Anu W. Turunen

Environmental noise is the second largest environmental risk factor in disease burden estimates for Europe. While socioeconomic inequalities in noise exposure have been reported, the impact of socioeconomic status (SES) on the disease burden attributable to noise exposure has to our knowledge not been reported previously. The aim of this study is to assess the impact of SES on traffic noise exposure and the associated disease burden in selected Nordic populations. We employed nationwide data on road traffic noise exposure and SES from Danish and Norwegian Nationwide Models. The impact of household income and education on traffic noise exposure was assessed using linear regression analyses. Burden of disease estimates were calculated for populations stratified according to their level of income and education in terms of Disability-Adjusted Life Years (DALY) for high degree of noise annoyance, high degree of sleep disturbance and ischaemic heart disease. The most consistent finding observed for the Danish population was that, compared to medium and low household income, high household income was associated with lower noise exposure. Moreover, the burden of disease estimates for high noise annoyance were up to 20% lower in the high compared to the lower household income groups.

Background Exposure to natural environments is thought to be beneficial for human health, but the evidence is inconsistent. Objective To examine whether exposure to green and blue spaces in urban environments is associated with mental and physical health in Finland. Methods The Helsinki Capital Region Environmental Health Survey was conducted in 2015−2016 in Helsinki, Espoo and Vantaa in Finland (n=7321). Cross-sectional associations of the amounts of residential green and blue spaces within 1 km radius around the respondent’s home (based on the Urban Atlas 2012), green and blue views from home and green space visits with self-reported use of psychotropic (anxiolytics, hypnotics and antidepressants), antihypertensive and asthma medication were examined using logistic regression models. Indicators of health behaviour, traffic-related outdoor air pollution and noise and socioeconomic status (SES) were used as covariates, the last of these also as a potential effect modifier. Results Amounts of residential green and blue spaces or green and blue views from home were not associated with medications. However, the frequency of green space visits was associated with lower odds of using psychotropic medication (OR=0.67, 95% CI 0.55 to 0.82 for 3–4 times/week; 0.78, 0.63 to 0.96 for ≥5 times/week) and antihypertensive (0.64, 0.52 to 0.78; 0.59, 0.48 to 0.74, respectively) and asthma (0.74, 0.58 to 0.94; 0.76, 0.59 to 0.99, respectively) medication use. The observed associations were attenuated by body mass index, but no consistent interactions with SES indicators were observed. Conclusions Frequent green space visits, but not the amounts of residential green or blue spaces, or green and blue views from home, were associated with less frequent use of psychotropic, antihypertensive and asthma medication in urban environments.

Large variations in transportation noise tolerance have been reported between communities. In addition to population sensitivity, exposure–response functions (ERFs) for the effects of transportation noise depend on the exposure estimation method used. In the EU, the new CNOSSOS-EU method will change the estimations of exposure by changing the assignment of noise levels and populations to buildings. This method was officially used for the first time in the strategic noise mapping performed by Finnish authorities in 2017. Compared to the old method, the number of people exposed to traffic noise above 55 dB decreased by 50%. The main aim of this study, conducted in the Helsinki Capital Region, Finland, was to evaluate how the exposure estimation method affects ERFs for road traffic noise. As an example, with a façade road traffic noise level of 65 dB, the ERF based on the highest façade noise level of the residential building resulted in 5.1% being highly annoyed (HA_V), while the ERF based on the exposure estimation method that is similar to the CNOSSOS-EU method resulted in 13.6%. Thus, the substantial increase in the health effect estimate compensates for the reduction in the number of highly exposed people. This demonstrates the need for purpose–fitted ERFs when the CNOSSOS-EU method is used to estimate exposure in the health impact assessment of transportation noise.

Urban dwellers are simultaneously exposed to several environmental health risk factors. This study aimed to examine the relationship between long-term exposure to fine particulate matter (PM_2.5, diameter < 2.5 µm) of residential-wood-burning and road-traffic origin, road-traffic noise, green space around participants’ homes, and hypertension. In 2015 and 2016, we conducted a survey of residents of the Helsinki Capital Region to determine their perceptions of environmental quality and safety, lifestyles, and health statuses. Recent antihypertensive medication was used as an indicator of current hypertensive illness. Individual-level exposure was estimated by linking residential coordinates with modelled outdoor levels of wood-smoke- and traffic-related PM_2.5, road-traffic noise, and coverage of natural spaces. Relationships between exposure and hypertension were modelled using multi-exposure and single-exposure binary logistic regression while taking smooth functions into account. Twenty-eight percent of the participants were current users of antihypertensive medication. The odds ratios (95% confidence interval) for antihypertensive use were 1.12 (0.78–1.57); 0.97 (0.76–1.26); 0.98 (0.93–1.04) and 0.99 (0.94–1.04) for wood-smoke PM_2.5, road-traffic PM_2.5, road-traffic noise, and coverage of green space, respectively. We found no evidence of an effect of the investigated urban exposures on prevalent hypertension in the Helsinki Capital Region.

Exposure to road-traffic noise commonly engenders annoyance, the extent of which is determined by factors not fully understood. Our aim was to estimate the prevalence and determinants of road-traffic noise annoyance and noise sensitivity in the Finnish adult population, while comparing the perceptions of road-traffic noise to exhausts as environmental health problems. Using a questionnaire that yielded responses from 1112 randomly selected adult Finnish respondents, we estimated road-traffic noise- and exhausts-related perceived exposures, health-risk perceptions, and self-reported annoyance on five-point scales, while noise sensitivity estimates were based on four questions. Determinants of noise annoyance and sensitivity were investigated using multivariate binary logistic regression and linear regression models, respectively. High or extreme noise annoyance was reported by 17% of respondents. Noise sensitivity scores approximated a Gaussian distribution. Road-traffic noise and exhausts were, respectively, considered high or extreme population-health risks by 22% and 27% of respondents. Knowledge of health risks from traffic noise, OR: 2.04 (1.09–3.82) and noise sensitivity, OR: 1.07 (1.00–1.14) were positively associated with annoyance. Knowledge of health risks (p < 0.045) and positive environmental attitudes (p < 000) were associated with higher noise sensitivity. Age and sex were associated with annoyance and sensitivity only in bivariate models. A considerable proportion of Finnish adults are highly annoyed by road-traffic noise, and perceive it to be a significant health risk, almost comparable to traffic exhausts. There is no distinct noise-sensitive population subgroup. Knowledge of health risks of road-traffic noise, and attitudinal variables are associated with noise annoyance and sensitivity.