Traffic-related air pollution and childhood obesity in an Italian birth cohort

Effect modifications of parents' age at childbirth on association between ambient particulate matter and children obesity

BACKGROUND

There is limited evidence regarding the modifying effects of parents' age at childbirth on the relationship between air pollution and obesity in plateau areas. This study aimed to explore the association between particulate matter (PM) and child obesity, specifically investigating whether parents' age at childbirth could modify this relationship in the Tibetan plateau, China.

METHODS

Satellite-based random forest models were used to estimate the concentrations of PM2.5 (particulate matter with aerodynamic diameters ≤ 2.5 μm), PMc (particulate matter with aerodynamic diameters between 2.5 μm and 10 μm), and PM10 (particulate matter with aerodynamic diameters ≤ 10 μm). Linear and logistic regression models were employed to assess associations between PM exposure and obesity indicators, and effect estimates of PM across different particle sizes were compared.

RESULTS

The study comprised 2,015 children under five years old. Postnatal exposure to PM was positively associated with overweight and obesity (OWO), waist-to-hip ratio (WHR) and body mass index (BMI). Among these pollutants, PM10 exhibited the strongest association with BMI and OWO, whereas PMc showed the strongest association with WHR. An interquartile range (IQR) increase in PM2.5 (5.67 µg/m3), PMc (5.25 µg/m3), and PM10 (11.06 µg/m3) was positively associated with OWO (odd ratio [OR] for PM2.5 = 1.52, 95% confidence interval [CI] for PM2.5 = 1.24 to 1.85; OR for PMc = 1.50, 95% CI for PMc = 1.19 to 1.88; OR for PM10 = 1.56, 95% CI for PM10 = 1.25 to 1.96), respectively. Stratified analysis by parents' age at childbirth indicated that the effects of PM on obesity indicators were more pronounced in the advanced age group.

CONCLUSIONS

Long-term exposure to PM was positively associated with OWO, WHR, and BMI. Our findings also underscore the importance of examining the effects of ambient PM exposure on OWO, particularly in parents of advanced age at childbirth.

Impact of childhood exposure to traffic related air pollution on adult cardiometabolic health: Exploring the role of perceived stress

BACKGROUND

Little is known about how childhood exposure to traffic-related air pollution (TRAP) and stress interact to affect adults' cardiometabolic health. We examined this interaction and assessed the impact of over 10 years of childhood TRAP exposure on cardiometabolic health.

METHODS

From 2018 to 2023, 313 young adults from the Southern California Children's Health Study were enrolled in a follow-up assessment. Using CALINE4 line source dispersion model, average childhood TRAP exposures (from pregnancy to age 13) were estimated for nitrogen oxides (NOx) from all roads. Traffic density was calculated within a 300-m residential buffer. Cardiometabolic health was assessed in adulthood (mean age 24 ± 1.7) based on blood lipids (total cholesterol, high- and low-density lipoprotein [HDL, LDL], triglycerides), glucose metabolism (fasting glucose, fasting insulin, HbA1c), body composition (BMI, android/gynoid ratio [AG ratio], percent body fat), and blood pressure. A PDAY (Pathobiologic Determinants of Atherosclerosis in Youth) score was generated to evaluate overall cardiometabolic health. Participants' perceived stress was assessed in childhood and adulthood (ages 13 and 24 years, respectively).

RESULTS

Results of mixed effects linear models, adjusted for demographics and smoking status, suggested that each standard deviation increase in childhood exposure to traffic-related total NOx was associated with 0.62 increase in PDAY score (95% Confidence Interval [CI]:0.10,1.14), 0.09% increase in HbA1c (95%CI: 0.04, 0.15), 1.19% increase in percent body fat (95%CI: 0.18, 2.20), and 0.96 kg/m2 increase in BMI (0.11, 1.80) in adulthood. Among participants with higher childhood stress levels, we observed significant associations of traffic-related total NOx with total cholesterol, HDL, LDL, HbA1c, insulin, and BMI. None of these associations were significant among people with lower stress levels. We observed similar statistically significant associations of traffic density.

CONCLUSION

Long-term childhood exposure to TRAP in childhood may have lasting adverse impacts on cardiometabolic health, especially for children with higher stress levels.

Examining the Link between Air Quality (PM, SO2, NO2, PAHs) and Childhood Obesity: A Systematic Review

Background/Objectives: Childhood obesity has emerged as a global health concern with profound implications for long-term health outcomes. In recent years, there has been increasing interest in the potential role of environmental factors in the development of childhood obesity. This comprehensive review aims to elucidate the intricate relationship between various components of air pollution and childhood obesity. Methods: We systematically analyze the existing literature from the past 5 years to explore the mechanistic pathways linking air pollution, including particulate matter (PM), nitrogen oxides (NOx), sulfur dioxide (SO2), and polycyclic aromatic hydrocarbons (PAHs), to childhood obesity. This systematic review examines 33 epidemiological studies on the link between air pollution and childhood obesity, published from 1 January 2018, to 31 January 2024. Results: Studies from counties with low overall air pollution noticed only low to no impact of the exposure to childhood obesity, unlike studies from countries with higher levels of pollution, suggesting that the mitigation of air pollutants can reduce the chance of it being a negative factor for the development of obesity. This relationship was noticed for PM2.5, PM1, PM10, NOx, and SO2 but not for PAHs, which showed a negative effect on children's health across 10 out of 11 studies. Conclusions: This review underscores the need for interdisciplinary approaches to address both environmental and socio-economic determinants of childhood obesity. Efforts aimed at reducing air pollution levels and promoting healthy lifestyle behaviors are essential for safeguarding the health and well-being of children worldwide.

Use of lichens as bioindicators of contamination by agrochemicals and metals

The presence or absence of lichens serves as an indicator of the condition of an ecosystem and the degree to which it is contaminated by various agents, such as agrochemicals and metals. Evaluating the use of lichens as bioindicators of agrochemical contamination could provide a more comprehensive perspective of current contamination levels. Monitoring was conducted over a 4-month period in two study areas: one was a well-conserved area contaminated by metals, and the other was an area surrounded by agricultural crops contaminated by agrochemicals. Data on the presence and abundance of lichens in each study area were recorded at 10 monitoring points, a procedure that was repeated 16 times (every 15 days), and concentrations of heavy metals and "organophosphate" agrochemicals in the lichens collected were measured by means of Inductively Coupled Plasma Atomic Emission Spectroscopy (ICP-OES) and Gas Chromatography (GC), respectively. Generalized linear mixed models were used to assess abundance and richness, while general linear mixed models were used to attain Shannon diversity and Simpson dominance indices. Moreover, a multivariate analysis was performed in order to compare the lichen communities in both areas. The results indicated differences between the area contaminated by metals and that contaminated by agrochemicals in terms of abundance and Simpson's dominance index, while no differences were found in the case of the richness and diversity models. The PERMANOVA analysis additionally showed differences between the lichen communities in the two areas. The results also demonstrated that Canoparmelia caroliniana bioaccumulated metals in both areas. The levels of barium, cadmium, and sodium were higher in the area contaminated by metals, while concentrations of chromium and copper were higher in the area contaminated by agrochemicals. Finally, the concentrations of agrochemicals were higher in the area contaminated by agrochemicals and included toxic substances such as Methylparathion and Parathion, which are prohibited in Ecuador. In conclusion, this research underscores the importance of lichens as precise indicators of environmental health and contamination by agrochemicals and metals.

Independent and joint effects of neighborhood-level environmental and socioeconomic exposures on body mass index in early childhood: The environmental influences on child health outcomes (ECHO) cohort

Past studies support the hypothesis that the prenatal period influences childhood growth. However, few studies explore the joint effects of exposures that occur simultaneously during pregnancy. To explore the feasibility of using mixtures methods with neighborhood-level environmental exposures, we assessed the effects of multiple prenatal exposures on body mass index (BMI) from birth to age 24 months. We used data from two cohorts: Healthy Start (n = 977) and Maternal and Developmental Risks from Environmental and Social Stressors (MADRES; n = 303). BMI was measured at delivery and 6, 12, and 24 months and standardized as z-scores. We included variables for air pollutants, built and natural environments, food access, and neighborhood socioeconomic status (SES). We used two complementary statistical approaches: single-exposure linear regression and quantile-based g-computation. Models were fit separately for each cohort and time point and were adjusted for relevant covariates. Single-exposure models identified negative associations between NO2 and distance to parks and positive associations between low neighborhood SES and BMI z-scores for Healthy Start participants; for MADRES participants, we observed negative associations between O3 and distance to parks and BMI z-scores. G-computations models produced comparable results for each cohort: higher exposures were generally associated with lower BMI, although results were not significant. Results from the g-computation models, which do not require a priori knowledge of the direction of associations, indicated that the direction of associations between mixture components and BMI varied by cohort and time point. Our study highlights challenges in assessing mixtures effects at the neighborhood level and in harmonizing exposure data across cohorts. For example, geospatial data of neighborhood-level exposures may not fully capture the qualities that might influence health behavior. Studies aiming to harmonize geospatial data from different geographical regions should consider contextual factors when operationalizing exposure variables.

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.

Ambient air pollution and hypertensive disorders of pregnancy in Rome

BACKGROUND

Ambient air pollution has been associated with hypertensive disorders of pregnancy (HDP), but few studies rely on assessment of fine-scale variation in air quality, specific subtypes and multi-pollutant exposures.

AIM

To study the impact of long-term exposure to individual and mixture of air pollutants on all and specific subtypes of HDP.

METHODS

We obtained data from 130,470 liveborn singleton pregnacies in Rome during 2014-2019. Spatiotemporal land-use random-forest models at 1 km spatial resolution assigned to the maternal residential addresses were used to estimate the exposure to particulate matter (PM2.5 and PM10), nitrogen dioxide (NO2), and ozone (O3).

RESULTS

For PM2.5, PM10 and NO2, there was suggestive evidence of increased risk of preeclampsia (PE, n = 442), but no evidence of increased risk for all subtypes of HDP (n = 2297) and gestational hypertension (GH, n = 1901). For instance, an interquartile range of 7.0 μg/m3 increase in PM2.5 exposure during the first trimester of pregnancy was associated with an odds ratio (OR) of 1.06 (95% confidence interval: 0.81, 1.39) and 1.04 (0.92, 1.17) after adjustment for NO2 and the corresponding results for a 15.7 μg/m3 increase in NO2 after adjustment for PM2.5 were 1.11 (0.92, 1.34) for PE and 0.83 (0.76, 0.90) for HDP. Increased risks for HDP and GH were suggested for O3 in single-pollutant models and for PM after adjustment for NO2, but all other associations were stable or attenuated in two-pollutant models.

CONCLUSIONS

The results of our study suggest that PM2.5, PM10 and NO2 increases the risk of PE and that these effects are robust to adjustment for O3 while the increased risks for GH and HDP suggested for O3 attenuated after adjustment for PM or NO2. Additional studies are needed to evaluate the effects of source-specific component of PM on subtypes as well as all types of HDP which would help to target preventive actions.

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.

Longitudinal associations between ambient PM2.5 exposure and lipid levels in two Indian cities

Background

Exposure to ambient PM2.5 is known to affect lipid metabolism through systemic inflammation and oxidative stress. Evidence from developing countries, such as India with high levels of ambient PM2.5 and distinct lipid profiles, is sparse.

Methods

Longitudinal nonlinear mixed-effects analysis was conducted on >10,000 participants of Centre for cArdiometabolic Risk Reduction in South Asia (CARRS) cohort in Chennai and Delhi, India. We examined associations between 1-month and 1-year average ambient PM2.5 exposure derived from the spatiotemporal model and lipid levels (total cholesterol [TC], triglycerides [TRIG], high-density lipoprotein cholesterol [HDL-C], and low-density lipoprotein cholesterol [LDL-C]) measured longitudinally, adjusting for residential and neighborhood-level confounders.

Results

The mean annual exposure in Chennai and Delhi was 40 and 102 μg/m3 respectively. Elevated ambient PM2.5 levels were associated with an increase in LDL-C and TC at levels up to 100 µg/m3 in both cities and beyond 125 µg/m3 in Delhi. TRIG levels in Chennai increased until 40 µg/m3 for both short- and long-term exposures, then stabilized or declined, while in Delhi, there was a consistent rise with increasing annual exposures. HDL-C showed an increase in both cities against monthly average exposure. HDL-C decreased slightly in Chennai with an increase in long-term exposure, whereas it decreased beyond 130 µg/m3 in Delhi.

Conclusion

These findings demonstrate diverse associations between a wide range of ambient PM2.5 and lipid levels in an understudied South Asian population. Further research is needed to establish causality and develop targeted interventions to mitigate the impact of air pollution on lipid metabolism and cardiovascular health.

Causal effect of air pollution on the risk of cardiovascular and metabolic diseases and potential mediation by gut microbiota

BACKGROUND

Epidemiological studies have explored the relationship between air pollution and cardiovascular and metabolic diseases (CVMDs). Accumulating evidence has indicated that gut microbiota deeply affects the risk of CVMDs. However, the findings are controversial and the causality remains uncertain. To evaluate whether there is the causal association of four air pollutants with 19 CVMDs and the potential effect of gut microbiota on these relationships.

METHODS

Genetic instruments for particulate matter (PM) with aerodynamic diameter < 2.5 μm (PM2.5), <10 μm (PM10), PM2.5 absorbance, nitrogen oxides (NOx) and 211 gut microbiomes were screened. Univariable Mendelian randomization (UVMR) was used to estimate the causal effect of air pollutants on CVMDs in multiple MR methods. Additionally, to account for the phenotypic correlation among pollutant, the adjusted model was constructed using multivariable Mendelian randomization (MVMR) analysis to strength the reliability of the predicted associations. Finally, gut microbiome was assessed for the mediated effect on the associations of identified pollutants with CVMDs.

RESULTS

Causal relationships between NOx and angina, heart failure and hypercholesterolemia were observed in UVMR. After adjustment for air pollutants in MVMR models, the genetic correlations between PM2.5 and hypertension, type 2 diabetes mellitus (T2DM) and obesity remained significant and robust. In addition, genus-ruminococcaceae-UCG003 mediated 7.8 % of PM2.5-effect on T2DM.

CONCLUSIONS

This study firstly provided the genetic evidence linking air pollution to CVMDs and gut microbiota may mediate the association of PM2.5 with T2DM. Our findings highlight the significance of air quality in CVMDs risks and suggest the potential of modulating intestinal microbiota as novel therapeutic targets between air pollution and CVMDs.

Association of air pollution exposure with overweight or obesity in children and adolescents: A systematic review and meta-analysis

Childhood overweight and obesity is a global problem. 38 million children under five years old were reported as being overweight/obese in 2019. However, current evidence regarding the effects of air pollution on children weight status remains scarce and inconsistent. This study aimed to determine the association between air pollutants and the weight status of children and adolescents. Four databases were searched up to August 9, 2023. Adjusted merged odds ratios (ORs), regression coefficients (β), and their 95 % confidence intervals (95 % CIs) were calculated and pooled. A total of 27 studies were included. The results showed that air pollutants had adverse effects on the body weight of children and adolescents. Exposure to PM1, PM2.5, PMcoarse, and PM10 were associated with increased risk of overweight/obesity, with pooled ORs (95 % CI) of 1.23 (1.09, 1.40), 1.18 (1.10, 1.28), 1.04 (1.03, 1.05) and 1.11 (1.06, 1.17) per 10 μg/m3 increment, respectively. Individuals with higher exposure levels to NOX, O3, SO2 and CO (per 10 μg/m3 increment) were associated with 12 %, 6 %, 28 % and 1 % increased odds of being overweight/obese, respectively. With respect to the level of body mass index, the pooled β (95 % CIs) for each 10 μg/m3 increase in PM1, PM2.5, PM10, and NOX exposure were 0.15 (0.12, 0.18), 0.11 (0.06, 0.16), 0.07 (0.03, 0.10), and 0.03 (0.01, 0.04), respectively. PM1 has relatively strong adverse effects on body weight status. The subgroup analysis revealed a significantly increase in the risk of overweight/obesity when the concentrations of PM2.5, PM10, and NO2 exceeded 35 μg/m3, 50 μg/m3, and 40 μg/m3, respectively. Exposure to PM2.5, PM10 and NOX increased the risk of overweight/obesity, especially in Asia. This study provides evidence of the association between air pollution and being overweight/obese in children and adolescents.

The causal relationship between air pollution, obesity, and COVID-19 risk: a large-scale genetic correlation study

Objective

Observational evidence reported that air pollution is a significant risk element for numerous health problems, such as obesity and coronavirus disease 2019 (COVID-19), but their causal relationship is currently unknown. Our objective was to probe the causal relationship between air pollution, obesity, and COVID-19 and to explore whether obesity mediates this association.

Methods

We obtained instrumental variables strongly correlated to air pollutants [PM2.5, nitrogen dioxide (NO2) and nitrogen oxides (NOx)], 9 obesity-related traits (abdominal subcutaneous adipose tissue volume, waist-to-hip ratio, body mass index, hip circumference, waist circumference, obesity class 1-3, visceral adipose tissue volume), and COVID-19 phenotypes (susceptibility, hospitalization, severity) from public genome-wide association studies. We used clinical and genetic data from different public biological databases and performed analysis by two-sample and two-step Mendelian randomization.

Results

PM2.5 genetically correlated with 5 obesity-related traits, which obesity class 1 was most affected (beta = 0.38, 95% CI = 0.11 - 0.65, p = 6.31E-3). NO2 genetically correlated with 3 obesity-related traits, which obesity class 1 was also most affected (beta = 0.33, 95% CI = 0.055 - 0.61, p = 1.90E-2). NOx genetically correlated with 7 obesity-related traits, which obesity class 3 was most affected (beta = 1.16, 95% CI = 0.42-1.90, p = 2.10E-3). Almost all the obesity-related traits genetically increased the risks for COVID-19 phenotypes. Among them, body mass index, waist circumference, hip circumference, waist-to-hip ratio, and obesity class 1 and 2 mediated the effects of air pollutants on COVID-19 risks (p < 0.05). However, no direct causal relationship was observed between air pollution and COVID-19.

Conclusion

Our study suggested that exposure to heavy air pollutants causally increased risks for obesity. Besides, obesity causally increased the risks for COVID-19 phenotypes. Attention needs to be paid to weight status for the population who suffer from heavy air pollution, as they are more likely to be susceptible and vulnerable to COVID-19.

Changes in air pollution exposure after residential relocation and body mass index in children and adolescents: A natural experiment study

Air pollution exposure may affect child weight gain, but observational studies provide inconsistent evidence. Residential relocation can be leveraged as a natural experiment by studying changes in health outcomes after a sudden change in exposure within an individual. We aimed to evaluate whether changes in air pollution exposure due to residential relocation are associated with changes in body mass index (BMI) in children and adolescents in a natural experiment study. This population-based study included children and adolescents, between 2 and 17 years, who moved during 2011-2018 and were registered in the primary healthcare in Catalonia, Spain (N = 46,644). Outdoor air pollutants (nitrogen dioxides (NO2), particulate matter <10 μm (PM10) and <2.5 μm (PM2.5)) were estimated at residential census tract level before and after relocation; tertile cut-offs were used to define changes in exposure. Routinely measured weight and height were used to calculate age-sex-specific BMI z-scores. A minimum of 180 days after moving was considered to observe zBMI changes according to changes in exposure using linear fixed effects regression. The majority of participants (60-67% depending on the pollutant) moved to areas with similar levels of air pollution, 15-49% to less polluted, and 14-31% to more polluted areas. Moving to areas with more air pollution was associated with zBMI increases for all air pollutants (β NO2 = 0.10(95%CI 0.09; 0.12), β PM2.5 0.06(0.04; 0.07), β PM10 0.08(0.06; 0.10)). Moving to similar air pollution areas was associated with decreases in zBMI for all pollutants. No associations were found for those moving to less polluted areas. Associations with moving to more polluted areas were stronger in preschool- and primary school-ages. Associations did not differ by area deprivation strata. This large, natural experiment study suggests that increases in outdoor air pollution may be associated with child weight gain, supporting ongoing efforts to lower air pollution levels.

Causality of particulate matter on cardiovascular diseases and cardiovascular biomarkers

Background

Previous observational studies have shown that the prevalence of cardiovascular diseases (CVDs) is related to particulate matter (PM). However, given the methodological limitations of conventional observational research, it is difficult to identify causality conclusively. To explore the causality of PM on CVDs and cardiovascular biomarkers, we conducted a Mendelian randomization (MR) analysis.

Method

In this study, we obtained summary-level data for CVDs and cardiovascular biomarkers including atrial fibrillation (AF), heart failure (HF), myocardial infarction (MI), ischemic stroke (IS), stroke subtypes, body mass index (BMI), lipid traits, fasting glucose, fasting insulin, and blood pressure from several large genome-wide association studies (GWASs). Then we used two-sample MR to assess the causality of PM on CVDs and cardiovascular biomarkers, 16 single nucleotide polymorphisms (SNPs) for PM2.5 and 6 SNPs for PM10 were obtained from UK Biobank participants. Inverse variance weighting (IVW) analyses under the fixed effects model were used as the main analytical method to calculate MR Estimates, followed by multiple sensitivity analyses to confirm the robustness of the results.

Results

Our study revealed increases in PM2.5 concentration were significantly related to a higher risk of MI (odds ratio (OR), 2.578; 95% confidence interval (CI), 1.611-4.127; p = 7.920 × 10-5). Suggestive evidence was found between PM10 concentration and HF (OR, 2.015; 95% CI, 1.082-3.753; p = 0.027) and IS (OR, 2.279; 95% CI,1.099-4.723; p = 0.027). There was no evidence for an effect of PM concentration on other CVDs. Furthermore, PM2.5 concentration increases were significantly associated with increases in triglyceride (TG) (OR, 1.426; 95% CI, 1.133-1.795; p = 2.469 × 10-3) and decreases in high-density lipoprotein cholesterol (HDL-C) (OR, 0.779; 95% CI, 0.615-0.986; p = 0.038). The PM10 concentration increases were also closely related to the decreases in HDL-C (OR, 0.563; 95% CI, 0.366-0.865; p = 8.756 × 10-3). We observed no causal effect of PM on other cardiovascular biomarkers.

Conclusion

At the genetic level, our study suggested the causality of PM2.5 on MI, TG, as well HDL-C, and revealed the causality of PM10 on HF, IS, and HDL-C. Our findings indicated the need for continued improvements in air pollution abatement for CVDs prevention.

Body composition modify the association between ambient particulate matter and lung function among asthma patients

The effect of ambient PM10 and PM2.5 on lung function modified by body muscle and adipose tissue is not fully understood at present. Our aims were to investigate the association between seasonal average air pollutants and lung function in asthmatic patients modified by body composition indicators. In this cross-sectional study, we recruited 914 doctor-diagnosed asthmatic patients, and performed interaction and stratified analysis using the median values of total body muscle (TBM), total body fat (TBF), and percentage body fat (PBF) as well as body mass index (BMI) =25 as the cutoff points of the high/low body composition groups. The adjusted R2 values of the developed LUR models of PM2.5 and PM10 were 91.4% and 90.5% and also verified by cross-validation, respectively. After adjusting for confounding factors, we found that TBM significantly modified the association between PM10 and lung function among asthma patients (interaction P value <0.05). In the low TBM group, seasonal average concentrations of PM10 estimated by the LUR model increased by 10 μg/m3, and negative associations with lung function indicators were observed. For obese patients with BMI>25 and high TBF, the increase in PM10 was associated with the decrease in lung function. The asthma patients with obesity and low total body muscle were more susceptible to adverse effects of PM10 on lung function.

Association of air pollution exposure during gestational and the first year of life with physical growth in preschoolers

This study explored the association of exposure to air pollutants during gestational and the first year of life with physical growth in preschoolers. The linear and logistic regression models were used to estimate the associations between air pollution and childhood growth. After adjusting for confounders, z-scores of body mass index (zBMI, and 95% confidence intervals, 95%CI) increased by 1.164(1.054,1.285), 1.136(1.050,1.228) and 1.165(1.041,1.303), associated with per interquartile range (IQR) increase in NO₂ (nitrogen dioxide), PM_2.5 and PM₁₀ (particulate matter with aerodynamic diameters ≤2.5 μm and 10 μm) during gestational, respectively. The odds ratios (and 95%CI) of childhood overweight/obesity associated with per IQR increase in NO₂, PM_2.5 and PM₁₀ during gestational were 1.425(1.168,1.737), 1.255(1.087,1.450) and 1.332(1.104,1.605). Positive associations were found between air pollution during the first year of life and zBMI or overweight/obesity. Our findings suggest exposure to air pollution were associated with childhood growth, and improving air quality is beneficial for childhood growth.

Long-term effect of submicronic particulate matter (PM1) and intermodal particulate matter (PM1-2.5) on incident dyslipidemia in China: A nationwide 5-year cohort study

BACKGROUND

There is insufficient evidence of associations between incident dyslipidemia with PM₁ (submicronic particulate matter) and PM_1-2.5 (intermodal particulate matter) in the middle-aged and elderly. We aimed to determine the long-term effects of PM₁ and PM_1-2.5 on incident dyslipidemia respectively.

METHODS

We studied 6976 individuals aged ≥45 from the China Health and Retirement Longitudinal Study from 2013 to 2018. The concentrations of particular matter (PM) for every individual's address were evaluated using a satellite-based spatiotemporal model. Dyslipidemia was evaluated by self-reported. The generalized linear mixed model was applied to quantify the correlations between PM and incident dyslipidemia.

RESULTS

After a 5-year follow-up, 333 (4.77%) participants developed dyslipidemia. Per 10 μg/m³ uptick in four-year average concentrations of PMs (PM₁ and PM_1-2.5) corresponded to 1.11 [95% confidence interval (CI): 1.01-1.23)] and 1.23 (95% CI: 1.06-1.43) fold risks of incident dyslipidemia. Nonlinear exposure-response curves were observed between PM and incident dyslipidemia. The effect size of PM₁ on incident dyslipidemia was slightly higher in males [1.14 (95% CI: 0.98-1.32) vs. 1.04 (95% CI: 0.89-1.21)], the elderly [1.23 (95% CI: 1.04-1.45) vs. 1.03 (95% CI: 0.91-1.17)], people with less than primary school education [1.12 (95% CI: 0.94-1.33) vs. 1.08 (95% CI: 0.94-1.23)], and solid cooking fuel users [1.17 (95% CI: 1.00-1.36) vs. 1.06 (95% CI: 0.93-1.21)], however, the difference was not statistically significant (Z = -0.82, P = 0.413; Z = -1.66, P = 0.097; Z = 0.32, P = 0.752; Z = -0.89, P = 0.372).

CONCLUSIONS

Long-term exposure to PM₁ and PM_1-2.5 were linked with an increased morbidity of dyslipidemia in the middle-aged and elderly population. Males, the elderly, and solid cooking fuel users had higher risk. Further studies would be warranted to establish an accurate reference value of PM to mitigate growing dyslipidemia.

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

BACKGROUND

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

METHODS

Using data from the China Health and Retirement Longitudinal Study (2011-2015), we conducted a nationwide cohort study of 7424 adults. We measured overweight/obesity according to body mass index. We used annual average ground-level air pollutants, including ozone (O₃), nitrogen dioxide (NO2), and particulate matter with aerodynamic diameters ≤2.5 μm (PM_2.5), to demonstrate air pollution levels. We used the Normalized difference vegetation index (NDVI) to measure greenness exposure. We used time-varying Cox proportional hazard regression models to analyze the connections among air pollution, greenness, and the development of overweight/obesity in middle-aged and older adults in China. We also conducted mediation analyses to examine the mediating effects of air pollution.

RESULTS

We found that lower risk of overweight/obesity was associated with more greenness exposure and lower levels of air pollution. We identified that an interquartile increment in NDVI was correlated with a lower hazard ratio (HR) of becoming overweight or obese (HR = 0.806, 95% confidence interval [CI]: 0.754-0.862). Although a 10 μg/m³ increase in PM_2.5 and NO₂ was correlated with higher risks (HR = 1.049, 95% CI = 1.022-1.075, HR = 1.376, 95% CI = 1.264-1.499). Effects of PM_2.5 on being overweight or obese were stronger in men than in women. According to the mediation analysis, PM_2.5 and NO₂ mediated 8.85% and 19.22% of the association between greenness and being overweight or obese.

CONCLUSIONS

An increased risk of being overweight or obese in middle-aged and older adults in China was associated with long-term exposure to higher levels of PM_2.5 and NO₂. This risk was reduced through NDVI exposure, and the associations were partially mediated by air pollutants. To verify these findings, fine-scale studies are needed.

Associations of Air Pollution and Serum Biomarker Abnormalities in Individuals with Hemodialysis-Dependent Kidney Failure

BACKGROUND

Ambient particles with a median aerodynamic diameter of <2.5 µm (PM2.5) is a ubiquitous air pollutant with established adverse health consequences. While postulated to promote a systemic inflammatory response, limited studies have demonstrated changes in serum biomarkers related to PM2.5 exposure. We aim to examine associations between short-term PM2.5 exposure and commonly measured biomarkers known to be affected by inflammation among patients receiving maintenance in-center hemodialysis.

METHODS

We conducted a retrospective open cohort study from January 1, 2008, to December 31, 2014. Adult hemodialysis patients were identified from the United States Renal Data System and linked at the patient level to laboratory data from a large dialysis organization. Daily ambient PM2.5 was estimated on a 1-km grid and assigned to cohort patients based on the ZIP codes of dialysis clinics. Serum albumin, serum ferritin, transferrin saturation (TSAT), and serum hemoglobin were ascertained from the dialysis provider organization database. Mixed-effect models were used to assess the changes in biomarker levels associated with PM2.5 exposure.

RESULTS

The final cohort included 173,697 hemodialysis patients. Overall, the daily ZIP-level ambient PM2.5 averages were 8.4-8.5 µg/m3. A 10-µg/m3 increase in same-day ambient PM2.5 exposure was associated with higher relative risks of lower albumin (relative risk [RR], 1.01; 95% confidence interval [95% CI], 1.01 to 1.02) and lower hemoglobin (RR, 1.02; 95% CI, 1.01 to 1.03). Associations of same-day ambient PM2.5 exposure and higher ferritin and lower TSAT did not reach statistical significance.

CONCLUSIONS

Short-term PM2.5 exposure was associated with lower serum hemoglobin and albumin among patients receiving in-center hemodialysis. These findings lend support to the role of inflammation in PM2.5 exposure-outcome associations.

Multi-omics reveals hypertrophy of adipose tissue and lipid metabolism disorder via mitochondria in young mice under real-ambient exposure to air pollution

Air pollution has become one of the most serious health risks as a result of industrialization, especially in developing countries. More attention has been drawn to the relationship between obesity/overweight and fine particulate matter (PM2.5). Especially for susceptible populations, the impact of air pollution on children and adolescents has attracted more public attentions. However, the detailed underlying mechanism influencing obesity or overweight under PM2.5 exposure is still unknown. Therefore, young mice were exposed to PM2.5 using the real-ambient exposure system that we previously established in Shijiazhuang city. Compared with the traditionally concentrated air particle (CAP) system, our real-ambient exposure system provides similar PM2.5 concentrations and characteristics as outdoor ambient air and minimizes the influence of external interfering factors. After 8 weeks of exposure to PM2.5, the weight of gonadal white adipose tissue (gWAT) and subcutaneous white adipose tissue (sWAT) was considerably increased, accompanied by a significantly enlarged size of adipocytes in sWAT. Importantly, multiomics analysis indicated altered metabolites involved in the lipid metabolism pathway, and transcriptomic analysis revealed notably changed signaling pathways related to fatty acid metabolism. Moreover, the mtDNA copy number, mitochondrial activity and fatty acid oxidation (FAO) were increased in the liver under PM2.5 exposure. Taken together, our research investigated the hypotrophy of adipose tissue in young mice, supported an imbalance in lipid metabolism based on multiomics analysis, and revealed disordered mitochondrial function under PM2.5 exposure. Our study provided new insight into the hazardous effects of air pollution, and extended our understanding on the underlying mechanism.

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

PURPOSE

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

METHODS

This was an ecological cross-sectional study using data from the 2017 wave of the Encuesta Nacional de Salud Española (ENSE), a nationally representative survey of the Spanish young and adult population. The final sample included 4378 young Spanish people (51.0% boys). The weight (kg) and height (cm) of the study participants were proxy-reported by parents or guardians. Excess weight was determined according to the age- and sex-criteria of the International Obesity Task Force. The PM_2.5 level was calculated as the annual monitoring data indicator for 2017 among the different regions in Spain. Logistic regression models were performed to estimate the relationships between PM_2.5 and weight.

RESULTS

Compared to young people located in regions with low levels of PM_2.5, those reporting greater odds for excess weight were found in regions with medium PM_2.5 (OR = 1.23; 95% CI, 1.02-1.49) and high PM_2.5 (OR = 1.35; 95% CI, 1.11-1.64) after adjusting for several sociodemographic, lifestyle and environmental covariates.

CONCLUSIONS

The prevalence of excess weight in young people was positively associated with PM_2.5 levels in Spain. This finding supports the hypothesis that air pollution exposure can result in excess weight in the young population, which, in turn, might lead to the development of metabolic disorders. From a socioecological perspective, a practical need to take environmental factors into consideration is important to address unhealthy weight in Spanish young people.

Air Pollution: Another Threat to HDL Function

Epidemiological studies have consistently demonstrated a positive association between exposure to air pollutants and the incidence of cardiovascular disease, with the strongest evidence for particles with a diameter < 2.5 μm (PM2.5). Therefore, air pollution has been included among the modifiable risk factor for cardiovascular outcomes as cardiovascular mortality, acute coronary syndrome, stroke, heart failure, and arrhythmias. Interestingly, the adverse effects of air pollution are more pronounced at higher levels of exposure but were also shown in countries with low levels of air pollution, indicating no apparent safe threshold. It is generally believed that exposure to air pollution in the long-term can accelerate atherosclerosis progression by promoting dyslipidemia, hypertension, and other metabolic disorders due to systemic inflammation and oxidative stress. Regarding high density lipoproteins (HDL), the impact of air pollution on plasma HDL-cholesterol levels is still debated, but there is accumulating evidence that HDL function can be impaired. In particular, the exposure to air pollution has been variably associated with a reduction in their cholesterol efflux capacity, antioxidant and anti-inflammatory potential, and ability to promote the release of nitric oxide. Further studies are needed to fully address the impact of various air pollutants on HDL functions and to elucidate the mechanisms responsible for HDL dysfunction.

Is city-level travel time by car associated with individual obesity or diabetes in Latin American cities? Evidence from 178 cities in the SALURBAL project

There is growing evidence that longer travel time by private car poses physical and mental risks. Individual-level obesity and diabetes, two of the main public health challenges in low- and middle-income contexts, could be associated to city-level travel times by car. We used individual obesity and diabetes data from national health surveys from individuals in 178 Latin American cities, compiled and harmonized by the SALURBAL project. We calculated city-level travel times by car using the Google Maps Distance Matrix API. We estimated associations between peak hour city-level travel time by car and obesity and diabetes using multilevel logistic regression models, while adjusting for individual characteristics and other city-level covariates. In our study we did not observe a relationship between city-level peak-hour travel time by car and individual obesity and diabetes, as reported in previous research for individual time spent in vehicles in high-income settings. Our results suggest that this relationship may be more complex in Latin America compared to other settings, especially considering that cities in the region are characterized by high degrees of population density and compactness and by a higher prevalence of walking and public transportation use.

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

AIMS

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Using non-parametric Bayes shrinkage to assess relationships between multiple environmental and social stressors and neonatal size and body composition in the Healthy Start cohort

BACKGROUND

Both environmental and social factors have been linked to birth weight and adiposity at birth, but few studies consider the effects of exposure mixtures. Our objective was to identify which components of a mixture of neighborhood-level environmental and social exposures were driving associations with birth weight and adiposity at birth in the Healthy Start cohort.

METHODS

Exposures were assessed at the census tract level and included air pollution, built environment characteristics, and socioeconomic status. Prenatal exposures were assigned based on address at enrollment. Birth weight was measured at delivery and adiposity was measured using air displacement plethysmography within three days. We used non-parametric Bayes shrinkage (NPB) to identify exposures that were associated with our outcomes of interest. NPB models were compared to single-predictor linear regression. We also included generalized additive models (GAM) to assess nonlinear relationships. All regression models were adjusted for individual-level covariates, including maternal age, pre-pregnancy BMI, and smoking.

RESULTS

Results from NPB models showed most exposures were negatively associated with birth weight, though credible intervals were wide and generally contained zero. However, the NPB model identified an interaction between ozone and temperature on birth weight, and the GAM suggested potential non-linear relationships. For associations between ozone or temperature with birth weight, we observed effect modification by maternal race/ethnicity, where effects were stronger for mothers who identified as a race or ethnicity other than non-Hispanic White. No associations with adiposity at birth were observed.

CONCLUSIONS

NPB identified prenatal exposures to ozone and temperature as predictors of birth weight, and mothers who identify as a race or ethnicity other than non-Hispanic White might be disproportionately impacted. However, NPB models may have limited applicability when non-linear effects are present. Future work should consider a two-stage approach where NPB is used to reduce dimensionality and alternative approaches examine non-linear effects.

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 long-term PM2.5 exposure on metabolic syndrome among adults and elderly in Guangdong, China

BACKGROUND

We aimed to explore the association between long-term exposure to particulate matter ≤ 2.5 µm (PM_2.5) and metabolic syndrome (MetS) and its components including fasting blood glucose (FBG), blood pressure, triglyceride (TG), high-density lipoprotein cholesterol (HDL-c) and waist circumference among adults and elderly in south China.

METHODS

We surveyed 6628 participants in the chronic disease and risk factors surveillance conducted in 14 districts of Guangdong province in 2015. MetS was defined based on the recommendation by the Joint Interim Societies' criteria. We used the spatiotemporal land-use regression (LUR) model to estimate the two-year average exposure of ambient air pollutants (PM_2.5, PM₁₀, SO₂, NO₂, and O₃) at individual levels. We recorded other covariates by using a structured questionnaire. Generalized linear mixed model was used for analysis.

RESULTS

A 10-μg/m³ increase in the two-year mean PM_2.5 exposure was associated with a higher risk of developing MetS [odd ratio (OR): 1.17, 95% confidence interval (CI): 1.01, 1.35], increased risk of fasting blood glucose level. (OR: 1.18, 95% CI: 1.02, 1.36), and hypertriglyceridemia (OR: 1.36, 95% CI: 1.18, 1.58) in the adjusted/unadjusted models (all P < 0.05). We found significant interaction between PM_2.5 and the region, exercise on the high TG levels, and an interaction with the region, age, exercise and grain consumption on FBG (P _interaction < 0.05).

CONCLUSIONS

Long-term exposure to PM_2.5 was associated with MetS, dyslipidemia and FBG impairment. Efforts should be made for environment improvement to reduce the burden of MetS-associated non-communicable disease.

Health Outcomes in Children Associated with Prenatal and Early-Life Exposures to Air Pollution: A Narrative Review

(1) Background: The developmental origins of health and disease (DOHaD) hypothesis links adverse fetal exposures with developmental mal-adaptations and morbidity later in life. Short- and long-term exposures to air pollutants are known contributors to health outcomes; however, the potential for developmental health effects of air pollution exposures during gestation or early-childhood have yet to be reviewed and synthesized from a DOHaD lens. The objective of this study is to summarize the literature on cardiovascular and metabolic, respiratory, allergic, and neuropsychological health outcomes, from prenatal development through early childhood, associated with early-life exposures to outdoor air pollutants, including traffic-related and wildfire-generated air pollutants. (2) Methods: We conducted a search using PubMed and the references of articles previously known to the authors. We selected papers that investigated health outcomes during fetal or childhood development in association with early-life ambient or source-specific air pollution exposure. (3) Results: The current literature reports that prenatal and early-childhood exposures to ambient and traffic-related air pollutants are associated with a range of adverse outcomes in early life, including cardiovascular and metabolic, respiratory and allergic, and neurodevelopmental outcomes. Very few studies have investigated associations between wildfire-related air pollution exposure and health outcomes during prenatal, postnatal, or childhood development. (4) Conclusion: Evidence from January 2000 to January 2022 supports a role for prenatal and early-childhood air pollution exposures adversely affecting health outcomes during development. Future studies are needed to identify both detrimental air pollutants from the exposure mixture and critical exposure time periods, investigate emerging exposure sources such as wildfire, and develop feasible interventional tools.

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

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

Traffic-related air pollution, biomarkers of metabolic dysfunction, oxidative stress, and CC16 in children

BACKGROUND

Previous research has revealed links between air pollution exposure and metabolic syndrome in adults; however, these associations are less explored in children.

OBJECTIVE

This study aims to investigate the association between traffic-related air pollutants (TRAP) and biomarkers of metabolic dysregulation, oxidative stress, and lung epithelial damage in children.

METHODS

We conducted cross-sectional analyses in a sample of predominantly Latinx, low-income children (n = 218) to examine associations between air pollutants (nitrogen dioxide (NO₂), nitrogen oxides (NO_x), elemental carbon, polycyclic aromatic hydrocarbons, carbon monoxide (CO), fine particulates (PM_2.5)) and biomarkers of metabolic function (high-density lipoprotein (HDL), hemoglobin A1c (HbA1c), oxidative stress (8-isoprostane), and lung epithelial damage (club cell protein 16 (CC16)).

RESULTS

HDL cholesterol showed an inverse association with NO₂ and NO_x, with the strongest relationship between HDL and 3-month exposure to NO₂ (-15.4 mg/dL per IQR increase in 3-month NO₂, 95% CI = -27.4, -3.4). 8-isoprostane showed a consistent pattern of increasing values with 1-day and 1-week exposure across all pollutants. Non-significant increases in % HbA1c were found during 1-month time frames and decreasing CC16 in 3-month exposure time frames.

CONCLUSION

Our results suggest that TRAP is significantly associated with decreased HDL cholesterol in longer-term time frames and elevated 8-isoprostane in shorter-term time frames. TRAP could have the potential to influence lifelong metabolic patterns, through metabolic effects in childhood.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Obesity II: Establishing causal links between chemical exposures and obesity

Obesity is a multifactorial disease with both genetic and environmental components. The prevailing view is that obesity results from an imbalance between energy intake and expenditure caused by overeating and insufficient exercise. We describe another environmental element that can alter the balance between energy intake and energy expenditure: obesogens. Obesogens are a subset of environmental chemicals that act as endocrine disruptors affecting metabolic endpoints. The obesogen hypothesis posits that exposure to endocrine disruptors and other chemicals can alter the development and function of the adipose tissue, liver, pancreas, gastrointestinal tract, and brain, thus changing the set point for control of metabolism. Obesogens can determine how much food is needed to maintain homeostasis and thereby increase the susceptibility to obesity. The most sensitive time for obesogen action is in utero and early childhood, in part via epigenetic programming that can be transmitted to future generations. This review explores the evidence supporting the obesogen hypothesis and highlights knowledge gaps that have prevented widespread acceptance as a contributor to the obesity pandemic. Critically, the obesogen hypothesis changes the narrative from curing obesity to preventing obesity.

The Impact of PM2.5 on the Growth Curves of Children's Obesity Indexes: A Prospective Cohort Study

Aims

To explore the effect of long-term exposure to particulate matter with an aerodynamic diameter of 2.5 μm or less (PM2.5) on childhood obesity based on a cohort study in Chongqing.

Methods

A total of 4,284 children aged 6-8 years at baseline were enrolled from the Chongqing Children Health Cohort in 2014-2015 and were followed up in 2019. A stratified cluster sampling was applied to select the participants. A Mixed-effects linear regression model was used to examine the effect of long-term exposure to PM2.5 on the growth curve of obesity indicators [including body mass index (BMI), BMI Z-score (BMIz), and waist-to-height ratio (WHtR)]. A mixed-effects logistic regression model was used to study the dose relationship between PM2.5 exposure and the risk of obesity indicators.

Results

A higher level of accumulating exposure to PM2.5 was associated with an increased childhood obesity index, and the effect was the most significant for WHtR than BMI and BMIz. This effect was more pronounced in boys than in girls except for WHtR, and it was the most significant under the PM2.5 exposure period from pregnancy to 6 years old. Compared the annual average PM2.5 exposure level of <60 μg/m³, the WHtR and BMI were increased by 0.019 [(95% CIs): 0.014, 0.024] and 0.326 [(95% CIs): 0.037, 0.616] Kg/m² for participants living with the PM2.5 exposure level of 70-75 μg/m³, respectively. For every 5 μg/m³ increase in PM2.5 levels (from pregnancy to 6 years old), the risk of central obesity was increased by 1.26 {odds ratio [OR] (95% CIs): 1.26 (1.16, 1.37), p < 0.001} times.

Conclusions

This study confirmed a dose-response relationship between PM2.5 exposure and childhood obesity, especially central obesity, suggesting that controlling ambient air pollution can prevent the occurrence of obesity in children and adolescents.

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

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

Near-roadway air pollution, immune cells and adipokines among obese young adults

BACKGROUND

Air pollution has been associated with metabolic disease and obesity. Adipokines are potential mediators of these effects, but studies of air pollution-adipokine relationships are inconclusive. Macrophage and T cells in adipose tissue (AT) and blood modulate inflammation; however, the role of immune cells in air pollution-induced dysregulation of adipokines has not been studied. We examined the association between air pollution exposure and circulating and AT adipokine concentrations, and whether these relationships were modified by macrophage and T cell numbers in the blood and AT.

METHODS

Fasting blood and abdominal subcutaneous AT biopsies were collected from 30 overweight/obese 18-26 year-old volunteers. Flow cytometry was used to quantify T effector (Teff, inflammatory) and regulatory (Treg, anti-inflammatory) lymphocytes and M1 [inflammatory] and M2 [anti-inflammatory]) macrophage cell number. Serum and AT leptin and adiponectin were measured using enzyme-linked immunosorbent assay (ELISA). Exposure to near-roadway air pollution (NRAP) from freeway and non-freeway vehicular sources and to regional particulate matter, nitrogen dioxide and ozone were estimated for the year prior to biopsy, based on participants' residential addresses. Linear regression models were used to examine the association between air pollution exposures and adipokines and to evaluate effect modification by immune cell counts.

RESULTS

An interquartile increase in non-freeway NRAP exposure during 1 year prior to biopsy was associated with higher leptin levels in both serum [31.7% (95% CI: 10.4, 52.9%)] and AT [19.4% (2.2, 36.6%)]. Non-freeway NRAP exposure effect estimates were greater among participants with greater than median Teff/Treg ratio and M1/M2 ratio in blood, and with greater M1 counts in AT. No adipokine associations with regional air pollutants were found.

DISCUSSION

Our results suggest that NRAP may increase serum leptin levels in obese young adults, and this association may be promoted in a pro-inflammatory immune cell environment in blood and AT.

The built environment as determinant of childhood obesity: A systematic literature review

We evaluated the epidemiological evidence on the built environment and its link to childhood obesity, focusing on environmental factors such as traffic noise and air pollution, as well as physical factors potentially driving obesity-related behaviors, such as neighborhood walkability and availability and accessibility of parks and playgrounds. Eligible studies were (i) conducted on human children below the age of 18 years, (ii) focused on body size measurements in childhood, (iii) examined at least one built environment characteristic, (iv) reported effect sizes and associated confidence intervals, and (v) were published in English language. A z test, as alternative to the meta-analysis, was used to quantify associations due to heterogeneity in exposure and outcome definition. We found strong evidence for an association of traffic-related air pollution (nitrogen dioxide and nitrogen oxides exposure, p < 0.001) and built environment characteristics supportive of walking (street intersection density, p < 0.01 and access to parks, p < 0.001) with childhood obesity. We identified a lack of studies that account for interactions between different built environment exposures or verify the role and mechanism of important effect modifiers such as age.

Dynamic Linkages Among Energy Consumption, Environment and Health Sustainability: Evidence from the Different Income Level Countries

Environment pollution was closely related to human health. The energy consumption is one of the important sources of environmental pollution in the development of economy. This paper used undesirable two-stage meta-frontier DDF (distance difference function) data envelopment analysis model to explore the impact of environment pollutants from energy consumption on the mortality of children and the aged, survival rate of 65 years old and health expenditure efficiency in 27 high income countries, 21 upper middle income countries, and 16 lower middle income countries from 2010 to 2014. High income countries had higher efficiency of energy and health than middle income countries in general. But whether in high income or middle income countries, the efficiency of non-renewable energy is higher than renewable energy. There was much room for both high income countries and middle income countries to improve renewable energy efficiency. Besides, middle income countries need to improve the efficiency of non-renewable energy and reduce pollutant emissions per unit of GDP. In terms of health efficiency, upper middle income countries performed worse than lower income countries. This phenomenon might indicate there was a U-shaped relationship between health efficiency and income level. Upper income countries should pay more attention to the environmental and health problems and cross the U-shaped turning point. The contribution of this article was to consider the heterogeneous performance of energy efficiency, environmental efficiency, and health efficiency under the influence of income level differences, and found that there might be a U-shaped relationship between health efficiency and income level.

Ambient air pollution and endocrinologic disorders in childhood

Ambient air pollution has been proposed as an important environmental risk factor that increases global mortality and morbidity. Over the past decade, several human and animal studies have reported an association between exposure to air pollution and altered metabolic and endocrine systems in children. However, the results for these studies were mixed and inconclusive and did not demonstrate causality because different outcomes were observed due to different study designs, exposure periods, and methodologies for exposure measurements. Current proposed mechanisms include altered immune response, oxidative stress, neuroinflammation, inadequate placental development, and epigenetic modulation. In this review, we summarized the results of previous pediatric studies that reported effects of prenatal and postnatal air pollution exposure on childhood type 1 diabetes mellitus, obesity, insulin resistance, thyroid dysfunction, and timing of pubertal onset, along with underlying related mechanisms.

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

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

PARTICIPANT CONSENT

Obtained.

ETHICS APPROVAL

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

COMPETING INTERESTS

The authors declare no competing financial interests.

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

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

Associations of Particulate Matter Sizes and Chemical Constituents with Blood Lipids: A Panel Study in Guangzhou, China

Existing evidence is scarce concerning the various effects of different PM sizes and chemical constituents on blood lipids. A panel study that involved 88 healthy college students with five repeated measurements (440 blood samples in total) was performed. We measured mass concentrations of particulate matter with diameters ≤ 2.5 μm (PM_2.5), ≤1.0 μm (PM_1.0), and ≤0.5 μm (PM_0.5) as well as number concentrations of particulate matter with diameters ≤ 0.2 μm (PN_0.2) and ≤0.1 μm (PN_0.1). We applied linear mixed-effect models to assess the associations between short-term exposure to different PM size fractions and PM_2.5 constituents and seven lipid metrics. We found significant associations of greater concentrations of PM in different size fractions within 5 days before blood collection with lower high-density lipoprotein cholesterol (HDL-C) and apolipoprotein A (ApoA1) levels, higher apolipoprotein B (ApoB) levels, and lower ApoA1/ApoB ratios. Among the PM_2.5 constituents, we observed that higher concentrations of tin and lead were significantly associated with decreased HDL-C levels, and higher concentrations of nickel were associated with higher HDL-C levels. Our results suggest that short-term exposure to PM in different sizes was deleteriously associated with blood lipids. Some constituents, especially metals, might be the major contributors to the detrimental effects.

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

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

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

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

Traffic-related environmental factors and childhood obesity: A systematic review and meta-analysis

A growing body of research links traffic-related environmental factors to childhood obesity; however, the evidence is still inconclusive. This review aims to fill this important research gap by systematically reviewing existing research on the relationship between traffic-related environmental factors and childhood obesity. Based on the inclusion criteria, 39 studies are selected with environmental factors of interest, including traffic flow, traffic pollution, traffic noise, and traffic safety. Weight-related behaviours include active travel/transport, physical activity (PA), and intake of a high trans-fat diet or stress symptoms; weight-related outcomes are mainly body mass index (BMI) or BMI z-scores and overweight/obesity. Of 16 studies of weight-related behaviours, significant associations are reported in 11 out of 12 studies on traffic flow (two positively and nine negatively associated with PA), five out of six studies on traffic safety (four positively and one negatively associated with PA), one study on traffic pollution (positively with unhealthy food consumption), and one study on traffic noise (negatively associated with PA). Among 23 studies of weight-related outcomes, significant associations are reported in six out of 14 studies on traffic flow (five positively and one negatively associated with obesity outcome), seven out of 10 studies on traffic pollution (all positively associated with obesity outcome), and two out of five on traffic noise (all positively associated with obesity outcome). Our findings show that long-term traffic pollution is weakly positively associated with children's BMI growth, and traffic flow, pollution, and noise could affect weight-related behaviours. Associations between traffic density and noise and weight status are rather inconclusive.

The association between ambient air pollution and blood lipids: A longitudinal study in Shijiazhuang, China

BACKGROUND

Few studies have explored the associations between ambient air pollution and blood lipid levels. This study aimed to fill this knowledge gap based on a routine health examination cohort in Shijiazhuang, China.

METHODS

We included 7063 participants who took the routine health examination for 2-3 times at Hebei General Hospital from January 2016 to December 2018. Individual serum levels of cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) were measured. Their three-month average exposure to air pollution prior to the routine health examinations was estimated using inverse distance weighted method. We used linear mixed-effects regression models to examine the associations between air pollution and levels of blood lipids while controlling for age, gender, body mass index (BMI), smoking, alcohol drinking, temperature, humidity, with a random effect for each individual.

RESULTS

Particles with diameters ≤2.5 μm and ≤10 μm (PM_2.5 and PM₁₀), nitrogen dioxide (NO₂), sulfur dioxide (SO₂) and ozone (O₃) were all positively associated with TC, TG, and LDL-C and negatively associated with HDL-C, in single pollutant models. Each 10 μg/m³ increment of 3-month average PM_2.5 was associated with 0.65% [95% confidence interval (CI): 0.03%-1.28%], 0.56% (95%CI: 0.33%-0.79%) and 0.63% (95%CI: 0.35%-0.91%) increment in TG, TC, and LDL-C, and 0.91% (95%CI: 0.68%-1.13%) decrease in HDL-C. In two-pollutant models, the effects of gaseous pollutants on blood lipids were weakened, while those of PMs were strengthened. Stronger associations were presented in the elderly (≥60 years) and overweight/obese (BMI ≥ 24) participants.

CONCLUSIONS

Ambient air pollution had significantly adverse effects on blood lipid levels, especially in overweight/obese and elderly individuals.

CAPSULE

Significant associations between increased air pollution and worse blood lipid levels were found, especially in overweight/obese and elderly individuals.

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.