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.

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.

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.

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 smoking differences in life expectancy with and without disability in Belgium.

Background: Smoking is the leading cause of premature mortality and morbidity. This study aimed at assessing the impact of smoking on life expectancy (LE) and LE with (LED) and without disability (DFLE). We further estimated the contribution of disability and mortality and their causes to differences in LED and DFLE by smoking. Methods: Data on disability, chronic conditions, and smoking from 17 148 participants of the 1997, 2001, 2004 Belgian Health Interview Surveys were used to estimate causes of disability using the attribution method. A 10-year mortality follow-up of survey participants was used. The Sullivan method was applied to estimate LED and DFLE. The contribution of disability and mortality and of causes of disability and death to smoking differences in LED and DFLE was assessed using decomposition methods. Results: Never smokers live longer than daily smokers. DFLE advantage at age 15 of +8.5/+4.3 years (y) in men/women never compared with daily smokers was the result of lower mortality (+6.2y/+3y) and lower disability (2.3y/1.3y). The extra 0.3y/1.6y LED in never smokers was due to lower mortality (+2.6y/+2.9y) and lower disability (-2.3y/-1.3y). Lower mortality from lung/larynx/trachea cancer, chronic respiratory, and ischaemic heart diseases was the main contributor to higher LED and DFLE in never smokers. Lower disability from musculoskeletal conditions in men and chronic respiratory diseases in women increased LED and DFLE in never smokers. Conclusions: Mortality and disability advantage among never smokers contributed to longer DFLE, while mortality advantage contributed to their longer LED.

Multinomial additive hazard model to assess the disability burden using cross-sectional data.

Population aging is accompanied by the burden of chronic diseases and disability. Chronic diseases are among the main causes of disability, which is associated with poor quality of life and high health care costs in the elderly. The identification of which chronic diseases contribute most to the disability prevalence is important to reduce the burden. Although longitudinal studies can be considered the gold standard to assess the causes of disability, they are costly and often with restricted sample size. Thus, the use of cross-sectional data under certain assumptions has become a popular alternative. Among the existing methods based on cross-sectional data, the attribution method, which was originally developed for binary disability outcomes, is an attractive option, as it enables the partition of disability into the additive contribution of chronic diseases, taking into account multimorbidity and that disability can be present even in the absence of disease. In this paper, we propose an extension of the attribution method to multinomial responses, since disability is often measured as a multicategory variable in most surveys, representing different severity levels. The R function constrOptim is used to maximize the multinomial log-likelihood function subject to a linear inequality constraint. Our simulation study indicates overall good performance of the model, without convergence problems. However, the model must be used with care for populations with low marginal disability probabilities and with high sum of conditional probabilities, especially with small sample size. For illustration, we apply the model to the data of the Belgian Health Interview Surveys.

Contribution of chronic diseases to the disability burden in a population 15 years and older, Belgium, 1997-2008.

BACKGROUND: Age-associated disability reduces quality of life in older populations and leads to wide-range implications for social and health policy. The identification of diseases that contribute to the disability burden is crucial to the development of prevention and intervention strategies to reduce disability. In this study, we assessed the contribution of chronic diseases to the prevalence of disability in Belgium. METHODS: Data from 35,837 individuals aged 15 years or older who participated in the 1997, 2001, 2004, or 2008 Belgian Health Interview Surveys were used. Disability was defined as difficulties in doing at least one of six activities of daily living (transfer in and out of bed, transfer in and out of chair, dressing, washing hands and face, feeding, and going to the toilet) and/or mobility limitations (ability to walk without stopping less than 200 m). Multiple additive regression models were fitted separately for men and women to estimate the age-specific background disability rate (experienced by everyone, independent of the presence of specific diseases) and disease-specific disability rates (disability rate in subjects who reported selected chronic diseases). RESULTS: Musculoskeletal, cardiovascular, and respiratory diseases were the main contributors to the disability burden in Belgium. Musculoskeletal diseases were the most prevalent diseases in men and women in all age groups. Neurological diseases and stroke were the most disabling diseases, i.e. caused the highest level of disability among the diseased individuals, in all age groups for men and women, respectively. Back pain was the main cause of disability in men aged 15 to 64 years, while heart attack was the major contributor to the disability prevalence in men aged 65 or older. Likewise, arthritis was the main cause of disability among women across all age groups. Depression was also an important contributor in young subjects (15-54 years). Cancer was not an important contributor to the disability prevalence in Belgium. CONCLUSIONS: To reduce the burden of disability in Belgium, interventions should target musculoskeletal, cardiovascular and respiratory diseases especially among elderly. Furthermore, attention should also be given to depression in young individuals.

The Association Between Physical Distancing Behaviors to Avoid COVID-19 and Health-Related Quality of Life in Immunocompromised and Nonimmunocompromised Individuals: Patient-Informed Protocol for the Observational, Cross-Sectional EAGLE Study.

BACKGROUND: Immunocompromised individuals are known to respond inadequately to SARS-CoV-2 vaccines, placing them at high risk of severe or fatal COVID-19. Thus, immunocompromised individuals and their caregivers may still practice varying degrees of social or physical distancing to avoid COVID-19. However, the association between physical distancing to avoid COVID-19 and quality of life has not been comprehensively evaluated in any study. OBJECTIVE: We aim to measure physical distancing behaviors among immunocompromised individuals and the association between those behaviors and person-centric outcomes, including health-related quality of life (HRQoL) measures, health state utilities, anxiety and depression, and work and school productivity impairment. METHODS: A patient-informed protocol was developed to conduct the EAGLE Study, a large cross-sectional, observational study, and this paper describes that protocol. EAGLE is designed to measure distancing behaviors and outcomes in immunocompromised individuals, including children (aged ≥6 mo) and their caregivers, and nonimmunocompromised adults in the United States and United Kingdom who report no receipt of passive immunization against COVID-19. We previously developed a novel self- and observer-reported instrument, the Physical Distancing Scale for COVID-19 Avoidance (PDS-C19), to measure physical distancing behavior levels cross-sectionally and retrospectively. Using an interim or a randomly selected subset of the study population, the PDS-C19 psychometric properties will be assessed, including structural validity, internal consistency, known-group validity, and convergent validity. Associations (correlations) will be assessed between the PDS-C19 and validated HRQoL-related measures and utilities. Structural equation modeling and regression will be used to assess these associations, adjusting for potential confounders. Participant recruitment and data collection took place from December 2022 to June 2023 using direct-to-patient channels, including panels, clinician referral, patient advocacy groups, and social media, with immunocompromising diagnosis confirmation collected and assessed for a randomly selected 25% of immunocompromised participants. The planned total sample size is 3718 participants and participant-caregiver pairs. Results will be reported by immunocompromised status, immunocompromising condition category, country, age group, and other subgroups. RESULTS: All data analyses and reporting were planned to be completed by December 2023. Results are planned to be submitted for publication in peer-reviewed journals in 2024-2025. CONCLUSIONS: This study will quantify immunocompromised individuals' physical distancing behaviors to avoid COVID-19 and their association with HRQoL as well as health state utilities. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/52643.

Risk factors for death from pandemic (H1N1) 2009, southern Brazil.

To identify risk factors for death from pandemic (H1N1) 2009, we obtained data for 157 hospitalized patients with confirmed cases of this disease. Multivariate analysis showed that diabetes and class III obesity were associated with death. These findings helped define priority vaccination groups in Brazil.

Potential impact of reduced tobacco use on life and health expectancies in Belgium.

OBJECTIVES: We investigated the potential impact of reduced tobacco use scenarios on total life expectancy and health expectancies, i.e., healthy life years and unhealthy life years. METHODS: Data from the Belgian Health Interview Survey 2013 were used to estimate smoking and disability prevalence. Disability was based on the Global Activity Limitation Indicator. We used DYNAMO-HIA to quantify the impacts of risk factor changes and to compare the "business-as-usual" with alternative scenarios. RESULTS: The "business-as-usual" scenario estimated that in 2028 the 15-year-old men/women would live additional 50/52 years without disability and 14/17 years with disability. The "smoking-free population" scenario added 3.4/2.8 healthy life years and reduced unhealthy life years by 0.79/1.9. Scenarios combining the prevention of smoking initiation with smoking cessation programs are the most effective, yielding the largest increase in healthy life years (1.9/1.7) and the largest decrease in unhealthy life years (- 0.80/- 1.47). CONCLUSIONS: Health impact assessment tools provide different scenarios for evidence-informed public health actions. New anti-smoking strategies or stricter enforcement of existing policies potentially gain more healthy life years and reduce unhealthy life years in Belgium.

Methods to assess the contribution of diseases to disability using cross-sectional studies: comparison of different versions of the attributable fraction and the attribution method.

BACKGROUND: This study aims to illustrate the differences between approaches proposed for apportioning disability to different diseases in a multicausal situation, i.e. the unadjusted attributable fraction (AF), the adjusted AF, the average AF and the attribution method (AM). This information is useful to better interpret results obtained from cross-sectional data and help policy makers decide on public health strategies. METHODS: Data for 29 931 individuals, representative of the French household population, who participated in the 2008-09 cross-sectional Disability-Health Survey, were included. Disability was defined as any limitation reported with the Global Activity Limitation Indicator. Unadjusted AFs were calculated using Levin's formula. Adjusted AFs were estimated for each disease by calculating predicted probabilities of disability for each individual in the dataset, under the assumption that the individual is unexposed to this specific disease (logistic model). Average AFs are based on the same methodology, but have the additional advantage that the average AFs for different diseases sum to the total AF associated with eliminating all diseases. AM accounts for competing risks and partitions total disability prevalence into additive contributions of different diseases and background disability (additive model). RESULTS: All methods obtained similar results with respect to the estimates of the disease contribution to disability prevalences and to ranking of the diseases, except unadjusted AFs, as the method ignores multimorbidity. Confounders other than diseases, such as age and gender, should be accurately taken into account. CONCLUSIONS: Conceptual differences, strengths and limitations of the different approaches were discussed.

Contribution of chronic diseases to educational disparity in disability in France: results from the cross-sectional "disability-health" survey.

BACKGROUND: This study aimed 1) to assess whether the contribution of chronic conditions to disability varies according to the educational attainment, 2) to disentangle the contributions of the prevalence and of the disabling impact of chronic conditions to educational disparities. METHODS: Data of the 2008-09 Disability Health Survey were examined (N = 23,348). The disability indicator was the Global Activity Limitation Indicator (GALI). The attribution method based on an additive hazard model was used to estimate educational differences in disabling impacts and in the contributions of diseases to disability. Counterfactual analyses were used to disentangle the contribution of differences in disease prevalence vs. disabling impact. RESULTS: In men, the main contributors to educational difference in disability prevalence were arthritis (contribution to disability prevalence: 5.7% (95% CI 5.4-6.0) for low-educated vs. 3.3% (3.0-3.9) for high-educated men), spine disorders (back/neck pain, deformity) (3.8% (3.6-4.0) vs. 1.9% (1.8-2.1)), chronic obstructive pulmonary diseases (2.4% (2.3-2.6) vs. 0.6% (0.5-0.7)) and ischemic heart /peripheral artery diseases (4.1% (3.9-4.3) vs. 2.4% (2.2-3.0)). In women, arthritis (9.5% (9.1-9.9) vs. 4.5%, (4.1-5.2)), spine disorders (4.5% (4.3-4.7) vs. 2.1% 1.9-2.3) and psychiatric diseases (3.1% (3.0-3.3) vs. 1.1% (1.0-1.3)) contributed most to education gap in disability. The educational differences were equally explained by differences in the disease prevalence and in their disabling impact. CONCLUSIONS: Public health policies aiming to reduce existing socioeconomic disparities in disability should focus on musculoskeletal, pulmonary, psychiatric and ischemic heart diseases, reducing their prevalence as well as their disabling impact in lower socioeconomic groups.

Measuring disability: a systematic review of the validity and reliability of the Global Activity Limitations Indicator (GALI).

BACKGROUND: GALI or Global Activity Limitation Indicator is a global survey instrument measuring participation restriction. GALI is the measure underlying the European indicator Healthy Life Years (HLY). Gali has a substantial policy use within the EU and its Member States. The objective of current paper is to bring together what is known from published manuscripts on the validity and the reliability of GALI. METHODS: Following the PRISMA guidelines, two search strategies (PUBMED, Google Scholar) were combined to identify manuscripts published in English with publication date 2000 or beyond. Articles were classified as reliability studies, concurrent or predictive validity studies, in national or international populations. RESULTS: Four cross-sectional studies (of which 2 international) studied how GALI relates to other health measures (concurrent validity). A dose-response effect by GALI severity level on the association with the other health status measures was observed in the national studies. The 2 international studies (SHARE, EHIS) concluded that the odds of reporting participation restriction was higher in subjects with self-reported or observed functional limitations. In SHARE, the size of the Odds Ratio's (ORs) in the different countries was homogeneous, while in EHIS the size of the ORs varied more strongly. For the predictive validity, subjects were followed over time (4 studies of which one international). GALI proved, both in national and international data, to be a consistent predictor of future health outcomes both in terms of mortality and health care expenditure. As predictors of mortality, the two distinct health concepts, self-rated health and GALI, acted independently and complementary of each other. The one reliability study identified reported a sufficient reliability of GALI. CONCLUSION: GALI as inclusive one question instrument fits all conceptual characteristics specified for a global measure on participation restriction. In none of the studies, included in the review, there was evidence of a failing validity. The review shows that GALI has a good and sufficient concurrent and predictive validity, and reliability.

Contribution of chronic conditions to functional limitations using a multinomial outcome: results for the older population in Belgium and Brazil.

BACKGROUND: The global phenomenon of population ageing is creating new challenges in both high and middle income countries, as functional limitations are expected to increase with age. The attribution method has been proposed to identify which conditions contribute most to disability using cross-sectional data. Although the original method was based on binary outcomes, we recently proposed an extension to multinomial responses, since different disability levels are often investigated in surveys. This is the first application of the extended method to evaluate differences in the contribution of chronic conditions to functional limitations in the older population of Brazil and Belgium. METHODS: Representative data from individuals aged ≥65 years who participated in the 2008 or 2013 Health Interview Surveys in Belgium (N = 4521) or in the 2008 National Household Sample Survey in Brazil (N = 28,437) were analysed. Individuals were classified as without, moderate or severe functional limitations, based on three activities of daily living: eating, showering, and toileting. Six chronic conditions common to the surveys - diabetes, heart diseases, musculoskeletal conditions, depression, chronic respiratory diseases, and cancer - were included in the analysis. Separate multinomial additive hazards models by gender for each country were fitted. RESULTS: The prevalence of moderate functional limitations was larger in men in Brazil (8.4%) compared to Belgium (6.0%) and similar in women (approximately 12.0%). Conversely, the severe prevalence in men was similar in the two countries (around 8.0%) and higher in women from Belgium (16.6%) than from Brazil (9.1%). Musculoskeletal conditions were the main contributors to the prevalence of functional limitations in men and women in Belgium but only in men and women with moderate functional limitations in Brazil. Depression and heart diseases contributed most to the severe prevalence of functional limitations in men and women in Brazil, respectively. CONCLUSIONS: Our findings provide a better understanding of differences in the prevalence of different levels of functional limitations in Brazil and Belgium. These differences can be related to differences in socioeconomic conditions, health care access and quality, disease diagnosis, stage of epidemiology transition, life expectancy, and the prevalence of lifestyle risk factors in the two countries.

Contribution of chronic diseases to the mild and severe disability burden in Belgium.

BACKGROUND: Population aging accompanied by an increased longevity with disability has raised international concern, especially due to its costs to the health care systems. Chronic diseases are the main causes of physical disability and their simultaneous occurrence in the population can impact the disablement process, resulting in different severity levels. In this study, the contribution of chronic diseases to both mild and severe disability burden in Belgium was investigated. METHODS: Data on 21 chronic diseases and disability from 35,799 individuals aged 15 years or older who participated in the 1997, 2001, 2004, or 2008 Belgian Health Interview Surveys were analysed. Mild and severe disability were defined based on questions related to six activities of daily living and/or mobility limitations. To attribute disability by severity level to selected chronic diseases, multiple additive hazard models were fitted to each disability outcome, separately for men and women. RESULTS: A stable prevalence of mild (5 %) and severe (2-3 %) disability was observed for the Belgian population aged 15 years or older between 1997 and 2008. Arthritis was the most important contributor in women with mild and severe disability. In men, low back pain and chronic respiratory diseases contributed most to the mild and severe disability burden, respectively. The contribution also differed by age: for mild disability, depression and chronic respiratory diseases were important contributors among young individuals, while heart attack had a large contribution for older individuals. For severe disability, neurological diseases and stroke presented a large contribution in young and elderly individuals, respectively. CONCLUSIONS: Our results indicate that the assessment of the contribution of chronic diseases on disability is more informative if different levels of disability are taken into consideration. The identification of diseases which are related to different levels of disability - mild and severe - can assist policymakers in the definition and prioritisation of strategies to tackle disability, involving prevention, rehabilitation programs, support services, and training for disabled individuals.