Cost-benefit analysis to address runaway health care expenditures through lifestyle modification recommendations

The cost of health care in the United States has been increasing at an annual rate of 9.8%, faster than the cost of living, since 1970. This is due to many factors, the most significant being preventable and manageable chronic conditions and diseases, known as comorbidities. These comorbidities are associated with individuals who classify as being overweight or obese, representing 68% of the United States population. This creates a strain on the health care system and the economy. Decreasing the number of overweight or obese individuals is necessary to reduce the prevalence of weight-related comorbidities. This can be accomplished through establishing and maintaining the proper energy balance between caloric intake and physical activity. The government leads many efforts to educate individuals on the importance of incorporating nutrition and physical activity. Since limited budgets for encouraging participation exist, a need exists for a system designed to assist policy makers in determining which age cohorts, or groups, given a level of adherence to recommendations, would result in the most benefit to stakeholders. An analysis was conducted to determine which 10-year age cohort(s) should be targeted for health promotion in efforts to reduce the prevalence of overweight and obese individuals. Each age cohort's participation and predicted weight loss was simulated using a validated weight prediction model. Weight loss resulted from partial cohort adherence to nutritional and physical activity recommendations. Design Alternatives were evaluated on effectiveness, determined by weight loss The analysis showed that if 30, 60, or 90 percent of a given cohort adhered to government recommendations, the 60-year age cohorts' outcome would result in the greatest benefit for the smallest cost. The remaining alternatives were ranked based on their cost benefit. A sensitivity analysis was conducted to determine if the results were sensitive to changes of the importance of the benefit measures. The results demonstrated that the 60-year age cohort was the best alternative in all cases.