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Exploring Neighborhood Environments and Active Commuting in Chennai, India

Author

Listed:
  • Deepti Adlakha

    (School of Natural and Built Environment, Queen’s University Belfast BT9 5AG, UK)

  • J. Aaron Hipp

    (Department of Parks, Recreation, and Tourism Management, Centre for Geospatial Analytics, Centre for Human Health and the Environment, North Carolina State University, Raleigh, NC 27695-8004, USA)

  • James F. Sallis

    (Department of Family Medicine and Public Health, University of California, San Diego, CA 92161, USA
    Department of Family Medicine and Public Health, Australian Catholic University, Melbourne, VIC 3065, Australia)

  • Ross C. Brownson

    (Prevention Research Centre in St. Louis, Brown School, Washington University in St. Louis, St. Louis, MO 63130, USA
    Department of Surgery (Division of Public Health Sciences) and Alvin J. Siteman Cancer Centre, School of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA)

Abstract

Few studies assess built environment correlates of active commuting in low-and-middle-income countries (LMICs), but the different context could yield distinct findings. Policies and investments to promote active commuting remain under-developed in LMICs like India, which grapples with traffic congestion, lack of activity-supportive infrastructure, poor enforcement of traffic rules and regulations, air pollution, and overcrowding. This cross-sectional study investigated associations between home neighborhood environment characteristics and active commuting in Chennai, India. Adults (N = 370, 47.2% female, mean age = 37.9 years) were recruited from 155 wards in the metropolitan area of Chennai in southern India between January and June 2015. Participants self-reported their usual mode of commute to work, with responses recoded into three categories: (1) multi-modal or active commuting (walking and bicycling; n = 56); (2) public transit (n = 52); and (3) private transport (n = 111). Environmental attributes around participants’ homes were assessed using the Neighborhood Environment Walkability Scale for India (NEWS-India). Associations between environmental characteristics and likelihood of active commuting and public transit use were modeled using logistic regression with private transport (driving alone or carpool) as the reference category, adjusting for age, gender, and household car ownership. Consistent with other international studies, participants living in neighborhoods with a mix of land uses and a transit stop within a 10-minute walk from home were more likely to use active commuting (both p < 0.01). Land-use mix was significantly associated with the use of public transit compared to private transport (adjusted odds ratio (aOR) = 5.2, p = 0.002). Contrary to findings in high-income countries, the odds of active commuting were reduced with improved safety from crime (aOR = 0.2, p = 0.003), aesthetics (aOR = 0.2, p = 0.05), and street connectivity (aOR = 0.2, p = 0.003). Different environmental attributes were associated with active commuting, suggesting that these relationships are complex and may distinctly differ from those in high-income countries. Unexpected inverse associations of perceived safety from crime and aesthetics with active commuting emphasize the need for high-quality epidemiologic studies with greater context specificity in the study of physical activity in LMICs. Findings have public health implications for India and suggest that caution should be taken when translating evidence across countries.

Suggested Citation

  • Deepti Adlakha & J. Aaron Hipp & James F. Sallis & Ross C. Brownson, 2018. "Exploring Neighborhood Environments and Active Commuting in Chennai, India," IJERPH, MDPI, vol. 15(9), pages 1-15, August.
  • Handle: RePEc:gam:jijerp:v:15:y:2018:i:9:p:1840-:d:165894
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    References listed on IDEAS

    as
    1. Saelens, B.E. & Sallis, J.F. & Black, J.B. & Chen, D., 2003. "Neighborhood-Based Differences in Physical Activity: An Environment Scale Evaluation," American Journal of Public Health, American Public Health Association, vol. 93(9), pages 1552-1558.
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    3. Torres, A. & Sarmiento, O.L. & Stauber, C. & Zarama, R., 2013. "The ciclovia and cicloruta programs: Promising interventions to promote physical activity and social capital in bogotá, Colombia," American Journal of Public Health, American Public Health Association, vol. 103(2), pages 23-30.
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    5. Mario Azevedo & Cora Araújo & Felipe Reichert & Fernando Siqueira & Marcelo Silva & Pedro Hallal, 2007. "Gender differences in leisure-time physical activity," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 52(1), pages 8-15, February.
    6. Deepti Adlakha & J. Aaron Hipp & Ross C. Brownson, 2016. "Adaptation and Evaluation of the Neighborhood Environment Walkability Scale in India (NEWS-India)," IJERPH, MDPI, vol. 13(4), pages 1-24, April.
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    Cited by:

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    2. Peter Congdon, 2019. "Obesity and Urban Environments," IJERPH, MDPI, vol. 16(3), pages 1-6, February.
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    4. Hossain Mohiuddin & Md Musfiqur Rahman Bhuiya & Shaila Jamal & Zhi Chen, 2022. "Exploring the Choice of Bicycling and Walking in Rajshahi, Bangladesh: An Application of Integrated Choice and Latent Variable (ICLV) Models," Sustainability, MDPI, vol. 14(22), pages 1-20, November.

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