Cost-Effectiveness and Cost-Utility of an Early Childhood Obesity Prevention Programme: Modelled Economic Evaluation of the Prevention of Overweight in Infancy (POI) Trial

Background: Evidence of cost-effectiveness of early childhood obesity prevention is scarce. Most childhood obesity prevention programs are, by necessity,conducted over a short time period without extended follow-up. As benefits from these programs will likely extend beyond the intervention period it is important for these to be captured in a corresponding CEA or CUA. Most published economic evaluations pertain to either trial-based cost-effectiveness analyses, or modelled economic evaluations that take a lifetime horizon and account only for healthcare costs and quality of life in later life. The Prevention of Overweight in Infancy (POI) was a 4-arm randomized controlled trial including sleep, nutrition and physical activity education delivered in the first 2 years of life. Children in the sleep intervention had significantly lower BMI-z scores at age 4 years whilst other arms of the trial had no significant effect.
Objective: To carry out modelled economic evaluation using individual-level data from POI conducted in New Zealand. As benefits from this program will likely extend beyond early childhood, we carried out cost-effectiveness and cost-utility over a child and adolescent time horizon.

Data and Methods: The economic evaluation used the EPOCH model, based on population-representative data from the Longitudinal Study of Australian Children, a published meta-analysis of the association between utility and weight status and national direct health care costs. We initialized the model with individual level data from children aged 4 years old from the sleep and control arms of POI. No persistent intervention effect was assumed, and simulations were run separately for the sleep and control groups to age 15 to determine mean BMI, QALYs and direct healthcare costs. The cost of delivering the sleep intervention was determined in 2018 Australian dollars using standard micro-costing techniques. Incremental cost-effectiveness ratios (ICERs) were determined, with costs and outcomes discounted at 5%.

Results: At age 15, the model predicted notable differences in BMI but only small QALY differences between the two groups. Simulated mean BMI in the sleep and control groups was 22.7kg/m2 (95% CI 22.2 – 23.2) and 23.2 kg/m2(95% CI 22.8 – 23.7) respectively, a difference of 0.54 units. Simulated mean QALYs in the sleep and control groups were 10.10 (95% CI 10.08 – 10.12) and 10.11 (95% CI 10.09 – 10.13) respectively, a difference of 0.01 QALYs. The mean cost of the sleep intervention was AUD$115 per child. Over the 11 years, mean total discounted costs (including intervention cost) were slightly higher at AUD$7,610 per child in the sleep group compared to AUD$7,528 per child in the control group. The ICERs were AUD$258 (US$161) per unit BMI avoided and AUD$8,930 (US$5,569) per QALY gained.

Conclusions: Despite the relatively small difference in QALYs between the two groups, the sleep intervention was highly cost-effective based on a nominal AUD$50,000/QALY threshold. Regarding ICER for BMI, the sleep intervention would appear to be more cost-effective than similar interventions in this age group using the same outcome, but willingness to pay thresholds are unknown. The strengths and weaknesses of using the two different outcome measures will be discussed.