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Objectives Road traffic noise is a common environmental nuisance, which has been thought to increase the risk of many types of health problems. However, population-level evidence often remains scarce. This study examined whether road traffic noise is associated with self-rated health and use of psychotropic medication in a cohort of public sector employees. Methods Data are from the Finnish Public Sector Study cohort. Geographical information system (GIS) was used to link modeled outdoor road traffic noise levels (Lden) to residential addresses of 15 611 men and women with cross-sectional survey responses on self-rated health and register-based information on the use of antidepressants, anxiolytics, and hypnotics. High trait anxiety scores were used to identify potentially vulnerable individuals.The analyses were run with logistic regression models adjusting for individual and area-level variables. All participants were blind to the aim of the study. Results Mean level of road traffic noise at participants' home addresses was 52 decibels (dB) (standard deviation 8.1). Noise level >60 dB versus <45 dB was associated with poor self-rated health in men [odds ratio (OR) 1.58, 95% confidence interval (95% CI) 1.14-2.21]. Further stratification revealed that the association was evident only among men with high trait anxiety scores (OR 2.23, 95% CI 1.28-3.89). No association was found with psychotropic medication use or among women. Conclusion Exposure to road traffic noise was not associated with increased use of psychotropic medication, although it was associated with weakened self-rated health among men.

Background: It is known that particulate air pollution affects cardiorespiratory health; however, it is unclear which particle size fractions and sources of particles are responsible for the health effects. Methods: Daily levels of nucleation (<0.03 μm), Aitken (0.03–0.1 μm), accumulation (0.1–0.29 μm), and coarse mode (2.5–10 μm) particles, particles with diameter <2.5 μm (PM2.5), and gaseous pollutants were measured at central outdoor measurement sites in Helsinki, Finland between 1998 and 2004. We determined the associations of particles with daily cardiorespiratory mortality and acute hospital admissions among the elderly (≥65 years). For the analyses we used Poisson generalized additive models and for the source apportionment of PM we used the EPA positive matrix factorization method. Results: There was a suggestion of an association of hospital admissions for arrhythmia with Aitken mode particles and PM from traffic. Otherwise few associations were observed between various sizes and types of particles and either cardiovascular admissions or mortality. In contrast, most particle fractions had positive associations with admissions for pneumonia and asthma-chronic obstructive pulmonary disease (COPD). The strongest and most consistent associations were found for accumulation mode particles (3.1%; 95% confidence interval = 0.43–5.8 for pneumonia over the 5-day mean, and 3.8%; 1.3–6.3 for asthma-COPD at lag 0, for an interquartile increase in particles). We also found a positive association of respiratory mortality mainly with accumulation mode particles (5.1%; 1.2–9.0 at lag 0). Conclusions: All particle fractions including Aitken, accumulation, and coarse mode had especially adverse respiratory health effects among the elderly. Overall associations were stronger for respiratory than for cardiovascular outcomes.

Background: Associations between traffic noise and sleep problems have been detected in experimental studies, but population-level evidence is scarce. Objectives: We studied the relationship between the levels of nighttime traffic noise and sleep disturbances and identified vulnerable population groups. Methods: Noise levels of nighttime—outdoor traffic were modeled based on the traffic intensities in the cities of Helsinki and Vantaa, Finland. In these cities, 7,019 public sector employees (81% women) responded to postal surveys on sleep and health. We linked modeled outdoor noise levels to the residences of the employees who responded to the postal survey. We used logistic regression models to estimate associations of noise levels with subjectively assessed duration of sleep and symptoms of insomnia (i.e., difficulties falling asleep, waking up frequently during the night, waking up too early in the morning, nonrestorative sleep). We also used stratified models to investigate the possibility of vulnerable subgroups. Results: For the total study population, exposure to levels of nighttime—outside (Lnight, outside) traffic noise > 55 dB was associated with any insomnia symptom ≥ 2 nights per week [odds ratio (OR) = 1.32; 95% confidence interval (CI): 1.05, 1.65]. Among participants with higher trait anxiety scores, which we hypothesized were a proxy for noise sensitivity, the ORs for any insomnia symptom at exposures to Lnight, outside traffic noises 50.1—55 dB and > 55 dB versus ≤ 45 dB were 1.34 (95% CI: 1.00, 1.80) and 1.61 (95% CI: 1.07, 2.42), respectively. Conclusions: Nighttime traffic noise levels > 50 dB Lnight, outside was associated with insomnia symptoms among persons with higher scores for trait anxiety. For the total study population, Lnight, outside > 55 dB was positively associated with any symptoms.

Objective To compare short-term effects of fine particles (PM2.5; aerodynamic diameter <2.5 µm) from different sources on the blood levels of markers of systemic inflammation. Methods We followed a panel of 52 ischaemic heart disease patients from 15 November 2005 to 21 April 2006 with clinic visits in every second week in the city of Kotka, Finland, and determined nine inflammatory markers from blood samples. In addition, we monitored outdoor air pollution at a fixed site during the study period and conducted a source apportionment of PM2.5 using the Environmental Protection Agency's model EPA PMF 3.0. We then analysed associations between levels of source-specific PM2.5 and markers of systemic inflammation using linear mixed models. Results We identified five source categories: regional and long-range transport (LRT), traffic, biomass combustion, sea salt, and pulp industry. We found most evidence for the relation of air pollution and inflammation in LRT, traffic and biomass combustion; the most relevant inflammation markers were C-reactive protein, interleukin-12 and myeloperoxidase. Sea salt was not positively associated with any of the inflammatory markers. Conclusions Results suggest that PM2.5 from several sources, such as biomass combustion and traffic, are promoters of systemic inflammation, a risk factor for cardiovascular diseases.

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 (PM2.5, 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 PM2.5, 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 PM2.5, road-traffic PM2.5, 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.

The existing knowledge on the effect of air cleaners in reducing different indoor impurities and health symptoms in real-life applications is still insufficient. PUHHO study aimed to fill this knowledge gap with a blinded intervention study in 18 primary school classrooms. The study was conducted during 8 weeks with 2 weeks without air cleaner, 3 weeks with air cleaner in full operation (filtration) with moderate airflow (200 - 400 m 3 /h) and 3 weeks sham operation (air cleaner blowing air without filtration). The latter two interventions were conducted in a blinded and mixed setup. Small, but statistically non-significant reductions in particulate matter levels (PM2.5; particulate matter with diameter less than 2.5 µm and PM10; diameter of particles less than 10 µm) were observed when comparing air cleaner filtration to air recirculation alone (sham operation). The use of air cleaners had no significant effect on the level of total volatile organic compounds (TVOC). Air cleaners did not have significant effect on the microbial levels or on the microbiome of the classrooms. Filtration by air cleaners was found to statistically significantly reduce upper (4.0%) and lower airway (2.5%) and other (4.0%) symptoms, but a nearly equivalent effect was observed with air recirculation alone.

A simple method for correcting for the loading effects of aethalometer data is presented. The formula BC(CORRECTED) = (1 + k x ATN) x BC(NONCORRECTED), where ATN is the attenuation and BC is black carbon, was used for correcting aethalometer data obtained from measurements at three different sites: a subway station in Helsinki, an urban background measurement station in Helsinki, and a rural station in Hyytiälä in central Finland. The BC data were compared with simultaneously measured aerosol volume concentrations (V). After the correction algorithm, the BC-to-V ratio remained relatively stable between consequent filter spots, which can be regarded as indirect evidence that the correction algorithm works. The k value calculated from the outdoor sites had a clear seasonal cycle that could be explained by darker aerosol in winter than in summer. When the contribution of BC to the total aerosol volume was high, the k factor was high and vice versa. In winter, the k values at all wavelengths were very close to that obtained from the subway station data. In summer, the k value was wavelength dependent and often negative. When the k value is negative, the noncorrected BC concentrations overestimated the true concentrations.

IntroductionAir pollution has been suggested to be associated with depression. However, current evidence is conflicting, and no study has considered different sources of ambient particulate matter with an aerodynamic diameter below 2.5 µm (PM2.5). We evaluated the associations of long-term exposure to PM2.5 from road traffic and residential wood combustion with the prevalence of depression in the Helsinki region, Finland.MethodsWe conducted a cross-sectional analysis based on the Helsinki Capital Region Environmental Health Survey 2015–2016 (N=5895). Modelled long-term outdoor concentrations of PM2.5 were evaluated using high-resolution emission and dispersion modelling on an urban scale and linked to the home addresses of study participants. The outcome was self-reported doctor-diagnosed or treated depression. We applied logistic regression and calculated the OR for 1 μg/m3 increase in PM2.5, with 95% CI. Models were adjusted for potential confounders, including traffic noise and urban green space.ResultsOf the participants, 377 reported to have been diagnosed or treated for depression by a doctor. Long-term exposure to PM2.5 from road traffic (OR=1.23, 95% CI 0.86 to 1.73; n=5895) or residential wood combustion (OR=0.78, 95% CI 0.43 to 1.41; n=5895) was not associated with the prevalence of depression. The estimates for PM2.5 from road traffic were elevated, but statistically non-significant, for non-smokers (OR=1.38, 95% CI 0.94 to 2.01; n=4716).ConclusionsWe found no convincing evidence of an effect of long-term exposure to PM2.5 from road traffic or residential wood combustion on depression.

Abstract Background Prior studies suggest that physical activity lowers circulating C-reactive protein (CRP) levels. However, little is known about the association between regular active commuting, i.e. walking or cycling to work, and CRP concentrations. This study examines whether active commuting is associated with lower CRP. Methods We conducted a cross-sectional study using population-based FINRISK data from 1997, 2002, 2007 and 2012. Participants were working adults living in Finland (n = 6208; mean age = 44 years; 53.6% women). We used linear and additive models adjusted for potential confounders to analyze whether daily active commuting, defined as the time spent walking or cycling to work, was associated with lower high-sensitivity (hs-) CRP serum concentrations compared with passive commuting. Results We observed that daily active commuting for 45 min or more (vs. none) was associated with lower hs-CRP [% mean difference in the main model: −16.8%; 95% confidence interval (CI) −25.6% to −7.0%), and results were robust to adjustment for leisure-time and occupational physical activity, as well as diet. Similarly, active commuting for 15–29 min daily was associated with lower hs-CRP in the main model (−7.4; 95% CI −14.1 to −0.2), but the association attenuated to null after further adjustments. In subgroup analyses, associations were only observed for women. Conclusions Active commuting for at least 45 min a day was associated with lower levels of low-grade inflammation. Promoting active modes of transport may lead not only to reduced emissions from motorized traffic but also to population-level health benefits.

BackgroundExposure to natural environments is thought to be beneficial for human health, but the evidence is inconsistent.ObjectiveTo examine whether exposure to green and blue spaces in urban environments is associated with mental and physical health in Finland.MethodsThe 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.ResultsAmounts 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.ConclusionsFrequent 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.