Assessing the influence of the density of built neighborhood features on body mass index among an urban Swiss cohort Pubblico

Abstract

Previous research done in Lausanne, Switzerland found persistent spatial clusters of high body mass index (BMI) over a 5 year period. Reasons for this spatial dependency of BMI have not been investigated. The spatial distribution of neighborhood destinations (shops, food outlets, open spaces) may be related to BMI. Kernel density estimation (KDE) is a spatial analysis technique that accounts for spatial variation in the density of environmental features. Using KDE, this study investigated the association between living in an area of low density of neighborhood destinations and elevated individual-level BMI. Data comes from the 6,481 individuals from CoLaus study cohort at baseline and 4,460 individuals at follow-up. Destinations were geocoded, and kernel density estimates of destination intensity were created using kernels of 200, 400, 800 and 1200 m. Using multilevel linear regression, the association between destination intensity (classified in quintiles 1 (least)-5 (most)) and individual BMI was estimated at baseline visit and 5 year follow-up. At baseline, higher density of neighborhood destinations was associated with higher raw and adjusted BMI at the 200m and 800m kernel sizes. However, the opposite effect was observed at the 400m kernel size. In the second wave of data collection five years later, the observed associations at baseline do not hold. These inconclusive results suggest that proximity to parks, open spaces, shops, food outlets and other services may not be a strong predictor BMI in Lausanne. Future research should investigate other neighborhood level factors that can explain spatial dependence of BMI.

Table of Contents

Contents

Introduction ..............................................................................................................................................1
Background and Literature Review .................................................................................................................3
Methods .................................................................................................................................................13
Results ...................................................................................................................................................19
Discussion................................................................................................................................................22
Conclusion ...............................................................................................................................................25

References ..............................................................................................................................................26
Tables .....................................................................................................................................................31
Figures. ...................................................................................................................................................40
Appendices ..............................................................................................................................................48

About this Master's Thesis

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School	Rollins School of Public Health
Department	Epidemiology
Degree	MPH
Submission	Master's Thesis
Language	English
Research Field	Health Sciences, Public Health Health Sciences, Epidemiology
Parola chiave	Kernel Density Estimation Body mass index Public Health Neighborhoods Built environment Epidemiology
Committee Chair / Thesis Advisor	Kramer, Michael R, Emory University
Partnering Agencies	University, college or educational institution (other than Emory)

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