Deborah B Ehrenthal1,2, Hsiang-Hui Daphne Kuo3, Russell S Kirby4. 1. Departments of Obstetrics and Gynecology and ehrenthal@wisc.edu. 2. Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin; and. 3. Departments of Obstetrics and Gynecology and. 4. College of Public Health, University of South Florida, Tampa, Florida.
Abstract
BACKGROUND AND OBJECTIVES: Rural counties have the highest infant mortality rates across the United States when compared with rates in more urban counties. We use a social-ecological framework to explain infant mortality disparities across the rural-urban continuum. METHODS: We created a cohort of all births in the United States linked to infant death records for 2014 to 2016. Records were linked to county-level data from the Area Health Resources File and the American Community Survey and classified using the National Center for Health Statistics Urban-Rural Classification Scheme. Using multilevel generalized linear models, we investigated the association of infant mortality with county urban-rural classification, considering county health system resources and measures of socioeconomic advantage, net of individual-level characteristics, and controlling for US region and county centroid. RESULTS: Infant mortality rates were highest in noncore (odds ratio [OR] = 1.32, 95% confidence interval [CI]: 1.26-1.39) and micropolitan counties (OR = 1.26, 95% CI: 1.20-1.32) when compared with large metropolitan fringe counties, controlling for geospatial measures. Inclusion of county health system characteristics did little to attenuate the greater odds of infant mortality in rural counties. Instead, a composite measure of county-level socioeconomic advantage was highly protective (adjusted OR = 0.84; 95% CI: 0.82-0.86) and eliminated any difference between the micropolitan and noncore counties and the large metropolitan fringe counties. CONCLUSIONS: Higher infant mortality rates in rural counties are best explained by their greater socioeconomic disadvantage than more-limited access to health care or the greater prevalence of mothers' individual health risks.
BACKGROUND AND OBJECTIVES: Rural counties have the highest infant mortality rates across the United States when compared with rates in more urban counties. We use a social-ecological framework to explain infant mortality disparities across the rural-urban continuum. METHODS: We created a cohort of all births in the United States linked to infant death records for 2014 to 2016. Records were linked to county-level data from the Area Health Resources File and the American Community Survey and classified using the National Center for Health Statistics Urban-Rural Classification Scheme. Using multilevel generalized linear models, we investigated the association of infant mortality with county urban-rural classification, considering county health system resources and measures of socioeconomic advantage, net of individual-level characteristics, and controlling for US region and county centroid. RESULTS: Infant mortality rates were highest in noncore (odds ratio [OR] = 1.32, 95% confidence interval [CI]: 1.26-1.39) and micropolitan counties (OR = 1.26, 95% CI: 1.20-1.32) when compared with large metropolitan fringe counties, controlling for geospatial measures. Inclusion of county health system characteristics did little to attenuate the greater odds of infant mortality in rural counties. Instead, a composite measure of county-level socioeconomic advantage was highly protective (adjusted OR = 0.84; 95% CI: 0.82-0.86) and eliminated any difference between the micropolitan and noncore counties and the large metropolitan fringe counties. CONCLUSIONS: Higher infant mortality rates in rural counties are best explained by their greater socioeconomic disadvantage than more-limited access to health care or the greater prevalence of mothers' individual health risks.
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Authors: Sara C Handley; Molly Passarella; Heidi M Herrick; Julia D Interrante; Scott A Lorch; Katy B Kozhimannil; Ciaran S Phibbs; Elizabeth E Foglia Journal: JAMA Netw Open Date: 2021-10-01