The potential impact fraction of population weight reduction scenarios on non-communicable diseases in Belgium: application of the g-computation approach

Abstract Background Overweight is a major risk factor for non-communicable diseases (NCDs) in Europe, affecting almost 60% of all adults. Tackling obesity is therefore a key long-term health challenge and is vital to reduce premature mortality from NCDs. Methodological challenges remain however, to provide actionable evidence on the potential health benefits of population weight reduction interventions. This study aims to use a g-computation approach to assess the impact of hypothetical weight reduction scenarios on NCDs in Belgium in a multi-exposure context. Methods Belgian health interview... Mehr ...

Verfasser: Ingrid Pelgrims
Brecht Devleesschauwer
Stefanie Vandevijvere
Eva M. De Clercq
Johan Van der Heyden
Stijn Vansteelandt
Dokumenttyp: Artikel
Erscheinungsdatum: 2024
Reihe/Periodikum: BMC Medical Research Methodology, Vol 24, Iss 1, Pp 1-15 (2024)
Verlag/Hrsg.: BMC
Schlagwörter: Non-communicable diseases / Overweight / g-computation / Potential impact fractions / Health policy / Health impact assessment / Medicine (General) / R5-920
Sprache: Englisch
Permalink: https://search.fid-benelux.de/Record/base-28971208
Datenquelle: BASE; Originalkatalog
Powered By: BASE
Link(s) : https://doi.org/10.1186/s12874-024-02212-7

Abstract Background Overweight is a major risk factor for non-communicable diseases (NCDs) in Europe, affecting almost 60% of all adults. Tackling obesity is therefore a key long-term health challenge and is vital to reduce premature mortality from NCDs. Methodological challenges remain however, to provide actionable evidence on the potential health benefits of population weight reduction interventions. This study aims to use a g-computation approach to assess the impact of hypothetical weight reduction scenarios on NCDs in Belgium in a multi-exposure context. Methods Belgian health interview survey data (2008/2013/2018, n = 27 536) were linked to environmental data at the residential address. A g-computation approach was used to evaluate the potential impact fraction (PIF) of population weight reduction scenarios on four NCDs: diabetes, hypertension, cardiovascular disease (CVD), and musculoskeletal (MSK) disease. Four scenarios were considered: 1) a distribution shift where, for each individual with overweight, a counterfactual weight was drawn from the distribution of individuals with a “normal” BMI 2) a one-unit reduction of the BMI of individuals with overweight, 3) a modification of the BMI of individuals with overweight based on a weight loss of 10%, 4) a reduction of the waist circumference (WC) to half of the height among all people with a WC:height ratio greater than 0.5. Regression models were adjusted for socio-demographic, lifestyle, and environmental factors. Results The first scenario resulted in preventing a proportion of cases ranging from 32.3% for diabetes to 6% for MSK diseases. The second scenario prevented a proportion of cases ranging from 4.5% for diabetes to 0.8% for MSK diseases. The third scenario prevented a proportion of cases, ranging from 13.6% for diabetes to 2.4% for MSK diseases and the fourth scenario prevented a proportion of cases ranging from 36.4% for diabetes to 7.1% for MSK diseases. Conclusion Implementing weight reduction scenarios among individuals with excess weight ...