Previous meta-analyses on associations between air pollution (AP) and type 2 diabetes mellitus (T2DM) were mainly focused on studies conducted in high-income countries. Evidence should be updated by ...including more recent studies, especially those conducted in low- and middle-income countries. We therefore conducted a systematic review and meta-analysis of epidemiological studies to conclude an updated pooled effect estimates between long-term AP exposure and the prevalence and incidence of T2DM. We searched PubMed, Embase, and Web of Science to identify studies regarding associations of AP with T2DM prevalence and incidence prior to January 2019. A random-effects model was employed to analyze the overall effects. A total of 30 articles were finally included in this meta-analysis. The pooled results showed that higher levels of AP exposure were significantly associated with higher prevalence of T2DM (per 10 μg/m3 increase in concentrations of particles with aerodynamic diameter < 2.5 μm (PM2.5): odds ratio (OR) = 1.09, 95% confidence interval (95%CI): 1.05, 1.13; particles with aerodynamic diameter < 10 μm (PM10): OR = 1.12, 95%CI: 1.06, 1.19; nitrogen dioxide (NO2): OR = 1.05, 95%CI:1.03, 1.08). Besides, higher level of PM2.5 exposure was associated with higher T2DM incidence (per 10 μg/m3 increase in concentration of PM2.5: hazard ratio (HR) = 1.10, 95%CI:1.04, 1.16), while the associations between PM10, NO2 and T2DM incidence were not statistically significant. The associations between AP exposure and T2DM prevalence showed no significant difference between high-income countries and low- and middle-incomes countries. However, different associations were identified between PM2.5 exposure and T2DM prevalence in different geographic areas. No significant differences were found in associations of AP and T2DM prevalence/incidence between females and males, except for the effect of NO2 on T2DM incidence. Overall, AP exposure was positively associated with T2DM. There still remains a need for evidence from low- and middle-income countries on the relationships between AP and T2DM.
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•Long-term exposure to air pollution was associated with an increased risk of T2DM.•Different associations between females and males were not identified.•Epidemiologic studies on exposure-response relationship should be encouraged.
Long-term exposure to air pollution was positively associated with T2DM.
Abstract
Thermoelectric materials generate electric energy from waste heat, with conversion efficiency governed by the dimensionless figure of merit, ZT. Single-crystal tin selenide (SnSe) was ...discovered to exhibit a high ZT of roughly 2.2–2.6 at 913 K, but more practical and deployable polycrystal versions of the same compound suffer from much poorer overall ZT, thereby thwarting prospects for cost-effective lead-free thermoelectrics. The poor polycrystal bulk performance is attributed to traces of tin oxides covering the surface of SnSe powders, which increases thermal conductivity, reduces electrical conductivity and thereby reduces ZT. Here, we report that hole-doped SnSe polycrystalline samples with reagents carefully purified and tin oxides removed exhibit an ZT of roughly 3.1 at 783 K. Its lattice thermal conductivity is ultralow at roughly 0.07 W m
–1
K
–1
at 783 K, lower than the single crystals. The path to ultrahigh thermoelectric performance in polycrystalline samples is the proper removal of the deleterious thermally conductive oxides from the surface of SnSe grains. These results could open an era of high-performance practical thermoelectrics from this high-performance material.
•Long-term exposure to PM2.5 was associated with poor sleep quality (OR = 1.15).•Long-term exposure to NO2 was associated with poor sleep quality (OR = 1.14).•Exposure to air pollution showed adverse ...effects on sleep quality in rural China.•Health effects of air pollution in rural areas should be given more attention.
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.
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 μm and 10 μm, 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.
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.
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.
Abstract
The purpose of this study was to examine the changes in severity of anxiety and depression symptoms, stress and sleeping quality after three months of mass quarantine for COVID-19 among ...undergraduate fresh students compared to their pre-COVID-19 measures. We used participants from the Chinese Undergraduate Cohort (CUC), a national prospective longitudinal study to examine the changes in anxiety and depression symptoms severity, stress and sleep quality after being under mass quarantine for three months. Wilcoxon matched pair signed-rank test was used to compare the lifestyle indicators. Severity of anxiety, depression symptoms, stress and sleep quality were compared with Wilcoxon signed-rank test. We used generalized estimating equation (GEE) to further quantify the change in mental health indicators and sleep quality after the COVID-19 mass quarantine compared to baseline. This study found that there was no deterioration in mental health status among Chinese new undergraduate students in 2020 after COVID-19 mass quarantine compared with the baseline measures in 2019. There was an improvement in sleep quality and anxiety symptoms. After adjusting for age, sex, exercise habit, time spent on mobile gadgets, and time spent outdoors, year 2020 was significantly associated with severity of depression symptoms in males (OR:1.52. 95%CI:1.05–2.20,
p
-value = 0.027). Year 2020 was significantly associated with the improvement of sleeping quality in total (OR:0.45, 95%CI:0.38–0.52,
p
< 0.001) and in all the subgroups. This longitudinal study found no deterioration in mental health status among Chinese new undergraduate students after three months of mass quarantine for COVID-19.
•Positive associations of air pollutants with MetS were found in rural Chinese adults.•Physical activity was negatively associated with MetS in rural Chinese adults.•Air pollutants attenuated the ...negative association of physical activity with MetS.
Long-term exposure to ambient air pollution and physical activity are linked to metabolic syndrome (MetS). However, the joint effect of physical activity and ambient air pollution on MetS remains largely unknown in rural Chinese adult population.
In this study, 39 089 individuals were included from the Henan Rural Cohort study that recruited 39 259 individuals at the baseline. Participants' exposure to air pollutants (including particulate matter with an aerodynamic diameter ≤ 1.0 µm (PM1), ≤2.5 µm (PM2.5), or ≤ 10 µm (PM10) and nitrogen dioxide (NO2)) were evaluated by using a spatiotemporal model based on satellites data. Individuals were defined as MetS according to the recommendation of the Joint Interim Societies. Physical activity-metabolic equivalent (MET) was calculated based on the formula of MET coefficient of activity × duration (hour per time) × frequency (times per week). Generalized linear models were used to analyze the individual air pollutant or physical activity and their interaction on MetS. Interaction effects of individual air pollutant and physical activity on MetS were assessed by using Interaction plots which exhibited the estimated effect of physical activity on MetS as a function of individual air pollutant.
The prevalence of MetS was 30.8%. The adjusted odd ratio of MetS with a per 5 µg/m3 increase in PM1, PM2.5, PM10, NO2 or a 10 MET (hour/day) of physical activity increment was 1.251(1.199, 1.306), 1.424(1.360, 1.491), 1.228(1.203, 1.254), 1.408(1.363, 1.455) or 0.814(0.796, 0.833). The protective effect of physical activity on MetS was decreased with accompanying air pollutant concentrations increased.
The results indicated that long-term exposure to ambient air pollutants related to increased risk of MetS and physical activity attenuated the effects of ambient air pollutants on increased risk for MetS.
•Solid fuel use was positively associated with 10-year ASCVD risk in rural regions.•Synergistic effects between solid fuel use and air pollutants on high 10-year ASCVD risk were found.•Clean fuel use ...and air pollutants control may jointly alleviate ASCVD's burden.
Although exposure to ambient air pollution (AAP) increases the risk for arteriosclerotic cardiovascular disease (ASCVD), evidence on the association of solid fuel use with ASCVD and its association modified by ambient air pollution remains limited.
A total of 16,779 adults were derived from the Henan Rural Cohort Study. Concentrations of ambient air pollutants (PM1, PM2.5, PM10, and NO2) were estimated by a spatiotemporal model based on satellites data. Solid fuel use was assessed by a self-reported questionnaire. The associations of solid fuel use with high 10-year ASCVD risk and the modified association by exposure to air pollutants were explored using logistic regression models.
There were positive associations of AAP exposure with high 10-year ASCVD risk among individuals with self-cooking. The joint associations between high AAP exposures and solid fuel use with high 10-year ASCVD risk were found. Compared to clean fuel user with low PM2.5 exposure, the odds ratios (ORs) and 95% confidence intervals (CIs) of high 10-year ASCVD risk was 1.25 (1.09, 1.42) for solid fuel user with low PM2.5 exposure, 1.93 (1.75, 2.12) for clean fuel user with high PM2.5 exposure, and 3.08 (2.67, 3.54) for solid fuel user with high PM2.5 exposure, respectively. Their additive effect on high 10-year ASCVD risk was observed (relative excess risk due to interaction (RERI): 0.90 (95 %CI: 0.50, 1.30), attributable proportion due to interaction (AP): 0.29 (95 %CI: 0.19, 0.40), and synergy index (SI): 1.77 (95 %CI: 1.38, 2.26)).
This study showed a synergistic effect of AAP and household air pollution reflected by solid fuel use on high 10-year ASCVD risk, suggesting that reducing solid cooking fuels and controlling air pollution may have a joint effect on public health improvement.
The exploitation of mineral resources is very important for economic development, but disorderly exploitation poses a serious threat to the ecological environment. However, investigations on the ...advantages of plant species and environmental pollution in polluted mining areas are limited. Thus, a survey was conducted to evaluate the impacts of abandoned mines on the surrounding ecological environment along rivers in polluted areas and to determine the Arsenic (As) pollution status in soil and plants. The results showed that the soil and vegetation along the river in the survey area were seriously polluted by As. The total As content of the 15 samples was significantly greater than the national soil background value (GB 15618-2018), and degree of pollution was nonlinearly related to the distance from the mine source, R2 = 0.9844. B. bipinnata, P. vittata and B. nivea were predominant with degrees of dominance of 0.01–0.33, 0.05–0.11, and 0.06–0.14 respectively. The As enrichment capacities of Juncus and P. vittata were significantly greater than those of the other plants, while the bioaccumulation factors (BCFs) were 21.81 and 7.04, respectively.
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•The As pollution status of plants and soil in mine polluted area was evaluated by comprehensive investigation.•The degree of soil pollution was found to have a non-linear relationship with the distance from the mine source, with a high correlation (R2 = 0.9844).•B. bipinnata, P. vittata and B. nivea are dominant species in As-contaminated soils.•Juncus and P. vittata were found to have significantly higher Arsenic (As) enrichment capacity compared to other plant species.
The epidemiological evidence on relationships between long-term exposure to particulate matter and hypertension and blood pressure has been inconclusive. Limited evidence was available for ...particulate matter with an aerodynamic diameter ≤ 1 μm (PM1) in rural areas of developing countries.
This study aimed to investigate the associations between long-term exposure to PM1 and hypertension and blood pressure among rural Chinese population.
This study included 39,259 participants who had completed the baseline survey from Henan Rural Cohort. Participants' exposure to PM1 was assessed by a satellite-based spatiotemporal model. The binary logistic regression model was used to examine the association between long-term PM1 exposure and hypertension, and multivariable linear regression model was used to investigate the associations between long-term PM1 exposure and systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP) and pulse pressure (PP). Moreover, we examined potential effect modifications by demographic, lifestyle and diet factors.
The mean concentration of PM1 for all participants during the 3-year before baseline survey was 59.98 μg/m3. Each 1 μg/m3 increase in PM1 concentration was significantly associated with an increase of 4.3% Odds ratio(OR) = 1.043, 95% confidence interval(CI): 1.033, 1.053 in odds for hypertension, an increase of 0.401 mm Hg (95% CI, 0.335, 0.467), 0.328 mm Hg (95% CI, 0.288, 0.369), 0.353 mm Hg (95% CI, 0.307, 0.399) and 0.073 mm Hg (95% CI, 0.030, 0.116) in SBP, DBP, MAP and PP, respectively. Further stratified analyses showed that the effect of PM1 on hypertension and blood pressure could be modified by sex, lifestyle and diet.
This study suggests that long-term exposure to ambient PM1 increases the risk of hypertension and is associated with elevations in blood pressure in rural Chinese adults, especially in male and those with unhealthy habits.
•Rural cohort participants were exposed to high level of PM1 during the study period.•PM1 was related to increased risk of hypertension and elevated blood pressure.•Males and those with unhealthy habits were more susceptible to the adverse effect.
•Higher residential greenness was associated with better sleep quality in rural China.•The association was stronger in males and participants with higher household income.•The association was ...stronger in participants with higher educational attainment.•Exposure to air pollution modified the association of greenness with sleep quality.
Epidemiological studies on the association of residential greenness with sleep quality are limited in China.
This study aims to investigate the association of long-term exposure to residential greenness with sleep quality in rural China.
In our study, 27,654 rural residents were selected from 4 counties of Henan Province by a multi-stage stratified cluster sampling method. Participants’ sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). The Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), two satellite-derived vegetation indexes, were used to assess the level of residential greenness. Long-term greenness exposure was defined as the averages of NDVI and EVI during the three years prior to the baseline survey. The relationship between sleep quality and greenness was assessed using the mixed-effect linear regression models.
Among 27,654 rural residents, the mean age was 55.89 years (standard deviation, SD = 12.22) and 60.18% of them were female. In the crude model, the PSQI score decreased with per interquartile range (IQR) increase in EVI and NDVI ΔPSQI score (95% confidence interval, 95%CI): −0.073 (−0.115, −0.030) and −0.047 (−0.089, −0.002). After controlling potential confounders, ΔPSQI scores and 95%CIs were −0.055 (−0.095, −0.012) and −0.090 (−0.151, −0.025) associated with per IQR increment in EVI and NDVI. The results of stratified analyses showed the effect of residential greenness on sleep was stronger among males and individuals with higher household income and educational attainment than females and those with lower household income and educational attainment. Moreover, the modification effect of air pollution was observed in the greenness-sleep association.
Our study indicated that higher residential greenness was significantly associated with better sleep quality in Chinese rural population, which highlights the significant effect of green space on human health.
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