The socioeconomic landscape of the exposome during pregnancy

Socioeconomic Inequalities in the External Exposome in European Cohorts: The EXPANSE Project

Socioeconomic inequalities in the exposome have been found to be complex and highly context-specific, but studies have not been conducted in large population-wide cohorts from multiple countries. This study aims to examine the external exposome, encompassing individual and environmental factors influencing health over the life course, and to perform dimension reduction to derive interpretable characterization of the external exposome for multicountry epidemiological studies. Analyzing data from over 25 million individuals across seven European countries including 12 administrative and traditional cohorts, we utilized domain-specific principal component analysis (PCA) to define the external exposome, focusing on air pollution, the built environment, and air temperature. We conducted linear regression to estimate the association between individual- and area-level socioeconomic position and each domain of the external exposome. Consistent exposure patterns were observed within countries, indicating the representativeness of traditional cohorts for air pollution and the built environment. However, cohorts with limited geographical coverage and Southern European countries displayed lower temperature variability, especially in the cold season, compared to Northern European countries and cohorts including a wide range of urban and rural areas. The individual- and area-level socioeconomic determinants (i.e., education, income, and unemployment rate) of the urban exposome exhibited significant variability across the European region, with area-level indicators showing stronger associations than individual variables. While the PCA approach facilitated common interpretations of the external exposome for air pollution and the built environment, it was less effective for air temperature. The diverse socioeconomic determinants suggest regional variations in environmental health inequities, emphasizing the need for targeted interventions across European countries.

Socioeconomic position during pregnancy and pre-school exposome in children from eight European birth cohort studies

Distribution of environmental hazards and vulnerability to their effects vary across socioeconomic groups. Our objective was to analyse the relationship between child socioeconomic position (SEP) at birth and the external exposome at pre-school age (0-4 years). This study included more than 60,000 children from eight cohorts in eleven European cities (Oslo, Copenhagen, Bristol, Bradford, Rotterdam, Nancy, Poitiers, Gipuzkoa, Sabadell, Valencia and Turin). SEP was measured through maternal education and a standardised indicator of household income. Three child exposome domains were investigated: behavioral, diet and urban environment. We fitted separate logistic regression model for each exposome variable - dichotomised using the city-specific median - on SEP (medium/low vs high) adjusting for maternal age, country of birth and parity. Analyses were carried out separately in each study-area. Low-SEP children had, consistently across study-areas, lower Odds Ratios (ORs) of breastfeeding, consumption of eggs, fish, fruit, vegetables and higher ORs of TV screen time, pet ownership, exposure to second-hand smoke, consumption of dairy, potatoes, sweet beverages, savory biscuits and crisps, fats and carbohydrates. For example, maternal education-breastfeeding OR (95% Confidence Interval (CI)) ranged from 0.18 (0.14-0.24) in Bristol to 0.73 (0.58-0.90) in Oslo. SEP was also strongly associated with the urban environment with marked between-city heterogeneity. For example, income-PM2.5 OR (95%CI) ranged from 0.69 (0.47-1.02) in Sabadell to 2.44 (2.16-2.72) in Oslo. Already at pre-school age, children with lower SEP have consistently poorer diets and behaviours, which might influence their future health and wellbeing. SEP-urban environment relationships are strongly context-dependent.

Socioeconomic disadvantage and long-term survival duration in out-of-hospital cardiac arrest patients: A population-based cohort study

Background

Socioeconomic status (SES) is a well-established determinant of cardiovascular health. However, the relationship between SES and clinical outcomes in long-term out-of-hospital cardiac arrest (OHCA) is less well-understood. The Singapore Housing Index (SHI) is a validated building-level SES indicator. We investigated whether SES as measured by SHI is associated with long-term OHCA survival in Singapore.

Methods

We conducted an open cohort study with linked data from the Singapore Pan-Asian Resuscitation Outcomes Study (PAROS), and the Singapore Registry of Births and Deaths (SRBD) from 2010 to 2020. We fitted generalized structural equation models, calculating hazard ratios (HRs) using a Weibull model. We constructed Kaplan-Meier survival curves and calculated the predicted marginal probability for each SHI category.

Results

We included 659 cases. In both univariable and multivariable analyses, SHI did not have a significant association with survival. Indirect pathways of SHI mediated through covariates such as Emergency Medical Services (EMS) response time (HR of low-medium, high-medium and high SHI when compared to low SHI: 0.98 (0.88-1.10), 1.01 (0.93-1.11), 1.02 (0.93-1.12) respectively), and age of arrest (HR of low-medium, high-medium and high SHI when compared to low SHI: 1.02 (0.75-1.38), 1.08 (0.84-1.38), 1.18 (0.91-1.54) respectively) had no significant association with OHCA survival. There was no clear trend in the predicted marginal probability of survival among the different SHI categories.

Conclusions

We did not find a significant association between SES and OHCA survival outcomes in residential areas in Singapore. Among other reasons, this could be due to affordable healthcare across different socioeconomic classes.

Urban environment during pregnancy and lung function, wheezing, and asthma in school-age children. The generation R study

The urban environment during pregnancy may influence child's respiratory health, but scarce evidence exists on systematic evaluation of multiple urban exposures (e.g., air pollution, natural spaces, noise, built environment) on children's lung function, wheezing, and asthma development. We aimed to examine the association of the urban environment during pregnancy with lung function, preschool wheezing, and school-age asthma. We included 5624 mother-child pairs participating in a population-based prospective birth cohort. We estimated 30 urban environmental exposures including air pollution, road traffic noise, traffic, green spaces, blue spaces, and built environment during pregnancy. At 10 years of age, lung function was measured by spirometry. Information on preschool wheezing and physician-diagnosed school-age asthma was obtained from multiple questionnaires. We described single-exposure associations with respiratory outcomes using an exposome-wide association study. We also identified patterns of urban exposures with hierarchical clustering on principal components analysis and examined their associations with respiratory outcomes using multivariate regression models. Single-exposure analyses showed associations of higher particulate matter (PM) with lower mid-expiratory flow (FEF25-75%) (e.g., for PM < 2.5 μm of diameter [PM2.5] z-score = -0.06 [-0.09, -0.03]) and higher forced expiratory volume in 1s (FEV1) and forced vital capacity (FVC) (e.g., for PM2.5 FEV1 0.05 [0.02, 0.08]) after correction for multiple-hypothesis testing. Cluster analysis described three patterns of urban exposures during pregnancy and showed that the cluster characterised by higher levels of air pollution, noise, walkability, street connectivity, and lower levels of natural spaces were associated with lower FEF25-75% (-0.08 [-0.17, 0.00]), and higher odds of preschool wheezing (1.21 [1.03, 1.43]). This study shows that the characteristics of the urban environment during pregnancy are of relevance to the offspring's respiratory health during childhood.

Questionnaire-based exposome-wide association studies for common diseases in the Personalized Environment and Genes Study

The exposome collectively refers to all exposures, beginning in utero and continuing throughout life, and comprises not only standard environmental exposures such as point source pollution and ozone levels but also exposures from diet, medication, lifestyle factors, stress, and occupation. The exposome interacts with individual genetic and epigenetic characteristics to affect human health and disease, but large-scale studies that characterize the exposome and its relationships with human disease are limited. To address this gap, we used extensive questionnaire data from the diverse North Carolina-based Personalized Environment and Genes Study (PEGS, n = 9, 429) to evaluate exposure associations in relation to common diseases. We performed an exposome-wide association study (ExWAS) to examine single exposure models and their associations with 11 common complex diseases, namely allergic rhinitis, asthma, bone loss, fibroids, high cholesterol, hypertension, iron-deficient anemia, ovarian cysts, lower GI polyps, migraines, and type 2 diabetes. Across diseases, we found associations with lifestyle factors and socioeconomic status as well as asbestos, various dust types, biohazardous material, and textile-related exposures. We also found disease-specific associations such as fishing with lead weights and migraines. To differentiate between a replicated result and a novel finding, we used an AI-based literature search and database tool that allowed us to examine the current literature. We found both replicated findings, especially for lifestyle factors such as sleep and smoking across diseases, and novel findings, especially for occupational exposures and multiple diseases.

Integrating the social environment with an equity perspective into the exposome paradigm: A new conceptual framework of the Social Exposome

The importance of the social environment and social inequalities in disease etiology is well-known due to the profound research and conceptual framework on social determinants of health. For a long period, in exposome research with its classical orientation towards detrimental health effects of biological, chemical, and physical exposures, this knowledge remained underrepresented. But currently it gains great awareness and calls for innovations in rethinking the role of social environmental health determinants. To fill this gap that exists in terms of the social domain within exposome research, we propose a novel conceptual framework of the Social Exposome, to integrate the social environment in conjunction with the physical environment into the exposome concept. The iterative development process of the Social Exposome was based on a systematic compilation of social exposures in order to achieve a holistic portrayal of the human social environment - including social, psychosocial, socioeconomic, sociodemographic, local, regional, and cultural aspects, at individual and contextual levels. In order to move the Social Exposome beyond a mere compilation of exposures, three core principles are emphasized that underly the interplay of the multitude of exposures: Multidimensionality, Reciprocity, and Timing and continuity. The key focus of the conceptual framework of the Social Exposome is on understanding the underlying mechanisms that translate social exposures into health outcomes. In particular, insights from research on health equity and environmental justice have been incorporated to uncover how social inequalities in health emerge, are maintained, and systematically drive health outcomes. Three transmission pathways are presented: Embodiment, Resilience and Susceptibility or Vulnerability, and Empowerment. The Social Exposome conceptual framework may serve as a strategic map for, both, research and intervention planning, aiming to further explore the impact of the complex social environment and to alter transmission pathways to minimize health risks and health inequalities and to foster equity in health.

Exposure to perfluoroalkyl substances and women's fertility outcomes in a Singaporean population-based preconception cohort

OBJECTIVES

Experimental models have demonstrated a link between exposure to perfluoroalkyl substances (PFAS) and decreased fertility and fecundability; however, human studies are scarce. We assessed the associations between preconception plasma PFAS concentrations and fertility outcomes in women.

METHODS

In a case-control study nested within the population-based Singapore Preconception Study of Long-Term Maternal and Child Outcomes (S-PRESTO), we measured PFAS in plasma collected in 2015-2017 from 382 women of reproductive age trying to conceive. Using Cox proportional hazards regression (fecundability ratios [FRs]) and logistic regression (odds ratios [ORs]) models, we assessed the associations of individual PFAS with time-to-pregnancy (TTP), and the likelihoods of clinical pregnancy and live birth, respectively, over one year of follow-up, adjusting for analytical batch, age, education, ethnicity, and parity. We used Bayesian weighted quantile sum (BWQS) regression to assess the associations of the PFAS mixture with fertility outcomes.

RESULTS

We found a 5-10 % reduction in fecundability per quartile increase of exposure to individual PFAS (FRs [95 % CIs] for clinical pregnancy = 0.90 [0.82, 0.98] for PFDA; 0.88 [0.79, 0.99] for PFOS; 0.95 [0.86, 1.06] for PFOA; 0.92 [0.84, 1.00] for PFHpA). We observed similar decreased odds of clinical pregnancy (ORs [95 % CIs] = 0.74 [0.56, 0.98] for PFDA; 0.76 [0.53, 1.09] for PFOS; 0.83 [0.59, 1.17] for PFOA; 0.92 [0.70, 1.22] for PFHpA) and live birth per quartile increases of individual PFAS and the PFAS mixture (ORs [95 % CIs] = 0.61 [0.37, 1.02] for clinical pregnancy, and 0.66 [0.40, 1.07] for live birth). Within the PFAS mixture, PFDA followed by PFOS, PFOA, and PFHpA were the biggest contributors to these associations. We found no evidence of association for PFHxS, PFNA, and PFHpS and the fertility outcomes examined.

CONCLUSIONS

Higher PFAS exposures may be associated with decreased fertility in women. The potential impact of ubiquitous PFAS exposures on infertility mechanisms requires further investigation.

Modelling socioeconomic position as a driver of the exposome in the first 18 months of life of the NINFEA birth cohort children

BACKGROUND

The exposome drivers are less studied than its consequences but may be crucial in identifying population subgroups with unfavourable exposures.

OBJECTIVES

We used three approaches to study the socioeconomic position (SEP) as a driver of the early-life exposome in Turin children of the NINFEA cohort (Italy).

METHODS

Forty-two environmental exposures, collected at 18 months of age (N = 1989), were classified in 5 groups (lifestyle, diet, meteoclimatic, traffic-related, built environment). We performed cluster analysis to identify subjects sharing similar exposures, and intra-exposome-group Principal Component Analysis (PCA) to reduce the dimensionality. SEP at childbirth was measured through the Equivalised Household Income Indicator. SEP-exposome association was evaluated using: 1) an Exposome Wide Association Study (ExWAS), a one-exposure (SEP) one-outcome (exposome) approach; 2) multinomial regression of cluster membership on SEP; 3) regressions of each intra-exposome-group PC on SEP.

RESULTS

In the ExWAS, medium/low SEP children were more exposed to greenness, pet ownership, passive smoking, TV screen and sugar; less exposed to NO₂, NO_X, PM_25abs, humidity, built environment, traffic load, unhealthy food facilities, fruit, vegetables, eggs, grain products, and childcare than high SEP children. Medium/low SEP children were more likely to belong to a cluster with poor diet, less air pollution, and to live in the suburbs than high SEP children. Medium/low SEP children were more exposed to lifestyle PC1 (unhealthy lifestyle) and diet PC2 (unhealthy diet), and less exposed to PC1s of the built environment (urbanization factors), diet (mixed diet), and traffic (air pollution) than high SEP children.

CONCLUSIONS

The three approaches provided consistent and complementary results, suggesting that children with lower SEP are less exposed to urbanization factors and more exposed to unhealthy lifestyles and diet. The simplest method, the ExWAS, conveys most of the information and is more replicable in other populations. Clustering and PCA may facilitate results interpretation and communication.