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Behavioral interventions to reduce obesity for adults: High-intensity, in-person programs

Healthcare: Obesity and Diabetes
Benefit-cost methods last updated December 2024.  Literature review updated December 2014.
This program was archived December 2024.
Behavioral interventions for obesity include behavioral counseling, therapy, and educational components, and often include diet and exercise components as well. For this review of interventions for obese adults, we excluded studies that targeted diabetic populations as well as those aimed at preventing obesity.
Programs in this specific category are delivered to obese adults, and conducted face-to-face, with 12 or more sessions a year for 12 months or more.
 
ALL
BENEFIT-COST
META-ANALYSIS
CITATIONS
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 2023 Technical Documentation.
Benefit-Cost Summary Statistics Per Participant
Benefits to:
Taxpayers $680 Benefits minus costs $1,723
Participants $1,282 Benefit to cost ratio $3.34
Others $351 Chance the program will produce
Indirect $145 benefits greater than the costs 61%
Total benefits $2,458
Net program cost ($735)
Benefits minus cost $1,723

^WSIPP’s benefit-cost model does not monetize this outcome.

Meta-analysis is a statistical method to combine the results from separate studies on a program, policy, or topic to estimate its effect on an outcome. WSIPP systematically evaluates all credible evaluations we can locate on each topic. The outcomes measured are the program impacts measured in the research literature (for example, impacts on 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 on how we estimate effect sizes.

The effect size may be adjusted from the unadjusted effect size estimated in the meta-analysis. Historically, WSIPP adjusted effect sizes to some programs based on the methodological characteristics of the study. For programs reviewed in 2024 or later, we do not make additional adjustments, and we use the unadjusted effect size whenever we run a benefit-cost analysis.

Research shows the magnitude of effects may change 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. More details about these adjustments can be found in our 2023 Technical Documentation.

Meta-Analysis of Program Effects
Outcomes measured Treatment age No. of effect sizes Treatment N 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
Weight change
Loss or gain of total body weight
 50 12 2070 -0.174 0.050 50 0.000 0.012 55 -0.174 0.001
Diastolic blood pressure^
The blood pressure in the arteries when the heart rests between beats. This is the second (or bottom) number in a blood pressure reading.
 50 8 1641 -0.340 0.165 50 n/a n/a n/a -0.340 0.040
Systolic blood pressure^
The blood pressure in the arteries when the heart beats. This is the first (or top) number in a blood pressure reading.
 50 8 1641 -0.123 0.047 50 n/a n/a n/a -0.123 0.009
HDL cholesterol^
“Good cholesterol” that is associated with lower risk of cardiovascular disease.
 50 7 986 0.049 0.051 50 n/a n/a n/a 0.049 0.343
LDL cholesterol^
“Bad cholesterol” that is associated with higher risk of cardiovascular disease.
 50 7 986 -0.011 0.051 50 n/a n/a n/a -0.011 0.827
Obesity
Obese based on clinical guidelines for adults (body mass index of 30 or higher) or children (body mass index at or above the 95th percentile for children of the same age and sex), as appropriate.
50 9 1357 -0.238 0.087 50 0.000 0.086 55 -0.238 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 $499 $1,175 $0 $0 $1,674
Health care associated with obesity $168 $76 $351 $84 $679
Mortality associated with obesity $13 $30 $0 $428 $472
Program cost Adjustment for deadweight cost of program $0 $0 $0 ($367) ($367)
Totals $680 $1,282 $351 $145 $2,458
Click here to see populations selected
Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $313 2014 Present value of net program costs (in 2022 dollars) ($735)
Comparison costs $0 2014 Cost range (+ or -) 25%
On average, these programs provide approximately 52 contact hours over 24 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 2023 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

Appel, L.J., Clark, J.M., Yeh, H.C., Wang, N.Y., Coughlin, J.W., Daumit, G., Miller, E.R., Dalcin, A., Jerome, G., Geller, S., Noronha, G., Pozefsky, T., Charleston, J., Reynolds., Durkin, N., Rubin, R., Louis, T.A., & Brancati, F.L. (2011). Comparative effectiveness of weight-loss interventions in clinical practice. The New England Journal of Medicine, 365(21), 1959-1968.

Burke, V., Beilin, L.J., Cutt, H.E., Mansour, J., Wilson, A., & Mori, T.A. (2005). Effects of a lifestyle programme on ambulatory blood pressure and drug dosage in treated hypertensive patients: a randomized controlled trial. Journal of Hypertension, 23(6), 1241-1249.

de Vos, B.C., Runhaar, J., & Bierma-Zeinstra, S.M. (2014). Effectiveness of a tailor-made weight loss intervention in primary care. European Journal of Nutrition, 53(1), 95-104.

Eriksson, M.K., Franks, P.W., & Eliasson, M. (2009). A 3-year randomized trial of lifestyle intervention for cardiovascular risk reduction in the primary care setting: the Swedish Björknäs study. Plos One, 4(4), e5195.

Fitzgibbon, M.L., Stolley, M.R., Schiffer, L., Sharp, L.K., Singh, V., & Dyer, A. (2010). Obesity reduction black intervention trial (ORBIT): 18-month results. Obesity, 18(12), 2317-2325.

Jeffery, R.W., Wing, R.R., Thorson, C., Burton, L.R., Raether, C., Harvey, J., & Mullen, M. (1993). Strengthening behavioral interventions for weight loss: a randomized trial of food provision and monetary incentives. Journal of Consulting and Clinical Psychology, 61(6), 1038-1045.

Kumanyika, S.K., Fassbender, J.E., Sarwer, D.B., Phipps, E., Allison, K.C., Localio, R., Morales, K.H., Wesby, L., Harralson, T., Kessler, R., Tan-Torres, S., Han, X., Tsai, A.G., & Wadden, T.A. (2012). One-year results of the Think Health! study of weight management in primary care practices.Obesity, 20(6), 1249-1257.

The Trials of Hypertension Collaborative Research Group (1997). Effects of Weight Loss and Sodium Reduction Intervention on Blood Pressure and Hypertension Incidence in Overweight People With High-Normal Blood Pressure. Archives of Internal Medicine, 157(6), 657-667.

Ross, R., Lam, M., Blair, S.N., Church, T.S., Godwin, M., Hotz, S.B., Johnson, A., Katzmarzyk, P.T., Levesque, L. & MacDonald, S. (2012). Trial of prevention and reduction of obesity through active living in clinical settings: a randomized controlled trial. Archives of Internal Medicine, 172(5), 414-424.

Silva, M.N., Vieira, P.N., Coutinho, S.R., Minderico, C.S., Matos, M.G., Sardinha, L.B., & Teixeira, P.J. (2010). Using self-determination theory to promote physical activity and weight control: a randomized controlled trial in women. Journal of Behavioral Medicine, 33(2), 110-122.

Vetter, M.L., Wadden, T.A., Chittams, J., Diewald, L.K., Panigrahi, E., Volger, S., Sarwer, D.B., & Moore, R.H.. (2013). Effect of lifestyle intervention on cardiometabolic risk factors: results of the POWER-UP trial. International Journal of Obesity, 37(1), 19-24.

Villareal, D.T., Shah, K., Banks, M.R., Sinacore, D.R., & Klein, S. (2008). Effect of weight loss and exercise therapy on bone metabolism and mass in obese older adults: a one-year randomized controlled trial. The Journal of Clinical Endocrinology and Metabolism, 93(6), 2181-2187.

Wadden, T.A., Volger, S., Sarwer, D.B., Vetter, M.L., Tsai, A.G., Berkowitz, R.I., Kumanyika, S., Schmitz, K.H., Diewald, L.K., Barg, R., Chittams, J., & Moore, R.H. (2011). A two-year randomized trial of obesity treatment in primary care practice. The New England Journal of Medicine, 365(21), 1969-1979.

Wood, P.D., Stefanick, M.L., Williams, P.T., & Haskell, W.L. (1991). The effects on plasma lipoproteins of a prudent weight-reducing diet, with or without exercise, in overweight men and women. The New England Journal of Medicine, 325(7), 461-466.

Woollard, J., Burke, V., Beilin, L.J., Verheijden, M., & Bulsara, M.K. (2003). Effects of a general practice-based intervention on diet, body mass index and blood lipids in patients at cardiovascular risk. Journal of Cardiovascular Risk, 10(1), 31-40.