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Background: Air pollution exposure has been linked with increased risk of preterm birth, which is one of the leading causes of infant mortality. Limited studies have attempted to explore these associations in low-polluted areas. In this study, we aimed to assess the association between short-term exposure to ambient air pollution and preterm birth in Sweden., Method: In this population-based study we included preterm births between 2014 and 2019 from the Swedish Pregnancy Register. We applied a spatiotemporal model to estimate daily levels of particulate matter <2.5 μm (PM 2.5 ), PM < 10 μm (PM 10 ), nitrogen dioxide (NO 2), and ozone (O 3 ) at the residential address of each participant. We applied a time-stratified case-crossover design with conditional logistic regression analysis to estimate odds ratios (OR) of preterm birth per 10 μg/m 3 (PM 10 , NO 2 , O 3 ) and 5 μg/m 3 (PM 2.5 ) increase in air pollution exposure at 0-6-day lag. Two-pollutant models were applied to evaluate the independent association of each exposure on preterm birth. We also stratified by maternal characteristics to identify potential effect modifiers., Results: 28,216 (4.5%) preterm births were included. An increase in O 3 exposure was associated with increased odds of preterm birth [OR = 1.06 per 10 μg/m 3 (95% CI, 1.02; 1.10]. PM 2.5 and PM 10 were not significantly associated with preterm birth, and NO 2 displayed a negative nonlinear association with preterm birth. We did not observe any notable effect modification, but we found suggestive larger associations between O 3 and preterm birth when stratifying by male sex, spontaneous delivery, and spring season., Conclusions: Increased O 3 exposure one week before delivery was associated with an increased risk of preterm birth in Sweden, a country with levels of air pollution below the current World Health Organization air quality guidelines. Increases in O 3 levels with climate change make these findings especially concerning., (Copyright © 2024 The Authors. Published by Elsevier GmbH.. All rights reserved.)

Background: The evidence for acute effects of air pollution on mortality in India is scarce, despite the extreme concentrations of air pollution observed. This is the first multi-city study in India that examines the association between short-term exposure to PM 2·5 and daily mortality using causal methods that highlight the importance of locally generated air pollution., Methods: We applied a time-series analysis to ten cities in India between 2008 and 2019. We assessed city-wide daily PM 2·5 concentrations using a novel hybrid nationwide spatiotemporal model and estimated city-specific effects of PM 2·5 using a generalised additive Poisson regression model. City-specific results were then meta-analysed. We applied an instrumental variable causal approach (including planetary boundary layer height, wind speed, and atmospheric pressure) to evaluate the causal effect of locally generated air pollution on mortality. We obtained an integrated exposure-response curve through a multivariate meta-regression of the city-specific exposure-response curve and calculated the fraction of deaths attributable to air pollution concentrations exceeding the current WHO 24 h ambient PM 2·5 guideline of 15 μg/m 3 . To explore the shape of the exposure-response curve at lower exposures, we further limited the analyses to days with concentrations lower than the current Indian standard (60 μg/m 3 )., Findings: We observed that a 10 μg/m 3 increase in 2-day moving average of PM 2·5 was associated with 1·4% (95% CI 0·7-2·2) higher daily mortality. In our causal instrumental variable analyses representing the effect of locally generated air pollution, we observed a stronger association with daily mortality (3·6% [2·1-5·0]) than our overall estimate. Our integrated exposure-response curve suggested steeper slopes at lower levels of exposure and an attenuation of the slope at high exposure levels. We observed two times higher risk of death per 10 μg/m 3 increase when restricting our analyses to observations below the Indian air quality standard (2·7% [1·7-3·6]). Using the integrated exposure-response curve, we observed that 7·2% (4·2%-10·1%) of all daily deaths were attributed to PM 2·5 concentrations higher than the WHO guidelines., Interpretation: Short-term PM 2·5 exposure was associated with a high risk of death in India, even at concentrations well below the current Indian PM 2·5 standard. These associations were stronger for locally generated air pollutants quantified through causal modelling methods than conventional time-series analysis, further supporting a plausible causal link., Funding: Swedish Research Council for Sustainable Development., Competing Interests: Declaration of interests PP reports working as a consultant for World Bank for climate change and health outcomes. GAW reports receiving consulting income from the Health Efects Institute and Google. PL has received air travel and hotel accommodation paid by Fondazione Menarini to attend and hold a presentation at the Respirami meeting in Milan. He is the Scientific Secretary of the Swedish Society of Cardiology and co-chair of the European Chapter of International Society of Environmental Epidemiology (both unpaid). He was a paid member of the ethical committee board for the Swedish Ethical Authority 2022–23. All other authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

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 (NO 2 ), particulate matter <10 μm (PM 10 ) and <2.5 μm (PM 2.5 )) 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 NO 2  = 0.10(95%CI 0.09; 0.12), β PM 2.5 0.06(0.04; 0.07), β PM 10 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., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Introduction: The complex interplay of multiple environmental factors and cardiovascular has scarcely been studied. Within the EXPANSE project, we evaluated the association between long-term exposure to multiple environmental indices and stroke incidence across Europe., Methods: Participants from three traditional adult cohorts (Germany, Netherlands and Sweden) and four administrative cohorts (Catalonia [region Spain], Rome [city-wide], Greece and Sweden [nationwide]) were followed until incident stroke, death, migration, loss of follow-up or study end. We estimated exposures at residential addresses from different exposure domains: air pollution (nitrogen dioxide (NO 2 ), particulate matter < 2.5 μm (PM 2.5 ), black carbon (BC), ozone), built environment (green/blue spaces, impervious surfaces) and meteorology (seasonal mean and standard deviation of temperatures). Associations between environmental exposures and stroke were estimated in single and multiple-exposure Cox proportional hazard models, and Principal Component (PC) Analyses derived prototypes for specific exposures domains. We carried out random effects meta-analyses by cohort type., Results: In over 15 million participants, increased levels of NO 2 and BC were associated with increased higher stroke incidence in both cohort types. Increased Normalized Difference Vegetation Index (NDVI) was associated with a lower stroke incidence in both cohort types, whereas an increase in impervious surface was associated with an increase in stroke incidence. The first PC of the air pollution domain (PM 2.5 , NO 2 and BC) was associated with an increase in stroke incidence. For the built environment, higher levels of NDVI and lower levels of impervious surfaces were associated with a protective effect [%change in HR per 1 unit = -2.0 (95 %CI, -5.9;2.0) and -1.1(95 %CI, -2.0; -0.3) for traditional adult and administrative cohorts, respectively]. No clear patterns were observed for distance to blue spaces or temperature parameters., Conclusions: We observed increased HRs for stroke with exposure to PM 2.5 , NO 2 and BC, lower levels of greenness and higher impervious surface in single and combined exposure models., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Residential relocation is increasingly used as a natural experiment in epidemiological studies to assess the health impact of changes in environmental exposures. Since the likelihood of relocation can be influenced by individual characteristics that also influence health, studies may be biased if the predictors of relocation are not appropriately accounted for. Using data from Swedish and Dutch adults (SDPP, AMIGO), and birth cohorts (BAMSE, PIAMA), we investigated factors associated with relocation and changes in multiple environmental exposures across life stages. We used logistic regression to identify baseline predictors of moving, including sociodemographic and household characteristics, health behaviors and health. We identified exposure clusters reflecting three domains of the urban exposome (air pollution, grey surface, and socioeconomic deprivation) and conducted multinomial logistic regression to identify predictors of exposome trajectories among movers. On average, 7 % of the participants relocated each year. Before relocating, movers were consistently exposed to higher levels of air pollution than non-movers. Predictors of moving differed between the adult and birth cohorts, highlighting the importance of life stages. In the adult cohorts, moving was associated with younger age, smoking, and lower education and was independent of cardio-respiratory health indicators (hypertension, BMI, asthma, COPD). Contrary to adult cohorts, higher parental education and household socioeconomic position were associated with a higher probability of relocation in birth cohorts, alongside being the first child and living in a multi-unit dwelling. Among movers in all cohorts, those with a higher socioeconomic position at baseline were more likely to move towards healthier levels of the urban exposome. We provide new insights into predictors of relocation and subsequent changes in multiple aspects of the urban exposome in four cohorts covering different life stages in Sweden and the Netherlands. These results inform strategies to limit bias due to residential self-selection in epidemiological studies using relocation as a natural experiment., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: The association between air pollution and green spaces with breast cancer risk stratified by menopausal status has not been frequently investigated despite its importance given the different impact of risk factors on breast cancer risk depending on menopausal status., Objectives: To study the association between air pollution, green spaces and pre and postmenopausal breast cancer risk., Methods: We conducted a population-based cohort study using electronic primary care records in Catalonia. We included women aged 17-85 years free of cancer at study entry between 2009 and 2017. Our exposures were particulate matter <2.5 μm (PM 2.5 ) & <10 μm (PM 10 ), nitrogen dioxide (NO 2 ), normalized difference vegetation index (NDVI), and percentage of green spaces estimated at the census tract level. Breast cancer was identified with ICD-10 code C50. We estimated cause-specific hazard ratios (HR) for the relationship between each individual exposure and pre and postmenopausal breast cancer risk, using linear and non-linear models., Results: Of the 1,054,180 pre and 744,658 postmenopausal women followed for a median of 10 years, 6,126 and 17,858 developed breast cancer, respectively. Among premenopausal women, only very high levels of PM 10 (≥46 μg/m 3 ) were associated with increased cancer risk (compared to lower levels) in non-linear models. Among postmenopausal women, an interquartile range increase in PM 2.5 (HR:1.03; 95%CI:1.01-1.04), PM 10 (1.03; 1.01-1.05), and NO 2 (1.05; 1.02-1.08) were associated with higher cancer risk. NDVI was negatively associated with decreased cancer risk only among postmenopausal women who did not change residence during follow-up (0.84; 0.71-0.99) or who were followed for at least three years (0.82; 0.69-0.98)., Discussion: Living in areas with high concentrations of PM 2.5 , PM 10 , and NO 2 increases breast cancer risk in postmenopausal women while long-term exposure to green spaces may decrease this risk. Only very high concentrations of PM 10 increase breast cancer risk in premenopausal women., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Previous studies have explored the relationships of air pollution and metabolic profiles with lung function. However, the metabolites linking air pollution and lung function and the associated mechanisms have not been reviewed from a life-course perspective. Here, we provide a narrative review summarising recent evidence on the associations of metabolic profiles with air pollution exposure and lung function in children and adults. Twenty-six studies identified through a systematic PubMed search were included with 10 studies analysing air pollution-related metabolic profiles and 16 studies analysing lung function-related metabolic profiles. A wide range of metabolites were associated with short- and long-term exposure, partly overlapping with those linked to lung function in the general population and with respiratory diseases such as asthma and COPD. The existing studies show that metabolomics offers the potential to identify biomarkers linked to both environmental exposures and respiratory outcomes, but many studies suffer from small sample sizes, cross-sectional designs, a preponderance on adult lung function, heterogeneity in exposure assessment, lack of confounding control and omics integration. The ongoing EXposome Powered tools for healthy living in urbAN Settings (EXPANSE) project aims to address some of these shortcomings by combining biospecimens from large European cohorts and harmonised air pollution exposure and exposome data., Competing Interests: Conflict of interest: M.G.M. Pinho reports a Leadership or fiduciary role in other board, society, committee or advocacy group, paid or unpaid as an Associate editor at the journal Public Health Nutrition. C.E. Wheelock has received support for the present manuscript from Swedish Heart Lung Foundation. M. Chadeau-Hyam has shares in the OSMOSE consulting company; work performed in the company has no link with the present work. N. Probst-Hensch reports salary support from Swiss TPH Core Funds. The remaining authors have nothing to disclose., (Copyright ©The authors 2022.)

The available evidence on the effects of ambient air pollution on cardiovascular diseases (CVDs) has increased substantially. In this umbrella review, we summarized the current epidemiological evidence from systematic reviews and meta-analyses linking ambient air pollution and CVDs, with a focus on geographical differences and vulnerable subpopulations. We performed a search strategy through multiple databases including articles between 2010 and 31 January 2021. We performed a quality assessment and evaluated the strength of evidence. Of the 56 included reviews, the most studied outcomes were stroke (22 reviews), all-cause CVD mortality, and morbidity (19). The strongest evidence was found between higher short- and long-term ambient air pollution exposure and all-cause CVD mortality and morbidity, stroke, blood pressure, and ischemic heart diseases (IHD). Short-term exposures to particulate matter <2.5 μm (PM 2.5 ), <10 μm (PM 10 ), and nitrogen oxides (NO x ) were consistently associated with increased risks of hypertension and triggering of myocardial infarction (MI), and stroke (fatal and nonfatal). Long-term exposures of PM 2.5 were largely associated with increased risk of atherosclerosis, incident MI, hypertension, and incident stroke and stroke mortality. Few reviews evaluated other CVD outcomes including arrhythmias, atrial fibrillation, or heart failure but they generally reported positive statistical associations. Stronger associations were found in Asian countries and vulnerable subpopulations, especially among the elderly, cardiac patients, and people with higher weight status. Consistent with experimental data, this comprehensive umbrella review found strong evidence that higher levels of ambient air pollution increase the risk of CVDs, especially all-cause CVD mortality, stroke, and IHD. These results emphasize the importance of reducing the alarming levels of air pollution across the globe, especially in Asia, and among vulnerable subpopulations., (© 2022 The Authors. Journal of Internal Medicine published by John Wiley & Sons Ltd on behalf of Association for Publication of The Journal of Internal Medicine.)

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/km 2 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., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Ambient air pollution may play a role in childhood obesity development, but evidence is scarce, and the modifying role of socioeconomic status (SES) is unclear. We aimed to examine the association between exposure to air pollution during early childhood and subsequent risk of developing overweight and obesity, and to evaluate whether SES is a modifier of this association., Methods: This longitudinal study included 416,955 children identified as normal weight between 2-5 years old and registered in an electronic primary healthcare record between 2006 and 2016 in Catalonia (Spain). Children were followed-up until they developed overweight or obesity, reached 15 years of age, died, transferred out, or end of study period (31/12/2018). Overweight and obesity were defined following the WHO reference obtained from height and weight measures. We estimated annual residential census levels of nitrogen dioxide (NO 2 ) and particulate matter <10 μm (PM 10 ), <2.5 μm (PM 2.5 ), and 2.5-10 μm (PM coarse ) at study entry. We estimated the risk of developing overweight and obesity per interquartile range increase in air pollution exposure with Cox proportional hazard models., Results: A total of 142,590 (34.2%) children developed overweight or obesity. Increased exposure to NO 2 , PM 10 , and PM coarse was associated with a 2-3% increased risk of developing overweight and obesity (hazard ratio [HR] per 21.8 μg/m 3 NO 2  = 1.03 [95% CI: 1.02-1.04]; HR per 6.4 μg/m 3 PM 10  = 1.02 [95% CI: 1.02-1.03]; HR per 4.6 µg/m 3 PM coarse  = 1.02, [95% CI: 1.01-1.02]). For all air pollutants, associations were stronger among children living in most compared to least deprived areas., Conclusions: This study suggests that early life exposure to air pollution may be associated with a small increase in the risk of developing overweight and obesity in childhood, and that this association may be exacerbated in the most deprived areas. Even these small associations are of potential global health importance because air pollution exposure is widespread and the long-term health consequences of childhood obesity are clear.

Urban environments are characterized by multiple exposures that may influence body mass index (BMI) growth in early life. Previous studies are few, with inconsistent results and no evaluation of simultaneous exposures. Thus, this study aimed to assess the associations between exposure to air pollution, green spaces and built environment characteristics, and BMI growth trajectories from 0 to 5 years. This longitudinal study used data from an electronic primary care health record database in Catalonia (Spain), including 79,992 children born between January 01, 2011 and December 31, 2012 in urban areas and followed until 5 years of age. Height and weight were measured frequently during childhood and BMI (kg/m 2 ) was calculated. Urban exposures were estimated at census tract level and included: air pollution (nitrogen dioxide (NO 2 ), particulate matter <10 μm (PM 10 ) and <2.5 μm (PM 2.5) ), green spaces (Normalized Difference Vegetation Index (NDVI) and % green space) and built environment (population density, street connectivity, land use mix, walkability index). Individual BMI trajectories were estimated using linear spline multilevel models with several knot points. In single exposure models, NO 2, PM 10, PM 2.5, and population density were associated with small increases in BMI growth (e.g. β per IQR PM 10 increase = 0.023 kg/m 2 , 95%CI: 0.013, 0.033), and NDVI, % of green spaces and land use mix with small reductions in BMI growth (e.g. β per IQR % green spaces increase = -0.015 kg/m 2, 95%CI: -0.026, -0.005). These associations were strongest during the first two months of life. In multiple exposure models, most associations were attenuated, with only those for PM 10 and land use mix remaining statistically significant. This large longitudinal study suggests that early life exposure to air pollution, green space and built environment characteristics may be associated with small changes in BMI growth trajectories during the first years of life, and that it is important to account for multiple exposures in urban settings., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

The human exposome affects child development and health later in life, but its personal external levels, variability, and correlations are largely unknown. We characterized the personal external exposome of pregnant women and children in eight European cities. Panel studies included 167 pregnant women and 183 children (aged 6-11 years). A personal exposure monitoring kit composed of smartphone, accelerometer, ultraviolet (UV) dosimeter, and two air pollution monitors were used to monitor physical activity (PA), fine particulate matter (PM 2.5 ), black carbon, traffic-related noise, UV-B radiation, and natural outdoor environments (NOE). 77% of women performed the adult recommendation of ≥150 min/week of moderate to vigorous PA (MVPA), while only 3% of children achieved the childhood recommendation of ≥60 min/day MVPA. 11% of women and 17% of children were exposed to daily PM 2.5 levels higher than recommended (≥25μg/m 3 ). Mean exposure to noise ranged from Lden 51.1 dB in Kaunas to Lden 65.2 dB in Barcelona. 4% of women and 23% of children exceeded the recommended maximum of 2 Standard-Erythemal-Dose of UV-B at least once a week. 33% of women and 43% of children never reached the minimum NOE contact recommendation of ≥30 min/week. The variations in air and noise pollution exposure were dominated by between-city variability, while most of the variation observed for NOE contact and PA was between-participants. The correlations between all personal exposures ranged from very low to low (Rho < 0.30). The levels of personal external exposures in both pregnant women and children are above the health recommendations, and there is little correlation between the different exposures. The assessment of the personal external exposome is feasible but sampling requires from one day to more than one year depending on exposure due to high variability between and within cities and participants., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Background: Ambient air pollution may increase the risk of overweight and obesity in children. However, available evidence is still scarce and has mainly focused on ambient air pollution exposure occurring at home without considering the school environment. The aim of this study is to assess whether exposure to ambient air pollution at home and school is associated with overweight and obesity in primary school children., Methods: We studied 2660 children aged 7-10 years during 2012 in Barcelona. Child weight and height were measured and age- and sex-specific z-scores for body mass index (zBMI) were calculated using the WHO growth reference 2007. Overweight and obesity were defined using the same reference. Land use regression models were used to estimate levels of nitrogen dioxide (NO 2 ), particulate matter <2.5 μm (PM 2.5 ), <10 μm (PM 10 ) and coarse (PM coarse ) at home. Outdoor levels of NO 2 , PM 2.5 , elemental carbon (EC), and ultrafine particles (UFP) were measured in the schoolyard. Multilevel mixed linear and ordered logistic models were used to assess the association between ambient air pollution (continuous per interquartile range (IQR) increase and categorical with tertile cutoffs) and zBMI (continuous and ordinal: normal, overweight, obese), after adjusting for socio-demographic characteristics., Results: An IQR increase in PM 10 -home (5.6 μg/m 3 ) was associated with a 10% increase in the odds of being overweight or obese (odds ratio (OR) = 1.10; 95% CI = 1.00, 1.22). Children exposed to the highest tertile of UFP-school (>27,346 particles/cm 3 ) had a 30% higher odds of being overweight or obese (OR = 1.30; 95%CI = 1.03, 1.64) compared to the lowest tertile of UFP exposure. We also observed that exposure to NO 2 , PM 2.5 or EC at schools was associated with higher odds of overweight or obese at medium compared to low levels of exposure. Home and school exposures did not show any significant associations with zBMI (except PM 2.5 -school comparing tertile 2 vs tertile 1) but were similar in direction., Conclusions: This study suggests that exposure to ambient air pollution, especially at school, is associated with childhood risk for overweight and obesity. A cautious interpretation is warranted because associations were not always linear and because school and home air pollution measurements were not directly comparable., (Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.)