Walkability and Body Mass Index

Smith, Ken R.; Brown, Barbara; Yamada, Ikuho; Kowaleski‐Jones, Lori; Zick, Cathleen D.; Fan, Jessie X.

doi:10.1016/j.amepre.2008.05.028

Cited by 169 publications

(100 citation statements)

References 38 publications

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“…Recent research on neighborhood environment and obesity relationship has found that the three Census AC variables we studied to be significantly associated with individual risk of obesity (Smith et al, 2008, Zick et al, 2009, Brown et al, 2013). The researchers have argued that percentages of workers walking and biking to work capture some aspects of land use diversity if home and work are within walking or biking distance of each other for some (Zick et al, 2009), although the empirical validation of such relationship has been limited.…”

Section: Discussionmentioning

confidence: 97%

“…Tract median housing age is computed from tract median housing build year from the 2007-2011 American Community Survey and is used as a proxy measure of neighborhood walkability because older neighborhoods were built before people began to rely on cars and are typically more walkable than newer neighborhoods with better land use diversity, narrower streets, and more extensive sidewalks (Boer et al, 2007, Smith et al, 2008, Berrigan and Troiano, 2002). The design aspect of the 3D's is captured by a tract-level street connectivity measure, defined as the number of intersections per square kilometer in the tract.…”

Section: Data and Variablesmentioning

confidence: 99%

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An ecological analysis of environmental correlates of active commuting in urban U.S.

2014

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We conduct a cross-sectional ecological analysis to examine environmental correlates of active commuting in 39,660 urban tracts using data from the 2010 Census, 2007-2011 American Community Survey, and other sources. The five-year average (2007-2011) prevalence is 3.05% for walking, 0.63% for biking, and 7.28% for public transportation to work, with higher prevalence for all modes in lower-income tracts. Environmental factors account for more variances in public transportation to work but economic and demographic factors account for more variances in walking and biking to work. Population density, median housing age, street connectivity, tree canopy, distance to parks, air quality, and county sprawl index are associated with active commuting, but the association can vary in size and direction for different transportation mode and for higher-income and lower-income tracts.

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Section: Discussionmentioning

confidence: 97%

Section: Data and Variablesmentioning

confidence: 99%

An ecological analysis of environmental correlates of active commuting in urban U.S.

2014

Self Cite

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“…It is also possible that walkability effects are simply just weaker compared to other built environment features like food environments and park accessibility in Utah. However, population-based studies also conducted in Utah (Smith et al 2008; Zick et al 2013) used different walkability indicators and examined the walkability and obesity link reporting that increasing levels of walkability decrease the risks of excess weight. Perhaps empirical results of the walkability and excessive weight link are to some extent to the specific walkable-environment measures used in the analysis.…”

Section: Discussionmentioning

confidence: 99%

Multilevel built environment features and individual odds of overweight and obesity in Utah

Wen

Wang

2015

Applied Geography

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Based on the data from the Behavioral Risk Factor Surveillance System (BRFSS) in 2007, 2009 and 2011 in Utah, this research uses multilevel modeling (MLM) to examine the associations between neighborhood built environments and individual odds of overweight and obesity after controlling for individual risk factors. The BRFSS data include information on 21,961 individuals geocoded to zip code areas. Individual variables include BMI (body mass index) and socio-demographic attributes such as age, gender, race, marital status, education attainment, employment status, and whether an individual smokes. Neighborhood built environment factors measured at both zip code and county levels include street connectivity, walk score, distance to parks, and food environment. Two additional neighborhood variables, namely the poverty rate and urbanicity, are also included as control variables. MLM results show that at the zip code level, poverty rate and distance to parks are significant and negative covariates of the odds of overweight and obesity; and at the county level, food environment is the sole significant factor with stronger fast food presence linked to higher odds of overweight and obesity. These findings suggest that obesity risk factors lie in multiple neighborhood levels and built environment features need to be defined at a neighborhood size relevant to residents' activity space.

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“…Sedentary lifestyles are not simply attributed to personal choice but also the built environment, which refers broadly to the collective availability of green spaces, sidewalks, parks, trails, recreational facilities, traffic safety, neighborhood safety, and other neighborhood characteristics that may promote recreational physical activity as well as functional physical activity, such as active transport to work, school, or errands 354-359 . Evidence suggests that physical-activity-friendly facilities are much less common in predominantly minority and economically disadvantaged neighborhoods (relative to white, or more affluent neighborhoods) where there is also greater obesity prevalence 360-364 .…”

Section: Introductionmentioning

confidence: 99%

Weighing the Evidence of Common Beliefs in Obesity Research

Casazza

Brown

Astrup

et al. 2014

Critical Reviews in Food Science and Nutrition

155

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Obesity is a topic on which many views are strongly held in the absence of scientific evidence to support those views, and some views are strongly held despite evidence to contradict those views. We refer to the former as “presumptions” and the latter as “myths”. Here we present nine myths and ten presumptions surrounding the effects of rapid weight loss; setting realistic goals in weight loss therapy; stage of change or readiness to lose weight; physical education classes; breast-feeding; daily self-weighing; genetic contribution to obesity; the “Freshman 15”; food deserts; regularly eating (versus skipping) breakfast; eating close to bedtime; eating more fruits and vegetables; weight cycling (i.e. yo-yo dieting); snacking; built environment; reducing screen time in childhood obesity; portion size; participation in family mealtime; and drinking water as a means of weight-loss. For each of these, we describe the belief and present evidence that the belief is widely held or stated, reasons to support the conjecture that the belief might be true, evidence to directly support or refute the belief, and findings from randomized controlled trials, if available. We conclude with a discussion of the implications of these determinations, conjecture on why so many myths and presumptions exist, and suggestions for limiting the spread of these and other unsubstantiated beliefs about obesity domain.

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Walkability and Body Mass Index

Cited by 169 publications

References 38 publications

An ecological analysis of environmental correlates of active commuting in urban U.S.

An ecological analysis of environmental correlates of active commuting in urban U.S.

Multilevel built environment features and individual odds of overweight and obesity in Utah

Weighing the Evidence of Common Beliefs in Obesity Research

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