Dataset Information

Association between Ambient Air Pollution and MRI-Defined Brain Infarcts in Health Examinations in China.

ABSTRACT: The study aimed to evaluate the relationships between air pollutants and risk of magnetic resonance imaging (MRI)-defined brain infarcts (BI). We used data from routine health examinations of 1,400,503 participants aged ≥18 years who underwent brain MRI scans in 174 cities in 30 provinces in China in 2018. We assessed exposures to particulate matter (PM)2.5, PM10, nitrogen dioxide (NO2), and carbon monoxide (CO) from 2015 to 2017. MRI-defined BI was defined as lesions ≥3 mm in diameter. Air pollutants were associated with a higher risk of MRI-defined BI. The odds ratio (OR) (95% CI) for MRI-defined BI comparing the highest with the lowest tertiles of air pollutant concentrations was 2.00 (1.96-2.03) for PM2.5, 1.68 (1.65-1.71) for PM10, 1.58 (1.55-1.61) for NO2, and 1.57 (1.54-1.60) for CO. Each SD increase in air pollutants was associated with 16-42% increases in the risk of MRI-defined BI. The associations were stronger in the elderly subgroup. This is the largest survey to evaluate the association between air pollution and MRI-defined BI. Our findings indicate that ambient air pollution was significantly associated with a higher risk of MRI-defined BI.

SUBMITTER: Wu J

PROVIDER: S-EPMC8072670 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Association between Ambient Air Pollution and MRI-Defined Brain Infarcts in Health Examinations in China.

Wu Jing J Ning Yi Y Gao Yongxiang Y Shan Ruiqi R Wang Bo B Lv Jun J Li Liming L

International journal of environmental research and public health 20210419 8

The study aimed to evaluate the relationships between air pollutants and risk of magnetic resonance imaging (MRI)-defined brain infarcts (BI). We used data from routine health examinations of 1,400,503 participants aged ≥18 years who underwent brain MRI scans in 174 cities in 30 provinces in China in 2018. We assessed exposures to particulate matter (PM)2.5, PM10, nitrogen dioxide (NO2), and carbon monoxide (CO) from 2015 to 2017. MRI-defined BI was defined as le ...[more]

PMID: 33921763

Similar Datasets

Project description:Background and purposePrevious studies examining genetic associations with MRI-defined brain infarct have yielded inconsistent findings. We investigated genetic variation underlying covert MRI infarct in persons without histories of transient ischemic attack or stroke. We performed meta-analysis of genome-wide association studies of white participants in 6 studies comprising the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium.MethodsUsing 2.2 million genotyped and imputed single nucleotide polymorphisms, each study performed cross-sectional genome-wide association analysis of MRI infarct using age- and sex-adjusted logistic regression models. Study-specific findings were combined in an inverse-variance-weighted meta-analysis, including 9401 participants with mean age 69.7 (19.4% of whom had >or=1 MRI infarct).ResultsThe most significant association was found with rs2208454 (minor allele frequency, 20%), located in intron 3 of MACRO domain containing 2 gene and in the downstream region of fibronectin leucine-rich transmembrane protein 3 gene. Each copy of the minor allele was associated with lower risk of MRI infarcts (odds ratio, 0.76; 95% confidence interval, 0.68-0.84; P=4.64x10(-7)). Highly suggestive associations (P<1.0x10(-5)) were also found for 22 other single nucleotide polymorphisms in linkage disequilibrium (r(2)>0.64) with rs2208454. The association with rs2208454 did not replicate in independent samples of 1822 white and 644 black participants, although 4 single nucleotide polymorphisms within 200 kb from rs2208454 were associated with MRI infarcts in the black population sample.ConclusionsThis first community-based, genome-wide association study on covert MRI infarcts uncovered novel associations. Although replication of the association with top single nucleotide polymorphisms failed, possibly because of insufficient power, results in the black population sample are encouraging, and further efforts at replication are needed.

Project description:BackgroundAir pollution disparities by socioeconomic status (SES) are well documented for the United States, with most literature indicating an inverse relationship (i.e., higher concentrations for lower-SES populations). Few studies exist for China, a country accounting for 26% of global premature deaths from ambient air pollution.ObjectiveOur objective was to test the relationship between ambient air pollution exposures and SES in China.MethodsWe combined estimated year 2015 annual-average ambient levels of nitrogen dioxide (NO2) and fine particulate matter [PM ≤2.5μm in aerodynamic diameter (PM2.5)] with national demographic information. Pollution estimates were derived from a national empirical model for China at 1-km spatial resolution; demographic estimates were derived from national gridded gross national product (GDP) per capita at 1-km resolution, and (separately) a national representative sample of 21,095 individuals from the China Health and Retirement Longitudinal Study (CHARLS) 2015 cohort. Our use of global data on population density and cohort data on where people live helped avoid the spatial imprecision found in publicly available census data for China. We quantified air pollution disparities among individual's rural-to-urban migration status; SES factors (education, occupation, and income); and minority status. We compared results using three approaches to SES measurement: individual SES score, community-averaged SES score, and gridded GDP per capita.ResultsAmbient NO2 and PM2.5 levels were higher for higher-SES populations than for lower-SES population, higher for long-standing urban residents than for rural-to-urban migrant populations, and higher for the majority ethnic group (Han) than for the average across nine minority groups. For the three SES measurements (individual SES score, community-averaged SES score, gridded GDP per capita), a 1-interquartile range higher SES corresponded to higher concentrations of 6-9 μg/m3 NO2 and 3-6 μg/m3 PM2.5; average concentrations for the highest and lowest 20th percentile of SES differed by 41-89% for NO2 and 12-25% for PM2.5. This pattern held in rural and urban locations, across geographic regions, across a wide range of spatial resolution, and for modeled vs. measured pollution concentrations.ConclusionsMultiple analyses here reveal that in China, ambient NO2 and PM2.5 concentrations are higher for high-SES than for low-SES individuals; these results are robust to multiple sensitivity analyses. Our findings are consistent with the idea that in China's current industrialization and urbanization stage, economic development is correlated with both SES and air pollution. To our knowledge, our study provides the most comprehensive picture to date of ambient air pollution disparities in China; the results differ dramatically from results and from theories to explain conditions in the United States. https://doi.org/10.1289/EHP9872.

Project description:ImportanceSchizophrenia episodes may be triggered by short-term environmental stimuli. Short-term increases in ambient air pollution levels may elevate the risk of schizophrenia episodes, yet few epidemiologic studies have examined this association.ObjectiveTo investigate whether short-term increases in air pollution levels are associated with an additional risk of schizophrenia episodes, independent of absolute air pollution concentrations, and whether sustained increases in air pollution levels for several days are associated with more pronounced risks of schizophrenia episodes.Design, setting, and participantsThis nationwide, population-based, time-stratified case-crossover study was performed based on hospitalization records for schizophrenia across 295 administrative divisions of prefecture-level or above cities in China. Records were extracted from 2 major health insurance systems from January 1, 2013, to December 31, 2017. Thirty-six cities with a small number of schizophrenia hospitalizations (n < 50) were excluded. Data analysis for this study was performed from January to March 2024.ExposureDaily absolute concentrations of fine particulate matter (PM2.5), inhalable particulate matter (PM10), nitrogen dioxide, sulfur dioxide, ozone, and carbon monoxide were collected. Air pollution increases between neighboring days (APINs) were generated as the differences in absolute air pollution concentrations on the current day minus that on the previous day. Sustained increases (APIN ≥5 μg/m3 for PM2.5 and PM10, APIN ≥1 μg/m3 for nitrogen dioxide and sulfur dioxide, and APIN ≥0.05 mg/m3 for carbon monoxide) lasting for 1 or more to 4 or more days were defined for different air pollutants.Main outcome and measurePatients with schizophrenia episodes were identified by principal discharge diagnoses of schizophrenia. A conditional logistic regression model was used to capture the associations of absolute concentrations, APINs, and sustained increase events for different air pollutants with risks of schizophrenia hospitalizations.ResultsThe study included 817 296 hospitalization records for schizophrenia across 259 Chinese cities (30.6% aged 0-39 years, 56.4% aged 40-64 years, and 13.0% aged ≥65 years; 55.04% male). After adjusting for the absolute concentrations of respective air pollutants, per-IQR increases in 6-day moving average (lag0-5) APINs of PM2.5, PM10, nitrogen dioxide, sulfur dioxide, and carbon monoxide were associated with increases of 2.37% (95% CI, 0.88%-3.88%), 2.95% (95% CI, 1.46%-4.47%), 4.61% (95% CI, 2.93%-6.32%), 2.16% (95% CI, 0.59%-3.76%), and 2.02% (95% CI, 0.39%-3.68%) in schizophrenia hospitalizations, respectively. Greater risks of schizophrenia hospitalizations were associated with sustained increases in air pollutants lasting for longer durations up to 4 or more days.Conclusions and relevanceThis case-crossover study of the association between ambient air pollution increases and schizophrenia hospitalizations provides novel evidence that short-term increases in ambient air pollution levels were positively associated with an elevated risk of schizophrenia episodes. Future schizophrenia prevention practices should pay additional attention to APINs, especially sustained increases in air pollution levels for longer durations, besides the absolute air pollution concentrations.

Project description:Antenatal exposure to air pollutants is thought to be associated with a variety of maternal blood markers as well as adverse birth outcomes. However, the dysgenic influence of air pollutants on the antiphospholipid syndrome (APS) in mothers and their pregnancy outcomes remains unclear. In the current study, 371 mother-infant pairs (189 healthy: 182 APS) from Nanjing Maternal and Child Health Hospital as well as air pollutants concentration from their living environment were used to investigate correlations between air pollution with maternal blood indicators and fetal birth weight in the groups of APS and healthy mothers. Generalized linear model was used to evaluate the contributions of air pollutant exposure during pregnancy to the blood indicators variation. The relationships between birth weight with specific air pollutant and blood index were analyzed using ridge regression. Results showed that APS fetal birth weight was significantly impacted by air pollutant exposure during pregnancy, in particular, the birth weight decreased significantly along with increasing fine particulate matter 2.5 (PM2.5) and fine particulate matter 10 (PM10) exposure concentrations throughout pregnancy. In contrast, birth weight increased significantly with sulfur dioxide (SO2) exposure. In addition, APS-related blood indicators comprised of platelet distribution width (PDW), total bilirubin (TBIL), mean platelet volume (MPV), platelet-larger cell ratio (P_LCR), homocysteine (HCY), alkaline phosphatase (ALP), direct bilirubin (DBIL), basophilic granulocyte (BAS), platelet thrombocytocrit (PCT), preprandial glucose levels (OGTT0), monocytes (MON), and monocytes ratio (MON_ratio) were also strongly related with prenatal exposure to PM2.5 and PM10, in which PDW levels showed most strongly negative impaction on fetal birth weight. Together, we showed that prenatal exposure to air pollutant (PM2.5 and PM10) may exacerbate the poor birth outcomes of low birth weight by impacting APS maternal blood indicators especially for PDW.

Project description:With the continuous rapid urbanization process over the last three decades, outdoors air pollution has become a progressively more serious public health hazard in China. To investigate the possible associations, lag effects and seasonal differences of urban air quality on respiratory health (allergic rhinitis) in Changchun, a city in Northeastern China, we carried out a time-series analysis of the incidents of allergic rhinitis (AR) from 2013 to 2015. Environmental monitoring showed that PM2.5 and PM10 were the major air pollutants in Changchun, followed by SO₂, NO₂ and O₃. The results also demonstrated that the daily concentrations of air pollutants had obvious seasonal differences. PM10 had higher daily mean concentrations in spring (May, dust storms), autumn (October, straw burning) and winter (November to April, coal burning). The mean daily number of outpatient AR visits in the warm season was higher than in the cold season. The prevalence of allergic rhinitis was significantly associated with PM2.5, PM10, SO₂ and NO₂, and the increased mobility was 10.2% (95% CI, 5.5%-15.1%), 4.9% (95% CI, 0.8%-9.2%), 8.5% (95% CI, -1.8%-19.8%) and 11.1% (95% CI, 5.8%-16.5%) for exposure to each 1-Standard Deviation (1-SD) increase of pollutant, respectively. Weakly or no significant associations were observed for CO and O₃. As for lag effects, the highest Relative Risks (RRs) of AR from SO₂, NO₂, PM10 and PM2.5 were on the same day, and the highest RR from CO was on day 4 (L4). The results also indicated that the concentration of air pollutants might contribute to the development of AR. To summarize, this study provides further evidence of the significant association between ambient particulate pollutants (PM2.5 and PM10, which are usually present in high concentrations) and the prevalence of respiratory effects (allergic rhinitis) in the city of Changchun, located in Northeastern China. Environmental control and public health strategies should be enforced to address this increasingly challenging problem.

Dataset Information

Association between Ambient Air Pollution and MRI-Defined Brain Infarcts in Health Examinations in China.

Publications

Association between Ambient Air Pollution and MRI-Defined Brain Infarcts in Health Examinations in China.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets