• Article

The economic power of lower protein infant formula for the children of overweight and obese mothers


Marsh, K., Moller, J., Basarir, H., Orfanos, P., & Detzel, P. (2016). The economic power of lower protein infant formula for the children of overweight and obese mothers. Nutrients, 8(1), [18]. DOI: 10.3390/nu8010018


The global prevalence of obesity is rising rapidly, highlighting the importance of understanding risk factors related to the condition. Childhood obesity, which has itself become increasingly prevalent, is an important predictor of adulthood obesity. Studies suggest that the protein content consumed in infanthood is an important predictor of weight gain in childhood, which may contribute to higher body mass index (BMI). For instance, there is evidence that a lower protein infant formula (lpIF) for infants of overweight or obese mothers can offer advantages over currently-used infant formulas with regard to preventing excessive weight gain. The current study used health economic modelling to predict the long-term clinical and economic outcomes in Mexico associated with lpIF compared to a currently-used formula. A discrete event simulation was constructed to extrapolate the outcomes of trials on the use of formula in infanthood to changes in lifetime BMI, the health outcomes due to the changes in BMI and the healthcare system costs, productivity and quality of life impact associated with these outcomes. The model predicts that individuals who receive lpIF in infancy go on to have lower BMI levels throughout their lives, are less likely to be obese or develop obesity-related disease, live longer, incur fewer health system costs and have improved productivity. Simulation-based economic modelling suggests that the benefits seen in the short term, with the use of lpIF over a currently-used formula, could translate into considerable health and economic benefits in the long term. Modelling over such long timeframes is inevitably subject to uncertainty. Further research should be undertaken to improve the certainty of the model.