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Exposure to particulate air pollution increases total natural and cardiovascular mortality. However, it is less clear which types and sources of particles are the most harmful. We analyzed associations between long-term exposure to source-specific locally emitted particles and total natural and cardiovascular mortality in Swedish cohorts. Using high-resolution dispersion models of particles from different sources, and address registries, we assigned annual individual residential mean concentrations to population-based cohorts in Gothenburg, Stockholm and Umeå 1990–2011. Time and cause of death were assigned from registries. Associations between long-term mean lagged exposures and mortality were estimated using Cox regression models adjusted for possible confounders, and meta-analyzed. 7344 natural deaths, including 2755 cardiovascular deaths, occurred among the 68,679 participants. Exposure levels were moderate but generally above the WHO 2021 guidelines. We observed positive associations with natural mortality for the last five years of exposure to road traffic exhaust particles (HR 1.02, 95% CI 1.00-1.04, per IQR, and 1.10, 95% CI 1.00-1.22, per 1 µg/m3), and road wear particles (HR 1.02, 95% CI 1.00-1.04, per IQR, and HR 1.02, 95% CI 1.00-1.03, per 1 µg/m3), but not for particles from residential heating. Adjustment for road traffic noise, or particles from residential heating, did not substantially affect the results for traffic-related particles. For cardiovascular mortality, associations with particles from both sources were positive but not statistically significant. Natural mortality was associated with local emissions of traffic-related particles in a multi-cohort study at moderate exposure-levels, lending some support for further efforts to reduce traffic emissions.

Fine particulate matter (PM2.5) is a well-known risk factor for premature mortality; however, the relative effect size varies between different studies. The current study aims to estimate the concentration–response function (CFR) between all-cause mortality and PM2.5 while adjusting for differences in population characteristics and exposure assessment method. Separate functions by exposure assessment method by dispersion, land use regression (LUR), and hybrid models as well as monitoring station measurements and by model resolution will be provided. We used the same keywords as those in the review by Chen and Hoek (2020), which included studies up to October 2018. Our updated search covered the period from July 1, 2018, to May 15, 2023, to include more recent publications. A random-effects meta-regression model was developed using the metafor package in R to account for variations in exposure estimates. Exposure assessment methods were categorized into Monitoring, Land-Use Regression (LUR), Dispersion Modeling, and Hybrid approaches, and spatial resolution was classified as high (≤ 1 km) or low (> 1 km). We evaluated linear, logarithmic, inverse, and inverse square root transformations as potential parametric forms of the CRF and selected the one that provided the best fit according to the Akaike Information Criterion (AIC). Additionally, spline-based modeling was employed to test for deviations from this parametric forms in the CFR. The analysis identified 68 eligible studies, incorporating diverse exposure assessment methodologies and geographic regions. In the fully adjusted model, the relative risk (RR) per 10 µg/m3 higher PM2.5 concentration at a mean exposure of 10 µg/m3 was 1.22 (95% CI: 1.02–1.47) and at a mean exposure of 17.85 µg/m3 1.15, (95% CI: 0.97–1.36). In the subgroup analysis, the best-fitting functional form for the CRF varied by exposure assessment method: linear for monitoring, logarithmic for LUR, and inverse for dispersion and hybrid models. For resolution, logarithmic fit best for low-resolution models, and inverse square root for high-resolution models. This study underscores the role of modeling choices in quantifying PM2.5-related health risks. Our analysis offers an updated increased CRF, including the recent evidence, for use in global health risk assessments of particulate air pollution.

Background: Although physical activity is associated with cardiovascular health benefits and reduced all-cause mortality, vigorous exertion is also recognized as a trigger for sudden cardiac death (SCD). This study investigated vigorous exertion as a trigger for SCD resulting from myocardial infarction (MI) and the potential modifying effect of habitual vigorous exercise training among Swedish men who subsequently experienced SCD due to MI.

Methods: This prospective nested case-crossover study was performed within the Västerbotten Intervention Programme cohort from 1985 to 2006 and included male participants who later experienced SCD caused by MI. The risk of SCD during and within 30 min of vigorous exertion was compared with the risk during periods of non-exertion. Participants were categorized into three groups according to baseline frequency of habitual vigorous exercise training to assess effect modification.

Results: We included 192 men with SCD caused by MI, with a mean time from screening to event of 6.5 years. A majority of cases reported physical inactivity, with 161 cases reporting no exercise or <1 exercise event per week. 24 men suffered SCD in relation to vigorous exertion, yielding a relative risk of 43.6 (95% CI: 27.1-70.3) compared to non-exertion. The highest relative risk (107.7 [95% CI: 63.4-182.9]) was found among physically inactive men and was mitigated by a higher frequency of habitual exercise training at baseline.

Conclusion: Among Swedish men who experienced SCD caused by MI, vigorous exertion was associated with a transiently increased risk, which was mitigated by higher levels of habitual vigorous exercise training.

The European Union (EU) Ambient Air Quality Directive (AAQD) and Drinking Water Directive (DWD) are aimed at maintaining and improving air quality and ensuring high standards for potable water across the EU. Besides several other indicators, the AAQD and DWD consist of chemical parameters (substances or substance groups) that are regulated within this framework. All the substances are associated with various health outcomes, and many of them are classified as carcinogenic or probably/possibly carcinogenic with causal links. To quantify the health burden of the chemical substances included in the AAQD and DWD, we need information regarding population exposure, current baseline mortality/morbidity rates in the populations, and exposure-response functions (ERFs) or unit risks (URs) from previous epidemiological studies. During this study, we analyzed the availability of ERFs or URs and discussed their applicability in health impact assessments (HIAs). From the HIA perspective, ERFs─in terms of relative risk (RR), standardized mortality ratio (SMR), odds ratio (OR), or UR data─were available for many of the analyzed substances. However, for some substances such as acrylamide, antimony, boron, chlorate and chlorite, copper, microcystin-LR, and selenium, no risk measures could be identified. The aim of this study is to derive ERFs, which will allow HIAs for a larger number of chemicals when exposure data and baseline mortality/morbidity data are available. Currently, HIAs have largely focused only on main ambient pollutants such as particulate matter (PM10), fine particulate matter (PM2.5), nitrogen oxides (NOX), and ozone (O3). In contrast, health risks related to exposure to chemicals are much more diverse, and the health burdens should be quantified to a much greater extent.

Background:The impact of air pollution and road traffic noise on depression remains inconclusive. This study examined long-term residential exposure to air pollutants and road traffic noise in relation to dispensed antidepressant medications.

Methods:A cohort study was conducted using the Swedish Malmö Diet and Cancer Study, with the outcome defined as a first dispensed antidepressant (ATC: N06A) and/or a first clinical depression diagnosis (ICD-10: F32/F33) during follow-up (2007–2011). Exposure was assessed through modelled annual mean concentrations of particulate matter (PM2.5, PM10), nitrogen oxides (NOx), and road traffic noise (Lden). Cox proportional hazards regression was applied, adjusted for potential confounders including sociodemographic and lifestyle factors.

Results:A total of 18 373 individuals were included, among whom 2224 with the outcome (89 % had dispensed antidepressant, 6 % both clinical diagnosis and antidepressant, and 5 % clinical diagnosis) during follow-up. Increased hazard ratios (HRs) were observed in association with long-term air pollution exposure, but only among women. Increased but statistically non-significant HRs were found for road traffic noise in women, while no associations were found in men. For lag1-5 (1–5 years exposure window prior to the event) in women, HRs per 10-unit increase were: PM2.5, 1.29 (95 % CI, 1.09–1.52); PM10, 1.10 (1.03–1.17); NOx, 1.15 (1.04–1.26); and Lden, 1.06 (0.99–1.13). Similar patterns were found for lag1 and in the two-pollutant models.

Conclusion:Long-term exposure to air pollution was positively associated with dispensed antidepressant medications in women but not in men. For road traffic noise, evidence was less clear, but a potential link was seen in women. Though associations were seen only in women, the findings suggest that air quality improvements and possibly also noise reductions may help reduce health burdens related to depressive symptoms.

Background: Studies on long-term exposure to air pollution at high levels suggest an association with increased risk of metabolic syndrome (MetS). We aimed to study this relationship at very low levels, less well-studied, yet of public health importance.

Methods: The Swedish CArdioPulmonary bioImage Study (SCAPIS) consists of randomly selected subjects aged 50–64 years from six large cities in Sweden (n = 30,154). Participants underwent medical examination and answered a health-related questionnaire at enrolment. MetS was defined using established criteria. Residential exposure to PM2.5 and NO2 was modelled annually for each subject over 10 years before enrolment. Adjusted prevalence ratios (adj PR) were calculated both by quartiles of exposure and per 1 μg/m3 increment in PM2.5 and NO2, with adjustments for age, lifestyle and socioeconomic factors.

Results: Full information on exposure, covariates, and MetS was obtained for 13,997 (90.26 %) females and 12,978 (88.61 %) males, respectively. The 10-years mean exposures of PM2.5 and NO2 before enrolment were 6.57 and 11.47 μg/m3, respectively. The prevalence of MetS was 28.75 % in females and 38.20 % in males, respectively. Quartile analysis of PM2.5 did not reveal significant increased adj PR for MetS, neither in females nor in males. For females the adj PR per 1 μg/m3 was 0.91 (0.89–0.94) and for males 0.95 (0.92–0.97), respectively. Similar, but somewhat weaker, associations were seen for NO2.

Conclusion: Some inverse associations between air pollution and MetS were observed, but these results should be interpreted with caution due to limitations in the cross-sectional design. Results should not be interpreted beyond our studied exposure range.

Trafikverket har beviljat Institutionen för folkhälsa och klinisk medicin, Umeå universitet ett FOI-bidrag för projektet Reviderat underlag om hälsokonsekvenser av luftföroreningar, vilket ska komplettera underlagen om luftföroreningars hälsoeffekter till grund för rekommendationer i rapporten Analysmetod och samhällsekonomiska kalkylvärden för transportsektorn (ASEK-rapporten).

Projektets fyra delmoment syftar till

• att analysera hur morbiditetseffekter av kvävedioxid i sig kan uppskattas med direkta beräkningar
• att studera hur de i ASEK beräknade ohälsokostnaderna för slitageemissioner som PM10 påverkas av senare års resultat om sambanden mellan PM10, slitagepartiklar och mortalitet
• att bedöma vilka effekter av vägtrafikens föroreningar, specifikt kväveoxider och partiklar, på barns hälsa som det finns olika grad av evidens för och hur konsekvenserna kan uppskattas och värderas
• att föreslå en metod att uppskatta kostnader för emissioner genererande exponering för sekundärt bildade partiklar

Background: The association between socioeconomic status (SES) and environmental burden is context-dependent. Those with low SES may be more likely to live near major roads and industries where environmental exposures are high but may also be more likely to live further away from city centers. The aim of this study was to investigate the association between SES and environmental burden in Sweden.

Methods: The Swedish CArdioPulmonary bioImage Study (SCAPIS) cohort recruited participants from six Swedish cities during 2013–2018. Residential environmental exposures (particulate matter <2.5 µm [PM2.5], road traffic noise, and lack of greenspace) and neighborhood-level SES factors (proportions with low-income, low education, unemployment, rental units, foreign born) were assessed from participants’ addresses in 2018. Individual-level SES factors (financial buffer, education, occupation, type of living, foreign born) were obtained from a questionnaire and neighborhood data from Statistics Sweden. Linear regression models were used to analyze the link between environmental exposures and SES factors. Correlations between SES factors were analyzed using Cramér's V and Spearman rank correlations.

Results: The study included 23 320 SCAPIS participants in 1939 neighborhoods. The explanatory power of SES factors differed substantially between factors and cities. A model with all ten SES factors could account for 25–88 %, 36–60 %, and 49–81 % of the spatial variance in PM2.5, noise, and lack of greenspace respectively. Neighborhoods with more low-income earners, rental units and foreign born had more environmental burden. Neighborhoods with more inhabitants with low education and unemployment had less environmental burden. Associations were generally non-linear. Individual-level SES factors were not associated with environmental burdens after adjusting for neighborhood SES factors. Individual and neighborhood SES were weakly correlated.

Conclusion: Neighborhood SES factors accounted for a large proportion of the variance in environmental burdens, whereas individual SES factors did not. The relationship between SES and environmental burden differed greatly between indicators and cities.

Objectives: Socioeconomic status (SES) is in many cases related to air pollution exposure, but less is known about its effects on susceptibility to air pollution. The main aim of this study was to analyse the impact of SES on health effects associated with exposure to fine particles (PM_2.5).

Methods: Firstly, a systematic literature review of studies analysing the impacts of SES on health effects related to air pollution exposure was carried out. Secondly, a meta-analysis was performed by analysing studies on long-term mortality associated with exposure to PM_2.5 divided into different SES groups.

Results: The meta-analysis showed that the relative risk (RR) for all-cause mortality associated with PM_2.5 did not depend on individual education or income. It also revealed that adjustment for individual lifestyle factors (such as smoking, alcohol intake, physical activity, eating behaviours, and body mass index), in addition to adjustment for SES, did not significantly change the RR.

Conclusion: The association between all-cause mortality and PM_2.5 did not depend on education or individual income. Due to the high heterogeneity observed, further studies are required to draw firm conclusions.

Background: Residential greenness is linked to health, but its relationships with environmental exposures and lifestyle factors—often treated as confounders or mediators—are less clear.

Objective: We investigated the associations between residential greenness and air pollution, traffic noise and lifestyle factors (smoking, alcohol consumption, leisure-time physical activity) at six study sites in the S wedish CA rdio P ulmonary bio I mage S tudy (SCAPIS), using waist circumference as an illustrative outcome.

Methods: Greenness assessment was based on the average 5-year pre-recruitment values of Normalized Difference Vegetation Index (NDVI) within 250 m buffers around participants’ residences (n = 29,376; 50–65 years). We used linear regression to estimate associations between NDVI and fine particulate matter (PM2.5), respirable particulate matter (PM10), nitrogen dioxide (NO2) road traffic noise (Lden), and waist circumference; logistic regression to estimate associations between NDVI and smoking, alcohol consumption and sedentary lifestyle.

Results: NDVI (mean 0.47; range 0.08–0.79) varied across SCAPIS sites. Higher greenness was associated with lower air pollution and traffic noise and lower smoking and alcohol consumption, but not with sedentary lifestyle. Waist circumference (mean 89.4 cm in women; 99.7 cm in men) differed by site, but showed no independent association with greenness, after adjustment for urbanicity, site and socioeconomic variables. SCAPIS participants more often lived in urban, less green areas than the general population.

Significance: Greenness relates to environmental and lifestyle factors, partly in site-specific ways, underscoring the need to carefully consider what we adjust for in greenness epidemiology.