Research

The cost-effectiveness of a school-based overweight program

Henry Shelton Brown17*, Adriana Pérez2, Yen-Peng Li3, Deanna M Hoelscher47, Steven H Kelder57 and Roberto Rivera6

Author Affiliations

1 Division of Management, Policy and Community Health, University of Texas School of Public Health, Austin, TX 78701, USA

2 Department of Bioinformatics and Biostatistics School of Public Health and Information Sciences University of Louisville 555 S. Floyd Street, Suite 4026 Louisville, KY 40292, USA

3 Division of Biostatistics, University of Texas School of Public Health, Houston, TX 77225, USA

4 Division of Behavioral Science, University of Texas School of Public Health, Austin, TX 78701, USA

5 Division of Epidemiology, University of Texas School of Public Health, Austin, TX 78701, USA

6 Valley Baptist Hospital, Harlingen, TX 78520, USA

7 Michael & Susan Dell Center for Advancement of Healthy Living, University of Texas School of Public Health, Austin, TX 78701, USA

For all author emails, please log on.

International Journal of Behavioral Nutrition and Physical Activity 2007, 4:47  doi:10.1186/1479-5868-4-47

 Received: 26 January 2007 Accepted: 1 October 2007 Published: 1 October 2007

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background

This study assesses the net benefit and the cost-effectiveness of the Coordinated Approach to Child Health (CATCH) intervention program, using parameter estimates from the El Paso trial. There were two standard economic measures used. First, from a societal perspective on costs, cost-effectiveness ratios (CER) were estimated, revealing the intervention costs per quality-adjusted life years (QALYs) saved. QALY weights were estimated using National Health Interview Survey (NHIS) data. Second, the net benefit (NB) of CATCH was estimated, which compared the present value of averted future costs with the cost of the CATCH intervention. Using National Health and Nutrition Examination Survey I (NHANES) and NHANES follow-up data, we predicted the number of adult obesity cases avoided for ages 40–64 with a lifetime obesity progression model.

Results

The results show that CATCH is cost-effective and net beneficial. The CER was US$900 (US$903 using Hispanic parameters) and the NB was US$68,125 (US$43,239 using Hispanic parameters), all in 2004 dollars. This is much lower than the benchmark for CER of US$30,000 and higher than the NB of US$0. Both were robust to sensitivity analyses.

Conclusion

Childhood school-based programs such as CATCH are beneficial investments. Both NB and CER declined when Hispanic parameters were included, primarily due to the lower wages earned by Hispanics. However, both NB and CER for Hispanics were well within standard cost-effectiveness and net benefit thresholds.

Background

Childhood overweight is a major threat to child health in the US [1]. Unfortunately, overweight children are not likely to return to normal weight later in life [2-4]. Aside from the correlation of lifetime behaviors [5], treatment strategies for obese adults remain largely ineffective [6-11]. Obesity in adulthood is closely associated with chronic diseases including cardiovascular disease (CVD), type 2 diabetes, high blood pressure, stroke, high blood cholesterol levels, joint problems, some cancers, and gall bladder disease [12-15]. The prevalence of overweight [1] among children has doubled in the last twenty years [16], disproportionately affecting minorities [17-20].

Because no other institution has as much continuous and intensive contact with children, schools can provide a pivotal role in physical activity and nutrition interventions. Further, school programs can be delivered at low cost to families, reaching all socioeconomic levels. A number of school-based interventions aimed at promoting healthy behaviors have been evaluated for effectiveness in terms of outcomes in the last 15 years [21-30]. Of all these programs, two stand out among the rest because of their sophisticated study design (Coordinated Approach to Child Health (CATCH)) and program impact on childhood overweight (Planet Health). Given that there are relatively few dollars for overweight prevention, comparisons between alternative prevention programs are warranted [31].

Labor productivity costs (indirect costs)

Equations (5, 6, and 7) in the appendix were used to estimate labor productivity costs. In order to estimate labor productivity costs averted, we estimated the number of sick days missed per year by obese adults in comparison to non-obese adults for persons aged 40–64, inclusive, or from the age of 40 until the person turns 65 years of age. We used median wages to place values on the lost time due to obesity-related illnesses for persons aged 40–64, inclusive. We also estimated the number of lost sick days for the obese and the non-obese using Poisson regression. The model controlled for age, age 40–64, smoking status, Hispanic ethnicity, and gender.

In addition to increased sick days, obese adults also have reduced life expectancy. Therefore, to assume that people aged 40 will live and work until they turn 65 years old would be to over-estimate labor productivity losses averted because more obese 40 year olds will die before 65 than non-obese 40 year olds. Therefore, life expectancy and mortality for obese and non-obese 40-year olds who die before 65 were calculated. We also estimated the life expectancy for those alive at 40 who die before 65 by gender for obese adults and for non-obese adults.

Data

In order to project lost work days, we used 2002 National Health Interview Survey (NHIS) data. Because of the complex sampling design of the NHIS data, we estimated the model with STATA 7.0©, again using the 'svy' feature. As seen in Table 3, we included overall costs of work-loss estimates and Hispanic costs of work-loss estimates.

Peeters et al. created life tables for both men and women by obesity status based on Framingham data [51]. Thus, we were able to project the life expectancy at 40 for an obese person conditional on dying before 65 years of age.

In order to place a value on the sick days averted in our net benefit analysis, we used U.S. Department of Labor, Bureau of Labor Statistics Current Population Survey data [52]. The data are for full-time workers only above 25 years of age for all workers, above 16 years of age for Hispanics. The median wage data is reported by week only. Therefore, in order to estimate the daily wage, the weekly wage was divided by five; in order to calculated the yearly wage, the weekly wage was multiplied by 52.

Equation (4) in the appendix was used to estimate QALYs. QALYs in our context are the additional quality-adjusted life-years gained through avoiding adult obesity. Activity scales were used in QALY to weight, or quality-adjust, years of life that may be added due to the intervention based on questions regarding their activity limitations, if any, and perceived health status [53]. In our study, we estimated scales using the Centers for Disease Control and Prevention's activity scale matrix using 2002 NHIS data. Depending on a person's answer to NHIS survey questions, a health state value is assigned ranging from 0.10 (limited with poor health) up to 1.00 (no limitation with excellent health).

Data

NHIS survey questions on self-assessed health and activity limitations were used. We again used life tables due to Peeters et al. to project the life expectancy at 40 for an obese person [51].

Sensitivity analysis

In order to determine the extent to which our results are dependent on the parameters we used, sensitivity analysis was conducted for both overall parameters and with parameters for Hispanics. All 48 parameters used in the analysis in Tables 2 and 4 were included in the sensitivity analysis (the Hispanic parameters in the lower part of Table 4 replace the corresponding parameters in the upper part of the table). In order to avoid the problems of the infinite support in the normal distribution, the triangular distribution, which has a finite support, was assumed. The support of the triangular distribution was created from the 95th percentile confidence intervals of our 48 parameters. We conducted 1,000 independent simulations trials. Each simulation trial draws were made for each of the 48 parameters simultaneously, and CER and NB calculated (see Table 5). Separate simulations, using the same method as above, were conducted for each of the 48 parameters, holding the other 47 parameters constant.

Table 4. Sensitivity Analysis

Table 5. Parameters Used in the Sensitivity Analysis†

Results

The results are shown below in Table 3. As noted earlier, the generally accepted conservative threshold is US$30,000 per QALY gained [43-45]. Notice that when overall parameters are used and lifetime medical costs are used, the CER was US$900 in 2004 dollars. This indicates that the intervention is cost-effective. When Hispanic parameters are used, the CER remains very low at US$903. NB was also quite high, meaning that CATCH is a good investment of public resources. In this case, using Hispanic parameters for QALYs, labor productivity, and median wages reduced the NB by approximately one-third. This is mainly due to the lower wages that Hispanics earn. When the higher medical costs used in Wang et al. [35] are used, the NB rose to US$83,368.

From our calculations based on Oster et al. [49], the lifetime medical cost differential for obese males 35–64 years old and non-obese males was US$9,716 while the difference for an obese woman 35–64 years old and a non-obese woman was US$11,086 [49]. In present value terms, using a 3% interest rate, the difference in lifetime medical costs for obese men versus non-obese men was US$4,123 and for women the difference was US$4,704, as seen in Table 3.

The sensitivity analysis revealed that in all cases, the intervention remained cost-effective and net beneficial. To ensure the robustness of our results, we also varied the rate of discount. Not surprisingly, the greater the future was discounted, the lower the NB and CER. Still, even when the rate of discount was five percent, CATCH remained cost-effective and net beneficial.

Discussion

There is a dearth of economic research on the value of school-based health promotions for the Hispanic population. The results here are the first to indicate that these programs are net beneficial and cost-effective. This is despite the lower wages earned by Hispanics, which means that the value of averted labor costs is lower.

CATCH compares favorably to alternative school-based health promotions. Wang et al. [35] estimated Planet Health's cost-effectiveness ratio to be US$5,166 per QALY (2004 dollars). When the medical costs used by Wang et al. [35] to evaluate Planet Health are used to evaluate CATCH (recall that this necessitated substituting female medical costs for males), the CER of CATCH decreased to US$0 for both the overall estimate and estimate based on Hispanic parameters (This is referred to as a cost saving result). However, note that Planet Health is cost-effective.

Wang et al. [35] estimated Planet Health's cost-effectiveness ratio to be US$8,776 (2004 dollars). Although Planet health is clearly net beneficial, it is less so than CATCH. This is mainly due to the fact that in the CATCH trial, there were averted overweight and at-risk boys which lead to averted obese males. Therefore, because males earn higher wages than females, the NBs were higher for males Conclusion This is the second study of the cost-effectiveness of a school-based intervention for programs targeting childhood obesity. The CER for CATCH was US$900. Further, when we used the medical costs used in Wang et al. (see II. Cost-effectiveness ratio in Table 3) [35], the CER decreased to US$0. Both estimates are well underneath the US$30,000 threshold value [43-45] of a human life-year. Our sensitivity analysis reveals that the results are robust.

With the growth of the Hispanic population in the United States, school-based overweight programs that are cost-effective for this population will be increasingly important. CER was US$903 when Hispanic parameters were used. The N B was US$69,764. Therefore, this study confirms that school-based overweight programs such as CATCH are both cost-effective and net beneficial in Hispanic populations.

Wang et al. estimated Planet Health's cost-effectiveness ratio to be US$4,305 per QALY (US$5,166 in 2004 dollars) However, note that there were many different parameters used in our study, necessitated by the fact that the CATCH trial was successful in curbing the prevalence of both boys and girls at-risk for overweight and overweight, whereas Planet Health only curbed girl overweight prevalence. Both programs are easily under any CER threshold.

There are limitations of this study. First, we are forced to project of adult obesity cases averted. Future medical technology or other changes mean that obesity rates may decline in the future, our sensitivity analysis allows to vary. One of the strengths of our approach is that our results are robust to changes in our estimates.

A second limitation is the lack of availability of medical cost estimates for obese males 40–64.

Despite the limitations of the study, the results show that an expansion of CATCH and/or similar school-based health promotion interventions would aid in limiting overweight prevalence in a cost-effective and net beneficial manner. Thus, public health efforts should focus on the implementation of school-based programs as an effective means of prevention of overweight, by advocating policy efforts such as mandates for health promotion in Texas, as well as convincing educators and administrators that their school-based obesity prevention programs are as essential to society as their academic programs.

Appendix

Q = { i M n i S n i [ 1 r 1 r ( 1 + r ) L n i ] i M o i S o i [ 1 r 1 r ( 1 + r ) L o i ] + [ i ( 1 M n i ) S n i ( 1 M o i ) S o i ] [ 1 r 1 r ( 1 + r ) 25 ] } ( 1 + r ) 29 MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacH8akY=wiFfYdH8Gipec8Eeeu0xXdbba9frFj0=OqFfea0dXdd9vqai=hGuQ8kuc9pgc9s8qqaq=dirpe0xb9q8qiLsFr0=vr0=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@A294@ (4)

where

Sni = Activity scale for non-obese by gender

Soi = Activity scale for obese by gender

Mni = Death probability 40–64 for non-obese by gender

Moi = Death probability 40–64 for obese by gender

Lni = Life expectancy for non-obese 40 who die by 65 by gender

Loi = Life expectancy for obese 40 who die by 65 by gender

r = the rate of discount

Productivity

B1 + B2 = B(5)

B 1 = W d i { M o i D o i [ 1 r 1 r ( 1 + r ) L o i ] M n i D n i [ 1 r 1 r ( 1 + r ) L n i ] + [ ( 1 M o i ) D o i ( 1 M n i ) D n i ] [ 1 r 1 r ( 1 + r ) 25 ] } ( 1 + r ) 29 MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacH8akY=wiFfYdH8Gipec8Eeeu0xXdbba9frFj0=OqFfea0dXdd9vqai=hGuQ8kuc9pgc9s8qqaq=dirpe0xb9q8qiLsFr0=vr0=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@9D2F@ (6)

B 2 = W y i { M n i [ 1 r 1 r ( 1 + r ) L n i ] M o i [ 1 r 1 r ( 1 + r ) L o i ] + ( M o i M n i ) [ 1 r 1 r ( 1 + r ) 25 ] } ( 1 + r ) 29 MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacH8akY=wiFfYdH8Gipec8Eeeu0xXdbba9frFj0=OqFfea0dXdd9vqai=hGuQ8kuc9pgc9s8qqaq=dirpe0xb9q8qiLsFr0=vr0=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@853F@ (7)

where

Dni = Missed days for the non-obese by gender

Doi = Missed days for the obese by gender

Wdi = Daily wage by gender

Wyi = Yearly wage by gender.

Acknowledgements

The authors would like to thank Peter Cribb, Norma Aros, Karen Coleman and David Lairson for their input. A special thanks to Anna Peeters for allowing us to use her life tables. This work was supported by grants from The Texas Department of State Health Services Innovations Grants, CDC and Prevention Division of Nutrition and Physical Activity (#U58/CCU619293-01) to the Texas Department of Health Bureau of Nutrition Services, and National Institutes of Health, National Center on Minority Health and Health Disparities (NCMHD), "Creation of an Hispanic Health Research Center in the Lower Rio Grande Valley." (#1P20MD000170-019001).

References

1. Mokdad AH, Marks JS, Stroup DF, Gerberding JL: Actual causes of death in the United States, 2000.

JAMA : The Journal of the American Medical Association 2004, 291(10):1238-1245. PubMed Abstract | Publisher Full Text

2. Kelder SH, Osganian SK, Feldman HA, Webber LS, Parcel GS, Leupker RV, Wu MC, Nader PR: Tracking of physical and physiological risk variables among ethnic subgroups from third to eighth grade: The Child and Adolescent Trial for Cardiovascular Health cohort study.

Preventive Medicine 2002, 34(3):324-333. PubMed Abstract | Publisher Full Text

3. Guo SS, Chumlea WC: Tracking of body mass index in children in relation to overweight in adulthood.

Am J Clin Nutr 1999, 70(1):145S-148S.

4. Clarke WR, Lauer RM: Does childhood obesity track into adulthood?

Crit Rev Food Sci Nutr 1993, 33(4-5):423-430. PubMed Abstract

5. Kelder SH, Perry CL, Klepp KI, Lytle LL: Longitudinal tracking of adolescent smoking, physical activity, and food choice behaviors.

American Journal of Public Health 1994, 84(7):1121-1126. PubMed Abstract | PubMed Central Full Text

6. Reilly J, Methven E, McDowell ZC, Hacking B, Alexander D, Stewart L, Kelnar CJ: Health consequences of obesity.

Archives of Disease in Childhood 2003, 88(9):748-752. PubMed Abstract | Publisher Full Text

7. Ebbeling CB, Pawlak DB, Ludwig DS: Childhood obesity: public-health crisis, common sense cure.

Lancet 2002, 360(9331):473-482. PubMed Abstract | Publisher Full Text

8. Koplan JP, Liverman CT, Kraak VA: Preventing Childhood Obesity: Health in the Balance. [http://www.nap.edu/catalog/11015.html]

Committee on Prevention of Obesity in Children and Youth 2004.

9. Whitaker RC, Wright JA, Pepe MS, Seidel KD, Dietz WH: Predicting obesity in young adulthood from childhood and parental obesity.

The New England Journal of Medicine 1997, 337(13):869-873. PubMed Abstract | Publisher Full Text

10. Guo SS, Roche AF, Chumlea WC, Gardner JD, Siervogel RM: The predictive value of childhood body mass index values for overweight at age 35.

The American Journal of Clinical Nutrition 1994, 59(4):810-819. PubMed Abstract

11. Serdula MK, Ivery D, Coates RJ, Freedman DS, Williamson DF, Byers T: Do obese children become obese adults? A review of the literature.

Preventive Medicine 1993, 22(2):167-177. PubMed Abstract | Publisher Full Text

12. Sturm R, Wells KB: Does obesity contribute as much to morbidity as poverty or smoking?

Public Health 2001, 115(3):229-235. PubMed Abstract | Publisher Full Text

13. Allison DB, Fontaine KR, Manson JE, Stevens J, VanItallie TB: Annual deaths attributable to obesity in the United States.

JAMA : The Journal of the American Medical Association 1999, 282(16):1530-1538. PubMed Abstract | Publisher Full Text

14. Allison DB, Zannolli R, Narayan KM: The direct health care costs of obesity in the United States.

American Journal of Public Health 1999, 89(8):1194-1199. PubMed Abstract | PubMed Central Full Text

15. Dietz WH: Health consequences of obesity in youth: Childhood predictors of adult disease.

Pediatrics 1998, 101(3 Pt 2):518-525. PubMed Abstract | Publisher Full Text

16. National Center for Health Statistics: Prevalence of overweight among children and adolescents: United States, 1999. [http://www.cdc.gov/nchs/products/pubs/pubd/hestats/overwght99.htm]

National Center for Health Statistics 1999.

17. Troiano RP, Flegal KM: Overweight children and adolescents: Description, epidemiology, and demographics.

Pediatrics 1998, 101(3 Pt 2):497-504. PubMed Abstract | Publisher Full Text

18. Campaigne BN, Morrison JA, Schumann BC, Falkner F, Lakatos E, Sprecher D, Schreiber GB: Indexes of obesity and comparisons with previous national survey data in 9- and 10-year-old black and white girls: The National Heart, Lung, and Blood Institute Growth and Health Study.

The Journal of Pediatrics 1994, 124(5 Pt 1):675-680. PubMed Abstract | Publisher Full Text

19. Dwyer JT, Stone EJ, Yang M, Feldman H, Webber LS, Must A, Perry CL, Nader PR, Parcel GS: Predictors of overweight and overfatness in a multiethnic pediatric population. Child and Adolescent Trial for Cardiovascular Health Collaborative Research Group.

The American Journal of Clinical Nutrition 1998, 67(4):602-610. PubMed Abstract | Publisher Full Text

20. Hoelscher DM, Day RS, Lee ES, Frankowski RF, Kelder SH, Ward JL, Scheurer ME: Measuring the prevalence of overweight in Texas schoolchildren.

American Journal of Public Health 2004, 94(6):1002-1008. PubMed Abstract | Publisher Full Text | PubMed Central Full Text

21. Gortmaker SL, Cheung LW, Peterson KE, Chomitz G, Cradle JH, Dart H, Fox MK, Bullock RB, Sobol AM, Colditz G, Field AE, Laird N: Impact of a school-based interdisciplinary intervention on diet and physical activity among urban primary school children: Eat well and keep moving.

Archives of Pediatrics & Adolescent Medicine 1999, 153(9):975-983. PubMed Abstract | Publisher Full Text

22. Killen JD, Robinson TN, Telch MJ, Saylor KE, Maron DJ, Rich T, Bryson S: The Stanford Adolescent Heart Health Program.

Health Education Quarterly 1989, 16(2):263-283. PubMed Abstract

23. Simons-Morton BG, Parcel GS, O'Hara NM: Implementing organizational changes to promote healthful diet and physical activity at school.

Health Education Quarterly 1988, 15:115-130. PubMed Abstract

24. Sallis JF, McKenzie TL, Alcaraz JE, Kolody B, Hovell MF, Nader PR: Project SPARK. Effects of physical education on adiposity in children.

Annals of the New York Academy of Sciences 1993, 699:127-136. PubMed Abstract | Publisher Full Text

25. Trevino RP, Pugh JA, Hernandez AE, Menchaca VD, Ramirez RR, Mendoza M: Bienestar: A diabetes risk-factor prevention program.

The Journal of School Health 1998, 68(2):62-67. PubMed Abstract

26. Walter HJ, Hofman A, Vaughan RD, Wynder EL: Modification of risk factors for coronary heart disease. Five-year results of a school-based intervention trial.

The New England Journal of Medicine 1988, 318(17):1093-1100. PubMed Abstract

27. Wechsler H, Basch CE, Zybert P, Shea S: Promoting the selection of low-fat milk in elementary school cafeterias in an inner-city Latino community: Evaluation of an intervention.

American Journal of Public Health 1998, 88(3):427-433. PubMed Abstract | PubMed Central Full Text

28. Perry CL, Stone EJ, Parcel GS, Ellison RC, Nader PR, Webber LS, Luepker RV: School-based cardiovascular health promotion: The child and adolescent trial for cardiovascular health (CATCH).

The Journal of School Health 1990, 60(8):406-413. PubMed Abstract

29. Luepker RV, Perry CL, McKinlay SM, Nader PR, Parcel GS, Stone EJ, Webber LS, Elder JP, Feldman HA, Johnson CC: Outcomes of a field trial to improve children's dietary patterns and physical activity. The Child and Adolescent Trial for Cardiovascular Health. CATCH collaborative group.

JAMA : The Journal of the American Medical Association 1996, 275(10):768-776. PubMed Abstract | Publisher Full Text

30. Nader P, Stone E, Lytle L, Perry C, Osganian S, Kelder S, Webber L, Elder J, Montgomery D, Feldman H, Wu M, Johnson C, Parcel G, Luepker R: Three-year maintenance of improved diet and physical activity: The CATCH cohort.

Arch Pediatr Adolesc Med 1999, 153(7):695-704. PubMed Abstract | Publisher Full Text

31. Roux L, Donaldson C: Economics and Obesity: Costing the Problem or Evaluating Solutions.

Obesity Research 2004, 12(2):173-179. PubMed Abstract | Publisher Full Text

32. Burton WN, Chen CY, Schultz AB, Edington DW: The economic costs associated with body mass index in a workplace.

Journal of Occupational and Environmental Medicine/American College of Occupational and Environmental Medicine 1998, 40(9):786-792. PubMed Abstract | Publisher Full Text

33. Burton WN, Chen CY, Schultz AB, Edington DW: The costs of body mass index levels in an employed population.

Statistical Bulletin (Metropolitan Life Insurance Company : 1984) 1999, 80(3):8-14. PubMed Abstract

34. Wolf AM, Colditz GA: Current estimates of the economic cost of obesity in the United States.

Obesity Research 1998, 6(2):97-106. PubMed Abstract

35. Wang LY, Yang Q, Lowry R, Wechsler H: Economic analysis of a school-based obesity prevention program.

Obesity Research 2003, 11(11):1313-1324. PubMed Abstract | Publisher Full Text

36. Kahn M: Health and Labor Market Performance: The Case of Diabetes.

Journal of Labor Economics 1998, 16(4):878-899. Publisher Full Text

37. Brown HS III, Pagán JA, Bastida E: The Impact of Diabetes on Employment: Genetic IVs in a Bivariate Probit.

Health Economics 2005, 14(5):537-544. PubMed Abstract | Publisher Full Text

38. Bastida E, Pagán JA: The Impact of Diabetes on Adult Employment and Earnings of Mexican-Americans: Findings from a Community Based Study.

Health Economics 2002, 11(5):403-13. PubMed Abstract | Publisher Full Text

39. Thompson D, Wolf AM: The medical-care cost burden of obesity.

Obesity Reviews 2001, 2:189-197. PubMed Abstract | Publisher Full Text

40. Coleman KJ, Tiller CL, Sanchez J, Heath EM, Sy O, Milliken G, Dzewaltowski DA: Prevention of the Epidemic Increase in Child Risk of Overweight in Low-Income Schools: The El Paso Coordinated Approach to Child Health (El Paso.

Archives of Pediatrics & Adolescent Medicine 2005, 159:217-224. PubMed Abstract | Publisher Full Text

41. Heath EM, Coleman KJ: Adoption and institutionalization of the Child and Adolescent Trial for Cardiovascular Health (CATCH) in El Paso, Texas.

Health Promotion Practice 2003, 4(2):157-164. PubMed Abstract | Publisher Full Text

42. Heath EM, Coleman KJ: Evaluation of the institutionalization of the coordinated approach to child health (CATCH) in a U.S./Mexico border community.

Health Education & Behavior : The official publication of the Society for Public Health Education 2002, 29(4):444-460. PubMed Abstract | Publisher Full Text

43. Laupacis A, Feeny D, Detsky AS, Tugwell PX: Tentative guidelines for using clinical and economic evaluations revisited.

Canadian Medical Association Journal 1993, 148(6):927-929. PubMed Abstract | PubMed Central Full Text

44. Owens D, Nease R, Harris R: Use of cost-effectiveness and value of information analyses to customize guidelines for specific clinical practice settings.

Medical Decision Making 1993, 13:395.

45. Tolley G, Fabian R: Valuing Health for Policy: An Economic Approach. Chicago, IL: University of Chicago Press; 1994.

46. Hirth RA, Chernew ME, Miller E, Fendrick M, Weissart WG: Willingness to Pay for a Quality-adjusted Life Year: Search of a Standard.

Medical Decision Making 2000, 20(3):332-342. PubMed Abstract | Publisher Full Text

47. Cohen BB, Barbano HE, Cox CS, Feldman JJ, Finucane FF, Kleinman JC, Madans JH: Plan and operation of the NHANES I Epidemiologic Followup Study: 1982–84.

Vital Health Stat 1 1987, 22():1-142. PubMed Abstract

48. Gorsky RD, Pamuk E, Williamson DF, Shaffer PA, Koplan JP: The 25-year health care costs of women who remain overweight after 40 years of age.

American Journal of Preventive Medicine 1996, 12(5):388-394. PubMed Abstract

49. Oster G, Thompson D, Edelsberg J, Bird AP, Colditz GA: Lifetime health and economic benefits of weight loss among obese persons.

American Journal of Public Health 1999, 89(10):1536-1542. PubMed Abstract | PubMed Central Full Text

50. National Center for Health Statistics: Plan and operation of the Third National Health and Nutrition Examination Survey, 1988-94. Series 1: programs and collection procedures.

Vital Health Stat 1 1994, 32:1-407. PubMed Abstract

51. Peeters A, Barendregt JJ, Willekens F, Mackenbach JP, Mamun AA, Bonneux L, NEDCOM tNE, of Morbidity Research Group DC: Obesity in adulthood and its consequences for life expectancy: a life-table analysis.

Annals of Internal Medicine 2003, 138:24-32. PubMed Abstract | Publisher Full Text

52. US Department of Labor: Highlights of Women's Earnings in 2003. Tech rep, Bureau of Labor Statistics; 2004.

53. Erickson P, Wilson R, Shannon I: Years of healthy life.

Healthy People 2000 Statistical Notes/National Center for Health Statistics 1995, 7(7):1-15. PubMed Abstract