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Background: Transportation noise is increasingly acknowledged as a cardiovascular risk factor, but the evidence base for an association with stroke is sparse., Objective: We aimed to investigate the association between transportation noise and stroke incidence in a large Scandinavian population., Methods: We harmonized and pooled data from nine Scandinavian cohorts (seven Swedish, two Danish), totaling 135,951 participants. We identified residential address history and estimated road, railway, and aircraft noise for all addresses. Information on stroke incidence was acquired through linkage to national patient and mortality registries. We analyzed data using Cox proportional hazards models, including socioeconomic and lifestyle confounders, and air pollution., Results: During follow-up ( median = 19.5 y ), 11,056 stroke cases were identified. Road traffic noise ( L den ) was associated with risk of stroke, with a hazard ratio (HR) of 1.06 [95% confidence interval (CI): 1.03, 1.08] per 10-dB higher 5-y mean time-weighted exposure in analyses adjusted for individual- and area-level socioeconomic covariates. The association was approximately linear and persisted after adjustment for air pollution [particulate matter (PM) with an aerodynamic diameter of ≤ 2.5 μ m ( PM 2.5 ) and NO 2 ]. Stroke was associated with moderate levels of 5-y aircraft noise exposure (40-50 vs. ≤ 40  dB ) ( HR = 1.12 ; 95% CI: 0.99, 1.27), but not with higher exposure ( ≥ 50  dB , HR = 0.94 ; 95% CI: 0.79, 1.11). Railway noise was not associated with stroke., Discussion: In this pooled study, road traffic noise was associated with a higher risk of stroke. This finding supports road traffic noise as an important cardiovascular risk factor that should be included when estimating the burden of disease due to traffic noise. https://doi.org/10.1289/EHP8949.

In epidemiological studies, levels of PM2.5 need to be estimated over time and space. Because of logistical constraints, very few studies have been conducted to assess the variability within and across homes and the predictors of this variability. This study evaluated within- and between-home variability of indoor PM2.5 and identified predictors for PM2.5 in homes of mothers participating in the urban Mother and Child in the Environment birth cohort study in Durban, South Africa. Thirty homes were selected from 300 homes that were previously sampled for PM2.5. Two measurements of PM2.5 levels were conducted in each home within a 1 week interval in both warm and cold seasons (four samplings per home) using Airmetrics MiniVol samplers. A linear mixed-effect model was used to evaluate within- and between-home variability and to identify fixed effects (predictors) that result in reduced variability. The PM2.5 levels in the 30 homes ranged from 2 to 303 μg m-3. The within-home variability accounted for 94% of the total variability in the log-transformed PM2.5 levels for the 30 homes. The fixed effects extracted from the repeated samplings in the present study were used to improve a previously developed multivariable linear regression model for 300 homes, and thereby increased the R2 from 0.50 to 0.54. Inclusion of fixed-effects in multivariable linear regression models resulted in a reasonably robust model that can be used to predict PM2.5 levels in unmeasured homes of the cohort.

We conducted a study within the framework of the interdisciplinary European Mercury Emission from Chloralkali Plants (EMECAP) project to assess exposure to mercury (Hg) and the contribution of Hg emissions from a mercury cell chloralkali plant to urinary mercury (U-Hg) in adults living near the plant. We collected data from questionnaires and first morning urine samples from 75 subjects living near the Tarnow plant in Poland and 100 subjects living in a reference area. Median U-Hg was 0.32 mug/g creatinine (microg/gC) and 0.20 microg/gC, respectively. The median U-Hg was also higher in the amalgam-free subjects living near the plant (0.26 microg/gC) than in the reference group (0.18 microg/gC), but no such association was found in a multivariate analysis. There was a statistically significant positive association between U-Hg and number of teeth with amalgams, a negative association with age and a tendency towards higher U-Hg in female subjects. In the amalgam-free subjects there were statistically significant effects of female sex and fish consumption, and a negative association with age. The additional long-term average air Hg concentration from the plant, based on EMECAP environmental measurements and modelling, was estimated to be 1-3.5 ng/m(3) for the residential study area and should have a very small effect on U-Hg. The other Hg emission sources such as coal combustion facilities located nearby should be taken into account in assessing the overall impact of air Hg on U-Hg in this area.

Personal exposures and indoor, residential outdoor, and urban background levels of PM(2.5) and PM(1) were measured simultaneously in Göteborg, Sweden. A total of 270 24 hour samples from 30 subjects were analyzed for elemental concentrations using X-ray fluorescence (XRF) spectroscopy. Personal exposures to PM(2.5) were significantly higher for Cl, Ca, Ti, and Fe compared with the other locations. For most elements, residential outdoor levels were significantly higher than urban background levels. Correlations between personal exposure and stationary measurements were moderate to high for Zn, Br, and Pb (r(s)= 0.47-0.81), while Ca and Cu showed low correlations. The penetration indoors from outdoors was 0.7, as calculated from S and Pb ratios. For the pairs of parallel PM(1) and PM(2.5) measurements, only Ca and Fe levels were significantly lower for PM(1) at all sites. Significant correlations were found between urban background mass concentrations and personal exposure levels for elements attributed to combustion processes (S, V, and Pb) and resuspended dust (Ti, Fe, and Zn), indicating that both sources could be relevant to health effects related to urban background mass. Air mass origin strongly affected the measured urban background concentrations of some elements (S, Cl, V, Ni, Br, and Pb). These findings were also seen for personal exposure (S, Cl, V, and Pb) and indoor levels (S, Cl, V, Ni, and Pb). No differences were seen for crustal elements. Air mass origin should be taken into account in the description and interpretation of time series studies of air pollution and health.

Formaldehyde is a ubiquitous environmental pollutant and is probably carcinogenic to humans. Exposure to formaldehyde was investigated in the general population with personal as well as stationary measurements. The results from two campaigns in two Swedish cities are presented, including measurements of personal exposure among a total of 65 randomly selected subjects together with simultaneous measurements of individual indoor and outdoor concentrations. Diffusive GMD samplers were placed in the breathing zone, in the participants' bedrooms, and outside their homes for 24 h in campaign A and six days in campaign B. Repeated measurements were also conducted in order to study the variability between and within individuals. Median personal exposure to formaldehyde was 22 microg/m(3) (campaign A) and 23 microg/m(3) (campaign B), which is within the guideline value range of 12-60 microg/m(3) proposed in Sweden. Bedroom concentrations were generally slightly higher than personal exposure, while outdoor concentrations (measured only in campaign B) were low. In campaign B, the stationary measurements were used to model personal exposure. Bedroom concentrations were found to explain 90% of the variation of the measured personal exposure and predicted personal exposure nearly as well as an extended model that also included the outdoor contribution. Subjects living in single-family houses had significantly higher exposure to formaldehyde compared with subjects living in apartments. The 24-h and 6-day sampling periods yield a relatively low within-individual variability for formaldehyde measurements with GMD samplers.

Biological monitoring of mercury in whole blood (B-Hg) or urine (U-Hg) can be used to assess exposure to mercury vapor if the kinetics and other sources of variation are taken into account. Its rapid rise postexposure makes B-Hg a good indicator of recent exposure peaks, while U-Hg (corrected for urinary flow rate) reflects average long-term exposure. However, high intraindividual variation sometimes requires the average of several U-Hg determinations. In the general population, methylmercury from fish and mercury from dental amalgam influence B-Hg and U-Hg, respectively, and must be considered if other exposures are being monitored. The quantitative relations between mercury in biological fluids and critical organs are poorly understood. Monitoring U-Hg is useful for assessing the risk of adverse effects and the need for preventive measures. At average U-Hg levels of about 50 micrograms.g creatinine-1 (28 nmol.mmol creatinine-1) the prevalence of symptoms and slight objective changes in the central nervous system and the excretion of certain urinary proteins are increased.