Association between long-term exposure to ambient air pollution and obesity in a Chinese rural population: The Henan Rural Cohort Study

Global Perspectives on Obesity and Being Overweight: A Bibliometric Analysis in Relation to Sustainable Development Goals

Obesity and being overweight are significant risk factors for diseases and disabilities, making it crucial to address malnutrition in all its forms to ensure health and well-being for all, as well as to achieve sustainable development. This study conducted a bibliometric analysis of research on obesity in relation to Sustainable Development Goals (SDGs) using data from the Web of Science database from 2015 to 2024 and the VOSviewer software. The findings revealed that while research on obesity and SDGs has grown slowly, SDG 3 (Good Health and Well-Being) is predominant in the literature. This study highlighted the fragmentation of research due to the complex, multifactorial nature of obesity, emphasizing the need for a more holistic approach. Furthermore, international collaborations were found to be vital for advancing research and formulating effective public policies. This analysis also identified gaps in the research related to several SDGs, including education (SDG 4), affordable and clean energy (SDG 7), and partnerships (SDG 17), suggesting the need for a broader, more holistic approach. Additionally, emerging research related to SDG 11 (Sustainable Cities and Communities) underscores the importance of urban environments in tackling obesity. In conclusion, future research should adopt an interdisciplinary approach to address these gaps and contribute to advancing the 2030 Agenda.

Association Between Exposure to Particulate Matter Air Pollution with Risk of Obesity Among Children and Adolescents in Northern and Central Taiwan

INTRODUCTION

The present study investigated the relationship between air pollution, specifically PM2.5 and PM10, and childhood and adolescent obesity in northern and central Taiwan. Previous research has shown a positive correlation between air pollution and pediatric obesity, but no study has been conducted in Taiwan. We used data from the K-12 Education Administration, Ministry of Education, and the Taiwan Air Quality Monitoring Network to analyze the association between PM2.5 and PM10 exposures and obesity rates among elementary and junior high school students.

METHODS

Data on students' height and weight were combined with air pollution data obtained from monitoring stations to assess exposure. A multivariable model estimated the relative risk and 95% confidence intervals of obesity linked to PM2.5 and PM10 exposures. Cities were categorized into quartiles (Q1-Q4) based on pollutant accumulation to compare the obesity rates.

RESULTS

Students living in areas with higher PM2.5 and PM10 exposures (Q4) had a significantly higher risk of obesity than those living in areas with lower exposures (Q1). The effect was more pronounced in girls and older students, with PM2.5 exhibiting a stronger relationship than PM10.

CONCLUSIONS

PM2.5 and PM10 exposures are significantly associated with an increased obesity risk in children and adolescents, particularly in girls and older students. Further research is needed to explore the underlying mechanisms and to control for socioeconomic and demographic factors.

Molecular Pathways Linking High-Fat Diet and PM2.5 Exposure to Metabolically Abnormal Obesity: A Systematic Review and Meta-Analysis

Obesity, influenced by environmental pollutants, can lead to complex metabolic disruptions. This systematic review and meta-analysis examined the molecular mechanisms underlying metabolically abnormal obesity caused by exposure to a high-fat diet (HFD) and fine particulate matter (PM2.5). Following the PRISMA guidelines, articles from 2019 to 2024 were gathered from Scopus, Web of Science, and PubMed, and a random-effects meta-analysis was performed, along with subgroup analyses and pathway enrichment analyses. This study was registered in the Open Science Framework. Thirty-three articles, mainly case-control studies and murine models, were reviewed, and they revealed that combined exposure to HFD and PM2.5 resulted in the greatest weight gain (82.835 g, p = 0.048), alongside increases in high-density lipoproteins, insulin, and the superoxide dismutase. HFD enriched pathways linked to adipocytokine signaling in brown adipose tissue, while PM2.5 impacted genes associated with fat formation. Both exposures downregulated protein metabolism pathways in white adipose tissue and activated stress-response pathways in cardiac tissue. Peroxisome proliferator-activated receptor and AMP-activated protein kinase signaling pathways in the liver were enriched, influencing non-alcoholic fatty liver disease. These findings highlight that combined exposure to HFD and PM2.5 amplifies body weight gain, oxidative stress, and metabolic dysfunction, suggesting a synergistic interaction with significant implications for metabolic health.

Association between long-term exposure to PM2.5 chemical components and metabolic syndrome in middle-aged and older adults

Background

Previous studies indicated that exposure to ambient fine particulate matter (PM2.5) could increase the risk of metabolic syndrome (MetS). However, the specific impact of PM2.5 chemical components remains uncertain.

Methods

A national cross-sectional study of 12,846 Chinese middle-aged and older adults was conducted. Satellite-based spatiotemporal models were employed to determine the 3-year average PM2.5 components exposure, including sulfates (SO4 2-), nitrates (NO3 -), ammonia (NH4 +), black carbon (BC), and organic matter (OM). Generalized linear models were used to investigate the associations of PM2.5 components with MetS and the components of MetS, and restricted cubic splines curves were used to establish the exposure-response relationships between PM2.5 components with MetS, as well as the components of MetS.

Results

MetS risk increased by 35.1, 33.5, 33.6, 31.2, 32.4, and 31.4% for every inter-quartile range rise in PM2.5, SO4 2-, NO3 -, NH4 +, OM and BC, respectively. For MetS components, PM2.5 chemical components were associated with evaluated risks of central obesity, high blood pressure (high-BP), high fasting glucose (high-FBG), and low high-density lipoprotein cholesterol (low-HDL).

Conclusion

This study indicated that exposure to PM2.5 components is related to increased risk of MetS and its components, including central obesity, high-BP, high-FBG, and low-HDL. Moreover, we found that the adverse effect of PM2.5 chemical components on MetS was more sensitive to people who were single, divorced, or widowed than married people.

Association between Personal Abiotic Airborne Exposures and Body Composition Changes among Healthy Adults (60-69 Years Old): A Combined Exposome-Wide and Lipidome Mediation Approach from the China BAPE Study

BACKGROUND

Evidence suggested that abiotic airborne exposures may be associated with changes in body composition. However, more evidence is needed to identify key pollutants linked to adverse health effects and their underlying biomolecular mechanisms, particularly in sensitive older adults.

OBJECTIVES

Our research aimed to systematically assess the relationship between abiotic airborne exposures and changes in body composition among healthy older adults, as well as the potential mediating mechanisms through the serum lipidome.

METHODS

From September 2018 to January 2019, we conducted a monthly survey among 76 healthy adults (60-69 years old) in the China Biomarkers of Air Pollutant Exposure (BAPE) study, measuring their personal exposures to 632 abiotic airborne pollutions using MicroPEM and the Fresh Air wristband, 18 body composition indicators from the InBody 770 device, and lipidomics from venous blood samples. We used an exposome-wide association study (ExWAS) and deletion/substitution/addition (DSA) model to unravel complex associations between exposure to contaminant mixtures and body composition, a Bayesian kernel machine regression (BKMR) model to assess the overall effect of key exposures on body composition, and mediation analysis to identify lipid intermediators.

RESULTS

The ExWAS and DSA model identified that 2,4,5-T methyl ester (2,4,5-TME), 9,10-Anthracenedione (ATQ), 4b,8-dimethyl-2-isopropylphenanthrene, and 4b,5,6,7,8,8a,9,10-octahydro-(DMIP) were associated with increased body fat mass (BFM), fat mass indicators (FMI), percent body fat (PBF), and visceral fat area (VFA) in healthy older adults [Bonferroni-Hochberg false discovery rate ( FD R BH ) < 0.05 ]. The BKMR model demonstrated a positive correlation between contaminants (anthracene, ATQ, copaene, di-epi-α -cedrene, and DMIP) with VFA. Mediation analysis revealed that phosphatidylcholine [PC, PC(16:1e/18:1), PC(16:2e/18:0)] and sphingolipid [SM, SM(d18:2/24:1)] mediated a significant portion, ranging from 12.27% to 26.03% (p-value < 0.05 ), of the observed increase in VFA.

DISCUSSION

Based on the evidence from multiple model results, ATQ and DMIP were statistically significantly associated with the increased VFA levels of healthy older adults, potentially regulated through lipid intermediators. These findings may have important implications for identifying potentially harmful environmental chemicals and developing targeted strategies for the control and prevention of chronic diseases in the future, particularly as the global population is rapidly aging. https://doi.org/10.1289/EHP13865.

Associations of long-term exposure to air pollution and noise with body composition in children and adults: Results from the LEAD general population study

BACKGROUND

While long-term air pollution and noise exposure has been linked to increasing cardiometabolic disease risk, potential effects on body composition remains unclear. This study aimed to investigate the associations of long-term air pollution, noise and body composition.

METHODS

We used repeated data from the LEAD (Lung, hEart, sociAl, boDy) study conducted in Vienna, Austria. Body mass index (BMI; kg/m2), fat mass index (FMI; z-score), and lean mass index (LMI; z-score) were measured using dual-energy x-ray absorptiometry at the first (t0; 2011-ongoing) and second (t1; 2017-ongoing) examinations. Annual particulate matter (PM10) and nitrogen dioxide (NO2) concentrations were estimated with the GRAMM/GRAL model (2015-2021). Day-evening-night (Lden) and night-time (Lnight) noise levels from transportation were modeled for 2017 following the European Union Directive 2002/49/EC. Exposures were assigned to residential addresses. We performed analyses separately in children/adolescents and adults, using linear mixed-effects models with random participant intercepts and linear regression models for cross-sectional and longitudinal associations, respectively. Models were adjusted for co-exposure, lifestyle and sociodemographics.

RESULTS

A total of 19,202 observations (nt0 = 12,717, nt1 = 6,485) from participants aged 6-86 years (mean age at t0 = 41.0 years; 52.9 % female; mean PM10 = 21 µg/m3; mean follow-up time = 4.1 years) were analyzed. Among children and adolescents (age ≤ 18 years at first visit), higher PM10exposure was cross-sectionally associated with higher FMI z-scores (0.09 [95 % Confidence Interval (CI): 0.03, 0.16]) and lower LMI z-scores (-0.05 [95 % CI: -0.10, -0.002]) per 1.8 µg/m3. Adults showed similar trends in cross-sectional associations as children, though not reaching statistical significance. We observed no associations for noise exposures. Longitudinal analyses on body composition changes over time yielded positive associations for PM10, but not for other exposures.

CONCLUSION

Air pollution exposure, mainly PM10, was cross-sectionally and longitudinally associated with body composition in children/adolescents and adults. Railway/road-traffic noise exposures showed no associations in both cross-sectional and longitudinal analyses.

A causal relationship between particulate matter 2.5 and obesity and its related indicators: a Mendelian randomization study of European ancestry

BACKGROUND

In recent years, the prevalence of obesity has continued to increase as a global health concern. Numerous epidemiological studies have confirmed the long-term effects of exposure to ambient air pollutant particulate matter 2.5 (PM2.5) on obesity, but their relationship remains ambiguous.

METHODS

Utilizing large-scale publicly available genome-wide association studies (GWAS), we conducted univariate and multivariate Mendelian randomization (MR) analyses to assess the causal effect of PM2.5 exposure on obesity and its related indicators. The primary outcome given for both univariate MR (UVMR) and multivariate MR (MVMR) is the estimation utilizing the inverse variance weighted (IVW) method. The weighted median, MR-Egger, and maximum likelihood techniques were employed for UVMR, while the MVMR-Lasso method was applied for MVMR in the supplementary analyses. In addition, we conducted a series of thorough sensitivity studies to determine the accuracy of our MR findings.

RESULTS

The UVMR analysis demonstrated a significant association between PM2.5 exposure and an increased risk of obesity, as indicated by the IVW model (odds ratio [OR]: 6.427; 95% confidence interval [CI]: 1.881-21.968; P FDR = 0.005). Additionally, PM2.5 concentrations were positively associated with fat distribution metrics, including visceral adipose tissue (VAT) (OR: 1.861; 95% CI: 1.244-2.776; P FDR = 0.004), particularly pancreatic fat (OR: 3.499; 95% CI: 2.092-5.855; PFDR =1.28E-05), and abdominal subcutaneous adipose tissue (ASAT) volume (OR: 1.773; 95% CI: 1.106-2.841; P FDR = 0.019). Furthermore, PM2.5 exposure correlated positively with markers of glucose and lipid metabolism, specifically triglycerides (TG) (OR: 19.959; 95% CI: 1.269-3.022; P FDR = 0.004) and glycated hemoglobin (HbA1c) (OR: 2.462; 95% CI: 1.34-4.649; P FDR = 0.007). Finally, a significant negative association was observed between PM2.5 concentrations and levels of the novel obesity-related biomarker fibroblast growth factor 21 (FGF-21) (OR: 0.148; 95% CI: 0.025-0.89; P FDR = 0.037). After adjusting for confounding factors, including external smoke exposure, physical activity, educational attainment (EA), participation in sports clubs or gym leisure activities, and Townsend deprivation index at recruitment (TDI), the MVMR analysis revealed that PM2.5 levels maintained significant associations with pancreatic fat, HbA1c, and FGF-21.

CONCLUSION

Our MR study demonstrates conclusively that higher PM2.5 concentrations are associated with an increased risk of obesity-related indicators such as pancreatic fat content, HbA1c, and FGF-21. The potential mechanisms require additional investigation.

An association between PM2.5 components and respiratory infectious diseases: A China's mainland-based study

The particulate matter with diameter of less than 2.5 µm (PM2.5) is an important risk factor for respiratory infectious diseases, such as scarlet fever, tuberculosis, and similar diseases. However, it is not clear which component of PM2.5 is more important for respiratory infectious diseases. Based on data from 31 provinces in mainland China obtained between 2013 and 2019, this study investigated the effects of different PM2.5 components, i.e., sulfate (SO42-), nitrate (NO3-), ammonium (NH4+), and organic matter (OM), and black carbon (BC), on respiratory infectious diseases incidence [pulmonary tuberculosis (PTB), scarlet fever (SF), influenza, hand, foot, and mouth disease (HFMD), and mumps]. Geographical probes and the Bayesian kernel machine regression (BKMR) model were used to investigate correlations, single-component effects, joint effects, and interactions between components, and subgroup analysis was used to assess regional and temporal heterogeneity. The results of geographical probes showed that the chemical components of PM2.5 were associated with the incidence of respiratory infectious diseases. BKMR results showed that the five components of PM2.5 were the main factors affecting the incidence of respiratory infectious diseases (PIP>0.5). The joint effect of influenza and mumps by co-exposure to the components showed a significant positive correlation, and the exposure-response curve for a single component was approximately linear. And single-component modelling revealed that OM and BC may be the most important factors influencing the incidence of respiratory infections. Moreover, respiratory infectious diseases in southern and southwestern China may be less affected by the PM2.5 component. This study is the first to explore the relationship between different components of PM2.5 and the incidence of five common respiratory infectious diseases in 31 provinces of mainland China, which provides a certain theoretical basis for future research.

Association of the external environmental exposome and obesity: A comprehensive nationwide study in 2019 among Chinese children and adolescents

OBJECTIVE

Children and adolescents are particularly vulnerable to the effects of various environmental factors, which could disrupt growth processes and potentially lead to obesity. Currently, comprehensive and systematic assessments of these environmental exposures during developmental periods are lacking. Therefore, this study aims to evaluate the association between external environmental exposures and the incidence of obesity in children and adolescents.

METHODS

Data was collected from the 2019 Chinese National Survey on Students' Constitution and Health, including 214,659 Han children aged 7 to 19. Body Mass Index (BMI) and BMI-for-age z-score (zBMI) were the metrics used to assess overweight and obesity prevalence. The study assessed 18 environmental factors, including air pollutants, natural space, land cover, meteorological conditions, built environment, road conditions, and artificial light at night. Exposome-wide association study (ExWAS) to analyze individual exposures' associations with health outcomes, and Weighted Quantile Sum (WQS) to assess cumulative exposure effects.

RESULTS

Among the children and adolescents, there were 24.2 % participants classified as overweight or obesity. Notably, 17 out of 18 environmental factors exhibited significant associations with zBMI and overweight/obesity. Seven air pollutants, road conditions, and built density were positively correlated with higher zBMI and obesity risk, while NDVI, forests, and meteorological factors showed negative correlations. Co-exposure analysis highlighted that SO2, ALAN, PM10, and trunk road density significantly increased zBMI, whereas rainfall, grassland, and forest exposure reduced it. Theoretically reduction in the number and prevalence of cases was calculated, indicating potential reductions in prevalence of up to 4.51 % for positive exposures and 5.09 % for negative exposures. Notably, substantial reductions were observed in regions with high pollution levels.

CONCLUSION

This large-scale investigation, encompassing various environmental exposures in schools, highlights the significant impact of air pollution, road characteristics, rainfall, and forest coverage on childhood obesity.

Inflammatory markers and androstenedione modify the effect of serum testosterone on obesity among men: Findings from a Chinese population

BACKGROUND

Few studies are available on the relationship of androstenedione with inflammation and obesity and the effect of androstenedione and inflammation on the association between testosterone and obesity. This study intended to examine the mediation effect of inflammatory markers on the association of testosterone with obesity and the moderation effect of androstenedione on the association of testosterone with inflammation and obesity in Chinese rural men.

MATERIALS AND METHODS

This cross-sectional research enrolled 2536 male rural inhabitants from the Henan Rural Cohort study. The serum concentrations of testosterone and androstenedione were determined by liquid chromatography-tandem mass spectrometry. Linear and logistic regression were used to examine the relationships between testosterone, inflammatory markers, and obesity. Mediation and moderation analyses were carried out to evaluate the potential effects of inflammatory markers on the relationship between testosterone and obesity, as well as androstenedione on the relationships of testosterone with inflammation and obesity.

RESULTS

After adjusting for confounding factors, the results showed that testosterone and androstenedione were negatively related to obesity, and inflammatory markers were positively associated with obesity. Besides, testosterone and androstenedione were negatively associated with inflammatory markers. Mediation analysis showed that white blood cell, neutrophil, monocyte, and high-sensitivity C-reactive protein had mediating effects on the association between testosterone and obesity. The most vital mediator was high-sensitivity C-reactive protein, and its proportion of the effect was 11.02% (defined by waist circumference), 11.15% (defined by waist-to-hip ratio), 12.92% (defined by waist-to-height ratio), and full mediating effect (defined by body mass index). Moreover, androstenedione played negative moderation effects on the associations of testosterone with inflammation and obesity.

CONCLUSION

Inflammatory markers and androstenedione were first found to have modifying effects on the association of testosterone with obesity. Higher levels of testosterone and androstenedione could reduce the inflammation level and risk of obesity, indicating their potential roles in the prevention and treatment of chronic diseases.

Physical activity diminished adverse associations of obesity with lipid metabolism in the population of rural regions of China

The interactive effects of obesity and physical inactivity on lipid metabolism and prevalent dyslipidemia are scarcely reported in rural regions. 39029 subjects were obtained from the Henan Rural Cohort, and their metabolic equivalents (METs) of physical activity (PA) were computed. Independent associations of the obesity indices and PA with either lipid indices or prevalent dyslipidemia were analyzed by generalized linear models, and additive effects of obesity and PA on prevalent dyslipidemia were further quantified. Each obesity index was positively associated with total cholesterol, triglyceride, low-density lipoprotein or prevalent dyslipidemia but negatively associated with high-density lipoprotein, whereas the opposite association of PA with either each lipid index or prevalent dyslipidemia was observed. Joint association of PA and each obesity index with each lipid index and prevalent dyslipidemia was observed. Furthermore, the association of each obesity index in association with each lipid index was attenuated by increased PA levels.

Characterization of risks and pathogenesis of respiratory diseases caused by rural atmospheric PM2.5

Forty-six percent of the world's population resides in rural areas, the majority of whom belong to vulnerable groups. They mainly use cheap solid fuels for cooking and heating, which release a large amount of PM2.5 and cause adverse effects to human health. PM2.5 exhibits urban-rural differences in its health risk to the respiratory system. However, the majority of research on this issue has focused on respiratory diseases induced by atmospheric PM2.5 in urban areas, while rural areas have been ignored for a long time, especially the pathogenesis of respiratory diseases. This is not helpful for promoting environmental equity to aid vulnerable groups under PM2.5 pollution. Thus, this study focuses on rural atmospheric PM2.5 in terms of its chemical components, toxicological effects, respiratory disease types, and pathogenesis, represented by PM2.5 from rural areas in the Sichuan Basin, China (Rural SC-PM2.5). In this study, organic carbon is the most significant component of Rural SC-PM2.5. Rural SC-PM2.5 significantly induces cytotoxicity, oxidative stress, and inflammatory response. Based on multiomics, bioinformatics, and molecular biology, Rural SC-PM2.5 inhibits ribonucleotide reductase regulatory subunit M2 (RRM2) to disrupt the cell cycle, impede DNA replication, and ultimately inhibit lung cell proliferation. Furthermore, this study supplements and supports the epidemic investigation. Through an analysis of the transcriptome and human disease database, it is found that Rural SC-PM2.5 may mainly involve pulmonary hypertension, sarcoidosis, and interstitial lung diseases; in particular, congenital diseases may be ignored by epidemiological surveys in rural areas, including tracheoesophageal fistula, submucous cleft of the hard palate, and congenital hypoplasia of the lung. This study contributes to a greater scientific understanding of the health risks posed by rural PM2.5, elucidates the pathogenesis of respiratory diseases, clarifies the types of respiratory diseases, and promotes environmental equity.

Effects of ambient air pollution on obesity and ectopic fat deposition: a protocol for a systematic review and meta-analysis

INTRODUCTION

Globally, the prevalence of obesity tripled from 1975 to 2016. There is evidence that air pollution may contribute to the obesity epidemic through an increase in oxidative stress and inflammation of adipose tissue. However, the impact of air pollution on body weight at a population level remains inconclusive. This systematic review and meta-analysis will estimate the association of ambient air pollution with obesity, distribution of ectopic adipose tissue, and the incidence and prevalence of non-alcoholic fatty liver disease among adults.

METHODS AND ANALYSIS

The study will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines for conduct and reporting. The search will include the following databases: Ovid Medline, Embase, PubMed, Web of Science and Latin America and the Caribbean Literature on Health Sciences, and will be supplemented by a grey literature search. Each article will be independently screened by two reviewers, and relevant data will be extracted independently and in duplicate. Study-specific estimates of associations and their 95% Confidence Intervals will be pooled using a DerSimonian and Laird random-effects model, implemented using the RevMan software. The I2 statistic will be used to assess interstudy heterogeneity. The confidence in the body of evidence will be assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach.

ETHICS AND DISSEMINATION

As per institutional policy, ethical approval is not required for secondary data analysis. In addition to being published in a peer-reviewed journal and presented at conferences, the results of the meta-analysis will be shared with key stakeholders, health policymakers and healthcare professionals.

PROSPERO REGISTRATION NUMBER

CRD42023423955.

Joint effects of prenatal exposure to air pollution and pregnancy-related anxiety on birth weight: A prospective birth cohort study in Ma'anshan, China

BACKGROUND

A growing number of studies have shown that prenatal exposure to chemical and non-chemical stressors has effects on fetal growth. The co-exposure of both better reflects real-life exposure patterns. However, no studies have included air pollutants and pregnancy-related anxiety (PrA) as mixtures in the analysis.

METHOD

Using the birth cohort study method, 576 mother-child pairs were included in the Ma'anshan Maternal and Child Health Hospital. Evaluate the exposure levels of six air pollutants during pregnancy using inverse distance weighting (IDW) based on the pregnant woman's residential address and air pollution data from monitoring stations. Prenatal anxiety levels were assessed using the PrA Questionnaire. Generalized linear regression (GLR), quantile g-computation (QgC) and bayesian kernel machine regression (BKMR) were used to assess the independent or combined effects of air pollutants and PrA on birth weight for gestational age z-score (BWz).

RESULT

The results of GLR indicate that the correlation between the six air pollutants and PrA with BWz varies depending on the different stages of pregnancy and pollutants. The QgC shows that during trimester 1, when air pollutants and PrA are considered as a whole exposure, an increase of one quartile is significantly negatively correlated with BWz. The BKMR similarly indicates that during trimester 1, the combined exposure of air pollutants and PrA is moderately correlated with a decrease in BWz.

CONCLUSION

Using the method of analyzing mixed exposures, we found that during pregnancy, the combined exposure of air pollutants and PrA, particularly during trimester 1, is associated with BWz decrease. This supports the view that prenatal exposure to chemical and non-chemical stressors has an impact on fetal growth.

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.

Salt reduction behavior of adults in Anhui province in 2019: a cross-sectional survey of 3,378 participants

Objective

A high-sodium diet is an important risk factor for hypertension in the Chinese population, which can increase the risk of cardiovascular and cerebrovascular diseases. Although a large number of related studies have been carried out in Anhui province, clear, effective salt reduction interventions and policies that can be widely promoted have not yet been formed. This study sought to understand the prevalence and precise measures of salt reduction behavior, the variables affecting salt reduction behavior, and the reasons why salt reduction behavior was not practiced in Anhui Province, China.

Methods

The total number of participants in the study was 3,378. Using a multi-stage stratified cluster random sampling method, residents between the ages of 18 and 69 years in 10 counties and districts were selected from March to October 2019. A survey questionnaire and physical measurements were given to each participant. The influencing factors of residents' salt reduction behavior were examined using a multi-factor unconditional logistic regression analysis. The chi-squared (χ2) test was used to analyze the implementation of salt reduction behaviors among different age groups and gender, the factors influencing the implementation of salt reduction measures, and the reasons for not implementing salt reduction measures.

Results

A history of hypertension was associated with salt reduction strategies (P = 0.014). Patients with hypertension were more likely to adopt salt reduction behaviors than those without hypertension (OR = 1.218, P = 0.040). The influence of eating out on the adoption of salt-reduction measures varied by age group (χ2 = 50.463, P < 0.001) and gender (χ2 = 81.348, P < 0.001).

Conclusion

In summary, residents of the Anhui Province are not very knowledgeable about salt reduction. Age, gender, education level, hypertension, and marital status are the main determinants. Our findings have significant implications for policymakers who want to devise salt reduction strategies.

The association between outdoor air pollution and body mass index, central obesity, and visceral adiposity index among middle-aged and elderly adults: a nationwide study in China

Background

Previous animal studies have suggested that air pollution (AP) exposure may be a potential risk factor for obesity; however, there is limited epidemiological evidence available to describe the association of obesity with AP exposure.

Methods

A retrospective cross-sectional study was conducted on 11,766 participants across mainland China in 2015. Obesity was assessed using body mass index (BMI), waist circumference (WC), and visceral adiposity index (VAI). The space-time extremely randomized tree (STET) model was used to estimate the concentration of air pollutants, including SO2, NO2, O3, PM1, PM2.5, and PM10, matched to participants' residential addresses. Logistic regression models were employed to estimate the associations of obesity with outdoor AP exposure. Further stratified analysis was conducted to evaluate whether sociodemographics or lifestyles modified the effects.

Results

Increased AP exposure was statistically associated with increased odds of obesity. The odds ratio (ORs) and 95% confidence interval (CI) of BMI-defined obesity were 1.21 (1.17, 1.26) for SO2, 1.33 (1.26, 1.40) for NO2, 1.15 (1.10, 1.21) for O3, 1.38 (1.29, 1.48) for PM1, 1.19 (1.15, 1.22) for PM2.5, and 1.11 (1.09, 1.13) for PM10 per 10 μg/m3 increase in concentration. Similar results were found for central obesity. Stratified analyses suggested that elderly participants experienced more adverse effects from all 6 air pollutants than middle-aged participants. Furthermore, notable multiplicative interactions were found between O3 exposure and females as well as second-hand smokers in BMI-defined obesity.

Conclusions

This study suggested that outdoor AP exposure had a significant association with the risk of obesity in the middle-aged and elderly Chinese population. Elderly individuals and women may be more vulnerable to AP exposure.

Spatial analysis of overweight prevalence in China: exploring the association with air pollution

BACKGROUND

Overweight is a known risk factor for various chronic diseases and poses a significant threat to middle-aged and elderly adults. Previous studies have reported a strong association between overweight and air pollution. However, the spatial relationship between the two remains unclear due to the confounding effects of spatial heterogeneity.

METHODS

We gathered height and weight data from the 2015 China Health and Retirement Long-term Survey (CHARLS), comprising 16,171 middle-aged and elderly individuals. We also collected regional air pollution data. We then analyzed the spatial pattern of overweight prevalence using Moran's I and Getis-Ord Gi* statistics. To quantify the explanatory power of distinct air pollutants for spatial differences in overweight prevalence across Southern and Northern China, as well as across different age groups, we utilized Geodetector's q-statistic.

RESULTS

The average prevalence of overweight among middle-aged and elderly individuals in each city was 67.27% and 57.39%, respectively. In general, the q-statistic in southern China was higher than that in northern China. In the north, the prevalence was significantly higher at 54.86% compared to the prevalence of 38.75% in the south. SO2 exhibited a relatively higher q-statistic in middle-aged individuals in both the north and south, while for the elderly in the south, NO2 was the most crucial factor (q = 0.24, p < 0.01). Moreover, fine particulate matter (PM2.5 and PM10) also demonstrated an important effect on overweight. Furthermore, we found that the pairwise interaction between various risk factors improved the explanatory power of the prevalence of overweight, with different effects for different age groups and regions. In northern China, the strongest interaction was found between NO2 and SO2 (q = 0.55) for middle-aged individuals and PM2.5 and SO2 (q = 0.27) for the elderly. Conversely, in southern China, middle-aged individuals demonstrated the strongest interaction between SO2 and PM10 (q = 0.60), while the elderly showed the highest interaction between NO2 and O3 (q = 0.42).

CONCLUSION

Significant spatial heterogeneity was observed in the effects of air pollution on overweight. Specifically, air pollution in southern China was found to have a greater impact on overweight than that in northern China. And, the impact of air pollution on middle-aged individuals was more pronounced than on the elderly, with distinct pollutants demonstrating significant variation in their impact. Moreover, we found that SO2 had a greater impact on overweight prevalence among middle-aged individuals, while NO2 had a greater impact on the elderly. Additionally, we identified significant statistically interactions between O3 and other pollutants.

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.

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.

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.

Exposure to air pollution and prevalence of metabolic syndrome: A nationwide study in China from 2011 to 2015

BACKGROUND

Evidence concerning the influence of air pollution on metabolic syndrome (MetS) is still limited. We aimed to investigate whether sustained exposure to air pollutants are associated with increased prevalence of MetS and its individual components.

METHODS

We conducted a cross-sectional study comprised of 14,097 individuals participated in the first or third survey of the CHARLS. The personal cumulative (3-year averaged) exposure concentrations of nitrogen dioxide (NO₂), particulate matter (PM) with a diameter of 1.0 μm or less (PM₁), PM with a diameter of 10 μm or less (PM₁₀) and PM with a diameter of 2.5 μm or less (PM_2.5) were estimated using a spatiotemporal random forest model at 0.1° × 0.1° spatial resolution based on residential address of each participant provided. We utilized logistic regression models to estimate the associations of the four air pollutants with the prevalence of MetS and its individual components, and performed interaction analyses to evaluate potential effect modifications by gender, health status, age and drinking status.

RESULTS

Sustained exposure to air pollutants is associated with increased prevalence of MetS. For every 10 μg/m³ increase in NO₂, PM₁, PM₁₀ and PM_2.5, the adjusted odds ratio (OR) of MetS was 2.276 (95 % CI: 2.148, 2.412), 1.207 (95 % CI: 1.155, 1.263), 1.027 (95 % CI: 1.006, 1.048) and 1.027 (95 % CI: 0.989, 1.066), respectively. For MetS components, we observed significant associations between NO₂, PM₁, PM₁₀ and central obesity, high blood pressure, elevated fasting glucose and low high-density lipoprotein cholesterol. For example, the adjusted OR of low high-density lipoprotein cholesterol for every 10 μg/m³ increase in NO₂ was 1.855 (95 % CI: 1.764, 1.952). We also identified that age could significantly modified the association between NO₂ and prevalence of MetS.

CONCLUSIONS

Chinese adults sustained exposure to higher concentrations of air pollutants are associated with increased prevalence of MetS and its components.

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.

Physical activity attenuated the association of ambient ozone with type 2 diabetes mellitus and fasting blood glucose among rural Chinese population

The association of ozone with type 2 diabetes mellitus (T2DM) is uncertain. Moreover, the moderating effect of physical activity on this association is largely unknown. This study aims to evaluate the independent and combined effects of ozone and physical activity on T2DM and fasting blood glucose (FBG) in a Chinese rural adult population. A total of 39,192 participants were enrolled in the Henan Rural Cohort Study. Individual ozone exposure was assessed by using a satellite-based random forest model. The logistic regression and generalized linear models were used to evaluate the associations of ozone and physical activity with T2DM and FBG, respectively. Interaction plots were used to visualize the interaction effects of ozone and physical activity on T2DM or FBG. An interquartile range (IQR) increase in ozone exposure concentration was related to a 53.3% (odds ratio (OR),1.533; 95% confidence interval (CI), 1.426, 1.648) increase in odds of T2DM and a 0.292 mmol/L (95%CI, 0.263, 0.321) higher FBG level, respectively. The effects of ozone on T2DM and FBG generally decreased as physical activity levels increased. Negative additive interactions between ozone and physical activity on T2DM risk were observed (relative excess risk due to interaction (RERI), -0.261; 95%CI, -0.473, -0.048; attributable proportion due to interaction (AP), -0.203; 95%CI, -0.380, -0.027; synergy index (S), 0.520; 95%CI, 0.299, 0.904). The larger effects of ozone were observed among elderly and men on T2DM and FBG than young and women. Long-term exposure to ozone was associated with higher odds of T2DM and higher FBG levels, and these associations might be attenuated by increasing physical activity levels. In addition, there was a negative additive interaction (antagonistic effect) between ozone exposure and physical activity level on T2DM risk, suggesting that physical activity might be an effective method to reduce the burden of T2DM attributed to ozone exposure. Trail registration: The Henan Rural Cohort Study has been registered at Chinese Clinical Trial Register (registration number: ChiCTR-OOC-15006699). Date of registration: 06 July 2015, http://www.chictr.org.cn/showproj.aspx?proj=11375.

Exposure to ultrafine particles and childhood obesity: A cross-sectional analysis of the Seven Northeast Cities (SNEC) Study in China

BACKGROUND

Studies on the obesogenic effect of air pollution on children have been mixed and sparse. Moreover, due to insufficient air monitoring, few studies have investigated the role of more tiny but unregulated particles (ambient particles with a diameter of 0.1 μm or less, ultrafine particles).

OBJECTIVE

We sought to explore the associations between long-term exposure to ambient ultrafine particles (UFPs) and childhood obesity in Chinese children.

METHODS

In this cross-sectional study, we randomly recruited 47,990 children, aged 6-18 years, from seven cities in Northeastern China between 2012 and 2013. Child age- and sex-specific z-scores for body mass index (BMI Z-score) and weight status were generated using the World Health Organization growth reference. Four-year average concentrations of UFPs and airborne particulates of diameter ≤ 1 μm (PM₁), ≤2.5 μm (PM_2.5), and ≤10 μm (PM₁₀) were estimated at home, using neural network simulated WRF-Chem model and spatiotemporal model, respectively. Confounder-adjusted generalized linear mixed models examined the associations between air pollution and BMI Z-score and the prevalence of childhood obesity.

RESULT

We found that UFPs exposure was associated with greater childhood BMI Z-score and a higher likelihood of obesity. Compared with the lowest quartile, higher quartiles of UFPs were associated with greater odds for obesity prevalence in children (i.e., the adjusted OR was 1.25; 95 % CI, 1.12-1.39; 1.43; 95 % CI, 1.27-1.61; and 1.41; 95 % CI, 1.25-1.58 for the second, third, and fourth quartile, respectively). Similar associations were observed for PM₁, PM_2.5, and PM₁₀, and were greater in boys and children living close to roadways.

CONCLUSIONS

Long-term UFPs exposure was associated with a greater likelihood of childhood obesity, and stronger associations on BMI Z-score were observed in boys and children living close to roadways. This study indicates that more attention should be paid to the health effects of UFPs, and routinely monitoring of UFPs should be considered.

Effects of air pollution on human health - Mechanistic evidence suggested by in vitro and in vivo modelling

Airborne particulate matter (PM) comprises both solid and liquid particles, including carbon, sulphates, nitrate, and toxic heavy metals, which can induce oxidative stress and inflammation after inhalation. These changes occur both in the lung and systemically, due to the ability of the small-sized PM (i.e. diameters ≤2.5 μm, PM_2.5) to enter and circulate in the bloodstream. As such, in 2016, airborne PM caused ∼4.2 million premature deaths worldwide. Acute exposure to high levels of airborne PM (eg. during wildfires) can exacerbate pre-existing illnesses leading to hospitalisation, such as in those with asthma and coronary heart disease. Prolonged exposure to PM can increase the risk of non-communicable chronic diseases affecting the brain, lung, heart, liver, and kidney, although the latter is less well studied. Given the breadth of potential disease, it is critical to understand the mechanisms underlying airborne PM exposure-induced disorders. Establishing aetiology in humans is difficult, therefore, in-vitro and in-vivo studies can provide mechanistic insights. We describe acute health effects (e.g. exacerbations of asthma) and long term health effects such as the induction of chronic inflammatory lung disease, and effects outside the lung (e.g. liver and renal change). We will focus on oxidative stress and inflammation as this is the common mechanism of PM-induced disease, which may be used to develop effective treatments to mitigate the adverse health effect of PM exposure.

Exposure to outdoor and indoor air pollution and risk of overweight and obesity across different life periods: A review

Due to the highly evolved industrialization and modernization, air quality has deteriorated in most countries. As reported by the World Health Organization (WHO), air pollution is now considered as one of the major threats to global health and a principal risk factor for noncommunicable diseases. Meanwhile, the increasing worldwide prevalence of overweight and obesity is attracting more public attentions. Recently, accumulating epidemiological studies have provided evidence that overweight and obesity may be partially attributable to environmental exposure to air pollution. This review summarizes the epidemiological evidence for the correlation between exposure to various outdoor and indoor air pollutants (mainly particulate matter (PM), nitrogen oxides (NO_x), ozone (O₃), and polycyclic aromatic hydrocarbons (PAHs)) and overweight and obesity outcomes in recent years. Moreover, it discusses the multiple effects of air pollution during exposure periods throughout life and sex differences in populations. This review also describes the potential mechanism underlying the increased risk of obesity caused by air pollution, including inflammation, oxidative stress, metabolic imbalance, intestinal flora disorders and epigenetic modifications. Finally, this review proposes macro- and micro-measures to prevent the negative effects of air pollution exposure on the obesity prevalence.

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.

A longitudinal analysis of PM2.5 exposure and multimorbidity clusters and accumulation among adults aged 45-85 in China

While previous studies have emphasised the role of individual factors in understanding multimorbidity disparities, few have investigated contextual factors such as air pollution (AP). We first use cross-sectional latent class analysis (LCA) to assess the associations between PM2.5 exposure and multimorbidity disease clusters, and then estimate the associations between PM2.5 exposure and the development of multimorbidity longitudinally using growth curve modelling (GCM) among adults aged 45-85 in China. The results of LCA modelling suggest four latent classes representing three multimorbidity patterns (respiratory, musculoskeletal, cardio-metabolic) and one healthy pattern. The analysis shows that a 1 μg/m3 increase in cumulative exposure to PM2.5 is associated with a higher likelihood of belonging to respiratory, musculoskeletal or cardio-metabolic clusters: 2.4% (95% CI: 1.02, 1.03), 1.5% (95% CI: 1.01, 1.02) and 3.3% (95% CI: 1.03, 1.04), respectively. The GCM models show that there is a u-shaped association between PM2.5 exposure and multimorbidity, indicating that both lower and higher PM2.5 exposure is associated with increased multimorbidity levels. Higher multimorbidity in areas of low AP is explained by clustering of musculoskeletal diseases, whereas higher AP is associated with cardio-metabolic disease clusters. The study shows how multimorbidity clusters vary contextually and that PM2.5 exposure is more detrimental to health among older adults.

Effects of physical activity intensity on adulthood obesity as a function of long-term exposure to ambient PM2.5: Observations from a Chinese nationwide representative sample

Long-term exposure to PM_2.5 has been associated with increased obesity risk, while physical activity (PA) is a suggested protective factor. This raises a dilemma whether the increased dose of PM_2.5 due to PA-intensified ventilation would offset the benefits of PA. Using a national representative sample, we aim to (1) ascertain inclusive findings of the association between PA and obesity, and (2) examine whether PM_2.5 exposure modifies the PA-obesity relationship. We recruited 91,121 Chinese adults from 31 provinces using a multi-stage stratified-clustering random sampling method. PM_2.5 was estimated using a validated machine learning method with a spatial resolution of 0.1° × 0.1°. PA intensity was calculated as metabolic equivalent (MET)-hour/week by summing all activities. Body weight, height, and waist circumference (WC) were measured after overnight fasting. Obesity-related traits included continuous outcomes (Body mass index [BMI], WC, and waist-to-height ratio (WHtR)) and binomial outcomes (general obesity, abdominal obesity, and WHtR obesity). Generalized linear regression models were used to estimate the interaction effects between PM_2.5 and PA on obesity, controlling for covariates. The results indicated that each IQR increase in PA was associated with 0.078 (95% CI: -0.096 to -0.061) kg/m², 0.342 (-0.389 to -0.294) cm, and 0.0022 (-0.0025 to -0.0019) decrease in BMI, WC, and WHtR, respectively. The joint association showed that benefits of PA on obesity were attenuated as PM_2.5 increased. Risk of abdominal obesity decreased 11.3% (OR = 0.887, 95% CI: 0.866, 0.908) per IQR increase in PA among the low-PM_2.5 (≤55.9 μg/m³) exposure group, but only 5.5% (OR = 0.945, 95% CI: 0.930, 0.960) among the high-PM_2.5 (>55.9 μg/m³) exposure group. We concluded the increase in PA intensity was significantly associated with lower risk of obesity in adults living across mainland China, where annual level of PM_2.5 were mostly exceeding the standard. Reducing PM_2.5 exposure would enhance the PA benefits as a risk reduction strategy.

Adverse associations of different obesity measures and the interactions with long-term exposure to air pollutants with prevalent type 2 diabetes mellitus: The Henan Rural Cohort study

BACKGROUND

Obesity and ambient air pollution are independent risk factors of type 2 diabetes mellitus (T2DM), however, the evidence regarding their joint associations on T2DM was sparsely studied in low-middle income countries.

METHODS

A total of 38,841 participants were selected from Henan Rural Cohort study which was carried out during 2015-2017. Obesity was identified by body mass index (BMI), WC (waist circumstance), WHR (waist-to-hip ratio), WHtR (waist-to-height ratio), BFP (body fat percent), and VFI (visceral fat index). Three-year averaged-concentrations of NO2, PM1, PM2.5, and PM10 were assessed by using the method of spatiotemporal model incorporated into the satellites data. The independent associations of obesity indicators and exposure to air pollutants on fasting blood glucose (FBG) and T2DM were assessed by generalized linear and logistic regression model, respectively, and their interaction associations on T2DM were quantified by using relative excess risk due to interaction (RERI), attributable proportion due to interaction (AP), and synergy index (S).

RESULTS

Positive associations of six obesity measures and four air pollutants with FBG levels and prevalent T2DM were observed. Obese participants measured by BMI plus high exposure to NO2, PM1, PM2.5 and PM10 were related to a 2.96-fold (2.66-3.29), 2.87-fold (2.58-3.20), 2.98-fold (2.67-3.32) and 3.01-fold (2.70-3.35) increased risk for prevalent T2DM, respectively; similarity of joint associations of the other obesity measures and air pollutants on T2DM were observed. The additive associations of different obesity measures and air pollutants with prevalent T2DM were further found.

CONCLUSIONS

The synergistic associations of obesity and air pollutants on FBG levels and prevalent T2DM were observed, indicating that obese participants were at high risk for prevalent T2DM in highly polluted rural regions.

Nonlaboratory-based risk assessment model for coronary heart disease screening: Model development and validation

BACKGROUND

Identifying groups at high risk of coronary heart disease (CHD) is important to reduce mortality due to CHD. Although machine learning methods have been introduced, many require laboratory or imaging parameters, which are not always readily available; thus, their wide applications are limited.

OBJECTIVE

The aim of this study was to develop and validate a simple, efficient, and joint machine learning model for identifying individuals at high risk of CHD using easily obtainable nonlaboratory parameters.

METHODS

This prospective study used data from the Henan Rural Cohort Study, which was conducted in rural areas of Henan Province, China, between July 2015 and September 2017. A joint machine learning model was developed by selecting and combining four base machine learning algorithms, including logistic regression (LR), artificial neural network (ANN), random forest (RF), and gradient boosting machine (GBM). We used readily accessible variables, including demographics, medical and family history, lifestyle and dietary factors, and anthropometric data, to inform the model. The model was also externally validated by a cohort of individuals from the Dongfeng-Tongji cohort study. Model discrimination was assessed by using the area under the receiver operating characteristic curve (AUC), and calibration was measured by using the Brier score (BS).

RESULTS

A total of 38 716 participants (mean [SD] age, 55.64[12.19] years; 23449[60.6%] female) from the Henan Rural Cohort Study and 17 958 subjects (mean [SD] age, 62.74 [7.59] years; 10,076 [56.1%] female) from the Dongfeng-Tongji cohort study were included in the analysis. Age, waist circumference, pulse pressure, heart rate, family history of CHD, education level, family history of type 2 diabetes mellitus (T2DM), and family history of dyslipidaemia were strongly associated with the development of CHD. In regard to internal validation, the model we built demonstrated good discrimination (AUC, 0.844 (95% CI 0.828-0.860)) and had acceptable calibration (BS, 0. 066). In regard to external validation, the model performed well with clearly useful discrimination (AUC, 0.792 (95% CI 0.774-0.810)) and robust calibration (BS, 0.069).

CONCLUSIONS

In this study, the novel and simple, machine learning-based model comprising readily accessible variables accurately identified individuals at high risk of CHD. This model has the potential to be widely applied for large-scale screening of CHD populations, especially in medical resource-constrained settings.

TRIAL REGISTRATION

The Henan Rural Cohort Study has been registered at the Chinese Clinical Trial Register. (Trial registration: ChiCTR-OOC-15006699. Registered 6 July 2015 - Retrospectively registered) http://www.chictr.org.cn/showproj.aspx?proj=11375.

Walking Environment and Obesity: A Gender-Specific Association Study in Shanghai

Walking environment is commonly cited as an element that reduces the risk of obesity. Many literatures have shown that the impact of walking environment on the incidence rate of obesity may vary across gender, but few studies have conducted in-depth investigations. The present study aimed to provide empirical evidence for a cross-sectional association between the built community environment and the incidence of obesity among male and female residents. Thus, we collected height and weight level of 1355 residents and constructed seven walking environment indicators around 54 communities. Also, BMI was calculated and categorized to define overweight and obesity. We used generalized estimation equation to evaluate the gender-specific association between walking environment on obesity based on a diverse population sample. The study showed that female residents who lived in neighborhoods with higher road sky view index (p = 0.033; OR = 0.002 [95% CI = 0.001-0.619]) and increased intersection density (p = 0.009; OR = 0.979 [95% CI = 0.963-0.995]) showed lower risk of increased BMI, but the advantage does not successfully radiate significant obesity consequences. In addition, the increased density of bus stops can also reduce the risk of obesity in women groups (p = 0.035; OR = 0.910 [95% CI = 0.836-0.990]). These findings suggest that women were more sensitive and were more likely to make different behavioral choices and physiological responses due to distinct walking environments. This provides useful evidence for future obesity prevention and urban planning.

Geographical distinctions of longevity indicators and their correlation with climatic factors in the area where most Chinese Yao are distributed

Longevity research is a hot topic in the health field. Considerable research focuses on longevity phenomenon in Bama Yao Autonomous County, which has a typical karst landform and is located in Southwest China. This study aims to illustrate the spatial feature of longevity indicators in other Yao areas, to analyze the correlation between climatic factors and longevity indicators, and to provide new clues and targets for further longevity studies. We collect and integrate population, climate, and terrain data into a spatial database. The main analysis methods include spatial autocorrelation, high/low clustering, and multiscale geographically weighted regression (MGWR). Two longevity clusters are identified in Guijiang River Basin (longevity index (LI%): 2.49 ± 0.63) and Liujiang River Basin (LI%: 2.13 ± 0.60). The spatial distribution of longevity indicators is autocorrelative (Moran's I = 0.652, p < 0.001) and clustered significantly (Z score = 4.268, p < 0.001). MGWR shows that the atmospheric pressure significantly affects the spatial distribution of LI% (estimate value (EV) =  - 0.566, p = 0.012), centenarity index (CI%) (EV =  - 0.425, p = 0.007), UC (EV =  - 0.502, p = 0.006), and CH (EV =  - 0.497, p = 0.007). Rainfall significantly affects the spatial distribution of LI% (EV = 0.300, p = 0.003) and CI% (EV =  - 0.191, p = 0.016). The spatial distribution of the main longevity indicators shows significant heterogeneity and autocorrelation, and they cluster in the Guijiang River and Liujiang River basins. Atmospheric pressure and rainfall may contribute to the longevity phenomenon through complex mechanisms. The longevity phenomenon in the Yao nationality in Guijiang River Basin requires further study to improve our understanding of the health effect of meteorological, environmental, and social conditions on longevity.

Plasma Fatty Acids, Not Dietary Fatty Acids, Associated with Obesity in Four Ethnic Minority Groups Unique to Southwest China: A Cross-Sectional Study

BACKGROUND

Dietary fatty acids (DFAs) and plasma fatty acids (PFAs) are linked to obesity. However, whether this association exists among ethnic minorities remains lacking. The present cross-sectional study was designed to investigate the correlation between DFAs, PFAs and obesity in four ethnic minority groups to Southwest China.

METHODS

A total of 166 obese people, and 166 normal-BMI subjects matched based on their age-, sex-, and ethnicity- were recruited from four different ethnic minority groups. DFAs were obtained through food frequency questionnaires. PFAs were assayed by GC/MS method. Binary and multiple regression analyses were performed to evaluate the correlation among DFAs, PFAs and obesity. Canonical correlation analysis (CCA) was conducted to assess the relationship between DFAs and PFAs.

RESULTS

FAs were found to be highest in the Naxi people and lowest in the Hani people. Multiple logistic regression analysis revealed that plasma C16:0 (OR = 1.310; 95% CI, 1.028-1.669) in the Hani people; plasma C20:3 n-6 (OR = 6.250; 95% CI, 1.224-31.927) and dietary C20:1 (OR = 9.231; 95% CI, 1.253-68.016) in the Wa people; plasma C18:0 (OR = 0.788; 95% CI, 0.681-0.912) in the Naxi people were seen to be independent predictive factors for obesity. CCA showed that DFAs were positively correlated with PFAs in the Naxi (r: 0.676; P < 0.05) and Bulang people (r: 0.897; P < 0.05), but there was no correlation in the Hani and Wa people.

CONCLUSION

In this study, PFAs but not DFAs were independently associated with obesity, and different among the four ethnic minorities.

Associations of mixture of air pollutants with estimated 10-year atherosclerotic cardiovascular disease risk modified by socio-economic status: The Henan Rural Cohort Study

BACKGROUND

Low socio-economic status (SES) and exposure to single-air pollutant relate to increased prevalent atherosclerotic cardiovascular diseases (ASCVD), however, interactive effect between SES and exposure to single- or multiple-air pollutants on high 10-year ASCVD risk remains unclear.

METHODS

A total of 31,162 individuals were derived from the Henan Rural Cohort Study. Concentrations of air pollutants (particulate matter with an aerodynamic diameter ≤ 1.0 μm (PM1), ≤2.5 μm (PM2.5) or ≤10 μm (PM10), nitrogen dioxide (NO2)) were assessed using a spatiotemporal model based on satellites data. Independent and joint associations of SES, single- and multiple- air pollutants with high 10-year ASCVD risk were evaluated using logistic regression models, quantile g-computation and structural equation models. The interactive effects of SES and exposure to single- or multiple air pollutants on high 10-year ASCVD risk were visualized by using Interaction plots.

RESULTS

Exposure to single air pollutant (PM1, PM2.5, PM10 or NO2) related to increased high 10-year ASCVD risk among individuals with low education level or personal average monthly income, compared to the ones with high education level or personal average monthly income. Furthermore, similar results of exposure to mixture of air pollutants with high 10-year ASCVD risk were observed. Positive interactive effects between low SES and exposure to high single air pollutant or the mixture of air pollutants on high 10-year ASCVD risk were observed.

CONCLUSION

Positive association of low SES with high 10-year ASCVD risk was amplified by exposure to high levels of single air pollutant or a mixture of air pollutants, implying that individuals with low SES may more susceptible to air pollution-related adverse health effect.

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

Although emerging researches have linked ambient fine particulate matter (PM2.5) to obesity, evidence from high-polluted regions is still lacking. We thus assessed the long-term impacts of PM2.5 on body mass index (BMI) and the risk of the prevalence of overweight/obesity (BMI≥25 kg/m2), by incorporating the well-established Prediction for Atherosclerotic Cardiovascular Disease Risk in China (China-PAR) project comprising 77,609 participants with satellite-based PM2.5 estimates at 1-km spatial resolution. The average of long-term PM2.5 level was 70.4 μg/m3, with the range of 32.1-94.2 μg/m3. Each 10 μg/m3 increment of PM2.5 was associated with 0.421 kg/m2 (95% confidence interval [CI]: 0.402, 0.439) and 13.5% (95% CI: 12.8%, 14.3%) increased BMI and overweight/obesity risk, respectively. Moreover, compared with the lowest quartile of PM2.5 (≤57.5 μg/m3), the relative risk of the prevalence of overweight/obesity from the highest quartile (>85.9 μg/m3) was 1.611 (95% CI: 1.566, 1.657). The exposure-response curve suggested a non-linear relationship between PM2.5 exposure and overweight/obesity. Besides, the association was modified by age, diabetes mellitus, hypertension and dyslipidemia status. Our study provides the evidence for the adverse impacts of long-term PM2.5 on BMI and overweight/obesity in China, and the findings are important for policy development on air quality, especially in severely polluted areas.

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.

Long-term exposure to low-level ambient air pollution and incidence of stroke and coronary heart disease: a pooled analysis of six European cohorts within the ELAPSE project

BACKGROUND

Long-term exposure to outdoor air pollution increases the risk of cardiovascular disease, but evidence is unclear on the health effects of exposure to pollutant concentrations lower than current EU and US standards and WHO guideline limits. Within the multicentre study Effects of Low-Level Air Pollution: A Study in Europe (ELAPSE), we investigated the associations of long-term exposures to fine particulate matter (PM2·5), nitrogen dioxide (NO2), black carbon, and warm-season ozone (O3) with the incidence of stroke and acute coronary heart disease.

METHODS

We did a pooled analysis of individual data from six population-based cohort studies within ELAPSE, from Sweden, Denmark, the Netherlands, and Germany (recruited 1992-2004), and harmonised individual and area-level variables between cohorts. Participants (all adults) were followed up until migration from the study area, death, or incident stroke or coronary heart disease, or end of follow-up (2011-15). Mean 2010 air pollution concentrations from centrally developed European-wide land use regression models were assigned to participants' baseline residential addresses. We used Cox proportional hazards models with increasing levels of covariate adjustment to investigate the association of air pollution exposure with incidence of stroke and coronary heart disease. We assessed the shape of the concentration-response function and did subset analyses of participants living at pollutant concentrations lower than predefined values.

FINDINGS

From the pooled ELAPSE cohorts, data on 137 148 participants were analysed in our fully adjusted model. During a median follow-up of 17·2 years (IQR 13·8-19·5), we observed 6950 incident events of stroke and 10 071 incident events of coronary heart disease. Incidence of stroke was associated with PM2·5 (hazard ratio 1·10 [95% CI 1·01-1·21] per 5 μg/m3 increase), NO2 (1·08 [1·04-1·12] per 10 μg/m3 increase), and black carbon (1·06 [1·02-1·10] per 0·5 10-5/m increase), whereas coronary heart disease incidence was only associated with NO2 (1·04 [1·01-1·07]). Warm-season O3 was not associated with an increase in either outcome. Concentration-response curves indicated no evidence of a threshold below which air pollutant concentrations are not harmful for cardiovascular health. Effect estimates for PM2·5 and NO2 remained elevated even when restricting analyses to participants exposed to pollutant concentrations lower than the EU limit values of 25 μg/m3 for PM2·5 and 40 μg/m3 for NO2.

INTERPRETATION

Long-term air pollution exposure was associated with incidence of stroke and coronary heart disease, even at pollutant concentrations lower than current limit values.

FUNDING

Health Effects Institute.

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.

Foetal 25-hydroxyvitamin D moderates the association of prenatal air pollution exposure with foetal glucolipid metabolism disorder and systemic inflammatory responses

BACKGROUND

Previous studies have indicated that systemic inflammation may play an important role in the association between air pollution exposure and glucolipid metabolism disorders, and vitamin D supplementation was beneficial in improving systemic inflammation and glucolipid metabolism. However, the role of foetal 25-hydroxyvitamin D (25(OH)D) and high-sensitivity C-reactive protein (hs-CRP) in the association between prenatal air pollution exposure and foetal glucolipid metabolism disorders is still not clear.

OBJECTIVE

To verify whether foetal 25(OH)D can improve glucolipid metabolism disorders induced by prenatal air pollution exposure by inhibiting the systemic inflammation.

METHODS

A total of 2,754 mother-newborn pairs were enrolled from three hospitals in Hefei city, China, between 2015 and 2019. We obtained air pollutants (PM_2.5, PM₁₀, SO₂, CO, and NO₂) data from the Hefei City Ecology and Environment Bureau. Cord blood biomarkers (25(OH)D, hs-CRP, C-peptide, HDL-C, LDL-C, TC, and TG) were measured.

RESULTS

We found that prenatal air pollution exposure was positively associated with foetal glucolipid metabolic index levels after adjusting for confounders. Additionally, an IQR increase in exposure to PM_2.5, PM₁₀, SO₂, and CO was associated with 20.0% (95% confidence interval (CI): 16.9, 23.6), 20.1% (16.8, 23.3), 22.9% (20.6, 25.3), and 16.7% (14.4, 19.0) higher cord blood hs-CRP levels, respectively, and an SD increase in hs-CRP was associated with 1.4% (0.1, 2.8), 2.2% (1.6, 2.9), 1.4% (0.9, 2.0), and 3.9% (2.8, 4.9) higher C-peptide, LDL-C, TC, and TG levels in the cord blood, respectively. However, there was a monotonic decrease in βs between cord blood 25(OH)D and biomarkers (P for trend < 0.001). Furthermore, mediation analysis revealed that the association between air pollution exposure and foetal glucolipid metabolic indexes mediated by hs-CRP and 25(OH)D was 19.35%. In stratified analyses, the significant negative association between cord blood 25(OH)D with foetal hs-CRP and glucolipid metabolic indexes was observed only at low-medium levels of air pollution exposure.

CONCLUSIONS

Prenatal air pollution exposure could damage foetal glucolipid metabolic function through systemic inflammation. High foetal 25(OH)D levels may improve foetal systemic inflammation and glucolipid metabolism at low-medium levels of prenatal air pollution exposure.

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.

Long-term exposure to air pollutants enhanced associations of obesity with blood pressure and hypertension

Although obesity reflected by BMI can enhance the association of air pollution with increase blood pressures (BP) and prevalent hypertension in susceptible population, there remains lack evidence on interactive effects of different obesity indices and air pollutants on BP and prevalent hypertension in rural adults. 39,259 individuals were recruited from the Henan Rural Cohort. Concentrations of air pollutants (PM1, PM2.5, PM10 and NO2) were evaluated by a spatio-temporal model based on satellites data. Independent associations of air pollutants and obesity reflected by BMI, WC, WHR, WHtR, BFP and VFI on BP indicators (SBP, DBP, MAP and PP) and prevalent hypertension were analyzed by linear regression and logistic regression models, respectively. Furthermore, their additive effects were quantified by RERI, AP and S. Six obesity indices enhanced the associations of four air pollutants and BP indicators. Individuals with high PM1 concentrations plus obesity classified by BMI, WC, WHR, WHtR, BFP and VFI had a 4.18-fold (95% CI: 3.86, 4.53), 3.58-fold (95% CI: 3.34, 3.84), 3.53-fold (95% CI: 3.28, 3.81), 4.02-fold (95% CI: 3.72, 4.35), 3.89-fold (95% CI: 3.59, 4.23), 3.87-fold (95% CI: 3.62, 4.14) increase in prevalent hypertension, respectively, compared to non-obese individuals with low PM1 concentrations; similar results were observed for combined effect of PM2.5, PM10 or NO2 and obesity indices on prevalent hypertension. The significant values of RERI, AP and S indicated additive effects of air pollutants and obesity indices on hypertension. Obesity amplified the effects of exposure to high levels of air pollutants on increased BP values and prevalent hypertension, implying that obese individuals may be susceptible to elevate BP and prevalent hypertension in relation to air pollution exposure. CLINICAL TRIAL REGISTRATION: The Henan Rural Cohort study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699, http://www.chictr.org.cn/showproj.aspx?proj=11375).

Independent and combined associations of solid-fuel use and smoking with obesity among rural Chinese adults

Although solid-fuel use or smoking is associated with obesity measured by body mass index (BMI), research on their interactive effects on general and central obesity is limited. Data of 20,140 individuals in the Henan Rural Cohort Study was examined the independent and combined associations of solid-fuel use and smoking with prevalent obesity, which was measured by BMI, waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), body fat percentage (BFP), and visceral fat index (VFI). Multiple adjusted logistic regression models showed that the OR (95% CI) of prevalent obesity measured by BMI associated with exposure to solid fuels alone or with smoking was 0.78 (0.70, 0.86) or 0.46 (0.32, 0.66), compared with neither smoking nor solid-fuel exposure. Similar results had been found in other obese anthropometric indices and in the results of linear regression analysis. The results indicated that solid-fuel use and smoking have a synergistic effect on reduction in obesity indices. The effects of household air pollution from solid-fuel use and smoking on obesity should be considered when exploring the influencing factors of obesity.

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.

Associations of Socioeconomic Status and Physical Activity With Obesity Measures in Rural Chinese Adults

Background: Although independent association of socioeconomic status (SES) or physical activity (PA) with obesity has been well-documented in urban settings, their independent and joint associations on obesity measures are limited in rural regions. Methods: Almost 38,000 (n = 37,922) individuals were included from the Henan Rural Cohort Study. The International Physical Activity Questionnaire (IPAQ) was used to evaluate PA. Obesity was reflected by body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), body fat percentage (BFP), and visceral fat index (VFI). The independent and interactive effects of SES and PA on obesity were analyzed by logistic regression models and generalized linear regression models, respectively. Results: Compared with high education level, the OR (95%CI) of obesity defined by BMI with low education level was 1.466 (1.337, 1.608), 1.064 (0.924, 1.225), and 1.853 (1.625, 2.114) in total population, men and women, respectively. Besides, the OR (95%CI) of obesity defined by BMI associated with per capita monthly income were 1.089 (1.015, 1.170), 1.192 (1.055, 1.347), 1.038 (0.951, 1.133) in total population, men and women, respectively. Similar results had been observed in other obesity measures. Negative interactive association of low education level and PA on obesity measures were observed only in women (all P < 0.05). Conclusions: This study suggests that women are more susceptible to obesity concerning low SES and that adequate PA may be a potential target for mitigating the negative effect of low SES on obesity in women. Clinical Trial Registration: The Henan Rural Cohort Study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699) http://www.chictr.org.cn/showproj.aspx?proj=11375.

Long-Term Exposure to Ambient PM2.5, Sunlight, and Obesity: A Nationwide Study in China

BACKGROUND

Accumulated researches revealed that both fine particulate matter (PM_2.5) and sunlight exposure may be a risk factor for obesity, while researches regarding the potential effect modification by sunlight exposure on the relationship between PM_2.5 and obesity are limited. We aim to investigate whether the effect of PM_2.5 on obesity is affected by sunlight exposure among the general population in China.

METHODS

A sample of 47,204 adults in China was included. Obesity and abdominal obesity were assessed based on body mass index, waist circumference and waist-to-hip ratio, respectively. The five-year exposure to PM_2.5 and sunlight were accessed using the multi-source satellite products and a geochemical transport model. The relationship between PM_2.5, sunshine duration, and the obesity or abdominal obesity risk was evaluated using the general additive model.

RESULTS

The proportion of obesity and abdominal obesity was 12.6% and 26.8%, respectively. Levels of long-term PM_2.5 ranged from 13.2 to 72.1 μg/m³ with the mean of 46.6 μg/m³. Each 10 μg/m³ rise in PM_2.5 was related to a higher obesity risk [OR 1.12 (95% CI 1.09-1.14)] and abdominal obesity [OR 1.10 (95% CI 1.07-1.13)]. The association between PM_2.5 and obesity varied according to sunshine duration, with the highest ORs of 1.56 (95% CI 1.28-1.91) for obesity and 1.66 (95% CI 1.34-2.07) for abdominal obesity in the bottom quartile of sunlight exposure (3.21-5.34 hours/day).

CONCLUSION

Long-term PM_2.5 effect on obesity risk among the general Chinese population are influenced by sunlight exposure. More attention might be paid to reduce the adverse impacts of exposure to air pollution under short sunshine duration conditions.

Air Pollutants Interaction and Gender Difference on Bone Mineral Density T-Score in Taiwanese Adults

Osteoporosis is defined as a systemic skeletal disease characterized by a reduction in bone mass and microarchitectural deterioration of bone tissue. Previous studies have reported associations between air pollution and lower bone mineral density; however, few studies have investigated the association between air pollution and osteoporosis. In this study, we combined two databases, the first including 5000 individuals registered in the Taiwan Biobank, and the second containing detailed daily data on air pollution. After multivariable adjustments, ozone (O3) (unstandardized coefficient β, 0.015; p = 0.008) was significantly positively associated with T-score, whereas carbon monoxide (CO) (unstandardized coefficient β, -0.809; p < 0.001), sulfur dioxide (SO2) (unstandardized coefficient β, -0.050; p = 0.005), nitric oxide (NO) (unstandardized coefficient β, -0.040; p < 0.001), nitrogen dioxide (NO2) (unstandardized coefficient β, -0.023; p < 0.001), and nitrogen oxide (NOx) (unstandardized coefficient β, -0.017; p < 0.001) were significantly negatively associated with T-score. The interactions between CO and NOx (p = 0.001) and SO2 and NO2 (p = 0.004) on T-score were statistically significant. An increase in exposure to CO, NO and NOx was associated with a faster decline in T-score in the female participants compared to the male participants. In addition, an increase in O3 was associated with a faster increase in T-score in the female participants compared to the male participants. In conclusion, the air pollutants CO, SO2, NO, NO2, and NOx were associated with osteoporosis. In addition, there were interaction and synergetic effects between CO and NOx and SO2 and NO2 on T-score. We also observed differences in the associations between air pollutants and T-score between the female and male participants.

Municipal Residence Level of Long-Term PM10 Exposure Associated with Obesity among Young Adults in Seoul, Korea

BACKGROUND

long-term effects of ambient pollutants used to be defined in cohort studies using biomarkers. Health effects on young adults from long-term exposure to particulate matters (PM) in residential ambiance have received less attention.

METHODS

using the data of population-representative aged 19-29 in Seoul, the relationship between obesity and PM10 levels of the living district was examined. We defined obesity as Body Mass Index (BMI) 25 kg/m2 and more. Survey logistic regression was conducted according to individual residence periods in the current municipality. Individual characteristics were adjusted overall and were age-specific; aged 19-24 and 25-29.

RESULTS

study population was 3655 (1680 (46%) men and 1933 aged 19-24 (52.9%)) individuals. Relationship between length of residence in municipalities with a greater level of PM10 from 2001-2005 and obesity was increased over the residing period; 10 years ≤ (odds ratio (OR) 1.071, 95% confidence interval (CI) 0.969-1.185), 15 years ≤ (1.120, 1.006-1.247), and 20 years ≤ (1.158, 1.034-1.297) in aged 19-29. Age-specific effects showed slight differences.

CONCLUSIONS

Although PM10 levels are currently decreasing, higher levels of PM10 exposure in the residential area during the earlier lifetime may contribute to obesity increase among young adults.