• Nasim B Ferdows, María P Aranda, Julie A Baldwin, Soroosh Baghban Ferdows, Jasjit S Ahluwalia, and Amit Kumar.
• Department of Health Administration and Policy, Hudson College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City.
• JAMA Netw Open. 2020 Aug 3; 3 (8): e2012241.

ImportancePopulation-based mortality rates are important indicators of overall health status. Mortality rates may reflect underlying disparities in access to health care, quality of care, racial and geographical variations, and other socioeconomic factors associated with health. However, there is limited information on historical trends in mortality rates between older Black and White adults living in urban compared with rural communities.ObjectiveTo examine historical trends of mortality rates among White adults compared with Black adults and among rural residents compared with urban residents by comparing sex-specific age-adjusted all-cause mortality rates between older adults of both races who reside in rural and urban counties in the US.Design, Setting, And ParticipantsIn this county-level cross-sectional longitudinal study of US counties from January 1, 1968, to December 31, 2016, mortality data were obtained from the CDC WONDER database of the Centers for Disease Control and Prevention, and socioeconomic characteristics were obtained from the Area Health Resources Files of the US Health Resources and Services Administration. The study population included older adults (≥65 years) of Black and White ancestry living in 3131 rural and urban counties in the US. Using ordinary least squares regression analyses, race- and sex-specific trends in mortality rates with 95% CIs were examined, and trends adjusted by county-level socioeconomic characteristics using year and county fixed-effects were calculated. Data were analyzed from March 24 to May 10, 2020.ExposuresThree geographic regions were examined: urban counties, rural counties adjacent to an urban county (rural-adjacent counties), and rural counties not adjacent to an urban county (rural-nonadjacent counties).Main Outcomes And MeasuresAll-cause age-adjusted mortality rates of Black and White adults 65 years and older.ResultsFor 1968, a total of 3076 counties (19 240 437 adults ≥65 years; 11 100 000 women [57.69%]; 1 484 747 Black individuals [7.74%]) were identified; of those, 1138 counties were urban, 1018 counties were rural adjacent, and 922 counties were rural nonadjacent. For 2016, a total of 3087 counties (46 400 000 adults ≥65 years; 25 800 000 women [55.72%]; 4 447 733 Black individuals [9.60%]) were identified; of those, 1163 counties were urban, 1020 counties were rural adjacent, and 904 counties were rural nonadjacent. Between 1968 and 2016, mortality rates per 100 000 persons decreased from 9063 to 4896 deaths (46%) among White men and from 6175 to 3760 deaths (39%) among White women. During the same period, mortality rates decreased from 8801 to 5477 deaths (38%) among Black men and from 6380 to 3960 deaths (38%) among Black women. However, the racial mortality gap increased among men living in rural counties after 1980. From 1968 to 2016, the mortality rate among White men decreased from 9063 to 4751 deaths (48%) in urban counties, from 9113 to 5338 deaths (41%) in rural-adjacent counties, and from 8971 to 5229 deaths (42%) in rural-nonadjacent counties. The mortality rate among Black men during the same period decreased from 8715 to 5368 deaths (38%) in urban counties, from 8924 to 6458 deaths (28%) in rural-adjacent counties, and from 9500 to 6941 deaths (27%) in rural-nonadjacent counties.Conclusions And RelevanceRural and urban socioeconomic differences were associated with mortality rate disparities among both White and Black women. However, rural vs urban disparities in mortality rates among men remained significant, especially among Black men living in rural counties. Notably, the current mortality rate of Black men living in rural areas is similar to that of White men living in urban and rural areas in the mid-1980s. Understanding the intersectional factors associated with health disparities may help to inform public health and clinical interventions.

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