Association between ambient air pollution a week prior to delivery and preterm birth using a nationwide study in Sweden.

BACKGROUND: Air pollution exposure has been linked with increased risk of preterm birth, which is one of the leading causes of infant mortality. Limited studies have attempted to explore these associations in low-polluted areas. In this study, we aimed to assess the association between short-term exposure to ambient air pollution and preterm birth in Sweden. METHOD: In this population-based study we included preterm births between 2014 and 2019 from the Swedish Pregnancy Register. We applied a spatiotemporal model to estimate daily levels of particulate matter <2.5 µm (PM2.5), PM < 10 µm (PM10), nitrogen dioxide (NO2), and ozone (O3) at the residential address of each participant. We applied a time-stratified case-crossover design with conditional logistic regression analysis to estimate odds ratios (OR) of preterm birth per 10 µg/m3 (PM10, NO2, O3) and 5 µg/m3 (PM2.5) increase in air pollution exposure at 0-6-day lag. Two-pollutant models were applied to evaluate the independent association of each exposure on preterm birth. We also stratified by maternal characteristics to identify potential effect modifiers. RESULTS: 28,216 (4.5%) preterm births were included. An increase in O3 exposure was associated with increased odds of preterm birth [OR = 1.06 per 10 µg/m3 (95% CI, 1.02; 1.10]. PM2.5 and PM10 were not significantly associated with preterm birth, and NO2 displayed a negative nonlinear association with preterm birth. We did not observe any notable effect modification, but we found suggestive larger associations between O3 and preterm birth when stratifying by male sex, spontaneous delivery, and spring season. CONCLUSIONS: Increased O3 exposure one week before delivery was associated with an increased risk of preterm birth in Sweden, a country with levels of air pollution below the current World Health Organization air quality guidelines. Increases in O3 levels with climate change make these findings especially concerning.

Long-term ambient air pollution exposure and renal function and biomarkers of renal disease.

BACKGROUND: Despite accumulating evidence of an association between air pollution and renal disease, studies on the association between long-term exposure to air pollution and renal function are still contradictory. This study aimed to investigate this association in a large population with relatively low exposure and with improved estimation of renal function as well as renal injury biomarkers. METHODS: We performed a cross-sectional analysis in the middle-aged general population participating in the Swedish CardioPulmonary bioImaging Study (SCAPIS; n = 30 154). Individual 10-year exposure to total and locally emitted fine particulate matter (PM2.5), inhalable particulate matter (PM10), and nitrogen oxides (NOx) were modelled using high-resolution dispersion models. Linear regression models were used to estimate associations between exposures and estimated glomerular filtration rate (eGFR, combined creatinine and cystatin C) and serum levels of renal injury biomarkers (KIM-1, MCP-1, IL-6, IL-18, MMP-2, MMP-7, MMP-9, FGF-23, and uric acid), with consideration of potential confounders. RESULTS: Median long-term PM2.5 exposure was 6.2 µg/m3. Almost all participants had a normal renal function and median eGFR was 99.2 mL/min/1.73 m2. PM2.5 exposure was associated with 1.3% (95% CI 0.6, 2.0) higher eGFR per 2.03 µg/m3 (interquartile range, IQR). PM2.5 exposure was also associated with elevated serum matrix metalloproteinase 2 (MMP-2) concentration, with 7.2% (95% CI 1.9, 12.8) higher MMP-2 per 2.03 µg/m3. There was a tendency towards an association between PM10 and higher levels of uric acid, but no associations were found with the other biomarkers. Associations with other air pollutants were null or inconsistent. CONCLUSION: In this large general population sample at low exposure levels, we found a surprising association between PM2.5 exposure and a higher renal filtration. It seems unlikely that particle function would improve renal function. However, increased filtration is an early sign of renal injury and may be related to the relatively healthy population at comparatively low exposure levels. Furthermore, PM2.5 exposure was associated with higher serum concentrations of MMP-2, an early indicator of renal and cardiovascular pathology.

Improved Air Quality and Asthma Incidence from School-Age to Young Adulthood: A Population-based Prospective Cohort Study.

Background The benefits of improved air quality on asthma remain understudied. Therefore, our aim was to investigate associations of changes in ambient air pollution with incident asthma from school-age until young adulthood in an area with mostly low air pollution levels. Methods Participants in the BAMSE birth cohort from Stockholm without asthma before the 8-year follow-up were included (N=2371). We estimated the association of change in individual-level air pollutant exposure (particulate matter with diameter ⩽2.5 µm (PM2.5) and, ⩽10 µm (PM10), black carbon (BC) and nitrogen oxides (NOx)) from the first year of life to the 8-year follow-up with asthma incidence from the 8-year until the 24-year follow-up. Multi-pollutant trajectories were identified using Group-Based Multivariate Trajectory model. We also used parametric g-computation to quantify the asthma incidence under different hypothetical interventions regarding air pollution levels. Results Air pollution levels at residency decreased during the period, with median reductions of 5.6% for PM2.5, 3.1% for PM10, 5.9% for BC, and 26.8% for NOx. A total of 395 incident asthma cases were identified from the 8-year until the 24-year follow-up. The odds ratio for asthma was 0.89 (95%CI: 0.80, 0.99) for each interquartile range reduction in PM2.5 (equal to 8.1% reduction). Associations appeared less clear for PM10, BC and NOx. Five multi-pollutant trajectories were identified, where the largest reduction trajectory displayed the lowest odds of asthma (OR=0.55, 95%CI: 0.31, 0.98) compared with the least reduction trajectory. If the PM2.5 exposure had not declined up to the 8-year follow-up, the hypothetical asthma incidence was estimated to have been 10.9% higher (95%CI: 0.8%, 20.8%). Conclusions Decrease in PM2.5 levels during childhood was associated with lower risk of incident asthma from school-age to young adulthood in an area with relatively low air pollution levels, suggesting broad respiratory health benefits from improved air quality. This article is open access and distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).

Long-term exposure to transportation noise and obesity: A pooled analysis of eleven Nordic cohorts.

Background: Available evidence suggests a link between exposure to transportation noise and an increased risk of obesity. We aimed to assess exposure-response functions for long-term residential exposure to road traffic, railway and aircraft noise, and markers of obesity. Methods: Our cross-sectional study is based on pooled data from 11 Nordic cohorts, including up to 162,639 individuals with either measured (69.2%) or self-reported obesity data. Residential exposure to transportation noise was estimated as a time-weighted average Lden 5 years before recruitment. Adjusted linear and logistic regression models were fitted to assess beta coefficients and odds ratios (OR) with 95% confidence intervals (CI) for body mass index, overweight, and obesity, as well as for waist circumference and central obesity. Furthermore, natural splines were fitted to assess the shape of the exposure-response functions. Results: For road traffic noise, the OR for obesity was 1.06 (95% CI = 1.03, 1.08) and for central obesity 1.03 (95% CI = 1.01, 1.05) per 10 dB Lden. Thresholds were observed at around 50-55 and 55-60 dB Lden, respectively, above which there was an approximate 10% risk increase per 10 dB Lden increment for both outcomes. However, linear associations only occurred in participants with measured obesity markers and were strongly influenced by the largest cohort. Similar risk estimates as for road traffic noise were found for railway noise, with no clear thresholds. For aircraft noise, results were uncertain due to the low number of exposed participants. Conclusion: Our results support an association between road traffic and railway noise and obesity.

Ambient air pollution and daily mortality in ten cities of India: a causal modelling study.

BACKGROUND: The evidence for acute effects of air pollution on mortality in India is scarce, despite the extreme concentrations of air pollution observed. This is the first multi-city study in India that examines the association between short-term exposure to PM2·5 and daily mortality using causal methods that highlight the importance of locally generated air pollution. METHODS: We applied a time-series analysis to ten cities in India between 2008 and 2019. We assessed city-wide daily PM2·5 concentrations using a novel hybrid nationwide spatiotemporal model and estimated city-specific effects of PM2·5 using a generalised additive Poisson regression model. City-specific results were then meta-analysed. We applied an instrumental variable causal approach (including planetary boundary layer height, wind speed, and atmospheric pressure) to evaluate the causal effect of locally generated air pollution on mortality. We obtained an integrated exposure-response curve through a multivariate meta-regression of the city-specific exposure-response curve and calculated the fraction of deaths attributable to air pollution concentrations exceeding the current WHO 24 h ambient PM2·5 guideline of 15 µg/m3. To explore the shape of the exposure-response curve at lower exposures, we further limited the analyses to days with concentrations lower than the current Indian standard (60 µg/m3). FINDINGS: We observed that a 10 µg/m3 increase in 2-day moving average of PM2·5 was associated with 1·4% (95% CI 0·7-2·2) higher daily mortality. In our causal instrumental variable analyses representing the effect of locally generated air pollution, we observed a stronger association with daily mortality (3·6% [2·1-5·0]) than our overall estimate. Our integrated exposure-response curve suggested steeper slopes at lower levels of exposure and an attenuation of the slope at high exposure levels. We observed two times higher risk of death per 10 µg/m3 increase when restricting our analyses to observations below the Indian air quality standard (2·7% [1·7-3·6]). Using the integrated exposure-response curve, we observed that 7·2% (4·2%-10·1%) of all daily deaths were attributed to PM2·5 concentrations higher than the WHO guidelines. INTERPRETATION: Short-term PM2·5 exposure was associated with a high risk of death in India, even at concentrations well below the current Indian PM2·5 standard. These associations were stronger for locally generated air pollutants quantified through causal modelling methods than conventional time-series analysis, further supporting a plausible causal link. FUNDING: Swedish Research Council for Sustainable Development.

External exposome and all-cause mortality in European cohorts: the EXPANSE project.

Background: Many studies reported associations between long-term exposure to environmental factors and mortality; however, little is known on the combined effects of these factors and health. We aimed to evaluate the association between external exposome and all-cause mortality in large administrative and traditional adult cohorts in Europe. Methods: Data from six administrative cohorts (Catalonia, Greece, Rome, Sweden, Switzerland and the Netherlands, totaling 27,913,545 subjects) and three traditional adult cohorts (CEANS-Sweden, EPIC-NL-the Netherlands, KORA-Germany, totaling 57,653 participants) were included. Multiple exposures were assigned at the residential addresses, and were divided into three a priori defined domains: (1) air pollution [fine particulate matter (PM2.5), nitrogen dioxide (NO2), black carbon (BC) and warm-season Ozone (warm-O3)]; (2) land/built environment (Normalized Difference Vegetation Index-NDVI, impervious surfaces, and distance to water); (3) air temperature (cold- and warm-season mean and standard deviation). Each domain was synthesized through Principal Component Analysis (PCA), with the aim of explaining at least 80% of its variability. Cox proportional-hazards regression models were applied and the total risk of the external exposome was estimated through the Cumulative Risk Index (CRI). The estimates were adjusted for individual- and area-level covariates. Results: More than 205 million person-years at risk and more than 3.2 million deaths were analyzed. In single-component models, IQR increases of the first principal component of the air pollution domain were associated with higher mortality [HRs ranging from 1.011 (95% CI: 1.005-1.018) for the Rome cohort to 1.076 (1.071-1.081) for the Swedish cohort]. In contrast, lower levels of the first principal component of the land/built environment domain, pointing to reduced vegetation and higher percentage of impervious surfaces, were associated with higher risks. Finally, the CRI of external exposome increased mortality for almost all cohorts. The associations found in the traditional adult cohorts were generally consistent with the results from the administrative ones, albeit without reaching statistical significance. Discussion: Various components of the external exposome, analyzed individually or in combination, were associated with increased mortality across European cohorts. This sets the stage for future research on the connections between various exposure patterns and human health, aiding in the planning of healthier cities.

Long-term ambient air pollution and coronary atherosclerosis: Results from the Swedish SCAPIS study.

BACKGROUND AND AIMS: Despite firm evidence for an association between long-term ambient air pollution exposure and cardiovascular morbidity and mortality, results from epidemiological studies on the association between air pollution exposure and atherosclerosis have not been consistent. We investigated associations between long-term low-level air pollution exposure and coronary atherosclerosis. METHODS: We performed a cross-sectional analysis in the large Swedish CArdioPulmonary bioImaging Study (SCAPIS, n = 30 154), a random general population sample. Concentrations of total and locally emitted particulate matter <2.5 µm (PM2.5), <10 µm (PM10), and nitrogen oxides (NOx) at the residential address were modelled using high-resolution dispersion models. We estimated associations between air pollution exposures and segment involvement score (SIS), coronary artery calcification score (CACS), number of non-calcified plaques (NCP), and number of significant stenoses, using ordinal regression models extensively adjusted for potential confounders. RESULTS: Median 10-year average PM2.5 exposure was 6.2 µg/m3 (range 3.5-13.4 µg/m3). 51 % of participants were women and 51 % were never-smokers. None of the assessed pollutants were associated with a higher SIS or CACS. Exposure to PM2.5 was associated with NCP (adjusted OR 1.34, 95 % CI 1.13, 1.58, per 2.05 µg/m3). Associations with significant stenoses were inconsistent. CONCLUSIONS: In this large, middle-aged general population sample with low exposure levels, air pollution was not associated with measures of total burden of coronary atherosclerosis. However, PM2.5 appeared to be associated with a higher prevalence of non-calcified plaques. The results suggest that increased risk of early-stage atherosclerosis or rupture, but not increased total atherosclerotic burden, may be a pathway for long-term air pollution effects on cardiovascular disease.

Long-term exposure to air pollution and chronic kidney disease-associated mortality-Results from the pooled cohort of the European multicentre ELAPSE-study.

Despite the known link between air pollution and cause-specific mortality, its relation to chronic kidney disease (CKD)-associated mortality is understudied. Therefore, we investigated the association between long-term exposure to air pollution and CKD-related mortality in a large multicentre population-based European cohort. Cohort data were linked to local mortality registry data. CKD-death was defined as ICD10 codes N18-N19 or corresponding ICD9 codes. Mean annual exposure at participant's home address was determined with fine spatial resolution exposure models for nitrogen dioxide (NO2), black carbon (BC), ozone (O3), particulate matter ≤2.5 µm (PM2.5) and several elemental constituents of PM2.5. Cox regression models were adjusted for age, sex, cohort, calendar year of recruitment, smoking status, marital status, employment status and neighbourhood mean income. Over a mean follow-up time of 20.4 years, 313 of 289,564 persons died from CKD. Associations were positive for PM2.5 (hazard ratio (HR) with 95% confidence interval (CI) of 1.31 (1.03-1.66) per 5 µg/m3, BC (1.26 (1.03-1.53) per 0.5 × 10- 5/m), NO2 (1.13 (0.93-1.38) per 10 µg/m3) and inverse for O3 (0.71 (0.54-0.93) per 10 µg/m3). Results were robust to further covariate adjustment. Exclusion of the largest sub-cohort contributing 226 cases, led to null associations. Among the elemental constituents, Cu, Fe, K, Ni, S and Zn, representing different sources including traffic, biomass and oil burning and secondary pollutants, were associated with CKD-related mortality. In conclusion, our results suggest an association between air pollution from different sources and CKD-related mortality.

Nationwide estimation of daily ambient PM2.5 from 2008 to 2020 at 1 km2 in India using an ensemble approach.

High-resolution assessment of historical levels is essential for assessing the health effects of ambient air pollution in the large Indian population. The diversity of geography, weather patterns, and progressive urbanization, combined with a sparse ground monitoring network makes it challenging to accurately capture the spatiotemporal patterns of ambient fine particulate matter (PM2.5) pollution in India. We developed a model for daily average ambient PM2.5 between 2008 and 2020 based on monitoring data, meteorology, land use, satellite observations, and emissions inventories. Daily average predictions at each 1 km × 1 km grid from each learner were ensembled using a Gaussian process regression with anisotropic smoothing over spatial coordinates, and regression calibration was used to account for exposure error. Cross-validating by leaving monitors out, the ensemble model had an R2 of 0.86 at the daily level in the validation data and outperformed each component learner (by 5-18%). Annual average levels in different zones ranged between 39.7 µg/m3 (interquartile range: 29.8-46.8) in 2008 and 30.4 µg/m3 (interquartile range: 22.7-37.2) in 2020, with a cross-validated (CV)-R2 of 0.94 at the annual level. Overall mean absolute daily errors (MAE) across the 13 years were between 14.4 and 25.4 µg/m3. We obtained high spatial accuracy with spatial R2 greater than 90% and spatial MAE ranging between 7.3-16.5 µg/m3 with relatively better performance in urban areas at low and moderate elevation. We have developed an important validated resource for studying PM2.5 at a very fine spatiotemporal resolution, which allows us to study the health effects of PM2.5 across India and to identify areas with exceedingly high levels.

Impact of heatwaves on all-cause mortality in India: A comprehensive multi-city study.

BACKGROUND: Heatwaves are expected to increase with climate change, posing a significant threat to population health. In India, with the world's largest population, heatwaves occur annually but have not been comprehensively studied. Accordingly, we evaluated the association between heatwaves and all-cause mortality and quantifying the attributable mortality fraction in India. METHODS: We obtained all-cause mortality counts for ten cities in India (2008-2019) and estimated daily mean temperatures from satellite data. Our main extreme heatwave was defined as two-consecutive days with an intensity above the 97th annual percentile. We estimated city-specific heatwave associations through generalised additive Poisson regression models, and meta-analysed the associations. We reported effects as the percentage change in daily mortality, with 95% confidence intervals (CI), comparing heatwave vs non-heatwave days. We further evaluated heatwaves using different percentiles (95th, 97th, 99th) for one, two, three and five-consecutive days. We also evaluated the influence of heatwave duration, intensity and timing in the summer season on heatwave mortality, and estimated the number of heatwave-related deaths. FINDINGS: Among âˆ¼ 3.6 million deaths, we observed that temperatures above 97th percentile for 2-consecutive days was associated with a 14.7 % (95 %CI, 10.3; 19.3) increase in daily mortality. Alternative heatwave definitions with higher percentiles and longer duration resulted in stronger relative risks. Furthermore, we observed stronger associations between heatwaves and mortality with higher heatwave intensity. We estimated that around 1116 deaths annually (95 %CI, 861; 1361) were attributed to heatwaves. Shorter and less intense definitions of heatwaves resulted in a higher estimated burden of heatwave-related deaths. CONCLUSIONS: We found strong evidence of heatwave impacts on daily mortality. Longer and more intense heatwaves were linked to an increased mortality risk, however, resulted in a lower burden of heatwave-related deaths. Both definitions and the burden associated with each heatwave definition should be incorporated into planning and decision-making processes for policymakers.

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

Background: 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. Methods: 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. Results: 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. Discussion: 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.