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Behavioral interventions to reduce obesity for children: Low-intensity, in-person programs

Health Care: Obesity and Diabetes
Benefit-cost methods last updated December 2023.  Literature review updated December 2014.
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The behavioral interventions included in this analysis target obese and overweight youth under age 18, providing them with counseling, education, and other supports to improve diet, increase physical activity, and reduce weight. The programs use techniques designed to promote and sustain behavioral changes, including goal setting, self-monitoring, stimulus control, and other strategies.

The programs in this specific category provided less than 25 hours of face-to-face intervention.
For an overview of WSIPP's Benefit-Cost Model, please see this guide. The estimates shown are present value, life cycle benefits and costs. All dollars are expressed in the base year chosen for this analysis (2022). The chance the benefits exceed the costs are derived from a Monte Carlo risk analysis. The details on this, as well as the economic discount rates and other relevant parameters are described in our Technical Documentation.
Benefit-Cost Summary Statistics Per Participant
Benefits to:
Taxpayers $14 Benefits minus costs ($232)
Participants $7 Benefit to cost ratio ($0.20)
Others $30 Chance the program will produce
Indirect ($89) benefits greater than the costs 46%
Total benefits ($38)
Net program cost ($193)
Benefits minus cost ($232)

Meta-analysis is a statistical method to combine the results from separate studies on a program, policy, or topic in order to estimate its effect on an outcome. WSIPP systematically evaluates all credible evaluations we can locate on each topic. The outcomes measured are the types of program impacts that were measured in the research literature (for example, crime or educational attainment). Treatment N represents the total number of individuals or units in the treatment group across the included studies.

An effect size (ES) is a standard metric that summarizes the degree to which a program or policy affects a measured outcome. If the effect size is positive, the outcome increases. If the effect size is negative, the outcome decreases. See Estimating Program Effects Using Effect Sizes for additional information.

Adjusted effect sizes are used to calculate the benefits from our benefit cost model. WSIPP may adjust effect sizes based on methodological characteristics of the study. For example, we may adjust effect sizes when a study has a weak research design or when the program developer is involved in the research. The magnitude of these adjustments varies depending on the topic area.

WSIPP may also adjust the second ES measurement. Research shows the magnitude of some effect sizes decrease over time. For those effect sizes, we estimate outcome-based adjustments which we apply between the first time ES is estimated and the second time ES is estimated. We also report the unadjusted effect size to show the effect sizes before any adjustments have been made. More details about these adjustments can be found in our Technical Documentation.

Meta-Analysis of Program Effects
Outcomes measured Treatment age No. of effect sizes Treatment N Adjusted effect sizes(ES) and standard errors(SE) used in the benefit - cost analysis Unadjusted effect size (random effects model)
First time ES is estimated Second time ES is estimated
ES SE Age ES SE Age ES p-value
10 4 94 -0.201 0.143 10 0.000 0.070 12 -0.201 0.160
10 12 778 -0.148 0.054 10 0.000 0.101 12 -0.148 0.006
1In addition to the outcomes measured in the meta-analysis table, WSIPP measures benefits and costs estimated from other outcomes associated with those reported in the evaluation literature. For example, empirical research demonstrates that high school graduation leads to reduced crime. These associated measures provide a more complete picture of the detailed costs and benefits of the program.

2“Others” includes benefits to people other than taxpayers and participants. Depending on the program, it could include reductions in crime victimization, the economic benefits from a more educated workforce, and the benefits from employer-paid health insurance.

3“Indirect benefits” includes estimates of the net changes in the value of a statistical life and net changes in the deadweight costs of taxation.
Detailed Monetary Benefit Estimates Per Participant
Affected outcome: Resulting benefits:1 Benefits accrue to:
Taxpayers Participants Others2 Indirect3 Total
Obesity Labor market earnings associated with obesity $0 $0 $0 $0 $0
Health care associated with obesity $14 $6 $30 $7 $57
Mortality associated with obesity $0 $0 $0 $1 $1
Program cost Adjustment for deadweight cost of program $0 $0 $0 ($97) ($97)
Totals $14 $7 $30 ($89) ($38)
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Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $162 2014 Present value of net program costs (in 2022 dollars) ($193)
Comparison costs $0 2014 Cost range (+ or -) 25%
On average, these programs provide approximately nine contact hours over six months, including both group and individual sessions. The average per-participant cost of these programs was computed using contact hours and average Washington State 2014 hourly wages of the appropriate professionals who conducted the intervention (generally dietitians, nurses, general practitioners, or therapists).
The figures shown are estimates of the costs to implement programs in Washington. The comparison group costs reflect either no treatment or treatment as usual, depending on how effect sizes were calculated in the meta-analysis. The cost range reported above reflects potential variation or uncertainty in the cost estimate; more detail can be found in our Technical Documentation.
Benefits Minus Costs
Benefits by Perspective
Taxpayer Benefits by Source of Value
Benefits Minus Costs Over Time (Cumulative Discounted Dollars)
The graph above illustrates the estimated cumulative net benefits per-participant for the first fifty years beyond the initial investment in the program. We present these cash flows in discounted dollars. If the dollars are negative (bars below $0 line), the cumulative benefits do not outweigh the cost of the program up to that point in time. The program breaks even when the dollars reach $0. At this point, the total benefits to participants, taxpayers, and others, are equal to the cost of the program. If the dollars are above $0, the benefits of the program exceed the initial investment.

Citations Used in the Meta-Analysis

Balagopal, P., George, D., Yarandi, H., Funanage, V., & Bayne, E. (2005). Reversal of obesity-related hypoadiponectinemia by lifestyle intervention: a controlled, randomized study in obese adolescents. The Journal of Clinical Endocrinology and Metabolism, 90(11), 6192-7.

Danielsen, Y.S., Hordhus, I.H., Juliusson, P.B., Maehle, M., & Pallesen, S. (2013). Effect of a family-based cognitive behavioural intervention on body mass index, self-esteem and symptoms of depression in children with obesity (aged 7-13): A randomised waiting list controlled trial. Obesity Research and Clinical Practice, 7(16), e116-e128.

Epstein, L.H., Roemmich, J.N., Robinson, J.L., Paluch, R.A., Winiewicz, D.D., Fuerch, J.H., & Robinson, T.N. (2008). A randomized trial of the effects of reducing television viewing and computer use on body mass index in young children. Archives of Pediatrics & Adolescent Medicine, 162(3), 239-45.

Flodmark, C., Ohlsson, T., Rydén, O., & Sveger, T. (1993). Prevention of progression to severe obesity in a group of obese schoolchildren treated with family therapy. Pediatrics, 91(5), 880-884.

Golley, R.K., Magarey, A.M., Baur, L.A., Steinbeck, K.S., & Daniels, L.A. (2007). Twelve-month effectiveness of a parent-led, family-focused weight-management program for prepubertal children: a randomized, controlled trial. Pediatrics, 119(3), 517-525.

Janicke, D.M., Sallinen, B.J., Perri, M.G., Lutes, L.D., Huerta, M., Silverstein, J.H., & Brumback, B. (2008). Comparison of parent-only vs family-based interventions for overweight children in underserved rural settings: outcomes from project STORY. Archives of Pediatrics & Adolescent Medicine, 162(12), 1119-1125.

Kitzman-Ulrich, H., Hampson, R., Wilson, D.K., Presnell, K., Brown, A., & O'Boyle, M. (2009). An adolescent weight-loss program integrating family variables reduces energy intake. Journal of the American Dietetic Association, 109(3), 491-6.

Mårild, S., Gronowitz, E., Forsell, C., Dahlgren, J., & Friberg, P. (2013). A controlled study of lifestyle treatment in primary care for children with obesity. Pediatric Obesity, 8(3), 207-217.

McCallum, Z., Wake, M., Gerner, B., Baur, L. A., Gibbons, K., Gold, L. ... Waters, E. (2007). Outcome data from the LEAP (Live, Eat and Play) trial: A randomized controlled trial of a primary care intervention for childhood overweight/mild obesity. International Journal of Obesity, 31, 630-636.

O'Connor, T.M., Hilmers, A., Watson, K., Baranowski, T., & Giardino, A.P. (2013). Feasibility of an obesity intervention for paediatric primary care targeting parenting and children: Helping HAND. Child: Care, Health and Development, 39(1), 141-149.

Rocchini, A.P., Katch, V., Anderson, J., Hinderliter, J., Becque, D., Martin, M., & Marks, C. (1988). Blood pressure in obese adolescents: effect of weight loss. Pediatrics, 82(1), 16-23.

Senediak, C., & Spence, S. H. (1985). Rapid versus gradual scheduling of therapeutic contact in a family based behavioural weight control programme for children. Behavioural Psychotherapy, 13, 265-287.

Taveras, E.M., Gortmaker, S.L., Hohman, K.H., Horan, C.M., Kleinman, K.P., Mitchell, K., Price, S., ... Gillman, M.W. (2011). Randomized controlled trial to improve primary care to prevent and manage childhood obesity: the High Five for Kids study. Archives of Pediatrics & Adolescent Medicine, 165(8), 714-22.

Wake, M. B., Baur, L.A., Gerner, B., Gibbons, K. Gold, L., Gunn, J., ... Ukoumunne, O.C. (2009). Outcomes and costs of primary care surveillance and intervention for overweight or obese children: The LEAP 2 randomised controlled trial. BMJ, 339:b3308, doi. 10.1136/bmj.b3308.

West, F., Sanders, M. R., Cleghorn, G. J., & Davies, P. S. W. (2010). Randomised clinical trial of a family-based lifestyle intervention for childhood obesity involving parents as the exclusive agents of change. Behaviour Research and Therapy, 48(12), 1170-1179.