PurposeEssential to exposome research is the collection of data on many environmental exposures from different domains in the same subjects. The aim of the Human Early Life Exposome (HELIX) study was to measure and describe multiple environmental exposures during early life (pregnancy and childhood) in a prospective cohort and associate these exposures with molecular omics signatures and child health outcomes. Here, we describe recruitment, measurements available and baseline data of the HELIX study populations.ParticipantsThe HELIX study represents a collaborative project across six established and ongoing longitudinal population-based birth cohort studies in six European countries (France, Greece, Lithuania, Norway, Spain and the UK). HELIX used a multilevel study design with the entire study population totalling 31 472 mother-child pairs, recruited during pregnancy, in the six existing cohorts (first level); a subcohort of 1301 mother-child pairs where biomarkers, omics signatures and child health outcomes were measured at age 6–11 years (second level) and repeat-sampling panel studies with around 150 children and 150 pregnant women aimed at collecting personal exposure data (third level).Findings to dateCohort data include urban environment, hazardous substances and lifestyle-related exposures for women during pregnancy and their offspring from birth until 6–11 years. Common, standardised protocols were used to collect biological samples, measure exposure biomarkers and omics signatures and assess child health across the six cohorts. Baseline data of the cohort show substantial variation in health outcomes and determinants between the six countries, for example, in family affluence levels, tobacco smoking, physical activity, dietary habits and prevalence of childhood obesity, asthma, allergies and attention deficit hyperactivity disorder.Future plansHELIX study results will inform on the early life exposome and its association with molecular omics signatures and child health outcomes. Cohort data are accessible for future research involving researchers external to the project.

Traditional methods of exposure assessment in epidemiological studies often fail to integrate important information on activity patterns, which may lead to bias, loss of statistical power or both in health effects estimates. Novel sensing technologies integrated with mobile phones offer potential to reduce exposure measurement error. We sought to demonstrate the usability and relevance of the CalFit smartphone technology to track person-level time, geographic location, and physical activity patterns for improved air pollution exposure assessment. We deployed CalFit-equipped smartphones in a free living-population of 36 subjects in Barcelona, Spain. Information obtained on physical activity and geographic location was linked to space-time air pollution mapping. For instance, we found on average travel activities accounted for 6% of people’s time and 24% of their daily inhaled NO2. Due to the large number of mobile phone users, this technology potentially provides an unobtrusive means of collecting epidemiologic exposure data at low cost.

Background:By 2050, nearly 70% of the global population is projected to live in urban areas. Because the environments we inhabit affect our health, urban and transport designs that promote healthy living are needed.Objective:We estimated the number of premature deaths preventable under compliance with international exposure recommendations for physical activity (PA), air pollution, noise, heat, and access to green spaces.Methods:We developed and applied the Urban and TranspOrt Planning Health Impact Assessment (UTOPHIA) tool to Barcelona, Spain. Exposure estimates and mortality data were available for 1,357,361 residents. We compared recommended with current exposure levels. We quantified the associations between exposures and mortality and calculated population attributable fractions to estimate the number of premature deaths preventable. We also modeled life-expectancy and economic impacts.Results:We estimated that annually, nearly 20% of mortality could be prevented if international recommendations for performance of PA; exposure to air pollution, noise, and heat; and access to green space were followed. Estimations showed that the greatest portion of preventable deaths was attributable to increases in PA, followed by reductions of exposure to air pollution, traffic noise, and heat. Access to green spaces had smaller effects on mortality. Compliance was estimated to increase the average life expectancy by 360 (95% CI: 219, 493) days and result in economic savings of 9.3 (95% CI: 4.9, 13.2) billion EUR/year.Conclusions:PA factors and environmental exposures can be modified by changes in urban and transport planning. We emphasize the need for a) the reduction of motorized traffic through the promotion of active and public transport and b) the provision of green infrastructure, both of which are suggested to provide opportunities for PA and for mitigation of air pollution, noise, and heat.Citation:Mueller N, Rojas-Rueda D, Basagaña X, Cirach M, Cole-Hunter T, Dadvand P, Donaire-Gonzalez D, Foraster M, Gascon M, Martinez D, Tonne C, Triguero-Mas M, Valentín A, Nieuwenhuijsen M. 2017. Urban and transport planning related exposures and mortality: a health impact assessment for cities. Environ Health Perspect 125:89–96; http://dx.doi.org/10.1289/EHP220

BACKGROUND: Chemical and nonchemical environmental exposures are increasingly suspected to influence the development of obesity, especially during early life, but studies mostly consider single exposure groups. OBJECTIVES: Our study aimed to systematically assess the association between a wide array of early-life environmental exposures and childhood obesity, using an exposome-wide approach. METHODS: The HELIX (Human Early Life Exposome) study measured child body mass index (BMI), waist circumference, skinfold thickness, and body fat mass in 1,301 children from six European birth cohorts age 6-11 y. We estimated 77 prenatal exposures and 96 childhood exposures (crosssectionally), including indoor and outdoor air pollutants, built environment, green spaces, tobacco smoking, and biomarkers of chemical pollutants (persistent organic pollutants, metals, phthalates, phenols, and pesticides). We used an exposure-wide association study (ExWAS) to screen all exposure-outcome associations independently and used the deletion-substitution-addition (DSA) variable selection algorithm to build a final multiexposure model. RESULTS: The prevalence of overweight and obesity combined was 28.8%. Maternal smoking was the only prenatal exposure variable associated with higher child BMI (z-score increase of 0.28, 95% confidence interval: 0.09, 0.48, for active vs. no smoking). For childhood exposures, the multiexposure model identified particulate and nitrogen dioxide air pollution inside the home, urine cotinine levels indicative of secondhand smoke exposure, and residence in more densely populated areas and in areas with fewer facilities to be associated with increased child BMI. Child blood levels of copper and cesium were associated with higher BMI, and levels of organochlorine pollutants, cobalt, and molybdenum were associated with lower BMI. Similar results were found for the other adiposity outcomes. DISCUSSION: This first comprehensive and systematic analysis of many suspected environmental obesogens strengthens evidence for an association of smoking, air pollution exposure, and characteristics of the built environment with childhood obesity risk. Cross-sectional biomarker results may suffer from reverse causality bias, whereby obesity status influenced the biomarker concentration.

No abstract

Our findings indicate that contact with NOE benefits mental health. Our results also suggest that having contact with NOE that can facilitate stress reduction could be particularly beneficial.

Long-term ultrafine particle (UFP) exposure estimates at a fine spatial scale are needed for epidemiological studies. Land use regression (LUR) models were developed and evaluated for six European areas based on repeated 30 min monitoring following standardized protocols. In each area; Basel (Switzerland), Heraklion (Greece), Amsterdam, Maastricht, and Utrecht (“The Netherlands”), Norwich (United Kingdom), Sabadell (Spain), and Turin (Italy), 160–240 sites were monitored to develop LUR models by supervised stepwise selection of GIS predictors. For each area and all areas combined, 10 models were developed in stratified random selections of 90% of sites. UFP prediction robustness was evaluated with the intraclass correlation coefficient (ICC) at 31–50 external sites per area. Models from Basel and The Netherlands were validated against repeated 24 h outdoor measurements. Structure and model R2 of local models were similar within, but varied between areas (e.g., 38–43% Turin; 25–31% Sabadell). Robustness of predictions within areas was high (ICC 0.73–0.98). External validation R2 was 53% in Basel and 50% in The Netherlands. Combined area models were robust (ICC 0.93–1.00) and explained UFP variation almost equally well as local models. In conclusion, robust UFP LUR models could be developed on short-term monitoring, explaining around 50% of spatial variance in longer-term measurements.

Background:The urban exposome is the set of environmental factors that are experienced in the outdoor urban environment and that may influence child development.Objective:The authors’ goal was to describe the urban exposome among European pregnant women and understand its socioeconomic determinants.Methods:Using geographic information systems, remote sensing and spatio-temporal modeling we estimated exposure during pregnancy to 28 environmental indicators in almost 30,000 women from six population-based birth cohorts, in nine urban areas from across Europe. Exposures included meteorological factors, air pollutants, traffic noise, traffic indicators, natural space, the built environment, public transport, facilities, and walkability. Socioeconomic position (SEP), assessed at both the area and individual level, was related to the exposome through an exposome-wide association study and principal component (PC) analysis.Results:Mean±standard deviation (SD) NO2 levels ranged from 13.6±5.1 μg/m3 (in Heraklion, Crete) to 43.2±11 μg/m3 (in Sabadell, Spain), mean±SD walkability score ranged from 0.22±0.04 (Kaunas, Lithuania) to 0.32±0.07 (Valencia, Spain) and mean±SD Normalized Difference Vegetation Index ranged from 0.21±0.05 in Heraklion to 0.51±0.1 in Oslo, Norway. Four PCs explained more than half of variation in the urban exposome. There was considerable heterogeneity in social patterning of the urban exposome across cities. For example, high-SEP (based on family education) women lived in greener, less noisy, and less polluted areas in Bradford, UK (0.39 higher PC1 score, 95% confidence interval (CI): 0.31, 0.47), but the reverse was observed in Oslo (−0.57 PC1 score, 95% CI: −0.73, −0.41). For most cities, effects were stronger when SEP was assessed at the area level: In Bradford, women living in high SEP areas had a 1.34 higher average PC1 score (95% CI: 1.21, 1.48).Conclusions:The urban exposome showed considerable variability across Europe. Pregnant women of low SEP were exposed to higher levels of environmental hazards in some cities, but not others, which may contribute to inequities in child health and development. https://doi.org/10.1289/EHP2862