Evaluation of associations between estimates of particulate matter exposure and new onset type 2 diabetes in the REGARDS cohort

Small-area geographical variation in the prevalence of diabetes amongst Australian youth aged <20 years in 2021

OBJECTIVES

To characterise small-area geographical variation in the prevalence of diabetes in Australian youth.

METHODS

A combined statistical reconstruction and small-area estimation algorithm was applied to privacy-modulated data from the 2021 Australian Census. The census instrument and reconstruction accuracy was examined by comparisons against a hospital-based register and community register. Diabetes prevalence maps were created from the small-area estimates.

RESULTS

The median and interquartile range of estimated diabetes prevalence by small-area unit under our geospatial smoothing model were 1.76 [1.49-1.97] cases per 1000 population for those aged 0-14 years and 5.2 [4.4-5.9] cases per 1000 population for those aged 15-19 years old. Concentrations of elevated prevalence were identified in the vicinities of regional towns across South-East Queensland, regional New South Wales and regional Victoria. Across each of Australia's five largest cities a gradient of decreasing youth diabetes prevalence from the outer suburbs to the urban centre was identified.

CONCLUSION

Diabetes burden is systematically higher among rural and peri-urban resident youth in Australia compared with their urban counterparts.

IMPLICATIONS FOR PUBLIC HEALTH

Hotspots of prevalence in regional areas deserve attention from public health authorities.

Ambient air fine particulate matter (PM10 and PM2.5) and risk of type 2 diabetes mellitus and mechanisms of effects: a global systematic review and meta-analysis

Type 2 diabetes causes early mortality worldwide. Air pollution's relationship with T2DM has been studied. The association between them is unclear because of inconsistent outcomes. Studies on this topic have been published since 2019, but not thoroughly evaluated. We conducted a systematic review and meta-analysis using relevant data. The study protocol was registered in PROSPIRO and conducted according to MOOSE guidelines. In total, 4510 manuscripts were found. After screening, 46 studies were assessed using the OHAT tool. This meta-analysis evaluated fine particles with T2DM using OR and HR effect estimates. Evaluation of publication bias was conducted by Egger's test, Begg's test, and funnel plot analysis. A sensitivity analysis was conducted to evaluate the influence of several studies on the total estimations. Results show a significant association between PM2.5 and PM10 exposure and T2DM. Long-term exposure to fine air particles may increase the prevalence and incidence of T2DM. Fine air pollution increases the chance of developing T2DM mainly via systemic inflammation, oxidative stress, and endoplasmic reticulum stress.

Associations of insulin sensitivity and immune inflammatory responses with child blood lead (Pb) and PM2.5 exposure at an e-waste recycling area during the COVID-19 lockdown

Fine particular matter (PM2.5) and lead (Pb) exposure can induce insulin resistance, elevating the likelihood of diabetes onset. Nonetheless, the underlying mechanism remains ambiguous. Consequently, we assessed the association of PM2.5 and Pb exposure with insulin resistance and inflammation biomarkers in children. A total of 235 children aged 3-7 years in a kindergarten in e-waste recycling areas were enrolled before and during the Corona Virus Disease 2019 (COVID-19) lockdown. Daily PM2.5 data was collected and used to calculate the individual PM2.5 daily exposure dose (DED-PM2.5). Concentrations of whole blood Pb, fasting blood glucose, serum insulin, and high mobility group box 1 (HMGB1) in serum were measured. Compared with that before COVID-19, the COVID-19 lockdown group had lower DED-PM2.5 and blood Pb, higher serum HMGB1, and lower blood glucose and homeostasis model assessment of insulin resistance (HOMA-IR) index. Decreased DED-PM2.5 and blood Pb levels were linked to decreased levels of fasting blood glucose and increased serum HMGB1 in all children. Increased serum HMGB1 levels were linked to reduced levels of blood glucose and HOMA-IR. Due to the implementation of COVID-19 prevention and control measures, e-waste dismantling activities and exposure levels of PM2.5 and Pb declined, which probably reduced the association of PM2.5 and Pb on insulin sensitivity and diabetes risk, but a high level of risk of chronic low-grade inflammation remained. Our findings add new evidence for the associations among PM2.5 and Pb exposure, systemic inflammation and insulin resistance, which could be a possible explanation for diabetes related to environmental exposure.

County Rurality and Incidence and Prevalence of Diagnosed Diabetes in the United States

OBJECTIVE

To examine differences in the incidence and prevalence of diagnosed diabetes by county rurality.

PATIENTS AND METHODS

This observational, cross-sectional study used US Centers for Disease Control and Prevention data from 2004 through 2019 for county estimates of incidence and prevalence of diagnosed diabetes. County rurality was based on 6 levels (large central metro counties [most urban] to noncore counties [most rural]). Weighted least squares regression was used to relate rurality with diabetes incidence rates (IRs; per 1000 adults) and prevalence (percentage) in adults aged 20 years or older after adjusting for county-level sociodemographic factors (eg, food environment, health care professionals, inactivity, obesity).

RESULTS

Overall, in 3148 counties and county equivalents, the crude IR and prevalence of diabetes were highest in noncore counties. In age and sex ratio-adjusted models, the IR of diabetes increased monotonically with increasing rurality (P<.001), whereas prevalence had a weak, nonmonotonic but statistically significant increase (P=.002). Further adjustment for sociodemographic factors including food environment, health care professionals, inactivity, and obesity attenuated differences in incidence across rurality levels, and reversed the pattern for prevalence (prevalence ratios [vs large central metro] ranged from 0.98 [95% CI, 0.97 to 0.99] for large fringe metro to 0.94 [95% CI, 0.93 to 0.96] for noncore). In region-stratified analyses adjusted for sociodemographic factors including inactivity and obesity, increasing rurality was inversely associated with incidence in the Midwest and West only and inversely associated with prevalence in all regions.

CONCLUSION

The crude incidence and prevalence of diagnosed diabetes increased with increasing county rurality. After accounting for sociodemographic factors including food environment, health care professionals, inactivity, and obesity, county rurality showed no association with incidence and an inverse association with prevalence. Therefore, interventions targeting modifiable sociodemographic factors may reduce diabetes disparities by region and rurality.

Associations between PM2.5 and O3 exposures and new onset type 2 diabetes in regional and national samples in the United States

BACKGROUND

Exposure to particulate matter ≤2.5 μm in diameter (PM2.5) and ozone (O3) has been linked to numerous harmful health outcomes. While epidemiologic evidence has suggested a positive association with type 2 diabetes (T2D), there is heterogeneity in findings. We evaluated exposures to PM2.5 and O3 across three large samples in the US using a harmonized approach for exposure assignment and covariate adjustment.

METHODS

Data were obtained from the Veterans Administration Diabetes Risk (VADR) cohort (electronic health records [EHRs]), the Reasons for Geographic and Racial Disparities in Stroke (REGARDS) cohort (primary data collection), and the Geisinger health system (EHRs), and reflect the years 2003-2016 (REGARDS) and 2008-2016 (VADR and Geisinger). New onset T2D was ascertained using EHR information on medication orders, laboratory results, and T2D diagnoses (VADR and Geisinger) or report of T2D medication or diagnosis and/or elevated blood glucose levels (REGARDS). Exposure was assigned using pollutant annual averages from the Downscaler model. Models stratified by community type (higher density urban, lower density urban, suburban/small town, or rural census tracts) evaluated likelihood of new onset T2D in each study sample in single- and two-pollutant models of PM2.5 and O3.

RESULTS

In two pollutant models, associations of PM2.5, and new onset T2D were null in the REGARDS cohort except for in suburban/small town community types in models that also adjusted for NSEE, with an odds ratio (95% CI) of 1.51 (1.01, 2.25) per 5 μg/m3 of PM2.5. Results in the Geisinger sample were null. VADR sample results evidenced nonlinear associations for both pollutants; the shape of the association was dependent on community type.

CONCLUSIONS

Associations between PM2.5, O3 and new onset T2D differed across three large study samples in the US. None of the results from any of the three study populations found strong and clear positive associations.

Risk of type 2 diabetes after diagnosed gestational diabetes is enhanced by exposure to PM2.5

BACKGROUND

Air pollution and gestational diabetes mellitus (GDM) are both associated with increased diabetes mellitus (DM) occurrence. However, whether air pollutants modify the effects of GDM on the occurrence of DM has been unknown. This study aims to determine whether the effect of GDM on DM development can be modified by exposure to ambient air pollutants.

METHODS

Women with one singleton birth delivery during 2004-14 according to the Taiwan Birth Certificate Database (TBCD) were included as the study cohort. Those newly diagnosed as having DM 1 year or later after childbirth were identified as DM cases. Controls were selected among women without DM diagnosis during follow-up. Personal residence was geocoded and linked with interpolated concentrations of air pollutants into township levels. Conditional logistic regression was used to determine the odds ratio (OR) of pollutant exposure and GDM, adjusting for age, smoking and meteorological variables.

RESULTS

There were 9846 women who were newly diagnosed as having DM over a mean follow-up period of 10.2 years. We involved them and the 10-fold matching controls involved in our final analysis. The OR (odds ratio) (95% confidence interval, 95% CI) of DM occurrence per interquartile range increased in particulate matter (PM) smaller than or equal to 2.5 µm (PM2.5) and ozone (O3) was 1.31 (1.22-1.41) and 1.20 (1.16-1.25), respectively. The effects of PM exposure on DM development were significantly higher in the GDM group (OR: 2.46, 95% CI: 1.84-3.30) than in the non-GDM group (OR: 1.30, 95% CI: 1.21-1.40).

CONCLUSIONS

Exposure to high levels of PM2.5 and O3 elevates the risk of DM. GDM acted synergistically in DM development with exposure to PM2.5 but not with that to O3.

Ambient air pollution associated with incidence and dynamic progression of type 2 diabetes: a trajectory analysis of a population-based cohort

BACKGROUND

Though the association between air pollution and incident type 2 diabetes (T2D) has been well documented, evidence on the association with development of subsequent diabetes complications and post-diabetes mortality is scarce. We investigate whether air pollution is associated with different progressions and outcomes of T2D.

METHODS

Based on the UK Biobank, 398,993 participants free of diabetes and diabetes-related events at recruitment were included in this analysis. Exposures to particulate matter with a diameter ≤ 10 μm (PM₁₀), PM_2.5, nitrogen oxides (NO_x), and NO₂ for each transition stage were estimated at each participant's residential addresses using data from the UK's Department for Environment, Food and Rural Affairs. The outcomes were incident T2D, diabetes complications (diabetic kidney disease, diabetic eye disease, diabetic neuropathy disease, peripheral vascular disease, cardiovascular events, and metabolic events), all-cause mortality, and cause-specific mortality. Multi-state model was used to analyze the impact of air pollution on different progressions of T2D. Cumulative transition probabilities of different stages of T2D under different air pollution levels were estimated.

RESULTS

During the 12-year follow-up, 13,393 incident T2D patients were identified, of whom, 3791 developed diabetes complications and 1335 died. We observed that air pollution was associated with different progression stages of T2D with different magnitudes. In a multivariate model, the hazard ratios [95% confidence interval (CI)] per interquartile range elevation in PM_2.5 were 1.63 (1.59, 1.67) and 1.08 (1.03, 1.13) for transitions from healthy to T2D and from T2D to complications, and 1.50 (1.47, 1.53), 1.49 (1.36, 1.64), and 1.54 (1.35, 1.76) for mortality risk from baseline, T2D, and diabetes complications, respectively. Generally, we observed stronger estimates of four air pollutants on transition from baseline to incident T2D than those on other transitions. Moreover, we found significant associations between four air pollutants and mortality risk due to cancer and cardiovascular diseases from T2D or diabetes complications. The cumulative transition probability was generally higher among those with higher levels of air pollution exposure.

CONCLUSIONS

This study indicates that ambient air pollution exposure may contribute to increased risk of incidence and progressions of T2D, but to diverse extents for different progressions.