Ambient air pollution and overweight and obesity in school-aged children in Barcelona, Spain

Status and frontier analysis of indoor PM2.5-related health effects: a bibliometric analysis

Epidemiological data indicate atmospheric particulate matter, especially fine particulate matter (PM2.5), has many negative effects on human health. Of note, people spend about 90% of their time indoors. More importantly, according to the World Health Organization (WHO) statistics, indoor air pollution causes nearly 1.6 million deaths each year, and it is considered as one of the major health risk factors. In order to obtain a deeper understanding of the harmful effects of indoor PM2.5 on human health, we used bibliometric software to summarize articles in this field. In conclusion, since 2000, the annual publication volume has increased year by year. America topped the list for the number of articles, and Professor Petros Koutrakis and Harvard University were the author and institution with the most published in this research area, respectively. Over the past decade, scholars gradually paid attention to molecular mechanisms, therefore, the toxicity can be better explored. Particularly, apart from timely intervention and treatment for adverse consequences, it is necessary to effectively reduce indoor PM2.5 through technologies. In addition, the trend and keywords analysis are favorable ways to find out future research hotspots. Hopefully, various countries and regions strengthen academic cooperation and integration of multi-disciplinary.

Contribution of greenness, air pollution, and residential food environment to excess gestational weight gain: A cross-sectional study in Wuhan, China

OBJECTIVES

Our goal was to explore how greenness, air pollution, and residential food environment were linked to excessive gestational weight gain (EGWG), and to estimate their combined effects on this condition.

METHOD

This cross-sectional analysis included 51,507 pregnant women from the Wuhan Maternal and Child Health Management Information System between 2016 and 2019. Generalized linear mixed regression models were employed to explore the relationships between greenness, air pollution, residential food environmental exposure, and EGWG; and the combined effects were further estimated by cluster analysis and principal components analysis.

RESULT

We only found a significant association between convenience store density within the 250 m buffer zone (OR = 1.03 and 95% CI: 1.01,1.05) and EGWG. In terms of air pollution, sulfur dioxide(SO2), particulate matter with a diameter of 10 μm or less(PM10), and particulate matter with a diameter of 2.5 μm or less(PM2.5) were substantially correlated with a higher prevalence of EGWG and higher GWG, with (OR = 1.16 and 95% CI: 1.12,1.21; OR = 1.12 and 95% CI: 1.08,1.16; OR = 1.17 and 95% CI: 1.14,1.21, respectively) per interquartile range(IQR) increase. Cluster analysis revealed the presence of three clusters representing urban exposures. In contrast to urban environment clusters characterized by favourable conditions, those exhibiting elevated air pollution levels, high-density residential food environment and low levels of greenness were found to have increased odds of EGWG (OR = 1.10, 95% CI: 1.03, 1.19).

CONCLUSION

This study emphasizes that exposure to elevated air pollution, high-density residential neighbourhood food environments, and low levels of greenness is a neighbourhood obesogenic environment for pregnant women.

Long-term exposure to air pollution at residential and workplace addresses and breast cancer risk: A case-control study nested in the French E3N-Générations cohort from 1990 to 2011

BACKGROUND

An increasing evidence links air pollution to breast cancer (BC) risk. Yet, pollutant exposure estimates at the workplace location in pollution exposure assessment have not been considered.

OBJECTIVES

This study investigates the association between particulate matters (PM2·5, PM10) and nitrogen dioxide (NO2) atmospheric concentrations (1990-2011), at the women's residential and workplace locations, and BC risk.

METHODS

This case-control study of 2419 BC cases and 2984 controls, was nested in the French prospective E3N cohort. The annual mean PM2·5, PM10 and NO2 concentrations were estimated using a Land Use Regression model (50 m x 50 m resolution) and assigned to the women's geocoded residential and workplace locations, from cohort recruitment to their index date (date of case diagnosis). Odds ratios (OR) and 95 % confidence intervals (CI) were estimated using multivariate logistic regression models.

RESULTS

An increased BC risk was observed for a 10 µg/m3 increase of the 1990-2011 average PM2·5 concentration estimates (OR=1·28; CI 1·00, 1·63). An increased risk was suggested for a 10 µg/m3 increase for PM10 (OR=1·09; CI 0·92, 1·30) and NO2 (OR=1·05; CI 0·97, 1·13). No effect modification by menopausal status, nor difference by hormone receptor status were observed.

DISCUSSION

This study is the first to estimate BC risk and long-term air pollutant exposure from both, residential and workplace location histories. Results suggest that residential PM2·5, PM10 and NO2 concentrations are strongly correlated with workplace ones, indicating that residential data may serve as proxy for overall exposure. Future studies should consider exposure during commuting.

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.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Exposure to Airborne PM2.5 Water-Soluble Inorganic Ions Induces a Wide Array of Reproductive Toxicity

Water-soluble inorganic ions (WSIIs, primarily NH4+, SO42-, and NO3-) are major components in ambient PM2.5, but their reproductive toxicity remains largely unknown. An animal study was conducted where parental mice were exposed to PM2.5 WSIIs or clean air during preconception and the gestational period. After delivery, all maternal and offspring mice lived in a clean air environment. We assessed reproductive organs, gestation outcome, birth weight, and growth trajectory of the offspring mice. In parallel, we collected birth weight and placenta transcriptome data from 150 mother-infant pairs from the Rhode Island Child Health Study. We found that PM2.5 WSIIs induced a broad range of adverse reproductive outcomes in mice. PM2.5 NH4+, SO42-, and NO3- exposure reduced ovary weight by 24.22% (p = 0.005), 14.45% (p = 0.048), and 16.64% (p = 0.022) relative to the clean air controls. PM2.5 SO42- exposure reduced the weight of testicle by 5.24% (p = 0.025); further, mice in the PM2.5 SO42- exposure group had 1.81 (p = 0.027) fewer offspring than the control group. PM2.5 NH4+, SO42-, and NO3- exposure all led to lower birth than controls. In mice, 557 placenta genes were perturbed by exposure. Integrative analysis of mouse and human data suggested hypoxia response in placenta as an etiological mechanism underlying PM2.5 WSII exposure's reproductive toxicity.

Is environment destiny? Spatial analysis of the relationship between geographic factors and obesity in Türkiye

This study aims to evaluate the relationship of geographical factors, including precipitation, slope, air pollution and elevation with adult obesity prevalence in Türkiye (TR) using a cross-regional study design. Ordinary least squares (OLS) and geographically weighted regression (GWR) were performed to evaluate the spatial variation in the relationship between all geographic factors and obesity prevalence. In the model, a positive relationship was found between obesity prevalence and slope, whereas a negative significant relationship was determined between obesity prevalence and elevation (p < 0.05). These results, revealing spatially varying associations, were very useful in refining the interpretations of the statistical results on adult obesity. This research suggests that geographical factors should be considered as one of the components of the obesogenic environment. In addition, it is recommended that national and international strategies to overcome obesity should be restructured by taking into account the geographical characteristics of the region.

The impact of long-term PM1 exposure on all-cause mortality and its interaction with BMI: A nationwide prospective cohort study in China

BACKGROUND

China has a serious air pollution problem and a high prevalence of obesity. The interaction between the two and its impact on all-cause mortality is a public health issue of great concern.

OBJECTIVES

This study aimed to investigate the association between long-term exposure to particulate matter with aerodynamic diameter ≤ 1 μm (PM1) and all-cause mortality, as well as the interaction effect of body mass index (BMI) in the association.

METHODS

A total of 33,087 participants from 162 counties in 25 provinces in China were included, with annual average PM1 exposure being estimated based on the county address. The PM1-mortality relation was evaluated using the time-varying Cox proportional hazards models, with the dose-response relationship being fitted using the penalized splines. Besides, the potential interaction effect of BMI in the PM1-mortality relation was evaluated.

RESULTS

The incidence of all-cause deaths was 76.99 per 10,000 person-years over a median of 8.2 years of follow-up. After controlling for potential confounders, the PM1-mortality relation was approximately J-shaped. The full-adjustment analysis observed the hazard ratio (HR) of all-cause mortality was 1.114 [95 % confidence interval (CI): 1.017-1.220] corresponding to a 10 μg/m3 rise in PM1 concentration. Further stratified analyses suggested the adverse effects of PM1 might be more pronounced among the underweight.

DISCUSSION

Higher PM1 concentrations were associated with an increase in all-cause mortality. The BMI might further alter the relation, and the underweight population was the sensitive subgroup of the population that needed to be protected.

Updates in Air Pollution: Current Research and Future Challenges

Background

The United Nations has declared that humans have a right to clean air. Despite this, many deaths and disability-adjusted life years are attributed to air pollution exposure each year. We face both challenges to air quality and opportunities to improve, but several areas need to be addressed with urgency.

Objective

This paper summarises the recent research presented at the Pacific Basin Consortium for Environment and Health Symposium and focuses on three key areas of air pollution that are important to human health and require more research.

Findings and conclusion

Indoor spaces are commonly places of exposure to poor air quality and are difficult to monitor and regulate. Global climate change risks worsening air quality in a bi-directional fashion. The rising use of electric vehicles may offer opportunities to improve air quality, but it also presents new challenges. Government policies and initiatives could lead to improved air and environmental justice. Several populations, such as older people and children, face increased harm from air pollution and should become priority groups for action.

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 association between outdoor light at night exposure and adult obesity in Northeastern China

Previous studies have linked exposure to light at night (LAN) with various health outcomes, but evidence is limited for the LAN-obesity association. Thestudy analysed data from 24,845 participants of the 33 Communities Chinese Health Study and obesity (BMI ≥28 kg/m2) was defined according to the Working Group on Obesity in China. The Global Radiance Calibrated Nighttime Lights data were used to estimate participants' LAN exposure. The mixed-effect regression models examined the LAN-BMI and LAN-obesity association. We found that higher LAN exposure was significantly associated with greater BMI and higher risk of obesity. Changes of BMI and the odds ratios (ORs) of obesity and 95% confidence intervals (CIs) for 2nd, 3rd, and 4th against the 1st quartile of LAN exposure were 0.363 (0.208, 0.519), 0.364 (0.211, 0.516) and 0.217 (0.051, 0.383); 1.228 (1.099, 1.371), 1.356 (1.196, 1.538) and 1.269 (1.124, 1.433), respectively. Age and regular exercise showed significant modification effects on the LAN-obesity association.

The Climate Crisis and Breastfeeding: Opportunities for Resilience

The climate crisis is an emerging global challenge that poses potential risks to breastfeeding practices and outcomes. There are multifaceted effects of climate change affecting the breastfeeding dyad across environmental, societal, and human health dimensions. Breastfeeding support in the face of climate change will require solutions at the structural level-healthcare, community, and workplace settings-and at the mother-infant dyad level. Breastfeeding can additionally be an adaptive response to crisis situations and can mitigate some of the environmental challenges associated with climate change. Despite the undeniable significance of climate change on breastfeeding (and vice versa), our perspective as experts in the field is that this topic has not been systematically addressed. Although we highlight some of the challenges, potential solutions, and co-benefits of breastfeeding in the context of climate change, there are numerous issues that could be further explored and necessitate additional preparedness planning.

PM2.5 constituents associated with childhood obesity and larger BMI growth trajectory: A 14-year longitudinal study

BACKGROUND

The association of specific PM2.5 chemical constituents with childhood overweight or obesity (OWOB) remain unclear. Furthermore, the long-term impacts of PM2.5 exposure on the trajectory of children's body mass index (BMI) have not been explored.

METHODS

We conducted a longitudinal study among 1,450,830 Chinese children aged 6-19 years from Beijing and Zhongshan in China during 2005-2018 to examine the associations of PM2.5 and its chemical constituents with incident OWOB risk. We extracted PM2.5 mass and five main component exposure from Tracking Air Pollution in China (TAP) dataset. Cox proportional hazards models were applied to quantify exposure-response associations. We further performed principal component analysis (PCA) to handle the multi-collinearity and used quantile g-computation (QGC) approach to analyze the impacts of exposure mixtures. Additionally, we selected 125,863 children with at least 8 physical examination measurements and combined group-based trajectory models (GBTM) with multinomial logistic regression models to explore the impacts of exposure to PM2.5 mass and five constituents on BMI and BMI Z-score trajectories during 6-19 years.

RESULTS

We observed each interquartile range increment in PM2.5 exposure was significantly associated with a 5.1 % increase in the risk of incident OWOB (95 % confidence Interval [CI]: 1.036-1.066). We also found black carbon, sulfate, organic matter, often linked to fossil combustion, had comparable or larger estimates of the effect (HR = 1.139-1.153) than PM2.5. Furthermore, Exposure to PM2.5 mass, sulfate, nitrate, ammonium, organic matter and black carbon was significantly associated with an increased odds of being in a larger BMI trajectory and being assigned to persistent OWOB trajectory.

CONCLUSIONS

Our findings provide evidence that the constituents mainly from fossil fuel combustion may have a perceptible influence on increased OWOB risk associated with PM2.5 exposure in China. Moreover, long-term exposure to PM2.5 contributes to an increased odds of being in a lager BMI and a persistent OWOB trajectories.

The Built Environment and Pediatric Health

Buildings, parks, and roads are all elements of the "built environment," which can be described as the human-made structures that comprise the neighborhoods and communities where people live, work, learn, and recreate (https://www.epa.gov/smm/basic-information-about-built-environment). The design of communities where children and adolescents live, learn, and play has a profound impact on their health. Moreover, the policies and practices that determine community design and the built environment are a root cause of disparities in the social determinants of health that contribute to health inequity. An understanding of the links between the built environment and pediatric health will help to inform pediatricians' and other pediatric health professionals' care for patients and advocacy on their behalf. This technical report describes the range of pediatric physical and mental health conditions influenced by the built environment, as well as historical and persistent effects of the built environment on health disparities. The accompanying policy statement outlines community design solutions that can improve pediatric health and health equity, including opportunities for pediatricians and the health care sector to incorporate this knowledge in patient care, as well as to play a role in advancing a health-promoting built environment for all children and families.

Influence of Air Pollution Exposures on Cardiometabolic Risk Factors: a Review

PURPOSE OF REVIEW

The increasing prevalence of cardiometabolic risk factors (CRFs) contributes to the rise in cardiovascular disease. Previous research has established a connection between air pollution and both the development and severity of CRFs. Given the ongoing impact of air pollution on human health, this review aims to summarize the latest research findings and provide an overview of the relationship between different types of air pollutants and CRFs.

RECENT FINDINGS

CRFs include health conditions like diabetes, obesity, hypertension etc. Air pollution poses significant health risks and encompasses a wide range of pollutant types, air pollutants, such as particulate matter (PM), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O2). More and more population epidemiological studies have shown a positive correlation between air pollution and CRFs. Although various pollutants have diverse effects on specific cellular molecular pathways, their main influence is on oxidative stress, inflammation response, and impairment of endothelial function. More and more studies have proved that air pollution can promote the occurrence and development of cardiovascular and metabolic risk factors, and the research on the relationship between air pollution and CRFs has grown intensively. An increasing number of studies are using new biological monitoring indicators to assess the occurrence and development of CRFs resulting from exposure to air pollution. Abnormalities in some important biomarkers in the population (such as homocysteine, uric acid, and C-reactive protein) caused by air pollution deserve more attention. Further research is warranted to more fully understand the link between air pollution and novel CRF biomarkers and to investigate potential prevention and interventions that leverage the mechanistic link between air pollution and CRFs.

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.

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.

Ecological study on household air pollution exposure and prevalent chronic disease in the elderly

Older people spend most of their time indoors. Limited evidence demonstrates that exposure to indoor air pollutants might be related to chronic complications. This study aimed to estimate the correlation between household air pollution (HAP)'s long-term exposure and the prevalence of elevated hypertension, diabetes mellitus (DM), obesity, and low-density lipoprotein (LDL) cholesterol. From the Global Burden disease dataset, we extracted HAP, hypertension, DM, body mass index, and LDL cholesterol data from Iran from 1990 to 2019 to males and females in people over 50 years. We present APC and AAPC and their confidence intervals using Joinpoint Software statistical software. R software examined the correlation between HAP and hypertension, DM2, Obesity, and high LDL cholesterol. Our finding showed a significant and positive correlation between HAP exposure and prevalence of high low-density lipoprotein cholesterol (p ≤ 0.001, r = 0.70), high systolic blood pressure (p ≤ 0.001, r = 0.63), and high body mass index (p ≤ 0.001, r = 0.57), and DM2 (p ≤ 0.001, r = 0.38). The analysis results also illustrated a positive correlation between indoor air pollution and smoking (p ≤ 0.001, r = 0.92). HAP exposure might be a risk factor for elevated blood pressure, DM, obesity, and LDL cholesterol and, consequently, more serious health problems. According to our results, smoking is one of the sources of HAP. However, ecological studies cannot fully support causal relationships, and this article deals only with Iran. Our findings should be corroborated in personal exposure and biomonitoring approach studies.

Link between obesity and atopic dermatitis: Does obesity predispose to atopic dermatitis, or vice versa?

Two serious health conditions, obesity and atopic dermatitis (AD), share some pathological features such as insulin resistance, leptin resistance and inflammation, and a growing body of evidence suggests a link between obesity and AD. Obesity predisposes an individual to and/or worsens AD, whereas AD increases the risk of obesity. Obesity and AD's interactions are mediated by cytokines, chemokines and immune cells. Obese individuals with AD are more resistant to anti-inflammatory therapy, while weight loss can alleviate AD. In this review, we summarize the evidence linking AD and obesity. We also discuss the pathogenic role of obesity in AD, and vice versa. Because of the connection between these two conditions, mitigation of one could possibly prevent the development of or alleviate the other condition. Effective management of AD and weight loss can enhance the wellness of individuals with both of these conditions. However, proper clinical studies are warranted to validate this speculation.

Findings of indoor air pollution and childhood obesity in a cross-sectional study of Chinese schoolchildren

BACKGROUND

Air pollution exposures are increasingly suspected to influence the development of childhood adiposity, especially focusing on outdoor exposure, but few studies investigated indoor exposure and childhood obesity.

OBJECTIVES

We aimed to examine the association between exposure to multiple indoor air pollutants and childhood obesity in Chinese schoolchildren.

METHODS

In 2019, we recruited 6499 children aged 6-12 years from five Chinese elementary schools in Guangzhou, China. We measured age-sex-specific body mass index z score (z-BMI), waist circumference (WC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR) on standard procedures. Four different indoor air pollution (IAP) exposures, including cooking oil fumes (COFs), home decoration, secondhand smoke (SHS), and incense burning, were collected by questionnaire and then converted into an IAP exposure index with four categories. Association between indoor air pollutants and childhood overweight/obesity as well as four obese anthropometric indices were assessed by logistic regression models and multivariable linear regression models, respectively.

RESULTS

Children exposed to ≥3 types of indoor air pollutants had higher z-BMI (coefficient [β]:0.142, 95% confidence interval [CI]:0.011-0.274) and higher risk of overweight/obesity (odd ratio [OR]:1.27, 95%CI:1.01-1.60). And a dose-response relationship was discovered between the IAP exposure index and z-BMI as well as overweight/obesity (p_{for trend}<0.05). We also found that exposure to SHS and COFs was positively associated with z-BMI and overweight/obesity (p < 0.05). Moreover, there was a significant interaction between SHS exposure and COFs on the higher risk of overweight/obesity among schoolchildren. Boys appear more susceptible to multiple indoor air pollutants than girls.

CONCLUSIONS

Indoor air pollution exposures were positively associated with higher obese anthropometric indices and increased odds of overweight/obesity in Chinese schoolchildren. More well-designed cohort studies are needed to verify our results.

Sex-dependent obesogenic effect of tetracycline on Drosophila melanogaster deteriorated by dysrhythmia

Antibiotics have been identified as obesogens contributing to the prevalence of obesity. Moreover, their environmental toxicity shows sex dependence, which might also explain the sex-dependent obesity observed. Yet, the direct evidence for such a connection and the underlying mechanisms remain to be explored. In this study, the effects of tetracycline, which is a representative antibiotic found in both environmental and food samples, on Drosophila melanogaster were studied with consideration of both sex and circadian rhythms (represented by the eclosion rhythm). Results showed that in morning-eclosed adults, tetracycline significantly stimulated the body weight of females (AM females) at 0.1, 1.0, 10.0 and 100.0 µg/L, while tetracycline only stimulated the body weight of males (AM males) at 1.0 µg/L. In the afternoon-eclosed adults, tetracycline significantly stimulated the body weight of females (PM females) at 0.1, 1.0 and 100.0 µg/L, while it showed more significant stimulation in males (PM males) at all concentrations. Notably, the stimulation levels were the greatest in PM males among all the adults. The results showed the clear sex dependence of the obesogenic effects, which was diminished by dysrhythmia. Further biochemical assays and clustering analysis suggested that the sex- and rhythm-dependent obesogenic effects resulted from the bias toward lipogenesis against lipolysis. Moreover, they were closely related to the preference for the energy storage forms of lactate and glucose and also to the presence of excessive insulin, with the involvement of glucolipid metabolism. Such relationships indicated potential bridges between the obesogenic effects of pollutants and other diseases, e.g., cancer and diabetes.

Comparison of static and dynamic exposures to air pollution, noise, and greenness among seniors living in compact-city environments

GPS technology and tracking study designs have gained popularity as a tool to go beyond the limitations of static exposure assessments based on the subject's residence. These dynamic exposure assessment methods offer high potential upside in terms of accuracy but also disadvantages in terms of cost, sample sizes, and types of data generated. Because of that, with our study we aim to understand in which cases researchers need to use GPS-based methods to guarantee the necessary accuracy in exposure assessment. With a sample of 113 seniors living in Barcelona (Spain) we compare their estimated daily exposures to air pollution (PM2.5, PM10, NO2), noise (dB), and greenness (NDVI) using static and dynamic exposure assessment techniques. Results indicate that significant differences between static and dynamic exposure assessments are only present in selected exposures, and would thus suggest that static assessments using the place of residence would provide accurate-enough values across a number of exposures in the case of seniors. Our models for Barcelona's seniors suggest that dynamic exposure would only be required in the case of exposure to smaller particulate matter (PM2.5) and exposure to noise levels. The study signals to the need to consider both the mobility patterns and the built environment context when deciding between static or dynamic measures of exposure assessment.

Does Neighborhood Social Capital Longitudinally Affect the Nutritional Status of School-Aged Children? Evidence from China

Previous research linking social capital to child nutritional status primarily constitutes cross-sectional studies. To investigate whether a longitudinal relationship exists, by conducting fixed-effects analyses with 16,977 repeatedly measured observations of 6193 children from the 2012, 2014, 2016, and 2018 China Family Panel Studies, this study explored the longitudinal effects of neighborhood participation, bonding trust, and bridging trust on the BMI-for-age z-score (BAZ) and BMI categories of school-aged children, differentiating between urban and rural residence. We found an increasing average BAZ, a decreasing prevalence of underweight, an increasing prevalence of overweight/obesity, and a reducing urban/rural gap in nutritional status. The levels of social capital components descended faster in the urban area. Bonding trust was predictive of a lower BAZ, a higher likelihood of being underweight, and a lower likelihood of being overweight/obese. Bridging trust was predictive of a higher BAZ. The longitudinal effects of bonding trust were significant among only the rural children. Our findings indicate that neighborhood social capital may impose causal impacts on the nutritional status of children. To effectively improve child nutritional status, a more empathetic governmental approach that promotes a more supportive distal social environment is needed.

School-Based Interventions to Support Healthy Indoor and Outdoor Environments for Children: A Systematic Review

Environmental exposures are associated with children's health. Schools are often urban exposure 'hotspots' for pollution, noise, lack of green space and un-walkable built environments. The aim of this systematic review was to explore the impact of school-based interventions on the modification of indoor and outdoor stressors related to the built and natural environment on children's exposure and health. A systematic review of seven databases was performed. We included quantitative studies on children aged 5-12, which reported intervention delivered within school settings aimed at addressing key environmental exposures including air pollution, green spaces, traffic noise or active travel; and reported physical and mental health, physical activity or active travel behavior. The quality of studies was assessed and interventions were described using a standardized framework. A narrative synthesis approach was used to describe the findings. Thirty-nine papers were included on three main intervention types: improve indoor air quality by the increase of ventilation rates in classrooms; increase children's green time or greening schools, and multicomponent interventions to increase active travel to school by changes in pedestrian facilities. No eligible intervention to reduce traffic noise at school was found. Increasing ventilation rates improved short-term indoor air quality in classrooms, but the effect on cognitive performance was inconsistent. Greening schools and increasing children's green time have consistent positive effects on cognition and physical activity, but not in behavior. Multi-component interventions can increase walking and cycling after three years. Overall, the studies were rated as having poor quality owing to weak study designs. We found modest evidence that school-based built and natural environment interventions can improve children's exposure and health.

Association of urinary and ambient black carbon, and other ambient air pollutants with risk of prediabetes and metabolic syndrome in children and adolescents

The effects of exposure to black carbon (BC) on various diseases remains unclear, one reason being potential exposure misclassification following modelling of ambient air pollution levels. Urinary BC particles may be a more precise measure to analyze the health effects of BC. We aimed to assess the risk of prediabetes and metabolic syndrome (MetS) in relation to urinary BC particles and ambient BC and to compare their associations in 5453 children from IDEFICS/I. Family cohort. We determined the amount of BC particles in urine using label-free white-light generation under femtosecond pulsed laser illumination. We assessed annual exposure to ambient air pollutants (BC, PM_2.5 and NO₂) at the place of residence using land use regression models for Europe, and we calculated the residential distance to major roads (≤250 m vs. more). We analyzed the cross-sectional relationships between urinary BC and air pollutants (BC, PM_2.5 and NO₂) and distance to roads, and the associations of all these variables to the risk of prediabetes and MetS, using logistic and linear regression models. Though we did not observe associations between urinary and ambient BC in overall analysis, we observed a positive association between urinary and ambient BC levels in boys and in children living ≤250 m to a major road compared to those living >250 m away from a major road. We observed a positive association between log-transformed urinary BC particles and MetS (OR_{per unit increase} = 1.72, 95% CI = 1.21; 2.45). An association between ambient BC and MetS was only observed in children living closer to a major road. Our findings suggest that exposure to BC (ambient and biomarker) may contribute to the risk of MetS in children. By measuring the internal dose, the BC particles in urine may have additionally captured non-residential sources and reduced exposure misclassification. Larger studies, with longitudinal design including measurement of urinary BC at multiple time-points are warranted to confirm our findings.

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.

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.

DNA Damage as a Mechanistic Link between Air Pollution and Obesity?

It has been shown that the risk of developing obesity, a serious modern health problem, increases with air pollution. However, the molecular links are yet to be fully elucidated. Herein, we propose a hypothesis via which air pollution-induced DNA damage would be the mechanistic link between air pollution and the enhanced risk of obesity and overweight. Indeed, whereas air pollution leads to DNA damage, DNA damage results in inflammation, oxidative stress and metabolic impairments that could be behind energy balance changes contributing to obesity. Such thoughts, worth exploring, seems an important starting point to better understand the impact of air pollution on obesity development independently from the two main energy balance pillars that are diet and physical activity. This could possibly lead to new applications both for therapies as well as for policies and regulations.

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.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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.

The effect of air pollution and emotional and behavioral problems on preschoolers' overweight and obesity

Childhood overweight and obesity (OWO) has risen dramatically in both developed and developing countries over the past few decades, creating a huge burden of disease. Ambient air pollution and emotional and behavioral problems are important influencing factors of OWO in preschoolers, but few studies have evaluated the impact of air pollution and emotional and behavioral problems on OWO of preschoolers in rural areas and their potential interactions. This study selected 3802 preschool children from 26 kindergartens in 4 rural areas of Anhui Province for a cross-sectional study. A total of 3636 individuals were included in the final analysis. In this study, outdoor air pollutants (PM_2.5 and O₃) were derived from the China Air Pollution Tracking (TAP) data set, matching preschoolers' external air pollution exposure according to their kindergarten address codes to neighborhoods or administrative villages. OWO were assessed based on WHO Child Growth and Development Standards. Generalized linear model (GLM) and interplot model were used to evaluate the separate effects and potential interactions of air pollutants and emotional and behavioral problems on preschoolers' OWO. In the separate analysis, we found a significant positive association between air pollution and emotional and behavioral problems and OWO among preschoolers. In the interaction analysis, air pollution could enhance the positive effect of emotional and behavioral problems on OWO in preschoolers. In addition, the effect of air pollution and emotional and behavioral problems on overweight and obesity was stronger in preschoolers aged 5 to 6 years. Finally, we also found a stronger positive association between emotional and behavioral problems among girls, macrosomia, non-left-behind children, and preschoolers without eating problems. This study provided a scientific basis for the control of air pollution and overweight and obesity among preschool children in Anhui Province.

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

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

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.

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.

Spatial Estimation of PM2.5 Exposure and its Association with Asthma Exacerbation: A Prospective Study in Thai Children

Background:

The acceptable fine particulate matter (PM_2.5) level in Thailand is double the recommendation of the World Health Organization. It is necessary to have an accurate measure of PM_2.5 exposure and its association with health problems in vulnerable groups such as asthma exacerbation in Thai children to urge the Clean Air Act in Thailand, which is currently in the process of revision.

Objective:

To study the association between PM_2.5 exposure and asthma exacerbation in children living in Bangkok Metropolitan Region and Chiang Mai Province.

Methods:

A pilot prospective observational study was conducted at the Chest and Allergy clinic at Ramathibodi Hospital, Mahidol University, Bangkok and at the Chest Clinic at Nakornping Hospital, Chiang Mai, Thailand, from June 2020 to February 2021. Children with asthma, aged 5–18 years old, were recruited. Respiratory symptoms, including cough, chest tightness, dyspnea or wheezing, peak expiratory flow rate, and asthma exacerbation, were recorded twice daily by caregivers. Estimated average daily PM_2.5 exposure levels were calculated using ArcGIS® at exacerbation day, three days before exacerbation (lag day 3), and 7 days before exacerbation (lag day 7). Regression analysis was applied to examine the association between PM_2.5 exposure and asthma exacerbation.

Findings:

Seventy asthmatic patients were enrolled. The median age was 9.7 (IQR 5–18) years old. There were 53 respiratory symptoms, 5 admissions, and 1 intensive care unit admission. Daily PM_2.5 levels above 12 mcg/m³ (the US cut-off level for the sensitive group) has higher sensitivity to detect asthma exacerbation compared to Thai cut-off level for the sensitive group (37 mcg/m³) (sensitivity 98.2% vs 32.1%). The average daily PM_2.5 level exposure at lag day 3 in the exacerbation vs the non-exacerbation group was 27.5 and 13.6 mcg/m³ (p < 0.01), respectively. The daily PM_2.5 level at lag day 3 was also correlated with an acute asthmatic attack (r = 0.62, p < 0.01) with the 0.2 events increasing of asthmatic exacerbation every 10 mcg/m³ of increment of daily PM_2.5 level.

Conclusions:

Our findings suggest that asthmatic children are sensitive to daily PM_2.5 levels above 12 mcg/m³. Exposure to high daily PM_2.5 levels can lead to asthma exacerbation within three days. Further participant recruitment is needed to emphasize this association and establish the national data.

Associations of perinatal exposure to PM2.5 with gestational weight gain and offspring birth weight

BACKGROUND

PM_2.5 have been associated with weight change in animal models and non-pregnant populations. Evidence of associations between PM_2.5 and gestational weight gain (GWG), an important determinant of course and outcomes of pregnancy, and subsequent birth outcomes is limited.

METHODS

The study was conducted among a subset of participants from the Omega Study, a prospective pregnancy cohort. Exposure to PM_2.5 (μg/m³) was ascertained for participants (N = 855) based on their residential address using a validated national spatiotemporal model. Adjusted multivariable linear regression models were used to estimate associations of trimester-specific and pregnancy-month PM_2.5 exposures with early (<20 weeks gestation), late (≥20 weeks gestation), and total GWG and infant birth weight. Stratified models and product terms were used to examine whether pre-pregnancy BMI (ppBMI) and infant sex modified the associations.

RESULTS

Average monthly PM_2.5 exposure during the first, second, and third trimesters were 7.3 μg/m³, 7.9 μg/m³, and 7.7 μg/m³, respectively. Higher third trimester PM_2.5 exposure was associated with higher late (0.40 kg per 5 μg/m (McDowell et al., 2018); 95%CI: 0.12, 0.67) and total (0.35 kg; 95%CI: 0.01, 0.70) GWG among participants with normal ppBMI. Higher second month PM_2.5 exposure was associated with lower early (-0.70 kg; 95%CI: 1.22, -0.18), late (-0.84 kg; 95% CI: 1.54, -0.14), and total (-1.70 kg; 95%CI: 2.57, -0.82) GWG among participants with overweight/obese ppBMI. Product terms between PM_2.5 and ppBMI were significant for second month PM_2.5 exposure and early (p-value = 0.01) and total GWG (p-value<0.01). Higher third trimester PM_2.5 exposure was associated with higher birth weight, though higher fourth month PM_2.5 exposure was associated with lower birth weight, particularly among those with normal ppBMI and male infants.

CONCLUSIONS

Associations of PM_2.5 with GWG vary by exposure window and ppBMI, while associations of PM_2.5 with birth weight potentially vary by exposure window, ppBMI and infant sex. Further exploration of associations between PM_2.5 and maternal/child health outcomes are needed.

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.

COVID-19 and childhood obesity (CO-BESITY) in the era of new normal life: A need for a policy research

BACKGROUND

In the era of new normal life (after Coronavirus Disease 2019 (COVID-19)), our children are experiencing the double threat of COVID-19 and Childhood Obesity (CO-BESITY). The rate of childhood obesity has been rapidly increasing in developed as well as low middle-income countries during the pandemic.

DESIGN AND METHODS

The current paper aims to identify the probable reasons of increase in childhood obesity during this pandemic and offers suggestions to reduce the burden of it. Literature search was done using PubMed, Google Scholar, and Scopus databases for the key terms "childhood obesity," "obesity," "pandemic," and/or childhood obesity. All the relevant articles were included to support the argument for this viewpoint.

RESULTS

Childhood obesity is a complicated disorder having diverse outcomes. The incidence of childhood obesity is clearly analysed from Bronfenbrenner's model of child development. The model examines an overabundance of bio-psycho-social backgrounds, risks, and probable outcomes on the development of a child. COVID-19 pandemic has disrupted the ecosystem of this dynamic model and has created an economic and social-cultural crisis that has ignited a chain reaction of stressors upon children and their families. In this paper, we have described how this Bronfenbrenner's model of child development also known as the Bioecological Model can be effective for the estimation and prevention of childhood obesity.

CONCLUSION

We propose that this Bioecological Model will help the children and their families further to understand and manage the problem of childhood obesity during this pandemic on their own.

Long-term ambient PM2.5 exposure associated with cardiovascular risk factors in Chinese less educated population

INTRODUCTION

Long-term exposure to ambient air pollution is related to major cardiovascular risk factors including diabetes, hypertension, hyperlipidemia and overweight, but with few studies in high-concentration nations like China so far. We aimed to investigate the association between long-term exposure to ambient fine particulate matter (particles with an aerodynamic diameter ≤ 2.5 μm, PM_2.5) and major cardiovascular risk factors in China.

METHODS

Adult participants with selected biochemical tests were recruited from the Chinese Physiological Constant and Health Condition (CPCHC) survey conducted from 2007 to 2011. Gridded PM_2.5 data used were derived from satellite-observed data with adjustment of ground-observed data. District-level PM_2.5 data were generated to estimate the association using multivariate logistic regression model and generalized additive model.

RESULTS

A total of 19,236 participants from the CPCHC survey were included with an average age of 42.8 ± 16.1 years, of which nearly half were male (47.0%). The annual average PM_2.5 exposure before the CPCHC survey was 33.4 (14.8-53.4) μg/m³, ranging from 8.0 μg/m³ (Xiwuqi) to 94.7 μg/m³ (Chengdu). Elevated PM_2.5 was associated with increased prevalence of hypertension (odds ratio (OR) =1.022, 95% confidence interval (95%CI): 1.001, 1.043) and decreased prevalence of overweight (OR = 0.926, 95%CI: 0.910, 0.942). Education significantly interacted with PM_2.5 in association with all the interesting risk factors. Each 10 μg/m³ increment of PM_2.5 was associated with increased prevalence of diabetes (OR = 1.118, 95%CI: 1.037, 1.206), hypertension (OR = 1.101, 95%CI: 1.056, 1.147), overweight (OR = 1.071, 95%CI: 1.030, 1.114) in participants with poor education, but not in well-educated population. PM_2.5 exposure was negatively associated with hyperlipidemia in all participants (OR = 0.939, 95%CI: 0.921, 0.957). The results were robust in all the sensitivity analyses.

CONCLUSION

Association between long-term PM_2.5 exposure and cardiovascular risk factors might be modified by education. PM_2.5 was associated with a higher prevalence of diabetes, hypertension, and overweight in a less-educated population with time-expose dependency. Long-term exposure to PM_2.5 might be associated with a lower prevalence of hyperlipidemia.

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

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

Advancing tools for human early lifecourse exposome research and translation (ATHLETE): Project overview

Early life stages are vulnerable to environmental hazards and present important windows of opportunity for lifelong disease prevention. This makes early life a relevant starting point for exposome studies. The Advancing Tools for Human Early Lifecourse Exposome Research and Translation (ATHLETE) project aims to develop a toolbox of exposome tools and a Europe-wide exposome cohort that will be used to systematically quantify the effects of a wide range of community- and individual-level environmental risk factors on mental, cardiometabolic, and respiratory health outcomes and associated biological pathways, longitudinally from early pregnancy through to adolescence. Exposome tool and data development include as follows: (1) a findable, accessible, interoperable, reusable (FAIR) data infrastructure for early life exposome cohort data, including 16 prospective birth cohorts in 11 European countries; (2) targeted and nontargeted approaches to measure a wide range of environmental exposures (urban, chemical, physical, behavioral, social); (3) advanced statistical and toxicological strategies to analyze complex multidimensional exposome data; (4) estimation of associations between the exposome and early organ development, health trajectories, and biological (metagenomic, metabolomic, epigenetic, aging, and stress) pathways; (5) intervention strategies to improve early life urban and chemical exposomes, co-produced with local communities; and (6) child health impacts and associated costs related to the exposome. Data, tools, and results will be assembled in an openly accessible toolbox, which will provide great opportunities for researchers, policymakers, and other stakeholders, beyond the duration of the project. ATHLETE's results will help to better understand and prevent health damage from environmental exposures and their mixtures from the earliest parts of the life course onward.

Urban environment and obesity and weight-related behaviours in primary school children

BACKGROUND

Urban environments are characterised by many factors that may influence children's lifestyle and increase the risk of childhood obesity, but multiple urban exposures have scarcely been studied.

OBJECTIVE

We evaluated the association between multiple urban exposures and childhood obesity outcomes and weight-related behaviours.

METHODS

We conducted a cross-sectional study including 2213 children aged 9-12 years in Sabadell, Spain. We estimated ambient air pollution, green spaces, built and food environment, road traffic and road traffic noise at residential addresses through a total of 28 exposure variables in various buffers. Childhood obesity outcomes included body mass index (BMI), waist circumference and body fat. Weight-related behaviours included diet (fast food and sugar-sweetened beverage consumption), physical activity, sedentary behaviour, sleep duration and well-being. Associations between exposures (urban environment) and outcomes (obesity and behaviours) were estimated in single and multiple-exposure regression models and in a hierarchical clustering on principal components (HCPC) analysis.

RESULTS

Forty percent of children were overweight or obese. In single exposure models, very few associations were observed between the urban exposures and obesity outcomes or weight-related behaviours after correction for multiple testing. In multiple exposure models, PM_coarse, denser unhealthy food environment and land use mix were statistically significant associated with childhood obesity outcomes (e.g 17.7 facilities/km² increase of unhealthy food environment (OR overweight/obesity status) = 1.20 [95% CI: 1.01; 1.44]). Cluster analysis identified 5 clusters of urban exposures. Compared to the most neutral cluster, the cluster with high air pollution, road traffic, and road noise levels was associated with a higher BMI and higher odds of overweight and obesity (β (zBMI) = 0.17, [95% CI: 0.01, 0.17]; OR (overweight/obesity) = 1.36, [95% CI: 0.99, 1.85]); the clusters were not associated with the weight-related behaviours.

CONCLUSIONS

This systematic study of many exposures in the urban environment suggests that an exposure pattern characterised by higher levels of ambient air pollution, road traffic and road traffic noise is associated with increased childhood obesity risk and that PM_coarse, land use mix and food environment are separately associated with obesity risk. These findings require follow-up in longitudinal studies and different settings.

Analysis of the spatial effect of outward foreign direct investment on air pollution: evidence from China

Outward foreign direct investment (OFDI) plays a pivotal role in the strategy to build a high-level and open economy. This research used spatial panel models and data from 30 provinces in China from 2004 to 2017 to empirically analyse the relationship between OFDI and air pollution. The results revealed that, first, China's air pollution showed two spatial clustering areas: the eastern coastal area (e.g. Zhejiang) and the north-western area (e.g. Xinjiang). Second, with the increase in OFDI, the direct effect on the concentration of respirable suspended particulate matter (PM₁₀) and sulphur dioxide (SO₂) was negative, and the direct effect on nitrogen dioxide (NO₂) was positive; however, the total effect was negative. An increase of 1% in OFDI would directly decrease the concentrations of PM₁₀ and SO₂ by 0.024% and 0.096%, respectively, while NO₂ would directly increase by 0.061%, but the total effect of OFDI on the three air pollutants was negative. Third, the environmental Kuznets curve hypothesis existed between economic growth and SO₂ and NO₂ but not between economic growth and PM₁₀. The spatial panel model results revealed that the spatial spillover effects of air pollutants (i.e. PM₁₀, SO_2, and NO₂) were 0.494, 0.447 and 0.314, respectively. Moreover, the impact of OFDI on air pollution had significant temporal heterogeneity. To make the results robust, this research conducted a robustness test by replacing the spatial weight matrix and dependent variables. Finally, the conclusion of this article demonstrates the importance of OFDI in improving air pollution, and we could benefit from OFDI. Our research conclusions provide an important reference for policymakers in implementing trade policies and improving air pollution.

Mortality and Morbidity Effects of Long-Term Exposure to Low-Level PM2.5, BC, NO2, and O3: An Analysis of European Cohorts in the ELAPSE Project

INTRODUCTION

Epidemiological cohort studies have consistently found associations between long-term exposure to outdoor air pollution and a range of morbidity and mortality endpoints. Recent evaluations by the World Health Organization and the Global Burden of Disease study have suggested that these associations may be nonlinear and may persist at very low concentrations. Studies conducted in North America in particular have suggested that associations with mortality persisted at concentrations of particulate matter with an aerodynamic diameter of less than 2.5 μm (PM2.5) well below current air quality standards and guidelines. The uncertainty about the shape of the concentration-response function at the low end of the concentration distribution, related to the scarcity of observations in the lowest range, was the basis of the current project. Previous studies have focused on PM2.5, but increasingly associations with nitrogen dioxide (NO2) are being reported, particularly in studies that accounted for the fine spatial scale variation of NO2. Very few studies have evaluated the effects of long-term exposure to low concentrations of ozone (O3). Health effects of black carbon (BC), representing primary combustion particles, have not been studied in most large cohort studies of PM2.5. Cohort studies assessing health effects of particle composition, including elements from nontailpipe traffic emissions (iron, copper, and zinc) and secondary aerosol (sulfur) have been few in number and reported inconsistent results. The overall objective of our study was to investigate the shape of the relationship between long-term exposure to four pollutants (PM2.5, NO2, BC, and O3) and four broad health effect categories using a number of different methods to characterize the concentration-response function (i.e., linear, nonlinear, or threshold). The four health effect categories were (1) natural- and cause-specific mortality including cardiovascular and nonmalignant as well as malignant respiratory and diabetes mortality; and morbidity measured as (2) coronary and cerebrovascular events; (3) lung cancer incidence; and (4) asthma and chronic obstructive pulmonary disease (COPD) incidence. We additionally assessed health effects of PM2.5 composition, specifically the copper, iron, zinc, and sulfur content of PM2,5.

METHODS

We focused on analyses of health effects of air pollutants at low concentrations, defined as less than current European Union (EU) Limit Values, U.S. Environmental Protection Agency (U.S. EPA), National Ambient Air Quality Standards (NAAQS), and/or World Health Organization (WHO) Air Quality Guideline values for PM2.5, NO2, and O3. We address the health effects at low air pollution levels by performing new analyses within selected cohorts of the ESCAPE study (European Study of Cohorts for Air Pollution Effects; Beelen et al. 2014a) and within seven very large European administrative cohorts. By combining well-characterized ESCAPE cohorts and large administrative cohorts in one study the strengths and weaknesses of each approach can be addressed. The large administrative cohorts are more representative of national or citywide populations, have higher statistical power, and can efficiently control for area-level confounders, but have fewer possibilities to control for individual-level confounders. The ESCAPE cohorts have detailed information on individual confounders, as well as country-specific information on area-level confounding. The data from the seven included ESCAPE cohorts and one additional non-ESCAPE cohort have been pooled and analyzed centrally. More than 300,000 adults were included in the pooled cohort from existing cohorts in Sweden, Denmark, Germany, the Netherlands, Austria, France, and Italy. Data from the administrative cohorts have been analyzed locally, without transfer to a central database. Privacy regulations prevented transfer of data from administrative cohorts to a central database. More than 28 million adults were included from national administrative cohorts in Belgium, Denmark, England, the Netherlands, Norway, and Switzerland as well as an administrative cohort in Rome, Italy. We developed central exposure assessment using Europewide hybrid land use regression (LUR) models, which incorporated European routine monitoring data for PM2.5, NO2, and O3, and ESCAPE monitoring data for BC and PM2.5 composition, land use, and traffic data supplemented with satellite observations and chemical transport model estimates. For all pollutants, we assessed exposure at a fine spatial scale, 100 × 100 m grids. These models have been applied to individual addresses of all cohorts including the administrative cohorts. In sensitivity analyses, we applied the PM2.5 models developed within the companion HEI-funded Canadian MAPLE study (Brauer et al. 2019) and O3 exposures on a larger spatial scale for comparison with previous studies. Identification of outcomes included linkage with mortality, cancer incidence, hospital discharge registries, and physician-based adjudication of cases. We analyzed natural-cause, cardiovascular, ischemic heart disease, stroke, diabetes, cardiometabolic, respiratory, and COPD mortality. We also analyzed lung cancer incidence, incidence of coronary and cerebrovascular events, and incidence of asthma and COPD (pooled cohort only). We applied the Cox proportional hazard model with increasing control for individual- and area-level covariates to analyze the associations between air pollution and mortality and/or morbidity for both the pooled cohort and the individual administrative cohorts. Age was used as the timescale because of evidence that this results in better adjustment for potential confounding by age. Censoring occurred at the time of the event of interest, death from other causes, emigration, loss to follow-up for other reasons, or at the end of follow-up, whichever came first. A priori we specified three confounder models, following the modeling methods of the ESCAPE study. Model 1 included only age (time axis), sex (as strata), and calendar year of enrollment. Model 2 added individual-level variables that were consistently available in the cohorts contributing to the pooled cohort or all variables available in the administrative cohorts, respectively. Model 3 further added area-level socioeconomic status (SES) variables. A priori model 3 was selected as the main model. All analyses in the pooled cohort were stratified by subcohort. All analyses in the administrative cohorts accounted for clustering of the data in neighborhoods by adjusting the variance of the effect estimates. The main exposure variable we analyzed was derived from the Europewide hybrid models based on 2010 monitoring data. Sensitivity analyses were conducted using earlier time periods, time-varying exposure analyses, local exposure models, and the PM2.5 models from the Canadian MAPLE project. We first specified linear single-pollutant models. Two-pollutant models were specified for all combinations of the four main pollutants. Two-pollutant models for particle composition were analyzed with PM2.5 and NO2 as the second pollutant. We then investigated the shape of the concentration-response function using natural splines with two, three, and four degrees of freedom; penalized splines with the degrees of freedom determined by the algorithm and shape-constrained health impact functions (SCHIF) using confounder model 3. Additionally, we specified linear models in subsets of the concentration range, defined by removing concentrations above a certain value from the analysis, such as for PM2.5 25 μg/m3 (EU limit value), 20, 15, 12 μg/m3 (U.S. EPA National Ambient Air Quality Standard), and 10 μg/m3 (WHO Air Quality Guideline value). Finally, threshold models were evaluated to investigate whether the associations persisted below specific concentration values. For PM2.5, we evaluated 10, 7.5, and 5 μg/m3 as potential thresholds. Performance of threshold models versus the corresponding no-threshold linear model were evaluated using the Akaike information criterion (AIC).

RESULTS

In the pooled cohort, virtually all subjects in 2010 had PM2.5 and NO2 annual average exposures below the EU limit values (25 μg/m3 and 40 μg/m3, respectively). More than 50,000 had a residential PM2.5 exposure below the U.S. EPA NAAQS (12 μg/m3). More than 25,000 subjects had a residential PM2.5 exposure below the WHO guideline (10 μg/m3). We found significant positive associations between PM2.5, NO2, and BC and natural-cause, respiratory, cardiovascular, and diabetes mortality. In our main model, the hazard ratios (HRs) (95% [confidence interval] CI) were 1.13 (CI = 1.11, 1.16) for an increase of 5 μg/m3 PM2.5, 1.09 (CI = 1.07, 1.10) for an increase of 10 μg/m3 NO2, and 1.08 (CI = 1.06, 1.10) for an increase of 0.5 × 10-5/m BC for natural-cause mortality. The highest HRs were found for diabetes mortality. Associations with O3 were negative, both in the fine spatial scale of the main ELAPSE model and in large spatial scale exposure models. For PM2.5, NO2, and BC, we generally observed a supralinear association with steeper slopes at low exposures and no evidence of a concentration below which no association was found. Subset analyses further confirmed that these associations remained at low levels: below 10 μg/m3 for PM2.5 and 20 μg/m3 for NO2. HRs were similar to the full cohort HRs for subjects with exposures below the EU limit values for PM2.5 and NO2, the U.S. NAAQS values for PM2.5, and the WHO guidelines for PM2.5 and NO2. The mortality associations were robust to alternative specifications of exposure, including different time periods, PM2.5 from the MAPLE project, and estimates from the local ESCAPE model. Time-varying exposure natural spline analyses confirmed associations at low pollution levels. HRs in two-pollutant models were attenuated but remained elevated and statistically significant for PM2.5 and NO2. In two-pollutant models of PM2.5 and NO2 HRs for natural-cause mortality were 1.08 (CI = 1.05, 1.11) for PM2.5 and 1.05 (CI = 1.03, 1.07) for NO2. Associations with O3 were attenuated but remained negative in two-pollutant models with NO2, BC, and PM2.5. We found significant positive associations between PM2.5, NO2, and BC and incidence of stroke and asthma and COPD hospital admissions. Furthermore, NO2 was significantly related to acute coronary heart disease and PM2.5 was significantly related to lung cancer incidence. We generally observed linear to supralinear associations with no evidence of a threshold, with the exception of the association between NO2 and acute coronary heart disease, which was sublinear. Subset analyses documented that associations remained even with PM2.5 below 20 μg/m3 and possibly 12 μg/m3. Associations remained even when NO2 was below 30 μg/m3 and in some cases 20 μg/m3. In two-pollutant models, NO2 was most consistently associated with acute coronary heart disease, stroke, asthma, and COPD hospital admissions. PM2.5 was not associated with these outcomes in two-pollutant models with NO2. PM2.5 was the only pollutant that was associated with lung cancer incidence in two-pollutant models. Associations with O3 were negative though generally not statistically significant. In the administrative cohorts, virtually all subjects in 2010 had PM2.5 and NO2 annual average exposures below the EU limit values. More than 3.9 million subjects had a residential PM2.5 exposure below the U.S. EPA NAAQS (12 μg/m3) and more than 1.9 million had residential PM2.5 exposures below the WHO guideline (10 μg/m3). We found significant positive associations between PM2.5, NO2, and BC and natural-cause, respiratory, cardiovascular, and lung cancer mortality, with moderate to high heterogeneity between cohorts. We found positive but statistically nonsignificant associations with diabetes mortality. In our main model meta-analysis, the HRs (95% CI) for natural-cause mortality were 1.05 (CI = 1.02, 1.09) for an increase of 5 μg/m3 PM2.5, 1.04 (CI = 1.02, 1.07) for an increase of 10 μg/m3 NO2, and 1.04 (CI = 1.02, 1.06) for an increase of 0.5 × 10-5/m BC, and 0.95 (CI = 0.93, 0.98) for an increase of 10 μg/m3 O3. The shape of the concentration-response functions differed between cohorts, though the associations were generally linear to supralinear, with no indication of a level below which no associations were found. Subset analyses documented that these associations remained at low levels: below 10 μg/m3 for PM2.5 and 20 μg/m3 for NO2. BC and NO2 remained significantly associated with mortality in two-pollutant models with PM2.5 and O3. The PM2.5 HR attenuated to unity in a two-pollutant model with NO2. The negative O3 association was attenuated to unity and became nonsignificant. The mortality associations were robust to alternative specifications of exposure, including time-varying exposure analyses. Time-varying exposure natural spline analyses confirmed associations at low pollution levels. Effect estimates in the youngest participants (<65 years at baseline) were much larger than in the elderly (>65 years at baseline). Effect estimates obtained with the ELAPSE PM2.5 model did not differ from the MAPLE PM2.5 model on average, but in individual cohorts, substantial differences were found.

CONCLUSIONS

Long-term exposure to PM2.5, NO2, and BC was positively associated with natural-cause and cause-specific mortality in the pooled cohort and the administrative cohorts. Associations were found well below current limit values and guidelines for PM2.5 and NO2. Associations tended to be supralinear, with steeper slopes at low exposures with no indication of a threshold. Two-pollutant models documented the importance of characterizing the ambient mixture with both NO2 and PM2.5. We mostly found negative associations with O3. In two-pollutant models with NO2, the negative associations with O3 were attenuated to essentially unity in the mortality analysis of the administrative cohorts and the incidence analyses in the pooled cohort. In the mortality analysis of the pooled cohort, significant negative associations with O3 remained in two-pollutant models. Long-term exposure to PM2.5, NO2, and BC was also positively associated with morbidity outcomes in the pooled cohort. For stroke, asthma, and COPD, positive associations were found for PM2.5, NO2, and BC. For acute coronary heart disease, an increased HR was observed for NO2. For lung cancer, an increased HR was found only for PM2.5. Associations mostly showed steeper slopes at low exposures with no indication of a threshold.

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.

Association between ambient particulate matter exposure and metabolic syndrome risk: A systematic review and meta-analysis

Although the association between ambient particulate matter and metabolic syndrome (MetS) has been investigated, the effect of particulate matter (PM) on MetS is inconclusive. We conducted a systematic review and meta-analysis to study the association between long-term ambient PM exposure and MetS risk. The data from five databases were extracted to analyze the association between ambient PM exposure and MetS risk. A random-effects model was performed to estimate the overall risk effect. The present systematic review and meta-analysis illustrated that an increase of 5 μg/m³ in annual PM_2.5 or PM₁₀ concentration was associated with 14% or 9% increases of MetS risk, respectively (PM_2.5, RR = 1.14, 95%CI [1.03, 1.25]; PM₁₀, RR = 1.09, 95%CI [1.00, 1.19]). The population-attributable risk (PAR) was 12.28% for PM_2.5 exposure or 8.26% for PM₁₀ exposure, respectively. There was statistical association between PM_2.5 exposure and risk of MetS in male proportion ≥50%, Asia, related disease or medication non-adjustment subgroup as well as cohort study subgroups, respectively. The significant association between PM₁₀ exposure and risk of MetS was observed in male proportion ≥50% and calories intake adjustment subgroups, respectively. Sensitivity analyses showed the robustness of our results. No publication bias was detected. In conclusion, there was positive association between long-term PM exposure and MetS risk. 12.28% of MetS risk could be attributable to PM_2.5 exposure.