Association of long-term air pollution exposure with the risk of prediabetes and diabetes: Systematic perspective from inflammatory mechanisms, glucose homeostasis pathway to preventive strategies

Long-Term Exposure to Air Pollution and Incidence of Type 2 Diabetes in the Nurses' Health Study and Nurses' Health Study II

BACKGROUND

Research has detected associations between air pollution exposure and type 2 diabetes (T2DM), but findings from large cohort studies are needed to ascertain the most influential pollutants, susceptible subpopulations, and low-level exposure associations. Our aim was to prospectively evaluate the association between long-term exposure to fine particulate matter < 2.5 μ m in aerodynamic diameter (PM 2.5 ) and nitrogen dioxide (NO 2 ) and T2DM incidence in the Nurses' Health Study (NHS) and Nurses' Health Study II (NHSII) cohorts of US women.

METHODS

Monthly PM 2.5 and NO 2 exposures were predicted from spatiotemporal models and linked to participants' residential addresses. We used Cox proportional hazards models to assess the association between 24-month moving average PM 2.5 and NO 2 exposure and self-reported, clinician-diagnosed T2DM from 1992-2019. We adjusted for time-varying lifestyle factors, reproductive hormonal factors, and individual and neighborhood socioeconomic status (SES). Results were meta-analyzed. We evaluated whether relationships persisted at levels below the current US EPA National Ambient Air Quality Standards (NAAQS). Lastly, we examined multiplicative and additive interactions by body mass index (BMI), smoking status, physical activity, neighborhood SES, and region.

RESULTS

Over follow-up, there were 19,083 incident T2DM cases among the 208,733 women in NHS and NHSII. In fully adjusted single-pollutant models, the hazard ratio (HR) for an interquartile range (IQR) (IQR = 4.9   μ g / m 3 ) higher 24-month average PM 2.5 exposure was 1.05 [95% confidence interval (CI): 1.02, 1.08] for incident T2DM. The HR for an IQR (7.3 ppb ) higher NO 2 exposure was 1.05 (95% CI: 1.01, 1.09). Both associations were robust to co-adjustment. Associations remained stable when restricting to PM 2.5 levels below the NAAQS as compared to the full dataset. Stronger associations were observed in individuals who had a BMI ≥ 30 , were physically active, and resided in the Northeast.

CONCLUSIONS

Our results showed a positive association between T2DM and long-term exposure to PM 2.5 and NO 2 , persisting even at levels below the current EPA NAAQS. https://doi.org/10.1289/EHP15673.

Impact of the Wood-Burning Justa Cookstove on Glycated Hemoglobin (HbA1c): A Stepped-Wedge Randomized Trial in Rural Honduras

BACKGROUND

Type 2 diabetes is a rapidly growing global health challenge in low- and middle-income countries (LMICs), and evidence suggests that air pollution exposure contributes. Household air pollution from burning solid fuels for cooking is a major burden in LMICs, but studies demonstrating associations between reductions in household air pollution and improvements in HbA1c, a biomarker of diabetes risk, are lacking. We previously reported substantial reductions in fine particulate matter with an aerodynamic diameter ≤ 2.5 μ m (PM 2.5 ) and black carbon concentrations following an intervention in rural Honduras with the Justa cookstove, a wood-burning stove with an engineered combustion chamber and chimney.

OBJECTIVE

In a stepped-wedge randomized controlled trial among 230 Honduran women using traditional wood-burning stoves at baseline, we evaluated the effect of the Justa intervention on HbA1c and characterized the longitudinal associations between air pollution exposures and HbA1c.

METHODS

At each of six visits over 3 y, we measured 24-h PM 2.5 and black carbon concentrations, and finger-stick HbA1c levels. We used linear mixed models in intent-to-treat (condition by assigned stove type), exposure-response (using 24-h measures and modeled estimates of long-term exposures), and "per protocol" self-reported stove use analyses.

RESULTS

HbA1c was reduced for the Justa condition in comparison with the traditional stove condition, but estimates were small and not statistically significant [- 0.03 percentage points, 95% confidence interval (CI): - 0.13 , 0.07, n = 1,208 observations]. A slightly stronger effect was observed when using self-reported stove use in per protocol analyses. Exposure-response analyses demonstrated positive associations between HbA1c and air pollution [e.g., HbA1c was 0.22 percentage points higher (95% CI: 0.13, 0.30) per log-unit higher long-term average personal PM 2.5 ].

DISCUSSION

Our study provides novel evidence of exposure-response associations between household air pollution and HbA1c within a randomized cookstove trial, contributing to the evidence base necessary to support clean cooking policy initiatives. https://doi.org/10.1289/EHP15095.

Association Between Area-Level Deprivation and Cardio-Metabolic Risk Factors Among the Adult Population in Russia

BACKGROUND

Cardiovascular diseases have been the leading cause of death in the Russian population to date.

METHODS

Using generalized estimating equations, we examined the links of area-level socio-economic and environmental deprivation with cardiovascular disease risk factors in the adult population as a whole, as well as in men and women separately.

RESULTS

People living in more economically deprived areas had 61 percent higher odds of being obese (Q4: odds ratio (OR) 1.61; 95% confidence interval (CI): 1.20-2.16), 2.32 times higher odds of having chronic kidney disease (OR 2.32; 95% CI: 1.56-3.44), up to 57 percent higher odds of having hyperuricemia (OR 1.57; 95% CI: 1.31-1.88), and up to 80 percent higher odds of having diabetes mellitus (OR 1.80; 95% CI: 1.71-1.89), compared to those in the least deprived areas. Individuals living in the most environmentally deprived areas were associated with higher odds of hypertension (OR 1.37; 95% CI: 1.19-1.57) and these associations persisted for both when considering men (OR 1.38; 95% CI: 1.19-1.61) and women (OR 1.37; 95% CI: 1.14-1.65) separately.

CONCLUSIONS

This is the first study to examine the relationship of area characteristics with cardio-metabolic risk factors such as elevated blood pressure and prediabetes, taking into account individual characteristics among the Russian population.

Air Pollution and Diabetes Mellitus: Association and Validation in a Desert Area in China

CONTEXT

Despite the growing evidence pointing to the detrimental effects of air pollution on diabetes mellitus (DM), the relationship remains poorly explored, especially in desert-adjacent areas characterized by high aridity and pollution.

OBJECTIVE

We conducted a cross-sectional study with health examination data from more than 2.9 million adults in 2 regions situated in the southern part of the Taklamakan Desert, China.

METHODS

We assessed 3-year average concentrations (2018-2020) of particulate matter (PM1, PM2.5, and PM10), carbon monoxide (CO), nitrogen dioxide (NO2), and sulfur dioxide (SO2) through a space-time extra-trees model. After adjusting for various covariates, we employed generalized linear mixed models to evaluate the association between exposure to air pollutants and DM.

RESULTS

The odds ratios for DM associated with a 10 µg/m3 increase in PM1, PM2.5, PM10, CO, and NO2 were 1.898 (95% CI, 1.741-2.070), 1.07 (95% CI, 1.053-1.086), 1.013 (95% CI, 1.008-1.018), 1.009 (95% CI, 1.007-1.011), and 1.337 (95% CI, 1.234-1.449), respectively. Notably, men, individuals aged 50 years or older, those with lower educational attainment, nonsmokers, and those not engaging in physical exercise appeared to be more susceptible to the adverse effects of air pollution. Multiple sensitivity analyses confirmed the stability of these findings.

CONCLUSION

Our study provides robust evidence of a correlation between prolonged exposure to air pollution and the prevalence of DM among individuals living in desert-adjacent areas. This research contributes to the expanding knowledge on the relationship between air pollution exposure and DM prevalence in desert-adjacent areas.

Life Course Associations Between Ambient Fine Particulate Matter and the Prevalence of Prediabetes and Diabetes: A Longitudinal Cohort Study in Taiwan and Hong Kong

OBJECTIVE

Both air pollution and diabetes are key urban challenges. The association between particulate matter with a diameter of <2.5 μm (PM2.5) exposure and prediabetes/diabetes in adults is well documented, but the health effects of life course exposure remain unclear. This study evaluated the impact of PM2.5 exposure throughout various life stages on the prevalence of prediabetes/diabetes in adulthood.

RESEARCH DESIGN AND METHODS

We included 4,551 individuals with 19,593 medical visits from two open cohorts in Taiwan and Hong Kong between 2000 and 2018. Ambient PM2.5 exposure was assessed using a satellite-based model, delivering a 2-year average exposure at a resolution of 1 km2. Logistic mixed-effects models were used to investigate longitudinal associations between PM2.5 exposure and the prevalence of prediabetes/diabetes. Life course models were used to examine the impact of PM2.5 exposure at different life stages on prediabetes/diabetes in adulthood.

RESULTS

Over an average follow-up period of 9.93 years, 1,660 individuals with prediabetes/diabetes were observed. For the longitudinal association, every 10 μg/m3 increase in PM2.5 was associated with an increased odds of having prediabetes/diabetes (odds ratio 1.32, 95% CI 1.13, 1.54). The odds of adulthood prediabetes/diabetes increased by 15%, 18%, and 29% for each 10 μg/m3 increase in PM2.5 exposure during school age, adolescence, and adulthood, respectively.

CONCLUSIONS

Our findings suggest a link between PM2.5 exposure during each life stage and the prevalence of prediabetes/diabetes in adulthood, with the health impacts of exposure during adulthood being slightly greater. This study underscores the need for life course air pollution control strategies to mitigate the substantial disease burden of diabetes.

Disturbed glucose homeostasis and its increased allostatic load in response to individual, joint and fluctuating air pollutants exposure: Evidence from a longitudinal study in prediabetes

We investigated the effect of individual, joint and fluctuating exposure to air pollution (PM2.5, BC, NO3-, NH4+, OM, SO42-, PM10, NO2, SO2, O3) on glucose metabolisms among prediabetes, and simultaneously explored the modifying effect of lifestyle. We conducted a longitudinal study among prediabetes during 2018-2022. Exposure windows within 60-days moving averages and their variabilities were calculated. FBG, insulin, HOMA-IR, HOMA-B, triglyceride glucose index (TyG), glucose insulin ratio (GI) and allostatic load of glucose homeostasis system (AL-GHS) was included. Linear mixed-effects model and BKMR were adopted to investigate the individual and overall effects, respectively. We also explored the preventive role of lifestyle. Individual air pollutant was associated with increased FBG, insulin, HOMA-IR, HOMA-B, TyG, and decreased GI. People with FBG ≥6.1 mmol/L were more susceptible. Air pollutants mixture were only associated with increased HOMA-B, and constituents have the highest group-PIP. Air pollutants variation also exert harmful effect. We observed similar diabetic effect on AL-GHS. Finally, the diabetic effect of air pollutants disappeared if participants adopt a favorable lifestyle. Our findings highlighted the importance of comprehensively assessing multiple air pollutants and their variations, focusing on metabolic health status in the early prevention of T2D, and adopting healthy lifestyle to mitigate such harmful effect.

Exposure to ambient air pollution mixture and senescence-associated secretory phenotype proteins among middle-aged and older women

Our study aimed to investigate the impact of environmental exposures, such as ambient air pollutants, on systemic inflammation and cellular senescence in middle-aged and older women. We utilized epidemiological data linked with exposure data of six air pollutants (particulate matters [PM10, PM2.5], sulphur dioxide [SO2], nitrogen dioxide [NO2], carbon monoxide [CO], and ozone [O3]) and blood samples of 380 peri- and postmenopausal women participants of the Korean Genome and Epidemiology Study. We measured blood high-sensitivity C-reactive protein (hsCRP) and age-related 27 circulatory senescence-associated secretory phenotypes (SASP) produced by senescent cells. We employed single exposure models to explore the general pattern of association between air pollution exposure and proteomic markers. Using quantile g-computation models, we assessed the association of six air pollutant mixtures with hsCRP and SASP proteins. In single-exposure, single-period models, nine out of the 27 SASP proteins including IFN-γ (β = 0.04, 95% CI: 0.01, 0.07 per interquartile range-increase), IL-8 (0.15, 95% CI: 0.09, 0.20), and MIP1α (0.11, 95% CI: 0.04, 0.18) were positively associated with the average level of O3 over one week. Among the age-related SASP proteins, IFN-γ (0.11, 95% CI: 0.03, 0.20) and IL-8 (0.22, 95% CI: 0.05, 0.39) were positively associated with exposure to air pollutant mixture over one week. The MIP1β was higher with an increasing one-month average concentration of the air pollutant mixture (0.11, 95% CI: 0.00, 0.21). The IL-8 showed consistently positive association with the ambient air pollutant mixture for the exposure periods ranging from one week to one year. O3 predominantly showed positive weights in the associations between air pollutant mixtures and IL-8. These findings underscore the potential of proteomic indicators as markers for biological aging attributed to short-term air pollution exposure.

Association Between Long-Term Exposure to Ambient Air Pollution and Fasting Blood Glucose: A Systematic Review and Meta-Analysis

Increasing studies are indicating a potential association between ambient air pollution exposure and fasting blood glucose (FBG), an indicator of prediabetes and diabetes. However, there is inconsistency within the existing literature. The aim of this study was to summarize the associations of exposures to particulate matters (PMs) (with aerodynamic diameters of ≤1 μm (PM1), ≤2.5 μm (PM2.5), and ≤10 μm (PM10), respectively) and gaseous pollutants (sulfur dioxide (SO2), nitrogen dioxide (NO2) and ozone (O3)) with FBG based on the existing epidemiological research for a better understanding of the relationship between air pollution and diabetes. Up to 2 July 2024, we performed a comprehensive literature retrieval from various electronic databases (PubMed, Web of Science, Scopus, and Embase). Random-effect and fixed-effect models were utilized to estimate the pooled percent changes (%) and 95% confidence intervals (CIs). Then, subgroup meta-analyses and meta-regression analyses were applied to recognize the sources of heterogeneity. There were 33 studies eligible for the meta-analysis. The results showed that for each 10 μg/m3 increase in long-term exposures to PM1, PM2.5, PM10, and SO2, the pooled percent changes in FBG were 2.24% (95% CI: 0.54%, 3.96%), 1.72% (95% CI: 0.93%, 2.25%), 1.19% (95% CI: 0.41%, 1.97%), and 0.52% (95% CI:0.40%, 0.63%), respectively. Long-term exposures to ambient NO2 and O3 were not related to alterations in FBG. In conclusion, our findings support that long-term exposures to PMs of various aerodynamic diameters and SO2 are associated with significantly elevated FBG levels.

Association between PM2.5 constituents and cardiometabolic risk factors: Exploring individual and combined effects, and mediating inflammation

BACKGROUND

The individual and combined effects of PM2.5 constituents on cardiometabolic risk factors are sparsely investigated. Besides, the key cardiometabolic risk factor that PM2.5 constituents targeted and the biological mechanisms remain unclear.

METHOD

A multistage, stratified cluster sampling survey was conducted in two typically air-polluted Chinese cities. The PM2.5 and its constituents including sulfate, nitrate, ammonium, organic matter, and black carbon were predicted using a machine learning model. Twenty biomarkers in three category were simultaneously adopted as cardiometabolic risk factors. We explored the individual and mixture association of long-term PM2.5 constituents with these markers using generalized additive model and quantile-based g-computation, respectively. To minimize potential confounding effects, we accounted for covariates including demographic, lifestyle, meteorological, temporal trends, and disease-related information. We further used ROC curve and mediation analysis to identify the key subclinical indicators and explore whether inflammatory mediators mediate such association, respectively.

RESULT

PM2.5 constituents was positively correlated with HOMA-B, TC, TG, LDL-C and LCI, and negatively correlated with PP and RC. Further, PM2.5 constituent mixture was positive associated with DBP, MAP, HbA1c, HOMA-B, AC, CRI-1 and CRI-2, and negative associated with PP and HDL-C. The ROC analysis further reveals that multiple cardiometabolic risk factors can collectively discriminate exposure to PM2.5 constituents (AUC>0.9), among which PP and CRI-2 as individual indicators exhibit better identifiable performance for nitrate and ammonium (AUC>0.75). We also found that multiple blood lipid indicators may be affected by PM2.5 and its constituents, possibly mediated through complement C3 or hsCRP.

CONCLUSION

Our study suggested associations of individual and combined PM2.5 constituents exposure with cardiometabolic risk factors. PP and CRI-2 were the targeted markers of long-term exposure to nitrate and ammonium. Inflammation may serve as a mediating factor between PM2.5 constituents and dyslipidemia, which enhance current understanding of potential pathways for PM2.5-induced preclinical cardiovascular responses.

Associations of Long-Term Exposure to Fine Particulate Constituents With Cardiovascular Diseases and Underlying Metabolic Mediations: A Prospective Population-Based Cohort in Southwest China

BACKGROUND

The health effects of particulate matter with an aerodynamic diameter ≤2.5 μm (PM2.5) might differ depending on compositional variations. Little is known about the joint effect of PM2.5 constituents on metabolic syndrome and cardiovascular disease (CVD). This study aims to evaluate the combined associations of PM2.5 components with CVD, identify the most detrimental constituent, and further quantify the mediation effect of metabolic syndrome.

METHODS AND RESULTS

A total of 14 427 adults were included in a cohort study in Sichuan, China, and were followed to obtain the diagnosis of CVD until 2021. Metabolic syndrome was defined by the simultaneous occurrence of multiple metabolic disorders measured at baseline. The concentrations of PM2.5 chemical constituents within a 1-km2 grid were derived based on satellite- and ground-based detection methods. Cox proportional hazard models showed that black carbon, organic matter (OM), nitrate, ammonium, chloride, and sulfate were positively associated with CVD risks, with hazard ratios (HRs) ranging from 1.24 to 2.11 (all P<0.05). Quantile g-computation showed positive associations with 4 types of CVD risks (HRs ranging from 1.48 to 2.25, all P<0.05). OM and chloride had maximum weights for CVD risks. Causal mediation analysis showed that the positive association of OM with total CVD was mediated by metabolic syndrome, with a mediation proportion of 1.3% (all P<0.05).

CONCLUSIONS

Long-term exposure to PM2.5 chemical constituents is positively associated with CVD risks. OM and chloride appear to play the most responsible role in the positive associations between PM2.5 and CVD. OM is probably associated with CVD through metabolic-related pathways.

Metabolic Alteration Bridging the Prediabetic State and Colorectal Cancer

Prediabetes and colorectal cancer (CRC) represent compelling health burdens responsible for high mortality and morbidity rates, sharing several modifiable risk factors. It has been hypothesized that metabolic abnormalities linking prediabetes and CRC are hyperglycemia, hyperinsulinemia, and adipokines imbalance. The chronic stimulation related to these metabolic signatures can favor CRC onset and development, as well as negatively influence CRC prognosis. To date, the growing burden of prediabetes and CRC has generated a global interest in defining their epidemiological and molecular relationships. Therefore, a deeper knowledge of the metabolic impairment determinants is compelling to identify the pathological mechanisms promoting the onset of prediabetes and CRC. In this scenario, this review aims to provide a comprehensive overview on the metabolic alterations of prediabetes and CRC as well as an overview of recent preventive and therapeutic approaches for both diseases, focusing on the role of the metabolic state as a pivotal contributor to consider for the development of future preventive and therapeutic strategies.

Green space and its types can attenuate the associations of PM2.5 and its components with prediabetes and diabetes-- a multicenter cross-sectional study from eastern China

BACKGROUND

The effect of fine particulate matter (PM2.5) components on prediabetes and diabetes is of concern, but the evidence is limited and the specific role of different green space types remains unclear. This study aims to investigate the relationship of PM2.5 and its components with prediabetes and diabetes as well as the potential health benefits of different types and combinations of green spaces.

METHODS

A multicenter cross-sectional study was conducted in eastern China by using a multi-stage random sampling method. Health screening and questionnaires for 98,091 participants were performed during 2017-2020. PM2.5 and its five components were estimated by the inverse distance weighted method, and green space was reflected by the Normalized Difference Vegetation Index (NDVI), percentages of tree or grass cover. Multivariate logistic regression and quantile g-computing were used to explore the associations of PM2.5 and five components with prediabetes and diabetes and to elucidate the potential moderating role of green space and corresponding type combinations in these associations.

RESULTS

Each interquartile range (IQR) increment of PM2.5 was associated with both prediabetes (odds ratio [OR]: 1.15, 95%CI [confidence interval]: 1.10-1.20) and diabetes (OR: 1.18, 95% CI: 1.11-1.25), respectively. All five components of PM2.5 were related to prediabetes and diabetes. The ORs of PM2.5 on diabetes were 1.49 (1.35-1.63) in the low tree group and 0.90 (0.82-0.98) in the high tree group, respectively. In the high tree-high grass group, the harmful impacts of PM2.5 and five components were significantly lower than in the other groups.

CONCLUSION

Our study suggested that PM2.5 and its components were associated with the increased risk of prediabetes and diabetes, which could be diminished by green space. Furthermore, the coexistence of high levels of tree and grass cover provided greater benefits. These findings had critical implications for diabetes prevention and green space-based planning for healthy city.

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.

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.