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

Efficacy of anti PD-1 therapy in children and adolescent melanoma patients (MELCAYA study)

Background: Data on the efficacy and safety of anti PD-1 antibodies in children and adolescents (CA) with melanoma are lacking. The aim of this study was to determine outcomes of CA melanoma patients receiving anti PD-1 antibodies. Methods: Melanoma patients ≤18 years treated with anti PD-1 were retrospectively retrieved from 15 academic centers. Information on histopathological diagnosis, surgical treatment, systemic therapy, objective response rate (ORR), safety profile was collected. Progression-free survival (PFS) and overall survival (OS) were assessed by Kaplan-Meier method. Results: Between April 2016 and March 2024, 99 patients treated with systemic therapy were retrieved, 81 treated with anti PD-1 therapy. Median age was 14 years (range 2–18 years), 37 pts were ≤12 yrs. Overall, 38 CA patients received anti PD-1 in adjuvant setting, and the 3-year PFS and OS were 70.6 % and 81.1 %, respectively. Two patients received anti-PD-1 based neoadjuvant treatment, both had a pathologic complete response and remain disease free. Fifty-six received a systemic therapy for advanced disease and among them, 43 received anti PD-1-based therapy for advanced disease in 1st line, while 12 and 5 pts received a 2nd and 3rd line, respectively. Among patients receiving a 1st line therapy with anti PD-1 monotherapy the ORR was 25 %, and the 3-year OS was 34 %. Toxicities were consistent with previous studies in adult melanoma patients. Conclusions: Our study provides the first evidence of efficacy of anti PD-1 in CA melanoma patients and supports the use of anti PD-1 therapy in pts ≤18 years, included those <12 years

Variation in smoking attributable all-cause mortality across municipalities in Belgium, 2018:application of a Bayesian approach for small area estimations

Background Smoking is one of the leading causes of preventable mortality and morbidity worldwide, with the European Region having the highest prevalence of tobacco smoking among adults compared to other WHO regions. The Belgian Health Interview Survey (BHIS) provides a reliable source of national and regional estimates of smoking prevalence; however, currently there are no estimates at a smaller geographical resolution such as the municipality scale in Belgium. This hinders the estimation of the spatial distribution of smoking attributable mortality at small geographical scale (i.e., number of deaths that can be attributed to tobacco). The objective of this study was to obtain estimates of smoking prevalence in each Belgian municipality using BHIS and calculate smoking attributable mortality at municipality level. Methods Data of participants aged 15 + on smoking behavior, age, gender, educational level and municipality of residence were obtained from the BHIS 2018. A Bayesian hierarchical Besag-York-Mollie (BYM) model was used to model the logit transformation of the design-based Horvitz-Thompson direct prevalence estimates. Municipality-level variables obtained from Statbel, the Belgian statistical office, were used as auxiliary variables in the model. Model parameters were estimated using Integrated Nested Laplace Approximation (INLA). Deviance Information Criterion (DIC) and Conditional Predictive Ordinate (CPO) were computed to assess model fit. Population attributable fractions (PAF) were computed using the estimated prevalence of smoking in each of the 589 Belgian municipalities and relative risks obtained from published meta-analyses. Smoking attributable mortality was calculated by multiplying PAF with age-gender standardized and stratified number of deaths in each municipality. Results BHIS 2018 data included 7,829 respondents from 154 municipalities. Smoothed estimates for current smoking ranged between 11% [Credible Interval 3;23] and 27% [21;34] per municipality, and for former smoking between 4% [0;14] and 34% [21;47]. Estimates of smoking attributable mortality constituted between 10% [7;15] and 47% [34;59] of total number of deaths per municipality. Conclusions Within-country variation in smoking and smoking attributable mortality was observed. Computed estimates should inform local public health prevention campaigns as well as contribute to explaining the regional differences in mortality

Premature Mortality Attributable to Socioeconomic Inequality in Belgium between 1991 and 2020

Socioeconomic deprivation is associated with increased premature mortality. Our aim is to measure the health inequality in premature mortality in the Belgian population between 1991-2020 by using the Belgian Index of Multiple Deprivation 2011 (BIMD2011). We built the time- and area-specific BIMD2011 combining data on income, employment, education, crime and housing from the census 2011, National Register, Intermutualistisch Agentschap, and the Federal Police. We then utilized mortality data at ages 0-74 between 1991 and 2020 to compute age-and-sex-standardized premature mortality rates, population attributable fraction (PAF) and potential years-life-lost (PYLLs) due to premature mortality in overall and cause-specific mortality. Finally, we calculated these health inequality indicators by major causes of death in Belgium. Our study covered 294 million person-years in people aged from 0 to 74, with 1,164,777 premature deaths occurring between 1991 and 2020. In total, 29.7% (95%CI:29.1-29.9) premature deaths were attributable to SE inequality causing a mean of YLLs of 8.7 per person in the observed period. Out of 74 564 premature deaths that occurred between 1998 and 2017 and that were attributable to socioeconomic inequality, the causes of death that contributed most deaths were diseases of circulatory system (23,763;31%), diseases of respiratory system (16,690;22%) and neoplasm (14,108;19%). We created a small-area BIMD that can locate hot spots of SE inequality and help policy makers to effectively allocate funding and put in place new SE policies. Our findings showed that deprivation in Belgium is strongly associated with health inequality and interventions addressing SE inequality should be prioritized

Cluster pattern analysis of environmental stressors and quantifying their impact on all-cause mortality in Belgium

Abstract Environmental stress represents an important burden on health and leads to a considerable number of diseases, hospitalisations, and excess mortality. Our study encompasses a representative sample size drawn from the Belgian population in 2016 (n = 11.26 million, with a focus on n = 11.15 million individuals). The analysis is conducted at the geographical level of statistical sectors, comprising a total of n = 19,794 sectors, with a subset of n = 18,681 sectors considered in the investigation. We integrated multiple parameters at the finest spatial level and constructed three categories of environmental stress through clustering: air pollution, noise stress and stress related to specific land-use types. We observed identifiable patterns in the spatial distribution of stressors within each cluster category. We assessed the relationship between age-standardized all-cause mortality rates (ASMR) and environmental stressors. Our research found that especially very high air pollution values in areas where traffic is the dominant local component of air pollution (ASMR + 14,8%, 95% CI: 10,4 – 19,4%) and presence of industrial land (ASMR + 14,7%, 95% CI: 9,4 – 20,2%) in the neighbourhood are associated with an increased ASMR. Cumulative exposure to multiple sources of unfavourable environmental stress (simultaneously high air pollution, high noise, presence of industrial land or proximity of primary/secondary roads and lack of green space) is associated with an increase in ASMR (ASMR + 26,9%, 95% CI: 17,1 – 36,5%)

Trends in socioeconomic inequalities in cause-specific premature mortality in Belgium, 1998–2019

Background Higher levels of socioeconomic deprivation have been consistently associated with increased risk of premature mortality, but a detailed analysis by causes of death is lacking in Belgium. We aim to investigate the association between area deprivation and all-cause and cause-specific premature mortality in Belgium over the period 1998–2019. Methods We used the 2001 and 2011 Belgian Indices of Multiple Deprivation to assign statistical sectors, the smallest geographical units in the country, into deprivation deciles. All-cause and cause-specific premature mortality rates, population attributable fraction, and potential years of life lost due to inequality were estimated by period, sex, and deprivation deciles. Results Men and women living in the most deprived areas were 1.96 and 1.78 times more likely to die prematurely compared to those living in the least deprived areas over the period under study (1998–2019). About 28% of all premature deaths could be attributed to socioeconomic inequality and about 30% of potential years of life lost would be averted if the whole population of Belgium faced the premature mortality rates of the least deprived areas. Conclusion Premature mortality rates have declined over time, but inequality has increased due to a faster pace of decrease in the least deprived areas compared to the most deprived areas. As the causes of death related to poor lifestyle choices contribute the most to the inequality gap, more effective, country-level interventions should be put in place to target segments of the population living in the most deprived areas as they are facing disproportionately high risks of dying

Trends in socioeconomic inequalities in cause-specific premature mortality in Belgium, 1998–2019

Background Higher levels of socioeconomic deprivation have been consistently associated with increased risk of premature mortality, but a detailed analysis by causes of death is lacking in Belgium. We aim to investigate the association between area deprivation and all-cause and cause-specific premature mortality in Belgium over the period 1998-2019.Methods We used the 2001 and 2011 Belgian Indices of Multiple Deprivation to assign statistical sectors, the smallest geographical units in the country, into deprivation deciles. All-cause and cause-specific premature mortality rates, population attributable fraction, and potential years of life lost due to inequality were estimated by period, sex, and deprivation deciles.Results Men and women living in the most deprived areas were 1.96 and 1.78 times more likely to die prematurely compared to those living in the least deprived areas over the period under study (1998-2019). About 28% of all premature deaths could be attributed to socioeconomic inequality and about 30% of potential years of life lost would be averted if the whole population of Belgium faced the premature mortality rates of the least deprived areas.ConclusionPremature mortality rates have declined over time, but inequality has increased due to a faster pace of decrease in the least deprived areas compared to the most deprived areas. As the causes of death related to poor lifestyle choices contribute the most to the inequality gap, more effective, country-level interventions should be put in place to target segments of the population living in the most deprived areas as they are facing disproportionately high risks of dying