Assessment of short-term heat effects on cardiovascular mortality and vulnerability factors using small area data in Europe.

BACKGROUND: Short-term associations between heat and cardiovascular disease (CVD) mortality have been examined mostly in large cities. However, different vulnerability and exposure levels may contribute to spatial heterogeneity. This study assessed heat effects on CVD mortality and potential vulnerability factors using data from three European countries, including urban and rural settings. METHODS: We collected daily counts of CVD deaths aggregated at the small-area level in Norway (small-area level: municipality), England and Wales (lower super output areas), and Germany (district) during the warm season (May-September) from 1996 to 2018. Daily mean air temperatures estimated by spatial-temporal models were assigned to each small area. Within each country, we applied area-specific Quasi-Poisson regression using distributed lag nonlinear models to examine the heat effects at lag 0-1 days. The area-specific estimates were pooled by random-effects meta-analysis to derive country-specific and overall heat effects. We examined individual- and area-level heat vulnerability factors by subgroup analyses and meta-regression, respectively. RESULTS: We included 2.84 million CVD deaths in analyses. For an increase in temperature from the 75th to the 99th percentile, the pooled relative risk (RR) for CVD mortality was 1.14 (95% CI: 1.03, 1.26), with the country-specific RRs ranging from 1.04 (1.00, 1.09) in Norway to 1.24 (1.23, 1.26) in Germany. Heat effects were stronger among women [RRs (95% CIs) for women and men: 1.18 (1.08, 1.28) vs. 1.12 (1.00, 1.24)]. Greater heat vulnerability was observed in areas with high population density, high degree of urbanization, low green coverage, and high levels of fine particulate matter. CONCLUSION: This study provides evidence for the heat effects on CVD mortality in European countries using high-resolution data from both urban and rural areas. Besides, we identified individual- and area-level heat vulnerability factors. Our findings may facilitate the development of heat-health action plans to increase resilience to climate change.

Health impact assessment for air pollution in the presence of regional variation in effect sizes: The implications of using different meta-analytic approaches.

The estimated health effects of air pollution vary between studies, and this variation is caused by factors associated with the study location, hereafter termed regional heterogeneity. This heterogeneity raises a methodological question as to which studies should be used to estimate risks in a specific region in a health impact assessment. Should one use all studies across the world, or only those in the region of interest? The current study provides novel insight into this question in two ways. Firstly, it presents an up-to-date analysis examining the magnitude of continent-level regional heterogeneity in the short-term health effects of air pollution, using a database of studies collected by Orellano et al. (2020). Secondly, it provides in-depth simulation analyses examining whether existing meta-analyses are likely to be underpowered to identify statistically significant regional heterogeneity, as well as evaluating which meta-analytic technique is best for estimating region-specific estimates. The techniques considered include global and continent-specific (sub-group) random effects meta-analysis and meta-regression, with omnibus statistical tests used to quantify regional heterogeneity. We find statistically significant regional heterogeneity for 4 of the 8 pollutant-outcome pairs considered, comprising NO2, O3 and PM2.5 with all-cause mortality, and PM2.5 with cardiovascular mortality. From the simulation analysis statistically significant regional heterogeneity is more likely to be identified as the number of studies increases (between 3 and 30 in each region were considered), between region heterogeneity increases and within region heterogeneity decreases. Finally, while a sub-group analysis using Cochran's Q test has a higher median power (0.71) than a test based on the moderators' coefficients from meta-regression (0.59) to identify regional heterogeneity, it also has an inflated type-1 error leading to more false positives (median errors of 0.15 compared to 0.09).

Long-term exposure to elemental components of fine particulate matter and all-natural and cause-specific mortality in a Danish nationwide administrative cohort study.

BACKGROUND: Fine particulate matter (PM2.5) is a well-recognized risk factor for premature death. However, evidence on which PM2.5 components are most relevant is unclear. METHODS: We evaluated the associations between mortality and long-term exposure to eight PM2.5 elemental components [copper (Cu), iron (Fe), zinc (Zn), sulfur (S), nickel (Ni), vanadium (V), silicon (Si), and potassium (K)]. Studied outcomes included death from diabetes, chronic kidney disease (CKD), dementia, and psychiatric disorders as well as all-natural causes, cardiovascular disease (CVD), respiratory diseases (RD), and lung cancer. We followed all residents in Denmark (aged ≥30 years) from January 1, 2000 to December 31, 2017. We used European-wide land-use regression models at a 100 × 100 m scale to estimate the residential annual mean levels of exposure to PM2.5 components. The models were developed with supervised linear regression (SLR) and random forest (RF). The associations were evaluated by Cox proportional hazard models adjusting for individual- and area-level socioeconomic factors and total PM2.5 mass. RESULTS: Of 3,081,244 individuals, we observed 803,373 death from natural causes during follow-up. We found significant positive associations between all-natural mortality with Si and K from both exposure modeling approaches (hazard ratios; 95% confidence intervals per interquartile range increase): SLR-Si (1.04; 1.03-1.05), RF-Si (1.01; 1.00-1.02), SLR-K (1.03; 1.02-1.04), and RF-K (1.06; 1.05-1.07). Strong associations of K and Si were detected with most causes of mortality except CKD and K, and diabetes and Si (the strongest associations for psychiatric disorders mortality). In addition, Fe was relevant for mortality from RD, lung cancer, CKD, and psychiatric disorders; Zn with mortality from CKD, RD, and lung cancer, and; Ni and V with lung cancer mortality. CONCLUSIONS: We present novel results of the relevance of different PM2.5 components for different causes of death, with K and Si seeming to be most consistently associated with mortality in Denmark.

Effect modification of greenness on the association between heat and mortality: A multi-city multi-country study.

BACKGROUND: Identifying how greenspace impacts the temperature-mortality relationship in urban environments is crucial, especially given climate change and rapid urbanization. However, the effect modification of greenspace on heat-related mortality has been typically focused on a localized area or single country. This study examined the heat-mortality relationship among different greenspace levels in a global setting. METHODS: We collected daily ambient temperature and mortality data for 452 locations in 24 countries and used Enhanced Vegetation Index (EVI) as the greenspace measurement. We used distributed lag non-linear model to estimate the heat-mortality relationship in each city and the estimates were pooled adjusting for city-specific average temperature, city-specific temperature range, city-specific population density, and gross domestic product (GDP). The effect modification of greenspace was evaluated by comparing the heat-related mortality risk for different greenspace groups (low, medium, and high), which were divided into terciles among 452 locations. FINDINGS: Cities with high greenspace value had the lowest heat-mortality relative risk of 1·19 (95% CI: 1·13, 1·25), while the heat-related relative risk was 1·46 (95% CI: 1·31, 1·62) for cities with low greenspace when comparing the 99th temperature and the minimum mortality temperature. A 20% increase of greenspace is associated with a 9·02% (95% CI: 8·88, 9·16) decrease in the heat-related attributable fraction, and if this association is causal (which is not within the scope of this study to assess), such a reduction could save approximately 933 excess deaths per year in 24 countries. INTERPRETATION: Our findings can inform communities on the potential health benefits of greenspaces in the urban environment and mitigation measures regarding the impacts of climate change. FUNDING: This publication was developed under Assistance Agreement No. RD83587101 awarded by the U.S. Environmental Protection Agency to Yale University. It has not been formally reviewed by EPA. The views expressed in this document are solely those of the authors and do not necessarily reflect those of the Agency. EPA does not endorse any products or commercial services mentioned in this publication. Research reported in this publication was also supported by the National Institute on Minority Health and Health Disparities of the National Institutes of Health under Award Number R01MD012769. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Also, this work has been supported by the National Research Foundation of Korea (2021R1A6A3A03038675), Medical Research Council-UK (MR/V034162/1 and MR/R013349/1), Natural Environment Research Council UK (Grant ID: NE/R009384/1), Academy of Finland (Grant ID: 310372), European Union's Horizon 2020 Project Exhaustion (Grant ID: 820655 and 874990), Czech Science Foundation (22-24920S), Emory University's NIEHS-funded HERCULES Center (Grant ID: P30ES019776), and Grant CEX2018-000794-S funded by MCIN/AEI/ 10.13039/501100011033 The funders had no role in the design, data collection, analysis, interpretation of results, manuscript writing, or decision to publication.

Variability in the association between long-term exposure to ambient air pollution and mortality by exposure assessment method and covariate adjustment: A census-based country-wide cohort study.

BACKGROUND: Ambient air pollution exposure has been associated with higher mortality risk in numerous studies. We assessed potential variability in the magnitude of this association for non-accidental, cardiovascular disease, respiratory disease, and lung cancer mortality in a country-wide administrative cohort by exposure assessment method and by adjustment for geographic subdivisions. METHODS: We used the Belgian 2001 census linked to population and mortality register including nearly 5.5 million adults aged ≥30 (mean follow-up: 9.97 years). Annual mean concentrations for fine particulate matter (PM2.5), nitrogen dioxide (NO2), black carbon (BC) and ozone (O3) were assessed at baseline residential address using two exposure methods; Europe-wide hybrid land use regression (LUR) models [100x100m], and Belgium-wide interpolation-dispersion (RIO-IFDM) models [25x25m]. We used Cox proportional hazards models with age as the underlying time scale and adjusted for various individual and area-level covariates. We further adjusted main models for two different area-levels following the European Nomenclature of Territorial Units for Statistics (NUTS); NUTS-1 (n = 3), or NUTS-3 (n = 43). RESULTS: We found no consistent differences between both exposure methods. We observed most robust associations with lung cancer mortality. Hazard Ratios (HRs) per 10 µg/m3 increase for NO2 were 1.060 (95%CI 1.042-1.078) [hybrid LUR] and 1.040 (95%CI 1.022-1.058) [RIO-IFDM]. Associations with non-accidental, respiratory disease and cardiovascular disease mortality were generally null in main models but were enhanced after further adjustment for NUTS-1 or NUTS-3. HRs for non-accidental mortality per 5 µg/m3 increase for PM2.5 for the main model using hybrid LUR exposure were 1.023 (95%CI 1.011-1.035). After including random effects HRs were 1.044 (95%CI 1.033-1.057) [NUTS-1] and 1.076 (95%CI 1.060-1.092) [NUTS-3]. CONCLUSION: Long-term air pollution exposure was associated with higher lung cancer mortality risk but not consistently with the other studied causes. Magnitude of associations varied by adjustment for geographic subdivisions, area-level socio-economic covariates and less by exposure assessment method.

Socioeconomic inequalities in suicide mortality in European urban areas before and during the economic recession.

BACKGROUND: Few studies have assessed the impact of the financial crisis on inequalities in suicide mortality in European urban areas. The objective of the study was to analyse the trend in area socioeconomic inequalities in suicide mortality in nine European urban areas before and after the beginning of the financial crisis. METHODS: This ecological study of trends was based on three periods, two before the economic crisis (2000-2003, 2004-2008) and one during the crisis (2009-2014). The units of analysis were the small areas of nine European cities or metropolitan areas, with a median population ranging from 271 (Turin) to 193 630 (Berlin). For each small area and sex, we analysed smoothed standardized mortality ratios of suicide mortality and their relationship with a socioeconomic deprivation index using a hierarchical Bayesian model. RESULTS: Among men, the relative risk (RR) comparing suicide mortality of the 95th percentile value of socioeconomic deprivation (severe deprivation) to its 5th percentile value (low deprivation) were higher than 1 in Stockholm and Lisbon in the three periods. In Barcelona, the RR was 2.06 (95% credible interval: 1.24-3.21) in the first period, decreasing in the other periods. No significant changes were observed across the periods. Among women, a positive significant association was identified only in Stockholm (RR around 2 in the three periods). There were no significant changes across the periods except in London with a RR of 0.49 (95% CI: 0.35-0.68) in the third period. CONCLUSIONS: Area socioeconomic inequalities in suicide mortality did not change significantly after the onset of the crisis in the areas studied.

Population Health Inequalities Across and Within European Metropolitan Areas through the Lens of the EURO-HEALTHY Population Health Index.

The different geographical contexts seen in European metropolitan areas are reflected in the uneven distribution of health risk factors for the population. Accumulating evidence on multiple health determinants point to the importance of individual, social, economic, physical and built environment features, which can be shaped by the local authorities. The complexity of measuring health, which at the same time underscores the level of intra-urban inequalities, calls for integrated and multidimensional approaches. The aim of this study is to analyse inequalities in health determinants and health outcomes across and within nine metropolitan areas: Athens, Barcelona, Berlin-Brandenburg, Brussels, Lisbon, London, Prague, Stockholm and Turin. We use the EURO-HEALTHY Population Health Index (PHI), a tool that measures health in two components: Health Determinants and Health Outcomes. The application of this tool revealed important inequalities between metropolitan areas: Better scores were found in Northern cities when compared with their Southern and Eastern counterparts in both components. The analysis of geographical patterns within metropolitan areas showed that there are intra-urban inequalities, and, in most cities, they appear to form spatial clusters. Identifying which urban areas are measurably worse off, in either Health Determinants or Health Outcomes, or both, provides a basis for redirecting local action and for ongoing comparisons with other metropolitan areas.

Ozone exposure assessment for children in Greece - Results from the RESPOZE study.

Ozone exposure of 179 children in Athens and Thessaloniki, Greece was assessed during 2013-2014, by repeated weekly personal measurements, using passive samplers. O3 was also monitored at school locations of participants to characterize community-level ambient exposure. Average personal concentrations in the two cities (5.0 and 2.8ppb in Athens and Thessaloniki, respectively) were considerably lower than ambient concentrations (with mean personal/ambient ratios of 0.13-0.15). The temporal variation of personal concentrations followed the -typical for low-latitude areas- pattern of cold-warm seasons. However, differences were detected between temporal distributions of personal and ambient concentrations, since personal exposures were affected by additional factors which present seasonal variability, such as outdoor activity and house ventilation. Significant spatial contrasts were observed between urban and suburban areas, for personal concentrations in Athens, with higher exposure for children residing in the N-NE part of the area. In Thessaloniki, spatial variations in personal concentrations were less pronounced, echoing the spatial pattern of ambient concentrations, a result of complex local meteorology and the smaller geographical expansion of the study area. Ambient concentration was identified as the most important factor influencing personal exposures (correlation coefficients between 0.36 and 0.67). Associations appeared to be stronger with ambient concentrations measured at school locations of children, than to those reported by the nearest site of the air quality monitoring network, indicating the importance of community-representative outdoor monitoring for characterization of personal-ambient relationships. Time spent outdoors by children was limited (>90% of the time they remained indoors), but -due to the lack of indoor sources- it was found to exert significant influence on personal concentrations, affecting inter-subject and spatiotemporal variability. Additional parameters that were identified as relevant for the determination of personal concentrations were indoor ventilation conditions (specifically indoor times with windows open) and the use of wood-burning in open fireplaces for heating as an ozone sink.

Quantifying the health impacts of ambient air pollutants: recommendations of a WHO/Europe project.

OBJECTIVE: Quantitative estimates of air pollution health impacts have become an increasingly critical input to policy decisions. The WHO project "Health risks of air pollution in Europe--HRAPIE" was implemented to provide the evidence-based concentration-response functions for quantifying air pollution health impacts to support the 2013 revision of the air quality policy for the European Union (EU). METHODS: A group of experts convened by WHO Regional Office for Europe reviewed the accumulated primary research evidence together with some commissioned reviews and recommended concentration-response functions for air pollutant-health outcome pairs for which there was sufficient evidence for a causal association. RESULTS: The concentration-response functions link several indicators of mortality and morbidity with short- and long-term exposure to particulate matter, ozone and nitrogen dioxide. The project also provides guidance on the use of these functions and associated baseline health information in the cost-benefit analysis. CONCLUSIONS: The project results provide the scientific basis for formulating policy actions to improve air quality and thereby reduce the burden of disease associated with air pollution in Europe.

Risk assessment of diesel exhaust and lung cancer: combining human and animal studies after adjustment for biases in epidemiological studies.

BACKGROUND: Risk assessment requires dose-response data for the evaluation of the relationship between exposure to an environmental stressor and the probability of developing an adverse health effect. Information from human studies is usually limited and additional results from animal studies are often needed for the assessment of risks in humans. Combination of risk estimates requires an assessment and correction of the important biases in the two types of studies. In this paper we aim to illustrate a quantitative approach to combining data from human and animal studies after adjusting for bias in human studies. For our purpose we use the example of the association between exposure to diesel exhaust and occurrence of lung cancer. METHODS: Firstly, we identify and adjust for the main sources of systematic error in selected human studies of the association between occupational exposure to diesel exhaust and occurrence of lung cancer. Evidence from selected animal studies is also accounted for by extrapolating to average ambient, occupational exposure concentrations of diesel exhaust. In a second stage, the bias adjusted effect estimates are combined in a common effect measure through meta-analysis. RESULTS: The random-effects pooled estimate (RR) for exposure to diesel exhaust vs. non-exposure was found 1.37 (95% C.I.: 1.08-1.65) in animal studies and 1.59 (95% C.I.: 1.09-2.10) in human studies, whilst the overall was found equal to 1.49 (95% C.I.: 1.21-1.78) with a greater contribution from human studies. Without bias adjustment in human studies, the pooled effect estimate was 1.59 (95% C.I.: 1.28-1.89). CONCLUSIONS: Adjustment for the main sources of uncertainty produced lower risk estimates showing that ignoring bias leads to risk estimates potentially biased upwards.

Acute effects of ambient particulate matter on mortality in Europe and North America: results from the APHENA study.

BACKGROUND: THE APHENA (AIR POLLUTION AND HEALTH: A Combined European and North American Approach) study is a collaborative analysis of multicity time-series data on the effect of air pollution on population health, bringing together data from the European APHEA (Air Pollution and Health: A European Approach) and U.S. NMMAPS (National Morbidity, Mortality and Air Pollution Study) projects, along with Canadian data. OBJECTIVES: The main objective of APHENA was to assess the coherence of the findings of the multicity studies carried out in Europe and North America, when analyzed with a common protocol, and to explore sources of possible heterogeneity. We present APHENA results on the effects of particulate matter (PM) < or = 10 microm in aerodynamic diameter (PM(10)) on the daily number of deaths for all ages and for those < 75 and > or = 75 years of age. We explored the impact of potential environmental and socioeconomic factors that may modify this association. METHODS: In the first stage of a two-stage analysis, we used Poisson regression models, with natural and penalized splines, to adjust for seasonality, with various degrees of freedom. In the second stage, we used meta-regression approaches to combine time-series results across cites and to assess effect modification by selected ecologic covariates. RESULTS: Air pollution risk estimates were relatively robust to different modeling approaches. Risk estimates from Europe and United States were similar, but those from Canada were substantially higher. The combined effect of PM(10) on all-cause mortality across all ages for cities with daily air pollution data ranged from 0.2% to 0.6% for a 10-microg/m(3) increase in ambient PM(10) concentration. Effect modification by other pollutants and climatic variables differed in Europe and the United States. In both of these regions, a higher proportion of older people and higher unemployment were associated with increased air pollution risk. CONCLUSIONS: Estimates of the increased mortality associated with PM air pollution based on the APHENA study were generally comparable with results of previous reports. Overall, risk estimates were similar in Europe and in the United States but higher in Canada. However, PM(10) effect modification patterns were somewhat different in Europe and the United States.

Collaborative research: accomplishments & potential.

Although a substantial part of scientific research is collaborative and increasing globalization will probably lead to its increase, very few studies actually investigate the advantages, disadvantages, experiences and lessons learned from collaboration. In environmental epidemiology interdisciplinary collaboration is essential and the contrasting geographical patterns in exposure and disease make multi-location projects essential. This paper is based on a presentation given at the Annual Conference of the International Society for Environmental Epidemiology, Paris 2006, and is attempting to initiate a discussion on a framework for studying collaborative research. A review of the relevant literature showed that indeed collaborative research is rising, in some countries with impressive rates. However, there are substantial differences between countries in their outlook, need and respect for collaboration. In many situations collaborative publications receive more citations than those based on national authorship. The European Union is the most important host of collaborative research, mainly driven by the European Commission through the Framework Programmes. A critical assessment of the tools and trends of collaborative networks under FP6, showed that there was a need for a critical revision, which led to changes in FP7. In conclusion, it is useful to study the characteristics of collaborative research and set targets for the future. The added value for science and for the researchers involved may be assessed. The motivation for collaboration could be increased in the more developed countries. Particular ways to increase the efficiency and interaction in interdisciplinary and intercultural collaboration may be developed. We can work towards "the principles of collaborative research" in Environmental Epidemiology.

Assessment and prevention of acute health effects of weather conditions in Europe, the PHEWE project: background, objectives, design.

BACKGROUND: The project "Assessment and prevention of acute health effects of weather conditions in Europe" (PHEWE) had the aim of assessing the association between weather conditions and acute health effects, during both warm and cold seasons in 16 European cities with widely differing climatic conditions and to provide information for public health policies. METHODS: The PHEWE project was a three-year pan-European collaboration between epidemiologists, meteorologists and experts in public health. Meteorological, air pollution and mortality data from 16 cities and hospital admission data from 12 cities were available from 1990 to 2000. The short-term effect on mortality/morbidity was evaluated through city-specific and pooled time series analysis. The interaction between weather and air pollutants was evaluated and health impact assessments were performed to quantify the effect on the different populations. A heat/health watch warning system to predict oppressive weather conditions and alert the population was developed in a subgroup of cities and information on existing prevention policies and of adaptive strategies was gathered. RESULTS: Main results were presented in a symposium at the conference of the International Society of Environmental Epidemiology in Paris on September 6th 2006 and will be published as scientific articles. The present article introduces the project and includes a description of the database and the framework of the applied methodology. CONCLUSION: The PHEWE project offers the opportunity to investigate the relationship between temperature and mortality in 16 European cities, representing a wide range of climatic, socio-demographic and cultural characteristics; the use of a standardized methodology allows for direct comparison between cities.

Hypertension and Exposure to Noise near Airports (HYENA): study design and noise exposure assessment.

An increasing number of people live near airports with considerable noise and air pollution. The Hypertension and Exposure to Noise near Airports (HYENA) project aims to assess the impact of airport-related noise exposure on blood pressure (BP) and cardiovascular disease using a cross-sectional study design. We selected 6,000 persons (45-70 years of age) who had lived at least 5 years near one of six major European airports. We used modeled aircraft noise contours, aiming to maximize exposure contrast. Automated BP instruments are used to reduce observer error. We designed a standardized questionnaire to collect data on annoyance, noise disturbance, and major confounders. Cortisol in saliva was collected in a subsample of the study population (n = 500) stratified by noise exposure level. To investigate short-term noise effects on BP and possible effects on nighttime BP dipping, we measured 24-hr BP and assessed continuous night noise in another subsample (n = 200). To ensure comparability between countries, we used common noise models to assess individual noise exposure, with a resolution of 1 dB(A). Modifiers of individual exposure, such as the orientation of living and bedroom toward roads, window-opening habits, and sound insulation, were assessed by the questionnaire. For four airports, we estimated exposure to air pollution to explore modifying effects of air pollution on cardiovascular disease. The project assesses exposure to traffic-related air pollutants, primarily using data from another project funded by the European Union (APMoSPHERE, Air Pollution Modelling for Support to Policy on Health and Environmental Risks in Europe).

The temporal pattern of mortality responses to air pollution: a multicity assessment of mortality displacement.

Although the association between particulate matter and mortality or morbidity is generally accepted, controversy remains about the importance of the association. If it is due solely to the deaths of frail individuals, which are brought forward by only a brief period of time, the public health implications of the association are fewer than if there is an increase in the number of deaths. Recently, other research has addressed the mortality displacement issue in single-city analysis. We analyzed this issue with a distributed lag model in a multicity hierarchic modeling approach, within the Air Pollution and Health: A European Approach (APHEA-2) study. We fit a Poisson regression model and a polynomial distributed lag model with up to 40 days of delay in each city. In the second stage we combined the city-specific results. We found that the overall effect of particulate matter less than 10 microM in aerodynamic diameter (PM10) per 10 microg/m3 for the fourth-degree distributed lag model is a 1.61% increase in daily deaths (95% CI = 1.02-2.20), whereas the mean of PM10 on the same day and the previous day is associated with only a 0.70% increase in deaths (95% CI = 0.43-0.97). This result is unchanged using an unconstrained distributed lag model. Our study confirms that the effects observed in daily time-series studies are not due primarily to short-term mortality displacement. The effect size estimate for airborne particles more than doubles when we consider longer-term effects, which has important implications for risk assessment.