Long-term Air Pollution Exposure Research Articles

Low-level ambient sulfur dioxide exposure and genetic susceptibility associated with incidence of idiopathic pulmonary fibrosis: A national prospective cohort study

BackgroundThe association between long-term air pollution exposure and the development of idiopathic pulmonary fibrosis (IPF) has been established, but the evidence regarding the effect of low levels of air pollution, especially ambient sulfur dioxide (SO2), is limited. Besides, the combined effect and interaction between genetic susceptibility and ambient SO2 on IPF remain uncertain. MethodsThis study retrieved data from 402,042 participants who were free of IPF at baseline in the UK Biobank. The annual mean concentration of ambient SO2 was estimated for each participant based on their residential addresses using a bilinear interpolation method. Cox proportional hazard models were used to examine the relationship between ambient SO2 and incident IPF. We further generated a polygenic risk score (PRS) for IPF and estimated the combined effects of genetic susceptibility and ambient SO2 on incident IPF. ResultsAfter a median follow-up of 11.78 years, 2562 cases of IPF were identified. The results indicated that each 1 μg/m3 increase in ambient SO2 was associated with a hazard ratio (HR) (95% confidence interval [CI]) of 1.67 (1.58, 1.76) for incident IPF. The study found statistically significant synergistic additive interaction between genetic susceptibility and ambient SO2. Individuals with high genetic risk and high ambient SO2 exposure had a higher risk of developing IPF (HR = 7.48, 95% CI:5.66, 9.90). ConclusionThe study suggests that long-term exposure to ambient SO2, even at concentrations lower than current air quality guidelines set by the Word Health Organization and European Union, may be an important risk factor for IPF. This risk is more pronounced among people with a high genetic risk. Therefore, these findings emphasize the need to consider the potential health effects of SO2 exposure and the necessity for stricter air quality standards.

Effect of Air Pollution on Heart Failure: Systematic Review and Meta-Analysis.

Heart failure (HF) poses a significant global disease burden. The current evidence on the impact of air pollution on HF remains inconsistent. We aimed to conduct a systematic review of the literature and meta-analysis to provide a more comprehensive and multiperspective assessment of the associations between short- and long-term air pollution exposure and HF from epidemiological evidences. Three databases were searched up to 31 August 2022 for studies investigating the association between air pollutants (, , , , CO, ) and HF hospitalization, incidence, or mortality. A random effects model was used to derive the risk estimations. Subgroup analysis was conducted by geographical location, age of participants, outcome, study design, covered area, the methods of exposure assessment, and the length of exposure window. Sensitivity analysis and adjustment for publication bias were performed to test the robustness of the results. Of 100 studies covering 20 countries worldwide, 81 were for short-term and 19 were for long-term exposure. Almost all air pollutants were adversely associated with the risk of HF in both short- and long-term exposure studies. For short-term exposures, we found the risk of HF increased by 1.8% [relative risk , 95% confidence interval (CI): 1.011, 1.025] and 1.6% (, 95% CI: 1.011, 1.020) per increment of and , respectively. HF was also significantly associated with , , and CO, but not . Positive associations were stronger when exposure was considered over the previous 2 d (lag 0-1) rather than on the day of exposure only (lag 0). For long-term exposures, there were significant associations between several air pollutants and HF with RR (95% CI) of 1.748 (1.112, 2.747) per increment in , 1.212 (1.010, 1.454) per increment in , and 1.204 (1.069, 1.356) per increment in , respectively. The adverse associations of most pollutants with HF were greater in low- and middle-income countries than in high-income countries. Sensitivity analysis demonstrated the robustness of our results. Available evidence highlighted adverse associations between air pollution and HF regardless of short- and long-term exposure. Air pollution is still a prevalent public health issue globally and sustained policies and actions are called for to reduce the burden of HF. https://doi.org/10.1289/EHP11506.

Long-term exposure to air pollution and cognitive function in older adults: a systematic review and meta-analysis

BackgroundNow more than ever before, air pollution and cognitive decline are global concerns. Credible links are now emerging between exposure to specific pollutants and cognitive decline. However, the role of specific pollutants on different cognitive domains in adults are inconclusive as the pathways to cognitive decline remain poorly understood.ObjectiveTo systematically review and meta-analyse the evidence for the association between long-term air pollution exposure and cognitive function in adults.Data sourcesWeb of Science, PubMed, Embase searched up to February 2021 with no language restrictions. Individual studies were identified from similar review articles.Eligibility criteriaStudies investigating the long-term (>3 years) associations between airborne pollutants and cognitive function in older adults (>50 years old).ResultsFrom 1996 records, 26 satisfied the inclusion criteria. The total sample size included over 2.4 million (53.8% female) subjects with ages ranging from 45 to 100 years (estimated mean age 70 years). Only 18/26 publications included both male and female subjects. Pollutants reported included particulate matter ≤2.5 µm (PM2.5); particulate matter ≤10 µm (PM10); nitrogen dioxide (NO2); nitrogen oxide species (NOx) and ozone (O3). Papers showed great variance in their study characteristics, air pollution modelling methodology and assessment of cognitive domain. Long-term exposure to increased levels of PM2.5 and NO2 were most strongly associated with increased risk of dementia. Decline in cognitive function, executive function, memory and language were most strongly associated with greater exposure to PM2.5, PM10 and NO2 to varying degrees.ConclusionAn increasing number of studies are supporting the hypothesis that greater exposure to air pollutants is associated with decline in cognitive functions.

Associations of air pollutant concentrations with longitudinal kidney function changes in patients with chronic kidney disease

This longitudinal cohort study investigated the associations of air pollutant exposures, including CO, NO, NO2, NOx, O3, PM10, PM2.5, and SO2, with long-term kidney function changes in patients with chronic kidney disease (CKD). We enrolled 447 CKD patients who took part in a universal hospital pre-ESRD care program during 2011–2015. The daily average air pollutant exposures and temperature were estimated for each patient, with different levels of air pollutant concentrations defined by 5-knot and restricted cubic spline function. Predicted annual estimated glomerular filtration (eGFR) slope values by one mixed model were considered as the study outcome. The average age of the study population was 77.1 ± 12.6 years, and the median annual eGFR decreased by 2.1 ml/min/1.73 m2 per year from 30 ml/min/1.73 m2 at baseline during a mean follow-up time of 3.4 years. The univariable and multivariable analyses revealed no significant linear and non-linear associations between 5-knot air pollutant concentrations and annual eGFR slope. In addition, the visualized spline effect plots show insignificant variation patterns in annual eGFR slope values with increased air pollutant concentrations. These results encourage more extensive studies to clarify the causal relationships and mechanisms of long-term specific air pollutant exposures and longitudinal kidney function change, especially in CKD populations.

Association between long-term exposure to ambient air pollutants and the risk of tuberculosis: A time-series study in Nantong, China

BackgroundIncreasing evidence has shown that the risk of tuberculosis (TB) might be related to the exposure to air pollutants; however, the findings are inconsistent and studies on long-term air pollutant exposure and TB risk are scarce. This study aime to assess the relationship between monthly exposure to air pollution and TB risk in Nantong, China. MethodsWe collected the time series data on the number of TB cases, as well as environmental and socioeconomic covariates from January 2005 to December 2020. The impact of air pollutant exposure on TB risk was evaluated using the distributed lag nonlinear model (DLNM). Stratified analyses were conducted to examine the effect modifications of sex and age on the association between air pollutants and TB risk. Sensitivity analyses were applied to test the stability of the model. ResultsThere were a total of 54,096 cases of TB in Nantong during the study period. In the single-pollutant model, for each 10 μg/m3 increase in concentration, the pooled relative risks (RRs) of TB reached the maximum to 1.10 (95% confidence interval (CI): 1.04–1.16, lag 10 months) for particulate matter with aerodynamic diameter less than 2.5 μm (PM2.5), 1.05 (95% CI: 1.01–1.10, lag 9 months) for particulate matter with aerodynamic diameter less than 10 μm (PM10), and 1.11 (95%CI: 1.04–1.19, lag 10 months) for nitrogen dioxide (NO2). Ozone (O3) did not show significant effect on TB risk. Effect modifications of sex and age on the association between air pollutants and TB risk were not observed. The multi-pollutant model results showed no significant variation compared with the single-pollutant model. ConclusionsOur study suggests that air pollutants pose a substantial threat to the TB risk. Reducing air pollution might be crucial for TB prevention and control.

Association of SO2/CO exposure and greenness with high blood pressure in children and adolescents: A longitudinal study in China.

We aimed to investigate the association between greenness around schools, long-term gaseous air pollution exposure (SO2 and CO), and blood pressure in children and adolescents. From 2006 to 2018, a total of 219,956 Chinese children and adolescents aged 7-17 years in Beijing and Zhongshan were included in this longitudinal study. Annual average concentrations of SO2 and CO and the mean values of normalized difference vegetation index around schools were calculated. We used the generalized estimation equation model, restricted cubic spline model, and Cox model to analyze the health effects. Among all the subjects, 52,515 had the first onset of HBP. During the follow-up, HBP's cumulative incidence and incidence density were 23.88% and 7.72 per 100 person-year respectively. Exposures to SO2 and CO were significantly associated with SBP [β = 1.30, 95% CI: (1.26, 1.34) and 0.78 (0.75, 0.81)], DBP [β = 0.81 (0.79, 0.84) and 0.46 (0.44, 0.48)] and HBP [HR = 1.58 (1.57, 1.60) and 1.42 (1.41, 1.43)]. The risks of HBP attributed to SO2 and CO pollution would be higher in school-aged children in the low greenness group: the attributable fractions (AFs) were 26.31% and 20.04%, but only 13.90% and 17.81% in the higher greenness group. The AFs were also higher for normal-BMI children and adolescents in the low greenness group (AFs = 30.90% and 22.64%, but 14.41% and 18.65% in the high greenness group), while the AFs were not as high as expected for obese children in the low greenness group (AFs = 10.64% and 8.61%), nor was it significantly lower in the high greenness group (AFs = 9.60% and 10.72%). Greenness could alleviate the damage effects of SO2/CO exposure on the risks of HBP among children and adolescents, and the benefit is BMI sensitivity. It might offer insights for policymakers in making effective official interventions to prevent and control the prevalence of childhood HBP and the future disease burden caused by air pollution.

Association of long-term air pollution and ambient noise with cognitive decline in the Heinz Nixdorf Recall study

Little is known about the impact of long-term ambient air pollution (AP) and noise exposure on change in cognitive function over years in the elderly. In this study, we wanted to examine the association between long-term exposure to AP and noise with the rate of cognitive decline in a population aged 50 and older and susceptible groups with mild cognitive impairment or at a genetically higher risk of Alzheimer's disease (Apolipoprotein E ε4 positive). Participants in the German population-based Heinz Nixdorf Recall study carried out five neuropsychological tests. Individual tests scores at the first (T1 = 2006–2008) and second (T2 = 2011–2015) follow-up for each test were used as outcomes after standardization using predicted means adjusted for age and education. Global cognitive score (GCS) was defined as sum of five standardized scores of individual tests. Long-term exposures to particulate matter (PM2.5, PM10, PM2.5 absorbance), accumulation mode particle number (PNacc), a proxy of ultrafine particles, and nitrogen dioxide were estimated by the land-use regression and chemistry transport models. Noise exposures were assessed as outdoor weighted nighttime road traffic noise (Lnight) means. We performed linear regression analyses adjusted for sex, age, individual and neighborhood socio-economic status, and lifestyle variables. Effect modification in vulnerable groups was estimated using multiplicative interaction terms between exposure and a modifier. Overall, 2554 participants (49.5% men, median age is 63 (IQR = 12)) were included. We found weak associations between higher exposure to PM10 and PM2.5 with faster decline in the immediate verbal memory test. Adjustment for potential confounders and for co-exposures did not change the results. We saw no effects on GCS, and no effect of noise exposure. In susceptible groups, higher AP and noise exposure were tended to be associated with faster decline in GCS. Our results suggest that AP exposure may accelerate cognitive decline in older ages, particularly in susceptible groups.

Combined effects of ambient air pollution and PM2.5 components on renal function and the potential mediation effects of metabolic risk factors in China

Growing evidence links long-term air pollution exposure with renal function. However, little research has been conducted on the combined effects of air pollutant mixture on renal function and multiple mediation effects of metabolic risk factors. This study enrolled 8996 adults without chronic kidney disease (CKD) at baseline from the CHCN-BTH cohort study. Three-year exposure to air pollutants [particulate matter ≤ 2.5 µm (PM2.5), PM10, PM1, ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2) and carbon monoxide (CO)] and PM2.5 components [black carbon (BC), ammonium (NH4+), nitrate (NO3-), sulfate (SO42-) and organic matter (OM)] were assessed using well-validated machine learning methods. Linear mixed models were applied to investigate the associations between air pollutants and estimated glomerular filtration rate (eGFR). Quantile G-computation was used to assess the combined effects of pollutant mixtures. Causal mediation analysis and Bayesian mediation analysis were employed to estimate the mediation effects of metabolic risk factors. An interquartile range increases in BC (−0.256, 95 %CI: −0.331, −0.180) and OM (−0.603, 95 %CI: −0.810, −0.397) were significantly associated with eGFR decline; while O3 (1.151, 95 %CI: 0.813, 1.489), PM10 (0.721, 95 %CI: 0.309, 1.133), NH4+ (0.990, 95 %CI: 0.638, 1.342), and NO3- (0.610, 95 %CI: 0.405, 0.815) were associated with higher eGFR. The combined effect of the PM2.5 component mixture was found to be associated with lower eGFR (−1.147, 95 % CI: −1.456, −0.839), with OM contributing 72.4 % of the negative effect. Univariate mediation analyses showed that high-density lipoprotein (HDL) mediated 7.1 %, 6.9 %, and 6.1 % effects of O3, BC, and OM, respectively. However, these mediation effects were not significant in Bayesian mediation analysis. These findings suggest the effect of the PM2.5 component mixture on eGFR decline and the strong contribution of OM. Metabolic risk factors may not mediate the effects of air pollutants. Further study is warranted to clarify the potential mechanisms involved.

Long-term air pollution exposure and markers of cardiometabolic health in the National Longitudinal Study of Adolescent to Adult Health (Add Health)

BackgroundAir pollution exposure is associated with cardiovascular morbidity and mortality. Although exposure to air pollution early in life may represent a critical window for development of cardiovascular disease risk factors, few studies have examined associations of long-term air pollution exposure with markers of cardiovascular and metabolic health in young adults. ObjectivesBy combining health data from the National Longitudinal Study of Adolescent to Adult Health (Add Health) with air pollution data from the Fused Air Quality Surface using Downscaling (FAQSD) archive, we: (1) calculated multi-year estimates of exposure to ozone (O3) and particulate matter with an aerodynamic diameter ≤ 2.5 µm (PM2.5) for Add Health participants; and (2) estimated associations between air pollution exposures and multiple markers of cardiometabolic health. MethodsAdd Health is a nationally representative longitudinal cohort study of over 20,000 adolescents aged 12–19 in the United States (US) in 1994–95 (Wave I). Participants have been followed through adolescence and into adulthood with five in-home interviews. Estimated daily concentrations of O3 and PM2.5 at census tracts were obtained from the FAQSD archive and used to generate tract-level annual averages of O3 and PM2.5 concentrations. We estimated associations between average O3 and PM2.5 exposures from 2002 to 2007 and markers of cardiometabolic health measured at Wave IV (2008–09), including hypertension, hyperlipidemia, body mass index (BMI), diabetes, C-reactive protein, and metabolic syndrome. ResultsThe final sample size was 11,259 individual participants. The average age of participants at Wave IV was 28.4 years (range: 24–34 years). In models adjusting for age, race/ethnicity, and sex, long-term O3 exposure (2002–07) was associated with elevated odds of hypertension, with an odds ratio (OR) of 1.015 (95% confidence interval [CI]: 1.011, 1.029); obesity (1.022 [1.004, 1.040]); diabetes (1.032 [1.009,1.054]); and metabolic syndrome (1.028 [1.014, 1.041]); PM2.5 exposure (2002–07) was associated with elevated odds of hypertension (1.022 [1.001, 1.045]). ConclusionFindings suggest that long-term ambient air pollution exposure, particularly O3 exposure, is associated with cardiometabolic health in early adulthood.

Association of long-term exposure to air pollutant mixture and incident cardiovascular disease in a highly polluted region of China

Despite growing evidence that links long-term air pollution exposure to cardiovascular disease (CVD), the combined effects of air pollutants and particulate matter with an aerodynamic diameter of less than 2.5 μm (PM2.5) components are still limited. A prospective cohort study was performed based on the Cohort Study on Chronic Disease of the Community Natural Population in the Beijing-Tianjin-Hebei Region (CHCN-BTH) to assess the association of long-term air pollutants with incident CVD and the combined effect of the air pollutants mixture among 26,851 adults. Three-year residential exposure to air pollutants (PM2.5, O3, PM10, PM1, NO2, SO2 and CO) and PM2.5 components [black carbon (BC), NH4+, SO42-, NO3− and organic matter (OM)] were calculated based on well-validated models. Proportional hazard models were applied to assess the association of air pollutants with incident CVD. Quantile g-Computation was used to examine the combined effect of the pollutant mixture. During the 56,090 person-years follow-up, 629 participants reported incident CVD. Adjusted hazard ratios with 95% confidence intervals (CIs) of CVD per interquartile range increase in O3, PM2.5, PM1, NO2, BC, and OM concentrations were 4.52 (95%CI: 2.61, 7.83), 2.39 (95%CI: 1.83, 3.13), 2.37 (95%CI: 1.20, 4.70), 1.36 (95%CI: 1.19, 1.56), 3.84 (95%CI: 2.38, 6.18), and 3.07 (95%CI: 2.01, 4.69), respectively. In multi-pollutant models, the combined effect of air pollutant mixture on incident CVD was 2.37 (95%CI: 2.30, 2.44). PM2.5 and O3 contributed 54.3% and 44.5% of the combined effect of the air pollutant mixture, respectively. After using PM2.5 components instead of PM2.5 as part of the mixture, OM drove 55.2% of the combined effect. The findings indicated associations of air pollutant mixtures with CVD incidence. PM2.5 (especially OM) and O3 might strongly contribute to air pollutant mixtures that lead to incident CVD.

Invited Perspective: Still Hazy? Air Pollution and Acute Kidney Injury.

Invited Perspective: Still Hazy? Air Pollution and Acute Kidney Injury.

The Impact of Long-Term Air Pollution Exposure on Type 1 Diabetes Mellitus-Related Mortality among U.S. Medicare Beneficiaries.

Little of the previous literature has investigated associations between air pollution exposure and type 1 diabetes mellitus (T1DM)-related mortality, despite a well-established link between air pollution exposure and other autoimmune diseases. In a cohort of 53 million Medicare beneficiaries living across the conterminous United States, we used Cox proportional hazard models to assess the association of long-term PM2.5 and NO2 exposures on T1DM-related mortality from 2000 to 2008. Models included strata for age, sex, race, and ZIP code and controlled for neighborhood socioeconomic status (SES); we additionally investigated associations in two-pollutant models, and whether associations were modified by participant demographics. A 10 μg/m3 increase in 12-month average PM2.5 (HR: 1.183; 95% CI: 1.037-1.349) and a 10 ppb increase in NO2 (HR: 1.248; 95% CI: 1.089-1.431) was associated with an increased risk of T1DM-related mortality in age-, sex-, race-, ZIP code-, and SES-adjusted models. Associations for both pollutants were consistently stronger among Black (PM2.5: HR:1.877, 95% CI: 1.386-2.542; NO2: HR: 1.586, 95% CI: 1.258-2.001) and female (PM2.5: HR:1.297, 95% CI: 1.101-1.529; NO2: HR: 1.390, 95% CI: 1.187-1.627) beneficiaries. Long-term NO2 and, to a lesser extent, PM2.5 exposure is associated with statistically significant elevations in T1DM-related mortality risk.

Association between long-term air pollution exposure and development of diabetes among community-dwelling adults: Modification of the associations by dietary nutrients

BackgroundStudies on the modifying effects of dietary factors on the association between air pollution and diabetes-related outcomes are limited. We examined whether dietary nutrients could modify the association between long-term air pollution exposure and the development of diabetes. MethodsWe used data from the Cardiovascular Disease Association Study, which enrolled adults aged 40–69 years in Korea between 2005 and 2011 and followed them up until 2016 (n = 14,667). Annual concentrations of fine particulate matter (PM2.5) and nitrogen dioxide (NO2) at each participant’s residence(s) were estimated using community multiscale air quality models. Intake of 22 dietary nutrients was assessed using a validated food frequency questionnaire during the baseline survey. We examined the product terms between air pollution levels (continuous) and each dietary nutrient (quartile) using Cox regression models, adjusted for potential confounders. ResultsPM2.5 [hazard ratio (HR) = 1.49, 95 % confidence interval (CI): 1.11, 2.00] and NO2 (HR = 1.29, 95 % CI: 1.12, 1.49) concentrations were found to be associated with incident diabetes. NO2 levels interacted with dietary intake of retinol, vitamin A, and cholesterol (p-values for interaction < 0.05). Stronger associations were observed between NO2 levels and the occurrence of diabetes among individuals with a lower intake of these nutrients compared to those with a higher intake. No interaction was found between PM2.5 and the 22 investigated dietary nutrients. ConclusionsAdequate intake of dietary nutrients, such as retinol, vitamin A, and cholesterol, from various food items in a balanced diet may prevent the occurrence of diabetes in a setting wherein reduction of air pollution levels cannot be achieved in a short time frame.

Long-term ambient air pollution exposure and cardio-respiratory disease in China: findings from a prospective cohort study

BackgroundExisting evidence on long-term ambient air pollution (AAP) exposure and risk of cardio-respiratory diseases in China is mainly on mortality, and based on area average concentrations from fixed-site monitors for individual exposures. Substantial uncertainty persists, therefore, about the shape and strength of the relationship when assessed using more personalised individual exposure data. We aimed to examine the relationships between AAP exposure and risk of cardio-respiratory diseases using predicted local levels of AAP.MethodsA prospective study included 50,407 participants aged 30–79 years from Suzhou, China, with concentrations of nitrogen dioxide (NO2), sulphur dioxide (SO2), fine (PM2.5), and inhalable (PM10) particulate matter, ozone (O3) and carbon monoxide (CO) and incident cases of cardiovascular disease (CVD) (n = 2,563) and respiratory disease (n = 1,764) recorded during 2013–2015. Cox regression models with time-dependent covariates were used to estimate adjusted hazard ratios (HRs) for diseases associated with local-level concentrations of AAP exposure, estimated using Bayesian spatio–temporal modelling.ResultsThe study period of 2013–2015 included a total of 135,199 person-years of follow-up for CVD. There was a positive association of AAP, particularly SO2 and O3, with risk of major cardiovascular and respiratory diseases. Each 10 µg/m3 increase in SO2 was associated with adjusted hazard ratios (HRs) of 1.07 (95% CI: 1.02, 1.12) for CVD, 1.25 (1.08, 1.44) for COPD and 1.12 (1.02, 1.23) for pneumonia. Similarly, each 10 µg/m3 increase in O3 was associated with adjusted HR of 1.02 (1.01, 1.03) for CVD, 1.03 (1.02, 1.05) for all stroke, and 1.04 (1.02, 1.06) for pneumonia.ConclusionsAmong adults in urban China, long-term exposure to ambient air pollution is associated with a higher risk of cardio-respiratory disease.

Comparison of traditional Cox regression and causal modeling to investigate the association between long-term air pollution exposure and natural-cause mortality within European cohorts

Most studies investigating the health effects of long-term exposure to air pollution used traditional regression models, although causal inference approaches have been proposed as alternative. However, few studies have applied causal models and comparisons with traditional methods are sparse. We therefore compared the associations between natural-cause mortality and exposure to fine particulate matter (PM2.5) and nitrogen dioxide (NO2) using traditional Cox and causal models in a large multicenter cohort setting. We analysed data from eight well-characterized cohorts (pooled cohort) and seven administrative cohorts from eleven European countries. Annual mean PM2.5 and NO2 from Europe-wide models were assigned to baseline residential addresses and dichotomized at selected cut-off values (PM2.5: 10, 12, 15 μg/m³; NO2: 20, 40 μg/m³). For each pollutant, we estimated the propensity score as the conditional likelihood of exposure given available covariates, and derived corresponding inverse-probability weights (IPW). We applied Cox proportional hazards models i) adjusting for all covariates (“traditional Cox”) and ii) weighting by IPW (“causal model”). Of 325,367 and 28,063,809 participants in the pooled and administrative cohorts, 47,131 and 3,580,264 died from natural causes, respectively. For PM2.5 above vs. below 12 μg/m³, the hazard ratios (HRs) of natural-cause mortality were 1.17 (95% CI 1.13–1.21) and 1.15 (1.11–1.19) for the traditional and causal models in the pooled cohort, and 1.03 (1.01–1.06) and 1.02 (0.97–1.09) in the administrative cohorts. For NO2 above vs below 20 μg/m³, the HRs were 1.12 (1.09–1.14) and 1.07 (1.05–1.09) for the pooled and 1.06 (95% CI 1.03–1.08) and 1.05 (1.02–1.07) for the administrative cohorts. In conclusion, we observed mostly consistent associations between long-term air pollution exposure and natural-cause mortality with both approaches, though estimates partly differed in individual cohorts with no systematic pattern. The application of multiple modelling methods might help to improve causal inference.299 of 300 words.

Assessing the causal effect of long-term exposure to air pollution on cognitive decline in middle-aged and older adults – Empirical evidence from a nationwide longitudinal cohort

Air pollution remains a risk factor for the global burden of disease. Middle-aged and older people are more susceptible to air pollution because of their declining physical function and are more likely to develop diseases from long-term air pollution exposure. Studies of the effects of air pollution on cognitive function in middle-aged and older adults have been inconsistent. More representative and definitive evidence is needed. This study analysed data from the Chinese Family Panel Study, an ongoing nationwide prospective cohort study, collected in waves 2014, 2016 and 2018. Rigorously tested instrument was selected for analysis and participants’ PM2.5 and instrument exposures were assessed using high-precision satellite data. The causal relationship between long-term exposure to air pollution and poor cognitive function in middle-aged and older adults was investigated using the Correlated Random Effects Control Function (CRE-CF) method within a quasi-experimental framework. This study included a total of 7042 participants aged 45 years or older. A comparison of CRE-CF with other models (OLS model, ordered probit model, and ordered probit-CRE model) demonstrated the necessity of using CRE-CF given the endogeneity of air pollution. The credibility and validity of the instrumental variable were verified. In the CRE-CF model, long-term exposure to PM2.5 was found to accelerate cognitive decline in middle-aged and older adults (coefficients of −0.159, −0.336 and −0.244 for the total cognitive, verbal and mathematical scores, respectively). Taken together, these results suggest that chronic exposure to ambient air pollution is associated with cognitive decline in middle-aged and older adults, which highlights the need for appropriate protective policies.

Air pollution impacts on in-hospital case-fatality rate of ischemic stroke patients

BackgroundA growing body of evidence suggests that air pollution exposure is associated with an increased risk for cardiovascular diseases. Data regarding the impact of long-term air pollution exposure on ischemic stroke mortality are sparse. MethodsThe German nationwide inpatient sample was used to analyse all cases of hospitalized patients with ischemic stroke in Germany 2015–2019, which were stratified according to their residency. Data of the German Federal Environmental Agency regarding average values of air pollutants were assessed from 2015 to 2019 at district-level. Data were combined and the impact of different air pollution parameters on in-hospital case-fatality was analyzed. ResultsOverall, 1,505,496 hospitalizations of patients with ischemic stroke (47.7% females; 67.4 % ≥70 years old) were counted in Germany 2015–2019, of whom 8.2 % died during hospitalization. When comparing patients with residency in federal districts with high vs. low long-term air pollution, enhanced levels of benzene (OR 1.082 [95%CI 1.034–1.132],P = 0.001), ozone (O3, OR 1.123 [95%CI 1.070–1.178],P < 0.001), nitric oxide (NO, OR 1.076 [95%CI 1.027–1.127],P = 0.002) and PM2.5 fine particulate matter concentrations (OR 1.126 [95%CI 1.074–1.180],P < 0.001) were significantly associated with increased case-fatality independent from age, sex, cardiovascular risk-factors, comorbidities, and revascularization treatments. Conversely, enhanced carbon monoxide, nitrogen dioxide, PM10, and sulphur dioxide (SO2) concentrations were not significantly associated with stroke mortality. However, SO2−concentrations were significantly associated with stroke-case-fatality rate of >8 % independent of residence area-type and area use (OR 1.518 [95%CI 1.012–2.278],P = 0.044). ConclusionElevated long-term air pollution levels in residential areas in Germany, notably of benzene, O3, NO, SO2, and PM2.5, were associated with increased stroke mortality of patients. Research in contextEvidence before this study:Besides typical, established risk factors, increasing evidence suggests that air pollution is an important and growing risk factor for stroke events, estimated to be responsible for approximately 14 % of all stroke-associated deaths. However, real-world data regarding the impact of long-term exposure to air pollution on stroke mortality are sparse.Added value of this study:The present study demonstrates that the long-term exposure to the air pollutants benzene, O3, NO, SO2 and PM2.5 are independently associated with increased case-fatality of hospitalized patients with ischemic stroke in Germany.Implications of all the available evidence:The results of our study support the urgent need to reduce the exposure to air pollution by tightening emission controls to reduce the stroke burden and stroke mortality.

Comparing “causal” and “traditional” approaches in the association of long-term exposure to ambient air pollution on mortality: How sensitive are the results?

BackgroundFew comparisons between causal inference and traditional approaches have been performed. We applied “causal” and “traditional” methods to investigate the association between long-term air pollution exposure (PM2.5 and NO2) and mortality. MethodsWe analyzed pooled data from eight well-characterized cohorts and one administrative cohort. We defined the generalized propensity score (GPS) as the conditional likelihood of exposure given confounders, and derived corresponding inverse-probability weights (IPW). We applied Cox-proportional hazard models weighted by IPW, adjusted for GPS, and directly adjusting for all confounders. ResultsIn IPW models, PM2.5 5 µg/m3 increases were associated with hazard ratios (HR) = 1.141 (95% confidence interval (CI): 1.107, 1.176) and 1.050 (1.014, 1.088) in the pooled and administrative cohorts. Corresponding estimates for traditional Cox models were 1.132 (1.107, 1.158) and 1.057 (1.025, 1.089). Almost identical results were found for all approaches and both pollutants, when unbalanced covariates were adjusted for in causal models. ConclusionsTraditional and causal approaches provided consistent associations between long-term exposure to air pollution and mortality.

The long-term and short-term effects of ambient air pollutants on sleep characteristics in the Chinese population: big data analysis from real world by sleep records of consumer wearable devices

Several studies on long-term air pollution exposure and sleep have reported inconsistent results. Large-scale studies on short-term air pollution exposures and sleep have not been conducted. We investigated the associations of long- and short-term exposure to ambient air pollutants with sleep in a Chinese population based on over 1 million nights of sleep data from consumer wearable devices. Air pollution data including particulate matter (PM2.5, PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), and ozone (O3) were collected from the Ministry of Ecology and Environment. Short-term exposure was defined as a moving average of the exposure level for different lag days from Lag0 to Lag0-6. A 365-day moving average of air pollution was regarded as long-term exposure. Sleep data were recorded using wearable devices from 2017 to 2019. The mixed-effects model was used to evaluate the associations. We observed that sleep parameters were associated with long-term exposure to all air pollutants. Higher levels of air pollutant concentrations were associated with longer total sleep and light sleep duration, shorter deep sleep duration, and decreases in wake after sleep onset (WASO), with stronger associations of exposures to NO2 and CO [a 1-interquartile range (IQR) increased NO2 (10.3 μg/m3) was associated with 8.7 min (95% CI: 8.08 to 9.32) longer sleep duration, a 1-IQR increased CO (0.3 mg/m3) was associated with 5.0 min (95% CI: − 5.13 to − 4.89) shorter deep sleep duration, 7.7 min (95% CI: 7.46 to 7.85) longer light sleep duration, and 0.5% (95% CI: − 0.5 to − 0.4%) lower proportion of WASO duration to total sleep]. The cumulative effect of short-term exposure on Lag0-6 is similar to long-term exposure but relatively less. Subgroup analyses indicated generally greater effects on individuals who were female, younger (< 45 years), slept longer (≥ 7 h), and during cold seasons, but the pattern of effects was mixed. We supplemented two additional types of stratified analyses to reduce repeated measures of outcomes and exposures while accounting for individual variation. The results were consistent with the overall results, proving the robustness of the overall results. In summary, both short- and long-term exposure to air pollution affect sleep, and the effects are comparable. Although people tend to have prolonged total sleep duration with increasing air pollutant concentrations, their sleep quality might remain poor because of the reduction in deep sleep.

High-resolution patterns and inequalities in ambient fine particle mass (PM2.5) and black carbon (BC) in the Greater Accra Metropolis, Ghana

Growing cities in sub-Saharan Africa (SSA) experience high levels of ambient air pollution. However, sparse long-term city-wide air pollution exposure data limits policy mitigation efforts and assessment of the health and climate effects. In the first study of its kind in West Africa, we developed high resolution spatiotemporal land use regression (LUR) models to map fine particulate matter (PM2.5) and black carbon (BC) concentrations in the Greater Accra Metropolitan Area (GAMA), one of the fastest sprawling metropolises in SSA. We conducted a one-year measurement campaign covering 146 sites and combined these data with geospatial and meteorological predictors to develop separate Harmattan and non-Harmattan season PM2.5 and BC models at 100 m resolution. The final models were selected with a forward stepwise procedure and performance was evaluated with 10-fold cross-validation. Model predictions were overlayed with the most recent census data to estimate the population distribution of exposure and socioeconomic inequalities in exposure at the census enumeration area level. The fixed effects components of the models explained 48–69 % and 63–71 % of the variance in PM2.5 and BC concentrations, respectively. Spatial variables related to road traffic and vegetation explained the most variability in the non-Harmattan models, while temporal variables were dominant in the Harmattan models. The entire GAMA population is exposed to PM2.5 levels above the World Health Organization guideline, including even the Interim Target 3 (15 μg/m3), with the highest exposures in poorer neighborhoods. The models can be used to support air pollution mitigation policies, health, and climate impact assessments. The measurement and modelling approach used in this study can be adapted to other African cities to bridge the air pollution data gap in the region.