ArticleSSM. Mental health2023
Mapping high-risk clusters and identifying place-based risk factors of mental health burden in pregnancy.
Article in SSM. Mental health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
8 citing papers in PubMed, 7 citations in OpenAlex.
- Geospatial clustering of suicide, mental health, sociodemographic and workforce features in Australia.Social psychiatry and psychiatric epidemiology · 2026Article
- 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
- Spatial patterns and determinants of anxiety, depressive symptoms and their co-occurrence among currently married women of reproductive age in Bangladesh.Global mental health (Cambridge, England) · 2026Article
- Effects of Sociospatial Inequality on Exposure to Stress, Symptoms of Depression, and Cortisol Rhythms in Pregnancy.Journal of obstetric, gynecologic, and neonatal nursing : JOGNN · 2025Observational
- A small area analysis of acute exposure to temperatures and mental health in North Carolina.International journal of biometeorology · 2025Article
- Mapping maternity care deserts: Driving distance and health outcomes in North Carolina.The Journal of rural health : official journal of the American Rural Health Association and the National Rural Health Care Association · 2025Article
- Mental health disparities among maternal populations following heatwave exposure in North Carolina (2011-2019): a matched analysis.Lancet regional health. Americas · 2025Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
Purpose: Despite affecting up to 20% of women and being the leading cause of preventable deaths during the perinatal and postpartum period, maternal mental health conditions are chronically understudied. This study is the first to identify spatial patterns in perinatal mental health conditions, and relate these patterns to place-based social and environmental factors that drive cluster development. Methods: We performed spatial clustering analysis of emergency department (ED) visits for perinatal mood and anxiety disorders (PMAD), severe mental illness (SMI), and maternal mental disorders of pregnancy (MDP) using the Poisson model in SatScan from 2016 to 2019 in North Carolina. Logistic regression was used to examine the association between patient and community-level factors and high-risk clusters. Results: The most significant spatial clustering for all three outcomes was concentrated in smaller urban areas in the western, central piedmont, and coastal plains regions of the state, with odds ratios greater than 3 for some cluster locations. Individual factors (e.g., age, race, ethnicity) and contextual factors (e.g., racial and socioeconomic segregation, urbanity) were associated with high risk clusters. Conclusions: Results provide important contextual and spatial information concerning at-risk populations with a high burden of maternal mental health disorders and can better inform targeted locations for the expansion of maternal mental health services.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.