MAXIMUM COST OF EFFICIENT WEIGHT-LOSS PROGRAMS FOR OVERWEIGHT AND OBESE POPULATIONS

To estimate economic and health benefit of different body-mass index reduction targets for overall overweight and obese populations as well as each age subgroup, we conducted a simulated trials over 10 years using Archimedes model based on representative sample of the US population. We also defined a Program-cost target measure to facilitate cost-effectiveness considerations in planning weight-loss programs. Our simulations predict that achieving weight loss targets would result in decreased cumulative for five obesity-related disorders, but that these benefits vary widely by subgroups and target effect. Older subgroups showed higher health benefit for the same BMI reduction target. Estimated PCT ranged from $18,119 to $99,893, with the highest PCT predicted for the subgroups (age 65-84) achieving sustained BMI reductions to 30 kg/m2, which implies the highest health value for the same cost. Our analysis predicts weight loss interventions targeted to high BMI elderly as the best relative value among the alternatives we considered. PCT is comprehensive enough for even academically untrained business/policy professionals to use, and may facilitate more CE evaluations and early stage program planning without the help of experts. Average costs of weight-loss interventions are much higher than PCTs estimated in this study, suggesting emerging smartphone/GPS-based exercise monitoring applications such as Nike+ Move® may be potentially efficient alternatives. Purpose (a): 1) To estimate economic and health benefit of different body-mass index (BMI) reduction targets for overall overweight and obese populations as well as each age subgroup 2) To define a Program-cost target (PCT) measure to facilitate cost-effectiveness considerations in planning weight-loss programs. Methods (b): Person-specific data from a representative sample of the US population (National Health and Nutrition Education Survey IV) was used to determine current population and characteristics of adults aged 30-84 years in the U.S. with BMI exceeding 25, and are candidates for different weight-reduction programs. We used the Archimedes modeling tool to create a simulated population matched to the current US population and simulate the 10-year aggregate effects of achieving three different weight-reduction targets among that population. We then compared economic and health benefits among different subgroups and reduction targets and to estimate the maximum intervention cost for which the program would remain cost effective. Results (c): Simulations predict that achieving weight loss targets would result in decreased cumulative for five obesity-related disorders, but that these benefits vary widely by subgroups and target effect. Predicted health benefits range from a net present value of 0.01 to 0.17 QALYs. Optimal relative results are predicted for programs that produce a sustained reduction of BMI level down to 25 kg/m2. Older subgroups showed higher health benefit for the same BMI reduction target. Estimated PCT ranged from $18,119 to $99,893, with the highest PCT predicted for the subgroups (age 65-84) achieving sustained BMI reductions to 30 kg/m2, which implies the highest health value for the same cost. Conclusions (d): We found substantial variation in program cost targets/value thresholds for weight loss/control interventions by population and effect; such investments will require careful targeting of interventions to appropriate populations. Our analysis predicts weight loss interventions targeted to high BMI elderly as the best relative value among the alternatives we considered. PCT is comprehensive enough for even academically untrained business/policy professionals to use, and may facilitate more CE evaluations and early stage program planning without the help of experts. Average costs of weight-loss interventions are much higher than PCTs estimated in this study, suggesting emerging smartphone/GPS-based exercise monitoring applications such as Nike+ Move® may be potentially efficient alternatives. CE of weight-loss interventions largely depend on population age and target BMI, which an optimal target should consider. Our PCT estimation showed that concentrating older subpopulations could maximize CE. Further studies should validate the statistical robustness of this approach and the practical bounds of its utility.