Associations and effect modification between transportation noise, self-reported response to noise and the wider determinants of health: A narrative synthesis of the literature

Neighborhood Environmental Burden and Cardiovascular Health in the US

Importance

Cardiovascular disease is the leading cause of death in the US. However, little is known about the association between cumulative environmental burden and cardiovascular health across US neighborhoods.

Objective

To evaluate the association of neighborhood-level environmental burden with prevalence of cardiovascular risk factors and diseases, overall and by levels of social vulnerability.

Design, Settings, and Participants

This was a national cross-sectional study of 71 659 US Census tracts. Environmental burden (EBI) and social vulnerability indices from the US Centers for Disease Control and Prevention (CDC) and Agency for Toxic Substances and Disease Registry were linked to the 2020 CDC PLACES data set. Data were analyzed from March to October 2023.

Exposures

The EBI, a measure of cumulative environmental burden encompassing 5 domains (air pollution, hazardous or toxic sites, built environment, transportation infrastructure, and water pollution).

Main Outcomes and Measures

Neighborhood-level prevalence of cardiovascular risk factors (hypertension, diabetes, and obesity) and cardiovascular diseases (coronary heart disease and stroke).

Results

Across the US, neighborhoods with the highest environmental burden (top EBI quartile) were more likely than those with the lowest environmental burden (bottom EBI quartile) to be urban (16 626 [92.7%] vs 13 414 [75.4%]), in the Midwest (5191 [28.9%] vs 2782 [15.6%]), have greater median (IQR) social vulnerability scores (0.64 [0.36-0.85] vs 0.42 [0.20-0.65]), and have higher proportions of adults in racial or ethnic minority groups (median [IQR], 34% [12-73] vs 12% [5-30]). After adjustment, neighborhoods with the highest environmental burden had significantly higher rates of cardiovascular risk factors than those with the lowest burden, including hypertension (mean [SD], 32.83% [7.99] vs 32.14% [6.99]; adjusted difference, 0.84%; 95% CI, 0.71-0.98), diabetes (mean [SD], 12.19% [4.33] vs 10.68% [3.27]; adjusted difference, 0.62%; 95% CI, 0.53-0.70), and obesity (mean [SD], 33.57% [7.62] vs 30.86% [6.15]; adjusted difference, 0.77%; 95% CI, 0.60-0.94). Similarly, neighborhoods with the highest environmental burden had significantly higher rates of coronary heart disease (mean [SD], 6.66% [2.15] vs 6.82% [2.41]; adjusted difference, 0.28%; 95% CI, 0.22-0.33) and stroke (mean [SD], 3.65% [1.47] vs 3.31% [1.12]; adjusted difference, 0.19%; 95% CI, 0.15-0.22). Results were consistent after matching highest and lowest environmentally burdened neighborhoods geospatially and based on other covariates. The associations between environmental burden quartiles and cardiovascular risk factors and diseases were most pronounced among socially vulnerable neighborhoods.

Conclusions and Relevance

In this cross-sectional study of US neighborhoods, cumulative environmental burden was associated with higher rates of cardiovascular risk factors and diseases, although absolute differences were small. The strongest associations were observed in socially vulnerable neighborhoods. Whether initiatives that address poor environmental conditions will improve cardiovascular health requires additional prospective investigations.

Environmental Noise Exposure and Mental Health: Evidence From a Population-Based Longitudinal Study

INTRODUCTION

Exposure to environmental noise from within homes has been associated with poor mental health. Existing evidence rests on cross-sectional studies prone to residual confounding, reverse causation, and small sample sizes, failing to adequately consider the causal nature of this relationship. Furthermore, few studies have examined the sociodemographic distribution of noise exposure at a country level.

METHODS

The study, conducted in 2021, examined the impact of environmental noise from road traffic, airplanes, trains, and industry on mental health and psychological distress as reported by 31,387 respondents using a 19-year longitudinal data set in Australia (2001‒2019). To improve the capacity to make causal inference and reduce bias from measurement error, reverse causation, and unobserved confounders, analyses used instrumental variables, fixed-effects models, and an aggregated area-level measure of noise exposure. Utilizing the large-scale national data set, sociospatial distributions of noise exposure were described.

RESULTS

Private and public rental tenants, lone parents, residents of socioeconomically disadvantaged areas, and those with long-term health conditions were more likely to report residential noise exposure. This exposure to noise was consistently associated with poorer mental health (self-reported noise: β= -0.58; 95% CI= -0.76, -0.39; area-level noise: β= -0.43; 95% CI= -0.61, -0.26), with the relationship strongest for traffic noise (β= -0.79; 95% CI= -1.07, -0.51). Notably, when noise exposure decreased over time, there was an increase in mental health (β= 0.43; 95% CI= 0.14, 0.72).

CONCLUSIONS

The study provides strong evidence of a negative mental health effect of perceived residential noise, and the results have implications for healthy home design and urban planning. These findings should be validated with further studies that measure noise intensity and housing quality.

Environmental Noise and Effects on Sleep: An Update to the WHO Systematic Review and Meta-Analysis

BACKGROUND

Nighttime noise carries a significant disease burden. The World Health Organization (WHO) recently published guidelines for the regulation of environmental noise based on a review of evidence published up to the year 2015 on the effects of environmental noise on sleep.

OBJECTIVES

This systematic review and meta-analysis will update the WHO evidence review on the effects of environmental noise on sleep disturbance to include more recent studies.

METHODS

Investigations of self-reported sleep among residents exposed to environmental traffic noise at home were identified using Scopus, PubMed, Embase, and PsycINFO. Awakenings, falling asleep, and sleep disturbance were the three outcomes included. Extracted data were used to derive exposure-response relationships for the probability of being highly sleep disturbed by nighttime noise [average outdoor A-weighted noise level (Lnight) 2300-0700 hours] for aircraft, road, and rail traffic noise, individually. The overall quality of evidence was assessed using Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) criteria.

RESULTS

Eleven studies (n=109,070 responses) were included in addition to 25 studies (n=64,090 responses) from the original WHO analysis. When sleep disturbance questions specifically mentioned noise as the source of disturbance, there was moderate quality of evidence for the probability of being highly sleep disturbed per 10-dB increase in Lnight for aircraft [odds ratio (OR)=2.18; 95% confidence interval (CI): 2.01, 2.36], road (OR=2.52; 95% CI: 2.28, 2.79), and railway (OR=2.97; 95% CI: 2.57, 3.43) noise. When noise was not mentioned, there was low to very low quality of evidence for being sleep disturbed per 10-dB increase in Lnight for aircraft (OR=1.52; 95% CI: 1.20, 1.93), road (OR=1.14; 95% CI: 1.08, 1.21), and railway (OR=1.17; 95% CI: 0.91, 1.49) noise. Compared with the original WHO review, the exposure-response relationships closely agreed at low (40 dB Lnight) levels for all traffic types but indicated greater disturbance by aircraft traffic at high noise levels. Sleep disturbance was not significantly different between European and non-European studies.

DISCUSSION

Available evidence suggests that transportation noise is negatively associated with self-reported sleep. Sleep disturbance in this updated meta-analysis was comparable to the original WHO review at low nighttime noise levels. These low levels correspond to the recent WHO noise limit recommendations for nighttime noise, and so these findings do not suggest these WHO recommendations need revisiting. Deviations from the WHO review in this updated analysis suggest that populations exposed to high levels of aircraft noise may be at greater risk of sleep disturbance than determined previously. https://doi.org/10.1289/EHP10197.

The neighborhood environment and its association with the spatio-temporal footprint of tobacco consumption and changes in smoking-related behaviors in a Swiss urban area

This study aimed to evaluate the association of the neighborhood environment with the spatio-temporal dependence of tobacco consumption and changes in smoking-related behaviors in a Swiss urban area. Data were obtained from the CoLaus cohort (2003-2006, 2009-2012, and 2014-2017) in Lausanne, Switzerland. Local Moran's I was performed to assess the spatial dependence of tobacco consumption. Prospective changes in tobacco consumption and the location of residence of participants were assessed through Cox regressions. Analyses were adjusted by individual and neighborhood data. The neighborhood environment was spatially associated with tobacco consumption and changes in smoking-related behaviors independently of individual factors.

Assessing community noise annoyance: A review of two decades of the international technical specification ISO/TS 15666:2003

The robust assessment of noise annoyance is of key importance given that it is the most prevalent community response in populations exposed to environmental noise. In 1993, the International Commission on Biological Effects of Noise Community Response to Noise team began formalizing a standardized methodology for assessing noise annoyance which resulted in reporting guidelines and recommendations later published as a Technical Specification (TS) in 2003 by the International Standards Organization (ISO) [(2003). ISO/TS 15666]. This TS, intended to inform the international community on the quantification of the exposure-response relationship between noise exposure and annoyance, has been in circulation for nearly two decades and was updated in 2021 by ISO [(2021). ISO/TS 15666] by an international working group (ISO TC43/SC1/WG62). This paper reviews use of the 2003 TS, identifies common adaptations in use, and summarizes the revisions. Methodological issues arising from the use of the 5-point verbal and the 11-point numeric scale questions and the scoring of "highly annoyed" are discussed. The revisions are designed to encourage further standardization in noise annoyance research. The paper highlights research needs that, if addressed, would strengthen the methodology underlying the assessment of noise annoyance including multidimensional assessments of annoyance.

A multi-scalar perspective on health and urban housing: an umbrella review

With more than half the world's population living in cities, understanding how the built environment impacts human health at different urban scales is crucial. To be able to shape cities for health, an understanding is needed of planetary health impacts, which encompass the human health impacts of human-caused disruptions on the Earth's natural ecosystems. This umbrella review maps health evidence across the spatial scales of the built environment (building; neighbourhood; and wider system, including city, regional and planetary levels), with a specific focus on urban housing. Systematic reviews published in English between January 2011 and December 2020 were searched across 20 databases, with 1176 articles identified and 124 articles screened for inclusion. Findings suggests that most evidence reports on health determinants at the neighbourhood level, such as greenspace, physical and socio-economic conditions, transport infrastructure and access to local services. Physical health outcomes are also primarily reported, with an emerging interest in mental health outcomes. There is little evidence on planetary health outcomes and significant gaps in the research literature are identified. Based on these findings, three potential directions are identified for future research.

Contributors to Neighbour Noise Annoyance

Noise from neighbours has been shown to be one of the most noise annoying sources in Germany, but research on the influencing factors for the annoyance ratings is scarce. Therefore, we investigated whether different personal and contextual (social, physical) factors contribute to neighbour noise annoyance to better understand the neighbour noise annoyance situation. A population-representative survey in four areas in Germany was conducted, with each area further stratified according to their density of agglomeration (inner city, urban outskirt, rural area). Randomly selected residents from each area were invited by mail to participate in the study, either online or via a paper–pencil mode. Noise annoyance was assessed for different noise sources (e.g., neighbourhood, road, railway, aircrafts, different types of industry). In total, 1973 questionnaires were completed. We identified several factors to be predictive of neighbour noise annoyance: satisfaction with the neighbourhood, relationship with neighbours, residential satisfaction, noise sensitivity, and density of agglomeration for people living in the inner city in comparison to rural areas. Particularly, social aspects such as the relationship with neighbours and satisfaction with the neighbourhood have been shown to affect neighbour noise annoyance.