Long-term exposure to transportation noise and risk of type 2 diabetes: A cohort study

Long-term exposure to transportation noise and diabetes mellitus mortality: a national cohort study and updated meta-analysis

BACKGROUND

Long-term exposure to transportation noise is related to cardio-metabolic diseases, with more recent evidence also showing associations with diabetes mellitus (DM) incidence. This study aimed to evaluate the association between transportation noise and DM mortality within the Swiss National Cohort.

METHODS

During 15 years of follow-up (2001-2015; 4.14 million adults), over 72,000 DM deaths were accrued. Source-specific noise was calculated at residential locations, considering moving history. Multi-exposure, time-varying Cox regression was used to derive hazard ratios (HR, and 95%-confidence intervals). Models included road traffic, railway and aircraft noise, air pollution, and individual and area-level covariates including socio-economic position. Analyses included exposure-response modelling, effect modification, and a subset analysis around airports. The main findings were integrated into meta-analyses with published studies on mortality and incidence (separately and combined).

RESULTS

HRs were 1.06 (1.05, 1.07), 1.02 (1.01, 1.03) and 1.01 (0.99, 1.02) per 10 dB day evening-night level (Lden) road traffic, railway and aircraft noise, respectively (adjusted model, including NO2). Splines suggested a threshold for road traffic noise (~ 46 dB Lden, well below the 53 dB Lden WHO guideline level), but not railway noise. Substituting for PM2.5, or including deaths with type 1 DM hardly changed the associations. HRs were higher for males compared to females, and in younger compared to older adults. Focusing only on type 1 DM showed an independent association with road traffic noise. Meta-analysis was only possible for road traffic noise in relation to mortality (1.08 [0.99, 1.18] per 10 dB, n = 4), with the point estimate broadly similar to that for incidence (1.07 [1.05, 1.09] per 10 dB, n = 10). Combining incidence and mortality studies indicated positive associations for each source, strongest for road traffic noise (1.07 [1.05, 1.08], 1.02 [1.01, 1.03], and 1.02 [1.00, 1.03] per 10 dB road traffic [n = 14], railway [n = 5] and aircraft noise [n = 5], respectively).

CONCLUSIONS

This study provides new evidence that transportation noise is associated with diabetes mortality. With the growing evidence and large disease burden, DM should be viewed as an important outcome in the noise and health discussion.

Association of transportation noise with cardiovascular diseases

This comprehensive article delves into the intricate and multifaceted issue of noise pollution, shedding light on its diverse sources, profound health implications, and the economic burden it imposes on societies. Noise pollution is an increasingly prevalent environmental challenge, impacting millions of people worldwide, often without their full awareness of its adverse effects. Drawing from a wealth of scientific research, the article underscores the well-established links between noise pollution and a spectrum of health issues, including cardiovascular diseases, sleep disturbances, and psychological stress. While exploring the sources and consequences of noise pollution, the article highlights the urgent need for a holistic and collaborative approach to mitigate its impact. This entails a combination of regulatory measures, technological innovations, urban planning strategies, and public education campaigns. It is increasingly evident that the detrimental effects of noise pollution extend beyond physical health, encompassing mental and social well-being. The article also addresses the synergistic relationship between noise pollution and other environmental stressors, emphasizing the importance of considering noise in conjunction with factors like air pollution and access to green spaces. It examines the potential of green spaces to mitigate the effects of noise pollution and enhance overall health.

Transportation Noise Pollution and Cardiovascular Health

Epidemiological studies have found that transportation noise increases the risk for cardiovascular morbidity and mortality, with solid evidence for ischemic heart disease, heart failure, and stroke. According to the World Health Organization, at least 1.6 million healthy life years are lost annually from traffic-related noise in Western Europe. Traffic noise at night causes fragmentation and shortening of sleep, elevation of stress hormone levels, and increased oxidative stress in the vasculature and the brain. These factors can promote vascular (endothelial) dysfunction, inflammation, and arterial hypertension, thus elevating cardiovascular risk. The present review focusses on the indirect, nonauditory cardiovascular health effects of noise. We provide an updated overview of epidemiological research on the effects of transportation noise on cardiovascular risk factors and disease, and mechanistic insights based on the latest clinical and experimental studies and propose new risk markers to address noise-induced cardiovascular effects in the general population. We will discuss the potential effects of noise on vascular dysfunction, oxidative stress, and inflammation in humans and animals. We will elaborately explain the underlying pathomechanisms by alterations of gene networks, epigenetic pathways, circadian rhythm, signal transduction along the neuronal-cardiovascular axis, and metabolism. We will describe current and future noise mitigation strategies. Finally, we will conduct an overall evaluation of the status of the current evidence of noise as a significant cardiovascular risk factor.

Coupling Different Road Traffic Noise Models with a Multilinear Regressive Model: A Measurements-Independent Technique for Urban Road Traffic Noise Prediction

Road traffic noise is a severe environmental hazard, to which a growing number of dwellers are exposed in urban areas. The possibility to accurately assess traffic noise levels in a given area is thus, nowadays, quite important and, on many occasions, compelled by law. Such a procedure can be performed by measurements or by applying predictive Road Traffic Noise Models (RTNMs). Although the first approach is generally preferred, on-field measurement cannot always be easily conducted. RTNMs, on the contrary, use input information (amount of passing vehicles, category, speed, among others), usually collected by sensors, to provide an estimation of noise levels in a specific area. Several RTNMs have been implemented by different national institutions, adapting them to the local traffic conditions. However, the employment of RTNMs proves challenging due to both the lack of input data and the inherent complexity of the models (often composed of a Noise Emission Model-NEM and a sound propagation model). Therefore, this work aims to propose a methodology that allows an easy application of RTNMs, despite the availability of measured data for calibration. Four different NEMs were coupled with a sound propagation model, allowing the computation of equivalent continuous sound pressure levels on a dataset (composed of traffic flows, speeds, and source-receiver distance) randomly generated. Then, a Multilinear Regressive technique was applied to obtain manageable formulas for the models' application. The goodness of the procedure was evaluated on a set of long-term traffic and noise data collected in a French site through several sensors, such as sound level meters, car counters, and speed detectors. Results show that the estimations provided by formulas coming from the Multilinear Regressions are quite close to field measurements (MAE between 1.60 and 2.64 dB(A)), confirming that the resulting models could be employed to forecast noise levels by integrating them into a network of traffic sensors.

Health position paper and redox perspectives - Disease burden by transportation noise

Transportation noise is a ubiquitous urban exposure. In 2018, the World Health Organization concluded that chronic exposure to road traffic noise is a risk factor for ischemic heart disease. In contrast, they concluded that the quality of evidence for a link to other diseases was very low to moderate. Since then, several studies on the impact of noise on various diseases have been published. Also, studies investigating the mechanistic pathways underlying noise-induced health effects are emerging. We review the current evidence regarding effects of noise on health and the related disease-mechanisms. Several high-quality cohort studies consistently found road traffic noise to be associated with a higher risk of ischemic heart disease, heart failure, diabetes, and all-cause mortality. Furthermore, recent studies have indicated that road traffic and railway noise may increase the risk of diseases not commonly investigated in an environmental noise context, including breast cancer, dementia, and tinnitus. The harmful effects of noise are related to activation of a physiological stress response and nighttime sleep disturbance. Oxidative stress and inflammation downstream of stress hormone signaling and dysregulated circadian rhythms are identified as major disease-relevant pathomechanistic drivers. We discuss the role of reactive oxygen species and present results from antioxidant interventions. Lastly, we provide an overview of oxidative stress markers and adverse redox processes reported for noise-exposed animals and humans. This position paper summarizes all available epidemiological, clinical, and preclinical evidence of transportation noise as an important environmental risk factor for public health and discusses its implications on the population level.

Noise and mental health: evidence, mechanisms, and consequences

The recognition of noise exposure as a prominent environmental determinant of public health has grown substantially. While recent years have yielded a wealth of evidence linking environmental noise exposure primarily to cardiovascular ailments, our understanding of the detrimental effects of noise on the brain and mental health outcomes remains limited. Despite being a nascent research area, an increasing body of compelling research and conclusive findings confirms that exposure to noise, particularly from sources such as traffic, can potentially impact the central nervous system. These harms of noise increase the susceptibility to mental health conditions such as depression, anxiety, suicide, and behavioral problems in children and adolescents. From a mechanistic perspective, several investigations propose direct adverse phenotypic changes in brain tissue by noise (e.g. neuroinflammation, cerebral oxidative stress), in addition to feedback signaling by remote organ damage, dysregulated immune cells, and impaired circadian rhythms, which may collectively contribute to noise-dependent impairment of mental health. This concise review linking noise exposure to mental health outcomes seeks to fill research gaps by assessing current findings from studies involving both humans and animals.