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Interventions to prevent excessive gestational weight gain (general population)

Health Care: Maternal and Infant Health
Benefit-cost estimates updated May 2017.  Literature review updated December 2016.
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A wide range of programs aim to prevent excessive gestational weight gain. We included programs that offer an exercise class and programs that offer counseling on recommended weight gain during pregnancy. Typically athletic trainers lead exercise programs in groups and counseling is delivered one-on-one in a clinical setting by a health educator, midwife, or obstetrician. Counseling ranged from one to nine sessions.
BENEFIT-COST
META-ANALYSIS
CITATIONS
The estimates shown are present value, life cycle benefits and costs. All dollars are expressed in the base year chosen for this analysis (2016). 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 $119 Benefits minus costs ($1,112)
Participants ($133) Benefit to cost ratio ($5.03)
Others $183 Chance the program will produce
Indirect ($1,097) benefits greater than the costs 36 %
Total benefits ($928)
Net program cost ($184)
Benefits minus cost ($1,112)
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
Benefits from changes to:1 Benefits to:
Taxpayers Participants Others2 Indirect3 Total
Labor market earnings associated with diabetes ($4) ($8) $0 $0 ($12)
Health care associated with Cesarean sections $45 $2 $45 $22 $114
Health care associated with preterm births ($11) $0 ($11) ($6) ($28)
Subtotals $30 ($6) $34 $17 $74
From secondary participant
Infant mortality ($60) ($133) $0 ($1,097) ($1,289)
Health care associated with preterm births ($90) ($4) ($90) ($44) ($227)
Health care associated with NICU admissions $239 $10 $239 $119 $606
Subtotals $89 ($127) $149 ($1,022) ($910)
Adjustment for deadweight cost of program $0 $0 $0 ($92) ($92)
Totals $119 ($133) $183 ($1,097) ($928)
Detailed Annual Cost Estimates Per Participant
Annual cost Year dollars Summary
Program costs $182 2015 Present value of net program costs (in 2016 dollars) ($184)
Comparison costs $0 2015 Cost range (+ or -) 50 %
The length of these interventions vary from a single session up to seven months. The average per-participant cost was calculated by multiplying the number of staff hours per participant by the average 2015 salary of the staff member as reported by the Bureau of Labor Statistics (http://www.bls.gov/oes/current/oes_wa.htm#29-0000). We multiplied the average salary by 1.441 to estimate the total staff costs including benefits.
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.
Estimated Cumulative Net Benefits Over Time (Non-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 non-discounted dollars to simplify the “break-even” point from a budgeting perspective. 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.

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

***We report this outcome twice: once for mothers (designated as the primary participant) and once for infants (designated as the secondary participant). We do this because the outcome is associated with costs and benefits for both mothers and infants, and the amount of the cost or benefit is different for mothers than it is for infants.

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.

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 Primary or secondary participant 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
Blood pressure^ Primary 2 468 -0.461 0.189 31 0.000 0.000 32 -0.461 0.015
Cesarean sections Primary 5 1054 -0.081 0.102 31 0.000 0.000 32 -0.081 0.425
Excess gestational weight gain^ Primary 10 1172 -0.184 0.052 31 0.000 0.000 32 -0.184 0.001
Gestational diabetes^ Primary 5 621 -0.256 0.120 31 0.000 0.000 32 -0.256 0.033
Low birthweight births*** Primary 4 719 0.025 0.070 31 0.000 0.000 32 0.025 0.722
Preeclampsia^ Primary 3 706 -0.009 0.136 31 0.000 0.000 32 -0.009 0.945
Preterm birth (< 37 weeks)*** Primary 6 1247 0.070 0.066 31 0.000 0.000 32 0.070 0.287
Weight change Primary 2 148 0.048 0.117 31 0.000 0.000 32 0.048 0.682
Low birthweight births*** Secondary 4 719 0.025 0.070 1 0.000 0.000 2 0.025 0.722
Macrosomia (birth weight > 4000g)^ Secondary 7 1272 -0.131 0.111 1 0.000 0.000 2 -0.131 0.239
NICU admission Secondary 1 421 -0.135 0.327 1 0.000 0.000 2 -0.135 0.680
Preterm birth (< 37 weeks)*** Secondary 6 1247 0.070 0.066 1 0.000 0.000 2 0.070 0.287

Citations Used in the Meta-Analysis

Althuizen, E., Wijden, C.L.V.D., Mechelen, W.V., Seidell, J.C., & Poppel, M.N.M.V. (2012). The effect of a counseling intervention on weight changes during and after pregnancy: a randomised trial. BJOG: an International Journal of Obstetrics & Gynecology, 120(1), 92-99.

Barakat, R., Lucia, A., & Ruiz, J.R. (2009). Resistance exercise training during pregnancy and newborn's birth size: a randomised controlled trial. International Journal of Obesity, 33(9), 1048-1057.

Barakat, R., Pelaez, M., Lopez, C., Lucia, A., & Ruiz, J.R. (2013). Exercise during pregnancy and gestational diabetes-related adverse effects: a randomised controlled trial. British Journal of Sports Medicine, 47(10), 630-36.

Haakstad, L.A.H., & Bø, K. (2011). Effect of regular exercise on prevention of excessive weight gain in pregnancy: A randomised controlled trial. The European Journal of Contraception and Reproductive Health Care, 16(2), 116-125.

Hui, A.L., Ludwig, S.M., Gardiner, P., Sevenhuysen, G., Murray, R., Morris, M., & Shen, G.X. (2006). Community-based exercise and dietary intervention during pregnancy: A pilot study. Canadian Journal of Diabetes, 30(2), 169-175.

Hui, A.L., Back, L., Ludwig, S., Gardiner, P., Sevenhuysen, G., Dean, H.J., . . . Shen, G.X. (2014). Effects of lifestyle intervention on dietary intake, physical activity level, and gestational weight gain in pregnant women with different prepregnancy Body Mass Index in a randomized control trial. BMC Pregnancy and Childbirth, 14(1), 331-40.

Olson, C.M., Strawderman, M.S., & Reed, R.G. (2004). Efficacy of an intervention to prevent excessive gestational weight gain. American Journal of Obstetrics and Gynecology, 191(2), 530-536.

Polley, B.A., Wing, R.R., & Sims, C.J. (2002). Randomized controlled trial to prevent excessive weight gain in pregnant women. International Journal of Obesity, 26(11), 1494-1502.

Ronnberg, A.K., Ostlund, I., Fadl, H., Gottvall, T., & Nilsson, K. (2015). Intervention during pregnancy to reduce excessive gestational weight gain-a randomised controlled trial. BJOG: an International Journal of Obstetrics & Gynaecology, 122(4), 537-544.

Ruiz, J.R., Perales, M., Pelaez, M., Lopez, C., Lucia, A., & Barakat, R. (2013). Supervised exercise-based intervention to prevent excessive gestational weight gain: a randomized controlled trial. Mayo Clinic Proceedings, 88(12), 1388- 97.

Smith, K.M. (2014). The Blossom Project Online: Use of a behaviorally-based website to promote physical activity and prevent excessive gestational weight gain in previously sedentary pregnant women. Digital Repository @ Iowa State University.

Stafne, S.N., Salvesen, K.A., Romundstad, P.R., Eggebø, T.M., Carlsen, S.M., & Mørkved, S. (2012). Regular exercise during pregnancy to prevent gestational diabetes: a randomized controlled trial. Obstetrics and Gynecology, 119(1), 29- 36.

For more information on the methods
used please see our Technical Documentation.
360.664.9800
institute@wsipp.wa.gov