Citizen science in environmental health research: A comparison with conventional approaches and creation of a guidance tool issued from the LILAS initiative.

CONTEXT: Public interest for citizen science (CS) in environmental health is growing. The goals of environmental health research projects are diverse, as are the methods used to reach these goals. Opportunities for greater implication of the civil society and related challenges differ at each step of such projects. These methodological aspects need to be widely shared and understood by all stakeholders. The LILAS initiative (acronym for "application of citizen science approaches such as LIving LAbS to research on environmental exposures and chronic risks") aimed to 1) favor a mutual understanding of the main issues and research methods in environmental health, of their stakes for different actors, but also of the requirements, strengths and limitations of these methods and to 2) identify expected benefits and points of attention related to stronger degrees of participation as part of environmental health research projects. METHODS: The LILAS initiative gathered institutional researchers, academics and civil society representatives interested in environmental exposures. Five meetings allowed to collectively identify different types of environmental health research studies and reflect about the benefits, limitations, and methodological issues related to the introduction of growing citizen participation as part of such studies. An analytic table matrix summarizing these aspects was co-created and filled by participants, as a tool devoted to help stakeholders with the definition of future CS research projects in environmental health. RESULTS: For different fields of research (e.g.: studies for assessment of environmental exposures, interventions on these exposures, quantitative risk assessment, epidemiological studies), the matrix lists expected benefits for various stakeholders, the fundamental principles of research methods and related practical constraints, but also advantages and limitations related to the use of CS or conventional research approaches. CONCLUSION: The LILAS initiative allowed to develop a tool which provides consolidated grounds for the co-creation of research projects on environmental exposures involving CS.

[Health and environment, prevention or precaution?] / Santé et environnement, prévention ou précaution ?

The health status of the populations of developed countries has never been as satisfactory, but will it stay that way? Research on the subject is difficult due to the complex interactions between our environment and our health, with risks inherent to each noxious agent. Preventing the risks proven to be linked to the quality of our living environments is usually the responsibility of authorities, but individuals can also adopt precautionary practices.

Ozone, NO2 and PM10 are associated with the occurrence of multiple sclerosis relapses. Evidence from seasonal multi-pollutant analyses.

BACKGROUND: Triggers of multiple sclerosis (MS) relapses are essentially unknown. PM10 exposure has recently been associated with an increased risk of relapses. OBJECTIVES: We further explore the short-term associations between PM10, NO2, benzene (C6H6), O3, and CO exposures, and the odds of MS relapses' occurrence. METHODS: Using a case-crossover design, we studied 424 MS patients living in the Strasbourg area, France between 2000 and 2009 (1783 relapses in total). Control days were chosen to be ± 35 days relative to the case (relapse) day. Exposure was modeled through ADMS-Urban software at the census block scale. We consider single-pollutant and multi-pollutant conditional logistic regression models coupled with a distributed-lag linear structure, stratified by season ("hot" vs. "cold"), and adjusted for meteorological parameters, pollen count, influenza-like epidemics, and holidays. RESULTS: The single-pollutant analyses indicated: 1) significant associations between MS relapse incidence and exposures to NO2, PM10, and O3, and 2) seasonality in these associations. For instance, an interquartile range increase in NO2 (lags 0-3) and PM10 exposure were associated with MS relapse incidence (OR = 1.08; 95%CI: [1.03-1.14] and OR = 1.06; 95%CI: [1.01-1.11], respectively) during the "cold" season (i.e., October-March). We also observed an association with O3 and MS relapse incidence during "hot" season (OR = 1.16; 95%CI: [1.07-1.25]). C6H6 and CO were not significantly related to MS relapse incidence. However, using multi-pollutant models, only O3 remained significantly associated with the odds of relapse triggering during "hot" season. CONCLUSION: We observed significant single-pollution associations between the occurrence of MS relapses and exposures to NO2, O3 and PM10, only O3 remained significantly associated with occurrence of MS relapses in the multi-pollutant model.

Developing a data-driven spatial approach to assessment of neighbourhood influences on the spatial distribution of myocardial infarction.

BACKGROUND: There is a growing understanding of the role played by 'neighbourhood' in influencing health status. Various neighbourhood characteristics-such as socioeconomic environment, availability of amenities, and social cohesion, may be combined-and this could contribute to rising health inequalities. This study aims to combine a data-driven approach with clustering analysis techniques, to investigate neighbourhood characteristics that may explain the geographical distribution of the onset of myocardial infarction (MI) risk. METHODS: All MI events in patients aged 35-74 years occurring in the Strasbourg metropolitan area (SMA), from January 1, 2000 to December 31, 2007 were obtained from the Bas-Rhin coronary heart disease register. All cases were geocoded to the census block for the residential address. Each areal unit, characterized by contextual neighbourhood profile, included socioeconomic environment, availability of amenities (including leisure centres, libraries and parks, and transport) and psychosocial environment as well as specific annual rates standardized (per 100,000 inhabitants). A spatial scan statistic implemented in SaTScan was then used to identify statistically significant spatial clusters of high and low risk of MI. RESULT: MI incidence was non-randomly spatially distributed, with a cluster of high risk of MI in the northern part of the SMA [relative risk (RR) = 1.70, p = 0.001] and a cluster of low risk of MI located in the first and second periphery of SMA (RR 0.04, p value  =  0.001). Our findings suggest that the location of low MI risk is characterized by a high socioeconomic level and a low level of access to various amenities; conversely, the location of high MI risk is characterized by a high level of socioeconomic deprivation-despite the fact that inhabitants have good access to the local recreational and leisure infrastructure. CONCLUSION: Our data-driven approach highlights how the different contextual dimensions were inter-combined in the SMA. Our spatial approach allowed us to identify the neighbourhood characteristics of inhabitants living within a cluster of high versus low MI risk. Therefore, spatial data-driven analyses of routinely-collected data georeferenced by various sources may serve to guide policymakers in defining and promoting targeted actions at fine spatial level.

Air pollution by particulate matter PM10 may trigger multiple sclerosis relapses.

BACKGROUND: Seasonal variation of relapses in multiple sclerosis (MS) suggests that season-dependent factors, such as ambient air pollution, may trigger them. However, only few studies have considered possible role of air pollutants as relapse's risk factor. OBJECTIVE: We investigated the effect of particulate matter of aerodynamic diameter smaller than 10µm (PM10) on MS relapses. METHODS: In total, 536 relapsing MS patients from Strasbourg city (France) were included, accounting for 2052 relapses over 2000-2009 period. A case-crossover design was used with cases defined as the days of relapse and controls being selected in the same patient at plus and minus 35 days. Different lags from 0 to 30 days were considered. Conditional logistic regressions, adjusted on meteorological parameters, school and public holidays, were used and exposure was considered first as a quantitative variable and second, as a binary variable. RESULTS: The natural logarithm of the average PM10 concentration lagged from 1 to 3 days before relapse onset was significantly associated with relapse risk (OR =1.40 [95% confidence interval 1.08-1.81]) in cold season. Consistent results were observed when considering PM10 as a binary variable, even if not significant. CONCLUSION: With an appropriate study design and robust ascertainment of neurological events and exposure, the present study highlights the effect of PM10 on the risk of relapse in MS patients, probably through oxidative stress mechanisms.

Les changements climatiques et leurs conséquences sur la santé

Le changement climatique est une réalité inéluctable pour les décennies à venir, compte tenu de l'inertie du système climatique. L'ampleur du changement est à ce stade incertaine au niveau planétaire, et plus encore localement. Cependant, des conséquences sont à prévoir dans tous les cas sur la santé humaine, considérée à l'échelle de la planète, avec des retentissements sanitaires directs (vagues de chaleur, inondations, pollution de l'air…) et surtout indirects sur la disponibilité de l'eau potable et des ressources alimentaires, la destruction de l'habitat. Ces impacts sont source potentielle de déplacement de populations, de violences, de conflits. Il est non seulement possible mais nécessaire de se préparer à répondre à l'incertitude et à l'inconnu par des politiques publiques volontaristes d'atténuation des émissions de gaz à effet de serre et d'adaptation aux impacts déjà en développement et à venir. Ces politiques doivent s'appuyer sur une interdisciplinarité scientifique mais aussi sur l'implication des populations

Traffic-related air pollution and the onset of myocardial infarction: disclosing benzene as a trigger? A small-area case-crossover study.

BACKGROUND AND OBJECTIVES: Exposure to traffic is an established risk factor for the triggering of myocardial infarction (MI). Particulate matter, mainly emitted by diesel vehicles, appears to be the most important stressor. However, the possible influence of benzene from gasoline-fueled cars has not been explored so far. METHODS AND RESULTS: We conducted a case-crossover study from 2,134 MI cases recorded by the local Coronary Heart Disease Registry (2000-2007) in the Strasbourg Metropolitan Area (France). Available individual data were age, gender, previous history of ischemic heart disease and address of residence at the time of the event. Nitrogen dioxide, particles of median aerodynamic diameter <10 µm (PM10), ozone, carbon monoxide and benzene air concentrations were modeled on an hourly basis at the census block level over the study period using the deterministic ADMS-Urban air dispersion model. Model input data were emissions inventories, background pollution measurements, and meteorological data. We have found a positive, statistically significant association between concentrations of benzene and the onset of MI: per cent increase in risk for a 1 µg/m3 increase in benzene concentration in the previous 0, 0-1 and 1 day was 10.4 (95% confidence interval 3-18.2), 10.7 (2.7-19.2) and 7.2 (0.3-14.5), respectively. The associations between the other pollutants and outcome were much lower and in accordance with the literature. CONCLUSION: We have observed that benzene in ambient air is strongly associated with the triggering of MI. This novel finding needs confirmation. If so, this would mean that not only diesel vehicles, the main particulate matter emitters, but also gasoline-fueled cars--main benzene emitters-, should be taken into account for public health action.

Cancer mortality among two different populations of French nuclear workers.

PURPOSE: The aim of this paper is to study the effect of external photon radiation on the mortality of two populations of French nuclear workers: workers exposed only to external photon radiation and workers potentially exposed also to internal contamination or to neutrons. METHOD: External photon radiation has been measured through individual dosimeters. Potential exposure to internal contamination or to neutrons has been assessed by experts on the basis of quantitative measurements or of worksite and type of activity. The mortality observed in each population was compared with that expected from national mortality statistics, by computing standardized mortality ratios. Dose-effect relationships were analyzed through trend tests and log-linear Poisson regressions. RESULTS: 14,796 workers were exposed only to external photon radiation; 14,408 workers were also potentially exposed to internal radiation or to neutrons. Between 1968 and 1994, the number of deaths is respectively, 645 and 1,197. The mean external photon dose was respectively, 3.7 and 12.9 mSv. Similar Healthy Worker Effects were observed in the two populations (SMR = 0.59). SMR of 2.41 90% CI [1.39-3.90] was observed for malignant melanoma among workers of the second population. Significant dose-effect relationships were observed: among workers exposed only to external photon radiation for leukemia except CLL and in the other population, for cancers and other diseases related to tobacco or alcohol consumption. CONCLUSIONS: Results differed between the two populations. The increase in leukemia risk with dose in the first population will have to be confirmed with extended follow-up. In the other population, results may have been confounded by alpha-emitters inhalation, tobacco, or alcohol consumption.

A small-area ecologic study of myocardial infarction, neighborhood deprivation, and sex: a Bayesian modeling approach.

BACKGROUND: Socioeconomic inequalities in the risk of coronary heart disease (CHD) are well documented for men and women. CHD incidence is greater for men but its association with socioeconomic status is usually found to be stronger among women. We explored the sex-specific association between neighborhood deprivation level and the risk of myocardial infarction (MI) at a small-area scale. METHODS: We studied 1193 myocardial infarction events in people aged 35-74 years in the Strasbourg metropolitan area, France (2000-2003). We used a deprivation index to assess the neighborhood deprivation level. To take into account spatial dependence and the variability of MI rates due to the small number of events, we used a hierarchical Bayesian modeling approach. We fitted hierarchical Bayesian models to estimate sex-specific relative and absolute MI risks across deprivation categories. We tested departure from additive joint effects of deprivation and sex. RESULTS: The risk of MI increased with the deprivation level for both sexes, but was higher for men for all deprivation classes. Relative rates increased along the deprivation scale more steadily for women and followed a different pattern: linear for men and nonlinear for women. Our data provide evidence of effect modification, with departure from an additive joint effect of deprivation and sex. CONCLUSIONS: We document sex differences in the socioeconomic gradient of MI risk in Strasbourg. Women appear more susceptible at levels of extreme deprivation; this result is not a chance finding, given the large difference in event rates between men and women.

Traffic-related air pollution and socioeconomic status: a spatial autocorrelation study to assess environmental equity on a small-area scale.

BACKGROUND: : Most ecologic studies of environmental equity show that groups with lower socioeconomic status (SES) are more likely to be exposed to higher air pollution levels than groups of higher SES. However, these studies rarely consider spatial autocorrelation in the data. We investigated the associations between traffic-related air pollution and SES on a small-area level in Strasbourg (France) and assessed the impact of spatial autocorrelation on the results. METHODS: : We used a deprivation index, constructed from census data, to estimate SES at the block level. Average ambient nitrogen dioxide (NO2) levels during year 2000, modeled at the block level by a dispersion model, served as a marker of traffic exhaust. We estimated the association between exposure to NO2 and the deprivation index by using an ordinary least squares model and a simultaneous autoregressive model that controls for the spatial autocorrelation of data. RESULTS: : The association between the deprivation index and NO2 levels was positive and nonlinear with both regression models; the midlevel deprivation areas were the most exposed. Control of spatial autocorrelation strongly reduced the strength of the association but clearly improved the model's goodness-of-fit; the most pronounced reduction was observed for the midlevel deprivation areas (regression coefficients decreased by 67%). CONCLUSIONS: : This study confirms the need to take spatial autocorrelation into account in ecologic studies and shows that failure to do so may lead to biased and unreliable estimates and thus to erroneous conclusions. This may be especially important in studying the role of air pollution on social inequalities in health.

Influence of socioeconomic deprivation on the relation between air pollution and beta-agonist sales for asthma.

BACKGROUND: Air pollution triggers asthma attacks hours to days after exposure. It remains unclear whether socioeconomic deprivation modulates these effects. Investigation of these interactions requires adequate statistical power, obtainable by using either a sufficient number of observations or very sensitive indicators of asthma attacks. Using a small-area temporal ecologic approach, we studied the short-term relations between ambient air pollution and sales of short-acting beta-agonist (SABA) drugs, a frequent and specific treatment for control of asthma attacks in children and young adults, and then tested the influence of deprivation on these relations. METHODS: The study took place in Strasbourg, France in 2004. Health insurance funds provided data on 15,121 SABA sales for patients aged 0 to 39 years. Deprivation was estimated by small geographic areas using an index constructed from census data. Daily average ambient concentrations of particulate matter (particles with an aerodynamic diameter < 10 microm [PM(10)]), nitrogen dioxide (NO(2)), and ozone (O(3)) were modeled on a small-area level. Adjusted case-crossover models were used for statistical analysis. RESULTS: Increased of 10 microg/m(3) in ambient PM(10), NO(2), and O(3) concentrations were associated, respectively, with increases of 7.5% (95% confidence interval [CI], 4 to 11.2%), 8.4% (95% CI, 5 to 11.9%), and 1% (95% CI, - 0.3 to 2.2%) in SABA sales. Deprivation had no influence on these relations. CONCLUSION: The associations observed are consistent with those reported by studies focusing on SABA use. Similar studies in other settings should confirm whether the lack of interaction with deprivation is due to specific local conditions.

A small-area index of socioeconomic deprivation to capture health inequalities in France.

In the absence of individual data, ecological or contextual measures of socioeconomic level are frequently used to describe social inequalities in health. This work focuses on the methodological aspects of the development and validation of a French small-area index of socioeconomic deprivation and its application to the evaluation of the socioeconomic differentials in health outcomes. This index was derived from a principal component analysis of 1999 national census data from the Strasbourg metropolitan area in eastern France, at the census block level. Composed of 19 variables that reflect the multiple aspects of socioeconomic status (income, employment, housing, family and household, and educational level), it can discriminate disadvantaged urban centres from more privileged rural and suburban areas. Several statistical tests (Cronbach's alpha coefficient, convergent validity tests with other deprivation indices from the literature) provided internal and external validation. Its successful application to another French metropolitan area (Lille, in northern France) confirmed its transposability. Finally, its capacity to capture the social inequalities in health when applied to myocardial infarction data shows its potential value. This study thus provides a new tool in French public health research for characterising neighbourhood deprivation and detecting socioeconomic disparities in the distribution of health outcomes at the small-area level.

Air pollution, asthma attacks, and socioeconomic deprivation: a small-area case-crossover study.

With few exceptions, studies of short-term health effects of air pollution use pollutant concentrations that are averaged citywide as exposure indicators. They are thus prone to exposure misclassification and consequently to bias. Measurement of the relations between air pollution and health, generally and in specific populations, could be improved by employing more geographically precise exposure estimates. The authors investigated short-term relations between ambient air pollution estimated in small geographic areas (French census blocks) and asthma attacks in Strasbourg, France, in 2000-2005--in the general population and in populations with contrasting levels of socioeconomic deprivation. Emergency health-care networks provided data on 4,683 telephone calls made for asthma attacks. Deprivation was estimated using a block-level index constructed from census data. Hourly concentrations of particulate matter less than 10 microm in aerodynamic diameter (PM(10)), sulfur dioxide, nitrogen dioxide, and ozone were modeled by block with ADMS-Urban software. Adjusted case-crossover analyses showed that asthma calls were positively but not significantly associated with PM(10) (for a 10-microg x m(-3) increase, odds ratio (OR) = 1.035, 95% confidence interval (CI): 0.997, 1.075), sulfur dioxide (OR = 1.056, 95% CI: 0.979, 1.139), and nitrogen dioxide (OR = 1.025, 95% CI: 0.990, 1.062). No association was observed for ozone (OR = 0.998, 95% CI: 0.965, 1.032). Socioeconomic deprivation had no significant influence on these relations.

Environmental disasters: preparing for impact assessments and operational feedback.

On March 24, 2006, the French Minister of Environment asked the Committee for Prevention and Precaution (CPP), an independent multidisciplinary committee created in 1996, to conduct a methodological analysis of operational feedback of natural and technological disasters to determine if France is equipped to collect the information and data necessary for the assessment, and optimal management of a disaster and its consequences. The Committee's analysis was based on the testimony it heard from 13 experts--scientists and representatives of associations and advocacy groups--and its review of the literature, including operational feedback reports. Its response to the Minister focused on the assessment of the health, social, environmental, and economic impacts of disasters and on their operational feedback (defined as the systematic analysis of a past event to draw lessons for the management of the risk), as practiced in France. It presents the results of the literature review about the consequences of disasters, expert's views on the current utility and limitations of impact assessments and operational feedback, the CPP's discussion of these results, and its recommendations to improve impact assessment and operational feedback of disasters. These recommendations cover preparation for and activation of data collection and operational feedback, financial provisions, coordination of stakeholders, education and training in disaster preparedness, and the distribution and use of data from operational feedback.

Effect of socioeconomic status on the relationship between atmospheric pollution and mortality.

Current knowledge about potential interactions between socioeconomic status and the short- and long-term effects of air pollution on mortality was reviewed. A systematic search of the Medline database through April 2006 extracted detailed information about exposure measures, socioeconomic indicators, subjects' characteristics and principal results. Fifteen articles (time series, case-crossover, cohort) examined short-term effects. The variety of socioeconomic indicators studied made formal comparisons difficult. One striking fact emerged: studies using socioeconomic characteristics measured at coarser geographic resolutions (city- or county-wide) found no effect modification, but those using finer geographic resolutions found mixed results, and five of six studies using individually-measured socioeconomic characteristics found that pollution affected disadvantaged subjects more. This finding was echoed by the six studies of long-term effects (cohorts) identified; these had substantial methodological differences, which we discuss extensively. Current evidence does not yet justify a definitive conclusion that socioeconomic characteristics modify the effects of air pollution on mortality. Nevertheless, existing results, most tending to show greater effects among the more deprived, emphasise the importance of continuing to investigate this topic.

Probabilistic modeling of young children's overall lead exposure in France: integrated approach for various exposure media.

OBJECTIVES: Emissions of lead into the environment (and thus its environmental concentrations) have decreased in recent years. We sought to estimate the overall lead exposure of children aged 6 months to 6 years (the population group most exposed and most sensitive to lead) in France through the various media (air, food, water, soils, and dust) and the respective contributions of each medium to the total dose. We have focused on the general population, leaving aside specific risk factors such as deteriorated lead paints. METHODS: We used the most recent French intake data for food and water, and a daily ingested quantity selected from the literature for soils and dust. Contamination data came from the first total diet study of contaminant levels in France (2000-2001), from regulatory testing of tap water (2004), a literature review of lead in urban soils, and a pilot study (2005) of lead in dust. Air quality monitoring measurements showed that the contribution of air could now be safely ignored. Weekly exposure doses were estimated with Monte Carlo simulations. RESULTS: Median weekly exposure dose was 7.5 microg/kg bw.week for children aged 6 months to 3 years and 4.7 for those aged from 3-6 years. 95th percentiles were 13.5 and 8.7 microg/kg bw.week. Exposure came mainly from food. The principal uncertainties are associated with quantification limits in food and water, representativeness and traceability of tap water samples, and absence of recent data about urban soil contamination. CONCLUSIONS: These results differ quite notably from earlier estimates and highlight the need, especially for policy-making purposes, to update exposure measurements for this metal.

Assessment of exposure to a flood disaster in a mental-health study.

The lasting psychological consequences of disasters are an important public health issue, especially for determining the support needed by victims. One important question in evaluating psychological consequences remains the assessment of individual disaster-related experiences or stressors. This article proposes two approaches towards the construction of cumulative exposure indicators (CEIs) for a disaster and discusses their relevance for other disasters. In 1997, we carried out a cross-sectional study of the association between the severity of exposure to a 1992 flood in southeastern France and the prevalence of psychological symptoms 5 years later. We interviewed 500 randomly selected subjects residing in one of the most affected municipalities and constructed two CEIs: one based on relevant articles in the literature and the second based on the results of a principal component analysis (PCA) of all the items exploring exposure to the flood. We compared these CEIs with a map of flood damage and tested the association between these indicators and a score of post-traumatic stress symptoms. Most of the subjects (79.1%) had been exposed to at least one stressor besides physical presence. The two CEIs were significantly correlated with one another; comparisons with the map showed that both had good ability to discriminate between mild and severe exposure. Multiple regression analyses showed a significant exposure-effect relation, of the same level of magnitude and significance, between the post-traumatic stress disorder score and each CEI. Our results show the appropriateness of such indicators in assessing the effect of cumulative stress from natural disasters. Guidelines should be developed to improve the comparability of instruments and help standardize methods for evaluating cumulative stress from disasters insofar as possible. Further research is nonetheless necessary to assess the consistency and reproducibility of the data collected.