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1 | P a g e United States Community Profile

UNITED STATES


TABLE OF CONTENTS

TABLE OF CONTENTS .................................................................................................. 2

ABOUT SUSAN G. KOMEN® ........................................................................................ 3

COMMUNITY PROFILE INTRODUCTION ................................................................ 4

ANALYSIS OF THE 2015 COMMUNITY PROFILE DATA ..................................... 5

PURPOSE ........................................................................................................................................ 5 METHODS ...................................................................................................................................... 6 CHALLENGES AND LIMITATIONS ............................................................................................... 10

DISCUSSION................................................................................................................... 12

QUANTITATIVE DATA ANALYSIS .............................................................................................. 12 HEALTH SYSTEMS ANALYSIS ................................................................................................... 23 QUALITATIVE DATA ANALYSIS ................................................................................................ 32

CONCLUSIONS ............................................................................................................. 34

REFERENCES ................................................................................................................ 39

APPENDICES ................................................................................................................. 41


ABOUT SUSAN G. KOMEN®

In 1980, Nancy G. Brinker promised her dying sister, Susan, that she would do

everything in her power to end breast cancer forever. In 1982, that promise became a

global movement. What started with $200 and a shoebox full of potential donor

names has now grown into the world’s largest nonprofit source of funding for the

fight against breast cancer - the Susan G. Komen® organization.

Komen funds more breast cancer research than any other nonprofit organization

outside of the U.S. government while also providing real-time help to those facing

the disease. Since 1982, Komen and its local Affiliates have funded more than $920

million in research and provided more than $2 billion for breast cancer screening,

education and treatment programs serving millions of people in more than 30

countries worldwide.

Our efforts have contributed to advancements in early detection and treatment that

have reduced death rates from breast cancer by 37 percent (between 1990 and

2013).


COMMUNITY PROFILE INTRODUCTION

The Community Profile is a needs assessment completed by Susan G. Komen and its

Affiliates to assess the breast cancer burden within the U.S. by identifying areas at

highest risk of negative breast cancer outcomes. Through the Community Profile,

populations most at-risk of dying from breast cancer can be identified. The

Community Profile provides detailed information about these populations, including

demographic and socioeconomic characteristics, as well as needs and disparities that

exist in availability, access and utilization of quality care. This assessment allows

Komen to make data-driven decisions in the development of collaborative

opportunities, grant funding priorities and implementation of evidence-based

community health programs that will meet the most urgent needs and address the

most common barriers to breast cancer care in order to make the biggest impact.

This report contains data for the seven Komen United States (US) Regions and the

National Capital Region. As of August 2016, there were 100 Komen Affiliates1 located

across the U.S. Appendix A provides a list of the Komen Affiliates in each region.

Northeast Region –Vermont, New Hampshire, Massachusetts, Rhode Island,

Connecticut, New York, New Jersey, Pennsylvania, Delaware and Maryland. 14

Komen Affiliates.

Southeast Region –North Carolina, South Carolina, Tennessee, Alabama,

Mississippi, Georgia, Florida and Virginia. 25 Komen Affiliates.

East Central Region – Michigan, Indiana, Kentucky, Ohio and West Virginia. 10

Komen Affiliates

North Central Region – North Dakota, South Dakota, Nebraska, Kansas,

Minnesota, Iowa, Missouri, Wisconsin, and Illinois. 14 Komen Affiliates.

South Central Region – New Mexico, Texas, Oklahoma, Arkansas and

Louisiana. 20 Komen Affiliates.

Northwest Region –Alaska, Washington, Oregon, Idaho, Montana, Wyoming,

Utah and Colorado. 8 Komen Affiliates.

Southwest Region – Hawaii, California, Arizona and Nevada. 10 Komen

Affiliates.

In addition, Komen Headquarters manages community-level activities in the National

Capital Region, which includes Washington D.C. and surrounding counties in

Maryland and Virginia (Appendix A).

Figure 1 represents the U.S. counties, cities, parishes and boroughs serviced by

Komen Headquarters and Affiliates as of February 1, 2017.

1 While 112 Affiliates within the Komen Regions completed the 2015 Community Profile process, only 100 remain due to mergers and/or dissolution


Figure 1. U.S. counties/cities/parishes and boroughs served by a Komen Affiliate or

Headquarters (as of February 1, 2017).

ANALYSIS OF THE 2015 COMMUNITY PROFILE DATA

Purpose

From 2014-2016, Komen Affiliates completed Community Profiles of their local

service areas while Komen Headquarters completed a Community Profile for the

National Capital Region as well as State-level Community Profiles.

While Komen Affiliates provide services at the community level, they are also

grouped into seven regions that provide an opportunity for collaboration on a multi-

state level. Although local and state level data are included in the Affiliate, National

Capital Region and State Community Profile Reports, a broader look at breast cancer

outcomes, needs and disparities across the nation is not. In addition, there is a lack of

information regarding common strategies that Komen Headquarters and Affiliates

are implementing to address Community Profile findings.

Therefore, the Evaluation and Outcomes team at Komen Headquarters conducted an

analysis of the local and state level Community Profiles in order to compile data and

provide a broader perspective of the results found across the U.S. The data provided

in this report are meant to aid Komen Headquarters and the Affiliates in identifying

issues and barriers to care that are common throughout the U.S., and enable Komen


Headquarters and Affiliates to work together to address common goals, when

appropriate.

Methods

Komen Headquarters Evaluation and Outcomes team reviewed State- and Affiliate-

level data from the 100 Affiliate Community Profiles in the seven Affiliate regions

(East Central, North Central, Northeast Region, Northwest, South Central, Southeast,

Southwest) and the National Capital Region. These data were compiled into this U.S.

Community Profile Report.

Quantitative Data To determine which communities (e.g., counties, parishes, cities) in the U.S. bear the

greatest burden of breast cancer, data representing all communities from the State

Community Profiles were compared to Healthy People 2020 (HP2020) breast cancer

targets, the benchmark for each community. HP2020 is a major federal government

initiative that provides specific health objectives for communities and for the country

as a whole. HP2020 has several cancer-related objectives, including the targets used

in this report: reducing the number of breast cancers that are diagnosed at a late-

stage and reducing women’s death rate from breast cancer.

For this report, late-stage breast cancer is defined as regional (Stage III) or distant

stage (Stage IV) using the Surveillance, Epidemiology and End Results (SEER)

Summary Stage definitions (Young et al., 2001). The breast cancer late-stage

diagnosis rate is calculated as the number of women with regional (Stage III) or

distant (Stage IV) breast cancer at the time of diagnosis in a particular geographic

area divided by the number of women living in that area. Late-stage diagnosis rates

are presented in terms of 100,000 women and have been adjusted for age. Late-

stage diagnosis rates are important because medical experts agree that it’s best for

breast cancer to be detected early. Women whose breast cancers are found at an

early stage (Stage I or Stage II) usually need less aggressive treatment and do better

overall than those whose cancers are found at a later stage (US Preventive Services

Task Force, 2016).

The breast cancer death rate shows the frequency of death from breast cancer

among women living in a given area during a certain time period. The death rate is

calculated as the number of women from a particular geographic area who died from

breast cancer divided by the total number of women living in that area. Death rates

are presented in terms of 100,000 women and have been adjusted for age.

The Evaluation and Outcomes team compiled breast cancer late-stage diagnosis and

death rates and trends (changes over time) from the State Community Profile

Reports. Communities that are predicted not to meet both the HP2020 breast


cancer late-stage diagnosis rate and death rate benchmarks are referred to as

“Highest Priority” communities, since they carry the highest burden of breast cancer

within the region.

The Evaluation and Outcomes team also compiled key demographic and

socioeconomic characteristics from the State Community Profile Reports including

race, ethnicity, age, education level, poverty, unemployment, immigration (i.e.,

foreign born), use of English language (e.g., linguistically isolated), medically

underserved, rural areas and uninsured. These population characteristics are known

to impact health outcomes and may provide information on the types of services and

interventions necessary to alleviate the burden of breast cancer in these areas (Adler

and Rehkopf, 2008; American Cancer Society, 2015a; American Cancer Society,

2015c; Braveman, 2010; Danforth, 2013; Lurie and Dubowitz, 2007; Robert Wood

Johnson Foundation, 2008).

The following sources were used for gathering the quantitative data:

Death rate data: Centers for Disease Control and Prevention (CDC)- National

Center for Health Statistics- Surveillance, Epidemiology and End Results

(SEER)* Stat, 2006-2010

Death trend data: National Cancer Institute (NCI) and CDC- State Cancer

Profiles, 2006-2010

Late-stage diagnosis and trends data: North American Association of Central

Cancer Registries (NAACCR)-CINA Deluxe Analytic File, 2006-2010

Race, ethnicity and age data: U.S. Census Bureau- Population Estimates, 2011

Education level, poverty, unemployment, immigration and use of English

language data: U.S. Census Bureau- American Community Survey, 2007-2011

Rural population data: U.S. Census Bureau- Census, 2010

Medically underserved data: Health Resources and Services Administration,

2013

Health insurance data: U.S. Census Bureau- Small Area Health Insurance

Estimates, 2011

Health Systems Analysis The Evaluations and Outcomes team used a comprehensive internet search to

identify and classify facilities offering breast cancer services including screening

providers, diagnostic providers and treatment providers for each state.

The internet search included the following sites. For additional detail regarding the

internet search please see Appendix B.

Community Health Centers: http://nachc.org/about-our-health-centers/find-a-

health-center/


Title X: http://www.hhs.gov/opa/title-x-family-planning/initiatives-and-

resources/title-x-grantees-list/

Mammography Centers:

http://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfMQSA/mqsa.cfm

Hospitals:

https://data.medicare.gov/Hospital-Compare/Hospital-General-

Information/v287-28n3

The internet search consisted of locating the following types of facilities in the

communities identified as having the greatest need (“Highest Priority” communities):

Hospitals (e.g., public or private, for-profit or non-profit)

Community health centers that provide care regardless of an individual’s

ability to pay (e.g., Federally Qualified Health Centers (FQHCs) and FQHC

look-alikes)

Free and charitable clinics that utilize a volunteer staff model and restrict

eligibility to individuals who are uninsured, underinsured and/or have limited

to no access to primary health care

Health departments (e.g., local county or city health department funded by a

government entity)

Title X providers that are usually family planning centers that also offer breast

cancer screening services

Facilities that provide breast cancer services, but do not fit under any of the

other categories. (e.g., non-medical service providers)

Facilities were classified as screening if they provided clinical breast exams,

screening mammograms and/or patient navigation into screening. Classification as a

diagnostic service provider included locations that provide diagnostic

mammography, ultrasound, biopsy, magnetic resonance imaging (MRI) scanning

and/or patient navigation into diagnostic services. Classification as a treatment

service provider included locations that provide chemotherapy, radiation therapy,

surgery, reconstruction and/or patient navigation into treatment services. A facility

may be classified under more than one classification depending on the breast cancer

services provided.

The comprehensive internet search also included the identification of facilities that

provide breast cancer services that are accredited by a national organization that

monitors the facility to ensure that the quality of care being provided meets specific

benchmarks. Each national organization’s website was used to identify the

accredited facilities in each state. For this report, the following national

accreditations were used to measure the quality of care available:

American College of Surgeons Commission on Cancer Certification (CoC) -

https://www.facs.org/quality-programs/cancer/coc


American College of Surgeons National Accreditation Program for Breast

Centers (NAPBC)- https://www.facs.org/quality-programs/napbc)

American College of Radiology Breast Imaging Centers of Excellence (BICOE)-

http://www.acr.org/Quality-Safety/Accreditation/BICOE

National Cancer Institute’s designated Cancer Centers -

http://www.cancer.gov/research/nci-role/cancer-centers

Each State Community Profile Report contains the number, type and location of

facilities that provide breast cancer services along with the number of accredited

facilities that are available. The Evaluations and Outcomes team extracted from the

State Community Profile Reports the number, type and location of facilities that

provide breast cancer services in the “Highest Priority” communities. In addition, the

number and type of accredited facilities in the “Highest Priority” communities were

extracted and used in this report.

The following icons are used in the health systems analysis and discussion section to

represent the different types of breast cancer services available in the “Highest

Priority” communities. Screening Diagnostic Treatment

Qualitative Data The Evaluations and Outcomes team analyzed qualitative data from Komen Affiliates

and the National Capital Region, which were collected during the 2015 Community

Profile process. Only data from the HP2020 “Highest Priority” communities are

included in the qualitative data section of this report. Data were gathered from

health care providers, breast cancer survivors and community members who

represented the target communities selected by Komen Headquarters and Affiliates.

The methods used by Komen Headquarters and Affiliates to collect an individual’s

attitude and beliefs about breast cancer care in the local community included:

Surveys: open-ended questions to gather information in an online or paper

format

Focus groups: structured discussion used to obtain in-depth information from

a group of people

Key informant interviews: in-depth, structured discussions with people who

are very familiar with the community

Document review: review of published materials that used qualitative data

collection methods


Using thematic analysis, the Evaluations and Outcomes team identified common

themes from the qualitative data findings presented in the Affiliate Community

Profile Reports. Themes were added, combined and revised as commonalities

became more prevalent. The themes were tracked in a spreadsheet and were

classified by region and community of interest. The most frequently cited themes

are discussed in the qualitative data section of this report. A list of all themes and

their corresponding definitions are located in Appendix C.

The following icons were used to represent different data collection methods

conducted by the Affiliates.

Survey Focus Group Key Informant Interview Document Review

Mission Action Plan Using the data collected during the Community Profile process, Komen Headquarters

and Affiliates developed an action plan, referred to as the Mission Action Plan (MAP),

to implement within a four-year time period to address the breast cancer needs

identified for their target communities. Each Affiliate’s MAP consists of problem

statements, priorities and objectives. The problem statements summarize the issues

revealed during the Community Profile process in the communities of interest.

Priorities represented the goals that the Affiliates expected to achieve within five

years. Objectives are the activities that an Affiliate is going to do to reach the

priorities.

The Evaluations and Outcomes team used descriptive analysis to identify

commonalities within the problem statements, priorities and objectives in each

Affiliate’s Mission Action Plan. The problem statements, priorities and objectives

were first classified into descriptive categories. The categories were then analyzed to

identify commonalities. Commonalities identified from the Affiliates’ MAPs are

presented in the conclusions section of this report.

Challenges and Limitations

The various methods used to gather data for the 2015 Community Profile process

resulted in challenges that limit the generalizability of the data collected.

Recent data At the time of quantitative data collection for the Community Profile Reports, the

most recent data available were used but, for breast late-stage diagnosis and death

rates, these data are still several years behind. For example, the breast cancer late-

stage diagnosis and death rates that were available in 2013, when data were being


collected, were from 2010. For the U.S. as a whole and for most states, breast cancer

late-stage diagnosis and death rates do not often change rapidly. Rates in individual

communities might change more rapidly. In particular, if a cancer control program

has been implemented in 2011-2013, any impact of the program on late-stage

diagnosis and death rates would not be reflected in this report.

As time passes, the data in this report will become more out-of-date. However, the

trend data included in the report can help estimate current values. Also, the State

Cancer Profiles Web site (http://statecancerprofiles.cancer.gov/) is updated annually

with the latest cancer data for states and can be a valuable source of information

about the latest breast cancer rates. However, it is unlikely that the data that is

presented in this report will change significantly in the five years between

Community Profile updates to result in changes to the “Highest Priority”

communities.

The available breast cancer services (e.g., screening, diagnostic and treatment) and

accredited facilities (e.g., CoC, BICOE, NAPBC, and NCI Cancer Centers) identified in

the health system analysis section of this report were collected between September

2014 – March 2015. Therefore, local facilities that provide breast cancer services

(e.g., screening, diagnostics and treatment) may have changed since March 2015 and

may be either over-represented or under-represented in the community.

Data Availability For some communities, data might not be available or might be of varying quality.

Cancer surveillance programs vary from state to state in their level of funding and

this can impact the quality and completeness of the data in the cancer registries and

the state programs for collecting death information. There are also differences in the

legislative and administrative rules for the release of cancer statistics used for studies

such as community needs assessments. These factors can result in missing data for

some of the data categories in this report. Communities missing both death and

late-stage diagnosis rate data were excluded from HP2020 priority classification.

This does not mean that the community may not have high needs; it only means that

sufficient data are not available to classify the community.

There are also many factors that impact breast cancer risk and survival for which

quantitative data are not available. Some examples include family history, genetic

markers like HER2 and BRCA, other medical conditions that can complicate

treatment, and the level of family and community support available to the patient.

Good quantitative data are not available on how factors such as these vary from

place to place.


Qualitative Data Qualitative methods (e.g., surveys, focus groups, key informant interviews) that were

used during the Affiliate Community Profile process gathered information regarding

an individual’s attitude and beliefs about breast cancer care in their local community.

The qualitative data used in this report have some specific limitations that were

unable to be controlled for because the methods implemented and data collected

were completed by over 100 different Affiliates. These limitations include, but are not

limited to:

Small sample sizes limit the ability of the data to accurately represent

everyone in the community

Data collected by the Affiliates were not always from communities that were

classified as “Highest Priority” in this report

Bias of the facilitator and/or interviewer in which they give preference to their

own view over others and recall information that favors their view only

Response bias in which participants provide answers they believe the

facilitator or interviewer wants to hear, even if untrue

Poor wording of questions may have resulted in inaccurate, or unrelated

responses that do not match the intent of the question

Sampling bias in which attitudes and beliefs of those that participated in the

different qualitative methods may be different than those that did not (e.g.,

those that participated may have less barriers than those that did not

participate)

These limitations may result in the qualitative data in this report not being

representative of the geographic areas that are not predicted to meet HP2020

targets for late-stage diagnosis and death rates, and may only represent the

perspectives of those that participated in the surveys, focus groups and key

informant interviews.

DISCUSSION

In order to better understand the breast cancer issues and barriers to care that are

common across the U.S. and enable Affiliates to work together to address common

goals, Komen Headquarters Evaluation and Outcomes team compiled available

quantitative, health systems and qualitative data within the U.S. This section details

the findings of this national analysis.

Quantitative Data Analysis

Breast cancer late-stage diagnosis and death rates and trends were analyzed across

the U.S. in order to assess the nation-wide burden of breast cancer. These data were

then compared to Healthy People 2020 targets for breast cancer to identify the

areas of greatest need within the U.S. Table 1 shows both late-stage diagnosis and


death rates and trends for the U.S. states. The numbers in red are higher than the

National rate or trend.

Table 1. Female breast cancer late-stage diagnosis and death rates and trends-

United States.

Population Group

Female Population

(Annual Average)

Late-Stage Diagnosis and Trends Death Rates and Trends # of New

Late-stage Cases

(Annual Average)

Age-adjusted Late-stage Incidence

Rate /100,000

Late-stage Trend

(Annual Percentage

Change)

# of Deaths (Annual

Average)

Age-adjusted Death Rate /100,000

Death Trend (Annual Percent Change)

US (states with available data)

145,332,861 70,218 43.7 -1.20% 40,736 22.6 -1.90%

Alabama 2,426,817 1,307 47.3 -2.50% 674 23.3 -1.20%

Alaska 332,250 133 43.2 2.70% 64 24.2 -1.20%

Arizona 3,138,990 1,294 38.2 0.00% 733 20.6 -2.00%

Arkansas 1,435,070 717 44.2 -2.30% 416 23.4 -1.20%

California 18,413,837 8,287 43.5 -1.70% 4,251 21.9 -2.10%

Colorado 2,437,011 1,089 42.5 1.20% 495 19.6 -2.30%

Connecticut 1,820,737 958 44.6 0.00% 507 21.6 -2.30%

Delaware 454,255 222 42.6 0.30% 125 22.8 -2.90%

Florida 9,457,566 4,844 41.8 -0.80% 2,723 21.3 -1.40%

Georgia 4,838,820 2,253 45.5 -0.40% 1,146 23.4 -1.40%

Hawaii 665,806 294 38.3 3.50% 133 16.4 -1.80%

Idaho 761,268 346 43.9 -2.90% 176 21.6 -2.00%

Illinois 6,492,949 3,341 47.1 0.10% 1,763 23.6 -2.40%

Indiana 3,260,368 1,488 41.1 -0.60% 909 23.9 -1.90%

Iowa 1,525,409 755 42.7 1.00% 431 21.3 -2.40%

Kansas 1,416,658 692 44.5 -3.20% 378 22.2 -1.80%

Kentucky 2,179,870 1,083 43.4 -2.60% 597 23.1 -1.80%

Louisiana 2,265,429 1,151 46.8 0.40% 642 25.4 -1.40%

Maine 677,964 354 41.6 -1.90% 193 20.9 -2.50%

Maryland 2,942,268 1,521 46.4 -0.50% 818 24.5 -2.00%

Massachusetts 3,344,752 1,586 41.4 -2.60% 895 21.3 -3.20%

Michigan 5,067,869 2,371 41 -0.60% 1,468 24 -2.00%

Minnesota NA NA NA NA 652 20.9 -2.50%

Mississippi 1,514,063 771 46.8 -0.40% 421 24.7 -0.90%

Missouri 3,024,156 1,574 45.7 -0.10% 890 24.2 -1.50%

Montana 485,248 255 43.7 1.80% 123 19.8 -2.50%

Nebraska 907,187 426 42.4 -4.30% 224 20.1 -2.60%

Nevada 1,273,022 527 39.5 2.30% 306 23 -1.50%

New Hampshire 665,676 326 41.6 1.10% 174 21.3 -3.10%

New Jersey 4,476,452 2,402 46.5 -1.60% 1,389 25.2 -2.40%

New Mexico 1,019,306 418 37.4 1.00% 243 20.9 -1.70%


Population Group

Female Population

(Annual Average)

Late-Stage Diagnosis and Trends Death Rates and Trends # of New

Late-stage Cases

(Annual Average)

Age-adjusted Late-stage Incidence

Rate /100,000

Late-stage Trend

(Annual Percentage

Change)

# of Deaths (Annual

Average)

Age-adjusted Death Rate /100,000

Death Trend (Annual Percent Change)

New York 9,929,239 5,026 44.6 -1.60% 2,704 22.3 -2.60%

North Carolina 4,751,657 2,401 45.4 -0.50% 1,260 23.1 -1.70%

North Dakota 327,214 179 47.6 1.30% 94 21.6 -2.20%

Ohio 5,889,869 2,972 44 0.60% 1,820 24.8 -1.90%

Oklahoma 1,857,419 931 44.8 -1.60% 520 23.9 -1.30%

Oregon 1,899,501 953 43.3 -1.70% 508 21.6 -2.00%

Pennsylvania 6,474,106 3,566 45.4 -0.40% 2,103 23.8 -2.30%

Rhode Island 546,285 272 42.6 -4.80% 149 20.8 -3.30%

South Carolina 2,316,194 1,212 45.9 -1.00% 638 23.5 -1.70%

South Dakota 400,083 200 44.1 -0.30% 105 20.3 -2.20%

Tennessee 3,195,539 1,605 44.1 -3.00% 880 23.3 -1.60%

Texas 12,251,113 4,905 40.7 -3.20% 2,610 21.8 -1.80%

Utah 1,322,539 469 42.4 -0.70% 238 21.8 -1.20%

Vermont 316,866 148 38.5 1.90% 84 20.4 -2.70%

Virginia 3,949,393 1,896 43.9 0.10% 1,074 24 -1.90%

Washington 3,293,650 1,599 44.2 -0.40% 802 21.5 -2.10%

West Virginia 935,126 455 38.9 0.80% 283 22.1 -1.60%

Wisconsin 2,841,001 NA NA NA 745 21.3 -2.50%

Wyoming 267,757 121 40.3 -4.40% 65 21.3 -2.40%

NA – data not available.

Rates are cases/deaths per 100,000.

Age-adjusted rates are adjusted to the 2000 U.S. standard population.

Late-stage diagnosis data are for years 2006-2010 except for Nevada, Ohio and Virginia which are 2005-2009.

Death data are for years 2006-2010

Numbers in red are higher than national rate or trend

Source of late-stage diagnosis rate and trend data: NAACCR – CINA Deluxe Analytic File.

Source of death rate data: CDC – NCHS mortality data in SEER*Stat.

Source of death trend data: NCI/CDC State Cancer Profiles

Comparison to Healthy People 2020 Targets Healthy People 2020 (HP2020) is a major federal government initiative that provides

specific health objectives for communities and for the country as a whole. HP2020

targets for breast cancer late-stage diagnosis and death rates were used as a

benchmark to determine which communities (e.g., county, city) in the U.S. have the

highest breast cancer needs. In 2014, the HP2020 target for breast cancer late-stage

diagnosis rate was 41.0 per 100,000 females and the target for breast cancer death

rate was 20.6 per 100,000 females.

Breast cancer late-stage diagnosis and death rates and trends (changes over time)

were used to calculate whether each community would meet the HP2020 target,


assuming the trend seen in years 2006 to 2010 continue for 2011 and beyond. A

negative trend means that the rates are predicted to decrease each year; while a

positive trend indicates that rates are increasing each year. For breast cancer late-

stage diagnosis and death rates, a negative trend is desired.

Communities are classified as follows:

Communities that are not likely to achieve either of the HP2020 targets for

late-stage diagnosis or death rates are considered to have the highest needs.

Communities that have already achieved both targets are considered to have

the lowest needs.

Other communities are classified based on the number of years needed to

achieve the two targets.

Table 2 shows how communities are assigned to priority categories. There has not

been any indication that either one of the two HP2020 targets is more important

than the other. Therefore, the report considers them equally important.

Table 2. Priority classification based on the projected time to achieve HP2020 breast

cancer targets. Time to Achieve Late-stage Incidence Reduction Target

Time to Achieve Death Rate Reduction Target

13 years or longer 7-12 yrs. 0 – 6 yrs.

Currently meets target Unknown

13 years or longer

Highest High Medium

High Medium Highest

7-12 yrs. High Medium

High Medium Medium Low

Medium High

0 – 6 yrs.Medium

High Medium

Medium Low

Low Medium

Low Currently

meets targetMedium

Medium Low

Low Lowest Lowest

Unknown Highest Medium High

Medium Low

Lowest Unknown

If the time to achieve the HP2020 target cannot be calculated for one of the HP2020

indicators (i.e., late-stage diagnosis rate or death rate), then the community is

classified based on the other indicator. If both indicators are missing, then the

community is classified as “unknown". This doesn’t mean that the community may

not have high needs; it only means that sufficient data are not available to classify

the community.

Appendix D represents communities that have been designated “Highest Priority”.

The “Highest Priority” designation means that they are not likely to meet the Healthy

People 2020 targets for breast cancer late-stage diagnosis or deaths. In addition, key

demographic and socioeconomic characteristics have been provided in Appendix D

that may assist in identifying who in these communities may be most in need of help.

For this report, demographic and socioeconomic characteristics are considered

influential factors when the percentage is substantially higher than the state.


Substantially higher is defined as three percentage points higher for a factor less

than 10.0 percent and five percentage points higher for a factor equal to or greater

than 10.0 percent.

Demographic characteristics include populations that have been found to have less

favorable breast cancer outcomes:

Black/African-American women: Breast cancer is the most common cancer

among Black/African-American women. In 2013, breast cancer deaths were

39 percent higher in Black/African-American women than in White women

(Howlader et al., 2016). Although breast cancer survival in Black/African-

American women has increased over time, survival rates remain lower than

among white women.

Hispanic/Latina women: Breast cancer is the leading cause of cancer death in

Hispanic/Latina women (American Cancer Society, 2015b).

Asian and Pacific Islander (API) women: Breast cancer incidence among

Asian-American, Native Hawaiian and Pacific Islander women have increased

since 2005 (American Cancer Society, 2016). Breast cancer is the second

leading cause of cancer death in Asian-American, Native Hawaiian and Pacific

Islander women (American Cancer Society, 2016).

American Indian and Alaska Native (AIAN) women: The last two decades have

seen large increases in both incidence and death rates for American Indian

and Alaska Native women (American Cancer Society, 2015a). Among AIAN

women, those who live in Alaska and the Southern Plains have the highest

death rates and women who live in the Southwest have the lowest mortality

rates (White et al., 2014).

Older women (65 and older): The risk of breast cancer increases as an

individual becomes older. Most breast cancers and breast cancer deaths occur

in women aged 50 and older (American Cancer Society, 2015a)

Socioeconomic characteristics include factors that have been identified as barriers

that may prevent individuals from being able to access care, afford care and/or

understand the care that their doctor recommends. For example, uninsured

individuals that have an annual income below 200 percent Federal Poverty Level

may not have the financial resources to pay for diagnostic services if they have an

abnormal mammogram. Immigrants that do not speak English fluently may

experience cultural and language barriers when receiving care. Individuals that

reside in rural and/or medically underserved areas may have to travel outside of their

community to access care which requires transportation resources as well as longer

periods of time off work.


In in the U.S., there are 561 communities that are projected to not meet HP2020

breast cancer targets and are, thus, considered “Highest Priority”. Of the 561 “Highest

Priority” communities, 151 communities are not in a local Komen Affiliate service area.

Southeast Region: 184 “Highest Priority” communities; 58 are not served by a

Komen Affiliate.

North Central Region: 97 “Highest Priority” communities; 31 are not served by

a Komen Affiliate.

East Central Region: 95 “Highest Priority” communities; 24 are not served by

a Komen Affiliate.

South Central Region: 94 “Highest Priority” communities; 29 are not served by

a Komen Affiliate.

Northwest Region: 50 “Highest Priority” communities; 7 are not served by a

Komen Affiliate.

Northeast Region= 27 “Highest Priority” communities; all are served by a

Komen Affiliate.

Southwest Region: 12 “Highest Priority” communities; 2 are not served by a

Komen Affiliate.

National Capital Region (NCR): 2 “Highest Priority” communities served by

Komen Headquarters.

In the U.S., there are 561 HP2020 “Highest Priority” communities. Figure 2 shows the

percentage of HP2020 “Highest Priority” communities in each Komen Region. In the

Southeast Region there are 184 “Highest Priority” communities which make up 24.8%

of all communities in that region and accounts for 32.8% of all the “Highest Priority”

communities in the U.S. In the North Central Region there are 97 “Highest Priority”

communities which make up 12.2% of all communities in that region and account for

17.3% of all the “Highest Priority” communities in the U.S. In the East Central Region

there are 95 “Highest Priority” communities which make up 21.7% of all communities

in that region and 16.9% of all the “Highest Priority” communities in the U.S.

In the South Central Region there are 94 “Highest Priority” communities which make

up 18.7% of all communities in that region and 16.8% of all the “Highest Priority”

communities in the U.S. In the Northwest Region there are 50 “Highest Priority”

communities which make up 15.7% of all communities in that region and 8.9% of all

the “Highest Priority” communities in the U.S. In the Northeast Region there are 27

“Highest Priority” communities which make up 11.2% of all communities in that region

and 4.8% of all the “Highest Priority” communities in the U.S. In the Southwest

Region there are 12 “Highest Priority” communities which make up 12.6% of all

communities in that region and 2.1% of all the “Highest Priority” communities in the

U.S. In the National Capital Region there are two “Highest Priority” communities

which make up 16.7% of all communities in that region and 0.3% of all the “Highest

Priority” communities in the U.S.


Figure 2. Percentage of communities in each Komen Region classified as a HP2020

“Highest Priority” community.

In the U.S., 76.3 percent (428 of the 561) of the HP2020 “Highest Priority”

communities have substantially higher percentage of individuals residing in rural

areas (Appendix E).

Southeast Region: 146 “Highest Priority” rural communities (GA=37; MS=20;

NC=20; VA=17; TN=16; AL=15; SC=11; FL=10).

East Central Region: 76 “Highest Priority” rural communities (KY=21; OH=19;

MI=15; IN=12; WV=9).

North Central Region: 73 “Highest Priority” rural communities (MO=23; IA=16;

IL=11; MN=7; WI=7; KS=4; NE=2; ND=2; SD=1).

South Central Region: 67 “Highest Priority” rural communities (TX=30; AR=14;

LA=10; OK=8; NM=5).

Northwest Region: 36 “Highest Priority” rural communities (ID=7; WA=6;

CO=5; OR=5; UT=4; WY=4; MT=3; AK=2).

Northeast Region: 20 “Highest Priority” rural communities (PA=7; MD=3;

MA=2; ME=2; NJ=2; NY=2; DE=1; VT=1).

Southwest Region: 10 “Highest Priority” rural communities (CA=5; AZ=2; NV=2;

HI=1).

In the U.S., 52.8 percent (296 of the 561) of the HP2020 “Highest Priority”

communities have substantially higher percentage of individuals residing in medically

underserved areas (Appendix F). According to the U.S. Department of Health and

Human Services, areas are designated as medically underserved when they have too

few primary care providers to serve the area residents, a high percentage of

12.6%

15.7%

18.7%

12.2%

24.8%

11.2%

16.7%

21.7%


residents with incomes below the poverty level and/or a high percentage of the

population being over the age of 65.

Southeast Region: 133 “Highest Priority” medically underserved communities

(GA=33; MS=27; NC=16; VA=16; TN=14; AL=12; SC=8; FL=7).

South Central Region: 65 “Highest Priority” medically underserved

communities (TX=27; AR=16; LA=14; NM=5; OK=3).

East Central Region: 38 “Highest Priority” medically underserved communities

(KY=11; MI=8; OH=8; WV=8; IN=3).

North Central Region: 26 “Highest Priority” medically underserved

communities (MO=12; WI=4; IL=3; IA=2; MN=2; KS=1; ND=1; SD=1).

Northwest Region: 19 “Highest Priority” medically underserved communities

(ID=4; OR=4; WA=4; MT=3; CO=2; UT=1; WY=1).

Northeast Region: 11 “Highest Priority” medically underserved communities

(PA=5; MD=3; ME=1; NJ=1; NY=1).

Southwest Region: 4 “Highest Priority” medically underserved communities

(CA=3; AZ=1).

These factors have been linked to barriers associated with accessing quality and

timely care. Collaboration among Komen Affiliates that have a higher percentage of

individuals residing in rural and medically underserved areas would allow sharing of

best practices on what has worked and what has not worked in reaching rural

populations and addressing the barriers they have in accessing care.

Black/African-American women are often diagnosed with late-stage breast cancer

when treatment options are limited, and the prognosis is poor. Black/African-

American women also have a 39 percent higher breast cancer death rate than white

women (Howlader et al., 2016). In the U.S., 18.0% of the HP2020 “Highest Priority”

communities (101 of 561) have a substantially larger Black/African-American female

population than their respective state as a whole (Appendix G).

Southeast Region: 65 “Highest Priority” communities with a substantially

larger African-American female population (GA=15; VA=13; MS=10; AL=9;

NC=8; SC=8; FL=1; TN=1).

South Central Region: 22 “Highest Priority” communities with a substantially

larger African-American female population (LA=9; AR=8; TX=4; OK=1).

Northeast Region: 5 “Highest Priority” “Highest Priority” communities with a

substantially larger African-American female population (MD=2; PA=2; NJ=1).

North Central Region: 5 “Highest Priority” “Highest Priority” communities with

a substantially larger African-American female population (MO=4; KS=1).

East Central Region: 3 “Highest Priority” “Highest Priority” communities with a

substantially larger African-American female population (IN=1; MI=1; OH=1).

Northwest Region: 1 “Highest Priority” “Highest Priority” community has a

substantially larger African-American female population (CO=1).


Breast cancer is the leading cause of cancer death in Hispanic/Latina women

(American Cancer Society, 2015b). In the U.S., 8.4% of the HP2020 “Highest Priority”

communities (47 of 561 ) have a substantially larger Hispanic/Latina female

population than their respective state as a whole (Appendix H).

South Central Region: 17 “Highest Priority” communities with a substantially

larger Hispanic/Latina population (TX=9; OK=4; AR=2; LA=1; NM=1).

Northwest Region: 11 “Highest Priority” communities with a substantially larger

Hispanic/Latina population (CO=3; ID=3; WA=3; WY=2).

North Central Region: 6 “Highest Priority” communities with a substantially

larger Hispanic/Latina population (MO=2; IA=1; KS=1; ND=1; NE=1).

Southeast Region: 6 “Highest Priority” communities with a substantially larger

Hispanic/Latina population (FL=2; GA=1; MS=1; NC=1; VA=1).

Southwest Region: 3 “Highest Priority” communities with a substantially larger

Hispanic/Latina population (CA=2; AZ=1).

East Central Region: 2 “Highest Priority” communities with a substantially

larger Hispanic/Latina population (IN=1; OH=1).

Northeast Region: 1 “Highest Priority” community has a substantially larger

Hispanic/Latina population (PA=1).

National Capital Region: 1 “Highest Priority” community has a substantially

larger Hispanic/Latina population (VA=1).

Figure 3 shows a map of the HP2020 priority classifications for the

counties/cities/parishes/boroughs in the U.S. When both of the indicators used to

establish a priority for a county/parish/borough are not available, the priority is

shown as “undetermined” on the map. Individual Komen Region maps are located in

Appendix I.

Within Komen Regions there are clusters of two or more “Highest Priority”

communities. There are 37 clusters in the Southeast Region, 21 clusters in the East

Central Region, 20 clusters in the South Central Region, 16 clusters in the North

Central Region, 10 clusters in the Northwest Region, two clusters in the Northeast

Region, no clusters in the National Capital Region or Southwest Region. More

detailed information on these clusters can be located in the respective regional

Community Profile. This may indicate greater needs than a single “Highest Priority”

community bordered by lower priority communities.

Additionally, the clusters below have two or more “Highest Priority” communities

that cross between Komen Regions:

East Central Region & Northeast Region

Ashtabula County (OH), Mahoning County (OH) and Mercer County (PA)

East Central Region & North Central Region


Lake County (IN), Jasper County (IN), Grundy County (IL) and Kankakee

County (IL)

East Central Region & Southeast Region

Wayne County (KY), Claiborne County (TN) and Union County (TN)

Northeast Region & Southeast Region

Calvert County (MD), Charles County (MD), Caroline County (VA) , Orange

County (VA), Spotsylvania County (VA) and Stafford County (VA)

Southeast Region & South Central Region

Concordia Parish (LA), Avoyelles Parish (LA), East Feliciana Parish (LA)Pointe

Coupee Parish (LA), West Baton Rouge Parish (LA), Iberville Parish (LA), Saint

Martin Parish (LA), Lafayette Parish (LA), Iberia Parish (LA) and Adams

County (MS)

Chicot County (AR), Drew County (AR), Bradley County (AR) and Bolivar

County (MS)


Figure 3. United States Healthy People 2020 priority classifications.


Health Systems Analysis

An inventory of breast cancer programs and services in the U.S. was collected by

Komen Headquarters Evaluation and Outcomes team through a comprehensive

internet search (Appendix B) to identify the following types of health care facilities

or community organizations that may provide breast cancer related services:

hospitals, community health centers, free clinics, health departments, Title X

providers, and additional facilities that provide breast cancer services (e.g., non-

medical service providers).

Figure 4 shows that in the U.S., 2.1 percent (12 of 561) HP2020 “Highest Priority”

communities do not have any in-community breast cancer services (e.g., screening,

diagnostics and treatment):

East Central Region

Spencer County, IN (Komen

Evansville Tri-State)

Shelby County, OH (Komen

Northwest Ohio)

National Capital Region

Falls Church City, VA

North Central Region

Warren County, IA (Komen

Iowa)

Fillmore County, MN (Komen

Minnesota)

Southeast Region

Staunton City, VA (Komen

Central Virginia)

Not Currently Served by Komen

Headquarters or an Affiliate

Carroll County, IL

LaGrange County, IN

Leelanau County, MI

Dallas County, MO

Lee County, TX

Morris County, TX

In the U.S., there are 19,358 facilities that provide screening

services (i.e., clinical breast exam, screening mammography

and/or patient navigation into screening services). Of those

facilities that provide screening services, 15.0 percent

(2,908) are located in a “Highest Priority” community.

Figure 4 shows that in the U.S., 25.7 percent (144 of 561)

HP2020 “Highest Priority” communities have access to in-

community breast cancer screening services only.


More detailed screening service information for these communities can be found in

the respective regional Community Profile.

Southeast Region: 65

South Central Region: 32

North Central Region: 21

East Central Region: 19

Northwest Region: 5

Northeast Region: 1

Southwest Region: 1

In the U.S., there are 8,782 facilities that provide diagnostic

services (i.e., diagnostic mammography, ultrasound, biopsy,

magnetic resonance imaging (MRI) scanning and/or patient

navigation into diagnostic services). Of those facilities that

provide diagnostic services, 14.0 percent (1,234) are located

in a “Highest Priority” community.



community screening and diagnostic services, but not

treatment services.

More detailed diagnostic service information for these communities can be found in






Northwest Region: 17

Northeast Region: 4

Southwest Region: 3

In the U.S., there are 3,023 facilities that provide treatment

services (i.e., chemotherapy, radiation, surgery,

reconstruction and/or patient navigation into treatment

services). Of those facilities that provide treatment services,

16.2 percent (491) are located in a “Highest Priority”

community.



community screening, diagnostic and treatment services.


More detailed treatment service information for these communities can be found in





Northwest Region: 28

Northeast Region: 22


Southwest Region: 8

National Capital Region 1

A facility may be classified under more than one classification depending on the

services provided. Appendix J provides the total number of screening, diagnostic

and treatment facilities for the U.S., each state and each Komen Region’s “Highest

Priority” communities.

These numbers, however, do not tell the whole story about the availability of services

for individuals that are residing in a “Highest Priority” community. An individual

residing in a “Highest Priority” community may only have only one or two of the

services available within a short distance from their residence and may have to travel

a greater distance within the community, or to another community, to receive

additional care. A lack of local services increases the likelihood that an individual will

have difficulty accessing initial screening services and follow-up care after an

abnormal screening. This, in turn, may contribute to breast cancer being diagnosed

at a later stage when treatment options are limited, and prognosis is poor, or may

result in delays in treatment after diagnosis, which contribute to poorer outcomes.

No Services

Screening

Services Only

Screening and Diagnostic Services Only

Screening Diagnostic and Treatment Services

12 “Highest Priority” Communities


175“Highest Priority” Communities


Figure 4. Total number of “Highest Priority” communities with services available.


Although these communities may have services, this doesn’t account for quality of

care that may be provided at these facilities. The Institute of Medicine defines quality

of care as “providing patients with appropriate services in a technically competent

manner, with good communication, shared decision-making and cultural sensitivity”

(Hewitt and Simone, 1999). Hospitals and medical centers that provide quality care

tend to have up-to-date facilities and equipment, follow current breast cancer

screening, diagnostic and treatment guidelines, and have doctors with appropriate

credentials and experience in treating breast cancer. Overall, quality of care is about

the process of care, outcomes of care, and patient satisfaction levels from a

particular program and/or organization.

Komen Headquarters Evaluation and Outcomes team collected data on the number

of facilities in the U.S. that were accredited by standard quality programs for breast

cancer care. The specific breast cancer related accreditations considered for this

report include American College of Radiology Breast Imaging Centers of Excellence,

American College of Surgeons Accreditation Program for Breast Centers, American

College of Surgeons Commission on Cancer Certification and the National Cancer

Institute’s designated Cancer Centers.

While screening, diagnostic and treatment services are available through facilities

located in HP2020 ”Highest Priority” communities, the services provided may not

follow recommended guidelines and lack care coordination to diagnostic and

treatment services. This may result in the individual having to coordinate their own

care within a complex health care system. Confusion and frustration of navigating a

complex health care system may lead to individuals forgoing care, not being aware

that additional tests are needed, or taking longer to be diagnosed leading to

potential delays in beginning recommended breast cancer treatment. Additionally,

patients may not be made aware of breast cancer clinical trials that they may be

eligible to participate in, and planning and coordination of care may be “siloed” (e.g.,

each medical provider focused one isolated part of care and not how that care

functions within a larger treatment plan). American College of Radiology Breast Imaging Centers of Excellence (BICOE) http://www.acr.org/Quality-Safety/Accreditation/BICOE

The American College of Radiology (ACR) BICOE designation is awarded to “breast

imaging centers that achieve excellence” in providing effective, safe and quality

breast imaging care to patients (American College of Radiology, n.d.). In order for a

facility to receive designation as a BICOE, the facility must meet quality breast

imaging screening and diagnostic performance measures for mammography,

stereotactic breast biopsy, breast ultrasound and breast MRI.


In the U.S., there are 8,283 facilities that

provide breast cancer screening and

diagnostic services; of those facilities, 1,343

(16.2%) are accredited as an ACR BICOE

facility; 171 of those facilities are located in a

HP2020 “Highest Priority” community.

Individuals that reside in communities that

have accredited screening and diagnostic

facilities have access to services that meet

quality breast imaging performance

measures. However, in the U.S. HP2020

“Highest Priority” communities there are

1,146 facilities located in 97 communities that

are not accredited as an ACR BICOE facility

and the services provided to individuals

seeking care may not meet quality breast

imaging performance measures.

More detailed information on these

communities can be found in the respective

regional Community Profile.

Northeast Region: 380 ACR BICOE

accredited facilities in region; 40

accredited facilities in HP2020 “Highest Priority” communities.

Southeast Region: 271 ACR BICOE accredited facilities in region; 44 facilities in

HP2020 “Highest Priority” communities.

East Central Region: 198 ACR BICOE accredited facilities in region; 44 facilities

in HP2020 “Highest Priority” communities.

North Central: 157 ACR BICOE accredited facilities in region; 16 facilities in


Southwest Region: 138 ACR BICOE accredited facilities in region; 5 facilities in


South Central Region: 93 ACR BICOE accredited facilities in region; 13 facilities


Northwest Region: 87 ACR BICOE accredited facilities in region; 9 facilities in


National Capital Region: 19 ACR BICOE accredited facilities the region; 0

facilities in HP2020 “Highest Priority” communities.


American College of Surgeons National Accreditation Program for Breast Centers (NAPBC) https://www.facs.org/quality-programs/napbc

The American College of Surgeons’ (ACS) NAPBC is focused on improving quality of

care and outcomes for patients with diseases of the breast (American College of

Surgeons, 2014b). The NAPBC utilizes evidence-based standards, patient and

provider education, and encourages leaders from major disciplines to work together

to diagnose and treat breast disease.

In order to be an ACS NAPBC programs, the breast center must demonstrate a

multidisciplinary, integrated and comprehensive model for providing breast care

services and meet high-quality breast cancer care performance measures. NAPBC

facilities must meet performance standards in providing screening, diagnostic and

treatment services, employing medical providers with specialized knowledge and

skills in diseases of the breast, participation in clinical trials, and implementation of

education, support and survivorship programs.


provide breast cancer screening,

diagnostic and treatment services; of those

facilities, 541 (18.5%) are accredited as an

ACS NAPBC facility; 75 of those facilities

are located in a HP2020 “Highest Priority”

community. Individuals that reside in

communities that have NAPBC facilities

have access to services that meet high-

quality breast cancer care performance

measures. However, in the US’ HP2020

“Highest Priority communities there are

406 facilities located in 206 communities

that are not ACS NAPBC accredited and

the services provided to individuals

seeking care may not meet high-quality

breast cancer care performance measures.


communities can be found in the

respective regional Community Profile.

Northeast Region: 137 ACS NAPBC

accredited facilities in region; 18 facilities in HP2020 “Highest Priority”

communities.

541facilities in

United States

75 facilities in

"Highest Priority" communities


Southeast Region: 110 ACS NAPBC accredited facilities in region; 21 facilities in


North Central: 93 ACS NAPBC accredited facilities in region; 6 facilities in


East Central Region: 73 ACS NAPBC accredited facilities in region; 13 facilities


South Central Region: 38 ACS NAPBC accredited facilities in region; 7 facilities


Southwest Region: 38 ACS NAPBC accredited facilities in region; 2 facilities in


Northwest Region: 37 ACS NAPBC accredited facilities in region; 6 facilities in


National Capital Region: 15 ACS NAPBC accredited facilities in region; 2


American College of Surgeons Commission on Cancer (CoC)

https://www.facs.org/quality-programs/cancer/coc

The American College of Surgeons (ACS) CoC “recognizes cancer care programs for

their commitment to providing comprehensive, high-quality and multidisciplinary

patient centered care” (American College of Surgeons, 2014a).

Throughout the cancer continuum of care, accredited programs are at the forefront

of improving survival and quality of life for those diagnosed with cancer by setting

care standards, research, prevention, education and monitoring to ensure

comprehensive quality care is being provided (American College of Surgeons,

2014a).

The benefits of having an ACS CoC accredited facility in the local community include

(American College of Surgeons, 2014a):

Dedicated resources to ensure quality treatment and supportive care services

are provided

Community-based cancer prevention and screening events

Guarantee that patients have access to treatment recommended by Health

and Medicine Division (formerly the Institute of Medicine), National Cancer

Comprehensive Network and American Society of Clinical Oncology

Patients’ care is coordinated through a multidisciplinary oncology team

Patients are informed about clinical trials

Patients are provided a standard of care verified by a national organization

Patients have access to quality cancer care that is close to home



provide breast cancer treatment services;

of those facilities, 1,422 (47.0%) are

accredited as an ACS CoC facility; 230 of

those facilities are located in a HP2020

“Highest Priority” community. Individuals

that reside in communities with ACS CoC

accredited facilities have access to

comprehensive, quality breast cancer

treatment close to home. However, in the

US’ HP2020 “Highest Priority”

communities, there are 262 facilities

located in 144 communities that are not

ACS CoC accredited and the service

provided to individual seeking care may

not meet ACS cancer care standards.


communities can be found in the

respective regional Community Profile.

Northeast Region: 331 ACS CoC

accredited facilities in region; 43


Southeast Region: 266 ACS CoC accredited facilities in region; 52 facilities in


North Central: 215 ACS CoC accredited facilities in region; 30 facilities in


East Central Region: 207 ACS CoC accredited facilities in region; 41 facilities in


South Central Region: 147 ACS CoC accredited facilities in region; 30 facilities


Southwest Region: 129 ACS CoC accredited facilities in region; 15 facilities in


Northwest Region: 104 ACS CoC accredited facilities in region; 17 facilities in


National Capital Region: 23 ACS CoC accredited facilities in region; 2 facilities


1,422facilities in United

States

230facilities in



National Cancer Institute-Designated Cancer Centers http://www.cancer.gov/research/nci-role/cancer-centers

A National Cancer Institute (NCI)- designated Cancer Center is an institution

dedicated to researching the development of more effective approaches to the

prevention, diagnosis, and treatment of cancer (National Cancer Institute, 2012). A

NCI-designated Cancer Center conducts cancer research that is multidisciplinary and

incorporates collaboration between institutions and university medical centers. This

collaboration also provides training for scientists, physicians, and other professionals

interested in specialized training or board certification in cancer-related disciplines.

NCI-designated Cancer Centers also provide clinical programs that offer the most

current forms of treatment for various types of cancer and typically incorporate

access to clinical trials of experimental treatments.

There are 69 NCI-designated Cancer

Centers in the US; seven of these centers

are located in HP2020 “Highest Priority”

communities:

Northeast Region: 19 NCI-

designated Cancer Centers in

region; 3 facilities in one HP2020

“Highest Priority” community

(Philadelphia County, PA).

Southwest Region: 12 NCI-


region; 1 facility in a HP2020


(Honolulu County, HI).

Southeast Region: 11 NCI-


region; 1 facility in a HP2020


(Jefferson County, AL).

North Central: 10 NCI-designated

Cancer Centers in region; 1 facility

in a HP2020 “Highest Priority”

community (Wyandotte County, KS).

East Central Region: 8 NCI-designated Cancer Centers in region; 1 facility in a

HP2020 “Highest Priority” community (Wayne County, MI).

South Central Region: 5 NCI-designated Cancer Centers in region; no facilities

in any of the HP2020 “Highest Priority” communities.

69facilities in United

States

7facilities in



Northwest Region: 3 NCI-designated Cancer Centers in region; no facilities in

any of the HP2020 “Highest Priority” communities.

National Capital Region: 1 NCI-designated Cancer Center in region; no facilities

in any of the HP2020 “Highest Priority” communities.

In conclusion, while the above-mentioned breast cancer accredited services may be

available within these communities, the number of available facilities may be too few

to service the population in need, facilities may not accept an individual’s health

insurance plan, individuals can become “lost in the system” after an abnormal

screening mammogram and/or the care received does not meet any quality-based

standards. In the U.S., there are 431 HP2020 “Highest Priority” communities that do

not have any of the above mentioned quality-based, accredited breast cancer

services. More detailed information regarding each region’s health system analysis

can be located in the regional Community Profiles.

Qualitative Data Analysis

In order to gain a better understanding of the key barriers to breast cancer care in

the local communities, Komen Headquarters Evaluation and Outcomes team

analyzed qualitative data collected within each region. This analysis includes the

review of qualitative data reports for all regions in the U.S. and the coding of central

themes that were cited most frequently by survey, interview and focus group

participants and published qualitative documents (Figure 5).

During 2014-2015, Affiliates conducted

qualitative data collection in communities of

interest (e.g., HP2020 “Highest Priority”

communities and/or non-“Highest Priority”

communities) within their service area to

“hear” from local health care providers and/or

community members the challenges local

residents have in accessing breast cancer care;

as well as potential solutions that may assist

individuals in receiving physician

recommended breast cancer screening,

diagnostic and treatment services.

Qualitative data collection was conducted in

325 of 393 (82.7%) communities of interest in

the Komen Affiliate Regions and National

Capital Region. Of those 325 Affiliate communities of interest, 227 (69.8%) were

HP2020 “Highest Priority” communities. Only qualitative data from the 227

communities were analyzed for this report. The common barriers to breast cancer

7,514

3,013

Surveys Focus Groups

2,374

157

Interviews

Document Reviews

Figure 5. United States qualitative data collection methods and number of participants/documents.


care identified were cited by interview, focus groups and survey participants with

varying demographics and socioeconomic factors and in published qualitative

literature in each Affiliate’s qualitative data report;

but may not have been a barrier in each community

of interest. Therefore, the qualitative data collected

may not be representative of the specific HP2020

“Highest Priority” communities, but only the

perspective of those that participated in the

qualitative data collection process.

Community members who provided feedback during the qualitative data collection

process along with the review of the documents frequently cited barriers that may

prevent an individual from getting breast cancer services in the U.S. and in each

Komen Region are:

Availability of Local Services – Lack of health services in community,

limited number of health professionals in community.

Breast Cancer Education – Lack of awareness of available services, lack of

understanding of screening guidelines and confusion of screening

guidelines.

Cultural/Language – Lack of interpreter services, education materials that

are not translated, lack of physicians who resemble patient’s culture, lack

of programs that are culturally appropriate.

Fear – Pain and discomfort during screening, diagnosis and treatment,

legal or immigration status concerns if treatment is obtained, denial of

diagnosis, afraid of breast cancer stigma.

Financial Barriers- Lack of funds

necessary to pay for the breast cancer

services throughout the continuum of

care.

Insurance Barriers- Lack of insurance, lack

of adequate insurance coverage

(underinsured).

Transportation Barriers- Lack of available

personal transportation, inadequate public transportation and distance to

services, availability of ride-share opportunities.

"Women don't know who to believe when it comes to changing health care conceptions, which leads to a lot of confusion as to what women should do."

-Key informant

“It was devastating financially. Even though we were in a good place and we had insurance, insurance only pays for so much. And then there were out-of-pocket expenses.”

- Survivor

“We don’t have much locally for treatment either, you have to drive and that gets expensive. Between the cost of gas and food on those days and missing work, it adds up quickly. I know I thought ‘why should I find out and worry, I can’t afford to do anything about it.” - Key informant


These are the most frequently cited barriers to receiving breast care as identified by

Affiliate and National Capital Region qualitative data participants from communities of

interest. To better understand the Affiliate themes and barriers across Komen Regions.

The most frequently cited barriers to care were ranked below in Table 3.

Table 3. Ranking of the most frequently cited barriers to care by qualitative data

participants in Komen Regions (1=Highest, 5= Lowest).

Note: Data provided for the National Capital Region themes did not include frequency or rankings but did include all barriers

mentioned above.

Other barriers that were less frequently mentioned by community members were

lack of social support, quality of care concerns and other health conditions that take

precedence (e.g., diabetes, asthma and weight management). In addition,

community members indicated that Black/African-Americans, Hispanics/Latinas,

medically-underserved populations, linguistically isolated populations, women who

partner with women, and rural populations may experience greater barriers to care

than others.

CONCLUSIONS

Healthy People 2020 breast cancer targets were used as the benchmark for all

communities in the U.S. Communities that are predicted not to meet the benchmarks

by 2020 are classified as “Highest Priority” since these communities are of greater

need for breast cancer interventions than other areas. Within the U.S., there are 561

communities that are considered “Highest Priority”. Of the 561 “Highest Priority”

communities, 151 communities are not in a local Komen Affiliate service area.

Southeast Region: 184 “Highest Priority” communities; 58 are not served by a

Komen Affiliate.

North Central Region: 97 “Highest Priority” communities; 31 are not served by

a Komen Affiliate.

Barriers

Komen Regions East

Central North

Central Northeast NorthwestSouth

Central Southeast SouthwestAvailability of Local Services

4 2 2 1 5 4 4

Breast Cancer Education

2 3 5 2 1 2 2

Cultural/Language - 5 - 4 - - 5Fear 5 5 1 - - -Financial Barriers 3 1 - 3 3 1 1Insurance Barriers - - 3 5 4 5 -Transportation Barriers

1 4 4 - 2 3 3


East Central Region: 95 “Highest Priority” communities; 24 are not served by

a Komen Affiliate.

South Central Region: 94 “Highest Priority” communities; 29 are not served by

a Komen Affiliate.

Northwest Region: 50 “Highest Priority” communities; 7 are not served by a

Komen Affiliate.

Northeast Region= 27 “Highest Priority” communities; all are served by a

Komen Affiliate.

Southwest Region: 12 “Highest Priority” communities; 2 are not served by a

Komen Affiliate.

National Capital Region: 2 “Highest Priority” communities served by Komen

Headquarters.

Even though the 561 “Highest Priority” communities are located across the U.S., there

are demographic and socioeconomic commonalities between the communities that

suggest that they may share similar barriers to accessing care that could be

addressed through the implementation of evidence-based and/or best practice

interventions. Quantitative data showed that these “Highest Priority” communities

are largely rural, medically underserved, and do not have access to high quality

services (or any services in some cases). These observations are supported by the

qualitative data since some of the highest cited barriers were availability of local

services, and transportation barriers.

Despite the fact that, within the 561 HP2020 “Highest Priority” communities in the

U.S., there are 2,908 screening facilities, 1,234 diagnostic and 491 treatment facilities,

12 (2.1%) of the HP2020 “Highest Priority” communities do not have access to any

breast cancer services (i.e., screening, diagnostic, treatment) within their community.

In addition, 144 (25.7%) HP2020 “Highest Priority” communities have access only to

in-community breast cancer screening services; 175 (31.2%) have access to screening

and diagnostic services; and 228 (40.6%) have access to screening, diagnostic and

treatment services.

Furthermore, in the U.S., only 12.7 percent (171 of 1,343) of ACR BICOE-accredited

facilities are located in a HP2020 “Highest Priority” community; 13.9 percent (75 of

541) of ACS NAPBC-accredited facilities are located in a HP2020 “Highest Priority”

community; 16.2 percent (230 of 1,422) of ACS CoC-accredited facilities are located

in a HP2020 “Highest Priority” community; and 10.1 percent (7 of 69) of the NCI-

designated cancer centers are in HP2020 “Highest Priority” Regions, which are the

highest areas of need for breast cancer and other HP2020 objectives.

While services may be available within the communities listed, the number of

available facilities may be too few to service the population in need, facilities may not


accept an individual’s health insurance plan, individuals can become “lost in the

system” after an abnormal screening mammogram and/or the care received does not

meet any quality-based standards. In the U.S., there are 431 HP2020 “Highest

Priority” communities that do not have any of the listed quality-based, accredited

breast cancer services. The communities that do not have facilities accredited by the

American College of Radiology, American College of Surgeons or the National

Cancer Institute tend to be rural and classified as medically underserved by the U.S.

Department of Health and Human Services.

As noted above, the majority of the HP2020 “Highest Priority” communities were

rural and/or medically underserved. In the U.S., 76.3 percent (428 of 561) of the

HP2020 “Highest Priority” communities have substantially higher percentage of

individuals residing in rural areas. The highest concentration of HP2020 “Highest

Priority” rural communities are in the Southeast Region (146 communities) and the

East Central Region (76 communities). In the U.S., 52.8 percent (296 of 561) of the

HP2020 “Highest Priority” communities have substantially higher percentage of

individuals residing in medically underserved areas, meaning that there too few

primary care providers to serve the area residents, a high percentage of residents

with incomes below the poverty level and/or a high percentage of the population

being over the age of 65. The highest concentration of HP2020 “Highest Priority”

medically underserved communities are in the Southeast Region (133 communities)

and South Central Region (65 communities). The Southeast Region had the highest

number of HP2020 “Highest Priority” communities in both the rural and medically

underserved categories. These factors have been linked to barriers associated with

accessing quality and timely care. Collaboration among Komen Affiliates that have a

higher percentage of individuals residing in rural and medically underserved areas

would allow sharing of best practices on what has worked and what has not worked

in reaching rural and medically underserved populations and addressing the barriers

they have in accessing care.

From interviews, surveys, focus groups and document reviews conducted in the

“Highest Priority” communities, individuals that reside in or provide services to

residents of these communities indicated that availability of services, lack of breast

cancer education, financial barriers, transportation, cultural/language barriers, lack of

insurance and fear were all barriers that prevent individuals from receiving or seeking

breast cancer care.

Additional population characteristics that may be factors towards having poorer

breast cancer outcomes can be found in Appendix D and in the HP2020 Targets

Section above. Some of these population characteristics are listed below. For

example, Black/African-American women are often diagnosed with late-stage breast

cancer when treatment options are limited, and the prognosis is poor. Black/African-


American women also have a 39 percent higher breast cancer death rate than white

women (Howlader et al., 2016). In the U.S., 18.0 percent (101 of 561) of the HP2020

“Highest Priority” communities have a substantially larger Black/African-American

female population than their respective state as a whole. The highest concentration

of HP2020 “Highest Priority” communities that have a substantially larger

Black/African-American female population are in the Southeast Region (65

communities) and South Central Region (22 communities). It should be considered

that these communities in the Southeast Region also have the highest number or

rural and medically underserved populations, as noted above.

Breast cancer is the leading cause of cancer death in Hispanic/Latina women

(American Cancer Society, 2015b). In the U.S., 8.4 percent (47 of 561) of the HP2020

“Highest Priority” communities have a substantially larger Hispanic/Latina female

population than their respective state as a whole. The highest concentration of

HP2020 “Highest Priority” communities that have a sustainably larger

Hispanic/Latina population are in the South Central Region (17 communities) and

Northwest Region (11 communities). The South Central Region also was listed as

having a large number of medically underserved communities.

To address the identified barriers in accessing quality breast cancer care, Komen

Headquarters and Affiliates have identified priorities within their local service area

that share commonalities. These are the most common priorities taken from Mission

Action Plans that Komen Headquarters and Affiliates intend to focus on to reduce

breast cancer late-stage diagnosis and deaths over the next five years:

Support programs that reduce or eliminate barriers that have been identified

as interfering with an individual being able to access breast cancer screening,

diagnostic and treatment services. Client-oriented programs to reduce barriers

include, but are not limited to, free or low-cost breast cancer services,

transportation assistance, mobile mammography, extended clinic

hours/locations and interpreter services.

Develop community and organizational partnerships to address concerns

raised by community members regarding lack of breast cancer education, lack

of available services and language and cultural barriers.

Provide and/or support breast cancer education programs in local

communities that provide accurate, evidence-based information.

Support patient navigation programs.

The majority of the “Highest Priority” communities include Rural and Medically-

underserved communities. These priorities will work towards the barriers that were

cited by Qualitative data participants and for the majority of the communities that

are rural and medically-underserved. The client-oriented programs, education and

organizational partnerships will reduce barriers to access to services by providing


services to the medically-underserved communities. Patient navigation will provide

assistance to those persons who are seeking services in the “Highest Priority”

communities that may not have resources available.

Komen Headquarters and Affiliates also identified that Black/African-American

women, Hispanic/Latina women, medically underserved populations, linguistically

isolated populations, women who partner with women, and rural populations may

experience greater challenges in overcoming barriers to care. Komen Headquarters

and Affiliates intend to focus efforts to reduce the breast cancer disparities that

these individuals may be experiencing.

In conclusion, community members who participated in focus groups, interviews and

surveys from the HP2020 “Highest Priority” communities most frequently identified

financial barriers, lack of appropriate breast cancer education, cultural/language

barriers, fear, transportation, lack of insurance and lack of available breast cancer

services as the barriers to receiving care. As noted in Table 3 in three Komen

Regions, Southeast, Southwest and North Central, financial barriers were cited most

frequently as a barrier to receiving care. Whereas, availability of breast cancer

services was the most cited barrier in the Northwest Region and lack of breast

cancer education was the most cited barrier in the South Central Region. Finally,

transportation barriers were the most frequently cited barrier to receiving care in the

East Central Region were also highlighted in Table 3.

Komen is a local breast cancer resource for “Highest Priority” communities within

each service area. Komen can assist with addressing the identified barriers to care,

convening stakeholders to develop solutions to increase access of available breast

cancer services, and provide “real-time” assistance to areas of greatest need through

funding of local community grants. Collaboration across service areas and state

borders provide an opportunity for Komen to share resources and best-practices,

provide consistent messaging and address similar barriers to care, all in an effort to

reduce the number of breast cancer deaths in the U.S. by 50.0 percent by 2026.


REFERENCES

Adler, N. and Rehkopf, D. 2008. U.S. disparities in health: descriptions, causes, and

mechanisms. Annu Rev Public Health, 29, 235-52.

American Cancer Society. 2015a. Breast cancer facts and figures, 2015-2016. Atlanta,

GA: American Cancer Society .

American Cancer Society. 2015b. Cancer facts and figures for Hispanics/Latinos,

2015-2017. Atlanta, GA: American Cancer Society.

American Cancer Society. 2015c. Cancer prevention & early detection facts & figures,

2015-2016. Atlanta, GA: American Cancer Society.

American Cancer Society. 2016. Cancer facts and figures, 2016. Atlanta, GA:

American Cancer Society.

American College of Radiology. n.d. Mammography accreditation. Accessed on

07/11/2014 from

http://www.acraccreditation.org/~/media/ACRAccreditation/Documents/Mammogr

aphy/Requirements.pdf?la=en

American College of Surgeons. 2014a. Commission on Cancer. Accessed on

7/11/2014 at https://www.facs.org/quality-programs/cancer/coc.

American College of Surgeons. 2014b. National accreditation program from breast

centers. Accessed on 07/11/2014 from http://napbc-breast.org/.

Braveman, E.A. 2010. Health disparities and health equity. Am J Public Health, 101(Suppl 1), S149-S155.

Danforth, D.N., Jr. 2013. Disparities in breast cancer outcomes between Caucasian

and African-American women: A model for describing the relationship of biological

and nonbiological factors. Breast Cancer Research, 15, 208.

Hewitt, M. and Simone, J.V. (eds). 1999. Ensuring quality cancer care. Washington,

DC: Institute of Medicine and Commission on Life Sciences.

Howlader, N., Noone, A.M., Krapcho, M., et al. (eds). 2016. SEER cancer statistics

Review, 1975-2013: Fast stats. Bethesda, MD: National Cancer Institute. Accessed

from http://seer.cancer.gov/csr/1975_2013/.


Lurie, N. and Dubowitz, T. 2007. Health disparities and access to health. JAMA, 297(10), 1118-1121.

National Cancer Institute. NCI-Designated cancer centers, 2012. Accessed on

07/11/2014 from

http://www.cancer.gov/researchandfunding/extramural/cancercenters/about.

Robert Wood Johnson Foundation. Overcoming Obstacles to Health. Commission to

Build a Healthier America, 2008. Available from

http://www.rwjf.org/content/dam/farm/reports/reports/2008/rwjf22441.

US Preventive Services Task Force. 2016. Final update summary: Breast cancer

screening. Accessed from

http://www.uspreventiveservicestaskforce.org/Page/Document/UpdateSummaryFin

al/breast-cancer-screening.

White, A., Richardson, L.C., Li, C., Ekwueme, D.U., and Kaur, J.S. 2014. Breast cancer

mortality among American Indian and Alaska Native women, 1990-2009. Am J Public Health. 104 (Suppl 3), S432-8.

Young, J.L. Jr., Roffers, S.D., Ries, L.A.G., Fritz, A.G., and Hurlbut, A.A. (eds). 2001.

SEER summary staging manual - 2000: Codes and coding instructions, Pub. No. 01-

4969, Bethesda, MD: National Cancer Institute. Accessed from

http://seer.cancer.gov/tools/ssm/.


APPENDICES

Appendix A. Komen Affiliates in each Region (as of August 2016)

Komen Northeast Region

Komen Central and South Jersey

Komen Central New York

Komen Greater New York City

Komen Maine

Komen Maryland

Komen Northeastern New York

Komen Northeastern Pennsylvania

Komen North Jersey

Komen Philadelphia

Komen Pittsburgh

Komen Southern New England

Komen Twin Tiers Region

Komen Vermont- New Hampshire

Komen Western New York

Komen Southeast Region

Komen Central Florida

Komen Central Georgia

Komen Central Mississippi Steel Magnolias

Komen Central Tennessee

Komen Central Virginia

Komen Charlotte

Komen Chattanooga

Komen Coastal Georgia

Komen Florida Suncoast

Komen Greater Atlanta

Komen Knoxville

Komen Lowcountry

Komen Memphis-MidSouth

Komen Miami/Ft. Lauderdale

Komen North Carolina Triangle to the Coast

Komen North Central Alabama

Komen North Florida

Komen North Mississippi

Komen Northwest North Carolina

Komen South Carolina Mountains to Midlands

Komen South Florida

Komen Southwest Florida


Komen Tidewater

Komen Northwest NC

Komen Virginia Blue Ridge

Komen East Central Region

Komen Central Indiana

Komen Columbus

Komen Evansville Tri-State

Komen Kentucky

Komen Michigan

Komen Northeast Ohio

Komen Northwest Ohio

Komen Southwest Ohio

Komen West Virginia

Komen North Central Region

Komen Central Wisconsin

Komen Chicagoland Area

Komen Greater Kansas City

Komen Iowa

Komen Kansas

Komen Memorial

Komen Minnesota

Komen Missouri

Komen Nebraska

Komen Quad Cities

Komen Siouxland

Komen South Central Wisconsin

Komen South Dakota

Komen Southeast Wisconsin

Komen South Central Region

Komen Acadiana

Komen Arkansas

Komen Austin

Komen Baton Rouge

Komen Bayou Region

Komen Central and Western Oklahoma

Komen Dallas County

Komen East Central Texas

Komen El Paso

Komen Greater Amarillo


Komen Greater Fort Worth

Komen Houston

Komen Lubbock Area

Komen New Orleans

Komen North Louisiana

Komen North Texas

Komen Ozark

Komen San Antonio

Komen Texarkana

Komen Tulsa

Komen Northwest Region

Komen Colorado

Komen Colorado South

Komen Eastern Washington

Komen Idaho Montana

Komen Oregon and Southwest

Washington

Komen Puget Sound

Komen Utah

Komen Wyoming

Komen Southwest Region

Komen Arizona

Komen Central Valley

Komen Hawaii

Komen Inland Empire

Komen Los Angeles

Komen Nevada

Komen Orange County

Komen Sacramento Valley

Komen San Diego

Komen San Francisco


Appendix B. Health System Analysis Internet Search

The Evaluations and Outcomes team developed a tracking template for the Health

Systems Analysis section to capture resources in target communities. The following

sites were used to capture data.

Community Health Centers (CHC’s) http://nachc.org/about-our-health-

centers/find-a-health-center/

The team used the “Download Health Centers and Look-Alikes Report by State

(PDF). Select the state you are working on and click “Generate Report”. Behavioral,

Dental, Teen, Children’s, Shelters, Nursing homes, Jails, Schools and Administrative

facilities were not be included in the information collected.

Title X http://www.hhs.gov/opa/title-x-family-planning/initiatives-and-

resources/title-x-grantees-list/

The team used the facilities in the Title X list on the page. If the facility found

matches the name and address information from CHC, the team retained the CHC.

Behavioral, Dental, Teen and Children’s facilities should not be included in the

information collected. The records are all listed by states that are applicable.

Mammography Centers

http://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfMQSA/mqsa.cfm

This site provides a listing by zip code or state, of all mammography facilities

certified by the FDA or Certifying State as meeting baseline quality standards for

equipment, personnel and practices under the Mammography Quality Standards Act

of 1992 (MQSA) and subsequent Mammography Quality Standards Reauthorization

Act (MQSRA) amendments. To legally perform mammography, a facility must be

FDA certified. This list of Food and Drug Administration (FDA) Certified

Mammography Facilities is updated weekly according to the website. The team

searched by state and list accordingly.

Hospitals https://data.medicare.gov/Hospital-Compare/Hospital-General-

Information/v287-28n3

This site is a list of all hospitals that have been registered with Medicare. The team

did not include psychiatric and children’s hospitals. The team verified what services

are offered across the Continuum of Care by visiting the hospital’s website.


Appendix C. Qualitative Data Themes

Availability of Services – Lack of health services in community, limited number of

health professionals in community

Awareness/Education – Lack of awareness of available services, lack of awareness

of screening guidelines and confusion of screening guidelines

Cultural/Language – Lack of interpreter services, education materials that are not

translated, lack of physicians who resemble patient’s culture, lack of programs that

are culturally appropriate

Fear –Pain and discomfort during screening, diagnosis and treatment, legal or

immigration status concerns if treatment is obtained, denial of diagnosis, afraid of

breast cancer stigma

Financial Barriers- Lack of funds necessary to pay for the breast cancer services

during the continuum of care

Insurance Lack of insurance, lack of adequate insurance coverage (underinsured)

Lack of Awareness of Resources - Lack of awareness of available resources that

may or may not be free or reduced cost including screening, diagnostic, treatment

and support services as well as Komen Affiliate activities

Lack of Childcare/Adult Care – Lack of assistance to watch or take care of children

or other adult family members during appointment

Lack of Social Support -Lack of counseling, family support, difficulty shopping,

cooking and caring for family, lack of emotional support or psychological services

Navigation – Lack of direction by health system, lack of appointment verification or

scheduling, lack of connectivity through continuum of care

No Symptoms – Patients feels/has no symptoms or health concerns so feels there is

no need to be screened or treated

Other Health Priorities – Health concerns that are immediate including weight

management, asthma, diabetes etc.

Pride/Modesty – Lack of female physicians in community and unwillingness to be

seen by male physician, unwillingness to accept cancer diagnosis, unwillingness to

ask for help

Quality of Care – Lack of accredited health services in community, patients distrust

in the health system due to experiences, lack of provider education and expertise,

lack of facility technology, poor provider-patient interaction


Religious Perspectives – Fatalistic attitudes, belief that God will take care of it, delay

of treatment due to religious beliefs

Transportation – Lack of personal transportation available, inadequate public

transportation, access to public transportation, distance to services, availability of

ride-share opportunities, and public transportation limited hours.

Time –Amount of time it takes for screening, diagnosis and appointments, lack of

time off work, school or away from family, work conflicts.


Appendix D. Healthy People 2020 “Highest Priority” communities in the United States

The red boxes indicate that the current rate or trend for the specific county indicated will not reach the target set for

HP2020 late-stage rate or death rate.

State Community Komen Region

Late-Stage Diagnosis Rate per 100,000

(trend) Death Rate per 100,000 (trend) Key Population Characteristics

Healthy People 2020 Target 41.0* 20.6*

United States (states with available data) 43.7 (-1.2%) 22.6 (-1.9%)

Alabama Barbour County Southeast 71.3 (+2.2%) 32.1 (+1.1%)%Black/African-American, education, poverty, employment, rural

Alabama Butler County Southeast 52.5 (+7.6%) SN%Black/African-American, education, poverty, rural, medically underserved

Alabama Geneva County Southeast 45.4 (+0.4%) 21.2 (+0.4%)Education, rural, medically underserved

Alabama Greene County Southeast 65.3 (+22.9%) SN%Black/African-American, education, poverty, employment, rural, medically underserved

Alabama Hale County Southeast 62.3 (+0.6%) 33.6 (NA)%Black/African-American, education, poverty, employment, rural, medically underserved

Alabama Jefferson County Southeast 55.7 (-1.0%) 27.2 (-1.2%) %Black/African-American

Alabama Lamar County Southeast 92.7 (+11.4%) 42.4 (NA)Older, education, rural, medically underserved

Alabama Lawrence County Southeast 40.4 (+13.0%)** SN %AIAN, rural, medically underserved

Alabama Madison County Southeast 41.7 (+7.8%) 25.6 (-0.8%)

Alabama Marengo County Southeast 49.9 (+9.6%) 24.7 (0.0%)%Black/African-American, rural, medically underserved

Alabama Marion County Southeast 55.7 (+1.2%) 26.3 (+2.2%)Older, education, rural, medically underserved

Alabama Montgomery County Southeast 48.3 (+1.1%) 26.3 (-1.8%) %Black/African-American

Alabama Perry County Southeast 48.3 (+4.1%) SN%Black/African-American, education, poverty, employment, rural, medically underserved

Alabama Pike County Southeast 30.6 (+39.4%)** 24.0 (-1.1%)%Black/African-American, poverty, rural

Alabama Randolph County Southeast 34.7 (+3.9%)** 22.5 (NA)Education, poverty, rural, medically underserved

Alabama Tallapoosa County Southeast 41.8 (+19.1%) 15.0 (NA) Rural, medically underserved

Alabama Walker County Southeast 46.8 (+4.7%) 23.7 (-0.8%) Education, employment, rural





Alabama Winston County Southeast 55.2 (+2.1%) 28.7 (1.2%)Education, rural, medically underserved

Alaska Anchorage Municipality Northwest 48.0 (+2.4%) 24.7 (-1.0%) %API

Alaska Kenai Peninsula Borough

Northwest 38.1 (+20.8%)** 29.7 (-1.2%) Rural

Alaska Matanuska-Susitna Borough

Northwest 52.6 (+0.7%) 30.7 (-1.0%) Rural

Arizona Graham County Southwest 44.2 (+8.2%) 31.8 (+1.4%) %AIAN, poverty, rural

Arizona Santa Cruz County Southwest 22.6 (+7.8%)** 22.2 (NA)%Hispanic/Latina, education, poverty, employment, foreign, language, rural, insurance, medically underserved

Arkansas Arkansas County South Central 67.4 (+5.7%) 24.1 (NA)%Black/African-American, medically underserved

Arkansas Boone County South Central 42.2 (+11.3%) 24.2 (-.05%) Rural

Arkansas Bradley County South Central 59.9 (+18.6%) SN%Black/African-American, %Hispanic/Latina, education, poverty, rural, medically underserved

Arkansas Chicot County South Central 52.3 (+25.7%) SN%Black/African-American, older, education, poverty, rural, medically underserved

Arkansas Cleburne County South Central 36.5 (+9.0%)** 23.6 (+2.0%) Older, rural, medically underserved

Arkansas Columbia County South Central 55.7 (+5.3%) 31.0 (+2.0%)%Black/African-American, rural, medically underserved

Arkansas Craighead County South Central 41.5 (+2.9%) 25.1 (+0.5%)

Arkansas Drew County South Central 32.2 (+9.1%)** 34.0 (NA)%Black/African-American, employment, medically underserved

Arkansas Garland County South Central 42.8 (+8.6%) 25.1 (-1.6%) Older

Arkansas Izard County South Central 45.1 (+22.7%) 32.7 (NA) Older, rural, medically underserved

Arkansas Johnson County South Central 35.4 (+19.9%)** SN%Hispanic/Latino, education, rural, medically underserved

Arkansas Lawrence County South Central 47.0 (+1.9%) 35.6 (NA)Education, rural, medically underserved

Arkansas Marion County South Central 49.7 (+10.0%) SN Older, rural, medically underserved

Arkansas Miller County South Central 32.8 (+4.5%)** 23.9 (+5.4%)%Black/African-American, medically underserved

Arkansas Nevada County South Central 55.2 (+6.9%) SN%Black/African-American, education, employment, rural, medically underserved





Arkansas Polk County South Central 36.5 (+3.3%)** SNOlder, rural, insurance, medically underserved

Arkansas Randolph County South Central 48.7 (+6.2%) 30.3 (NA) Rural, medically underserved

Arkansas Sharp County South Central 58.8 (+22.2%) SNOlder, poverty, rural, medically underserved

Arkansas St. Francis County South Central 47.6 (+9.4%) 30.8 (-2.2%)%Black/African-American, education, poverty, employment, rural, medically underserved

California Amador County Southwest 40.6 (+8.9%)** 22.8 (+0.5%)Older, employment, rural, medically underserved

California Colusa County Southwest 33.7 (+32.9%)** SN%Hispanic/Latina, education, employment, language, rural

California Humboldt County Southwest 38.8 (+2.9%)** 26.8 (-1.1%) %AIAN, rural, medically underserved

California Mariposa County Southwest 40.9 (+23.4%)** SNOlder, employment, rural, medically underserved

California San Bernardino County Southwest 42.6 (+1.7%) 25.1 (-1.2%) %Hispanic/Latina

California Yuba County Southwest 45.3 (+0.3%) 22.5 (-0.4%) Poverty, employment, rural

Colorado Adams County Northwest 41.3 (+10.4%) 17.3 (NA)%Hispanic/Latina, education, foreign, language

Colorado Broomfield County Northwest 42.4 (+4.8%) 24.7 (NA) %API

Colorado Denver County Northwest 46.6 (+5.2%) 21.2 (+4.4%)%Black/African-American, %Hispanic/Latina, poverty, foreign, language, medically underserved

Colorado Fremont County Northwest 42.6 (+0.3%) 26.4 (-1.1%)Older, education, rural, medically underserved

Colorado Grand County Northwest 40.5 (+4.1%)** SN Rural

Colorado Montezuma County Northwest 33.3 (+3.5%)** SN %AIAN, older, rural, insurance

Colorado Otero County Northwest 29.9 (+6.6%)** SN%Hispanic/Latina, older, education, poverty, employment, rural

Colorado Teller County Northwest 54.3 (+12.5%) 24.9 (NA) Rural

Delaware Kent County Northeast 45.4 (+3.0%) 27.7 (-1.7%) Rural

Florida Baker County Southeast 34.4 (+43.9%)** SNEducation, rural, medically underserved

Florida Citrus County Southeast 46.1 (+8.9%) 23.9 (-1.1%) Older, employment, rural





Florida DeSoto County Southeast 37.3 (+17.4%)** 25.3 (NA)Education, poverty, language, rural, insurance

Florida Dixie County Southeast 41.9 (+13.4%) SNEducation, rural, medically underserved

Florida Duval County Southeast 51.0 (-0.2%) 27.4 (-1.0%) %Black/African-American

Florida Gulf County Southeast 37.3 (+27.1%)** SN Education, rural

Florida Hardee County Southeast 30.4 (+55.7%)** SN%Hispanic/Latina, education, poverty, language, rural, insurance, medically underserved

Florida Okeechobee County Southeast 51.0 (+9.6%) 23.1 (+1.0%) Education, poverty, rural

Florida Osceola County Southeast 42.0 (+2.9%) 24.1 (-0.6%)%Hispanic/Latina, language, medically underserved

Florida Union County Southeast 65.5 (+10.1%) SNEducation, rural, medically underserved

Florida Wakulla County Southeast 39.4 (+6.2%)** SN Rural, medically underserved

Florida Washington County Southeast 29.2 (+16.5%)** 21.2 (NA)Education, poverty, rural, medically underserved

Georgia Appling County Southeast 59.5 (+67.3%) 28.4 (NA)Education, poverty, rural, medically underserved

Georgia Berrien County Southeast 47.0 (+8.2%) SNEducation, poverty, rural, medically underserved

Georgia Brooks County Southeast 42.5 (+6.2%) SN Older, rural

Georgia Bryan County Southeast 55.1 (+10.7%) 26.4 (NA) Rural, medically underserved

Georgia Butts County Southeast 49.4(-0.3%) 29.1 (NA)Education, rural, medically underserved

Georgia Clayton County Southeast 46.1 (+3.0%) 26.9 (+0.9%)%Black/African-American, employment, foreign

Georgia Colquitt County Southeast 42.4 (+5.0%) 16.3 (NA)%Hispanic/Latina, education, poverty, rural, insurance, medically underserved

Georgia Cook County Southeast 61.0 (+9.0%) 35.9 (+1.3%)Education, poverty, rural, medically underserved

Georgia Crisp County Southeast 30.6 (+3.1%)** 27.2 (-0.9%)%Black/African-American, education, poverty, rural

Georgia Dawson County Southeast 33.8 (+6.6%)** SN Rural, medically underserved

Georgia DeKalb County Southeast 51.8 (+0.2%) 26.1 (-1.2%) %Black/African-American, foreign

Georgia Dodge County Southeast 28.1 (+6.6%)** 25.5 (NA)Older, education, poverty, rural, medically underserved





Georgia Dougherty County Southeast 50.2 (+6.4%) 22.5 (-0.7%)%Black/African-American, poverty, employment

Georgia Elbert County Southeast 53.3 (-0.3%) 24.5 (NA)Older, education, poverty, rural, medically underserved

Georgia Fannin County Southeast 31.3 (+3.2%)** 25.1 (NA)Older, education, rural, medically underserved

Georgia Franklin County Southeast 37.5 (+1.2%)** 24.8 (NA)Older, education, rural, medically underserved

Georgia Fulton County Southeast 49.6 (-0.5%) 29.2 (-1.1%) %Black/African-American

Georgia Glynn County Southeast 53.2 (+6.0%) 23.1 (-0.4%)

Georgia Haralson County Southeast 34.2 (+2.6%)** 23.9 (NA) Education, employment, rural

Georgia Henry County Southeast 45.6 (+5.1%) 25.1 (-0.9%)%Black/African-American, medically underserved

Georgia Jasper County Southeast 62.4 (+18.6%) SNEmployment, rural, medically underserved

Georgia Jones County Southeast 41.0 (+0.4%)** SN Rural, medically underserved

Georgia Lamar County Southeast 59.2 (+6.1%) SN Employment, rural

Georgia Macon County Southeast 39.4 (+6.4%)** SN%Black/African-American, education, poverty, rural, medically underserved

Georgia McDuffie County Southeast 52.0 (+9.6%) SN%Black/African-American, education, rural, medically underserved

Georgia McIntosh County Southeast 36.4 (+33.9%)** SN%Black/African-American, older, education, rural, medically underserved

Georgia Meriwether County Southeast 30.1 (+6.7%)** SN%Black/African-American, older, education, rural, medically underserved

Georgia Monroe County Southeast 45.6 (-0.1%) SNEducation, rural, medically underserved

Georgia Murray County Southeast 45.3 (+17.5%) 37.8 (NA)Education, rural, medically underserved

Georgia Muscogee County Southeast 57.8 (+4.5%) 29.1 (-0.8%) %Black/African-American

Georgia Oglethorpe County Southeast 62.2 (+2.9%) SNEducation, rural, medically underserved

Georgia Peach County Southeast 54.8 (+24.3%) SN%Black/African-American, rural, medically underserved

Georgia Pickens County Southeast 32.3 (+4.4%)** 27.3 (NA) Older, rural, medically underserved

Georgia Pierce County Southeast 37.6 (13.2%)** SNEducation, rural, medically underserved





Georgia Polk County Southeast 45.7 (+1.5%) 28.1 (-1.0%)Education, poverty, rural, medically underserved

Georgia Putnam County Southeast 53.7 (+7.4%) SN Older, rural, medically underserved

Georgia Screven County Southeast 47.3 (+2.5%) SN%Black/African-American, education, poverty, employment, rural, medically underserved

Georgia Stephens County Southeast 48.4 (-0.2%) 17.8 (NA) Older, education, poverty, rural

Georgia Terrell County Southeast 69.8 (30.4%) SN%Black/African-American, older, education, poverty, employment, rural, medically underserved

Georgia Walker County Southeast 45.7 (+8.2%) 28.0 (-1.2%) Older, education, rural

Georgia Ware County Southeast 42.3 (15.6%) 25.9 (+4.3%) Older, poverty, medically underserved

Georgia Washington County Southeast 40.3 (+14.9%)** SN%Black/African-American, older, education, poverty, rural, medically underserved

Georgia Wayne County Southeast 33.3 (+6.2%)** 18.7 (NA)Education, rural, medically underserved

Georgia White County Southeast 24.5 (35.7%)** 18.3 (NA) Older, rural, medically underserved

Georgia Worth County Southeast 43.9 (+3.3%) SNEducation, poverty, employment, rural, medically underserved

Hawai’i Honolulu County Southwest 39.2 (+4.3%)** 15.6 (NA) %API

Hawai’i Maui County Southwest 35.6 (+8.8%)** 17.2 (NA) Rural

Idaho Bingham County Northwest 39.4 (+2.6%)** 29.8 (NA) %AIAN, %Hispanic/Latina, rural

Idaho Cassia County Northwest 36.7 (+32.7%)** SN%Hispanic/Latina, education, language, rural

Idaho Gem County Northwest 53.2(+26.9%) 28.4 (NA)Older, employment, rural, medically underserved

Idaho Idaho County Northwest 34.0 (+5.7%)** SN Older, rural

Idaho Madison County Northwest 54.6 (+15.9%) SN Poverty

Idaho Minidoka County Northwest 41.0 (+10.7%)** SN%Hispanic/Latina, education, language, rural, insurance, medically underserved

Idaho Payette County Northwest 55.1 (+4.8%) 27.5 (NA)Education, rural, medically underserved

Idaho Shoshone County Northwest 38.3% (+19.3%)** SNOlder, education, rural, medically underserved

Illinois Bond County North Central 49.6 (+4.3%) SN Rural





Illinois Carroll County North Central 56.9 (+12.8%) 30.0 (-1.4%) Older, rural, medically underserved

Illinois Cass County North Central 39.8 (+2.9%)** SN Rural, medically underserved

Illinois Fayette County North Central 47.8 (+2.4%) SN Rural, medically underserved

Illinois Fulton County North Central 48.9 (+5.9%) 27.7 (-1.7%) Older, rural

Illinois Grundy County North Central 41.0 (+8.9%)** 29.3 (NA) Rural

Illinois Hancock County North Central 50.1 (+9.5%) SN Older, rural

Illinois Kankakee County North Central 45.8 (+13.5%) 28.1 (-1.9%) Rural

Illinois Macon County North Central 47.1 (+0.6%) 26.4 (-0.8%)

Illinois Mason County North Central 54.5 (+8.0%) SN Older, rural

Illinois Moultrie County North Central 58.9 (+0.4%) SN Rural

Illinois Piatt County North Central 55.0(+6.4%) SN Rural

Indiana Boone County East Central 40.3 (+10.5%)** 31.8 (-0.1%) Rural

Indiana Carroll County East Central 37.9 (+32.9%)** 25.4 (-0.8%) Rural

Indiana DeKalb County East Central 43.7 (+6.4%) 24.5 (-0.5%) Rural

Indiana Floyd County East Central 41.9 (+6.3%) 25.1 (-1.2%)

Indiana Fulton County East Central 49.4 (-0.4%) 40.8 (+2.5%) Rural

Indiana Jasper County East Central 43.9 (+18.5%) 34.5 (-1.1%) Rural

Indiana Jennings County East Central 40.3 (+27.9%)** SN Employment, rural

Indiana LaGrange County East Central 23.1 (+26.5%)** SN Education, language, rural, insurance

Indiana Lake County East Central 46.8 (+2.0%) 28.2 (-1.9%)%Black/African-American, %Hispanic/Latina, medically underserved

Indiana Orange County East Central 38.7 (+11.3%)** SN Education, rural

Indiana Rush County East Central 42.5 (+1.3%) 27.7 (NA) Rural

Indiana Spencer County East Central 30.2 (+24.7%)** SN Rural, medically underserved

Indiana Vermillion County East Central 38.0 (+18.3%)** SN Rural

Indiana Vigo County East Central 40.3 (+12.9%)** 25.1 (-1.5%)

Indiana Warrick County East Central 32.4 (+16.9%)** 24.8 (-1.1%)

Indiana Washington County East Central 39.2 (+9.3%)** 20.5 (NA)Education, rural, medically underserved





Iowa Adair County North Central 66.9 (+16.3%) SN Older, rural

Iowa Buena Vista County North Central 47.3 (+5.3%) SN%API, %Hispanic/Latina, education, foreign, language, rural

Iowa Cherokee County North Central 38.9 (+11.4%)** SN Older, rural

Iowa Clay County North Central 27.0 (+5.7%)** SN

Iowa Clinton County North Central 45.3 (+5.8%) 26.6 (-1.6%)

Iowa Decatur County North Central 65.5 (-17.6%) SNEducation, poverty, rural, medically underserved

Iowa Dickinson County North Central 34.5 (+2.9%)** SN Older

Iowa Guthrie County North Central 46.2 (+52.6%) SN Older, rural

Iowa Henry County North Central 29.7 (+33.1%)** SN Rural

Iowa Ida County North Central 81.9 (+2.0%) SN Older, rural

Iowa Jackson County North Central 39.2 (+18.8%)** SN Rural

Iowa Jones County North Central 32.4 (+10.4%)** SN Rural

Iowa Keokuk County North Central 46.1 (+84.0%) SN Older, rural, medically underserved

Iowa Lyon County North Central 55.1 (+25.5%) SN Rural

Iowa Madison County North Central 59.5 (+13.3%) 36.2 (+1.5%) Rural

Iowa Montgomery County North Central 35.6 (+1.5%)** SN Older, rural

Iowa Osceola County North Central 77.1 (+6.3%) SN Older, rural

Iowa Page County North Central 39.4 (+20.4%)** SN Older

Iowa Warren County North Central 45.9 (+2.0%) 26.8 (+0.3%) Rural

Iowa Wright County North Central 43.6 (+5.6%) SN Older, rural

Kansas Cherokee County North Central NA 26.1 (-1.6%) %AIAN, rural, medically underserved

Kansas Douglas County North Central NA 27.3 (+1.5%)

Kansas Ellis County North Central NA 26.2 (+1.4%)

Kansas Franklin County North Central NA 27.3 (-2.1%) Rural

Kansas McPherson County North Central NA 26.2 (-1.7%) Older, rural

Kansas Montgomery County North Central NA 32.8 (-0.4%) %AIAN, older, employment, rural





Kansas Wyandotte County North Central NA 28.5 (-1.3%)

%Black/African-American, %Hispanic/Latina, education, poverty, employment, foreign, language, insurance

Kentucky Adair County East Central 41.9 (+2.1%) SNEducation, employment, rural, insurance

Kentucky Barren County East Central 43.2 (+0.9%) 23.2 (-0.5%) Rural

Kentucky Boyle County East Central 48.9 (+8.4%) 25.4 (-1.6%)

Kentucky Caldwell County East Central 36.9 (+33.7%)** SN Rural, medically underserved

Kentucky Casey County East Central 64.9 (+1.7%) SNEducation, poverty, rural, insurance, medically underserved

Kentucky Clark County East Central 35.2 (+7.0%)** 26.5 (-0.8%)

Kentucky Clay County East Central 43.2 (+9.2%) 37.2 (NA)Education, poverty, employment, rural, medically underserved

Kentucky Fleming County East Central 56.8 (-0.1%) SN Education, rural

Kentucky Floyd County East Central 37.3 (+1.6%)** 29.5 (-0.2%) Education, poverty, rural

Kentucky Garrard County East Central 50.5 (+8.2%) SNEmployment, rural, medically underserved

Kentucky Grant County East Central 56.7 (+0.3%) SN Rural

Kentucky Harrison County East Central 30.2 (+32.1%)** SN Rural

Kentucky Henry County East Central 40.6 (+10.8%)** SN Rural

Kentucky Johnson County East Central 45.6 (+31.3%) 26.8 (+3.9%) Education, rural

Kentucky Lawrence County East Central 39.8 (+8.0%)** SNEducation, poverty, rural, medically underserved

Kentucky Leslie County East Central 50.9 (+8.5%) SNEducation, poverty, rural, medically underserved

Kentucky Magoffin County East Central 53.8 (+29.6%) SNEducation, poverty, rural, insurance, medically underserved

Kentucky McLean County East Central 59.8 (+7.5%) SN Rural, medically underserved

Kentucky Oldham County East Central 41.3 (+3.3%) 26.6 (+0.3%)

Kentucky Perry County East Central 40.4 (+39.4%)** SN Education, poverty, rural

Kentucky Rowan County East Central 51.7 (+9.0%) 27.7 (NA) Poverty, rural

Kentucky Scott County East Central 53.7 (+4.4%) 26.7 (-1.2%) Medically underserved

Kentucky Simpson County East Central 38.3 (+1.3%)** SN





Kentucky Spencer County East Central 51.8 (+0.7%) SN Rural, medically underserved

Kentucky Taylor County East Central 49.4 (+6.3%) 21.4 (NA) Education, rural

Kentucky Wayne County East Central 50.6 (-1.3%) 34.1 (+0.2%)Education, poverty, employment, rural, medically underserved

Louisiana Allen Parish South Central 43.3 (+2.0%) SNEducation, rural, medically underserved

Louisiana Beauregard Parish South Central 55.5 (+2.8%) 25.0 (NA) Rural, medically underserved

Louisiana Caddo Parish South Central 46.5 (+4.3%) 28.0 (-1.4%) %Black/African-American

Louisiana Claiborne Parish South Central 32.3 (+14.1%)** SN%Black/African-American, older, education, poverty, employment, rural, medically underserved

Louisiana Concordia Parish South Central SN 29.4 (-2.3%)%Black/African-American, education, poverty, employment, rural, medically underserved

Louisiana East Feliciana Parish South Central 62.5 (+18.1%) 39.1 (NA)%Black/African-American, rural, medically underserved

Louisiana Evangeline Parish South Central 45.4 (+6.9%) 23.6 (-0.2%)Education, rural, medically underserved

Louisiana Iberia Parish South Central 52.1 (+13.0%) 23.9 (-1.1%) Education, medically underserved

Louisiana Iberville Parish South Central 46.6 (+12.7%) 25.8 (-1.8%)%Black/African-American, education, rural, medically underserved

Louisiana Jefferson Parish South Central 44.3 (0.0%) 24.9 (-1.4%) %Hispanic/Latina, foreign

Louisiana Lafayette Parish South Central 48.6 (+1.2%) 25.2 (-0.6%)

Louisiana Lafourche Parish South Central 51.8 (+2.0%) 26.6 (-0.5%) Education

Louisiana Orleans Parish South Central 52.8 (+3.0%) 30.8 (-1.4%)%Black/African-American, poverty, employment

Louisiana Pointe Coupee Parish South Central 60.8 (+11.6%) 30.5 (-1.6%) Rural, medically underserved

Louisiana St. Bernard Parish South Central 52.9 (+16.1%) SN Employment

Louisiana St. James Parish South Central 59.2 (+10.9%) SN%Black/African-American, medically underserved

Louisiana St. John the Baptist Parish

South Central 58.7 (+3.0%) 33.2 (+0.8%)%Black/African-American, medically underserved

Louisiana St. Martin Parish South Central 58.9 (+3.7%) 24.9 (-1.5%)Education, rural, medically underserved

Louisiana Webster Parish South Central 44.3 (+7.2%) 27.8 (-1.6%)Education, rural, medically underserved

Louisiana West Baton Rouge Parish

South Central 51.7 (+5.2%) SN%Black/African-American, medically underserved





Maine Knox County Northeast 50.5 (+8.9%) 26.8 (-1.4%) Rural

Maine Piscataquis County Northeast 44.7 (+26.2%) SN Rural, medically underserved

Maryland Baltimore City Northeast 51.9 (+7.1%) 27.9 (-0.2%)%Black/African-American, education, poverty, employment, medically underserved

Maryland Calvert County Northeast 52.6 (+1.7%) 27.6 (-1.5%) Rural, medically underserved

Maryland Charles County Northeast 45.4 (0.0%) 24.4 (-0.8%) %Black/African-American, rural

Maryland Worcester County Northeast 49.3 (+6.1%) 27.9 (-0.2%) Older, rural, medically underserved

Massachusetts Dukes County Northeast SN 26.5 (-0.9%) Rural

Massachusetts Nantucket County Northeast 72.9 (+12.3%) SN Rural

Michigan Arenac County East Central 36.8 (+3.4%)** SNOlder, education, rural, medically underserved

Michigan Benzie County East Central 42.9 (+10.7%) SN Older, rural

Michigan Cheboygan County East Central 32.7 (+14.4%)** 30.2 (-1.3%)Older, employment, rural, insurance, medically underserved

Michigan Emmet County East Central 30.8 (+18.1%)** SN %AIAN, rural

Michigan Grand Traverse County East Central 47.0 (+3.8%) 22.1 (+24.8%) Rural

Michigan Gratiot County East Central 51.0 (+3.0%) 30.8 (+0.1%) Rural, medically underserved

Michigan Leelanau County East Central 19.1 (+20.4%)** SN %AIAN, older, rural

Michigan Mackinac County East Central 59.3 (+29.6%) SN%AIAN, older, rural, insurance, medically underserved

Michigan Menominee County East Central SN 28.4 (+1.7%) Older, rural, medically underserved

Michigan Missaukee County East Central 41.4 (+10.3%) SN Rural, medically underserved

Michigan Montmorency County East Central 39.6 (+7.7%)** SNOlder, education, employment, rural, medically underserved

Michigan Ogemaw County East Central 26.2 (+6.7%)** SN Older, education, rural

Michigan Osceola County East Central 44.8 (+44.6%) 23.8 (-0.9%) Rural

Michigan Otsego County East Central 32.7 (+3.1%)** 27.8 (-1.8%) Rural

Michigan Wayne County East Central 46.2 (-0.1%) 29.2 (-1.6%)%Black/African-American, poverty, employment, medically underserved

Michigan Wexford County East Central 42.8 (+27.0%) SN Rural

Minnesota Faribault County North Central NA 27.9 (-1.7%) Older, rural

Minnesota Fillmore County North Central NA 26.0 (-0.9%) Older, rural, medically underserved





Minnesota Freeborn County North Central NA 25.8 (-1.2%) Older, rural

Minnesota Isanti County North Central NA 23.4 (-0.1%) Rural

Minnesota Martin County North Central NA 32.6 (+1.3%) Older, rural

Minnesota Pine County North Central NA 29.0 (0.0%) Rural, medically underserved

Minnesota Renville County North Central NA 37.4 (+2.7%) Older, rural

Mississippi Adams County Southeast 42.8 (+12.8%) 38.0 (-1.2%)%Black/African-American, poverty, medically underserved

Mississippi Bolivar County Southeast 40.8 (+8.5%) 27.1 (+0.4%)%Black/African-American, education, poverty, employment, medically underserved

Mississippi Calhoun County Southeast 46.5 (+6.7%) SNEducation, rural, medically underserved

Mississippi Chickasaw County Southeast 53.5 (+11.6%) SN%Black/African-American, education, rural, medically underserved

Mississippi Clay County Southeast 45.1 (+6.3%) 26.8 (NA)%Black/African-American, employment, medically underserved

Mississippi Covington County Southeast 52.3 (-0.2%) SN Rural, medically underserved

Mississippi George County Southeast 38.5 (+11.1%)** SN Rural, medically underserved

Mississippi Grenada County Southeast 56.1 (+1.7%) 28.9 (+1.6%) Medically underserved

Mississippi Holmes County Southeast 75.7 (+11.5%) 44.5 (NA)%Black/African-American, education, poverty, employment, rural, medically underserved

Mississippi Humphreys County Southeast 73.8 (+0.7%) SN%Black/African-American, education, poverty, employment, medically underserved

Mississippi Itawamba County Southeast 45.2 (+8.1%) SNEducation, rural, medically underserved

Mississippi Jefferson Davis County Southeast 47.3 (+11.4%) SN%Black/African-American, education, poverty, employment, rural, medically underserved

Mississippi Lawrence County Southeast 42.6 (+6.1%) SN Rural, medically underserved

Mississippi Leflore County Southeast 48.6 (+1.9%) 29.6 (NA)%Black/African-American, education, poverty, employment, medically underserved

Mississippi Lincoln County Southeast 44.2 (27.0%) 31.8 (+0.2%) Rural, medically underserved

Mississippi Neshoba County Southeast 50.0 (+7.4%) 22.7 (+0.1%)%AIAN, education, rural, insurance, medically underserved





Mississippi Noxubee County Southeast 50.6 (+2.9%) SN%Black/African-American, education, poverty, employment, rural, insurance, medically underserved

Mississippi Oktibbeha County Southeast 54.7 (+14.4%) 26.2 (+0.5%) Medically underserved

Mississippi Perry County Southeast 52.3 (+5.2%) SN Rural, medically underserved

Mississippi Pontotoc County Southeast 57.6 (-0.4%) 23.4 (NA)Education, rural, medically underserved

Mississippi Prentiss County Southeast 39.8 (+8.3%)** 28.5 (+2.3%)Education, rural, medically underserved

Mississippi Scott County Southeast 52.2 (+6.4%) SN%Hispanic/Latina, education, rural, insurance, medically underserved

Mississippi Tippah County Southeast 30.1 (+7.8%)** SNEducation, rural, medically underserved

Mississippi Tishomingo County Southeast 31.6 (+22.9%)** SN Older, rural

Mississippi Union County Southeast 26.1 (+13.3%)** SN Rural, medically underserved

Mississippi Warren County Southeast 51.1 (+17.1%) 31.0 (+1.5%)%Black/African-American, medically underserved

Mississippi Wayne County Southeast 45.0 (+14.6%) SNEducation, poverty, rural, medically underserved

Mississippi Yalobusha County Southeast 46.3 (+11.4%) SN Rural, medically underserved

Missouri Audrain County North Central 55.9 (+15.5%) 20.8 (NA) Rural

Missouri Barton County North Central 46.0 (+13.5%) SN Rural

Missouri Bates County North Central SN 27.1 (-2.2%) Rural

Missouri Camden County North Central 41.0 (+6.5%)** 22.5 (-0.4%) Older, rural, medically underserved

Missouri Carter County North Central 96.8 (+8.3%) SNEducation, poverty, rural, insurance, medically underserved

Missouri Chariton County North Central 59.2 (+1.2%) SN Older, rural, medically underserved

Missouri Clay County North Central 49.2 (+7.1%) 27.2 (-1.1%)

Missouri Dallas County North Central 52.9 (+10.5%) 31.6 (+1.6%)Education, poverty, employment, rural, insurance, medically underserved

Missouri Dent County North Central SN 36.1 (+1.6%) Older, education, rural

Missouri Harrison County North Central 48.2 (+15.1%) SN Older, rural, medically underserved

Missouri Jackson County North Central 49.9 (-1.1%) 26.7 (-1.0%) %Black/African-American

Missouri Johnson County North Central 50.6 (+7.6%) 30.6 (NA) Rural





Missouri Lewis County North Central 59.5 (-0.4%) SN Rural

Missouri Linn County North Central 45.9 (+14.7%) SN Older, rural, medically underserved

Missouri Livingston County North Central 43.8 (+38.8%) SN Rural

Missouri McDonald County North Central 32.0 (+20.6%)** SN%AIAN, %Hispanic/Latina, education, rural, insurance, medically underserved

Missouri Mississippi County North Central SN 40.0 (0.0%)%Black/African-American, education, poverty, employment, medically underserved

Missouri Morgan County North Central 24.0 (+21.0%)** SNOlder, education, employment, rural, insurance

Missouri New Madrid County North Central 28.6 (+6.7%)** 22.3 (NA)Education, poverty, rural, medically underserved

Missouri Perry County North Central 48.7 (+14.5%) SN Education, rural

Missouri Pettis County North Central 48.4 (+3.8%) 34.1 (+0.6%) Rural

Missouri Pike County North Central 55.3 (+5.6%) SN Education, rural

Missouri Polk County North Central 49.2 (+9.4%) 19.8 (NA) Poverty, rural

Missouri Pulaski County North Central 50.1 (+9.5%) 20.8 (NA)%Hispanic/Latina, employment, rural, medically underserved

Missouri Ray County North Central 50.3 (+10.1%) 22.7 (+0.6%) Rural

Missouri St. Louis City North Central 52.1 (+3.0%) 27.2 (-1.9%)%Black/African-American, poverty, employment, insurance, medically underserved

Missouri St. Louis County North Central 52.1 (+1.1%) 25.6 (-1.0%) %Black/African-American

Missouri Wayne County North Central 34.9 (+5.4%)** 33.0 (NA)Older, education, poverty, rural, medically underserved

Montana Gallatin County Northwest 54.4 (+7.6%) 22.4 (+0.4%)

Montana Hill County Northwest 40.7 (+2.8%)** 32.0 (NA) %AIAN

Montana Missoula County Northwest 41.8 (+3.6%) 24.1 (-0.1%)

Montana Park County Northwest 61.4 (+17.2%) 26.9 (NA) Medically underserved

Montana Rosebud County Northwest 71.8 (+10.6%) SN%AIAN, employment, rural, medically underserved

Montana Sanders County Northwest 48.3 (+0.2%) SNOlder, poverty, employment, rural, insurance, medically underserved

Montana Stillwater County Northwest 69.1 (+17.2%) SN Rural





Nebraska Custer County North Central 63.2 (+19.5%) SN Older, rural

Nebraska Dawson County North Central 37.2 (+12.0%)** SN%Hispanic/Latina, education, foreign, language, insurance

Nebraska Lincoln County North Central 60.1 (-0.9%) 28.7 (-0.1%)

Nebraska Saunders County North Central 50.4 (+5.0%) 25.3 (+0.7%) Rural

Nevada Humboldt County Southwest 44.0 (+3.8%) SN %AIAN, rural

Nevada Nye County Southwest 41.3 (+2.7%) 24.4(NA) Older, poverty, employment, rural

New Jersey Atlantic County Northeast 45.2 (+2.2%) 26.7 (-1.7%) Rural, medically underserved

New Jersey Camden County Northeast 53.3 (-0.9%) 28.3 (-2.3%) %Black/African-American

New Jersey Gloucester County Northeast 50.5 (+0.4%) 27.8 (-1.5%)

New Jersey Sussex County Northeast 52.8 (-2.0%) 29.5 (-1.2%) Rural

New Mexico Eddy County South Central 33.7 (+2.1%)** 28.7 (+2.3%) Medically underserved

New Mexico Lincoln County South Central 33.6 (+17.1%)** SN Older, rural, medically underserved

New Mexico Luna County South Central 33.5 (+10.1%)** 28.0 (NA)%Hispanic/Latina, education, poverty, employment, foreign, language, rural, insurance, medically underserved

New Mexico Otero County South Central 24.6 (+6.8%)** 22.8 (-0.3%) Rural

New Mexico Sierra County South Central 38.9 (+12.5%)** 36.2 (NA) Older, rural, medically underserved

New Mexico Socorro County South Central 36.2 (+1.7%)** SNEducation, poverty, language, rural, medically underserved

New York Monroe County Northeast 43.4 (+0.2%) 22.8 (+2.4%)

New York Seneca County Northeast 38.4 (+3.7%)** 23.6 (+21.4%) Rural

New York Wyoming County Northeast 55.1 (+18.6%) 24.7 (-0.5%) Rural, medically underserved

North Carolina Ashe County Southeast 42.9 (+12.0%) 16.9 (NA)Older, education, rural, medically underserved

North Carolina Avery County Southeast 46.7 (30.7%) 29.4 (NA)Older, rural, insurance, medically underserved

North Carolina Cabarrus County Southeast 47.8 (-0.9%) 23.1 (-0.6%)

North Carolina Cherokee County Southeast 44.3 (+5.4%) 31.8 (+1.7%) Older, rural, medically underserved

North Carolina Chowan County Southeast 30.4 (+28.6%)** 30.3 (NA)%Black/African-American, older, education, poverty, rural

North Carolina Currituck County Southeast 34.2 (+68.6%)** SN Rural, medically underserved

North Carolina Davidson County Southeast 43.8 (+8.7%) 22.9 (-0.7%) Education, rural





North Carolina Davie County Southeast 45.6 (+16.2%) 21.8 (NA) Rural, medically underserved

North Carolina Edgecombe County Southeast 47.7 (+4.4%) 33.2 (-1.0%)%Black/African-American, education, poverty, employment, rural, medically underserved

North Carolina Granville County Southeast 46.0 (+8.6%) 27.8 (-1.9%)%Black/African-American, rural, medically underserved

North Carolina Halifax County Southeast 48.5 (+1.1%) 36.6 (-0.7%)%Black/African-American, education, poverty, employment, rural, medically underserved

North Carolina Hertford County Southeast 47.2 (+1.1%) 33.0 (+0.4%)%Black/African-American, education, poverty, employment, rural, medically underserved

North Carolina Jones County Southeast 55.4 (+23.6%) SN%Black/African-American, rural, medically underserved

North Carolina Lee County Southeast 47.8 (+1.3%) 21.0 (NA) %Hispanic/Latina, language, rural

North Carolina Martin County Southeast 54.5 (-1.9%) 24.6 (-0.6%)%Black/African-American, older, poverty, rural, medically underserved

North Carolina Mitchell County Southeast 45.3 (+4.1%) 28.0 (NA) Older, rural, medically underserved

North Carolina Pamlico County Southeast 35.8 (+22.5%)** SN Older, rural, medically underserved

North Carolina Rockingham County Southeast 50.1 (+2.3%) 26.7 (-1.5%)Education, rural, medically underserved

North Carolina Rutherford County Southeast 57.3 (+6.0%) 23.2 (-0.3%)Employment, rural, medically underserved

North Carolina Surry County Southeast 43.7 (+1.5%) 23.6 (-0.4%) Education, rural

North Carolina Wayne County Southeast 43.4 (+1.6%) 25.4 (-1.5%)%Black/African-American, rural, medically underserved

North Dakota Rolette County North Central 64.3 (+18.0%) SN%AIAN, education, poverty, rural, insurance, medically underserved

North Dakota Stark County North Central 27.4 (+19.0%)** 20.8 (+0.1%)

North Dakota Stutsman County North Central 53.5 (-1.5%) 26.6 (-1.3%)

North Dakota Walsh County North Central 48.6 (+12.6%) 35.5 (NA)%Hispanic/Latina, older, education, rural

North Dakota Ward County North Central 57.3 (+19.0%) 23.7 (-0.5%)

North Dakota Williams County North Central 40.7 (+4.1%)** SN

Ohio Adams County East Central 39.3 (+5.9%)** 28.9 (+2.8%)Education, poverty, employment, rural, medically underserved

Ohio Ashtabula County East Central 43.0 (-0.5%) 25.7 (-1.8%) Rural





Ohio Auglaize County East Central 51.9 (+2.3%) 37.6 (+0.6%) Rural

Ohio Butler County East Central 43.6 (+2.0%) 24.7 (-1.3%)

Ohio Clark County East Central 49.7 (+3.3%) 27.1 (-1.2%)

Ohio Clinton County East Central 42.8 (+4.6%) 28.2 (+0.4%) Rural

Ohio Erie County East Central 53.9 (+6.1%) 30.8 (-1.4%)

Ohio Hamilton County East Central 46.2 (+2.2%) 26.3 (-1.9%) %Black/African-American

Ohio Harrison County East Central 37.8 (+16.3%)** SN Poverty, rural, medically underserved

Ohio Henry County East Central 35.6 (+5.5%)** 22.1 (NA) Rural

Ohio Hocking County East Central 32.2 (5.4%)** 25.1 (+0.9%) Rural, medically underserved

Ohio Jefferson County East Central 43.8 (+7.9%) 26.1 (-1.5%) Rural

Ohio Licking County East Central 40.5 (+4.4%)** 27.9 (-1.2%) Rural

Ohio Lorain County East Central 40.9 (+0.9%)** 27.5 (-2.1%) %Hispanic/Latina

Ohio Madison County East Central 57.7 (+11.9%) 28.2 (-1.8%) Rural

Ohio Mahoning County East Central 46.6 (+5.2%) 28.6 (-1.2%)

Ohio Meigs County East Central 23.6 (+13.3%)** SNPoverty, employment, rural, medically underserved

Ohio Monroe County East Central 40.3 (+21.0%)** SN Rural, medically underserved

Ohio Morgan County East Central 40.1 (+16.0%)** SN Rural, medically underserved

Ohio Muskingum County East Central 46.9 (+6.6%) 27.2 (-1.6%) Rural

Ohio Perry County East Central 49.0 (-1.4%) 28.1 (-1.8%) Rural, medically underserved

Ohio Putnam County East Central 39.6 (+14.8%)** 19.2 (NA) Rural, medically underserved

Ohio Shelby County East Central 45.2 (+22.1%) 20.8 (NA) Rural

Ohio Van Wert County East Central 43.3 (+14.6%) 24.3 (-0.5%) Rural

Ohio Washington County East Central 44.5 (+14.9%) 24.7 (-1.5%) Rural

Oklahoma Adair County South Central 38.6 (+6.2%)** SN%AIAN, education, poverty, rural, insurance

Oklahoma Beckham County South Central 37.1 (+17.9%)** SN

Oklahoma Garfield County South Central 31.3 (+2.3%)** 25.6 (-0.7%)

Oklahoma Hughes County South Central 56.9 (+49.0%) SN%AIAN, older, education, poverty, rural, medically underserved





Oklahoma Jackson County South Central 56.1 (+1.1%) SN %Hispanic/Latina

Oklahoma Kay County South Central 45.1 (+9.7%) 26.8 (NA)

Oklahoma Kingfisher County South Central 64.5 (+7.3%) SN Rural

Oklahoma Marshall County South Central 41.9 (+13.0%) SN%Hispanic/Latina, older, education, rural, insurance, medically underserved

Oklahoma Okfuskee County South Central 57.3 (+0.1%) SN%AIAN, education, poverty, rural, medically underserved

Oklahoma Oklahoma County South Central 49.4 (-0.3%) 24.6 (-0.8%)%Black/African-American, %Hispanic/Latina

Oklahoma Pawnee County South Central 51.6 (+6.7%) SN %AIAN, rural

Oklahoma Rogers County South Central 38.0 (+5.4%)** 27.3 (-1.6%) %AIAN, rural

Oklahoma Texas County South Central 37.6 (+32.3%)** SN%Hispanic/Latina, education, foreign, language, rural, insurance

Oklahoma Tulsa County South Central 52.3 (+3.3%) 27.2 (-1.2%)

Oklahoma Wagoner County South Central 36.4 (+5.0%)** 27.4 (+0.3%)

Oregon Crook County Northwest 50.4 (+17.4%) 24.7 (-1.3%)Older, employment, rural, medically underserved

Oregon Curry County Northwest 45.9 (0.0%) 21.9 (NA) Older, rural, medically underserved

Oregon Klamath County Northwest 38.2 (+3.1%)** 28.1 (+0.2%) %AIAN, rural

Oregon Tillamook County Northwest 38.4 (+5.0%)** SN Older, rural, medically underserved

Oregon Union County Northwest 41.3 (+7.4%) SN Rural, medically underserved

Pennsylvania Delaware County Northeast 46.3 (-0.1%) 27.5 (-2.1%) %Black/African-American

Pennsylvania Fayette County Northeast 44.7 (+2.9%) 25.9 (-1.7%) Poverty, rural, medically underserved

Pennsylvania Jefferson County Northeast 44.8 (+5.8%) 28.2 (-1.5%) Rural, medically underserved

Pennsylvania Mercer County Northeast 46.3 (+9.3%) 27.3 (-1.1%) Rural

Pennsylvania Mifflin County Northeast 50.2 (+3.0%) 24.9 (-0.3%)Education, rural, medically underserved

Pennsylvania Montour County Northeast 36.9 (+17.0%)** SN Rural

Pennsylvania Philadelphia County Northeast 51.6 (-0.6%) 29.0 (-2.2%)

%Black/African-American, %API, %Hispanic/Latina, education, poverty, employment, foreign, language, insurance, medically underserved

Pennsylvania Pike County Northeast 49.8 (+7.7%) 27.7 (+9.8%) Employment, rural





Pennsylvania Schuylkill County Northeast 46.9 (+4.9%) 28.6 (-0.2%) Rural, medically underserved

South Carolina Anderson County Southeast 48.8 (+4.4%) 25.3 (-0.2%)

South Carolina Barnwell County Southeast 45.4 (+11.8%) SN%Black/African-American, education, poverty, employment, rural, medically underserved

South Carolina Calhoun County Southeast 59.5 (+21.4%) SN%Black/African-American, rural, medically underserved

South Carolina Cherokee County Southeast 51.0 (+3.7%) 26.4 (+0.3%) Education, employment, rural

South Carolina Colleton County Southeast 36.7 (+16.8%)** 22.9 (-0.8%)%Black/African-American, education, poverty, employment, rural, medically underserved

South Carolina Darlington County Southeast 44.7 (+3.0%) 27.4 (-2.0%)%Black/African-American, education, rural, medically underserved

South Carolina Edgefield County Southeast 46.5 (+8.2%) 25.6 (NA)%Black/African-American, rural, medically underserved

South Carolina Greenwood County Southeast 51.5 (+6.8%) 28.0 (-2.5%) Rural

South Carolina Hampton County Southeast 39.2 (17.3%)** SN%Black/African-American, education, poverty, employment, rural, medically underserved

South Carolina Laurens County Southeast 51.0 (+8.3%) 31.7 (-0.3%) Education, rural

South Carolina Marion County Southeast 42.8 (+20.9%) 28.5 (+0.4%)%Black/African-American, poverty, rural, medically underserved

South Carolina Orangeburg County Southeast 55.6 (+7.4%) 30.8 (-0.8%)%Black/African-American, education, poverty, employment, rural, medically underserved

South Dakota Beadle County North Central 38.9 (+6.0%)** 24.4 (NA) Education

South Dakota Lake County North Central 57.2 (+13.2%) SN

South Dakota Lawrence County North Central 37.4 (+1.2%)** 31.4 (+3.4%)

South Dakota Union County North Central 62.8 (+0.5%) SN Rural, medically underserved

South Dakota Yankton County North Central 27.3 (+7.4%)** SN

Tennessee Claiborne County Southeast 49.6 (+2.4%) 28.0 (-0.7%)Education, poverty, rural, medically underserved

Tennessee Clay County Southeast 61.8 (-1.3%) SNOlder, education, rural, insurance, medically underserved

Tennessee Coffee County Southeast 30.0 (+3.3%)** 27.4 (-1.9%) Rural, medically underserved





Tennessee Crockett County Southeast 39.8 (+19.2%)** SNEducation, rural, medically underserved

Tennessee Grundy County Southeast 49.1 (+3.8%) 34.6 (NA)Education, poverty, rural, medically underserved

Tennessee Lauderdale County Southeast 32.4 (55.2%)** 27.3 (-0.3%)%Black/African-American, education, poverty, employment, rural, medically underserved

Tennessee Macon County Southeast 40.0 (+39.5%)** SNEducation, poverty, rural, insurance, medically underserved

Tennessee Marion County Southeast 45.8 (+6.1%) 23.9 (NA)Education, rural, medically underserved

Tennessee Overton County Southeast 37.3 (+7.9%)** 21.8 (NA)Education, rural, medically underserved

Tennessee Rhea County Southeast 45.3 (+11.2%) 20.1 (NA)Education, employment, rural, medically underserved

Tennessee Roane County Southeast 43.4 (+6.4%) 23.2 (-0.6%) Older, rural, medically underserved

Tennessee Smith County Southeast 60.9 (+4.1%) 34.8 (+1.3%) Education, rural

Tennessee Trousdale County Southeast 69.9 (+5.5%) SN Rural, medically underserved

Tennessee Union County Southeast 55.1 (+13.4%) SNEducation, rural, medically underserved

Tennessee Wayne County Southeast 40.5 (+6.5%)** SNEducation, employment, rural, medically underserved

Tennessee White County Southeast 41.3 (+4.8%) SN Education, rural

Texas Austin County South Central 53.8 (+28.5%) 24.7 (-0.4%) Older, rural, medically underserved

Texas Bee County South Central 33.8 (+4.5%)** 28.3 (NA)%Hispanic/Latina, education, rural, medically underserved

Texas Bosque County South Central 38.7 (+4.5%)** SN Older, rural, medically underserved

Texas Caldwell County South Central 55.0 (+1.3%) SN%Hispanic/Latina, employment, rural, medically underserved

Texas Calhoun County South Central 40.7 (+8.4%)** SN%Hispanic/Latina, employment, rural, medically underserved

Texas Chambers County South Central 44.8 (NA) SN Rural, medically underserved

Texas Comanche County South Central 45.2 (+14.5%) SNOlder, poverty, rural, insurance, medically underserved

Texas Eastland County South Central SN 33.7 (-0.5%) Older, rural, medically underserved

Texas Frio County South Central 40.5 (+16.3%)** SN%Hispanic/Latina, education, poverty, language, rural, medically underserved

Texas Hockley County South Central 49.1 (+4.1%) SN%Hispanic/Latina, education, rural, medically underserved





Texas Hutchinson County South Central 38.1 (+5.3%)** SN Rural, medically underserved

Texas Jasper County South Central 55.4 (+19.9%) 21.8 (-0.3%) Older, rural

Texas Jefferson County South Central 58.5 (+6.1%) 25.9 (-0.5%) %Black/African-American

Texas Johnson County South Central 37.5 (+0.8%)** 26.4 (-0.2%) Rural

Texas Jones County South Central 40.5 (+8.6%)** 29.2 (-0.4%)Older, education, rural, medically underserved

Texas Lamb County South Central 53.2 (-1.9%) SN%Hispanic/Latina, education, rural, insurance, medically underserved

Texas Lavaca County South Central 35.5 (+12.3%)** 20.6 (NA) Older, rural, medically underserved

Texas Lee County South Central 42.8 (+0.9%) SN Older, rural, medically underserved

Texas Leon County South Central 45.0 (+6.3%) SN Older, rural, medically underserved

Texas Liberty County South Central 35.0 (+2.9%)** 26.9 (-1.5%)Education, employment, rural, medically underserved

Texas Medina County South Central 25.0 (+27.7%)** 20.6 (+1.7%)**%Hispanic/Latina, rural, medically underserved

Texas Moore County South Central 46.8 (+7.4%) SN%Hispanic/Latina, education, foreign, language

Texas Morris County South Central 53.5 (-0.5%) SN%Black/African-American, older, rural, medically underserved

Texas Nolan County South Central 37.4 (+22.0%)** SN Older, rural, medically underserved

Texas Orange County South Central 53.2 (+0.2%) 23.2 (-0.6%) Rural

Texas Parker County South Central 39.9 (+7.2%)** 26.6 (-0.6%) Rural

Texas Potter County South Central 44.1 (+4.3%) 26.0 (-1.7%) Poverty

Texas Reeves County South Central 63.9 (+3.2%) SN%Hispanic/Latina, education, poverty, employment, language, medically underserved

Texas Sabine County South Central 41.5 (+6.7%) SN Older, rural, medically underserved

Texas Trinity County South Central 36.2 (+4.2%)** SN Older, rural, medically underserved

Texas Walker County South Central 44.6 (+7.1%) 28.2 (+1.9%)%Black/African-American, rural, medically underserved

Texas Washington County South Central 48.5 (+1.8%) 26.7 (-0.4%)%Black/African-American, older, rural, medically underserved

Texas Wilson County South Central 38.0 (+5.5%)** 19.8 (+0.7%)** Rural, medically underserved

Texas Young County South Central 38.7 (+10.9%)** 45.7 (+2.8%) Older, rural, medically underserved





Utah Iron County Northwest 27.1 (+11.2%)** SN Poverty, employment, rural, insurance

Utah Sanpete County Northwest 35.8 (+11.1%)** SN Rural, medically underserved

Utah Sevier County Northwest 50.4 (+14.7%) SN Older, rural

Utah Utah County Northwest 43.0 (+1.9%) 22.3 (-0.3%)

Utah Wasatch County Northwest 51.2 (+5.6%) SN Rural

Vermont Addison County Northeast 38.5 (15.3%)** 24.8 (+24.1%) Rural

Vermont Bennington County Northeast 40.8 (+4.1%)** 23.6 (-.09%)

Virginia Amelia County Southeast 67.4 (+18.7%) SNEducation, rural, insurance, medically underserved

Virginia Appomattox County Southeast 51.4 (+17.0%) SN Older, education, poverty, rural

Virginia Brunswick County Southeast 37.3 (+3.6%)** 31.1 (-1.6%)%Black/African-American, older, education, poverty, employment, rural, medically underserved

Virginia Caroline County Southeast 49.4 (+2.3%) 26.5 (NA)%Black/African-American, employment, rural, medically underserved

Virginia Gloucester County Southeast 49.5 (+6.8%) 22.7 (NA) Rural

Virginia Goochland County Southeast 65.9 (+1.4%) SN Rural, medically underserved

Virginia Henrico County Southeast 47.7 (+3.2%) 26.7 (-1.1%) %Black/African-American

Virginia James City County Southeast 43.5 (+4.1%) 24.5 (NA) Older

Virginia Lunenburg County Southeast 48.9 (+17.8%) SN%Black/African-American, older, education, poverty, rural, insurance, medically underserved

Virginia Middlesex County Southeast 45.1 (+31.6%) SN Older, rural, medically underserved

Virginia Nelson County Southeast 46.4 (+1.5%) SN Older, education, rural

Virginia Nottoway County Southeast 54.0 (+1.6%) SN%Black/African-American, older, education, poverty, rural, medically underserved

Virginia Orange County Southeast 45.3 (+12.65) 26.2 (-1.2%) Older, rural, medically underserved

Virginia Patrick County Southeast 30.4 (+13.6%)** SNOlder, education, poverty, employment, rural, insurance, medically underserved

Virginia Roanoke County Southeast 41.4 (+5.4%) 25.1 (-0.5%) Older

Virginia Shenandoah County Southeast 46.3 (+18.0%) 23.6 (-1.0%) Older, rural





Virginia Southampton County Southeast 37.5 (+1.0%)** 32.0 (+1.9%)%Black/African-American, education, poverty, rural, medically underserved

Virginia Spotsylvania County Southeast 49.1 (+1.9%) 24.8 (-0.8%) Rural

Virginia Stafford County Southeast 40.6 (+2.6%)** 28.3 (-0.9%) Medically underserved

Virginia Washington County Southeast 44.7 (+0.2%) 28.0 (-0.7%) Older, rural, medically underserved

Virginia Wythe County Southeast 35.7 (+16.5%)** 28.6 (-0.6%)Older, education, rural, medically underserved

Virginia Alexandria City National Capital 44.6 (+5.9%) 23.0 (+15.7%) %Hispanic/Latina, foreign, language

Virginia Chesapeake City Southeast 46.5 (+3.4%) 24.9 (-1.5%) %Black/African-American

Virginia Danville City Southeast 37.0 (+11.5%)** 28.7 (-1.7%)%Black/African-American, older, education, poverty, employment, medically underserved

Virginia Falls Church City National Capital 51.3 (+48.7%) SN %API, foreign

Virginia Fredericksburg City Southeast 64.4 (+15.2%) SN Poverty, employment

Virginia Hopewell City Southeast 53.3 (+13.9%) SN%Black/African-American, education, poverty, employment

Virginia Lynchburg City Southeast 42.9 (+4.5%) 26.7 (-2.0%)%Black/African-American, poverty, employment

Virginia Newport News City Southeast 44.0 (+0.6%) 27.5 (-1.9%) %Black/African-American

Virginia Portsmouth City Southeast 53.8 (+0.5%) 31.9 (+0.3%) %Black/African-American, poverty

Virginia Radford City Southeast 81.8 (-4.7%) SNPoverty, employment, medically underserved

Virginia Roanoke City Southeast 46.9 (+3.1%) 27.0 (-1.7%)%Black/African-American, education, poverty, medically underserved

Virginia Staunton City Southeast 30.3 (+18.6%)** SN Older, poverty

Virginia Winchester City Southeast 39.7 (+0.8%)** 39.1 (NA) %Hispanic/Latina, poverty

Washington Asotin County Northwest 25.8 (+5.0%)** SN Older, medically underserved

Washington Benton County Northwest 46.1 (+2.8%) 24.8 (-1.3%) %Hispanic/Latina

Washington Cowlitz County Northwest 51.8 (+2.8%) 24.6 (-0.9%) Employment, rural

Washington Douglas County Northwest 38.6 (+10.2%)** 15.5 (NA)%Hispanic/Latina, education, rural, insurance, medically underserved

Washington Klickitat County Northwest 26.1 (+6.0%)** SN Poverty, rural, insurance

Washington Pacific County Northwest 32.7 (+19.6%)** 19.3 (NA)Older, poverty, rural, insurance, medically underserved

Washington San Juan County Northwest 44.8 (+23.8%) SN Older, rural, medically underserved





Washington Skagit County Northwest 38.3 (+1.4%)** 24.4 (0.0%) %Hispanic/Latina, rural

West Virginia Barbour County East Central 37.6 (+58.0%)** SN Rural, medically underserved

West Virginia Berkeley County East Central 39.8 (+12.0)** 26.7 (-1.2%)

West Virginia Clay County East Central 59.0 (-0.1%) SNEducation, poverty, rural, medically underserved

West Virginia Hampshire County East Central 47.9 (+7.1%) 29.0 (NA)Rural, insurance, medically underserved

West Virginia Lewis County East Central 50.5 (+11.8%) 33.7 (+1.3%) Rural, medically underserved

West Virginia Marshall County East Central 45.9 (+11.2%) 23.0 (-0.4%)

West Virginia Mason County East Central 33.8 (+18.3%)** 32.8 (-0.9%) Rural, medically underserved

West Virginia Mingo County East Central 36.5 (+41.5%)** SNEducation, poverty, employment, rural, medically underserved

West Virginia Monroe County East Central 33.8 (+25.3%)** SN Rural, medically underserved

West Virginia Randolph County East Central 42.5 (+1.3%) 22.4 (+1.1%) Rural

West Virginia Summers County East Central 38.0 (+49.7%)** SNEducation, rural, medically underserved

Wisconsin Ashland County North Central NA 42.7 (+1.8%) %AIAN, poverty, rural

Wisconsin Chippewa County North Central NA 21.9 (+0.3%) Rural, medically underserved

Wisconsin Lincoln County North Central NA 27.7 (+9.0%) Older, rural

Wisconsin Oconto County North Central NA 26.5 (-0.4%) Rural, medically underserved

Wisconsin Pierce County North Central NA 32.5 (-0.5%) Rural

Wisconsin Shawano County North Central NA 24.9 (+0.6%) %AIAN, rural, medically underserved

Wisconsin Vilas County North Central NA 29.9 (-2.5%)%AIAN, older, rural, insurance, medically underserved

Wisconsin Washington County North Central NA 24.5 (-0.2%)

Wyoming Albany County Northwest 36.2 (+6.4%)** SN

Wyoming Big Horn County Northwest 57.3 (-0.2%) SNRural, insurance, medically underserved

Wyoming Campbell County Northwest 31.2 (+8.4%)** 26.2 (NA)

Wyoming Carbon County Northwest 54.7 (+24.2%) SN %Hispanic/Latina, rural

Wyoming Teton County Northwest 46.1 (+3.4%) SN %Hispanic/Latina, rural

Wyoming Uinta County Northwest 41.9 (+9.5%) SN Rural

*Target as of the writing of this report.


** While this community currently meets the HP2020 target, because the trend is increasing it should be treated the same as a community that will not meet the HP2020 target.

NA – data not available.

SN – data suppressed due to small numbers (15 deaths or fewer for the 5-year data period).

Rates are cases/deaths per 100,000.

Late-stage diagnosis data are for years 2006-2010 except for Nevada, Ohio and Virginia which are 2005-2009.

Death data are for years 2006-2010.

Age-adjusted rates are adjusted to the 2000 U.S. standard population.

Source of late-stage diagnosis rate and trend data: NAACCR – CINA Deluxe Analytic File.

Source of death rate data: CDC – NCHS mortality data in SEER*Stat.

Source of death trend data: NCI/CDC State Cancer Profiles


Appendix E. HP2020 “Highest Priority” communities with a sustainably larger

percentage of residents residing in rural communities.

State Community Komen Region Key Population Characteristics

Alabama Barbour County Southeast %Black/African-American, education, poverty, employment, rural

Alabama Butler County Southeast %Black/African-American, education, poverty, rural, medically underserved

Alabama Geneva County Southeast Education, rural, medically underserved

Alabama Greene County Southeast %Black/African-American, education, poverty, employment, rural, medically underserved

Alabama Hale County Southeast %Black/African-American, education, poverty, employment, rural, medically underserved

Alabama Lamar County Southeast Older, education, rural, medically underserved

Alabama Lawrence County Southeast %AIAN, rural, medically underserved

Alabama Marengo County Southeast %Black/African-American, rural, medically underserved

Alabama Marion County Southeast Older, education, rural, medically underserved

Alabama Perry County Southeast %Black/African-American, education, poverty, employment, rural, medically underserved

Alabama Pike County Southeast %Black/African-American, poverty, rural

Alabama Randolph County Southeast Education, poverty, rural, medically underserved

Alabama Tallapoosa County Southeast Rural, medically underserved

Alabama Walker County Southeast Education, employment, rural

Alabama Winston County Southeast Education, rural, medically underserved

Alaska Kenai Peninsula Borough

Northwest Rural

Alaska Matanuska-Susitna Borough

Northwest Rural

Arizona Graham County Southwest %AIAN, poverty, rural

Arizona Santa Cruz County Southwest %Hispanic/Latina, education, poverty, employment, foreign, language, rural, insurance, medically underserved

Arkansas Boone County South Central Rural

Arkansas Bradley County South Central %Black/African-American, %Hispanic/Latina, education, poverty, rural, medically underserved

Arkansas Chicot County South Central %Black/African-American, older, education, poverty, rural, medically underserved

Arkansas Cleburne County South Central Older, rural, medically underserved

Arkansas Columbia County South Central %Black/African-American, rural, medically underserved

Arkansas Izard County South Central Older, rural, medically underserved

Arkansas Johnson County South Central %Hispanic/Latino, education, rural, medically underserved

Arkansas Lawrence County South Central Education, rural, medically underserved

Arkansas Marion County South Central Older, rural, medically underserved

Arkansas Nevada County South Central %Black/African-American, education, employment, rural, medically underserved

Arkansas Polk County South Central Older, rural, insurance, medically underserved

Arkansas Randolph County South Central Rural, medically underserved

Arkansas Sharp County South Central Older, poverty, rural, medically underserved

Arkansas St. Francis County South Central %Black/African-American, education, poverty, employment, rural, medically underserved



California Amador County Southwest Older, employment, rural, medically underserved

California Colusa County Southwest %Hispanic/Latina, education, employment, language, rural

California Humboldt County Southwest %AIAN, rural, medically underserved

California Mariposa County Southwest Older, employment, rural, medically underserved

California Yuba County Southwest Poverty, employment, rural

Colorado Fremont County Northwest Older, education, rural, medically underserved

Colorado Grand County Northwest Rural

Colorado Montezuma County Northwest %AIAN, older, rural, insurance

Colorado Otero County Northwest %Hispanic/Latina, older, education, poverty, employment, rural

Colorado Teller County Northwest Rural

Delaware Kent County Northeast Rural

Florida Baker County Southeast Education, rural, medically underserved

Florida Citrus County Southeast Older, employment, rural

Florida DeSoto County Southeast Education, poverty, language, rural, insurance

Florida Dixie County Southeast Education, rural, medically underserved

Florida Gulf County Southeast Education, rural

Florida Hardee County Southeast %Hispanic/Latina, education, poverty, language, rural, insurance, medically underserved

Florida Okeechobee County Southeast Education, poverty, rural

Florida Union County Southeast Education, rural, medically underserved

Florida Wakulla County Southeast Rural, medically underserved

Florida Washington County Southeast Education, poverty, rural, medically underserved

Georgia Appling County Southeast Education, poverty, rural, medically underserved

Georgia Berrien County Southeast Education, poverty, rural, medically underserved

Georgia Brooks County Southeast Older, rural

Georgia Bryan County Southeast Rural, medically underserved

Georgia Butts County Southeast Education, rural, medically underserved

Georgia Colquitt County Southeast %Hispanic/Latina, education, poverty, rural, insurance, medically underserved

Georgia Cook County Southeast Education, poverty, rural, medically underserved

Georgia Crisp County Southeast %Black/African-American, education, poverty, rural

Georgia Dawson County Southeast Rural, medically underserved

Georgia Dodge County Southeast Older, education, poverty, rural, medically underserved

Georgia Elbert County Southeast Older, education, poverty, rural, medically underserved

Georgia Fannin County Southeast Older, education, rural, medically underserved

Georgia Franklin County Southeast Older, education, rural, medically underserved

Georgia Haralson County Southeast Education, employment, rural

Georgia Jasper County Southeast Employment, rural, medically underserved

Georgia Jones County Southeast Rural, medically underserved

Georgia Lamar County Southeast Employment, rural



Georgia Macon County Southeast %Black/African-American, education, poverty, rural, medically underserved

Georgia McDuffie County Southeast %Black/African-American, education, rural, medically underserved

Georgia McIntosh County Southeast %Black/African-American, older, education, rural, medically underserved

Georgia Meriwether County Southeast %Black/African-American, older, education, rural, medically underserved

Georgia Monroe County Southeast Education, rural, medically underserved

Georgia Murray County Southeast Education, rural, medically underserved

Georgia Oglethorpe County Southeast Education, rural, medically underserved

Georgia Peach County Southeast %Black/African-American, rural, medically underserved

Georgia Pickens County Southeast Older, rural, medically underserved

Georgia Pierce County Southeast Education, rural, medically underserved

Georgia Polk County Southeast Education, poverty, rural, medically underserved

Georgia Putnam County Southeast Older, rural, medically underserved

Georgia Screven County Southeast %Black/African-American, education, poverty, employment, rural, medically underserved

Georgia Stephens County Southeast Older, education, poverty, rural

Georgia Terrell County Southeast %Black/African-American, older, education, poverty, employment, rural, medically underserved

Georgia Walker County Southeast Older, education, rural

Georgia Washington County Southeast %Black/African-American, older, education, poverty, rural, medically underserved

Georgia Wayne County Southeast Education, rural, medically underserved

Georgia White County Southeast Older, rural, medically underserved

Georgia Worth County Southeast Education, poverty, employment, rural, medically underserved

Hawai’i Maui County Southwest Rural

Idaho Bingham County Northwest %AIAN, %Hispanic/Latina, rural

Idaho Cassia County Northwest %Hispanic/Latina, education, language, rural

Idaho Gem County Northwest Older, employment, rural, medically underserved

Idaho Idaho County Northwest Older, rural

Idaho Minidoka County Northwest %Hispanic/Latina, education, language, rural, insurance, medically underserved

Idaho Payette County Northwest Education, rural, medically underserved

Idaho Shoshone County Northwest Older, education, rural, medically underserved

Illinois Bond County North Central Rural

Illinois Carroll County North Central Older, rural, medically underserved

Illinois Cass County North Central Rural, medically underserved

Illinois Fayette County North Central Rural, medically underserved

Illinois Fulton County North Central Older, rural

Illinois Grundy County North Central Rural

Illinois Hancock County North Central Older, rural

Illinois Kankakee County North Central Rural

Illinois Mason County North Central Older, rural



Illinois Moultrie County North Central Rural

Illinois Piatt County North Central Rural

Indiana Boone County East Central Rural

Indiana Carroll County East Central Rural

Indiana DeKalb County East Central Rural

Indiana Fulton County East Central Rural

Indiana Jasper County East Central Rural

Indiana Jennings County East Central Employment, rural

Indiana LaGrange County East Central Education, language, rural, insurance

Indiana Orange County East Central Education, rural

Indiana Rush County East Central Rural

Indiana Spencer County East Central Rural, medically underserved

Indiana Vermillion County East Central Rural

Indiana Washington County East Central Education, rural, medically underserved

Iowa Adair County North Central Older, rural

Iowa Buena Vista County North Central %API, %Hispanic/Latina, education, foreign, language, rural

Iowa Cherokee County North Central Older, rural

Iowa Decatur County North Central Education, poverty, rural, medically underserved

Iowa Guthrie County North Central Older, rural

Iowa Henry County North Central Rural

Iowa Ida County North Central Older, rural

Iowa Jackson County North Central Rural

Iowa Jones County North Central Rural

Iowa Keokuk County North Central Older, rural, medically underserved

Iowa Lyon County North Central Rural

Iowa Madison County North Central Rural

Iowa Montgomery County North Central Older, rural

Iowa Osceola County North Central Older, rural

Iowa Warren County North Central Rural

Iowa Wright County North Central Older, rural

Kansas Cherokee County North Central %AIAN, rural, medically underserved

Kansas Franklin County North Central Rural

Kansas McPherson County North Central Older, rural

Kansas Montgomery County North Central %AIAN, older, employment, rural

Kentucky Adair County East Central Education, employment, rural, insurance

Kentucky Barren County East Central Rural

Kentucky Caldwell County East Central Rural, medically underserved

Kentucky Casey County East Central Education, poverty, rural, insurance, medically underserved

Kentucky Clay County East Central Education, poverty, employment, rural, medically underserved

Kentucky Fleming County East Central Education, rural



Kentucky Floyd County East Central Education, poverty, rural

Kentucky Garrard County East Central Employment, rural, medically underserved

Kentucky Grant County East Central Rural

Kentucky Harrison County East Central Rural

Kentucky Henry County East Central Rural

Kentucky Johnson County East Central Education, rural

Kentucky Lawrence County East Central Education, poverty, rural, medically underserved

Kentucky Leslie County East Central Education, poverty, rural, medically underserved

Kentucky Magoffin County East Central Education, poverty, rural, insurance, medically underserved

Kentucky McLean County East Central Rural, medically underserved

Kentucky Perry County East Central Education, poverty, rural

Kentucky Rowan County East Central Poverty, rural

Kentucky Spencer County East Central Rural, medically underserved

Kentucky Taylor County East Central Education, rural

Kentucky Wayne County East Central Education, poverty, employment, rural, medically underserved

Louisiana Allen Parish South Central Education, rural, medically underserved

Louisiana Beauregard Parish South Central Rural, medically underserved

Louisiana Claiborne Parish South Central %Black/African-American, older, education, poverty, employment, rural, medically underserved

Louisiana Concordia Parish South Central %Black/African-American, education, poverty, employment, rural, medically underserved

Louisiana East Feliciana Parish South Central %Black/African-American, rural, medically underserved

Louisiana Evangeline Parish South Central Education, rural, medically underserved

Louisiana Iberville Parish South Central %Black/African-American, education, rural, medically underserved

Louisiana Pointe Coupee Parish South Central Rural, medically underserved

Louisiana St. Martin Parish South Central Education, rural, medically underserved

Louisiana Webster Parish South Central Education, rural, medically underserved

Maine Knox County Northeast Rural

Maine Piscataquis County Northeast Rural, medically underserved

Maryland Calvert County Northeast Rural, medically underserved

Maryland Charles County Northeast %Black/African-American, rural

Maryland Worcester County Northeast Older, rural, medically underserved

Massachusetts Dukes County Northeast Rural

Massachusetts Nantucket County Northeast Rural

Michigan Arenac County East Central Older, education, rural, medically underserved

Michigan Benzie County East Central Older, rural

Michigan Cheboygan County East Central Older, employment, rural, insurance, medically underserved

Michigan Emmet County East Central %AIAN, rural

Michigan Grand Traverse County

East Central Rural

Michigan Gratiot County East Central Rural, medically underserved



Michigan Leelanau County East Central %AIAN, older, rural

Michigan Mackinac County East Central %AIAN, older, rural, insurance, medically underserved

Michigan Menominee County East Central Older, rural, medically underserved

Michigan Missaukee County East Central Rural, medically underserved

Michigan Montmorency County East Central Older, education, employment, rural, medically underserved

Michigan Ogemaw County East Central Older, education, rural

Michigan Osceola County East Central Rural

Michigan Otsego County East Central Rural

Michigan Wexford County East Central Rural

Minnesota Faribault County North Central Older, rural

Minnesota Fillmore County North Central Older, rural, medically underserved

Minnesota Freeborn County North Central Older, rural

Minnesota Isanti County North Central Rural

Minnesota Martin County North Central Older, rural

Minnesota Pine County North Central Rural, medically underserved

Minnesota Renville County North Central Older, rural

Mississippi Calhoun County Southeast Education, rural, medically underserved

Mississippi Chickasaw County Southeast %Black/African-American, education, rural, medically underserved

Mississippi Covington County Southeast Rural, medically underserved

Mississippi George County Southeast Rural, medically underserved

Mississippi Holmes County Southeast %Black/African-American, education, poverty, employment, rural, medically underserved

Mississippi Itawamba County Southeast Education, rural, medically underserved

Mississippi Jefferson Davis County

Southeast %Black/African-American, education, poverty, employment, rural, medically underserved

Mississippi Lawrence County Southeast Rural, medically underserved

Mississippi Lincoln County Southeast Rural, medically underserved

Mississippi Neshoba County Southeast %AIAN, education, rural, insurance, medically underserved

Mississippi Noxubee County Southeast %Black/African-American, education, poverty, employment, rural, insurance, medically underserved

Mississippi Perry County Southeast Rural, medically underserved

Mississippi Pontotoc County Southeast Education, rural, medically underserved

Mississippi Prentiss County Southeast Education, rural, medically underserved

Mississippi Scott County Southeast %Hispanic/Latina, education, rural, insurance, medically underserved

Mississippi Tippah County Southeast Education, rural, medically underserved

Mississippi Tishomingo County Southeast Older, rural

Mississippi Union County Southeast Rural, medically underserved

Mississippi Wayne County Southeast Education, poverty, rural, medically underserved

Mississippi Yalobusha County Southeast Rural, medically underserved

Missouri Audrain County North Central Rural

Missouri Barton County North Central Rural



Missouri Bates County North Central Rural

Missouri Camden County North Central Older, rural, medically underserved

Missouri Carter County North Central Education, poverty, rural, insurance, medically underserved

Missouri Chariton County North Central Older, rural, medically underserved

Missouri Dallas County North Central Education, poverty, employment, rural, insurance, medically underserved

Missouri Dent County North Central Older, education, rural

Missouri Harrison County North Central Older, rural, medically underserved

Missouri Johnson County North Central Rural

Missouri Lewis County North Central Rural

Missouri Linn County North Central Older, rural, medically underserved

Missouri Livingston County North Central Rural

Missouri McDonald County North Central %AIAN, %Hispanic/Latina, education, rural, insurance, medically underserved

Missouri Morgan County North Central Older, education, employment, rural, insurance

Missouri New Madrid County North Central Education, poverty, rural, medically underserved

Missouri Perry County North Central Education, rural

Missouri Pettis County North Central Rural

Missouri Pike County North Central Education, rural

Missouri Polk County North Central Poverty, rural

Missouri Pulaski County North Central %Hispanic/Latina, employment, rural, medically underserved

Missouri Ray County North Central Rural

Missouri Wayne County North Central Older, education, poverty, rural, medically underserved

Montana Rosebud County Northwest %AIAN, employment, rural, medically underserved

Montana Sanders County Northwest Older, poverty, employment, rural, insurance, medically underserved

Montana Stillwater County Northwest Rural

Nebraska Custer County North Central Older, rural

Nebraska Saunders County North Central Rural

Nevada Humboldt County Southwest %AIAN, rural

Nevada Nye County Southwest Older, poverty, employment, rural

New Jersey Atlantic County Northeast Rural, medically underserved

New Jersey Sussex County Northeast Rural

New Mexico Lincoln County South Central Older, rural, medically underserved

New Mexico Luna County South Central %Hispanic/Latina, education, poverty, employment, foreign, language, rural, insurance, medically underserved

New Mexico Otero County South Central Rural

New Mexico Sierra County South Central Older, rural, medically underserved

New Mexico Socorro County South Central Education, poverty, language, rural, medically underserved

New York Seneca County Northeast Rural

New York Wyoming County Northeast Rural, medically underserved



North Carolina Ashe County Southeast Older, education, rural, medically underserved

North Carolina Avery County Southeast Older, rural, insurance, medically underserved

North Carolina Cherokee County Southeast Older, rural, medically underserved

North Carolina Chowan County Southeast %Black/African-American, older, education, poverty, rural

North Carolina Currituck County Southeast Rural, medically underserved

North Carolina Davidson County Southeast Education, rural

North Carolina Davie County Southeast Rural, medically underserved

North Carolina Edgecombe County Southeast %Black/African-American, education, poverty, employment, rural, medically underserved

North Carolina Granville County Southeast %Black/African-American, rural, medically underserved

North Carolina Halifax County Southeast %Black/African-American, education, poverty, employment, rural, medically underserved

North Carolina Hertford County Southeast %Black/African-American, education, poverty, employment, rural, medically underserved

North Carolina Jones County Southeast %Black/African-American, rural, medically underserved

North Carolina Lee County Southeast %Hispanic/Latina, language, rural

North Carolina Martin County Southeast %Black/African-American, older, poverty, rural, medically underserved

North Carolina Mitchell County Southeast Older, rural, medically underserved

North Carolina Pamlico County Southeast Older, rural, medically underserved

North Carolina Rockingham County Southeast Education, rural, medically underserved

North Carolina Rutherford County Southeast Employment, rural, medically underserved

North Carolina Surry County Southeast Education, rural

North Carolina Wayne County Southeast %Black/African-American, rural, medically underserved

North Dakota Rolette County North Central %AIAN, education, poverty, rural, insurance, medically underserved

North Dakota Walsh County North Central %Hispanic/Latina, older, education, rural

Ohio Adams County East Central Education, poverty, employment, rural, medically underserved

Ohio Ashtabula County East Central Rural

Ohio Auglaize County East Central Rural

Ohio Clinton County East Central Rural

Ohio Harrison County East Central Poverty, rural, medically underserved

Ohio Henry County East Central Rural

Ohio Hocking County East Central Rural, medically underserved

Ohio Jefferson County East Central Rural

Ohio Licking County East Central Rural

Ohio Madison County East Central Rural

Ohio Meigs County East Central Poverty, employment, rural, medically underserved

Ohio Monroe County East Central Rural, medically underserved

Ohio Morgan County East Central Rural, medically underserved

Ohio Muskingum County East Central Rural

Ohio Perry County East Central Rural, medically underserved



Ohio Putnam County East Central Rural, medically underserved

Ohio Shelby County East Central Rural

Ohio Van Wert County East Central Rural

Ohio Washington County East Central Rural

Oklahoma Adair County South Central %AIAN, education, poverty, rural, insurance

Oklahoma Hughes County South Central %AIAN, older, education, poverty, rural, medically underserved

Oklahoma Kingfisher County South Central Rural

Oklahoma Marshall County South Central %Hispanic/Latina, older, education, rural, insurance, medically underserved

Oklahoma Okfuskee County South Central %AIAN, education, poverty, rural, medically underserved

Oklahoma Pawnee County South Central %AIAN, rural

Oklahoma Rogers County South Central %AIAN, rural

Oklahoma Texas County South Central %Hispanic/Latina, education, foreign, language, rural, insurance

Oregon Crook County Northwest Older, employment, rural, medically underserved

Oregon Curry County Northwest Older, rural, medically underserved

Oregon Klamath County Northwest %AIAN, rural

Oregon Tillamook County Northwest Older, rural, medically underserved

Oregon Union County Northwest Rural, medically underserved

Pennsylvania Fayette County Northeast Poverty, rural, medically underserved

Pennsylvania Jefferson County Northeast Rural, medically underserved

Pennsylvania Mercer County Northeast Rural

Pennsylvania Mifflin County Northeast Education, rural, medically underserved

Pennsylvania Montour County Northeast Rural

Pennsylvania Pike County Northeast Employment, rural

Pennsylvania Schuylkill County Northeast Rural, medically underserved

South Carolina Barnwell County Southeast %Black/African-American, education, poverty, employment, rural, medically underserved

South Carolina Calhoun County Southeast %Black/African-American, rural, medically underserved

South Carolina Cherokee County Southeast Education, employment, rural

South Carolina Colleton County Southeast %Black/African-American, education, poverty, employment, rural, medically underserved

South Carolina Darlington County Southeast %Black/African-American, education, rural, medically underserved

South Carolina Edgefield County Southeast %Black/African-American, rural, medically underserved

South Carolina Greenwood County Southeast Rural

South Carolina Hampton County Southeast %Black/African-American, education, poverty, employment, rural, medically underserved

South Carolina Laurens County Southeast Education, rural

South Carolina Marion County Southeast %Black/African-American, poverty, rural, medically underserved

South Carolina Orangeburg County Southeast %Black/African-American, education, poverty, employment, rural, medically underserved

South Dakota Union County North Central Rural, medically underserved

Tennessee Claiborne County Southeast Education, poverty, rural, medically underserved



Tennessee Clay County Southeast Older, education, rural, insurance, medically underserved

Tennessee Coffee County Southeast Rural, medically underserved

Tennessee Crockett County Southeast Education, rural, medically underserved

Tennessee Grundy County Southeast Education, poverty, rural, medically underserved

Tennessee Lauderdale County Southeast %Black/African-American, education, poverty, employment, rural, medically underserved

Tennessee Macon County Southeast Education, poverty, rural, insurance, medically underserved

Tennessee Marion County Southeast Education, rural, medically underserved

Tennessee Overton County Southeast Education, rural, medically underserved

Tennessee Rhea County Southeast Education, employment, rural, medically underserved

Tennessee Roane County Southeast Older, rural, medically underserved

Tennessee Smith County Southeast Education, rural

Tennessee Trousdale County Southeast Rural, medically underserved

Tennessee Union County Southeast Education, rural, medically underserved

Tennessee Wayne County Southeast Education, employment, rural, medically underserved

Tennessee White County Southeast Education, rural

Texas Austin County South Central Older, rural, medically underserved

Texas Bee County South Central %Hispanic/Latina, education, rural, medically underserved

Texas Bosque County South Central Older, rural, medically underserved

Texas Caldwell County South Central %Hispanic/Latina, employment, rural, medically underserved

Texas Calhoun County South Central %Hispanic/Latina, employment, rural, medically underserved

Texas Chambers County South Central Rural, medically underserved

Texas Comanche County South Central Older, poverty, rural, insurance, medically underserved

Texas Eastland County South Central Older, rural, medically underserved

Texas Frio County South Central %Hispanic/Latina, education, poverty, language, rural, medically underserved

Texas Hockley County South Central %Hispanic/Latina, education, rural, medically underserved

Texas Hutchinson County South Central Rural, medically underserved

Texas Jasper County South Central Older, rural

Texas Johnson County South Central Rural

Texas Jones County South Central Older, education, rural, medically underserved

Texas Lamb County South Central %Hispanic/Latina, education, rural, insurance, medically underserved

Texas Lavaca County South Central Older, rural, medically underserved

Texas Lee County South Central Older, rural, medically underserved

Texas Leon County South Central Older, rural, medically underserved

Texas Liberty County South Central Education, employment, rural, medically underserved

Texas Medina County South Central %Hispanic/Latina, rural, medically underserved

Texas Morris County South Central %Black/African-American, older, rural, medically underserved

Texas Nolan County South Central Older, rural, medically underserved



Texas Orange County South Central Rural

Texas Parker County South Central Rural

Texas Sabine County South Central Older, rural, medically underserved

Texas Trinity County South Central Older, rural, medically underserved

Texas Walker County South Central %Black/African-American, rural, medically underserved

Texas Washington County South Central %Black/African-American, older, rural, medically underserved

Texas Wilson County South Central Rural, medically underserved

Texas Young County South Central Older, rural, medically underserved

Utah Iron County Northwest Poverty, employment, rural, insurance

Utah Sanpete County Northwest Rural, medically underserved

Utah Sevier County Northwest Older, rural

Utah Wasatch County Northwest Rural

Vermont Addison County Northeast Rural

Virginia Amelia County Southeast Education, rural, insurance, medically underserved

Virginia Appomattox County Southeast Older, education, poverty, rural

Virginia Brunswick County Southeast %Black/African-American, older, education, poverty, employment, rural, medically underserved

Virginia Caroline County Southeast %Black/African-American, employment, rural, medically underserved

Virginia Gloucester County Southeast Rural

Virginia Goochland County Southeast Rural, medically underserved

Virginia Lunenburg County Southeast %Black/African-American, older, education, poverty, rural, insurance, medically underserved

Virginia Middlesex County Southeast Older, rural, medically underserved

Virginia Nelson County Southeast Older, education, rural

Virginia Nottoway County Southeast %Black/African-American, older, education, poverty, rural, medically underserved

Virginia Orange County Southeast Older, rural, medically underserved

Virginia Patrick County Southeast Older, education, poverty, employment, rural, insurance, medically underserved

Virginia Shenandoah County Southeast Older, rural

Virginia Southampton County Southeast %Black/African-American, education, poverty, rural, medically underserved

Virginia Spotsylvania County Southeast Rural

Virginia Washington County Southeast Older, rural, medically underserved

Virginia Wythe County Southeast Older, education, rural, medically underserved

Washington Cowlitz County Northwest Employment, rural

Washington Douglas County Northwest %Hispanic/Latina, education, rural, insurance, medically underserved

Washington Klickitat County Northwest Poverty, rural, insurance

Washington Pacific County Northwest Older, poverty, rural, insurance, medically underserved

Washington San Juan County Northwest Older, rural, medically underserved

Washington Skagit County Northwest %Hispanic/Latina, rural

West Virginia Barbour County East Central Rural, medically underserved



West Virginia Clay County East Central Education, poverty, rural, medically underserved

West Virginia Hampshire County East Central Rural, insurance, medically underserved

West Virginia Lewis County East Central Rural, medically underserved

West Virginia Mason County East Central Rural, medically underserved

West Virginia Mingo County East Central Education, poverty, employment, rural, medically underserved

West Virginia Monroe County East Central Rural, medically underserved

West Virginia Randolph County East Central Rural

West Virginia Summers County East Central Education, rural, medically underserved

Wisconsin Ashland County North Central %AIAN, poverty, rural

Wisconsin Chippewa County North Central Rural, medically underserved

Wisconsin Lincoln County North Central Older, rural

Wisconsin Oconto County North Central Rural, medically underserved

Wisconsin Pierce County North Central Rural

Wisconsin Shawano County North Central %AIAN, rural, medically underserved

Wisconsin Vilas County North Central %AIAN, older, rural, insurance, medically underserved

Wyoming Big Horn County Northwest Rural, insurance, medically underserved

Wyoming Carbon County Northwest %Hispanic/Latina, rural

Wyoming Teton County Northwest %Hispanic/Latina, rural

Wyoming Uinta County Northwest Rural


Appendix F. HP2020 “Highest Priority” communities with a sustainably larger

population residing in medically underserved areas.



Alabama Geneva County Southeast Education, rural, medically underserved



Alabama Lamar County Southeast Older, education, rural, medically underserved

Alabama Lawrence County Southeast %AIAN, rural, medically underserved


Alabama Marion County Southeast Older, education, rural, medically underserved


Alabama Randolph County Southeast Education, poverty, rural, medically underserved

Alabama Tallapoosa County Southeast Rural, medically underserved

Alabama Winston County Southeast Education, rural, medically underserved


Arkansas Arkansas County South Central %Black/African-American, medically underserved



Arkansas Cleburne County South Central Older, rural, medically underserved


Arkansas Drew County South Central %Black/African-American, employment, medically underserved

Arkansas Izard County South Central Older, rural, medically underserved


Arkansas Lawrence County South Central Education, rural, medically underserved

Arkansas Marion County South Central Older, rural, medically underserved

Arkansas Miller County South Central %Black/African-American, medically underserved


Arkansas Polk County South Central Older, rural, insurance, medically underserved

Arkansas Randolph County South Central Rural, medically underserved

Arkansas Sharp County South Central Older, poverty, rural, medically underserved


California Amador County Southwest Older, employment, rural, medically underserved

California Humboldt County Southwest %AIAN, rural, medically underserved

California Mariposa County Southwest Older, employment, rural, medically underserved

Colorado Denver County Northwest %Black/African-American, %Hispanic/Latina, poverty, foreign, language, medically underserved

Colorado Fremont County Northwest Older, education, rural, medically underserved



Florida Baker County Southeast Education, rural, medically underserved

Florida Dixie County Southeast Education, rural, medically underserved


Florida Osceola County Southeast %Hispanic/Latina, language, medically underserved

Florida Union County Southeast Education, rural, medically underserved

Florida Wakulla County Southeast Rural, medically underserved

Florida Washington County Southeast Education, poverty, rural, medically underserved

Georgia Appling County Southeast Education, poverty, rural, medically underserved

Georgia Berrien County Southeast Education, poverty, rural, medically underserved

Georgia Bryan County Southeast Rural, medically underserved

Georgia Butts County Southeast Education, rural, medically underserved


Georgia Cook County Southeast Education, poverty, rural, medically underserved

Georgia Dawson County Southeast Rural, medically underserved

Georgia Dodge County Southeast Older, education, poverty, rural, medically underserved

Georgia Elbert County Southeast Older, education, poverty, rural, medically underserved

Georgia Fannin County Southeast Older, education, rural, medically underserved

Georgia Franklin County Southeast Older, education, rural, medically underserved

Georgia Henry County Southeast %Black/African-American, medically underserved

Georgia Jasper County Southeast Employment, rural, medically underserved

Georgia Jones County Southeast Rural, medically underserved





Georgia Monroe County Southeast Education, rural, medically underserved

Georgia Murray County Southeast Education, rural, medically underserved

Georgia Oglethorpe County Southeast Education, rural, medically underserved


Georgia Pickens County Southeast Older, rural, medically underserved

Georgia Pierce County Southeast Education, rural, medically underserved

Georgia Polk County Southeast Education, poverty, rural, medically underserved

Georgia Putnam County Southeast Older, rural, medically underserved



Georgia Ware County Southeast Older, poverty, medically underserved




Georgia Wayne County Southeast Education, rural, medically underserved

Georgia White County Southeast Older, rural, medically underserved

Georgia Worth County Southeast Education, poverty, employment, rural, medically underserved

Idaho Gem County Northwest Older, employment, rural, medically underserved


Idaho Payette County Northwest Education, rural, medically underserved

Idaho Shoshone County Northwest Older, education, rural, medically underserved

Illinois Carroll County North Central Older, rural, medically underserved

Illinois Cass County North Central Rural, medically underserved

Illinois Fayette County North Central Rural, medically underserved

Indiana Lake County East Central %Black/African-American, %Hispanic/Latina, medically underserved

Indiana Spencer County East Central Rural, medically underserved

Indiana Washington County East Central Education, rural, medically underserved

Iowa Decatur County North Central Education, poverty, rural, medically underserved

Iowa Keokuk County North Central Older, rural, medically underserved

Kansas Cherokee County North Central %AIAN, rural, medically underserved

Kentucky Caldwell County East Central Rural, medically underserved

Kentucky Casey County East Central Education, poverty, rural, insurance, medically underserved

Kentucky Clay County East Central Education, poverty, employment, rural, medically underserved

Kentucky Garrard County East Central Employment, rural, medically underserved

Kentucky Lawrence County East Central Education, poverty, rural, medically underserved

Kentucky Leslie County East Central Education, poverty, rural, medically underserved

Kentucky Magoffin County East Central Education, poverty, rural, insurance, medically underserved

Kentucky McLean County East Central Rural, medically underserved

Kentucky Scott County East Central Medically underserved

Kentucky Spencer County East Central Rural, medically underserved

Kentucky Wayne County East Central Education, poverty, employment, rural, medically underserved

Louisiana Allen Parish South Central Education, rural, medically underserved

Louisiana Beauregard Parish South Central Rural, medically underserved




Louisiana Evangeline Parish South Central Education, rural, medically underserved

Louisiana Iberia Parish South Central Education, medically underserved


Louisiana Pointe Coupee Parish South Central Rural, medically underserved

Louisiana St. James Parish South Central %Black/African-American, medically underserved




South Central %Black/African-American, medically underserved

Louisiana St. Martin Parish South Central Education, rural, medically underserved

Louisiana Webster Parish South Central Education, rural, medically underserved



Maine Piscataquis County Northeast Rural, medically underserved

Maryland Baltimore City Northeast %Black/African-American, education, poverty, employment, medically underserved

Maryland Calvert County Northeast Rural, medically underserved

Maryland Worcester County Northeast Older, rural, medically underserved

Michigan Arenac County East Central Older, education, rural, medically underserved

Michigan Cheboygan County East Central Older, employment, rural, insurance, medically underserved

Michigan Gratiot County East Central Rural, medically underserved

Michigan Mackinac County East Central %AIAN, older, rural, insurance, medically underserved

Michigan Menominee County East Central Older, rural, medically underserved

Michigan Missaukee County East Central Rural, medically underserved

Michigan Montmorency County East Central Older, education, employment, rural, medically underserved

Michigan Wayne County East Central %Black/African-American, poverty, employment, medically underserved

Minnesota Fillmore County North Central Older, rural, medically underserved

Minnesota Pine County North Central Rural, medically underserved

Mississippi Adams County Southeast %Black/African-American, poverty, medically underserved

Mississippi Bolivar County Southeast %Black/African-American, education, poverty, employment, medically underserved

Mississippi Calhoun County Southeast Education, rural, medically underserved


Mississippi Clay County Southeast %Black/African-American, employment, medically underserved

Mississippi Covington County Southeast Rural, medically underserved

Mississippi George County Southeast Rural, medically underserved

Mississippi Grenada County Southeast Medically underserved


Mississippi Humphreys County Southeast %Black/African-American, education, poverty, employment, medically underserved

Mississippi Itawamba County Southeast Education, rural, medically underserved

Mississippi Jefferson Davis County Southeast %Black/African-American, education, poverty, employment, rural, medically underserved

Mississippi Lawrence County Southeast Rural, medically underserved

Mississippi Leflore County Southeast %Black/African-American, education, poverty, employment, medically underserved

Mississippi Lincoln County Southeast Rural, medically underserved

Mississippi Neshoba County Southeast %AIAN, education, rural, insurance, medically underserved




Mississippi Oktibbeha County Southeast Medically underserved

Mississippi Perry County Southeast Rural, medically underserved

Mississippi Pontotoc County Southeast Education, rural, medically underserved

Mississippi Prentiss County Southeast Education, rural, medically underserved


Mississippi Tippah County Southeast Education, rural, medically underserved

Mississippi Union County Southeast Rural, medically underserved

Mississippi Warren County Southeast %Black/African-American, medically underserved

Mississippi Wayne County Southeast Education, poverty, rural, medically underserved

Mississippi Yalobusha County Southeast Rural, medically underserved

Missouri Camden County North Central Older, rural, medically underserved

Missouri Carter County North Central Education, poverty, rural, insurance, medically underserved

Missouri Chariton County North Central Older, rural, medically underserved

Missouri Dallas County North Central Education, poverty, employment, rural, insurance, medically underserved

Missouri Harrison County North Central Older, rural, medically underserved

Missouri Linn County North Central Older, rural, medically underserved


Missouri Mississippi County North Central %Black/African-American, education, poverty, employment, medically underserved

Missouri New Madrid County North Central Education, poverty, rural, medically underserved


Missouri St. Louis City North Central %Black/African-American, poverty, employment, insurance, medically underserved

Missouri Wayne County North Central Older, education, poverty, rural, medically underserved

Montana Park County Northwest Medically underserved

Montana Rosebud County Northwest %AIAN, employment, rural, medically underserved

Montana Sanders County Northwest Older, poverty, employment, rural, insurance, medically underserved

New Jersey Atlantic County Northeast Rural, medically underserved

New Mexico Eddy County South Central Medically underserved

New Mexico Lincoln County South Central Older, rural, medically underserved


New Mexico Sierra County South Central Older, rural, medically underserved

New Mexico Socorro County South Central Education, poverty, language, rural, medically underserved

New York Wyoming County Northeast Rural, medically underserved

North Carolina Ashe County Southeast Older, education, rural, medically underserved

North Carolina Avery County Southeast Older, rural, insurance, medically underserved

North Carolina Cherokee County Southeast Older, rural, medically underserved

North Carolina Currituck County Southeast Rural, medically underserved

North Carolina Davie County Southeast Rural, medically underserved









North Carolina Mitchell County Southeast Older, rural, medically underserved

North Carolina Pamlico County Southeast Older, rural, medically underserved

North Carolina Rockingham County Southeast Education, rural, medically underserved

North Carolina Rutherford County Southeast Employment, rural, medically underserved


North Dakota Rolette County North Central %AIAN, education, poverty, rural, insurance, medically underserved

Ohio Adams County East Central Education, poverty, employment, rural, medically underserved

Ohio Harrison County East Central Poverty, rural, medically underserved

Ohio Hocking County East Central Rural, medically underserved

Ohio Meigs County East Central Poverty, employment, rural, medically underserved

Ohio Monroe County East Central Rural, medically underserved

Ohio Morgan County East Central Rural, medically underserved

Ohio Perry County East Central Rural, medically underserved

Ohio Putnam County East Central Rural, medically underserved

Oklahoma Hughes County South Central %AIAN, older, education, poverty, rural, medically underserved


Oklahoma Okfuskee County South Central %AIAN, education, poverty, rural, medically underserved

Oregon Crook County Northwest Older, employment, rural, medically underserved

Oregon Curry County Northwest Older, rural, medically underserved

Oregon Tillamook County Northwest Older, rural, medically underserved

Oregon Union County Northwest Rural, medically underserved

Pennsylvania Fayette County Northeast Poverty, rural, medically underserved

Pennsylvania Jefferson County Northeast Rural, medically underserved

Pennsylvania Mifflin County Northeast Education, rural, medically underserved

Pennsylvania Philadelphia County Northeast %Black/African-American, %API, %Hispanic/Latina, education, poverty, employment, foreign, language, insurance, medically underserved

Pennsylvania Schuylkill County Northeast Rural, medically underserved











South Dakota Union County North Central Rural, medically underserved

Tennessee Claiborne County Southeast Education, poverty, rural, medically underserved

Tennessee Clay County Southeast Older, education, rural, insurance, medically underserved

Tennessee Coffee County Southeast Rural, medically underserved

Tennessee Crockett County Southeast Education, rural, medically underserved

Tennessee Grundy County Southeast Education, poverty, rural, medically underserved


Tennessee Macon County Southeast Education, poverty, rural, insurance, medically underserved

Tennessee Marion County Southeast Education, rural, medically underserved

Tennessee Overton County Southeast Education, rural, medically underserved

Tennessee Rhea County Southeast Education, employment, rural, medically underserved

Tennessee Roane County Southeast Older, rural, medically underserved

Tennessee Trousdale County Southeast Rural, medically underserved

Tennessee Union County Southeast Education, rural, medically underserved

Tennessee Wayne County Southeast Education, employment, rural, medically underserved

Texas Austin County South Central Older, rural, medically underserved


Texas Bosque County South Central Older, rural, medically underserved



Texas Chambers County South Central Rural, medically underserved

Texas Comanche County South Central Older, poverty, rural, insurance, medically underserved

Texas Eastland County South Central Older, rural, medically underserved



Texas Hutchinson County South Central Rural, medically underserved

Texas Jones County South Central Older, education, rural, medically underserved


Texas Lavaca County South Central Older, rural, medically underserved

Texas Lee County South Central Older, rural, medically underserved



Texas Leon County South Central Older, rural, medically underserved

Texas Liberty County South Central Education, employment, rural, medically underserved



Texas Nolan County South Central Older, rural, medically underserved

Texas Reeves County South Central %Hispanic/Latina, education, poverty, employment, language, medically underserved

Texas Sabine County South Central Older, rural, medically underserved

Texas Trinity County South Central Older, rural, medically underserved



Texas Wilson County South Central Rural, medically underserved

Texas Young County South Central Older, rural, medically underserved

Utah Sanpete County Northwest Rural, medically underserved

Virginia Amelia County Southeast Education, rural, insurance, medically underserved



Virginia Danville City Southeast %Black/African-American, older, education, poverty, employment, medically underserved

Virginia Goochland County Southeast Rural, medically underserved


Virginia Middlesex County Southeast Older, rural, medically underserved


Virginia Orange County Southeast Older, rural, medically underserved

Virginia Patrick County Southeast Older, education, poverty, employment, rural, insurance, medically underserved

Virginia Radford City Southeast Poverty, employment, medically underserved

Virginia Roanoke City Southeast %Black/African-American, education, poverty, medically underserved


Virginia Stafford County Southeast Medically underserved

Virginia Washington County Southeast Older, rural, medically underserved

Virginia Wythe County Southeast Older, education, rural, medically underserved

Washington Asotin County Northwest Older, medically underserved


Washington Pacific County Northwest Older, poverty, rural, insurance, medically underserved

Washington San Juan County Northwest Older, rural, medically underserved

West Virginia Barbour County East Central Rural, medically underserved

West Virginia Clay County East Central Education, poverty, rural, medically underserved

West Virginia Hampshire County East Central Rural, insurance, medically underserved



West Virginia Lewis County East Central Rural, medically underserved

West Virginia Mason County East Central Rural, medically underserved

West Virginia Mingo County East Central Education, poverty, employment, rural, medically underserved

West Virginia Monroe County East Central Rural, medically underserved

West Virginia Summers County East Central Education, rural, medically underserved

Wisconsin Chippewa County North Central Rural, medically underserved

Wisconsin Oconto County North Central Rural, medically underserved

Wisconsin Shawano County North Central %AIAN, rural, medically underserved

Wisconsin Vilas County North Central %AIAN, older, rural, insurance, medically underserved

Wyoming Big Horn County Northwest Rural, insurance, medically underserved


Appendix G. HP2020 “Highest Priority” communities with a sustainably larger

Black/African-American female population


Alabama Barbour County Southeast %Black/African-American, education, poverty, employment, rural




Alabama Jefferson County Southeast %Black/African-American


Alabama Montgomery County Southeast %Black/African-American


Alabama Pike County Southeast %Black/African-American, poverty, rural

Arkansas Arkansas County South Central %Black/African-American, medically underserved




Arkansas Drew County South Central %Black/African-American, employment, medically underserved

Arkansas Miller County South Central %Black/African-American, medically underserved




Florida Duval County Southeast %Black/African-American

Georgia Clayton County Southeast %Black/African-American, employment, foreign

Georgia Crisp County Southeast %Black/African-American, education, poverty, rural

Georgia DeKalb County Southeast %Black/African-American, foreign

Georgia Dougherty County Southeast %Black/African-American, poverty, employment

Georgia Fulton County Southeast %Black/African-American

Georgia Henry County Southeast %Black/African-American, medically underserved





Georgia Muscogee County Southeast %Black/African-American








Kansas Wyandotte County North Central %Black/African-American, %Hispanic/Latina, education, poverty, employment, foreign, language, insurance

Louisiana Caddo Parish South Central %Black/African-American





Louisiana Orleans Parish South Central %Black/African-American, poverty, employment

Louisiana St. James Parish South Central %Black/African-American, medically underserved





Maryland Baltimore City Northeast %Black/African-American, education, poverty, employment, medically underserved

Maryland Charles County Northeast %Black/African-American, rural

Michigan Wayne County East Central %Black/African-American, poverty, employment, medically underserved

Mississippi Adams County Southeast %Black/African-American, poverty, medically underserved

Mississippi Bolivar County Southeast %Black/African-American, education, poverty, employment, medically underserved


Mississippi Clay County Southeast %Black/African-American, employment, medically underserved


Mississippi Humphreys County Southeast %Black/African-American, education, poverty, employment, medically underserved

Mississippi Jefferson Davis County

Southeast %Black/African-American, education, poverty, employment, rural, medically underserved

Mississippi Leflore County Southeast %Black/African-American, education, poverty, employment, medically underserved


Mississippi Warren County Southeast %Black/African-American, medically underserved

Missouri Jackson County North Central %Black/African-American

Missouri Mississippi County North Central %Black/African-American, education, poverty, employment, medically underserved

Missouri St. Louis City North Central %Black/African-American, poverty, employment, insurance, medically underserved

Missouri St. Louis County North Central %Black/African-American

New Jersey Camden County Northeast %Black/African-American

North Carolina Chowan County Southeast %Black/African-American, older, education, poverty, rural










Ohio Hamilton County East Central %Black/African-American

Oklahoma Oklahoma County South Central %Black/African-American, %Hispanic/Latina

Pennsylvania Delaware County Northeast %Black/African-American

Pennsylvania Philadelphia County Northeast

%Black/African-American, %API, %Hispanic/Latina, education, poverty, employment, foreign, language, insurance, medically underserved










Texas Jefferson County South Central %Black/African-American






Virginia Chesapeake City Southeast %Black/African-American

Virginia Danville City Southeast %Black/African-American, older, education, poverty, employment, medically underserved

Virginia Henrico County Southeast %Black/African-American

Virginia Hopewell City Southeast %Black/African-American, education, poverty, employment


Virginia Lynchburg City Southeast %Black/African-American, poverty, employment

Virginia Newport News City Southeast %Black/African-American




Virginia Portsmouth City Southeast %Black/African-American, poverty

Virginia Roanoke City Southeast %Black/African-American, education, poverty, medically underserved



Appendix H. HP2020 “Highest Priority” communities with a sustainably larger

Hispanic/Latina female population





California Colusa County Southwest %Hispanic/Latina, education, employment, language, rural

California San Bernardino County Southwest %Hispanic/Latina

Colorado Adams County Northwest %Hispanic/Latina, education, foreign, language


Colorado Otero County Northwest %Hispanic/Latina, older, education, poverty, employment, rural


Florida Osceola County Southeast %Hispanic/Latina, language, medically underserved


Idaho Bingham County Northwest %AIAN, %Hispanic/Latina, rural

Idaho Cassia County Northwest %Hispanic/Latina, education, language, rural



Iowa Buena Vista County North Central %API, %Hispanic/Latina, education, foreign, language, rural

Kansas Wyandotte County North Central %Black/African-American, %Hispanic/Latina, education, poverty, employment, foreign, language, insurance

Louisiana Jefferson Parish South Central %Hispanic/Latina, foreign




Nebraska Dawson County North Central %Hispanic/Latina, education, foreign, language, insurance


North Carolina

Lee County Southeast %Hispanic/Latina, language, rural

North Dakota

Walsh County North Central %Hispanic/Latina, older, education, rural

Ohio Lorain County East Central %Hispanic/Latina

Oklahoma Jackson County South Central %Hispanic/Latina


Oklahoma Oklahoma County South Central %Black/African-American, %Hispanic/Latina

Oklahoma Texas County South Central %Hispanic/Latina, education, foreign, language, rural, insurance



Pennsylvania Philadelphia County Northeast %Black/African-American, %API, %Hispanic/Latina, education, poverty, employment, foreign, language, insurance, medically underserved








Texas Moore County South Central %Hispanic/Latina, education, foreign, language

Texas Reeves County South Central %Hispanic/Latina, education, poverty, employment, language, medically underserved

Virginia Alexandria City National Capital %Hispanic/Latina, foreign, language

Virginia Winchester City Southeast %Hispanic/Latina, poverty

Washington Benton County Northwest %Hispanic/Latina


Washington Skagit County Northwest %Hispanic/Latina, rural

Wyoming Carbon County Northwest %Hispanic/Latina, rural

Wyoming Teton County Northwest %Hispanic/Latina, rural


Appendix I. Komen Regional Healthy People 2020 priority classifications

Komen Northeast Region Healthy People 2020 Priority Map


Komen Southeast Region Healthy People 2020 Priority Map


Komen East Central Region Healthy People 2020 Priority Map


Komen North Central Region Healthy People 2020 Priority Map


Komen South Central Region Healthy People 2020 Priority Map


Komen Northwest Region Healthy People 2020 Priority Map


Komen Southwest Region Healthy People 2020 Priority Map


Komen National Capital Region Healthy People 2020 Priority Map


Appendix J. Breast cancer services available within the U.S. and the HP2020

“Highest Priority” communities

“Highest Priority” State



Alabama 122 369 50 125 19 52 Alaska 27 181 8 15 6 9 Arizona 8 343 2 156 2 31 Arkansas 52 261 10 50 8 35 California 104 2,118 50 859 10 214 Colorado 74 310 25 123 18 76 Connecticut NA 225 NA 115 NA 30 Delaware 13 64 7 35 2 7 District of Columbia 0 197 0 120 0 34 Florida 105 1,083 51 617 15 160 Georgia 195 599 87 248 31 83 Hawaii 77 110 34 40 10 14 Idaho 24 147 10 52 5 32 Illinois 33 748 17 359 9 136 Indiana 60 327 39 198 19 86 Iowa 31 257 21 147 14 87 Kansas 28 271 13 125 5 47 Kentucky 78 402 29 154 12 53 Louisiana 168 396 62 159 24 63 Maine 5 107 1 39 0 20 Maryland 96 311 38 160 20 50 Massachusetts 2 345 1 199 0 62 Michigan 110 541 56 302 29 108 Minnesota 8 340 6 218 2 76 Mississippi 105 401 15 96 3 22 Missouri 112 397 65 176 36 83 Montana 29 155 11 48 3 22 Nebraska 11 162 6 97 3 48 Nevada 9 100 7 69 2 21 New Hampshire NA 71 NA 30 NA 24 New Jersey 54 260 24 107 6 63 New Mexico 34 210 6 36 2 21 New York 57 1060 25 576 6 145 North Carolina 87 555 32 268 16 81 North Dakota 24 102 17 64 6 23 Ohio 180 650 96 369 34 132 Oklahoma 126 335 67 137 12 22 Oregon 21 301 7 111 4 43 Pennsylvania 140 719 34 280 21 112 Rhode Island NA 76 NA 43 NA 12 South Carolina 56 312 11 69 3 33 South Dakota 17 142 9 54 4 14 Tennessee 40 490 14 209 3 46 Texas 77 972 34 498 19 222 Utah 26 134 10 55 3 18 Vermont 7 80 2 16 2 13 Virginia 142 481 73 233 22 66 Washington 42 459 17 191 8 53 West Virginia 45 287 10 73 3 19 Wisconsin 33 331 20 238 7 88 Wyoming 14 64 5 24 3 12 United States 2,908 19,358 1,234 8,782 491 3,023

* Data represents information gathered through an internet search in 2014. Therefore, not all services in a community may be

represented.

NA- Not applicable- State did not have any “Highest Priority” communities.

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