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

Effects of exposure to environmental factors on obesity-related growth parameters and leptin (LEP) methylation in children

The prevalence of childhood obesity is rapidly increasing. Therefore, gaining more information on the role of environmental parameters is key. With overexpression of leptin (encoded by LEP) in obesity, LEP methylation might be altered by environmental exposures. This study aims to assess effects of ambient air pollution and nearby greenness on obesity-related growth and LEP methylation in early childhood. We monitored 120 mother-child pairs from conception until the age of five. Buccal swabs and anthropometric measurements of the children were taken at six months, one year, and five years old. Buccal DNA was extracted to determine LEP methylation levels. Estimates of air pollution and nearby greenness were calculated using high-resolution models. Effects of air pollution and nearby greenness on growth or LEP methylation were investigated using linear mixed effects models. Positive associations were shown for air pollution between conception and age one on impedance in six-month-olds and one-year-olds in the crude model. PM with aerodynamic diameter ≤10 (PM10) and ≤2.5 μm (PM2.5) positively associated with waist-hip-ratio and waist circumference at age five in the fully adjusted model. In early childhood, closest distance to forest negatively, and urban green and forest positively associated with weight-for-length, body mass index, and fat percentage in five-year-olds in the fully adjusted model. No significant associations for noise, and walkability on growth were seen. Negative associations were shown for smaller green clusters and positive associations for greater green clusters on LEP methylation in one-year-olds. For forest distance, walkability, noise, or all green on LEP methylation, no significant associations were found. Evidence is provided that ambient air pollution might have a significant effect on impedance and waist-hip-ratio, suggesting an increased risk of childhood obesity. Based on LEP methylation, greater green clusters might associate with a decreased risk of childhood obesity, while smaller green clusters showed the opposite.

Measuring environmental exposures in people's activity space: The need to account for travel modes and exposure decay

BACKGROUND

Accurately quantifying people's out-of-home environmental exposure is important for identifying disease risk factors. Several activity space-based exposure assessments exist, possibly leading to different exposure estimates, and have neither considered individual travel modes nor exposure-related distance decay effects.

OBJECTIVE

We aimed (1) to develop an activity space-based exposure assessment approach that included travel modes and exposure-related distance decay effects and (2) to compare the size of such spaces and the exposure estimates derived from them across typically used activity space operationalizations.

METHODS

We used 7-day-long global positioning system (GPS)-enabled smartphone-based tracking data of 269 Dutch adults. People's GPS trajectory points were classified into passive and active travel modes. Exposure-related distance decay effects were modeled through linear, exponential, and Gaussian decay functions. We performed cross-comparisons on these three functional decay models and an unweighted model in conjunction with four activity space models (i.e., home-based buffers, minimum convex polygons, two standard deviational ellipses, and time-weighted GPS-based buffers). We applied non-parametric Kruskal-Wallis tests, pair-wise Wilcoxon signed-rank tests, and Spearman correlations to assess mean differences in the extent of the activity spaces and correlations across exposures to particulate matter (PM2.5), noise, green space, and blue space.

RESULTS

Participants spent, on average, 42% of their daily life out-of-home. We observed that including travel modes into activity space delineation resulted in significantly more compact activity spaces. Exposure estimates for PM2.5 and blue space were significantly (p < 0.05) different between exposure estimates that did or did not account for travel modes, unlike noise and green space, for which differences did not reach significance. While the inclusion of distance decay effects significantly affected noise and green space exposure assessments, the decay functions applied appear not to have had any impact on the results. We found that residential exposure estimates appear appropriate for use as proxy values for the overall amount of PM2.5 exposure in people's daily lives, while GPS-based assessments are suitable for noise, green space, and blue space.

SIGNIFICANCE

For some exposures, the tested activity space definitions, although significantly correlated, exhibited differing exposure estimate results based on inclusion or exclusion of travel modes or distance decay effect. Results only supported using home-based buffer values as proxies for individuals' daily short-term PM2.5 exposure.

Effect of built environment on BMI of older adults in regions of different socio-economic statuses

Background

Numerous studies have ignored the influence of underdeveloped urban surroundings on the physical health of China's ageing population. Lanzhou is a typical representative of a less developed city in China.

Methods

This study investigated the relationship between body mass index (BMI) and built environment amongst older adults in regions of different socio-economic statuses (SES) using data from medical examinations of older adults in Lanzhou, as well as calculating community built environment indicators for regions of different SES based on multiple linear regression models.

Results

Results showed that age and underlying disease were negatively associated with overall older adult BMI in the study buffer zone. Land use mix, number of parks and streetscape greenery were positively associated with older adult BMI. Street design and distance to bus stops were negatively connected in low SES regions, but population density and street design were negatively correlated in high SES areas.

Conclusion

These findings indicate that the built environment of SES regions has varying impacts on the BMI of older persons and that planners may establish strategies to lower the incidence of obesity amongst older adults in different SES locations.

Spatial machine learning for predicting physical inactivity prevalence from socioecological determinants in Chicago, Illinois, USA

The increase in physical inactivity prevalence in the USA has been associated with neighborhood characteristics. While several studies have found an association between neighborhood and health, the relative importance of each component related to physical inactivity or how this value varies geographically (i.e., across different neighborhoods) remains unexplored. This study ranks the contribution of seven socioecological neighborhood factors to physical inactivity prevalence in Chicago, Illinois, using machine learning models at the census tract level, and evaluates their predictive capabilities. First, we use geographical random forest (GRF), a recently proposed nonlinear machine learning regression method that assesses each predictive factor's spatial variation and contribution to physical inactivity prevalence. Then, we compare the predictive performance of GRF to geographically weighted artificial neural networks, another recently proposed spatial machine learning algorithm. Our results suggest that poverty is the most important determinant in the Chicago tracts, while on the other hand, green space is the least important determinant in the rise of physical inactivity prevalence. As a result, interventions can be designed and implemented based on specific local circumstances rather than broad concepts that apply to Chicago and other large cities.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10109-023-00415-y.

The effect of air pollution and emotional and behavioral problems on preschoolers' overweight and obesity

Childhood overweight and obesity (OWO) has risen dramatically in both developed and developing countries over the past few decades, creating a huge burden of disease. Ambient air pollution and emotional and behavioral problems are important influencing factors of OWO in preschoolers, but few studies have evaluated the impact of air pollution and emotional and behavioral problems on OWO of preschoolers in rural areas and their potential interactions. This study selected 3802 preschool children from 26 kindergartens in 4 rural areas of Anhui Province for a cross-sectional study. A total of 3636 individuals were included in the final analysis. In this study, outdoor air pollutants (PM_2.5 and O₃) were derived from the China Air Pollution Tracking (TAP) data set, matching preschoolers' external air pollution exposure according to their kindergarten address codes to neighborhoods or administrative villages. OWO were assessed based on WHO Child Growth and Development Standards. Generalized linear model (GLM) and interplot model were used to evaluate the separate effects and potential interactions of air pollutants and emotional and behavioral problems on preschoolers' OWO. In the separate analysis, we found a significant positive association between air pollution and emotional and behavioral problems and OWO among preschoolers. In the interaction analysis, air pollution could enhance the positive effect of emotional and behavioral problems on OWO in preschoolers. In addition, the effect of air pollution and emotional and behavioral problems on overweight and obesity was stronger in preschoolers aged 5 to 6 years. Finally, we also found a stronger positive association between emotional and behavioral problems among girls, macrosomia, non-left-behind children, and preschoolers without eating problems. This study provided a scientific basis for the control of air pollution and overweight and obesity among preschool children in Anhui Province.

Spatial Heterogeneity of Public Service Facilities in the Living Circle and Its Influence on Housing Prices: A Case Study of Central Urban Dalian, China

The spatial layout of public service facilities (PSFs) markedly influences residents’ quality of life. Based on Baidu map data, spatial information on 27,552 PSFs across eight categories was collected for urban Dalian, China, and analyzed using the nearest neighbor index and nuclear density. Then, PSF accessibility across eight dimensions of residential quarters was calculated based on the cumulative opportunity method, and its impact on housing prices was analyzed. The results revealed the following: (1) The degree of spatial agglomeration for PSFs varied, with that of business facilities being higher than that of other public welfare facilities. The distribution of business facilities was characterized by a dense center and sparse periphery, whereas public welfare facilities were laid out in a relatively balanced “multi-center” distribution across the study area. (2) Significant spatial differences in the number and types of accessible resident facilities were identified. The number of accessible PSFs in the core area of central urban regions was large and the types were relatively complete, whereas the accessible PSFs in the western and northern marginal areas were limited in number, few in type, and lacking across certain categories, such as educational facilities and life services. (3) The spatial distribution of PSF accessibility was unbalanced. The accessibility of various PSFs in the Shahekou District was the highest, followed by that in the Zhongshan, Xigang, and Ganjingzi Districts. (4) The accessibility of educational, sport, and cultural facilities, and the total accessibility and greening rate of residential areas were the most significantly positively correlated with housing prices; however, the number of households in residential areas and the distances between residential areas and large shopping centers were significantly negatively correlated. Our findings will expand the research perspective of PSFs, provide a basis for meeting residents’ needs and a rational allocation of PSFs, and provide references for people’s decisions to buy houses.

Exploring the Relationship Between Neighborhood-Built Environment and Elderly Health: A Research Based on Heterogeneity of Age and Gender Groups in Beijing

Background

The built environment quality of neighborhoods has a significant impact on the health of the elderly. Although there has been a wealth of studies on low-density Western cities, research on the impacts of built environment on elderly health in high-density Chinese cities is far from sufficient. The pathways by which the built environment affects elderly health remain to be observed, particularly whether such pathways vary for different ages and genders.

Methods

Based on the data of the "Fourth Survey on the Living Conditions of the Elderly in China" in 2015, a sample survey of 3,360 older adults, aged 60 years and over, in Beijing was conducted. We first explored the built environment factors that affect elderly health with a multilevel regression model. We then adopted a multilevel structural equation model (MSEM) to reveal the mediating effect of health activities. Moreover, a stratified analysis was applied to explore the impact of age and gender heterogeneity on the relationship between built environment and elderly health.

Results

(1) Neighborhood-built environment measured within a 500 m buffer area had a higher correlation with elderly health when compared with other areas. (2) Physical activity and social interaction played a mediating role in the correlation between the built environment and elderly health. Even if the interference of residential self-selection was controlled within the subgroups, majority of the built environment elements had significant impacts on elderly health. (3) The impacts of built environment variables on elderly health vary among different age and gender groups. Population density mainly promoted elderly health through health activities in the middle-aged (aged 70-79) group and high-aged (aged 80+) group, and shorter distance to transit stations affects health by promoting the social interaction among high-aged males (aged 80+) group compared to with other groups, and high-quality built environment significantly promotes physical activity to alleviate loneliness only in elderly females.

Conclusion

To effectively boost elderly health by improving the quality of the built environment, adequate considerations should also be given to the differentiated demands of adults of different age and gender groups, precise health behavior interventions should be provided, and the construction of personalized aging-friendly and livable spatial environments should be emphasized to realize healthy and active aging.

Food Environment Inequalities and Moderating Effects of Obesity on Their Relationships with COVID-19 in Chicago

The COVID-19 outbreak has raised challenges for people with health problems. Obesity is a global issue related to COVID-19. The Centers for Disease Control (CDC) finds that obesity worsens COVID-19 outcomes. As body mass index increases, the COVID-19 death risk increases. Additionally, due to different restriction policies, the pandemic has transformed our food environment. Thus, it is important to develop an antivirus-enabled paradigm to decrease the COVID-19 spreading rate in neighborhoods with obesity concerns and design a sustainable and healthy food environment. It is found that both COVID-19 and obesity inequalities are associated with food environment inequalities, but few studies have examined the moderating effects of obesity and food environment on COVID-19. According to the Chicago Department of Public Health, more than 30% of the Chicago adult population is obese. Additionally, Chicago has 340,676 COVID-19 cases during the period between 1 March 2020 and 26 November 2021. This study uses regression models to examine the moderating effects of obesity and food environment on COVID-19 in Chicago. Besides food environment factors, green spaces and transportation access are considered. The results show COVID-19 is concentrated in areas with a high obesity rate and low food access. A 1 percent increase in obesity rate is associated with a 2.83 percent increase in COVID-19 death rate in a community. Additionally, the moderating effects of obesity on the association between food environment and COVID-19 are shown in the results.

Exploring the Mediating Effect of Physical Activities on Built Environment and Obesity for Elderly People: Evidence From Shanghai, China

There is still a scarcity of literature on the specific mechanisms of the linkage between the built environment and obesity. As a result, this study investigated whether and how physical activities mediate the associations between the objective built environment and the BMI of elderly people. To investigate the effect of the duration and intensity of physical activity on the effect of the built environment, the study made use of the bootstrap method. In general, we discovered that physical activity duration has a huge mediating effect on the elderly people in Shanghai, especially with respect to the density and accessibility of facilities (gyms, parks, fast-food restaurants) that can greatly stimulate physical activity in elderly people to reduce their BMI. There were both direct and indirect effects on their BMI, which means that the health benefits of green spaces for older people may be more complicated than first thought.

A longitudinal examination of objective neighborhood walkability, body mass index, and waist circumference: the REasons for Geographic And Racial Differences in Stroke study

Background

Studies have shown neighborhood walkability is associated with obesity. To advance this research, study designs involving longer follow-up, broader geographic regions, appropriate neighborhood characterization, assessment of exposure length and severity, and consideration of stayers and movers are needed. Using a cohort spanning the conterminous United States, this study examines the longitudinal relationship between a network buffer-derived, duration-weighted neighborhood walkability measure and two adiposity-related outcomes.

Methods

This study included 12,846 Black/African American and White adults in the REasons for Geographic And Racial Differences in Stroke study. Body mass index (BMI) and waist circumference (WC) were assessed at baseline and up to 13.3 years later (M (SD) = 9.4 (1.0) years). BMI and WC were dichotomized. Walk Score® was duration-weighted based on time at each address and categorized as Very Car-Dependent, Car-Dependent, Somewhat Walkable, Very Walkable, and Walker’s Paradise. Unadjusted and adjusted logistic regression models tested each neighborhood walkability-adiposity association. Adjusted models controlled for demographics, health factors, neighborhood socioeconomic status, follow-up time, and either baseline BMI or baseline WC. Adjusted models also tested for interactions. Post-estimation Wald tests examined whether categorical variables had coefficients jointly equal to zero. Orthogonal polynomial contrasts tested for a linear trend in the neighborhood walkability-adiposity relationships.

Results

The odds of being overweight/obese at follow-up were lower for residents with duration-weighted Walk Score® values in the Walker’s Paradise range and residents with values in the Very Walkable range compared to residents with values in the Very Car-Dependent range. Residents with duration-weighted Walk Score® values classified as Very Walkable had significantly lower odds of having a moderate-to-high risk WC at follow-up relative to those in the Very Car-Dependent range. For both outcomes, the effects were small but meaningful. The negative linear trend was significant for BMI but not WC.

Conclusion

People with cumulative neighborhood walkability scores in the Walker’s Paradise range were less likely to be overweight/obese independent of other factors, while people with scores in the Very Walkable range were less likely to be overweight/obese and less likely to have a moderate-to-high risk WC. Addressing neighborhood walkability is one approach to combating obesity.

A Spatial Analysis of Obesity: Interaction of Urban Food Environments and Racial Segregation in Chicago

The obesity rate in Chicago has increased up to more than 30% in the last two decades. Obesity is a major problem in Chicago, where 36% of the city's high school students and 61% of adults in the metropolitan area are overweight or obese. Simultaneously, Chicago remains highly segregated by race-a phenomenon that begs for spatial analysis of health. Extant work exploring associations between the food retail environment and obesity has provided mixed findings, and virtually, none of this work has been done with the effects of the interaction between racial segregation and the food retail environment on obesity, where obesity rates are among the highest in the segregation area for the city defined by racial segregation. This study explores whether being overweight or obese is associated with urban food environments, such as access to different types of food retail outlets, and how its associations interact with racial factors, at the community level. This study uses the 2016-2018 data from the Healthy Chicago Survey to investigate the spatial variations in obesity and their association with food environments in Chicago. Also, this study examines the moderating effects of racial segregation on associations between obesity and access to food retail outlets. Using spatial statistics and regression models with interaction terms, this study assesses how the urban food environment can interact with racial segregation to explain the spatial distribution of obesity. The results indicate that the obesity population is highly concentrated in the African American community. In Chicago, each additional convenience store in a community is associated with a 0.42% increase in the obesity rate. Fast food restaurant access is predictive of a greater obesity rate, and grocery store access is predictive of less obesity rate in a community with a higher percentage of African American population. Findings can be used to promote equitable access to food retail outlets, which may help reduce broader health inequities in Chicago.

Is food environment associated with body mass index, overweight and obesity? A study with adults and elderly subjects from southern Brazil

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Proximity to food establishments had few associations with body mass index.

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Living near a street fair was associated with a higher body mass index.

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Living near a convenience store was associated with a higher body mass index.

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Living near a restaurant was associated with lower body mass index.

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Living near a fruit shop was associated with lower body mass index.

The purpose of this article was to investigate the association of food environment variables with Body Mass Index (BMI), excess weight and obesity. This was a cross-sectional study determining the presence or absence of food establishments within a 100-m buffer zone from each sampled household. Individuals aged 18 years and older living in the urban area of Rio Grande, RS State, Brazil, in 2016, were considered eligible. A total of 1,139 individuals, with an average age of 46.5 years (SD 17.1), residing in the household for more than one year, were selected as a representative sample of the population. The mean BMI of study participants was 27.0 kg/m² (SD 4.8), and the prevalence of excess weight and obesity was 61.6% (95%CI: 58.9; 64.3) and 23.7% (95%CI: 21.3; 26.1), respectively. Living near a convenience store was associated with a higher BMI and a higher likelihood of being above normal weight and obese. In contrast, living near a restaurant was associated with a lower BMI and a lower likelihood of being above normal weight and obese. In addition, participants who lived close to fruit shops had lower BMI and a lower likelihood of being above normal weight. Concluding few associations were found between food environment and the health-related outcomes. Proximity to food establishments does not seem to significantly affect BMI, excess weight and obesity in the studied population.

Trade-Off Relationship of Arable and Ecological Land in Urban Growth When Altering Urban Form: A Case Study of Shenzhen, China

Over the last few decades, rapid urban expansion has spread over a great deal of arable and ecological land, leading to severe social and environmental issues. Although different urban growth scenarios cause varying types of urban forms to emerge, there is currently a lack of empirical studies and other research on these different forms. Therefore, it is important for decision-makers to have an improved understanding of the relationships between arable land and ecological land under different urban form conditions in order to implement sustainable urban development policies. This study utilized a patch-based, multilevel stochastic urban growth model to simulate Shenzhen’s urban growth until 2035. To determine the impacts of urban forms and population density on land use, we established five scenarios to simulate urban expansion and land-use changes at the sub-regional scale. The results revealed the trade-off relationships that emerge when altering the urban forms or population density, which shows that no single policy can conserve arable land and ecological land simultaneously. The results also revealed that sub-regions have distinct responses to alternative urban form scenarios compared with an entire region. Decision-makers and planners should consider the urban form in order to optimize development projects that fit local conditions and achieve more sustainable development.

Association between exposure to fine particulate matter and obesity in children: A national representative cross-sectional study in China

BACKGROUND

Childhood obesity is a global health issue, and limited evidence suggests that air pollution may be a contributing factor. This study aims to examine whether exposure to fine particulate matter (PM_2.5) is associated with obesity status in a nationally representative sample of schoolchildren in China.

METHODS

The study population consisted of 41,439 schoolchildren of 6-17 years old, recruited from 30 provinces in China using a multi-stage stratified sampling method. Weights and heights were measured for all the participants, and sociodemographic information was collected using a questionnaire. The obesity status was classified following the Chinese national standards. The PM_2.5 exposure was estimated as the 5-year average concentration at the school location for each participant. The association between obesity status and PM_2.5 exposure was examined using weighted logistic regressions adjusted for potential confounders.

RESULTS

The prevalence of normal weight, overweight, and obesity were 78.5%, 12.4%, and 9.0%, respectively. PM_2.5 exposure averaged 59.8 ± 17.6 μg/m³ with a range of 30.5-115.2 μg/m³ among all the participants. The risk of obesity increased by 10.0% (95% confidence interval: 3.0-16.0%) per 10 μg/m³ increase in PM_2.5 exposure. The PM_2.5-associated risk was significantly elevated in older age groups and children living in urban areas (interaction p-values < 0.05).

CONCLUSIONS

This national survey revealed that approximately 1 in 5 Chinese schoolchildren were overweight or obese. Exposure to PM_2.5 in the ambient air was significantly associated with childhood obesity. The findings suggest the need for further research to uncover the roles of PM_2.5 exposure in childhood obesity development.

A Review of Advancement on Influencing Factors of Acne: An Emphasis on Environment Characteristics

Background: Acne vulgaris is known as a commonly-seen skin disease with a considerable impact on the quality of life. At present, there have been a growing number of epidemiological, medical, demographic and sociological researches focusing on various influencing factors in the occurrence of acne. Nevertheless, the correlation between environmental factors and acne has yet to be fully investigated. Objective: To assess the impacts of individual, natural and social environmental factors on acne and to construct a framework for the potential impact of built environment on acne. Methods: A thorough review was conducted into the published social demographical, epidemiological, and environmental studies on acne through PubMed, Google Scholar and Web of Science, with reference made to the relevant literature. Results: The influencing factors in acne are classed into four major categories. The first one includes individual socio-economic and biological factors, for example, gender, age, economic level, heredity, obesity, skin type, menstrual cycle (for females), diet, smoking, cosmetics products, electronic products, sleep quality and psychological factors. The second one includes such natural environmental factors as temperature, humidity, sun exposure, air pollution and chloracne. The third one relates to social environment, including social network and social media. The last one includes built environmental factors, for example, population density, food stores, green spaces, as well as other built environment characteristics for transport. Acne can be affected negatively by family history, overweight, obesity, oily or mixed skin, irregular menstrual cycles, sugary food, greasy food, dairy products, smoking, the improper use of cosmetics, the long-term use of electronics, the poor quality of sleep, stress, high temperature, sun exposure, air pollution, mineral oils and halogenated hydrocarbons. Apart from that, there are also potential links between built environment and acne. Conclusions: It is necessary to determine the correlation between the built environment and acne based on the understanding of the impact of traditional factors (sociology of population and environment) on acne gained by multidisciplinary research teams. Moreover, more empirical studies are required to reveal the specific relationship between built environment and acne.

Establishing associations between residential greenness and markers of adiposity among middle-aged and older Chinese adults through multilevel structural equation models

OBJECTIVES

Residential greenness may prevent overweight/obesity, but the matter has not been investigated among middle-aged and older adults in China. This study 1) assessed associations between residential greenness and markers of adiposity among middle-aged and older Chinese adults and 2) investigated physical activity, sedentary behaviours, particulate matter (PM) with a diameter of <2.5 μm (PM_2.5) concentrations, and perennial mean temperature as mediators of the associations.

METHODS

We used data from the World Health Organization's Study on Global Ageing and Adult Health (SAGE) between 2007 and 2010. Overweight/obesity and abdominal obesity were measured by body mass index and waist circumference. Exposure to neighbourhood greenness was measured by the normalized difference vegetation index (NDVI). Multilevel structural equation models were fitted to investigate the associations between neighbourhood greenness, the four potential mediators, and the prevalence of overweight/obesity and central obesity.

RESULTS

The results showed that greenness was inversely associated with the odds of overweight/obesity (odds = 0.73, 95% confidence interval (CI) 0.58-0.92) and abdominal adiposity (odds = 0.55, 95% CI 0.33-0.91). The greenness-overweight/obesity association varied significantly by sex and age, and the greenness-central obesity varied significantly by sex, age, and education. We found some indication that PM_2.5 concentrations had a suppressive effect on the greenness-adiposity associations. There was no evidence that physical activity, sedentary behaviours, and perennial mean temperature mediated the associations between neighbourhood greenness and markers of adiposity.

CONCLUSIONS

Exposure to higher levels of residential greenness was associated with lower odds of overweight/obesity and abdominal obesity among middle-aged and older Chinese adults. However, underlying mechanisms explaining these associations remain unclear requiring longitudinal studies and natural experiments.

Convenience and corner store fruit and vegetable access: attitudes and intentions among Colorado adults, 2014

Aim

The term food desert generally refers to areas where healthy food options, such as fresh fruits and vegetables, are unavailable within a certain number of miles. However, other factors besides distance may affect the ability to purchase healthier foods. The goal of this study was to understand Colorado adults' perceptions of their access to healthy food options and to assess how other structural and socio-demographic factors may affect that access.

Subject and methods

Colorado adults were asked questions about self-reported access to healthy food, likelihood of buying fresh fruits and vegetables from convenience/corner stores if available, perceived characteristics of fruits and vegetables available for purchase near respondents' residence, and demographics.

Results

A majority of Colorado adults in 2013-14 reported wanting fresh fruits and vegetables to be more available, more varied, higher quality, and/or less expensive. Socioeconomic status, race/ethnicity, and regular shopping habits were significantly associated with reported likelihood of purchasing fruits and vegetables from a convenience/corner store if available.

Conclusion

Factors other than proximity to a grocery store affect Colorado adults' perceived access to healthy food options and should be considered in the development and implementation of public health programs and policies geared toward improving healthy food access.

Contextual and Individual Determinants of Mental Health: A Cross-sectional Multilevel Study in Tehran, Iran

Objectives

Our aim was to answer the following questions: (1) Can mental health variance be partitioned to individual and higher levels (e.g., neighborhood and district); (2) How much (as a percentage) do individual-level determinants explain the variability of mental health at the individual-level; and (3) How much do determinants at the neighborhood- or district-level explain the variability of mental health at the neighborhood- or district-level?

Methods

We used raw data from the second round of the Urban Health Equity Assessment and Response Tool in Tehran (in 2012-2013, n=34 700 samples nested in 368 neighborhoods nested in 22 districts) and the results of the official report of Tehran’s Center of Studies and Planning (in 2012-2013, n=22 districts). Multilevel linear regression models were used to answer the study questions.

Results

Approximately 40% of Tehran residents provided responses suggestive of having mental health disorders (30-52%). According to estimates of residual variance, 7% of mental health variance was determined to be at the neighborhood-level and 93% at the individual-level. Approximately 21% of mental health variance at the individual-level and 49% of the remaining mental health variance at the neighborhood-level were determined by determinants at the individual-level and neighborhood-level, respectively.

Conclusions

If we want to make the most effective decisions about the determinants of mental health, in addition to considering the therapeutic perspective, we should have a systemic or contextual view of the determinants of mental health.

Why Public Health Needs GIS: A Methodological Overview

The short paper provides an overview on how geographic issues have become increasingly relevant to public health research and policy, particularly through the lens of geographic information systems (GIS). It covers six themes with an emphasis on methodological issues. (1) Our health-related behavior varies across geographic settings, so should public health policy. (2) Facilities (supply) and patients (demand) in a health care market interact with each other across geopolitical borders, and measures of health care accessibility need to capture that. (3) Our health outcome is the result of joint effects of individual attributes and neighborhood characteristics, and an adequate definition of neighborhood is critical for assessing neighborhood effect. (4) Disease rates in areas of small population are unreliable, and one effective way to mitigate the problem is to construct a larger, internally-homogenous and comparable area unit. (5) Defining a scientific geographic unit for health care market is critical for researchers, practitioners, and policy makers to evaluate health care delivery, and GIS enables us to define the unit (e.g., primary care service areas, hospital service areas, and cancer service areas) automatically, efficiently and optimally. (6) Aside from various optimization objectives around "efficiency", it is as important to plan the location and allocation of health care resources toward maximum equality in health care access. Case studies are cited to illustrate each theme.

Association of neighbourhood social and physical attributes with depression in older adults in Hong Kong: a multilevel analysis

Background

Previous studies investigating the independent effects of neighbourhood-level factors on depression are rare within the Asian context, especially in the elderly population.

Methods

Data for 29 099 older adults aged 65 years or above who have received health examinations at elderly health centres in Hong Kong in 2008–2011 were analysed. Using multilevel regression modelling, the cross-sectional associations of neighbourhood social attributes (neighbourhood poverty, ethnic minority, residential stability and elderly concentration) and physical (built) attributes (recreational services and walkability) with depression outcomes (depressive symptoms and depression) after adjusting for individual-level characteristics were investigated. Gender interaction effects were also examined.

Results

Neighbourhood poverty was associated with both depressive symptoms and depression in the elderly. Neighbourhood elderly concentration, recreational services and walkability were associated with fewer depressive symptoms. The association between neighbourhood poverty and elderly depressive symptoms was found in women only and not in men.

Conclusion

Policies aimed at reducing neighbourhood poverty, increasing access to recreational services and enhancing walkability might be effective strategies to prevent depression in older adults in the urban settings.

Impact of the Hydraulic Fracturing on Indoor Radon Concentrations in Ohio: A Multilevel Modeling Approach

According to the United States Environmental Protection Agency (U.S. EPA), exposure to radon gas is the second leading cause of lung cancer after smoking. Extant research that has reported that fracking activity increases the radon levels. “Fracking” also known as hydraulic fracturing, which is a technology that is used to extract naturally occurring shale gas from the Marcellus and the Utica shales. Based on the data from the Ohio Radon Information System (ORIS) from 2007 to 2014 in Ohio, this research uses multilevel modeling (MLM) to examine the association between the incidences of hydraulic fracturing and elevated airborne radon levels. The ORIS data include information on 118,421 individual records of households geocoded to zip code areas. Individual records include radon concentrations, device types of the test, and seasons. Euclidean distances between zip code centroid to the 1,162 fracking wells are measured at the zip code level. Two additional zip code variables, namely the population density and urbanicity, are also included as control variables. Multilevel modeling results show that at the zip code level, distance to fracking wells and population density are significant and negative covariate of the radon concentration. By comparing with urban areas, urban clusters, and rural areas are significant which linked to higher radon concentrations. These findings lend support to the effect of hydraulic fracturing in influencing radon concentrations, and promote public policies that need to be geographically adaptable.

Walk Score® and Its Associations with Older Adults' Health Behaviors and Outcomes

This study aimed to investigate the associations between Walk Score^® and lifestyle behaviors and health outcomes in older Taiwanese adults. A nationwide survey was conducted through telephone-based interviews with older adults (65 years and older) in Taiwan. Data on Walk Score^®, lifestyle behaviors (physical activity, sedentary behavior, healthy eating behavior, alcohol use, and smoking status), health outcomes (overweight/obesity, hypertension, type 2 diabetes, and cardiovascular disease), and personal characteristics were obtained from 1052 respondents. A binary logistic regression adjusting for potential confounders was employed. None of the Walk Score^® categories were related to the recommended levels of total physical activity. The categories "very walkable" and "walker's paradise" were positively related to total sedentary time and TV viewing among older adults. No significant associations were found between Walk Score^® and other lifestyle health behaviors or health outcomes. While Walk Score^® was not associated with recommended levels of physical activity, it was positively related to prolonged sedentary time in the context of a non-Western country. The different associations between the walk score and health lifestyle behaviors and health outcomes in different contexts should be noted.

Spatial clustering patterns of child weight status in a southeastern US county

Youth obesity is a major public health concern due to associated physical, social, and psychological health consequences. While rates and disparities of youth obesity levels are known, less research has explored spatial clustering patterns, associated correlates of spatial clustering, comparing patterns in urban and rural areas. Therefore, this study 1) examined spatial clustering of youth weight status, 2) investigated sociodemographic correlates of spatial clustering patterns, and 3) explored spatial patterns by level of urbanization. This study occurred in a southeastern US county (pop:474,266) in 2013. Trained physical education teachers collected height and weight for all 3^rd-5th grade youth (n = 13,469) and schools provided youth demographic attributes. BMI z-scores were calculated using standard procedures. Global Moran's Index and Anselin's Local Moran's I (LISA) were used detect global and local spatial clustering, respectively. To examine correlates of spatial clustering, BMI z-score residuals from a series of four linear regression models were spatially analyzed, mapped, and compared. SAS 9.4 and GeoDA were used for analyses; ArcGIS was used for mapping. Significant, positive global clustering (Index = 0.04,p < 0.001) was detected. LISA results showed that about 4.7% (n = 635) and 7.9% (n = 1058) of the sample were identified as high and low obesity localized spatial clusters (p < 0.01), respectively. Individual and neighborhood sociodemographic characteristics accounted for the majority of spatial clustering and differential patterns were observed by level of urbanization. Identifying geographic areas that contain significant spatial clusters is a powerful tool for understanding the location of and exploring contributing factors to youth obesity.

An Analytical Framework for Integrating the Spatiotemporal Dynamics of Environmental Context and Individual Mobility in Exposure Assessment: A Study on the Relationship between Food Environment Exposures and Body Weight

In past studies, individual environmental exposures were largely measured in a static manner. In this study, we develop and implement an analytical framework that dynamically represents environmental context (the environmental context cube) and effectively integrates individual daily movement (individual space-time tunnel) for accurately deriving individual environmental exposures (the environmental context exposure index). The framework is applied to examine the relationship between food environment exposures and the overweight status of 46 participants using data collected with global positioning systems (GPS) in Columbus, Ohio, and binary logistic regression models. The results indicate that the proposed framework generates more reliable measurements of individual food environment exposures when compared to other widely used methods. Taking into account the complex spatial and temporal dynamics of individual environmental exposures, the proposed framework also helps to mitigate the uncertain geographic context problem (UGCoP). It can be used in other environmental health studies concerning environmental influences on a wide range of health behaviors and outcomes.

Associations of neighbourhood walkability indices with weight gain

Background

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

Methods

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

Results

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

Conclusions

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

A cross-sectional study of the influence of neighborhood environment on childhood overweight and obesity: Variation by age, gender, and environment characteristics

To examine the influence of neighborhood environment on childhood overweight and obesity in Shelby County Schools, Tennessee, and whether and to what extent that influence varies by age, gender, and the specific environment characteristics. 41,283 students were surveyed covering both individual-level covariates and several objective measures of neighborhood environment. Multilevel logistic regressions were used to examine the influence of neighborhood-level variables on overweight+obesity and obesity with adjustment of individual-level covariates. Further, a stratified analysis for each of the six groups by school level and gender. For both overweight+obesity and obesity, younger children were less sensitive to neighborhood characteristics than older children, and boys are less sensitive than girls. For girls in middle and high schools, the risk of overweight+obesity and obesity were positively associated with population density, and negatively associated with percent of poverty and percent of unhealthy food. Boys' risk of overweight+obesity and obesity were positively associated with distance to park. Neighborhood environment plays an important role in childhood overweight and obesity, and the effects vary by age, gender, and the specific neighborhood characteristic. Intervention programs tailored to specific groups may be more effective than ones targeted to children as a whole.

The Uncertain Geographic Context Problem in the Analysis of the Relationships between Obesity and the Built Environment in Guangzhou

Traditionally, static units of analysis such as administrative units are used when studying obesity. However, using these fixed contextual units ignores environmental influences experienced by individuals in areas beyond their residential neighborhood and may render the results unreliable. This problem has been articulated as the uncertain geographic context problem (UGCoP). This study investigates the UGCoP through exploring the relationships between the built environment and obesity based on individuals’ activity space. First, a survey was conducted to collect individuals’ daily activity and weight information in Guangzhou in January 2016. Then, the data were used to calculate and compare the values of several built environment variables based on seven activity space delineations, including home buffers, workplace buffers (WPB), fitness place buffers (FPB), the standard deviational ellipse at two standard deviations (SDE2), the weighted standard deviational ellipse at two standard deviations (WSDE2), the minimum convex polygon (MCP), and road network buffers (RNB). Lastly, we conducted comparative analysis and regression analysis based on different activity space measures. The results indicate that significant differences exist between variables obtained with different activity space delineations. Further, regression analyses show that the activity space delineations used in the analysis have a significant influence on the results concerning the relationships between the built environment and obesity. The study sheds light on the UGCoP in analyzing the relationships between obesity and the built environment.

A new method to visualize obesity prevalence in Seattle-King County at the census block level

Objective

The aim of this study is to map obesity prevalence in Seattle King County at the census block level.

Methods

Data for 1,632 adult men and women came from the Seattle Obesity Study I. Demographic, socioeconomic and anthropometric data were collected via telephone survey. Home addresses were geocoded, and tax parcel residential property values were obtained from the King County tax assessor. Multiple logistic regression tested associations between house prices and obesity rates. House prices aggregated to census blocks and split into deciles were used to generate obesity heat maps.

Results

Deciles of property values for Seattle Obesity Study participants corresponded to county-wide deciles. Low residential property values were associated with high obesity rates (odds ratio, OR: 0.36; 95% confidence interval, CI [0.25, 0.51] in tertile 3 vs. tertile 1), adjusting for age, gender, race, home ownership, education, and incomes. Heat maps of obesity by census block captured differences by geographic area.

Conclusion

Residential property values, an objective measure of individual and area socioeconomic status, are a useful tool for visualizing socioeconomic disparities in diet quality and health.

Environmental Risk Factors for Developing Type 2 Diabetes Mellitus: A Systematic Review

Different elements of the environment have been posited to influence type 2 diabetes mellitus (T2DM). This systematic review summarizes evidence on the environmental determinants of T2DM identified in four databases. It proposes a theoretical framework illustrating the link between environment and T2DM, and briefly discusses some methodological challenges and potential solutions, and opportunities for future research. Walkability, air pollution, food and physical activity environment and roadways proximity were the most common environmental characteristics studied. Of the more than 200 reported and extracted relationships assessed in 60 studies, 82 showed significant association in the expected direction. In general, higher levels of walkability and green space were associated with lower T2DM risk, while increased levels of noise and air pollution were associated with greater risk. Current evidence is limited in terms of volume and study quality prohibiting causal inferences. However, the evidence suggests that environmental characteristics may influence T2DM prevention, and also provides a reasonable basis for further investigation with better quality data and longitudinal studies with policy-relevant environmental measures. This pursuit of better evidence is critical to support health-orientated urban design and city planning.

Walkable neighborhoods and obesity: Evaluating effects with a propensity score approach

Background

Research investigating the connection between neighborhood walkability and obesity often overlooks the issue of nonrandom residential selection.

Methods

We use propensity score methods to adjust for the nonrandom selection into residential neighborhoods in this cross-sectional, observational study. The sample includes 103,912 women residing in Salt Lake County, Utah age 20 or older. We measured percentage living in neighborhoods with more walkability, area level measures of neighborhood characteristics, and obesity (body mass index (BMI) > 30).

Results

Our findings confirm previous work that observes an association between living in more walkable neighborhoods and lower obesity. After adjusting for nonrandom selection, the odds of being obese when living in a less walkable neighborhood increase. Specifically, the odds ratio for being obese without the propensity score correction is 1.12. After adjusting for nonrandom selection, the odds ratio for being obese is 1.19, an increase of six percent.

Conclusion

Results demonstrate that residential selection bias inherent in cross-sectional analysis slightly attenuates the true association between neighborhood walkability and obesity. Results lend support to the growing body of research suggesting that more walkable neighborhoods have residents with a lower prevalence of obesity. Absent propensity score controls, the causal relationship between environment and obesity would be underestimated by 6%. Our analysis suggests there is an association between neighborhood walkability and obesity.

Varying age-gender associations between body mass index and urban greenspace

Urban greenspace benefits urbanites in numerous ways ranging from regulating flooding, air quality, and local climate to providing opportunities for exercise and relaxation. These benefits may influence human health. Greenspace, for example, may facilitate exercise, thereby helping to reduce body mass index (BMI) and combat obesity, a current epidemic of great public health concern. Little evidence exists to support this assertion, however, and we lack a full understanding of the mechanisms whereby this relationship operates, the populations for whom greenspace is linked to weight status, and the aspects of urban greenspace that are linked to weight status. This study seeks to identify relationships among the composition and arrangement of greenspace and BMI for different populations using regression models for eight age and gender groups in Cleveland, Ohio, US. We find that several greenspace variables are related to BMI for women under 65 years and males under 51 years, but not for older groups, and that the aspects and types of greenspace that are significantly related to BMI vary among groups. Relationships between greenspace attributes and BMI are generally stronger for female groups and for younger groups. Providing access to greenspace with particular attributes such as greenspaces with water, canopy cover, or connected greenspaces could support a healthy weight status for some populations, but these attributes are not consistent across age and gender groups. These results could help to inform policy aimed at designing urban greenspace to benefit the health of different population subgroups.

Built environment and obesity by urbanicity in the U.S

Based on the data from the Behavioral Risk Factor Surveillance System 2012, this study examines the association of neighborhood built environments with individual physical inactivity and obesity in the U.S. Multilevel modeling is used to control for the effects of individual socio-demographic characteristics. Neighborhood variables include built environment, poverty level and urbanicity at the county level. Among the built environment variables, a poorer street connectivity and a more prominent presence of fast-food restaurants are associated with a higher obesity risk (especially for areas of certain urbanicity levels). Analysis of data subsets divided by areas of different urbanicity levels and by gender reveals the variability of effects of independent variables, more so for the neighborhood variables than individual variables. This implies that some obesity risk factors are geographically specific and vary between men and women. The results lend support to the role of built environment in influencing people's health behavior and outcome, and promote public policies that need to be geographically adaptable and sensitive to the diversity of demographic groups.