Activity-Friendly Built Environment Attributes and Adult Adiposity

Deep-learning analysis of greenspace and metabolic syndrome: A street-view and remote-sensing approach

Evidence linking greenspace exposure to metabolic syndrome (MetS) remains sparse and inconsistent. This exploratory study evaluate the relationship between green visibility index (GVI) and normalized difference vegetation index (NDVI) with MetS prevalence, and quantifies the potential reduction in MetS burden from increased greenspace exposure. Participants were selected from the baseline survey of the Wuhan Chronic Disease Cohort. Street-view imagry was procured within buffer zones ranging from 50 to 500-m surrounding participants' residences. GVI was extracted from street-view images using a convolutional neural network model trained on CityScapes, while the NDVI was ascertained from satellite remote sensing data. We employed generalized linear mixed-effects models to assess the associations between greenspace with the risk of MetS. Additionally, restricted cubic spline function was applied to generate exposure-response curve. Leveraging a counterfactual causal inference framework, we quantified the potential diminution in MetS cases consequent to an elevation in NDVI levels within Wuhan. Within the 150-m buffer zone, each 0.1-unit increase in GVI and NDVI corresponded to 13% and 31% decline in the odds of MetS in the fully adjusted regression models, respectively. A negative non-linear relationship between GVI and MetS was observed when the GVI level exceeded 0.209, while a negative linear association for NDVI when its level exceeded 0.299. Assuming causality, 74,183 cases of MetS can be avoided by achieving greenness threshold of NDVI, amounting for 8.16% of total MetS prevalence in 2019. Our findings offer a compelling justification for the integration of greening policies in initiatives aimed at promoting metabolic health.

The association of obesogenic environments with weight status, blood pressure, and blood lipids: A cross-sectional pooled analysis across five cohorts

In this observational cross-sectional study, we investigated the relationship between combined obesogenic neighbourhood characteristics and various cardiovascular disease risk factors in adults, including BMI, systolic blood pressure, and blood lipids, as well as the prevalence of overweight/obesity, hypertension, and dyslipidaemia. We conducted a large-scale pooled analysis, comprising data from five Dutch cohort studies (n = 183,871). Neighbourhood obesogenicity was defined according to the Obesogenic Built-environmental CharacterisTics (OBCT) index. The index was calculated for 1000m circular buffers around participants' home addresses. For each cohort, the association between the OBCT index and prevalence of overweight/obesity, hypertension and dyslipidaemia was analysed using robust Poisson regression models. Associations with continuous measures of BMI, systolic blood pressure, LDL-cholesterol, HDL-cholesterol, and triglycerides were analysed using linear regression. All models were adjusted for age, sex, education level and area-level socio-economic status. Cohort-specific estimates were pooled using random-effects meta-analyses. The pooled results show that a 10 point higher OBCT index score was significantly associated with a 0.17 higher BMI (95%CI: 0.10 to 0.24), a 0.01 higher LDL-cholesterol (95% CI: 0.01 to 0.02), a 0.01 lower HDL cholesterol (95% CI: -0.02 to -0.01), and non-significantly associated with a 0.36 mmHg higher systolic blood pressure (95%CI: -0.14 to 0.65). A 10 point higher OBCT index score was also associated with a higher prevalence of overweight/obesity (PR = 1.03; 95% CI: 1.02 to 1.05), obesity (PR = 1.04; 95% CI: 1.01 to 1.08) and hypertension (PR = 1.02; 95% CI: 1.00 to 1.04), but not with dyslipidaemia. This large-scale pooled analysis of five Dutch cohort studies shows that higher neighbourhood obesogenicity, as measured by the OBCT index, was associated with higher BMI, higher prevalence of overweight/obesity, obesity, and hypertension. These findings highlight the importance of considering the obesogenic environment as a potential determinant of cardiovascular health.

Development of a neighborhood obesogenic built environment characteristics index for the Netherlands

OBJECTIVE

Environmental factors that drive obesity are often studied individually, whereas obesogenic environments are likely to consist of multiple factors from food and physical activity (PA) environments. This study aimed to compose and describe a comprehensive, theory-based, expert-informed index to quantify obesogenicity for all neighborhoods in the Netherlands.

METHODS

The Obesogenic Built Environment CharacterisTics (OBCT) index consists of 17 components. The index was calculated as an average of componential scores across both food and PA environments and was scaled from 0 to 100. The index was visualized and summarized with sensitivity analysis for weighting methods.

RESULTS

The OBCT index for all 12,821 neighborhoods was right-skewed, with a median of 44.6 (IQR = 10.1). Obesogenicity was lower in more urbanized neighborhoods except for the extremely urbanized neighborhoods (>2500 addresses/km² ), where obesogenicity was highest. The overall OBCT index score was moderately correlated with the food environment (Spearman ρ = 0.55, p <0.05) and with the PA environment (ρ = 0.38, p <0.05). Hierarchical weighting increased index correlations with the PA environment but decreased correlations with the food environment.

CONCLUSIONS

The novel OBCT index and its comprehensive environmental scores are potentially useful tools to quantify obesogenicity of neighborhoods.

Impacts of Built Environment on Risk of Women's Lung Cancer: A Case Study of China

Built environment factors such as air pollution are associated with the risk of respiratory disease, but few studies have carried out profound investigation. We aimed to evaluate the association between the built environment and Chinese women’s lung cancer incidence data from the China Cancer Registry Annual Report 2017, which covered 345,711,600 people and 449 qualified cancer registries in mainland China. The air quality indicator (PM2.5) and other built environment data are obtained from the China Statistical Yearbook and other official approved materials. An exploratory regression tool is applied by using Chinese women’s lung cancer incidence data (Segi population) as the dependent variable, PM2.5 index and other built environment factors as the independent variables. An apparent clustering region with a high incidence of women’s lung cancer was discovered, including regions surrounding Bohai bay and the three Chinese northeastern provinces, Heilongjiang, Liaoning and Inner Mongolia. Besides air quality, built environment factors were found to have a weak but clear impact on lung cancer incidence. Land-use intensity and the greening coverage ratio were positive, and the urbanization rate and population density were negatively correlated with lung cancer incidence. The role of green spaces in Chinese women’s lung cancer incidence has not been proven.

Assessing impacts of redeveloping public housing communities on obesity in low-income minority residents: Rationale, study design, and baseline data from the Watts Neighborhood Health Study

INTRODUCTION

Obesogenic built- and social-environments in low-income and minority communities are often blamed for the higher rates of obesity in this population, but existing evidence is based largely on observational studies. This study leverages a natural experiment created by the redevelopment of a public housing community to examine the impact of major improvements to the housing, built, and social environments on obesity among residents.

METHODS/DESIGN

The study design is a natural experiment where residents from the redeveloped community (treatment group) will be compared to those from a similar community (control group) in terms of their pre/post changes in primary outcomes using annual longitudinal data on a cohort of residents. Quasi-experimental variation in the timing of exposure to various redevelopment components within the treated community will be further leveraged within a stepped-wedge research design to assess the impact of the redevelopment components. Primary outcome measures include body mass index, overweight, and obese status.

RESULTS

A cohort of 868 adults and 704 children (ages 2-17 years) was recruited during 2018-2019 with up to two waves of baseline data. At baseline, the prevalence of obesity (overweight or obesity) was 57.2% (81.3%) in adults and 33.1% (52.4%) among children, with no significant differences by treatment status. No differential trends in primary outcomes were observed by treatment status during the two years of baseline.

DISCUSSION

This natural experiment study offers a unique opportunity to assess whether improvements to housing, built, and social environment in low-income minority communities can lead to reductions in obesity.

Associations between the built environment and obesity: an umbrella review

BACKGROUND

In the past two decades, the built environment emerged as a conceptually important determinant of obesity. As a result, an abundance of studies aiming to link environmental characteristics to weight-related outcomes have been published, and multiple reviews have attempted to summarise these studies under different scopes and domains. We set out to summarise the accumulated evidence across domains by conducting a review of systematic reviews on associations between any aspect of the built environment and overweight or obesity.

METHODS

Seven databases were searched for eligible publications from the year 2000 onwards. We included systematic literature reviews, meta-analyses and pooled analyses of observational studies in the form of cross-sectional, case-control, longitudinal cohort, ecological, descriptive, intervention studies and natural experiments. We assessed risk of bias and summarised results structured by built environmental themes such as food environment, physical activity environment, urban-rural disparity, socioeconomic status and air pollution.

RESULTS

From 1850 initial hits, 32 systematic reviews were included, most of which reported equivocal evidence for associations. For food- and physical activity environments, associations were generally very small or absent, although some characteristics within these domains were consistently associated with weight status such as fast-food exposure, urbanisation, land use mix and urban sprawl. Risks of bias were predominantly high.

CONCLUSIONS

Thus far, while most studies have not been able to confirm the assumed influence of built environments on weight, there is evidence for some obesogenic environmental characteristics. Registration: This umbrella review was registered on PROSPERO under ID CRD42019135857.

Impact of Built Environments on Body Weight (the Moving to Health Study): Protocol for a Retrospective Longitudinal Observational Study

BACKGROUND

Studies assessing the impact of built environments on body weight are often limited by modest power to detect residential effects that are small for individuals but may nonetheless comprise large attributable risks.

OBJECTIVE

We used data extracted from electronic health records to construct a large retrospective cohort of patients. This cohort will be used to explore both the impact of moving between environments and the long-term impact of changing neighborhood environments.

METHODS

We identified members with at least 12 months of Kaiser Permanente Washington (KPWA) membership and at least one weight measurement in their records during a period between January 2005 and April 2017 in which they lived in King County, Washington. Information on member demographics, address history, diagnoses, and clinical visits data (including weight) was extracted. This paper describes the characteristics of the adult (aged 18-89 years) cohort constructed from these data.

RESULTS

We identified 229,755 adults representing nearly 1.2 million person-years of follow-up. The mean age at baseline was 45 years, and 58.0% (133,326/229,755) were female. Nearly one-fourth of people (55,150/229,755) moved within King County at least once during the follow-up, representing 84,698 total moves. Members tended to move to new neighborhoods matching their origin neighborhoods on residential density and property values.

CONCLUSIONS

Data were available in the KPWA database to construct a very large cohort based in King County, Washington. Future analyses will directly examine associations between neighborhood conditions and longitudinal changes in body weight and diabetes as well as other health conditions.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/16787.

Are changes in depressive symptoms, general health and residential area socio-economic status associated with trajectories of waist circumference and body mass index?

Objective

This study sought to assess whether changes in depressive symptoms, general health, and area-level socio-economic status (SES) were associated to changes over time in waist circumference and body mass index (BMI).

Methods

A total of 2871 adults (18 years or older), living in Adelaide (South Australia), were observed across three waves of data collection spanning ten years, with clinical measures of waist circumference, height and weight. Participants completed the Centre for Epidemiologic Studies Depression (CES-D) and Short Form 36 health questionnaires (SF-36 general health domain). An area-level SES measure, relative location factor, was derived from hedonic regression models using residential property features but blind to location. Growth curve models with latent variables were fitted to data.

Results

Waist circumference, BMI and depressive symptoms increased over time. General health and relative location factor decreased. Worsening general health and depressive symptoms predicted worsening waist circumference and BMI trajectories in covariate-adjusted models. Diminishing relative location factor was negatively associated with waist circumference and BMI trajectories in unadjusted models only.

Conclusions

Worsening depressive symptoms and general health predict increasing adiposity and suggest the development of unhealthful adiposity might be prevented by attention to negative changes in mental health and overall general health.

Neighborhood Environment Measurements and Anthropometric Indicators of Obesity: Results from the Women and Their Children's Health (WaTCH) Study

We compared geographic information system (GIS)- and Census-based approaches for measuring the physical and social neighborhood environment at the census tract-level versus and audit approach on associations with body mass index (BMI), waist circumference (WC), and waist-to-hip ratio (WHR). Data were used from the 2012-2014 Women and Their Children's Health (WaTCH) Study (n=940). Generalized linear models were used to obtain odds ratios (ORs) for BMI (≥30 kg/m²), WC (>88 cm), and WHR (>0.85). Using an audit approach, more adverse neighborhood characteristics were associated with a higher odds of WC (OR: 1.10; 95% CI: 1.05, 1.15) and WHR (OR: 1.09; 95% CI: 1.05, 1.14) after adjustment for age, race/ethnicity, income, and oil spill exposure. There were no significant associations between GIS- and Census- based measures with obesity in adjusted models. Quality aspects of the neighborhood environment captured by audits at the individual-level may be more relevant to obesity than physical or social aspects at the census-tract level.

The Independent Associations between Walk Score® and Neighborhood Socioeconomic Status, Waist Circumference, Waist-To-Hip Ratio and Body Mass Index Among Urban Adults

Background: Environmental and policy factors can influence weight status via facilitating or discouraging physical activity and healthy diet. Despite mixed evidence, some findings suggest that the neighborhood built environment, including &ldquo;walkability&rdquo;, is associated with overweight and obesity. Most of these findings have measured body mass index (BMI), yet other weight status measures including waist circumference (WC) and waist-to-hip (W-H) ratio are also predictive of health outcomes, independent of BMI. Our study aim was to estimate the associations between walkability, measured using Walk Score^&reg;, and each of WC, W-H ratio, and BMI among urban Canadian adults. Methods: In 2014, n = 851 adults recruited from 12 structurally and socioeconomic diverse neighborhoods (Calgary, Alberta, Canada) provided complete data on a physical activity, health and demographic questionnaire and self-reported anthropometric measures (i.e., height and weight, WC and hip circumference). Anthropometric data were used to estimate WC, W-H ratio, and BMI which were categorized into low and high risk in relation to their potential adverse effect on health. WC and BMI were also combined to provide a proxy measure of both overall and abdominal adiposity. Multivariable logistic regression models estimated odds ratios (OR) and 95% confidence intervals (CI) for associations between each weight status outcome and Walk Score^&reg;. Results: A one-unit increase in Walk Score^&reg; was associated with lower odds of being high-risk based on WC (OR = 0.99; 95%CI 0.97⁻0.99). Notably, those residing in socioeconomically disadvantage neighborhoods had significantly higher odds of being high risk based on WC, BMI, and WC-BMI combined compared with advantaged neighborhoods. Conclusions: Interventions that promote healthy weight through the design of neighborhoods that support and enhance the effect of physical activity and diet-related interventions could have a significant population health impact.

Associations of neighbourhood walkability indices with weight gain

Background

Inconsistent associations of neighbourhood walkability with adults’ body weight have been reported. Most studies examining the relationships of walkability and adiposity are cross-sectional in design. We examined the longitudinal relationships of two walkability indices – conventional walkability and space syntax walkability, and their individual components, with weight change among adults over four years.

Methods

Data were from the Physical Activity in Localities and Community study in Adelaide, Australia. In 2003–2004, 2650 adults living in 154 Census Collection Districts (CCDs) returned baseline questionnaires; in 2007–2008, the follow-up survey was completed by 1098. Participants reported their weight at baseline and at follow-up. Neighbourhood walkability indices were calculated using geographic information systems and space syntax software. Linear marginal models using generalized estimating equations with robust standard errors were fitted to examine associations of the two walkability indices and their individual components with the weight at follow-up, adjusting for baseline weight, socio-demographic variables, and spatial clustering at the level of CCD.

Results

The overall mean weight gain over four years was 1.5 kg. The two walkability indices were closely correlated (r = 0.76, p < 0.01). No significant associations were found between the overall neighbourhood walkability indices and weight change. Among walkability components, there was a marginally significant negative association between space syntax measure of street integration and weight change: one standard deviation increment in street integration was associated with 0.31 kg less weight gain (p = 0.09).

Conclusions

Using a prospective study design and a novel space-syntax based measure of walkability, we were not able to identify relationships between neighbourhood walkability with weight gain. This is consistent with other inconclusive findings on the built environment and obesity. Research on the built environment and adults’ weight gain may need to consider not just local environments but also a larger scale environment within a city or workplace environment in order to capture multiple behaviours relevant to weight gain.

Physical Activity Environment and Japanese Adults' Body Mass Index

Evidence about the impacts of the physical activity environment on adults’ weight in the context of Asian countries is scarce. Likewise, no study exists in Asia examining whether Walk Score^®—a free online walkability tool—is related to obesity. This study aimed to examine associations between multiple physical activity environment measures and Walk Score^® ratings with Japanese adults’ body mass index (BMI). Data from 1073 adults in the Healthy Built Environment in Japan study were used. In 2011, participants reported their height and weight. Environmental attributes, including population density, intersection density, density of physical activity facilities, access to public transportation, and availability of sidewalks, were calculated using Geographic Information Systems. Walk Scores^® ratings were obtained from the website. Multiple linear regression analysis was conducted to examine the association between each environmental attribute and BMI. Adjusting for covariates, all physical activity environmental attributes were negatively associated with BMI. Similarly, an increase of one standard deviation of Walk Score^® was associated with a 0.29 (95% confidence interval (CI) of −0.49–−0.09) decrease in BMI. An activity-friendly built environment was associated with lower adults’ BMI in Japan. Investing in healthy community design may positively impact weight status in non-Western contexts.

Interactions between Neighbourhood Urban Form and Socioeconomic Status and Their Associations with Anthropometric Measurements in Canadian Adults

Neighbourhood-level socioeconomic composition and built context are correlates of weight-related behaviours. We investigated the relations between objective measures of neighbourhood design and socioeconomic status (SES) and their interaction, in relation to self-reported waist circumference (WC), waist-to-hip ratio, and body mass index (BMI) in a sample of Canadian adults (n = 851 from 12 Calgary neighbourhoods). WC and BMI were higher among residents of disadvantaged neighbourhoods, independent of neighbourhood design (grid, warped grid, and curvilinear street patterns) and individual-level characteristics (sex, age, education, income, dog ownership, marital status, number of dependents, motor vehicle access, smoking, sleep, mental health, physical health, and past attempts to modify bodyweight). The association between neighbourhood-level SES and WC was modified by neighbourhood design; WC was higher in disadvantaged-curvilinear neighbourhoods and lower in advantaged-grid neighbourhoods. Policies making less obesogenic neighbourhoods affordable to low socioeconomic households and that improve the supportiveness for behaviours leading to healthy weight in low socioeconomic neighbourhoods are necessary.

Assessing mediation of behavioral and stress pathways in the association between neighborhood environments and obesity outcomes

Although many studies have reported associations between characteristics of the neighborhood environment and obesity, little is understood about the pathways or mechanisms through which these associations operate. The purpose of this study was to examine possible behavioral and stress pathways hypothesized to mediate the association between neighborhood environments and obesity and whether pathways contribute to different obesity outcomes. Cross-sectional data were used from the 2012–2014 Women and Their Children's Health Study (WaTCH) in Louisiana (N = 909). Participants' neighborhoods, body mass index (BMI) and waist circumference (WC) were objectively measured. The causal inference approach to mediation analysis was used to obtain indirect estimates for self-reported measures of physical activity, low access to food, and depression. The mean BMI was 32.0 kg/m² and the mean WC was 98.6 cm. The (adverse) neighborhood environment was significantly associated BMI (β = 0.17 kg/m²; 95% Confidence Interval (CI): 0.03, 0.31) and WC (β = 0.64; 95% CI: 0.34, 0.95, after adjusting for covariates. Neither depression, physical activity, nor low food access mediated those associations. Further research that investigates and uses better measures of the behavioral and stress pathways through which the neighborhood environment influences obesity is warranted.

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Used mediation to examine mechanisms between neighborhoods and obesity.

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The neighborhood environment was significantly associated with BMI and WC.

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Neither depression, physical activity, nor food access were significant mediators.

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Better measures of mediators are warranted in future research.

A conduit between epidemiological research and regional health policy

OBJECTIVE

To transform data from a research setting into a format that could be used to support strategies encouraging healthy lifestyle choices and service planning within local government.

METHODS

Details of the health status and lifestyle behaviours of the Geelong, Victoria, population were generated independently by the Geelong Osteoporosis Study (GOS), a prospective population-based cohort study. Recent GOS follow-up phases provided evidence about patterns of unhealthy diet, physical inactivity, smoking and harmful alcohol use. These factors are well-recognised modifiable risk factors for chronic disease; the dataset was complemented with prevalence estimates for musculoskeletal disease, obesity, diabetes, cardiovascular disease, asthma and cancer.

RESULTS

Data were provided to Healthy Together Geelong in aggregate form according to age, sex and suburb. A population statistics company used the data to project health outcomes by suburb for use by local council. This data exchange served as a conduit between epidemiological research and policy development.

CONCLUSION AND IMPLICATIONS

Regional policy makers were informed by local evidence, rather than national or state health survey, thereby optimising potential intervention strategies.

Creating Cycling-Friendly Environments for Children: Which Micro-Scale Factors Are Most Important? An Experimental Study Using Manipulated Photographs

BACKGROUND

Increasing participation in transportation cycling represents a useful strategy for increasing children's physical activity levels. Knowledge on how to design environments to encourage adoption and maintenance of transportation cycling is limited and relies mainly on observational studies. The current study experimentally investigates the relative importance of micro-scale environmental factors for children's transportation cycling, as these micro-scale factors are easier to change within an existing neighborhood compared to macro-scale environmental factors (i.e. connectivity, land-use mix, …).

METHODS

Researchers recruited children and their parents (n = 1232) via 45 randomly selected schools across Flanders and completed an online questionnaire which consisted of 1) demographic questions; and 2) a choice-based conjoint (CBC) task. During this task, participants chose between two photographs which we had experimentally manipulated in seven micro-scale environmental factors: type of cycle path; evenness of cycle path; traffic speed; traffic density; presence of speed bumps; environmental maintenance; and vegetation. Participants indicated which route they preferred to (let their child) cycle along. To find the relative importance of these micro-scale environmental factors, we conducted Hierarchical Bayes analyses.

RESULTS

Type of cycle path emerged as the most important factor by far among both children and their parents, followed by traffic density and maintenance, and evenness of the cycle path among children. Among parents, speed limits and maintenance emerged as second most important, followed by evenness of the cycle path, and traffic density.

CONCLUSION

Findings indicate that improvements in micro-scale environmental factors might be effective for increasing children's transportation cycling, since they increase the perceived supportiveness of the physical environment for transportation cycling. Investments in creating a clearly designated space for the young cyclist, separated from motorized traffic, appears to be the most effective way to increase perceived supportiveness. Future research should confirm our laboratory findings with experimental on-site research.

Playability: Built and Social Environment Features That Promote Physical Activity Within Children

The role of neighbourhood built and social environments in shaping children's physical activity has received increasing interest over the past 10 years. We reviewed recent evidence published between 2011 and 2014. Most of the recent evidence continues to be cross-sectional. Few macro-level neighbourhood attributes were consistently associated with physical activity in the expected direction. The strongest evidence for associations between neighbourhood attributes and physical activity with was for the transportation environment, particularly in relation to proximity to school and transport-related physical activity. There was intermediate evidence that neighbourhood walking/cycling infrastructure and pedestrian safety structures are associated with transport-related PA. Recent evidence on associations between the neighbourhood built and social environment and children's PA is modest. Stronger study designs and greater attention to conceptual-matching and specificity of measures are critical to advance the evidence base.

Neighbourhood built environment associations with body size in adults: mediating effects of activity and sedentariness in a cross-sectional study of New Zealand adults

BACKGROUND

The aim of this study was to determine the associations between body size and built environment walkability variables, as well as the mediating role of physical activity and sedentary behaviours with body size.

METHODS

Objective environment, body size (body mass index (BMI), waist circumference (WC)), and sedentary time and physical activity data were collected from a random selection of 2033 adults aged 20-65 years living in 48 neighbourhoods across four New Zealand cities. Multilevel regression models were calculated for each comparison between body size outcome and built environment exposure.

RESULTS AND DISCUSSION

Street connectivity and neighborhood destination accessibility were significant predictors of body size (1 SDchange predicted a 1.27 to 1.41 % reduction in BMI and a 1.76 to 2.29 % reduction in WC). Significantrelationships were also observed for streetscape (1 SD change predicted a 1.33 % reduction in BMI) anddwelling density (1 SD change predicted a 1.97 % reduction in BMI). Mediation analyses revealed asignificant mediating effect of physical activity on the relationships between body size and street connectivity and neighbourhood destination accessibility (explaining between 10.4 and 14.6 % of the total effect). No significant mediating effect of sedentary behaviour was found. Findings from this cross-sectional study of a random selection of New Zealand adults are consistent with international research. Findings are limited to individual environment features only; conclusions cannot be drawn about the cumulative and combined effect of individual features on outcomes.

CONCLUSIONS

Built environment features were associated with body size in the expected directions. Objectively-assessed physical activity mediated observed built environment-body size relationships.

Can Walking or Biking to Work Really Make a Difference? Compact Development, Observed Commuter Choice and Body Mass Index

Objectives

Promoting active commuting is viewed as one strategy to increase physical activity and improve the energy balance of more sedentary individuals thereby improving health outcomes. However, the potential effectiveness of promotion policies may be seriously undermined by the endogenous choice of commute mode. Policy to promote active commuting will be most effective if it can be demonstrated that 1) those in compact cities do not necessarily have a preference for more physical activity, and 2) that current active commuting is not explained by unobserved characteristics that may be the true source of a lower body mass index (BMI).

Methods

Daily time-use diaries are used in combination with geographical characteristics of where respondents live and work to test 1) whether residents of more compact settlements are characterized by higher activity levels; and 2) whether residents of more compact settlements are more likely to bike or walk to work. An endogenous treatment model of active commuting allows testing whether reductions in BMI associated with walking or biking to work are in fact attributable to that activity or are more strongly associated with unobserved characteristics of these active commuters.

Results

The analysis of general activity levels confirms that residents of more compact cities do not expend more energy than residents of more sprawling cities, indicating that those in compact cities do not necessarily have a preference for more physical activity. The endogenous treatment model is consistent with walking or biking to work having an independent effect on BMI, as unobserved factors that contribute to a higher likelihood of active commuting are not associated with lower BMI.

Conclusions

Despite evidence that more compact settlement patterns enable active commuting, only a small share of workers in these areas choose to walk or bike to work. In general, the activity level of residents in more compact cities and residents in more sprawling areas is very similar. But, there is a robust association between active commuting and lower body mass index that is not explained by unobserved attributes or preferences suggests that policies to promote active commuting may be effective. In particular, active commuting has a greater effect on BMI. Consequently, compact settlement appears to be an effective infrastructure for promoting more active lifestyles. The policy challenge is finding ways to ensure that this infrastructure is more widely utilized.