Academic journal article Environmental Health Perspectives

Long-Term Exposure to Transportation Noise in Relation to Development of Obesity-A Cohort Study

Academic journal article Environmental Health Perspectives

Long-Term Exposure to Transportation Noise in Relation to Development of Obesity-A Cohort Study

Article excerpt


Large parts of the population are exposed to elevated levels of noise, particularly in urban areas. Road traffic is a dominating source but both railway and aircraft noise contribute in certain areas. Exposure to transportation noise may result in annoyance and sleep disturbance (Basner et al. 2014; Miedema and Oudshoorn 2001; Miedema and Vos 2007) as well as in cardiovascular disease (Munzel et al. 2016). Recently, it has been suggested that markers of obesity, such as waist circumference and body mass index (BMI), may be associated with exposure to transportation noise in adults (Christensen et al. 2015a, 2015b; Eriksson et al. 2014; Oftedal et al. 2015; Pyko et al. 2015), but the evidence is not wholly consistent. Only one of the studies focusing on road traffic noise was longitudinal and used self-reported data on weight and waist circumference, which are prone to bias. In addition, there are studies on obesity in relation to residence near major roads (Li et al. 2016) and air pollution exposure (Jerrett et al. 2014), which indicates that it is important to assess both air pollution and noise exposure to elucidate causal associations when exposure from road traffic is focused.

It has been hypothesized that the relation between environmental noise and cardiovascular disease may involve sleep disturbances and psychological stress (Munzel et al. 2016) and the same mechanisms may also be relevant for metabolic diseases such as obesity and type 2 diabetes. Sleep deprivation may lead to dysregulation of appetite-regulating hormones, such as leptin and ghrelin, and contribute to overweight (Chaput et al. 2007; Van Cauter et al. 2008). Furthermore, noise may act as a stressor and lead to the elevation of cortisol levels, thereby promoting central fat deposition and impaired glucose regulation (Bjorntorp 1997; Rosmond 2003). For example, it has been shown that subjects living near airports have elevated saliva cortisol levels related to noise exposure (Selander et al. 2009a). Combined exposure to several stressors, such as different noise sources or work stress may be particularly harmful (Pyko et al. 2015; Selander et al. 2013; Tetreault et al. 2013). However, data on interactions between exposure to several stressors in relation to development of obesity are limited as well as on the combined effects of noise and air pollution exposure.

In a previous publication we reported results based on a cross-sectional analysis of transportation noise exposure and markers of obesity in a cohort from Stockholm County (Pyko et al. 2015). The present study is based on the same study population, but has a longitudinal design, and uses a newly developed methodology enabling more precise assessment of long-term exposure to transportation noise from different sources as well as objective outcome data. The aim was to estimate the association between exposure to transportation noise and development of obesity markers. As a secondary objective, we assessed the role of combined exposure to multiple sources of transportation noise, including road traffic, railways, and aircraft as well as interactions with air pollution exposure.


The present study was based on the Stockholm Diabetes Prevention Program cohort, which has been described in detail previously (Eriksson et al. 2008). Briefly, the program was conducted between 1992 and 2006 in Stockholm County with the primary aim to study risk factors for type 2 diabetes as well as to implement and evaluate methods for prevention. Participants were recruited between 1992 and 1998 from five municipalities in Stockholm County (Upplands Bro, Upplands Vasby, Sigtuna, Varmdo, and Tyreso). These municipalities mainly include suburban and semirural areas.

By an enrichment procedure in the original design of the study, approximately half of the participants had a family history of diabetes (52%), that is, at least one first-degree relative (mother, father, or sibling) or two second-degree relatives (grandparent, uncle, or aunt) with diabetes. …

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