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  • Title: Neighborhood Deprivation and Severe Maternal Morbidity in a Medicaid Population.
    Author: Yu X, Johnson JE, Roman LA, Key K, McCoy White J, Bolder H, Raffo JE, Meng R, Nelson H, Meghea CI.
    Journal: Am J Prev Med; 2024 May; 66(5):850-859. PubMed ID: 37995948.
    Abstract:
    INTRODUCTION: Few studies have examined whether neighborhood deprivation is associated with severe maternal morbidity (SMM) in already socioeconomically disadvantaged populations. Little is known about to what extent neighborhood deprivation accounts for Black-White disparities in SMM. This study investigated these questions among a statewide Medicaid-insured population, a low-income population with heightened risk of SMM. METHODS: Data were from Michigan statewide linked birth records and Medicaid claims between 01/01/2016 and 12/31/2019, and were analyzed between 2022 and 2023. Neighborhood deprivation was measured with the Area Deprivation Index at census block group and categorized as low, medium, or high deprivation. Multilevel logistic models were used to examine the association between neighborhood deprivation and SMM. Fairlie nonlinear decomposition was conducted to quantify the contribution of neighborhood deprivation to SMM racial disparity. RESULTS: People in the most deprived neighborhoods had higher odds of SMM than those in the least deprived neighborhoods (aOR [95% CI]: 1.27 [1.15, 1.40]). Such association was observed in Black (aOR [95% CI]: 1.34 [1.07, 1.67]) and White (aOR [95% CI]: 1.26 [1.12, 1.42]) racial subgroups. Decomposition showed that of 57.5 (cases per 10,000) explained disparity in SMM, neighborhood deprivation accounted for 23.1 (cases per 10,000; 95% CI: 16.3, 30.0) or two-fifths (40.2%) of the Black-White disparity. Analysis on SMM excluding blood transfusion showed consistent but weaker results. CONCLUSIONS: Neighborhood deprivation may be used as an effective tool to identify at-risk individuals within a low-income population. Community-engaged interventions aiming at improving neighborhood conditions may be helpful to reduce both SMM prevalence and racial inequity in SMM.
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