ArticleMaternal and child health journal2022
An Exploratory Spatiotemporal Analysis of Socio-Environmental Patterns in Severe Maternal Morbidity.
Article in Maternal and child health journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- A Spatial Analytic Approach to Maternal Health Following Hurricane Florence (2018).Maternal and child health journal · 2026Article
- Temperature extremes and maternal health: differential risks of severe maternal morbidity during heatwaves and coldwaves in North Carolina.International journal of biometeorology · 2026Article
- Mapping high-risk clusters and identifying place-based risk factors of mental health burden in pregnancy.SSM. Mental health · 2023Article
- Severe maternal morbidity by race and ethnicity before vs. during the COVID-19 pandemic.Annals of epidemiology · 2023Article
- Analysis of Heat Exposure During Pregnancy and Severe Maternal Morbidity.JAMA network open · 2023Article
- Investigating the impact of structural racism on black birthing people - associations between racialized economic segregation, incarceration inequality, and severe maternal morbidity.Social science & medicine (1982) · 2023Article
- Relationship Between Neighborhood Socioeconomic Disadvantage and Severe Maternal Morbidity and Maternal Mortality.Ethnicity & disease · 2022Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesSevere Maternal Morbidity (SMM) is a group of pregnancy complications in which a woman nearly dies. Despite its increasing prevalence, little research has evaluated geographic patterns of SMM and the underlying social determinants that influence excess risk. This study examined the spatial clustering of SMM across South Carolina, US, and its associations with place-based social and environmental factors.
methodsHospitalized deliveries from 2012 to 2017 were analyzed using Kulldorff's spatial scan statistic to locate areas with abnormally high rates of SMM. SMM patients inside and outside risk clusters were compared using Generalized Estimating Equations (GEE) to determine underlying individual and community-level risk factors.
resultsGEE models revealed that the odds of living in a high-risk SMM21 (SMM including blood transfusions) cluster was 2.49 times higher among Black patients (p < .001) compared to those outside of a high-risk cluster. Women residing in a high-risk SMM20 (SMM excluding blood transfusions) cluster were 1.38 times more likely to experience the most number of extremely hot days and 1.70 times more likely to present with obesity than women in a low-risk SMM cluster (p < .001).
conclusionsThis study is the first to characterize the geographic clustering of SMM risk in the US. Our geospatial approach contributes a novel understanding to factors which influence SMM beyond patient-level characteristics and identifies the impact of hot ambient temperature on maternal morbidity. Findings address an important literature gap surrounding place-based risk factors by explaining the contextual social and built environmental factors that drive SMM risk.
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