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Interrelationships Between Walkability, Air Pollution, Greenness, and Body Mass Index

James, Petera,b,c; Kioumourtzoglou, Marianthi-Annad; Hart, Jaime E.b,c; Banay, Rachel F.b; Kloog, Itaie; Laden, Francinea,b,c

doi: 10.1097/EDE.0000000000000724
Built Environment

Background: Recent studies have linked urban environmental factors and body mass index (BMI); however, such factors are often examined in isolation, ignoring correlations across exposures.

Methods: Using data on Nurses’ Health Study participants living in the Northeastern United States in 2006, we estimated associations between neighborhood walkability (a composite of population density, street connectivity, and business access), greenness (from satellite imagery), and ambient air pollution (from satellite-based spatiotemporally resolved PM2.5 predictions and weighted monthly average concentrations of NO2 from up to five nearest monitors) and self-reported BMI using generalized additive models, allowing for deviations from linearity using penalized splines.

Results: Among 23,435 women aged 60–87 years, we observed nonlinear associations between walkability and BMI and between PM2.5 and BMI in single-exposure models adjusted for age, race, and individual- and area-level socioeconomic status. When modeling all exposures simultaneously, only the association between walkability and BMI remained nonlinear and nonmonotonic. Increasing walkability was associated with increasing BMI at lower levels of walkability (walkability index <1.8), while increasing walkability was linked to lower BMI in areas of higher walkability (walkability index >1.8). A 10 percentile increase in walkability, right above 1.8 was associated with a 0.84% decrease in log BMI. The relationship between walkability and BMI existed only among younger participants (<71 years old).

Conclusions: Neighborhood walkability was nonlinearly linked to lower BMI independent of air pollution and greenness. Our findings highlight the importance of accounting for nonlinear confounding by interrelated urban environmental factors when investigating associations between the environment and BMI.

Supplemental Digital Content is available in the text.

From the aDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA; bDepartment of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA; cChanning Division of Network Medicine, Department of Medicine, Brigham & Women’s Hospital and Harvard Medical School, Boston, MA; dDepartment of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY; and eThe Department of Geography and Environmental Development, Ben-Gurion University of the Negev, Beer Sheva, Israel.

Submitted 16 August 2016; accepted 25 July 2017.

The authors report no conflicts of interests.

Supported by training grants HL 098048 and NIH T32 ES007069 and NIH Grants K99 CA201542, P01 CA87969, R01 ES017017, P30 ES000002, and UM1 CA186107.

These data contain identifiable protected health information (participant addresses) and are, therefore, not made readily available. However, de-identified data sets may be available upon request. Code is available upon request.

Supplemental digital content is available through direct URL citations in the HTML and PDF versions of this article (www.epidem.com).

Correspondence: Peter James, 401 Park Drive, Suite 401, Boston, MA 02215. E-mail: pjames@hsph.harvard.edu.

Copyright © 2017 Wolters Kluwer Health, Inc. All rights reserved.