Association between long-term air pollution exposure and insulin resistance independent of abdominal adiposity in Korean adults

A review of air pollution as a driver of cardiovascular disease risk across the diabetes spectrum

The prevalence of diabetes is estimated to reach almost 630 million cases worldwide by the year 2045; of current and projected cases, over 90% are type 2 diabetes. Air pollution exposure has been implicated in the onset and progression of diabetes. Increased exposure to fine particulate matter air pollution (PM2.5) is associated with increases in blood glucose and glycated hemoglobin (HbA1c) across the glycemic spectrum, including normoglycemia, prediabetes, and all forms of diabetes. Air pollution exposure is a driver of cardiovascular disease onset and exacerbation and can increase cardiovascular risk among those with diabetes. In this review, we summarize the literature describing the relationships between air pollution exposure, diabetes and cardiovascular disease, highlighting how airborne pollutants can disrupt glucose homeostasis. We discuss how air pollution and diabetes, via shared mechanisms leading to endothelial dysfunction, drive increased cardiovascular disease risk. We identify portable air cleaners as potentially useful tools to prevent adverse cardiovascular outcomes due to air pollution exposure across the diabetes spectrum, while emphasizing the need for further study in this particular population. Given the enormity of the health and financial impacts of air pollution exposure on patients with diabetes, a greater understanding of the interventions to reduce cardiovascular risk in this population is needed.

Exploring the impact of environmental exposure changes on metabolic biomarkers: A 6-month GPS-GIS study among women with overweight or obesity

BACKGROUND

Little is known about the impact of environmental exposure change on metabolic biomarkers associated with cancer risk. Furthermore, this limited epidemiological evidence on metabolic biomarkers focused on residential exposure, without considering the activity space which can be done by modelling dynamic exposures. In this longitudinal study, we aimed to investigate the impact of environmental exposures change on metabolic biomarkers using GPS-GIS based measurements.

METHODS

Among two weight loss interventions, the Reach for Health and the MENU studies, which included ∼460 women at risk of breast cancer or breast cancer survivors residing in Southern California, three metabolic biomarkers (insulin resistance, fasting glucose, and C-reactive protein) were assessed. Dynamic GPS-GIS based exposure to green spaces, recreation, walkability, NO2, and PM2.5 were calculated at baseline and 6 months follow-up using time-weighted spatial averaging. Generalized estimating equations models were used to examine the relationship between changes in environmental exposures and biomarker levels over time.

RESULTS

Overall, six-month environmental exposure change was not associated with metabolic biomarkers change. Stratified analyses by level of environmental exposures at baseline revealed that reduced NO2 and PM2.5 exposure was associated with reduced fasting glucose concentration among women living in a healthier environment at baseline (β -0.010, 95%CI -0.025, 0.005; β -0.019, 95%CI -0.034, -0.003, respectively). Women living in poor environmental conditions at baseline and exposed to greener environments had decreased C-reactive protein concentrations (β -1.001, 95%CI -1.888, -0.131).

CONCLUSIONS

The impact of environmental exposure changes on metabolic biomarkers over time may be modified by baseline exposure conditions.

Associations of low levels of air pollution with cardiometabolic outcomes and the role of diet quality in individuals with obesity

BACKGROUND

Exposure to air pollution is associated with adverse cardiometabolic health effects and increased mortality, even at low concentrations. Some of the biological mechanisms through which air pollution can affect cardiometabolic health overlap with health outcomes associated with diet quality and changes in diet.

OBJECTIVE

The objective of this study is to investigate associations of air pollutants at average concentrations below the World Health Organization, 2021 air quality guidelines with cardiometabolic outcomes. Furthermore, potential interaction between air pollutants and diet quality will be assessed.

METHODS

82 individuals with obesity participated in a combined weight loss and weight loss maintenance study for a total of 33 weeks. A secondary analysis was conducted incorporating air pollution measurements. Data were analysed with linear mixed-effects models.

RESULTS

A total of 17 significant associations were observed for single pollutants with 10 cardiometabolic outcomes, predominantly related to blood lipids, hormones, and glucose regulation. Diet quality, as measured by the Baltic Sea Diet score, did not appear to mediate the association of air pollution with cardiometabolic outcomes, however, diet quality was observed to significantly modify the association of PM2.5 with total cholesterol, and the associations of NO and O3 with ghrelin.

DISCUSSION

These findings suggest that exposure to ambient air pollutants, especially particulate matter, at levels below World Health Organization, 2021 air quality guidelines, were associated with changes in cardiometabolic risk factors. Diet may be a personal-level approach for individuals to modify the impact of exposure to air pollution on cardiometabolic health.

Long-term exposure to air pollution and risk of insulin resistance: A systematic review and meta-analysis

OBJECTIVE

The effects of air pollution on metabolism have become a popular research topic, and a large number of studies had confirmed that air pollution exposure could induce insulin resistance (IR) to varying degrees, but the results were inconsistent, especially for the long-term exposures. The aim of the current study was to further investigate the potential effects of air pollution on IR.

METHODS

A systematic review and meta-analysis of four electronic databases, including PubMed, Embase, Web of Science and Cochrane were conducted, searching for relevant studies published before June 10, 2023, in order to explore the potential relationships between long-term exposure to air pollution and IR. A total of 10 studies were included for data analysis, including seven cohort studies and three cross-sectional studies. Four major components of air pollution, including PM2.5 (particulate matter with an aerodynamic diameter of 2.5 µm or less), PM10 (particulate matter with an aerodynamic diameter of 10 µm or less), NO2, and SO2 were selected, and each analyzed for the potential impacts on insulin resistance, in the form of adjusted percentage changes in the homeostasis assessment model of insulin resistance (HOMA-IR).

RESULTS

This systematic review and meta-analysis showed that for every 1 μg/m³ increase in the concentration of selected air pollutants, PM2.5 induced a 0.40% change in HOMA-IR (95%CI: -0.03, 0.84; I2 =67.4%, p = 0.009), while PM10 induced a 1.61% change (95%CI: 0.243, 2.968; I2 =49.1%, p = 0.001). Meanwhile, the change in HOMA-IR due to increased NO2 or SO2 exposure concentration was only 0.09% (95%CI: -0.01, 0.19; I2 =83.2%, p = 0.002) or 0.01% (95%CI: -0.04, 0.06; I2 =0.0%, p = 0.638), respectively.

CONCLUSIONS

Long-term exposures to PM2.5, PM10, NO2 or SO2 are indeed associated with the odds of IR. Among the analyzed pollutants, inhalable particulate matters appear to exert greater impacts on IR.