BACKGROUND: Disabilities are not evenly distributed across geography or age, yet few studies on disability have considered these factors. The purpose of this study was to explore rural-urban differences in disability rates, particularly related to gender and race, and what other rural-urban disparities help explain these differences. METHODS: Utilizing the 2008-2016 Current Population Survey (CPS), we first examined rural and urban disability trends by gender and race, estimating means and rural-urban percentage differences for men and women by race and conducting t test analysis to test group differences by age cohort (eg, comparing white, non-Hispanic, rural 15- to 24-year-old women to white, non-Hispanic, urban 15- to 24-year-old women). We then conducted a logistic regression to explore whether or not the effects of rurality on disability rates could be explained by rural-urban differences in demographic and socioeconomic characteristics. RESULTS: Descriptively, rural people report disability at higher rates than urban people across nearly all age category, gender, and racial combinations. These differences are more pronounced for nonwhite respondents in middle to older age categories. Additionally, while some of the rural disability disparity can be explained by adding demographic and socioeconomic variables to the logistic regression model, the effect of rurality remains significant. CONCLUSIONS: Our findings suggest that when researchers, policy makers, and service providers are addressing rural and urban differences in health and well-being, self-reported disability is another factor to consider. Future work should be mindful of how disability and space intersect with gender and race, creating significant disparities for people of color in rural places.
BACKGROUND: Disabilities are not evenly distributed across geography or age, yet few studies on disability have considered these factors. The purpose of this study was to explore rural-urban differences in disability rates, particularly related to gender and race, and what other rural-urban disparities help explain these differences. METHODS: Utilizing the 2008-2016 Current Population Survey (CPS), we first examined rural and urban disability trends by gender and race, estimating means and rural-urban percentage differences for men and women by race and conducting t test analysis to test group differences by age cohort (eg, comparing white, non-Hispanic, rural 15- to 24-year-old women to white, non-Hispanic, urban 15- to 24-year-old women). We then conducted a logistic regression to explore whether or not the effects of rurality on disability rates could be explained by rural-urban differences in demographic and socioeconomic characteristics. RESULTS: Descriptively, rural people report disability at higher rates than urban people across nearly all age category, gender, and racial combinations. These differences are more pronounced for nonwhite respondents in middle to older age categories. Additionally, while some of the rural disability disparity can be explained by adding demographic and socioeconomic variables to the logistic regression model, the effect of rurality remains significant. CONCLUSIONS: Our findings suggest that when researchers, policy makers, and service providers are addressing rural and urban differences in health and well-being, self-reported disability is another factor to consider. Future work should be mindful of how disability and space intersect with gender and race, creating significant disparities for people of color in rural places.
Authors: Carolyn J Presley; Nicole A Arrato; Peter G Shields; David P Carbone; Melisa L Wong; Jason Benedict; Sarah A Reisinger; Ling Han; Thomas M Gill; Heather Allore; Barbara L Andersen; Sarah Janse Journal: JTO Clin Res Rep Date: 2022-05-17
Authors: Carolyn J Presley; Nicole A Arrato; Sarah Janse; Peter G Shields; David P Carbone; Melisa L Wong; Ling Han; Thomas M Gill; Heather G Allore; Barbara L Andersen Journal: JCO Oncol Pract Date: 2021-05-03
Authors: Shyang-Woei Lin; Tzu-Ying Chiu; Tsan-Hon Liou; Chia-Feng Yen; Hui-Guan Chen Journal: Int J Environ Res Public Health Date: 2020-10-17 Impact factor: 3.390