Academic journal article Environmental Health Perspectives

Long-Term Exposure to Road Traffic Noise and Incidence of Diabetes in the Danish Nurse Cohort

Academic journal article Environmental Health Perspectives

Long-Term Exposure to Road Traffic Noise and Incidence of Diabetes in the Danish Nurse Cohort

Article excerpt

Introduction

Well-established risk factors for type 2 diabetes include poor dietary habits, physical inactivity, being overweight, and obesity, all of which are individually modifiable factors. Recent evidence suggests that environmental exposures, including air pollution (Hansen et al. 2016; Weinmayr et al. 2015) and transport-related (road traffic, railway, aircraft) noise (Eze et al. 2017a; Roswall et al. 2018; Sorensen et al. 2013) may also be risk factors, but epidemiological evidence, especially on noise, is limited. Air pollution and road traffic noise are often highly correlated, and few studies have sought to quantitatively disentangle the possible effects of traffic noise and traffic-related air pollution. Therefore, the question to what extent the reported associations of traffic noise are confounded by traffic-related air pollution is still largely unanswered and potentially relevant to implementing adequate abatement policies.

Three cohort studies examined the association of road traffic noise and diabetes incidence (Clark et al. 2017; Eze et al. 2017a; Sorensen et al. 2013), all suggesting positive association. Sorensen et al. reported an 8% increased risk of diabetes per 10 dB increase in road traffic noise levels, which was enhanced (11%) after adjustment for nitrogen oxide (N[O.sub.x]) in 50,187 members of the Danish Diet, Cancer and Health Cohort (Sorensen et al. 2013), and researchers reproduced this finding in the recent re-analyses with prolonged follow-up (Roswall et al. 2018). However, they did not have data on particulate matter with a diameter <2.5 [micro]m ([PM.sub.2.5]), an air pollutant which is also relevant for development of diabetes, as suggested by experimental (Sun et al. 2009) and epidemiological (Eze et al. 2015; Hansen et al. 2016) studies. In a Swiss Cohort Study on Air Pollution and Lung and Heart Diseases in Adults (SAPALDIA) of 2,631 participants, Eze et al. found a 20% increase in diabetes risk per 10 dB increase in road traffic noise levels, which was enhanced to 35% and reached statistical significance only in a model with air pollutants, [PM.sub.2.5] and nitrogen dioxide (N[O.sub.2]) (Eze et al. 2017a). In a population-based cohort from Vancouver, Canada, Clark et al. have detected an 8% increase in diabetes risk per 6.8 dB increase in transportation (mainly road traffic) noise, in a model with air pollutants [[PM.sub.2.5], N[O.sub.2], and black carbon (BC)], greenness, and neighborhood walkability (Clark et al. 2017). However, Clark et al., in contrast with Eze et al. and Sorensen et al., did not adjust for major diabetes risk factors, including physical activity, smoking, diet, and body mass index (BMI), etc. Finally, studies examining other sources of environmental noise, including railway noise (Eze et al. 2015, 2017a; Roswall et al. 2018; Sorensen et al. 2013) and wind turbines noise (Poulsen et al. 2018), found no evidence of association with diabetes, whereas the results on aircraft noise are conflicting (Eriksson et al. 2014; Eze et al. 2017a).

Here, we examine whether long-term exposure to residential road traffic noise over 25 years is associated with diabetes incidence in the nationwide Danish Nurse Cohort study, while accounting for a number of air pollutants.

Methods

The Danish Nurse Cohort

The Danish Nurse Cohort (Hundrup et al. 2012) was established in 1993 and includes a total of 28,731 female members of the Danish Nurse Organization who were 44 years of age or older at recruitment in 1993 or 1999. Inspired by the American Nurses' Health Study, the Danish Nurse Cohort aimed to provide the basis for research into the potential health effects related to use of hormone replacement therapy. In 1993, 19,898 nurses accepted an invitation and answered a comprehensive questionnaire on lifestyle (smoking, alcohol consumption, leisure time physical activity, diet, BMI, etc.), occupational characteristics (shift work, work environment, etc. …

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