Collider and reporting biases involved in the analyses of cause of death associations in death certificates: an illustration with cancer and suicide.

BACKGROUND: Mortality data obtained from death certificates have been studied to explore causal associations between diseases. However, these analyses are subject to collider and reporting biases (selection and information biases, respectively). We aimed to assess to what extent associations of causes of death estimated from individual mortality data can be extrapolated as associations of disease states in the general population. METHODS: We used a multistate model to generate populations of individuals and simulate their health states up to death from national health statistics and artificially replicate collider bias. Associations between health states can then be estimated from such simulated deaths by logistic regression and the magnitude of collider bias assessed. Reporting bias can be approximated by comparing the estimates obtained from the observed death certificates (subject to collider and reporting biases) with those obtained from the simulated deaths (subject to collider bias only). As an illustrative example, we estimated the association between cancer and suicide in French death certificates and found that cancer was negatively associated with suicide. Collider bias, due to conditioning inclusion in the study population on death, increasingly downwarded the associations with cancer site lethality. Reporting bias was much stronger than collider bias and depended on the cancer site, but not prognosis. RESULTS: The magnitude of the biases ranged from 1.7 to 9.3 for collider bias, and from 4.7 to 64 for reporting bias. CONCLUSIONS: These results argue for an assessment of the magnitude of both collider and reporting biases before performing analyses of cause of death associations exclusively from mortality data. If these biases cannot be corrected, results from these analyses should not be extrapolated to the general population.

Association of Daily Temperature With Suicide Mortality: A Comparison With Other Causes of Death and Characterization of Possible Attenuation Across 5 Decades.

Suicide is one of the leading causes of death in young adults in many Western countries. We examined the short-term association of temperature with cause-specific mortality, comparing suicide with other causes of death and describing possible attenuation of associations with temperature across decades. We considered all deaths that occurred in France between 1968 and 2016. For each cause of death, we conducted a 2-stage meta-analysis of associations with daily temperature. We stratified the association across time periods. A total of 502,017 deaths by suicide were recorded over 49 years. Temperature was monotonically associated with suicide mortality. The strongest association was found at lag 0 days. The relative risk of suicide mortality at the 99th (compared with the 1st) temperature percentile was 1.54 (95% confidence interval, 1.46, 1.63). Among all causes of death, suicide was the only cause displaying a monotonic trend with temperature and ranked seventh for heat-related mortality; 2 other causes of death implying the nervous system ranked third and fourth. Associations with temperature attenuated between the 1968-1984 and 1985-2000 periods for all-cause mortality and suicide mortality, without clear further attenuation in the 2001-2016 period. The robust short-term monotonic association between temperature and suicide risk could be considered in heat effects- and suicide-related prevention campaigns.

Time trend in excess mortality in children with type 1 diabetes from 1987 to 2016 in mainland France.

BACKGROUND: Mortality risk for children with type 1 diabetes (T1D) is unknown in France and their causes of death are not well documented. AIM: To determine the standardized mortality ratios (SMRs) and causes of death in children aged 1-14 years with T1D from 1987 to 2016. METHODS: The French Center for Epidemiology on Medical Causes of Death collected all death certificates in mainland France. SMRs, corrected SMRs (accounting for missing cases of deaths unrelated to diabetes), and 95% confidence intervals were calculated. RESULTS: Of 146 deaths with the contribution of diabetes, 97 were due to T1D. Mean age at death of the subjects with T1D was 8.8 ± 4.1 years (54% males). The cause of death was diabetic ketoacidosis (DKA) in 58% of the cases (70% in subjects 1-4 years), hypoglycemia or dead-in-bed syndrome in 4%, related to diabetes but not described in 24%, and unrelated to diabetes in 14%. The SMRs showed a significant decrease across the years, except for the 1-4 age group. In the last decade (2007-2016), the crude and corrected SMRs were significantly different from 1 in the 1-4 age group (5.4 [2.3; 10.7] and 6.1 [2.8; 11.5]), no longer significant in the 5-9 age group (1.7 [0.6; 4.0] and 2.1 [0.8; 4.5]) and borderline significant in the 10-14 age group (1.7 [0.8; 3.2] and 2.3 [1.2; 4.0]). CONCLUSIONS: Children with T1D aged 1-4 years still had a high mortality rate. Their needs for early recognition and safe management of diabetes are not being met.

National Variations in Recent Trends of Sudden Unexpected Infant Death Rate in Western Europe.

OBJECTIVE: To study recent epidemiologic trends of sudden unexpected death in infancy (SUDI) in Western Europe. STUDY DESIGN: Annual national statistics of death causes for 14 Western European countries from 2005 to 2015 were analyzed. SUDI cases were defined as infants younger than 1 year with the underlying cause of death classified as "sudden infant death syndrome," "unknown/unattended/unspecified cause," or "accidental threats to breathing." Poisson regression models were used to study temporal trends of SUDI rates and source of variation. RESULTS: From 2005 to 2015, SUDI accounted for 15 617 deaths, for an SUDI rate of 34.9 per 100 000 live births. SUDI was the second most common cause of death after the neonatal period (22.2%) except in Belgium, Finland, France, and the UK, where it ranked first. The overall SUDI rate significantly decreased from 40.2 to 29.9 per 100 000, with a significant rate reduction experienced for 6 countries, no significant evolution for 7 countries, and a significant increase for Denmark. The sudden infant death syndrome/SUDI ratio was 56.7%, with a significant decrease from 64.9% to 49.7% during the study period, and ranged from 6.1% in Portugal to 97.8% in Ireland. We observed between-country variations in SUDI and sudden infant death syndrome sex ratios. CONCLUSIONS: In studied countries, SUDI decreased during the study period but remained a major cause of infant deaths, with marked between-country variations in rates, trends, and components. Standardization is needed to allow for comparing data to improve the implementation of risk-reduction strategies.

A Note on the Measurement of Socioeconomic Inequalities in Life Years Lost by Cause of Death.

Quantifying socioeconomic inequalities in health in absolute terms is of prime interest for decision-making and for international comparisons. The Slope Index of Inequality (SII), an index that quantifies absolute socioeconomic inequalities, was recently formalized, particularly in the context of mortality differences measured in the rate or hazard scale. However, absolute inequalities using either rates or hazards do not translate into a time dimension, which makes their interpretation difficult for policymakers. We propose an extension of the (Equation is included in full-text article.)in terms of the expected number of life years lost before an upper age, as well as its decomposition by cause of death. The (Equation is included in full-text article.)in the life years lost metric quantifies the extent to which life expectancy is shortened when comparing the higher and lower ends of the socioeconomic scale. The methodology proposed builds on recent developments in survival analysis for decomposing the number of life years lost according to cause of death using a pseudo-value approach. We illustrate our proposal using a representative 1% sample of the French population. On average, the least educated men lost 7 years of life from age 30 up to age 90 compared to the most educated. The loss for women is twice as much with 3.5 years. The (Equation is included in full-text article.)in the life years lost metric is easily understood, and the decomposition of the all-cause mortality (Equation is included in full-text article.)into parts attributable to given causes provides a sound estimation of the burden of different causes of death on absolute socioeconomic inequalities in mortality.

Mortality causes and trends associated with giant cell arteritis: analysis of the French national death certificate database (1980-2011).

OBJECTIVES: Comprehensive analyses of cause-specific death patterns in GCA are sparse. We studied the patterns and time trends in GCA-related mortality using a large death certificate database. METHODS: We obtained multiple-cause-of-death data from the French national death certificate database for 1980-2011. GCA-associated deaths were defined as decedents ⩾55 years old with GCA listed as an underlying or non-underlying cause of death. Time trends of death rates were analysed and the mean age at death with GCA and in the general population ⩾55 years old were calculated. Standardized mortality odds ratios (SMORs) were calculated for 17 selected causes of death (based on 2000-11 data). RESULTS: The analyses pertained to approximately 15 000 death certificates listing GCA (including approximately 6300 for 2000-11). Annual standardized death rates for GCA increased to a peak in 1997 and then decreased (Spearman's correlation test, both P < 0.0001). Mean age at death was higher for GCA than for general population decedents (Student's t-test, P < 0.0001). GCA deaths were frequently or strongly associated with aortic aneurysm and dissection (1.85% of death certificates, SMOR: 3.09, 95% CI: 2.48, 3.82), hypertensive disease (20.78%, SMOR: 2.22, 95% CI: 1.97, 2.50), diabetes mellitus (11.27%, SMOR: 1.96, 95% CI: 1.72, 2.23), certain infectious and parasitic diseases (12.12%, SMOR: 1.76, 95% CI: 1.55, 2.00) and ischaemic heart disease (16.54%, SMOR: 1.45, 95% CI: 1.35, 1.64). CONCLUSION: GCA is associated with increased risk of dying from large-vessel disease, other cardiovascular diseases and potentially treatment-related co-morbidities. These findings help provide better insights into the outcomes of GCA.

The heart of the matter: years-saved from cardiovascular and cancer deaths in an elite athlete cohort with over a century of follow-up.

To quantify the years of life saved from cardiovascular (CVD), cancer and overall deaths among elite athletes according to their main type of physiological effort performed in the Olympic Games. All French athletes participating in the Games from 1912 to 2012, with vital status validated and cause of death (if concerned) identified by the national registries were included (n = 2814, 455 died) and classified according to 6 groups of effort: POWER (continuous effort < 45 s); INTERMEDIATE (45 s ≤ continuous effort < 600 s); ENDURANCE (continuous effort ≥ 600 s); POLYVALENT (participating in different events entering different classifications), INTERMITTENT (intermittent effort, i.e. team sports); PRECISION (targeting events). The theoretical years-lost method was adapted to calculate gains in longevity (years-saved) according to specific-risks under the competing risks model and was implemented in R software. Considering overall-deaths, all groups significantly saved, on average, 6.5 years of life (95% CI 5.8-7.2) compared to the general population. This longevity advantage is mainly driven by a lower risk of cancer which, isolated, contributed to significantly save 2.3 years of life (95% CI 1.2-1.9) on average in each group. The risk of CVD-related mortality in the ENDURANCE and PRECISION groups is not significantly different from the general population. The other groups significantly saved, on average, 1.6 years of life (95% CI 1.2-1.9) from CVD death. The longevity benefits in elite athletes are associated with the type of effort performed during their career, mainly due to differences on the CVD-risk of death.

Risk of hospitalisation and death related to baclofen for alcohol use disorders: Comparison with nalmefene, acamprosate, and naltrexone in a cohort study of 165 334 patients between 2009 and 2015 in France.

PURPOSE: Baclofen is widely used off-label for alcohol use disorders (AUD) in France, despite its uncertain efficacy and safety, particularly at high doses. This study was designed to evaluate the safety of this off-label use compared to the main approved drugs for AUD (acamprosate, naltrexone, nalmefene). METHODS: This cohort study from the French Health Insurance claims database included patients, aged 18 to 70 years, with no serious comorbidity (assessed by the Charlson score) initiating baclofen or approved drugs for AUD between 2009 and 2015. The risk of hospitalisation or death associated with baclofen, at variable doses over time (from low doses <30 mg/day to high doses ≥180 mg/day), compared to approved drugs, was evaluated by a Cox model adjusted to sociodemographic and medical characteristics. RESULTS: The cohort included 165 334 patients, 47 614 of whom were exposed to baclofen. Patients exposed to baclofen differed from those treated with approved drugs in terms of sociodemographic and medical characteristics (more females, higher socioeconomic status, fewer hospitalisations for alcohol-related problems), but these differences tended to fade at higher doses of baclofen. Baclofen exposure was significantly associated with hospitalisation (hazard ratio [HR] = 1.13 [95%CI: 1.09-1.17]) and death (HR = 1.31 [95%CI: 1.08-1.60]). The risk increased with dose, reaching 1.46 [1.28-1.65] for hospitalisation and 2.27 [1.27-4.07] for death at high doses. Similar results were in patients with a history of hospitalisation for alcohol-related problems. CONCLUSIONS: This study raises concerns about the safety of baclofen for AUD, particularly at high doses, with higher risks of hospitalisation and mortality than approved drugs.

Socio-economic factors associated with an increase in fruit and vegetable consumption: a 12-year study in women from the E3N-EPIC study.

OBJECTIVE: To identify individual and contextual socio-economic factors associated with an increase in fruit and vegetable (F&V) consumption over a 12-year period and evaluate if some socio-economic factors were differentially associated with the change in consumption of some types of F&V. DESIGN: Associations between increased F&V consumption and socio-economic factors were studied with multivariate logistic regression. SETTING: E3N, a French prospective cohort study of 98 995 women. SUBJECTS: E3N participants (n 58 193) with information on diet in 1993 and 2005, and numerous individual and contextual socio-economic factors available. RESULTS: Associations between some individual socio-economic factors and changes in F&V consumption were observed. For instance, women who lived in a large household (>3 children v. no child) had higher probability of increasing their vegetable consumption (OR=1·33; 95 % CI 1·24, 1·42). This association was driven by higher consumption of courgette and raw cucumber. Living with a partner was associated with higher odds of increasing consumption of fruits (OR=1·07; 95 % CI 1·02, 1·13) such as pear, peach and grape. CONCLUSIONS: Certain individual socio-economic factors, but none of the contextual socio-economic factors examined, were associated with an increase in F&V consumption. Factors associated with an increase in total F&V consumption were not necessarily associated with an increase in fruit or vegetable consumption separately, or with an increase in each subtype of fruit or vegetable. Magnitudes of the different associations observed also differed when F&V were considered together, separately or by subtype. Increases in F&V consumption were mostly observed in women with high socio-economic position. To develop effective nutritional interventions and policies that take the socio-economic environment of individuals into account, we recommend future research to further focus on (i) pathways through which population characteristics might influence changes in F&V consumption and (ii) existing interactions between individual and contextual socio-economic factors.

Survival Analysis with Multiple Causes of Death: Extending the Competing Risks Model.

Statistics on mortality related to each disease are usually based on the so-called underlying cause of death, which is selected from the diseases declared on the standardized death certificate using international rules. However, the assumption that each death is caused by exactly one disease is debatable, particularly with an aging population in an era where infectious diseases are replaced by chronic and degenerative diseases. The need to consider multiple causes of death has been acknowledged in epidemiologic research, with a growing body of literature producing statistics based on any mention of a disease on the death certificate. Yet there has not been a formal framework proposed for the statistical modeling of death arising from multiple causes. We propose a model for multiple cause of death data grounded on an empirical approach that assigns weights to each cause on the death certificate. We describe how this model for multiple-cause mortality, which extends the usual competing risks model used to conceptualize single-cause mortality, can serve to study the burden and etiology of mortality related to each disease, particularly using Cox regression methodology. We discuss how the multiple-cause, single-cause, and "any-mention" approaches compare in this regard. A simulation study and an application to a study of socioeconomic inequalities in mortality show the value of the proposed methods for exploiting this precious source of data to gain new insights, especially for certain diseases. See video abstract at, http://links.lww.com/EDE/B84.

Socio-economic factors associated with a healthy diet: results from the E3N study.

OBJECTIVE: To identify individual and contextual socio-economic factors associated with a healthy diet. DESIGN: Dietary data from a large cohort study were used to derive two mutually exclusive dietary patterns through a latent class analysis. Associations between dietary patterns and socio-economic factors were studied with logistic regression. SETTING: E3N, a French prospective cohort study composed of women recruited from a national health insurance plan covering people working in the national education system. SUBJECTS: E3N participants (n 73 031) with dietary and socio-economic data available. RESULTS: The 'Healthy' pattern was characterized by a large consumption of fruits and vegetables and the 'Less Healthy' pattern by a large consumption of pizza and processed meat. When all socio-economic factors were analysed together, all of the individual factors considered were associated with a healthy diet (e.g. women with three or more children were less likely to follow a healthy diet v. women with no children, OR (95 % CI): 0·70 (0·66, 0·75)) while the contextual factors associated with a healthy diet included the size of the agglomeration of residence and the area of birth and residence (e.g. women living in the West of France were less likely to follow a healthy diet v. those living in the South of France: 0·78 (0·72, 0·83)). CONCLUSIONS: We demonstrated that individual and contextual factors are both associated with diet. Rather than focusing only on individual factors, we recommend future studies or public health and nutritional strategies on diet to consider both types of factors.

Associations of cause-specific mortality with area level deprivation and travel time to health care in France from 1990 to 2007, a multilevel analysis.

BACKGROUND: It is now widely accepted that social and physical environment participate in shaping health. While mortality is used to guide public health policies and is considered as a synthetic measure of population health, few studies deals with the contextual features potentially associated with mortality in a representative sample of an entire country. This paper investigates the possible role of area deprivation (FDep99) and travel time to health care on French cause-specific mortality in a proper multilevel setting. METHODS: The study population was a 1% sample representative of the French population aged from 30 to 79 years in 1990 and followed up until 2007. A frailty Cox model was used to measure individual, contextual effects and spatial variances for several causes of death. The chosen contextual scale was the Zone d'Emploi of 1994 (348 units) which delimits the daily commute of people. The geographical accessibility to health care score was constructed with principal component analysis, using 40 variables of hospital specialties and health practitioners' travel time. RESULTS: The outcomes highlight a positive and significant association between area deprivation and mortality for all causes (HR = 1.24), cancers, cerebrovascular diseases, ischemic heart diseases, and preventable and amenable diseases (HR from 1.14 to 1.29). These contextual associations exhibit no substantial differences by sex except for premature ischemic heart diseases mortality which was much greater in women. Unexpectedly, mortality decreased as the time to reach health care resources increased. Only geographical disparities in cerebrovascular and ischemic heart diseases mortality were explained by compositional and contextual effects. DISCUSSION: The findings suggest the presence of confounding factors in the association between mortality and travel time to health care, possibly owing to population density and health-selected migration. Although the spatial scale considered to define the context of residence was relatively large, the associations with area deprivation were strong in comparison to the existing literature and significant for almost all the causes of deaths investigated. CONCLUSION: The broad spectrum of diseases associated with area deprivation and individual education support the idea of a need for a global health policy targeting both individual and territories to reduce social and socio-spatial inequalities.

Ability of ecological deprivation indices to measure social inequalities in a French cohort.

BACKGROUND: Despite the increasing interest in place effect to explain health inequalities, there is currently no consensus on which kind of area-based socioeconomic measures researchers should use to assess neighborhood socioeconomic position (SEP). The study aimed to evaluate the reliability of different area-based deprivation indices (DIs) in capturing socioeconomic residential conditions of French elderly women cohort. METHODS: We assessed area-based SEP using 3 DIs: Townsend Index, French European Deprivation Index (FEDI) and French Deprivation index (FDep), among women from E3N (Etude épidémiologique auprès des femmes de la Mutuelle Générale de l'Education Nationale). DIs were derived from the 2009 French census at IRIS level (smallest geographical units in France). Educational level was used to evaluate individual-SEP. To evaluate external validity of the 3 DIs, associations between two well-established socially patterned outcomes among French elderly women (smoking and overweight) and SEP, were compared. Odd ratios were computed with generalized estimating equations to control for clustering effects from participants within the same IRIS. RESULTS: The analysis was performed among 63,888 women (aged 64, 47% ever smokers and 30% overweight). Substantial agreement was observed between the two French DIs (Kappa coefficient = 0.61) and between Townsend and FEDI (0.74) and fair agreement between Townsend and FDep (0.21). As expected among French elderly women, those with lower educational level were significantly less prone to be ever smoker (Low vs. High; OR [95% CI] = 0.43 [0.40-0.46]) and more prone to being overweight (1.89 [1.77-2.01]) than women higher educated. FDep showed expected associations at area-level for both smoking (most deprived vs. least deprived quintile; 0.77 [0.73-0.81]) and overweight (1.52 [1.44-1.62]). For FEDI opposite associations with smoking (1.13 [1.07-1.19]) and expected association with overweight (1.20 [1.13-1.28]) were observed. Townsend showed opposite associations to those expected for both smoking and overweight (1.51 [1.43-1.59]; 0.93 [0.88-0.99], respectively). CONCLUSION: FDep seemed reliable to capture socioeconomic residential conditions of the E3N women, more educated in average than general French population. Results varied strongly according to the DI with unexpected results for some of them, which suggested the importance to test external validity before studying social disparities in health in specific populations.

Hospital quality measures: are process indicators associated with hospital standardized mortality ratios in French acute care hospitals?

BACKGROUND: Results of associations between process and mortality indicators, both used for the external assessment of hospital care quality or public reporting, differ strongly across studies. However, most of those studies were conducted in North America or United Kingdom. Providing new evidence based on French data could fuel the international debate on quality of care indicators and help inform French policy-makers. The objective of our study was to explore whether optimal care delivery in French hospitals as assessed by their Hospital Process Indicators (HPIs) is associated with low Hospital Standardized Mortality Ratios (HSMRs). METHODS: The French National Authority for Health (HAS) routinely collects for each hospital located in France, a set of mandatory HPIs. Five HPIs were selected among the process indicators collected by the HAS in 2009. They were measured using random samples of 60 to 80 medical records from inpatients admitted between January 1st, 2009 and December 31, 2009 in respect with some selection criteria. HSMRs were estimated at 30, 60 and 90 days post-admission (dpa) using administrative health data extracted from the national health insurance information system (SNIIR-AM) which covers 77% of the French population. Associations between HPIs and HSMRs were assessed by Poisson regression models corrected for measurement errors with a simulation-extrapolation (SIMEX) method. RESULTS: Most associations studied were not statistically significant. Only two process indicators were found associated with HSMRs. Completeness and quality of anesthetic records was negatively associated with 30 dpa HSMR (0.72 [0.52-0.99]). Early detection of nutritional disorders was negatively associated with all HSMRs: 30 dpa HSMR (0.71 [0.54-0.95]), 60 dpa HSMR (0.51 [0.39-0.67]) and 90 dpa HSMR (0.52 [0.40-0.68]). CONCLUSION: In absence of gold standard of quality of care measurement, the limited number of associations suggested to drive in-depth improvements in order to better determine associations between process and mortality indicators. A smart utilization of both process and outcomes indicators is mandatory to capture aspects of the hospital quality of care complexity.

Comparison of the temperature-mortality relationship in foreign born and native born died in France between 2000 and 2009.

The daily temperature-mortality relationship is typically U shaped. The temperature of minimum mortality (MMT) has been shown to vary in space (higher at lower latitudes) and time (higher in recent periods). This indicates human populations adapt to their local environment. The pace of this adaptation is unknown. The objective of this study was to investigate the differences in the temperature-mortality relationship in continental France between foreign born and natives. Source data were the 5,273,005 death certificates of individuals living in continental France between 2000 and 2009 at the time of their death. Foreign-born deaths (N = 573,384) were matched 1:1 with a native-born death based on date of birth, sex, and place of death. Four regions of France based on similarity of their temperatures profiles were defined by unsupervised clustering. For each of these four regions, variations of all causes mortality with season and temperature of the day were modeled and compared between four groups of foreign born (Maghreb, sub-Saharan Africa, Southern Europe, and Northern Europe) and matched groups of natives. Overall, the temperature-mortality relationship and MMT were close in foreign born and in native born: The only difference between foreign born and native born concerned the attributable mortality to cold, found in several instances larger in foreign born. There are little differences in France between the temperature-mortality relationships in native born and in foreign born. This supports the hypothesis of an adaptation of these populations to the temperature patterns of continental France, which for those born in Africa differ markedly from the climatic pattern of their birth country.

Quantifying cause-related mortality by weighting multiple causes of death.

OBJECTIVE: To investigate a new approach to calculating cause-related standardized mortality rates that involves assigning weights to each cause of death reported on death certificates. METHODS: We derived cause-related standardized mortality rates from death certificate data for France in 2010 using: (i) the classic method, which considered only the underlying cause of death; and (ii) three novel multiple-cause-of-death weighting methods, which assigned weights to multiple causes of death mentioned on death certificates: the first two multiple-cause-of-death methods assigned non-zero weights to all causes mentioned and the third assigned non-zero weights to only the underlying cause and other contributing causes that were not part of the main morbid process. As the sum of the weights for each death certificate was 1, each death had an equal influence on mortality estimates and the total number of deaths was unchanged. Mortality rates derived using the different methods were compared. FINDINGS: On average, 3.4 causes per death were listed on each certificate. The standardized mortality rate calculated using the third multiple-cause-of-death weighting method was more than 20% higher than that calculated using the classic method for five disease categories: skin diseases, mental disorders, endocrine and nutritional diseases, blood diseases and genitourinary diseases. Moreover, this method highlighted the mortality burden associated with certain diseases in specific age groups. CONCLUSION: A multiple-cause-of-death weighting approach to calculating cause-related standardized mortality rates from death certificate data identified conditions that contributed more to mortality than indicated by the classic method. This new approach holds promise for identifying underrecognized contributors to mortality.

All-cause and cause-specific mortality of different migrant populations in Europe.

This study aimed to examine differences in all-cause mortality and main causes of death across different migrant and local-born populations living in six European countries. We used data from population and mortality registers from Denmark, England & Wales, France, Netherlands, Scotland, and Spain. We calculated age-standardized mortality rates for men and women aged 0-69 years. Country-specific data were pooled to assess weighted mortality rate ratios (MRRs) using Poisson regression. Analyses were stratified by age group, country of destination, and main cause of death. In six countries combined, all-cause mortality was lower for men and women from East Asia (MRRs 0.66; 95 % confidence interval 0.62-0.71 and 0.76; 0.69-0.82, respectively), and Other Latin America (0.44; 0.42-0.46 and 0.56; 0.54-0.59, respectively) than local-born populations. Mortality rates were similar for those from Turkey. All-cause mortality was higher in men and women from North Africa (1.09; 1.08-1.11 and 1.19; 1.17-1.22, respectively) and Eastern Europe (1.30; 1.27-1.33 and 1.05; 1.01-1.08, respectively), and women from Sub-Saharan Africa (1.34; 1.30-1.38). The pattern differed by age group and country of destination. Most migrants had higher mortality due to infectious diseases and homicide while cancer mortality and suicide were lower. CVD mortality differed by migrant population. To conclude, mortality patterns varied across migrant populations in European countries. Future research should focus both on migrant populations with favourable and less favourable mortality pattern, in order to understand this heterogeneity and to drive policy at the European level.

Mortality among homeless people in France, 2008-10.

BACKGROUND: Studies in various countries have shown that homeless people have high mortality levels. The aims of this study concerning the French population were to investigate mortality among the homeless and to study their causes of death in comparison to those of the general population. METHODS: A representative sample of 1145 homeless deaths registered by an association was matched to the national database of medical causes of death using common descriptive variables. Log-binomial regression was used to compare mortality among the homeless to that of the general population. Multiple imputation was used to manage missing causes of deaths. RESULTS: Out of the 1145 registered homeless deaths, 693 were matched to the causes of death database. Homeless deaths were young (average age: 49). Overall, homeless deaths were slightly more frequent during winter. Among all deaths, the probability of being homeless was higher when dying from hypothermia (RR = 6.4), alcohol-related deaths (RR = 1.7), mental disorders, diseases of the digestive and circulatory systems, and undetermined causes (RR from 1.5 to 3.7). CONCLUSION: The homeless died at 49 years old on average compared with 77 in the general population in 2008-10. The health of homeless people should be considered not only in winter periods or in terms of alcohol- or cold-related conditions. This study also highlights the need for more precise data to estimate the mortality risks of the homeless in France.

Relative index of inequality and slope index of inequality: a structured regression framework for estimation.

BACKGROUND: The relative index of inequality and the slope index of inequality are the two major indices used in epidemiologic studies for the measurement of socioeconomic inequalities in health. Yet the current definitions of these indices are not adapted to their main purpose, which is to provide summary measures of the linear association between socioeconomic status and health in a way that enables valid between-population comparisons. The lack of appropriate definitions has dissuaded the application of suitable regression methods for estimating the slope index of inequality. METHODS: We suggest formally defining the relative and slope indices of inequality as so-called least false parameters, or more precisely, as the parameters that provide the best approximation of the relation between socioeconomic status and the health outcome by log-linear and linear models, respectively. From this standpoint, we establish a structured regression framework for inference on these indices. Guidelines for implementation of the methods, including R and SAS codes, are provided. RESULTS: The new definitions yield appropriate summary measures of the linear association across the entire socioeconomic scale, suitable for comparative studies in epidemiology. Our regression-based approach for estimation of the slope index of inequality contributes to an advancement of the current methodology, which mainly consists of a heuristic formula relying on restrictive assumptions. A study of the educational inequalities in all-cause and cause-specific mortality in France is used for illustration. CONCLUSION: The proposed definitions and methods should guide the use and estimation of these indices in future studies.

Hospital comparisons based on mortality: revisiting the choice of postadmission timeframe and evaluating the contribution of cause-of-death data, France, 2009.

BACKGROUND: In-hospital mortality is widely used to judge the quality of hospital care, but is biased by discharge patterns. Fixed-timeframe indicators have thus been recommended. However, the 30-day postadmission indicator may underestimate hospital-wide mortality, as patients dying in hospital >30 days after admission are considered as survivors. OBJECTIVES: To identify the most relevant timeframes and to assess the contribution of cause-of-death data. METHODS: The 2009 French hospital discharge database was linked to vital status records and to the causes of death register for 11.5 million hospital stays by beneficiaries of French general health insurance. Correlations and agreements between the 30-day hospital standardized mortality ratio (HSMR) and the in-hospital, 60-, 90-, 180-, and 365-day postadmission HSMRs were estimated. RESULTS: A total of 7.8%, 1.5%, and 0.5% of patients who died during their hospital stay were considered as survivors by the 30-, 60-, and 90-day HSMRs, respectively. The 30-day HSMR correlated strongly with the 60-day HSMR (Pearson coefficient=0.92), and their agreement on outlier status was excellent (κ coefficient=0.80). The association remained substantial at 90 days, but weakened at 180 days and even more so at 365 days. Regardless of the timeframe, exclusion of deaths likely due to independent causes barely modified the indicators. CONCLUSIONS: This nationwide study shows that 60- and 90-day HSMRs encompass in-hospital deaths better than the 30-day HSMR, while capturing the same interhospital variations. They should thus be preferred. The contribution of cause-of-death data to hospital-wide indicators seems negligible.