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

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)

PM2.5 and NO2 exposure errors using proxy measures, including derived personal exposure from outdoor sources: A systematic review and meta-analysis.

BACKGROUND: The use of proxy exposure estimates for PM2.5 and NO2 in air pollution studies instead of personal exposures, introduces measurement error, which can produce biased epidemiological effect estimates. Most studies consider total personal exposure as the gold standard. However, when studying the effects of ambient air pollution, personal exposure from outdoor sources is the exposure of interest. OBJECTIVES: We assessed the magnitude and variability of exposure measurement error by conducting a systematic review of the differences between personal exposures from outdoor sources and the corresponding measurements for ambient concentrations in order to increase understanding of the measurement error structures of the pollutants. DATA SOURCES AND ELIGIBILITY CRITERIA: We reviewed the literature (ISI Web of Science, Medline, 2000-2016) for English language studies (in any age group in any location (NO2) or Europe and North America (PM2.5)) that reported repeated measurements over time both for personal and ambient PM2.5 or NO2 concentrations. Only a few studies reported personal exposure from outdoor sources. We also collected data for infiltration factors and time-activity patterns of the individuals in order to estimate personal exposures from outdoor sources in every study. STUDY APPRAISAL AND SYNTHESIS METHODS: Studies using modelled rather than monitored exposures were excluded. Type of personal exposure monitor was assessed. Random effects meta-analysis was conducted to quantify exposure error as the mean difference between "true" and proxy measures. RESULTS: Thirty-two papers for PM2.5 and 24 for NO2 were identified. Outdoor sources were found to contribute 44% (range: 33-55%) of total personal exposure to PM2.5 and 74% (range: 57-88%) to NO2. Overall estimates of personal exposure (24-hour averages) from outdoor sources were 9.3 μg/m3 and 12.0 ppb for PM2.5 and NO2 respectively, while the corresponding difference between these exposures and the ambient concentrations (i.e. the measurement error) was 5.72 μg/m3 and 7.17 ppb. Our findings indicated also higher error variability for NO2 than PM2.5. Large heterogeneity was observed which was not explained sufficiently by geographical location or age group of the study sample. LIMITATIONS, CONCLUSIONS AND IMPLICATIONS OF KEY FINDINGS: Relying only on information available in published studies led to some limitations: the contribution of outdoor sources to total personal exposure for NO2 had to be inferred, individual variation in exposure misclassification was unavailable and instrument error could not be addressed. The larger magnitude and variability of errors for NO2 compared with PM2.5 has implications for biases in the health effect estimates of multi-pollutant epidemiological models. Results suggest that further research is needed regarding personal exposure studies and measurement error bias in epidemiological models

Measurement error in a multi-level analysis of air pollution and health: a simulation study.

BACKGROUND: Spatio-temporal models are increasingly being used to predict exposure to ambient outdoor air pollution at high spatial resolution for inclusion in epidemiological analyses of air pollution and health. Measurement error in these predictions can nevertheless have impacts on health effect estimation. Using statistical simulation we aim to investigate the effects of such error within a multi-level model analysis of long and short-term pollutant exposure and health. METHODS: Our study was based on a theoretical sample of 1000 geographical sites within Greater London. Simulations of "true" site-specific daily mean and 5-year mean NO2 and PM10 concentrations, incorporating both temporal variation and spatial covariance, were informed by an analysis of daily measurements over the period 2009-2013 from fixed location urban background monitors in the London area. In the context of a multi-level single-pollutant Poisson regression analysis of mortality, we investigated scenarios in which we specified: the Pearson correlation between modelled and "true" data and the ratio of their variances (model versus "true") and assumed these parameters were the same spatially and temporally. RESULTS: In general, health effect estimates associated with both long and short-term exposure were biased towards the null with the level of bias increasing to over 60% as the correlation coefficient decreased from 0.9 to 0.5 and the variance ratio increased from 0.5 to 2. However, for a combination of high correlation (0.9) and small variance ratio (0.5) non-trivial bias (> 25%) away from the null was observed. Standard errors of health effect estimates, though unaffected by changes in the correlation coefficient, appeared to be attenuated for variance ratios > 1 but inflated for variance ratios < 1. CONCLUSION: While our findings suggest that in most cases modelling errors result in attenuation of the effect estimate towards the null, in some situations a non-trivial bias away from the null may occur. The magnitude and direction of bias appears to depend on the relationship between modelled and "true" data in terms of their correlation and the ratio of their variances. These factors should be taken into account when assessing the validity of modelled air pollution predictions for use in complex epidemiological models

socioeconomic inequalities in suicide mortality in european urban areas before and during the economic recession

Abstract 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

Effects of Cold Weather on Mortality: Results From 15 European Cities Within the PHEWE Project

Weather-related health effects have attracted renewed interest because of the observed and predicted climate change. The authors studied the short-term effects of cold weather on mortality in 15 European cities. The effects of minimum apparent temperature on cause- and age-specific daily mortality were assessed for the cold season (October-March) by using data from 1990-2000. For city-specific analysis, the authors used Poisson regression and distributed lag models, controlling for potential confounders. Meta-regression models summarized the results and explored heterogeneity. A 1 degrees C decrease in temperature was associated with a 1.35% (95% confidence interval (CI): 1.16, 1.53) increase in the daily number of total natural deaths and a 1.72% (95% CI: 1.44, 2.01), 3.30% (95% CI: 2.61, 3.99), and 1.25% (95% CI: 0.77, 1.73) increase in cardiovascular, respiratory, and cerebrovascular deaths, respectively. The increase was greater for the older age groups. The cold effect was found to be greater in warmer (southern) cities and persisted up to 23 days, with no evidence of mortality displacement. Cold-related mortality is an important public health problem across Europe. It should not be underestimated by public health authorities because of the recent focus on heat-wave episodes

The temporal pattern of respiratory and heart disease mortality in response to air pollution.

Short-term changes in ambient particulate matter with aerodynamic diameters < 10 micro m (PM10) have been associated with short-term fluctuations in mortality or morbidity in many studies. In this study, we tested whether those deaths are just advanced by a few days or weeks using a multicity hierarchical modeling approach for all-cause, respiratory, and cardiovascular deaths, for all ages and stratifying by age groups, within the APHEA-2 (Air Pollution and Health: A European Approach) project. We fit a Poisson regression and used an unconstrained distributed lag to model the effect of PM10 exposure on deaths up to 40 days after the exposure. In baseline models using PM10 the day of and day before the death, we found that the overall PM10 effect (per 10 micro g/m3) was 0.74% [95% confidence interval (95% CI), -0.17 to 1.66] for respiratory deaths and 0.69% (95% CI, 0.31-1.08) for cardiovascular deaths. In unrestricted distributed lag models, the effect estimates increased to 4.2% (95% CI, 1.08-7.42) for respiratory deaths and to 1.97% (95% CI, 1.38-2.55) for cardiovascular deaths. Our study confirms that most of the effect of air pollution is not simply advanced by a few weeks and that effects persist for more than a month after exposure. The effect size estimate for PM10 doubles when we considered longer-term effects for all deaths and for cardiovascular deaths and becomes five times higher for respiratory deaths. We found similar effects when stratifying by age groups. These larger effects are important for risk assessment

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 sub-sample (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)

Estimating the Exposure–Response Relationships between Particulate Matter and Mortality within the APHEA Multicity Project

Several studies have reported significant health effects of air pollution even at low levels of air pollutants, but in most of theses studies linear nonthreshold relations were assumed. We investigated the exposure–response association between ambient particles and mortality in the 22 European cities participating in the APHEA (Air Pollution and Health—A European Approach) project, which is the largest available European database. We estimated the exposure–response curves using regression spline models with two knots and then combined the individual city estimates of the spline to get an overall exposure–response relationship. To further explore the heterogeneity in the observed city-specific exposure–response associations, we investigated several city descriptive variables as potential effect modifiers that could alter the shape of the curve. We conclude that the association between ambient particles and mortality in the cities included in the present analysis, and in the range of the pollutant common in all analyzed cities, could be adequately estimated using the linear model. Our results confirm those previously reported in Europe and the United States. The heterogeneity found in the different city-specific relations reflects real effect modification, which can be explained partly by factors characterizing the air pollution mix, climate, and the health of the population

The risks of acute exposure to black carbon in Southern Europe: results from the MED-PARTICLES project

While several studies have reported associations of daily exposures to PM2.5 (particles less than 2.5 µm) with mortality, few studies have examined the impact of its constituents such as black carbon (BC), which is also a significant contributor to global climate change. Methods: We assessed the association between daily concentrations of BC and total, cardiovascular and respiratory mortality in two southern Mediterranean cities. Daily averages of BC were collected for 2 years in Barcelona, Spain and Athens, Greece. We used case-crossover analysis and examined single and cumulative lags up to 3 days. Results: We observed associations between BC and all mortality measures. For a 3-day moving average, cardiovascular mortality increased by 4.5% (95% CI 0.7 to 8.5) and 2.0% (95% CI 0 to 4.0) for an interquartile change in BC in Athens and Barcelona, respectively. Considerably higher effects for respiratory mortality and for those above age 65 were observed. In addition, BC exhibited much greater toxicity per microgram than generic PM2.5. Conclusions: Our findings suggest that BC, derived in western industrialised nations primarily from diesel engines and biomass burning, poses a significant burden to public health, particularly in European cities with high-traffic density.Peer ReviewedPostprint (published version