Metrological performances of the global chronic morbidity indicator of the Minimum European Health Module and implications for chronic disease prevalence and socioeconomic gradient estimations.

BACKGROUND: Although the global chronic morbidity indicator (GCMI) of the Minimum European Health Module (MEHM) was not specifically designed to monitor chronic disease in the population, it is increasingly used for this purpose in Europe and elsewhere. However, its metrological characteristics have seldom been examined, with various sensitivity issues being raised. The present study investigated the metrological performances of the GCMI and analyzed its implications in terms of prevalence and demographic and socioeconomic gradients of chronic conditions in the population. METHODS: We used data from two large French nationwide representative surveys with cross-sectional and longitudinal data conducted between 2010 and 2021. The surveys used MEHM and collected data on numerous chronic conditions and socioeconomic indicators. Criterion and predictive validity of the GCMI regarding chronic conditions and the resultant socioeconomic gradients were compared with indicators based on reports of individual chronic conditions. RESULTS: GCMI sensitivity to capture chronic conditions varied from <20 to 80% depending on the chronic condition. Number of chronic conditions, gender, age and education were also associated with GCMI endorsement. However, the GCMI was predictive of mortality and activity limitations independently of individual conditions. CONCLUSION: The varying lack of sensitivity depending on the chronic condition and the respondent's sociodemographic status may bias estimates of demographic and socioeconomic gradients compared with indicators based on reports of individual chronic conditions. Differences between GCMI and list-based approaches should be more cautiously considered when monitoring chronic conditions in the population. These approaches should be viewed as complementary rather than contradictory or interchangeable.

Assessing European national health information systems in peer review format: lessons learnt.

BACKGROUND: Systematic assessments of a country's health information system (HIS) help identify strengths and weaknesses and may stimulate actions for improvement. They represent a capacity-building process for the country assessed as well as for the assessor. The joint action on HISs (InfAct) developed a peer-to-peer assessment methodology adapting an established WHO support tool. The aim of this study is to identify lessons learnt and the added value of the InfAct peer assessment for the assessors. METHODS: A qualitative evaluation of the peer HIS assessment was performed based on 12 semi-structured interviews: nine interviews were carried out with assessors from nine participating countries, and three with an observer (present during assessments). The interviews were carried out between May 2019 and January 2020. Interviews were analysed using qualitative content analysis. RESULTS: The interviews revealed the experiences of the assessors mainly occurred in five areas: assessors strengthened their understanding of what a population-based HIS is; they strengthened their understanding of how a HIS operates in different countries; they learnt how to carry out a HIS assessment; they strengthened their organization, communication, negotiation and reporting skills and they strengthened the networks in health information within and between countries. CONCLUSION: Since the assessors are key personnel in their respective national health systems, the impact of the assessment is not limited to the assessor alone but may extend to stakeholders in their country. The deployment of the InfAct HIS peer assessment, anchored in systematic HIS capacity building across European countries, is recommended.

Evaluating methodological approaches to assess the severity of infection with SARS-CoV-2 variants: scoping review and applications on Belgian COVID-19 data.

BACKGROUND: Differences in the genetic material of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants may result in altered virulence characteristics. Assessing the disease severity caused by newly emerging variants is essential to estimate their impact on public health. However, causally inferring the intrinsic severity of infection with variants using observational data is a challenging process on which guidance is still limited. We describe potential limitations and biases that researchers are confronted with and evaluate different methodological approaches to study the severity of infection with SARS-CoV-2 variants. METHODS: We reviewed the literature to identify limitations and potential biases in methods used to study the severity of infection with a particular variant. The impact of different methodological choices is illustrated by using real-world data of Belgian hospitalized COVID-19 patients. RESULTS: We observed different ways of defining coronavirus disease 2019 (COVID-19) disease severity (e.g., admission to the hospital or intensive care unit versus the occurrence of severe complications or death) and exposure to a variant (e.g., linkage of the sequencing or genotyping result with the patient data through a unique identifier versus categorization of patients based on time periods). Different potential selection biases (e.g., overcontrol bias, endogenous selection bias, sample truncation bias) and factors fluctuating over time (e.g., medical expertise and therapeutic strategies, vaccination coverage and natural immunity, pressure on the healthcare system, affected population groups) according to the successive waves of COVID-19, dominated by different variants, were identified. Using data of Belgian hospitalized COVID-19 patients, we were able to document (i) the robustness of the analyses when using different variant exposure ascertainment methods, (ii) indications of the presence of selection bias and (iii) how important confounding variables are fluctuating over time. CONCLUSIONS: When estimating the unbiased marginal effect of SARS-CoV-2 variants on the severity of infection, different strategies can be used and different assumptions can be made, potentially leading to different conclusions. We propose four best practices to identify and reduce potential bias introduced by the study design, the data analysis approach, and the features of the underlying surveillance strategies and data infrastructure.

Non-specific symptoms and post-treatment Lyme disease syndrome in patients with Lyme borreliosis: a prospective cohort study in Belgium (2016-2020).

BACKGROUND: Patients with Lyme borreliosis (LB) may report persisting non-specific symptoms such as fatigue, widespread musculoskeletal pain or cognitive difficulties. When present for more than 6 months and causing a reduction in daily activities, this is often referred to as post-treatment Lyme disease syndrome (PTLDS). This study aimed to compare the occurrence of symptoms between LB patients and controls, to estimate the proportion of LB patients developing PTLDS and to identify risk factors. METHODS: A prospective cohort study was set up including three subpopulations: patients with an erythema migrans (EM) (i) or disseminated/late LB (ii) and a non-LB control group (iii). At 6- and 12-months follow-up, the occurrence of several symptoms, including six symptoms used to define PTLDS, i.e. muscle pain, joint pain, fatigue, memory problems, difficulties concentrating and problems finding words, and impact on daily activities, was compared between LB patients and controls. Finally, the proportion of LB patients developing PTLDS as defined by the Infectious Disease Society of America was estimated, including a time frame for symptoms to be present. RESULTS: Although the risk of presenting PTLDS-related symptoms was significantly higher in EM patients (n = 120) compared to controls (n = 128) at 6 months follow-up, the risk of presenting at least one of these symptoms combined with impact on daily activities was not significantly higher in EM patients, at either 6- or 12-months follow-up. A significant association was found between disseminated/late LB (n = 15) and the occurrence of any PTLDS-symptom with an impact on daily activities at both time points. The proportion of patients with PTLDS was estimated at 5.9% (95% CI 2.7-12.9) in EM patients and 20.9% (95% CI 6.8-64.4) in patients with disseminated/late LB (RR = 3.53, 95% CI 0.98-12.68, p = 0.053). No significant risk factors were identified, which may be explained by small sample sizes. CONCLUSIONS: In our study, PTLDS was present in both LB cohorts, yet with a higher percentage in disseminated/late LB patients. Additional research is needed into risk factors for and causes of this syndrome. In addition, development and validation of standardized methods to assess the PTLDS case definition, easily applicable in practice, is of great importance.

Belgian population norms for the EQ-5D-5L, 2018.

PURPOSE: Health-related quality of life outcomes are increasingly used to monitor population health and health inequalities and to assess the (cost-) effectiveness of health interventions. The EQ-5D-5L has been included in the Belgian Health Interview Survey, providing a new source of population-based self-perceived health status information. This study aims to estimate Belgian population norms for the EQ-5D-5L by sex, age, and region and to analyze its association with educational attainment. METHODS: The BHIS 2018 provided EQ-5D-5L data for a nationally representative sample of the Belgian population. The dimension scores and index values were analyzed using logistic and linear regressions, respectively, accounting for the survey design. RESULTS: More than half of respondents reported problems of pain/discomfort, while over a quarter reported problems of anxiety/depression. The average index value was 0.84. Women reported more problems on all dimensions, but particularly on anxiety/depression and pain/discomfort, resulting in significantly lower index values. Problems with mobility, self-care, and usual activities showed a sharp increase after the age of 80 years. Consequently, index values decreased significantly by age. Lower education was associated with a higher prevalence of problems for all dimensions except anxiety/depression and with a significantly lower index value. CONCLUSION: This paper presents the first nationally representative Belgian population norms using the EQ-5D-5L. Inclusion of the EQ-5D in future surveys will allow monitoring over time of self-reported health, disease burden, and health inequalities.

Predictors of nursing home admission in the older population in Belgium: a longitudinal follow-up of health interview survey participants.

BACKGROUND: This study examines predictors of nursing home admission (NHA) in Belgium in order to contribute to a better planning of the future demand for nursing home (NH) services and health care resources. METHODS: Data derived from the Belgian 2013 health interview survey were linked at individual level with health insurance data (2012 tot 2018). Only community dwelling participants, aged ≥65 years at the time of the survey were included in this study (n = 1930). Participants were followed until NHA, death or end of study period, i.e., December 31, 2018. The risk of NHA was calculated using a competing risk analysis. RESULTS: Over the follow-up period (median 5.29 years), 226 individuals were admitted to a NH and 268 died without admission to a NH. The overall cumulative risk of NHA was 1.4, 5.7 and 13.1% at respectively 1 year, 3 years and end of follow-up period. After multivariable adjustment, higher age, low educational attainment, living alone and use of home care services were significantly associated with a higher risk of NHA. A number of need factors (e.g., history of falls, suffering from urinary incontinence, depression or Alzheimer's disease) were also significantly associated with a higher risk of NHA. On the contrary, being female, having multimorbidity and increased contacts with health care providers were significantly associated with a decreased risk of NHA. Perceived health and limitations were both significant determinants of NHA, but perceived health was an effect modifier on limitations and vice versa. CONCLUSIONS: Our findings pinpoint important predictors of NHA in older adults, and offer possibilities of prevention to avoid or delay NHA for this population. Practical implications include prevention of falls, management of urinary incontinence at home and appropriate and timely management of limitations, depression and Alzheimer's disease. Focus should also be on people living alone to provide more timely contacts with health care providers. Further investigation of predictors of NHA should include contextual factors such as the availability of nursing-home beds, hospital beds, physicians and waiting lists for NHA.

Lyme borreliosis in Belgium: a cost-of-illness analysis.

BACKGROUND: Lyme borreliosis (LB) is the most common tick-borne disease in Europe and North America, yet its economic burden remains largely unknown. This study aimed to estimate the economic cost associated with the different clinical manifestations of LB in Belgium. METHODS: An incidence approach and societal perspective were used to estimate the total cost-of-illness for LB in Belgium. Costs were calculated for patients with erythema migrans (EM) or disseminated/late LB, including patients who developed post-treatment Lyme disease syndrome (PTLDS). Direct medical, direct non-medical (transportation & paid help) and indirect non-medical costs (productivity losses) were included in the analysis. Ambulatory cost data were collected through a prospective cohort study from June 2016 to March 2020, in which patients with LB were followed up 6 to 12 months after diagnosis. Hospitalization costs were retrieved from the Minimal Clinical Data registry, a mandatory registry for all Belgian hospitals, linked to the Minimal Financial Data registry. Costs were expressed in 2019 euros. RESULTS: The total annual cost associated with clinical manifestations of LB in Belgium was estimated at €5.59 million (95% UI 3.82-7.98). Of these, €3.44 million (95% UI 2.05-5.48) or 62% was related to disseminated/late LB diagnoses and €2.15 million (95% UI 1.30-3.26) to EM. In general, direct medical costs and productivity losses accounted for 49.8% and 46.4% of the total costs, respectively, while direct non-medical costs accounted for only 3.8%. The estimated mean costs were €193 per EM patient and €5,148 per disseminated/late LB patient. While patients with PTLDS seemed to have somewhat higher costs compared to patients without PTLDS, the number of patients was too small to have representative estimates. CONCLUSIONS: We estimate the total annual direct medical costs, direct non-medical and indirect non-medical costs associated with LB to exceed €5.5 million per year, almost evenly distributed between EM (40%) and disseminated/late LB (60%). EM costs 26 times less per patient but occurs also 16 times more frequently than disseminated/late LB. The cost burden remains limited by comparison to other infectious diseases due to the relative lower incidence.

Capacity building in European health information systems: the InfAct peer assessment methodology.

BACKGROUND: A Health Information System (HIS) assessment is an evaluation of the functioning of the main elements that compose a national HIS. Assessors from nine countries performed peer assessments of each other's national HIS in the Joint Action on Health Information (InfAct). The aim of this study is to evaluate the advantages and disadvantages of the InfAct peer assessment methodology as well as the different steps involved in this assessment process. METHODS: Each peer assessment included a preparatory desk report, a country visit with semi-structured interviews with local stakeholders, a final report and a follow-up stakeholder meeting. A qualitative content analysis of the peer HIS assessment was performed based on 12 semi-structured interviews. RESULTS: The main advantage of the assessments is its informal atmosphere, high degree of objectiveness and its networking opportunities. Disadvantages are its informal request format and setting for recommendation uptake. The peer assessment helped the assessors to broaden their understanding of the assessed and their own HISs, to gain knowledge on how to carry out an HIS assessment and to practice their organization, communication, reporting and negotiation skills. All steps of the HIS assessment are essential and each contributes to the enriching experience of the participants. CONCLUSION: The InfAct peer HIS assessment methodology strengthened capacity in national HISs by building up the knowledge and expertise in participating countries and as such addressed health information inequalities. This study confirms the value and relatively easy to implement methodology, and therefore recommends its wide and more systematic application across Europe.

COVID-19 mortality, excess mortality, deaths per million and infection fatality ratio, Belgium, 9 March 2020 to 28 June 2020.

BackgroundCOVID-19 mortality, excess mortality, deaths per million population (DPM), infection fatality ratio (IFR) and case fatality ratio (CFR) are reported and compared for many countries globally. These measures may appear objective, however, they should be interpreted with caution.AimWe examined reported COVID-19-related mortality in Belgium from 9 March 2020 to 28 June 2020, placing it against the background of excess mortality and compared the DPM and IFR between countries and within subgroups.MethodsThe relation between COVID-19-related mortality and excess mortality was evaluated by comparing COVID-19 mortality and the difference between observed and weekly average predictions of all-cause mortality. DPM were evaluated using demographic data of the Belgian population. The number of infections was estimated by a stochastic compartmental model. The IFR was estimated using a delay distribution between infection and death.ResultsIn the study period, 9,621 COVID-19-related deaths were reported, which is close to the excess mortality estimated using weekly averages (8,985 deaths). This translates to 837 DPM and an IFR of 1.5% in the general population. Both DPM and IFR increase with age and are substantially larger in the nursing home population.DiscussionDuring the first pandemic wave, Belgium had no discrepancy between COVID-19-related mortality and excess mortality. In light of this close agreement, it is useful to consider the DPM and IFR, which are both age, sex, and nursing home population-dependent. Comparison of COVID-19 mortality between countries should rather be based on excess mortality than on COVID-19-related mortality.

A systematic review and meta-analysis of host genetic factors associated with influenza severity.

BACKGROUND: The severity of influenza disease can range from mild symptoms to severe respiratory failure and can partly be explained by host genetic factors that predisposes the host to severe influenza. Here, we aimed to summarize the current state of evidence that host genetic variants play a role in the susceptibility to severe influenza infection by conducting a systematic review and performing a meta-analysis for all markers with at least three or more data entries. RESULTS: A total of 34 primary human genetic association studies were identified that investigated a total of 20 different genes. The only significant pooled ORs were retrieved for the rs12252 polymorphism: an overall OR of 1.52 (95% CI [1.06-2.17]) for the rs12252-C allele compared to the rs12252-T allele. A stratified analysis by ethnicity revealed opposite effects in different populations. CONCLUSION: With exception for the rs12252 polymorphism, we could not identify specific genetic polymorphisms to be associated with severe influenza infection in a pooled meta-analysis. This advocates for the use of large, hypothesis-free, genome-wide association studies that account for the polygenic nature and the interactions with other host, pathogen and environmental factors.

Evaluation of the added value of viral genomic information for predicting severity of influenza infection.

BACKGROUND: The severity of an influenza infection is influenced by both host and viral characteristics. This study aims to assess the relevance of viral genomic data for the prediction of severe influenza A(H3N2) infections among patients hospitalized for severe acute respiratory infection (SARI), in view of risk assessment and patient management. METHODS: 160 A(H3N2) influenza positive samples from the 2016-2017 season originating from the Belgian SARI surveillance were selected for whole genome sequencing. Predictor variables for severity were selected using a penalized elastic net logistic regression model from a combined host and genomic dataset, including patient information and nucleotide mutations identified in the viral genome. The goodness-of-fit of the model combining host and genomic data was compared using a likelihood-ratio test with the model including host data only. Internal validation of model discrimination was conducted by calculating the optimism-adjusted area under the Receiver Operating Characteristic curve (AUC) for both models. RESULTS: The model including viral mutations in addition to the host characteristics had an improved fit ([Formula: see text]=12.03, df = 3, p = 0.007). The optimism-adjusted AUC increased from 0.671 to 0.732. CONCLUSIONS: Adding genomic data (selected season-specific mutations in the viral genome) to the model containing host characteristics improved the prediction of severe influenza infection among hospitalized SARI patients, thereby offering the potential for translation into a prospective strategy to perform early season risk assessment or to guide individual patient management.

Investigating the drivers of the spatio-temporal heterogeneity in COVID-19 hospital incidence-Belgium as a study case.

BACKGROUND: The COVID-19 pandemic is affecting nations globally, but with an impact exhibiting significant spatial and temporal variation at the sub-national level. Identifying and disentangling the drivers of resulting hospitalisation incidence at the local scale is key to predict, mitigate and manage epidemic surges, but also to develop targeted measures. However, this type of analysis is often not possible because of the lack of spatially-explicit health data and spatial uncertainties associated with infection. METHODS: To overcome these limitations, we propose an analytical framework to investigate potential drivers of the spatio-temporal heterogeneity in COVID-19 hospitalisation incidence when data are only available at the hospital level. Specifically, the approach is based on the delimitation of hospital catchment areas, which allows analysing associations between hospitalisation incidence and spatial or temporal covariates. We illustrate and apply our analytical framework to Belgium, a country heavily impacted by two COVID-19 epidemic waves in 2020, both in terms of mortality and hospitalisation incidence. RESULTS: Our spatial analyses reveal an association between the hospitalisation incidence and the local density of nursing home residents, which confirms the important impact of COVID-19 in elderly communities of Belgium. Our temporal analyses further indicate a pronounced seasonality in hospitalisation incidence associated with the seasonality of weather variables. Taking advantage of these associations, we discuss the feasibility of predictive models based on machine learning to predict future hospitalisation incidence. CONCLUSION: Our reproducible analytical workflow allows performing spatially-explicit analyses of data aggregated at the hospital level and can be used to explore potential drivers and dynamic of COVID-19 hospitalisation incidence at regional or national scales.

Developing a tool to monitor knowledge translation in the health system: results from an international Delphi study.

BACKGROUND: It is generally accepted that evidence-informed decision making contributes to better health system performance and health outcomes, yet we are lacking benchmarks to monitor the impact of national health information systems (HIS) in policy and practice. Hence in this study, we have aimed to identify criteria for monitoring Knowledge Translation (KT) capacity within countries. METHODS: We conducted a web-based Delphi with over 120 public health professionals from 45 countries to reach agreement on criteria to monitor KT at the level of national HIS. Public health professionals participated in three survey rounds, in which they ranked 85 preselected criteria and could suggest additional criteria. RESULTS: Experts working in national (public) health agencies and statistical offices, as well as in health policy and care agreed on 29 criteria which constitute the Health Information (HI)-Impact Index. The criteria cover four essential domains of evaluation: the production of high-quality evidence, broad access and dissemination, stakeholder engagement and knowledge integration across sectors and in civil society. The HI-Impact Index was pretested by officials working in ministries of health and public health agencies in eight countries; they found the tool acceptable and user-friendly. CONCLUSIONS: The HI-Impact Index provides benchmarks to monitor KT so that countries can assess whether high-quality evidence can be easily accessed and used by the relevant stakeholders in health policy and practice, by civil society and across sectors. Next steps include further refining the procedure for conducting the assessment in routine, and sharing experiences from HIS evaluations using the HI-Impact Index.

A Novel Approach to Optimize Vitamin D Intake in Belgium through Fortification Based on Representative Food Consumption Data.

BACKGROUND: Food fortification is a promising means to improve vitamin D intake of a population. Careful selection of food vehicles is needed to ensure that nearly all individuals within the population benefit from the fortification program. OBJECTIVES: The aim of the study was to develop and apply a model that simultaneously selects the optimal combination of food vehicles and defines the optimal fortification level that adequately increases vitamin D intake in the population without compromising safety. METHODS: Food consumption data from the Belgian Food Consumption Survey 2014 (n = 3200; age 3-64 y) were used. The optimization model included 63 combinations of 6 potential vehicles for food fortification, namely "bread," "breakfast cereals," "fats and oils," "fruit juices," "milk and milk beverages," and "yogurt and cream cheese." The optimization procedure was designed to minimize inadequate or excessive vitamin D intake in each of the food combinations. This allowed the relative ranking of the different combinations according to their fortification utility. The estimated average requirement and upper intake level were used as thresholds. An age-specific and population-based approach enabled the sensitivity of the population subgroups to adverse health effects to be taken into account. Feasibility, technical aspects, and healthiness of the food vehicles were used to select the optimal combination. RESULTS: Multiple combinations of food vehicles significantly reduced the prevalence of inadequate vitamin D intake within the Belgian population (from 92-96% to <2%). Taking other aforementioned criteria into account, the fortification of "milk and milk beverages" and "bread" with 6.9 µg vitamin D/100 kcal was proposed as an optimal fortification scenario. CONCLUSIONS: The optimization model allows identification of an effective fortification scenario to improve vitamin D intake within the Belgian population based on acceptable risks of inadequate and excessive intake. The model can be extended to other micronutrients and other populations.

The genetic structure of the Belgian population.

BACKGROUND: National and international efforts like the 1000 Genomes Project are leading to increasing insights in the genetic structure of populations worldwide. Variation between different populations necessitates access to population-based genetic reference datasets. These data, which are important not only in clinical settings but also to potentiate future transitions towards a more personalized public health approach, are currently not available for the Belgian population. RESULTS: To obtain a representative genetic dataset of the Belgian population, participants in the 2013 National Health Interview Survey (NHIS) were invited to donate saliva samples for DNA analysis. DNA was isolated and single nucleotide polymorphisms (SNPs) were determined using a genome-wide SNP array of around 300,000 sites, resulting in a high-quality dataset of 189 samples that was used for further analysis. A principal component analysis demonstrated the typical European genetic constitution of the Belgian population, as compared to other continents. Within Europe, the Belgian population could be clearly distinguished from other European populations. Furthermore, obvious signs from recent migration were found, mainly from Southern Europe and Africa, corresponding with migration trends from the past decades. Within Belgium, a small north-west to south-east gradient in genetic variability was noted, with differences between Flanders and Wallonia. CONCLUSIONS: This is the first study on the genetic structure of the Belgian population and its regional variation. The Belgian genetic structure mirrors its geographic location in Europe with regional differences and clear signs of recent migration.

Socioeconomic factors contributing to under-five mortality in sub-Saharan Africa: a decomposition analysis.

BACKGROUND: In sub-Saharan Africa, socioeconomic factors such as place of residence, mother's educational level, or household wealth, are strongly associated with risk factors of under-five mortality (U5M) such as health behavior or exposure to diseases and injuries. The aim of the study was to assess the relative contribution of four known socioeconomic factors to the variability in U5M in sub-Saharan countries. METHODS: The study was based on birth histories from the Demographic and Health Surveys conducted in 32 sub-Saharan countries in 2010-2016. The relative contribution of sex of the child, place of residence, mother's educational level, and household wealth to the variability in U5M was assessed using a regression-based decomposition of a Gini-type index. RESULTS: The Gini index - measuring the variability in U5M related to the four socioeconomic factors - varied from 0.006 (95%CI: 0.001-0.010) in Liberia 2013 to 0.034 (95%CI: 0.029-0.039) in Côte d'Ivoire 2011/12. The main contributors to the Gini index (with a relative contribution higher than 25%) were different across countries: mother's educational level in 13 countries, sex of the child in 12 countries, household wealth in 11 countries, and place of residence in 8 countries (in some countries, more than one main contributor was identified). CONCLUSIONS: Factors related to socioeconomic status exert varied effects on the variability in U5M in sub-Saharan African countries. The findings provide evidence in support of prioritizing intersectoral interventions aiming at improving child survival in all subgroups of a population.

Contribution of chronic conditions to gender disparities in health expectancies in Belgium, 2001, 2004 and 2008.

Background: We aimed to investigate the contribution of chronic conditions to gender differences in disability-free life expectancy (DFLE) and life expectancy with disability (LED) in Belgium in 2001, 2004 and 2008. Methods: Data on disability and chronic conditions from participants of the 2001, 2004 and 2008 Health Interview Surveys in Belgium were used to estimate disability prevalence by cause using the attribution method. Disability prevalence was applied to life tables to estimate DFLE and LED using the Sullivan method. Decomposition techniques were used to assess the contribution of mortality and disability and further of causes of death and disability to gender disparities in DFLE and LED. Results: Higher LE, DFLE and LED were observed for women compared with men in all years studied. A decrease in the gender gap in LE (2001: 5.9; 2004: 5.6; 2008: 5.3) was observed in our cross-sectional approach followed by a decrease in gender differences in DFLE (2001: 1.9; 2004: 1.3; 2008: 0.5) and increase in LED (2001: 4.0; 2004: 4.4; 2008: 4.8). The higher LED in women was attributed to their lower mortality due to lung/larynx/trachea cancer, ischaemic heart diseases, and external causes (2001 and 2004) and higher disability prevalence due to musculoskeletal conditions (2008). Higher DFLE was observed in women owing to their lower mortality from lung/larynx/trachea cancer, ischaemic heart diseases, digestive cancer and chronic respiratory diseases. Conclusion: To promote healthy ageing of populations, priority should be given to reduce the LED disadvantage in women by targeting non-fatal diseases, such as musculoskeletal conditions.

Women's excess unhealthy life years: disentangling the unhealthy life years gap.

BACKGROUND: Compared to men, women live longer but have more years with disability. We assessed the contribution of gender differences in mortality and disability, total and by cause, to women's excess unhealthy life years (ULYs). METHODS: We used mortality data for France 2008 from Eurostat, causes of death from the CépiDc-INSERM-database; and disability and chronic conditions data from the French Disability Health Survey 2008-09. ULYs were calculated by the Sullivan method. The contributions of mortality and disability differences to gender differences in ULY were based on decomposition analyses. RESULTS: Life expectancy of French women aged 50 was 36.3 years of which 19.0 were ULYs; life expectancy of men was 30.4 years of which 14.2 were ULYs. Of the 4.8 excess ULYs in women, 4.0 years were due to lower mortality. Of these 4.0 ULYs, 1.8 ULY originated from women's lower mortality from cancer, 0.8 ULY from heart disease and 0.3 ULY from accidents. The remaining 0.8 excess ULY in women were from higher disability prevalence, including higher disability from musculoskeletal diseases (+1.8 ULY) and anxiety-depression (+0.6 ULY) partly offset by lower disability from heart diseases (-0.8 ULY) and accidents (-0.3 ULY). CONCLUSION: Lower mortality and higher disability prevalence contributed to women's longer life expectancy with disability. Women's higher disability prevalence due to non-fatal disabling conditions was partly offset by lower disability from heart disease and accidents. Conditions differentially impact gender differences in ULY, depending on whether they are mainly life-threatening or disabling. The conclusions confirm the health-survival paradox.

Contribution of chronic conditions to disability in men and women in France.

Background: Women report more disability than men perhaps due to gender differences in the prevalence of diseases and/or in their disabling impact. We compare the contribution of chronic diseases to disability in men and women in France, using a disability survey conducted in both private households and institutions, and we also examine the effect of excluding the institutionalized population. Methods: Data comprised 17 549 individuals age 50+, who participated in the 2008-09 French Disability Health Survey including people living in institutions. Disability was defined by limitations in activities people usually do due to health problems (global activity limitation indicator). Additive regression models were fitted separately by gender to estimate the contribution of conditions to disability taking into account multi-morbidity. Results: Musculoskeletal diseases caused most disability for both men (10.1%, CI: 8.1-12.0) and women (16.0%, CI 13.6-18.2). The second contributor for men was heart diseases (5.7%, CI: 4.5-6.9%), and for women anxiety-depression (4.0, CI 3.1-5.0%) closely followed by heart diseases (3.8%, CI 2.9-4.7%). Women's higher contribution of musculoskeletal diseases reflected their higher prevalence and disabling impact; women's higher contribution of anxiety-depression and lower contributions of heart diseases reflected gender differences in prevalence. Excluding the institutionalized population did not change the overall conclusions. Conclusions: The largest contributors to the higher disability of women than men are moderately disabling conditions with a high prevalence. Whereas traditional disabling conditions such as musculoskeletal diseases are more prevalent and disabling in women, fatal diseases such as cardiovascular disease are also important contributors in women and men.