Impact of ambient air pollution on obesity: a systematic review

Physiotherapy and ecosystem services: improving the health of our patients, the population, and the environment

INTRODUCTION

The relevance of ecosystems to physiotherapy has traditionally been overlooked, despite its potential for health impacts relevant to conditions often managed by physiotherapists.

PURPOSE

The purpose of this article is to introduce the concept of ecosystem services to physiotherapists, and to discuss how understanding ecosystem services may improve patient care, and population and planetary health.

DISCUSSION AND CONCLUSION

Physiotherapists with an understanding of ecosystem services may improve patient care by value-adding to management through patient education, empathy, advocacy, and broader population health approaches. Physiotherapists are also well placed to promote the conservation and restoration of ecosystem through participation, advocacy, and the development of public health measures, to the benefit of global sustainability and population health. Further research is required into how physiotherapists currently use nature-based interventions, and the barriers and enablers to their use. To be adequately prepared to meet the challenges that climate change and environmental degradation pose to patient care, population health and health systems, both current and future physiotherapists need to take a broader view of their practice. By including consideration of the potential role of the environment and green space exposure in particular on their patient's health, physiotherapists can ultimately contribute more to population and planetary health.

Air pollution, greenness and risk of overweight among middle-aged and older adults: A cohort study in China

BACKGROUND

Exposure to air pollution may increase the risk of obesity, but living in greener space may reduce this risk. Epidemiological evidence, however, is inconsistent.

METHODS

Using data from the China Health and Retirement Longitudinal Study (2011-2015), we conducted a nationwide cohort study of 7424 adults. We measured overweight/obesity according to body mass index. We used annual average ground-level air pollutants, including ozone (O3), nitrogen dioxide (NO2), and particulate matter with aerodynamic diameters ≤2.5 μm (PM2.5), to demonstrate air pollution levels. We used the Normalized difference vegetation index (NDVI) to measure greenness exposure. We used time-varying Cox proportional hazard regression models to analyze the connections among air pollution, greenness, and the development of overweight/obesity in middle-aged and older adults in China. We also conducted mediation analyses to examine the mediating effects of air pollution.

RESULTS

We found that lower risk of overweight/obesity was associated with more greenness exposure and lower levels of air pollution. We identified that an interquartile increment in NDVI was correlated with a lower hazard ratio (HR) of becoming overweight or obese (HR = 0.806, 95% confidence interval [CI]: 0.754-0.862). Although a 10 μg/m3 increase in PM2.5 and NO2 was correlated with higher risks (HR = 1.049, 95% CI = 1.022-1.075, HR = 1.376, 95% CI = 1.264-1.499). Effects of PM2.5 on being overweight or obese were stronger in men than in women. According to the mediation analysis, PM2.5 and NO2 mediated 8.85% and 19.22% of the association between greenness and being overweight or obese.

CONCLUSIONS

An increased risk of being overweight or obese in middle-aged and older adults in China was associated with long-term exposure to higher levels of PM2.5 and NO2. This risk was reduced through NDVI exposure, and the associations were partially mediated by air pollutants. To verify these findings, fine-scale studies are needed.

What is the role of particulate matter 2.5 (PM2.5) on excess weight? A cross-sectional study in young Spanish people aged 2─14 years

PURPOSE

To assess the relationship between particulate matter 2.5 (PM2.5) levels and the prevalence of excess weight in a representative sample of Spanish young people aged 2─14 years.

METHODS

This was an ecological cross-sectional study using data from the 2017 wave of the Encuesta Nacional de Salud Española (ENSE), a nationally representative survey of the Spanish young and adult population. The final sample included 4378 young Spanish people (51.0% boys). The weight (kg) and height (cm) of the study participants were proxy-reported by parents or guardians. Excess weight was determined according to the age- and sex-criteria of the International Obesity Task Force. The PM2.5 level was calculated as the annual monitoring data indicator for 2017 among the different regions in Spain. Logistic regression models were performed to estimate the relationships between PM2.5 and weight.

RESULTS

Compared to young people located in regions with low levels of PM2.5, those reporting greater odds for excess weight were found in regions with medium PM2.5 (OR = 1.23; 95% CI, 1.02-1.49) and high PM2.5 (OR = 1.35; 95% CI, 1.11-1.64) after adjusting for several sociodemographic, lifestyle and environmental covariates.

CONCLUSIONS

The prevalence of excess weight in young people was positively associated with PM2.5 levels in Spain. This finding supports the hypothesis that air pollution exposure can result in excess weight in the young population, which, in turn, might lead to the development of metabolic disorders. From a socioecological perspective, a practical need to take environmental factors into consideration is important to address unhealthy weight in Spanish young people.

Chemical constituents of ambient fine particulate matter and obesity among school-aged children: A representative national study in China

BACKGROUND

Studies show that fine particulate matter (PM_2.5) contributes to childhood obesity. However, evidence on the effects of its constituents on obesity has not been explored.

METHODS

Using multistage stratified cluster sampling, we enrolled 41,439 school-age children (aged 6-17 years) from a representative nationwide survey of 30 provinces in China (mean age ± standard deviation: 12.0 ± 3.3 years). Weight and height were measured using a physician beam scale with a height rod, and covariates were determined using a standard questionnaire. The concentration of PM_2.5 chemical constituents was estimated by a chemical transport (GEOS-Chem) model using input satellite data and ground-based observations. The constituents included black carbon, ammonium, nitrate, organic matter, sulfate, and soil dust. Generalized linear models were used to estimate the association between the chemical constituents of PM_2.5 and obesity.

RESULTS

A positive association between the constituents of PM_2.5 and obesity were observed. Children were more susceptible to black carbon than other species. A 1-μg/m³ increase in black carbon led to a 0.079 (95 % confidence interval [CI]:0.028, 0.130)-kg/m² increase in body mass index (BMI). This also increased the odds of being obese and overweight to 1.174 (95 % CI: 1.111, 1.240) and 1.165 (95 % CI: 1.116, 1.216), respectively. Stratified analyses showed that the effects were stronger in girls and older children, as well as in urban and Northeast regions. The effect of the PM_2.5 constituents on obese and overweight children from urban areas significantly interacted with that of rural areas.

CONCLUSIONS

The PM_2.5 constituents were associated with an increased BMI and childhood obesity. Further studies are warranted to validate these results and clarify their potential mechanisms. We suggest focusing on black carbon and Northeast regions.

The Weight of Place: Built Environment Correlates of Obesity and Diabetes

In recent decades, the prevalence of obesity and diabetes has risen substantially in North America and worldwide. To address these dual epidemics, researchers and policymakers alike have been searching for effective means to promote healthy lifestyles at a population level. As a consequence, there has been a proliferation of research examining how the "built" environment in which we live influences physical activity levels, by promoting active forms of transportation, such as walking and cycling, over passive ones, such as car use. Shifting the transportation choices of local residents may mean that more members of the population can participate in physical activity during their daily routine without structured exercise programs. Increasingly, this line of research has considered the downstream metabolic consequences of the environment in which we live, raising the possibility that "healthier" community designs could help mitigate the rise in obesity and diabetes prevalence. This review discusses the evidence examining the relationship between the built environment, physical activity, and obesity-related diseases. We also consider how other environmental factors may interact with the built environment to influence metabolic health, highlighting challenges in understanding causal relationships in this area of research.

Effects of Ambient Particulate Matter (PM2.5) Exposure on Calorie Intake and Appetite of Outdoor Workers

Malaysia has been experiencing smoke-haze episodes almost annually for the past few decades. PM2.5 is the main component in haze and causes harmful impacts on health due to its small aerodynamic size. This study aimed to explore the implications of PM2.5 exposure on the dietary intake of working individuals. Two phased 13-weeks follow-up study was conducted involving 440 participants, consisting of two cohorts of outdoor and indoor workers. Ambient PM2.5 concentrations were monitored using DustTrakTM DRX Aerosol Monitor. Data on Simplified Nutritional Appetite Questionnaire (SNAQ) and 24 h diet recall were collected weekly. The highest PM2.5 concentration of 122.90 ± 2.07 µg/m3 was recorded in August, and it vastly exceeded the standard value stipulated by US EPA and WHO. SNAQ scores and calorie intake were found to be significantly (p < 0.05) associated with changes in PM2.5 exposure of outdoor workers. Several moderate and positive correlations (R-value ranged from 0.4 to 0.6) were established between SNAQ scores, calorie intake and PM2.5 exposure. Overall findings suggested that long hours of PM2.5 exposure affect personal dietary intake, potentially increasing the risk of metabolic syndromes and other undesired health conditions. The current policy should be strengthened to safeguard the well-being of outdoor workers.

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.

Long-Term Effects of Ambient Particulate and Gaseous Pollutants on Serum High-Sensitivity C-Reactive Protein Levels: A Cross-Sectional Study Using KoGES-HEXA Data

Ambient air pollutants reportedly increase inflammatory responses associated with multiple chronic diseases. We investigated the effects of long-term exposure to ambient air pollution on high-sensitivity C-reactive protein (hs-CRP) using data from 60,581 participants enrolled in the Korean Genome and Epidemiology Study-Health Examinees Study between 2012 and 2017. Community Multiscale Air Quality System with surface data assimilation was used to estimate the participants' exposure to criteria air pollutants based on geocoded residential addresses. Long-term exposure was defined as the 2-year moving average concentrations of PM₁₀, PM_2.5, SO₂, NO₂, and O₃. Multivariable linear and logistic regression models were utilized to estimate the percent changes in hs-CRP and odds ratios of systemic low-grade inflammation (hs-CRP > 3 mg/L) per interquartile range increment in air pollutants. We identified positive associations between hs-CRP and PM₁₀ (% changes: 3.75 [95% CI 2.68, 4.82]), PM_2.5 (3.68, [2.57, 4.81]), SO₂ (1.79, [1.10, 2.48]), and NO₂ (3.31, [2.12, 4.52]), while negative association was demonstrated for O₃ (-3.81, [-4.96, -2.65]). Elevated risks of low-grade inflammation were associated with PM₁₀ (odds ratio: 1.07 [95% CI 1.01, 1.13]), PM_2.5 (1.08 [1.02, 1.14]), and SO₂ (1.05 [1.01, 1.08]). The odds ratios reported indicated that the exposures might be risk factors for inflammatory conditions; however, they did not reflect strong associations. Our findings suggest that exposure to air pollutants may play a role in the inflammation process.

Leukocyte telomere length and obesity in children and adolescents: A systematic review and meta-analysis

Background: Several studies have revealed the negative effects of adiposity on telomere length shortening. However, the results of the studies assessing the negative relationship between obesity and leukocyte telomere length (LTL) are not consistent. This systematic review and meta-analysis are aimed to pool the results of articles assessing the relationship between obesity and LTL among children and adolescents. Methods: To retrieve the related studies, four online databases including PubMed, Embase, ProQuest, and Scopus were searched until May 2022. Observational studies evaluating the relationship between obesity and LTL among apparently healthy children and adolescents (aged ≤18 years) were included in the study. We considered the studies that had reported a mean ± standard deviation of LTL. The random-effects model was used to assess the pooled weighted mean difference (WMD) and a 95% confidence interval (CI). Results: The search yielded seven studies from an initial 3,403 records identified. According to the results of seven articles with 4,546 participants, obesity was associated with LTL shortening among children and adolescents (WMD = -0.081; 95% CI: -0.137 to -0.026; p = 0.004; I2 = 99.9%). Also, no publication bias was observed. According to the results of subgrouping, significant results were only attributed to the studies conducted in Europe, with high quality scores, among overweight and obese adolescents, with a baseline LTL lower than 1, and performed in community-based school settings. Also, according to the subgrouping and meta-regression results, the obesity definition criteria and baseline LTL were the possible sources of between-study heterogeneity. Conclusion: We observed shorter LTL among overweight and obese children and adolescents. To obtain more reliable results, further longitudinal prospective studies with large sample sizes and more consistent and accurate definitions of obesity are required.

Intrauterine and Extrauterine Environmental PM2.5 Exposure Is Associated with Overweight/Obesity (O/O) in Children Aged 6 to 59 Months from Lima, Peru: A Case-Control Study

There is evidence that PM2.5 could be obesogenic. Lima is one of the most polluted cities in South America, with an increasing prevalence of childhood obesity. This study aimed to determine the association between PM2.5 exposure of children aged 6 to 59 months and being overweight or obese (O/O) in a significant dataset survey. Cases were defined when weight for height Z-score (WHZ) was >2 standard deviations (SD) from the mean, for each sex. A control was defined when WHZ was between ±2 SD. We used a conditional logistic regression model to calculate the odds ratio (OR) between extrauterine and intrauterine PM2.5 exposure and O/O. Extrauterine PM2.5 exposure was evaluated as a 6-month PM2.5 mean prior to the survey. We found a significant association between O/O and extrauterine (OR: 1.57, 1.51−1.63) and intrauterine (OR: 1.99, 1.88−2.12) PM2.5 exposure for an increment of 10 μg/m3. The ORs increased as the quartile increased in both exposures. We observed a higher association in children aged 6−11 months (OR: 3.07, 2.84−3.31). In conclusion, higher levels of PM2.5 in Lima and Callao were associated with cases of O/O in children from 6 to 59 months, with the association higher for prenatal exposure.

The Nexus between Pollution and Obesity and the Magnifying Role of Media Consumption: International Evidence from GMM Systems Estimates

The aim of this paper is to uncover the associations between air pollution, media consumption, and the prevalence of obesity. Based on data availability, this study draws on an unbalanced panel of 28 countries and develops and extracts relationships through robust System-General Method of Moments (Sys-GMM) estimators that account for the dynamic nature and high persistence of the variables of interest. In light of previous findings, economic development, trade openness, and government consumption are included as controls in the dynamic panel models. The estimation results consistently indicate that pollution is a strong determinant of obesity, a link that remains robust through the alternative proxies for pollution (i.e., total greenhouse gas emissions (GHG) and carbon (CO₂) intensity of energy generation). However, CO₂ intensity shows the strongest association with obesity. Furthermore, the findings indicate that media consumption is an independent and significant driver of obesity, whilst its inclusion among regressors further magnifies the impact and significance of the pollution factor. Moreover, the combined effect of media consumption and pollution significantly contributes to spurring obesity in all model specifications. Thus, a vicious cycle emerges between air pollution, media consumption, and obesity, with synergistic detrimental health effects. The current findings highlight the importance of continuing and consistent efforts to mitigate pollution and reach related low-carbon policy targets. Moreover, for the sustainable reduction and prevention of obesity, these efforts should be complemented by policy interventions and public campaigns aimed at "healthy" media consumption, such as encouraging regular physical exercise and healthy nutrition.

The Physiological Effects of Air Pollution: Particulate Matter, Physiology and Disease

Nine out of 10 people breathe air that does not meet World Health Organization pollution limits. Air pollutants include gasses and particulate matter and collectively are responsible for ~8 million annual deaths. Particulate matter is the most dangerous form of air pollution, causing inflammatory and oxidative tissue damage. A deeper understanding of the physiological effects of particulate matter is needed for effective disease prevention and treatment. This review will summarize the impact of particulate matter on physiological systems, and where possible will refer to apposite epidemiological and toxicological studies. By discussing a broad cross-section of available data, we hope this review appeals to a wide readership and provides some insight on the impacts of particulate matter on human health.

Ambient ozone exposure combined with residential greenness in relation to serum sex hormone levels in Chinese rural adults

BACKGROUND

Long-term exposure to ambient ozone (O3) and residential greenness independently relate to altered hormones levels in urban settings and developed countries. However, independent and their joint associations with progestogen and androgen were sparsely studied in rural regions.

MATERIALS AND METHODS

A total of 6211 individuals were recruited in this study. Random forest model was applied to predict the daily average concentrations of O3 using the satellites data. Residential greenness was reflected by the normalized difference vegetation index (NDVI). Liquid chromatography-tandem mass spectrometry was used to measure serum progestogen and androgen concentrations. Gender and menopausal status modified associations of long-term exposure to O3 and residential greenness with hormones levels were analyzed by generalized linear models.

RESULTS

Long-term exposure to O3 was negatively related to 17-hydroxyprogesterone, testosterone, and androstenedione in both men and women (premenopausal and postmenopausal); the estimated β and 95% CI of ln-progesterone in response to per 10 μg/m3 increment in O3 concentration was -0.560 (-0.965, -0.155) in postmenopausal women. Association of long-term exposure to O3 with serum androgen levels in premenopausal and postmenopausal women were alleviated by residing in places with higher greenness. Additionally, a prominent effect of long-term exposure to O3 related to decreased serum progestogen and androgen levels was found in participants with middle- or high-level of physical activity or lower education level.

CONCLUSIONS

The results suggested that long-term exposure to high levels of O3 related to decreased serum androgen levels was attenuated by living in high greenness places in women regardless of menopause status. Future studies are needed to confirm the positive health effects of residential greenness on the potential detrimental effects due to exposure to O3.

A Review of Studies Using Air Q Software for Prediction of Air Pollution Health Effects in Iran

PURPOSE OF REVIEW

Exposure to air pollutants may lead to various health effects and is a major public health issue. Concerns about these effects exist in both developed and developing countries. The Air Q software was developed to estimate the health impacts of air pollution based on reported levels of air pollutants in real world studies. In Iran several studies have been conducted to estimate human morbidity and mortality based on this software. We conducted this review to summarize articles which have predicted the effects of air pollution on human health in Iran using Air Q. We conducted a systematic search for relevant studies published until 24 April 2021 in Web of Science, PubMed, Scopus, and SID (Scientific Information Database which includes articles in Farsi language). We applied no time or language restrictions.

RECENT FINDINGS

A total of 44 studies out of 525 identified articles met our inclusion criteria. The main air pollutants under investigation were particulate matter (PM), NO₂, O₃, and SO₂. Most studies were conducted in metropolitan areas, such as Ahvaz (9 studies), Tehran (9 studies), and Shiraz (7 studies). In all studies, the levels of most air pollutants were higher than the 2005 WHO guideline levels and were predicted to be related to considerable health effects. However, it was not possible to aggregate the results and report the total number of casualties during these years, because studies were done in different cities with fluctuating levels of multiple pollutants and in different years and time frames. This systematic review showed that air pollution remains at unacceptably high levels resulting in substantial detrimental health effects in various Iranian cities. Using clean renewable energies, increasing human capital, and increasing green spaces and vegetation can help improve air pollution and decrease human casualties in Iran.

PM2.5 induced weight loss of mice through altering the intestinal microenvironment: Mucus barrier, gut microbiota, and metabolic profiling

The experimental evidences linking PM_2.5 exposure to weight status disorder and the associated mechanisms were lacked. Here, we demonstrated exposure of 198.52 μg/m³ PM_2.5 (Baoji city, China) for 40 days induced body weight loss of male Balb/C mice, and then increased after 14-day recovery. Correspondingly, gut microbiota dysbiosis, ileum metabolism alterations, and histopathological changes of liver and ileum elucidated the underlying mechanism. The richness and function modules of flora in feces significantly reduced after exposure, and the ratios of Bacteroidetes/Firmicutes reduced from 1.58 to 0.79. At genus level, Lactobacillus and Clostridium increased markedly, while Bacteroides and Parabacteroides decreased at day 40. After recovery, Oscillospira became the dominant genus. Additionally, the key metabolites in the ileum mediated by PM_2.5 identified by metabolomics included arachidonic acid, prostaglandin H₂, prostaglandin F_2α, 5(S)-HPETE, AMP, and deoxyadenosine. Accordingly, conjoint analysis between the gut micorbiota and metabolic profiling revealed suppression of Arachidonic acid metabolism, linoleic acid metabolism, and PPAR signaling pathway and stimulation of ABC transporters might contribute to the liver injury, ileum inflammation, and then weight loss of mice. Our findings suggested PM_2.5 affected weight status of mice by meditating intestinal microenvironment, and provided new insight for further diagnosis of the air pollution dependent disease.

Global association between atmospheric particulate matter and obesity: A systematic review and meta-analysis

BACKGROUND

Among various air pollutants, particulate matter (PM) is the most harmful and representative pollutant. Although several studies have shown a link between particulate pollution and obesity, the conclusions are still inconsistent.

METHODS

We conducted a systematic review and meta-analysis to pool the effect of PM exposure on obesity. Five databases (including PubMed, Web of Science, Scopus, Embase, and Cochrane) were searched for relevant studies up to Jan 2022. Adjusted risk ratio (RR) with corresponding 95% confidence interval (CI) were retrieved from individual studies and pooled with random effect models by STATA software. Besides, we tested the stability of results by Egger's test, Begg's test, funnel plot, and using the trim-and-fill method to modify the possible asymmetric funnel graph. The NTP-OHAT guidelines were followed to assess the risk of bias. Then the GRADE was used to evaluate the certainty of evidence.

RESULTS

26 studies were included in this meta-analysis. 19 studies have shown that PM_2.5 can increase the risk of obesity per 10 μg/m³ increment (RR: 1.159, 95% CI: 1.111-1.209), while 15 studies have indicated that PM₁₀ increase the risk of obesity per 10 μg/m³ increment (RR: 1.092, 95% CI: 1.070-1.116). Besides, 5 other articles with maternal exposure showed that PM_2.5 increases the risk of obesity in children (RR: 1.06, 95% CI: 1.02-1.11). And we explored the source of heterogeneity by subgroup analysis, which suggested associations between PM and obesity tended to vary by region, age group, participants number, etc. The analysis results showed publication bias and other biases are well controlled, but most certainties of the evidence were low, and more research is required to reduce these uncertainties.

CONCLUSION

Exposure to PM_2.5 and PM₁₀ with per 10 μg/m³ increment could increase the risk of obesity in the global population.

Association between environmental composite quality index score and obesity in children and their family: A cross-sectional study in northeast China

BACKGROUND

Childhood obesity has emerged as a severe public health problem worldwide. Most studies focused on the association between single environmental risk factors and obesity. Thus, we investigate the association between environmental composite quality index (ECQI) score and obesity in children and their families.

METHOD

The cross-sectional study was conducted among 2354 children and 1761 mothers in Fuxin City, Liaoning Province, in 2015. The information was collected by questionnaires, including environmental factors, heights, weights, and sociodemographic data. We quantitated thirteen indoor and outdoor risk factors and constructed the ECQI. There were 4 household environmental factors in the household air quality index (HAQI) and 9 variables to evaluate the outdoor environmental quality index (OEQI). Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using the binary logistic regression model after adjusting the most common obesity risk factors.

RESULTS

A higher ECQI score was correlated with a higher risk of childhood obesity and family obesity. Comparing the ECQI score 0-2 to the ECQI score ≥5, ORs with childhood obesity was 1.73 (95%CI, 1.25-2.39, P for trend = 0.001), and 1.53 for family obesity (95%CI, 1.09-2.15; P for trend = 0.003) after adjusted confounding factors. Similarly, a significantly positive association was found between OEQI score, HAQI score, and childhood obesity, family obesity.

CONCLUSION

A higher ECQI score was associated with an increased risk of obesity in children and their families. Both HAQI score and OEQI score were associated to childhood obesity and family obesity. Further studies should elucidate the underlying mechanisms.

Assuring Healthy Populations During the COVID-19 Pandemic: Recognizing Women's Contributions in Addressing Syndemic Interactions

A syndemic framework examines disease interactions and the contributions of structural, social, economic, and environmental factors that synergistically interact to contribute to adverse health outcomes. Populations residing in environments with structural susceptibilities experience health disparities and syndemics to a greater extent than their less vulnerable counterparts. The interactions among the social determinants of health (SDoH) and the COVID-19 pandemic have had different results for marginalized populations and have worsened health outcomes for many in this synergistic pandemic. Also, the exposome, the exposure measures for an individual over their lifetime and how those exposures relate to the individual's health, may help to explain why some populations experience more serious cases of COVID-19 compared to other groups. The purpose of this perspective is to: (1) examine the relationship between the syndemic model and the SDoH-exposome; (2) highlight, via specific examples, the contributions of female health professionals to SDoH and the COVID-19 syndemic in response to the Women in Science Research Topic, and (3) propose health policy to address syndemic-exposome interactions to help mitigate or prevent public health challenges. By investing in policies that assure health for all populations, the investments could pay dividends in the form of a less severe syndemic next time since we are starting from a place of health and not disease. Lastly, due to the magnification of underlying societal inequities laid bare during the COVID-19 syndemic, we support the expansion of the disease-focused syndemic model to include societal syndemics, such as systemic racism.

Physical and social environmental factors related to co-occurrence of unhealthy lifestyle behaviors

Previous work identifying determinants of co-occurrence of behavioral risk factors have focused on their association with individuals' characteristics with scant attention paid to their relationship to contextual factors. Data came from 21,007 individuals ≥15 years of age who participated in the cross-sectional 2011-2012 Spanish National Health Survey. Two indicators were defined by tobacco consumption, alcohol intake, diet, physical activity, and body mass index. The first indicator, based on dichotomized measures, ranges from 0 to 5. The second one (unhealthy lifestyle index), ranges from 0 to 15, with 0 denoting the healthiest score. Among the determinants, we examined social support, five perceived characteristics of the neighborhood, and the socioeconomic deprivation index of the census tract of residence. Data were analyzed using multilevel linear and logistic regression models adjusted for the main sociodemographic characteristics. Using the dichotomized indicator, the probability of having 3-5 risk factors versus <3 factors was associated with low social support (Odds Ratio [OR] 1.50; 95% Confidence Interval [CI]: 1.25-1.80). Issues surrounding neighborhood cleanliness (OR = 1.18; 95%CI: 1.04-1.33), air pollution (OR = 1.38; 95%CI: 1.16-1.64), and street crime (OR = 1.21; 95%CI: 1.03-1.42) were associated with determinants of co-occurrence. Risk factors co-occurrence increased as deprivation level increased: the OR for the highest deprivation quintile versus the lowest was 1.30 (95%CI: 1.14-1.48). Similar results were observed when using the unhealthy lifestyle index. Poorer physical and social environments are related to greater co-occurrence of risk factors for chronic diseases. Health promotion interventions targeting the prevention of risk factors should consider the contextual characteristics of the neighborhood environment.

A Geographical Analysis of Socioeconomic and Environmental Drivers of Physical Inactivity in Post Pandemic Cities: The Case Study of Chicago, IL, USA

The pandemic’s lockdown has made physical inactivity unavoidable, forcing many people to work from home and increasing the sedentary nature of their lifestyle. The link between spatial and socio-environmental dynamics and people’s levels of physical activity is critical for promoting healthy lifestyles and improving population health. Most studies on physical activity or sedentary behaviors have focused on the built environment, with less attention to social and natural environments. We illustrate the spatial distribution of physical inactivity using the space scan statistic to supplement choropleth maps of physical inactivity prevalence in Chicago, IL, USA. In addition, we employ geographically weighted regression (GWR) to address spatial non-stationarity of physical inactivity prevalence in Chicago per census tract. Lastly, we compare GWR to the traditional ordinary least squares (OLS) model to assess the effect of spatial dependency in the data. The findings indicate that, while access to green space, bike lanes, and living in a diverse environment, as well as poverty, unsafety, and disability, are associated with a lack of interest in physical activities, limited language proficiency is not a predictor of an inactive lifestyle. Our findings suggest that physical activity is related to socioeconomic and environmental factors, which may help guide future physical activity behavior research and intervention decisions, particularly in identifying vulnerable areas and people.

The Association between Childhood Exposure to Ambient Air Pollution and Obesity: A Systematic Review and Meta-Analysis

Obesity has become a worldwide epidemic; 340 million of children and adolescents were overweight or obese in 2016, and this number continues to grow at a rapid rate. Epidemiological research has suggested that air pollution affects childhood obesity and weight status, but the current evidence remains inconsistent. Therefore, the aim of this meta-analysis was to estimate the effects of childhood exposure to air pollutants on weight. A total of four databases (PubMed, Web of Science, Embase, and Cochrane Library) were searched for publications up to December 31, 2021, and finally 15 studies met the inclusion criteria for meta-analysis. Merged odds ratios (ORs), coefficients (β), and 95% confidence intervals (95% CIs) that were related to air pollutants were estimated using a random-effects model. The meta-analysis indicated that air pollutants were correlated with childhood obesity and weight gain. For obesity, the association was considerable for PM₁₀ (OR = 1.12, 95% CI: 1.06, 1.18), PM_2.5 (OR = 1.28, 95% CI: 1.13, 1.45), PM₁ (OR = 1.41, 95% CI: 1.30, 1.53), and NO₂ (OR = 1.11, 95% CI: 1.06, 1.18). Similarly, BMI status increased by 0.08 (0.03-0.12), 0.11 (0.05-0.17), and 0.03 (0.01-0.04) kg/m² with 10 μg/m³ increment in exposure to PM₁₀, PM_2.5, and NO₂. In summary, air pollution can be regarded as a probable risk factor for the weight status of children and adolescents. The next step is to conduct longer-term and large-scale studies on different population subgroups, exposure concentrations, and pollutant combinations to provide detailed evidence. Meanwhile, integrated management of air pollution is essential.

Urban Neighbourhood Environments, Cardiometabolic Health and Cognitive Function: A National Cross-Sectional Study of Middle-Aged and Older Adults in Australia

Population ageing and urbanisation are global phenomena that call for an understanding of the impacts of features of the urban environment on older adults' cognitive function. Because neighbourhood characteristics that can potentially have opposite effects on cognitive function are interdependent, they need to be considered in conjunction. Using data from an Australian national sample of 4141 adult urban dwellers, we examined the extent to which the associations of interrelated built and natural environment features and ambient air pollution with cognitive function are explained by cardiometabolic risk factors relevant to cognitive health. All examined environmental features were directly and/or indirectly related to cognitive function via other environmental features and/or cardiometabolic risk factors. Findings suggest that dense, interconnected urban environments with access to parks, blue spaces and low levels of air pollution may benefit cognitive health through cardiometabolic risk factors and other mechanisms not captured in this study. This study also highlights the need for a particularly fine-grained characterisation of the built environment in research on cognitive function, which would enable the differentiation of the positive effects of destination-rich neighbourhoods on cognition via participation in cognition-enhancing activities from the negative effects of air pollutants typically present in dense, destination-rich urban areas.

Machine learning approaches to characterize the obesogenic urban exposome

BACKGROUND

Characteristics of the urban environment may contain upstream drivers of obesity. However, research is lacking that considers the combination of environmental factors simultaneously.

OBJECTIVES

We aimed to explore what environmental factors of the urban exposome are related to body mass index (BMI), and evaluated the consistency of findings across multiple statistical approaches.

METHODS

A cross-sectional analysis was conducted using baseline data from 14,829 participants of the Occupational and Environmental Health Cohort study. BMI was obtained from self-reported height and weight. Geocoded exposures linked to individual home addresses (using 6-digit postcode) of 86 environmental factors were estimated, including air pollution, traffic noise, green-space, built environmental and neighborhood socio-demographic characteristics. Exposure-obesity associations were identified using the following approaches: sparse group Partial Least Squares, Bayesian Model Averaging, penalized regression using the Minimax Concave Penalty, Generalized Additive Model-based boosting Random Forest, Extreme Gradient Boosting, and Multiple Linear Regression, as the most conventional approach. The models were adjusted for individual socio-demographic variables. Environmental factors were ranked according to variable importance scores attributed by each approach and median ranks were calculated across these scores to identify the most consistent associations.

RESULTS

The most consistent environmental factors associated with BMI were the average neighborhood value of the homes, oxidative potential of particulate matter air pollution (OP), healthy food outlets in the neighborhood (5 km buffer), low-income neighborhoods, and one-person households in the neighborhood. Higher BMI levels were observed in low-income neighborhoods, with lower average house values, lower share of one-person households and smaller amount of healthy food retailers. Higher BMI levels were observed in low-income neighborhoods, with lower average house values, lower share of one-person households, smaller amounts of healthy food retailers and higher OP levels. Across the approaches, we observed consistent patterns of results based on model's capacity to incorporate linear or nonlinear associations.

DISCUSSION

The pluralistic analysis on environmental obesogens strengthens the existing evidence on the role of neighborhood socioeconomic position, urbanicity and air pollution.

Portable HEPA filter air cleaner use during pregnancy and children's body mass index at two years of age: The UGAAR randomized controlled trial

IMPORTANCE

Gestational exposure to particulate matter (PM) air pollution may increase the risk of childhood obesity, but the impact of reducing air pollution during pregnancy on obesity-related outcomes in childhood has not been examined.

OBJECTIVE

To assess the impact of reducing gestational PM exposure on body mass index (BMI) at two years of age.

METHODS

In this single-blind, parallel group randomized controlled trial in Ulaanbaatar Mongolia, we randomly assigned 540 pregnant women to receive 1-2 portable high efficiency particulate air (HEPA) filter air cleaners or no air cleaners. We measured height and weight when children were a mean age of 23.8 months. Our primary outcome was age- and sex-specific BMI z-score based on the World Health Organization 2007 Growth Charts. Secondary outcomes included age- and sex-specific weight z score, overweight/obesity (defined as BMI z-score > 2.00), and catch-up growth (defined using various cut-offs to identify children with relatively low birth weight for sex and gestational age and relatively high age- and sex-specific weight in childhood). We imputed missing outcome data using multiple imputation with chained equations and our primary analysis was by intention to treat (ITT). We estimated intervention effects on continuous and binary outcomes using linear and logistic regression, respectively.

RESULTS

After excluding known miscarriages, still births, and neonatal deaths our analysis included 480 children (235 control and 245 intervention). The mean (SD) child BMI z score was 0.79 (1.0); 9.8% of children were overweight or obese. The mean BMI z score of children who were randomly assigned to the intervention group was 0.16-units lower (95% CI: -0.35, 0.04) than children in the control group. The intervention was also associated with reductions in overweight/obesity (odds ratio = 0.59; 95% CI: 0.31, 1.12). Catch-up growth occurred less frequently in the intervention group, but effect estimates varied depending on the specific definition of catch-up growth and confidence intervals consistently spanned no effect.

CONCLUSIONS

We found that the use of portable air cleaners during pregnancy was associated with improvements in obesity-related outcomes, although some effect estimates lacked precision. Reducing PM exposure during pregnancy may lead to improvements in cardiometabolic health in childhood.

Positive Association between Indoor Gaseous Air Pollution and Obesity: An Observational Study in 60 Households

This study aims to analyze whether exposure to indoor air pollution affects obesity. In our research, we recruited 127 participants, with an average age of 43.30 ± 15.38 years old, residing in 60 households. We monitored indoor air quality for 24 h, and conducted both questionnaire surveys and collected serum samples for analysis, to assess the relationship between indoor air pollutant exposure and obesity. After adjusting for demographic characteristics, the results showed that CO₂ exposure is positively associated with being overweight and with a higher risk of being abdominally obese. Exposures to CO and formaldehyde were also positively associated with being overweight. IQR increase in TVOC was positively associated with increases in the risk of a high BMI, being abdominally obese and having a high body fat percentage. Two-pollutant models demonstrate that TVOCs presented the strongest risks associated with overweightness. We concluded that persistent exposure to indoor gaseous pollutants increases the risk of overweightness and obesity, as indicated by the positive association with BMI, abdominal obesity, and percentage body fat. TVOCs display the strongest contribution to obesity.

Urban-rural differences in the association between long-term exposure to ambient air pollution and obesity in China

INTRODUCTION

Ambient air pollution might increase the risk of obesity; however, the evidence regarding the relationship between air pollution and obesity in comparable urban and rural areas is limited. Therefore, our aim was to contrast the effect estimates of varying air pollution particulate matter on obesity between urban and rural areas.

METHODS

Four obesity indicators were evaluated in this study, namely, body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR). Exposure to ambient air pollution (e.g., particulate matter with aerodynamic diameters 1.0 μm [PM₁], PM_2.5, and PM₁₀) was estimated using satellite-based random forest models. Linear regression and logistic regression models were used to assess the associations between air pollution particulate matter and obesity. Furthermore, the effect estimates of different air pollution particulates were contrasted between urban and rural areas.

RESULTS

A total of 36,998 participants in urban areas and 31, 256 in rural areas were included. We found positive associations between long-term exposure to PM₁, PM_2.5, and PM₁₀ and obesity. Of these air pollutants, PM_2.5 had the strongest association. The results showed that the odds ratios (ORs) for general obesity were 1.8 (95% CI, 1.64 to 1.98) per interquartile range (IQR) μg/m³ increase in PM₁, 1.89 (95% CI, 1.71 to 2.1) per IQR μg/m³ increase in PM_2.5, and 1.74 (95% CI, 1.58 to 1.9) per IQR μg/m³ increase in PM₁₀. The concentrations of air pollutants were lower in rural areas, but the effects of air pollution on obesity of rural residents were higher than those of urban residents.

CONCLUSION

Long-term (3 years average) exposure to ambient air pollution was associated with an increased risk of obesity. We observed regional disparities in the effects of particulate matter exposure from air pollution on the risk of obesity, with higher effect estimates found in rural areas. Air quality interventions should be prioritized not only in urban areas but also in rural areas to reduce the risk of obesity.

A Co-Twin control study of fine particulate matter and the prevalence of metabolic syndrome risk factors

The relationship between ambient fine particulate matter (PM_2.5) and metabolic syndrome (MetS) is understudied. It also remains unknown whether familial factors play a role in this relationship. In a study of 566 middle-aged twins, we examined the association of PM_2.5 with MetS risk factors, measured by a MetS score as a summation of individual risk factors (range, 0 to 5). High-resolution PM_2.5 estimates were obtained through previously validated models that incorporated monitor and satellite derived data. We estimated two-year average PM_2.5 concentrations based on the ZIP code of each twin's residence. We used ordinal response models adapted for twin studies. When treating twins as individuals, the odds ratio of having 1-point higher MetS score was 1.78 for each 10 μg/m³-increase in exposure to PM_2.5 (confidence interval [CI]: 1.01, 3.15), after adjusting for potential confounders. This association was mainly between pairs; the odds ratio was 1.97 (CI: 1.01, 3.84) for each 10 μg/m³-increase in the average pairwise exposure level. We found no significant difference in MetS scores within pairs who were discordant for PM_2.5 exposure. In conclusion, higher PM_2.5 in residence area is associated with more MetS risk factors. This association, however, is confounded by shared familial factors.

Street view greenness is associated with lower risk of obesity in adults: Findings from the 33 Chinese community health study

BACKGROUND

Urban greenness may protect against obesity, but very few studies have assessed 'street view' (SV) greenness metrics, which may better capture people's actual exposure to greenness compared to commonly-used satellite-derived metrics. We aimed to investigate these associations further in a Chinese adult study.

METHODS

Our analysis included 24,845 adults in the 33 Chinese Community Health Study in 2009. SV images from Tencent Map, segmented by machine learning algorithms, were used to determine the average proportion of green vegetation in SV images at community level in 800m road network buffer. Sensitivity analyses were performed with an alternative buffer size. Overall greenness was assessed as normalized difference vegetation index (NDVI) in 800 m buffer. We used predicted PM_2.5 and monitored NO₂ as proxies of air pollution. Body mass index (BMI), waist circumference (WC) and hip circumference (HC) were regressed on SV greenness by generalized linear mixed models, with adjustment for covariates. Mediation analyses were performed to assess the mediation effects of air pollution.

RESULTS

Each interquartile range (IQR = 3.6%) increase in street view greenness was associated with a 0.15 kg/m² (95% CI: -0.22, -0.09) decrease in BMI and 0.23 cm (95% CI: -0.35, -0.11) reduction in HC, and was associated with 7% lower odds of overweight (OR = 0.93, 95% CI:0.90, 0.96) and 18% lower odds of obesity (OR = 0.82, 95% CI:0.76, 0.89). Similar effect estimation was observed compared with commonly-used NDVI measures. PM_2.5 and NO₂ mediated 15.5% and 6.1% of the effects of SV greenness with BMI, respectively.

CONCLUSIONS

Our findings suggest beneficial associations between community-level SV greenness and lower body weight in Chinese adults. The effects were observed in women but not in men. Air pollution may partially mediate the association. These findings may have implications to support efforts to promote greening in urban areas.

Weekly-specific ambient fine particular matter exposures before and during pregnancy were associated with risks of small for gestational age and large for gestational age: results from Project ELEFANT

BACKGROUND

Investigations on the potential effects of ambient fine particulate matter (PM2.5) on large for gestational age (LGA) are limited. Furthermore, no study has explored weekly-specific susceptible exposure windows for small for gestational age (SGA) and LGA. This study evaluated the associations of exposure to ambient PM2.5 over the preconception and entire-pregnancy periods with risks of SGA and LGA, as well as explored critical weekly-specific exposure windows.

METHODS

10 916 singleton pregnant women with 24-42 completed gestational weeks from the Project Environmental and LifEstyle FActors iN metabolic health throughout life-course Trajectories between 2014 and 2016 were included in this study. Distributed lag models (DLMs) incorporated in Cox proportional-hazards models were applied to explore the associations of maternal exposure to weekly ambient PM2.5 throughout 12 weeks before pregnancy and pregnancy periods with risks of SGA and LGA after controlling for potential confounders.

RESULTS

For a 10-μg/m3 increase in maternal exposure to PM2.5, positive associations with SGA were observed during the 1st to 9th preconceptional weeks and the 1st to 2nd gestational weeks (P<0.05), with the strongest association in the 5th preconceptional week [hazard ratio (HR), 1.06; 95% confidential interval (CI), 1.03-1.09]. For LGA, positive associations were observed during the 1st to 12th preconceptional weeks and the 1st to 5th gestational weeks (P<0.05), with the strongest association in the 7th preconceptional week (HR, 1.10; 95% CI, 1.08-1.12).

CONCLUSIONS

Exposure to high-level ambient PM2.5 is associated with increased risks of both SGA and LGA, and the most susceptible exposure windows are the preconception and early-pregnancy periods.

Air Pollution: A Neglected Risk Factor for Dementia in Latin America and the Caribbean

The risk of dementia and Alzheimer's disease in Latin America and the Caribbean (LAC) rises with increasing age and polluted air. Currently, at least 172 million people breathe unhealthy levels of air pollution in LAC countries. Several cohort studies have indicated that air pollution increases the risk of developing dementia and neurodegenerative diseases, but the mechanisms underlying the association are still not clear. Air pollution causes and aggravates five established risk factors for dementia (obesity, hypertension, stroke, diabetes mellitus, and heart diseases) and is linked to three other risk factors (physical inactivity, cognitive inactivity, and depression). Some of these risk factors could be mediating the association between air pollution and dementia. Reducing the risks for dementia is crucial and urgently needed in LAC countries. There is room for improving air quality in many urban areas in the LAC region and other low- and middle-income countries (LMICs), a routealready explored by many urban areas in developing regions. Moreover, reducing air pollution has proved to improve health outcomes before. In this article, we propose that despite the ongoing and valid scientific discussion, if air pollution can or cannot directly affect the brain and cause or aggravate dementia, we are ready to consider air pollution as a potentially modifiable risk factor for dementia in LAC and possibly in other LMICs. We suggest that controlling and reducing current air pollution levels in LAC and other LMIC regions now could strongly contribute.

Long-term exposure to ambient PM2.5 increase obesity risk in Chinese adults: A cross-sectional study based on a nationwide survey in China

Certain studies suggest that air pollution could be a risk factor for obesity, but the evidence on the association between air pollution exposure and obesity in adults is limited. This study aims to examine the association between long-term exposure to fine particulate matter (PM_2.5) and obesity-related traits in Chinese adults. Thus, a cross-sectional study was conducted based on a nationally representative sample of 91, 121 adults from 31 provinces in China. Integrated the data from satellites, chemical transport model, and ground observations, annual average concentrations of PM_2.5 was obtained at the township level using a machine learning method. The information on body weight, height, and waist circumference (WC) were obtained from a questionnaire survey. The general obesity and abdominal obesity status were classified based on body mass index (BMI) and WC, respectively. Logistic and multivariate linear regression models were used to examine the association between PM_2.5 and obesity-related traits, along with the examination of potential effect modifications. After adjustment for covariates, a 10 μg/m³ increase in PM_2.5 concentration was associated with 8.0% [95% confidence interval (CI): 1.0%, 10.0%] and 10% (95% CI: 9.0%, 11.0%) increases in odds for general obesity and abdominal obesity, respectively. The odds ratios associated with per 10 μg/m³ PM_2.5 increase were significantly greater in individuals of older age (≥60 years), of Han ethnicity, with lower socioeconomic status (SES), cooking without using a ventilation device, using unclean household fuels, having near-home pollution sources, and doing no physical exercise. These findings suggest that long-term exposure to ambient PM_2.5 increase obesity risk in Chinese adults. It has significant significance to reduce air pollution to reducing the burden of obesity, particularly for the susceptible populations.

Climate and air pollution exposure are associated with thyroid function parameters: a retrospective cross-sectional study

OBJECTIVES

There are still controversies about the impact of climatic and environmental factors on thyroid function parameters in healthy populations. We investigated the relationships between climate, air pollution exposure, and thyroid function fluctuations.

METHODS

We retrospectively reviewed 327,913 individuals attending routine health checks from December 2013 to December 2018. We analyzed the associations between thyroid function and climatic factors using Spearman's correlation analysis. We explored the relationships between thyroid function and air pollution exposure using multiple linear regression analysis, after adjusting for age, sex, season, and outdoor temperature. We also performed subgroup analyses by age and sex and sensitivity analyses of different anti-thyroid peroxidase antibody status.

RESULTS

Thyroid-stimulating hormone (TSH) and free triiodothyronine (FT3) were negatively associated with outdoor temperature (r = - 0.66, P < 0.001; r = - 0.55, P < 0.001), while free thyroxine (FT4) and FT4/FT3 were positively associated with temperature (r = 0.35, P < 0.001; r = 0.79, P < 0.001). An increase of 10 μg/m³ in fine particulate matter ≤ 2.5 μm (PM2.5) was associated with a decrease of 0.12 pmol/L in FT4 and an increase of 0.07 pmol/L in FT3 (both P < 0.01). FT4/FT3 was significantly negatively associated with PM2.5 (coefficient: - 0.06, P < 0.01). These results remained robust in hierarchical analyses and sensitivity analyses.

CONCLUSIONS

Thyroid function parameters are associated with climate and air pollution exposure. These factors may influence variations in thyroid function. Our results also highlight the importance of public health interventions to reduce air pollution.

Prenatal exposure to ambient air pollutants and early infant growth and adiposity in the Southern California Mother's Milk Study

BACKGROUND

Prior epidemiological and animal work has linked in utero exposure to ambient air pollutants (AAP) with accelerated postnatal weight gain, which is predictive of increased cardiometabolic risk factors in childhood and adolescence. However, few studies have assessed changes in infant body composition or multiple pollutant exposures. Therefore, the objective of this study was to examine relationships between prenatal residential AAP exposure with infant growth and adiposity.

METHODS

Residential exposure to AAP (particulate matter < 2.5 and 10 microns in aerodynamic diameter [PM2.5, PM10]; nitrogen dioxide [NO2]; ozone [O3]; oxidative capacity [Oxwt: redox-weighted oxidative potential of O3 and NO2]) was modeled by spatial interpolation of monitoring stations via an inverse distance-squared weighting (IDW2) algorithm for 123 participants from the longitudinal Mother's Milk Study, an ongoing cohort of Hispanic mother-infant dyads from Southern California. Outcomes included changes in infant growth (weight, length), total subcutaneous fat (TSF; calculated via infant skinfold thickness measures) and fat distribution (umbilical circumference, central to total subcutaneous fat [CTSF]) and were calculated by subtracting 1-month measures from 6-month measures. Multivariable linear regression was performed to examine relationships between prenatal AAP exposure and infant outcomes. Models adjusted for maternal age, pre-pregnancy body mass index, socioeconomic status, infant age, sex, and breastfeeding frequency. Sex interactions were tested, and effects are reported for each standard deviation increase in exposure.

RESULTS

NO2 was associated with greater infant weight gain (β = 0.14, p = 0.02) and TSF (β = 1.69, p = 0.02). PM10 and PM2.5 were associated with change in umbilical circumference (β = 0.73, p = 0.003) and TSF (β = 1.53, p = 0.04), respectively. Associations of Oxwt (pinteractions < 0.10) with infant length change, umbilical circumference, and CTSF were modified by infant sex. Oxwt was associated with attenuated infant length change among males (β = -0.60, p = 0.01), but not females (β = 0.16, p = 0.49); umbilical circumference among females (β = 0.92, p = 0.009), but not males (β = -0.00, p = 0.99); and CTSF among males (β = 0.01, p = 0.03), but not females (β = 0.00, p = 0.51).

CONCLUSION

Prenatal AAP exposure was associated with increased weight gain and anthropometric measures from 1-to-6 months of life among Hispanic infants. Sex-specific associations suggest differential consequences of in utero oxidative stress. These results indicate that prenatal AAP exposure may alter infant growth, which has potential to increase childhood obesity risk.

Ambient air pollution and obesity in school-aged children and adolescents: A multicenter study in China

BACKGROUND

Environmental factors such as air pollution may contribute to the development of childhood obesity. However, current epidemiological evidence is limited and inconsistent.

OBJECTIVE

We investigated the associations between long-term air pollution exposure and obesity in a large population of Chinese children and adolescents.

METHODS

A total of 44,718 children and adolescents (50.5% boys) aged 7 to 18 years were recruited from seven provinces/municipalities in China. Body mass index (BMI), waist circumference, waist-to-height ratio (WHtR) and the prevalence of general and central obesity were measured. Satellite-based spatial-temporal models were used to estimate ambient concentrations of particulate matter with aerodynamic diameter < 1.0 μm (PM₁), <2.5 μm (PM_2.5), <10.0 μm (PM₁₀) and nitrogen dioxide (NO₂). We used mixed-effects linear and logistic regression models to examine the associations between air pollution exposure and body weight measures.

RESULTS

Exposure to PM₁, PM_2.5, PM₁₀ and NO₂ was associated with increased BMI Z-score, waist circumference and WHtR, and higher prevalence of both general and central obesity. Generally, stronger associations were observed for particles, especially PM₁ and PM_2.5, than for NO₂. Also, the associations of particles were generally more stable in two-pollutant models. Overall, the associations were more pronounced in boys than in girls except for general obesity.

CONCLUSIONS

Long-term exposure to air pollution was associated with increased body weight and higher prevalence of obesity in children and adolescents, suggesting potential obesogenic effects of air pollution.

Effect of Seasonal Variation on the Relationship of Indoor Air Particulate Matter with Measures of Obesity and Blood Pressure in Children

BACKGROUND

Particulate matter (PM) air pollution is an important environmental health risk factor. Although some studies have shown PM to be associated with obesity and hypertension, very few studies have assessed the association of indoor PM specifically with obesity and blood pressure measures in children with respect to seasonal variation.

OBJECTIVES

The present study investigated the relationship of PM with obesity and blood pressure variables in children across the winter and summer seasons.

METHODS

A comparative descriptive approach was adopted and school children from 10-14 years of age from selected rural and urban localities of the Eastern Cape Province of South Africa were assessed in winter and summer. Anthropometric measurements were taken, including height, weight, waist circumference, body mass index (BMI), and total fat mass (TFM), while blood pressure variables including systolic blood pressure (SBP), diastolic blood pressure (DBP) and heart rate (HR) were measured. Indoor air PM concentrations were measured in the classrooms in the presence of children.

RESULTS

The prevalence of obesity and hypertension in children were 13.4% and 5.1% in winter and 12.9% and 1.0% in summer, respectively. High blood pressure was more prevalent in children in rural areas, while the prevalence of obesity in children was higher in urban areas. Particulate matter was significantly (p<0.05) higher in rural areas compared to urban areas. Obese children in summer had a greater than 3-fold association (AOR: 3.681, p=0.005) with 4th interquartile range (IQR) of PM5 and a greater than 3- and 4-fold association (AOR: 3.08; 4.407; p<0.05) with 2nd and 4th IQR of PM10, respectively, than their overweight, normal weight or underweight counterparts. High blood pressure was not associated (p< 0.05) with PM.

CONCLUSIONS

High concentrations of indoor PM were positively associated with obesity in children in summer, particularly among rural children. This association could be accounted for by location and seasonal differences.

PARTICIPANT CONSENT

Obtained.

ETHICS APPROVAL

Ethics approval was obtained from the Health Sciences Ethics Committee of Walter Sisulu University, South Africa (Ref No: CHI011SCHU01).

COMPETING INTERESTS

The authors declare no competing financial interests.

Nontraditional Risk Factors for Obesity in Modern Society

Overweight and obesity, which have rapidly increased around the world in recent years, are significant health problems. They can lead to various morbidities, including cardiovascular diseases, cerebrovascular diseases, type 2 diabetes, some types of cancer, and even death. Obesity is caused by an energy imbalance due to excessive calorie intake and insufficient energy consumption, and genetic factors and individual behavioral problems are also known to be major contributing factors. However, these are insufficient to explain the surge in obesity that has occurred in recent decades. Recent studies have suggested that environmental factors arising from the process of socioeconomic development and modernization contribute to this phenomenon. These environmental factors include light pollution due to artificial lighting, air pollution, endocrine-disrupting chemicals, and reduced exposure to green spaces due to urbanization of residential areas. In this manuscript, the findings and mechanisms of these novel risk factors causing overweight and obesity are reviewed.

An external exposome-wide association study of COVID-19 mortality in the United States

The risk factors for severe COVID-19 beyond older age and certain underlying health conditions are largely unknown. Recent studies suggested that long-term environmental exposures may be important determinants of severe COVID-19. However, very few environmental factors have been studied, often separately, without considering the totality of the external environment (i.e., the external exposome). We conducted an external exposome-wide association study (ExWAS) using the nationwide county-level COVID-19 mortality data in the contiguous US. A total of 337 variables characterizing the external exposome from 8 data sources were integrated, harmonized, and spatiotemporally linked to each county. A two-phase procedure was used: (1) in Phase 1, a random 50:50 split divided the data into a discovery set and a replication set, and associations between COVID-19 mortality and individual factors were examined using mixed-effect negative binomial regression models, with multiple comparisons addressed, and (2) in Phase 2, a multivariable regression model including all variables that are significant from both the discovery and replication sets in Phase 1 was fitted. A total of 13 and 22 variables were significant in the discovery and replication sets in Phase 1, respectively. All the 4 variables that were significant in both sets in Phase 1 remained statistically significant in Phase 2, including two air toxicants (i.e., nitrogen dioxide or NO₂, and benzidine), one vacant land measure, and one food environment measure. This is the first external exposome study of COVID-19 mortality. It confirmed some of the previously reported environmental factors associated with COVID-19 mortality, but also generated unexpected predictors that may warrant more focused evaluation.

Ambient air pollution and the development of overweight and obesity in children: a large longitudinal study

BACKGROUND

Ambient air pollution may play a role in childhood obesity development, but evidence is scarce, and the modifying role of socioeconomic status (SES) is unclear. We aimed to examine the association between exposure to air pollution during early childhood and subsequent risk of developing overweight and obesity, and to evaluate whether SES is a modifier of this association.

METHODS

This longitudinal study included 416,955 children identified as normal weight between 2-5 years old and registered in an electronic primary healthcare record between 2006 and 2016 in Catalonia (Spain). Children were followed-up until they developed overweight or obesity, reached 15 years of age, died, transferred out, or end of study period (31/12/2018). Overweight and obesity were defined following the WHO reference obtained from height and weight measures. We estimated annual residential census levels of nitrogen dioxide (NO₂) and particulate matter <10 μm (PM₁₀), <2.5 μm (PM_2.5), and 2.5-10 μm (PM_coarse) at study entry. We estimated the risk of developing overweight and obesity per interquartile range increase in air pollution exposure with Cox proportional hazard models.

RESULTS

A total of 142,590 (34.2%) children developed overweight or obesity. Increased exposure to NO₂, PM₁₀, and PM_coarse was associated with a 2-3% increased risk of developing overweight and obesity (hazard ratio [HR] per 21.8 μg/m³ NO₂ = 1.03 [95% CI: 1.02-1.04]; HR per 6.4 μg/m³ PM₁₀ = 1.02 [95% CI: 1.02-1.03]; HR per 4.6 µg/m³ PM_coarse = 1.02, [95% CI: 1.01-1.02]). For all air pollutants, associations were stronger among children living in most compared to least deprived areas.

CONCLUSIONS

This study suggests that early life exposure to air pollution may be associated with a small increase in the risk of developing overweight and obesity in childhood, and that this association may be exacerbated in the most deprived areas. Even these small associations are of potential global health importance because air pollution exposure is widespread and the long-term health consequences of childhood obesity are clear.

Effect of Air Pollution on Obesity in Children: A Systematic Review and Meta-Analysis

Air pollution exposure has been identified as being associated with childhood obesity. Nevertheless, strong evidence of such an association is still lacking. To analyze whether air pollution exposure affects childhood obesity, we conducted a systematic review and meta-analysis utilizing the PRISMA guidelines. Of 7343 studies identified, eight studies that investigated the effects of air pollutant characteristics, including PM_2.5, PM₁₀, PM_coarse, PM_absorbance, NO_x, and NO₂, on childhood obesity were included. The polled effects showed that air pollution is correlated with a substantially increased risk of childhood obesity. PM_2.5 was found to be associated with a significantly increased risk (6%) of childhood obesity (OR 1.06, 95% CI 1.02–1.10, p = 0.003). In addition, PM₁₀, PM_{2.5absorbance}, and NO₂ appeared to significantly increase the risk of obesity in children (OR 1.07, 95% CI 1.04–1.10, p < 0.00; OR 1.23, 95% CI 1.06–1.43, p = 0.07; and OR 1.10, 95% CI 1.04–1.16, p < 0.001, respectively). PM_coarse and NO_x also showed trends towards being associated with an increased risk of childhood obesity (OR 1.07, 95% CI 0.95–1.20, p = 0.291, and OR 1.00, 95% CI 0.99–1.02, p = 0.571, respectively). Strong evidence was found to support the theory that air pollution exposure is one of the factors that increases the risk of childhood obesity.

Fine particulate matter and body weight status among older adults in China: Impacts and pathways

BACKGROUND

Population ageing and air pollution have become two major public health concerns in China. Longitudinal evidence on the body weight impacts of air pollution among older adults is rare. This study aims to investigate the impacts of ambient particulate matter with aerodynamic diameters ≤2.5 μm (PM_2.5) on weight status of older adults in China and the potential behavioral and metabolic pathways through which PM_2.5 influences weight status.

METHODS

The longitudinal data from the China Health and Retirement Longitudinal Study (body mass index-BMI, n = 9053; waist/height ratio-WHR, n = 9064) were linked to the air pollution data at the city-level with a rural-urban distinction. We used mixed-effects linear models to evaluate the impacts of PM_2.5 on individual weight status and multiple mediation analysis to examine potential pathways.

RESULTS

After adjusting for relevant socioeconomic and city-level risk factors, significant and robust positive impacts of PM_2.5 on BMI (0.025, 95%CI: 0.018, 0.031) and WHR*100 (0.058, 95%CI: 0.044, 0.072) were found among older adults in China. The PM_2.5-weight status relationship among older adults may be mediated through metabolic and inflammatory dysfunction pathways particularly HbA1c and C-reactive protein (CRP). As PM_2.5 deteriorates, the detrimental impacts tend to be more severe for rural-urban migrants and rural residents, compared to their urban counterparts. The worsening rural PM_2.5 profiles in some areas, such as the northern parts of the Central and the Eastern, may leave them particularly vulnerable to air pollution.

CONCLUSIONS

PM_2.5 has an independent and significant detrimental impact on weight status including BMI and WHR of older adults in China, especially among rural adults and rural-urban migrants. PM_2.5 may affect weight status of older adults through biomarkers such as HbA1c and CRP. More research is needed to confirm our findings.

Prevalence and Social and Built Environmental Determinants of Maternal Prepregnancy Obesity in 68 Major Metropolitan Cities of the United States, 2013-2016

Objective

Maternal prepregnancy obesity is related to increased maternal morbidity and mortality and poor birth outcomes. However, prevalence and risk factors for prepregnancy obesity in US cities are not known. This study examines the prevalence and social and environmental determinants of maternal prepregnancy obesity (BMI ≥30), overweight/obesity (BMI ≥25), and severe obesity (BMI ≥40) in the 68 largest metropolitan cities of the United States.

Methods

We fitted logistic and Poisson regression models to the 2013–2016 national vital statistics birth cohort data (N = 3,083,600) to derive unadjusted and adjusted city differentials in maternal obesity and to determine social and environmental determinants.

Results

Considerable disparities existed across cities, with the prevalence of prepregnancy obesity ranging from 10.4% in San Francisco to 36.6% in Detroit. Approximately 63.0% of mothers in Detroit were overweight or obese before pregnancy, compared with 29.2% of mothers in San Francisco. Severe obesity ranged from 1.4% in San Francisco to 8.5% in Cleveland. Women in Anchorage, Buffalo, Cleveland, Fresno, Indianapolis, Louisville, Milwaukee, Oklahoma City, Sacramento, St Paul, Toledo, Tulsa, and Wichita had >2 times higher adjusted odds of prepregnancy obesity compared to those in San Francisco. Race/ethnicity, maternal age, parity, marital status, nativity/immigrant status, and maternal education were important individual-level risk factors and accounted for 63%, 39%, and 72% of the city disparities in prepregnancy obesity, overweight/obesity, and severe obesity, respectively. Area deprivation, violent crime rates, physical inactivity rates, public transport use, and access to parkland and green spaces remained significant predictors of prepregnancy obesity even after controlling for individual-level covariates.

Conclusions

Substantial disparities in maternal prepregnancy obesity among the major US cities remain despite risk-factor adjustment, with women in several Southern and Midwestern cities experiencing high risks of obesity. Sound urban policies are needed to promote healthier lifestyles and favorable social and built environments for obesity reduction and improved maternal health.

Vehicle emissions-exposure alters expression of systemic and tissue-specific components of the renin-angiotensin system and promotes outcomes associated with cardiovascular disease and obesity in wild-type C57BL/6 male mice

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Vehicle emission-exposure increases systemic and adipose renin-angiotensin signaling.

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Emission-exposure promotes renal, vascular, and adipocyte AT1 receptor expression.

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Diet and emission-exposure are associated with adipocyte hypertrophy and weight gain.

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Emission-exposure promotes expression of adipokines and adipose inflammatory factors.

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High-fat diet promotes an obese adipose phenotype, exacerbated by emission-exposure.

Exposure to air pollution from traffic-generated sources is known to contribute to the etiology of inflammatory diseases, including cardiovascular disease (CVD) and obesity; however, the signaling pathways involved are still under investigation. Dysregulation of the renin-angiotensin system (RAS) can contribute to CVD and alter lipid storage and inflammation in adipose tissue. Our previous exposure studies revealed that traffic-generated emissions increase RAS signaling, further exacerbated by a high-fat diet. Thus, we investigated the hypothesis that exposure to engine emissions increases systemic and local adipocyte RAS signaling, promoting the expression of factors involved in CVD and obesity. Male C57BL/6 mice (6–8 wk old) were fed either a high-fat (HF, n = 16) or low-fat (LF, n = 16) diet, beginning 30d prior to exposures, and then exposed via inhalation to either filtered air (FA, controls) or a mixture of diesel engine + gasoline engine vehicle emissions (MVE: 100 μg PM/m³) via whole-body inhalation for 6 h/d, 7 d/wk, 30d. Endpoints were assessed via immunofluorescence and RT-qPCR. MVE-exposure promoted vascular adhesion factors (VCAM-1, ICAM-1) expression, monocyte/macrophage sequestration, and oxidative stress in the vasculature, associated with increased angiotensin II receptor type 1 (AT1) expression. In the kidney, MVE-exposure promoted the expression of renin, AT1, and AT2 receptors. In adipose tissue, both HF-diet and MVE-exposure mediated increased epididymal fat pad weight and adipocyte hypertrophy, associated with increased angiotensinogen and AT1 receptor expression; however, these outcomes were further exacerbated in the MVE + HF group. MVE-exposure also induced inflammation, monocyte chemoattractant protein (MCP)-1, and leptin, while reducing insulin receptor and glucose transporter, GLUT4, expression in adipose tissue. Our results indicate that MVE-exposure promotes systemic and local adipose RAS signaling, associated with increased expression of factors contributing to CVD and obesity, further exacerbated by HF diet consumption.

Traffic-related air pollution is associated with glucose dysregulation, blood pressure, and oxidative stress in children

BACKGROUND

Metabolic syndrome increases the risk of cardiovascular disease in adults. Antecedents likely begin in childhood and whether childhood exposure to air pollution plays a contributory role is not well understood.

OBJECTIVES

To assess whether children's exposure to air pollution is associated with markers of risk for metabolic syndrome and oxidative stress, a hypothesized mediator of air pollution-related health effects.

METHODS

We studied 299 children (ages 6-8) living in the Fresno, CA area. At a study center visit, questionnaire and biomarker data were collected. Outcomes included hemoglobin A1c (HbA1c), urinary 8-isoprostane, systolic blood pressure (SBP), and BMI. Individual-level exposure estimates for a set of four pollutants that are constituents of traffic-related air pollution (TRAP) - the sum of 4-, 5-, and 6-ring polycyclic aromatic hydrocarbon compounds (PAH456), NO₂, elemental carbon, and fine particulate matter (PM_2.5) - were modeled at the primary residential location for 1-day lag, and 1-week, 1-month, 3-month, 6-month, and 1-year averages prior to each participant's visit date. Generalized additive models were used to estimate associations between each air pollutant exposure and outcome.

RESULTS

The study population was 53% male, 80% Latinx, 11% Black and largely low-income (6% were White and 3% were Asian/Pacific Islander). HbA1c percentage was associated with longer-term increases in TRAP; for example a 4.42 ng/m³ increase in 6-month average PAH456 was associated with a 0.07% increase (95% CI: 0.01, 0.14) and a 3.62 μg/m³ increase in 6-month average PM_2.5 was associated with a 0.06% increase (95% CI: 0.01, 0.10). The influence of air pollutants on blood pressure was strongest at 3 months; for example, a 6.2 ppb increase in 3-month average NO₂ was associated with a 9.4 mmHg increase in SBP (95% CI: 2.8, 15.9). TRAP concentrations were not significantly associated with anthropometric or adipokine measures. Short-term TRAP exposure averages were significantly associated with creatinine-adjusted urinary 8-isoprostane.

DISCUSSION

Our results suggest that both short- and longer-term estimated individual-level outdoor residential exposures to several traffic-related air pollutants, including ambient PAHs, are associated with biomarkers of risk for metabolic syndrome and oxidative stress in children.

Long-term exposure to ambient air pollution and obesity in school-aged children and adolescents in Jiangsu province of China

Studies have shown that ambient air pollution is associated with obesity in adults, but epidemiological evidence is scarce for children and adolescents. This study sought to examine the association between long-term exposure to ambient air pollution and obesity in a large population of children and adolescents in China. A cross-sectional analysis was performed from a school-based health lifestyles intervention project between September 1, 2019 and November 31, 2019, including 36,456 participants aged 9-17 years in Jiangsu province of China. Exposure to air pollutants (nitrogen dioxide (NO₂), ozone (O₃), particulate matter with aerodynamic diameters ≤10 μm (PM₁₀), and ≤2.5 μm (PM_2.5)) were measured based on the nearest air monitoring station for each selected school. Data on each participant's weight and height was also recorded. Demographic and obesity-related behavioral information was collected using a self-reported questionnaire. We used the multivariate regression model to estimate the effects of three-year (2016-2018) average concentrations and the exceedance concentration days (ECD) of air pollutants on obesity after adjusting potential confounders. The ECD was defined as daily concentration exceeding the Chinese National Ambient Air Quality Standard and World Health Organization Ambient Air Quality Guidelines. We observed that higher concentrations of PM_2.5, NO₂, and O₃ were associated with elevated likelihood of obesity. For each 10 μg/m³ increment in concentration, odds ratio of obesity was 1.185 (95% confidence interval (CI): 1.054, 1.333) for PM_2.5, 1.127 (95%CI: 1.042, 1.219) for NO₂, and 1.041 (95%CI: 1.001, 1.082) for O₃, respectively. A significant association between the ECD and obesity was also found for PM_2.5 and O₃. Effects of air pollutants on obesity were stronger in males, low economic level regions, and age subgroups of 9-11 and 15-17 years. Our findings suggest that long-term exposures to PM_2.5, NO₂, and O₃ were associated with higher prevalence of obesity in children and adolescents. Continuous efforts to reduce air pollution level could help ease the increasing prevalence of obesity within a region.

Low socioeconomic status aggravated associations of exposure to mixture of air pollutants with obesity in rural Chinese adults: A cross-sectional study

OBJECTIVES

Socio-economic status (SES) and air pollutants are thought to play an important role in human obesity. The evidence of interactive effect between SES and long-term exposure to mixture of air pollutants on obesity is limited, thus, this study is aimed to investigate their interactive effects on obesity among a rural Chinese population.

METHODS

A total of 38,817 individuals were selected from the Henan Rural Cohort Study. Structural equation modeling (SEM) was applied to construct the latent variables of low SES (educational level, marital status, family yearly income, and number of family members), air pollution (particulate matter with aerodynamics diameters ≤ 1.0 μm, ≤ 2.5 μm or ≤ 10 μm, and nitrogen dioxide) and obesity (body mass index, waist circumference, waist-to-hip ratio, waist-to-height ratio, body fat percentage and visceral fat index). Generalized linear regression models were used to assess associations between the constructed latent variables. Interaction plots were applied to describe interactive effect of air pollution and low SES on obesity and biological interaction indicators (the relative excess risk due to interaction (RERI), attributable proportion due to interaction (AP) and synergy index (S)) were also calculated.

RESULTS

Increased latent variables of low SES and mixture of air pollution were associated with a higher odds of latent variable of obesity (odds ratios (OR) (95% confidence interval (CI)) were 1.055 (1.049, 1.060) and 1.050 (1.045, 1.055)). The association of the mixture of air pollutants on obesity was aggravated by increased values of the latent variable of low SES (P < 0.001). Furthermore, the values of RERI, AP and S were 0.073 (0.051, 0.094), 0.057 (0.040, 0.073) and 1.340 (1.214, 1.479), respectively, indicating an additive effect of estimated latent variable of low SES and air pollution on obesity.

CONCLUSIONS

These findings suggested that low SES aggravated the negative effect of mixture of air pollutants on obesity, implying that individuals with low SES may be more susceptible to exposure to high levels of mixture of air pollutants related to increased risk of prevalent obesity.

Exposure to PM2.5 and Obesity Prevalence in the Greater Mexico City Area

Exposure to PM2.5 has been associated with the prevalence of obesity. In the Greater Mexico City Area (GMCA), both are ranked among the highest in the world. Our aim was to analyze this association in children, adolescents, and adults in the GMCA. We used data from the 2006 and 2012 Mexican National Surveys of Health and Nutrition (ENSANUT). Participants' past-year exposure to ambient PM2.5 was assessed using land use terms and satellite-derived aerosol optical depth estimates; weight and height were measured. We used survey-adjusted logistic regression models to estimate the odds ratios (ORs) of obesity (vs. normal-overweight) for every 10 µg/m3 increase in annual PM2.5 exposure for children, adolescents, and adults. Using a meta-analysis approach, we estimated the overall odds of obesity. We analyzed data representing 19.3 million and 20.9 million GMCA individuals from ENSANUT 2006 and 2012, respectively. The overall pooled estimate between PM2.5 exposure and obesity was OR = 1.96 (95% CI: 1.21, 3.18). For adolescents, a 10 µg/m3 increase in PM2.5 was associated with an OR of 3.53 (95% CI: 1.45, 8.58) and 3.79 (95% CI: 1.40, 10.24) in 2006 and 2012, respectively. More studies such as this are recommended in Latin American cities with similar air pollution and obesity conditions.

Associations between the built environment and obesity: an umbrella review

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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