Neighborhood-based differences in walkability, physical activity, and weight status in India

被引:26
作者
Adlakha, Deepti [1 ]
Hipp, J. Aaron [2 ]
Brownson, Ross C. [1 ,3 ,4 ]
机构
[1] Queens Univ Belfast, Sch Med Dent & Biomed Sci, Ctr Publ Hlth, Belfast BT7 1NN, Antrim, North Ireland
[2] North Carolina State Univ, Ctr Human Hlth & Environm, Ctr Geospatial Analyt, Dept Pk Recreat & Tourism Management, Raleigh, NC 27695 USA
[3] Washington Univ, Brown Sch, Prevent Res Ctr St Louis, Div Publ Hlth Sci, St Louis, MO 63130 USA
[4] Washington Univ, Sch Med, Siteman Canc Ctr, St Louis, MO 63130 USA
关键词
India; Walkability; Physical activity; Sedentary behavior; Body mass index; Non-communicable diseases; BUILT ENVIRONMENT; LAND-USE; EMERGING TECHNOLOGIES; DIABETES-MELLITUS; AIR-POLLUTION; URBAN DESIGN; HEALTH; OBESITY; ADULTS; SCALE;
D O I
10.1016/j.jth.2016.10.008
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Introduction: Data on built environment (BE) and physical activity (PA) in low-and middle-income countries is sparse. This study compared BE features, PA levels, and weight status among adults living in neighborhoods stratified by walkability and socio-economic status (SES) in the city of Chennai, India. Methods: This cross sectional study design surveyed 370 adults (>= 18 years) from four neighborhoods with differing walkability and socio-economic status. Participants were asked to complete a survey on their neighborhood environment, leisure and travel PA, height, weight, and demographic characteristics. One-way analysis of variance tests were used to examine differences across neighborhoods. Results: Residents of high-walkability/high-SES neighborhoods reported higher land use mix diversity, land use mix access, street connectivity, aesthetics, and safety from crime. Residential density and walking/bicycling infrastructure were highest in the high-walkability/low-SES neighborhood. Transport PA was the maximum contributor to total PA in low-SES neighborhoods, while residents of high-SES neighborhoods reported greater levels of leisure-time PA. Sitting time and BMI were greater among high-SES participants. Patterns of PA, sedentary time, and weight status varied significantly by neighborhood walkability and SES. Conclusions: An understanding of BE correlates of domain-specific PA can support the development of contextually tailored interventions to promote physical activity and reverse the determinants of inactivity occurring through patterns of urbanization and sedentary behaviors in India. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:485 / 499
页数:15
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