Sustained air pollution exposures, fasting plasma glucose, glycated haemoglobin, prevalence and incidence of diabetes: a nationwide study in China

A causal relationship between particulate matter 2.5 and obesity and its related indicators: a Mendelian randomization study of European ancestry

Background

In recent years, the prevalence of obesity has continued to increase as a global health concern. Numerous epidemiological studies have confirmed the long-term effects of exposure to ambient air pollutant particulate matter 2.5 (PM2.5) on obesity, but their relationship remains ambiguous.

Methods

Utilizing large-scale publicly available genome-wide association studies (GWAS), we conducted univariate and multivariate Mendelian randomization (MR) analyses to assess the causal effect of PM2.5 exposure on obesity and its related indicators. The primary outcome given for both univariate MR (UVMR) and multivariate MR (MVMR) is the estimation utilizing the inverse variance weighted (IVW) method. The weighted median, MR-Egger, and maximum likelihood techniques were employed for UVMR, while the MVMR-Lasso method was applied for MVMR in the supplementary analyses. In addition, we conducted a series of thorough sensitivity studies to determine the accuracy of our MR findings.

Results

The UVMR analysis demonstrated a significant association between PM2.5 exposure and an increased risk of obesity, as indicated by the IVW model (odds ratio [OR]: 6.427; 95% confidence interval [CI]: 1.881-21.968; P FDR = 0.005). Additionally, PM2.5 concentrations were positively associated with fat distribution metrics, including visceral adipose tissue (VAT) (OR: 1.861; 95% CI: 1.244-2.776; P FDR = 0.004), particularly pancreatic fat (OR: 3.499; 95% CI: 2.092-5.855; PFDR =1.28E-05), and abdominal subcutaneous adipose tissue (ASAT) volume (OR: 1.773; 95% CI: 1.106-2.841; P FDR = 0.019). Furthermore, PM2.5 exposure correlated positively with markers of glucose and lipid metabolism, specifically triglycerides (TG) (OR: 19.959; 95% CI: 1.269-3.022; P FDR = 0.004) and glycated hemoglobin (HbA1c) (OR: 2.462; 95% CI: 1.34-4.649; P FDR = 0.007). Finally, a significant negative association was observed between PM2.5 concentrations and levels of the novel obesity-related biomarker fibroblast growth factor 21 (FGF-21) (OR: 0.148; 95% CI: 0.025-0.89; P FDR = 0.037). After adjusting for confounding factors, including external smoke exposure, physical activity, educational attainment (EA), participation in sports clubs or gym leisure activities, and Townsend deprivation index at recruitment (TDI), the MVMR analysis revealed that PM2.5 levels maintained significant associations with pancreatic fat, HbA1c, and FGF-21.

Conclusion

Our MR study demonstrates conclusively that higher PM2.5 concentrations are associated with an increased risk of obesity-related indicators such as pancreatic fat content, HbA1c, and FGF-21. The potential mechanisms require additional investigation.

The association between long-term exposure to ambient PM2.5 and high-density lipoprotein cholesterol level among chinese middle-aged and older adults

BACKGROUND

Recently, the impact of PM2.5 on human health has been intensively studied, especially the respiratory system. High-density lipoprotein plays a crucial role in removing excess cholesterol from cells and transporting it to the liver for excretion. However, the effects of ambient PM2.5 on high-density lipoprotein (HDL) level have not been further studied. Our research aims to investigate the potential association between ambient PM2.5 concentrations and high-density lipoprotein (HDL) levels within the middle-aged and older adults in China.

METHODS

We employed data from individuals aged 45 years and above who were participants in Wave 3 of the China Health and Retirement Longitudinal Study (CHARLS). The high-quality, high-resolution PM2.5 exposure concentration data for each participant were obtained from the ChinaHighAirPollutants (CHAP) dataset, while the HDL levels were derived from blood samples collected during CHARLS Wave 3. This analysis constitutes a cross-sectional study involving a total of 12,519 participants. To investigate associations, we conducted multivariate linear regression analysis, supplemented by subgroup analysis.

RESULTS

In this cross-sectional investigation, we discerned a negative association between prolonged exposure to ambient PM2.5 constituents and high-density lipoprotein (HDL) levels. The observed correlation between ambient PM2.5 and HDL levels suggests that older individuals residing in areas with elevated PM2.5 concentrations exhibit a reduction in HDL levels (Beta: -0.045; 95% CI: -0.056, -0.035; P < 0.001). Upon adjusting for age in Model I, the Beta coefficient remained consistent at -0.046 (95% CI: -0.056, -0.035; p < 0.001). This association persisted even after accounting for various potential confounding factors (Beta = -0.031, 95% CI: -0.041, -0.021, p < 0.001).

CONCLUSIONS

Our study reveals a statistically significant negative correlation between sustained exposure to higher concentrations of ambient PM2.5 and high-density lipoprotein (HDL) levels among Chinese middle-aged and older individuals.

The mediation effect of asprosin on the association between ambient air pollution and diabetes mellitus in the elderly population in Taiyuan, China

Evidence around the relationship between air pollution and the development of diabetes mellitus (DM) remains limited and inconsistent. To investigate the potential mediation effect of asprosin on the association between fine particulate matter (PM2.5), tropospheric ozone (O3) and blood glucose homeostasis. A case-control study was conducted on a total of 320 individuals aged over 60 years, including both diabetic and non-diabetic individuals, from six communities in Taiyuan, China, from July to September 2021. Generalized linear models (GLMs) suggested that short-term exposure to PM2.5 was associated with elevated fasting blood glucose (FBG), insulin resistance index (HOMA-IR), as well as reduced pancreatic β-cell function index (HOMA-β), and short-term exposure to O3 was associated with increased FBG and decreased HOMA-β in the total population and elderly diabetic patients. Mediation analysis showed that asprosin played a mediating role in the relationship of PM2.5 and O3 with FBG, with mediating ratios of 10.2% and 18.4%, respectively. Our study provides emerging evidence supporting that asprosin mediates the short-term effects of exposure to PM2.5 and O3 on elevated FBG levels in an elderly population. Additionally, the elderly who are diabetic, over 70 years, and BMI over 24 kg/m2 are more vulnerable to air pollutants and need additional protection to reduce their exposure to air pollution.

Long-term PM2.5 exposure and early-onset diabetes: Does BMI link this risk?

OBJECTIVE

Limited studies investigated the association between high-level fine particulate matter (PM2.5) pollution and early-onset diabetes, leaving the possible metabolic mechanisms unclear. We assessed the association of cumulative PM2.5 exposure with diabetes, including early-onset, in high-pollution areas of China and explored whether metabolic factors mediated this association.

METHODS

124,204 participants (≥18 years) from 121 counties in Hunan province, China, were enrolled between 2005 and 2020, with follow-up until 2021. The ground-level air pollution concentrations at each participant's residence were calculated using a high-quality dataset in China. The independent association of PM2.5 with incident diabetes and early-onset diabetes was assessed by Cox proportional hazards models. Restricted cubic splines were utilized to establish the exposure-response relationships. The role of metabolism-related mediators was estimated by mediation analysis.

RESULTS

During a median follow-up of 8.47 (IQR, 6.65-9.82) years, there were 3650 patients with new-onset diabetes. Each 1 μg/m3 increase in the level of cumulative PM2.5 exposure was positively related to an increased incidence of diabetes (HR 1.177, 95 % CI 1.172-1.181) among individuals in the PM2.5 > 50 μg/m3 group after adjusting for multiple variables. The relationship of the PM2.5 dose-response curve for diabetes was non-linear. Significant associations between PM2.5 exposure and early-onset diabetes risk were observed, with this risk showing an increase with the earlier age of early diabetes onset. Males, young individuals (≤45 years), and those with a lower body mass index (BMI <24 kg/m2) appeared to be more susceptible to diabetes. Moreover, change in BMI significantly mediated 31.06 % of the PM2.5-diabetes relationship.

CONCLUSIONS

Long-term cumulative PM2.5 exposure increased the risk of early-onset diabetes, which is partially mediated by BMI. Sustained air pollution control measures, priority protection of vulnerable individuals, and effective management of BMI should be taken to reduce the burden of diabetes.

Association of PM2.5 mass and its components with ovarian reserve in a northern peninsular province, China: The critical exposure period and components

BACKGROUND

A possible role of PM2.5 components on ovarian reserve has not been adequately unexplored.

OBJECTIVE

To evaluate the association between PM2.5 components and women' ovarian reserve over critical exposure periods in northern China, where the level of air pollution is among the nation's highest.

METHODS

We included 15,102 women with serum anti-Müllerian hormone (AMH) measurements from the Center for Reproductive Medicine of Shandong University during 2015-2019. Concentrations of PM2.5 and its five major components (0.1° × 0.1°), including sulfate, nitrate, ammonium, organic matter, and black carbon, were assigned to each residential address. Multivariable linear mixed effect models combined with constituent-residual models were performed to estimate the effect sizes of essential components over six short- to long-term exposure periods.

RESULTS

The strength of association was stronger during the process from primary to small antral follicle compared with other longer windows. For every interquartile range increase in PM2.5 mass was associated with - 8.7% (95%CI: -12.3%, -4.9%) change in AMH and the effect size was greatest for sulfate. Women with the lower level of attained education and those living inland were more susceptible compared with other population subgroups.

CONCLUSION

Exposure to specific components of air pollution during critical exposure windows is associated with a decline in ovarian reserve. These data add to the growing body of evidence that environmental factors have adverse effects on reproductive health, particularly for vulnerable population subgroups.

Air pollution and the risk of incident chronic kidney disease in patients with diabetes: An exposure-response analysis

Impact of air pollution on incident chronic kidney disease (CKD) in diabetic patients is insufficiently studied. We aimed to examine exposure-response associations of PM2.5, PM10, PM2.5-10, NO2, and NOX with incident CKD in diabetic patients in the UK. We also widened exposure level of PM2.5 and examined PM2.5-CKD association in diabetic patients across the entire range of global concentration. Based on data from UK biobank cohort, we applied Cox proportional hazards models and the shape constrained health impact function to investigate the associations between air pollutants and incident CKD in diabetic patients. Global exposure mortality model was applied to combine the PM2.5-CKD association in diabetic patients in the UK with all other published associations. Multiple air pollutants were positively associated with incident CKD in diabetic patients in the UK, with hazard ratios (HRs) of 1.034 (95 %CI: 1.015-1.053) and 1.021 (95 %CI: 1.007-1.036) for every 1 μg/m3 increase in PM2.5 and PM10 concentration, and 1.113 (95 %CI: 1.053-1.177) and 1.058 (95 %CI: 1.027-1.091) for every 10 μg/m3 increase in NO2 and NOX concentration, respectively. For PM2.5-10, associations with CKD in diabetic patients did not reach the statistical significance. Exposure-response associations with CKD in diabetic patients showed a near-linear trend for PM2.5, PM10, NO2, and NOX in the UK, whereas PM2.5-DKD associations in the globe exhibited a non-linear increasing trend. This study supports that air pollution could significantly increase the risk of CKD onset in diabetic patients.

Combined effects of organochlorine pesticides on type 2 diabetes mellitus: Insights from endocrine disrupting effects of hormones

Association between organochlorine pesticides (OCPs) exposure and type 2 diabetes mellitus (T2DM) remains contradictory, and the evidence is mostly focused on a single exposure. Here, we assessed the associations between individual and combined OCPs exposure and T2DM, and explored the underlying mechanism of sex hormones and the methylation levels of sex hormone receptors in above associations. A case-control study with 1812 participants was performed. Gas chromatography mass spectrometry, liquid chromatography-tandem mass spectrometry, and pyrosequencing were used to measure plasma OCPs, serum sex hormones, and whole blood methylation levels of sex hormone receptors, respectively. Generalized linear models were used to analyze the relationships between OCPs, sex hormones, the methylation levels of sex hormone receptors, and T2DM. Quantile based g-computation (QGC) and Bayesian Kernel Machine Regression (BKMR) were employed to assess the combined OCPs exposure. The roles of sex hormones and the methylation levels of their receptors were evaluated by moderating mediation models. After adjusting for covariates, each unit (2.718 ng/ml) increase in p,p'-DDE was associated with a higher risk of T2DM in males (odds ratio (OR) and 95% confidence interval (CI): 1.066 (1.023, 1.112)). QGC and BKMR showed a positive combined effect in the associations of OCPs mixtures on T2DM among premenopausal females, and positive effects but not statistically significant among males and postmenopausal females. p,p'-DDE was the largest contributor for the positive associations. Furthermore, testosterone mediated 21.149% of the associations of p,p'-DDE with T2DM moderated by the androgen receptor methylation (ARm) located in CpG island 1. Individual and mixtures of OCPs exposure were positively linked to elevated risk of T2DM. Testosterone and ARm may participate in the related processes of OCPs with T2DM, providing new insights into the adverse endocrine effects caused by OCPs and specific pathways for the etiology and control of diabetes.

Associations between air pollution, residential greenness, and glycated hemoglobin (HbA1c) in three prospective cohorts of U.S. adults

BACKGROUND

While studies suggest impacts of individual environmental exposures on type 2 diabetes (T2D) risk, mechanisms remain poorly characterized. Glycated hemoglobin (HbA1c) is a biomarker of glycemia and diagnostic criterion for prediabetes and T2D. We explored associations between multiple environmental exposures and HbA1c in non-diabetic adults.

METHODS

HbA1c was assessed once in 12,315 women and men in three U.S.-based prospective cohorts: the Nurses' Health Study (NHS), Nurses' Health Study II (NHSII), and Health Professionals Follow-up Study (HPFS). Residential greenness within 270 m and 1,230 m (normalized difference vegetation index, NDVI) was obtained from Landsat. Fine particulate matter (PM2.5) and nitrogen dioxide (NO2) were estimated from nationwide spatiotemporal models. Three-month and one-year averages prior to blood draw were assigned to participants' addresses. We assessed associations between single exposure, multi-exposure, and component scores from Principal Components Analysis (PCA) and HbA1c. Fully-adjusted models built on basic models of age and year at blood draw, BMI, alcohol use, and neighborhood socioeconomic status (nSES) to include diet quality, race, family history, smoking status, postmenopausal hormone use, population density, and season. We assessed interactions between environmental exposures, and effect modification by population density, nSES, and sex.

RESULTS

Based on HbA1c, 19% of participants had prediabetes. In single exposure fully-adjusted models, an IQR (0.14) higher 1-year 1,230 m NDVI was associated with a 0.27% (95% CI: 0.05%, 0.49%) lower HbA1c. In basic component score models, a SD increase in Component 1 (high loadings for 1-year NDVI) was associated with a 0.19% (95% CI: 0.04%, 0.34%) lower HbA1c. CI's crossed the null in multi-exposure and fully-adjusted component score models. There was little evidence of associations between air pollution and HbA1c, and no evidence of effect modification.

CONCLUSIONS

Among non-diabetic adults, environmental exposures were not consistently associated with HbA1c. More work is needed to elucidate biological pathways between the environment and prediabetes.

Impact of environmental factors on diabetes mortality: A comparison between inland and coastal areas

BACKGROUND

Diabetes mortality varies between coastal and inland areas in Shandong Province, China. However, evidence about the reasons for this disparity is limited. We assume that distinct environmental conditions may contribute to the disparities in diabetes mortality patterns between coastal and inland areas.

METHOD

Qingdao and Jinan were selected as typical coastal and inland cities in Shandong Province, respectively, with similar socioeconomic but different environmental characteristics. Data on diabetes deaths and environmental factors (i.e., temperature, relative humidity and air pollution particles with a diameter of 2.5 μm or less (PM2.5)) were collected from 2013 to 2020. Spatial kriging methods were used to estimate the aggregated diabetes mortality at the city level. A distributed lag non-linear model (DLNM) was used to quantify the possible cumulative and non-cumulative associations between environmental factors and diabetes mortality by age, sex and location.

RESULTS

In the coastal city (Qingdao), the maximum cumulative relative risks (RRs) of temperature and PM2.5 associated with diabetes deaths were 2.54 (95 % confidence interval (CI): 1.25-5.15), and 1.17 (95 % CI: 1.01-1.37) respectively, at lag 1 week. In the inland city (Jinan), only temperature exhibited significant cumulative associations with diabetes deaths (RR = 1.54, 95 % CI: 1.07-2.23 at 29 °C). Lower relative humidity (22 %-45 %) had a lag-specific association with diabetes deaths in inland areas at lag 3 weeks (RR = 1.33, 95 % CI: 1.03-1.70 at 22 %).

CONCLUSION

Despite the lower PM2.5 concentrations in the coastal location, diabetes mortality exhibited stronger links to environmental variables in the coastal city than in the inland city. These findings suggest that the control of air pollution could decrease the mortality burden of diabetes, even in the region with relatively good air quality. Additionally, the spatial estimation method is recommended to identify associations between environmental factors and diseases in studies with limited data.

Global burden of type 2 diabetes attributable to non-high body mass index from 1990 to 2019

BACKGROUND

The prevalence of type 2 diabetes mellitus (T2DM) currently was increased in some countries of the world like China. However, the epidemiological trends of T2DM attributable to non-high body mass index (BMI) remain unclear. Thus, we aimed to describe the burden of T2DM attributable to non-high BMI.

METHODS

To estimate the burden of T2DM attributable to non-high BMI, data from the Global Burden of Disease Study 2019 were used to calculate the deaths and disability-adjusted life years (DALYs) by age, sex, year, and location. The estimated annual percentage change (EAPC) was applied in the analysis of temporal trends in T2DM from 1990 to 2019.

RESULTS

Globally in 2019, the number of death cases and DALYs of T2DM attributable to non-high BMI accounted for 57.9% and 48.1% of T2DM-death from all risks, respectively. Asia accounted for 59.5% and 63.6% of the global non-high-BMI-related death cases and DALYs of T2DM in 2019, respectively. From 1990 to 2019, regions in the low-income experienced a rise in DALYs attributable to non-high BMI. As compared to other age groups, older participants had higher deaths and DALYs of T2DM attributable to non-high BMI. The death and DALY rates of T2DM due to non-high BMI were higher in males and people in regions with low socio-demographic index (SDI) countries.

CONCLUSIONS

The burden of T2DM attributable to non-high BMI is higher in the elderly and in people in regions with low- and middle-SDI, resulting in a substantial burden on human health and the social cost of healthcare.