Cancer Risk Factors and Rurality

This analysis aims to identify the factors that influence the risk and survival of cancer and how where you live affects your access to and quality of cancer care.

People who live in rural areas are more likely to die from cancer than people who live in urban areas. In fact, in 2017, rural areas had higher death rates from cancer than urban areas for all types of cancer except lung cancer (Yaemsiri et al., 2019). One of the reasons for this difference is that rural cancer patients have more challenges in getting the care they need. They often have to travel far to see a doctor or get treatment, and they have fewer opportunities to join clinical trials that could offer them new or better therapies (Zahnd & Ganai, 2019).

Another important consideration is that telehealth could be a solution to improving the care and support of rural cancer survivors. Telehealth is the use of technology such as phone, video, or internet to provide health services remotely. Telehealth could help rural cancer survivors stay in touch with their health care providers, receive follow-up care, and access psychosocial support after their treatment is over (DeGuzman et al., 2020). However, telehealth also faces some barriers in rural areas, such as limited broadband internet access, which could affect the quality and reliability of the service (DeGuzman et al., 2020).

Other factors that can affect the risk and survival of cancer patients are financial hardship, race, and health behaviors. For example, people who have low income, no insurance, or belong to racial or ethnic minorities may have less access to preventive care, screening, diagnosis, and treatment for cancer. They may also face more discrimination, stigma, or stress that could worsen their health outcomes (Hastert et al., 2019). Moreover, people who smoke, drink alcohol, eat unhealthy food, or do not exercise regularly may increase their chances of getting cancer or having complications from it.

This analysis shows that cancer is a major public health problem that affects different regions and populations differently. It also suggests that improving access to health care and promoting healthy behaviors could help prevent and treat cancer and save lives. By understanding the causes and consequences of cancer, we can take action to improve the health and well-being of our communities.

This data is available in a spreadsheet format:

Cancer Risk Factors and Rurality Demographics 2023 (Excel) (755.97 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.

Centers for Disease Control and Prevention (CDC) PLACES Data (data released July 2023)
County Health Rankings (data released 2023)
Health Resources and Services Administration (HRSA) Area Health Resources File (data released 2022)

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

State: The abbreviation of the state.

County: The name of the county. County names are listed as provided on the U.S. Census Bureau's list of 2020 FIPS Codes for Counties and County Equivalent Entities.

Population Size: The total number of individuals residing in the county. The data is derived from the Census Population Estimates from 2021.

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

Percent Uninsured: The estimated number of individuals in the county under age 65 without health insurance. Data is from the Small Area Health Insurance Estimates (SAHIE) Program from 2020.

Child Poverty Rate: The percentage of children under age 18 living in poverty. Poverty status is defined by family; either everyone in the family is in poverty or no one in the family is in poverty. Data is from the Small Area Income Poverty Estimates (SAIPE) in 2021.

Premature Age-Adjusted Mortality per 100,000: Number of deaths among residents under age 75 per 100,000 population (age-adjusted). The reporting period for this measure is 2018 through 2020 from CDC WONDER mortality data.

Child Mortality: Number of deaths among residents under age 18 per 100,000 population. The 2023 County Health Rankings used data from 2017-2020 for this measure.

Infant Mortality: Number of infant deaths (within one year) per 1,000 live births. The 2023 County Health Rankings used data from 2014-2020 for this measure.

Uninsured Adults: Percentage of adults under age 65 without health insurance. The 2023 County Health Rankings used data from 2020 for this measure.

Uninsured Children: Percentage of children under age 19 without health insurance. The 2023 County Health Rankings used data from 2020 for this measure.

Access to Broadband: Percentage of households with a broadband internet connection (e.g. cable, DSL, fiber-optic, cell phone, or satellite) through a subscription. The measure is provided by the American Community Survey (ACS) and includes data collected between 2017 and 2021.

Visits to Doctor: Percentage of respondents greater than 18 years old who report having been to a doctor for a routine checkup (e.g., a general physical exam, not an exam for a specific injury, illness, condition) in the previous year. Data is from the Behavioral Risk Factor Surveillance System (BRFSS).

Percent Cancer: Percentage of respondents aged ≥18 years who report ever having been told by a doctor, nurse, or other health professional that they have cancer, besides skin cancer. The measure is provided by the BRFSS survey. Data is only provided for counties with more than 50 respondents to the BRFSS survey and is from 2020.

Percent Men Preventative Screenings: Percentage of men aged ≥65 years reporting having received all of the following: an influenza vaccination in the past year; a pneumococcal vaccination (PPV) ever; and either a fecal occult blood test (FOBT) within the past year, a sigmoidoscopy within the past 5 years and a FOBT within the past 3 years, or a colonoscopy within the past 10 years. The measure is provided by the BRFSS survey. Data is only provided for counties with more than 50 respondents to the BRFSS survey and is from 2020.

Percent Women Preventative Screenings: Percentage of women aged ≥65 years reporting having received all of the following: an influenza vaccination in the past year; a PPV ever; either a FOBT within the past year, a sigmoidoscopy within the past 5 years and a FOBT within the past 3 years, or a colonoscopy within the previous 10 years; and a mammogram in the past 2 years. The measure is provided by the BRFSS survey. Data is only provided for counties with more than 50 respondents to the BRFSS survey and is from 2020.

Percent Smoking: Percentage of respondents aged ≥18 years who report having smoked ≥100 cigarettes in their lifetime and currently smoke every day or some days. The measure is provided by the BRFSS survey. Data is only provided for counties with more than 50 respondents to the BRFSS survey and is from 2020.

Percent Asian: The proportion of the county’s population that falls into the racial or ethnic category of Asian from the U.S. Census Bureau Population Estimates from 2021.

Percent Black: The proportion of the county’s population that falls into the racial or ethnic category of Black from the U.S. Census Bureau Population Estimates from 2021.

Percent Hispanic: The proportion of the county’s population that falls into the racial or ethnic category of Hispanic from the U.S. Census Bureau Population Estimates from 2021.

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 U.S. Census Bureau Population Estimates from 2021.

Percent Native American: The proportion of the county’s population that falls into the racial or ethnic category of Native American from the U.S. Census Bureau Population Estimates from 2021.

Percent White: The proportion of the county’s population that falls into the racial or ethnic category of White from the U.S. Census Bureau Population Estimates from 2021.

Tutorial Video

In this tutorial video, we look at Cancer Risk Factors and Rurality. The video guides you through how to use Tableau data analysis to compare the incidence of cancer to risk factors and geographic characteristics.