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Background Similar to many countries, Belgium experienced a rapid increase in cancer diagnoses in the last years. Considering that a large part of cancer types could be prevented, our study aimed to estimate the annual healthcare burden of cancer per site, and to compare cost with burden of disease estimates to have a better understanding of the impact of different cancer sites in Belgium. Methods We used nationally available data sources to estimate the healthcare expenditure. We opted for a prevalence‐based approach which measures the disease attributable costs that occur concurrently for 10‐year prevalent cancer cases in 2018. Average attributable costs of cancer were computed via matching of cases (patients with cancer by site) and controls (patients without cancer). Years of life lost due to disability (YLD) were used to summarize the health impact of the selected cancers. Results The highest attributable cost in 2018 among the selected cancers was on average €15,867 per patient for bronchus and lung cancer, followed by liver cancer, pancreatic cancer, and mesothelioma. For the total cost, lung cancer was the most costly cancer site with almost €700 million spent in 2018. Lung cancer was followed by breast and colorectal cancer that costed more than €300 million each in 2018. Conclusions In our study, the direct attributable cost of the most prevalent cancer sites in Belgium was estimated to provide useful guidance for cost containment policies. Many of these cancers could be prevented by tackling risk factors such as smoking, obesity, and environmental stressors.

Background and methodsHigh body mass index (BMI) is a major risk factor for several non-communicable diseases. The increasing concern about the health and economic burden of BMI makes it essential for countries to track their progress on major modifiable risk exposures. The aim of the study is to estimate the burden attributable to high BMI in Belgium, in terms of years of life lost due to disability (YLD), years of life lost due to premature mortality (YLL) and disease costs, using comparative risk assessment. We followed the general framework established in the Global Burden of Diseases, Injuries and Risk Factors study. Population attributable fractions were calculated for the year 2018 for selected health outcomes using local estimates of BMI and burden of disease estimates from the Belgian Burden of Disease study.ResultsAccording to our figures, around 37 800 YLD, 56 000 YLL and €1.85 billion in healthcare costs can be attributed to a high BMI. Diabetes had the highest number of YLD attributable to high BMI followed by musculoskeletal disorders. Cardiovascular diseases accounted for the highest burden in terms of YLL attributable to high BMI, followed by diabetes and different forms of cancers (i.e., breast, colon and rectum and oesophageal cancer).ConclusionA substantial proportion of the burden of disease could be prevented when reducing BMI in Belgium. This evidence on the impact of risk factors is important for monitoring disease burdens and setting priorities for health prevention policies.

Background Studies often evaluate mental health and well-being in association with individual health behaviours although evaluating multiple health behaviours that co-occur in real life may reveal important insights into the overall association. Also, the underlying pathways of how lifestyle might affect our health are still under debate. Here, we studied the mediation of different health behaviours or lifestyle factors on mental health and its effect on core markers of ageing: telomere length (TL) and mitochondrial DNA content (mtDNAc). Methods In this study, 6054 adults from the 2018 Belgian Health Interview Survey (BHIS) were included. Mental health and well-being outcomes included psychological and severe psychological distress, vitality, life satisfaction, self-perceived health, depressive and generalised anxiety disorder and suicidal ideation. A lifestyle score integrating diet, physical activity, smoking status, alcohol consumption and BMI was created and validated. On a subset of 739 participants, leucocyte TL and mtDNAc were assessed using qPCR. Generalised linear mixed models were used while adjusting for a priori chosen covariates. Results The average age (SD) of the study population was 49.9 (17.5) years, and 48.8% were men. A one-point increment in the lifestyle score was associated with lower odds (ranging from 0.56 to 0.74) for all studied mental health outcomes and with a 1.74% (95% CI: 0.11, 3.40%) longer TL and 4.07% (95% CI: 2.01, 6.17%) higher mtDNAc. Psychological distress and suicidal ideation were associated with a lower mtDNAc of − 4.62% (95% CI: − 8.85, − 0.20%) and − 7.83% (95% CI: − 14.77, − 0.34%), respectively. No associations were found between mental health and TL. Conclusions In this large-scale study, we showed the positive association between a healthy lifestyle and both biological ageing and different dimensions of mental health and well-being. We also indicated that living a healthy lifestyle contributes to more favourable biological ageing.

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.

Background Health literacy (HL) has been put forward as a potential mediator through which socioeconomic status (SES) affects health. This study explores whether HL mediates the relation between SES and a selection of health or health-related outcomes. Methods Data from the participants of the Belgian health interview survey 2018 aged 18 years or older were individually linked with data from the Belgian compulsory health insurance ( n  = 8080). HL was assessed with the HLS-EU-Q6. Mediation analyses were performed with health behaviour (physical activity, diet, alcohol and tobacco consumption), health status (perceived health status, mental health status), use of medicine (purchase of antibiotics), and use of preventive care (preventive dental care, influenza vaccination, breast cancer screening) as dependent outcome variables, educational attainment and income as independent variables of interest, age and sex as potential confounders and HL as mediating variable. Results The study showed that unhealthy behaviours (except alcohol consumption), poorer health status, higher use of medicine and lower use of preventive care (except flu vaccination) were associated with low SES (i.e., low education and low income) and with insufficient HL. HL partially mediated the relationship between education and health behaviour, perceived health status and mental health status, accounting for 3.8–16.0% of the total effect. HL also constituted a pathway by which income influences health behaviour, perceived health status, mental health status and preventive dental care, with the mediation effects accounting for 2.1–10.8% of the total effect. Conclusions Although the influence of HL in the pathway is limited, our findings suggest that strategies for improving various health-related outcomes among low SES groups should include initiatives to enhance HL in these population groups. Further research is needed to confirm our results and to better explore the mediating effects of HL.

Background Stroke is a leading cause of mortality and disability in Belgium and worldwide. Increasing evidence highlights air pollution as a significant stroke risk factor. Despite efforts in the past decade to mitigate air pollution in Belgium, a considerable part of the population remains exposed to concentrations exceeding the World Health Organization (WHO) Air Quality Guidelines. Therefore, quantifying the effectiveness of further pollution reduction interventions is crucial in supporting policymaking. This study applies a g-computation approach to assess the benefits of hypothetical air pollution reduction scenarios on stroke prevalence in Belgium within a multi-exposure context. Methods Belgian health interview survey data (2008/2013/2018, n  = 27536) were linked to environmental data at the participant’s residential address. Missing data and bias related to self-reported covariates were addressed based on data from the 2018 Belgian health examination survey and a random-forest multiple imputation. A g-computation approach was used to calculate the potential impact fractions of air pollution reduction scenarios on stroke prevalence in Belgium, with regression models adjusted for socio-demographic, environmental, and lifestyle factors. Scenarios included lowering annual exposure to fine particulate matter (PM 2.5 ) and nitrogen dioxide levels (NO 2 ) to levels recommended by WHO, and assessing dose-response effects of reducing exposure to PM 2.5 , NO 2 , and black carbon (BC) by 20–80%. Results Stroke was significantly associated with PM 2.5 , while associations with NO 2 and BC were borderline significant. Meeting WHO air quality guidelines for PM 2.5 and NO 2 would reduce stroke risk by 0.88% (SE: 0.24) and 0.33% (SE: 0.19), preventing 67% and 25% of stroke cases in Belgium, respectively. Results reveal a dose-response association between air pollution reduction and stroke prevalence. Reduction in air pollution exposure, ranging from 20% to 80% showed increasing potential impact fractions for stroke: PM 2.5 (29%, 48%, 61%, 69%), NO 2 (10%, 18%, 25%, 31%) and BC (8%, 14%, 20%, 23%). Conclusion This study highlights the importance of air pollution on the stroke burden and demonstrates that air pollution reduction interventions could significantly decrease the prevalence of stroke in Belgium. The g-computation approach represents a straightforward approach in epidemiology for making causal inference from observational data while also providing useful information for policymakers.

Background Multimorbidity is a rising public health concern. Indicators that address these complex health conditions are often exclusively devoted to physical diseases. Because of their high disease burden, mental health disorders ought to be considered as well. This paper aims to measure the added value of including a mental health dimension in a population-based multimorbidity indicator and identify which mental health measures are most appropriate. Methods Secondary analyses were conducted on data from the Belgian Health Interview Survey 2018. We compared the prevalence of different multimorbidity indicators (MIs) in relation to health impact measures, such as quality of life (EQ-5D score) and activity limitation (GALI). The MIs differed as to the health conditions involved: one was based on physical conditions only; the other three included mental health dimensions that were either self-reported or assessed by a scale (GAD-7, PHQ-9, and GHQ-12). We performed linear and logistic regressions to assess the association between the MIs and the health correlates and compared the goodness of fit of the different models. Results MI prevalence was higher when including a mental health dimension assessed with the GHQ-12 (42.0%) and with the GAD-7 or the PHQ-9 (39.4%) as compared to physical conditions only (35.0%). Associations between the MI and health correlates were consistently stronger if the MI included a mental health dimension. The regression models with MI including the GAD-7 and PHQ-9 showed the strongest association between MI and the health correlates and also had the best goodness-of-fit measures. Conclusions MIs that only take physical conditions into account underestimate their impact on individuals’ lives. Including mental ill-health in an MI is key to linking it to health correlates.

Background Recent studies showed that air pollution might play a role in the etiology of mental disorders. In this study we evaluated the association between air pollution and mental and self-rated health and the possible mediating effect of physical activity in this association. Methods In 2008, 2013 and 2018 the Belgian Health Interview Survey (BHIS) enrolled 16,455 participants who completed following mental health dimensions: psychological distress, suboptimal vitality, suicidal ideation, and depressive and generalized anxiety disorder and self-rated health. Annual exposure to nitrogen dioxide (NO 2 ), particulate matter ≤ 2.5 µm (PM 2.5 ) and black carbon (BC) were estimated at the participants’ residence by a high resolution spatiotemporal model. Multivariate logistic regressions were carried out taking into account a priori selected covariates. Results Long-term exposure to PM 2.5 , BC and NO 2 averaged 14.5, 1.4, and 21.8 µg/m 3 , respectively. An interquartile range (IQR) increment in PM 2.5 exposure was associated with higher odds of suboptimal vitality (OR = 1.27; 95% CI: 1.13, 1.42), poor self-rated health (OR = 1.20; 95% CI: 1.09, 1.32) and depressive disorder (OR = 1.19; 95% CI: 1.00, 1.41). Secondly, an association was found between BC exposure and higher odds of poor self-rated health and depressive and generalized anxiety disorder and between NO 2 exposure and higher odds of psychological distress, suboptimal vitality and poor self-rated health. No association was found between long-term ambient air pollution and suicidal ideation or severe psychological distress. The mediation analysis suggested that between 15.2% (PM 2.5 -generalized anxiety disorder) and 40.1% (NO 2 -poor self-rated health) of the association may be mediated by a difference in physical activity. Conclusions Long-term exposure to PM 2.5 , BC or NO 2 was adversely associated with multiple mental health dimensions and self-rated health and part of the association was mediated by physical activity. Our results suggest that policies aiming to reduce air pollution levels could also reduce the burden of mental health disorders in Belgium.

Potential is seen in web data collection for population health surveys due to its combined cost-effectiveness, implementation ease, and increased internet penetration. Nonetheless, web modes may lead to lower and more selective unit response than traditional modes, and this may increase bias in the measured indicators. This research assesses the unit response and costs of a web study versus face-to-face (F2F) study. Alongside the Belgian Health Interview Survey by F2F edition 2018 (BHISF2F; net sample used: 3316), a web survey (Belgian Health Interview Survey by Web [BHISWEB]; net sample used: 1010) was organized. Sociodemographic data on invited individuals was obtained from the national register and census linkages. Unit response rates considering the different sampling probabilities of both surveys were calculated. Logistic regression analyses examined the association between mode system and sociodemographic characteristics for unit nonresponse. The costs per completed web questionnaire were compared with the costs for a completed F2F questionnaire. The unit response rate is lower in BHISWEB (18.0%) versus BHISF2F (43.1%). A lower response rate was observed for the web survey among all sociodemographic groups, but the difference was higher among people aged 65 years and older (15.4% vs 45.1%), lower educated people (10.9% vs 38.0%), people with a non-Belgian European nationality (11.4% vs 40.7%), people with a non-European nationality (7.2% vs 38.0%), people living alone (12.6% vs 40.5%), and people living in the Brussels-Capital (12.2% vs 41.8%) region. The sociodemographic characteristics associated with nonresponse are not the same in the 2 studies. Having another European (OR 1.60, 95% CI 1.20-2.13) or non-European nationality (OR 2.57, 95% CI 1.79-3.70) compared to a Belgian nationality and living in the Brussels-Capital (OR 1.72, 95% CI 1.41-2.10) or Walloon (OR 1.47, 95% CI 1.15-1.87) regions compared to the Flemish region are associated with a higher nonresponse only in the BHISWEB study. In BHISF2F, younger people (OR 1.31, 95% CI 1.11-1.54) are more likely to be nonrespondents than older people, and this was not the case in BHISWEB. In both studies, lower educated people have a higher probability of being nonrespondent, but this effect is more pronounced in BHISWEB (low vs high education level: Web, OR 2.71, 95% CI 2.21-3.39 and F2F OR 1.70, 95% CI 1.48-1.95). The BHISWEB study had a considerable advantage; the cost per completed questionnaire was almost 3 times lower (€41 [US $48]) compared with F2F data collection (€111 [US $131]). The F2F unit response rate was generally higher, yet for certain groups the difference between web and F2F was more limited. Web data collection has a considerable cost advantage. It is therefore worth experimenting with adaptive mixed-mode designs to optimize financial resources without increasing selection bias (eg, only inviting sociodemographic groups who are keener to participate online for web surveys while continuing to focus on increasing F2F response rates for other groups).

Background Chronic diseases and multimorbidity are a major cause of disease burden—for patients, caregivers, and society. Little is known however about potential interaction effects between specific disease combinations. Besides an additive effect, the presence of multiple conditions could also act synergistically or antagonistically regarding the impact on patients’ health-related quality of life (HRQoL). The aim was to estimate the impact of coexisting chronic diseases on HRQoL of the adult general Belgian population. Methods The Belgian Health Interview Survey 2018 provided data on self-reported chronic conditions and HRQoL (EQ-5D-5L) for a nationally representative sample. Linear mixed models were used to analyze two-way and three-way interactions of disease combinations on HRQoL. Results Multimorbidity had a prevalence of 46.7% (≥ 2 conditions) and 29.7% (≥ 3 conditions). HRQoL decreased considerably with the presence of multiple chronic diseases. 14 out of 41 dyad combinations and 5 out of 13 triad combinations showed significant interactions, with a dominant presence of negative/synergistic effects. Positive/antagonistic effects were found in more subjective chronic diseases such as depression and chronic fatigue. Conditions appearing the most frequently in significant disease pair interactions were dorsopathies, respiratory diseases, and arthropathies. Conclusions Diverse multimorbidity patterns, both dyads and triads, were synergistically or antagonistically associated with lower HRQoL. Tackling the burden of multimorbidity is needed, especially because most disease combinations affect each other synergistically, resulting in a greater reduction in HRQoL. Further knowledge about those multimorbidity patterns with a greater impact on HRQoL is needed to better understand disease burden beyond mortality and morbidity data.