Dataset Information

Long-Term Exposure to Fine Particle Elemental Components and Natural and Cause-Specific Mortality-a Pooled Analysis of Eight European Cohorts within the ELAPSE Project.

ABSTRACT:

Background

Inconsistent associations between long-term exposure to particles with an aerodynamic diameter ≤2.5 μm [fine particulate matter (PM2.5)] components and mortality have been reported, partly related to challenges in exposure assessment.

Objectives

We investigated the associations between long-term exposure to PM2.5 elemental components and mortality in a large pooled European cohort; to compare health effects of PM2.5 components estimated with two exposure modeling approaches, namely, supervised linear regression (SLR) and random forest (RF) algorithms.

Methods

We pooled data from eight European cohorts with 323,782 participants, average age 49 y at baseline (1985-2005). Residential exposure to 2010 annual average concentration of eight PM2.5 components [copper (Cu), iron (Fe), potassium (K), nickel (Ni), sulfur (S), silicon (Si), vanadium (V), and zinc (Zn)] was estimated with Europe-wide SLR and RF models at a 100×100 m scale. We applied Cox proportional hazards models to investigate the associations between components and natural and cause-specific mortality. In addition, two-pollutant analyses were conducted by adjusting each component for PM2.5 mass and nitrogen dioxide (NO2) separately.

Results

We observed 46,640 natural-cause deaths with 6,317,235 person-years and an average follow-up of 19.5 y. All SLR-modeled components were statistically significantly associated with natural-cause mortality in single-pollutant models with hazard ratios (HRs) from 1.05 to 1.27. Similar HRs were observed for RF-modeled Cu, Fe, K, S, V, and Zn with wider confidence intervals (CIs). HRs for SLR-modeled Ni, S, Si, V, and Zn remained above unity and (almost) significant after adjustment for both PM2.5 and NO2. HRs only remained (almost) significant for RF-modeled K and V in two-pollutant models. The HRs for V were 1.03 (95% CI: 1.02, 1.05) and 1.06 (95% CI: 1.02, 1.10) for SLR- and RF-modeled exposures, respectively, per 2 ng/m3, adjusting for PM2.5 mass. Associations with cause-specific mortality were less consistent in two-pollutant models.

Conclusion

Long-term exposure to V in PM2.5 was most consistently associated with increased mortality. Associations for the other components were weaker for exposure modeled with RF than SLR in two-pollutant models. https://doi.org/10.1289/EHP8368.

SUBMITTER: Chen J

PROVIDER: S-EPMC8041432 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:ObjectiveTo investigate the associations between air pollution and mortality, focusing on associations below current European Union, United States, and World Health Organization standards and guidelines.DesignPooled analysis of eight cohorts.SettingMulticentre project Effects of Low-Level Air Pollution: A Study in Europe (ELAPSE) in six European countries.Participants325 367 adults from the general population recruited mostly in the 1990s or 2000s with detailed lifestyle data. Stratified Cox proportional hazard models were used to analyse the associations between air pollution and mortality. Western Europe-wide land use regression models were used to characterise residential air pollution concentrations of ambient fine particulate matter (PM2.5), nitrogen dioxide, ozone, and black carbon.Main outcome measuresDeaths due to natural causes and cause specific mortality.ResultsOf 325 367 adults followed-up for an average of 19.5 years, 47 131 deaths were observed. Higher exposure to PM2.5, nitrogen dioxide, and black carbon was associated with significantly increased risk of almost all outcomes. An increase of 5 µg/m3 in PM2.5 was associated with 13% (95% confidence interval 10.6% to 15.5%) increase in natural deaths; the corresponding figure for a 10 µg/m3 increase in nitrogen dioxide was 8.6% (7% to 10.2%). Associations with PM2.5, nitrogen dioxide, and black carbon remained significant at low concentrations. For participants with exposures below the US standard of 12 µg/m3 an increase of 5 µg/m3 in PM2.5 was associated with 29.6% (14% to 47.4%) increase in natural deaths.ConclusionsOur study contributes to the evidence that outdoor air pollution is associated with mortality even at low pollution levels below the current European and North American standards and WHO guideline values. These findings are therefore an important contribution to the debate about revision of air quality limits, guidelines, and standards, and future assessments by the Global Burden of Disease.

Project description:BackgroundThe health effects of suspended particulate matter (PM) may depend on its chemical composition. Associations between maternal exposure to chemical constituents of PM and newborn's size have been little examined.ObjectiveWe aimed to investigate the associations of exposure to elemental constituents of PM with term low birth weight (LBW; weight < 2,500 g among births after 37 weeks of gestation), mean birth weight, and head circumference, relying on standardized fine-scale exposure assessment and with extensive control for potential confounders.MethodsWe pooled data from eight European cohorts comprising 34,923 singleton births in 1994-2008. Annual average concentrations of elemental constituents of PM ? 2.5 and ? 10 ?m (PM2.5 and PM10) at maternal home addresses during pregnancy were estimated using land-use regression models. Adjusted associations between each birth measurement and concentrations of eight elements (copper, iron, potassium, nickel, sulfur, silicon, vanadium, and zinc) were calculated using random-effects regression on pooled data.ResultsA 200-ng/m3 increase in sulfur in PM2.5 was associated with an increased risk of LBW (adjusted odds ratio = 1.36; 95% confidence interval: 1.17, 1.58). Increased nickel and zinc in PM2.5 concentrations were also associated with an increased risk of LBW. Head circumference was reduced at higher exposure to all elements except potassium. All associations with sulfur were most robust to adjustment for PM2.5 mass concentration. All results were similar for PM10.ConclusionSulfur, reflecting secondary combustion particles in this study, may adversely affect LBW and head circumference, independently of particle mass.CitationPedersen M, Gehring U, Beelen R, Wang M, Giorgis-Allemand L, Andersen AM, Basagaña X, Bernard C, Cirach M, Forastiere F, de Hoogh K, Gražulevi?ien? R, Gruzieva O, Hoek G, Jedynska A, Klümper C, Kooter IM, Krämer U, Kukkonen J, Porta D, Postma DS, Raaschou-Nielsen O, van Rossem L, Sunyer J, Sørensen M, Tsai MY, Vrijkotte TG, Wilhelm M, Nieuwenhuijsen MJ, Pershagen G, Brunekreef B, Kogevinas M, Slama R. 2016. Elemental constituents of particulate matter and newborn's size in eight European cohorts. Environ Health Perspect 124:141-150; http://dx.doi.org/10.1289/ehp.1409546.

Project description:BackgroundThere is a lack of evidence for the associations between atmospheric particle components exposure and psychiatric health. We aimed to identify the most toxic particle component(s) and source(s) related with psychiatric illness.MethodsUsing Health Cost and Utilization Project (HCUP) State Inpatient Databases (SIDs), we analyzed the relative risk (RR) of psychiatric hospitalization associated with increased residential exposure to 14 particle components (Zn, V, Si, Pb, Ni, K, Fe, Cu, Ca, Br, sulfate (SO42-), nitrate (NO3-), organic carbon (OC), and elemental carbon (EC)). We covered the residents of eight U.S. states, who contributed to 5,012,041 psychiatric admissions over 2002-2018. Single component models were conducted via fitting zero-inflated negative binomial regression for each component with aggregated counts of total psychiatric hospitalizations per ZIP code per year as dependent variable. We used Nonnegative Matrix Factorization (NMF) to identify particle source factors and obtained the source-specific estimates. Generalized Weighted Quantile Sum (gWQS) Regression was applied to obtain an overall mixture effect. Separate but similar models were fitted for different age groups (<30 yrs. vs. ≥ 30 yrs) and psychiatric illness sub-categories to assess effect heterogeneity.ResultsSulfate, Fe, Pb and Zn were associated with the largest risk increases in single-component models. The biggest harmful associations were observed for metal industry source (high loadings of Pb and sulfate). For one quartile increase in components mixture score, we observed an adjusted RR of 1.24 (95 % CI, 1.21-1.26). Older population were more affected. We also observed higher increase in bipolar and psychotic admission risk for increased components source and mixture level.ConclusionLiving in areas with higher levels of particle components was associated with increased risk of psychiatric hospitalization among the residents in eight U.S. states. Certain components (i.e. Pb, sulfate) and sources (metal industry) were the most related.

Project description:Environmental exposures during pregnancy and early life may have adverse health effects. Single birth cohort studies often lack statistical power to tease out such effects reliably. To improve the use of existing data and to facilitate collaboration among these studies, an inventory of the environmental exposure and health data in these studies was made as part of the ENRIECO (Environmental Health Risks in European Birth Cohorts) project. The focus with regard to exposure was on outdoor air pollution, water contamination, allergens and biological organisms, metals, pesticides, smoking and second hand tobacco smoke (SHS), persistent organic pollutants (POPs), noise, radiation, and occupational exposures. The review lists methods and data on environmental exposures in 37 European birth cohort studies. Most data is currently available for smoking and SHS (N=37 cohorts), occupational exposures (N=33), outdoor air pollution, and allergens and microbial agents (N=27). Exposure modeling is increasingly used for long-term air pollution exposure assessment; biomonitoring is used for assessment of exposure to metals, POPs and other chemicals; and environmental monitoring for house dust mite exposure assessment. Collaborative analyses with data from several birth cohorts have already been performed successfully for outdoor air pollution, water contamination, allergens, biological contaminants, molds, POPs and SHS. Key success factors for collaborative analyses are common definitions of main exposure and health variables. Our review emphasizes that such common definitions need ideally be arrived at in the study design phase. However, careful comparison of methods used in existing studies also offers excellent opportunities for collaborative analyses. Investigators can use this review to evaluate the potential for future collaborative analyses with respect to data availability and methods used in the different cohorts and to identify potential partners for a specific research question.