BeBOD estimates of the burden of disease attributable to risk factors
Our results build on the estimates of causes of death from the Belgian National Burden of Disease Study and apply comparative risk assessment to estimate the proportion of that burden due to risk factors.
Population exposure
The attribution of disease burden to risk factors requires estimates of the level of exposure in the population.
Population attributable fraction
Based on the estimated level of exposure and the associated health risk, a population attributable fraction (PAF) is calculated. The PAF is the proportion of the disease burden that is caused by exposure to the risk factor.
Attributable burden
The burden of disease is quantified in deaths and in Years of Life Lost (YLL). To derive the burden attributable to a risk factor, its PAF is multiplied with the total observed burden.
Risk factors
Tobacco use
The prevalence of never, former, and current smokers, the daily number of cigarettes smoked by smokers, time since quitting for former smokers, and pack-years for smokers are all derived from the Belgian Health Interview Survey. Bayesian regression models are used to smooth, interpolate, and extrapolate the observed estimates.
Alcohol use
The prevalence of current drinkers, former drinkers, and lifetime abstainers is derived from the Belgian Health Interview Survey. Mean alcohol consumption in grams per day among current drinkers is sourced from the Global Health Observatory, with the BHIS distribution applied to these estimates. Bayesian regression models are used to smooth, interpolate, and extrapolate the observed estimates.
High Body Mass Index (BMI)
The prevalence of the different BMI categories and the mean BMI are based on the self-reported height and weight in the Belgian Health Interview Survey. The self-reported measures are adjusted using measured height and weight collected in the Belgian Health Examination Survey. Bayesian regression models are used to smooth, interpolate and extrapolate the observed estimates.
Air pollution (particulate matter, nitrogen dioxide, ozone)
Population exposure to particulate matter (PM2.5), nitrogen dioxide (NO2) and ozone (O3) is estimated based on air quality models developed by IRCEL-CELINE and population data from Statbel.
Environmental noise (road traffic noise)
Population exposure to road traffic noise is based on figures reported within the EU, which are interpolated using a generalized linear model.
Extreme temperatures (heat and cold)
Population exposure to temperature extremes is based on meteorological data provided by the Royal Meteorological Institute. The methodology for defining exposure categories is currently being developed.
Explore our estimates
Trends
Explore trends in risk factor attributable burden, by region, sex, and age.
Patterns
Explore patterns of risk factor attributable burden, by region, sex, age, and year.
Rankings
Rank causes of risk factor attributable burden, by region, sex, age, and year.
Heatmap
Compare the top 20 causes of risk factor attributable burden, across region, sex, age, or year.
Exposure
Explore trends in risk factor exposure, by region, sex, and age.
Results
Explore and download our estimates of attributable disease burden and risk factor exposure, by risk factor, region, sex, age, and year.
Download all estimates
All estimates can be downloaded in parquet format via Zenodo:
Attributable disease burden
Exposure
Citation
Kim Fernandez, Sarah Nayani, Sarah Croes, Arno Pauwels, Emilie Vandeputte, Masja Schmidt, Brecht Devleesschauwer & Vanessa Gorasso. (2026). BeBOD estimates of mortality and years of life lost attributable to risk factors, 2013-2022 (v2026-07-01) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.21130029
Kim Fernandez, Sarah Nayani, Sarah Croes, Arno Pauwels, Emilie Vandeputte, Masja Schmidt, Brecht Devleesschauwer & Vanessa Gorasso. (2026). BeBOD estimates of population exposure to risk factors, 2013-2022 (v2026-07-16) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.21395045
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Belgian National Burden of Disease Study (BeBOD)
What are the most important diseases in Belgium? Which risk factors contribute most to the overall disease burden? How is the burden of disease evolving over time, and how does it differ across the country? In a context of increasing budgetary constraints, a precise answer to these basic questions is more than ever necessary to inform policy-making.
To address this need, Sciensano is conducting a national burden of disease study. In addition to generating internally consistent estimates of death rate (mortality) or how unhealthy we are (morbidity) by age, sex and region, the estimates also include how much of that burden can be attributed to risk factors. This can be useful for priority setting and prevention policy planning.
For more info, please visit the BeBOD project page, or consult the general BeBOD protocol or the BeBOD risk factor protocol.
Other BeBOD visualisation tools
Estimates of the fatal and non-fatal burden of 38 key diseases
Estimates of the fatal burden of 131 causes of death
Estimates of the non-fatal burden of 57 cancer sites
Estimates of projected non-fatal burden of 33 causes
Estimates of social inequalities in the fatal burden of disease