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BMI, auto use, and the urban environment in San Francisco
Abstract
The epidemic of overweight and obesity has sparked interest in urban planning circles. Many believe the built environment directly influences physical health, and recent empirical evidence supports this notion. Cross-sectional survey data was collected from a sample of San Francisco residents (n=670) in the summer of 2005. Body mass index (BMI) served as the dependent variable. Independent variables included population density and auto use. Results indicate an inverse relationship between density and auto use as well as higher BMI scores for respondents reporting high levels of auto use for the work/school commute and trips to the grocery store.
... A growing number of studies have shown the striking link between commuting burden and obesity outcomes. A study in San Francisco indicated that urban residents with higher BMI scores reported high levels of automobile use for work/school commuting and trips to the grocery store (Pendola and Gen, 2007). Another study in Atlanta, Georgia, suggested that each additional hour spent in a car per day was associated with a 6% increase in the likelihood of obesity (Frank et al., 2004). ...
... We hypothesized that neighborhood commuting environment's association with obesity may be sensitive to regional urbanization levels. Almost all previous studies linking obesity and commuting were based on local population samples from urban settings (Frank et al., 2004;Hoehner et al., 2012;Lathey et al., 2009;Lopez-Zetina et al., 2006;Pendola and Gen, 2007). The potential urban-rural differences in the association between population automobile dependency and commuting time and obesity in the US are less well understood. ...
... Urban neighborhood automobile dependency was consistently and strongly associated with obesity in metropolitan statistical areas (large central metro, large fringe metro and medium metro, small metro areas). This finding is consistent with most previous urban studies relating commuting by car to obesity outcomes (Jacobson et al., 2011;Lopez-Zetina et al., 2006;Pendola and Gen, 2007). However, neighborhood automobile dependency did not demonstrate the expected association with obesity in non-metropolitan rural areas. ...
... Through the careful planning of buildings, land uses, and transport networks, urban areas can support both climate change mitigation and human health [6]. For example, the placement of residential buildings in relation to commercial areas influences people's choice of transit (walking, cycling, driving, or public transport use) and has a significant effect on the body mass index (BMI) [6,8]; people show higher BMI scores when car use to commute to work/school and the shops increases [8]. To address climate change, the risks to the population's public health need to be considered, and an understanding of ecological relations and the imperatives of environmental sustainability need to be established collectively [9,10]. ...
... Through the careful planning of buildings, land uses, and transport networks, urban areas can support both climate change mitigation and human health [6]. For example, the placement of residential buildings in relation to commercial areas influences people's choice of transit (walking, cycling, driving, or public transport use) and has a significant effect on the body mass index (BMI) [6,8]; people show higher BMI scores when car use to commute to work/school and the shops increases [8]. To address climate change, the risks to the population's public health need to be considered, and an understanding of ecological relations and the imperatives of environmental sustainability need to be established collectively [9,10]. ...
The beneficial effects of green and blue areas on human wellbeing are significant. Physical activity is a crucial factor for the promotion of good human health and wellbeing, and running constitutes one of the most popular forms of outdoor physical activity. This study examines the effect of six urban “route landscapes” with different landscape characters used for outdoor running on the heart rates and speeds of 30 people wearing a smartwatch while running. These routes included: (1) a running track in a stadium; (2) a road without street trees; (3) a road with street trees; (4) an urban park without sea view; (5) an urban park with sea view; and (6) a road by the sea. Additionally, a questionnaire survey was conducted to determine participants’ perceptions and preferred “route landscape” for running. In the study, higher heart rates were recorded on routes without trees, including the stadium. The lowest heart rate was recorded in the park by the sea, followed by the road by the sea, which were at the lowest altitudes amongst the routes studied. Additionally, the highest mean speed of participants was recorded during the run on the road by the sea. The results also showed that irrespectively of the routes, increases in altitude and gradient caused an increase in the heart rates. In the survey, the majority of respondents stated that they would have felt calm and joy during a run either in a park or in a park by the sea. With rising sea levels dictating not to build, carbon capture being necessary in parks, and trees by roads reducing the heat island effect, this study reveals the best “route landscapes” for runners’ health and global warming.
... The compact and connected ways that we built our cities for the last few thousand years quickly evolved into much sparser, dendritic street networks, as depicted in Fig. 1 (Southworth and Ben-Joseph, 1997). The existing literature suggests that our older cities can help facilitate less driving and more active transportation (Frank et al., 2007;Handy et al., 2002;Marshall and Garrick, 2010a;Pendola and Gen, 2007). But do they actually have a measurable public health benefit as well? ...
... The percent of non-white residents was significant in the diabetes model where an increase in the percentage of minorities was associated with an increase in diabetes. Average commute time was only significant in the obesity model but with a contrary effect to what has been seen in several notable studies Hoehner et al., 2012;Lindstrom, 2008;Mobley et al., 2006;Pendola and Gen, 2007;Wen et al., 2006). Our results suggest that a longer commute is significantly associated with a lower obesity rate. ...
Children who are too young to drive and adults who are unable to drive can represent a significant transportation burden, one typically shouldered by family members, i.e., “family chauffeur-associated-burdens” (Family CABs). This research examines how one’s experience chauffeuring family members influences support for strategies to address family chauffeuring burdens. The research also examines if one’s own experience chauffeuring family members affects perceptions of the possibility that they may reach a point at which they are no longer able to drive, and potentially become a transportation burden to others. Descriptive statistics and linear and logistic regression models of a household survey ( n = 349) demonstrate the significance of demographics in the type and extent of chauffeuring burdens. Chauffeur youth and money spent chauffeuring are each positively-correlated with the desire to move to a more walkable place to address chauffeuring burdens. Alternately, youth and being male are each positively-correlated with favoring technological solutions (e.g., autonomous vehicles) to address chauffeuring burdens. One’s own experience as a chauffeur does not significantly influence perceptions of eventually becoming a transportation burden for others. Women are more likely to prefer moving to a more walkable location and relying on family or friends if they are no longer able to drive, while men prefer the idea of relying on autonomous vehicles if they lose the ability to drive. Findings from this work can guide appropriate planning, policy, and technological responses to chauffeuring burdens.
... The compact and connected ways that we built our cities for the last few thousand years quickly evolved into much sparser, dendritic street networks, as depicted in Fig. 1 (Southworth and Ben-Joseph, 1997). The existing literature suggests that our older cities can help facilitate less driving and more active transportation (Frank et al., 2007;Handy et al., 2002;Marshall and Garrick, 2010a;Pendola and Gen, 2007). But do they actually have a measurable public health benefit as well? ...
... The percent of non-white residents was significant in the diabetes model where an increase in the percentage of minorities was associated with an increase in diabetes. Average commute time was only significant in the obesity model but with a contrary effect to what has been seen in several notable studies Hoehner et al., 2012;Lindstrom, 2008;Mobley et al., 2006;Pendola and Gen, 2007;Wen et al., 2006). Our results suggest that a longer commute is significantly associated with a lower obesity rate. ...
What is the influence of street network design on public health? While the literature linking the built environment to health outcomes is vast, it glosses over the role that specific street network characteristics play. The three fundamental elements of street networks are: street network density, connectivity, and configuration. Without sufficient attention being paid to these individual elements of street network design, building a community for health remains a guessing game. Our previous study found more compact and connected street networks highly correlated with increased walking, biking, and transit usage; while these trends suggest a health benefit, this study seeks to strengthen that connection.
Using a multilevel, hierarchical statistical model, this research seeks to fill this gap in the literature through a more robust accounting of street network design. Specifically, we ask the following: what is the influence of the three fundamental measures of street networks on obesity, diabetes, high blood pressure, heart disease, and asthma? We answer this question by examining 24 California cities exhibiting a range a street network typologies using health data from the California Health Interview Survey.
We control for the food environment, land uses, commuting time, socioeconomic status, and street design. The results suggest that more compact and connected street networks with fewer lanes on the major roads are correlated with reduced rates of obesity, diabetes, high blood pressure, and heart disease among residents. Given the cross-sectional nature of our study, proving causation is not feasible but should be examined in future research. Nevertheless, the outcome is a novel assessment of streets networks and public health that has not yet been seen but will be of benefit to planners and policy-makers.
... Although automobile travel and obesity may seem unrelated, there have been several studies that signify a relationship between them (Frank et al., 2004). A study of this issue in San Francisco, California, concluded that automobile travel is lower in regions where obesity is less prevalent (Pendola and Gen, 2007). A study among Colombian adults who do not have a car has shown a positive association between obesity and increased traveling in motor vehicles per week (Pregonero et al., 2012). ...
... The results of this study are consistent with recent studies that posit a relationship exists between automobile travel and obesity, such as those examining the impact of living in a "walkable" environment (e.g. Pendola and Gen (2007), Ewing et al. (2003), Frank et al. (2006), Frank and Engelke (2001)). Understanding the relationship between obesity and other societal factors can help to allay the considerable cost of obesity to the US economy, which was estimated to be $147 billion in 2008 (Finkelstein et al., 2009). ...
Objective:
The objective of this study is to assess the association between average adult body mass index (BMI), automobile travel, and caloric intake in the US in order to predict future trends of adult obesity.
Methods:
Annual BMI data (1984-2010) from the Behavioral Risk Factor Surveillance System (BRFSS), vehicle miles traveled data (1970-2009) from the Federal Highway Administration, licensed drivers data (1970-2009) from the Federal Highway Administration, and adult average daily caloric intake data (1970-2009) from the US Department of Agriculture were collected. A statistical model is proposed to capture multicollinearity across the independent variables.
Results:
The proposed statistical model provides an estimate of changes in the average adult BMI associated with changes in automobile travel and caloric intake. According to this model, reducing daily automobile travel by one mile per driver would be associated with a 0.21 kg/m(2) reduction in the national average BMI after six years. Reducing daily caloric intake by 100 calories per person would be associated with a 0.16 kg/m(2) reduction in the national average BMI after three years.
Conclusion:
Making small changes in travel or diet choices may lead to comparable obesity interventions, implying that travel-based interventions may be as effective as dietary interventions.
... Previous studies have examined the relationship between residential density and overweight/obesity, but the ndings have been contradictory (Doyle et al., 2006;Ewing et al., 2003;Lopez-Zetina et al., 2006). Some studies have found a negative relationship between residential density and overweight (Garden & Jalaludin, 2009;Rutt & Coleman, 2005), while others have not found any signi cant association (Kelly-Schwartz et al., 2004; Pendola & Gen, 2007). A study conducted in China by Wang et al. (2019) found that individuals living in neighborhoods with low and medium residential density were at a higher risk for overweight compared to those living in neighborhoods with higher residential density. ...
Due to the high rates of obesity and the lack of research on how the built environment contributes to obesity in Iran, this study aimed to investigate the relationship between density, accessibility to public transport and green spaces, obesity, and related diseases in Babol. Logistic regression was used to analyze data on health indicators such as body mass index (BMI), blood pressure, and diabetes, as well as environmental indicators including population density, residential density, accessibility to bus and taxi stations, the number of stations, the proximity to green spaces, and their proportion. The study found that living in areas with a density of over 120 people per square kilometer reduces the likelihood of being overweight or obese compared to areas with a density of 100 to 120 people. Access to green spaces within a 200-meter radius did not show a significant association with diseases. There was a weak negative relationship between the number of public transportation stations at different distances and body mass index, indicating lower levels of overweight and obesity. Changing from neighborhoods with lower residential densities to higher residential densities reduced the likelihood of developing heart disease and heart disease by about 74% and 44.4%, respectively. The presence of green spaces in neighborhoods had a weak correlation with physical activity and the reduction of obesity and related diseases. Increasing the number of taxi and bus stations from one to three within a 400-meter radius significantly reduced the likelihood of developing high blood pressure by approximately 70% and diabetes by 56.5% within a 200-meter radius. Living within a distance of less than 150 meters from the nearest public transportation station or nodal points was associated with a 51.3% lower probability of developing high blood pressure compared to living within a distance of 300 to 500 meters from public transportation stations.
... In terms of population density, a study based on the Atlanta SMARTRAQ travel survey by Bodea et al. (2009) showed that residents who live in neighborhoods with higher residential densities are 1.3 times less likely to be overweight and 1.5 times less likely to be obese. Similarly, a study in San Francisco showed that population density was negatively associated with individual BMI (Pendola & Gen, 2007). However, in the context of dense urban China, Sun et al. (2017) found that population density is positively associated with individual BMI. ...
The walkability of a neighborhood is closely related to residents’ travel behavior and daily life and, ultimately, their health and wellbeing. Although existing studies in this area have reached some enlightening conclusions, few of them have considered residents’ travel attitudes and preferences, or the mediating role of commute mode. Do travel attitudes and preferences matter in the relationship between neighborhood walkability and residents being obese? How does commute mode work as a mediator? To answer these questions, based on the 2019 travel survey data in Guangzhou, this paper uses the Multilevel Linear Model (MLM) to examine the association between neighborhood walkability and residents’ body mass index (BMI). Furthermore, the Mediation Model is used to identify the mediating role of commute mode in the relationship between walkability and BMI. The results show that (1) travel attitudes and preferences do affect the individual’s BMI through the mediator of commute mode. (2) After controlling the individual socio-demographics and travel attitudes and preferences, neighborhood walkability has a significant negative effect on BMI. Meanwhile, walkability has a significant positive effect on the use of non-private motorized commute modes. Non-private motorized commute modes have a significant negative effect on BMI. (3) The mediating effect of commute mode in the relationship of neighborhood walkability with the individual’s BMI is significant. The proportion of mediation is 32.90%. Insights into the relationship between neighborhood walkability, commute mode, and individual BMI highlight the importance of walkable neighborhoods that encourage people to use healthy commute modes.
... 2-4 From a public health perspective, creating more walkable neighbourhoods might be expected to lead to a healthier environment by encouraging reduced car usage and therefore lower car emissions and air pollution, and also by increasing opportunities for active transportation (physically active modes of transportation, such as walking, biking, rollerblading, skateboarding), which could increase overall levels of physical activity and decrease obesity. [5][6][7] Although a significant amount of research has shown that adults living in urban neighbourhoods walk more and have a lower bodymass index (BMI) than their suburban counterparts, other studies have found that this association is not consistent in all urban neighbourhoods or with all demographic groups. 4,8,9 Very little research has examined the impact of neighbourhood design on activity levels in children and youth, and the few studies that have looked specifically at youth activity have also produced mixed findings. ...
Objectives
To date, only a few studies have attempted to study the processes by which community design and the built and social environments affect individual physical activity, especially in children. Qualitative enquiry is useful for exploring perceptions and decision-making, and to understand the processes involved in how people interact with their environments. This study used qualitative methods to gain insight into the pathways linking the neighbourhood environment with children’s activity patterns.
Methods
Data were collected in semi-structured interviews with 24 child-parent dyads (children aged 10–14 years). Families lived in neighbourhoods ranging from lowest to highest median income and representing the three main design types found in Saskatoon - urban, semi-suburban and suburban.
Results
Parents and children underscored the importance of safe environments for children’s physical activity: streets or paths they can cycle on without feeling threatened, parks and green spaces free of criminal activity, and neighbourhoods where people know each other and children have friends to play with. Although grid-pattern urban neighbourhoods with a high density of destinations may in principle promote active transportation, the higher levels of crime and traffic danger that tend to exist in these areas may hinder physical activity in children.
Conclusion
Understanding what facilitates activity in children is a complex endeavour. It requires understanding the barriers to physical activity present at the neighbourhood level as well as social and perceptual factors that act in interdependent ways to either promote or hinder children’s physical activity.
... 2-4 From a public health perspective, creating more walkable neighbourhoods might be expected to lead to a healthier environment by encouraging reduced car usage and therefore lower car emissions and air pollution, and also by increasing opportunities for active transportation (physically active modes of transportation, such as walking, biking, rollerblading, skateboarding), which could increase overall levels of physical activity and decrease obesity. [5][6][7] Although a significant amount of research has shown that adults living in urban neighbourhoods walk more and have a lower bodymass index (BMI) than their suburban counterparts, other studies have found that this association is not consistent in all urban neighbourhoods or with all demographic groups. 4,8,9 Very little research has examined the impact of neighbourhood design on activity levels in children and youth, and the few studies that have looked specifically at youth activity have also produced mixed findings. ...
This study explored the influence of healthy vending contracts (HVC) on the nutritional quality of vending machine products in 46 Canadian publicly funded recreation and sport facilities. A quasi-experimental comparison design was used to examine the difference in nutritional quality of snack and beverage vending machine products at baseline (December 2015-May 2016) and 18-month follow-up. Staff Surveys assessed facility contract type (HVC or conventional) and vending machine audits identified product nutritional quality. Products were categorized by provincial guidelines as Do Not Sell (DNS), Sell Sometimes (SS) or Sell Most (SM). ANOVA compared categories cross-sectionally (HVC vs conventional) and repeated measures ANOVA compared them longitudinally (HVC-HVC, vs conventional-conventional and conventional-HVC). Approximately one quarter of contracts (24% beverage and 28% snack) had health stipulations at baseline or follow-up. Cross-sectionally, facilities with HVC at any time period had significantly lower percentage DNS (beverage: 56% vs 73%, p = 0.001; snack: 55% vs 85%, p < 0.001), higher SS (beverage: 24% vs 14%, p = 0.003; snack: 35% vs 12%, p < 0.001) and higher SM Products (beverage: 21% vs 13%, p = 0.030; snack: 10% vs 3%, p < 0.003). Longitudinally, facilities with consistent HVC or that changed to HVC showed greater decreases in DNS products over time (p < 0.050). Although less healthy products were still highly prevalent, facilities with HVC or that changed to HVC had fewer unhealthy products available in their vending machines over time compared to those without HVCs. Healthy vending contracts appear to be an effective change strategy.
... hemoglobin A1c for diabetes) (Loo et al., 2017). Conversely, time spent in vehicle travel has been associated with reduced physical activity, increased obesity, Type 2 diabetes and indicators of metabolic risk and increased mortality risk Goncalves et al., 2014;Hoehner et al., 2013;Jacobson et al., 2011;Lopez-Zetina et al., 2006;Nunez-Cordoba et al., 2013;Pendola and Gen, 2007;Reiner et al., 2013;Sugiyama et al., 2013;Warren et al., 2010). ...
Background and purpose: A growing body of evidence documents multiple ways in which land use and transportation investments influence health. To date, most evidence linking the built environment to health either focuses on behavioral change or environmental exposures. Few studies simultaneously assess how behavior and exposure-based impacts of the built environment interact. This is concerning as increased walkability and transit access can possibly lead to increased exposure to air pollution and injury risk. Method:
This paper synthesizes recent research on behavior and exposure-based mechanisms that connect land use and transportation investments with various health outcomes. Exploring the nexus between these pathways provides a framework to identify priority areas for research to inform policies and investments. Results:
The most studied pathway articulates how land use and transportation can support healthy behaviors, such as increased physical activity, healthy diet, and social interactions. The second pathway articulates exposure to harmful substances and stressors and potential differential impacts by travel modes. Increased rates of active travel lead to lower generation of vehicle emissions and kilometers traveled; but may actually result in increased exposure which may have adverse effects on sensitive populations such as elderly and youth. Unhealthy exposures have historically concentrated in areas where the most disadvantaged reside – along major transportation corridors where land is cheapest and more affordable housing is located. Implications: A high priority for future research is to examine mechanisms that spatially link built environment and chronic disease. More longitudinal evidence is required inclusive of biomarker data within clinical trials to isolate independent and interactive effects of biological and neurological mechanisms from behavioral and exposure related impacts of the environment. Downstream impacts of the built environment on healthcare utilization and costs and workforce productivity is needed for policy makers to justify the major investments required to plan or retrofit communities.
... Numerous factors could explain the significant positive association between 'residential density zones' and obesity found in women but not men. One possibility is that people who are living in lowdensity areas, such as in sprawling suburbs, tend to be car-dependent communities whereas those living in high-density areas such as central urban areas may have less reliance on cars [59,60]. Since driving a car is a relatively sedentary activity, those who rely on cars are more likely to have a higher BMI [27]. ...
Background: There is a lack of research pertaining to the links between built environment attributes and obesity in adults in the Eastern Mediterranean Region. In the Libyan context, no previous studies have been conducted to investigate this relationship. Therefore, the aim of this study was to examine associations between perceived neighbourhood built environmental attributes and obesity among Libyan men and women. The prevalence of overweight and obesity was also assessed. Methods: A cross-sectional study design was used for the population-based survey in Benghazi, Libya. A multi-stage cluster sampling technique was used to select Libyan adults from the Benghazi electoral register. The Physical Activity Neighbourhood Environment Scale (PANES) was used to measure participants’ perception of neighbourhood environmental factors. Using the Tanita BC-601 Segmental Body Composition Monitor and a portable stadiometer, anthropometric measurements were taken at a mutually agreeable place by qualified nurses. Results: Four hundred and one Libyan adults were recruited (78% response rate). Participants were aged 20–65 years, 63% were female, and all had lived in Benghazi for over 10 years. The prevalence of obesity and overweight was 42.4% and 32.9% respectively. A significant association was found between BMI and 6 neighbourhood environment attributes, specifically: street connectivity, unsafe environment and committing crimes at night, and neighbourhood aesthetics. For men only, these were: access to public transport, access to recreational facilities, and unsafe environment and committing crimes during the day. The attribute ‘residential density zones’ was only significant for women. Conclusions: The study suggests that Libyan people are at risk of living in neighbourhoods with unsupportive environmental features of physical activity, which are likely to promote obesity of both genders. The findings of this study could inform Libyan health policies about interventions in the obesogenic environments that might slow the obesity epidemic and contain the public health crisis. This study suggests that further research is needed, within the Libyan context, to explore the impact of the neighbourhood environment attributes on contributing to increased obesity.
... Car commuters have been shown to have higher odds of being overweight or obese, compared to non-car commuters (Laverty et al., 2013;Lindstrom, 2008). Frequent car use for commuting and errands has been associated with higher BMI (Pendola and Gen, 2007). A recent review has shown that longer car use (measured in time or in distance) was significantly associated with higher weight status in eight out of 10 studies (McCormack and Virk, 2014). ...
Objective: To examine associations of time spent sitting in cars with markers of cardio-metabolic risk in Australian adults.
Method: Data were from 2800 participants (age range: 34-65) in the 2011- 12 Australian Diabetes, Obesity and Lifestyle Study. Self-reported time spent in cars was categorized into four groups: ≤15 min/day; >15 to ≤30 min/day; >30 to ≤60 min/day; and >60 min/day. Markers of cardio-metabolic risk were BMI, waist circumference, systolic and diastolic blood pressure, triglycerides, HDL-cholesterol, fasting plasma glucose, 2-hr plasma glucose, a clustered cardio-metabolic risk score, and having the metabolic syndrome or not. Multilevel linear and logistic regression analyses examined associations of car time with each cardio-metabolic risk outcome, adjusting for socio-demographic and behavioral variables and medication use for blood pressure and cholesterol/triglycerides. Results: Compared to spending 15 min/day or less in cars, spending more than 1 hr/day in cars was significantly associated with higher BMI, waist circumference, fasting plasma glucose, and clustered cardio-metabolic risk, after adjusting for socio-demographic attributes and potentially relevant behaviors including leisure-time physical activity and dietary intake. Gender interactions showed car time to be associated with higher BMI in men only.
Conclusions: Prolonged time spent sitting in cars, in particular over 1 hr/day, was associated with higher total and central adiposity and a more-adverse cardio-metabolic risk profile. Further studies, ideally using objective measures of sitting time in cars and prospective designs, are needed to confirm the impact of car use on cardio-metabolic disease risk.
... Much of the literature on the commute modes of working-age adults have been cross-sectional in nature (Evans et al., 2002;Pendola and Gen, 2007;Handy and Xing, 2011;Hansson et al., 2011;Feng and Boyle, 2014), which presents challenges with understanding the relationship between changes in the commute landscape, such as improvements to transit, and mode choice, and similarly, between mode choice and health. Additionally, most previous research on this topic has been conducted in large metropolitan areas, especially in the USA, where transit improvements are often for higher-order infrastructure such as subways, light-rail transit, and bus rapid transit (Wener et al., 2003;Evans and Wener, 2006;Brown and Werner, 2007;Frank et al., 2007;Kam et al., 2011;Lachapelle and Noland, 2012). ...
Public transit ridership offers valuable opportunities for modest amounts of daily physical activity (PA). Transit is a more feasible option for most Canadian commuters who live too far from work to walk or cycle, yet public transit usage in midsized Canadian cities has historically remained low due to inefficient transit service.
The objectives of this longitudinal study were threefold: to assess whether the introduction of express transit service in the low-density city of Kingston, Ontario, has translated to greater transit use among a targeted employee group; to document the characteristics of those employees that have shifted to transit; and to examine the PA levels of employees using transit compared to other commute modes.
An online survey was administered in October 2013 and October 2014 to all non-student employees at Queen's University. 1356 employees completed the survey in 2013, and 1123 in 2014; 656 of these employees completed the survey both years, constituting our longitudinal sample.
Year-round transit ridership increased from 5.5% in 2013 to 8.5% in 2014 (p
... Conversely, each additional kilometre walked per day was associated with a 4.8% reduction. A cross-sectional survey found that individuals who reported higher levels of car use (particularly for trips to the shop and the work/school commute) had higher BMI scores (Pendola and Gen 2007). ...
The objective of this report is to consider the available evidence on the role of transport in increasing levels of physical activity, and so contribute to addressing the nation’s health problems caused by low levels of physical activity. Evidence on the links between transport and physical activity is examined, followed by examination of the effects of individual behaviour on physical activity. Whilst research on this topic has had some impact, there are a number on concerns about the approach, in particular the lack of evidence on long-term effects. Modifications to the built environment to increase physical activity are discussed: these need to be supported by other measures to be fully effective. The key relationship is between car use and physical activity. In order to increase levels of physical activity, it is necessary to reduce use of the car. Because so many households have adopted lifestyles that revolve around the use of the car, it is important to recognise that any policies to reduce car use must provide as much, or close to as much, accessibility as the car does. One way to do this is to shift the method of accessing cars from individual household ownership to a more flexible system of hiring or sharing cars. There would need to be a variety of supporting policy actions affecting transport and land use. It would be very useful to have a wide debate about transport modelling to ensure that the models represent travel and locational behaviour effectively, including factors that represent physical activity; the discussion should include the cost effectiveness of making changes to the existing modelling system. The implementation of the approach presented in the report could lead to significant improvements in the health of the nation and cost savings to the National Health Service.
... The literature suggests that levels of physical activity (walking for transportation and recreation, and vigorous exercise) increase in neighbourhoods with ''traditional'' or ''walkable'' designs and where there are pleasant safe parks and green spaces (Bauman et al., 1999;Ellaway, Macintyre, & Bonnefoy, 2005). Walkabillity, was associated with higher levels of moderate PA (Physical Activity) (Cerin et al., 2007), and reduction in body mass index (Frank et al., 2006;Leslie et al., 2007;Pendola & Gen, 2007). ...
... Increased walkability of streets would decrease the risk of overweight [39], each kilometer walked per day decreasing the likelihood of obesity by 5% and each hour spent in a car per day increasing the likelihood of obesity by 6% [40]. People are leaner in areas in which a higher percentage of the population walks to work [12], while those using a car for work travels or trips to grocery stores are fatter [41,42]. ...
The effect of urban sprawl on body weight in Finland is not well known. To provide more information, we examined whether body mass index (BMI) and the prevalence of overweight are associated with an individual's distance to the local community centre and population density in his/her resident area.
The sample consisted of 5363 men and women, members of the Northern Finland Birth Cohort 1966 (NFBC), who filled in a postal questionnaire and attended a medical checkup in 1997, at the age of 31 years. Body mass index (BMI; kg/m2) and the prevalence of overweight (BMI >= 25.0 kg/m2) were regressed on each subject's road distance to the resident commune's centre and on population density in the 1 km2 geographical grid in which he/she resided, using a generalized additive model. Adjustments were made for sex, marital status, occupational class, education, leisure-time and occupational physical activity, alcohol consumption and smoking.
The mean BMI among the subjects was 24.7 kg/m2, but it increased by increasing road distance (by 1.3 kg/m2 from 5--10 to 20--184 km) and by decreasing population density (by 1.7 kg/m2 from 1000--19,192 to 1--5 inhabitants/km2). The respective increases in overweight (overall prevalence 41%) were 13 per cent units for distance and 14 per cent units for population density. Adjusted regressions based on continuous explanatory variables showed an inverse L-shaped pattern with a mean BMI of 24.6 kg/m2 at distances shorter than 5 km and a rise of 2.6 kg/m2 at longer distances, and an increase of 2.5 kg/m2 from highest to lowest population density. The associations with road distance were stronger for women than men, while the sex difference in association with population density remained indeterminate.
We conclude that young adults in Northern Finland who live far away from local centres or in the most sparsely populated areas are fatter than those who live close to local centres or in densely populated areas. The likely explanations include variations in everyday physical activity in different residential environments, although causality of the associations remains to be confirmed.
... Galster (2001) notes that this term is not easily defined but generally refers to the patterns, processes, causes, and consequences of low-density and segregated-land use development in populated places. Sprawl has been criticized as having negative social impacts, such as increased racial and economic segregation (Yang and Jargowsky, 2006), and impacts on individual health, including increased childhood obesity (Ewing et al., 2006) and body mass index (Pendola and Gen, 2007;Ross et al., 2007) due to its influence on transportation choices. Sprawl has also been described as a comparatively costly design for municipalities to serve with public services such as water and sewer infrastructure (Speir and Stephenson, 2002) and roads (Burchell and Mukherji, 2003). ...
The objective of this research was to develop methods for urban land cover analysis using QuickBird high spatial resolution satellite imagery. Such imagery has emerged as a rich commercially available remote sensing data source and has enjoyed high-profile broadcast news media and Internet applications, but methods of quantitative analysis have not been thoroughly explored. The research described here consists of three studies focused on the use of pan-sharpened 61-cm spatial resolution QuickBird imagery, the spatial resolution of which is the highest of any commercial satellite. In the first study, a per-pixel land cover classification method is developed for use with this imagery. This method utilizes a per-pixel classification approach to generate an accurate six-category high spatial resolution land cover map of a developing suburban area. The primary objective of the second study was to develop an accurate land cover change detection method for use with QuickBird land cover products. This work presents an efficient fuzzy framework for transforming map uncertainty into accurate and meaningful high spatial resolution land cover change analysis. The third study described here is an urban planning application of the high spatial resolution QuickBird-based land cover product developed in the first study. This work both meaningfully connects this exciting new data source to urban watershed management and makes an important empirical contribution to the study of suburban watersheds. Its analysis of residential roads and driveways as well as retail parking lots sheds valuable light on the impact of transportation-related land use on the suburban landscape. Broadly, these studies provide new methods for using state-of-the-art remote sensing data to inform land cover analysis and urban planning. These methods are widely adaptable and produce land cover products that are both meaningful and accurate. As additional high spatial resolution satellites are launched and the cost of high resolution imagery continues to decline, this research makes an important contribution to this exciting era in the science of remote sensing.
... While this assumption has not been adequately evaluated, population density has been empirically linked to higher active transportation suggesting that high density neighborhoods have more destinations to travel to for the residents. That said, higher density is not always associated with lower BMI (Frank et al., 2004;Pendola and Gen, 2007;Ross et al., 2007) and as shown in the present study the density-obesity relationship can vary according to gender and likely other demographic factors as well (Frank et al., 2004). The density-obesity link needs to be further explored. ...
Using data from the 2003-2008 waves of the continuous National Health Nutrition Examination Survey merged with the 2000 census and GIS-based data, this study conducted genderspecific analyses to explore whether neighborhood built environment attributes are significant correlates of obesity risk and mediators of obesity disparities by race-ethnicity. Results indicate that the built environment is a significant correlate of obesity risk but is not much of a mediator of obesity disparities by race-ethnicity. Neighborhood walkability, density, and distance to parks are significant covariates of obesity risks net of individual and neighborhood controls. Gender differences are found for some of these associations.
... Analysis on the relationship between automobile travel and obesity in the United States has shown that automobile use tends to be lower in the regions that exhibit lower levels of obesity (e.g., Frank et al., 2004;Lopez-Zetina et al., 2006;Pendola and Gen, 2007). A recent study in Atlanta, Georgia, found that spending an additional hour per day in a car increased an individual's odds of being obese by 6% (Frank et al., 2004). ...
Due to the high rates of obesity in Iran, this study aimed to investigate the relationship between density, accessibility to public transport and green spaces, obesity, and related diseases in Babol. Data was collected from 1200 participants, and logistic regression was employed to analyze health indicators such as body mass index (BMI), blood pressure, and diabetes, alongside environmental indicators including population density, residential density, accessibility to bus and taxi stations, the number of stations, and green space area. The study found that living in areas with a density of over 120 people per square kilometer reduces the likelihood of being overweight or obese compared to areas with a density of 100 to 120 people. Access to green spaces within a 200-meter radius did not show a significant association with diseases. There was a weak negative relationship between the number of public transportation stations at different distances and body mass index, indicating lower levels of overweight and obesity. Changing from neighborhoods with lower residential densities to higher residential densities reduced the likelihood of developing heart disease and heart disease by about 74% and 44.4%, respectively. The presence of green spaces in neighborhoods had a weak correlation with the reduction of obesity and related diseases. Increasing the number of taxi and bus stations from one to three within a 400-meter radius significantly reduced the likelihood of developing high blood pressure by approximately 70% and diabetes by 56.5% within a 200-meter radius. Living within a distance of less than 150 meters from the nearest public transportation station or nodal points was associated with a 51.3% lower probability of developing high blood pressure compared to living within a distance of 300 to 500 meters from public transportation stations. Based on the findings, the paper presents possible implications for policy and practice.
Introduction:
COVID-19 has impacted millions of commuters by decreasing their mobility and transport patterns. While these changes in travel have been studied, less is known about how commute changes may have impacted individuals' body mass index (BMI). The present longitudinal study explores the relationship between commute mode and BMI of employed individuals in Montréal, Canada.
Methods:
This study uses panel data drawn from two waves of the Montréal Mobility Survey (MMS) conducted before and during the COVID-19 pandemic (n = 458). BMI was modeled separately for women and men as a function of commuting mode, WalkScore©, sociodemographic, and behavioral covariates using a multilevel regression modeling approach.
Results:
For women, BMI significantly increased during the COVID-19 pandemic, but telecommuting frequency, and more specifically telecommuting as a replacement of driving, led to a statistically significant decrease in BMI. For men, higher levels of residential local accessibility decreased BMI, while telecommuting did not have a statistically significant effect on BMI.
Conclusions:
This study's findings confirm previously observed gendered differences in the relations between the built environment, transport behaviors, and BMI, while offering new insights regarding the impacts of the changes in commute patterns linked to the COVID-19 pandemic. Since some of the COVID-19 impacts on commute are expected to be lasting, findings from this research can be of use by health and transport practitioners as they work towards generating policies that improve population health.
A revised version of popular handbook Spacematrix is released, where the authors demystify the use of concepts such as ‘urbanity’, ‘compact city’ and ‘park city’ by challenging the reliability of such concepts and critically examining the possibility of redefining them through quantification using multiple density measures.
What's new?
Meta Berghauser Pont says the extended version of the book Spacematrix is new in three ways, and first of all provides new insights on the effects of density through the inclusion of a systematic review of more than 200 empirical studies around the globe, including aspects such as mobility, economics, and health. Second is the trend of increased space consumption and decreased density in Amsterdam that was discussed in the 2010 edition is updated to also include recent development in Amsterdam and compared to developments worldwide.
She continues: Very interesting is that this decrease in density is not a phenomenon unique for Amsterdam but a general phenomenon in Asia, North and South America and Europe. However, through the detailed analysis of Amsterdam, we have been able to reveal a trend break. In Amsterdam, since 2000, densities have started to increase, from 63 inhabitants per hectare in 2000 to 74 in 2020. That is almost 20 percent! The third main streak added in the 2021 version is the database of building types, which is extended with two more cities in Europe and covers now Amsterdam, Berlin, Barcelona, London, and Stockholm. Examples from three Asian cities are used to contextualize the European examples.
Do higher urban densities contribute to more sustainable cities and communities? This paper examines the effectiveness of higher density (as a means) for achieving sustainable urban development (the goal) following three lines of inquiry. First, a systematic review of scientific literature (229 empirical studies) is presented on the effects of urban density. Second, the motivations for increasing urban density are studied in a systematic review of Swedish planning practices based on the comprehensive urban plans in 59 municipalities. Third, these two studies are compared to find matches and mismatches between evidence and practice. Although positive effects exist for public infrastructure, transport, and economics, there are also considerable negative environmental, social and health impacts. This creates a challenging task for urban planners to assess the trade-offs involving densification and accommodate current urbanization rates. Some topics are found to be over-represented in research (transport effects), seldom discussed in practice (environmental impact except) and misaligned when comparing motives and evidence (social impact). Furthermore, for some topics, urban density thresholds are found that are important because they may explain some divergences of results between studies.
Problem, research strategy, and findings: The literature widely reports a statistical association between the built environment and obesity. What is less clear is the reason for the association. Is it environmental determinism—the effect of the built environment on individual behavior—with compact places inducing more physical activity and hence lower weight? Or is it self-selection, the tendency of healthy-weight individuals to select to live in compact places where they can be more physically active and possibly the tendency of overweight or obese individuals to opt for sprawling places? Both theories have been promoted in the literature. In this study we seek to address this issue using data from the National Longitudinal Survey of Youth. We study body mass indices (BMIs) of survey participants, all young adults, at two points in time and follow them longitudinally for 9 years as they move from place to place. We estimate models for the entire cohort and also for young adult movers and stayers separately. We find more evidence of self-selection than of environmental determinism. First, we find that compactness is not significantly associated with BMI in young adults for those staying in the same place for the entire period. Second, we find no significant association between changes in sprawl and the changes in BMI for the cohort of young adult movers. Third, our longitudinal analysis shows that young adults who are not overweight tend to move in the direction of greater neighborhood compactness, whereas overweight young adults tend to move in the direction of greater sprawl. Because young adults are at a unique stage in the life cycle, these findings cannot be generalized to other cohorts.
Takeaway for practice: These findings do not suggest that place characteristics are unimportant; planners need to meet the growing demand for walkable, compact, and connected places, which are currently undersupplied. Still, they do not provide evidence that place characteristics influence the behaviors of young adults and hence their weight. Rather, they suggest that compact places appeal to more than half of the young adult population and that this latent demand should be met by providing dense, diverse, and well-designed residential options, even in the suburbs, through regional transportation plans and local planning and zoning. Education for primary and secondary school students, who are about to enter young adulthood, could also play a role.
Background
Residential density was found to be associated with excess body weight among adults in Western societies but it remains unclear in China. We aimed to explore the relationship between residential density and excess body weight among adults in China.
Methods
This cross-sectional study was conducted in 2017 in urban areas of Nanjing, China. A multi-stage sampling method was used to randomly select participants aged 35–74 years from 8 urban neighborhoods in Nanjing. Status of excess body weight was the outcome variable which was categorized as "yes (BMI≥24)" or "no (BMI<24)" according to specific recommendations for Chinese adults. Residential density was the main explanatory variable which was grouped into tertiles. Odds ratios (OR) and 95% confidence interval (CIs) were calculated to assess the relationship between residential density and excess body weight using mixed-effects regression models after adjusting for age, sex, education, occupation, marital status, redmeat, smoking, physical activity, diabetic status and potential neighborhood-level clustering effect.
Results
A total of 1551 participants were recruited with a response rate of 98.9% (1551/1568). The mean age (standard deviation) of participants was 54.7 (11.1) years, and 46% of them were men. With adjustment for potential influential factors, participants in neighborhoods with lower (OR = 1.38, 95% CI = 1.06–1.81) and middle (OR = 1. 29, 95% CI = 1. 01, 1. 64) tertile of residential density were at significantly higher risk of gaining excess body weight relative to their counterparts in communities with upper tertile of residential density. Such a negative association between residential density and excess body weight was observed for men only after stratified analysis by gender.
Conclusions
A negative association between residential density and excess body weight was identified in overall and male urban Chinese adults, and the association was independent of physical activity. Results of our study have important implications in guiding public health policy making regarding prevention of excess body weight at community level via establishment of health-friendly neighborhood environment in China.
Objective:
This study aims to identify groups of the social and built environment factors that have been studied substantially along with factors that need further attention, to guide the research, designing, and planning of the social and built environment for reducing obesity prevalence.
Data source:
A systematic search of literature was undertaken from PubMed, Google Scholar, and Web of Knowledge.
Study inclusion and exclusion criteria:
Keyword combination of "built environment," "social environment," and "obesity" were used to expand the search scope. Exclusion criteria included (1) any article with less than 50 citations from 2005 to 2010, and those with less than 25 citations from 2011 to 2015. In this way we included the most prominent peer-reviewed studies published in recent years while excluding less influential publications; (2) any article published in a language other than English; (3) literature review articles; (4) any article studying health outcomes not obesity related. We included research on eating behaviors since the studies contributed profoundly to food environment research.
Data synthesis:
A meta-analysis of 153 empirical studies, selected from 2005 to 2015 based on a series of criteria, was conducted using factor analysis. The exploratory factor analysis was undertaken to group the prevalence and use of the social and built environment factors associated with obesity.
Results:
The findings suggested that the research community has gained a substantial understanding of the D variables of the built environment, including density, diversity, design, distance to transit, and destination access. Factors concerning different age groups, minority populations, groups with low socioeconomic status, food environment, and street-level urban design features have been less examined.
Conclusions:
The findings are important to guide future research directions, giving more attention to the factors in need of more in-depth research.
Background
The health and social consequences of longer vehicle commutes have been observed in other studies. This study explores whether daily vehicle time during pregnancy is associated with greater mental health symptoms. As travel behavior can be related to where one can afford to live, we examined this by income groups.
Methods
We utilized a subsample of the 2007 Los Angeles Mommy and Baby study of more than 500 women, a cross-sectional survey with current and retrospective reporting. We modelled mental health symptoms during pregnancy and postpartum stratified by income.
Results
Women in this Los Angeles County study spend an average of 2 hours in daily vehicle travel. We found, controlling for physical inactivity and other stress events, that vehicle time was positively associated with mental health symptoms during pregnancy and postpartum among low income women only.
Conclusions
To our knowledge, this is the first paper to examine the mental health impact of daily vehicle time among pregnant women. From a policy perspective, this study points to what housing affordability, neighborhood accessibility, and workplace policies could mean for pregnant women and their families. Vehicle time is a daily demand that can compete with important health behaviors for pregnant women. The impact on low income women only could reflect other experiences in their lives (e.g. occupation, the lack of neighborhood choice and quality). In addition, there is research to suggest that higher income women can “buy back” some of their time. These are areas for future research.
Using data from China Family Panel Studies (CFPS), this paper examines the impacts of the built environment on individual BMI and the risk of overweight, directly and indirectly mediated by mode choice with structural equation model (SEM). The results suggest that population density and facilities accessibility are positively associated with individual BMI and distance to the nearest bus stop is negatively associated, both directly and totally, differing from the mainstream views of Western developed countries. Thus, Chinese healthy policies should orient itself toward improving the walkability and cycling-friendliness of open spaces rather than increasing density and facilities accessibility of communities as Western developed countries did.
Background
Auto-dependence has been linked to the physical inactivity epidemic across U.S. cities, resulting in unprecedented increases in incidences of obesity, cardiovascular diseases, depression, etc. The search for strategies to pull an overwhelming majority of auto-dependents out of their sedentary lifestyles by encouraging them to use transit, walk and bike continues to challenge planners and policy-makers.
Methods
We use the 2012–13 California Household Travel Survey data for analyzing the auto-dependence and physical inactivity connection. We select a sample of employed individuals with access to car in urban California, and classify them as discretionary transit riders (N=390), active auto-dependents (N=1287), or sedentary auto-dependents (N=8754) based on their self-reported travel mode use and time spent in physical activity over a 24-h period. We investigate factors that are associated with significantly high physical activity among some auto-dependents relative to the sedentary majority. We also revisit the transit-physical activity connection, and explore conditions that make transit use unfeasible for some active auto-dependents.
Results
Discretionary transit use is associated with higher physical activity. However, there is large variation in physical activity within auto-dependents; significantly higher physical activity is associated with factors such as higher income, flexible work schedule, shorter work hours, and mixed land use. Kids, inflexibility of work schedule, low residential density, lack of pedestrian and bicycling friendly street design, and long distance to transit stops prohibit otherwise active auto-dependents from choosing transit. Employment sector influences both physical activity and choice of transit.
Conclusion
To get sedentary auto-dependents out of endemic physical inactivity, our research indicates the need for targeting lower-incomes, incentivizing employers to provide flexible work hours, and to continue dense, mixed-use developments that make active travel feasible. In addition, to get active auto-dependents to use transit, transit managers must focus on retaining immigrant riders and non-Hispanic Asians, and attracting people with children.
The built, or physical, environment consists of its man-made, constructed components – roads and sidewalks, buildings and houses, parks and plazas, and more. Currently, our physical environment is built to accommodate and prioritize motorized transport, cars especially. Travel has been redirected to cars, reducing opportunities for active travel. In examining the built environment and its relationship to obesity, we must acknowledge that the built environment has no direct or immediate effect on obesity; rather, obesity is linked to the built environment as a consequence of human behavior – in this case physical activity. This chapter strives to objectively connect the built environment at varying urban scales – macro, meso, and micro – to the issue of obesity. Aspects of the built environment – specifically, conditions attributable to walkability and urban sprawl – are examined as contributing factors to (in)active travel. Also discussed is the importance of and need for more longitudinal studies to counter the plethora of cross-sectional studies. While cross-sectional studies can adequately define conditions at a point in time, longitudinal studies provide opportunities to establish causality. Self-selection bias is also considered, as it is a source of concern in some studies. We conclude by noting that rates of obesity have risen as our cities have become less walkable and more auto-dependent. Research at all three urban scales finds some relationship between the built environment and active travel but research is not without its shortcomings. More research is still needed, longitudinal and that which controls for self-selection bias in particular, and remains an important arena for further inquiry.
IPCC should more systematically consider health co-bene ts (and potential risks) of trans- port mitigation strategies to highlight policies with the greatest overall gains for society. The IPCC Fourth Assessment Report gives little, if any, consideration to health impacts. Improved active transport and rapid transit/ public transport is not only healthy: it is cost e ective. Studies cited by IPCC of Latin American cities note the large greenhouse gas (GHG) mitigation potential (25%) and relatively low cost (US $30/tonne CO2 reduced) for a package of bus- rapid transit (BRT), pedestrian upgrades and cycleways
Objective: To assess whether poor geographic accessibility to prenatal care, as indicated by long distance trips to prenatal care, produced high blood pressure (HPB) during pregnancy.
Methods: Using the 2007 Los Angeles Mommy and Baby Study for women without hypertension prior to pregnancy (n = 3405), we compared self-reported HBP by travel distance to prenatal care controlling for age, race/ethnicity, marital status, education, household income, weight status, and physical activity.
Results: Results of the multilevel logistic regression shows traveling more than 50 mi to prenatal care is associated with an increased odds for having HPB during pregnancy (odds ratio [OR] = 2.867, 95% confidence interval [CI] = 1.079,7.613), as compared with a travel distance shorter than 5 mi. Traveling 5–14 mi (OR = 0.917, 95% CI = 0.715–1.176), 15–29 mi (OR = 0.955, 95% CI = 0.634–1.438), or 30–50 mi (OR = 1.101, 95% CI = 0.485–2.499) were not significantly associated with more risk of HBP during pregnancy.
Conclusion: To our knowledge, no previous studies have examined the association between poor geographic accessibility to care and the possible harms of travel burdens for pregnant women. Future research that replicates these findings can assist in developing recommendations for pregnant women and health-care accessibility.
The built, or physical, environment consists of its man-made, constructed components – roads and sidewalks, buildings and houses, parks and plazas, and more. Currently, our physical environment is built to accommodate and prioritize motorized transport, cars especially. Travel has been redirected to cars, reducing opportunities for active travel. In examining the built environment and its relationship to obesity, we must acknowledge that the built environment has no direct or immediate effect on obesity; rather, obesity is linked to the built environment as a consequence of human behavior – in this case physical activity. This chapter strives to objectively connect the built environment at varying urban scales – macro, meso, and micro – to the issue of obesity. Aspects of the built environment – specifically, conditions attributable to walkability and urban sprawl – are examined as contributing factors to (in)active travel. Also discussed is the importance of and need for more longitudinal studies to counter the plethora of cross-sectional studies. While cross-sectional studies can adequately define conditions at a point in time, longitudinal studies provide opportunities to establish causality. Self-selection bias is also considered, as it is a source of concern in some studies. We conclude by noting that rates of obesity have risen as our cities have become less walkable and more auto-dependent. Research at all three urban scales finds some relationship between the built environment and active travel but research is not without its shortcomings. More research is still needed, longitudinal and that which controls for self-selection bias in particular, and remains an important arena for further inquiry.
Aim. The aim of the study was to investigate the associations between physical activity level, social demographic characteristics and environment in Chinese middle-aged and older adults, and to evaluate the physical activity-related environment of urban areas. Methods. Sociodemographics and perceived environment were assessed by questionnaires distributed to 1100 participants, aged 45-80 years, of 13 selected communities belonging to three districts from urban centers, subcivic centers and suburbs of Shanghai between April-October 2009. Physical activity was measured by a pedometer. The analysis of relationship between physical activity and environment and the evaluation of communities and districts of Shanghai were conducted with the method of gray correlation analysis in January-June, 2010. Results. Bivariate relationship analysis showed how employment status, education, "whether walking is the main exercise", health status have positive and body mass index has negative associations with physical activity; bodybuilding club, traffic safety, street design, ground surface, crossing the street and activity environment are the largest six factors affecting physical activities. The order of comprehensive evaluation of the three districts is: LuWan, YangPu and MinHang; the order of 13 communities is: N3 > N2 > N4 > N,0 > N9 > N n > N7 > N 6 > N5 > N8 > N, > NI 2 > N13. From above, the urban center environment is most appropriate for physical activity, subcivil center ranks the second position and suburbs the last. The urban environment is most appropriate for physical activity, subcivil center ranks the second position and suburb the last. The logical result proved the gray correlation analysis is an effective method to study the relationship between physical activity and environment. Conclusion. These findings collectively suggest that public health, city planning and environment protecting need to consider how to create more livable and pedestrian-friendly community areas, especially in developing countries, as China.
There has been increasing attention paid to children and young people's mobility in Australian transport research in recent years but the majority of studies to date have been conceptually narrow and focused on primarily on transport modes for school travel. In contrast, this paper presents findings from a doctoral research project exploring more broadly some of the social and spatial dimensions of mobility of children and young people living in Blacktown, western Sydney; a large, diverse and growing urban region. The study involved children, aged 9 to 12 years, and young people, aged 13 to 15 years, from government primary and high schools across five different localities in Blacktown local government area. The study applied a child-focused, mixed-method approach that included interactive classroom activities and discussion as well as individual drawings, travel and activity diaries and semi-structured interviews. Engaging the young participants in these activities produced a range of materials from which both quantitative and qualitative data was obtained. Unlike the high levels of car-dependence found in studies of school travel, this research found some notable variations in mobility of children and young people to other activities in terms of their levels of independent mobility and active travel. These variations were particularly evident across age and gender and between the different locations. Comments from the children and young people about their mobility enriched the interpretation of the findings and underscored the value of considering social and spatial differences in transport policy and planning in order to better meet the diversity of needs within local communities.
The term “co-benefits” refers to positive outcomes accruing from a policy beyond the intended outcome, often or usually in other sectors. In the urban context, policies implemented in particular sectors (such as transport, energy or waste) often generate multiple co-benefits in other areas. Such benefits may be related to the reduction of local or global environmental impacts and also extend into the area of public health. A key to identifying and realising co-benefits is the adoption of systems approaches to understand intersectoral linkages and, in particular, the translation of this understanding to improved sectorspecific and city governance. This paper reviews a range of policies which can yield health and climate co-benefits across different urban sectors and illustrates, through a series of cases, how taking a systems approach can lead to innovations in urban governance which aid the development of healthy and sustainable cities.
Objectives:
To date, only a few studies have attempted to study the processes by which community design and the built and social environments affect individual physical activity, especially in children. Qualitative enquiry is useful for exploring perceptions and decision-making, and to understand the processes involved in how people interact with their environments. This study used qualitative methods to gain insight into the pathways linking the neighbourhood environment with children's activity patterns.
Methods:
Data were collected in semi-structured interviews with 24 child-parent dyads (children aged 10-14 years). Families lived in neighbourhoods ranging from lowest to highest median income and representing the three main design types found in Saskatoon - urban, semi-suburban and suburban.
Results:
Parents and children underscored the importance of safe environments for children's physical activity: streets or paths they can cycle on without feeling threatened, parks and green spaces free of criminal activity, and neighbourhoods where people know each other and children have friends to play with. Although grid-pattern urban neighbourhoods with a high density of destinations may in principle promote active transportation, the higher levels of crime and traffic danger that tend to exist in these areas may hinder physical activity in children.CONOCLUSION: Understanding what facilitates activity in children is a complex endeavour. It requires understanding the barriers to physical activity present at the neighbourhood level as well as social and perceptual factors that act in interdependent ways to either promote or hinder children's physical activity.
Background:
Seldom studies are about the relationship between built environment and physical activity, weight, and health outcome in meso- and microscales.
Methods:
1100 residents aged 46 to 80 were recruited from 80 neighborhoods of 13 selected communities of Shanghai, China. An analysis of the relationship between dependent variables (physical activity, Body Mass Index [BMI], overweight/obesity, weight, and health outcomes) and independent variables (involved a geographic-information-system-derived measure of built environment) was conducted with hierarchical linear models.
Results:
Street connectivity was positively associated with physical activity (P < .01). River proximity was inversely related with overweight/obesity (P = .0220). Parkland and square proximity have a significant relationship with physical activity (P = .0270, .0010), BMI (P = .0260, .0130), and overweight/obesity (P = .0020, .0470). Land-use mix was positively associated with physical activity (P < .01) and inversely associated with BMI (P = .0240) and overweight/obesity (P = .0440). Green and open spaces were positively related with BMI (P < .01) and health status (P < .01). For residential style, residents living in a village were more likely to have a lower BMI and overweight/obesity than those living in an urban old or newer residential building. The direct effect of square proximity is much stronger than the indirect effect on BMI through physical activity.
Conclusions:
The findings can help planners build more pedestrian-friendly communities. They are also useful for creating interventions that are sensitive to possible environmental barriers to physical activity in older adults.
Understanding which physical environmental factors affect adult obesity, and how best to influence them, is important for public health and urban planning. Previous attempts to summarise the literature have not systematically assessed the methodological quality of included studies, or accounted for environmental differences between continents or the ways in which environmental characteristics were measured.
We have conducted an updated review of the scientific literature on associations of physical environmental factors with adult weight status, stratified by continent and mode of measurement, accompanied by a detailed risk-of-bias assessment. Five databases were systematically searched for studies published between 1995 and 2013.
Two factors, urban sprawl and land use mix, were found consistently associated with weight status, although only in North America.
With the exception of urban sprawl and land use mix in the US the results of the current review confirm that the available research does not allow robust identification of ways in which that physical environment influences adult weight status, even after taking into account methodological quality.
Background:
Rising rates of overweight and obesity in the U.S. have increased interest in community designs that encourage healthy weight. This study relates neighborhood walkability-density, pedestrian-friendly design, and two novel measures of land-use diversity-to residents' excess weight.
Methods:
Walkable-environment measures include two established predictors, higher density and pedestrian-friendly design (intersections within 0.25 mile of each address), and two new census-based, land-use diversity measures: the proportion of residents walking to work and the median age of housing. In 2006, weight, height, age, and address data from 453,927 Salt Lake County driver licenses for persons aged 25-64 years were linked to 2000 Census and GIS street-network information that was analyzed in 2007-2008. Linear regressions of BMI and logistic regressions of overweight and obesity include controls for individual-level age and neighborhood-level racial/ethnic composition, median age of residents, and median family income.
Results:
Increasing levels of walkability decrease the risks of excess weight. Approximately doubling the proportion of neighborhood residents walking to work decreases an individual's risk of obesity by almost 10%. Adding a decade to the average age of neighborhood housing decreases women's risk of obesity by about 8% and men's by 13%. Population density is unrelated to weight in four of six models, and inconsistently related to weight measures in two models. Pedestrian-friendly street networks are unrelated to BMI but related to lower risks of overweight and obesity in three of four models.
Conclusions:
Walkability indicators, particularly the two land-use diversity measures, are important predictors of body weight. Driver licenses should be considered as a source of data for community studies of BMI, as they provide extensive coverage at low cost.
Objectives:
We examined the association of participation in community gardening with healthy body weight.
Methods:
We examined body mass index (BMI) data from 198 community gardening participants in Salt Lake City, Utah, in relationship to BMI data for 3 comparison groups: neighbors, siblings, and spouses. In comparisons, we adjusted for gender, age, and the year of the BMI measurement.
Results:
Both women and men community gardeners had significantly lower BMIs than did their neighbors who were not in the community gardening program. The estimated BMI reductions in the multivariate analyses were -1.84 for women and -2.36 for men. We also observed significantly lower BMIs for women community gardeners compared with their sisters (-1.88) and men community gardeners compared with their brothers (-1.33). Community gardeners also had lower odds of being overweight or obese than did their otherwise similar neighbors.
Conclusions:
The health benefits of community gardening may go beyond enhancing the gardeners' intake of fruits and vegetables. Community gardens may be a valuable element of land use diversity that merits consideration by public health officials who want to identify neighborhood features that promote health.
Transport is associated with environmental problems, economic losses, health and social inequalities. A number of European and US cities have implemented initiatives to promote multimodal modes of transport. In Latin America changes are occurring in public transport systems and a number of projects aimed at stimulating non-motorized modes of transport (walking and cycling) have already been implemented. Based on articles from peer-reviewed academic journals, this paper examines experiences in Bogotá (Colombia), Curitiba (Brazil), and Santiago (Chile), and identifies how changes to the transport system contribute to encourage active transportation. Bus rapid transit, ciclovias, bike paths/lanes, and car use restriction are initiatives that contribute to promoting active transportation in these cities. Few studies have been carried out on the relationship between transport and physical activity. Car ownership continues to increase. The public health sector needs to be a stronger activist in the transport policy decision-making process to incorporate health issues into the transport agenda in Latin America.
Obesity has become a major health and economic problem with increasing prevalence. Unfortunately, no country can act as public health exemplar for reduction of obesity. The finding of associations between sedentary behaviors and obesity, independent of the level of physical activity, may offer new insights to prevent this burdensome problem.
To evaluate prospectively the relationship between annual distance traveled by motor vehicles and subsequent incidence of overweight or obesity in a Mediterranean cohort.
Data from a prospective cohort study (Seguimiento Universidad de Navarra Project, 1999-2011) with a permanently open recruitment were analyzed. Self-administered questionnaires are mailed every 2 years, collecting information on dietary habits, lifestyle, risk factors, and medical conditions. Annual kilometers traveled by motor vehicles were grouped into three categories (≤10,000; >10,000 to ≤20,000; and >20,000). Multivariate Cox regression analyses were used to assess the risk of overweight or obesity across categories of distance traveled annually.
In all, 9160 participants (58% female, average age=37 years) were followed up for a median of 6.4 years. During 39,175 person-years of follow-up, 1044 (15.3%) normal-weight participants at baseline became overweight or obese. Among participants who did not change their category of annual kilometers traveled during follow-up, an increased risk of overweight or obesity in the highest category of annual kilometers traveled was observed, compared with the lowest one (hazard ratio=1.4, 95% CI=1.1, 1.7).
This study suggests a potential pernicious effect of the use of motor vehicles on the risk of overweight or obesity.
A growing body of evidence suggests that the built environment influences people's propensity to lead (un)healthy lifestyles. Researchers have suggested that some environments may promote sedentary lifestyles, while providing access to large amounts of energy dense foods and as such these have been labelled ‘obesogenic’. Further, the concept of ‘environmental justice’ has been used to explain the disproportionate exposure to harmful environments by poorer communities. The complex dynamics of how individuals interact with the built environment, in terms of physical activity and eating behaviours, however, is still little understood. This paper is based on a pilot study which explored the use and location of six ‘Wellness Centres’ in Sunderland—a post-industrial city in the North East of England with high deprivation rates and a poor health profile. Although a small study, the research suggests that there were links between the type of neighbourhood and the life styles displayed by the Centre users. It proposes that the seemingly more active lifestyles of the inner-city residents accompanied by lower mean BMIs, suggests that some neighbourhoods are more supportive of known aspects of healthy lifestyles than others and, furthermore, these relationships are not directly related to socio-economic status.
Nutritional protein and body mass index, the neglected correlation Background. The temporal association between modern food habits, the occurrence of fast food, the trend towards convenience products, and the epidemic occurrence of obesity is evi-dent. The causal relation remains less evident. Material and methods. We re-analyzed body height, body weight, and macronutrient intake of 1028 children (51.3% girls, 48.7% boys) aged 2–18 years who were investigated between 1985 and 2006 as part of the Dortmund Nutritional and Anthropometric Longitudinally Designed (DONALD) Study. We determined the intake of energy, carbohydrates, fat, and protein. Results. No correlations were found between the standard deviation scores of the BMI (BMI-SDS) and daily energy intake (r = 0.060, p > 0.1), between BMI-SDS and fat intake (r = 0.031, p > 0.1), and BMI-SDS and carbohydrate intake (r = 0.050, p > 0.1). Yet, we detected a significant positive correlation between BMI-SDS and average daily nutritional protein (all protein: r = 0.143, p < 0.0001, animal protein: r = 0.151, p < 0.0001). The correlation further increased when protein uptake was calculated as a percent of energy uptake (all protein: r = 0.203, p < 0.0001, animal pro-tein: r = 0.163, p < 0.0001). The correlations depended on the age with maxima just before and during the early puberty (boys: r = 0.31, p < 0.0001, girls: r = 0.36, p < 0.0001). It appears that in these age groups up to 13% of the BMI variance can be explained by protein uptake. Conclusion. The present investigation confirms the hitherto existing evidence of a signifi-cant positive correlation between nutritional protein and body mass index.
Limited evidence exists on the metabolic and cardiovascular risk correlates of commuting by vehicle, a habitual form of sedentary behavior.
To examine the association between commuting distance, physical activity, cardiorespiratory fitness (CRF), and metabolic risk indicators.
This cross-sectional study included 4297 adults who had a comprehensive medical examination between 2000 and 2007 and geocoded home and work addresses in 12 Texas metropolitan counties. Commuting distance was measured along the road network. Outcome variables included weekly MET-minutes of self-reported physical activity, CRF, BMI, waist circumference, triglycerides, plasma glucose, high-density lipoprotein cholesterol, systolic and diastolic blood pressure, and continuously measured metabolic syndrome. Outcomes were also dichotomized using established cut-points. Linear and logistic regression models were adjusted for sociodemographic characteristics, smoking, alcohol intake, family history of diabetes, and history of high cholesterol, as well as BMI and weekly MET-minutes of physical activity and CRF (for BMI and metabolic risk models). Analyses were conducted in 2011.
Commuting distance was negatively associated with physical activity and CRF and positively associated with BMI, waist circumference, systolic and diastolic blood pressure, and continuous metabolic score in fully adjusted linear regression models. Logistic regression analyses yielded similar associations; however, of the models with metabolic risk indicators as outcomes, only the associations with elevated blood pressure remained significant after adjustment for physical activity and CRF.
Commuting distance was adversely associated with physical activity, CRF, adiposity, and indicators of metabolic risk.
This paper explores the association of socio-demographic and built environment characteristics on the odds of being overweight and obese using data from the Atlanta SMARTRAQ travel survey. A new methodological framework based on a multinomial logit (MNL) model and an enhanced odds ratio plot is presented. The use of an MNL model overcomes limitations of many prior studies that employ a sequence of binary logit models to examine multiple weight categories. The use of an enhanced odds ratio plot provides important information into the relative importance of socio-demographic and built environment characteristics. Several new findings for the Atlanta area result from this study. Socio-demographic variables, including age and educational attainment, exhibit a non-linear relationship with the odds of being overweight or obese. Gender, age, ethnicity, and educational attainment are strongly associated with the odds of being overweight or obese, while income and number of students between 5 and 16 years old in the household have smaller effects. Built environment characteristics such as increased net residential densities and enhanced street connectivity are associated with reductions in the odds of being overweight and/or obese. Relative to socio-demographic variables, however, such built environment characteristics have a much smaller impact on describing the odds of being overweight or obese.
Neotraditionaldevelopment has captured the attention of planners, architects, and developers. The various kinds of develop- ment under this label claim to replace the traditionalauto-dependent suburb with pedestrian-oriented mixed-use develop- ment that builds sense of community. The present study tests two claims of neotra- ditionalpl ans. In a community having a traditionalsuburb and nearby a tradi- tional small-town center, on which neotraditional development is modeled, interviewers surveyed 120 residents—60 from each area. The analyses compared measures of sense of community, auto use, and reasons the residents chose to live in each area. The results support the claim that higher density mixed-use develop- ments have lower auto use, but they failed to show that this form of development or the reduced use of autos translates into in- creased sense of community.
Tested a model for understanding the relationship of participation in block associations to block-level variables (i.e., demographics, the built environment, crime, the transient social and physical environment). Data were obtained from 48 city blocks using (1) a telephone survey of 1,081 residents, (2) a block environmental inventory (BEI), (3) police records of reported crime, and (4) a survey of 469 block association members. The BEI was reliable and correlated significantly with the social climate, crime, demographics, and participation. The transient portion of the framework received particular support as 4 variables independently explained almost 40% of the variance in participation. A combination of catalysts in the physical environment and enablers in the social environment may increase participation.
This study examined (1) descriptive patterns in perceived environmental and policy determinants of physical activity and (2) associations between these factors and behavior.
A cross-sectional study was conducted from 1999 to 2000 among US adults; individuals at lower income levels were oversampled.
Availability of areas for physical activity was generally higher among men than among women. The 4 most commonly reported personal barriers were lack of time, feeling too tired, obtaining enough exercise at one's job, and no motivation to exercise. Neighborhood characteristics, including the presence of sidewalks, enjoyable scenery, heavy traffic, and hills, were positively associated with physical activity. There was a high level of support for health policy-related measures. Up to one third of individuals who had used environmental supports reported an increase in physical activity.
An array of environmental and policy determinants, particularly those related to the physical environment, are associated with physical activity and should be taken into account in the design of interventions.
The drive from my office to my suburban Atlanta home is all too familiar: it begins with a scary 7-lane thoroughfare, infamous for its strip malls, lack of sidewalks, and high pedestrian fatality rates; progresses to a jumble of connecting interstate highways packed with rush-hour traffic despite 12 or more roadway lanes; and ends with clusters of new, low-density, single-family residential developments lacking public parks, playgrounds, libraries, nearby stores or cafes, sidewalks, bicycle trails, and public transit. Adults and children in my neighborhood travel by private automobile to virtually all of their destinations, because they have no practical transportation alternatives.
As the prevalence of obesity increases in the United States, concern over the association of body weight with excess mortality has also increased.
To estimate deaths associated with underweight (body mass index [BMI] <18.5), overweight (BMI 25 to <30), and obesity (BMI > or =30) in the United States in 2000.
We estimated relative risks of mortality associated with different levels of BMI (calculated as weight in kilograms divided by the square of height in meters) from the nationally representative National Health and Nutrition Examination Survey (NHANES) I (1971-1975) and NHANES II (1976-1980), with follow-up through 1992, and from NHANES III (1988-1994), with follow-up through 2000. These relative risks were applied to the distribution of BMI and other covariates from NHANES 1999-2002 to estimate attributable fractions and number of excess deaths, adjusted for confounding factors and for effect modification by age.
Number of excess deaths in 2000 associated with given BMI levels.
Relative to the normal weight category (BMI 18.5 to <25), obesity (BMI > or =30) was associated with 111,909 excess deaths (95% confidence interval [CI], 53,754-170,064) and underweight with 33,746 excess deaths (95% CI, 15,726-51,766). Overweight was not associated with excess mortality (-86,094 deaths; 95% CI, -161,223 to -10,966). The relative risks of mortality associated with obesity were lower in NHANES II and NHANES III than in NHANES I.
Underweight and obesity, particularly higher levels of obesity, were associated with increased mortality relative to the normal weight category. The impact of obesity on mortality may have decreased over time, perhaps because of improvements in public health and medical care. These findings are consistent with the increases in life expectancy in the United States and the declining mortality rates from ischemic heart disease.
Research in transportation, urban design, and planning has examined associations between physical environment variables and individuals' walking and cycling for transport. Constructs, methods, and findings from these fields can be applied by physical activity and health researchers to improve understanding of environmental influences on physical activity. In this review, neighborhood environment characteristics proposed to be relevant to walking/cycling for transport are defined, including population density, connectivity, and land use mix. Neighborhood comparison and correlational studies with nonmotorized transport outcomes are considered, with evidence suggesting that residents from communities with higher density, greater connectivity, and more land use mix report higher rates of walking/cycling for utilitarian purposes than low-density, poorly connected, and single land use neighborhoods. Environmental variables appear to add to variance accounted for beyond sociodemographic predictors of walking/cycling for transport. Implications of the transportation literature for physical activity and related research are outlined. Future research directions are detailed for physical activity research to further examine the impact of neighborhood and other physical environment factors on physical activity and the potential interactive effects of psychosocial and environmental variables. The transportation, urban design, and planning literatures provide a valuable starting point for multidisciplinary research on environmental contributions to physical activity levels in the population.
An increasing body of evidence suggests that moderate forms of physical activity (such as walking and bicycling), when engaged in regularly, can have important beneficial effects on public health. This article reviews current public health, planning, and urban design research to determine, first, how walking and bicycling might be critically important exercise behaviors for improving public health, second, how urban form affects the frequency of walking and bicycling as a form of physical activity, and third, how the public health considerations outlined in this article might reorient planners' thinking toward the realization of health-promotive environments. The current lack of emphasis on the interdependencies between built form and overall quality of life, as measured by health, safety, and welfare considerations, suggests the need for a rethinking of public policy approaches to transportation investment and land development.
In recent years, there has been a chorus of calls to redesign America's suburbs so chat they are less dependent on automobile access and more conducive to transit riding, walking, and bicycling. This article compares commuting characteristics of transit-oriented and auto-oriented suburban neighborhoods, in the San Francisco Bay Area and in Southern California. Transit neighborhoods averaged higher densities and had more gridded street patterns compared to their nearby counterparts with auto-oriented physical designs. Neighbor hoods were matched in terms of median incomes and, to the extent possible, transit service levels, to control for these effects. For both metropolitan areas, pedestrian modal shares and trip generation rates tended to be considerably higher in transit than in auto-oriented neighborhoods. Transit neighborhoods had decidedly higher rates of bus commuting only in the Bay Area. Islands of transit-oriented neighborhoods in a sea of freeway-oriented suburbs seem to have negligible effects on transit commuting.
Physical inactivity is associated with multiple adverse health outcomes. Results from the transportation literature suggest that aspects of the urban environment may influence walking for transportation. In this paper we examine the association between a proxy measure of the urban environment and walking behavior.
We analyzed the association between home age and walking behavior in U.S. adults using data from the Third National Health and Nutrition Examination Survey. Logistic regression was used to estimate odds ratios and 95% confidence intervals and to control for the effects of gender, race/ethnicity, age, education level, household income, and activity limitations.
Adults who lived in homes built before 1946 and from 1946 to 1973 were significantly more likely to walk 1+ miles > or =20 times per month than those who lived in homes built after 1973. This association was present among people living in urban and suburban counties, but absent among those living in rural counties. The association was also found in models that controlled for gender, race/ethnicity, age, education, income, and any health-related activity limitation. Other forms of leisure-time physical activity were not independently associated with home age.
These results support the hypothesis that environmental variables influence walking frequency and suggest that home age may be a useful proxy for features of the urban environment that influence physical activity in the form of walking. Such proxy measures could facilitate testing ecologic models of health behavior using survey data.
The link between the built environment and human behavior has long been of interest to the field of urban planning, but direct assessments of the links between the built environment and physical activity as it influences personal health are still rare in the field. Yet the concepts, theories, and methods used by urban planners provide a foundation for an emerging body of research on the relationship between the built environment and physical activity. Recent research efforts in urban planning have focused on the idea that land use and design policies can be used to increase transit use as well as walking and bicycling. The development of appropriate measures for the built environment and for travel behavior is an essential element of this research. The link between the built environment and travel behavior is then made using theoretical frameworks borrowed from economics, and in particular, the concept of travel as a derived demand. The available evidence lends itself to the argument that a combination of urban design, land use patterns, and transportation systems that promotes walking and bicycling will help create active, healthier, and more livable communities. To provide more conclusive evidence, however, researchers must address the following issues: An alternative to the derived-demand framework must be developed for walking, measures of the built environment must be refined, and more-complete data on walking must be developed. In addition, detailed data on the built environment must be spatially matched to detailed data on travel behavior.
Research in transportation, urban design, and planning has examined associations between physical environment variables and individuals' walking and cycling for transport. Constructs, methods, and findings from these fields can be applied by physical activity and health researchers to improve understanding of environmental influences on physical activity. In this review, neighborhood environment characteristics proposed to be relevant to walking/cycling for transport are defined, including population density, connectivity, and land use mix. Neighborhood comparison and correlational studies with nonmotorized transport outcomes are considered, with evidence suggesting that residents from communities with higher density, greater connectivity, and more land use mix report higher rates of walking/cycling for utilitarian purposes than low-density, poorly connected, and single land use neighborhoods. Environmental variables appear to add to variance accounted for beyond sociodemographic predictors of walking/cycling for transport. Implications of the transportation literature for physical activity and related research are outlined. Future research directions are detailed for physical activity research to further examine the impact of neighborhood and other physical environment factors on physical activity and the potential interactive effects of psychosocial and environmental variables. The transportation, urban design, and planning literatures provide a valuable starting point for multidisciplinary research on environmental contributions to physical activity levels in the population.
This study evaluated a neighborhood environment survey and compared the physical activity and weight status of the residents in 2 neighborhoods.
On 2 occasions, 107 adults from neighborhoods with differing "walkability" were selected to complete a survey on their neighborhood environment. Physical activity was assessed by self-report and by accelerometer; height and weight were assessed by self-report.
Neighborhood environment characteristics had moderate to high test-retest reliabilities. Residents of high-walkability neighborhoods reported higher residential density, land use mix, street connectivity, aesthetics, and safety. They had more than 70 more minutes of physical activity and had lower obesity prevalence (adjusted for individual demographics) than did residents of low-walkability neighborhoods.
The reliability and validity of self-reported neighborhood environment subscales were supported. Neighborhood environment was associated with physical activity and overweight prevalence.
Obesity is a major health problem in the United States and around the world. To date, relationships between obesity and aspects of the built environment have not been evaluated empirically at the individual level.
To evaluate the relationship between the built environment around each participant's place of residence and self-reported travel patterns (walking and time in a car), body mass index (BMI), and obesity for specific gender and ethnicity classifications.
Body Mass Index, minutes spent in a car, kilometers walked, age, income, educational attainment, and gender were derived through a travel survey of 10,878 participants in the Atlanta, Georgia region. Objective measures of land use mix, net residential density, and street connectivity were developed within a 1-kilometer network distance of each participant's place of residence. A cross-sectional design was used to associate urban form measures with obesity, BMI, and transportation-related activity when adjusting for sociodemographic covariates. Discrete analyses were conducted across gender and ethnicity. The data were collected between 2000 and 2002 and analysis was conducted in 2004.
Land-use mix had the strongest association with obesity (BMI >/= 30 kg/m(2)), with each quartile increase being associated with a 12.2% reduction in the likelihood of obesity across gender and ethnicity. Each additional hour spent in a car per day was associated with a 6% increase in the likelihood of obesity. Conversely, each additional kilometer walked per day was associated with a 4.8% reduction in the likelihood of obesity. As a continuous measure, BMI was significantly associated with urban form for white cohorts. Relationships among urban form, walk distance, and time in a car were stronger among white than black cohorts.
Measures of the built environment and travel patterns are important predictors of obesity across gender and ethnicity, yet relationships among the built environment, travel patterns, and weight may vary across gender and ethnicity. Strategies to increase land-use mix and distance walked while reducing time in a car can be effective as health interventions.
I examined the association between urban sprawl and the risk for being overweight or obese among US adults.
A measure of urban sprawl in metropolitan areas was derived from the 2000 US Census; individual-level data were obtained from the Behavioral Risk Factor Surveillance System. I used multilevel analysis to assess the association between urban sprawl and obesity.
After I controlled for gender, age, race/ethnicity, income, and education, for each 1-point rise in the urban sprawl index (0-100 scale), the risk for being overweight increased by 0.2% and the risk for being obese increased by 0.5%.
The current obesity epidemic has many causes, but there is an association between urban sprawl and obesity.
The underlying methods of all these studies involve the concept of population-attributable fraction. Population-attributable fraction (or attributable fraction or etiologic fraction) is the proportion of morbidity or mortality in a population that can be attributed to a particular cause or risk factor and is one of the empowering concepts of the public health perspective on health. The attributable fraction focuses attention not on a particular disease or risk of disease in the individual but on the health of populations. In its most basic equation, this quantity shows that the burden of disease caused by any risk factor is a function of the prevalence of that risk factor and the magnitude of its causal association with disease, usually expressed as relative risk. The greater the prevalence of the risk factor and the greater the relative risk, the greater the population-attributable fraction. The calculation offers a perspective on health that crosses disciplines and specialties and attempts to focus attention on causes of disease that are most responsible for death and illness. Over the past 40 years, cigarette smoking, a common habit with highly elevated relative risks for several different causes of death, has always risen to the top of the list. The attention paid to the problem of cigarette smoking as a major cause of disease and death has been in part a result of the information and perspective provided by population-attributable fraction calculations.
Consideration of the causal pathways through which obesity increases mortality is important. Body mass index itself is affected by dietary intake and physical activity levels, which may affect health in ways mediated by body mass index or independent of it. According to the most recent clinical guidelines for cardiovascular risk reduction, most of the risk of cardiovascular disease caused by obesity is thought to be mediated through traditional risk factors such as diabetes, cholesterol, and hypertension.⁶ Thus, the guidelines do not incorporate obesity as an independent factor in which to estimate risk of cardiovascular disease. Calculating obesity-related deaths without accounting for other cardiovascular risk factors, as has been done in previous studies,³- 5 assumes a consistent relationship between obesity and these mediating risk factors. However, in the study by Gregg et al² in this issue of JAMA, analysis of representative samples of Americans show that the association of obesity and other cardiovascular risk factors has changed over the past 40 years. Obese persons now smoke less and have lower cholesterol levels and lower blood pressure. Although mortality outcomes are not evaluated in the study by Gregg et al,² because of interactions between risk factors, this across-the-board decrease in risk factors across all weight groups could translate to a lowering of the elevated risk of death associated with obesity.
In the past year, scientists at the Centers for Disease Control and Prevention have published conflicting estimates on obesity-associated
deaths--the first three times greater than the second. The disagreement, some fear, is undermining the agency's health warnings.
We analyze an urban spatial model to examine the possible link between urban land use and obesity. Households maximize utility defined over housing, weight, and food subject to a fixed time budget allocated to commuting, calorie expenditure, and work. Our model explains the observed correspondence between high obesity rates and low development densities, but implies that these are determined endogenously in a spatial market equilibrium. We study the sorting of residents by attributes such as income, initial weight, and weight preferences, and examine the impacts on weight and density of urban design modifications that lower the costs of calorie expenditure. Copyright Blackwell Publishers, 2005
Measuring the Health Effects of Sprawl: a National Analysis of Physical Activity, Obesity and Chronic Disease. Smart Growth America Does neotraditional development build community
- B A Mccann
- R Ewing
McCann, B.A., Ewing, R., 2003. Measuring the Health Effects of Sprawl: a National Analysis of Physical Activity, Obesity and Chronic Disease. Smart Growth America, Washington, DC. Nasar, J.L., 2003. Does neotraditional development build community? Journal of Planning Education and Research 23, 58–68.
Relationship between urban sprawl and physical activity, obesity, and morbidity
- Ewing