Long-term impacts of ambient fine particulate matter exposure on overweight or obesity in Chinese adults: The China-PAR project

Dietary intake changes the associations between long-term exposure to fine particulate matter and the surrogate indicators of insulin resistance

The relationship of fine particulate matter (PM2.5) exposure and insulin resistance remains inclusive. Our study aimed to investigate this association in the project of Prediction for Atherosclerotic Cardiovascular Disease Risk in China (China-PAR). Specifically, we examined the associations between long-term PM2.5 exposure and three surrogate indicators of insulin resistance: the triglyceride-glucose index (TyG), TyG with waist circumference (TyG-WC) and metabolic score for insulin resistance (METS-IR). Additionally, we explored potential effect modification of dietary intake and components. Generalized estimating equations were used to evaluate the associations between PM2.5 and the indicators with an unbalanced repeated measurement design. Our analysis incorporated a total of 162,060 observations from 99,329 participants. Each 10 μg/m3 increment of PM2.5 was associated with an increase of 0.22 % [95 % confidence interval (CI): 0.20 %, 0.25 %], 1.60 % (95 % CI: 1.53 %, 1.67 %), and 2.05 % (95 % CI: 1.96 %, 2.14 %) in TyG, TyG-WC, and METS-IR, respectively. These associations were attenuated among participants with a healthy diet, particularly those with sufficient intake of fruit and vegetable, fish or tea (pinteraction < 0.0028). For instance, among participants with a healthy diet, TyG increased by 0.11 % (95 % CI: 0.08 %, 0.15 %) per 10 μg/m3 PM2.5 increment, significantly lower than the association observed in those with an unhealthy diet. The findings of this study emphasize the potential of a healthy diet to mitigate these associations, highlighting the urgency for improving air quality and implementing dietary interventions among susceptible populations in China.

A new method for vascular age estimation based on relative risk difference in vascular aging

OBJECTIVE

The current models of estimating vascular age (VA) primarily rely on the regression label expressed with chronological age (CA), which does not account individual differences in vascular aging (IDVA) that are difficult to describe by CA. This may lead to inaccuracies in assessing the risk of cardiovascular disease based on VA. To address this limitation, this work aims to develop a new method for estimating VA by considering IDVA. This method will provide a more accurate assessment of cardiovascular disease risk.

METHODS

Relative risk difference in vascular aging (RRDVA) is proposed to replace IDVA, which is represented as the numerical difference between individual predicted age (PA) and the corresponding mean PA of healthy population. RRDVA and CA are regard as the influence factors to acquire VA. In order to acquire PA of all samples, this work takes CA as the dependent variable, and mines the two most representative indicators from arteriosclerosis data as the independent variables, to establish a regression model for obtaining PA.

RESULTS

The proposed VA based on RRDVA is significantly correlated with 27 indirect indicators for vascular aging evaluation. Moreover, VA is better than CA by comparing the correlation coefficients between VA, CA and 27 indirect indicators, and RRDVA greater than zero presents a higher risk of disease.

CONCLUSION

The proposed VA overcomes the limitation of CA in characterizing IDVA, which may help young groups with high disease risk to promote healthy behaviors.

The combined effects of exposure to multiple PM2.5 components on overweight and obesity in middle-aged and older adults: a nationwide cohort study from 125 cities in China

The prevalence of overweight or obesity increased rapidly over the past decades in most countries, including China. However, little evidence exists about the effects of long-term exposure to PM2.5 components on overweight or obesity, particularly in developing countries. We measured different weight stages according to body mass index (BMI), and investigated the effects of exposure to PM2.5 components (ammonium [[Formula: see text]], sulfate [[Formula: see text]], nitrate [[Formula: see text]], black carbon and organic matter) on different BMI levels in middle-aged and elderly people of China. Our study explored the effects of single and multiple air pollution exposures on overweight and obesity by using the Generalized Linear Model and Quantile g-Computation model (QgC). This study found a significantly positive association between five PM2.5 components and overweight/obesity. In the QgC model, there was still a positive association between multiple exposure to PM2.5 components and overweight when all PM2.5 components were considered as a whole. In addition, males, the elderly, and urban residents were also more sensitive to five PM2.5 components.

Associations of residential greenness and ambient air pollution with overweight and obesity in older adults

OBJECTIVE

This study aimed to examine the impact of greenness and fine particulate matter <2.5 μm (PM2.5 ) on overweight/obesity among older adults in China.

METHODS

A total of 21,355 participants aged ≥65 years were included from the Chinese Longitudinal Healthy Longevity Survey between 2000 and 2018. Normalized difference vegetation index (NDVI) with a radius of 250 m and PM2.5 in a 1 × 1-km grid resolution were calculated around each participant's residence. Cox proportional hazards models were used to estimate the effects of NDVI and PM2.5 on overweight/obesity. Interaction and mediation analyses were conducted to explore combined effects.

RESULTS

The study observed 1895 incident cases of overweight/obesity over 109,566 person-years. For every 0.1-unit increase in NDVI the hazard ratio of overweight/obesity was 0.91 (95% CI: 0.88-0.95), and for every 10-μg/m3 increase in PM2.5 the hazard ratio was 1.11 (95% CI: 1.07-1.14). The effect of NDVI on overweight/obesity was partially mediated by PM2.5 , with a relative mediation proportion of 20.10% (95% CI: 1.63%-38.57%).

CONCLUSIONS

Greenness exposure appears to lower the risk of overweight/obesity in older adults in China, whereas PM2.5 , acting as a mediator, partly mediated this protective effect.

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.

Fine particulate matter induces adipose tissue expansion and weight gain: Pathophysiology

Dysregulations in energy balance represent a major driver of obesity. Recent evidence suggests that environmental factors also play a pivotal role in inducing weight gain. Chronic exposure to fine particulate matter (PM_2.5 ) is associated with white adipose tissue (WAT) expansion in animals and higher rates of obesity in humans. This review discusses metabolic adaptions in central and peripheral tissues that promote energy storage and WAT accumulation in PM_2.5 -exposed animals and humans. Chronic PM_2.5 exposure produces inflammation and leptin resistance in the hypothalamus, decreasing energy expenditure and increasing food intake. PM_2.5 promotes the conversion of brown adipocytes toward the white phenotype, resulting in decreased energy expenditure. The development of inflammation in WAT can stimulate adipogenesis and hampers catecholamine-induced lipolysis. PM_2.5 exposure affects the thyroid, reducing the release of thyroxine and tetraiodothyronine. In addition, PM_2.5 exposure compromises skeletal muscle fitness by inhibiting Nitric oxide (NO)-dependent microvessel dilation and impairing mitochondrial oxidative capacity, with negative effects on energy expenditure. This evidence suggests that pathological alterations in the hypothalamus, brown adipose tissue, WAT, thyroid, and skeletal muscle can alter energy homeostasis, increasing lipid storage and weight gain in PM_2.5 -exposed animals and humans. Further studies will enrich this pathophysiological model.

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.

Effect of long-term exposure to PM2.5 on the risk of type 2 diabetes and arthritis in type 2 diabetes patients: Evidence from a national cohort in China

BACKGROUND

It remains unclear whether type 2 diabetes and the complication of arthritis are causally related to the PM_2.5 pollutant. Therefore, we aimed to investigate the associations of long-term PM_2.5 exposure with type 2 diabetes and with arthritis in type 2 diabetes patients.

MATERIALS AND METHODS

This study used data from the China Health and Retirement Longitudinal Survey (CHARLS) implemented during 2011-2018. The associations were analyzed by Cox proportional hazards regression models, and the population-attributable fraction (PAF) was calculated to assess the burden of type 2 diabetes and arthritis-attributable to PM_2.5.

RESULTS

A total of 21,075 participants were finally included, with 19,121 analyzed for PM_2.5 and type 2 diabetes risk and 12,427 analyzed for PM_2.5 and arthritis risk, of which 1,382 with newly-diagnosed type 2 diabetes and 1,328 with arthritis during the follow-up. Overall, each 10 μg/m³ increment in PM_2.5 concentration was significantly associated with an increase in the risk of type 2 diabetes (HR = 1.26, 95 %CI1.22 to 1.31), and the PAF of type 2 diabetes attributable to PM_2.5 was 13.54 %. In type 2 diabetes patients, each 10 μg/m³ increment in PM_2.5 exposure was associated with an increase in arthritis (HR = 1.42, 95 %CI: 1.28 to 1.57), and the association was significantly greater than that (H = 1.23, 95 %CI: 1.19 to 1.28) in adults without type 2 diabetes. The PAFs of arthritis-attributable to PM_2.5 in participants with and without type 2 diabetes were 18.54 % and 10.69 %, respectively.

CONCLUSION

Long-term exposure to PM_2.5 may increase the risk of type 2 diabetes and make type 2 diabetes patients susceptible to arthritis.

Association of decreases in PM2.5 levels due to the implementation of environmental protection policies with the incidence of obesity in adolescents: A prospective cohort study

AIMS

To explore the association between decreased levels of particulate matter (≤2.5 µm; PM_2.5) due to the implementation of environmental protection policies and the incidence of obesity in adolescents in Chongqing, China through a prospective cohort study.

METHODS

A total of 2105 children (52.02% male; aged 7.33 ± 0.60 years at baseline) were enrolled from the Chongqing Children's Health Cohort. A mixed linear regression model was used to analyse the relationships of PM_2.5 levels with obesity indicators after adjusting for covariates. Additionally, a Poisson regression model was used to determine the relationship between PM_2.5 exposure and the incidence of overweight/obesity.

RESULTS

The average PM_2.5 exposure levels from participant conception to 2014, from 2015 to 2017, and from 2018 to 2019 were 66.64 ± 5.33 μg/m³, 55.49 ± 3.78 μg/m³, and 42.50 ± 1.87 μg/m³, respectively; these levels significantly decreased over time (P < 0.001). Throughout the entire follow-up period, the incidence of overweight/obesity after a ≥ 25 μg/m³ decrease in the PM_2.5 level was 4.57% among females; this incidence was the lowest among females who experienced remarkable decreases in PM_2.5 exposure. A 1-µg/m³ decrease in the PM_2.5 level significantly decreased the body mass index (BMI), BMI z score (BMI_z), and weight of adolescents (all P < 0.001). Compared with a < 20-μg/m³ decrease in the PM_2.5 level, a ≥ 25-μg/m³ decrease protected against increased BMI (net difference= -0.93; 95% confidence interval [CI]: (-1.23,-0.63) kg/m²), BMI_z (-0.28 (-0.39, -0.17)), weight (-1.59 (-2.44, -0.74) kg), and incidence of overweight/obesity (0.48 (0.37, 0.62), P < 0.001). Moreover, compared with a < 20-μg/m³ decrease in the PM_2.5 level, a ≥ 25-μg/m³ decrease resulted in significant absolute differences in BMI (-1.26 (-1.56, -0.96) kg/m²), BMI_z (-0.53 (-0.65, -0.40)) and weight (-3.01 (-3.8, -2.19) kg) (all P < 0.001).

CONCLUSIONS

This study showed the etiological relevance of declining PM_2.5 concentrations for the incidence of obesity in children and adolescents, suggesting that controlling ambient air pollutants may prevent the development of obesity in this age group. Continuous implementation of environmental protection policies in China has led to substantial health benefits.

Overview of particulate air pollution and human health in China: Evidence, challenges, and opportunities

Ambient particulate matter (PM) pollution in China continues to be a major public health challenge. With the release of the new WHO air quality guidelines in 2021, there is an urgent need for China to contemplate a revision of air quality standards (AQS). In the recent decade, there has been an increase in epidemiological studies on PM in China. A comprehensive evaluation of such epidemiological evidence among the Chinese population is central for revision of the AQS in China and in other developing countries with similar air pollution problems. We thus conducted a systematic review on the epidemiological literature of PM published in the recent decade. In summary, we identified the following: (1) short-term and long-term PM exposure increase mortality and morbidity risk without a discernible threshold, suggesting the necessity for continuous improvement in air quality; (2) the magnitude of long-term associations with mortality observed in China are comparable with those in developed countries, whereas the magnitude of short-term associations are appreciably smaller; (3) governmental clean air policies and personalized mitigation measures are potentially effective in protecting public and individual health, but need to be validated using mortality or morbidity outcomes; (4) particles of smaller size range and those originating from fossil fuel combustion appear to show larger relative health risks; and (5) molecular epidemiological studies provide evidence for the biological plausibility and mechanisms underlying the hazardous effects of PM. This updated review may serve as an epidemiological basis for China’s AQS revision and proposes several perspectives in designing future health studies.

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Acute effects of PM are smaller in China compared with developed countries

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Health effects caused by PM depend on particle composition, source, and size

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There are no thresholds for the health effects of PM

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Mechanistic studies support the biological plausibility of PM’s health effects

The macrophage senescence hypothesis: the role of poor heat shock response in pulmonary inflammation and endothelial dysfunction following chronic exposure to air pollution

INTRODUCTION

Cardiovascular diseases (CVD) have been associated with high exposure to fine particulate air pollutants (PM_2.5). Alveolar macrophages are the first defense against inhaled particles. As soon as they phagocytize the particles, they reach an inflammatory phenotype, which affects the surrounding cells and associates with CVD. Not coincidentally, CVD are marked by a depleted heat shock response (HSR), defined by a deficit in inducing 70-kDa heat shock protein (HSP70) expression during stressful conditions. HSP70 is a powerful anti-inflammatory chaperone, whose reduced levels trigger a pro-inflammatory milieu, cellular senescence, and a senescence-associated secretory phenotype (SASP). However, whether macrophage senescence is the main mechanism by which PM_2.5 propagates low-grade inflammation remains unclear.

OBJECTIVE AND DESIGN

In this article, we review evidence supporting that chronic exposure to PM_2.5 depletes HSR and determines the ability to solve the initial stress.

RESULTS AND DISCUSSION

When exposed to PM_2.5, macrophages increase the production of reactive oxygen species, which activate nuclear factor-kappa B (NF-κB). NF-κB is naturally a pro-inflammatory factor that drives prostaglandin E2 (PGE2) synthesis and causes fever. PGE2 can be converted into prostaglandin A2, a powerful inducer of HSR. Therefore, when transiently activated, NF-κB can trigger the anti-inflammatory response through negative feedback, by inducing HSP70 expression. However, when chronically activated, NF-κB heads a set of pathways involved in mitochondrial dysfunction, endoplasmic reticulum stress, unfolded protein response, inflammasome activation, and apoptosis. During chronic exposure to PM_2.5, cells cannot properly express sirtuin-1 or activate heat shock factor-1 (HSF-1), which delays the resolution phase of inflammation. Since alveolar macrophages are the first immune defense against PM_2.5, we suppose that the pollutant impairs HSR and, consequently, induces cellular senescence. Accordingly, senescent macrophages change its secretory phenotype to a more inflammatory one, known as SASP. Finally, macrophages' SASP would propagate the systemic inflammation, leading to endothelial dysfunction and atherosclerosis.

The underlying mechanism of PM2.5-induced ischemic stroke

Under the background of global industrialization, PM_2.5 has become the fourth-leading risk factor for ischemic stroke worldwide, according to the 2019 GBD estimates. This highlights the hazards of PM_2.5 for ischemic stroke, but unfortunately, PM_2.5 has not received the attention that matches its harmfulness. This article is the first to systematically describe the molecular biological mechanism of PM_2.5-induced ischemic stroke, and also propose potential therapeutic and intervention strategies. We highlight the effect of PM_2.5 on traditional cerebrovascular risk factors (hypertension, hyperglycemia, dyslipidemia, atrial fibrillation), which were easily overlooked in previous studies. Additionally, the effects of PM_2.5 on platelet parameters, megakaryocytes activation, platelet methylation, and PM_2.5-induced oxidative stress, local RAS activation, and miRNA alterations in endothelial cells have also been described. Finally, PM_2.5-induced ischemic brain pathological injury and microglia-dominated neuroinflammation are discussed. Our ultimate goal is to raise the public awareness of the harm of PM_2.5 to ischemic stroke, and to provide a certain level of health guidance for stroke-susceptible populations, as well as point out some interesting ideas and directions for future clinical and basic research.

Multiple environmental exposures and obesity in eastern China: An individual exposure evaluation model

Obesity has caused a huge burden of disease. Few studies have explored individuals' environmental exposure level and the impact of multiple environmental exposures on obesity. The aim of this study was to explore individual air pollution exposure evaluation, and the association between and multiple environmental factors and obesity among adult residents in rural areas of China. In this study, 8400 residents of 14 districts and counties in eastern of China were selected by multistage stratified cluster sampling, and a total of 8377 residents were included in the final analysis. We adopted BMI (Body Mass Index) > 28 kg/m² as the definition of obesity. First, an individual air pollution evaluation model was established based on the monitoring data of air pollution stations closest to residential address, different demographic characteristics of residents and daily living habits using generalized linear model and random forest model. Then, we used Bayesian Kernel Machine Regression (BKMR) and Quantile g-Computation (QgC) models to explore multiple environmental exposures on obesity. The results showed that six air pollutants were significantly positively associated with obesity, and green space had a significant protective effect on obesity. The BKMR model showed that the effects of different air pollutants on obesity were significantly enhanced by each other, while green space significantly reduced the positive effect of air pollution on obesity. The QgC model showed a significant positive association with obesity when all environmental factors were exposed as a whole, especially in males, higher household incomes and young people. It suggested that relevant authorities should improve regional air quality and green space to reduce the burden of disease caused by obesity.

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.