Dataset Information

Is long-term exposure to air pollution associated with poor sleep quality in rural China?

ABSTRACT: BACKGROUND:Poor sleep quality is associated with poor quality of life and may even lead to mental illnesses. Several studies have indicated the association between exposure to air pollution and sleep quality. However, the evidence is very limited in China, especially in rural areas. METHODS:Participants in this study were obtained from the Henan Rural Cohort established during 2015-2017. Sleep quality was evaluated using the Pittsburgh Sleep Quality Index (PSQI) in the baseline survey. Poor sleep quality was defined by the global score of PSQI?>?5. Participants' exposures to PM2.5, PM10 (particulate matter with aerodynamic diameters ?2.5??m and 10??m, respectively) and NO2 (nitrogen dioxide) during the three years before the baseline survey were estimated using a satellite-based prediction. The associations between long-term exposure to air pollutants and sleep quality were examined using both the linear regression and logistic regression models. RESULTS:The IQRs (interquartile range) of mean levels of participants' exposures to PM2.5, PM10 and NO2 were 3.3?µg/m3, 8.8?µg/m3, and 4.8?µg/m3, respectively. After adjusted for potential confounders, the global score of PSQI (and 95%CI, 95% confidence intervals) increased by 0.16 (0.04, 0.27), 0.09 (-0.01, 0.19) and 0.14 (0.03, 0.24), associated with per IQR increase in PM2.5, PM10 and NO2, respectively. The odds ratios (and 95%CI) of poor sleep quality associated with per IQR increase in PM2.5, PM10 and NO2 were 1.15 (1.03, 1.29), 1.11 (1.02, 1.21) and 1.14 (1.03, 1.25), respectively. CONCLUSIONS:Long-term exposures to PM2.5, PM10 and NO2 were associated with poor sleep quality in rural China. Improvement of air quality may help to improve sleep quality among rural population of China.

SUBMITTER: Chen G

PROVIDER: S-EPMC6853164 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Is long-term exposure to air pollution associated with poor sleep quality in rural China?

Chen Gongbo G Xiang Hao H Mao Zhenxing Z Huo Wenqian W Guo Yuming Y Wang Chongjian C Li Shanshan S

Environment international 20191019 Pt B

<h4>Background</h4>Poor sleep quality is associated with poor quality of life and may even lead to mental illnesses. Several studies have indicated the association between exposure to air pollution and sleep quality. However, the evidence is very limited in China, especially in rural areas.<h4>Methods</h4>Participants in this study were obtained from the Henan Rural Cohort established during 2015-2017. Sleep quality was evaluated using the Pittsburgh Sleep Quality Index (PSQI) in the baseline su ...[more]

PMID: 31639600

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Project description:BackgroundLong-term exposures to air pollution has been reported to be associated with inflammation and oxidative stress. However, the underlying metabolic mechanisms remain poorly understood.ObjectivesWe aimed to determine the changes in the blood metabolome and thus the metabolic pathways associated with long-term exposure to outdoor air pollution and ambient temperature.MethodsWe quantified metabolites using mass-spectrometry based global untargeted metabolomic profiling of plasma samples among men from the Normative Aging Study (NAS). We estimated the association between long-term exposure to PM2.5, NO2, O3, and temperature (annual average of central site monitors) with metabolites and their associated metabolic pathways. We used multivariable linear mixed-effect regression models (LMEM) while simultaneously adjusting for the four exposures and potential confounding and correcting for multiple testing. As a reduction method for the intercorrelated metabolites (outcome), we further used an independent component analysis (ICA) and conducted LMEM with the same exposures.ResultsMen (N?=?456) provided 648 blood samples between 2000 and 2016 in which 1158 metabolites were quantified. On average, men were 75.0?years and had an average body mass index of 27.7?kg/m2. Almost all men (97%) were not current smokers. The adjusted analysis showed statistically significant associations with several metabolites (58 metabolites with PM2.5, 15 metabolites with NO2, and 6 metabolites with temperature) while no metabolites were associated with O3. One out of five ICA factors (factor 2) was significantly associated with PM2.5. We identified eight perturbed metabolic pathways with long-term exposure to PM2.5 and temperature: glycerophospholipid, sphingolipid, glutathione, beta-alanine, propanoate, and purine metabolism, biosynthesis of unsaturated fatty acids, and taurine and hypotaurine metabolism. These pathways are related to inflammation, oxidative stress, immunity, and nucleic acid damage and repair.ConclusionsUsing a global untargeted metabolomic approach, we identified several significant metabolites and metabolic pathways associated with long-term exposure to PM2.5, NO2 and temperature. This study is the largest metabolomics study of long-term air pollution, to date, the first study to report a metabolomic signature of long-term temperature exposure, and the first to use ICA in the analysis of both.

Project description:Air pollutants (AP) play a role in subclinical inflammation, and are associated with cardiovascular morbidity and mortality. Metabolic syndrome (MetS) is inflammatory and precedes cardiovascular morbidity and type 2 diabetes. Thus, a positive association between AP and MetS may be hypothesized. We explored this association, (taking into account, pathway-specific MetS definitions), and its potential modifiers in Swiss adults. We studied 3769 participants of the Swiss Cohort Study on Air Pollution and Lung and Heart Diseases in Adults, reporting at least four-hour fasting time before venepuncture. AP exposures were 10-year mean residential PM10 (particulate matter <10μm in diameter) and NO2 (nitrogen dioxide). Outcomes included MetS defined by World Health Organization (MetS-W), International Diabetes Federation (MetS-I) and Adult Treatment Panel-III (MetS-A) using four- and eight-hour fasting time limits. We also explored associations with individual components of MetS. We applied mixed logistic regression models to explore these associations. The prevalence of MetS-W, MetS-I and MetS-A were 10%, 22% and 18% respectively. Odds of MetS-W, MetS-I and MetS-A increased by 72% (51-102%), 31% (11-54%) and 18% (4-34%) per 10μg/m3 increase in 10-year mean PM10. We observed weaker associations with NO2. Associations were stronger among physically-active, ever-smokers and non-diabetic participants especially with PM10 (p<0.05). Associations remained robust across various sensitivity analyses including ten imputations of missing observations and exclusion of diabetes cases. The observed associations between AP exposure and MetS were sensitive to MetS definitions. Regarding the MetS components, we observed strongest associations with impaired fasting glycemia, and positive but weaker associations with hypertension and waist-circumference-based obesity. Cardio-metabolic effects of AP may be majorly driven by impairment of glucose homeostasis, and to a less-strong extent, visceral adiposity. Well-designed prospective studies are needed to confirm these findings.

Project description:BackgroundAir pollution exposures have been shown to adversely impact health through a number of biological pathways associated with glucose metabolism. However, few studies have evaluated the associations between air pollution and glycosylated hemoglobin (HbA1c) levels. Further, no studies have evaluated these associations in US populations or investigated whether associations differ in diabetic as compared to non-diabetic populations. To address this knowledge gap, we investigated the associations between airborne fine particulate matter (PM2.5) and nitrogen dioxide (NO2) and HbA1c levels in both diabetic and non-diabetic older Americans. We also examined the impact of PM2.5 and NO2 on prevalent diabetes mellitus (DM) in this cohort.MethodsWe used multilevel logistic and linear regression models to evaluate the association between long-term average air pollutant levels and prevalence of DM and HbA1c levels, respectively, among 4121 older (57+ years) Americans enrolled in the National Social Life, Health, and Aging Project between 2005 and 2011. All models adjusted for age, sex, body mass index, smoking status, race, household income, education level, neighborhood socioeconomic status, geographic region, urbanicity and diabetic medication use. We estimated participant-specific exposures to PM2.5 on a six-kilometer grid covering the conterminous U.S. using spatio-temporal models, and to NO2 using nearest measurements from the Environmental Protection Agency's Air Quality System. HbA1c levels were measured for participants in each of two data collection waves from dried blood spots and log-transformed prior to analysis. Participants were considered diabetic if they had HbA1c values≥6.5% or reported taking diabetic medication.ResultsThe prevalence of diabetes at study entry was 22.2% (n=916) and the mean HbA1c was 6.0±1.1%. Mean one-year moving average PM2.5 and NO2 exposures were 10.4±3.0μg/m3 and 13.1±7.0 ppb, respectively. An inter-quartile range (IQR, 3.9μg/m3) increase in one-year moving average PM2.5 was positively associated with increased diabetes prevalence (prevalence odds ratio, POR 1.35, 95% CI: 1.19, 1.53). Similarly, an IQR (8.6 ppb) increase in NO2 was also significantly associated with diabetes prevalence (POR 1.27, 95% CI: 1.10, 1.48). PM2.5 (1.8%±0.6%, p<0.01) and NO2 (2.0%±0.7%, p<0.01) exposures were associated with higher HbA1c levels in diabetic participants, while only NO2 was significantly associated with HbA1c in non-diabetic participants (0.8%±0.2%, p<0.01). Significant dose response relationships were identified for both pollutants in diabetic participants and for NO2 in non-diabetic participants.Conclusions/interpretationsIn a cohort of older men and women in the United States, PM2.5 and NO2 exposures were significantly associated with prevalence of DM and increased HbA1c levels among both non-diabetic and diabetic participants. These associations suggest that air pollution could be a key risk factor for abnormal glucose metabolism and diabetes in the elderly.

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Is long-term exposure to air pollution associated with poor sleep quality in rural China?

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Is long-term exposure to air pollution associated with poor sleep quality in rural China?

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