Abstract A104: EpiTracker Cancer: A new webtool to visualize disparities in cancer death rates across demographics and county-level characteristics

Abstract There are known disparities in cancer death rates in the U.S. by demographic, geographic and socioeconomic factors. While there are several widely available webtools to visualize U.S. cancer death rates, none allow for direct comparison of cancer death rates across county-level measures of social determinants of health. The National Cancer Institute has developed a new webtool, EpiTracker Cancer (https://episphere.github.io/epitracker), to allow for customizable visualization of cancer death rates across geography, demographics and county-level characteristics. Cancer death data and decedent race (i.e., American Indian and Alaska Native, Asian, Black, Native Hawaiian and Pacific Islander, White), ethnicity (Hispanic, non-Hispanic), sex, age and county of residence were ascertained from the National Center for Health Statistics (NCHS) death certificate data for 2018-2022. Counts and rates based on <10 deaths are suppressed per NCHS policy. Population data were abstracted from the U.S. Census. County-level characteristics were derived from multiple sources, and include metrics of socioeconomic status (e.g., median income, proportion with a college degree), health status (e.g., proportion who smoke, proportion who are obese), and healthcare access and utilization (e.g., proportion uninsured, proportion of women who have had a mammogram). EpiTracker Cancer is comprised of three main pages, each featuring a different type of visualization. The first page displays bar charts of age-standardized or crude death rates by cancer type, sex, race, ethnicity and age group. The second displays maps of cancer death rates at the county, state and national level. Users can generate national, state and county-level maps for each cause of cancer death that can be compared by race, ethnicity and sex, and can control how outlying rates are handled. The final visualization plots cancer death rates across quartiles, quintiles or deciles of county- level characteristics. The user can choose to display rate ratios comparing to either the highest or lowest quantile of the county-level metric. As an example, a user could visualize the association between county-level education, measured by the fraction of adults with at least some college education, and lung cancer mortality. Compared to counties in the highest quintile of educational attainment, those in the lowest quintile have lung cancer age-adjusted death rates that are 1.77- times (95%CI 1.72-1.82) higher among men and 1.56-times (95%CI 1.51-1.61) higher in women. Future iterations will include more county-level variables, death rates over time and additional visualizations, as well as user suggested improvements and innovations. Citation Format: Meredith Shiels, Lee Mason, Jonas Almeida, Sahar Behpour, Neal Freedman, Peter Kraft, Wayne Lawrence. EpiTracker Cancer: A new webtool to visualize disparities in cancer death rates across demographics and county-level characteristics [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr A104.

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Journal
Cancer Epidemiology Biomarkers & Prevention
Published
2024-09-21
DOI
https://doi.org/10.1158/1538-7755.disp24-a104
Primary Topic
Social Media in Health Education
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article
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article

Abstract A104: EpiTracker Cancer: A new webtool to visualize disparities in cancer death rates across demographics and county-level characteristics

Jonas S. Almeida, Meredith S. Shiels, Peter Kraft, Lee Mason et al.
Cancer Epidemiology Biomarkers & Prevention
Social Media in Health Education
article

Abstract A104: EpiTracker Cancer: A new webtool to visualize disparities in cancer death rates across demographics and county-level characteristics

Jonas S. Almeida, Meredith S. Shiels, Peter Kraft, Lee Mason, Wayne R. Lawrence, Neal D. Freedman, Sahar Behpour
article en

Abstract

Abstract There are known disparities in cancer death rates in the U.S. by demographic, geographic and socioeconomic factors. While there are several widely available webtools to visualize U.S. cancer death rates, none allow for direct comparison of cancer death rates across county-level measures of social determinants of health. The National Cancer Institute has developed a new webtool, EpiTracker Cancer (https://episphere.github.io/epitracker), to allow for customizable visualization of cancer death rates across geography, demographics and county-level characteristics. Cancer death data and decedent race (i.e., American Indian and Alaska Native, Asian, Black, Native Hawaiian and Pacific Islander, White), ethnicity (Hispanic, non-Hispanic), sex, age and county of residence were ascertained from the National Center for Health Statistics (NCHS) death certificate data for 2018-2022. Counts and rates based on <10 deaths are suppressed per NCHS policy. Population data were abstracted from the U.S. Census. County-level characteristics were derived from multiple sources, and include metrics of socioeconomic status (e.g., median income, proportion with a college degree), health status (e.g., proportion who smoke, proportion who are obese), and healthcare access and utilization (e.g., proportion uninsured, proportion of women who have had a mammogram). EpiTracker Cancer is comprised of three main pages, each featuring a different type of visualization. The first page displays bar charts of age-standardized or crude death rates by cancer type, sex, race, ethnicity and age group. The second displays maps of cancer death rates at the county, state and national level. Users can generate national, state and county-level maps for each cause of cancer death that can be compared by race, ethnicity and sex, and can control how outlying rates are handled. The final visualization plots cancer death rates across quartiles, quintiles or deciles of county- level characteristics. The user can choose to display rate ratios comparing to either the highest or lowest quantile of the county-level metric. As an example, a user could visualize the association between county-level education, measured by the fraction of adults with at least some college education, and lung cancer mortality. Compared to counties in the highest quintile of educational attainment, those in the lowest quintile have lung cancer age-adjusted death rates that are 1.77- times (95%CI 1.72-1.82) higher among men and 1.56-times (95%CI 1.51-1.61) higher in women. Future iterations will include more county-level variables, death rates over time and additional visualizations, as well as user suggested improvements and innovations. Citation Format: Meredith Shiels, Lee Mason, Jonas Almeida, Sahar Behpour, Neal Freedman, Peter Kraft, Wayne Lawrence. EpiTracker Cancer: A new webtool to visualize disparities in cancer death rates across demographics and county-level characteristics [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr A104.

Cancer Epidemiology Biomarkers & PreventionVol. 33(9_Supplement)
Deloitte (United States) (US), National Cancer Institute (US)
No poverty
Openalex Percentile: Top 80%
Social Media in Health Education
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