Age at death during the Covid-19 lockdown in French metropolitan regions: a non parametric quantile regression approach.

BACKGROUND: Lockdowns have been implemented to limit the number of hospitalisations and deaths during the first wave of 2019 coronavirus disease. These measures may have affected differently death characteristics, such age and sex. France was one of the hardest hit countries in Europe with a decreasing east-west gradient in excess mortality. This study aimed at describing the evolution of age at death quantiles during the lockdown in spring 2020 (17 March-11 May 2020) in the French metropolitan regions focusing on 3 representatives of the epidemic variations in the country: Bretagne, Ile-de-France (IDF) and Bourgogne-Franche-Comté (BFC). METHODS: Data were extracted from the French public mortality database from 1 January 2011 to 31 August 2020. The age distribution of mortality observed during the lockdown period (based on each decile, plus quantiles 1, 5, 95 and 99) was compared with the expected one using Bayesian non-parametric quantile regression. RESULTS: During the lockdown, 5457, 5917 and 22 346 deaths were reported in Bretagne, BFC and IDF, respectively. An excess mortality from + 3% in Bretagne to + 102% in IDF was observed during lockdown compared to the 3 previous years. Lockdown led to an important increase in the first quantiles of age at death, irrespective of the region, while the increase was more gradual for older age groups. It corresponded to fewer young people, mainly males, dying during the lockdown, with an increase in the age at death in the first quantile of about 7 years across regions. In females, a less significant shift in the first quantiles and a greater heterogeneity between regions were shown. A greater shift was observed in eastern region and IDF, which may also represent excess mortality among the elderly. CONCLUSIONS: This study focused on the innovative outcome of the age distribution at death. It shows the first quantiles of age at death increased differentially according to sex during the lockdown period, overall shift seems to depend on prior epidemic intensity before lockdown and complements studies on excess mortality during lockdowns.

Regional excess mortality in France during COVID-19 pandemic: the first three epidemic periods (March 2020-June 2021).

BACKGROUND: This study aimed to describe the mortality excess during the three first epidemic periods of COVID-19 in all regions of France. METHODS: Two complementary approaches were implemented. First, we described the number of death of patients infected with or diagnosed with COVID-19 in health care (HC) and medico-social (MS) institutions. Then, we estimated general all-cause mortality excess (all ages) by comparing the mortality observed with the expected mortality. We used a daily number of death model according to a negative binomial distribution, as a function of the long-term trend in mortality (penalized spline function of time) and its seasonal variation (cyclic spline function). The model provided expected mortality during epidemic periods with a 95% credibility interval. Each region defined three epidemic periods, including the overseas territories. RESULTS: The two approaches were consistent in the most affected regions but there are major regional disparities that vary according to the epidemic period. There is an east-west gradient in the relative excess of deaths from all-causes during each epidemic period. The deaths observed in HC and MS institutions alone do not explain the excess (or deficit) of mortality in each region and epidemic period. CONCLUSION: An analysis by age group according to the two approaches and a comparison of death specific causes could provide a better understanding of these differences. Electronic death registration system (mortality by medical causes) would allow a rapid mortality related estimation to an emerging pathology like Coronavirus Disease-2019 (COVID-19) but is still insufficient for real-time medical causes of death monitoring.

On the supra-linearity of the relationship between air pollution, mortality and hospital admission in 18 French cities.

PURPOSE: Understanding the relationship between an environmental determinant and a given health outcome is key to inform public health policies. The short-term mortality and morbidity responses to outdoor air pollutants are traditionally assessed as a log-linear relationship, but few studies suggest a possible deviation from linearity. This paper investigates the shape of the relationship between ozone, NO2 and fine particulate matter (PM10 and PM2.5), mortality and hospital admissions in 18 French cities between 2000 and 2017. METHOD: A multi-centric time series design, using quasi-Poisson generalized additive models, was used. Four approaches were compared to model concentration-response curves (log-linear, piecewise-linear with a priori defined breakpoints, piecewise-linear with no a priori breakpoint and cubic spline). RESULTS: All the models indicated evidence of supra-linearity between PM10, PM2.5, NO2, mortality and hospital admissions. For instance, with a log-linear model, a 10 µg/m3 increase in PM2.5 was associated with a 0.4% [95% CI 0.2; 0.7] increase in non-accidental mortality. When using a piecewise model with a priori set breakpoint at 10 µg/m3, the mortality increase was 3.8% [4.4; 6.3] below 10 µg/m3, and 0.3% [0; 0.6] above. Non-significant impacts of ozone were found for concentrations below 90 µg/m3 to 120 µg/m3, with some variability in the identified threshold across the heath indicator studied. CONCLUSION: The supra-linearity of the relationship between PM10, PM2.5, NO2, mortality and hospital admissions supports the need to further reduce air pollution concentrations well below regulatory values.

Evolving heat waves characteristics challenge heat warning systems and prevention plans.

This paper analyses how recent trends in heat waves impact heat warning systems. We performed a retrospective analysis of the challenges faced by the French heat prevention plan since 2004. We described trends based on the environmental and health data collected each summer by the French heat warning system and prevention plan. Major evolutions of the system were tracked based on the evaluations organized each autumn with the stakeholders of the prevention plan. Excess deaths numbering 8000 were observed during heat waves between 2004 and 2019, 71% of these between 2015 and 2019. We observed major changes in the characteristics, frequency and the geographical spread of heat waves since 2015. Feedbacks led to several updates of the warning system such as the extension of the surveillance period. They also revealed that risk perception remained limited among the population and the stakeholders. The sharp increase in the number of heat warnings issued per year since 2015 challenges the acceptability of the heat warnings. Recent heat waves without historical equivalent interfere with the development of evidence-based prevention strategies. The growing public health impacts heat waves emphasize the urgent need to act to adapt the population, at different levels of intervention, from individual comportments to structural modifications. A specific attention should be given to increase the resources allocated to the evaluation and the management of heat-related risks, especially considering the needs to catch with the rapid rhythm of the changing climate.

Implementation of various hypothetical low emission zone scenarios in Greater Paris: Assessment of fine-scale reduction in exposure and expected health benefits.

OBJECTIVES: Literature assessing the effects of policies aimed at reducing traffic-related air pollution is scarce. The aims of this study were to evaluate the expected impacts, in terms of air quality and health effects, of various hypothetical low-emission zone (LEZ) scenarios in Greater Paris for a planned intervention in 2018/2019 which combine two different perimeters and two levels of vehicles ban, and to assess those impacts according to the socioeconomic status (SES) of the population. METHODS: We evaluated the effects of four hypothetical LEZ scenarios on various stages of the full-chain model, more specifically, road traffic modelling (traffic flow, type of vehicles and related number of kilometers driven), emissions, fine scale PM2.5 and NO2 concentrations, related resident population exposure, and health effects. We computed the overall benefits of expected air pollution improvements in terms of preventable deaths and a decrease in new cases of the following three major chronic diseases: ischemic heart diseases in adults, asthma in children and low weight in full-term newborns. RESULTS: The most stringent LEZ scenario would lower the maximum level of exposure from 55 µg/m3 to 42 µg/m3 in Paris. In one year, this scenario would help prevent: 340 deaths (-0.6%) representing 114,300 life years gained, 170 low-weight full-term births (-4.9%), 130 new cases of ischemic heart disease (IHD) (-1.8%) and 2930 new cases of asthma (-3.0%) among 9.4 million residents. Residents outside the LEZ would also benefit from this scenario. Results indicated that the intervention could contribute to increasing inequalities. The comparison of scenarios underlined the value of extending the LEZ to include a wider zone (including 80 more municipalities surrounding Paris). This would lead to a more equitable spread of the benefits over the population. CONCLUSION: Traffic control policies such as LEZ are difficult to accept for some categories of commuters and economic stakeholders. As of June 2019, the concertation process for the proposed Paris LEZ is still ongoing. This work provides authorities with detailed analyses of the options for this measure as well as information on related implications. It will help decision makers prioritize which preventive measures to introduce.

A new efficient method to monitor precocious puberty nationwide in France.

Clinical precocious puberty (PP) is a disease, reputed to be on the increase and suspected to be linked to endocrine disrupting chemicals (EDC) exposure. Population-based epidemiological data are lacking in France and scarce elsewhere. We accessed the feasibility of monitoring PP nationwide in France in this context, using a nationwide existing database, the French National Health Insurance Information System. Here, we present the method we used with a step-by-step approach to build and select the most suitable indicator. We built three indicators reflecting the incidence of idiopathic central precocious puberty (ICPP), the most frequent form of PP, and we compared these indicators according to their strengths and weaknesses with respect to surveillance purposes. CONCLUSION: Monitoring ICPP in France proved feasible using a Drug reimbursement indicator. Our method is cost efficient and highly relevant in public health surveillance. Our step-by-step approach proved helpful to achieve this project and could be proposed for assessing the feasibility of monitoring health outcomes of interest using existing data bases. What is known: • Precocious puberty (PP) is suspected to be related to EDC exposure and it is believed to be on the increase in France and in others countries. • Very few epidemiologic data on PP are currently available in the world at the national scale. What is new: • This is the first study describing a method to monitor the most frequent form of PP, idiopathic central PP (ICPP) nationwide in a cost-efficient way, using health insurance databases. • This cost-effective method will allow to estimate and monitor the incidence of ICPP in France and to analyze spatial variations at a very precise scale, which will be very useful to examine the role of environmental exposures, especially to EDCs.

Quantitative health impact of indoor radon in France.

Radon is the second leading cause of lung cancer after smoking. Since the previous quantitative risk assessment of indoor radon conducted in France, input data have changed such as, estimates of indoor radon concentrations, lung cancer rates and the prevalence of tobacco consumption. The aim of this work was to update the risk assessment of lung cancer mortality attributable to indoor radon in France using recent risk models and data, improving the consideration of smoking, and providing results at a fine geographical scale. The data used were population data (2012), vital statistics on death from lung cancer (2008-2012), domestic radon exposure from a recent database that combines measurement results of indoor radon concentration and the geogenic radon potential map for France (2015), and smoking prevalence (2010). The risk model used was derived from a European epidemiological study, considering that lung cancer risk increased by 16% per 100 becquerels per cubic meter (Bq/m3) indoor radon concentration. The estimated number of lung cancer deaths attributable to indoor radon exposure is about 3000 (1000; 5000), which corresponds to about 10% of all lung cancer deaths each year in France. About 33% of lung cancer deaths attributable to radon are due to exposure levels above 100 Bq/m3. Considering the combined effect of tobacco and radon, the study shows that 75% of estimated radon-attributable lung cancer deaths occur among current smokers, 20% among ex-smokers and 5% among never-smokers. It is concluded that the results of this study, which are based on precise estimates of indoor radon concentrations at finest geographical scale, can serve as a basis for defining French policy against radon risk.

Controlling for seasonal patterns and time varying confounders in time-series epidemiological models: a simulation study.

An important topic when estimating the effect of air pollutants on human health is choosing the best method to control for seasonal patterns and time varying confounders, such as temperature and humidity. Semi-parametric Poisson time-series models include smooth functions of calendar time and weather effects to control for potential confounders. Case-crossover (CC) approaches are considered efficient alternatives that control seasonal confounding by design and allow inclusion of smooth functions of weather confounders through their equivalent Poisson representations. We evaluate both methodological designs with respect to seasonal control and compare spline-based approaches, using natural splines and penalized splines, and two time-stratified CC approaches. For the spline-based methods, we consider fixed degrees of freedom, minimization of the partial autocorrelation function, and general cross-validation as smoothing criteria. Issues of model misspecification with respect to weather confounding are investigated under simulation scenarios, which allow quantifying omitted, misspecified, and irrelevant-variable bias. The simulations are based on fully parametric mechanisms designed to replicate two datasets with different mortality and atmospheric patterns. Overall, minimum partial autocorrelation function approaches provide more stable results for high mortality counts and strong seasonal trends, whereas natural splines with fixed degrees of freedom perform better for low mortality counts and weak seasonal trends followed by the time-season-stratified CC model, which performs equally well in terms of bias but yields higher standard errors.

Economic valuation of the mortality benefits of a regulation on SO2 in 20 European cities.

BACKGROUND: Since the 1970s, legislation has led to progress in tackling several air pollutants. We quantify the annual monetary benefits resulting from reductions in mortality from the year 2000 onwards following the implementation of three European Commission regulations to reduce the sulphur content in liquid fuels for vehicles. METHODS: We first compute premature deaths attributable to these implementations for 20 European cities in the Aphekom project by using a two-stage health impact assessment method. We then justify our choice to only consider mortality effects as short-term effects. We rely on European studies when selecting the central value of a life-year estimate (€ 2005 86 600) used to compute the monetary benefits for each of the cities. We also conduct an independent sensitivity analysis as well as an integrated uncertainty analysis that simultaneously accounts for uncertainties concerning epidemiology and economic valuation. RESULTS: The implementation of these regulations is estimated to have postponed 2212 (95% confidence interval: 772-3663) deaths per year attributable to reductions in sulphur dioxide for the 20 European cities, from the year 2000 onwards. We obtained annual mortality benefits related to the implementation of the European regulation on sulphur dioxide of € 2005 191.6 million (95% confidence interval: € 2005 66.9-€ 2005 317.2). CONCLUSION: Our approach is conservative in restricting to mortality effects and to short-term benefits only, thus only providing the lower-bound estimate. Our findings underline the health and monetary benefits to be obtained from implementing effective European policies on air pollution and ensuring compliance with them over time.

Two Decades of Air Pollution Health Risk Assessment: Insights From the Use of WHO's AirQ and AirQ+ Tools.

Objectives: We evaluated studies that used the World Health Organization's (WHO) AirQ and AirQ+ tools for air pollution (AP) health risk assessment (HRA) and provided best practice suggestions for future assessments. Methods: We performed a comprehensive review of studies using WHO's AirQ and AirQ+ tools, searching several databases for relevant articles, reports, and theses from inception to Dec 31, 2022. Results: We identified 286 studies that met our criteria. The studies were conducted in 69 countries, with most (57%) in Iran, followed by Italy and India (∼8% each). We found that many studies inadequately report air pollution exposure data, its quality, and validity. The decisions concerning the analysed population size, health outcomes of interest, baseline incidence, concentration-response functions, relative risk values, and counterfactual values are often not justified, sufficiently. Many studies lack an uncertainty assessment. Conclusion: Our review found a number of common shortcomings in the published assessments. We suggest better practices and urge future studies to focus on the quality of input data, its reporting, and associated uncertainties.

Definition of temperature thresholds: the example of the French heat wave warning system.

Heat-related deaths should be somewhat preventable. In France, some prevention measures are activated when minimum and maximum temperatures averaged over three days reach city-specific thresholds. The current thresholds were computed based on a descriptive analysis of past heat waves and on local expert judgement. We tested whether a different method would confirm these thresholds. The study was set in the six cities of Paris, Lyon, Marseille, Nantes, Strasbourg and Limoges between 1973 and 2003. For each city, we estimated the excess in mortality associated with different temperature thresholds, using a generalised additive model, controlling for long-time trends, seasons and days of the week. These models were used to compute the mortality predicted by different percentiles of temperatures. The thresholds were chosen as the percentiles associated with a significant excess mortality. In all cities, there was a good correlation between current thresholds and the thresholds derived from the models, with 0°C to 3°C differences for averaged maximum temperatures. Both set of thresholds were able to anticipate the main periods of excess mortality during the summers of 1973 to 2003. A simple method relying on descriptive analysis and expert judgement is sufficient to define protective temperature thresholds and to prevent heat wave mortality. As temperatures are increasing along with the climate change and adaptation is ongoing, more research is required to understand if and when thresholds should be modified.

Increase in psychotropic drug deliveries after the Xynthia storm, France, 2010.

INTRODUCTION: During the night of February 27 and the early morning of February 28, 2010, 15 coastal municipalities situated in two French departments, Vendée and Charente-Maritime, were violently stricken by a severe windstorm named "Xynthia." This storm caused the death of 12 individuals in Charente-Maritime and 29 people in Vendée. Houses, agricultural fields, and shellfish companies were severely flooded with seawater. Several thousand people temporarily had to leave their homes. The objective of this study was to estimate the short-term mental health impact of Xynthia, in terms of psychotropic drug delivery, on the resident population of the 15 coastal municipalities severely hit by the flooding. METHODS: The French national health insurance database was used to calculate a daily number of new psychotropic treatments from September 1, 2008 through December 24, 2010. New treatments were calculated for each of the following European Pharmaceutical Marketing Research Association (EphMRA) classes: tranquilizers (N05C), hypnotics (N05B), and antidepressants (N06A). A period of three weeks following the storm was defined as the exposure period. A generalized additive model with a Poisson distribution that allows for over-dispersion was used to analyze the correlation between the Xynthia variable and the number of new psychotropic treatments. RESULTS: With a relative risk (RR) of 1.54 (95% CI, 1.39-1.62) corresponding to an estimate of 409 new deliveries of psychotropic drugs during the three weeks following the storm, this study confirms the importance of the psychological impact of Xynthia. This impact is seen on all three classes of psychotropic drugs studied. The impact is greater for tranquilizers (RR of 1.78; 95% CI, 1.59-1.89) than for hypnotics (RR of 1.53; 95% CI, 1.31-1.67) and antidepressants (RR of 1.26; 95% CI, 1.06-1.40). The RR was higher for females than for males. CONCLUSION: This study shows the importance of the psychological impact of the storm as observed clinically by health workers who intervened in the field during the aftermath of Xynthia. It confirms that administrative databases can be used to show a health impact of a disaster even at a local level. This is one more step in the direction of a comprehensive strategy of collecting information to allow the assessment of the health impact of an extreme event, the detection of vulnerable populations, and the orientation of the short-, mid- and long-term public health response.

A time series study of drug sales and turbidity of tap water in Le Havre, France.

The 80,000 inhabitants of the lower part of Le Havre obtain their water supply from two karstic springs, Radicatel and Saint-Laurent. Until 2000, the Radicatel water was settled when turbidity exceeded 3 NTU, then filtered and chlorinated, whereas the Saint-Laurent water was simply chlorinated. Our study aimed to characterize the link between water turbidity and the incidence of acute gastroenteritis (AGE). Records on drug sales used for the treatment of AGE were collected from January 1994 to June 1996 (period 1) and from March 1997 to July 2000 (period 2). Daily counts of drug sales were modeled using a Poisson Regression. We used data set 2 as a discovery set, identifying relevant (i.e. both significant and plausible) exposure covariates and lags. We then tested this model on period 1 as a replication dataset. In period 2, the daily drug sales correlated with finished water turbidity at both resources. Settling substantially modified the risk related to turbidity of both raw and finished waters at Radicatel. Correlations were reproducible in period 1 for water from the Radicatel spring. Timeliness of treatment adaptation to turbidity conditions appears to be crucial for reducing the infectious risk due to karstic waters.

Influence of exposure assessment methods on associations between long-term exposure to outdoor fine particulate matter and risk of cancer in the French cohort Gazel.

BACKGROUND: Many studies investigated the relationship between outdoor fine particulate matter (PM2.5) and cancer. While they generally indicated positive associations, results have not been fully consistent, possibly because of the diversity of methods used to assess exposure. OBJECTIVES: To investigate how using different PM2.5 exposure assessment methods influences risk estimates in the large French general population-based Gazel cohort (20,625 participants at enrollment) with a 26-year follow-up with complete residential histories. METHODS: We focused on two cancer incidence outcomes: all-sites combined and lung. We used two distinct exposure assessment methods: a western European land use regression (LUR), and a chemistry-dispersion model (Gazel-Air) for France, each with a time series ≥20-years annual concentrations. Spearman correlation coefficient between the two estimates of PM2.5 was 0.71 across all person-years; the LUR tended to provide higher exposures. We used extended Cox models with attained age as time-scale and time-dependent cumulative exposures, adjusting for a set of confounders including sex and smoking, to derive hazard ratios (HRs) and their 95% confidence interval, implementing a 10-year lag between exposure and incidence/censoring. RESULTS: We obtained similar two-piece linear associations for all-sites cancer (3711 cases), with a first slope of HRs of 1.53 (1.24-1.88) and 1.43 (1.19-1.73) for one IQR increase of cumulative PM2.5 exposure for the LUR and the Gazel-Air models respectively, followed by a plateau at around 1.5 for both exposure assessments. For lung cancer (349 cases), the HRs from the two exposure models were less similar, with largely overlapping confidence limits. CONCLUSION: Our findings using long-term exposure estimates from two distinct exposure assessment methods corroborate the association between air pollution and cancer risk.

Identification of Workers at Increased Risk of Infection During a COVID-19 Outbreak in a Meat Processing Plant, France, May 2020.

On 13 May 2020, a COVID-19 cluster was detected in a French processing plant. Infected workers were described. The associations between the SARS-CoV-2 infection and the socio-demographic and occupational characteristics were assessed in order to implement risk management measures targeting workers at increased risk of contamination. Workers were tested by RT-PCR from samples taken during screening campaigns. Workers who tested positive were isolated and their contacts were quarantined. Workers were described and associations with the SARS-CoV-2 infection were assessed through risk ratios using multivariable Poisson regression. Of the 1347 workers, 87.5% were tested: 140 cases were identified; 4 were hospitalised, including 2 admitted to intensive care. In the company, the cluster remained limited to deboning and cutting activities. The attack rate was 11.9% in the company, reaching 16.6% in the cutting department. Being an employee of a subcontractor significantly increased the risk of infection by 2.98 [1.81-4.99]. In the cutting department, an association with virus infection was found for a group of non-French speaking workers from the same Eastern European country (RR = 2.67 [1.76-4.05]). They shared accommodation or carpooled more frequently than the other cases. The outbreak investigation revealed a significantly increased risk of SARS-CoV-2 infection for workers of subcontractors and some foreign-born workers. There are many such populations in meat processing plants; the observed associations and the ways in which these workers are contaminated need to be confirmed by further work. Prevention campaigns should now target these workers. Environmental risk factors in the workplace setting remain to be clarified.

Quantification of the heat wave effect on cause-specific mortality in Essen, Germany.

The impact of high temperatures on mortality is well known, but not all deaths that occur during heat waves can be explained by this effect. We evaluated whether an additional mechanism caused by periods of sustained heat without nightly cooling influenced mortality during the European heat wave in 2003 and whether this mechanism is different for varying causes of death. We obtained daily counts of total and cause-specific mortality for Essen, Germany, for the years 2000-2006. We used time-series regression methods to separate a possible additional effect of sustained heat from the temperature effect and included air pollution, influenza epidemics, long-term and seasonal trends, days of week and bank holidays as covariates. The maximum daily relative risk of all-cause mortality during the heat wave was 1.28 (95% CI 1.06-1.53). The maximum relative risks of cardiovascular and neoplastic mortality were 1.25 (95% CI 0.95-1.65) and 1.35 (95% CI 1.00-1.82), respectively. The effect on respiratory mortality was delayed; the maximum relative risk was 1.66 (95% CI 1.19-2.23) 6 days after the heat wave. We found that periods with sustained heat especially affected respiratory mortality, whereas for cardiovascular and neoplastic mortality no distinct influence could be shown.

Air pollution and health: a European and North American approach (APHENA).

INTRODUCTION: This report provides the methodology and findings from the project: Air Pollution and Health: a European and North American Approach (APHENA). The principal purpose of the project was to provide an understanding of the degree of consistency among findings of multicity time-series studies on the effects of air pollution on mortality and hospitalization in several North American and European cities. The project included parallel and combined analyses of existing data. The investigators sought to understand how methodological differences might contribute to variation in effect estimates from different studies, to characterize the extent of heterogeneity in effect estimates, and to evaluate determinants of heterogeneity. The APHENA project was based on data collected by three groups of investigators for three earlier studies: (1) Air Pollution and Health: A European Approach (APHEA), which comprised two multicity projects in Europe. (Phase 1 [APHEA1] involving 15 cities, and Phase 2 [APHEA2] involving 32 cities); (2) the National Morbidity, Mortality, and Air Pollution Study (NMMAPS), conducted in the 90 largest U.S. cities; and (3) multicity research on the health effects of air pollution in 12 Canadian cities. METHODS: The project involved the initial development of analytic approaches for first-stage and second-stage analyses of the time-series data and the subsequent application of the resulting methods to the time-series data. With regard to the first-stage analysis, the various investigative groups had used conceptually similar approaches to the key issues of controlling for temporal confounding and temperature; however, specific methods differed. Consequently, the investigators needed to establish a standard protocol, but one that would be linked to prior approaches. Based on exploratory analyses and simulation studies, a first-stage analysis protocol was developed that used generalized linear models (GLM) with either penalized splines (PS) or natural splines (NS) to adjust for seasonality, with 3, 8, or 12 degrees of freedom (df) per year and also the number of degrees of freedom chosen by minimizing the partial autocorrelation function (PACF) of the model's residuals. For hospitalization data, the approach for model specification followed that used for mortality, accounting for seasonal patterns, but also, for weekend and vacation effects, and for epidemics of respiratory disease. The data were also analyzed to detect potential thresholds in the concentration-response relationships. The second-stage analysis used pooling approaches and assessed potential effect modification by sociodemographic characteristics and indicators of the pollution mixture across study regions. Specific quality control exercises were also undertaken. Risks were estimated for two pollutants: particulate matter - 10 pm in aerodynamic diameter (PM10) and ozone (O3). RESULTS: The first-stage analysis yielded estimates that were relatively robust to the underlying smoothing approach and to the number of degrees of freedom. The first-stage APHENA results generally replicated the previous independent analyses performed by the three groups of investigators. PM10 effects on mortality risk estimates from the APHEA2 and NMMAPS databases were quite close, while estimates from the Canadian studies were substantially higher. For hospitalization, results were more variable without discernable patterns of variation among the three data sets. PM10 effect-modification patterns, explored only for cities with daily pollution data (i.e., 22 in Europe and 15 in the U.S.), were not entirely consistent across centers. Thus, the levels of pollutants modified the effects differently in Europe than in the United States. Climatic variables were important only in Europe. In both Europe and the United States, a higher proportion of older persons in the study population was associated with increased PM10 risk estimates, as was a higher rate of unemployment - the sole indicator of socioeconomic status uniformly available across the data sets. APHENA study results on the effects of O3 on mortality were less comprehensive than for PM10 because the studies from the three regions varied in whether they analyzed data for the full year or only for the summer months. The effects tended to be larger for summer in Europe and the United States. In the United States they were lower when controlled for PM10. The estimated effect of O3 varied by degrees of freedom and across the three geographic regions. The effects of O3 on mortality were larger in Canada, and there was little consistent indication of effect modification in any location. CONCLUSIONS: APHENA has shown that mortality findings obtained with the new standardized analysis were generally comparable to those obtained in the earlier studies, and that they were relatively robust to the data analysis method used. For PM10, the effect-modification patterns observed were not entirely consistent between Europe and the United States. For O3, there was no indication of strong effect modification in any of the three data sets.

Marked geographic patterns in the incidence of idiopathic central precocious puberty: a nationwide study in France.

OBJECTIVES: Precocious puberty seems to be increasing but epidemiological data are scarce. Our objective was to improve the epidemiologic knowledge on this disease. We analyzed the national incidence and spatial trends of idiopathic central precocious puberty in France in 2011-2013 in a cross-sectional descriptive study. DESIGN: We used an indicator based on treatment reimbursements recorded in the national insurance database, in girls under the age of nine years and in boys under the age of 10 years. We considered a time lag of up to one year from the onset of puberty to first drug delivery. We tested four different predictive spatial models at the département scale, selecting the model best fitting the data. We carried out semi-structured interviews with qualified hospital teams in five selected regions to investigate spatial differences in medical practices. RESULTS: The national annual incidence was 2.68 (95% CI: 2.55, 2.81) per 10 000 girls under the age of 9 years and 0.24 (95% CI: 0.21, 0.27) per 10 000 boys under the age of 10 years. Incidence rates conformed to a purely spatial heterogeneity model in girls, consistent between age groups, with a large incidence range. A similar pattern was observed for boys, with peaks in the South West and Center East. Differences in medical practices may have slightly affected incidence locally, but could not entirely explain the marked geographic pattern. CONCLUSIONS: The results suggest that the risk factors are similar for boys and girls and justify further investigations of the role of the environment.

The fraction of lung cancer incidence attributable to fine particulate air pollution in France: Impact of spatial resolution of air pollution models.

Outdoor air pollution is a leading environmental cause of death and cancer incidence in humans. We aimed to estimate the fraction of lung cancer incidence attributable to fine particulate matter (PM2.5) exposure in France, and secondarily to illustrate the influence of the input data and the spatial resolution of information on air pollution levels on this estimate. The population attributable fraction (PAF) was estimated using a nationwide spatially refined chemistry-transport model with a 2-km spatial resolution, neighbourhood-scale population density data, and a relative risk from a published meta-analysis. We used the WHO guideline value for PM2.5 exposure (10 µg/m3) as reference. Sensitivity analyses consisted in attributing the nation-wide median exposure to all areas and using alternative input data such as reference of PM2.5 exposure level and relative risk. Population-weighted median PM2.5 level in 2005 was 13.8 µg/m3; 87% of the population was exposed above the guideline value. The burden of lung cancer attributable to PM2.5 exposure corresponded to 1466 cases, or 3.6% of all cases diagnosed in 2015. Sensitivity analyses showed that the use of a national median of PM2.5 exposure would have led to an underestimation of the PAF by 11% (population-weighted median) and by 72% (median of raw concentration), suggesting that our estimates would have been higher with even more finely spatially-resolved models. When the PM2.5 reference level was replaced by the 5th percentile of country-scale exposure (4.9 µg/m3), PAF increased to 7.6%. Other sensitivity analyses resulted in even higher PAFs. Improvements in air pollution are crucial for quantitative health impacts assessment studies. Actions to reduce PM2.5 levels could substantially reduce the burden of lung cancer in France.

Epidemiology of Childhood Hyperthyroidism in France: A Nationwide Population-Based Study.

Context: Hyperthyroidism affects all age groups, but epidemiological data for children are scarce. Objective: To perform a nationwide epidemiological survey of hyperthyroidism in children and adolescents. Design: A cross-sectional descriptive study. Setting: Identification of entries corresponding to reimbursements for antithyroid drugs in the French national insurance database. Participants: All cases of childhood hyperthyroidism (6 months to 17 years of age) in 2015. Main Outcome Measures: National incidence rate estimated with a nonlinear Poisson model and spatial distribution of cases. Results: A total of 670 cases of childhood hyperthyroidism were identified. Twenty patients (3%) had associated autoimmune or genetic disease, with type 1 diabetes and Down syndrome the most frequent. The annual incidence for 2015 was 4.58/100,000 person-years (95% CI 3.00 to 6.99/100,000). Incidence increased with age, in both sexes. This increase accelerated after the age of 8 in girls and 10 in boys and was stronger in girls. About 10% of patients were affected before the age of 5 years (sex ratio 1.43). There was an interaction between age and sex, the effect of being female increasing with age: girls were 3.2 times more likely to be affected than boys in the 10 to 14 years age group and 5.7 times more likely to be affected in the 15 to 17 years age group. No conclusions about spatial pattern emerged. Conclusion: These findings shed light on the incidence of hyperthyroidism and the impact of sex on this incidence during childhood and adolescence. The observed incidence was higher than expected from the results published for earlier studies in Northern European countries.