Multi-exposure Models Research Articles

Linking joint exposures to residential greenness and air pollution with adults’ social health in dense Hong Kong

Despite the growing recognition of the impact of urban environments on social health, limited research explores the combined associations of multiple urban exposures, particularly in dense cities. This study examines the interplay between greenspace, air pollution, and social health as well as the underlying pathways and population heterogeneity in Hong Kong using cross-sectional survey data from 1977 adults and residential environmental data. Social health includes social contacts, relations, and support. Greenspace used street-view greenness (SVG), park density, and the normalized difference vegetation index (NDVI). 100-m daily ground NO2 and O3, indicative of air pollution, were derived using a spatiotemporal deep learning model. Mediators involved physical activity and negative emotions. Main analyses were performed in a 1000-m buffer with multivariate logistical regressions, stratification, interaction, and Partial Lease Square - Structural Equation Modelling (PLS-SEM). Multi-exposure models revealed positive associations between park density/SVG and social contacts, as well as between SVG and social relations, while O3 was negatively associated with social relations/support. Significant moderators included age, birthplace, employment, and education. PLS-SEM indicated direct positive associations between SVG and social contacts/relations and significant indirect negative associations between NO2/O3 and social health via negative emotions. This study adds to urban health research by exploring complex relationships between greenspace, air pollution, and social health, highlighting the role of the environment in fostering social restoration.

Prediction of overweight/obesity risk in adolescence using static and dynamic multi-exposure models

Abstract Background Studying the risk factors for obesity development and timely identification of individuals at increased risk are key for obesity prevention. We aimed to assess the associations of multiple prenatal, infancy and childhood exposures with overweight/obesity at 13 years (y) and develop static and dynamic multiple-exposure prediction models. Methods In 4232 mother-child pairs from the Generation XXI birth cohort, we assessed, during pregnancy/infancy and childhood, 55 sociodemographic factors, anthropometric measures, lifestyle behaviors, and clinical exposures related to the mother and the child and categorized body mass index z-scores as normal weight and overweight/obesity at 13y. Static models for pregnancy/infancy, 4, 7 and 10y, and a dynamic model were fitted using Elastic Net and logistic regression and were compared in terms of predictive performance. Results Mothers with lower educational level and household income, no partner, overweight/obesity before and after pregnancy, excessive gestational weight gain, pregnancy complications and who were smokers during pregnancy had children with a higher risk of overweight/obesity at 13y. Children with higher BMI during infancy, overweight/obesity during childhood, an early introduction of solid foods (before 4 months), a higher consumption of soft drinks at 4y and females had a higher risk of overweight/obesity at 13y. We observed the lowest predictive performance for the pregnancy/infancy model (prediction error of 36%) and the highest predictive performance for the 10y and dynamic models (prediction errors of 17%). Conclusions We identified the most important predictors of overweight/obesity in adolescence, most of them modifiable, and able to be targeted in prevention strategies. Predicting overweight/obesity risk in adolescence might be suboptimal if only considering pregnancy/infancy data and improves as closer to the age of the outcome, with no additional benefit in using a complex dynamic model. Key messages • Prevention of overweight/obesity should start during prenatal life. • Children at higher risk of overweight/obesity may be identified years earlier using prediction models in clinical practice.

Air pollution, traffic noise, mental health, and cognitive development: A multi-exposure longitudinal study of London adolescents in the SCAMP cohort

BackgroundThere is increasing evidence that air pollution and noise may have detrimental psychological impacts, but there are few studies evaluating adolescents, ground-level ozone exposure, multi-exposure models, or metrics beyond outdoor residential exposure. This study aimed to address these gaps. MethodsAnnual air pollution and traffic noise exposure at home and school were modelled for adolescents in the Greater London SCAMP cohort (N=7555). Indoor, outdoor and hybrid environments were modelled for air pollution. Cognitive and mental health measures were self-completed at two timepoints (baseline aged 11–12 and follow-up aged 13–15). Associations were modelled using multi-level multivariate linear or ordinal logistic regression. ResultsThis is the first study to investigate ground-level ozone exposure in relation to adolescent executive functioning, finding that a 1 interquartile range increase in outdoor ozone corresponded to −0.06 (p < 0.001) z-score between baseline and follow-up, 38 % less improvement than average (median development + 0.16). Exposure to nitrogen dioxide (NO2), 24-hour traffic noise, and particulate matter < 10 µg/m3 (PM10) were also significantly associated with slower executive functioning development when adjusting for ozone. In two-pollutant models, particulate matter and ozone were associated with increased externalising problems. Daytime and evening noise were associated with higher anxiety symptoms, and 24-hour noise with worse speech-in-noise perception (auditory processing). Adjusting for air pollutants, 24-hour noise was also associated with higher anxiety symptoms and slower fluid intelligence development. ConclusionsOzone’s potentially detrimental effects on adolescent cognition have been overlooked in the literature. Our findings also suggest harmful impacts of other air pollutants and noise on mental health. Further research should attempt to replicate these findings and use mechanistic enquiry to enhance causal inference. Policy makers should carefully consider how to manage the public health impacts of ozone, as efforts to reduce other air pollutants such as NO2 can increase ozone levels, as will the progression of climate change.

Urban environment exposures, energy balance-related behaviors and their combination in preschoolers from three European countries

BackgroundUrban environments are characterized by many factors that may influence children’s energy balance-related behaviors (EBRBs), but there is limited research on the impact of prospective exposure to multiple urban factors in preschoolers. We evaluated prospective associations between various urban exposures and EBRBs in preschoolers across Europe, with EBRBs considered both individually and combined into lifestyle patterns. MethodsWe used data from 4,073 preschoolers (aged 3–4 years) participating in three European cohorts from the EU Child Cohort Network: BiB (United Kingdom), EDEN (France), and INMA (Spain). Eighteen built and food environment, green spaces, road traffic and ambient air pollution exposures were characterized at residential addresses. Various EBRBs were considered as the outcomes including screen time, sleep duration and diet (fruit, vegetables, discretionary sweet foods, sweet beverages) individually and combined into unhealthy lifestyle patterns, using principal components analysis. Associations between urban exposures and outcomes were estimated using a single-exposure analysis and the deletion-substitution-addition algorithm was used to construct multi-exposure models. ResultsIn multi-exposure models, greater walkability and smaller distance to the nearest road were associated with higher scores on the unhealthy lifestyle patterns. Likewise, greater walkability was associated with higher screen time and more frequent discretionary sweet food consumption. A smaller distance to the nearest road was also associated with lower sleep duration and more frequent sweet beverages consumption. On the other hand, higher levels of street connectivity showed an inverse association with the unhealthy lifestyle patterns. In the same vein, greater street connectivity was associated with decreased screen time. ConclusionThis comprehensive examination of multiple urban exposures indicates that residing in walkable environments and in close proximity to roads in densely-populated areas may not be advantageous for children EBRBs, while residing in neighborhoods with higher street connectivity appears to supposedly be beneficial.

Long-term exposure to air pollution, road traffic noise and greenness, and incidence of myocardial infarction in women

BackgroundEmerging evidence shows that long-term exposure to air pollution, road traffic noise, and greenness can each be associated with cardiovascular disease, but only few studies combined these exposures. In this study, we assessed associations of multiple environmental exposures and incidence of myocardial infarction using annual time-varying predictors. Materials and MethodsIn a population-based cohort of 20,407 women in Sweden, we estimated a five-year moving average of residential exposure to air pollution (PM2.5, PM10 and NO2), road traffic noise (Lden), and greenness (normalized difference vegetation index, NDVI in 500 m buffers), from 1998 to 2017 based on annually varying exposures and address history. We used adjusted time-varying Cox proportional hazards regressions to estimate hazard ratios (HR) and 95 % confidence intervals (95 % CI) of myocardial infarction per interquartile range (IQR). Furthermore, we investigated interactions between the exposures and explored potential vulnerable subgroups. ResultsIn multi-exposure models, long-term exposure to greenness was inversely associated with incidence of myocardial infarction (HR 0.89; 95 % CI 0.80, 0.99 per IQR NDVI increase). Stronger associations were observed in some subgroups, e.g. among women with low attained education and in overweight (BMI ≥ 25 kg/m2) compared to their counterparts. For air pollution, we observed a tendency of an increased risk of myocardial infarction in relation to PM2.5 (HR 1.07; 95 % CI 0.93, 1.23) and the association appeared stronger in women with low attained education (HR 1.30; 95 % CI 1.06, 1.58). No associations were observed for PM10, NO2 or road traffic noise. Furthermore, there were no clear interaction patterns between the exposures. ConclusionOver a 20-year follow-up period, in multi-exposure models, we found an inverse association between residential greenness and risk of myocardial infarction among women. Furthermore, we observed an increased risk of myocardial infarction in relation to PM2.5 among women with low attained education. Road traffic noise was not associated with myocardial infarction.

Long-term exposure to air pollution, greenness and temperature and survival after a nonfatal myocardial infarction

BackgroundLittle is known about the impact of environmental exposures on mortality risk after a myocardial infarction (MI). ObjectiveThe goal of this study was to evaluate associations of long-term temperature, air pollution and greenness exposures with mortality among survivors of an MI. MethodsWe used data from the US-based Nurses’ Health Study to construct an open cohort of survivors of a nonfatal MI 1990–2017. Participants entered the cohort when they had a nonfatal MI, and were followed until death, loss to follow-up, end of follow-up, or they reached 80 years old, whichever came earliest. We assessed residential 12-month moving average fine particulate matter (PM2.5) and nitrogen dioxide (NO2), satellite-based annual average greenness (in a circular 1230 m buffer), summer average temperature and winter average temperature. We used Cox proportional hazard models adjusted for potential confounders to assess hazard ratios (HR and 95% confidence intervals). We also assessed potential effect modification. ResultsAmong 2262 survivors of a nonfatal MI, we observed 892 deaths during 19,216 person years of follow-up. In single-exposure models, we observed a HR (95%CI) of 1.20 (1.04, 1.37) per 10 ppb NO2 increase and suggestive positive associations were observed for PM2.5, lower greenness, warmer summer average temperature and colder winter average temperature. In multi-exposure models, associations of summer and winter average temperature remained stable, while associations of NO2, PM2.5 and greenness attenuated. The strength of some associations was modified by other exposures. For example, associations of greenness (HR = 0.88 (0.78, 0.98) per 0.1) were more pronounced for participants in areas with a lower winter average temperature. ConclusionWe observed associations of air pollution, greenness and temperature with mortality among MI survivors. Some associations were confounded or modified by other exposures, indicating that it is important to explore the combined impact of environmental exposures.

An exposome atlas of serum reveals the risk of chronic diseases in the Chinese population

Although adverse environmental exposures are considered a major cause of chronic diseases, current studies provide limited information on real-world chemical exposures and related risks. For this study, we collected serum samples from 5696 healthy people and patients, including those with 12 chronic diseases, in China and completed serum biomonitoring including 267 chemicals via gas and liquid chromatography-tandem mass spectrometry. Seventy-four highly frequently detected exposures were used for exposure characterization and risk analysis. The results show that region is the most critical factor influencing human exposure levels, followed by age. Organochlorine pesticides and perfluoroalkyl substances are associated with multiple chronic diseases, and some of them exceed safe ranges. Multi-exposure models reveal significant risk effects of exposure on hyperlipidemia, metabolic syndrome and hyperuricemia. Overall, this study provides a comprehensive human serum exposome atlas and disease risk information, which can guide subsequent in-depth cause-and-effect studies between environmental exposures and human health.

Disentangling associations between multiple environmental exposures and all-cause mortality: an analysis of European administrative and traditional cohorts.

We evaluated the independent and joint effects of air pollution, land/built environment characteristics, and ambient temperature on all-cause mortality as part of the EXPANSE project. We collected data from six administrative cohorts covering Catalonia, Greece, the Netherlands, Rome, Sweden, and Switzerland and three traditional cohorts in Sweden, the Netherlands, and Germany. Participants were linked to spatial exposure estimates derived from hybrid land use regression models and satellite data for: air pollution [fine particulate matter (PM2.5), nitrogen dioxide (NO₂), black carbon (BC), warm season ozone (O3)], land/built environment [normalized difference vegetation index (NDVI), distance to water, impervious surfaces], and ambient temperature (the mean and standard deviation of warm and cool season temperature). We applied Cox proportional hazard models accounting for several cohort-specific individual and area-level variables. We evaluated the associations through single and multiexposure models, and interactions between exposures. The joint effects were estimated using the cumulative risk index (CRI). Cohort-specific hazard ratios (HR) were combined using random-effects meta-analyses. We observed over 3.1 million deaths out of approximately 204 million person-years. In administrative cohorts, increased exposure to PM2.5, NO2, and BC was significantly associated with all-cause mortality (pooled HRs: 1.054, 1.033, and 1.032, respectively). We observed an adverse effect of increased impervious surface and mean season-specific temperature, and a protective effect of increased O3, NDVI, distance to water, and temperature variation on all-cause mortality. The effects of PM2.5 were higher in areas with lower (10th percentile) compared to higher (90th percentile) NDVI levels [pooled HRs: 1.054 (95% confidence interval (CI) 1.030-1.079) vs. 1.038 (95% CI 0.964-1.118)]. A similar pattern was observed for NO2. The CRI of air pollutants (PM2.5 or NO2) plus NDVI and mean warm season temperature resulted in a stronger effect compared to single-exposure HRs: [PM2.5 pooled HR: 1.061 (95% CI 1.021-1.102); NO2 pooled HR: 1.041 (95% CI 1.025-1.057)]. Non-significant effects of similar patterns were observed in traditional cohorts. The findings of our study not only support the independent effects of long-term exposure to air pollution and greenness, but also highlight the increased effect when interplaying with other environmental exposures.

Changes in neighborhood physical and social environments matter for change in mental health: Longitudinal evidence from Dutch panel data

Numerous neighborhood environments have been recognized to affect mental health, but only a few longitudinal studies investigated these associations jointly and whether different population groups are affected differently. We used three-wave panel data of 2699 adults between 2010 and 2016 in the Netherlands to assess the associations between changes in neighborhood physical and social environments and mental health changes. Further, we assessed possible effect modification of gender and income. Mental health was measured using the Mental Health Inventory. Time-varying exposure to green space, blue space, population density, air pollution, socioeconomic deprivation, and social fragmentation were assigned based on individuals' neighborhood histories. Fixed-effect regressions were conducted to assess within-person associations between single and multiple exposures on mental health for the entire sample and stratified by gender and income. Our single-exposure models showed that increases in blue space were significantly associated with mental health improvements, while increases in fine particulate matter (PM2.5) resulted in declines in mental health. These associations were not attenuated in the multi-exposure model. We observed no significant associations for the remaining environments. Stratification analyses showed that females’ mental health further declined as PM2.5 concentrations increased compared to males. Increasing levels of socioeconomic deprivation were associated with further declines in mental health among the less well-off compared with higher-income earners. Our longitudinal findings suggested that neighborhood physical and social environment changes were associated with mental health changes. Future research is required to establish the underlying pathways.

Exposure to insulating materials and risk of coronary artery diseases: a cross-sectional study.

Although previous reports link exposure to insulating materials with an increased risk of mesothelioma and chronic respiratory diseases, studies evaluating their associations with the risk of coronary artery diseases (CAD) are lacking. We aimed at evaluating the associations between exposure to insulating materials and the 10-year risk of CAD among insulators. In this cross-sectional study, we recruited 643 adults (≥18 years), full-time insulators from the Local 110 Heat and Frost Insulators and Allied Workers Union in Edmonton, Alberta. We obtained demographic information, personal and family history, and job-exposure history, including experience (years) and types of exposure to insulating materials. Clinical profiling including Framingham risk scores (FRS) was assessed. Of all insulators, 89% were men (mean ± SD age: 47 ± 12 years), 27% had a parental history of cardiac diseases, and 22% had a comorbid chronic respiratory disease. In total, 53% reported exposure to asbestos, while 61, 82, and 94% reported exposure to ceramic fibers, fiberglass, and mineral fibers, respectively. In single-exposure multivariable regression models adjusted for experience, marital status, and body mass index (BMI), asbestos was found to be associated with higher FRS (β: 1.004; 95%CI: 0.003-2.00). The association remained consistent in multi-exposure models and a higher association was found between asbestos exposure and FRS among insulators with comorbid chronic respiratory disease. Our study demonstrates that apart from cancer and chronic respiratory diseases, asbestos exposure may also have a cardiac effect, thus warranting the need for systematic surveillance to protect workers from the adverse effects of these materials.

Joint associations and pathways from greenspace, traffic-related air pollution, and noise to poor self-rated general health: A population-based study in Sofia, Bulgaria

BackgroundLittle is still known of how multiple urban exposures interact as health determinants. This study investigated various ways in which greenspace, traffic-related air pollution, and noise could operate together, influencing general health status. MethodsIn 2022, a cross-sectional population-based survey was conducted in Sofia, Bulgaria. Included were 917 long-term adult residents who completed questionnaires on poor self-rated health (PSRH), total time spent in physical activity (PA), home garden presence, time spent in urban greenspace and nature, and sociodemographics. Residential greenspace was operationalized using the normalized difference vegetation index (NDVI), tree cover density, number of trees, and access to local greenspace and parks. Nitrogen dioxide (NO2) was modeled for the study area. Road traffic, railway, and aircraft day-evening-night sound levels (Lden) were extracted from EU noise maps. Area-level income and urbanicity were considered. Analyses included multivariate ordinal regressions, interactions, and structural equation modeling (SEM). ResultsAssociations with PSRH were per 0.10 NDVI 300 m: OR = 0.65 (0.42–1.01), home garden: OR = 0.72 (0.49–1.07), per 5 μg/m3 NO2: OR = 1.57 (1.00–2.48), per 5 dB(A) Lden road traffic: OR = 1.06 (0.91–1.23), railway: OR = 1.11 (1.03–1.20), and aircraft: OR = 1.22 (1.11–1.34). Spending >30 min/week in nature related to better health. In multi-exposure models, only associations with aircraft and railway Lden persisted. People with lower education and financial difficulties or living in poorer districts experienced some exposures stronger. In SEM, time spent in nature and PA mediated the effect of greenspace. ConclusionsGreenspace was associated with better general health, with time spent in nature and PA emerging as intermediate pathways. NO2, railway, and aircraft noise were associated with poorer general health. These results could inform decision-makers, urban planners, and civil society organizations facing urban development problems. Mitigation and abatement policies and measures should target socioeconomically disadvantaged citizens.

Levels of persistent organic pollutants in breast milk samples representing Finnish and Danish boys with and without hypospadias

Hypospadias is a congenital malformation of penile urethra with unknown etiology in most cases. Persistent organic pollutant (POP) exposure may disrupt endocrine function during a critical window of development of male genitalia. In animal studies, POPs have been associated with male reproductive disorders, including hypospadias, but only few studies have assessed this relationship in humans. The aim of this study is to investigate the association between hypospadias and POP concentration levels in breast milk, as a proxy for prenatal exposure. This is a nested case-control study of Danish and Finnish mother-son pairs. Maternal breast milk samples were collected between 1997 and 2002, and they represent infant boys born with hypospadias [n = 33 (n = 22 Danish and n = 11 Finnish)] and their 1:1 matched controls. Breast milk samples were analyzed for six classes of POPs [including dioxins, polychlorinated biphenyls, flame retardants and perfluorinated alkylated substances (PFAS)]. We estimated odds ratios (ORs) and 95% confidence intervals (CI) for each chemical class using conditional logistic regression. In addition, a composite exposure score system was used to explore the effect of a POP mixture (four chemical classes): The composite score was categorized as low, moderate, or high exposure, and differences between cases and controls were tested with conditional logistic regression. No statistically significant associations were observed between the sums of the chemical classes and hypospadias in either country. The composite score was unable to detect differences in the risk of hypospadias between the tertiles of POP exposure. Levels of PFAS were significantly higher in Danish than in Finnish breast milk samples. This small study does not provide evidence for an association between hypospadias and exposure to POPs but adds information on quantitative exposures. Further development of multi-exposure models is needed for assessing the potential mixture effect associated with multiple chemical exposures.

Urban environment and physical activity and capacity in patients with chronic obstructive pulmonary disease

BackgroundPhysical activity and exercise capacity are key prognostic factors in chronic obstructive pulmonary disease (COPD) but their environmental determinants are unknown. ObjectivesTo test the association between urban environment and objective physical activity, physical activity experience and exercise capacity in COPD. MethodsWe studied 404 patients with mild-to-very severe COPD from a multi-city study in Catalonia, Spain. We measured objective physical activity (step count and sedentary time) by the Dynaport MoveMonitor, physical activity experience (difficulty with physical activity) by the Clinical visit-PROactive (C-PPAC) instrument, and exercise capacity by the 6-min walk distance (6MWD). We estimated individually (geocoded to the residential address) population density, pedestrian street length, slope of terrain, and long-term (i.e., annual) exposure to road traffic noise, nitrogen dioxide (NO2) and particulate matter (PM2.5). We built single- and multi-exposure mixed-effects linear regressions with a random intercept for city, adjusting for confounders. ResultsPatients were 85% male, had mean (SD) age 69 (9) years and walked 7524 (4045) steps/day. In multi-exposure models, higher population density was associated with fewer steps, more sedentary time and worse exercise capacity (−507 [95% CI: 1135, 121] steps, +0.2 [0.0, 0.4] h/day and −13 [-25, 0] m per IQR). Pedestrian street length related with more steps and less sedentary time (156 [9, 304] steps and −0.1 [-0.1, 0.0] h/day per IQR). Steeper slope was associated with better exercise capacity (15 [3, 27] m per IQR). Higher NO2 levels related with more sedentary time and more difficulty in physical activity. PM2.5 and noise were not associated with physical activity or exercise capacity. DiscussionPopulation density, pedestrian street length, slope and NO2 exposure relate to physical activity and capacity of COPD patients living in highly populated areas. These findings support the consideration of neighbourhood environmental factors during COPD management and the attention to patients with chronic diseases when developing urban and transport planning policies.

Urban environment and health behaviours in children from six European countries.

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. 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 6-11years 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. In multi-exposure models, green spaces (Normalized Difference Vegetation Index, NDVI) were positively associated with active transport, and inversely associated with sedentary time (22.71min/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 (-4.80min/day (95%CI -9.11, -0.48); compared with no major road). Results for the behavioural patterns were similar. 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.

Questionnaire-based exposome-wide association studies (ExWAS) reveal expected and novel risk factors associated with cardiovascular outcomes in the Personalized Environment and Genes Study

While multiple factors are associated with cardiovascular disease (CVD), many environmental exposures that may contribute to CVD have not been examined. To understand environmental effects on cardiovascular health, we performed an exposome-wide association study (ExWAS), a hypothesis-free approach, using survey data on endogenous and exogenous exposures at home and work and data from health and medical histories from the North Carolina-based Personalized Environment and Genes Study (PEGS) (n = 5015). We performed ExWAS analyses separately on six cardiovascular outcomes (cardiac arrhythmia, congestive heart failure, coronary artery disease, heart attack, stroke, and a combined atherogenic-related outcome comprising angina, angioplasty, atherosclerosis, coronary artery disease, heart attack, and stroke) using logistic regression and a false discovery rate of 5%. For each CVD outcome, we tested 502 single exposures and built multi-exposure models using the deletion-substitution-addition (DSA) algorithm. To evaluate complex nonlinear relationships, we employed the knockoff boosted tree (KOBT) algorithm. We adjusted all analyses for age, sex, race, BMI, and annual household income. ExWAS analyses revealed novel associations that include blood type A (Rh-) with heart attack (OR[95%CI] = 8.2[2.2:29.7]); paint exposures with stroke (paint related chemicals: 6.1[2.2:16.0], acrylic paint: 8.1[2.6:22.9], primer: 6.7[2.2:18.6]); biohazardous materials exposure with arrhythmia (1.8[1.5:2.3]); and higher paternal education level with reduced risk of multiple CVD outcomes (stroke, heart attack, coronary artery disease, and combined atherogenic outcome). In multi-exposure models, trouble sleeping and smoking remained important risk factors. KOBT identified significant nonlinear effects of sleep disorder, regular intake of grapefruit, and a family history of blood clotting problems for multiple CVD outcomes (combined atherogenic outcome, congestive heart failure, and coronary artery disease). In conclusion, using statistics and machine learning, these findings identify novel potential risk factors for CVD, enable hypothesis generation, provide insights into the complex relationships between risk factors and CVD, and highlight the importance of considering multiple exposures when examining CVD outcomes.

Exposure to multiple trace elements and miscarriage during early pregnancy: A mixtures approach.

Exposure to some conventional trace elements has been found to be associated with miscarriage; however, evidence for combined exposure is inconclusive. Therefore, it is important to explore the joint associations between toxic and essential trace elements and miscarriage. This cross-sectional study measured a wide range of element levels in the whole blood of pregnant women by using inductively coupled plasma mass spectrometry. The associations between individual elements and miscarriage were appraised using logistic regression model. Multi-exposure models, including Bayesian kernel machine regression (BKMR) and weighted quantile sum regression (WQS), were used to explore the mixed exposure to elements. Furthermore, grouped weighted quantile sum (GWQS) considered multiple elements with different magnitudes and directions of associations. In logistic regression, the odds ratios (ORs) with a 95% confidence interval (CI) in the highest quartiles were 5.45 (2.00, 15.91) for barium, 0.28 (0.09, 0.76) for copper, and 0.32 (0.12, 0.83) for rubidium. These exposure-outcome associations were confirmed and supplemented by BKMR, which indicated a positive association for barium and negative associations for copper and rubidium. In WQS, a positive association was found between mixed elements and miscarriage (OR: 1.71; 95% CI: 1.07, 2.78), in which barium (75.7%) was the highest weighted element. The results of GWQS showed that the toxic trace element group dominated by barium was significantly associated with increased ORs (OR: 2.71; 95% CI: 1.74, 4.38). Additionally, a negative association was observed between the essential trace element group and miscarriage (OR: 0.32; 95% CI: 0.18, 0.54), with rubidium contributing the most to the result. As a toxic trace element, barium was positively associated with miscarriage both by individual and multiple evaluations, while essential trace elements, particularly rubidium and copper, exhibited negative associations. Our findings provide significant evidence for exploring the effects of trace elements on miscarriage.

Urban environment and cognitive and motor function in children from four European birth cohorts

BackgroundThe urban environment may influence neurodevelopment from conception onwards, but there is no evaluation of the impact of multiple groups of exposures simultaneously. We investigated the association between early-life urban environment and cognitive and motor function in children. MethodsWe used data from 5403 mother–child pairs from four population-based birth-cohorts (UK, France, Spain, and Greece). We estimated thirteen urban home exposures during pregnancy and childhood, including: built environment, natural spaces, and air pollution. Verbal, non-verbal, gross motor, and fine motor functions were assessed using validated tests at five years old. We ran adjusted multi-exposure models using the Deletion-Substitution-Addition algorithm. ResultsHigher greenness exposure within 300 m during pregnancy was associated with higher verbal abilities (1.5 points (95% confidence interval 0.4, 2.7) per 0.20 unit increase in greenness). Higher connectivity density within 100 m and land use diversity during pregnancy were related to lower verbal abilities. Childhood exposure to PM2.5 mediated 74% of the association between greenness during childhood and verbal abilities. Higher exposure to PM2.5 during pregnancy was related to lower fine motor function (-1.2 points (-2.1, -0.4) per 3.2 μg/m3 increase in PM2.5). No associations were found with non-verbal abilities and gross motor function. DiscussionThis study suggests that built environment, greenness, and air pollution may impact child cognitive and motor function at five years old. This study adds evidence that well-designed urban planning may benefit children’s cognitive and motor development.

Quantifying the short-term effects of air pollution on health in the presence of exposure measurement error: a simulation study of multi-pollutant model results

BackgroundMost epidemiological studies estimate associations without considering exposure measurement error. While some studies have estimated the impact of error in single-exposure models we aimed to quantify the effect of measurement error in multi-exposure models, specifically in time-series analysis of PM2.5, NO2, and mortality using simulations, under various plausible scenarios for exposure errors. Measurement error in multi-exposure models can lead to effect transfer where the effect estimate is overestimated for the pollutant estimated with more error to the one estimated with less error. This complicates interpretation of the independent effects of different pollutants and thus the relative importance of reducing their concentrations in air pollution policy.MethodsMeasurement error was defined as the difference between ambient concentrations and personal exposure from outdoor sources. Simulation inputs for error magnitude and variability were informed by the literature. Error-free exposures with their consequent health outcome and error-prone exposures of various error types (classical/Berkson) were generated. Bias was quantified as the relative difference in effect estimates of the error-free and error-prone exposures.ResultsMortality effect estimates were generally underestimated with greater bias observed when low ratios of the true exposure variance over the error variance were assumed (27.4% underestimation for NO2). Higher ratios resulted in smaller, but still substantial bias (up to 19% for both pollutants). Effect transfer was observed indicating that less precise measurements for one pollutant (NO2) yield more bias, while the co-pollutant (PM2.5) associations were found closer to the true. Interestingly, the sum of single-pollutant model effect estimates was found closer to the summed true associations than those from multi-pollutant models, due to cancelling out of confounding and measurement error bias.ConclusionsOur simulation study indicated an underestimation of true independent health effects of multiple exposures due to measurement error. Using error parameter information in future epidemiological studies should provide more accurate concentration-response functions.

Association of Environmental Exposures and Socioeconomic Status with Presymptomatic Type 1 Diabetes Incidence in Children in Bavaria, Germany

BACKGROUND AND AIM: Increasing incidence of early-onset type 1 diabetes (T1D) has been reported worldwide. Evidence shows that environmental exposures contribute to developing pancreatic islet autoantibodies in individuals with predisposing genes. This study aimed to investigate the effect of environmental exposures and socioeconomic levels on childhood presymptomatic T1D incidence (defined as having at least 2 islet autoantibodies) in Bavaria, Germany. METHODS: Long-term exposure to air pollution (nitrogen dioxide (NO2), Ozone (O3) and particulate matter with a diameter 2.5 μm (PM2.5)) and ambient temperature as well as surrounding greenness and area-level socioeconomic status (SES) were assigned to the residential addresses of 52,636 children (6 years of age) participating in the Fr1da study from 2015 to 2019. Information on demographic characteristics was extracted from self-administered questionnaires. We applied generalized additive models to examine the association of environmental factors and SES with presymptomatic T1D incidence adjusting for sex, age and family history of diabetes. We inspected single as well as multi-exposure models. RESULTS:225 children were diagnosed with presymptomatic T1D. Higher age at the time of diagnosis and having family history of diabetes was related to developing presymptomatic T1D (p0.00). An interquartile range (IQR) increase in O3 was associated with significantly higher odds of developing presymptomatic T1D (IQR: 5.06, Odds ratio (OR): 1.26; 95% confidence interval (CI): 1.08-1.48). One IQR increase in ambient temperature had an inverse association (IQR: 0.92, OR: 0.78, 95% CI: 0.66-0.93). Multi-exposure models indicated similar results, though both effects estimates were slightly shifted to the null. Other exposures were not associated with presymptomatic T1D. CONCLUSIONS:Exposure to higher levels of O3 and low ambient temperature may predispose to T1D development in children. KEYWORDS: Air pollution, Long-term exposure, Ozone, Temperature, Green space, Socio-economic factors

Land use and semen quality: A fertility center cohort study.

This study explored the association between built environment and semen parameters among men who sought fertility evaluation. We used a data of 5,886 men living in the Seoul capital area whose semen was tested at a single fertility center during 2016-2018. Distance to fresh water, the coast, major roadways, and neighborhood greenness measured by Normalized Difference Vegetation Index (NDVI) were evaluated. Outcome indicators were semen volume, sperm concentration, percentage of progressive motility, vitality, normal morphology, and total motile sperm count. Linear regression models were fitted to standardized values of six semen indicators. Majority of men were white-collar, clerical, and service workers. Linear associations between built environment features and semen quality indicators were not evident except for NDVI within 500 m and sperm vitality (β = 0.05; 95% confidence interval (CI): 0.01, 0.09). The 2nd quartile of distance to fresh water was associated with lower progressive motility compared to the 1st quartile (β = -0.10; 95% CI: -0.17, -0.03). Proportion of vitality was higher among men in the 2nd quartile of distance to roadways than those in the 1st quartile (0.08; 95% CI: 0.01, 0.15). Men in the 2nd quartile of NDVI had higher total motile sperm count (0.09; 95% CI: 0.01, 0.17). In the multi-exposure model, the positive association between NDVI and vitality remained (0.03; 95% CI: 0.00, 0.06). We observed potential evidence regarding the impact of built environment on male fertility, specifically a positive association between residential greenness and sperm vitality among men with a history of infertility.