Long-term exposure to PM1 is associated with increased prevalence of metabolic diseases: evidence from a nationwide study in 123 Chinese cities.

Exposure to particulate matter (PM) has been linked to metabolic diseases. However, the effects of PM with an aerodynamic diameter ≤ 1.0 µm (PM1) on metabolic diseases remain unclear. This study is aimed at assessing the associations of PM1 with metabolic disease risk and quantifying the concentration-response (C-R) relationship of PM1 with metabolic disease risk. A national cross-sectional study was conducted, including 12,495 middle-aged and older adults in 123 Chinese cities. The two-year average concentration of PM1 was evaluated using satellite-based spatiotemporal models. Metabolic diseases, including abdominal obesity, diabetes, hypertension, dyslipidemia, and metabolic syndrome, were identified based on physical examination, blood standard biochemistry examination, and self-reported disease histories. Generalized linear models and C-R curves were used to evaluate the associations of PM1 with metabolic diseases. A total of 12,495 participants were included in this study, with a prevalence of 45.73% for abdominal obesity, 20.22% for diabetes, 42.46% for hypertension, 41.01% for dyslipidemia, and 33.78% for metabolic syndrome. The mean ± standard deviation age of participants was 58.79 ± 13.14 years. In addition to dyslipidemia, exposure to PM1 was associated with increased risks of abdominal obesity, diabetes, hypertension, and metabolic syndrome. Each 10 µg/m3 increase in PM1 concentrations was associated with 39% (odds ratio (OR) = 1.39, 95% confidence interval (CI) 1.33, 1.46) increase in abdominal obesity, 18% (OR = 1.18, 95%CI 1.12, 1.25) increase in diabetes, 11% (OR = 1.11, 95%CI 1.06, 1.16) increase in hypertension, and 25% (OR = 1.25, 95%CI 1.19, 1.31) in metabolic syndrome, respectively. C-R curves showed that the OR values of abdominal obesity, diabetes, hypertension, and metabolic syndrome were increased gradually with the increase of PM1 concentrations. Subgroup analysis indicated that exposure to PM1 was associated with increased metabolic disease risks among participants with different lifestyles and found that solid fuel users were more susceptible to PM1 than clean fuel users. This national cross-sectional study indicated that exposure to higher PM1 might increase abdominal obesity, diabetes, hypertension, and metabolic syndrome risk, and solid fuel use might accelerate the adverse effects of PM1 on metabolic syndrome risk. Further longitudinal cohort studies are warranted to establish a causal inference between PM1 exposure and metabolic disease risk.

Sociodemographic determinants of life satisfaction among grandparent caregivers.

Introduction: It has become a common contemporary phenomenon for grandparents to provide care for young children in their family in both urban and rural areas. This study attempted to investigate psychological wellbeing and quality of life among grandparents involved in childcare in China, and to explore the relationships between sociodemographic characteristics, quality of life, and life satisfaction in this group. Methods: Using stratified random cluster sampling, we conducted a survey of grandparent caregivers in Wuhan in November and December of 2020 (N = 1,640). Descriptive statistics to univariate analysis, multiple linear regression, and structural equation modeling were carried out. Results: Across all respondents, mean scores on life satisfaction, sleep quality, and quality of life were 14.05 ± 3.50, 5.02 ± 3.37, and 74.51 ± 16.88, respectively. Marital status, income, chronic diseases, family relationships, and physical exercise were found to be associated with life satisfaction. The results of structural equation modeling indicated that quality of life, sleep quality, and sociodemographic characteristics may exert direct and indirect effects on life satisfaction. Mediating effects accounted for 30.0% of the total effects. Conclusion: Overall, grandparent caregivers have poor life satisfaction, quality of life, and sleep quality. A higher household income, better relationships with family members, healthy lifestyle habits, and high-quality sleep may effectively help to improve life satisfaction among grandparent caregivers.

Associations of residential greenness with obesity and BMI level among Chinese rural population: findings from the Henan Rural Cohort Study.

In recent years, increasing evidence supports the notion that obesity risk is affected by residential greenness. However, limited studies have been established in low- and middle-income countries, especially in China. The study aimed to evaluate the associations of residential greenness with obesity and body mass index (BMI) level in Chinese rural-dwelling adults. A total of 39,259 adults from the Henan Rural Cohort Study (HRCS) were included in the analyses. According to the guideline for prevention and control of overweight and obesity in Chinese adults, obesity was defined as BMI ≥ 28 kg/m2. Residential greenness was measured by satellite-based normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). Generalized linear mixed models were used to study the associations between exposure to residential greenness with obesity and BMI level. Higher residential greenness was significantly correlated with lower odds of obesity and BMI level. For example, in the full-adjusted analyses, an interquartile range (IQR) increase in EVI500-m was linked with reduced odds of obesity (OR = 0.77, 95%CI 0.72-0.82) and BMI level (ß = - 0.41 kg/m2, 95%CI - 0.48 to - 0.33 kg/m2). Mediation analyses showed air pollution and physical activity could be potential mediators in these associations. Besides, we found that the association of NDVI500-m with BMI was stronger in females and low-income populations. Higher residential greenness was associated with a lower prevalence of obesity and BMI level, particularly among females and the low-income population. These relationships were partially mediated by reducing air pollution and increasing physical activity.

Is residential greenness associated with dyslipidemia and lipid levels in Chinese rural-dwelling adults? The Henan rural cohort study.

Scarce epidemiologic research examined the associations between residential greenness and dyslipidemia or lipid levels in low/middle-income countries. Baseline statistics (2015-2017) of 39,259 rural-dwelling adults were obtained from a Chinese longitudinal study. The blood lipid level was measured utilizing an enzymatic assay method. According to the 2016 Chinese guidelines on dyslipidemia (revision), patients with dyslipidemia were defined. Participants' exposure to residential greenness was characterized by the satellite-based normalized difference vegetation index (NDVI). Mixed effects logistic regression and mixed effects linear regression were performed to assess the associations of residential greenness with dyslipidemia and lipid levels. The median (interquartile range, IQR) of 3-year average NDVI1000-m was 0.521 (0.089) units. Each IQR increase in NDVI1000-m was significantly linked with increased odds of hyperbetalipoproteinemia (OR = 1.33, 95%CI 1.21-1.46). The same increment in NDVI1000-m was associated with lower total cholesterol (TC) levels and increased low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C) levels. For instance, the %changes in HDL-C levels was 0.71% (95%CI 0.17%-1.26%). The above relationships were partially mediated by reducing air pollution and lowering body mass index (BMI). Interaction effect analysis observed the greenness-lipid association was stronger in males than females (i.e., NDVI1000-m-TC association). Long-term exposure to residential greenness was associated with odds of dyslipidemia and lipid levels in Chinese rural-dwelling adults, particularly among males. Considering the cross-sectional study design, more longitudinal studies are needed to identify the causal associations.

Serum cardiovascular-related metabolites disturbance exposed to different heavy metal exposure scenarios.

Health effects induced by heavy metal components of particulate matter need further research. A total of 32 healthy volunteers were recruited to walk for 4 h in two different exposure scenarios in Wuhan from May 1 to Jun 30, 2019. Metabolomics technology was used to identify serum cardiovascular-related metabolites disturbance, and the health risk assessment model was employed to assess the non-carcinogenic and carcinogenic risks associated with airborne heavy metals. The results showed that the average mass concentrations of Co, Ni, Cd, Cu, Ag and Ba in PM10 from May 1 to Jun 30, 2019 were 0.22, 0.49, 11.53, 2.23, 34.47 and 4.19 ng/m3, respectively, and were 0.86, 128.47, 291.85, 291.94, 98.55 and 422.62 ng/m3 in PM2.5, respectively. Healthy young adults briefly exposed to heavy metals were associated with serum cardiovascular-related metabolites disturbance, including increased SM(d18:1/17:0) and Sphingomyelin, and decreased GlcCer(d16:1/18:0) and Galabiosylceramide, simultaneously accompanied by activation of the sphingolipid metabolism pathway. Non-carcinogenic and carcinogenic risks of airborne heavy metals via the inhalation route were observed, Ni and Cd most influenced to potential health risks. Findings indicated exposure to increment of heavy metals may increase health risks by causing cardiovascular-related metabolites disturbance via activating the sphingolipid metabolism pathway.

The short- and long-term associations of particulate matter with inflammation and blood coagulation markers: A meta-analysis.

Inflammation and the coagulation cascade are considered to be the potential mechanisms of ambient particulate matter (PM) exposure-induced adverse cardiovascular events. Tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), interleukin-8 (IL-8), and fibrinogen are arguably the four most commonly assayed markers to reflect the relationships of PM with inflammation and blood coagulation. This review summarized and quantitatively analyzed the existing studies reporting short- and long-term associations of PM2.5(PM with an aerodynamic diameter ≤2.5 µm)/PM10 (PM with an aerodynamic diameter≤10 µm) with important inflammation and blood coagulation markers (TNF-α, IL-6, IL-8, fibrinogen). We reviewed relevant studies published up to July 2020, using three English databases (PubMed, Web of Science, Embase) and two Chinese databases (Wang-Fang, China National Knowledge Infrastructure). The OHAT tool, with some modification, was applied to evaluate risk of bias. Meta-analyses were conducted with random-effects models for calculating the pooled estimate of markers. To assess the potential effect modifiers and the source of heterogeneity, we conducted subgroup analyses and meta-regression analyses where appropriate. The assessment and correction of publication bias were based on Begg's and Egger's test and "trim-and-fill" analysis. We identified 44 eligible studies. For short-term PM exposure, the percent change of a 10 µg/m3 PM2.5 increase on TNF-α and fibrinogen was 3.51% (95% confidence interval (CI): 1.21%, 5.81%) and 0.54% (95% confidence interval (CI): 0.21%, 0.86%) respectively. We also found a significant short-term association between PM10 and fibrinogen (percent change = 0.17%, 95% CI: 0.04%, 0.29%). Overall analysis showed that long-term associations of fibrinogen with PM2.5 and PM10 were not significant. Subgroup analysis showed that long-term associations of fibrinogen with PM2.5 and PM10 were significant only found in studies conducted in Asia. Our findings support significant short-term associations of PM with TNF-α and fibrinogen. Future epidemiological studies should address the role long-term PM exposure plays in inflammation and blood coagulation markers level change.

The association between short-term exposure to ambient air pollution and fractional exhaled nitric oxide level: A systematic review and meta-analysis of panel studies.

Several epidemiological studies have evaluated the fractional exhaled nitric oxide (FeNO) of ambient air pollution but the results were controversial. We therefore conducted a systematic review and meta-analysis to investigate the associations between short-term exposure to air pollutants and FeNO level. We searched PubMed and Web of Science and included a total of 27 articles which focused on associations between ambient air pollutants (PM10, PM2.5, black carbon (BC), nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3)) exposure and the change of FeNO. Random effect model was used to calculate the percent change of FeNO in association with a 10 or 1 µg/m3 increase in air pollutants exposure concentrations. A 10 µg/m3 increase in short-term PM10, PM2.5, NO2, and SO2 exposure was associated with a 3.20% (95% confidence interval (95%CI): 1.11%, 5.29%), 2.25% (95%CI: 1.51%, 2.99%),4.90% (95%CI: 1.98%, 7.81%), and 8.28% (95%CI: 3.61%, 12.59%) change in FeNO, respectively. A 1 µg/m3 increase in short-term exposure to BC was associated with 3.42% (95%CI: 1.34%, 5.50%) change in FeNO. The association between short-term exposure to O3 and FeNO level was insignificant (P＞0.05). Future studies are warranted to investigate the effect of multiple pollutants, different sources and composition of air pollutants on airway inflammation.

Is long-term PM1 exposure associated with blood lipids and dyslipidemias in a Chinese rural population?

BACKGROUND: Air pollution has been shown to be associated with blood lipid levels. However, studies on long-term ambient particulate matter with aerodynamic diameter ≤1 µm (PM1) exposure in high-exposure areas are still limited. This study aimed to explore the associations among long-term PM1 exposure, blood lipids and dyslipidemias. METHODS: Baseline data of The Henan Rural Cohort study was used in present study, including a total of 39,259 participants aged from 18 to 79 years. Daily levels of PM1 were estimated by a spatiotemporal model using ground-level measurements of PM1, satellite remote sensing data and other predictors, according to participants' home addresses. Individual exposure to PM1 was the 3-year average before baseline investigation. Linear regression and logistic regression models were applied to examine the associations among PM1, blood lipids ((total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C)), and prevalence of dyslipidemias. RESULTS: The 3-year concentration of PM1 was 55.7 ± 2.1 µg/m3. Each 1 µg/m3 increment of PM1 was associated with an increase of 0.21% (95% confidence interval (CI): 0.11%-0.31%) in TC and 0.75% (95% CI: 0.61%-0.90%) in LDL-C, while decrease of 2.68% (95% CI: 2.43%-2.93%) in TG and 0.47% (95% CI: 0.35%-0.59%) in HDL-C. Each 1 µg/m3 increase in PM1 was associated with 6% (95% CI: 4%-8%), 3% (95% CI: 2%-5%) and 5% (95% CI: 3%-7%) higher risks of hypercholesterolemia, hyperbetalipoproteinemia and hypoalphalipoproteinemia. Sex, age and BMI statistically modified the associations between PM1 with blood lipid levels and dyslipidemias. CONCLUSIONS: Higher PM1 exposure was associated with adverse changes of blood lipid levels and dyslipidemias. Males, older and overweight participants were susceptive to the adverse effects of PM1.

Associations between long-term exposure to air pollution and blood pressure and effect modifications by behavioral factors.

BACKGROUND: Studies on the hypertensive effect of long-term air pollution exposure were inconclusive and showed scarce evidence from rural areas in developing countries. In this context, we examined the associations of air pollution exposure with hypertension and blood pressure, and their effect modifiers in rural Chinese adults. METHODS: We studied 39,259 participants from a cohort established in five rural regions of central China. Individual exposures to PM2.5 and PM10 (particulate matter with an aerodynamic diameter less than or equal to 2.5 µm and 10 µm) and nitrogen dioxide (NO2) was evaluated using satellite-based spatiotemporal models. Mixed-effect regression models were applied to examine the associations of long-term exposure to air pollution with hypertension and four blood pressure component measurements, including systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP) and pulse pressure (PP). Several potential effect modifiers related to demographic and behavioral factors were also examined. RESULTS: The results showed that for each 1 µg/m3 increase in PM2.5, PM10 and NO2, the adjusted odds ratio of hypertension was 1.029 (95%CI: 1.001,1.057), 1.015 (95%CI: 1.001, 1.029) and 1.069 (95%CI: 1.038, 1.100), respectively. These three air pollutants were also associated with increased SBP (except for PM10), DBP and MAP. The hypertensive effects of air pollution were more pronounced among males, smokers, drinkers, individuals with a high-fat diet, and those with high-level physical activity. CONCLUSION: Long-term exposure to PM2.5, PM10 and NO2 was associated with increased blood pressure and hypertension in rural Chinese adults, and the associations were modified by several behavioral factors.

Long-term effects of ambient air pollutants to blood lipids and dyslipidemias in a Chinese rural population.

Both air pollution and dyslipidemias contributed to large number of deaths and disability-adjusted life lost years. Long-term air pollution exposure was related to changed blood lipids and risk of dyslipidemias. This study was designed to evaluate relationships between air pollutants, blood lipids and prevalence of dyslipidemias in a Chinese rural population exposed to high-level air pollution based on baseline data of The Henan Rural Cohort study. An amount of 39,057 participants from rural areas in China were included. The 3-year average exposure of air pollutants (PM2.5, PM10, NO2) was estimated by a spatiotemporal model. Logistic and linear regression models were employed to explore relationships between air pollutants, blood lipids (TC, TG, HDL-C and LDL-C) and prevalence of dyslipidemias. The three-year concentration of PM2.5, PM10 and NO2 was 72.8 ±â€¯2.3 µg/m3, 131.5 ±â€¯5.7 µg/m3and 39.1 ±â€¯3.1 µg/m3, respectively. Overall, increased air pollution exposure was related to increased TC and LDL-C, while decreased TG and HDL-C. Each 1-µg/m3 increment of PM2.5 was related to 0.10% (0.07%-0.19%) increase in TC, 0.63% (0.50%-0.77%) increase in LDL-C, 2.93% (2.70%-3.16%) decrease in TG, 0.49% (0.38%-0.60%) decrease in HDL-C; and 5.7% (95%CI: 3.7%-7.6%), 4.0% (95%CI: 2.1%-6.0%) and 3.8% (95%CI: 2.5%-5.1%) increase in odds for hypercholesterolemia, hyperbetalipoproteinemia and hypoalphalipoproteinemia, respectively. Stronger associations were found in male and older participants. Findings suggest that air pollutants were associated with changed blood lipid levels and higher risk of dyslipidemias among rural population. Male and elder people should pay more attention to personal safety protection.

Associations between long-term exposure to ambient air pollution and risk of type 2 diabetes mellitus: A systematic review and meta-analysis.

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.

Associations of long-term exposure to ambient PM1 with hypertension and blood pressure in rural Chinese population: The Henan rural cohort study.

BACKGROUND: 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. OBJECTIVE: This study aimed to investigate the associations between long-term exposure to PM1 and hypertension and blood pressure among rural Chinese population. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.