Associations between combined urban and lifestyle factors and respiratory health in European children.

INTRODUCTION: Previous studies identified some environmental and lifestyle factors independently associated with children respiratory health, but few focused on exposure mixture effects. This study aimed at identifying, in pregnancy and in childhood, combined urban and lifestyle environment profiles associated with respiratory health in children. METHODS: This study is based on the European Human Early-Life Exposome (HELIX) project, combining six birth cohorts. Associations between profiles of pregnancy (38 exposures) and childhood (84 exposures) urban and lifestyle factors, identified by clustering analysis, and respiratory health were estimated by regression models adjusted for confounders. RESULTS: Among the 1033 included children (mean ± standard-deviation (SD) age: 8.2 ± 1.6 years old, 47% girls) the mean ± SD forced expiratory volume in 1s (FEV1) and forced vital capacity (FVC) were 99 ± 13% and 101 ± 14%, respectively, and 12%, 12% and 24% reported ever-asthma, wheezing and rhinitis, respectively. Four profiles of pregnancy exposures and four profiles of childhood exposures were identified. Compared to the reference childhood exposure profile (low exposures), two exposure profiles were associated with lower levels of FEV1. One profile was characterized by few natural spaces in the surroundings and high exposure to the built environment and road traffic. The second profile was characterized by high exposure to meteorological factors and low levels of all other exposures and was also associated with an increased risk of ever-asthma and wheezing. A pregnancy exposure profile characterized by high exposure levels to all risk factors, but a healthy maternal lifestyle, was associated with a lower risk of wheezing and rhinitis in children, compared to the reference pregnancy profile (low exposures). CONCLUSION: This comprehensive approach revealed pregnancy and childhood profiles of urban and lifestyle exposures associated with lung function and/or respiratory conditions in children. Our findings highlight the need to pursue the study of combined exposures to improve prevention strategies for multifactorial diseases such as asthma.

Short-term effects of air pollution and weather on physical activity in patients with chronic obstructive pulmonary disease (COPD).

INTRODUCTION: Patients with chronic obstructive pulmonary disease (COPD) accumulate low levels of physical activity. How environmental factors affect their physical activity in the short-term is uncertain. AIM: to assess the short-term effects of air pollution and weather on physical activity levels in COPD patients. METHODS: This multi-center panel study assessed 408 COPD patients from Catalonia (Spain). Daily physical activity (i.e., steps, time in moderate-to-vigorous physical activity (MVPA), locomotion intensity, and sedentary time) was recorded in two 7-day periods, one year apart, using the Dynaport MoveMonitor. Air pollution (nitrogen dioxide (NO2), particulate matter below 10 µm (PM10) and a marker of black carbon (absorbance of PM2.5: PM2.5ABS), and weather (average and maximum temperature, and rainfall) were estimated the same day (lag zero) and up to 5 days prior to each assessment (lags 1-5). Mixed-effect distributed lag linear regression models were adjusted for age, sex, weekday, public holidays, greenness, season, and social class, with patient and city as random effects. RESULTS: Patients (85% male) were on average (mean ± SD) 68 ± 9 years old with a post-bronchodilator forced expiratory volume in 1 s (FEV1) of 57 ± 18% predicted. Higher NO2, PM10 and PM2.5ABS levels at lag four were associated with fewer steps, less time in MVPA, reduced locomotion intensity, and longer sedentary time (e.g., coefficient (95% CI) of -60 (-105, -15) steps per 10 µg/m3 increase in NO2). Higher average and maximum temperatures at lag zero were related to more steps and time in MVPA, and less sedentary time (e.g., +85 (15, 154) steps per degree Celsius). Higher rainfall at lag zero was related to fewer steps and more sedentary time. CONCLUSION: Air pollution affects the amount and intensity of physical activity performed on the following days in COPD patients, whereas weather affects the amount of physical activity performed on the same day.

Early-life external exposome in children 2-5 years old in Colombia.

Exposome studies are advancing in high-income countries to understand how multiple environmental exposures impact health. However, there is a significant research gap in low- and middle-income and tropical countries. We aimed to describe the spatiotemporal variation of the external exposome, its correlation structure between and within exposure groups, and its dimensionality. A one-year follow-up cohort study of 506 children under 5 in two cities in Colombia was conducted to evaluate asthma, acute respiratory infections, and DNA damage. We examined 48 environmental exposures during pregnancy and 168 during childhood in eight exposure groups, including atmospheric pollutants, natural spaces, meteorology, built environment, traffic, indoor exposure, and socioeconomic capital. The exposome was estimated using geographic information systems, remote sensing, spatiotemporal modeling, and questionnaires. The median age of children at study entry was 3.7 years (interquartile range: 2.9-4.3). Air pollution and natural spaces exposure decreased from pregnancy to childhood, while socioeconomic capital increased. The highest median correlations within exposure groups were observed in meteorology (r = 0.85), traffic (r = 0.83), and atmospheric pollutants (r = 0.64). Important correlations between variables from different exposure groups were found, such as atmospheric pollutants and meteorology (r = 0.76), natural spaces (r = -0.34), and the built environment (r = 0.53). Twenty principal components explained 70%, and 57 explained 95% of the total variance in the childhood exposome. Our findings show that there is an important spatiotemporal variation in the exposome of children under 5. This is the first characterization of the external exposome in urban areas of Latin America and highlights its complexity, but also the need to better characterize and understand the exposome in order to optimize its analysis and applications in local interventions aimed at improving the health conditions and well-being of the child population and contributing to environmental health decision-making.

The methodology of quantitative risk assessment studies.

Once an external factor has been deemed likely to influence human health and a dose response function is available, an assessment of its health impact or that of policies aimed at influencing this and possibly other factors in a specific population can be obtained through a quantitative risk assessment, or health impact assessment (HIA) study. The health impact is usually expressed as a number of disease cases or disability-adjusted life-years (DALYs) attributable to or expected from the exposure or policy. We review the methodology of quantitative risk assessment studies based on human data. The main steps of such studies include definition of counterfactual scenarios related to the exposure or policy, exposure(s) assessment, quantification of risks (usually relying on literature-based dose response functions), possibly economic assessment, followed by uncertainty analyses. We discuss issues and make recommendations relative to the accuracy and geographic scale at which factors are assessed, which can strongly influence the study results. If several factors are considered simultaneously, then correlation, mutual influences and possibly synergy between them should be taken into account. Gaps or issues in the methodology of quantitative risk assessment studies include 1) proposing a formal approach to the quantitative handling of the level of evidence regarding each exposure-health pair (essential to consider emerging factors); 2) contrasting risk assessment based on human dose-response functions with that relying on toxicological data; 3) clarification of terminology of health impact assessment and human-based risk assessment studies, which are actually very similar, and 4) other technical issues related to the simultaneous consideration of several factors, in particular when they are causally linked.

Conditional Poisson Regression with Random Effects for the Analysis of Multi-site Time Series Studies.

The analysis of time series studies linking daily counts of a health indicator with environmental variables (e.g., mortality or hospital admissions with air pollution concentrations or temperature; or motor vehicle crashes with temperature) is usually conducted with Poisson regression models controlling for long-term and seasonal trends using temporal strata. When the study includes multiple zones, analysts usually apply a two-stage approach: first, each zone is analyzed separately, and the resulting zone-specific estimates are then combined using meta-analysis. This approach allows zone-specific control for trends. A one-stage approach uses spatio-temporal strata and could be seen as a particular case of the case-time series framework recently proposed. However, the number of strata can escalate very rapidly in a long time series with many zones. A computationally efficient alternative is to fit a conditional Poisson regression model, avoiding the estimation of the nuisance strata. To allow for zone-specific effects, we propose a conditional Poisson regression model with a random slope, although available frequentist software does not implement this model. Here, we implement our approach in the Bayesian paradigm, which also facilitates the inclusion of spatial patterns in the effect of interest. We also provide a possible extension to deal with overdispersed data. We first introduce the equations of the framework and then illustrate their application to data from a previously published study on the effects of temperature on the risk of motor vehicle crashes. We provide R code and a semi-synthetic dataset to reproduce all analyses presented.

Statistical Approaches to Study Exposome-Health Associations in the Context of Repeated Exposure Data: A Simulation Study.

The exposome concept aims to consider all environmental stressors simultaneously. The dimension of the data and the correlation that may exist between exposures lead to various statistical challenges. Some methodological studies have provided insight regarding the efficiency of specific modeling approaches in the context of exposome data assessed once for each subject. However, few studies have considered the situation in which environmental exposures are assessed repeatedly. Here, we conduct a simulation study to compare the performance of statistical approaches to assess exposome-health associations in the context of multiple exposure variables. Different scenarios were tested, assuming different types and numbers of exposure-outcome causal relationships. An application study using real data collected within the INMA mother-child cohort (Spain) is also presented. In the simulation experiment, assessed methods showed varying performance across scenarios, making it challenging to recommend a one-size-fits-all strategy. Generally, methods such as sparse partial least-squares and the deletion-substitution-addition algorithm tended to outperform the other tested methods (ExWAS, Elastic-Net, DLNM, or sNPLS). Notably, as the number of true predictors increased, the performance of all methods declined. The absence of a clearly superior approach underscores the additional challenges posed by repeated exposome data, such as the presence of more complex correlation structures and interdependencies between variables, and highlights that careful consideration is essential when selecting the appropriate statistical method. In this regard, we provide recommendations based on the expected scenario. Given the heightened risk of reporting false positive or negative associations when applying these techniques to repeated exposome data, we advise interpreting the results with caution, particularly in compromised contexts such as those with a limited sample size.

Ambient temperature and risk of motor vehicle crashes: A countrywide analysis in Spain.

BACKGROUND: Some studies have documented that cold or hot ambient temperatures increase the risk of motor vehicle crashes. However, the number of existing studies is still limited, especially for the effects of cold. OBJECTIVES: To estimate the relationship between ambient temperatures and risk of motor vehicle crashes in Spain, and to estimate the same association when restricting to those crashes with driver performance-associated factors (namely distraction, fatigue, sleepiness or disease). METHODS: We used data for the period 1993-2013. We conducted a time series analysis controlling for seasonality and trends and using the distributed lag nonlinear model framework to estimate nonlinear and delayed effects of up to 7 days. Analyses were conducted at the province level and combined using multivariate meta-analysis. RESULTS: The study included 1,908,460 motor vehicle crashes, 37% of them with associated driver performance factors. The overall analysis showed that the risk of crashes increased almost linearly with temperature. The estimates of the cumulative effect of lags 0-7 when comparing the 99th percentile and the first percentile of temperature produced a relative risk (RR) of 1.15 (95% confidence interval (CI): 1.11, 1.20). The estimates were slightly higher when analyses were restricted to crashes with driver performance-associated factors (RR: 1.23, 95% CI: 1.17, 1.30). In some provinces that reached temperatures below 0 °C, an increased risk with cold temperatures was also observed. An added effect of both cold spell and heat wave periods was found only in the analysis of crashes with driver performance-associated factors (cold spells, RR: 1.029, 95% CI: 1.005, 1.053; heat waves, RR: 1.020, 95% CI: 1.002, 1.039). CONCLUSIONS: The increase of temperature increased the risk of motor vehicle crashes in Spain. Measures aimed at reducing the influence of heat on the risk of motor vehicle crashes can have important benefits for public health.

Individual blood concentrations of persistent organic pollutants and chemical elements, and COVID-19: A prospective cohort study in Barcelona.

BACKGROUND: There is wide, largely unexplained heterogeneity in immunological and clinical responses to SARS-CoV-2 infection. Numerous environmental chemicals, such as persistent organic pollutants (POPs) and chemical elements (including some metals, essential trace elements, rare earth elements, and minority elements), are immunomodulatory and cause a range of adverse clinical events. There are no prospective studies on the effects of such substances on the incidence of SARS-CoV-2 infection and COVID-19. OBJECTIVE: To investigate the influence of blood concentrations of POPs and elements measured several years before the pandemic on the development of SARS-CoV-2 infection and COVID-19 in individuals from the general population. METHODS: We conducted a prospective cohort study in 154 individuals from the general population of Barcelona. POPs and elements were measured in blood samples collected in 2016-2017. SARS-CoV-2 infection was detected by rRT-PCR in nasopharyngeal swabs and/or by antibody serology using eighteen isotype-antigen combinations measured in blood samples collected in 2020-2021. We analyzed the associations between concentrations of the contaminants and SARS-CoV-2 infection and development of COVID-19, taking into account personal habits and living conditions during the pandemic. RESULTS: Several historically prevalent POPs, as well as arsenic, cadmium, mercury, and zinc, were not associated with COVID-19, nor with SARS-CoV-2 infection. However, DDE (adjusted OR = 5.0 [95% CI: 1.2-21]), lead (3.9 [1.0-15]), thallium (3.4 [1.0-11]), and ruthenium (5.0 [1.8-14]) were associated with COVID-19, as were tantalum, benzo(b)fluoranthene, DDD, and manganese. Thallium (3.8 [1.6-8.9]), and ruthenium (2.9 [1.3-6.7]) were associated with SARS-CoV-2 infection, and so were lead, gold, and (protectively) iron and selenium. We identified mixtures of up to five substances from several chemical groups, with all substances independently associated to the outcomes. CONCLUSIONS: Our results provide the first prospective and population-based evidence of an association between individual concentrations of some contaminants and COVID-19 and SARS-CoV-2 infection. POPs and elements may contribute to explain the heterogeneity in the development of SARS-CoV-2 infection and COVID-19 in the general population. If the associations are confirmed as causal, means are available to mitigate the corresponding risks.

Environmental exposures in early-life and general health in childhood.

BACKGROUND: Early-life environmental exposures are suspected to be involved in the development of chronic diseases later in life. Most studies conducted so far considered single or few exposures and single-health parameter. Our study aimed to identify a childhood general health score and assess its association with a wide range of pre- and post-natal environmental exposures. METHODS: The analysis is based on 870 children (6-12 years) from six European birth cohorts participating in the Human Early-Life Exposome project. A total of 53 prenatal and 105 childhood environmental factors were considered, including lifestyle, social, urban and chemical exposures. We built a general health score by averaging three sub-scores (cardiometabolic, respiratory/allergy and mental) built from 15 health parameters. By construct, a child with a low score has a low general health status. Penalized multivariable regression through Least Absolute Shrinkage and Selection Operator (LASSO) was fitted in order to identify exposures associated with the general health score. FINDINGS: The results of LASSO show that a lower general health score was associated with maternal passive and active smoking during pregnancy and postnatal exposure to methylparaben, copper, indoor air pollutants, high intake of caffeinated drinks and few contacts with friends and family. Higher child's general health score was associated with prenatal exposure to a bluespace near residency and postnatal exposures to pets, cobalt, high intakes of vegetables and more physical activity. Against our hypotheses, postnatal exposure to organochlorine compounds and perfluorooctanoate were associated with a higher child's general health score. CONCLUSION: By using a general health score summarizing the child cardiometabolic, respiratory/allergy and mental health, this study reinforced previously suspected environmental factors associated with various child health parameters (e.g. tobacco, air pollutants) and identified new factors (e.g. pets, bluespace) warranting further investigations.

Urban-rural differences in hypertension prevalence in low-income and middle-income countries, 1990-2020: A systematic review and meta-analysis.

BACKGROUND: The influence of urbanicity on hypertension prevalence remains poorly understood. We conducted a systematic review and meta-analysis to assess the difference in hypertension prevalence between urban and rural areas in low-income and middle-income countries (LMICs), where the most pronounced urbanisation is underway. METHODS AND FINDINGS: We searched PubMed, Web of Science, Scopus, and Embase, from 01/01/1990 to 10/03/2022. We included population-based studies with ≥400 participants 15 years and older, selected by using a valid sampling technique, from LMICs that reported the urban-rural difference in hypertension prevalence using similar blood pressure measurements. We excluded abstracts, reviews, non-English studies, and those with exclusively self-reported hypertension prevalence. Study selection, quality assessment, and data extraction were performed by 2 independent reviewers following a standardised protocol. Our primary outcome was the urban minus rural prevalence of hypertension. Hypertension was defined as systolic blood pressure ≥140 mm Hg and/or diastolic blood pressure as ≥90 mm Hg and could include use of antihypertensive medication, self-reported diagnosis, or both. We investigated heterogeneity using study-level and socioeconomic country-level indicators. We conducted meta-analysis and meta-regression using random-effects models. This systematic review and meta-analysis has been registered with PROSPERO (CRD42018091671). We included 299 surveys from 66 LMICs, including 19,770,946 participants (mean age 45.4 ± SD = 9 years, 53.0% females and 63.1% from rural areas). The pooled prevalence of hypertension was 30.5% (95% CI, 28.9, 32.0) in urban areas and 27.9% (95% CI, 26.3, 29.6) in rural areas, resulting in a pooled urban-rural difference of 2.45% (95% CI, 1.57, 3.33, I-square: 99.71%, tau-square: 0.00524, Pheterogeneity < 0.001). Hypertension prevalence increased over time and the rate of change was greater in rural compared to urban areas, resulting in a pooled urban-rural difference of 5.75% (95% CI, 4.02, 7.48) in the period 1990 to 2004 and 1.38% (95% CI, 0.40, 2.37) in the period 2005 to 2020, p < 0.001 for time period. We observed substantial heterogeneity in the urban-rural difference of hypertension, which was partially explained by urban-rural definition, probably high risk of bias in sampling, country income status, region, and socioeconomic indicators. The urban-rural difference was 5.67% (95% CI, 4.22, 7.13) in low, 2.74% (95% CI, 1.41, 4.07) in lower-middle and -1.22% (95% CI, -2.73, 0.28) in upper-middle-income countries in the period 1990 to 2020, p < 0.001 for country income. The urban-rural difference was highest for South Asia (7.50%, 95% CI, 5.73, 9.26), followed by sub-Saharan Africa (4.24%, 95% CI, 2.62, 5.86) and reversed for Europe and Central Asia (-6.04%, 95% CI, -9.06, -3.01), in the period 1990 to 2020, p < 0.001 for region. Finally, the urban-rural difference in hypertension prevalence decreased nonlinearly with improvements in Human Development Index and infant mortality rate. Limitations included lack of data available from all LMICs and variability in urban and rural definitions in the literature. CONCLUSIONS: The prevalence of hypertension in LMICs increased between 1990 and 2020 in both urban and rural areas, but with a stronger trend in rural areas. The urban minus rural hypertension difference decreased with time, and with country-level socioeconomic development. Focused action, particularly in rural areas, is needed to tackle the burden of hypertension in LMICs.

In Utero Exposure to Mercury Is Associated With Increased Susceptibility to Liver Injury and Inflammation in Childhood.

BACKGROUND AND AIMS: Nonalcoholic fatty liver disease (NAFLD) is the most prevalent cause of liver disease in children. Mercury (Hg), a ubiquitous toxic metal, has been proposed as an environmental factor contributing to toxicant-associated fatty liver disease. APPROACH AND RESULTS: We investigated the effect of prenatal exposure to Hg on childhood liver injury by combining epidemiological results from a multicenter mother-child cohort with complementary in vitro experiments on monocyte cells that are known to play a key role in liver immune homeostasis and NAFLD. We used data from 872 mothers and their children (median age, 8.1 years; interquartile range [IQR], 6.5-8.7) from the European Human Early-Life Exposome cohort. We measured Hg concentration in maternal blood during pregnancy (median, 2.0 µg/L; IQR, 1.1-3.6). We also assessed serum levels of alanine aminotransferase (ALT), a common screening tool for pediatric NAFLD, and plasma concentrations of inflammation-related cytokines in children. We found that prenatal Hg exposure was associated with a phenotype in children that was characterized by elevated ALT (≥22.1 U/L for females and ≥25.8 U/L for males) and increased concentrations of circulating IL-1ß, IL-6, IL-8, and TNF-α. Consistently, inflammatory monocytes exposed in vitro to a physiologically relevant dose of Hg demonstrated significant up-regulation of genes encoding these four cytokines and increased concentrations of IL-8 and TNF-α in the supernatants. CONCLUSIONS: These findings suggest that developmental exposure to Hg can contribute to inflammation and increased NAFLD risk in early life.

Short- and medium-term air pollution exposure, plasmatic protein levels and blood pressure in children.

Exposure to air pollution influences children's health, however, the biological mechanisms underlying these effects are not completely elucidated. We investigated the association between short- and medium-term outdoor air pollution exposure with protein profiles and their link with blood pressure in 1170 HELIX children aged 6-11 years. Different air pollutants (NO2, PM10, PM2.5, and PM2.5abs) were estimated based on residential and school addresses at three different windows of exposure (1-day, 1-week, and 1-year before clinical and molecular assessment). Thirty-six proteins, including adipokines, cytokines, or apolipoproteins, were measured in children's plasma using Luminex. Systolic and diastolic blood pressure (SBP and DBP) were measured following a standardized protocol. We performed an association study for each air pollutant at each location and time window and each outcome, adjusting for potential confounders. After correcting for multiple-testing, hepatocyte growth factor (HGF) and interleukin 8 (IL8) levels were positively associated with 1-week home exposure to some of the pollutants (NO2, PM10, or PM2.5). NO2 1-week home exposure was also related to higher SBP. The mediation study suggested that HGF could explain 19% of the short-term effect of NO2 on blood pressure, but other study designs are needed to prove the causal directionality between HGF and blood pressure.

Co-creating a local environmental epidemiology study: the case of citizen science for investigating air pollution and related health risks in Barcelona, Spain.

BACKGROUND: While the health risks of air pollution attract considerable attention, both scholarly and within the general population, citizens are rarely involved in environmental health research, beyond participating as data subjects. Co-created citizen science is an approach that fosters collaboration between scientists and lay people to engage the latter in all phases of research. Currently, this approach is rare in environmental epidemiology and when co-creation processes do take place, they are often not documented. This paper describes the first stages of an ongoing co-created citizen science epidemiological project in Barcelona (Spain), that included identifying topics that citizens wish to investigate as regards air pollution and health, formulating their concerns into research questions and co-designing the study protocol. This paper also reflects key trade-offs between scientific rigor and public engagement and provides suggestions to consider when applying citizen science to environmental health studies. METHODS: Experts created an online survey and analyzed responses with descriptive statistics and qualitative coding. A pop-up intervention was held to discuss with citizens their concerns about air pollution and health. Later on, a community meeting was organized to narrow down the research topics and list potential research questions. In an online survey, citizens were asked to vote for the research question they would like to investigate with the experts. A workshop was held to choose a study design in which citizens would like to partake to answer their preferred research question. RESULTS: According to 488 respondents from the first survey, cognitive and mental health were the main priorities of investigation. Based on the second survey, with 27% of the votes from 556 citizens, the most popular research question was, "How does air pollution together with noise and green/blue spaces affect mental health?". The study design selected was an observational study in which citizens provide daily repeated measures of different cognitive and mental health outcomes and relate them to the air pollution concentrations. CONCLUSIONS: Based on the co-creation activities and the results obtained, we conclude that applying citizen science in an environmental health project is valuable for researchers despite some challenges such as engaging citizens and maximizing representativity.

Associations of Air Pollution on the Brain in Children: A Brain Imaging Study.

Introduction: Epidemiological studies are highlighting the negative effects of the exposure to air pollution on children's neurodevelopment. However, most studies assessed children's neurodevelopment using neuropsychological tests or questionnaires. Using magnetic resonance imaging (MRI) to precisely measure global and region-specific brain development would provide details of brain morphology and connectivity. This would help us understand the observed cognitive and behavioral changes related to air pollution exposure. Moreover, most studies assessed only a few air pollutants. This project investigates whether air pollution exposure to many pollutants during pregnancy and childhood is associated with the morphology and connectivity of the brain in school-age children and pre-adolescents. Methods: We used data from the Generation R Study, a population-based birth cohort set up in Rotterdam, the Netherlands in 2002-2006 (n = 9,610). We used land-use regression (LUR) models to estimate the levels of 14 air pollutants at participant's homes during pregnancy and childhood: nitrogen oxides (NOx), nitrogen dioxide (NO2), particulate matter with aerodynamic diameter ≤10 µm (PM10) or ≤2.5 µm (PM2.5), PM between 10 µm and 2.5 µm (PMCOARSE), absorbance of the PM2.5 fraction - a measure of soot (PM2.5absorbance), the composition of PM2.5 such as polycyclic aromatic hydrocarbons (PAHs), organic carbon (OC), copper (Cu), iron (Fe), silicon (Si), zinc (Zn), and the oxidative potential of PM2.5 evaluated using two acellular methods: dithiothreitol (OPDTT) and electron spin resonance (OPESR). We performed MRI measurements of structural morphology (i.e., brain volumes, cortical thickness, and cortical surface area) using T1-weighted images in 6- to 10-year-old school-age children and 9- to 12-year-old pre-adolescents, structural connectivity (i.e., white matter microstructure) using diffusion tensor imaging (DTI) in pre-adolescents, and functional connectivity (i.e., connectivity score between brain areas) using resting-state functional MRI (rs-fMRI) in pre-adolescents. We assessed cognitive function using the Developmental Neuropsychological Assessment test (NEPSY-II) in school-age children. For each outcome, we ran regression analysis adjusted for several socioeconomic and lifestyle characteristics. We performed single-pollutant analyses followed by multipollutant analyses using the deletion/substitution/addition (DSA) approach. Results: The project has air pollution and brain MRI data for 783 school-age children and 3,857 pre-adolescents. First, exposure to air pollution during pregnancy or childhood was not associated with global brain volumes (e.g., total brain, cortical gray matter, and cortical white matter) in school-age children or pre-adolescents. However, higher pregnancy or childhood exposure to several air pollutants was associated with a smaller corpus callosum and hippocampus, and a larger amygdala, nucleus accumbens, and cerebellum in pre-adolescents, but not in school-age children. Second, higher exposure to several air pollutants during pregnancy was associated with a thinner cortex in various regions of the brain in both school-age children and pre-adolescents. Higher exposure to air pollution during childhood was also associated with a thinner cortex in a single region in pre-adolescents. A thinner cortex in two regions mediated the association between higher exposure to air pollution during pregnancy and an impaired inhibitory control in school-age children. Third, higher exposure to air pollution during childhood was associated with smaller cortical surface areas in various regions of the brain except in a region where we observed a larger cortical surface area in pre-adolescents. In relation to brain structural connectivity, higher exposure to air pollution during pregnancy and childhood was associated with an alteration in white matter microstructure in pre-adolescents. In relation to brain functional connectivity, a higher exposure to air pollution, mainly during pregnancy and early childhood, was associated with a higher brain functional connectivity among several brain regions in pre-adolescents. Overall, we identified several air pollutants associated with brain structural morphology, structural connectivity, and functional connectivity, such as NOx, NO2, PM of various size fractions (i.e., PM10, PMCOARSE, and PM2.5), PM2.5absorbance, PAHs, OC, three elemental components of PM2.5 (i.e., Cu, Si, Zn), and the oxidative potential of PM2.5. Conclusions: The results of this project suggest that exposure to air pollution during pregnancy and childhood play an adverse role in brain development. We observed this relationship even at levels of exposure that were below the European Union legislations. We acknowledge that identifying the independent effects of specific pollutants was particularly challenging. Most of our conclusions generally refer to traffic-related air pollutants. However, we did identify pollutants specifically originating from brake linings, tire wear, and tailpipe emissions from diesel combustion. The current direction toward innovative solutions for cleaner energy vehicles is a step in the right direction. However, our findings indicate that these measures might not be completely adequate to mitigate health problems attributable to traffic-related air pollution, as we also observed associations with markers of brake linings and tire wear.

Variability of multi-omics profiles in a population-based child cohort.

BACKGROUND: Multiple omics technologies are increasingly applied to detect early, subtle molecular responses to environmental stressors for future disease risk prevention. However, there is an urgent need for further evaluation of stability and variability of omics profiles in healthy individuals, especially during childhood. METHODS: We aimed to estimate intra-, inter-individual and cohort variability of multi-omics profiles (blood DNA methylation, gene expression, miRNA, proteins and serum and urine metabolites) measured 6 months apart in 156 healthy children from five European countries. We further performed a multi-omics network analysis to establish clusters of co-varying omics features and assessed the contribution of key variables (including biological traits and sample collection parameters) to omics variability. RESULTS: All omics displayed a large range of intra- and inter-individual variability depending on each omics feature, although all presented a highest median intra-individual variability. DNA methylation was the most stable profile (median 37.6% inter-individual variability) while gene expression was the least stable (6.6%). Among the least stable features, we identified 1% cross-omics co-variation between CpGs and metabolites (e.g. glucose and CpGs related to obesity and type 2 diabetes). Explanatory variables, including age and body mass index (BMI), explained up to 9% of serum metabolite variability. CONCLUSIONS: Methylation and targeted serum metabolomics are the most reliable omics to implement in single time-point measurements in large cross-sectional studies. In the case of metabolomics, sample collection and individual traits (e.g. BMI) are important parameters to control for improved comparability, at the study design or analysis stage. This study will be valuable for the design and interpretation of epidemiological studies that aim to link omics signatures to disease, environmental exposures, or both.

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

BACKGROUND: Ambient air pollution may play a role in childhood obesity development, but evidence is scarce, and the modifying role of socioeconomic status (SES) is unclear. We aimed to examine the association between exposure to air pollution during early childhood and subsequent risk of developing overweight and obesity, and to evaluate whether SES is a modifier of this association. METHODS: This longitudinal study included 416,955 children identified as normal weight between 2-5 years old and registered in an electronic primary healthcare record between 2006 and 2016 in Catalonia (Spain). Children were followed-up until they developed overweight or obesity, reached 15 years of age, died, transferred out, or end of study period (31/12/2018). Overweight and obesity were defined following the WHO reference obtained from height and weight measures. We estimated annual residential census levels of nitrogen dioxide (NO2) and particulate matter <10 µm (PM10), <2.5 µm (PM2.5), and 2.5-10 µm (PMcoarse) at study entry. We estimated the risk of developing overweight and obesity per interquartile range increase in air pollution exposure with Cox proportional hazard models. RESULTS: A total of 142,590 (34.2%) children developed overweight or obesity. Increased exposure to NO2, PM10, and PMcoarse was associated with a 2-3% increased risk of developing overweight and obesity (hazard ratio [HR] per 21.8 µg/m3 NO2 = 1.03 [95% CI: 1.02-1.04]; HR per 6.4 µg/m3 PM10 = 1.02 [95% CI: 1.02-1.03]; HR per 4.6 µg/m3 PMcoarse = 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.

Prenatal Exposure to Perfluoroalkyl Substances Associated With Increased Susceptibility to Liver Injury in Children.

BACKGROUND AND AIMS: Per- and polyfluoroalkyl substances (PFAS) are widespread and persistent pollutants that have been shown to have hepatotoxic effects in animal models. However, human evidence is scarce. We evaluated how prenatal exposure to PFAS associates with established serum biomarkers of liver injury and alterations in serum metabolome in children. APPROACH AND RESULTS: We used data from 1,105 mothers and their children (median age, 8.2 years; interquartile range, 6.6-9.1) from the European Human Early-Life Exposome cohort (consisting of six existing population-based birth cohorts in France, Greece, Lithuania, Norway, Spain, and the United Kingdom). We measured concentrations of perfluorooctane sulfonate, perfluorooctanoate, perfluorononanoate, perfluorohexane sulfonate, and perfluoroundecanoate in maternal blood. We assessed concentrations of alanine aminotransferase, aspartate aminotransferase, and gamma-glutamyltransferase in child serum. Using Bayesian kernel machine regression, we found that higher exposure to PFAS during pregnancy was associated with higher liver enzyme levels in children. We also measured child serum metabolomics through a targeted assay and found significant perturbations in amino acid and glycerophospholipid metabolism associated with prenatal PFAS. A latent variable analysis identified a profile of children at high risk of liver injury (odds ratio, 1.56; 95% confidence interval, 1.21-1.92) that was characterized by high prenatal exposure to PFAS and increased serum levels of branched-chain amino acids (valine, leucine, and isoleucine), aromatic amino acids (tryptophan and phenylalanine), and glycerophospholipids (phosphatidylcholine [PC] aa C36:1 and Lyso-PC a C18:1). CONCLUSIONS: Developmental exposure to PFAS can contribute to pediatric liver injury.

Public Transport Strikes and Their Relationships With Air Pollution, Mortality, and Hospital Admissions.

There is limited suggestive evidence of relationships between public transport strikes and either increased air pollution or worse population health. In this study we aimed to assess whether public transport strikes were associated with increases in health events (overall, cardiovascular and respiratory mortality, and cardiovascular and respiratory hospitalizations). We also explored whether air pollution mediated those associations. We used data from the city of Barcelona (Spain) for the period 2005-2016 on strikes, health events, and ambient air pollution (nitrogen dioxide, nitrogen monoxide, particulate matter (PM) with an aerodynamic diameter ≤10 µm, PM with an aerodynamic diameter ≤2.5µm, PM with an aerodynamic diameter ≤1µm, number of particles with a diameter greater than 5 nm per cm3 (particle number concentration), and black carbon). We used linear and quasi-Poisson regression models to explore the associations between air pollution and public transport strikes and between public transport strikes and health outcomes. We also investigated potential causal mediation by air pollution. Overall, this study suggested that public transport strikes are associated with increased overall mortality, respiratory mortality, and respiratory hospitalizations. However, our findings suggest that such increases are not mediated by the increase in air pollution. Our results indicate the need to further investigate these relationships and potential mechanisms.

Comprehensive study of the exposome and omic data using rexposome Bioconductor Packages.

SUMMARY: Genomics has dramatically improved our understanding of the molecular origins of certain human diseases. Nonetheless, our health is also influenced by the cumulative impact of exposures experienced across the life course (termed 'exposome'). The study of the high-dimensional exposome offers a new paradigm for investigating environmental contributions to disease etiology. However, there is a lack of bioinformatics tools for managing, visualizing and analyzing the exposome. The analysis data should include both association with health outcomes and integration with omic layers. We provide a generic framework called rexposome project, developed in the R/Bioconductor architecture that includes object-oriented classes and methods to leverage high-dimensional exposome data in disease association studies including its integration with a variety of high-throughput data types. The usefulness of the package is illustrated by analyzing a real dataset including exposome data, three health outcomes related to respiratory diseases and its integration with the transcriptome and methylome. AVAILABILITY AND IMPLEMENTATION: rexposome project is available at https://isglobal-brge.github.io/rexposome/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Correlation between work impairment, scores of rhinitis severity and asthma using the MASK-air® App.

BACKGROUND: In allergic rhinitis, a relevant outcome providing information on the effectiveness of interventions is needed. In MASK-air (Mobile Airways Sentinel Network), a visual analogue scale (VAS) for work is used as a relevant outcome. This study aimed to assess the performance of the work VAS work by comparing VAS work with other VAS measurements and symptom-medication scores obtained concurrently. METHODS: All consecutive MASK-air users in 23 countries from 1 June 2016 to 31 October 2018 were included (14 189 users; 205 904 days). Geolocalized users self-assessed daily symptom control using the touchscreen functionality on their smart phone to click on VAS scores (ranging from 0 to 100) for overall symptoms (global), nose, eyes, asthma and work. Two symptom-medication scores were used: the modified EAACI CSMS score and the MASK control score for rhinitis. To assess data quality, the intra-individual response variability (IRV) index was calculated. RESULTS: A strong correlation was observed between VAS work and other VAS. The highest levels for correlation with VAS work and variance explained in VAS work were found with VAS global, followed by VAS nose, eye and asthma. In comparison with VAS global, the mCSMS and MASK control score showed a lower correlation with VAS work. Results are unlikely to be explained by a low quality of data arising from repeated VAS measures. CONCLUSIONS: VAS work correlates with other outcomes (VAS global, nose, eye and asthma) but less well with a symptom-medication score. VAS work should be considered as a potentially useful AR outcome in intervention studies.