Influence of the Urban Exposome on Birth Weight

Associations between neighborhood characteristics and child well-being before and during the COVID-19 pandemic: A repeated cross-sectional study in the Environmental influences on Child Health Outcomes (ECHO) program

The corona virus disease (COVID-19) pandemic disrupted daily life worldwide, and its impact on child well-being remains a major concern. Neighborhood characteristics affect child well-being, but how these associations were affected by the pandemic is not well understood. We analyzed data from 1039 children enrolled in the Environmental influences on Child Health Outcomes Program whose well-being was assessed using the Patient-Reported Outcomes Measurement Information System Global Health questionnaire and linked these data to American Community Survey (ACS) data to evaluate the impacts of neighborhood characteristics on child well-being before and during the pandemic. We estimated the associations between more than 400 ACS variables and child well-being t-scores stratified by race/ethnicity (non-Hispanic white vs. all other races and ethnicities) and the timing of outcome data assessment (pre-vs. during the pandemic). Network graphs were used to visualize the associations between ACS variables and child well-being t-scores. The number of ACS variables associated with well-being t-scores decreased during the pandemic period. Comparing non-Hispanic white with other racial/ethnic groups during the pandemic, different ACS variables were associated with child well-being. Multiple ACS variables representing census tract-level housing conditions and neighborhood racial composition were associated with lower well-being t-scores among non-Hispanic white children during the pandemic, while higher percentage of Hispanic residents and higher percentage of adults working as essential workers in census tracts were associated with lower well-being t-scores among non-white children during the same study period. Our study provides insights into the associations between neighborhood characteristics and child well-being, and how the COVID-19 pandemic affected this relationship.

Greenness, air pollution, and temperature exposure effects in predicting premature mortality and morbidity: A small-area study using spatial random forest model

BACKGROUND

Although studies have provided negative impacts of air pollution, heat or cold exposure on mortality and morbidity, and positive effects of increased greenness on reducing them, a few studies have focused on exploring combined and synergetic effects of these exposures in predicting these health outcomes, and most had ignored the spatial autocorrelation in analyzing their health effects. This study aims to investigate the health effects of air pollution, greenness, and temperature exposure on premature mortality and morbidity within a spatial machine-learning modeling framework.

METHODS

Years of potential life lost reflecting premature mortality and comparative illness and disability ratio reflecting chronic morbidity from 1673 small areas covering Greater Manchester for the year 2008-2013 obtained. Average annual levels of NO2 concentration, normalized difference vegetation index (NDVI) representing greenness, and annual average air temperature were utilized to assess exposure in each area. These exposures were linked to health outcomes using non-spatial and spatial random forest (RF) models while accounting for spatial autocorrelation.

RESULTS

Spatial-RF models provided the best predictive accuracy when accounted for spatial autocorrelation. Among the exposures considered, air pollution emerged as the most influential in predicting mortality and morbidity, followed by NDVI and temperature exposure. Nonlinear exposure-response relations were observed, and interactions between exposures illustrated specific ranges or sweet and sour spots of exposure thresholds where combined effects either exacerbate or moderate health conditions.

CONCLUSION

Air pollution exposure had a greater negative impact on health compared to greenness and temperature exposure. Combined exposure effects may indicate the highest influence of premature mortality and morbidity burden.

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.

Associations of Maternal Educational Level, Proximity to Green Space During Pregnancy, and Gestational Diabetes With Body Mass Index From Infancy to Early Adulthood: A Proof-of-Concept Federated Analysis in 18 Birth Cohorts

International sharing of cohort data for research is important and challenging. We explored the feasibility of multicohort federated analyses by examining associations between 3 pregnancy exposures (maternal education, exposure to green vegetation, and gestational diabetes) and offspring body mass index (BMI) from infancy to age 17 years. We used data from 18 cohorts (n = 206,180 mother-child pairs) from the EU Child Cohort Network and derived BMI at ages 0-1, 2-3, 4-7, 8-13, and 14-17 years. Associations were estimated using linear regression via 1-stage individual participant data meta-analysis using DataSHIELD. Associations between lower maternal education and higher child BMI emerged from age 4 and increased with age (difference in BMI z score comparing low with high education, at age 2-3 years = 0.03 (95% confidence interval (CI): 0.00, 0.05), at 4-7 years = 0.16 (95% CI: 0.14, 0.17), and at 8-13 years = 0.24 (95% CI: 0.22, 0.26)). Gestational diabetes was positively associated with BMI from age 8 years (BMI z score difference = 0.18, 95% CI: 0.12, 0.25) but not at younger ages; however, associations attenuated towards the null when restricted to cohorts that measured gestational diabetes via universal screening. Exposure to green vegetation was weakly associated with higher BMI up to age 1 year but not at older ages. Opportunities of cross-cohort federated analyses are discussed.

Green space exposure and blood DNA methylation at birth and in childhood - A multi-cohort study

Green space exposure has been associated with improved mental, physical and general health. However, the underlying biological mechanisms remain largely unknown. The aim of this study was to investigate the association between green space exposure and cord and child blood DNA methylation. Data from eight European birth cohorts with a total of 2,988 newborns and 1,849 children were used. Two indicators of residential green space exposure were assessed: (i) surrounding greenness (satellite-based Normalized Difference Vegetation Index (NDVI) in buffers of 100 m and 300 m) and (ii) proximity to green space (having a green space ≥ 5,000 m2 within a distance of 300 m). For these indicators we assessed two exposure windows: (i) pregnancy, and (ii) the period from pregnancy to child blood DNA methylation assessment, named as cumulative exposure. DNA methylation was measured with the Illumina 450K or EPIC arrays. To identify differentially methylated positions (DMPs) we fitted robust linear regression models between pregnancy green space exposure and cord blood DNA methylation and between cumulative green space exposure and child blood DNA methylation. Two sensitivity analyses were conducted: (i) without adjusting for cellular composition, and (ii) adjusting for air pollution. Cohort results were combined through fixed-effect inverse variance weighted meta-analyses. Differentially methylated regions (DMRs) were identified from meta-analysed results using the Enmix-combp and DMRcate methods. There was no statistical evidence of pregnancy or cumulative exposures associating with any DMP (False Discovery Rate, FDR, p-value < 0.05). However, surrounding greenness exposure was inversely associated with four DMRs (three in cord blood and one in child blood) annotated to ADAMTS2, KCNQ1DN, SLC6A12 and SDK1 genes. Results did not change substantially in the sensitivity analyses. Overall, we found little evidence of the association between green space exposure and blood DNA methylation. Although we identified associations between surrounding greenness exposure with four DMRs, these findings require replication.

Modifiable factors associated with cognitive performance in Chinese adolescents: a national environment-wide association study

Growing evidence exists about the candidate factors of childhood cognitive performance, but mainly limited to single-exposure studies. We sought to systematically and simultaneously identify and validate a wide range of potential modifiable factors for childhood cognitive performance. We used data from five waves of data from the China Family Panel Studies (CFPS-2010, 2012, 2014, 2016 and 2018). Our analytical sample was restricted to those children aged 2-5 at baseline with valid exposure information. A total of 80 modifiable factors were identified. Childhood cognitive performance was assessed using vocabulary and mathematics test at wave 5. We used an environment-wide association study (EnWAS) to screen all exposure-outcome associations independently and used the least absolute shrinkage and selection operator (LASSO) variable selection algorithm to identify factors associated with cognitive performance. Multivariable linear model was then used to evaluate causal relationships between identified factors and cognitive performance. Of the 1305 participants included in the study (mean ± SD, 3.5 ± 1.1 years age at baseline, 45.1% girls). Eight factors were retained in the LASSO regression analysis. Six factors across community characteristics (percentage of poverty in the community; percentage of children in the community), household characteristics (family size), child health and behaviors (mobile internet access), parenting behaviors and cognitive enrichment (parental involvement in child' s education), and parental wellbeing (paternal happiness) domains were significantly associated with childhood cognition. Using a three-stage approach, this study validates several actionable targets for improving childhood cognitive performance.

Urban environment during pregnancy and childhood and white matter microstructure in preadolescence in two European birth cohorts

Growing evidence suggests that urban environment may influence cognition and behavior in children, but the underlying pollutant and neurobiological mechanisms are unclear. We evaluated the association of built environment and urban natural space indicators during pregnancy and childhood with brain white matter microstructure in preadolescents, and examined the potential mediating role of air pollution and road-traffic noise. We used data of the Generation R Study, a population-based birth cohort in Rotterdam, the Netherlands (n = 2725; 2002-2006) for the primary analyses. Replication of the main findings was attempted on an independent neuroimaging dataset from the PELAGIE birth cohort, France (n = 95; 2002-2006). We assessed exposures to 12 built environment and 4 urban natural spaces indicators from conception up to 9 years of age. We computed 2 white matter microstructure outcomes (i.e., average of fractional anisotropy (FA) and mean diffusivity (MD) from 12 white matte tracts) from diffusion tensor imaging data. Greater distance to the nearest major green space during pregnancy was associated with higher whole-brain FA (0.001 (95%CI 0.000; 0.002) per 7 m increase), and higher land use diversity during childhood was associated with lower whole-brain MD (-0.001 (95%CI -0.002; -0.000) per 0.12-point increase), with no evidence of mediation by air pollution nor road-traffic noise. Higher percentage of transport and lower surrounding greenness during pregnancy were associated with lower whole-brain FA, and road-traffic noise mediated 19% and 52% of these associations, respectively. We found estimates in the same direction in the PELAGIE cohort, although confidence intervals were larger and included the null. This study suggests an association between urban environment and white matter microstructure, mainly through road-traffic noise, indicating that greater access to green space nearby might promote white matter development.

Maternal greenness exposure and preterm birth in Brazil: A nationwide birth cohort study

In the dynamic landscape of maternal and child health, understanding the intricate interplay between environmental factors and pregnancy outcomes is of paramount importance. This study investigates the relationship between maternal greenness exposure and preterm births in Brazil using data spanning from 2010 to 2019. Satellite-derived indices, including the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), were employed to assess greenness exposure during whole pregnancy in maternal residential area. Employing Cox proportional hazard models, we calculated the hazard ratios (HRs) with 95% confidence intervals (CIs) for changes in NDVI, while adjusting for individual and area-level covariates. In total, 24,010,250 live births were included. Prevalence of preterm birth was 11.5%, with a modest but statistically significant decreasing trend (p = 0.013) observed across the nation over the study period. The findings reveal a significant association between greenness exposure and a reduced risk of preterm birth. Specifically, for every 0.1 increase in NDVI, there was a 2.0% decrease in the risk of preterm birth (95%CI: 1.9%-2.2%). Stratified analyses based on maternal education and ethnicity indicated potential effect modifications, with stronger protective effects observed among younger mothers and those with less years of education. Sensitivity analyses using EVI yielded consistent results. In conclusion, this study suggests that higher maternal greenness exposure is linked to a decreased risk of preterm birth in Brazil. These findings imply that enhancing residential greenspaces could be a valuable public health strategy to promote maternal and child health in Brazil.

[New advances in exposomics-analysis methods and research paradigms based on chromatography-mass spectrometry]

The occurrence and development of human diseases are influenced by both genetic and environmental factors. Research models that describe disease occurrence only from the perspective of genetics present certain limitations. In recent years, effects of environment factors on the occurrence and development of diseases have attracted extensive attentions. Exposomics focuses on the measurement of all exposure factors in an individual's life and how these factors are related to disease development. Exposomics provides new ideas to promote studies on the relationship between human health and environmental factors. Environmental exposures are characterized with different physical and chemical properties, as well as very low concentrations in vivo, which contribute great challenges in the comprehensive measurement of chemical residues in the human body. Chromatography-mass spectrometry-based technologies combine the high-efficiency separation ability of chromatography with the high resolution and sensitive detection characteristics of mass spectrometry; the combination of these techniques can achieve the high-coverage, high-throughput, and sensitive detection of environmental exposures, thus providing a powerful tool for measuring chemical exposures. Exposomics-analysis methods based on chromatography-mass spectrometry mainly include targeted quantitative analysis, suspect screening, and non-targeted screening. To explore the relationship between environmental exposure and the occurrence and development of diseases, researchers have developed research paradigms, including exposome wide association study, mixed-exposure study, exposomics and multi-omics (genome, transcriptome, proteome, metabolome)-association study, and so on. The emergence of these methods has brought about unprecedented developments in exposomics studies. In this manuscript, analytical methods based on chromatography-mass spectrometry, exposomics research paradigms, and their relevant prospects are reviewed.

Association between residential green spaces and pregnancy outcomes: a systematic review and meta-analysis

Residential exposure to greenness has shown positive influences on pregnancy outcomes like birth weight, preterm births, and small to gestational age (SGA) deliveries. We aimed to comprehensively review and investigate these associations by conducting a systematic review with meta-analysis. Relevant studies were retrieved from PubMed, EMBASE, ScienceDirect, and Google Scholar databases before June 2023. Summary effect estimates included birth weight, low birth weight (LBW), preterm births, and SGA which were calculated for 0.1 unit increase in residential greenness exposure. Overall quality of the evidence was examined through Joanna Briggs Institute (JBI) critical appraisal tool. The review included 31 articles and found a statistically significant increase in birth weight measured at 250 m buffer distance (β = 8.95, 95% CI = 1.63-16.27). Green spaces were also associated with lower odds of LBW (OR = 0.97, 95% CI = 0.96-0.98). Residential greenness had positive impacts on pregnancy outcomes that calls for emphasis on urban planning, especially in developing countries.

Adopting a child perspective for exposome research on mental health and cognitive development - Conceptualisation and opportunities

Mental disorders among children and adolescents pose a significant global challenge. The exposome framework covering the totality of internal, social and physical exposures over a lifetime provides opportunities to better understand the causes of and processes related to mental health, and cognitive functioning. The paper presents a conceptual framework on exposome, mental health, and cognitive development in children and adolescents, with potential mediating pathways, providing a possibility for interventions along the life course. The paper underscores the significance of adopting a child perspective to the exposome, acknowledging children's specific vulnerability, including differential exposures, susceptibility of effects and capacity to respond; their susceptibility during development and growth, highlighting neurodevelopmental processes from conception to young adulthood that are highly sensitive to external exposures. Further, critical periods when exposures may have significant effects on a child's development and future health are addressed. The paper stresses that children's behaviour, physiology, activity pattern and place for activities make them differently vulnerable to environmental pollutants, and calls for child-specific assessment methods, currently lacking within today's health frameworks. The importance of understanding the interplay between structure and agency is emphasized, where agency is guided by social structures and practices and vice-versa. An intersectional approach that acknowledges the interplay of social and physical exposures as well as a global and rural perspective on exposome is further pointed out. To advance the exposome field, interdisciplinary efforts that involve multiple scientific disciplines are crucial. By adopting a child perspective and incorporating an exposome approach, we can gain a comprehensive understanding of how exposures impact children's mental health and cognitive development leading to better outcomes.

Associations between urban exposome and recurrence risk among survivors of acute myocardial infarction in Beijing, China

Few previous studies have investigated the impacts of coexposure to multiple urban environmental factors on the prognosis of acute myocardial infarction (AMI) events. This study aimed to evaluate the associations between the urban exposome and AMI recurrence. We used data from 88,509 AMI patients from a large cohort obtained from the Beijing Cardiovascular Disease Surveillance System between 2013 and 2019. Twenty-six types of urban exposures were assessed within 300-m, 500-m, and 1000-m buffers of patients' home addresses in the baseline and cumulative average levels. We used the Cox proportional hazard model along with the Elastic Net (ENET) algorithm to estimate the hazard ratios (HRs) of recurrent AMI per interquartile range increase in each selected urban exposure. The increased risk of AMI recurrence was significantly associated with lower urban function diversity in the 500-m buffer, longer distance to subway stations and higher PM2.5 for both baseline and cumulative average exposure. The cumulative averages of two urban factors, including the distance to parks, and the density of fruit and vegetable shops in the 1000-m buffer, were also identified as significant factors affecting the risk of AMI recurrence. These findings can help improve the urban design for promoting human cardiovascular health.

Beyond the single-outcome approach: A comparison of outcome-wide analysis methods for exposome research

Outcome-wide analysis can offer several benefits, including increased power to detect weak signals and the ability to identify exposures with multiple effects on health, which may be good targets for preventive measures. Recently, advanced statistical multivariate techniques for outcome-wide analysis have been developed, but they have been rarely applied to exposome analysis. In this work, we provide an overview of a selection of methods that are well-suited for outcome-wide exposome analysis and are implemented in the R statistical software. Our work brings together six different methods presenting innovative solutions for typical problems arising from outcome-wide approaches in the context of the exposome, including dependencies among outcomes, high dimensionality, mixed-type outcomes, missing data records, and confounding effects. The identified methods can be grouped into four main categories: regularized multivariate regression techniques, multi-task learning approaches, dimensionality reduction approaches, and bayesian extensions of the multivariate regression framework. Here, we compare each technique presenting its main rationale, strengths, and limitations, and provide codes and guidelines for their application to exposome data. Additionally, we apply all selected methods to a real exposome dataset from the Human Early-Life Exposome (HELIX) project, demonstrating their suitability for exposome research. Although the choice of the best method will always depend on the challenges to be faced in each application, for an exposome-like analysis we find dimensionality reduction and bayesian methods such as reduced rank regression (RRR) or multivariate bayesian shrinkage priors (MBSP) particularly useful, given their ability to deal with critical issues such as collinearity, high-dimensionality, missing data or quantification of uncertainty.

Associations of green and blue space exposure in pregnancy with epigenetic gestational age acceleration

Early life is seen as a particularly sensitive period for environmental exposures. Natural space exposure during pregnancy has been associated with offspring health. Epigenetic gestational age acceleration, a discrepancy between clinical and DNA methylation-based gestational age, may underlie these associations. In 1359 mother-newborn pairs from the population-based Generation R Study, we examined the associations of natural space exposure, defined as surrounding greenness, distance to major green and blue (water) space, and size of the blue space during pregnancy with offspring epigenetic gestational age acceleration. Natural space exposure was based on participants' geocoded addresses, and epigenetic gestational age acceleration was calculated from cord blood DNA methylation using Bohlin's and Knight's epigenetic clocks. Sensitivity analyses were conducted in a subgroup of newborns with optimal pregnancy dating, based on last menstrual period. Surrounding greenness, measured in normalized difference vegetation index values, was intermediate (median 0.4, IQR 0.2), and 84% and 56% of the participants had a major green or blue space near their home address, respectively. We did not observe associations of natural space availability during pregnancy with offspring epigenetic gestational age acceleration. This could imply that epigenetic gestational age acceleration in cord blood does not underlie the effects of residential natural space availability in pregnancy on offspring health. Future studies could investigate whether residential natural space availability during pregnancy is associated with offspring differential DNA methylation at other CpGs than those included in the epigenetic gestational clocks.

Surrounding greenness is associated with lower risk and burden of low birth weight in Iran

The nexus between prenatal greenspace exposure and low birth weight (LBW) remains largely unstudied in low- and middle-income countries (LMICs). We investigated a nationwide retrospective cohort of 4,021,741 live births (263,728 LBW births) across 31 provinces in Iran during 2013-2018. Greenness exposure during pregnancy was assessed using satellite-based normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). We estimated greenness-LBW associations using multiple logistic models, and quantified avoidable LBW cases under scenarios of improved greenspace through counterfactual analyses. Association analyses provide consistent evidence for approximately L-shaped exposure-response functions, linking 7.0-11.5% declines in the odds of LBW to each 0.1-unit rise in NDVI/EVI with multiple buffers. Assuming causality, 3931-5099 LBW births can be avoided by achieving greenness targets of mean NDVI/EVI, amounting to 4.4-5.6% of total LBW births in 2015. Our findings suggest potential health benefits of improved greenspace in lowering LBW risk and burden in LMICs.

Constrained groupwise additive index models

In environmental epidemiology, there is wide interest in creating and using comprehensive indices that can summarize information from different environmental exposures while retaining strong predictive power on a target health outcome. In this context, the present article proposes a model called the constrained groupwise additive index model (CGAIM) to create easy-to-interpret indices predictive of a response variable, from a potentially large list of variables. The CGAIM considers groups of predictors that naturally belong together to yield meaningful indices. It also allows the addition of linear constraints on both the index weights and the form of their relationship with the response variable to represent prior assumptions or operational requirements. We propose an efficient algorithm to estimate the CGAIM, along with index selection and inference procedures. A simulation study shows that the proposed algorithm has good estimation performances, with low bias and variance and is applicable in complex situations with many correlated predictors. It also demonstrates important sensitivity and specificity in index selection, but non-negligible coverage error on constructed confidence intervals. The CGAIM is then illustrated in the construction of heat indices in a health warning system context. We believe the CGAIM could become useful in a wide variety of situations, such as warning systems establishment, and multipollutant or exposome studies.

Development of a composite healthy ageing score: evidence from middle-to-older aged Australians

We developed and validated a composite healthy ageing score (HAS) to address the absence of a definitive composite score comprising multiple health domains that measure healthy ageing in epidemiology. The HAS is developed from 13 health domains reported to influence healthy ageing. Data to measure these domains was extracted from the 45 and Up Study baseline. We applied best practices for scale validation and development. Physical functioning, cognitive function, mental health, sleep, quality of life, balance, social connections and overall health were retained. Functional capacity and resilience were uncovered as underlying latent structures. The HAS ranges from 0 to 16 with higher scores indicating a better health profile. This research contributes a comprehensive measuring tool, HAS, It enables examination and comparison of individual or collective health profiles and the investigation of the factors that influence their chances of living healthy for longer.

Methodological Challenges in Spatial and Contextual Exposome-Health Studies

The concept of the exposome encompasses the totality of exposures from a variety of external and internal sources across an individual's life course. The wealth of existing spatial and contextual data makes it appealing to characterize individuals' external exposome to advance our understanding of environmental determinants of health. However, the spatial and contextual exposome is very different from other exposome factors measured at the individual-level as spatial and contextual exposome data are more heterogenous with unique correlation structures and various spatiotemporal scales. These distinctive characteristics lead to multiple unique methodological challenges across different stages of a study. This article provides a review of the existing resources, methods, and tools in the new and developing field for spatial and contextual exposome-health studies focusing on four areas: (1) data engineering, (2) spatiotemporal data linkage, (3) statistical methods for exposome-health association studies, and (4) machine- and deep-learning methods to use spatial and contextual exposome data for disease prediction. A critical analysis of the methodological challenges involved in each of these areas is performed to identify knowledge gaps and address future research needs.

Exposure to outdoor residential noise during pregnancy, embryonic size, fetal growth, and birth outcomes

INTRODUCTION

Previous literature suggested that noise exposure during pregnancy was not associated with adverse birth outcomes. However, no studies evaluated the association between noise exposure and embryonic and fetal growth, or mutually assessed other urban environmental exposures such as traffic-related air pollution or natural spaces.

METHODS

We included 7947 pregnant women from the Generation R Study, the Netherlands. We estimated total (road traffic, aircraft, railway, and industry), road traffic, and railway noise at the participants' home addresses during pregnancy using environmental noise maps. We estimated traffic-related air pollution using land-use regression models, greenness within a 300 m buffer using the normalized difference vegetation index, and distance to blue spaces using topographical maps at the home addresses. Embryonic size (crown-rump length) and fetal growth parameters (head circumference, femur length, and estimated fetal weight) were measured by ultrasound at several gestational ages. Information on neonatal anthropometrics at birth (head circumference, length, and weight) and adverse birth outcomes (preterm birth, low birth weight, and small for gestational age) were retrieved from medical records.

RESULTS

Higher total noise exposure during pregnancy was associated with larger crown-rump length (0.07 SDS [95%CI 0.00 to 0.14]). No association was found with fetal growth parameters, neonatal anthropometrics, and adverse birth outcomes. Similar results were observed for road traffic noise exposure, while railway noise exposure was not associated with any of the outcomes. Traffic-related air pollution was not associated with crown-rump length. Total noise exposure mediated 15% of the association between exposure to greenness and smaller crown-rump length. No association was observed between distance to blue spaces and total noise exposure.

CONCLUSION

Exposure to outdoor residential noise during pregnancy was associated with larger embryonic size. Moreover, a reduction of total noise exposure during pregnancy partially mediated the association between exposure to greenness and smaller embryonic size. Additional research is warranted to confirm and further understand these novel findings.

The public health exposome and pregnancy-related mortality in the United States: a high-dimensional computational analysis

BACKGROUND

Racial inequities in maternal mortality in the U.S. continue to be stark.

METHODS

The 2015-2018, 4-year total population, county-level, pregnancy-related mortality ratio (PRM; deaths per 100,000 live births; National Center for Health Statistics (NCHS), restricted use mortality file) was linked with the Public Health Exposome (PHE). Using data reduction techniques, 1591 variables were extracted from over 62,000 variables for use in this analysis, providing information on the relationships between PRM and the social, health and health care, natural, and built environments. Graph theoretical algorithms and Bayesian analysis were applied to PHE/PRM linked data to identify latent networks.

RESULTS

PHE variables most strongly correlated with total population PRM were years of potential life lost and overall life expectancy. Population-level indicators of PRM were overall poverty, smoking, lack of exercise, heat, and lack of adequate access to food.

CONCLUSIONS

In this high-dimensional analysis, overall life expectancy, poverty indicators, and health behaviors were found to be the strongest predictors of pregnancy-related mortality. This provides strong evidence that maternal death is part of a broader constellation of both similar and unique health behaviors, social determinants and environmental exposures as other causes of death.

City-scale assessment of long-term air quality impacts on the respiratory and cardiovascular health

Background

The impact of the urban environment on human health is a contemporary subject of environmental research. Air pollution is often considered a leading environmental driver. However, a plethora of other factors within the urban exposome may be involved. At the same time, the resolution of spatial data is also an important facet to consider. Generally, systematic tools for accurate health risk assessment in the urban environment are missing or are not implemented.

Methods

The long-term impact of air quality (PM₁₀, PM_2.5, NO₂, benzene, and SO₂) on respiratory and cardiovascular health was assessed with a log-linear model. We used the most accurate health data in high city scale spatial resolution over the period 2010 to 2018. Selected external exposome parameters were also included in the analysis.

Results

Statistically significant associations between air pollution and the health of the urban population were found. The strongest association was between benzene and the incidence of bronchitis in the adult population [RR 1.552 95% CI (1.415-1.704) per 0.5 μg/m³ change in benzene concentration]. A similar relation was observed between NO₂ and the same health condition [RR 1.483 95% CI (1.227-1.792) per 8.9 μg/m³ of change in NO₂]. Other weaker associations were also found between asthma in children and PMs, NO₂, or benzene. Cardiovascular-related hospitalizations in the general population were linked with NO₂ [RR 1.218 95% CI (1.119-1.325) per 9.7 μg/m³ change in NO₂]. The remaining pollutants were slightly less but still significantly associated with cardiovascular-related hospitalizations.

Conclusion

Our findings are mostly highly statistically significant (p ≤ 0.001) and are in line with current literature on the adverse effects of air pollution on the human population. The results highlight the need for continual improvements in air quality. We propose the implementation of this approach as a systematic tool for the investigation of possible health risks over a long period of time. However, further research involving other variables is an essential step toward understanding the complex urban exposome and its implications for human health. An increase in data spatial resolution is especially important in this respect as well as for improving city health risk management.

A review on the application of the exposome paradigm to unveil the environmental determinants of age-related diseases

Age-related diseases account for almost half of all diseases among adults worldwide, and their incidence is substantially affected by the exposome, which is the sum of all exogenous and endogenous environmental exposures and the human body’s response to these exposures throughout the entire lifespan. Herein, we perform a comprehensive review of the epidemiological literature to determine the key elements of the exposome that affect the development of age-related diseases and the roles of aging hallmarks in this process. We find that most exposure assessments in previous aging studies have used a reductionist approach, whereby the effect of only a single environmental factor or a specific class of environmental factors on the development of age-related diseases has been examined. As such, there is a lack of a holistic and unbiased understanding of the effect of multiple environmental factors on the development of age-related diseases. To address this, we propose several research strategies based on an exposomic framework that could advance our understanding—in particular, from a mechanistic perspective—of how environmental factors affect the development of age-related diseases. We discuss the statistical methods and other methods that have been used in exposome-wide association studies, with a particular focus on multiomics technologies. We also address future challenges and opportunities in the realm of multidisciplinary approaches and genome–exposome epidemiology. Furthermore, we provide perspectives on precise public health services for vulnerable populations, public communications, the integration of risk exposure information, and the bench-to-bedside translation of research on age-related diseases.

Urban environment and health behaviours in children from six European countries

BACKGROUND

Urban environmental design is increasingly considered influential for health and wellbeing, but evidence is mostly based on adults and single exposure studies. We evaluated the association between a wide range of urban environment characteristics and health behaviours in childhood.

METHODS

We estimated exposure to 32 urban environment characteristics (related to the built environment, traffic, and natural spaces) for home and school addresses of 1,581 children aged 6-11 years from six European cohorts. We collected information on health behaviours including total amount of overall moderate-to-vigorous physical activity, physical activity outside school hours, active transport, sedentary behaviours and sleep duration, and developed patterns of behaviours with principal component analysis. We used an exposure-wide association study to screen all exposure-outcome associations, and the deletion-substitution-addition algorithm to build a final multi-exposure model.

RESULTS

In multi-exposure models, green spaces (Normalized Difference Vegetation Index, NDVI) were positively associated with active transport, and inversely associated with sedentary time (22.71 min/day less (95 %CI -39.90, -5.51) per interquartile range increase in NDVI). Residence in densely built areas was associated with more physical activity and less sedentary time, and densely populated areas with less physical activity outside school hours and more sedentary time. Presence of a major road was associated with lower sleep duration (-4.80 min/day (95 %CI -9.11, -0.48); compared with no major road). Results for the behavioural patterns were similar.

CONCLUSIONS

This multicohort study suggests that areas with more vegetation, more building density, less population density and without major roads are associated with improved health behaviours in childhood.

Using an Exposome-Wide Approach to Explore the Impact of Urban Environments on Blood Pressure among Adults in Beijing-Tianjin-Hebei and Surrounding Areas of China

Existing studies mostly explored the association between urban environmental exposures and blood pressure (BP) in isolation, ignoring correlations across exposures. This study aimed to systematically evaluate the impact of a wide range of urban exposures on BP using an exposome-wide approach. A multicenter cross-sectional study was conducted in ten cities of China. For each enrolled participant, we estimated their urban exposures, including air pollution, built environment, surrounding natural space, and road traffic indicator. On the whole, this study comprised three statistical analysis steps, that is, single exposure analysis, multiple exposure analysis and a cluster analysis. We also used deletion-substitution-addition algorithm to conduct variable selection. After considering multiple exposures, for hypertension risk, most significant associations in single exposure model disappeared, with only neighborhood walkability remaining negatively statistically significant. Besides, it was observed that SBP (systolic BP) raised gradually with the increase in PM_2.5, but such rising pattern slowed down when PM_2.5 concentration reached a relatively high level. For surrounding natural spaces, significant protective associations between green and blue spaces with BP were found. This study also found that high population density and public transport accessibility have beneficially significant association with BP. Additionally, with the increase in the distance to the nearest major road, DBP (diastolic BP) decreased rapidly. When the distance was beyond around 200 m, however, there was no obvious change to DBP anymore. By cluster analysis, six clusters of urban exposures were identified. These findings reinforce the importance of improving urban design, which help promote healthy urban environments to optimize human BP health.

Causal Relations between Exposome and Stroke: A Mendelian Randomization Study

BACKGROUND AND PURPOSE

To explore the causal relationships of elements of the exposome with ischemic stroke and its subtypes at the omics level and to provide evidence for stroke prevention.

METHODS

We conducted a Mendelian randomization study between exposure and any ischemic stroke (AIS) and its subtypes (large-artery atherosclerotic disease [LAD], cardioembolic stroke [CE], and small vessel disease [SVD]). The exposure dataset was the UK Biobank involving 361,194 subjects, and the outcome dataset was the MEGASTROKE consortium including 52,000 participants.

RESULTS

We found that higher blood pressure (BP) (systolic BP: odds ratio [OR], 1.02; 95% confidence interval [CI], 1.01 to 1.04; diastolic BP: OR, 1.03; 95% CI, 1.01 to 1.05; pulse pressure: OR, 1.03; 95% CI, 1.00 to 1.06), atrial fibrillation (OR, 1.18; 95% CI, 1.13 to 1.25), and diabetes (OR, 1.13; 95% CI, 1.07 to 1.18) were significantly associated with ischemic stroke. Importantly, higher education (OR, 0.69; 95% CI, 0.60 to 0.79) decreased the risk of ischemic stroke. Higher systolic BP (OR, 1.06; 95% CI, 1.02 to 1.10), pulse pressure (OR, 1.08; 95% CI, 1.02 to 1.14), diabetes (OR, 1.28; 95% CI, 1.13 to 1.45), and coronary artery disease (OR, 1.58; 95% CI, 1.25 to 2.00) could cause LAD. Atrial fibrillation could cause CE (OR, 1.90; 95% CI, 1.71 to 2.11). For SVD, higher systolic BP (OR, 1.04; 95% CI, 1.00 to 1.07), diastolic BP (OR, 1.06; 95% CI, 1.01 to 1.12), and diabetes (OR, 1.22; 95% CI, 1.10 to 1.36) were causal factors.

CONCLUSIONS

The study revealed elements of the exposome causally linked to ischemic stroke and its subtypes, including conventional causal risk factors and novel protective factors such as higher education.

Green Walkability and Physical Activity in UK Biobank: A Cross-Sectional Analysis of Adults in Greater London

Urban greenspace provides opportunities for outdoor exercise and may increase physical activity, with accompanying health benefits. Areas suitable for walking (walkability) are also associated with increased physical activity, but interactions with greenspace are poorly understood. We investigated associations of walkability and green walkability with physical activity in an urban adult cohort. We used cross-sectional data from Greater London UK Biobank participants (n = 57,726) and assessed walkability along roads and footpaths within 1000 m of their residential addresses. Additionally, we assessed green walkability by integrating trees and low-lying vegetation into the walkability index. Physical activity outcomes included self-reported and accelerometer-measured physical activity and active transport. We assessed associations using log-linear, logistic and linear regression models, adjusted for individual- and area-level confounders. Higher green walkability was associated with favourable International Physical Activity Questionnaire responses and achievement of weekly UK government physical activity guideline recommendations. Participants living in the highest versus lowest quintile of green walkability participated in 2.41 min (95% confidence intervals: 0.22, 4.60) additional minutes of moderate-and-vigorous physical activity per day. Higher walkability and green walkability scores were also associated with choosing active transport modes such as walking and cycling. Our green walkability approach demonstrates the utility in accounting for walkability and greenspace simultaneously to understand the role of the built environment on physical activity.

Neighborhood environmental exposures and incidence of attention deficit/hyperactivity disorder: A population-based cohort study

BACKGROUND

Emerging studies have associated low greenspace and high air pollution exposure with risk of child attention deficit/hyperactivity disorder (ADHD). Population-based studies are limited, however, and joint effects are rarely evaluated. We investigated associations of ADHD incidence with greenspace, air pollution, and noise in a population-based birth cohort.

METHODS

We assembled a cohort from administrative data of births from 2000 to 2001 (N ∼ 37,000) in Metro Vancouver, Canada. ADHD was identified by hospital records, physician visits, and prescriptions. Cox proportional hazards models were applied to assess associations between environmental exposures and ADHD incidence adjusting for available covariates. Greenspace was estimated using vegetation percentage derived from linear spectral unmixing of Landsat imagery. Fine particulate matter (PM_2.5) and nitrogen dioxide (NO₂) were estimated using land use regression models; noise was estimated using a deterministic model. Exposure period was from birth until the age of three. Joint effects of greenspace and PM_2.5 were analysed in two-exposure models and by categorizing values into quintiles.

RESULTS

During seven-year follow-up, 1217 ADHD cases were diagnosed. Greenspace was associated with lower incidence of ADHD (hazard ratio, HR: 0.90 [0.81-0.99] per interquartile range increment), while PM_2.5 was associated with increased incidence (HR: 1.11 [1.06-1.17] per interquartile range increment). NO₂ (HR: 1.01 [0.96, 1.07]) and noise (HR: 1.00 [0.95, 1.05]) were not associated with ADHD. There was a 50% decrease in the HR for ADHD in locations with the lowest PM_2.5 and highest greenspace exposure, compared to a 62% increase in HR in locations with the highest PM_2.5 and lowest greenspace exposure. Effects of PM_2.5 were attenuated by greenspace in two-exposure models.

CONCLUSIONS

We found evidence suggesting environmental inequalities where children living in greener neighborhoods with low air pollution had substantially lower risk of ADHD compared to those with higher air pollution and lower greenspace exposure.

Green CURIOCITY: a study protocol for a European birth cohort study analysing childhood heat-related health impacts and protective effects of urban natural environments

INTRODUCTION

The European climate is getting warmer and the impact on childhood health and development is insufficiently understood. Equally, how heat-related health risks can be reduced through nature-based solutions, such as exposure to urban natural environments, is unknown. Green CURe In Outdoor CITY spaces (Green CURIOCITY) will analyse how heat exposure during pregnancy affects birth outcomes and how long-term heat exposure may influence children's neurodevelopment. We will also investigate if adverse effects can be mitigated by urban natural environments. A final goal is to visualise intraurban patterns of heat vulnerability and assist planning towards healthier cities.

METHODS AND ANALYSIS

We will use existing data from the Human Early-Life Exposure cohort, which includes information on birth outcomes and neurodevelopment from six European birth cohorts. The cohort is linked to data on prenatal heat exposure and impact on birth outcomes will be analysed with logistic regression models, adjusting for air pollution and noise and sociobehavioural covariates. Similarly, impact of cumulative and immediate heat exposure on neurodevelopmental outcomes at age 5 will be assessed. For both analyses, the potentially moderating impact of natural environments will be quantified. For visualisation, Geographical information systems data will be combined to develop vulnerability maps, demonstrating urban 'hot spots' where the risk of negative impacts of heat is aggravated due to sociodemographic and land use patterns. Finally, geospatial and meteorological data will be used for informing GreenUr, an existing software prototype developed by the WHO Regional Office for Europe to quantify health impacts and augment policy tools for urban green space planning.

ETHICS AND DISSEMINATION

The protocol was approved by the Comité Ético de Investigación Clínica Parc de Salut MAR, Spain. Findings will be published in peer-reviewed journals and presented at policy events. Through stakeholder engagement, the results will also reach user groups and practitioners.

Determinants of Chronic Biological Stress, Measured as Hair Cortisol Concentration, in a General Population of Adolescents: From Individual and Household Characteristics to Neighborhood Urbanicity

Chronic biological stress may adversely affect adolescents' physical and mental health, but insight in the personal and environmental factors that determine chronic stress is limited. We measured 3-month cumulative hair cortisol concentration (HCC) in 419 adolescents, participating in the Flemish Environment and Health Study. Adolescents' health and lifestyle characteristics, household and neighborhood socio-economic status as well as neighborhood urbanicity were assessed as potential determinants of HCC, using multiple linear regression models. We additionally explored heterogeneity of our results by sex. HCC were significantly higher in boys from densely populated neighborhoods, the association was not significant in girls. Accordingly, boys living outside cities had significantly lower HCC than boys, living in cities. HCC was significantly lower in adolescents with an optimal vitality, a measure of a positive mental health status. In adolescent girls, menarcheal status (pre-/postmenarche) was a significant determinant of HCC. Our findings are the first to suggest that residential urbanicity may have an impact on chronic biological stress in a general population of adolescent boys.

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.

Greener neighbourhoods, healthier birth outcomes? Evidence from Australia

Growing body of research recognizes the importance of green spaces on the perinatal outcomes however, further evidence from different geographies are warranted. We aimed to investigate association between, and differential responses to, maternal exposure to green space and birthweight. Birth records (n = 82,221) were extracted from the Perinatal Data Collection (PDC) in Sydney's metropolitan area between January 2016 and December 2017. Association between green space quantity and birthweight, term birthweight, low birthweight, term low birthweight and preterm were assessed using linear and logistic regressions. Potential modification by area-level socioeconomic status and maternal country of birth were tested using interaction terms. Difference in birth weight for the ≥40% versus <20% green space within SA2s was 59.0 g (95%CI: 42.9, 75.3) in unadjusted models which dropped to 25.6 g (95%CI: 13.0, 38.2) in adjusted models. Stratified analysis suggested stronger associations for babies of mothers from affluent neighbourhoods, while statistically significant association was not observed in deprived areas. Furthermore, the association was more pronounced among babies to mothers who were born overseas. Associations were consistent for term births. Higher levels of green space were associated with lower odds of preterm birth in adjusted models. However, we did not identify statistically significant association between green space quantity and the risk of low birthweight (LBW). Our study suggests that green space may support healthier birth outcomes and help to reduce the birthweight gap between newborns of mothers born in Australia and overseas. However, disproportionate benefits among women in affluent neighbourhoods may widen socioeconomic inequities in birthweight.

Association between moderated level of air pollution and fetal growth: the potential role of noise exposure

This study aims to analyze, in a population of singletons, the potential confounding or modifying effect of noise on the relationship between fetal growth restriction (FGR) or small for gestational age (SGA) and environmental exposure to air pollution. All women with single pregnancies living in one of two medium-sized cities (Besançon, Dijon) and who delivered at a university hospital between 2005 and 2009 were included. FGR and SGA were obtained from medical records. Outdoor residential exposure to nitrogen dioxide (NO₂) and particulate matter (PM₁₀) was quantified at the mother’s address at delivery over defined pregnancy periods; outdoor noise exposure was considered to be the annual average daily noise levels in the façade of building (L_{Aeq,24 h}). Adjusted odds ratios (OR_a) were estimated by multivariable logistic regressions. Among the 8994 included pregnancies, 587 presented FGR and 918 presented SGA. In the two-exposure models, for SGA, the OR_a for a 10-µg/m³ increase of PM₁₀ during the two last months before delivery was 1.18, 95%CI 1.00–1.41 and for FGR, these OR_a were for the first and the third trimesters, and the two last months before delivery: 0.77 (0.61–0.97), 1.38 (1.12–1.70), and 1.35 (1.11–1.66), respectively. Noise was not associated with SGA or FGR and did not confound the relationship between air pollution and SGA or FGR. These results are in favor of an association between PM₁₀ exposure and fetal growth, independent of noise, particularly towards the end of pregnancy, and of a lack of association between noise and fetal growth.

Characterizing environmental geographic inequalities using an integrated exposure assessment

BACKGROUND

At a regional or continental scale, the characterization of environmental health inequities (EHI) expresses the idea that populations are not equal in the face of pollution. It implies an analysis be conducted in order to identify and manage the areas at risk of overexposure where an increasing risk to human health is suspected. The development of methods is a prerequisite for implementing public health activities aimed at protecting populations.

METHODS

This paper presents the methodological framework developed by INERIS (French National Institute for Industrial Environment and Risks) to identify a common framework for a structured and operationalized assessment of human exposure. An integrated exposure assessment approach has been developed to integrate the multiplicity of exposure pathways from various sources, through a series of models enabling the final exposure of a population to be defined.

RESULTS

Measured data from environmental networks reflecting the actual contamination of the environment are used to gauge the population's exposure. Sophisticated methods of spatial analysis are applied to include additional information and take benefit of spatial and inter-variable correlation to improve data representativeness and characterize the associated uncertainty. Integrated approaches bring together all the information available for assessing the source-to-human-dose continuum using a Geographic Information System, multimedia exposure and toxicokinetic model.

DISCUSSION

One of the objectives of the integrated approach was to demonstrate the feasibility of building complex realistic exposure scenarios satisfying the needs of stakeholders and the accuracy of the modelling predictions at a fine spatial-temporal resolution. A case study is presented to provide a specific application of the proposed framework and how the results could be used to identify an overexposed population.

CONCLUSION

This framework could be used for many purposes, such as mapping EHI, identifying vulnerable populations and providing determinants of exposure to manage and plan remedial actions and to assess the spatial relationships between health and the environment to identify factors that influence the variability of disease patterns.

Natural outdoor environments' health effects in gentrifying neighborhoods: Disruptive green landscapes for underprivileged neighborhood residents

BACKGROUND

Cities are restoring existing natural outdoor environments (NOE) or creating new ones to address diverse socio-environmental and health challenges. The idea that NOE provide health benefits is supported by the therapeutic landscapes concept. However, several scholars suggest that NOE interventions may not equitably serve all urban residents and may be affected by processes such as gentrification. Applying the therapeutic landscapes concept, this study assesses the impacts of gentrification processes on the associations between NOE and the health of underprivileged, often long-term, neighborhood residents.

METHODS

We examined five neighborhoods in five cities in Canada, the United States and Western Europe. Our case studies were neighborhoods experiencing gentrification processes and NOE interventions. In each city, we conducted semi-structured qualitative interviews on NOE interventions, equity/justice, gentrification and health (n = 117) with case study neighborhood residents, community-based organizations, neighborhood resident leaders and other stakeholders such as public agencies staff.

RESULTS

Respondents highlighted a variety of interconnected and overlapping factors: the insufficient benefits of NOE to counterbalance other factors detrimental to health, the use of NOE for city branding and housing marketing despite pollution, unwelcomeness, increase of conflicts, threats to physical displacement for themselves and their social networks, unattractiveness, deficient routes, inadequate NOE maintenance and lack of safety in NOE.

CONCLUSIONS

Our study demonstrated that underprivileged neighborhood residents were perceived to experience new or improved NOE as what we call "disruptive green landscapes" (i.e. non-therapeutic landscapes with which they were not physically or emotionally engaged) instead of as therapeutic landscapes.

Instability of Variable-selection Algorithms Used to Identify True Predictors of an Outcome in Intermediate-dimension Epidemiologic Studies

BACKGROUND

Machine-learning algorithms are increasingly used in epidemiology to identify true predictors of a health outcome when many potential predictors are measured. However, these algorithms can provide different outputs when repeatedly applied to the same dataset, which can compromise research reproducibility. We aimed to illustrate that commonly used algorithms are unstable and, using the example of Least Absolute Shrinkage and Selection Operator (LASSO), that stabilization method choice is crucial.

METHODS

In a simulation study, we tested the stability and performance of widely used machine-learning algorithms (LASSO, Elastic-Net, and Deletion-Substitution-Addition [DSA]). We then assessed the effectiveness of six methods to stabilize LASSO and their impact on performance. We assumed that a linear combination of factors drawn from a simulated set of 173 quantitative variables assessed in 1,301 subjects influenced to varying extents a continuous health outcome. We assessed model stability, sensitivity, and false discovery proportion.

RESULTS

All tested algorithms were unstable. For LASSO, stabilization methods improved stability without ensuring perfect stability, a finding confirmed by application to an exposome study. Stabilization methods also affected performance. Specifically, stabilization based on hyperparameter optimization, frequently implemented in epidemiology, increased the false discovery proportion dramatically when predictors explained a low share of outcome variability. In contrast, stabilization based on stability selection procedure often decreased the false discovery proportion, while sometimes simultaneously lowering sensitivity.

CONCLUSIONS

Machine-learning methods instability should concern epidemiologists relying on them for variable selection, as stabilizing a model can impact its performance. For LASSO, stabilization methods based on stability selection procedure (rather than addressing prediction stability) should be preferred to identify true predictors.

Unravelling the chemical exposome in cohort studies: routes explored and steps to become comprehensive

Environmental factors contribute to the risk for adverse health outcomes against a background of genetic predisposition. Among these factors, chemical exposures may substantially contribute to disease risk and adverse outcomes. In fact, epidemiological cohort studies have established associations between exposure against individual chemicals and adverse health effects. Yet, in daily life individuals are exposed to complex mixtures in varying compositions. To capture the totality of environmental exposures the concept of the exposome has been developed. Here, we undertake an overview of major exposome projects, which pioneered the field of exposomics and explored the links between chemical exposure and health outcomes using cohort studies. We seek to reflect their achievements with regard to (i) capturing a comprehensive picture of the environmental chemical exposome, (ii) aggregating internal exposures using chemical and bioanalytical means of detection, and (iii) identifying associations that provide novel options for risk assessment and intervention. Various complementary approaches can be distinguished in addressing relevant exposure routes and it emerges that individual exposure histories may not easily be grouped. The number of chemicals for which human exposure can be detected is substantial and highlights the reality of mixture exposures. Yet, to a large extent it depends on targeted chemical analysis with the specific challenges to capture all relevant exposure routes and assess the chemical concentrations occurring in humans. The currently used approaches imply prior knowledge or hypotheses about relevant exposures. Typically, the number of chemicals considered in exposome projects is counted in dozens-in contrast to the several thousands of chemicals for which occurrence have been reported in human serum and urine. Furthermore, health outcomes are often still compared to single chemicals only. Moreover, explicit consideration of mixture effects and the interrelations between different outcomes to support causal relationships and identify risk drivers in complex mixtures remain underdeveloped and call for specifically designed exposome-cohort studies.

Residential exposure to air pollution and access to neighborhood greenspace in relation to hair cortisol concentrations during the second and third trimester of pregnancy

BACKGROUND

Exposure to air pollution during pregnancy has been associated with adverse pregnancy outcomes in studies worldwide, other studies have described beneficial effects of residential greenspace on pregnancy outcomes. The biological mechanisms that underlie these associations are incompletely understood. A biological stress response, which implies release of cortisol, may underlie associations of air pollution exposure and access to neighborhood greenspaces with health.

METHODS

We explored residential exposure to air pollution and residential access to neighborhood greenspaces in relation to hair cortisol concentrations of participants in a prospective pregnancy cohort study in Flanders, Belgium. Hair samples were collected at the end of the second pregnancy trimester (n = 133) and shortly after delivery (n = 81). Cortisol concentrations were measured in 3-cm scalp-near hair sections, to reflect second and third pregnancy trimester cortisol secretion. We estimated long-term (3 months before sampling) residential exposure to fine particulate matter (PM_2.5), nitrogen dioxide (NO₂) and black carbon (BC), assessed residential distance to major roads and residential access to neighborhood greenspaces (NHGS). Associations between residential exposures and hair cortisol concentrations were studied using linear regression models while adjusting for season of sampling.

RESULTS

Three-month mean residential NO₂ and BC concentrations were positively associated with third pregnancy trimester hair cortisol concentrations (p = 0.008 and p = 0.017). Access to a large NHGS (10 ha or more within 800 m from residence) was negatively associated with third trimester hair cortisol concentrations (p = 0.019). Access to a large NHGS significantly moderated the association between residential proximity to major roads and second trimester hair cortisol concentrations (p = 0.021). Residential distance to major roads was negatively associated with second trimester hair cortisol concentrations of participants without access to a large NHGS (p = 0.003). The association was not significant for participants with access to a large NHGS. The moderation tended towards significance in the third pregnancy trimester (p < 0.10).

CONCLUSIONS

Our findings suggest a positive association between long-term residential exposure to air pollution and biological stress during pregnancy, residential access to neighborhood greenspaces may moderate the association. Further research is needed to confirm our results.

TRIAL REGISTRATION

The IPANEMA study is registered under number  NCT02592005 at clinicaltrials.gov .

Residential greenness and birth outcomes: A systematic review and meta-analysis of observational studies

BACKGROUND

The amount of natural vegetation surrounding homes (residential greenness) has been proposed as a mitigation measure to buffer the adverse health effects of urban living, associated with promoting health and wellbeing including birth outcomes. This study aimed to systematically review the epidemiological evidence on the association of residential greenness with birth outcomes and quantitatively provide summary effect estimates of the current literature.

METHODS

We extensively searched epidemiological studies related to residential greenness and birth outcomes in three electronic databases (EMBASE, Web of Science, and PubMed) using terms related to residential greenness and birth outcomes before July 10, 2020. Summary effect estimates of residential greenness on birth outcomes including SGA (small for gestational age), PTB (preterm birth), LBW (low birth weight), and birth weight were calculated for each 0.1 unit increase in residential greenness exposure, as well as comparing the highest to the lowest categories using random-effects meta-analyses. We assessed the risk of bias of each individual study, and the overall quality of the body of evidence and level of evidence for each exposure-outcome were also evaluated.

RESULTS

The initial search identified 161 studies, of which 29 studies were finally included. Meta-analysis for continuous exposure suggested that an increase in residential greenness, measured by NDVI (normalized difference vegetation index) with different buffer sizes, was generally associated with higher birth weights ranging from 7.99 g [95% confidence interval (CI) = 4.29-11.70] to 15.35 g (95% CI = 11.41-19.29) and lower odds of LBW ranging from 0.79 (95% CI = 0.65-0.96) to 0.93 (95% CI = 0.86-1.00), but associations between residential greenness and PTB or SGA were not significant. When introducing the exposure as high versus low categories, similar results were found. The overall evidence for each exposure-outcome combination was considered to be of "moderate" certainty.

CONCLUSIONS

This study indicated a potential positive association between residential greenness and several birth outcomes. However, because of the moderate to high between-study heterogeneity, further studies with better adjustment of covariates, improved residential greenness assessment in a longitudinal approach throughout pregnancy rather than a cross-sectional approach at time of delivery, and accounting thoroughly for socioeconomic status, are warranted to replicate these findings as well as to explore in greater detail in their implications.

The Exposome Approach to Decipher the Role of Multiple Environmental and Lifestyle Determinants in Asthma

Asthma is a widespread respiratory disease caused by complex contribution from genetic, environmental and behavioral factors. For several decades, its sensitivity to environmental factors has been investigated in single exposure (or single family of exposures) studies, which might be a narrow approach to tackle the etiology of such a complex multifactorial disease. The emergence of the exposome concept, introduced by C. Wild (2005), offers an alternative to address exposure-health associations. After presenting an overview of the exposome concept, we discuss different statistical approaches used to study the exposome-health associations and review recent studies linking multiple families of exposures to asthma-related outcomes. The few studies published so far on the association between the exposome and asthma-related outcomes showed differences in terms of study design, population, exposome definition and statistical methods used, making their results difficult to compare. Regarding statistical methods, most studies applied successively univariate (Exposome-Wide Association Study (ExWAS)) and multivariate (adjusted for co-exposures) (e.g., Deletion-Substitution-Addition (DSA) algorithm) regression-based models. This latest approach makes it possible to assess associations between a large set of exposures and asthma outcomes. However, it cannot address complex interactions (i.e., of order ≥3) or mixture effects. Other approaches like cluster-based analyses, that lead to the identification of specific profiles of exposure at risk for the studied health-outcome, or mediation analyses, that allow the integration of information from intermediate biological layers, could offer a new avenue in the understanding of the environment-asthma association. European projects focusing on the exposome research have recently been launched and should provide new results to help fill the gap that currently exists in our understanding of the effect of environment on respiratory health.

Landscapes of becoming social: A systematic review of evidence for associations and pathways between interactions with nature and socioemotional development in children

BACKGROUND

Existing research indicates that spending time in nature is associated with diverse aspects of children's health and wellbeing. Although fundamental to later life chances and health, no systematic reviews, to our knowledge, have focused specifically on the effects of interaction with nature on socioemotional functioning in childhood.

OBJECTIVES

Amongst children, what is the consistency of associations between the availability of or spending time in nature on socioemotional function and development? Furthermore, which child behaviours and states independently associate with socioemotional function and availability of or spending time in nature, and what is the consistency of associations between these behaviours and states and contact with nature?

DATA SOURCES

Embase, Environment Complete, MEDLINE, and APA PsycINFO. Eligible studies were backward and forward snowball-searched.

STUDY ELIGIBILITY CRITERIA

Studies investigating effects of, or associations between, availability of or interaction with nature on socioemotional or proximal outcomes in children under the age of 12 years were included in this review.

STUDY APPRAISAL AND SYNTHESIS METHODS

The internal validity of studies investigating socioemotional outcomes were based on assessments of elements of study design, conduct, and reporting to identify potential issues related to confounding or other biases. The number of analyses indicating positive, negative, and non-significant associations between availability or interaction with green space and the outcomes were summed.

RESULTS

A total of 223 eligible full-texts, of which 43 pertained to socioemotional outcomes and 180 to proximal outcomes, met eligibility criteria. Positive associations between availability of and spending time in green space were found with children's intra- and interpersonal socioemotional function and development. Proportions of positive findings ranged from 13.9% to 55% across experimental and observational research, exposures, populations, and contexts. Modifying and mediating factors were identified. We found consistent evidence for improved aspects of cognition and, for children over six years, reduced risk of obesity and overweight in association with green space; consistent links between movement behaviours in the experimental, but not observational research; tentative trends suggesting associations with play, motor skills, language, screen time, and communication skills; little evidence for positive associations between green space and mood, physical wellbeing, and stress; some evidence for associations with healthy birth outcomes, and little evidence for direct associations between availability of green space and asthma and allergy prevalence, however, mediation via, for example, air pollution was likely.

LIMITATIONS

We identified few studies without either probable or severe risk of bias in at least one item. Improved study quality may therefore result in different results. Restricting analyses to include only studies considered at low risk of bias indicated similar or slightly lower proportions of positive findings. Risk of bias in proximal outcomes was not assessed.

CONCLUSIONS

The empirical evidence for benefits of availability of and interaction green space for child socioemotional function and development must currently be considered limited. A number of proximal indicators were identified. Systematic review registration number.

PROSPERO ID

CRD42019135016.

Estimating the Combined Effects of Natural and Built Environmental Exposures on Birthweight among Urban Residents in Massachusetts

Intrauterine growth has health implications both in childhood and adulthood. Birthweight is partially determined by prenatal environmental exposures. We aim to identify important predictors of birthweight out of a set of environmental, built environment exposures, and socioeconomic environment variables during pregnancy (i.e., fine particulate matter (PM2.5), temperature, greenness, walkability, noise, and economic indices). We included all singleton live births of mothers who resided in urban census block-groups and delivered in Massachusetts between 2001 and 2011 (n = 640,659). We used an elastic-net model to select important predictors of birthweight and constructed a multivariate model including the selected predictors, with adjustment for confounders. We additionally used a weighted quantile sum regression to assess the contribution of each exposure to differences in birthweight. All exposures were selected as important predictors of birthweight. In the multivariate model, lower birthweight was significantly associated with lower greenness and with higher temperature, walkability, noise, and segregation of the "high income" group. Treating the exposures individually, nighttime noise had the highest weight in its contribution to lower birthweight. In conclusion, after accounting for individual confounders, maternal environmental exposures, built environment exposures, and socioeconomic environment during pregnancy were important predictors of birthweight, emphasizing the role of these exposures in fetal growth and development.

Early life exposure to air pollution, green spaces and built environment, and body mass index growth trajectories during the first 5 years of life: A large longitudinal study

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/m²) was calculated. Urban exposures were estimated at census tract level and included: air pollution (nitrogen dioxide (NO₂), particulate matter <10 μm (PM₁₀) 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 PM₁₀ increase = 0.023 kg/m², 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 PM₁₀ 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.

Exposure to greenspace and birth weight in a middle-income country

An emerging body of evidence has associated exposure to greenspace during pregnancy with improved fetal growth; however, all available studies have been conducted in high-income countries and the available evidence evaluating such an association for visual access to greenspace, use of green spaces and indoor plants is non-existent. We aimed to evaluate the association between a comprehensive array of indicators of exposure to greenspace during pregnancy, including the aforementioned indicators, and birth weight, in a middle-income country and evaluating air pollution and visual access as possible mechanisms underlying the association. This study was based on 301 pregnant women residing in Su et al. (2019). For each pregnant woman, we characterized exposure to residential surrounding greenspace, visual access to greenspace, residential proximity to green space, use of green spaces, and the number of plant pots at home. We used linear regression models adjusted for relevant covariates including measures of socioeconomic status. We found positive associations of maternal exposure to residential surrounding greenspace across a 100 m buffer, frequent viewing of greenspace through the window, percentage of window area covered by greenspace, residential proximity to any green space regardless of its area, time spent in public green spaces and total time spent in public and private green spaces with birth weight. We also observed positive associations of maternal exposure to residential surrounding greenspace across 300 m and 500 m buffers, residential proximity to a green space with an area ≥5000 m², and indoor plant pots with birth weight, but none of these associations were statistically significant. The magnitude of the associations tended to be higher among parents with lower socioeconomic status. Mediation through air pollution or visual access was not established. Findings from this study suggested a positive role of different aspects of exposure to greenspace during pregnancy on birth weight in a middle-income country.

Traffic-related metrics and adverse birth outcomes: A systematic review and meta-analysis

Given the inconsistency of epidemiologic evidence for associations between maternal exposures to traffic-related metrics and adverse birth outcomes, this manuscript aims to provide clarity on this topic. Pooled meta-estimates were calculated using random-effects analyses. Subgroup analyses were conducted by study area, study design, and Newcastle-Ottawa quality score (NOS). Funnel plots and Egger's test were conducted to evaluate the publication bias, and Fail-safe Numbers (Fail-safe N) were measured to evaluate the robustness of models. From the initial 740 studies (last search, July 11, 2019), 26 studies were included in our analysis. The pooled odds ratio for the change in small for gestational age associated with per 500 m decrease in the distance to roads was 1.016 (95% CI: 1.004, 1.029). Subgroup analyses revealed significant positive associations between term low birth weight and traffic density in higher-quality literatures with higher NOS [1.060 (95% CI: 1.002, 1.121)], cohort studies [1.020 (95% CI: 1.006, 1.033)], and studies in North America [1.018 (95% CI: 1.005, 1.131)]. The buffer of traffic density made no difference in the effect size. Traffic density seemed to be a better indicator of traffic pollution than the distance to roads.

Associations between green space and preterm birth: Windows of susceptibility and interaction with air pollution

BACKGROUND

Recent studies have reported inconsistent associations between maternal residential green space and preterm birth (PTB, born < 37 completed gestational weeks). In addition, windows of susceptibility during pregnancy have not been explored and potential interactions of green space with air pollution exposures during pregnancy are still unclear.

OBJECTIVES

To evaluate the relationships between green space and PTB, identify windows of susceptibility, and explore potential interactions between green space and air pollution.

METHODS

Birth certificate records for all births in California (2001-2008) were obtained. The Normalized Difference Vegetation Index (NDVI) was used to characterized green space exposure. Gestational age was treated as a time-to-event outcome; Cox proportional hazard models were applied to estimate the association between green space exposure and PTB, moderately PTB (MPTB, gestational age < 35 weeks), and very PTB (VPTB, gestational age < 30 weeks), after controlling for maternal age, race/ethnicity, education, and median household income. Month-specific green space exposure was used to identify potential windows of susceptibility. Potential interactions between green space and air pollution [fine particulate matter < 2.5 µm (PM_2.5), nitrogen dioxide (NO₂), and ozone (O₃)] were examined on both additive and multiplicative scales.

RESULTS

In total, 3,753,799 eligible births were identified, including 341,123 (9.09%) PTBs, 124,631 (3.32%) MPTBs, and 22,313 (0.59%) VPTBs. A reduced risk of PTB was associated with increases in residential NDVI exposure in 250 m, 500 m, 1000 m, and 2000 m buffers. In the 2000 m buffer, the association was strongest for VPTB [adjusted hazard ratio (HR) per interquartile range increase in NDVI: 0.959, 95% confidence interval (CI): 0.942-0.976)], followed by MPTB (HR = 0.970, 95% CI: 0.962-0.978) and overall PTB (HR = 0.972, 95% CI: 0.966-0.978). For PTB, green space during the 3rd - 5th gestational months had stronger associations than those in the other time periods, especially during the 4th gestational month (NDVI 2000 m: HR = 0.970, 95% CI: 0.965-0.975). We identified consistent positive additive and multiplicative interactions between decreasing green space and higher air pollution.

CONCLUSION

This large study found that maternal exposure to residential green space was associated with decreased risk of PTB, MPTB, and VPTB, especially in the second trimester. There is a synergistic effect between low green space and high air pollution levels on PTB, indicating that increasing exposure to green space may be more beneficial for women with higher air pollution exposures during pregnancy.

The associations of residential greenness with fetal growth in utero and birth weight: A birth cohort study in Beijing, China

BACKGROUND

Although studies have examined the association between residential greenness and birth weight, there is no evidence regarding the association between residential greenness and fetal growth in utero. We aimed to investigate the associations of residential greenness with both fetal growth in utero and birth weight.

METHODS

A birth cohort (2014-2017) with 18,665 singleton pregnancies was established in Tongzhou Maternal and Child hospital of Beijing, China. Residential greenness was matched with maternal residential address and estimated from remote satellite data using normalized difference vegetation index with 200 m and 500 m buffers (NDVI-200 and NDVI-500). Fetal parameters including estimated fetal weight (EFW), abdominal circumference (AC), head circumference (HC) and femur length (FL) were assessed by ultrasound measurements during pregnancy. Fetal parameters were standardized as gestational-age- and gender-adjusted Z-score and undergrowth was defined as Z-score < -1.88. Birth weight Z-score, low birth weight (LBW) and small for gestational age (SGA) were assessed as birth outcomes. Generalized estimating equations with the autoregressive working correlation structure and generalized linear regression were used to examine the associations of residential greenness with quantitative and categorized outcomes.

RESULTS

We found an increase Z-score of EFW [0.054, 95% confidence interval (CI): 0.020-0.087], AC (0.045, 95%CI: 0.011-0.080) and HC (0.054, 95%CI: 0.020-0.089) associated with residential greenness above NDVI-500 median compared to less than and equal to NDVI-500 median. Stratified analyses indicated that the associations might be stronger in women exposed to lower levels of particles with aerodynamic diameters ≤2.5 µm. No associations were found in the analyses of NDVI-250 with fetal growth in utero. We didn't observe significant associations of NDVI with birth weight Z-score, LBW and SGA.

CONCLUSIONS

This study identified a positive association of NDVI-500 and fetal growth in utero, but we didn't observe its association with birth weight measures. Our results suggest that building sufficient green infrastructure might potentially promote early life health.

An external exposome-wide association study of hypertensive disorders of pregnancy

It is widely recognized that exogenous factors play an important role in the development of hypertensive disorders of pregnancy (HDP). However, only a few external environmental factors have been studied, often separately, with no attempt to examine the totality of the external environment, or the external exposome. We conducted an external exposome-wide association study (ExWAS) using the Florida Vital Statistics Birth Records including 819,399 women with live births in 2010-2013. A total of 5784 factors characterizing women's surrounding natural, built, and social environment during pregnancy from 10 data sources were collected, harmonized, integrated, and spatiotemporally linked to the women based on pregnancy periods using 250 m buffers around their geocoded residential addresses. A random 50:50 split divided the data into discovery and replication sets, and a 3-phase procedure was used. In phase 1, associations between HDP and individual factors were examined, and Bonferroni adjustment was performed. In phase 2, an elastic net model was used to perform variable selection among significant variables from phase 1. In phase 3, a multivariable logistic regression model including all variables selected by the elastic net model was fitted. Variables that were significant in both the discovery and replication sets were retained. Among the 528 and 490 variables identified in Phase 1, 232 and 224 were selected by the elastic net model in Phase 2, and 67 and 48 variables remained statistically significant in Phase 3 in the discovery and replication sets, respectively. A total of 12 variables were significant in both the discovery and replication sets, including air toxicants (e.g., 2,2,4-trimethylpentane), meteorological factors (e.g., omega or vertical velocity at 125mb pressure level), neighborhood crime and safety (e.g., burglary rate), and neighborhood sociodemographic status (e.g., urbanization). This is the first large external exposome study of HDP. It confirmed some of the previously reported associations and generated unexpected predictors within the environment that may warrant more focused evaluation.

Testing the Multiple Pathways of Residential Greenness to Pregnancy Outcomes Model in a Sample of Pregnant Women in the Metropolitan Area of Donostia-San Sebastián

Residential greenness may positively impact diverse human health indicators through the reduction of air pollution, the improvement of psychological health, and the promotion of physical activity. Previous studies indicate a weak but positive association with pregnancy outcomes. Our aim was to test the multiple pathways from residential greenness to pregnancy outcomes model, using residential NO₂ concentrations, psychological health, and moderate-to-vigorous physical activity (MVPA) during the first trimester of pregnancy, in a sample of 440 pregnant women residing in Donostia, Spain. Three metrics of residential greenness were calculated around each participant’s home address: normalized difference vegetation index (NDVI) within 300 m, and green space (>5000 m²) availability within 300 and 500 m. Residential NO₂ concentrations, psychological health, and MVPA were explored as mediators of the associations between these metrics and the following pregnancy outcomes: birth weight (BW), low birth weight (LBW), prematurity, small for gestational age (SGA), and large for gestational age (LGA). Educational attainment, parity, and body mass index (BMI) were treated as covariates. Counterfactual mediation analyses showed very low to null statistical support for an association between any of the greenspace metrics and pregnancy outcomes in the full sample. Green space availability (300 m) was associated with lower BW and showed a marginal protective effect against LGA.