Using Indoor Air Filtration to Reduce PM 2.5 Cardio-metabolic Effects in At-risk Individuals

June 9, 2022 0 Comments

Mounting evidence suggests that air pollution contributes to the rapidly growing type 2 diabetes epidemic. Epidemiological studies have found exposures to ambient air pollutants, particularly fine particulate matter (PM2.5) and nitrogen dioxide (NO2), were associated with increased diabetes prevalence,1-13 incidence14-19 and mortality.20 Studies have also indicated that short- and long-term air pollution exposures may negatively impact early indicators of cardiometabolic dysfunction including hyperglycemia,21-25 insulin resistance, dyslipidemia and hypertension.23-29 Our previous study in Hispanic adults consistently found that up to 58 days of cumulative exposure to PM2.5 was associated with higher fasting glucose and insulin levels as well as homeostatic model assessment of insulin resistance (HOMA-IR) and lower insulin sensitivity.33 Previous studies including ours also found that short-term PM2.5 exposure was associated with increased low-density lipoprotein cholesterol (LDL) and decreased high-density lipoprotein cholesterol (HDL).22,33,34

Using HEPA air purifiers can reduce indoor PM2.5 levels by 40% to >90% 45,47,49-53 and can improve acute cardiovascular outcomes after using such a device for a short period (3 days to 2-month).45-48 However, no published studies have evaluated the potential benefits of a longer-term indoor HEPA filtration intervention in improving cardio-metabolic profiles in at-risk adults. Here we propose to conduct a 6-month residential HEPA filtration trial in individuals with a baseline health condition of elevated risk for type 2 diabetes. The participants reside in the Los Angeles area where ambient air pollution levels are among the highest in the US and also prone to wildfire exposure. This would be the longest-duration residential intervention trial, providing an opportunity to observe chronic changes in health outcomes. Based on our extensive experience in cross-over studies, we propose to use this most cost-effective study design in which subjects will serve as their own controls. This intervention trial has three specific aims.

Aim 1: To assess the effect of a 6-month residential HEPA intervention on changes of type 2 diabetes-related metabolic outcomes in 52 adults. We hypothesize that compared to sham filtration, HEPA filtration will lead to an improved cardio-metabolic profile including reduced fasting glucose, HbA1C, HOMA-IR, LDL and blood pressure as well as increased HDL. The findings will provide the first evidence on intervention benefits with respect to diabetes-related quantitative traits.

Aim 2: To examine the association between reduction in indoor PM2.5 exposure brought by the intervention and changes in metabolic outcomes adjusting for ambient PM2.5 exposure. We hypothesize that a greater reduction in indoor PM2.5 exposure will result in a greater improvement in the cardio-metabolic profile. If the hypothesis is proven true, the finding will support practices to maximize indoor PM2.5 reduction through expanding the proper use of filtration devices in other indoor environments.

Aim 3: To explore major pathophysiologic changes pertinent to the cardio-metabolic profile of type 2 diabetes relevance in response to the intervention and changes in PM2.5 exposure. The findings from this aim will help identify novel biomarkers to predict the disease risk and improve the understanding of biological mechanisms. The insights can help develop other personal-level preventive strategies such as therapeutic interventions.

Impact: We plan to use a low-cost HEPA filtration device in this double-blind cross-over trial. If the intervention is proven to be beneficial, residential use of air purifiers will be recommended as a practical means to reduce air pollution-induced risk for diabetes, which has no foreseeable side effects.

Leave a Reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.