BACKGROUND
There is great interest in understanding whether interventions on sugar-sweetened beverage (SSB) consumption through pregnancy and early childhood affect adolescent body mass index (BMI). Without data from randomised trials, unbiased estimation of such effects might be achieved with observational data given sufficient and appropriate adjustment for both baseline and time-varying confounders.
OBJECTIVES
To illustrate the use of inverse probability (IP) weighting of marginal structural models (MSM) for estimating the effects of SSB consumption through pregnancy and early childhood on the mean early adolescent BMI z-score.
METHODS
Our baseline sample consisted of 1584 pregnant women from a pre-birth cohort. We defined 6 intervention intervals: early pregnancy, late pregnancy, 3, 4, 5, and 6 years. We fitted a MSM via a weighted linear regression with IP exposure and censoring weights to estimate the mean difference in BMI z-score under interventions: "maintain SSB consumption below (vs above) 0.5 servings/day in all intervals."
RESULTS
The estimated difference in mean BMI z-score under interventions maintaining SSB consumption at or below (vs above) 0.5 servings/day from pregnancy to 6 years was -0.94 (95% confidence interval [CI] -1.52, -0.08). The effect estimate in pregnancy, while fixing the exposure range in childhood, was -0.05 (95% CI -0.34, 0.23), and in early childhood, while fixing the range in pregnancy was -0.89 (95% CI -1.46, -0.11). The effect estimates were largely unchanged under sensitivity analyses to different implementation choices except for the choice of time interval length.
CONCLUSIONS
Under assumptions that include no unmeasured confounding and selection bias, and no model misspecification, results of this IP weighting application are in line with a lower mean BMI z-score in early adolescence under interventions ensuring lower, vs greater, SSB consumption in early life. This application provides a resource for researchers working with longitudinal birth cohort studies and interested in similar causal questions.