Uncovering Patterns for Adverse Pregnancy Outcomes with Spatial Analysis: Evidence from Philadelphia

Autor:	Balocchi, Cecilia, Bai, Ray, Liu, Jessica, Canelón, Silvia P., George, Edward I., Chen, Yong, Boland, Mary R.
Rok vydání:	2021
Předmět:	Methodology (stat.ME) FOS: Computer and information sciences population characteristics Applications (stat.AP) social sciences Statistics - Applications Statistics - Methodology
DOI:	10.48550/arxiv.2105.04981
Popis:	We introduce a spatial model for analyzing patient-specific and neighborhood risks of stillbirth and preterm birth in Philadelphia. Using electronic health records and census tract data, we find that both patient-level characteristics (e.g. self-identified race/ethnicity) and neighborhood-level characteristics (e.g. violent crime) are associated with patients' odds of stillbirth or preterm birth. Census tracts with higher rates of women in poverty or on public assistance have greater neighborhood risk for these outcomes, whereas census tracts with higher rates of college-educated women or women in the labor force have lower risk. Our findings could be useful for targeted individual and neighborhood interventions. Comment: 27 pages, 7 figures, 9 tables
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c179778c54e23777fc357485fdc603fa Zobrazit plný text záznamu