) 4 (29%)
Native American 1 (9%) 4 (36%) 6 (55%)
Other 1 (9%) 7 (64%) 3 (27%)
Non-Hispanic, Non-White 0 (0%) 1 (100%) 0 (0%)
Hispanic and/or Other Race n/a n/a n/a
White, including Hispanic n/a n/a n/a
Data Note: Assessing Differences Between Groups
Wherever possible, statistical testing was conducted in order to see whether differences between the finding
for the overall outcome or perception and the finding for each racial and ethnic group included in the data were
statistically significant. It should be noted that significance testing was not possible in several circumstances: 1)
raw numbers for the different groups were not provided (e.g., percentages only), 2) measures of variance were
not provided (e.g., standard error), or 3) for ACS data, standard tables including margins of error were not
available and data were pulled from the Microdata portal instead. In keeping with the City’s focus on leading
with race, ISLG tested for statistical significance for differences based on race and ethnicity only, with the
exception of a few select measures.
One thing that is important to keep in mind is that statistical significance is impacted by sample size. There was
a very small sample size for a number of measures across the landscape analysis, particularly for racial and
ethnic groups that represent a smaller proportion of the population. For that reason, it is possible that
meaningful differences were not statistically significant in the data that was able to be included here, but would
have been had a larger sample size been possible.
Where statistical testing could not be conducted, ISLG used a set threshold (see How Information is Reported)
to establish whether or not to call two numerical findings different based on the magnitude of differences that
tended to appear as meaningful or significant in the background research reviewed. Despite the use of set
thresholds, caution should be used in drawing conclusions about the differences between groups where
statistical significance could not be conducted.
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Academic Achievement
Third Grade Reading Proficiency
Disparities in third grade reading were found by both race and ethnicity and by income (i.e., free or
reduced lunch status). Hispanic/Latinx third graders were significantly less likely to meet expectations in
reading than third graders overall, while white third graders were significantly more likely to meet them.
While statistical significance testing was not conducted for income, the percentage of economically-
disadvantaged third graders (those eligible for free or reduced lunch) not meeting expectations was 15
points higher than for third graders overall.
Race/ethnicity
Percent of third-grade Poudre School District students not meeting expectations on the English Language
Arts Colorado Measures of Academic Success (CMAS) exam, 2019
Source: Colorado Department of Education
Race/ethnicity
Number of
valid scores
Number not meeting
expectations
Percent not meeting
expectations
Difference
from overall
White* 1,588 119 7.50% 3.76%
Hispanic/Latinx* 359 103 28.70% -17.44%
Asian 69 4 5.80% 5.46%
Black 26 4 15.40% 4.14%
Overall 2,042 230 11.26% -
*Statistically significant at p < .05
Disparity Graph: Racial/ethnic differences in third grade reading
3.76%
-17.44%
5.46%4.14%
-20.00%
-15.00%
-10.00%
-5.00%
0.00%
5.00%
10.00%
White Hispanic/Latinx Asian Black
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Free or Reduced Lunch Status
Percent of third-grade Poudre School District students not meeting expectations on the English Language
Arts Colorado Measures of Academic Success (CMAS) exam, 2019
Source: Colorado Department of Education
Free or reduced
lunch status†
Number of
valid scores
Number not meeting
expectations
Percent not meeting
expectations
Difference
from overall
Not eligible 1,506 74 4.90% 6.47%
Eligible 632 169 26.70% -15.33%
Overall 2,138 243 11.37% -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Income (free or reduced lunch) status differences in third grade reading
Third Grade Math Proficiency
Similar racial and ethnic disparities to those found in third grade reading were found in third grade math;
Hispanic/Latinx third graders were more likely and white third graders were less likely not to meet
expectations than third graders overall. Additionally, the percentage of economically-disadvantaged third
graders (those eligible for free or reduced lunch) not meeting expectations was 10 points higher than for
third graders overall.
Race/ethnicity
Percent of third-grade Poudre School District students not meeting expectations on the Math Colorado
Measures of Academic Success (CMAS) exam, 2019
Source: Colorado Department of Education
Race/ethnicity
Number of valid
scores
Number not meeting
expectations
Percent not meeting
expectations
Difference
from overall
White* 1,589 71 4.39% 3.23%
Hispanic/Latinx* 381 78 20.20% -12.77%
Black 26 3 11.53% -3.84%
Two or More Races 82 8 9.63% -2.06%
Overall 2,078 160 7.44% -
*Statistically significant at p < .05
6.47%
-15.33%-20.00%
-15.00%
-10.00%
-5.00%
0.00%
5.00%
10.00%
Not Eligible Eligible
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Disparity Graph: Racial/ethnic differences in third grade math
Free or Reduced Lunch Status
Percent of third-grade Poudre School District students not meeting expectations on the Math Colorado
Measures of Academic Success (CMAS) exam, 2019
Source: Colorado Department of Education
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Income (free or reduced lunch) status differences in third grade math
AP Enrollment
Participation in advanced placement (AP) classes was assessed using rates, since it was not possible to
determine the extent to which individual students were enrolled in multiple AP classes. Using that metric,
rates of enrollment in AP classes differed considerably by race and ethnicity with rates almost 23 and 13
percentage points lower for Hispanic/Latinx and Native American students than the overall AP enrollment
rate, respectively; enrollment rates were almost 61 percentage points higher than overall for Asian or
Pacific Islander students.
3.23%
-12.77%
-3.84%
-2.06%
-15.00%
-10.00%
-5.00%
0.00%
5.00%
White Hispanic/Latinx Black Two or More Races
4.63
-10.43-15.00
-10.00
-5.00
0.00
5.00
10.00
Not Eligible Eligible
Free or reduced
lunch Status†
Number of valid
scores
Number not meeting
expectations
Percent not meeting
expectations
Difference
from overall
Not eligible 1,525 43 2.81 4.62
Eligible 677 121 17.87 -10.42
Overall 2,202 164 7.44
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Race/ethnicity
Number of AP enrollments per 100 students of the same race/ethnicity in the Poudre School District,
2017-2018
Source: Colorado Department of Education
Race/ethnicity†
Total students
enrolled
Number of AP
enrollments
AP enrollment
rate
Difference
from overall
White 7,519 3,419 45.47 1.47
Hispanic/Latinx 1,565 331 21.15 -22.85
Asian or Pacific Islander 367 384 104.63 60.63
Black 127 59 46.46 2.46
Native American 45 14 31.11 -12.89
Two or more races 377 193 51.19 7.19
Overall 10,000 4,400 44.00 -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Racial/ethnic differences in AP enrollment rates
SAT Scores
Average SAT scores differed considerably by both race and ethnicity and income (i.e., free or reduced
lunch status). Scores for Hispanic/Latinx students were 140 points lower than average scores, a significant
difference, while white and Asian students scored significantly higher than average. Scores for students
who were eligible for free or reduced lunch status were 160 points below the overall SAT score.
1.47
-22.85
60.63
2.46
-12.89
7.19
-30.00
-20.00
-10.00
0.00
10.00
20.00
30.00
40.00
50.00
60.00
70.00
White Hispanic/Latinx Asian or Pacific
Islander
Black Native American Two or more races
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Race/ethnicity
Average overall SAT scores of Poudre School District students, 2019
Source: Colorado Department of Education
Race/ethnicity
Number of valid
scores
Mean overall
score
Difference
from overall
White* 1,349 1,110 26
Hispanic/Latinx* 293 944 -140
Asian* 73 1,240 156
Black 27 989 -95
Two or More Races 68 1,075 -9
Overall 1822 1,084 -
*Statistically significant at p < .05
Disparity Graph: Racial/ethnic differences in SAT scores
Free or Reduced Lunch Status
Average overall SAT scores of Poudre School District students, 2019
Source: Colorado Department of Education
Free or Reduced
Lunch Status
Number of valid
scores
Average
overall score
Difference
from overall
Not eligible 1,430 1,128 44
Eligible 392 924 -160
Overall 1,822 1,084 -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
26
-140
156
-95
-9
-200
-150
-100
-50
0
50
100
150
200
White Hispanic/Latinx Asian Black Two or More Races
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Disparity Graph: Income (free or reduced lunch) status differences in SAT scores
On-Time High School Graduation
In the most recent cohort available, four-year graduation rates differed considerably by race and ethnicity
with rates 26 percentage points lower for Native American students, 18 percentage points lower for
Hispanic/Latinx students, and 12 percentage points lower for Black students than the overall graduation
rate, all significant differences. Graduation rates for Asian or Pacific Islander and white students were
significantly higher, 15 and four percentage points higher than overall rates, respectively.
Race/ethnicity
Percent of Poudre School District high school students graduating within four years, 2018-2019
Source: Colorado Department of Education Graduation Statistics
Race/ethnicity
Number of
students in cohort
Number graduating
in four years
Percent graduating
in four years
Difference
from overall
White* 1,584 1,383 87.31% 4.12%
Hispanic/Latinx* 368 239 64.95% -18.25%
Asian or Pacific Islander* 66 65 98.48% 15.29%
Black* 38 27 71.05% -12.14%
Native American* 14 8 57.14% -26.05%
Two or more races 96 80 83.33% 0.14%
Overall 2,166 1,802 83.19% -
*Statistically significant at p < .05
Disparity Graph: Racial/ethnic differences in on-time high school graduation
44
-160-200
-150
-100
-50
0
50
100
Not Eligible Free/Reduced Lunch Eligible
4.12%
-18.25%
15.29%
-12.14%
-26.05%
0.14%
-30.00%
-25.00%
-20.00%
-15.00%
-10.00%
-5.00%
0.00%
5.00%
10.00%
15.00%
20.00%
White Hispanic/Latinx Asian or Pacific
Islander
Black Native American Two or more races
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Staff Representation
Teacher Representation
There were disparities in teacher representation in the Poudre School District with all non-white racial
and ethnic groups underrepresented compared to the overall representation rates. Asian and
Hispanic/Latinx students were least represented with rates roughly five points lower than the overall
rates.
Race/ethnicity
Number of Poudre School District teachers per 100 students of the same race, 2019-2020
Source: Colorado Department of Education
Race/ethnicity†
Student
population
Number of
teachers
Representation
rate
Difference
from overall
White 22,406 1,752 7.82 1.45
Hispanic/Latinx 5,724 102 1.78 -4.58
Asian 890 12 1.35 -5.02
Black 359 9 2.51 -3.86
Native American 165 6 3.64 -2.73
Overall 29,544 1,881 6.37 -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Racial/ethnic differences in teacher representation
Principal Representation
While smaller than for teacher representation, disparities were still noted in principal representation in
the Poudre School District with Hispanic/Latinx, Asian, and Black students somewhat more likely to be
underrepresented among principals than students overall. The representation rate was highest for Native
Americans, although it should be noted that this is in part due to the small number of Native American
students; the total number of Native American principals was two.
1.45
-4.58 -5.02
-3.86
-2.73
-6
-4
-2
0
2
White Hispanic/Latinx Asian Black Native American
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Race/ethnicity
Number of Poudre School District principals and assistant principals per 1,000 students of the same race
Source: Colorado Department of Education, 2019-2020
Race/ethnicity†
Student
population
Number of
principals
Representation
rate
Difference
from overall
White 22,406 101 4.5 0.60
Hispanic/Latinx 5,724 10 1.7 -2.18
Asian 890 2 2.2 -1.68
Black 359 1 2.8 -1.14
Native American 165 2 12.1 8.19
Overall 29,544 116 3.9 -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Racial/ethnic differences in principal representation
School Connections
Student-to-Adult Connections
Student-to-adult connections represents the extent to which Poudre School District students report
feeling connected to, understood by, and supported by teachers and other adults at their school. Overall,
students responded positively to approximately nine in 10 questions, and any differences among students
from different racial and ethnic groups were small. The same was true when looking at levels of support,
a measure of how students are performing across district and state assessments.
0.6
-2.18 -1.68 -1.14
8.19
-4
-2
0
2
4
6
8
10
White Hispanic/Latinx Asian Black Native American
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Race/ethnicity
Percent of questions about student-to-adult connections receiving positive responses, 2019
Source: PSD Secondary Student Connections Survey, Middle School
Race/ethnicity†
Middle school
students
Percent of questions
with positive responses
Difference
from overall
White 4,331 91.6% 0.2%
Hispanic/Latinx 1,114 89.6% -1.8%
Asian or Pacific Islander 172 93.8% 2.4%
Black 65 87.5% -3.9%
Native American 26 92.7% 1.3%
Two or More Races 228 89.8% -1.6%
Overall 5,936 91.4% -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Racial/ethnic differences in student-to-adult connections
Level of Support
Levels of Support are a measure of how students are performing across district and state assessments
and to identify students who may need additional support to improve academic outcomes. The four
levels range from Additional Support—students with test score indicating the need for more targeted
academic support—to Exceptional Outcomes—students with test scores in the upper percentiles.
Percent of questions about student-to-adult connections receiving positive responses, 2019
Source: PSD Secondary Student Connections Survey, Middle School
Level of Support (LOS) †
Middle school students
with the same LOS
category for Math and ELA
Percent of questions
with positive responses
Difference
from overall
LOS 1: Additional Support 426 86.8% -4.6%
LOS 2: Team Awareness 440 87.3% -4.1%
LOS 3: Met Targets 3,075 93.2% 1.8%
LOS 4: Exceptional Outcomes 95 95.2% 3.8%
Overall 4,036 91.4% -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
0.2%
-1.8%
2.4%
-3.9%
1.3%
-1.6%
-6.0%
-4.0%
-2.0%
0.0%
2.0%
4.0%
White Hispanic/Latinx Asian or Pacific
Islander
Black Native American Two or More Races
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Disparity Graph: Level of Support differences in student-to-adult connections
Student-to-Student Connections
Student-to-student connections represents the extent to which Poudre School District students report
feeling connected to, understood by, and supported by other students at their school. Overall 86% of
students across racial and ethnic groups responded positively about the student-to-student connections
at their school, and the differences between racial and ethnic groups were small. The same was true for
students with differing levels of academic performance (i.e., Levels of Support).
Race/ethnicity
Percent of questions about student-to-student connections receiving positive responses, 2019
Source: PSD Secondary Student Connections Survey, Middle School
Race/ethnicity†
Middle school
students
Percent of questions with
positive responses
Difference from
overall
White 4,331 86.0% 0.2%
Hispanic/Latinx 1,114 85.1% -0.7%
Asian or Pacific Islander 172 89.8% 4.0%
Black 65 81.2% -4.6%
Native American 26 81.2% -4.6%
Two or More Races 228 83.9% -1.9%
Overall 5,936 85.8% -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Racial/ethnic differences in student-to-student connections
-4.6%-4.1%
1.8%
3.8%
-6.0%
-4.0%
-2.0%
0.0%
2.0%
4.0%
6.0%
LOS 1: Additional Support LOS 2: Team Awareness LOS 3: Met Targets LOS 4: Exceptional Outcomes
0.2%
-0.7%
4.0%
-4.6%-4.6%
-1.9%
-6.0%
-4.0%
-2.0%
0.0%
2.0%
4.0%
6.0%
White Hispanic/Latinx Asian or Pacific
Islander
Black Native American Two or More Races
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Level of Support
Percent of questions about student-to-student connections receiving positive responses, 2019
Source: PSD Secondary Student Connections Survey, Middle School
Level of Support (LOS) †
Middle school students
with the same LOS
category for Math and ELA
Percent of questions with
positive responses
Difference
from overall
LOS 1: Additional Support 426 81.8% -4.0%
LOS 2: Team Awareness 440 83.5% -2.3%
LOS 3: Met Targets 3,075 87.3% 1.5%
LOS 4: Exceptional Outcomes 95 87.2% 1.4%
Overall 4,036 85.8% -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Level of Support differences in student-to-student connections
Barriers to Academic Success
High School Dropout Rates
Overall rates were quite low, with only one in 100 students dropping out of high school. Because base
rates were so low, the differences between different racial and ethnic groups were also quite small.
However, it is worth noting that dropout rates among Native American, Hispanic/Latinx, and Black
students were twice as high as for students overall and the difference in rates from the overall rate was
significant for Hispanic/Latinx students.
Race/ethnicity
Percent of Poudre School District students dropping out of high school, 2017-2018
Source: City of Fort Collins Social Sustainability Gaps Analysis—2020 update
Race/ethnicity Total students
Number
dropping out
Percent
dropping out
Difference
from overall
White* 10,811 77 0.70% 0.30%
Hispanic/Latinx* 2,664 58 2.20% -1.20%
Asian or Pacific Islander 521 1 0.20% 0.80%
Black 201 4 2.00% -1.00%
Native American 91 2 2.20% -1.20%
Two or More Races 568 6 1.10% -0.10%
Overall 14,856 148 1.00% -
*Statistically significant at p < .05
-4.0%
-2.3%
1.5%1.4%
-6.0%
-4.0%
-2.0%
0.0%
2.0%
LOS 1: Additional Support LOS 2: Team Awareness LOS 3: Met Targets LOS 4: Exceptional
Outcomes
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Disparity Graph: Racial/ethnic differences in high school dropout rates
School Discipline
Stark disparities in school discipline were found for students of color in the Poudre School District. Native
American students were three times more likely than students overall to experience school discipline;
Black and Hispanic/Latinx students were approximately twice as likely to experience school discipline as
students overall.
Race/ethnicity
Percent of Poudre School District students who received discipline,9 2018-2019
Source: Colorado Department of Education
Race/ethnicity Total students
Number of students
disciplined
Percent of students
disciplined
Difference
from overall
White* 22,255 866 3.89% 1.15%
Hispanic/Latinx* 5,581 518 9.28% -4.24%
Asian or Pacific Islander* 936 23 2.46% 2.58%
Black* 369 37 10.03% -4.98%
Native American* 167 25 14.97% -9.93%
Two or more races 1,155 67 5.80% -0.76%
Overall 30,463 1,536 5.04% -
*Statistically significant at p < .05
Disparity Graph: Racial/ethnic differences in school discipline
9 Discipline includes classroom removal, in school suspension, out of school suspension, expulsion, referral to law
enforcement, and school related arrest.
0.30%
-1.00%-1.20%
0.80%
-1.20%
-0.10%
-2.00%
-1.00%
0.00%
1.00%
White Hispanic/Latinx Asian or Pacific
Islander
Black Native American Two or More Races
1.15%
-4.24%
2.58%
-4.98%
-9.93%
-0.76%
-12.00%
-10.00%
-8.00%
-6.00%
-4.00%
-2.00%
0.00%
2.00%
4.00%
White Hispanic/Latinx Asian or Pacific
Islander
Black Native American Two or more races
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School-Based Summonses and Arrests
Among different types of school discipline, some of the most severe involve legal summonses or arrests.
While differences were found in school-based summonses and arrests by ethnicity, they were smaller
than for school discipline overall. Rates were not available for other individual racial groups.
Race/ethnicity
Number of instances of summons and arrests per 1,000 students of the same race in the Poudre School
District, 2018-2019
Source: Colorado Department of Education
Race/ethnicity†
Number of
students enrolled
Number of summonses
and arrests
Summonses
and arrests rate
Difference
from overall
Non-Hispanic white 22,252 154 6.92 1.32
Hispanic/Latinx 5,572 82 14.71 -6.47
Other 2,623 15 5.72 2.53
Overall 30,447 251 8.24 -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Racial/ethnic differences in school-based summonses and arrests
School District Mobility
Changing schools, and school districts can disrupt learning, and disparities in school mobility were found
by race and ethnicity. Native American and Black students were three times more likely than students
overall to move in or out of the Poudre School District during the academic year; rates were also higher
for Hispanic/Latinx students although the difference from overall was smaller.
1.32
-6.47
2.53
-8.00
-6.00
-4.00
-2.00
0.00
2.00
4.00
Non-Hispanic White Hispanic/Latinx Other
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Race/ethnicity
Percent of students moving in or out of the Poudre School District, 2017-2018
Source: City of Fort Collins Social Sustainability Gaps Analysis—2020 update
Race/ethnicity Total students
Number moving
in/out of district
Percent moving
in/out of district
Difference
from overall
White* 22,616 1,194 5.28% 1.09%
Hispanic/Latinx* 5,690 493 8.66% -2.29%
Asian or Pacific Islander 998 70 7.01% -0.64%
Black* 408 81 19.85% -13.48%
Native American* 174 38 21.84% -15.47%
Two or More Races* 1,167 102 8.74% -2.37%
Overall 31,053 1,978 6.37% -
*Statistically significant at p < .05
Disparity Graph: Racial/ethnic differences in school district mobility
Educational Attainment
High School Attainment
There were dramatic disparities in educational attainment by race and ethnicity, with one in six
Hispanic/Latinx adults 25 and over not having a high school degree or equivalency compared to one in 28
among Fort Collins adults overall. Native Americans and Asians were also significantly less likely to have
completed high school, although the disparity was larger for the former. In contrast, non-Hispanic whites
and Blacks were significantly more likely to have a high school degree or equivalency.
1.09%
-2.29%
-0.64%
-13.48%
-15.47%
-2.37%
-18.00%
-16.00%
-14.00%
-12.00%
-10.00%
-8.00%
-6.00%
-4.00%
-2.00%
0.00%
2.00%
White Hispanic/Latinx Asian or Pacific
Islander
Black Native American Two or More Races
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Race/ethnicity
Percent of adults age 25 and older that did not attain a high school degree or equivalency, 2018
Source: American Community Survey 5-year estimates
Race/ethnicity
Population 25
and over
Number without
high school degree
Percent without
high school degree
Difference
from overall
Non-Hispanic white* 79,075 1,496 1.89% 1.61%
Hispanic/Latinx* 9,080 1,507 16.60% -13.09%
Asian* 2,926 171 5.84% -2.34%
Black* 1,182 24 2.03% 1.48%
Native American* 796 92 11.56% -8.05%
Other* 1,275 222 17.41% -13.91%
Overall 94,264 3,305 3.51% -
*Statistically significant at p < .05
Disparity Graph: Racial/ethnic differences in high school attainment
Bachelor’s Degree Attainment
Racial and ethnic disparities in attainment of a bachelor’s degree or higher demonstrated similar
disparities to lack a high school diploma, with an attainment rate almost 30 percentage points lower for
Native Americans and 24 percentage points lower for Hispanics/Latinx than for Fort Collins residents
overall. Two notable differences, however, were that Blacks had considerably lower baccalaureate
attainment rates than residents overall, while Asians or Pacific Islanders had considerably higher
attainment rates—a full 22 percentage points higher than the overall rate. Non-Hispanic whites were
more likely to have received a bachelor’s degree or higher than residents overall.
1.61%
-13.09%
-2.34%
1.48%
-8.05%
-13.91%-16.00%
-14.00%
-12.00%
-10.00%
-8.00%
-6.00%
-4.00%
-2.00%
0.00%
2.00%
4.00%
Non-Hispanic white Hispanic/Latinx Asian Black Native American Other
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Race/ethnicity
Percent of adults age 25 and older that have a bachelor’s degree or higher
Source: American Community Survey 5-year estimates, 2018
Race/ethnicity
Population 25
and older
Number with a
bachelor’s
degree or higher
Percent with a
bachelor’s degree
or higher
Difference
from overall
Non-Hispanic white* 79,075 45,334 57.33% 2.8%
Hispanic/Latinx* 9,080 2,744 30.22% -24.3%
Asian* 2,926 2,018 68.97% 14.4%
Black* 1,182 485 41.03% -13.5%
Native American* 796 219 27.51% -27.0%
Other* 1,275 413 32.39% -22.1%
Overall 94,264 51,391 54.52% -
*Statistically significant at p < .05
Disparity Graph: Racial/ethnic differences in attaining a bachelor’s degree or higher
2.8%
-24.3%
14.4%
-13.5%
-27.0%
-22.1%
-30.0%
-25.0%
-20.0%
-15.0%
-10.0%
-5.0%
0.0%
5.0%
10.0%
15.0%
20.0%
Non-Hispanic
white
Hispanic/Latinx Asian Black Native American Other
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Environmental Justice
Across five measures, two different facets of Environmental Justice were explored: reported impact of
pollutants that are experienced on a regular basis such as unclean air and water, and climate vulnerability
factors that may put people at risk in the face of climate change or natural disasters. Racial and ethnic
disparities were found on two of these measures, with a higher percentage of respondents of color than
respondents overall reporting more negative outcomes or perceptions.
Table 13. Number (percentage) of measures with more positive, equivalent, or more negative outcomes or
perceptions than the overall outcome or perception for each racial and ethnic grouping included
Racial/ethnic group
Number (%) of
measures with
positive outcomes or
perceptions
Number (%) of
measures with
equivalent outcomes
or perceptions
Number (%) of
measures with
negative outcomes
or perceptions
Non-Hispanic White 1 (20%) 4 (80%) 0 (0%)
Hispanic/Latinx 0 (0%) 1 (50%) 1 (50%)
Asian or Pacific Islander n/a n/a n/a
Black n/a n/a n/a
Native American n/a n/a n/a
Other n/a n/a n/a
Non-Hispanic, Non-White 0 (0%) 2 (100%) 0 (0%)
Hispanic and/or Other Race 0 (0%) 2 (67%) 1 (33%)
White, including Hispanic n/a n/a n/a
Data Note: Assessing Differences Between Groups
Wherever possible, statistical testing was conducted in order to see whether differences between the finding
for the overall outcome or perception and the finding for each racial and ethnic group included in the data were
statistically significant. It should be noted that significance testing was not possible in several circumstances: 1)
raw numbers for the different groups were not provided (e.g., percentages only), 2) measures of variance were
not provided (e.g., standard error), or 3) for ACS data, standard tables including margins of error were not
available and data were pulled from the Microdata portal instead. In keeping with the City’s focus on leading
with race, ISLG tested for statistical significance for differences based on race and ethnicity only, with the
exception of a few select measures.
One thing that is important to keep in mind is that statistical significance is impacted by sample size. There was
a very small sample size for a number of measures across the landscape analysis, particularly for racial and
ethnic groups that represent a smaller proportion of the population. For that reason, it is possible that
meaningful differences were not statistically significant in the data that was able to be included here, but would
have been had a larger sample size been possible.
Where statistical testing could not be conducted, ISLG used a set threshold (see How Information is Reported)
to establish whether or not to call two numerical findings different based on the magnitude of differences that
tended to appear as meaningful or significant in the background research reviewed. Despite the use of set
thresholds, caution should be used in drawing conclusions about the differences between groups where
statistical significance could not be conducted.
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Pollutants
Problems with Unclean Indoor Air
Overall, only 4% of respondents reported major problems with unclean air where they live. The
percentage was almost twice as high for respondents of color; however, this difference was not
statistically significant.
Race/ethnicity (Larimer County)
Percent of individuals who reported finding unclean indoor air to be a major problem where they live
(mold, radon, etc.), 2019
Source: Health District of Northern Larimer County Community Health Survey
Race/ethnicity
Percent reporting
major problem
Difference
from overall
Non-Hispanic white 3.7% 0.5%
Hispanic/Latinx or other race 8.1% -3.9%
Overall 4.2% -
Disparity Graph: Racial/ethnic differences in major problems with unclean indoor air
Problems with Pollution from Industry
Overall, almost nine in 10 Larimer County respondents reported having major problems with pollution
from industry where they live. The percentage of respondents who found pollution from industry to be a
major problem where they live was almost eight percentage points higher for Hispanic/Latinx
respondents and non-white, non-Hispanic respondents than for respondents overall, but this difference
was not statistically significant.
0.5%
-3.9%-6.0%
-4.0%
-2.0%
0.0%
2.0%
Non-Hispanic white Hispanic/Latinx or other race
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Race/ethnicity (Larimer County)
Percent of individuals who reported finding pollution from industry to be a major problem where they
live, 2019
Source: Health District of Northern Larimer County Community Health Survey
Race/ethnicity
Percent reporting
major problem
Difference
from overall
Non-Hispanic white 10.0% 1.1%
Hispanic/Latinx or other race† 18.9% -7.8%
Hispanic/Latinx 18.2% -7.1%
Non-white non-Hispanic 20.0% -8.9%
Overall 11.1% -
† Due to small sample size, Hispanic/Latinx and non-white non-Hispanic groups were combined for
statistical significance testing
Disparity Graph: Racial/ethnic differences in major problems with pollution from industry
Problems with Unsafe or Unclean Drinking Water
Racial and ethnic disparities in the safety and cleanliness of drinking water were pronounced, with more
than three times as many respondents of color reporting finding unsafe or unclean water for drinking to
be a major problem where they live than respondents overall.
Race/ethnicity (Larimer County)
Percent of individuals who reported finding unsafe or unclean water for drinking to be a major problem
where they live, 2019
Source: Health District of Northern Larimer County Community Health Survey
Race/ethnicity
Number of
respondents
Percent reporting
major problem
Difference
from overall
Non-Hispanic white 2,231 2.8% 0.7%
Hispanic/Latinx or other race*† 224 8.4% -4.9%
Hispanic/Latinx 133 7.2% -3.7%
Non-white non-Hispanic 91 10.9% -7.4%
Overall 2,455 3.5% -
*Statistically significant at p < .05
† Due to small sample size, Hispanic/Latinx and non-white non-Hispanic groups were combined for
statistical significance testing
1.1%
-7.1%-8.9%-10.0%
-8.0%
-6.0%
-4.0%
-2.0%
0.0%
2.0%
Non-Hispanic white Hispanic/Latinx Non-white non-Hispanic
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Disparity Graph: Racial/ethnic differences in major problems with unsafe or unclean drinking water
Climate Vulnerability Factors
Lack of Air Conditioning
Lack of air conditioning is not only a quality of life issue, but can be dangerous in extreme heat
particularly for those in poor health. Overall, approximately one in three respondents reported lacking air
conditioning; while the rate rose to two in five for Hispanic/Latinx respondents, the difference was not
statistically significant.
Race/ethnicity
Percent of individuals reporting that their home has no air conditioning, 2020
Source: City of Fort Collins Our Climate Future Demographic Survey†
Race/ethnicity
Number of
respondents
Number
without AC
Percent
without AC
Difference
from overall
Non-Hispanic white 253 73 29% 1.82%
Hispanic/Latinx 37 15 41% -9.87%
Non-Hispanic non-white or
multiple 23 8 35% -4.11%
Overall 313 96 31%
† Note that the Our Climate Future Demographic Survey was conducted as part of a larger community
engagement strategy and may not be fully representative of all segments of the population
Disparity Graph: Racial/ethnic differences in lacking air conditioning
Mobile Home Occupancy
While there can be advantages to living in mobile homes—and some in the Fort Collins community report
it as a preference—living in a mobile home can also put people at risk in natural disasters; for this reason,
0.7%
-3.7%
-7.4%-8.0%
-6.0%
-4.0%
-2.0%
0.0%
2.0%
Non-Hispanic white Hispanic/Latinx Non-white non-Hispanic
1.82%
-9.87%
-4.11%
-12.00%
-10.00%
-8.00%
-6.00%
-4.00%
-2.00%
0.00%
2.00%
4.00%
Non-Hispanic white Hispanic/Latinx Non-Hispanic non-white or multiple
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from the standpoint of climate vulnerability, it is considered a negative (i.e., riskier) outcome. Large racial
and ethnic differences were found in mobile home occupancy. Overall, only 6% of respondents reported
living in a mobile home, but among Hispanic/Latinx respondents almost two in five reported living in one.
Race/ethnicity
Percent of individuals reporting that they live in a mobile home, 2020
Source: City of Fort Collins Our Climate Future Demographic Survey†
Race/ethnicity
Number of
respondents
Number living in
mobile homes
Percent living in
mobile homes
Difference
from overall
Non-Hispanic white* 253 6 2% 4.02%
Hispanic/Latinx* 37 14 38% -31.45%
Non-Hispanic non-white
or multiple 23 0 0% 6.39%
Overall 313 20 6%
*Statistically significant at p < .05
† Note that the Our Climate Future Demographic Survey was conducted as part of a larger community
engagement strategy and may not be fully representative of all segments of the population
Disparity Graph: Racial/ethnic differences in mobile home occupancy
4.02%
-31.45%
6.39%
-35.00%
-30.00%
-25.00%
-20.00%
-15.00%
-10.00%
-5.00%
0.00%
5.00%
10.00%
Non-Hispanic white Hispanic/Latinx Non-Hispanic non-white or multiple
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Housing
Nine measures within the domain of Housing were explored, looking at affordability, homelessness, and
neighborhood. Racial and ethnic disparities were found in both affordability and homelessness. Where
disparities were present, people of color experienced worse outcomes than the population overall,
although the specific communities impacted varied depending on the measure. Disparities were also
found in housing cost burden by median income and in perceived access to basic needs by neighborhood.
Table 14. Number (percentage) of measures with more positive, equivalent, or more negative outcomes or
perceptions than the overall outcome or perception for each racial and ethnic grouping included
Racial/ethnic group
Number (%) of
measures with
positive outcomes or
perceptions
Number (%) of
measures with
equivalent outcomes
or perceptions
Number (%) of
measures with
negative outcomes
or perceptions
Non-Hispanic White 0 (0%) 7 (100%) 0 (0%)
Hispanic/Latinx 0 (0%) 3 (60%) 2 (40%)
Asian or Pacific Islander 0 (0%) 4 (80%) 1 (20%)
Black 0 (0%) 2 (40%) 3 (60%)
Native American 0 (0%) 2 (40%) 3 (60%)
Other 1 (20%) 2 (40%) 2 (40%)
Non-Hispanic, Non-White n/a n/a n/a
Hispanic and/or Other Race 0 (0%) 3 (75%) 1 (25%)
White, including Hispanic 0 (0%) 2 (100%) 0 (0%)
Data Note: Assessing Differences Between Groups
Wherever possible, statistical testing was conducted in order to see whether differences between the finding
for the overall outcome or perception and the finding for each racial and ethnic group included in the data were
statistically significant. It should be noted that significance testing was not possible in several circumstances: 1)
raw numbers for the different groups were not provided (e.g., percentages only), 2) measures of variance were
not provided (e.g., standard error), or 3) for ACS data, standard tables including margins of error were not
available and data were pulled from the Microdata portal instead. In keeping with the City’s focus on leading
with race, ISLG tested for statistical significance for differences based on race and ethnicity only, with the
exception of a few select measures.
One thing that is important to keep in mind is that statistical significance is impacted by sample size. There was
a very small sample size for a number of measures across the landscape analysis, particularly for racial and
ethnic groups that represent a smaller proportion of the population. For that reason, it is possible that
meaningful differences were not statistically significant in the data that was able to be included here, but would
have been had a larger sample size been possible.
Where statistical testing could not be conducted, ISLG used a set threshold (see How Information is Reported)
to establish whether or not to call two numerical findings different based on the magnitude of differences that
tended to appear as meaningful or significant in the background research reviewed. Despite the use of set
thresholds, caution should be used in drawing conclusions about the differences between groups where
statistical significance could not be conducted.
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Housing Affordability
Housing Cost Burden
Disparities in housing cost burden were found for every characteristic examined including race and
ethnicity, homeowner income, and renter income. Within racial and ethnic groups, housing cost burden
rates were highest for Blacks and Native American households, with one in two households experiencing
cost burden, compared to a third of households overall. Homeowner income also had an impact on
housing cost burden, with households earning 0-30% of the area median income (AMI) three times more
likely to be housing cost burdened than households overall, and those earning 31-80% of the AMI
approximately twice as likely. Similarly, renter households that earned 0-60% of the AMI were
considerably more likely to be housing cost burdened than overall renter households.
Race/ethnicity
Percent of households that are housing cost burdened (spend more than 30% of household income on
rent or owner costs), 2018
Source: American Community Survey Public Use Microdata Sample 5-year estimates
Race/ethnicity of
householder†
Total
households
Number housing
cost burdened
Percent housing
cost burdened
Difference
from overall
White 67,196 23,395 34.80% 0.8%
Hispanic/Latinx 6,886 2,591 37.60% -2.0%
Asian or Pacific Islander 1,913 684 35.80% -0.2%
Black 548 299 54.60% -19.0%
Native American 435 222 51.00% -15.4%
Other 1674 817 48.80% -13.2%
Overall 78,652 28,008 35.60% -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Racial/ethnic differences in housing cost burden
0.8%
-2.0%
-0.2%
-19.0%
-15.4%
-13.2%
-20.0%
-15.0%
-10.0%
-5.0%
0.0%
5.0%
White Hispanic/Latinx Asian or Pacific
Islander
Black Native American Other
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Homeowner income
Percent of owner households that are housing cost burdened (spend more than 30% of household
income on owner costs), by percent area median income for a four-person household, 2020
Source: Feasibility Study for Inclusionary Housing and Affordable Housing Linkage Fees
Homeowner percent
area median income†
Total
Households
Number housing
cost burdened
Percent housing
cost burdened
Difference
from overall
0-30% 2,958 1,854 63.0% -42.0%
31-50% 3,184 1,458 46.0% -25.0%
51-60% 1,461 721 49.0% -28.0%
61-80% 3,662 1,442 39.0% -18.0%
81-100% 3,267 639 20.0% 1.0%
101-120% 2,935 89 3.0% 18.0%
>120% 15,629 798 5.0% 16.0%
Overall 33,096 7,000 21.0% -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Homeowner income differences in housing cost burden
-42.0%
-25.0%-28.0%
-18.0%
1.0%
18.0%16.0%
-50.0%
-40.0%
-30.0%
-20.0%
-10.0%
0.0%
10.0%
20.0%
30.0%
0-30%31-50%51-60%61-80%81-100%101-120%>120%
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Renter income
Percent of renter households that are housing cost burdened (spend more than 30% of household
income on rent and other housing costs), by percent area median income for a four-person household,
2020
Source: Feasibility Study for Inclusionary Housing and Affordable Housing Linkage Fees
Renter percent area
median income
Total
Households
Number housing
cost burdened
Percent housing
cost burdened
Difference
from overall
0-30% 8,951 7,029 79.0% -26.0%
31-50% 5,060 5,047 100.0% -47.0%
51-60% 2,529 1,877 74.0% -21.0%
61-80% 5,912 2,189 37.0% 16.0%
81-100% 3,787 905 24.0% 29.0%
101-120% 2,189 25 1.0% 52.0%
>120% 4,166 228 5.0% 48.0%
Overall 32,594 17,300 53.0% -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Renter income differences in housing cost burden
Worry About Paying Housing Costs
Although the findings for housing cost burden suggest that housing costs are a struggle for many
residents of Fort Collins, only 7% of Larimer County respondents overall reported that they were usually
or always being stressed about paying housing costs. Rates were somewhat higher among Hispanic/Latinx
and/or other race respondents than respondents overall, but this difference did not reach statistical
significance.
-26.0%
-47.0%
-21.0%
16.0%
29.0%
52.0%48.0%
-60.0%
-40.0%
-20.0%
0.0%
20.0%
40.0%
60.0%
0-30%31-50%51-60%61-80%81-100%101-120%>120%
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Race/ethnicity (Larimer County)
Percent of individuals reporting that they were usually or always worried or stressed about paying their
rent or mortgage, 2019
Source: Source: Health District of Northern Larimer County Community Health Survey
Race/ethnicity Number of
respondents
Percent worried
about costs
Difference
from overall
Non-Hispanic white 2,231 5.7% 0.8%
Hispanic/Latinx or other race† 224 11.6% -5.2%
Hispanic/Latinx 133 9.8% -3.3%
Non-white non-Hispanic 91 14.7% -8.2%
Overall 2,455 6.4% -
† Due to small sample size, Hispanic/Latinx and non-white non-Hispanic groups were combined for
statistical significance testing
Disparity Graph: Racial/ethnic differences in worry or stress about paying rent or mortgage
Use of Housing Assistance
Overall, just over 3% of respondents reported having needed and used housing assistance; while
Hispanic/Latinx and/or other race respondents were more likely than non-Hispanic whites to need and
use housing assistance, this difference did not reach significance.
Race/ethnicity (Larimer County)
Percent of individuals reporting that they needed and used housing assistance, 2019
Source: Source: Health District of Northern Larimer County Community Health Survey
Race/ethnicity Percent using
assistance
Difference
from overall
Non-Hispanic white 2.7% 0.7%
Hispanic/Latinx or other race† 7.3% -3.9%
Hispanic/Latinx 5.4% -2.0%
Non-white non-Hispanic 10.7% -7.3%
Overall 3.4% -
† Due to small sample size, Hispanic/Latinx and non-white non-Hispanic groups were combined for
statistical significance testing
0.7%
-3.4%
-8.3%-10.0%
-8.0%
-6.0%
-4.0%
-2.0%
0.0%
2.0%
Non-Hispanic white Hispanic/Latinx Non-white non-Hispanic
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Disparity Graph: Racial/ethnic differences in needing and using housing assistance
Needing But Not Using Housing Assistance
While some of the respondents who reported needed housing assistance received it, there were also
respondents who reported that they needed housing assistance but did not use it (based on the
information available it is not possible to determine the reason that they did not, or were not able, to
make use of housing assistance, however). Racial and ethnic disparities were found, with Hispanic/Latinx
and/or other race respondents considerably more likely to have needed but not used housing assistance
than respondents overall.
Race/ethnicity (Larimer County)
Percent of individuals reporting that they needed but did not use housing assistance
Source: Source: Health District of Northern Larimer County Community Health Survey, 2019
Race/ethnicity Number of
respondents
Percent needing but
not using assistance
Difference
from overall
Non-Hispanic white 2,231 2.6% 1.1%
Hispanic/Latinx or other race*† 224 10.4% -6.7%
Hispanic/Latinx 133 9.3% -5.6%
Non-white non-Hispanic 91 12.3% -8.6%
Overall 2,455 3.7% -
*Statistically significant at p < .05
† Due to small sample size, Hispanic/Latinx and non-white non-Hispanic groups were combined for
statistical significance testing
Disparity Graph: Racial/ethnic differences in needing but not using housing assistance
0.7%
-2.0%
-7.3%-8.0%
-6.0%
-4.0%
-2.0%
0.0%
2.0%
Non-Hispanic white Hispanic/Latinx Non-white non-Hispanic
1.1%
-5.6%
-8.6%-10.0%
-8.0%
-6.0%
-4.0%
-2.0%
0.0%
2.0%
Non-Hispanic white Hispanic/Latinx Non-white non-Hispanic
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Homeownership
Stark racial and ethnic disparities were found in homeownership rates. While roughly half of Fort Collins
households were owner-occupied, the rates were roughly one in five for Black households and two in five
for Hispanic/Latinx and Native American households. Rates of homeownership were comparable to the
overall rates for Asian and non-Hispanic white households.
Race/ethnicity
Percent of householders who live in owner-occupied housing units, 2018
Source: American Community Survey 5-year estimates
Race/ethnicity of
Householder†
Total occupied
housing units
Number owner
occupied
Percent owner
occupied
Difference
from overall
Non-Hispanic white 53,554 29,427 54.95% 1.8%
Hispanic/Latinx 5,351 2,252 42.09% -11.0%
Asian 1,843 965 52.36% -0.8%
Black 650 133 20.46% -32.7%
Native American 437 204 46.68% -6.5%
Other 635 236 37.17% -16.0%
Overall 62,796 33,367 53.14% -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Racial/ethnic differences in homeownership
Home Loan Denials
Racial and ethnic disparities in the approval of home loan applications by race and ethnicity were found.
Hispanic/Latinx applicants were particularly likely to be denied home loans. While overall denial rates
1.8%
-11.0%
-0.8%
-32.7%
-6.5%
-16.0%
-35.0%
-30.0%
-25.0%
-20.0%
-15.0%
-10.0%
-5.0%
0.0%
5.0%
Non-Hispanic white Hispanic/Latinx Asian Black Native American Other
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were just under 11% for applicants overall, they were two times higher than overall for Hispanic/Latinx
applicants.
Race/ethnicity
Percent of home loan applications that are denied by the financial institution, 2019
Source: Home Mortgage Disclosure Act data
Race/ethnicity†
Number of
applications Percent denied
Difference
from overall
White 10,485 10.2% 0.7%
Hispanic/Latinx 631 23.5% -12.6%
Asian or Pacific Islander 320 7.2% 3.7%
Black 57 15.8% -4.9%
Native American 35 14.3% -3.4%
Joint/two or more 589 11.4% -0.5%
Overall 12,117 10.9% -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Racial/ethnic differences in home loan denials
Homelessness
Sheltered Homelessness
Dramatic racial disparities in sheltered homelessness (i.e., housed in emergency shelters or transitional
housing) were found, with sheltered homelessness rates more than four times higher than the overall
rate for Blacks, and approximately three-and-a-half times higher for Native Americans and Asians or
Pacific Islanders.
0.7%
-12.6%
3.7%
-4.9%
-3.4%
-0.5%
-14.0%
-12.0%
-10.0%
-8.0%
-6.0%
-4.0%
-2.0%
0.0%
2.0%
4.0%
6.0%
White Hispanic/Latinx Asian or Pacific
Islander
Black Native American joint/two or more
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Race/ethnicity
Percent of individuals experiencing sheltered homelessness (housed in emergency shelters or transitional
housing) during point-in-time survey, January 2019
Source: City of Fort Collins Social Sustainability Gaps Analysis—2020 Update
Race/ethnicity‡ Total population
Number in
emergency shelter/
transitional housing
Sheltered
homelessness rate
per 10,000
Difference
from overall
Race
White 144,533 195 13.49 2.45
Asian or Pacific Islander* 5,745 31 53.96 -38.02
Black* 2,579 18 69.79 -53.85
Native American* 1,383 8 57.85 -41.90
Multiple* 5,699 3 5.26 10.68
Overall 159,939 255 15.94 -
Ethnicity
Non-Hispanic 142,775 222 15.55 0.27
Hispanic/Latinx 19,736 35 17.73 -1.92
Overall 162,511 257 15.81 -
*Statistically significant at p < .05
‡ Population numbers are taken from the American Community Survey 5-year estimates, 2018
Disparity Graph: Racial differences in sheltered homelessness
Disparity Graph: Ethnic differences in sheltered homelessness
2.45
-38.02
-53.85
-41.90
10.68
-60.00
-50.00
-40.00
-30.00
-20.00
-10.00
0.00
10.00
20.00
White Asian or Pacific
Islander
Black Native American Multiple/Other
0.27
-1.92-5.00
0.00
5.00
Non-Hispanic Hispanic/Latinx
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Unsheltered Homelessness
Differences in unsheltered homelessness were also found with rates almost three times higher for Native
Americans than for the overall population. Blacks were more than twice as likely to experience
unsheltered homelessness, while Asians or Pacific Islanders were more than one-and-a-half times as
likely. However, none of these differences were statistically significantly different from the overall rate,
likely due to small sample size.
Race/ethnicity
Percent of individuals experiencing unsheltered homelessness during point-in-time survey, January 2019
Source: City of Fort Collins Social Sustainability Gaps Analysis—2020 Update
Race/ethnicity‡ Total population
Number
unsheltered
Unsheltered
homelessness rate
per 10,000
Difference
from overall
Race
White 144,533 66 4.57 0.50
Asian or Pacific Islander 5,745 5 8.70 -3.64
Black 2,579 3 11.63 -6.57
Native American 1,383 2 14.46 -9.40
Multiple 5,699 5 8.77 -3.71
Overall 159,939 81 5.06 -
Ethnicity
Non-Hispanic 142,775 72 5.04 0.13
Hispanic/Latinx 19,736 12 6.08 -0.91
Overall 162,511 84 5.17 -
‡ Population numbers are taken from the American Community Survey 5-year estimates, 2018
Disparity Graph: Racial differences in unsheltered homelessness
Disparity Graph: Ethnic differences in unsheltered homelessness
0.50
-3.64
-6.57
-9.40
-3.71
-10.00
-8.00
-6.00
-4.00
-2.00
0.00
2.00
White Asian or Pacific
Islander
Black Native American Multiple
0.13
-0.91-2.00
0.00
2.00
Non-Hispanic Hispanic/Latinx
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Neighborhood
Access to Basic Needs Ratings
Rated access to everyday needs within their neighborhood was similar across racial and ethnic groups.
Ratings by neighborhood differed, however, with residents of Northeast and Southwest giving lower
ratings than respondents overall, while residents of East Central gave higher ratings.
Race/ethnicity
Average rating of access within own neighborhood to everyday needs (i.e., grocery shopping, services,
and amenities) on a scale of 0 to 100, 2019
Source: Fort Collins Community Survey
Race/ethnicity†
Number of
respondents
Average access
rating
Difference
from overall
White 528 79 0
Hispanic and/or other race 86 77 -2
Overall 614 79 -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Racial/ethnic differences in rated access to basic needs
Neighborhood
Average rating of access within own neighborhood to everyday needs (i.e., grocery shopping, services,
and amenities) on a scale of 0 to 100, 2019
Source: Fort Collins Community Survey
Neighborhood
Number of
respondents
Average access
rating
Difference
from overall
Northeast 78 70 -9
East Central 144 85 6
Southeast 103 80 1
Northwest/CSU 0 80 1
West Central 131 79 0
Southwest 29 66 -13
Overall 626 79 -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
0
-2
-5
0
White Hispanic and/or other race
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Disparity Graph: Neighborhood differences in rated access to basic needs
-9
6
1 1 0
-13-15
-10
-5
0
5
10
Northeast East Central Southeast Northwest/CSU West Central Southwest
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Public Health
Within Public Health, 17 measures of access to care (including affordability), physical health, and mental
health were examined. Significant racial and ethnic disparities were not found on the majority of
measures, although small sample size likely impacted this finding since some of the numerical differences
were sizeable. Where significant disparities were found, they centered on access to care and affordability,
with disparities in insurance rates, worry about health care costs, and delaying both medical and mental
health care due to the cost. It is also worth noting that mental health concerns seemed to be fairly
common, with roughly a third of Larimer County residents reporting depression, anxiety, or another
mental health concern, one in five reporting high stress, and one in 14 reporting have considered suicide
in the past year, with rates even higher among LBGQ+ individuals and those with lower income.
Table 15. Number (percentage) of measures with more positive, equivalent, or more negative outcomes or
perceptions than the overall outcome or perception for each racial and ethnic grouping included
Racial/ethnic group
Number (%) of
measures with
positive outcomes or
perceptions
Number (%) of
measures with
equivalent outcomes
or perceptions
Number (%) of
measures with
negative outcomes
or perceptions
Non-Hispanic White 0 (0%) 17 (100%) 0 (0%)
Hispanic/Latinx 0 (0%) 0 (0%) 1 (100%)
Asian or Pacific Islander 0 (0%) 1 (100%) 0 (0%)
Black 0 (0%) 1 (100%) 0 (0%)
Native American 0 (0%) 1 (100%) 0 (0%)
Other 0 (0%) 0 (0%) 1 (100%)
Non-Hispanic, Non-White n/a n/a n/a
Hispanic and/or Other Race 0 (0%) 13 (81%) 3 (19%)
White, including Hispanic n/a n/a n/a
Data Note: Assessing Differences Between Groups
Wherever possible, statistical testing was conducted in order to see whether differences between the finding
for the overall outcome or perception and the finding for each racial and ethnic group included in the data were
statistically significant. It should be noted that significance testing was not possible in several circumstances: 1)
raw numbers for the different groups were not provided (e.g., percentages only), 2) measures of variance were
not provided (e.g., standard error), or 3) for ACS data, standard tables including margins of error were not
available and data were pulled from the Microdata portal instead. In keeping with the City’s focus on leading
with race, ISLG tested for statistical significance for differences based on race and ethnicity only, with the
exception of a few select measures.
One thing that is important to keep in mind is that statistical significance is impacted by sample size. There was
a very small sample size for a number of measures across the landscape analysis, particularly for racial and
ethnic groups that represent a smaller proportion of the population. For that reason, it is possible that
meaningful differences were not statistically significant in the data that was able to be included here, but would
have been had a larger sample size been possible.
Where statistical testing could not be conducted, ISLG used a set threshold (see How Information is Reported)
to establish whether or not to call two numerical findings different based on the magnitude of differences that
tended to appear as meaningful or significant in the background research reviewed. Despite the use of set
thresholds, caution should be used in drawing conclusions about the differences between groups where
statistical significance could not be conducted.
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Access to Care
Uninsured Rates
Racial and ethnic disparities were found in uninsured rates. While only one in 16 lacked coverage in the
Fort Collins population overall, one in 10 Hispanic/Latinx individuals did not have health insurance, and
the uninsured rate for this ethnic group was almost twice the overall rate.
Race/ethnicity
Percent of the total population that does not have health insurance coverage, 2018
Source: American Community Survey 5-year estimates
Race/ethnicity Population
Number
uninsured
Percent
uninsured
Difference
from overall
Non-Hispanic white 128,622 7,122 5.54% 0.70%
Hispanic/Latinx* 19,400 2,117 10.91% -4.67%
Asian 5,564 281 5.05% 1.19%
Black 2,430 174 7.16% -0.92%
Native American 1,349 103 7.64% -1.40%
Other* 2,567 307 11.96% -5.72%
Overall 160,659 10,025 6.24% -
*Statistically significant at p < .05
Disparity Graph: Racial/ethnic differences in uninsured rates
Very Poor Access to Health Care
Overall, only 2% of respondents said that their access to health care was very poor. While rates were
higher for people of color, these differences did not reach statistical significance, and the same was true
for LGBQ+ respondents. There were significant differences by income, however, with individuals from
lower-income households more likely to report very poor access to care and individuals from higher-
income households less likely to report very poor access to care.
0.70%
-4.67%
1.19%
-0.92%-1.40%
-5.72%-8.00%
-6.00%
-4.00%
-2.00%
0.00%
2.00%
Non-Hispanic white Hispanic/Latinx Asian Black Native American Other
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Race/ethnicity (Larimer County)
Percent of individuals rating their access to health care as very poor, 2019
Source: Health District of Northern Larimer County Community Health Survey
Race/ethnicity
Percent reporting
very poor access
Difference
from overall
Non-Hispanic white 1.7% 0.5%
Hispanic/Latinx or other race 4.9% -2.7%
Overall 2.2% -
Disparity Graph: Racial/ethnic differences in very poor reported access to health care
Sexual Orientation (Larimer County)
Percent of individuals rating their access to health care as very poor, 2019
Source: Health District of Northern Larimer County Community Health Survey
Sexual orientation
Percent reporting
very poor access
Difference
from overall
Straight 2.0% 0.2%
LGBQ+ 4.3% -2.1%
Overall 2.2%
Disparity Graph: Sexual orientation differences in very poor reported access to health care
Income (Larimer County)
Percent of individuals rating their access to health care as very poor, 2019
Source: Health District of Northern Larimer County Community Health Survey
Household income
level
Percent reporting
very poor access
Difference
from overall
<250% FPL* 7.40% -5.20%
>=250% FPL* 0.70% 1.50%
Overall 2.20% -
*Statistically significant at p < .05
0.5%
-2.7%-4.0%
-2.0%
0.0%
2.0%
Non-Hispanic white Hispanic/Latinx or other race
0.2%
-2.1%-4.0%
-2.0%
0.0%
2.0%
Straight LGBQ+
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Disparity Graph: Income-based differences in very poor reported access to health care
Regular Health Care Provider
Having a regular provider increases access to preventive care and reduces reliance on emergency care,
and lacking one can be a risk factor for poor overall health. While respondents of color and LGBQ+
respondents were more likely to report lacking a regular health care provider, these differences did not
reach statistical significance. There were large and statistically significant disparities by income, however,
with lower-income respondents considerably more likely to report not having a regular health care
provider.
Race/ethnicity (Larimer County)
Percent reporting that they do not have a regular health care provider, 2019
Source: Health District of Northern Larimer County Community Health Survey
Race/ethnicity Number of
respondents
Percent without a
regular provider
Difference
from overall
Non-Hispanic white 2,231 24.8% 1.0%
Hispanic/Latinx or other race† 224 34.2% -8.4%
Hispanic/Latinx 133 32.5% -6.7%
Non-white non-Hispanic 91 37.2% -11.4%
Overall 2,455 25.8%
† Due to small sample size, Hispanic/Latinx and non-white non-Hispanic groups were combined for
statistical significance testing
Disparity Graph: Racial/ethnic differences in lacking a regular health care provider
-5.20%
1.50%
-10.00%
-5.00%
0.00%
5.00%
<250% FPL >=250% FPL
1.0%
-6.7%
-11.4%-14.0%
-12.0%
-10.0%
-8.0%
-6.0%
-4.0%
-2.0%
0.0%
2.0%
Non-Hispanic white Hispanic/Latinx Non-white non-Hispanic
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Sexual Orientation (Larimer County)
Percent reporting that they do not have a regular health care provider, 2019
Source: Health District of Northern Larimer County Community Health Survey
Sexual orientation
Number of
respondents
Percent without a
regular provider
Difference
from overall
Straight 2,419 25.4% 0.4%
LGBQ+ 100 33.9% -8.1%
Overall 2,519 25.8%
Disparity Graph: Sexual orientation differences in lacking a regular health care provider
Income (Larimer County)
Percent reporting that they do not have a regular health care provider, 2019
Source: Health District of Northern Larimer County Community Health Survey
Household income
level
Number of
respondents
Percent without a
regular provider
Difference
from overall
<250% FPL*† 452 42.2% -16.4%
<100% FPL 81 46.0% -20.2%
101-185% FPL 191 42.2% -16.4%
186-250% FPL 180 39.6% -13.8%
>=250% FPL† 1,662 22.9% 2.9%
250-400% FPL 499 26.7% -0.9%
>400% FPL 1,163 21.3% 4.5%
Overall 2,033 25.8% -
*Statistically significant at p < .05
† Due to small sample size, higher and lower income groups were combined for statistical significance
testing
0.4%
-8.1%-10.0%
-8.0%
-6.0%
-4.0%
-2.0%
0.0%
2.0%
Straight LGBQ+
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Disparity Graph: Income-based differences in lacking a regular health care provider
Emergency Room Visits
A greater number of visits to the emergency room can be connected with more severe health problems, a
greater likelihood of injury, and/or a lack of regular source of care. While Hispanic/Latinx and non-white
respondents were somewhat more likely than respondents overall to have made two or more trips to the
emergency room in the past year, this difference was not statistically significant.
Race/ethnicity (Larimer County)
Percent of individuals who visited the emergency room two or more times in the past year, 2019
Source: Health District of Northern Larimer County Community Health Survey
Race/ethnicity Number of
respondents
Percent with 2+
visits
Difference
from overall
Non-Hispanic white 2,231 4.3% 0.9%
Hispanic/Latinx or other race† 224 9.1% -3.9%
Hispanic/Latinx 133 10.8% -5.6%
Non-white non-Hispanic 91 6.2% -1.0%
Overall 2,455 5.2% -
† Due to small sample size, Hispanic/Latinx and non-white non-Hispanic groups were combined for
statistical significance testing
Disparity Graph: Racial/ethnic differences in emergency room visits
Use of Emergency Services for Regular Care
As noted above, emergency services are sometimes utilized when individuals do not have access to a
regular care provider. Overall, almost a third of respondents who had visited the emergency room
reported that they would have seen a doctor if one had been available. While these rates were not
-20.2%
-16.4%
-13.8%
-0.9%
4.5%
-25.0%
-20.0%
-15.0%
-10.0%
-5.0%
0.0%
5.0%
10.0%
<100% FPL 101-185% FPL 186-250% FPL 250-400% FPL >400% FPL
0.9%
-5.6%
-1.0%
-6.0%
-4.0%
-2.0%
0.0%
2.0%
Non-Hispanic white Hispanic/Latinx Non-white non-Hispanic
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significantly different by race and ethnicity, they suggest high rates of avoidable emergency care across
groups.
Race/ethnicity (Larimer County)
Percent of individuals receiving care in an emergency room who would have seen a doctor if they were
available, 2019
Source: Health District of Northern Larimer County Community Health Survey
Race/ethnicity
Percent receiving emergency
care in lieu of doctor
Difference
from overall
Non-Hispanic white 29.8% 1.6%
Hispanic/Latinx or other race† 34.0% -2.6%
Hispanic/Latinx 37.9% -6.5%
Non-white non-Hispanic 18.1% 13.3%
Overall 31.4% -
† Due to small sample size, Hispanic/Latinx and non-white non-Hispanic groups were combined for
statistical significance testing
Disparity Graph: Racial/ethnic differences in using emergency services for regular care
Worry about Medical Care Costs
Overall, roughly one in six respondents reported being very worried about affording needed medical care,
and there were significant racial and ethnic disparities between groups. One in four respondents of color
reported being very worried about being able to pay for needed care. This worry was particularly high
among Hispanic/Latinx respondents, consistent with the higher uninsured rates among this group. No
significant differences were found by sexual orientation, but there were significant and marked disparities
by income: respondents from low-income households were more than twice as likely as respondents
overall to report worry about affording needed care.
1.6%
-6.5%
13.3%
-10.0%
-5.0%
0.0%
5.0%
10.0%
15.0%
Non-Hispanic white Hispanic/Latinx Non-white non-Hispanic
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Race/ethnicity (Larimer County)
Percent of individuals reporting being very worried about affording needed medical care, 2019
Source: Health District of Northern Larimer County Community Health Survey
Race/ethnicity
Number of
respondents
Percent worried about
medical care costs
Difference
from overall
Non-Hispanic white 2,231 15.3% 1.4%
Hispanic/Latinx or other race*† 224 25.5% -8.8%
Hispanic/Latinx 133 29.8% -13.1%
Non-white non-Hispanic 91 18.2% -1.5%
Overall 2,455 16.7% -
*Statistically significant at p < .05
† Due to small sample size, Hispanic/Latinx and non-white non-Hispanic groups were combined for
statistical significance testing
Disparity Graph: Racial/ethnic differences in worry about affording medical care
Sexual Orientation (Larimer County)
Percent of individuals reporting being very worried about affording medical care, 2019
Source: Health District of Northern Larimer County Community Health Survey
Sexual orientation
Number of
respondents
Percent worried about
medical care costs
Difference
from overall
Straight 2,419 16.3% 0.3%
LGBQ+ 100 23.2% -6.5%
Overall 2,519 16.7%
Disparity Graph: Sexual orientation differences in worry about affording medical care
1.4%
-13.1%
-1.5%
-14.0%
-12.0%
-10.0%
-8.0%
-6.0%
-4.0%
-2.0%
0.0%
2.0%
4.0%
Non-Hispanic white Hispanic/Latinx Non-white non-Hispanic
0.4%
-6.5%-8.0%
-6.0%
-4.0%
-2.0%
0.0%
2.0%
Straight LGBQ+
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Income (Larimer County)
Percent of individuals reporting being very worried about affording medical care, 2019
Source: Health District of Northern Larimer County Community Health Survey
Household income
level
Number of
Respondents
Percent worried
about medical
care costs
Difference from
overall
<250% FPL* 452 35.7% -19.0%
>=250% FPL* 1,662 11.6% 5.1%
Overall 2,033 16.7% -
*Statistically significant at p < .05
Disparity Graph: Income-based differences in worry about affording medical care
Delaying Health Care Due to Costs
Almost a third of respondents reported often or occasionally delaying seeking health care due to the cost,
with significantly higher percentages for respondents of color than respondents overall. While rates were
higher for LGBQ+ respondents than respondents overall, the difference did not reach significance. There
were sizeable and significant disparities by income, however, with lower-income respondents more likely
to have delayed needed care due to the cost.
-19.0%
5.1%
-25.0%
-20.0%
-15.0%
-10.0%
-5.0%
0.0%
5.0%
10.0%
<250% FPL >=250% FPL
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Race/ethnicity (Larimer County)
Percent of individuals who reported often or occasionally delaying seeking health care due to the cost,
2019
Source: Health District of Northern Larimer County Community Health Survey
Race/ethnicity
Percent
delaying care
Difference
from overall
Non-Hispanic white 30.2% 1.1%
Hispanic/Latinx or other race*† 41.3% -10.0%
Hispanic/Latinx 40.9% -9.6%
Non-white non-Hispanic 42.1% -10.8%
Overall 31.3% -
*Statistically significant at p < .05
† Due to small sample size, Hispanic/Latinx and non-white non-Hispanic groups were combined for
statistical significance testing
Disparity Graph: Racial/ethnic differences in delaying healthcare due to the cost
Sexual Orientation (Larimer County)
Percent of individuals who reported often or occasionally delaying seeking health care due to the cost,
2019
Source: Health District of Northern Larimer County Community Health Survey
Sexual orientation
Percent
delaying care
Difference
from overall
Straight 31.0% 0.3%
LGBQ+ 39.1% -7.8%
Overall 31.3%
Disparity Graph: Sexual orientation differences in delaying healthcare due to the cost
1.1%
-9.6%-10.8%-12.0%
-10.0%
-8.0%
-6.0%
-4.0%
-2.0%
0.0%
2.0%
Non-Hispanic white Hispanic/Latinx Non-white non-Hispanic
0.3%
-7.8%-10.0%
-8.0%
-6.0%
-4.0%
-2.0%
0.0%
2.0%
Straight LGBQ+
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Income (Larimer County)
Percent of individuals who reported often or occasionally delaying seeking health care due to the cost,
2019
Source: Health District of Northern Larimer County Community Health Survey
Household income
level
Percent
delaying care
Difference
from overall
<250% FPL* 49.1% -17.8%
>=250% FPL 28.3% 3.0%
Overall 31.3% -
*Statistically significant at p < .05
Disparity Graph: Income-based differences in delaying health care due to the cost
Delaying Mental Health Care Due to Costs
Similar to physical healthcare, disparities were found in the likelihood of delaying mental health care.
Overall, roughly a third of respondents reported delaying mental health care due to the cost but almost
of half of respondents of color reported doing so, a significant difference. Significant differences were
also found by sexual orientation and by income. More than half of LGBQ+ and lower-income respondents
reported having delayed mental health care due to costs than respondents overall, while higher-income
respondents were significantly less likely to have delayed mental health care.
Race/ethnicity (Larimer County)
Percent of individuals who reported often or occasionally delaying seeking mental health care due to the
cost, 2019
Source: Health District of Northern Larimer County Community Health Survey
Race/ethnicity
Percent
delaying care
Difference
from overall
Non-Hispanic white 29.9% 2.0%
Hispanic/Latinx or other race*† 47.1% -15.2%
Hispanic/Latinx 49.1% -17.2%
Non-white non-Hispanic 43.8% -11.9%
Overall 31.9% -
*Statistically significant at p < .05
† Due to small sample size, Hispanic/Latinx and non-white non-Hispanic groups were combined for
statistical significance testing
-17.8%
3.0%
-20.0%
-15.0%
-10.0%
-5.0%
0.0%
5.0%
<250% FPL >=250% FPL
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Disparity Graph: Racial/ethnic differences in delaying mental health care due to the cost
Sexual Orientation (Larimer County)
Percent of individuals who reported often or occasionally delaying seeking mental health care due to the
cost, 2019
Source: Health District of Northern Larimer County Community Health Survey, 2019
Sexual orientation
Percent
delaying care
Difference
from overall
Straight 30.5% 1.4%
LGBQ+* 53.3% -21.4%
Overall 31.9%
*Statistically significant at p < .05
Disparity Graph: Sexual orientation differences in delaying mental health care due to the cost
Income (Larimer County)
Percent of individuals who reported often or occasionally delaying seeking mental health care due to the
cost, 2019
Source: Health District of Northern Larimer County Community Health Survey
Household income
level
Number of
respondents
Percent
delaying care
Difference
from overall
<250% FPL* 452 54.8% -22.9%
>=250% FPL* 1,662 26.2% 5.7%
Overall 2,033 31.9% -
*Statistically significant at p < .05
2.0%
-17.2%
-11.9%
-20.0%
-15.0%
-10.0%
-5.0%
0.0%
5.0%
Non-Hispanic white Hispanic/Latinx Non-white non-Hispanic
1.4%
-21.4%-25.0%
-20.0%
-15.0%
-10.0%
-5.0%
0.0%
5.0%
Straight LGBQ+
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Disparity Graph: Income-based differences in delaying mental health care due to the cost
Forgoing Prescription Medication Due to Costs
The disparate impacts of the high costs of healthcare also were apparent when looking at the ability to
obtain needed prescription medication, although differences were significant only by income.
Respondents of color and LGBQ+ respondents were more likely than respondents overall to report have
been unable to refill a prescription medication because they could not afford it, but these differences
were not significant. Lower-income respondents were significantly more likely to report having been
unable to refill a prescription medication than respondents overall.
Race/ethnicity (Larimer County)
Percent of individuals who reported having been unable to have a prescription refill filled in the past two
years because they could not afford it, 2019
Source: Health District of Northern Larimer County Community Health Survey
Race/ethnicity
Number of
respondents
Percent unable to
refill prescription
Difference
from overall
Non-Hispanic white 2,231 9.3% 0.4%
Hispanic/Latinx or other race† 224 12.8% -3.1%
Hispanic/Latinx 133 14.2% -4.5%
Non-white non-Hispanic 91 10.4% -0.7%
Overall 2,455 9.7% -
† Due to small sample size, Hispanic/Latinx and non-white non-Hispanic groups were combined for
statistical significance testing
Disparity Graph: Racial/ethnic differences in difficulty affording prescriptions
-22.9%
5.7%
-25.0%
-20.0%
-15.0%
-10.0%
-5.0%
0.0%
5.0%
10.0%
<250% FPL >=250% FPL
0.4%
-4.5%
-0.7%
-6.0%
-4.0%
-2.0%
0.0%
2.0%
Non-Hispanic white Hispanic/Latinx Non-white non-Hispanic
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Sexual Orientation (Larimer County)
Percent of individuals who reported having been unable to have a prescription refill filled in the past two
years because they could not afford it, 2019
Source: Health District of Northern Larimer County Community Health Survey
Sexual orientation
Number of
respondents
Percent unable to
refill prescription
Difference
from overall
Straight 2,419 9.4% 0.3%
LGBQ+ 100 16.3% -6.6%
Overall 2,519 9.7% -
Disparity Graph: Sexual orientation differences in difficulty affording prescriptions
Income (Larimer County)
Percent of individuals who reported having been unable to have a prescription refill filled in the past two
years because they could not afford it
Source: Health District of Northern Larimer County Community Health Survey, 2019
Household income
level
Number of
respondents
Percent unable to
refill prescription
Difference
from overall
<250% FPL* 452 16.2% -6.5%
>=250% FPL 1,662 8.0% 1.7%
Overall 2,033 9.7% -
*Statistically significant at p < .05
Disparity Graph: Income-based differences in difficulty affording prescriptions
Physical Health
Poor Physical Health
Interestingly given differences in concerns about affording care, disparities were not found in the
likelihood of reporting poor health. Overall, just over 1% of respondents reported poor overall health, and
these rates were similar across racial and ethnic groups.
0.3%
-6.6%-8.0%
-6.0%
-4.0%
-2.0%
0.0%
2.0%
Straight Not Straight
-6.5%
1.7%
-8.0%
-6.0%
-4.0%
-2.0%
0.0%
2.0%
4.0%
<250% FPL >=250% FPL
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Race/ethnicity (Larimer County)
Percent of individuals who reported their overall health as poor, 2019
Source: Health District of Northern Larimer County Community Health Survey
Race/ethnicity
Number of
respondents
Percent with poor
overall health
Difference
from overall
Non-Hispanic white 2,231 0.9% 0.4%
Hispanic/Latinx or other race 224 3.6% -2.3%
Overall 2,455 1.3% -
Disparity Graph: Racial/ethnic differences in poor physical health ratings
Asthma
Overall, almost one in 10 respondents reported having asthma. No significant differences were found by
race and ethnicity, sexual orientation, or income.
Race/ethnicity (Larimer County)
Percent of individuals who reported currently having asthma, 2019
Source: Health District of Northern Larimer County Community Health Survey
Race/ethnicity Number of
respondents
Percent with
asthma
Difference
from overall
Non-Hispanic white 2,231 8.7% 0.2%
Hispanic/Latinx or other race† 224 10.0% -1.1%
Hispanic/Latinx 133 7.7% 1.2%
Non-white non-Hispanic 91 14.0% -5.1%
Overall 2,455 8.9% -
† Due to small sample size, Hispanic/Latinx and non-white non-Hispanic groups were combined for
statistical significance testing
Disparity Graph: Racial/ethnic differences in asthma rates
0.4%
-2.3%-4.0%
-2.0%
0.0%
2.0%
Non-Hispanic white Hispanic/Latinx or other race
0.2%
1.2%
-5.1%-6.0%
-4.0%
-2.0%
0.0%
2.0%
Non-Hispanic white Hispanic/Latinx Non-white non-Hispanic
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Sexual Orientation (Larimer County)
Percent of individuals who reported currently having asthma, 2019
Source: Health District of Northern Larimer County Community Health Survey
Sexual orientation
Number of
respondents
Percent with
asthma
Difference
from overall
Straight 2,419 8.7% 0.2%
LGBQ+ 100 12.9% -4.0%
Overall 2,519 8.9%
Disparity Graph: Sexual orientation differences in asthma rates
Income (Larimer County)
Percent of individuals who reported currently having asthma, 2019
Source: Health District of Northern Larimer County Community Health Survey
Household income
level
Number of
respondents
Percent with
asthma
Difference
from overall
<250% FPL† 452 6.2% 2.7%
<100% FPL 81 7.4% 1.5%
101-185% FPL 191 5.6% 3.3%
186-250% FPL 180 6.0% 2.9%
>=250% FPL† 1,662 9.3% -0.4%
250-400% FPL 499 9.9% -1.0%
>400% FPL 1,163 9.0% -0.1%
Overall 2,033 8.9% -
† Due to small sample size, higher and lower income groups were each combined for statistical
significance testing
Disparity Graph: Income-based differences in asthma rates
0.2%
-4.0%-5.0%
-4.0%
-3.0%
-2.0%
-1.0%
0.0%
1.0%
Straight LGBQ+
1.5%
3.3%2.9%
-1.0%
-0.1%
-2.0%
0.0%
2.0%
4.0%
<100% FPL 101-185% FPL 186-250% FPL 250-400% FPL >400% FPL
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High Cholesterol
Approximately one in our respondents overall reported high cholesterol rates. Rates did not differ
significantly by race and ethnicity.
Race/ethnicity (Larimer County)
Percent of individuals who reported ever having been diagnosed with high cholesterol, 2019
Source: Health District of Northern Larimer County Community Health Survey
Race/ethnicity
Number of
respondents
Percent with
high cholesterol
Difference
from overall
Non-Hispanic white 2,231 26.4% 0.8%
Hispanic/Latinx or other race† 224 29.1% -1.9%
Hispanic/Latinx 133 31.7% -4.5%
Non-white non-Hispanic 91 24.6% 2.6%
Overall 2,455 27.2% -
† Due to small sample size, Hispanic/Latinx and non-white non-Hispanic groups were combined for
statistical significance testing
Disparity Graph: Racial/ethnic differences in high cholesterol
Cardiovascular Disease
Rates of cardiovascular disease were almost identical across racial and ethnic groups, with approximately
5% of respondents across all groups reporting ever having been diagnosed with heart attack, coronary
artery disease, or stroke.
0.8%
-4.5%
2.6%
-6.0%
-4.0%
-2.0%
0.0%
2.0%
4.0%
Non-Hispanic white Hispanic/Latinx Non-white non-Hispanic
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Race/ethnicity (Larimer County)
Percent of individuals who reported ever having been diagnosed with heart attack, coronary artery
disease, or stroke, 2019
Source: Health District of Northern Larimer County Community Health Survey
Race/ethnicity Number of
respondents
Percent with
cardiovascular disease
Difference
from overall
Non-Hispanic white 2,231 4.6% 0.0%
Hispanic/Latinx or other race† 224 4.8% -0.2%
Hispanic/Latinx 133 4.8% -0.2%
Non-white non-Hispanic 91 4.8% -0.2%
Overall 2,455 4.6% -
† Due to small sample size, Hispanic/Latinx and non-white non-Hispanic groups were combined for
statistical significance testing
Disparity Graph: Racial/ethnic differences in cardiovascular disease
Diabetes
Overall, approximately one in 16 respondents reporting ever having been diagnosed with diabetes. Rates
were higher among respondents of color, but these differences did not reach statistical significance. It
should be noted, however, that rates were noticeably higher among non-Hispanic, non-white
respondents, and the inability to reliably compare that group to respondents overall directly due to small
sample size may have masked meaningful disparities.
Race/ethnicity (Larimer County)
Percent of individuals who reported ever having been diagnosed with diabetes, 2019
Source: Health District of Northern Larimer County Community Health Survey
Race/ethnicity Number of
respondents
Percent with
diabetes
Difference
from overall
Non-Hispanic white 2,231 4.7% 0.9%
Hispanic/Latinx or other race† 224 9.0% -3.4%
Hispanic/Latinx 133 6.1% -0.5%
Non-white non-Hispanic 91 14.1% -8.5%
Overall 2,455 5.6% -
† Due to small sample size, Hispanic/Latinx and non-white non-Hispanic groups were combined for
statistical significance testing
0.0%
-0.2%-0.2%-0.5%
0.0%
Non-Hispanic white Hispanic/Latinx Non-white non-Hispanic
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Disparity Graph: Racial/ethnic differences in diabetes
Mental Health
High Stress
Roughly one in five respondents reported experiencing high levels of stress in the month prior to the
completing the survey. Rates were similar across racial and ethnic groups, but there were significant
disparities by sexual orientation and income. LGBQ+ respondents reported stress at a rate almost
eighteen percentage points higher than respondents overall, while rates were roughly 12 percentage
points higher among lower-income respondents than respondents overall.
Race/ethnicity (Larimer County)
Percent of individuals who reported experiencing a great deal of stress in the past month, 2019
Source: Health District of Northern Larimer County Community Health Survey, 2019
Race/ethnicity Number of
respondents
Percent reporting
high stress
Difference
from overall
Non-Hispanic white 2,231 22.6% -0.6%
Hispanic/Latinx or other race† 224 20.6% 1.4%
Hispanic/Latinx 133 21.9% 0.1%
Non-white non-Hispanic 91 18.2% 3.8%
Overall 2,455 22.0% -
† Due to small sample size, Hispanic/Latinx and non-white non-Hispanic groups were combined for
statistical significance testing
Disparity Graph: Racial/ethnic differences in high stress
0.9%
-0.5%
-8.5%-10.0%
-8.0%
-6.0%
-4.0%
-2.0%
0.0%
2.0%
Non-Hispanic white Hispanic/Latinx Non-white non-Hispanic
-0.6%
0.1%
3.8%
-2.0%
0.0%
2.0%
4.0%
6.0%
Non-Hispanic white Hispanic/Latinx Non-white non-Hispanic
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Sexual Orientation (Larimer County)
Percent of individuals who reported experiencing a great deal of stress in the past month, 2019
Source: Health District of Northern Larimer County Community Health Survey
Sexual orientation
Number of
respondents
Percent reporting
high stress
Difference
from overall
Straight 2,419 20.9% 1.1%
LGBQ+* 100 39.5% -17.5%
Overall 2,519 22.0%
*Statistically significant at p < .05
Disparity Graph: Sexual orientation differences in high stress
Income (Larimer County)
Percent of individuals who reported experiencing a great deal of stress in the past month, 2019
Source: Health District of Northern Larimer County Community Health Survey
Household income
level
Number of
Respondents
Percent reporting
high stress
Difference
from overall
<250% FPL*† 452 34.3% -12.3%
<100% FPL 81 32.4% -10.4%
101-185% FPL 191 33.9% -11.9%
186-250% FPL 180 36.0% -14.0%
>=250% FPL† 1,662 19.0% 3%
250-400% FPL 499 19.8% 2.2%
>400% FPL 1,163 18.7% 3.3%
Overall 2,033 22.0% -
*Statistically significant at p < .05
† Due to small sample size, higher and lower income groups were combined for statistical significance
testing
1.1%
-17.5%-20.0%
-15.0%
-10.0%
-5.0%
0.0%
5.0%
Straight LGBQ+
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Disparity Graph: Income-based differences in high stress
Current Mental Health Concern
Almost a third of respondents across race and ethnicity reported currently experiencing depression,
anxiety, or another mental health concern. While disparities were not found by race, large and significant
disparities were found by sexual orientation and income. LGBQ+ respondents reported having a current
mental health concern at a rate almost 30 percentage points higher than respondents overall,
representing more than half of LGBQ+ respondents. Lower-income respondents reported current mental
health concerns at a rate 13 percentage points higher than respondents overall.
Race/ethnicity (Larimer County)
Percent of individuals who reported currently experiencing depression, anxiety, or another mental health
concern, 2019
Source: Health District of Northern Larimer County Community Health Survey
Race/ethnicity Number of
respondents
Percent with mental
health concern
Difference
from overall
Non-Hispanic white 2,231 29.9% 0.2%
Hispanic/Latinx or other race† 224 32.3% -2.2%
Hispanic/Latinx 133 32.5% -2.4%
Non-white non-Hispanic 91 31.9% -1.8%
Overall 2,455 30.1% -
† Due to small sample size, Hispanic/Latinx and non-white non-Hispanic groups were combined for
statistical significance testing
Disparity Graph: Racial/ethnic differences in current mental health concern
-10.4%
-11.9%
-14.0%
2.2%3.3%
-15.0%
-10.0%
-5.0%
0.0%
5.0%
<100% FPL 101-185% FPL 186-250% FPL 250-400% FPL >400% FPL
0.2%
-2.4%-1.8%
-4.0%
-2.0%
0.0%
2.0%
Non-Hispanic white Hispanic/Latinx Non-white non-Hispanic
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Sexual Orientation (Larimer County)
Percent of individuals who reported currently experiencing depression, anxiety, or another mental health
concern, 2019
Source: Health District of Northern Larimer County Community Health Survey
Sexual orientation
Number of
respondents
Percent with mental
health concern
Difference
from overall
Straight 2,419 28.5% 1.6%
LGBQ+* 100 58.2% -28.1%
Overall 2,519 30.1%
*Statistically significant at p < .05
Disparity Graph: Sexual orientation differences in current mental health concern
Income (Larimer County)
Percent of individuals who reported currently experiencing depression, anxiety, or another mental health
concern, 2019
Source: Health District of Northern Larimer County Community Health Survey
Household income
level
Number of
respondents
Percent with mental
health concern
Difference
from overall
<250% FPL*† 452 43.1% -13.1%
<100% FPL 81 41.6% -11.5%
101-185% FPL 191 47.0% -16.9%
186-250% FPL 180 40.0% -9.9%
>=250% FPL† 1,662 26.8% 3.3%
250-400% FPL 499 31.5% -1.4%
>400% FPL 1,163 24.8% 5.3%
Overall 2,033 30.1% -
*Statistically significant at p < .05
† Due to small sample size, higher and lower income groups were each combined for statistical
significance testing
1.6%
-28.1%-30.0%
-25.0%
-20.0%
-15.0%
-10.0%
-5.0%
0.0%
5.0%
Straight LGBQ+
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Disparity Graph: Income-based differences in current mental health concern
Suicidality
Approximately one in 14 respondents reported having considered suicide as a solution to their problems
in the year prior to completing the survey, with equivalent rates across racial and ethnic groups. There
were significant and large disparities in suicidality for sexual orientation and income, however, with close
to one in five LGBQ+ respondents reporting that they had considered suicide, and one in eight lower-
income respondents.
Race/ethnicity (Larimer County)
Percent of individuals who reported having considered suicide as a solution to their problems, 2019
Source: Health District of Northern Larimer County Community Health Survey, 2019
Race/ethnicity
Number of
respondents
Percent reporting
suicidality
Difference
from overall
Non-Hispanic white 2,231 7.4% -0.2%
Hispanic/Latinx or other race† 224 7.9% -0.7%
Hispanic/Latinx 133 7.2% 0.0%
Non-white non-Hispanic 91 9.0% -1.8%
Overall 2,455 7.2% -
† Due to small sample size, Hispanic/Latinx and non-white non-Hispanic groups were combined for
statistical significance testing
Disparity Graph: Racial/ethnic differences in suicidality
-11.5%
-16.9%
-9.9%
-1.4%
5.3%
-20.0%
-15.0%
-10.0%
-5.0%
0.0%
5.0%
10.0%
<100% FPL 101-185% FPL 186-250% FPL 250-400% FPL >400% FPL
-0.2%
0.0%
-1.8%-2.0%
0.0%
Non-Hispanic white Hispanic/Latinx Non-white non-Hispanic
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Sexual Orientation (Larimer County)
Percent of individuals who reported having considered suicide as a solution to their problems, 2019
Source: Health District of Northern Larimer County Community Health Survey
Sexual orientation
Number of
respondents
Percent reporting
suicidality
Difference
from overall
Straight 2,419 6.5% 0.7%
LGBQ+* 100 19.4% -12.2%
Overall 2,519 7.2%
*Statistically significant at p < .05
Disparity Graph: Sexual orientation differences in suicidality
Income (Larimer County)
Percent of individuals who reported having considered suicide as a solution to their problems, 2019
Source: Health District of Northern Larimer County Community Health Survey
Household income
level
Number of
Respondents
Percent worried
about medical
care costs
Difference from
overall
<250% FPL*† 452 13.0% -5.8%
<100% FPL 81 12.0% -4.8%
101-185% FPL 191 8.9% -1.7%
186-250% FPL 180 17.7% -10.5%
>=250% FPL† 1,662 6.1% 1.1%
250-400% FPL 499 9.2% -2.0%
>400% FPL 1,163 4.8% 2.4%
Overall 2,033 7.2% -
*Statistically significant at p < .05
† Due to small sample size, higher and lower income groups were each combined for statistical
significance testing
0.7%
-12.2%-15.0%
-10.0%
-5.0%
0.0%
5.0%
Straight LGBQ+
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Disparity Graph: Income-based differences in suicidality
-4.8%
-1.7%
-10.5%
-2.0%
2.4%
-12.0%
-10.0%
-8.0%
-6.0%
-4.0%
-2.0%
0.0%
2.0%
4.0%
<100% FPL 101-185% FPL 186-250% FPL 250-400% FPL >400% FPL
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Services
Within Services, 18 measures within the areas of essential services and parks and recreation were
examined. There were 11 measures for which race and ethnicity were available, and disparities were
found on six of those measures. It is important to note that due to sample size many of the data sources
from which measures were drawn grouped all people of color together, meaning that nuanced
investigation of the racial and ethnic groups most impacted was not possible. That being said, where
differences were found people of color more often fared more poorly than the Fort Collins population as
a whole, while whites were equivalent across all measures. Disparities were also found by income and
neighborhood for sidewalk conditions and parks and recreation, respectively. Additionally, some
differences in reported proximity to parks and the extent to which needs for different outdoor features
were being met were found by neighborhood, although generally ratings were quite high.
Table 16. Number (percentage) of measures with more positive, equivalent, or more negative outcomes or
perceptions than the overall outcome or perception for each racial and ethnic grouping included
Racial/ethnic group
Number (%) of
measures with
positive outcomes or
perceptions
Number (%) of
measures with
equivalent outcomes
or perceptions
Number (%) of
measures with
negative outcomes
or perceptions
Non-Hispanic White 0 (0%) 11 (100%) 0 (0%)
Hispanic/Latinx 0 (0%) 3 (75%) 1 (25%)
Asian or Pacific Islander 1 (33%) 2 (67%) 0 (0%)
Black 1 (33%) 2 (67%) 0 (0%)
Native American 0 (0%) 3 (100%) 0 (0%)
Other 0 (0%) 2 (100%) 0 (0%)
Non-Hispanic, Non-White 0 (0%) 1 (100%) 0 (0%)
Hispanic and/or Other Race 0 (0%) 2 (29%) 5 (71%)
White, including Hispanic n/a n/a n/a
Data Note: Assessing Differences Between Groups
Wherever possible, statistical testing was conducted in order to see whether differences between the finding
for the overall outcome or perception and the finding for each racial and ethnic group included in the data were
statistically significant. It should be noted that significance testing was not possible in several circumstances: 1)
raw numbers for the different groups were not provided (e.g., percentages only), 2) measures of variance were
not provided (e.g., standard error), or 3) for ACS data, standard tables including margins of error were not
available and data were pulled from the Microdata portal instead. In keeping with the City’s focus on leading
with race, ISLG tested for statistical significance for differences based on race and ethnicity only, with the
exception of a few select measures.
One thing that is important to keep in mind is that statistical significance is impacted by sample size. There was
a very small sample size for a number of measures across the landscape analysis, particularly for racial and
ethnic groups that represent a smaller proportion of the population. For that reason, it is possible that
meaningful differences were not statistically significant in the data that was able to be included here, but would
have been had a larger sample size been possible.
Where statistical testing could not be conducted, ISLG used a set threshold (see How Information is Reported)
to establish whether or not to call two numerical findings different based on the magnitude of differences that
tended to appear as meaningful or significant in the background research reviewed. Despite the use of set
thresholds, caution should be used in drawing conclusions about the differences between groups where
statistical significance could not be conducted.
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Essential Services
Internet Access
Overall, roughly 5% of households lacked internet access, and no significant racial or ethnic differences in
internet access were found.
Race/ethnicity
Percent of households without access to the internet, 2018
Source: American Community Survey 5-year estimates
Race/ethnicity of
householder Population
Number without
internet access
Percent without
internet access
Difference
from overall
Non-Hispanic white 123,798 6,159 4.98% 0.47%
Hispanic/Latinx 18,521 1,476 7.97% -2.52%
Asian 5,152 443 8.60% -3.15%
Black 2,320 139 5.99% -0.54%
Native American 1,337 46 3.44% 2.01%
Other 2,508 116 4.63% 0.82%
Overall 154,250 8,405 5.45% -
Disparity Graph: Racial/ethnic differences in internet access
Computer in Household
The vast majority of households in Fort Collins had a computer, with approximately two in 100
households reporting lacking one. While the differences by race and ethnicity were small, Asian and Black
households were significantly more likely to have a computer, while Hispanic/Latinx households were
significant more likely to lack one.
0.47%
-2.52%
-3.15%
-0.54%
2.01%
0.82%
-4.00%
-3.00%
-2.00%
-1.00%
0.00%
1.00%
2.00%
3.00%
Non-Hispanic
white
Hispanic/Latinx Asian Black Native American Other
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Race/ethnicity
Percent of households without a computer, 2018
Source: American Community Survey 5-year estimates
Race/ethnicity Population
Number of
households with
no computer
Percent of
households with
no computer
Difference from
overall
Non-Hispanic white 123,798 2,568 2.07% 0.18%
Hispanic/Latinx* 18,521 842 4.55% -2.29%
Asian* 5,152 35 0.68% 1.58%
Black* 2,320 7 0.30% 1.96%
Native American 1,337 18 1.35% 0.91%
Other 2,508 77 3.07% -0.81%
Overall 154,250 3,485 2.26% -
*Statistically significant at p < .05
Disparity Graph: Racial/ethnic differences in computer access
Phone Access
Overall, most respondents reported having access to a cell phone or landline. There were some
differences by race and ethnicity, with non-Hispanic non-white or multiple race respondents almost seven
percentage points more likely than respondents overall to report lacking access; however, these
differences did not reach statistical significance.
Race/ethnicity
Percent reporting not having access to a cell phone or landline, 2020
Source: City of Fort Collins Our Climate Future Demographics Survey†
Race/ethnicity
Number of
respondents
Number without
phone access
Percent without
phone access
Difference from
overall
Non-Hispanic white 253 13 5.14% 1.25%
Hispanic/Latinx 37 4 10.81% -4.42%
Non-Hispanic non-white or
multiple 23 3 13.04% -6.65%
Overall 313 20 6.39% -
† Note that the Our Climate Future Demographic Survey was conducted as part of a larger community
engagement strategy and may not be fully representative of all segments of the population
0.18%
-2.29%
1.58%1.96%
0.91%
-0.81%
-4.00%
-2.00%
0.00%
2.00%
4.00%
Non-Hispanic white Hispanic/Latinx Asian Black Native American Other
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Disparity Graph: Racial/ethnic differences in phone access
Sewer Service Quality Ratings
Ratings of sewer services quality differed by race and ethnicity, with Hispanic and other race respondents
giving ratings eight points lower than the overall rating, while whites gave equivalent ratings to the overall
rating.
Race/ethnicity
Average rating of sewer services quality on a scale of 0 to 100, 2019
Source: Fort Collins Community Survey
Race/ethnicity†
Number of
respondents
Average rating of
sewer services quality
Difference
from overall
White 528 82 2
Hispanic and/or other race 86 72 -8
Overall 614 80 -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Racial/ethnic differences in sewer services ratings
1.25%
-4.42%
-6.65%-8.00%
-6.00%
-4.00%
-2.00%
0.00%
2.00%
Non-Hispanic white Hispanic/Latinx Non-Hispanic non-white or multiple
2
-8-10
-8
-6
-4
-2
0
2
4
White Hispanic and/or other race
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Recycling Programs Ratings
Ratings of recycling programs were largely consistent across racial and ethnic groups, with an overall
rating of 73 out of 100 across groups.
Race/ethnicity
Average rating of recycling programs on a scale of 0 to 100, 2019
Source: Fort Collins Community Survey
Race/ethnicity†
Number of
respondents
Average rating of
recycling programs
Difference
from overall
White 528 73 0
Hispanic and/or other race 86 71 -2
Overall 614 73 -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Racial/ethnic differences in recycling programs ratings
Disaster Response Ratings
Ratings of disaster response and restoration of services differed by race and ethnicity, with Hispanic
and/or other race respondents giving ratings eight points lower than the overall rating, while whites gave
equivalent ratings.
Race/ethnicity
Average rating of disaster response and restoration of services on a scale of 0 to 100, 2019
Source: Fort Collins Community Survey
Race/ethnicity†
Number of
respondents
Average rating of
disaster response
Difference
from overall
White 528 77 1
Hispanic and/or other race 86 68 -8
Overall 614 76 -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
0
-2
-4
-2
0
White Hispanic and/or other race
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Disparity Graph: Racial/ethnic differences in disaster response ratings
Street Maintenance Ratings
Ratings of street maintenance quality differed by race and ethnicity, with Hispanic and/or other race
respondents giving ratings seven points lower than the overall rating, while whites gave equivalent
ratings.
Race/ethnicity
Average rating of street maintenance on a scale of 0 to 100, 2019
Source: Fort Collins Community Survey
Race/ethnicity†
Number of
respondents
Average rating of
street maintenance
Difference
from overall
White 528 68 2
Hispanic and/or other race 86 59 -7
Overall 614 66 -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Racial/ethnic differences in street maintenance ratings
Sidewalk Condition
To examine differences in sidewalk condition by area income, the census tracts were grouped based on
median income to create five area income categories. Overall, roughly a third of sidewalks were rated in
good condition in the most recent inspection by the City of Fort Collins’ Planning, Development, and
Transportation Department, but significant differences were found based on census tract income. While
sidewalk condition in the lowest income group did not differ significantly from sidewalk condition overall,
1
-8-10
-8
-6
-4
-2
0
2
White Hispanic and/or other race
2
-7-8
-6
-4
-2
0
2
4
White Hispanic and/or other race
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sidewalks in the middle three income groups were all rated significantly lower than the overall rating,
although the differences were small. Sidewalks in the top income group were rated significantly higher
than the overall rating, however, and the difference was larger.
Income
Percent of sidewalks rated as in good condition, 2020
City of Fort Collins Planning, Development, and Transportation Department
Income group by
census tract
Number of
sidewalks rated
Number in good
condition
Percent in good
condition
Difference
from overall
Bottom 20% 5,234 1,706 32.59% 1.14%
20-40%* 8,570 2,421 28.25% -3.20%
40-60%* 7,326 2,128 29.05% -2.41%
60-80%* 9,484 2,801 29.53% -1.92%
Top 20%* 6,346 2,569 40.48% 9.03%
Overall 36,960 11,625 31.45% -
*Statistically significant at p < .05
Disparity Graph: Income differences in sidewalk condition
Sidewalk ADA Accessibility
Sidewalk ADA compliance was determined based on a number of factors including condition, width, and
slope. Analysis of the most recent inspection data by the City of Fort Collins’ Planning, Development, and
Transportation Department found that a little more than half of sidewalks in Fort Collins were ADA
compliant, while just over four in 10 were not. Significant differences in sidewalk ADA compliance were
found by census tract income, with sidewalks in the two lowest income groups less likely than sidewalks
overall to be ADA compliant and sidewalks in the top three income groups more likely to be compliant.
Disability Status
Percent of sidewalks that were ADA compliant, 2020
City of Fort Collins Planning, Development, and Transportation Department
Accessibility Number of sidewalks Percent of sidewalks
ADA compliant 21,510 57%
Not ADA compliant 16,526 43%
Overall 38,036 100%
1.14%
-3.20%-2.41%-1.92%
9.03%
-4.00%
-2.00%
0.00%
2.00%
4.00%
6.00%
8.00%
10.00%
Bottom 20%20-40%40-60%60-80%Top 20%
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Income
Percent of sidewalks that were ADA compliant, 2020
City of Fort Collins Planning, Development, and Transportation Department
Income group by
census tract
Number of
sidewalks rated
Number ADA
compliant
Percent ADA
compliant
Difference from
overall
Bottom 20%* 5,411 2,545 47.03% -9.52%
20-40%* 8,888 3,986 44.85% -11.70%
40-60%* 7,549 4,600 60.94% 4.38%
60-80%* 9,751 6,016 61.70% 5.14%
Top 20%* 6,437 4,363 67.78% 11.23%
Overall 38,036 21,510 56.55% -
*Statistically significant at p < .05
Disparity Graph: Income differences in sidewalk accessibility
Sidewalk Ramp ADA Accessibility
Sidewalk ramp ADA compliance was determined based on several factors including the presence of
truncated domes that warn people where sidewalks end and streets begin. Analysis of the most recent
inspection data from the City of Fort Collins’ Planning, Development, and Transportation Department
found that overall, more than eight in 10 ramps across Fort Collins were not ADA compliant. Differences
between income areas were small, although they were significant for the middle and top income groups;
ramps in the former were slightly less likely to be compliant, while ramps in the latter were slightly more
likely to be compliant.
Disability Status
Percent of sidewalk ramps that were ADA compliant, 2020
City of Fort Collins Planning, Development, and Transportation Department
Accessibility
Number of
ramps
Percent of
ramps
ADA accessible 3,890 16%
Not ADA accessible 20,359 84%
Overall 24,249 100%
-9.52%
-11.70%
4.38%5.14%
11.23%
-15.00%
-10.00%
-5.00%
0.00%
5.00%
10.00%
15.00%
Bottom 20%20-40%40-60%60-80%Top 20%
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Income
Percent of sidewalks that were ADA compliant, 2020
City of Fort Collins Planning, Development, and Transportation Department
Income group
Number of
ramps
Number ADA
compliant
Percent ADA
compliant
Difference
from overall
Bottom 20% 4,608 779 16.91% 0.86%
20-40% 5,547 897 16.17% 0.13%
40-60%* 4,333 574 13.25% -2.79%
60-80% 5,638 901 15.98% -0.06%
Top 20%* 4,123 739 17.92% 1.88%
Overall 24,249 3,890 16.04% -
*Statistically significant at p < .05
Disparity Graph: Income differences in sidewalk ramp accessibility
Utility Cost Burden
The utility burden estimate included here is an estimate of the percentage of annual income spent on
electricity and water costs; in future, the City of Fort Collins will be working to include cost estimates for
natural gas, stormwater, and wastewater to provide a fuller picture of the economic burden utility costs
represent for different communities in Fort Collins. Examining water and electricity alone, residents spent
roughly 2% of their annual income on utilities, with minimal differences between racial and ethnic groups.
Race/ethnicity
Percentage of annual income spent on water and electricity costs, 2020
Source: City of Fort Collins Utilities Department
Race/ethnicity† Median income
Median annual
utility cost Utility burden
Difference
from overall
Non-Hispanic white $65,061 $1,078 1.66% 0.15%
Hispanic/Latinx $49,646 $978 1.97% -0.16%
Asian $58,505 $1,023 1.75% 0.06%
Black $50,614 $1,086 2.15% -0.34%
Native American $51,797 $997 1.92% -0.12%
Overall $62,132 $1,123 1.81%
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
0.86%
0.13%
-2.79%
-0.06%
1.88%
-4.00%
-2.00%
0.00%
2.00%
4.00%
Bottom 20%20-40%40-60%60-80%Top 20%
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Disparity Graph: Racial/ethnic differences in utility burden
Library Service Quality Ratings
Libraries are essential for many different communities, providing not only books and written materials,
but access to the internet and computers, workshops, entertainment, and a host of other resources.
Racial and ethnic disparities were found in ratings of library service quality, however, with Hispanic
and/or other race respondents rating library service quality lower than respondents overall.
Race/ethnicity
Average rating of the quality of public library services on a scale of 0 to 100, 2019
Source: Fort Collins Community Survey
Race/ethnicity Number of
respondents
Average rating of public
library services quality
Difference
from overall
White 528 84 2
Hispanic and/or other race 86 77 -5
Overall 614 82 -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Racial/ethnic differences in library service quality ratings
0.15%
-0.16%
0.06%
-0.34%
-0.12%
-0.40%
-0.30%
-0.20%
-0.10%
0.00%
0.10%
0.20%
Non-Hispanic white Hispanic/Latinx Asian Black Native American
2
-5-6
-4
-2
0
2
4
White Hispanic and/or other race
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Parks and Recreation
Park Quality Ratings
Respondents generally gave high ratings to the quality of parks in Fort Collins, and ratings were similar
across racial and ethnic groups.
Race/ethnicity
Average rating of park quality on a scale of 0 to 100, 2019
Source: Fort Collins Community Survey
Race/ethnicity†
Number of
respondents
Average rating of
park quality
Difference
from overall
White 528 88 1
Hispanic and/or other race 86 84 -3
Overall 614 87 -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Racial/ethnic differences in park quality ratings
Sufficient Proximity to Parks
Neighborhood differences in reported proximity to sufficient parks, natural areas, and open spaces were
found, although overall more than three quarters of respondents reported sufficient proximity. Notably,
respondents living in Northeast Fort Collins were particularly likely to report a lack of proximity, with the
percent reporting that they had sufficient parks and related areas nearby more than 20 percentage points
lower than respondents overall. Respondents living in Northwest Fort Collins/Colorado State University
and West Central were similarly and most likely to report proximity than other neighborhoods.
1
-3-5
0
5
White Hispanic and/or other race
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Neighborhood
Percent of respondents saying there are sufficient public parks, natural areas, & open spaces within
walking distance of their residence, 2019
Source: City of Fort Collins Parks and Recreation Needs Assessment
Neighborhood†
Percent reporting
sufficient park proximity
Difference
from overall
East Central 76.50% -3%
Northeast 58.50% -21%
Northwest/CSU 84.90% 6%
Southeast 83.30% 4%
Southwest 73.80% -5%
West Central 84.10% 5%
Overall 79.00% -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Neighborhood differences in rated proximity to parks
Unprogrammed Outdoor Spaces Needs Met
Unprogrammed outdoor spaces (areas that are intentionally designed to support casual, drop-in use &
connection with nature) fulfill a range of needs, and almost 90% of respondents overall reported their
needs were fully or mostly met. Few differences were found by neighborhood, with the exception of
Southwest, where the percentage of respondents reporting that their needs were met was seven points
lower than respondents overall.
-3%
-21%
6%4%
-5%
5%
-25%
-20%
-15%
-10%
-5%
0%
5%
10%
East Central Northeast Northwest/CSU Southeast Southwest West Central
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Neighborhood
Percent of respondents reporting that their needs for unprogrammed outdoor spaces were fully or
mostly met, 2019
Source: City of Fort Collins Parks and Recreation Needs Assessment
Neighborhood†
Percent fully or
mostly met
Difference
from overall
East Central 88.80% 1%
Northeast 89.80% 2%
Northwest/CSU 86.70% -1%
Southeast 86.00% -1%
Southwest 80.00% -7%
West Central 89.20% 2%
Overall 87.40% -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Neighborhood differences in needs met for outdoor space
Paved Trails Needs Met
Paved trails are important for activities like running and biking, but also for people with limited mobility
and those using wheelchairs, as unpaved paths are more difficult to navigate. The vast majority of
respondents reported that their needs for paved trails were fully or mostly met, although rates were
lower than overall for those living in Northeast and Southwest and higher than overall for those in West
Central.
1%
2%
-1%-1%
-7%
2%
-8%
-6%
-4%
-2%
0%
2%
4%
East Central Northeast Northwest/CSU Southeast Southwest West Central
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Neighborhood
Percent of respondents reporting that their needs for paved trails, multi-use trails are fully or mostly met,
2019
Source: City of Fort Collins Parks and Recreation Needs Assessment
Neighborhood†
Percent fully or
mostly met
Difference
from overall
East Central 88.00% -2%
Northeast 83.70% -7%
Northwest/CSU 92.00% 2%
Southeast 91.00% 1%
Southwest 82.90% -8%
West Central 95.90% 6%
Overall 90.40% -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Neighborhood differences in needs met for paved trails
Natural Areas Needs Met
The vast majority of respondents reported that their needs for natural areas and wildlife areas were being
fully or mostly met, but some differences were found by neighborhood: rates were somewhat lower than
overall in Northeast and Southwest, and somewhat higher than overall in West Central.
-2%
-7%
2%
1%
-8%
6%
-10%
-8%
-6%
-4%
-2%
0%
2%
4%
6%
8%
East Central Northeast Northwest/CSU Southeast Southwest West Central
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Neighborhood
Percent of respondents reporting that their needs for natural areas and wildlife habitats are fully or
mostly met, 2019
Source: City of Fort Collins Parks and Recreation Needs Assessment
Neighborhood†
Percent fully
or mostly met
Difference
from overall
East Central 86.00% 2%
Northeast 79.00% -5%
Northwest/CSU 83.10% -1%
Southeast 82.20% -2%
Southwest 78.10% -6%
West Central 88.90% 5%
Overall 84.40% -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Neighborhood differences in needs met for natural areas
Youth Recreation Program Quality Ratings
Differences in respondents’ ratings of the quality of youth recreation programs were found, with Hispanic
and/or other race respondents rating them six points lower than respondents overall, while ratings for
whites were similar to overall ratings.
Race/ethnicity
Average rating of youth/teen recreation program quality on a scale of 0 to 100, 2019
Source: Fort Collins Community Survey
Race/ethnicity†
Number of
respondents
Average rating of youth/
teen program quality
Difference
from overall
White 528 78 2
Hispanic and/or other race 86 70 -6
Overall 614 76 -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
2%
-5%
-1%
-2%
-6%
5%
-8%
-6%
-4%
-2%
0%
2%
4%
6%
East Central Northeast Northwest/CSU Southeast Southwest West Central
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Disparity Graph: Racial/ethnic differences in youth recreation quality ratings
2
-6
-10
-5
0
5
White Hispanic and/or other race
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Social Inclusion
Eight measures of social inclusion were examined in the areas of community and City inclusiveness, most
of which were drawn from surveys of the Fort Collins community. The findings suggest that Hispanic
and/or non-white Fort Collins community members (i.e., people of color) may have felt somewhat less
respect and acceptance from the City and the broader Fort Collins community than community members
overall while white community members did not; however, Hispanic and/or non-white respondents were
generally equally likely to report being engaged with their neighbors. In addition to survey measures,
residential segregation was examined, and the majority of census tracts in Fort Collins were found to have
disproportionate racial or ethnic composition when compared to the general Fort Collins population.
Table 17. Number (percentage) of measures with more positive, equivalent, or more negative outcomes or
perceptions than the overall outcome or perception for each racial and ethnic grouping included
Racial/ethnic group
Number (%) of
measures with
positive outcomes or
perceptions
Number (%) of
measures with
equivalent outcomes
or perceptions
Number (%) of
measures with
negative outcomes
or perceptions
Non-Hispanic White 0 (0%) 7 (100%) 0 (0%)
Hispanic/Latinx 0 (0%) 1 (100%) 0 (0%)
Asian or Pacific Islander n/a n/a n/a
Black n/a n/a n/a
Native American n/a n/a n/a
Other n/a n/a n/a
Non-Hispanic, Non-White 0 (0%) 1 (100%) 0 (0%)
Hispanic and/or Other Race 1 (17%) 3 (50%) 2 (33%)
White, including Hispanic n/a n/a n/a
Data Note: Assessing Differences Between Groups
Wherever possible, statistical testing was conducted in order to see whether differences between the finding
for the overall outcome or perception and the finding for each racial and ethnic group included in the data were
statistically significant. It should be noted that significance testing was not possible in several circumstances: 1)
raw numbers for the different groups were not provided (e.g., percentages only), 2) measures of variance were
not provided (e.g., standard error), or 3) for ACS data, standard tables including margins of error were not
available and data were pulled from the Microdata portal instead. In keeping with the City’s focus on leading
with race, ISLG tested for statistical significance for differences based on race and ethnicity only, with the
exception of a few select measures.
One thing that is important to keep in mind is that statistical significance is impacted by sample size. There was
a very small sample size for a number of measures across the landscape analysis, particularly for racial and
ethnic groups that represent a smaller proportion of the population. For that reason, it is possible that
meaningful differences were not statistically significant in the data that was able to be included here, but would
have been had a larger sample size been possible.
Where statistical testing could not be conducted, ISLG used a set threshold (see How Information is Reported)
to establish whether or not to call two numerical findings different based on the magnitude of differences that
tended to appear as meaningful or significant in the background research reviewed. Despite the use of set
thresholds, caution should be used in drawing conclusions about the differences between groups where
statistical significance could not be conducted.
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Community
Openness and Acceptance Ratings
In general, respondents reported finding the community to be moderately open and accepting of people
from diverse backgrounds, a rating of 65 out of 100. However, Hispanic and/or other race respondents
reported finding the community to be less open and accepting than respondents overall.
Race/ethnicity
Average rating of the openness and acceptance of the community toward people of diverse backgrounds
on a scale of 0 to 100, 2019
Source: Fort Collins Community Survey
Race/ethnicity†
Number of
respondents
Average rating of openness
and acceptance
Difference
from overall
White 528 65 0
Hispanic and/or other race 86 60 -5
Overall 614 65 -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Racial/ethnic differences in rated openness and acceptance of the community
Attending Neighborhood Events
Approximately half of respondents overall reported having attended a neighborhood event in the past
year, but rates were eight percentage points higher among respondents of color.
Race/ethnicity
Percent of survey respondents who reported having attended a neighborhood-sponsored event in the
last 12 months, 2019
Source: Fort Collins Community Survey
Race/ethnicity†
Number of
respondents
Percent who attended a
neighborhood event
Difference
from overall
White 528 47% -1%
Hispanic and/or other race 86 56% 8%
Overall 614 48% -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
0
-5-6
-4
-2
0
White Hispanic and/or other race
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Disparity Graph: Racial/ethnic differences in attending neighborhood events
Interacting with Neighbors
The vast majority of both white and Hispanic and/or other race respondents reported having talked to or
visited with their neighbors—approximately nine in 10.
Race/ethnicity
Percent of survey respondents who reported having talked to or visited with their immediate neighbors in
the last 12 months, 2019
Source: Fort Collins Community Survey
Race/ethnicity†
Number of
respondents
Percent who interacted
with neighbors
Difference
from overall
White 528 90% 1%
Hispanic and/or other race 86 89% 0%
Overall 614 89% -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Racial/ethnic differences in interacting with neighbors
Neighbor Relationships
Differences were found in the extent to which respondents reported having relationships with their
neighbors. Overall, just over half of respondents reported having a relationship with their neighbors, but
the rate was almost 17 percentage points lower for non-Hispanic non-white respondents. Likely due to
small sample sizes, however, these differences were not statistically significant.
-1%
8%
-2%
0%
2%
4%
6%
8%
10%
White Hispanic and/or other race
1%0%
0%
2%
White Hispanic and/or other race
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Race/ethnicity
Percent of individuals reporting that they have a relationship with their neighbors, 2020
Source: City of Fort Collins Our Climate Future Demographic Survey†
Race/ethnicity
Number of
respondents
Number reporting
relationship with
neighbors
Percent reporting
relationship with
neighbors
Difference
from overall
Non-Hispanic white 253 147 58% 2.19%
Hispanic/Latinx 37 19 51% -4.56%
Non-Hispanic non-white
or multiple 23 9 39% -16.78%
Overall 313 175 56%
† Note that the Our Climate Future Demographic Survey was conducted as part of a larger community
engagement strategy and may not be fully representative of all segments of the population
Disparity Graph: Racial/ethnic differences in relationships with neighbors
Helping Neighbors
Helping neighbors is an important aspect of inclusiveness, and approximately three in four respondents
across racial and ethnic groups reported having done a favor for a neighbor in the past year.
Race/ethnicity
Percent of survey respondents who reported having done a favor for a neighbor in the last 12 months,
2019
Source: Fort Collins Community Survey
Race/ethnicity†
Number of
respondents
Percent who did a
favor for a neighbor
Difference
from overall
White 528 75% -1%
Hispanic and/or other race 86 79% 3%
Overall 614 76% -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
2.19%
-4.56%
-16.78%-20.00%
-15.00%
-10.00%
-5.00%
0.00%
5.00%
Non-Hispanic white Hispanic/Latinx Non-Hispanic non-white or
multiple
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Disparity Graph: Racial/ethnic differences in helping neighbors
Residential Segregation
Residential segregation was examined by looking at the racial and ethnic composition of each census tract
in Fort Collins and then comparing it to the racial and ethnic composition of the city as a whole. A tract
was considered over-representative of a given racial or ethnic group if the percentage of people from
that group was 10% or more above the percentage of that group in the general population. By that
metric, almost two-thirds of census tracts in Fort Collins were not representative.
Race/ethnicity
Percent of tracts where the racial/ethnic composition of the tract is representative or non-representative
(10% higher or more) of the general population in Fort Collins, 2019
Source: American Community Survey 5-year estimates
Racial/ethnic representativeness†
Number of
tracts
Percent of
tracts
Non-representative tracts‡ 26 59.1%
White-overrepresented 5 11.4%
Hispanic/Latinx overrepresented 16 36.4%
Non-Hispanic non-white overrepresented 9 20.5%
Representative tracts 18 40.9%
Total tracts 44 100%
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
‡ The total number of non-representative tracts is smaller than the number of non-representative tracts
for individual racial/ethnic groups because in some tracts both Hispanic/Latinx and non-Hispanic, non-
white individuals were overrepresented
Graph: Racial/ethnic representativeness by census tract
-1%
3%
-2%
0%
2%
4%
White Hispanic and/or other race
59.1%
40.9%
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
Non-representative tracts Representative tracts
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City Inclusiveness
City Fosters Belonging Ratings
Respondents overall reported that the City was moderately likely to create a welcoming, inclusive
community that fosters a sense of belonging, a rating of 65 out of 100. However, perceptions were
somewhat more negative among respondents of color, who gave ratings five points lower than
respondents overall.
Race/ethnicity
Average rating of the extent to which the City of Fort Collins creates a welcoming, inclusive community
where all community members feel a sense of belonging on a scale of 0 to 100, 2019
Source: Fort Collins Community Survey
Race/ethnicity†
Number of
respondents
Average rating of whether
City fosters belonging
Difference
from overall
White 528 67 2
Hispanic and/or other race 86 60 -5
Overall 614 65 -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Racial/ethnic differences in ratings of the extent to which the City fosters belonging
City Respects All Ratings
Overall, respondents rated the City as moderately likely to demonstrate respect for all community
members regardless of their characteristics, a rating of 67 out of 100. The rating was similar across racial
and ethnic groups.
Race/ethnicity
Average rating of the extent to which the City of Fort Collins respects all community members
regardless of race/ethnic background, gender, religion, age, disability, sexual orientation, or marital status
on a scale of 0 to 100, 2019
Source: Fort Collins Community Survey
Race/ethnicity†
Number of
respondents
Average rating of City's
respect for all communities
Difference
from overall
White 528 68 1
Hispanic and/or other race 86 63 -4
Overall 614 67 -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
2%
-5%-6%
-4%
-2%
0%
2%
4%
White Hispanic and/or other race
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Disparity Graph: Racial/ethnic differences in perceptions that the City shows respect for all
1%
-4%-6%
-4%
-2%
0%
2%
White Hispanic and/or other race
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Transportation
Within transportation, 11 measures examined the areas of commuting, personal transportation, and
public transportation.10 Findings for transportation measures did not follow predictable patterns by race
and ethnicity, with considerable variation among groups and few consistent patterns in terms of whether
people of color, and within those, which groups, differed from the patterns for Fort Collins or Larimer
County as a whole. Ratings of the ability to use public transit varied considerably by neighborhood,
however, and there were also some differences in ratings of different bus routes.
Table 18. Number (percentage) of measures with more positive, equivalent, or more negative outcomes or
perceptions than the overall outcome or perception for each racial and ethnic grouping included
Racial/ethnic group
Number (%) of
measures with
positive outcomes or
perceptions
Number (%) of
measures with
equivalent outcomes
or perceptions
Number (%) of
measures with
negative outcomes
or perceptions
Non-Hispanic White 1 (11%) 8 (89%) 0 (0%)
Hispanic/Latinx 0 (0%) 1 (50%) 1 (50%)
Asian or Pacific Islander 0 (0%) 1 (50%) 1 (50%)
Black 1 (50%) 1 (50%) 0 (0%)
Native American 1 (50%) 1 (50%) 0 (0%)
Other 0 (0%) 1 (50%) 1 (50%)
Non-Hispanic, Non-White n/a n/a n/a
Hispanic and/or Other Race 0 (0%) 5 (71%) 2 (29%)
White, including Hispanic n/a n/a n/a
10 Note that this includes two measures each of reported ease of bicycling and reported ease of traveling by public
transportation, one looking at Fort Collins and one at Larimer County more broadly.
Data Note: Assessing Differences Between Groups
Wherever possible, statistical testing was conducted in order to see whether differences between the finding
for the overall outcome or perception and the finding for each racial and ethnic group included in the data were
statistically significant. It should be noted that significance testing was not possible in several circumstances: 1)
raw numbers for the different groups were not provided (e.g., percentages only), 2) measures of variance were
not provided (e.g., standard error), or 3) for ACS data, standard tables including margins of error were not
available and data were pulled from the Microdata portal instead. In keeping with the City’s focus on leading
with race, ISLG tested for statistical significance for differences based on race and ethnicity only, with the
exception of a few select measures.
One thing that is important to keep in mind is that statistical significance is impacted by sample size. There was
a very small sample size for a number of measures across the landscape analysis, particularly for racial and
ethnic groups that represent a smaller proportion of the population. For that reason, it is possible that
meaningful differences were not statistically significant in the data that was able to be included here, but would
have been had a larger sample size been possible.
Where statistical testing could not be conducted, ISLG used a set threshold (see How Information is Reported)
to establish whether or not to call two numerical findings different based on the magnitude of differences that
tended to appear as meaningful or significant in the background research reviewed. Despite the use of set
thresholds, caution should be used in drawing conclusions about the differences between groups where
statistical significance could not be conducted.
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Commuting
Commute Time
The majority of people living in Fort Collins had commute times under half an hour; only approximately
one in seven had longer commutes. The percentage of people with commute times over half an hour was
somewhat smaller for Native Americans than the percentage overall, but it was similar to the overall
percentage for all other racial and ethnic groups.
Race/ethnicity
Percent of individuals that have a commute time of 30 minutes or more, 2018
Source: American Community Survey Public Use Microdata Sample 5-year estimates
Race/ethnicity† Population
Number with
commutes over
30 minutes
Percent with
commutes over
30 minutes
Difference
from overall
White 82,633 12,378 15.00% -0.03%
Hispanic/Latinx 11,133 1,870 16.80% -1.83%
Asian or Pacific Islander 3,447 388 11.30% 3.67%
Black 1,300 181 13.90% 1.07%
Native American 465 36 7.70% 7.27%
Other 2,052 272 13.30% 1.67%
Overall 101,030 15,125 14.97% -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Racial/ethnic differences in commutes over 30 minutes
Personal Transportation
Car Ownership
Access to a vehicle is important for many daily-life tasks, and overall only 4% of households reported not
owning a car. Car ownership rates were similar to the overall rate for most racial and ethnic groups, but
Asian or Pacific Islander households were more than three times as likely not to own a car as households
overall in Fort Collins.
-0.03%
-1.83%
3.67%
1.07%
7.27%
1.67%
-4.00%
-2.00%
0.00%
2.00%
4.00%
6.00%
8.00%
White Hispanic/Latinx Asian or Pacific
Islander
Black Native American Other
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Race/ethnicity
Percent of households lacking access to a personal vehicle, 2018
Source: American Community Survey Public Use Microdata Sample 5-year estimates
Race/ethnicity†
Total
households
Number of households
lacking access
Percent of households
lacking access
Difference
from overall
White 68,566 2,533 3.70% 0.46%
Hispanic/Latinx 7,026 368 5.20% -1.04%
Asian or Pacific Islander 1,984 299 15.10% -10.94%
Black 567 14 2.50% 1.66%
Native American 444 22 5.00% -0.84%
Other 1689 104 6.20% -2.04%
Overall 80,276 3,340 4.16% -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Racial/ethnic differences in car ownership
Reported Ease of Driving
Overall, respondents rated it only somewhat easy to drive in Fort Collins, a rating of 58 out of 100.
Hispanic and/or other-race respondents reported that it was more difficult to drive in Fort Collins than
respondents overall, however.
Race/ethnicity
Average rating of ease of driving in Fort Collins on a scale of 0 to 100, 2019
Source: Fort Collins Community Survey
Race/ethnicity†
Number of
respondents
Average rating of
ease of driving
Difference
from overall
White 528 61 3
Hispanic and/or other race 86 48 -10
Overall 614 58 -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
0.46%
-1.04%
-10.94%
1.66%
-0.84%
-2.04%
-12.00%
-10.00%
-8.00%
-6.00%
-4.00%
-2.00%
0.00%
2.00%
4.00%
White Hispanic/Latinx Asian or Pacific
Islander
Black Native American Other
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Disparity Graph: Racial/ethnic differences in reported ease of driving
Reported Ease of Biking
Respondents reported that it was fairly easy to travel by bicycle in Fort Collins, a rating of 81 of 100, and
ratings were similar across racial and ethnic groups. For Larimer County, however, respondents of color
reported that it was somewhat more difficult to travel by bicycle than respondents overall, but this
difference was not statistically significant.
Race/ethnicity
Average rating of ease of traveling by bicycle in Fort Collins on a scale of 0 to 100, 2019
Source: Fort Collins Community Survey
Race/ethnicity†
Number of
respondents
Average rating of ease
of traveling by bicycle
Difference
from overall
White 528 83 2
Hispanic and/or other race 86 78 -3
Overall 614 81 -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Racial/ethnic differences in reported ease of bicycling
3
-10
-15
-10
-5
0
5
White Hispanic and/or other race
2
-3-4
-2
0
2
4
White Hispanic and/or other race
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Race/ethnicity (Larimer County)
Percent of individuals who agree or strongly agree that it is easy to bike in their community (Larimer
County), 2019
Source: Health District of Northern Larimer County Community Health Survey, 2019
Race/ethnicity
Number of
respondents
Percent reporting
ease of biking
Difference
from overall
Non-Hispanic white 2,231 80.7% 1.3%
Hispanic/Latinx or other race† 224 71.3% -8.1%
Hispanic/Latinx 133 70.5% -8.9%
Non-white non-Hispanic 91 72.6% -6.8%
Overall 2,455 79.4% -
† Due to small sample size, Hispanic/Latinx and non-white non-Hispanic groups were combined for
statistical significance testing
Disparity Graph: Racial/ethnic differences in reported ease of bicycling
Reported Walkability
While the majority of respondents agreed or strongly agreed that it was easy to walk in their community,
there were differences by race and ethnicity. Hispanic/Latinx and non-white respondents were
significantly less likely to agree that it was easy to walk in their community than respondents overall.
Race/ethnicity (Larimer County)
Percent of individuals who agree or strongly agree that it is easy to walk in their community, 2019
Source: Health District of Northern Larimer County Community Health Survey
Race/ethnicity
Number of
respondents
Percent
reporting
walkability
Difference
from overall
Non-Hispanic white 2,231 85.1% 1.4%
Hispanic/Latinx or other race*† 224 74.7% -9.0%
Hispanic/Latinx 133 72.7% -11.0%
Non-white non-Hispanic 91 78.3% -5.4%
Overall 2,455 83.7% -
*Statistically significant at p < .05
† Due to small sample size, Hispanic/Latinx and non-white non-Hispanic groups were combined for
statistical significance testing
1.3%
-8.9%
-6.8%
-10.0%
-8.0%
-6.0%
-4.0%
-2.0%
0.0%
2.0%
Non-Hispanic white Hispanic/Latinx Non-white non-Hispanic
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Disparity Graph: Racial/ethnic differences in reported walkability
Public Transportation
Reported Ease of Traveling by Public Transportation
Respondents reported that it was somewhat easy to travel by public transportation in Fort Collins, and it
received an overall rating of 56 out of 100. Similarly, within Larimer County as a whole approximately a
third of respondents reported that it was easy to ride public transit. Ratings of ease of traveling were
fairly similar across racial and ethnic groups in both geographies, but there were differences by Fort
Collins neighborhood with respondents giving the lowest ratings in Southeast and the highest in
Southwest.
Race/ethnicity
Average rating of the ease of traveling by public transportation on a scale of 0 to 100
Source: Fort Collins Community Survey, 2019
Race/ethnicity†
Number of
respondents
Average rating of ease of
traveling by public transit
Difference
from overall
White 528 55 -1
Hispanic and/or other race 86 60 4
Overall 614 56 -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Racial/ethnic differences in reported ease of traveling by public transportation
1.4%
-11.0%
-5.4%
-12.0%
-10.0%
-8.0%
-6.0%
-4.0%
-2.0%
0.0%
2.0%
4.0%
Non-Hispanic white Hispanic/Latinx Non-white non-Hispanic
-1
4
-2
0
2
4
6
White Hispanic and/or other race
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Race/ethnicity (Larimer County)
Percent of individuals who agree or strongly agree that it is easy to ride public transit in their community,
2019
Source: Health District of Northern Larimer County Community Health Survey
Race/ethnicity
Number of
respondents
Percent reporting ease
of riding public transit
Difference
from overall
Non-Hispanic white 2,231 34.0% -0.6%
Hispanic/Latinx or other race† 224 35.1% 0.5%
Hispanic/Latinx 133 35.9% 1.3%
Non-white non-Hispanic 91 33.7% -0.9%
Overall 2,455 34.6% -
† Due to small sample size, Hispanic/Latinx and non-white non-Hispanic groups were combined for
statistical significance testing
Disparity Graph: Racial/ethnic differences in reported ease of traveling by public transportation
Neighborhood
Average rating of the ease of traveling by public transportation on a scale of 0 to 100
Source: Fort Collins Community Survey, 2019
Neighborhood†
Number of
respondents
Average rating of ease of
traveling by public transit
Difference
from overall
Northeast 78 51 -5
East Central 144 52 -4
Southeast 103 50 -6
Northwest/CSU 1,689 62 6
West Central 131 60 4
Southwest 29 65 9
Overall 626 56 -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
-0.6%
1.3%
-0.9%-1.5%
-1.0%
-0.5%
0.0%
0.5%
1.0%
1.5%
Non-Hispanic white Hispanic/Latinx Non-white non-Hispanic
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Disparity Graph: Neighborhood differences in reported ease of traveling by public transportation
Reported Public Transit Connectivity
Overall, only approximately a quarter of respondents across Larimer County reported that they were able
to get where they needed to go by public transportation. No significant differences were found by race
and ethnicity or by sexual orientation, although reported access was lower for non-white, non-Hispanic
respondents.
Race/ethnicity (Larimer County)
Percent of individuals who agree or strongly agree that they can get where they need to go by public
transportation, 2019
Source: Health District of Northern Larimer County Community Health Survey
Race/ethnicity
Number of
respondents
Percent able to
access needs
Difference
from overall
Non-Hispanic white 2,231 28.3% 0.1%
Hispanic/Latinx or other race† 224 26.5% -1.7%
Hispanic/Latinx 133 32.3% 4.1%
Non-white non-Hispanic 91 16.4% -11.8%
Overall 2,455 28.2% -
† Due to small sample size, Hispanic/Latinx and non-white non-Hispanic groups were combined for
statistical significance testing
Disparity Graph: Racial/ethnic differences in reported access to needs by public transportation
-5 -4
-6
6
4
9
-10
-5
0
5
10
Northeast East Central Southeast Northwest/CSU West Central Southwest
0.10%
4.10%
-11.80%-15.00%
-10.00%
-5.00%
0.00%
5.00%
Non-Hispanic white Hispanic/Latinx Non-white non-Hispanic
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Sexual Orientation (Larimer County)
Percent of individuals who agree or strongly agree that they can get where they need to go by public
transportation, 2019
Source: Health District of Northern Larimer County Community Health Survey
Sexual orientation
Number of
respondents
Percent able to
access needs
Difference
from overall
Straight 2,419 27.6% -0.6%
LGBQ+ 100 33.8% 5.6%
Overall 2,519 28.2% -
Disparity Graph: Sexual orientation differences in access to needs by public transportation
Bus Service Frequency Ratings
Ratings of satisfaction with bus service frequency on a scale of 1 to 4 were examined by bus route in
Transfort’s on-board survey of riders. While ratings were similar across most routes, they were noticeably
lower for Route 14, suggesting that riders of that route may be less able to get where they need to go in a
timely fashion.
Bus route
Ratings of satisfaction with the frequency of bus service on a scale of 1 to 4, 2017
Source: City of Fort Collins Transfort Onboard and Paratransit Surveys
Route†
Number of
respondents
Frequency of
service rating
Difference
from overall
Route 2 174 2.78 -0.19
Route 3 295 3.08 0.11
Route 5 60 2.62 -0.35
Route 6 76 2.58 -0.39
Route 7 116 2.75 -0.22
Route 8 109 2.90 -0.07
Route 9 27 2.93 -0.04
Route 10 26 2.79 -0.18
Route 12 48 2.75 -0.22
Route 14 49 2.16 -0.81
Route 16 72 2.77 -0.20
Route 18 49 2.55 -0.42
Route 19 85 2.60 -0.37
Route 31 518 3.15 0.18
-0.6%
5.6%
-5.0%
0.0%
5.0%
10.0%
Straight LGBQ+
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Route 32 149 2.84 -0.13
Route 33 11 2.82 -0.15
Route 81 65 2.90 -0.07
FLEX 140 2.75 -0.22
HORN 289 3.04 0.07
MAX 944 3.05 0.08
Overall 3,302 2.97 -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Differences in rated bus frequency by bus route
Bus Access to Key Destinations Ratings
Ratings of satisfaction with the ability to access key destinations on a scale of 1 to 4 were examined by
bus route in Transfort’s on-board survey of riders. While ratings were similar across most routes, they
were noticeably lower for Rough 14 and higher for Route 33, suggesting that the ability to access key
destinations may vary by route.
Bus route
Ratings of satisfaction with access to key destinations on a scale of 1 to 4, 2017
Source: City of Fort Collins Transfort Onboard and Paratransit Surveys
Route†
Number of
respondents
Access to key
destinations
Difference
from overall
Route 2 174 3.18 -0.04
Route 3 295 3.30 0.08
Route 5 60 2.94 -0.28
Route 6 76 3.12 -0.10
Route 7 116 3.18 -0.04
Route 8 109 3.16 -0.06
Route 9 27 3.52 0.30
Route 10 26 3.00 -0.22
-0.19
0.11
-0.35 -0.39
-0.22
-0.07 -0.04
-0.18 -0.22
-0.81
-0.20
-0.42 -0.37
0.18
-0.13 -0.15
-0.07
-0.22
0.07 0.08
-1.00
-0.80
-0.60
-0.40
-0.20
0.00
0.20
0.40
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Route 12 48 3.30 0.08
Route 14 49 2.59 -0.63
Route 16 72 3.01 -0.21
Route 18 49 3.04 -0.18
Route 19 85 3.19 -0.03
Route 31 518 3.26 0.04
Route 32 149 3.19 -0.03
Route 33 11 3.64 0.42
Route 81 65 3.14 -0.08
FLEX 140 3.17 -0.05
HORN 289 3.17 -0.05
MAX 944 3.16 -0.06
Overall 3,302 3.22 -
† Statistical significance testing was not conducted for this measure, so caution is advised in interpreting
results
Disparity Graph: Differences in rated access to key destinations by bus route
-0.04
0.08
-0.28
-0.10 -0.04 -0.06
0.30
-0.22
0.08
-0.63
-0.21 -0.18
-0.03
0.04
-0.03
0.42
-0.08 -0.05 -0.05 -0.06
-0.80
-0.60
-0.40
-0.20
0.00
0.20
0.40
0.60
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Equity Indicators
How Indicators Were Selected
ISLG used community and other stakeholder input to select a final pool of potential Equity Indicators from
the measures included in the final landscape analysis. In addition to the general criteria for including
measures in the landscape analysis, the following criteria were used to determine whether measures
could serve as Equity Indicators:
1. Are data collected on a regular basis (e.g., annually, every three years)? If not, it is not possible to
track change over time.
2. Is it clear what an increase or a decrease in the measure would mean? If not, the City will not be
able to interpret what changes mean.
Most measures that involve complaint or reporting data would not meet the second criteria because it is
not possible to determine whether an increase means that the problems are greater or whether some
people are more empowered to file a complaint or more comfortable making a report. For example, in
some places it is the most affluent neighborhoods that generate the most complaints about things like
street maintenance, yet quality is not worse in their neighborhoods—they are simply more willing or able
to file a complaint. With that in mind, if the number of complaints increases in a neighborhood, it could
mean the condition is worsening, but it could also mean that residents were provided with information or
resources to file complaints or in other ways empowered to do so. Another example is crime rates. Crime
rates can be driven by both the actual number of crimes and the number of people reporting crimes.
What that means is that an increase in crime rates could be showing that more crimes are being
committed or it could be showing that people are more comfortable reporting crimes to police, which
could be an indication of greater trust in police. For that reason, without more information it would not
be possible to determine whether an increase in crime rates in a given neighborhood was good or bad.
The majority of measures met these criteria, meaning that they were eligible to be included as Equity
Indicators. To select which indicators should be included, ISLG first used community survey selections,
and then supplemented those selections with suggestions for new measures from community members
and other stakeholders. Survey respondents were provided with the names of all measures identified at
the time the survey was fielded and asked which ones they thought should be included as Equity
Indicators; the measures selected by a third or more survey respondents were then chosen. Next, ISLG
reviewed the suggestions for additional measures provided by community members in surveys and focus
groups and by City and County stakeholders including the Fort Collins City Council. While many of those
suggestions could not be included in either the landscape analysis or as Equity Indicators due to lack of
data availability (see Findings from Community Input for more detail), there were also a number that did,
with 35 added to the landscape analysis in total. If the measures themselves or the issues they
represented surfaced as important across multiple individual sources, they were selected as potential
Equity Indicators in addition to being included in the landscape analysis.
Final Equity Indicators
Using the criteria and methodology described above, ISLG identified a pool of 72 measures across the 10
domains as potential Equity Indicators for the City of Fort Collins to track moving forward; the City will
select the final set of indicators to be reported and tracked from this initial pool.
Civic Engagement (3 indicators)
Engagement with Government Voter turnout
Engagement with Community Volunteering
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Opportunities to Volunteer Ratings
Criminal Justice and Public Safety (8 indicators)
Law Enforcement
Criminal Arrest or Citation
Traffic Citation
Use of Force in the Population
Use of Force for Arrestees
Representation Among Police Officers
Police Service Quality Ratings
Incarceration and Community
Supervision
Jail Incarceration
Probation
Perceptions of Safety Neighborhood Safety Ratings
Economic Opportunity (8 indicators)
Poverty and Food Security
Poverty Status
Use of Food Assistance Programs
Worry About Affording Nutritious Meals
Income Household Income
Low Income Status
Employment Unemployment
Business Ownership Representation Among Business Owners
Childcare Difficulty Finding Affordable Childcare
Education (13 indicators)
Academic Achievement
Third Grade Reading Proficiency
Third Grade Math Proficiency
AP Enrollment Rates
SAT Scores
On-Time High School Graduation
Staff Representation Teacher Representation
Principal Representation
School Connections Student-to-Adult Connections
Barriers to Academic Success
School Discipline
School-Based Summonses and Arrests
High School Dropout Rates
Educational Attainment High School Attainment
Bachelor’s Degree Attainment
Environmental Justice (2 indicators)
Pollutants Problems with Unsafe or Unclean Water for Drinking
Problems with Pollution from Industry
Housing (8 indicators)
Housing Affordability
Housing Cost Burden
Worry About Paying Housing Costs
Use of Housing Assistance
Needing But Not Using Housing Assistance
Homeownership
Homelessness Sheltered Homelessness
Unsheltered Homelessness
Neighborhood Access to Basic Needs Ratings
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Public Health (10 indicators)
Access to Care
Uninsured Rates
Regular Health Care Provider
Worry About Medical Care Costs
Delaying Health Care Due to Costs
Delaying Mental Health Care Due to Costs
Forgoing Prescription Medication Due to Costs
Physical Health Poor Physical Health
Mental Health
High Stress
Current Mental Health Concern
Suicidality
Services (10 indicators)
Essential Services
Internet Access
Utility Cost Burden
Street Maintenance Ratings
Sidewalk Condition
Sidewalk Accessibility
Sidewalk Ramp Accessibility
Disaster Response Ratings
Library Service Quality Ratings
Parks and Recreation Park Quality Ratings
Youth Recreation Program Quality Ratings
Social Inclusion (5 indicators)
Community
Community Openness and Acceptance Ratings
Attending Neighborhood Events
Helping Neighbors
Residential Segregation
City Inclusiveness City Fosters Belonging Ratings
Transportation (5 indicators)
Commuting Commute Time
Personal Transportation Car Ownership
Reported Ease of Biking
Public Transportation Reported Ease of Traveling by Public Transit
Reported Public Transit Connectivity
While these were the measures currently identified, the City and other stakeholders may wish to
supplement or replace specific indicators moving forward based on shifting priorities, data availability, or
based on additional feedback from the community or other stakeholders. For example, the Poudre School
District hopes to have data on early education such as kindergarten readiness available in future; if so, it is
possible that one or more Equity Indicators measuring differences in early education could be included.
Changing a subset of indicators is not uncommon among cities using Equity Indicators to track change in
disparities; however, ISLG recommends that a clear rationale be provided whenever such a change is
made (particularly if it involves replacing indicators).
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Next Steps
This report provides baseline findings for the Fort Collins Equity Indicators project as a whole; findings for
the final Equity Indicators will also be presented on a public dashboard developed and maintained by the
City of Fort Collins. The City will update the findings for these indicators on an ongoing basis moving
forward in order to assess progress towards increasing equity within and across the 10 domains. The City
will also be using the findings from the Equity Indicators and the Landscape Analysis more broadly to
inform decision-making about policy and practice, and guide the allocation of resources by identifying
areas where there are greater opportunities for investment and growth. The City will also be beginning
the work of conducting root cause analyses to uncover the drivers behind different disparities and work
with the community and other stakeholders to develop targeted solutions. ISLG will further support the
City in its work by collecting comparison data for other jurisdictions at the local, state, or national level,
where possible.
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Appendix A
Survey Participant Details
Race/Ethnicity, Country of Origin, and Languages Spoken
The majority of the survey participants (67.1%) identified as non-Hispanic white, while roughly a third
identified as a race/ethnicity other than non-Hispanic white. This reflects an oversampling of racial/ethnic
minority groups compared to their relative representation in the Fort Collins population (which is 80%
non-Hispanic white). Close to 10% of participants were born in a country other than the United States,
and 11% speak a language other than English at home (either alone or in addition to English).
Race/Ethnicity
Race/Ethnicity Frequency
Percent of survey
respondents
Percent of Fort
Collins population
White 49 67.1% 80.0%
Hispanic/Latinx 6 8.2% 12.1%
Asian or Pacific Islander 3 4.1% 3.4%
Black 8 11.0% 1.4%
Native American 1 1.4% 0.7%
Multiple or other 5 6.9% 2.3%
Prefer not to answer 1 1.4% n/a
Country of Birth
Were you born in the
United States? Frequency Percent
Yes 63 86.3%
No 7 9.6%
Prefer not to answer 3 4.1%
Language(s) Spoken
Language Frequency Percent
English Only 63 86.3%
Language other than
English* 8 11.0%
Prefer not to answer 2 2.8%
*Note that all but two respondents reported speaking English at home in addition to another language
Age, Gender or Gender Identity, and Sexual Orientation
Respondents represented a wide range of ages, with the youngest being 17 years old and the oldest 64
years old. Approximately two thirds of participants identified as women (69.9%), and a quarter identified
as men. No participants identified as non-binary, and the vast majority of the men and women in the
sample were cisgender, with one participant identifying as a transgender man. Additionally, 16.5% of
participants identified as LGBQ+, while 74% identified as heterosexual.
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Age
Minimum Maximum Mean
Age 17 64 37.5
Gender/Gender Identity
Gender Frequency Percent
Man 19 26.1%
Woman 51 69.9%
Non-binary 0 0.0%
Prefer not to answer 3 4.1%
Transgender status Frequency Percent
Cisgender 69 94.6%
Transgender 1 1.4%
Prefer not to answer 3 4.1%
Sexual Orientation
Sexual Orientation Frequency Percent
Heterosexual 54 74.0%
LGBQ+ 12 16.50%
Prefer not to answer 7 9.50%
Disability or Chronic Health Condition
Close to one in four respondents identified as having a disability or chronic health condition, with 15.1%
reporting having a physical/medical condition, and 12.3% reporting a psychological/cognitive condition
(note that these categories were not mutually exclusive; some respondents reported experiencing both).
Disability Status
Disability/Chronic
Health Condition
Overall Frequency Percent
Yes 17 23.3%
No 50 68.5%
Prefer Not to answer 6 8.2%
Physical/Medical
Disability or
Condition Frequency Percent
Yes 11 15.1%
No 53 72.6%
Prefer not to answer 9 12.3%
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Cognitive/Mental
Health Disability or
Condition Frequency Percent
Yes 9 12.3%
No 55 75.3%
Prefer not to answer 9 12.3%
Education, Student Status, and Tenure
Educational attainment among respondents was high: the majority had a bachelor’s or graduate degree
(71.3%), while just over a quarter had an associate degree or less; one in 10 had less than a high school
degree. Some respondents were current students, with 16.4% currently attending a college or university
in Fort Collins. Additionally, the amount of time respondents reported having lived in Fort Collins ranged
considerably, with a minimum of 1 year and a maximum of 50 years. The average residential tenure was
13.5 years.
Education
Education Frequency Percent
Less than a high school degree 8 10.9%
High school diploma/GED 0 0.0%
Some college or associate degree 13 17.8%
Bachelor's degree 18 24.7%
Graduate degree 34 46.6%
Missing 2 2.7%
Student Status
Student Status Frequency Percent
Non-student 57 78.1%
Student 12 16.4%
Prefer not to answer 4 5.4%
Tenure in Fort Collins
Minimum Maximum Mean
Number of Years in
Fort Collins 1 50 13.5
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Appendix B
Additional Findings from Focus Groups
While focus group participants provided feedback and suggestions for domains and measures that should
be included in the landscape analysis and/or as Equity Indictors, participants also spoke about how they
and others within their community have been impacted by disparities. While some of these were specific
to individual groups, there were also four key themes that emerged across groups: social exclusion,
intersecting areas, policies as drivers of disparities, and budgeting and representation within the City of
Fort Collins. A brief description of each of these and how they manifested across groups follows.
Key Themes
Social Exclusion
Feeling socially excluded as members of the Fort Collins community came up in all of the focus groups
conducted for this project. Community members shared many experiences demonstrating that feeling
welcomed and recognized by the broader Fort Collins community was important for their well-being, and
that social inclusion cut across all of the other areas. For example, members who attended the focus
groups centered on the Hispanic/Latinx, undocumented or mixed-status, religious minority, Native
American, and people living with disabilities communities shared experiencing discrimination across a
wide range of areas including education, economic opportunity, housing, and criminal justice. In
particular, community members across these focus groups shared experiencing how a lack of
understanding and/or respect for diversity translated into realities such as the following, each of which
came up within one or more focus groups (i) neighbors calling the police due to suspicion about family
gatherings or cultural practices, (ii) being viewed in schools by teachers as less capable of educational
success and attainment than other students, (iii) bullying in schools, (iv) difficulty in navigating processes
such as procuring loans for housing, (v) feeling unsafe about calling social services for unmet needs.
Interestingly, many community members across multiple focus groups (e.g., Asian and Pacific Islander,
religious minority, people living with disabilities, LGBTQIA+ communities) specifically named lack of
inclusive programming/events in the library and other cultural centers such as Lincoln Center as
indicators of exclusion. In particular, community members pointed to a focus on Euro-Centric, white, or
Christian-focused programming, or having whites serve as guides to cultures or countries they had
experienced as visitors at the expense of those with lived experience.
Intersecting Areas
An important takeaway that arose in multiple focus groups was how interconnected/intersectional each
of the areas are and how lived experiences across all of these areas are also deeply intertwined.
Participants would name one area as important, and then immediately draw a link between that area and
others. For example, members of the LGBTQIA+ community discussed the common difficulty members of
their community have in finding LGBTQIA+-inclusive healthcare providers, and how transportation issues
made access to inclusive providers even more challenging. After first commenting on the scarcity of
inclusive health care providers in Fort Collins, they described how the few that did provide LGBTQIA+
affirming services were often too far from community members’ homes and/or not easily accessible by
public transportation. Community members living with disabilities also shared how problems related to
City Services (e.g., well-maintained sidewalks) were directly implicated in their health (both physical and
mental), and how a lack of training on the part of frontline workers (e.g., emergency medical technicians,
police) also sometimes translated into discriminatory experiences that impacted their quality of life. As
another example, members in the Asian and Pacific Islander group named experiencing disparities in the
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area of housing (specifically home ownership and difficulties associated with being approved for a
housing loan) as interconnected with both the areas of economic opportunity and social inclusion.
Policies as Drivers of Disparities
A much more systems-oriented takeaway that emerged in five focus groups was the view that multiple
disparities experienced by various communities across these 11 areas are linked to policies and laws in
place in City of Fort Collins and the state of Colorado writ large. For example, community members who
participated in the Asian and Pacific Islander, Hispanic/Latinx, and Native American focus groups named
the “U plus 2” occupancy ordinance11 as having a harmful impact on their community. While this is a law
that was ostensibly enacted to avoid over-occupancy complaints and overcrowding, for communities of
color and mixed-status communities, in particular, the everyday consequence of this ordinance is that it
can mean cultural family arrangements that are against the dominant norms (e.g., intergenerational
households) are discouraged or reacted to punitively such as when family gatherings are deemed to be
problematic and result in contact with the police. As another example of the intersectionality of areas,
participants also noted that economic hardship is one reason that multiple families or extended families
might need to live together, and so by prohibiting these living arrangements, the U plus 2 ordinance
compounds this economic hardship.
As another example of policies driving inequities, members in the LGBTQIA+ focus group referenced City
health care policies that do not recognize the needs of LGBTQIA+ individuals and drive disparities across
the areas of public health and social inclusion. Participants in this group explained how healthcare
coverage afforded to City employees, as an example, does not include care for transgender -related health
needs despite statewide protections for to the LGBTQIA+ community; this exclusion from health care also
intersected with a lack of feeling accepted or recognized in the community.
Budgeting and Representation Within the City of Fort Collins
Importantly, a handful of community members across multiple focus groups (e.g., LGBTQIA+, religious
minority, Hispanic/Latinx groups, Black) raised concerns that their participation in the focus groups held
regularly by the City of Fort Collins did not result seem to result in changes to policy and practice, and,
more specifically, to the budget. Participants voiced the opinion that the City’s efforts in working towards
equity would be more transformative if the budget reflected that commitment more strongly. For
example, in the area of housing, community members across groups cited a lack of affordable housing as
a driver of disparities, but felt that the City’s budget suggested it was moving away from investing in
affordable housing, which may further exacerbate inequity.
Community members also named a lack of diverse representation across departments within the City of
Fort Collins as a driver of disparities as this meant that their concerns and recommendations were not
well understood or shared by those with governing power over their lives. For example, in one of the
focus groups, participants named that the most diverse department was the Utilities Department, while
in another, participants noted that were no LGBTQIA+ specific positions in the City government.
11 The U plus 2 occupancy ordinance restricts household occupancy to one family (which is defined by the
ordinance) or two adults and their dependents. For more information, see
https://www.fcgov.com/neighborhoodservices/occupancy.
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Appendix C
List of All Measures Included in the Landscape Analysis
Civic Engagement
Engagement with Government
Voter Turnout
Representation on Boards and Commissions
Attending Government Events
Trust in Local Government
Engagement with Community
Community Group Membership
Volunteering
Opportunities to Volunteer Ratings
Criminal Justice and Public Safety
Law Enforcement
Criminal Arrest or Citation
Traffic Citation
Use of Force in the Population
Use of Force for Arrestees
Representation among Police Officers
Police Service Quality Ratings
Incarceration and Community Supervision
Jail Incarceration
Probation
Perceptions of Safety
Neighborhood Safety Ratings
Economic Opportunity
Poverty and Food Security
Poverty Status
Emergency Fund
Use of Food Assistance Programs
Worry About Affording Nutritious Meals
Problems with Unsafe Food in Grocery Stores and Restaurants
Income
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Household Income
Personal Earnings
High Wage Occupations
Low Income Status
Employment
Labor Force Nonparticipation
Unemployment
Use of Work-Related or Employment Services
Needed But Did Not Use Work-Related or Employment Services
Business Ownership
Representation among Business Owners
Childcare
Difficulty Finding Childcare
Difficulty Finding Affordable Childcare
Availability of Affordable Childcare
Education
Academic Achievement
Third Grade Reading Proficiency
Third Grade Math Proficiency
AP Enrollment
SAT Scores
On-Time High School Graduation
Staff Representation
Teacher Representation
Principal Representation
School Connections
Student-to-Adult Connections
Student-to-Student Connections
Barriers to Academic Success
High School Dropout Rates
School Discipline
School-Based Summonses and Arrests
School District Mobility
Educational Attainment
High School Attainment
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Bachelor’s Degree Attainment
Environmental Justice
Pollutants
Problems with Unclean Indoor Air
Problems with Pollution from Industry
Problems with Unsafe or Unclean Drinking Water
Climate Vulnerability Factors
Lack of Air Conditioning
Mobile Home Occupancy
Housing
Housing Affordability
Housing Cost Burden
Worry About Paying Housing Costs
Use of Housing Assistance
Needing But Not Using Housing Assistance
Homeownership
Home Loan Denials
Homelessness
Sheltered Homelessness
Unsheltered Homelessness
Neighborhood
Access to Basic Needs Ratings
Public Health
Access to Care
Uninsured Rates
Very Poor Access to Health Care
Regular Health Care Provider
Emergency Room Visits
Use of Emergency Services for Regular Care
Worry about Medical Care Costs
Delaying Health Care Due to Costs
Delaying Mental Health Care Due to Costs
Forgoing Prescription Medication Due to Costs
Physical Health
Poor Physical Health
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Asthma
High Cholesterol
Cardiovascular Disease
Diabetes
Mental Health
High Stress
Current Mental Health Concern
Suicidality
Services
Essential Services
Internet Access
Computer in Household
Phone Access
Sewer Service Quality Ratings
Recycling Programs Ratings
Disaster Response Ratings
Street Maintenance Ratings
Sidewalk Condition
Sidewalk ADA Accessibility
Sidewalk Ramp ADA Accessibility
Utility Cost Burden
Library Service Quality Ratings
Parks and Recreation
Park Quality Ratings
Sufficient Proximity to Parks
Unprogrammed Outdoor Spaces Needs Met
Paved Trails Needs Met
Natural Areas Needs Met
Youth Recreation Program Quality Ratings
Social Inclusion
Community
Openness and Acceptance Ratings
Attending Neighborhood Events
Interacting with Neighbors
Neighbor Relationships
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Helping Neighbors
Residential Segregation
City Inclusiveness
City Fosters Belonging Ratings
City Respects All Ratings
Transportation
Commuting
Commute Time
Personal Transportation
Car Ownership
Reported Ease of Driving
Reported Ease of Biking
Reported Walkability
Public Transportation
Reported Ease of Traveling by Public Transportation
Reported Public Transit Connectivity
Bus Service Frequency Ratings
Bus Access to Key Destinations Ratings
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About
This report was authored by Victoria Lawson, Sukhmani Singh, and Kate Jassin of the
CUNY Institute for State and Local Governance. Additional support was provided by
Jocelyn Drummond, Elizabeth DeWolf, and Julia Bowling.
The CUNY Institute for State and Local
Governance is a good governance think and
do tank. We craft the research, policies,
partnerships and infrastructures necessary to
help government and public institutions work
more effectively, efficiently, and equitably.
For more information, visit islg.cuny.edu or
follow us @CUNYISLG.
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Social Sustainability
222 Laporte Ave.
PO Box 580
Fort Collins, CO 80522
970.221.6758
MEMORANDUM
DATE: May 15, 2020
TO: Mayor Wade Troxell & City Councilmembers
THRU: Darin Atteberry, City Manager
Jeff Mihelich, Deputy City Manager
Jacqueline Kozak-Thiel, Chief Sustainability Officer
Beth Sowder, Social Sustainability Department Director
FROM: Janet Freeman, Equity and Inclusion Coordinator
Leo Escalante, Engagement Specialist
RE: May 12, 2020 Work Session Summary: Equity and Inclusion
At the May 12 Council Work Session, staff provided an update on how the City is
working to embed equity and inclusion into its COVID-19 response and recovery efforts.
The update included an overview of the City’s Racial Equity Rapid Response team,
several projects and preliminary frameworks for accomplishing principles of community
and equity indicator work.
Highlights include:
• Council expressed support for how the City is embedding equity and inclusion
into its COVID-19 response efforts and preliminary framework for an equitable
recovery
• Council expressed desire to continue to prioritize equity work
• Council expressed support for a data-informed approach to the City’s equity and
inclusion work and prioritization of revision offer to assist with this
• Council expressed support for principles of community work and for ensuring the
City leverages perspectives that represent all members of the community
• Council expressed desire to make sure residents have services they need
Follow-up:
• The Adopt-A-Neighbor program currently has 369 volunteers and 60 paired
neighbors.
• The City will continue identifying opportunities where the program can be
used to help low-income neighborhoods
• The program is also currently attempting to launch a pilot program that
equips isolated seniors at-risk for mental health burden brought on by
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social distancing with technological devices to connect them with family
and friends; current barrier is lack of $1500 for equipment purchase
• The Equity Indicator project will cover a broad range of indicators related to
social determinants of health, and will include robust stakeholder engagement
• The City is applying the Just in Time equity lens to the CARES-CV funding
allocation, and will work to embed equity considerations into future budget
decisions and provide relevant data
• The City currently works with community partners such as CSU, PSD, nonprofits
and businesses, as well as others, to help ensure a systemic approach to
advancing equity and inclusion and will continue to leverage those partnerships
• The City is committed to continue developing participatory community solutions
that are data informed and action oriented
• Minority- and women-owned businesses have struggled to access the Payroll
Protection Program (PPP) for a variety of reasons: (a) required loan documents –
many of these businesses do not have full time accounting staff to maintain these
documents; (b) understanding the document requirements – many applications
were received with incomplete documentation (across all business owner types);
(c) language barrier – none of the SBA documents, press releases were sent in
English (the City and partners have been working diligently to provide translation
and services for folks preferring a different language than English); (d) existing
relationships with a bank – this is probably the biggest barrier, many small
businesses including minority- and women-owned do not have a standing
relationships with their bank.
Next Steps
• Staff will continue to use the Just in Time equity lens in response and recovery
efforts while strengthening staff capacity for applying the full robust toolkit
• Staff will continue to identify disproportionate burdens and impacts related to the
coronavirus and its cascading impacts, and create targeted interventions to help
mitigate
• Staff will provide Council with updates on equity indicator work, including seeking
input on which service areas might undergo gaps analysis
• Staff will provide a memo that specifically addresses minority and women owned
businesses impacts and strategies
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Social Sustainability
222 Laporte Ave.
PO Box 580
Fort Collins, CO 80522
970.221.6758
MEMORANDUM
DATE: December 11, 2020
TO: Mayor Wade Troxell & City Councilmembers
THRU: Darin Atteberry, City Manager
Jacqueline Kozak-Thiel, Chief Sustainability Officer
Beth Sowder, Social Sustainability Department Director
FROM: Janet Freeman, Equity and Inclusion Coordinator
RE: December 8, 2020 Work Session Summary: Equity and Inclusion
At the December 8, 2020 Council Work Session, staff provided an update on the City’s Equity
Indicator project. All Councilmembers were present.
Highlights include:
• Council supported the project and expressed a desire to uncover the root causes of
existing disparities and solve underlying barriers to equity
• Council recommended analyzing near-term versus longer-term transformation
opportunities, and prioritizing where we can have the most immediate impact
• Council suggested adding indicators on:
• Health outcomes related to COVID
• Utilities
• Food security (access to healthy foods)
• Infrastructure (e.g. sidewalks)
• Distance to parks
• Preschool attendance
• Vulnerable CSU students
• Council wanted to make sure the final report shares full numbers and other
contextualizing information (e.g. disaggregating college population as able) to deepen
understanding, and to ensure the dashboard visualizations support clear interpretation
• Council supported a regional approach and ensuring residents and community partners
are able to utilize the data
• Council suggested integrating a longitudinal approach that helps uncover reasons
behind drop in racial diversity over time
• Council discussed approaches that include focusing solely on what is under the City
purview versus systemic outcomes, and recommended including both by categorizing
the indicators into three distinct areas:
• Broader community landscape
• City purview and impact
• Future topic areas (e.g. Connexion, community interests, changes over
time)
Follow-up:
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• Staff will continue to work with the CUNY Institute for State and Local Governance to
see if data are available on recommended indicators, and to finalize the disparity
landscape analysis
• A final report will be available mid-January and a subsequent presentation to the Ad-Hoc
Committee is scheduled for January 25th, 2021
• Staff will begin working on the dashboard Q1 of 2021
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