Cost-effectiveness analyses of weight loss programs for university students can inform administrator decision-making. This study quantifies and compares the costs and cost-effectiveness of implementing two digitally-delivered weight loss interventions designed… Click to show full abstract
Cost-effectiveness analyses of weight loss programs for university students can inform administrator decision-making. This study quantifies and compares the costs and cost-effectiveness of implementing two digitally-delivered weight loss interventions designed for university populations. Healthy Body Healthy U (HBHU) was a randomized controlled trial comparing TAILORED (personalized) versus TARGETED (generic) weight loss interventions adapted specifically for young adults to a CONTROL intervention. Participants (N = 459; 23.3 ± 4.4 years; mean BMI 31.2 ± 4.4 kg/m2) were recruited from two universities. Implementation costs were examined from a payer (i.e., university) perspective, comparing both the average cost effectiveness ratio (ACER) and the incremental cost effectiveness ratio (ICER) of the two interventions. Cost-effectiveness measures were calculated for changes in body weight, abdominal circumference, HDL cholesterol, systolic and diastolic blood pressure, and HbA1c. The overall 6-month implementation costs were $105.66 per person for the TAILORED intervention and $91.44 per person for the TARGETED intervention. The ACER for weight change was $107.82 for the TAILORED and $179.29 for the TARGETED interventions. The ICER comparing TAILORED with TARGETED for change in body weight was $5.05, and was even lower ($2.28) when including only those with overweight and not obesity. The ICERs for change in abdominal circumference, HDL cholesterol, systolic and diastolic blood pressure, and HbA1c were $3.49, $59.37, $1.57, $2.64, and $47.49, respectively. The TAILORED intervention was generally more cost-effective compared with the TARGETED intervention, particularly among those with overweight. Young adults with obesity may require more resource-intensive precision-based approaches.
               
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