The impact of hypothetical interventions on adiposity in adolescence

Mekdes K Gebremariam,Yngvar Ommundsen,Knut-Inge Klepp,Ingunn H Bergh,Roch A Nianogo,Mona Bjelland,Onyebuchi A Arah,Nanna Lien

doi:10.1038/s41598-021-90415-z

Abstract

In order to develop effective public health initiatives aimed at promoting healthy weight development, identifying the interventions/combination of interventions with the highest beneficial effect on body weight is vital. The study aimed to estimate the mean BMI at age 13 under hypothetical interventions targeting dietary behavior, physical activity and screen time at age 11. We used data from a school-based cohort study of 530 participants followed between the ages of 11 and 13. We used g-computation, a causal modeling method, to estimate the impact of single and combined hypothetical behavioral interventions at age 11 on BMI at age 13. Of the hypothetical interventions, the one with the largest population mean difference in BMI was the one combining all interventions (dietary behavior, physical activity and screen time interventions) and assuming 100% intervention adherence, with a population mean differences of − 0.28 (95% CI − 0.59, 0.07). Isolated behavioral interventions had a limited impact on BMI. This study demonstrated that a combination of healthy dietary behavior and physical activity promotion, as well as screen time reduction interventions at age 11 could have the highest beneficial effect on the reduction of BMI at age 13, although the change in BMI was small. The findings highlight the importance of a systems approach to obesity prevention focusing on multicomponent interventions.

Highlights

In order to develop effective public health initiatives aimed at promoting healthy weight development, identifying the interventions/combination of interventions with the highest beneficial effect on body weight is vital
Sixty four percent met the daily Physical activity (PA) recommendation of 60 min per day Moderate- to-vigorous PA (MVPA) while 42% met the recommendations of 2 h or less per day of screen time
The only exception was for sex, whereby boys were more likely to have missing data compared to girls (p = 0.003)

Summary

Introduction

In order to develop effective public health initiatives aimed at promoting healthy weight development, identifying the interventions/combination of interventions with the highest beneficial effect on body weight is vital. A useful alternative or supplemental approach is the use of causal modeling methods applied to observational data, in order to estimate the potential effects of hypothetical interventions on predefined outcomes under realistic or real-world scenarios Such modern modeling methods include the use of the g-computation algorithm to assess the potential effects of single or combined interventions on body weight[15]. By applying this approach, it is possible to quantify the population impact of a particular health intervention on childhood obesity when all children are exposed to the intervention. The overall aim of this paper was to estimate the impact of hypothetical behavioral interventions (separately and combined, with different adherence levels) at age 11 on the BMI of 13 year-olds, by applying g-computation (using the parametric g-formula) to longitudinal data

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Conclusion