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Air pollution's short-term effects on a wide range of health outcomes have been studied extensively, primarily focused on vulnerable groups (e.g., children and the elderly). However, the air pollution effects on the adult working population through sick leave have received little attention. This study aims to 1) estimate the associations between particulate matter ≤2.5 μm³ (PM_2.5) and sick leave episodes and 2) calculate the attributable number of sick leave days and the consequential productivity loss in the City of Stockholm, Sweden. Individual level daily sick leave data was obtained from Statistics Sweden for the years 2011–2019. Daily average concentrations of PM_2.5 were obtained from the main urban background monitoring station in Stockholm. A case-crossover study design was applied to estimate the association between short-term PM_2.5 and onset of sick leave episodes. Conditional logistic regression was used to estimate the relative increase in odds of onset per 10 μg/m³ of PM_2.5, adjusting for temperature, season, and pollen. A human capital method was applied to estimate the PM2.5 attributable productivity loss. In total, 1.5 million (M) individual sick leave occurrences were studied. The measured daily mean PM_2.5 concentration was 4.2 μg/m³ (IQR 3.7 μg/m³). The odds of a sick leave episode was estimated to increase by 8.5% (95% CI: 7.8–9.3) per 10 μg/m³ average exposure 2–4 days before. Sub-group analysis showed that private sector and individuals 15–24 years old had a lower increase in odds of sick leave episodes in relation to PM_2.5 exposure. In Stockholm, 4% of the sick leave episodes were attributable to PM_2.5 exposure, corresponding to €17 M per year in productivity loss. Our study suggests a positive association between PM_2.5 and sick leave episodes in a low exposure area.

Few studies have explored the influence of socioeconomic status (SES) on the heat vulnerability of mental health (MH) patients. As individual socioeconomic data was unavailable, we aimed to fill this gap by using the healthcare system type as a proxy for SES. Brazilian national statistics indicate that public patients have lower SES than private. Therefore, we compared the risk of emergency department visits (EDVs) for MH between patients from both healthcare types. EDVs for MH disorders from all nine public (101,452 visits) and one large private facility (154,954) in Curitiba were assessed (2017–2021). Daily mean temperature was gathered and weighed from 3 stations. Distributed-lag non-linear model with quasi-Poisson (maximum 10-lags) was used to assess the risk. We stratified by private and public, age, and gender under moderate and extreme heat. Additionally, we calculated the attributable fraction (AF), which translates individual risks into population-representative burdens – especially useful for public policies. Random-effects meta-regression pooled the risk estimates between healthcare systems. Public patients showed significant risks immediately as temperatures started to increase. Their cumulative relative risk (RR) of MH-EDV was 7.5 % higher than the private patients (Q-Test 26.2 %) under moderate heat, suggesting their particular heat vulnerability. Differently, private patients showed significant risks only under extreme heat, when their RR became 4.3 % higher than public (Q-Test 6.2 %). These findings suggest that private patients have a relatively greater adaptation capacity to heat. However, when faced with extreme heat, their current adaptation means were potentially insufficient, so they needed and could access healthcare freely, unlike their public counterparts. MH patients would benefit from measures to reduce heat vulnerability and access barriers, increasing equity between the healthcare systems in Brazil. AF of EDVs due to extreme heat was 0.33 % (95%CI 0.16;0.50) for the total sample (859 EDVs). This corroborates that such broad population-level policies are urgently needed as climate change progresses.

BACKGROUND: Incident cases of stroke, myocardial infarction, and preterm birth have established exposure-response functions associated with air pollution. However, there are no studies reporting detailed costs per case for these health outcomes that are adapted to the cost-benefit tools that guide the regulation of air pollution.

OBJECTIVES: The primary objective was to establish non-fatal per-case monetary estimates for stroke, myocardial infarction, and preterm birth attributable to air pollution in Sweden, and the secondary objective was to ease the economic evaluation process of air pollution morbidity effects and their inclusion in cost-benefit assessments.

METHODS: Based on recommendations from the literature, the case-cost analysis considered direct and indirect medical costs, as well as production losses and informal costs relevant for the calculation of the net present value. A literature search was conducted to estimate the costs of each category for each incident case in Sweden. Informal costs were estimated using the quality-adjusted life-years approach and the corresponding willingness-to-pay in the Swedish population. The total average per-case cost was estimated based on specific health outcome durations and severity and was discounted by 3.5% per year. Sensitivity analysis included varying discount rates, severity of health outcome, and the range of societal willingness to pay for quality-adjusted life years.

RESULTS: The average net present value cost estimate was €2016 460k (185k-1M) for non-fatal stroke, €2016 24k (16k-38k) for myocardial infarction, and €2016 34k (19k-57k) for late preterm birth. The main drivers of the per-case total cost estimates were health outcome severity and societal willingness to pay for risk reduction. Varying the discount rate had the largest effect on preterm birth, with costs changing by ±30% for the discount rates analysed.

RECOMMENDATION: Because stroke, myocardial infarction, and preterm birth have established exposure-response functions linking these to air pollution, cost-benefit analyses should include the costs for these health outcomes in order to adequately guide future air pollution and climate change policies.

Record-breaking temperatures were recorded across the globe in 2023. Without climate action, adverse climate-related health impacts are expected to worsen worldwide, affecting billions of people. Temperatures in Europe are warming at twice the rate of the global average, threatening the health of populations across the continent and leading to unnecessary loss of life. The Lancet Countdown in Europe was established in 2021, to assess the health profile of climate change aiming to stimulate European social and political will to implement rapid health-responsive climate mitigation and adaptation actions. In 2022, the collaboration published its indicator report, tracking progress on health and climate change via 33 indicators and across five domains.

This new report tracks 42 indicators highlighting the negative impacts of climate change on human health, the delayed climate action of European countries, and the missed opportunities to protect or improve health with health-responsive climate action. The methods behind indicators presented in the 2022 report have been improved, and nine new indicators have been added, covering leishmaniasis, ticks, food security, health-care emissions, production and consumption-based emissions, clean energy investment, and scientific, political, and media engagement with climate and health. Considering that negative climate-related health impacts and the responsibility for climate change are not equal at the regional and global levels, this report also endeavours to reflect on aspects of inequality and justice by highlighting at-risk groups within Europe and Europe's responsibility for the climate crisis.

Background and aims: Climate change affects our societies and lives through our economies, our livelihoods, and our health. Economic losses of climate change are estimated at $23 trillion, largely through externalities due to premature mortality, healthcare expenditure, and health-related work losses. Even if there are established methods to quantify the health economic burden, there is limited information on how people perceive this information. The current study aimed to examine different health cost evaluation methods and observe perceptions of stakeholders in the climate change context.

Method: The participatory research approach of the World Café with 41 participants was applied to explore four topics associated with valuing the costs of climate change. The data were analyzed following an inductive approach.

Results: Despite the willingness-to-pay approach being widely applied, many experts see actual healthcare costs as a more explicit indicator of costs; however, this approach might underestimate actual costs. Participants experienced difficulties accepting and understanding cost estimates that indicated very high externalities as a percentage of gross domestic product. The cost-effectiveness of mitigation and adaptation measures was also challenged by a concern that while the costs of such measures are incurred now, the benefits do not come to fruition until later, for example, when building bike lanes or dams.

Conclusions: Policies should favor environmentally friendly activities such as making cycling more convenient in cities with the health benefits presented in monetary terms, while limiting car driving. Moreover, the public might better understand the costs of climate change via tools that map how solutions influence different sectors and outlining the costs in evaluating the benefits for health and the environment.

Transportation noise is a growing public health concern worldwide, especially in urban areas, causing annoyance, sleep disturbance, cardiovascular diseases and other health effects. Recently, European Commission (EC) has developed a mutual methodology for assessing health impacts of transportation noise in European Union using strategic noise mapping. Applying this methodology, our aim was to quantify the health effects of road, rail and aircraft noise in two Estonian cities, Tallinn and Tartu. We also aimed to assess sensitivity of this methodology, while implementing lower threshold values and employing additional health outcomes.

The proportion of highly annoyed residents due to road traffic noise was 11.6% in Tallinn, and 9.2% in Tartu; around 2.5% residents in both cities could have high sleeping disturbances. As exposure to railway and aircraft noise was relatively low in both cities, people with high annoyance and high sleep disturbance caused by railway and aircraft noise was below 1%. Ischemic heart disease (IHD) cases attributable to road traffic noise was estimated to be 122.6 in Tallinn and 21.5 in Tartu. Altogether transportation noise was estimated to cause 1807 disability adjusted life years (DALYs) in Tallinn and 370 DALYs in Tartu. The health costs were calculated as €126.5 and €25.9 million annually, respectively in the two cities.

When we included higher number of health outcomes (stroke incidence, IHD deaths) and lowered exposure threshold by 5 dB, the annual burden of disease was doubled. As the latest epidemiological studies showed transportation noise having larger number of effects on lower noise levels, the results with the currently applied European Commission health impact assessment (HIA) methodology were rather conservative. Despite of uncertainties associated to applied methodology, transportation noise, especially road traffic noise, is an important environmental risk factor, that leads to considerable loss of healthy life years and causes large health costs in urban areas.

Introduction: Part of the European Strategy to achieve climate neutrality in the transport sector is to increase the proportion of electric vehicles (EVs) and active commuting. Health co-benefits from reduced air pollution and increased active commuting are assumed to follow; however, all dimensions of expected health effects are not quantified nor valued monetarily. Current state-of-the art health impact assessments (HIAs) of air pollution assume immediate change in health with exposure; however, the time-window of importance for health outcomes is unknown. Moreover, the currently applied risk estimate of sick leaves in relation to air pollution is poorly generalizable due to outdated exposure assessment and subjective data on outcome. The overall aim of this thesis is to assess the health economic effects of sustainable urban transport solutions and improve the epidemiological knowledge base of air pollution effects. 

Methods: The health effects of increased active commuting and the resulting change in air pollution exposure were valued monetarily from a health care perspective, and a cost-effectiveness analysis of investment in bicycle infrastructure was conducted. A health economic assessment from a societal perspective was also conducted for an increased proportion of EVs in the vehicle fleet, considering a change in both exhaust and non-exhaust particles. The exposure-lag response between air pollution and risk for ischemic heart disease (IHD) and stroke was assessed in a multi-cohort study using distributed lag-nonlinear models (DLNMs). A case cross-over study design was applied to estimate the odds of sick leaves in relation to short-term PM_2.5 exposure, and production losses were valued using the human capital method. 

Results: Investing in bicycle infrastructure to enable increased active commuting was estimated to be cost-effective from a health care perspective. An increased proportion of EVs was estimated to decrease population-weighted PM_2.5 concentrations without the use of studded winter tires, but was estimated to increase with the current use of studded winter tires in Stockholm Sweden. For a 0-50% use of studded winter tires the health economic costs ranged between €20 and €122 million (M). An independent effect of PM_2.5 on sick leaves was estimated to correspond to €2M per year in productivity loss for the population of Stockholm municipality. Exposure time windows closer in time and local sources of air pollution were suggested to be of greater importance for incident IHD and stroke.

Conclusions: This thesis has demonstrated the health economic potential in policies seeking to transform the transport sector towards sustainability. Investment in the transport sector could lead to decreased morbidity and decreased monetary burden in the health care sector. Non-exhaust particles should be considered in order to fully assess the health economic effects of EVs. Moreover, the risk estimate of sick leaves in relation to air pollution exposure could be included in international HIAs.

Long-term air pollution exposure increases the risk for cardiovascular disease, but little is known about the temporal relationships between exposure and health outcomes. This study aims to estimate the exposure-lag response between air pollution exposure and risk for ischemic heart disease (IHD) and stroke incidence by applying distributed lag non-linear models (DLNMs). Annual mean concentrations of particles with aerodynamic diameter less than 2.5 µm (PM2.5 ) and black carbon (BC) were estimated for participants in five Swedish cohorts using dispersion models. Simultaneous estimates of exposure lags 1–10 years using DLNMs were compared with separate year specific (single lag) estimates and estimates for lag 1–5-and 6–10-years using moving average exposure. The DLNM estimated no exposure lag-response between PM2.5 total, BC, and IHD. However, for PM2.5 from local sources, a 20% risk increase per 1 µg/m3 for 1-year lag was estimated. A risk increase for stroke was suggested in relation to lags 2–4-year PM2.5 and BC, and also lags 8–9-years BC. No associations were shown in single lag models. Increased risk estimates for stroke in relation to lag 1–5-and 6–10-years BC moving averages were observed. Estimates generally supported a greater contribution to increased risk from exposure windows closer in time to incident IHD and incident stroke.

Introduction: Electric vehicles (EVs) are heavily promoted as beneficial for climate and health. In most studies, it is assumed that EVs contribution to urban air pollution is zero due to no tailpipe emissions, ignoring the contribution of non-exhaust particles (brake, tire and road wear), which are unregulated in EU. This study of Stockholm, Sweden, aims to 1) assess how a future vehicle fleet impacts concentrations of particles of size less than 2.5 μm (PM2.5) and evaluate the expected health outcomes economically and 2) compare this with CO2 savings.

Methods: Source specific dispersion models of exhaust and non-exhaust PM2.5 was used to estimate the population weighted concentrations. Thereafter exposure differences within a business as usual (BAU2035) and a fossil free fuel (FFF2035) scenario were used to assess expected health and economic impacts. The assessment considered both exhaust and non-exhaust emissions, considering the vehicle weight and the proportion of vehicles using studded winter tires. Health economic costs were retrieved from the literature and societal willingness to pay was used to value quality-adjusted life-years lost due to morbidity and mortality.

Results: The mean population weighted exhaust PM2.5 concentration decreased 0.012 μg/m3 (39%) in FFF2035 as compared to BAU2035. Assuming 50% higher road and tire wear PM2.5 emission because of higher weight among EVs and 30% less brake wear emissions, the estimated decrease in wear particle exposures were 0.152 (22%) and 0.014 μg/m3 (1.9%) for 0 and 30% use on studded winter tires, respectively. The resulting health economic costs were estimated to €217M and €32M, respectively. An increase by 0.079 μg/m3 (11%) was however estimated for 50% use of studded winter tires, corresponding to an €89M increase in health costs.

Conclusion: Considering both exhaust and wear generated particles, it is not straight forward that an increase of EVs will decrease the negative health impacts.

BACKGROUND: Alzheimer's disease (AD) and other dementias currently represent the fifth most common cause of death in the world, according to the World Health Organization, with a projected future increase as the proportion of the elderly in the population is growing. Air pollution has emerged as a plausible risk factor for AD, but studies estimating dementia cases attributable to exposure to fine particulate matter (PM_2.5) air pollution and resulting monetary estimates are lacking.

METHODS: We used data on average population-weighted exposure to ambient PM_2.5 for the entire population of Sweden above 30 years of age. To estimate the annual number of dementia cases attributable to air pollution in the Swedish population above 60 years of age, we used the latest concentration response functions (CRF) between PM_2.5 exposure and dementia incidence, based on ten longitudinal cohort studies, for the population above 60 years of age. To estimate the monetary burden of attributable cases, we calculated total costs related to dementia, including direct and indirect lifetime costs and intangible costs by including quality-adjusted life years (QALYs) lost. Two different monetary valuations of QALYs in Sweden were used to estimate the monetary value of reduced quality-of-life from two different payer perspectives.

RESULTS: The annual number of dementia cases attributable to PM_2.5 exposure was estimated to be 820, which represents 5% of the annual dementia cases in Sweden. Direct and indirect lifetime average cost per dementia case was estimated to correspond € 213,000. A reduction of PM_2.5 by 1 μg/m³ was estimated to yield 101 fewer cases of dementia incidences annually, resulting in an estimated monetary benefit ranging up to 0.01% of the Swedish GDP in 2019.

CONCLUSION: This study estimated that 5% of annual dementia cases could be attributed to PM_2.5 exposure, and that the resulting monetary burden is substantial. These findings suggest the need to consider airborne toxic pollutants associated with dementia incidence in public health policy decisions.