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

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          Abstract

          <div class="section"> <a class="named-anchor" id="S1"> <!-- named anchor --> </a> <h5 class="section-title" id="d1138336e167">Background</h5> <p id="P1">Recent studies have linked urban environmental factors and body mass index (BMI); however, such factors are often examined in isolation, ignoring correlations across exposures. </p> </div><div class="section"> <a class="named-anchor" id="S2"> <!-- named anchor --> </a> <h5 class="section-title" id="d1138336e172">Methods</h5> <p id="P2">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 PM <sub>2.5</sub> predictions and weighted monthly average concentrations of NO <sub>2</sub> from up to five nearest monitors) and self-reported BMI using generalized additive models, allowing for deviations from linearity using penalized splines. </p> </div><div class="section"> <a class="named-anchor" id="S3"> <!-- named anchor --> </a> <h5 class="section-title" id="d1138336e183">Results</h5> <p id="P3">Among 23,435 women aged 60–87 years, we observed non-linear associations between walkability and BMI, and PM <sub>2.5</sub> 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 non-linear and non-monotonic. Increasing walkability was associated with increasing BMI at lower levels of walkability (walkability index &lt;1.8), while increasing walkability was linked to lower BMI in areas of higher walkability (walkability index &gt;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 (&lt;71 years old). </p> </div><div class="section"> <a class="named-anchor" id="S4"> <!-- named anchor --> </a> <h5 class="section-title" id="d1138336e191">Conclusions</h5> <p id="P4">Neighborhood walkability was non-linearly linked to lower BMI independent of air pollution and greenness. Our findings highlight the importance of accounting for non-linear confounding by interrelated urban environmental factors when investigating associations between the environment and BMI. </p> </div>

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          Most cited references35

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          Role of built environments in physical activity, obesity, and cardiovascular disease.

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            A Review of the Health Benefits of Greenness.

            Researchers are increasingly exploring how neighborhood greenness, or vegetation, may affect health behaviors and outcomes. Greenness may influence health by promoting physical activity and social contact; decreasing stress; and mitigating air pollution, noise, and heat exposure. Greenness is generally measured using satellite-based vegetation indices or land-use databases linked to participants' addresses. In this review, we found fairly strong evidence for a positive association between greenness and physical activity, and a less consistent negative association between greenness and body weight. Research suggests greenness is protective against adverse mental health outcomes, cardiovascular disease, and mortality, though most studies were limited by cross-sectional or ecological design. There is consistent evidence that greenness exposure during pregnancy is positively associated with birth weight, though findings for other birth outcomes are less conclusive. Future research should follow subjects prospectively, differentiate between greenness quantity and quality, and identify mediators and effect modifiers of greenness-health associations.
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              The built environment and obesity: a systematic review of the epidemiologic evidence.

              We completed a systematic search of the epidemiologic literature on built environment and obesity and identified 63 relevant papers, which were then evaluated for the quality of between-study evidence. We were able to classify studies into one of two primary approaches for defining place and corresponding geographic areas of influence: those based on contextual effects derived from shared pre-determined administrative units and those based on individually unique geographic buffers. The 22 contextual papers evaluated 80 relations, 38 of which did not achieve statistical significance. The 15 buffer papers evaluated 40 relations, 24 of which did not achieve statistical significance. There was very little between-study similarity in methods in both types of approaches, which prevented estimation of pooled effects. The great heterogeneity across studies limits what can be learned from this body of evidence. Copyright 2009 Elsevier Ltd. All rights reserved.
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                Author and article information

                Journal
                Epidemiology
                Epidemiology
                Ovid Technologies (Wolters Kluwer Health)
                1044-3983
                2017
                November 2017
                : 28
                : 6
                : 780-788
                Article
                10.1097/EDE.0000000000000724
                5617802
                28767514
                c1b1807f-f19d-44c6-9dfa-1737c10d9e9a
                © 2017
                History

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