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      Neighborhood Self-Selection: The Role of Pre-Move Health Factors on the Built and Socioeconomic Environment

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          Abstract

          Residential self-selection bias is a concern in studies of neighborhoods and health. This bias results from health behaviors predicting neighborhood choice. To quantify this bias, we examined associations between pre-move health factors (body mass index, walking, and total physical activity) and post-move neighborhood factors (County Sprawl Index, Census tract socioeconomic status (SES)) in the Nurses’ Health Study (n = 14,159 moves from 1986–2008). Individuals in the highest quartile of pre-move BMI (BMI > 28.4) compared to the lowest quartile (BMI < 22.5) moved to counties that averaged 2.57 points lower on the sprawl index (95% confidence interval −3.55, −1.59) indicating that individuals moved to less dense counties; however, no associations were observed for pre-move walking nor total physical activity. Individuals with higher pre-move BMI tended to move to Census tracts with lower median income and home values and higher levels of poverty. Analyses examining the change in neighborhood environments after a move demonstrated that healthy pre-move behaviors were associated with moves to worse socioeconomic environments. This type of self-selection would bias results downward, underestimating the true relationship between SES and physical activity. Generally, the magnitudes of associations between pre-move health factors and neighborhood measures were small and indicated that residential self-selection was not a major source of bias in analyses in this population.

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          Most cited references28

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          Neighborhoods and health.

          Features of neighborhoods or residential environments may affect health and contribute to social and race/ethnic inequalities in health. The study of neighborhood health effects has grown exponentially over the past 15 years. This chapter summarizes key work in this area with a particular focus on chronic disease outcomes (specifically obesity and related risk factors) and mental health (specifically depression and depressive symptoms). Empirical work is classified into two main eras: studies that use census proxies and studies that directly measure neighborhood attributes using a variety of approaches. Key conceptual and methodological challenges in studying neighborhood health effects are reviewed. Existing gaps in knowledge and promising new directions in the field are highlighted.
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            Compendium of physical activities: classification of energy costs of human physical activities.

            A coding scheme is presented for classifying physical activity by rate of energy expenditure, i.e., by intensity. Energy cost was established by a review of published and unpublished data. This coding scheme employs five digits that classify activity by purpose (i.e., sports, occupation, self-care), the specific type of activity, and its intensity as the ratio of work metabolic rate to resting metabolic rate (METs). Energy expenditure in kilocalories or kilocalories per kilogram body weight can be estimated for all activities, specific activities, or activity types. General use of this coding system would enhance the comparability of results across studies using self reports of physical activity.
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              Travel and the Built Environment: A Synthesis

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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Int J Environ Res Public Health
                Int J Environ Res Public Health
                ijerph
                International Journal of Environmental Research and Public Health
                MDPI
                1661-7827
                1660-4601
                08 October 2015
                October 2015
                : 12
                : 10
                : 12489-12504
                Affiliations
                [1 ]Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA 02215, USA; E-Mail: francine.laden@ 123456channing.harvard.edu
                [2 ]Department of Environmental Health, Harvard TH Chan School of Public Health, Boston, MA 02115, USA; E-Mails: jaime.hart@ 123456channing.harvard.edu (J.E.H.); francine.laden@ 123456channing.harvard.edu (F.L.)
                [3 ]Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02215, USA; E-Mail: hpdif@ 123456channing.harvard.edu
                [4 ]Department of Social and Behavioral Sciences, Harvard TH Chan School of Public Health, Boston, MA 02115, USA; E-Mails: marcaya@ 123456hsph.harvard.edu (M.C.A); svsubram@ 123456hsph.harvard.edu (S.V.S.)
                Author notes
                [* ]Author to whom correspondence should be addressed; E-Mail: pjames@ 123456hsph.harvard.edu ; Tel.: +1-617-525-2567; Fax: +1-617-525-2578.
                Article
                ijerph-12-12489
                10.3390/ijerph121012489
                4626981
                26457712
                cec9ca00-91c4-410e-82ac-9c1221c13328
                © 2015 by the authors; licensee MDPI, Basel, Switzerland.

                This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 30 June 2015
                : 23 September 2015
                Categories
                Article

                Public health
                residential self-selection,built environment,socioeconomic status,body mass index,physical activity

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