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

The association between air pollution and obesity: an umbrella review of meta-analyses and systematic reviews

The objective of this umbrella review was to investigate comprehensive and synthesized evidence of the association between ambient air pollution and obesity based on the current systematic reviews and meta-analyses. Related studies from databases including PubMed, EMBASE, Web of Science, and the Cochrane Library, published before July 16, 2023, were considered in the analysis. All selected systematic reviews and meta-analyses were included in accordance with PRISMA guidelines. The risk of bias and the methodological quality were evaluated using the AMSTAR 2 tool. The protocol for this umbrella review was documented in PROSPERO with the registration number: CRD42023450191. This umbrella review identified 7 studies, including 5 meta-analyses and 2 systematic reviews, to assess the impacts of air pollutants on obesity. Commonly examined air pollutants included PM1, PM2.5, PM10, NO2, SO2, O3. Most of the included studies presented that air pollution exposure was positively associated with the increased risk of obesity. The impact of air pollution on obesity varied by different ambient air pollutants. This study provided compelling evidence that exposure to air pollution had a positive association with the risk of obesity. These findings further indicate the importance of strengthening air pollution prevention and control. Future studies should elucidate the possible mechanisms and pathways linking air pollution to obesity.

Sex-specific associations of environmental exposures with prevalent diabetes and obesity - Results from the KORA Fit study

Promising evidence suggests a link between environmental factors, particularly air pollution, and diabetes and obesity. However, it is still unclear whether men and women are equally susceptible to environmental exposures. Therefore, we aimed to assess sex-specific long-term effects of environmental exposures on metabolic diseases. We analyzed cross-sectional data from 3,034 participants (53.7% female, aged 53-74 years) from the KORA Fit study (2018/19), a German population-based cohort. Environmental exposures, including annual averages of air pollutants [nitrogen oxides (NO2, NOx), ozone, particulate matter of different diameters (PM10, PMcoarse, PM2.5), PM2.5abs, particle number concentration], air temperature and surrounding greenness, were assessed at participants' residences. We evaluated sex-specific associations of environmental exposures with prevalent diabetes, obesity, body-mass-index (BMI) and waist circumference using logistic or linear regression models with an interaction term for sex, adjusted for age, lifestyle factors and education. Further effect modification, in particular by urbanization, was assessed in sex-stratified analyses. Higher annual averages of air pollution, air temperature and greenness at residence were associated with diabetes prevalence in men (NO2: Odds Ratio (OR) per interquartile range increase in exposure: 1.49 [95% confidence interval (CI): 1.13, 1.95], air temperature: OR: 1.48 [95%-CI: 1.15, 1.90]; greenness: OR: 0.78 [95%-CI: 0.59, 1.01]) but not in women. Conversely, higher levels of air pollution, temperature and lack of greenness were associated with lower obesity prevalence and BMI in women. After including an interaction term for urbanization, only higher greenness was associated with higher BMI in rural women, whereas higher air pollution was associated with higher BMI in urban men. To conclude, we observed sex-specific associations of environmental exposures with metabolic diseases. An additional interaction between environmental exposures and urbanization on obesity suggests a higher susceptibility to air pollution among urban men, and higher susceptibility to greenness among rural women, which needs corroboration in future studies.

Transition of cooking fuels and obesity risk in Chinese adults

BACKGROUND

Since 1990 s, China has witnessed a widespread transition to clean cooking fuels, presenting an opportunity to investigate whether household fuel transition could mitigate obesity risk and reconcile inconsistencies in the literature regarding the association between cooking fuels and obesity.

METHODS

The China Health and Nutrition Survey (CHNS) is a prospective cohort study covering 12 provinces of China (1989-2015). Participants were classified into persistent cleaner fuel users, fuel transitioners, and persistent polluting fuel users according to self-reported primary cooking fuels. Obesity and central obesity were defined as BMI ≥ 28.0 kg/m2 and waist circumference ≥ 90 cm in men and ≥ 85 cm in women according to Chinese criteria.

FINDINGS

Among 13,032 participants, 3657 (28.06 %) were persistent cleaner fuel users; 5264 (40.39 %) transitioned from using polluting fuels to cleaner fuels after the baseline survey; and 4111 (31.55 %) were persistent polluting fuel users. During the period of follow-up of 9.0 ± 6.8 years, 1248 (9.58 %) participants were classified into the obesity category, and 4703 (36.09 %) into the central obesity category. Persistent polluting fuel users had a significantly higher risk of developing obesity (hazard ratio [HR]: 1.45, 95 %CI: 1.22-1.72) and central obesity (HR: 1.32, 95 %CI: 1.21-1.44), compared to persistent cleaner fuel users. Persistent polluting fuel use was positively associated with developing obesity in women (HR: 1.64, 95 %CI: 1.30-2.06), but not in men. Subgroup analyses showed higher HR of persistent polluting fuel use among individuals aged 18-44 years (HR: 2.04, 95 %CI: 1.62-2.56). In contrast, the transitioners did not exhibit a significantly different risk of developing obesity (HR: 0.94, 95 %CI: 0.80-1.10) compared to persistent cleaner fuel users, which was consistent across different sex, age and urbanicity. Similar trends were observed for developing central obesity.

INTERPRETATION

Persistent polluting fuel use increased obesity risk while the obesity risk of the transition to cleaner fuels was similar to persistent use of cleaner fuels. The finding underscores the significance of advocating for the adoption of cleaner fuels as a strategy to mitigate the disease burden associated with obesity.

Association between short-term exposure to ambient air pollutants and the risk of hospital visits for acute upper respiratory tract infections among adults: a time-series study in Ningbo, China

OBJECTIVES

Acute upper respiratory tract infections (AURTIs) are prevalent in the general population. However, studies on the association of short-term exposure to air pollution with the risk of hospital visits for AURTIs in adults are limited. This study aimed to explore the short-term exposure to air pollutants among Chinese adults living in Ningbo.

METHODS

Quasi-Poisson time serious regressions with distributed lag non-linear models (DLNM) were applied to explore the association between ambient air pollution and AURTIs cases. Patients ≥ 18 years who visit three hospitals, being representative for urban, urban-rural junction and rural were included in this retrospective study.

RESULTS

In total, 104,441 cases with AURTIs were enrolled in hospital during 2015-2019. The main results showed that particulate matter with an aerodynamic diameter less than 2.5 μm (PM2.5), nitrogen dioxide (NO2) and nitrogen dioxide (SO2), were positively associated to hospital visits for AURTIs, except for nitrogen dioxide (O3), which was not statistically significant. The largest single-lag effect for PM2.5 at lag 8 days (RR = 1.02, 95%CI: 1.08-1.40), for NO2 at lag 13 days (RR = 1.03, 95%CI: 1.00-1.06) and for SO2 at lag 5 days (RR = 1.27, 95%CI: 1.08-1.48), respectively. In the stratified analysis, females, and young adults (18-60 years) were more vulnerable to PM2.5 and SO2 and the effect was greater in rural areas and urban-rural junction.

CONCLUSIONS

Exposure to ambient air pollution was significantly associated with hospital visits for AURTIs. This study provides epidemiological evidence for policymakers to control better air quality and establish an enhanced system of air pollution alerts.

Long-term exposure to PM2.5 chemical constituents and diabesity: evidence from a multi-center cohort study in China

Background

Long-term exposure to PM2.5 is known to increase the risks for diabetes and obesity, but its effects on their coexistence, termed diabesity, remain uncertain. This study aimed to investigate the associations of long-term exposure to PM2.5 and its chemical constituents with the risks for diabesity, diabetes, and obesity.

Methods

This cross-sectional study used the baseline data of a multi-center cohort, consisting of three provincially representative cohorts comprising a total of 134,403 participants from the eastern (Fujian Province), central (Hubei Province), and western (Yunnan Province) regions of China. Obesity and diabetes, and diabesity were identified by a body mass index (BMI) ≥28 kg/m2 and fasting plasma glucose (FPG) ≥126 mg/dL. The average concentrations of PM2.5 and five chemical constituents (NO3 -, SO4 2-, NH4 +, organic matter, and black carbon) over participants' residence during the past three years were estimated using machine learning models. Logistic regression models with double robust estimators, Bayesian kernel machine regression, and weighted quantile sum regression were employed to estimate independent and joint effects of PM2.5 chemical constituents on the risks for diabesity, diabetes, and obesity, as well as the differences from the effects on obesity. Stratified analyses were performed to examine effect modification of sociodemographic and lifestyle factors.

Findings

There were 129,244 participants with a mean age of 54.1 ± 13.8 years included in the study. Each interquartile range increase in PM2.5 concentration (8.53 μg/m3) was associated with an increased risk for diabesity (OR = 1.23 [1.17, 1.30]), diabetes only (OR = 1.16 [1.13, 1.19]), and obesity only (OR = 1.03 [1.00, 1.05]). Long-term exposure to each PM2.5 chemical constituent was associated with an increased risk for diabesity, where organic matter exposure, with maximum weight (48%), was associated with a higher risk for diabesity (OR = 1.21 [1.16, 1.27]). Among those with obesity, black carbon contributed most (68%) to the joint effect of PM2.5 chemical constituents on diabesity (OR = 1.16 [1.11, 1.22]). Physical activity reduced adverse effects of PM2.5 on diabesity. Also, additive rather than multiplicative effects of obesity on the PM2.5-diabetes association were observed.

Interpretation

Long-term exposure to PM2.5 and its chemical constituents was associated with an increased risk for diabesity, stronger than associations for diabetes and obesity alone. The main constituents associated with diabesity and obesity were black carbon and organic matter.

Funding

National Natural Science Foundation of China (42271433, 723B2017), National Key R&D Program of China (2023YFC3604702), Fundamental Research Funds for the Central Universities (2042023kfyq04, 2042024kf1024), the Science and Technology Major Project of Tibetan Autonomous Region of China (XZ202201ZD0001G), Science and technology project of Tibet Autonomous Region（XZ202303ZY0007G), Key R&D Project of Sichuan Province (2023YFS0251), Renmin Hospital of Wuhan University (JCRCYG-2022-003), Jiangxi Provincial 03 Special Foundation and 5G Program (20224ABC03A05), Wuhan University Specific Fund for Major School-level Internationalization Initiatives (WHU-GJZDZX-PT07).

The Association between Short-Term Exposure to PM1 and Daily Hospital Admission and Related Expenditures in Beijing

Ambient particulate matter (PM) pollution is a leading environmental health threat worldwide. PM with an aerodynamic diameter ≤ 1.0 μm, also known as PM1, has been implicated in the morbidity and mortality of several cardiorespiratory and cerebrovascular diseases. However, previous studies have mostly focused on analyzing fine PM (PM2.5) associated with disease metrics, such as emergency department visits and mortality, rather than ultrafine PM, including PM1. This study aimed to evaluate the association between short-term PM1 exposure and hospital admissions (HAs) for all-cause diseases, chronic obstructive pulmonary disease (COPD), and respiratory infections (RIs), as well as the associated expenditures, using Beijing as a case study. Here, based on air pollution and hospital admission data in Beijing from 2015 to 2017, we performed a time-series analysis and meta-analysis. It was found that a 10 μg/m3 increase in the PM1 concentration significantly increased all-cause disease HAs by 0.07% (95% Confidence Interval (CI): [0, 0.14%]) in Beijing between 2015 and 2017, while the COPD and RI-related HAs were not significantly associated with short-term PM1 exposure. Meanwhile, we estimated the attributable number of HAs and hospital expenditures related to all-cause diseases. This study revealed that an average of 6644 (95% CI: [351, 12,917]) cases of HAs were attributable to ambient PM1, which was estimated to be associated with a 106 million CNY increase in hospital expenditure annually (95% CI: [5.6, 207]), accounting for 0.32% (95% CI: [0.02, 0.62%]) of the annual total expenses. The findings reported here highlight the underlying impact of ambient PM pollution on health risks and economic burden to society and indicate the need for further policy actions on public health.

Urban-rural differences in the association between long-term exposure to ambient particulate matter (PM) and malnutrition status among children under five years old: A cross-sectional study in China

Background

The evidence regarding the relationship between postnatal exposure of air pollution and child malnutrition indicators, as well as the corresponding urban-rural disparities, is limited, especially in low-pollution area of low- and middle-income countries (LMICs). Therefore, our aim was to contrast the effect estimates of varying ambient particulate matter (PM) on malnutrition indicators between urban and rural areas in Tibet, China.

Methods

Six malnutrition indicators were evaluated in this study, namely, Z-scores of height for age (HFA), Z-scores of weight for age (WFA), Z-scores of weight for height (WFH), stunting, underweight, and wasting. Exposure to particles with an aerodynamic diameter ≤2.5 micron (μm) (PM2.5), particles with an aerodynamic diameter ≤10 μm (PM10) and particles with an aerodynamic diameter between 2.5 and 10 μm (PMc) was estimated using satellite-based random forest models. Linear regression and logistic regression models were used to assess the associations between PM and the above malnutrition indicators. Furthermore, the effect estimates of different PM were contrasted between urban and rural areas.

Results

A total of 2511 children under five years old were included in this study. We found long-term exposure to PM2.5, PMc, and PM10 was associated with an increased risk of stunting and a decreased risk of underweight. Of these air pollutants, PMc had the strongest association for Z-scores of HFA and stunting, while PM2.5 had the strongest association for underweight. The results showed that the odds ratio (OR) for stunting were 1.36 (95% confidence interval (CI) = 1.06 to 1.75) per interquartile range (IQR) microgrammes per cubic metre (μg/m3) increase in PM2.5, 1.80 (95% CI = 1.30 to 2.50) per IQR μg/m3 increase in PMc and 1.55 (95% CI = 1.17 to 2.05) per IQR μg/m3 increase in PM10. The concentrations of PM were higher in urban areas, and the effects of PM on malnutrition indicators among urban children were higher than those of rural children.

Conclusions

Our results suggested that PM exposure might be an important trigger of child malnutrition. Further prospective researches are needed to provide important scientific literature for understanding child malnutrition risk concerning postnatal exposure of air pollutants and formulating synthetically social and environmental policies for malnutrition prevention.

The association between chemical constituents of ambient fine particulate matter and obesity in adults: A large population-based cohort study

OBJECTIVES

Current evidence demonstrated that ambient fine particulate matter with an aerodynamic diameter ≤2.5 μm (PM2.5) and its constituents may be obesogenic in children, but evidence from adults is lacking. Our aim was to characterize the association between PM2.5 and its constituents and obesity in adults.

METHODS

We included 68,914 participants from the China Multi-Ethnic Cohort (CMEC) baseline survey. Three-year average concentrations of PM2.5 and its constituents were evaluated by linking pollutant estimates to the geocoded residential addresses. Obesity was defined as body mass index (BMI) ≥ 28 kg/m2. Logistic regression was used to examine the relationship between PM2.5 and its constituents and obesity. We performed weighed quantile sum (WQS) regression to get the overall effect of PM2.5 and its constituents and the relative contribution of each constituent.

RESULTS

Per-SD increase in PM2.5 (odds ratio [OR] = 1.43, 95% confidence interval [CI]: 1.37-1.49), black carbon (BC) (1.42, 1.36-1.48), ammonium (1.43, 1.37-1.49), nitrate (1.44, 1.38-1.50), organic matter (OM) (1.45, 1.39-1.51), sulfate (1.42, 1.35-1.48), and soil particles (SOIL) (1.31, 1.27-1.36) were positively associated with obesity, and SS (0.60, 0.55-0.65) was negatively associated with obesity. The overall effect (OR = 1.34, 95% CI: 1.29-1.41) of the PM2.5 and its constituents was positively associated with obesity, and ammonium made the most contribution to this relationship. Participants who were older, female, never smoked, lived in urban areas, had lower income or higher levels of physical activity were more significantly adversely affected by PM2.5, BC, ammonium, nitrate, OM, sulfate and SOIL compared to other individuals.

CONCLUSION

Our study revealed that PM2.5 constituents except SS were positively associated with obesity, and ammonium played the most important role. These findings provided new evidence for public health interventions, especially the precise prevention and control of obesity.

Individual and joint associations of long-term exposure to air pollutants and cardiopulmonary mortality: a 22-year cohort study in Northern China

Background

Evidence on the associations between long-term exposure to multiple air pollutants and cardiopulmonary mortality is limited, especially for developing regions with higher pollutant levels. We aimed to characterise the individual and joint (multi-pollutant) associations of long-term exposure to air pollutants with cardiopulmonary mortality, and to identify air pollutant that primarily contributes to the mortality risk.

Methods

We followed 37,442 participants with a mean age of 43.5 years in four cities in northern China (Tianjin, Shenyang, Taiyuan, and Rizhao) from January 1998 to December 2019. Annual particulate matter (PM) with diameters ≤2.5 μm (PM2.5), ≤10 μm (PM10), sulfur dioxide (SO2) and nitrogen dioxide (NO2) were estimated using daily average values from satellite-derived machine learning models and monitoring stations. Time-varying Cox proportional hazards model was used to evaluate the individual association between air pollutants and mortality from non-accidental causes, cardiovascular diseases (CVDs), non-malignant respiratory diseases (RDs) and lung cancer, accounting for demographic and socioeconomic factors. Effect modifications by age, sex, income and education level were also examined. Quantile-based g-Computation integrated with time-to-event data was additionally applied to evaluate the co-effects and the relative weight of contributions for air pollutants.

Findings

During 785,807 person-years of follow-up, 5812 (15.5%) died from non-accidental causes, among which 2932 (7.8%) were from all CVDs, 479 (1.3%) from non-malignant RDs, and 552 (1.4%) from lung cancer. Long-term exposure to PM10 (mean [baseline]: 136.5 μg/m3), PM2.5 (mean [baseline]: 70.2 μg/m3), SO2 (mean [baseline]: 113.0 μg/m3) and NO2 (mean [baseline]: 39.2 μg/m3) were adversely and consistently associated with all mortality outcomes. A 10 μg/m3 increase in PM2.5 was associated with higher mortality from non-accidental causes (hazard ratio 1.20; 95% confidence interval 1.17-1.23), CVDs (1.23; 1.19-1.28), non-malignant RDs (1.37; 1.25-1.49) and lung cancer (1.14; 1.05-1.23). A monotonically increasing curve with linear or supra-linear shape with no evidence of a threshold was observed for the exposure-response relationship of mortality with individual or joint exposure to air pollutants. PM2.5 consistently contributed most to the elevated mortality risks related to air pollutant mixture, followed by SO2 or PM10.

Interpretation

There was a strong and positive association of long-term individual and joint exposure to PM10, PM2.5, SO2, and NO2 with mortalities from non-accidental causes, CVDs, non-malignant RDs and lung cancer in high-exposure settings, with PM2.5 potentially being the main contributor. The shapes of associations were consistent with a linear or supra-linear exposure-response relationship, with no lower threshold observed within the range of concentrations in this study.

Funding

National Key Research and Development Program of China, the China Scholarship Council, the National Natural Science Foundation of China, Natural Science Foundation of Guangdong Province.

Fine particulate matter (PM2.5)-induced pulmonary oxidative stress contributes to increases in glucose intolerance and insulin resistance in a mouse model of circadian dyssynchrony

Results of human and animal studies independently suggest that either ambient fine particulate matter (PM2.5) air pollution exposure or a disturbed circadian rhythm (circadian dyssynchrony) are important contributing factors to the rapidly evolving type-2-diabetes (T2D) epidemic. The objective of this study is to investigate whether circadian dyssynchrony increases the susceptibility to PM2.5 and how PM2.5 affects metabolic health in circadian dyssynchrony. We examined systemic and organ-specific changes in glucose homeostasis and insulin sensitivity in mice maintained on a regular (12/12 h light/dark) or disrupted (18/6 h light/dark, light-induced circadian dyssynchrony, LICD) light cycle exposed to air or concentrated PM2.5 (CAP, 6 h/day, 30 days). Exposures during Zeitgeber ZT3-9 or ZT11-17 (Zeitgeber in circadian time, ZT0 = begin of light cycle) tested for time-of-day PM2.5 sensitivity (chronotoxicity). Mice transgenic for lung-specific overexpression of extracellular superoxide dismutase (ecSOD-Tg) were used to assess the contribution of CAP-induced pulmonary oxidative stress. Both, CAP exposure from ZT3-9 or ZT11-17, decreased glucose tolerance and insulin sensitivity in male mice with LICD, but not in female mice or in mice kept on a regular light cycle. Although changes in glucose homeostasis in CAP-exposed male mice with LICD were not associated with obesity, they were accompanied by white adipose tissue (WAT) inflammation, impaired insulin signaling in skeletal muscle and liver, and systemic and pulmonary oxidative stress. Preventing CAP-induced oxidative stress in the lungs mitigated the CAP-induced decrease in glucose tolerance and insulin sensitivity in LICD. Our results demonstrate that circadian dyssynchrony is a novel susceptibility state for PM2.5 and suggest that PM2.5 by inducing pulmonary oxidative stress increases glucose intolerance and insulin resistance in circadian dyssynchrony.

Association Between Weight Status and Rate of Cognitive Decline: China Health and Nutrition Survey 1997-2018

BACKGROUND

There is a close relationship between weight status and cognitive impairment in older adults. This study examined the association between weight status and the trajectory of cognitive decline over time in a population-based cohort of older adults in China.

METHODS

We used data from adults aged ≥55 years participating in the China health and nutrition survey (1997-2018). Underweight (body mass index [BMI] ≤ 18.5 kg/m2), normal weight (18.5-23 kg/m2), overweight (23-27.5 kg/m2), and obesity (BMI ≥ 27.5 kg/m2) were defined using the World Health Organization Asian cutpoints. Global cognition was estimated every 2-4 years through a face-to-face interview using a modified telephone interview for cognitive status (scores 0-27). The association between BMI and the rate of global cognitive decline, using a restricted cubic spline for age and age category, was examined with linear mixed-effects models accounting for correlation within communities and individuals.

RESULTS

We included 5 992 adults (53% female participants, mean age of 62 at baseline). We found differences in the adjusted rate of global cognitive decline by weight status (p = .01 in the cubic spline model). Models were adjusted for sex, marital status, current employment status, income, region, urbanization, education status, birth cohort, leisure activity, smoking status, and self-reported diagnosis of hypertension, diabetes, or Myocardial Infarction (MI)/stroke. In addition, significant declines by age in global cognitive function were found for all weight status categories except individuals with obesity.

CONCLUSIONS

In a cohort of adults in China, cognitive decline trajectory differed by weight status. A slower rate of change was observed in participants classified as having obesity.

The effects of green space and physical activity on muscle strength: a national cross-sectional survey with 128,759 Chinese adults

Background

Muscle strength is closely related to chronic noncommunicable diseases; specifically, a decline in handgrip strength (HS) is predominant globally. Exposure to green space-built environment components used for health intervention-reportedly decreases the risk of certain diseases and all-cause mortality. However, evidence in this area is limited.

Objective

We aimed to explore the association between green space exposure and muscle strength and ascertain the combined effect of physical activity and green space exposure on muscle strength.

Method

Data from 128,759 participants (aged 20-79  years) were obtained using a complex stratified multistage probability cluster sampling design. The green space was assessed as normalized difference vegetation index (NDVI) data for a 500-m buffer zone based on the geolocation information of sampling sites. We used a questionnaire to investigate transportation, occupation, physical activity, leisure-time exercise behaviors, and sedentary time within a usual week of the preceding year. The outcome was low relative HS, defined as HS-to-body weight ratio, and the percentage of men and women with relative HS in the lower third. We defined adequate physical activity as 150  min of moderate-intensity or 75  min of vigorous physical activity per week and calculated the weighted proportion of participants with insufficient physical activity. Categorical variables of NDVI and physical activity were used as exposure variables and their interrelationship was evaluated in a generalized linear mixed model (GLMM) to estimate the odds ratios (ORs) and 95% confidence intervals (95% CI). We measured interaction on an additive or multiplicative scale using a GLMM to test the interaction between green space exposure and physical activity. All analyses were performed for the total sample and subgroups (urban and rural).

Result

The high NDVI group had a lower risk of low relative HS than the low NDVI group (OR [95% CI]: 0.92 [0.88-0.95]). The sufficient physical activity group had a lower risk of low relative HS than the insufficient physical activity group (OR [95% CI]: 0.85 [0.81-0.88]). There was an interactive effect on the additive scale (relative excess risk owing to interaction: 0.29, 95% CI 0.22-0.36, p < 0.001) between green space exposure and physical activity.

Conclusion

High NDVI and adequate physical activity were protective factors against low relative HS in Chinese adults. Increasing green space exposure and physical activity together may have a greater potentiating effect on muscle strength improvement than these two protective factors individually. Green spaces should be incorporated into city design or built environments.

Exposure to air pollution and gains in body weight and waist circumference among middle-aged and older adults

INTRODUCTION

Emerging research suggested a nexus between air pollution exposure and risks of overweight and obesity, while existing longitudinal evidence was extensively sparse, particularly in densely populated regions. This study aimed to quantify concentration-response associations of changes in weight and waist circumference (WC) related to air pollution in Chinese adults.

METHODS

We conceived a nationally representative longitudinal study from 2011 to 2015, by collecting 34,854 observations from 13,757 middle-aged and older adults in 28 provincial regions of China. Participants' height, weight and WC were measured by interviewers using standardized devices. Concentrations of major air pollutants including fine particulate matter (PM_2.5), nitrogen dioxide (NO₂) and ozone (O₃) predicted by well-validated spatiotemporal models were assigned to participants according to their residential cities. Possible exposure biases were checked through 1000 random simulated exposure at individual level, using a Monte Carlo simulation approach. Linear mixed-effects models were applied to estimate the relationships of air pollution with weight and WC changes, and restricted cubic spline functions were adopted to smooth concentration-response (C-R) curves.

RESULTS

Each 10-μg/m³ rise in PM_2.5, NO₂ and O₃ was associated with an increase of 0.825 (95% confidence interval: 0.740, 0.910), 0.921 (0.811, 1.032) and 1.379 (1.141, 1.616) kg in weight, respectively, corresponding to WC gains of 0.688 (0.592, 0.784), 1.189 (1.040, 1.337) and 0.740 (0.478, 1.002) cm. Non-significant violation for linear C-R relationships was observed with exception of NO₂-weight and PM_2.5/NO₂-WC associations. Sex-stratified analyses revealed elevated vulnerability in women to gain of weight in exposure to PM_2.5 and NO₂. Sensitive analyses largely supported our primary findings via assessing exposure estimates from 1000 random simulations, and performing reanalysis based on non-imputed covariates and non-obese participants, as well as alternative indicators (i.e., body mass index and waist-to-height ratio).

CONCLUSIONS

We found positively robust associations of later-life exposure to air pollutants with gains in weight and WC based on a national sample of Chinese adult men and women. Our findings suggested that mitigation of air pollution may be an efficient intervention to relieve obesity burden.

Long-term exposure to fine particulate matter and site-specific cancer mortality: A difference-in-differences analysis in Jiangsu province, China

BACKGROUND

Accumulating studies have reported that chronic exposure to ambient fine particulate matter (PM_2.5) can lead to adverse effects on lung cancer mortality; however, such chronic effects are less clear for mortality from other site-specific cancers.

OBJECTIVE

To explore the causal effect of long-term PM_2.5 exposure on mortality from all-site and a variety of site-specific cancers in Jiangsu province, China during 2015-2020 using a difference-in-differences analysis.

METHODS

For each of 53 county-based spatial units in Jiangsu province, we calculated annual death counts for all-site cancer and 23 site-specific cancers. Using a validated high-resolution PM_2.5 grid dataset, long-term PM_2.5 exposure of a spatial unit within a given year was evaluated as the average of population-weighted annual concentrations during recent 10 years. Conditional Poisson regression models were employed to evaluate exposure-response associations adjusting for spatial and temporal variables, seasonal temperatures, relative humidity, and gross domestic product (GDP).

RESULTS

During the study period, we identified 947,337 adult cancer deaths in Jiangsu province. Each 1 μg/m³ increment in PM_2.5 exposure was significantly associated with a 2.7% increase in the risk of all-site cancer mortality. PM_2.5-mortality associations were also observed in cancer of lip, oral cavity and pharynx, stomach, colorectum, pancreas, lung, bone and joints, ovary, prostate, and lymphoma (all adjusted P < 0.05), with the relative risks ranging from 1.028 (95% confidence interval [CI]: 1.011, 1.046) for stomach cancer to 1.201 (95% CI: 1.120, 1.308) for bone and joints cancers. Exposure-response curves showed that these associations were close to linearity, though most of them had increasing slopes at high exposure levels. Overall, women and subjects in low GDP regions were more vulnerable to PM_2.5 exposures.

CONCLUSIONS

Long-term exposure to ambient PM_2.5 contributes to a higher risk of mortality from multiple site-specific cancers.

Regional urbanicity levels modify the association between ambient air pollution and prevalence of obesity: A nationwide cross-sectional survey

Ambient air pollution exposure may increase the risk of obesity, but the population susceptibility associated with urbanicity has been insufficiently investigated. Based on a nationwide representative cross-sectional survey on 44,544 adults, high-resolution night light satellite remote sensing products, and multi-source ambient air pollution inversion data, the present study evaluated the associations of fine particulate matter (PM_2.5) and nitrogen dioxide (NO₂) concentrations with the prevalence of obesity and abdominal obesity. We further calculated the associations in regions with different urbanicity levels characterized by both administrative classification of urban/rural regions and night light index (NLI). We found that 10 μg/m³ increments in PM_2.5 at 1-year moving average and in NO₂ at 5-year moving average were associated with increased prevalence of obesity [odds ratios (OR) = 1.16 (1.14, 1.19); 1.12 (1.09, 1.15), respectively] and abdominal obesity [OR = 1.08 (1.07, 1.10); 1.07 (1.05, 1.09), respectively]. People in rural regions experienced stronger adverse effects than those in urban regions. For instance, a 10 μg/m³ increment in PM_2.5 was associated with stronger odds of obesity in rural regions than in urban regions [OR = 1.27 (1.23, 1.31) vs 1.10 (1.05, 1.14), P for interaction <0.001]. In addition, lower NLI values were associated with constantly amplified associations of PM_2.5 and NO₂ with obesity and abdominal obesity (all P for interaction <0.001). In summary, people in less urbanized regions are more susceptible to the adverse effects of ambient air pollution on obesity, suggesting the significance of collaborative planning of urbanization development and air pollution control, especially in less urbanized regions.

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 (PM_2.5), 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 PM_2.5 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 PM_2.5 on being overweight or obese were stronger in men than in women. According to the mediation analysis, PM_2.5 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 PM_2.5 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.

Associations and pathways between residential greenness and metabolic syndromes in Fujian Province

Background

Greenness exposure is beneficial to human health, but its potential mechanisms through which the risk for metabolic syndrome (MetS) could be reduced have been poorly studied. We aimed to estimate the greenness-MetS association in southeast China and investigate the independent and joint mediation effects of physical activity (PA), body mass index (BMI), and air pollutants on the association.

Methods

A cross-sectional study was conducted among the 38,288 adults based on the Fujian Behavior and Disease Surveillance (FBDS), established in 2018. MetS was defined as the presence of three or more of the five components: abdominal obesity, elevated triglyceride, reduced high-density lipoprotein cholesterol (HDL-C), high blood pressure, and elevated fasting glucose. The residential greenness exposure was measured as the 3-year mean values of the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) within the 250, 500, and 1,000 meters (m) buffer zones around the residential address of each participant. Logistic regression models were used to estimate the greenness-MetS association. The causal mediation analysis was used to estimate the independent and joint mediation effects of PA, BMI, particulate matter with an aerodynamic diameter of 2.5 μm (PM_2.5), particulate matter with an aerodynamic diameter ≤ 10 μm (PM₁₀), nitrogen dioxide (NO₂), and sulfur dioxide (SO₂).

Results

Each interquartile range (IQR) increase in greenness was associated with a decrease of 13% (OR = 0.87 [95%CI: 0.83, 0.92] for NDVI_500m and OR = 0.87 [95%CI: 0.82, 0.91] for EVI_500m) in MetS risk after adjusting for covariates. This association was stronger in those aged < 60 years (e.g., OR = 0.86 [95%CI: 0.81, 0.92] for NDVI_500m), males (e.g., OR = 0.73 [95%CI: 0.67, 0.80] for NDVI_500m), having an educational level of primary school or above (OR = 0.81 [95%CI: 0.74, 0.89] for NDVI_500m), married/cohabitation (OR = 0.86 [95%CI: 0.81, 0.91] for NDVI_500m), businessman (OR = 0.82 [95%CI: 0.68, 0.99] for NDVI_500m), other laborers (OR = 0.77 [95%CI: 0.68, 0.88] for NDVI_500m), and non-smokers (OR = 0.77 [95%CI: 0.70, 0.85] for NDVI_500m). The joint effect of all six mediators mediated about 48.1% and 44.6% of the total effect of NDVI_500m and EVI_500m on the MetS risk, respectively. Among them, BMI showed the strongest independent mediation effect (25.0% for NDVI_500m), followed by NO₂ and PM₁₀.

Conclusion

Exposure to residential greenness was associated with a decreased risk for MetS. PA, BMI, and the four air pollutants jointly interpreted nearly half of the mediation effects on the greenness-MetS association.

High-altitude exposure decreases bone mineral density and its relationship with gut microbiota: Results from the China multi-ethnic cohort (CMEC) study

BACKGROUND

Geographic altitude is a potent environmental factor for human microbiota and bone mineral density. However, little evidence exists in population-based studies with altitude diversity ranges across more than 3000 m. This study assessed the associations between a wide range of altitudes and bone mineral density, as well as the potential mediating role of microbiota in this relationship.

METHODS

A total of 99,556 participants from the China Multi-Ethnic Cohort (CMEC) study were enrolled. The altitude of each participant was extracted from global Shuttle Radar Topography Mission (SRTM) 4 data. Bone mineral density was measured by calcaneus quantitative ultrasound index (QUI). Stool samples were collected for 16S rRNA gene sequencing (n = 1384). The metabolites of gut microbiota, seven kinds of short-chain fatty acids (SCFAs), were detected by gas chromatography-mass spectrometry (GC-MS, n = 128). After screening, 73,974 participants were selected for the "altitude-QUI" analysis and they were placed into the low-altitude (LA) and high-altitude (HA) groups. Additionally, a subgroup (n = 1384) was further selected for the "altitude-microbiota-QUI" analysis. Multivariate linear regression models and mediation analyses were conducted among participants.

RESULTS

A significant negative association between high-altitude and QUI was obtained (mean difference = -0.373 standard deviation [SD], 95% confidence interval [CI]: -0.389, -0.358, n = 73,974). The same negative association was also observed in the population with microbiota data (mean difference = -0.185 SD, 95%CI: -0.360, -0.010, n = 1384), and a significant mediating effect of Catenibacteriumon on the association between altitude and QUI (proportion mediated = 25.2%, P = 0.038) was also noticed. Additionally, the acetic acid, butyric acid, and total amount of seven SCFAs of the low-altitude group were significantly higher than that of the high-altitude group (P < 0.05).

CONCLUSION

High-altitude exposure may decrease bone mineral density in adults, thus increasing the risk of osteoporosis. The modulation of gut microbiota may be a potential strategy for alleviating the decrease of bone mineral density.

Associations and pathways between residential greenness and hyperuricemia among adults in rural and urban China

BACKGROUND

Residential greenness may decrease the risk for hyperuricemia in rural areas, but the urban-rural disparities in this association and underlying pathways have not been studied.

OBJECTIVES

To investigate the associations and potential pathways between residential greenness and hyperuricemia in urban and rural areas.

METHODS

The baseline survey of the China Multi-Ethnic Cohort (CMEC) was used. Hyperuricemia was defined as serum uric acid (SUA) > 417 μmol/L for men and >357 μmol/L for women. The satellite-based normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) were used to capture residential greenness. A propensity score inverse-probability weighting method was used to assess urban-rural differences in the associations between residential greenness and hyperuricemia, with possible mediation effects of physical activity (PA), body mass index (BMI), PM_2.5, and NO₂ examined by causal mediation analyses.

RESULTS

A total of 72,372 participants were included. The increases in the EVI_500m and NDVI_500m residential greenness were associated with a decreased risk for hyperuricemia and the SUA level in both urban and rural areas. For example, each 0.1-unit increase in EVI_500m was associated with a decreased hyperuricemia risk of 7% (OR = 0.93 [0.91, 0.96]) and a decreased SUA level of -1.77 μmol/L [-2.60, -0.93], respectively; such associations were stronger in urban areas for both the risk for hyperuricemia (OR = 0.84 [0.83, 0.86]) and SUA level (-7.18 μmol/L [-7.91, -6.46]). The subgroup analysis showed that the greenness-hyperuricemia/SUA association varied by age, sex, and annual household income. The percentage of the joint mediation effect of PA, BMI, PM_2.5, and NO₂ on the association between EVI_500m and the risk for hyperuricemia was higher in urban (34.92%) than rural areas (15.40%). BMI, PM_2.5, and PA showed significantly independently mediation effects for the greenness-hyperuricemia association in both rural and urban areas.

CONCLUSIONS

Exposure to residential greenness was associated with a decreased risk for hyperuricemia, partially through the pathways of PA, BMI, PM_2.5, and NO₂, which varied in urban and rural areas.

Long-term exposure to air pollution might decrease bone mineral density T-score and increase the prevalence of osteoporosis in Hubei province: evidence from China Osteoporosis Prevalence Study

We hypothesized that air pollution could cause oxidative damage and inflammation in the human body, which was linked to bone loss. Our result showed that long-term exposure to air pollution might decrease bone mineral density (BMD) T-score and increase the prevalence of osteoporosis in Hubei province.

INTRODUCTION

Osteoporosis is becoming an increasingly serious public health problem with the advent of global aging. Long-term exposure to air pollution has been linked to multitudinous adverse health outcomes, but evidence is still relatively limited and inconsistent for BMD T-score and osteoporosis. This study aimed at exploring the associations between long-term exposure to air pollution and BMD T-score and osteoporosis.

METHODS

The Hubei part of the China Osteoporosis Prevalence Study was extracted. Data on air pollutants were collected by the national air quality real-time release platform of China Environmental Monitoring Station. Linear mixed models and multilevel logistic regression analyses were performed to assess the associations between air pollution and BMD T-score and osteoporosis, respectively. Subgroup analyses were conducted to identify vulnerable populations.

RESULTS

A total of 1845 participants were included in this cross-section study. Per 10 ug/m³ increase in PM_2.5 and SO₂ were associated with 0.20 (95% CI: 0.04, 0.36) and 0.31 (95% CI: 0.11, 0.51) decrease in BMD T-score of the neck of femur, respectively. Per 10 ug/m³ increase in CO was linked with 0.03 (95% CI: 0.02, 0.05) decrease in BMD T-score of the total hip. Per 1 ug/m³ increase in PM_2.5 was associated with 5% increase in the prevalence of osteoporosis in all participants. In general, the higher concentrations of PM_2.5 with the more adverse effect on osteoporosis (P for trend = 0.01). The impact of PM_2.5 on osteoporosis in males was higher than that in females [1.29, 95% CI (1.11, 1.50) vs 1.01, 95% CI (0.95, 1.07)]. Per 1 ug/m³ increase in PM₁₀ corresponded with 4% elevation in the risks of osteoporosis in rural population. The ORs (95% CI) for the association of osteoporosis and NO₂ in ever/current smoking and drinking population were 1.07 (1.01, 1.13) and 1.05 (1.00, 1.09), respectively. SO₂ had a statistically significant positive effect on people with comorbidity [OR = 1.10, (95% CI: 1.00 to 1.21)], while none in people without comorbidity [OR = 0.96, (95% CI: 0.88 to 1.05)].

CONCLUSION

Our study provided evidence that long-term exposure to PM_2.5 was linked with the decreased BMD T-score and increased risk of osteoporosis among all participants. The adverse impacts of PM_2.5, PM₁₀, and NO₂ were larger in males than in females. People having comorbidity, living in rural areas, and current/ever smoking or drinking were more vulnerable to air pollution. Public health departments should consider air pollution to formulate better preventive measures for osteoporosis.

Ethnic disparities in the association between ambient air pollution and risk for cardiometabolic abnormalities in China

BACKGROUND

Long-term exposure to ambient air pollution has been associated with cardiometabolic abnormalities (CAs), which, however, may be stronger in vulnerable populations, such as minorities. The variation of the association between ambient air pollution and CAs between the majority (Han) and minority populations in China have been poorly studied.

OBJECTIVES

We aimed to estimate and compare the Hans' and minorities' risks for CAs associated with long-term exposure to ambient air pollution in Southwest China.

METHODS

A cross-sectional study was conducted on the basis of the China Multi-Ethnic Cohort. CAs were defined by the presence of at least three pre-defined metabolic dysfunctions (central obesity, elevated triglycerides, reduced high-density lipoprotein cholesterol, elevated blood pressure, and elevated fasting glucose). The concentrations of ambient air pollutants, including particulate matters (PM₁, PM_2.5, and PM₁₀) and nitrogen dioxide (NO₂), were generated from random forest models on the basis of multi-source data. One- and two-pollutant regression models were fit to assess associations between air pollutant exposure and CA risks. Sensitivity analyses were performed to examine the robustness of the associations.

RESULTS

The final sample included 51,037 Hans and 28,702 minority participants. The prevalence of CAs was 25.0%, slightly higher in the minorities (25.5%) than the Hans (24.4%). The higher risks for CAs in the overall population were associated with each 10 μg/m³ increase in the exposure to PM₁ (OR = 1.07 [1.05-1.09]), PM_2.5 (OR = 1.11 [1.06-1.17]), PM₁₀ (OR = 1.04 [1.03-1.06]), and NO₂ (OR = 1.04 [1.03-1.07]). Compared to the Hans, the higher risks for CAs were observed in the minorities for PM₁ (OR = 1.35 [1.18-1.53]), PM_2.5 (OR = 1.61 [1.34-1.93]), and PM₁₀ (OR = 1.15 [1.07-1.23]). The associations of metabolic dysfunctions (CA components) with ambient air pollution also varied between the Han and minority populations.

CONCLUSIONS

The associations between exposure to ambient air pollution and CA risks were stronger in the minorities than Hans. Our findings provide a better understanding of ethnic disparities in CA risks when being exposed to ambient air pollution in China, which also have important implications for other low- and middle-income countries where less health resources (e.g., cohort populations) are available to conduct such studies.

Associations of long-term ambient air pollution and traffic-related pollution with blood pressure and hypertension defined by the different guidelines worldwide: the CHCN-BTH study

The assessment of the generalization of the strict hypertension definition in the 2017 ACC/AHA Hypertension Guideline from environmental condition remains sparse. The aims of this study are to investigate and compare the associations of ambient air pollution and traffic-related pollution (TRP) with hypertension defined by the different criteria. A total of 32,135 participants were recruited from the baseline survey of the CHCN-BTH in 2017. We defined hypertension as SBP/DBP ≥ 140/90 mmHg according to the hypertension guidelines in China, Japan, Europe and ISH (traditional criteria) and defined as SBP/DBP ≥ 130/80 mmHg according to the 2017 ACC/AHA Hypertension Guideline (strict criteria). A two-level generalized linear mixed models were applied to investigate the associations of air pollutants (i.e. PM_2.5, SO₂, NO₂) and TRP with blood pressure (BP) measures and hypertension. Stratified analyses and two-pollutant models were also performed. The stronger associations of air pollutants were found in the hypertension defined by the strict criteria than that defined by the traditional criteria. The ORs per an IQR increase in PM_2.5 were 1.17 (95% CI: 1.09, 1.25) for the strict criteria and 1.14 (95% CI: 1.06, 1.23) for the traditional criteria. The similar conditions were also observed for TRP. The above results were robust in both stratified analyses and two-pollutant models. Our study assessed the significance of the hypertension defined by the strict criteria from environmental aspect and called attention to the more adverse effects of air pollution and TRP on the earlier stage of hypertension.

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.

Effects of the COVID-19 Lockdown on Air Pollutant Levels and Associated Reductions in Ischemic Stroke Incidence in Shandong Province, China

Background

Local governments in China took restrictive measures after the outbreak of COVID-19 to control its spread, which unintentionally resulted in reduced anthropogenic emission sources of air pollutants. In this study, we intended to examine the effects of the COVID-19 lockdown policy on the concentration levels of particulate matter with aerodynamic diameters of ≤1 μm (PM₁), ≤2.5 μm (PM_2.5), and ≤10 μm (PM₁₀), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ozone (O₃), and carbon monoxide (CO) and the potential subsequent reductions in the incidence of ischemic and hemorrhagic stroke in Shandong Province, China.

Methods

A difference-in-difference model combining the daily incidence data for ischemic and hemorrhagic stroke and air pollutant data in 126 counties was used to estimate the effect of the COVID-19 lockdown on the air pollutant levels and ischemic and hemorrhagic stroke incident counts. The avoided ischemic stroke cases related to the changes in air pollutant exposure levels were further estimated using concentration-response functions from previous studies.

Results

The PM₁, PM_2.5, PM₁₀, NO₂, and CO levels significantly decreased by −30.2, −20.9, −13.5, −46.3, and −13.1%, respectively. The O₃ level increased by 11.5% during the lockdown compared with that in the counterfactual lockdown phase of the past 2 years. There was a significant reduction in population-weighted ischemic stroke cases (−15,315, 95% confidence interval [CI]: −27,689, −2,942), representing a reduction of 27.6% (95% CI: −49.9%, −5.3%). The change in the number of hemorrhagic stroke cases was not statistically significant. The total avoided PM₁-, PM_2.5-, PM₁₀-, NO₂-, and CO–related ischemic stroke cases were 739 (95% CI: 641, 833), 509 (95% CI: 440, 575), 355 (95% CI: 304, 405), 1,132 (95% CI: 1,024, 1,240), and 289 (95% CI: 236, 340), respectively.

Conclusion

The COVID-19 lockdown indirectly reduced the concentration levels of PM₁, PM_2.5, PM₁₀, NO₂, and CO and subsequently reduced the associated ischemic stroke incidence. The health benefits due to the lockdown are temporary, and long-term measures should be implemented to increase air quality and related health benefits in the post-COVID-19 period.

An Estimation Method for PM2.5 Based on Aerosol Optical Depth Obtained from Remote Sensing Image Processing and Meteorological Factors

Understanding the spatiotemporal variations in the mass concentrations of particulate matter ≤2.5 µm (PM2.5) in size is important for controlling environmental pollution. Currently, ground measurement points of PM2.5 in China are relatively discrete, thereby limiting spatial coverage. Aerosol optical depth (AOD) data obtained from satellite remote sensing provide insights into spatiotemporal distributions for regional pollution sources. In this study, data from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) AOD (1 km resolution) product from Moderate Resolution Imaging Spectroradiometer (MODIS) and hourly PM2.5 concentration ground measurements from 2015 to 2020 in Dalian, China were used. Although trends in PM2.5 and AOD were consistent over time, there were seasonal differences. Spatial distributions of AOD and PM2.5 were consistent (R2 = 0.922), with higher PM2.5 values in industrial areas. The method of cross-dividing the test set by year was adopted, with AOD and meteorological factors as the input variable and PM2.5 as the output variable. A backpropagation neural network (BPNN) model of joint cross-validation was established; the stability of the model was evaluated. The trend in the predicted values of BPNN was consistent with the monitored values; the estimation result of the BPNN with the introduction of meteorological factors is better; coefficient of determination (R2) and RMSE standard deviation (SD) between the predicted values and the monitored values in the test set were 0.663–0.752 and 0.01–0.05 μg/m3, respectively. The BPNN was simpler and the training time was shorter compared with those of a regression model and support vector regression (SVR). This study demonstrated that BPNN could be effectively applied to the MAIAC AOD data to estimate PM2.5 concentrations.

Life-Time Environmental Chemical Exposure and Obesity: Review of Epidemiological Studies Using Human Biomonitoring Methods

The exponential global increase in the incidence of obesity may be partly attributable to environmental chemical (EC) exposure. Humans are constantly exposed to ECs, primarily through environmental components. This review compiled human epidemiological study findings of associations between blood and/or urinary exposure levels of ECs and anthropometric overweight and obesity indices. The findings reveal research gaps that should be addressed. We searched MEDLINE (PubMed) for full text English articles published in 2006-2020 using the keywords "environmental exposure" and "obesity". A total of 821 articles were retrieved; 102 reported relationships between environmental exposure and obesity indices. ECs were the predominantly studied environmental exposure compounds. The ECs were grouped into phenols, phthalates, and persistent organic pollutants (POPs) to evaluate obesogenic roles. In total, 106 articles meeting the inclusion criteria were summarized after an additional search by each group of EC combined with obesity in the PubMed and Scopus databases. Dose-dependent positive associations between bisphenol A (BPA) and various obesity indices were revealed. Both individual and summed di(2-ethylhexyl) phthalate (DEHP) and non-DEHP metabolites showed inconsistent associations with overweight and obesity indices, although mono-butyl phthalate (MBP), mono-ethyl phthalate (MEP), and mono-benzyl phthalate (MBzP) seem to have obesogenic roles in adolescents, adults, and the elderly. Maternal exposure levels of individual POP metabolites or congeners showed inconsistent associations, whereas dichlorodiphenyldichloroethylene (DDE) and perfluorooctanoic acid (PFOA) were positively associated with obesity indices. There was insufficient evidence of associations between early childhood EC exposure and the subsequent development of overweight and obesity in late childhood. Overall, human evidence explicitly reveals the consistent obesogenic roles of BPA, DDE, and PFOA, but inconsistent roles of phthalate metabolites and other POPs. Further prospective studies may yield deeper insights into the overall scenario.