title: Greenness and Birth Outcomes in a Range of Pennsylvania Communities.
abstract: Living in communities with more vegetation during pregnancy has been associated with higher birth weights, but fewer studies have evaluated other birth outcomes, and only one has been conducted in the Eastern United States, in regions with a broad range, including high levels, of greenness. We evaluated associations between prenatal residential greenness and birth outcomes (term birth weight, small for gestational age, preterm birth, and low 5 min Apgar score) across a range of community types using electronic health record data from 2006-2013 from the Geisinger Health System in Pennsylvania. We assigned greenness based on mother's geocoded address using the normalized difference vegetation index from satellite imagery. We used propensity scores to restrict the study population to comparable groups among those living in green vs. less-green areas. Analyses were adjusted for demographic, clinical, and environmental covariates, and stratified by community type (city, borough, and township). In cities, higher greenness (tertiles 2-3 vs. 1) was protective for both preterm (OR = 0.78, 95% CI: 0.61-0.99) and small for gestational age birth (OR = 0.73, 95% CI: 0.58-0.97), but not birth weight or Apgar score. We did not observe associations between greenness and birth outcomes in adjusted models in boroughs or townships. These results add to the evidence that greener cities might be healthier cities.
authors.affiliation: Robert Wood Johnson Foundation Health and Society Scholars Program, UC San Francisco and UC Berkeley, CA 94704, USA. joanacasey@berkeley.edu.
authors.forename: Joan A
authors.initials: JA
authors.lastname: Casey
authors.affiliation: Departments of Epidemiology and Environmental Health, Harvard TH Chan School of Public Health, Boston, MA 02215, USA. pjames@hsph.harvard.edu.
authors.forename: Peter
authors.initials: P
authors.lastname: James
authors.affiliation: Robert Wood Johnson Foundation Health and Society Scholars Program, UC San Francisco and UC Berkeley, CA 94704, USA. Kara.Rudolph@ucsf.edu.
authors.forename: Kara E
authors.initials: KE
authors.lastname: Rudolph
authors.affiliation: Department of Forestry and Natural Resources, National Chiayi University, Chiayi City 60004, Taiwan. wu@hsph.harvard.edu.
authors.forename: Chih-Da
authors.initials: CD
authors.lastname: Wu
authors.affiliation: Departments of Environmental Health Sciences and Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA. bschwar1@jhu.edu.|Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA. bschwar1@jhu.edu.|Center for Health Research, Geisinger Health System, Danville, PA 17822, USA. bschwar1@jhu.edu.
authors.forename: Brian S
authors.initials: BS
authors.lastname: Schwartz
mesh_terms: D000328:Adult; D001724:Birth Weight; D002947:Cities / Q000706:statistics & numerical data*; D004777:Environment; D005260:Female; D006801:Humans; D007231:Infant, Newborn; D008297:Male; D010414:Pennsylvania; D011247:Pregnancy; D011256:Pregnancy Outcome / Q000523:psychology*; D037841:Pregnant People / Q000523:psychology*; D011788:Quality of Life / Q000523:psychology*; D012111:Residence Characteristics; D055815:Young Adult
keywords: greenness; low birth weight; machine learning; pregnancy outcome; preterm birth; propensity score; small for gestational age