Diabetes Risk Factors and Rurality

The purpose of this analysis is to compare diabetes rates, age, and rurality for each county and state.

According to the Centers for Disease Control and Prevention (CDC), the percentage of individuals with Type II diabetes is approximately 11.6%, with 22.8% of adults with diabetes undiagnosed. The prevalence of diabetes increases with age. Over one in four adults (29.2%) adults over 65 years old have diabetes. Diabetes prevalence varies across counties in the United States and has been linked to socioeconomic factors such as education level, family income, and population size. For both men and women, the prevalence of diabetes was higher among adults living in nonmetropolitan areas compared to those in metropolitan areas (CDC, 2024). Trends suggest that diabetes-related hospital deaths have been linked to place-based disparities (Dugani et al., 2021). Studies have also reported significantly higher mortality rates associated with diabetes in areas experiencing shortages of health care providers (Ferdinand et al., 2018). While trends indicating a decrease in the mortality rate for diabetes may be evident in urbanized areas, the rate of diabetes mortality remains largely unchanged in rural areas (Dugani et al., 2021).

This analysis aims to compare diabetes rates and age across counties and states in the U.S. The data can reveal how diabetes prevalence and mortality are related to geographic and demographic factors and provide insights for health policy and practice to address the disparities and challenges in diabetes care.

This data is also available as an Excel spreadsheet.

Diabetes2024.xlsx (664.49 KB)

Data Sources
Data Definitions

This data represents the most current publicly available information sources that are commonly used to study health care trends. The data is derived from the data sources listed below and combined to support the analysis.

County Health Ranking s (data released 2024)
Dartmouth Health Atlas - Medicare Reimbursements/Enrollee (data released 2020)

A blank entry indicates unreported data. A value of zero is a defined value and does not represent unreported data.

FIPS: The federal information processing standard (FIPS) code for the geographic location.

State Abbreviation: The abbreviated name of the state where the county is located.

Name: The name of the county.

Population Size: The total number of individuals residing in the county. This data is derived from the Census Population Estimates from 2022.

Medicare Enrollees: The total number of Medicare beneficiaries age 65-99 in the county for 2019 enrolled in both Medicare Parts A and B. Patients enrolled in risk-bearing health maintenance organizations (HMOs) are excluded.

Medicare Reimbursements/Enrollee: The average Medicare reimbursement for 100% of the claims for each county in 2019.

Diabetes Rate: The percentage of the county’s population that have diabetes. The measure is provided by the CDC Diabetes Interactive Atlas from 2021.

Child Poverty Rate: The percentage of children in the population who fall below the poverty level obtained from Small Area Income Poverty Estimates (SAIPE) in 2022.

Percent Asian: The proportion of the county’s population that falls into the racial or ethnic category of Asian from the US Census Bureau Population Estimates from 2022.

Percent Black: The proportion of the county’s population that falls into the racial or ethnic category of Black from the US Census Bureau Population Estimates from 2022.

Percent Hispanic: The proportion of the county’s population that falls into the racial or ethnic category of Hispanic from the US Census Bureau Population Estimates from 2022.

Percent Native Hawaiian or Other Pacific Islander: The proportion of the county’s population that falls into the racial or ethnic category of Native Hawaiian or Other Pacific Islander from the US Census Bureau Population Estimates from 2022.

Percent Native American: The proportion of the county’s population that falls into the racial or ethnic category of Native American from the US Census Bureau Population Estimates from 2022.

Percent White: The proportion of the county’s population that falls into the racial or ethnic category of White from the US Census Bureau Population Estimates from 2022.

Percent Age 65 and Older: The proportion of the county’s population that falls into the age category of 65 years old and older from the US Census Bureau Population Estimates from 2022.

Percent Age <18: The proportion of the county’s population that falls into the age category of less than 18 years old from the US Census Bureau Population Estimates from 2022.

HS Diploma: The estimated number of individuals in the county with a high school (HS) diploma from the US Department of Education EDFacts data from 2020-2021.

Uninsured Rate: The estimated percentage of individuals in the county under age 65 without health insurance. Data is from the Small Area Health Insurance Estimates Program (SAHIE) from 2021.

Percent Unemployed: The estimated percentage of individuals in the county who had no employment, were available for work and had made specific efforts to find employment. The number is from the annual US Bureau of Labor Statistics’ Labor Force Data in 2022.

Primary Care Physicians: The number of primary care providers per 100,000 population. The data is derived from the Small Area Resource File and the American Medical Association from 2021.

% Rural: The percentage of the county population living in a census-defined rural area.

Population Type: The population type is determined based on the population size of a specific county. The population types include metro, nonmetro cities, and nonmetro towns. These types are adapted from the rural-urban commuting area codes (RUCA) and core-based statistical areas (CBSA) definitions of rural and urban. The population types for counties are defined as follows:

Metro - A population of 50,000 or more
Nonmetro cities - A population between 2,500 and less than 50,000
Nonmetro towns - A population of less than 2,500

Tutorial Video

In this tutorial video, we look at Diabetes Risk Factors and Rurality data. The video guides you through how to use Tableau data analysis to compare diabetes rates and population age for each county and state.