Academic journal article Environmental Health Perspectives

Air Pollution and Glucose Metabolism: An Analysis in Non-Diabetic Participants of the Heinz Nixdorf Recall Study

Academic journal article Environmental Health Perspectives

Air Pollution and Glucose Metabolism: An Analysis in Non-Diabetic Participants of the Heinz Nixdorf Recall Study

Article excerpt

Introduction

Exposure to particulate matter (PM) in ambient air is a major environmental health risk, accounting for an estimated 3.1 million deaths and 3.1% of global disability-adjusted life years lost worldwide in 2010 (Lim et al. 2010). Short- and long-term exposure to these inhalable particles can aggravate respiratory and cardiovascular conditions, increase hospital admissions, and result in mortality from cardiovascular and respiratory diseases as well as from lung cancer (WHO 2006). Emerging evidence suggests that exposure to PM may also increase the risk of type 2 diabetes mellitus (T2DM) in the general population (Balti et al. 2014). Although specific pathophysiological mechanisms that might contribute to associations between PM and T2DM are unclear at present, one plausible hypothesis is that inhalation of particulate matter causes oxidative stress in the lungs that can lead to systemic inflammation, inflammation of adipose tissue, and insulin resistance. Together, these intermediate outcomes may contribute to a diabetogenic metabolism and eventually lead to the onset of T2DM (Franklin et al. 2015; Rajagopalan and Brook 2012).

In an effort to clarify these pathways, several epidemiological studies have explored whether higher air pollution exposure is associated with elevated blood glucose levels, a potential sign of increased insulin resistance. Short-term (days to weeks; Peng et al. 2016), medium-term (weeks to months; Peng et al. 2016; Sade et al. 2015, 2016), and long-term ([greater than or equal to] 1 year; Cai et al. 2017; Chuang et al. 2011; Liu et al. 2016; Ward-Caviness et al. 2015; Wolf et al. 2016) exposure studies have shown positive associations between a variety of air pollution measures and blood glucose levels. Nevertheless, study findings have been inconsistent for specific pollutants [e.g., particulate matter (PM), nitrogen dioxide (N[O.sub.2]), sulfur dioxide (S[O.sub.2])], and the latency period required for a cause-effect relationship has received little attention.

Because blood glucose measures are subject to high intrapersonal variability, glycated hemoglobin A1c (HbA1c), a biomarker that reflects average blood glucose levels over the previous 6-8 wk, is a useful instrument for assessing glucose levels and potential insulin resistance. At present, the epidemiological studies that have evaluated associations between long-term outdoor air pollution exposures (PM, N[O.sub.2], S[O.sub.2]) and HbA1c level show mixed results (Chuang et al. 2011; Honda et al. 2017; Liu et al. 2016; Tamayo et al. 2014, 2016; Wolf et al. 2016). The few studies investigating medium-term exposure periods, which may be the more relevant period for HbA1c levels, have also yielded mixed results (Sade et al. 2015,2016).

Additionally, few studies have examined these associations in persons without diabetes (Brook et al. 2013; Chen et al. 2016; Honda et al. 2017; Kim and Hong 2012; Peng et al. 2016; Wolf et al. 2016), an important study group for bettering our understanding of how air pollution exposure may play a role in the early development of diabetes. We examined whether exposure to medium-term (28-, 91-d mean) air pollution [particulate matter with aerodynamic diameter [less than or equal to] 2.5 [micro]m (P[M.sub.2.5]), particulate matter with aerodynamic diameter [less than or equal to] 10 [micro]m (P[M.sub.10]), N[O.sub.2], and accumulation mode particle number (P[N.sub.AM])] is associated with blood glucose and HbA1c levels in nondiabetic participants of the German population-based prospective Heinz Nixdorf Recall (HNR) study using data from two examination times. Because blood glucose levels vary more with daily changes than HbA1c levels do, we hypothesized that 28-d mean exposure windows would be more strongly associated with blood glucose measures, whereas 91-d mean exposure windows would be more strongly associated with HbA1c levels.

Methods

Study Design

This study was conducted using data from the baseline (2000-2003) and first follow-up (2006-2008) examinations of the HNR study, an ongoing prospective population-based cohort study located in three adjacent cities (Bochum, Essen, and Mulheim) within the highly urbanized German Ruhr area. …

Search by... Author
Show... All Results Primary Sources Peer-reviewed

Oops!

An unknown error has occurred. Please click the button below to reload the page. If the problem persists, please try again in a little while.