Literature DB >> 31728900

Neighborhood Physical Disorder and Adverse Pregnancy Outcomes among Women in Chicago: a Cross-Sectional Analysis of Electronic Health Record Data.

Stephanie L Mayne1,2, Bernard F Pellissier3, Kiarri N Kershaw3.   

Abstract

Adverse pregnancy outcomes increase infants' risk for mortality and future health problems. Neighborhood physical disorder may contribute to adverse pregnancy outcomes by increasing maternal chronic stress. Google Street View technology presents a novel method for assessing neighborhood physical disorder but has not been previously examined in the context of birth outcomes. In this cross-sectional study, trained raters used Google's Street View imagery to virtually audit a randomly sampled block within each Chicago census tract (n = 809) for nine indicators of physical disorder. We used an item-response theory model and spatial interpolation to calculate tract-level neighborhood physical disorder scores across Chicago. We linked these data with geocoded electronic health record data from a large, academic women's hospital in Chicago (2015-2017, n = 14,309 births). We used three-level hierarchical Poisson regression to estimate prevalence ratios for the associations of neighborhood physical disorder with preterm birth (overall and spontaneous), small for gestational age (SGA), and hypertensive disorder of pregnancy (HDP). After adjustment for maternal sociodemographics, multiparity, and season of birth, living in a neighborhood with high physical disorder was associated with higher prevalence of PTB, SGA, and HDP (prevalence ratios and 95% confidence intervals 1.21 (1.06, 1.39) for PTB, 1.13 (1.01, 1.37) for SGA, and 1.23 (1.07, 1.42) for HDP). Adjustment for neighborhood poverty and maternal health conditions (e.g., hypertension, diabetes, asthma, substance use) attenuated associations. Results suggest that an adverse neighborhood physical environment may contribute to adverse pregnancy outcomes. However, future work is needed to disentangle the unique contribution of physical disorder from other characteristics of disadvantaged neighborhoods.

Entities:  

Keywords:  Electronic health records; Neighborhood physical disorder; Pregnancy outcomes; Premature birth

Year:  2019        PMID: 31728900      PMCID: PMC6904761          DOI: 10.1007/s11524-019-00401-0

Source DB:  PubMed          Journal:  J Urban Health        ISSN: 1099-3460            Impact factor:   3.671


  53 in total

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Authors:  Christine Dunkel Schetter
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4.  Validation of a Google Street View-Based Neighborhood Disorder Observational Scale.

Authors:  Miriam Marco; Enrique Gracia; Manuel Martín-Fernández; Antonio López-Quílez
Journal:  J Urban Health       Date:  2017-04       Impact factor: 3.671

5.  Neighborhood factors associated with physical activity and adequacy of weight gain during pregnancy.

Authors:  Barbara Laraia; Lynne Messer; Kelly Evenson; Jay S Kaufman
Journal:  J Urban Health       Date:  2007-08-21       Impact factor: 3.671

6.  Neighborhood social cohesion and disorder in relation to walking in community-dwelling older adults: a multilevel analysis.

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Journal:  J Aging Health       Date:  2009-02

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Journal:  Int J Epidemiol       Date:  2002-12       Impact factor: 7.196

8.  Street Audits to Measure Neighborhood Disorder: Virtual or In-Person?

Authors:  Stephen J Mooney; Michael D M Bader; Gina S Lovasi; Julien O Teitler; Karestan C Koenen; Allison E Aiello; Sandro Galea; Emily Goldmann; Daniel M Sheehan; Andrew G Rundle
Journal:  Am J Epidemiol       Date:  2017-08-01       Impact factor: 4.897

9.  Assessing environmental features related to mental health: a reliability study of visual streetscape images.

Authors:  Yu-Tzu Wu; Paul Nash; Linda E Barnes; Thais Minett; Fiona E Matthews; Andy Jones; Carol Brayne
Journal:  BMC Public Health       Date:  2014-10-22       Impact factor: 3.295

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Authors:  Lindsey A Knake; Monika Ahuja; Erin L McDonald; Kelli K Ryckman; Nancy Weathers; Todd Burstain; John M Dagle; Jeffrey C Murray; Prakash Nadkarni
Journal:  BMC Pediatr       Date:  2016-04-29       Impact factor: 2.125

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