Evaluating clinic and community-based lifestyle interventions for obesity reduction in a low-income Latino neighborhood: Vivamos Activos Fair Oaks Program

Rebecca L Drieling, Jun Ma, Randall S Stafford, Rebecca L Drieling, Jun Ma, Randall S Stafford

Abstract

Background: Obesity exerts an enormous health impact through its effect on coronary heart disease and its risk factors. Primary care-based and community-based intensive lifestyle counseling may effectively promote weight loss. There has been limited implementation and evaluation of these strategies, particularly the added benefit of community-based intervention, in low-income Latino populations.

Design: The Vivamos Activos Fair Oaks project is a randomized clinical trial designed to evaluate the clinical and cost-effectiveness of two obesity reduction lifestyle interventions: clinic-based intensive lifestyle counseling, either alone (n = 80) or combined with community health worker support (n = 80), in comparison to usual primary care (n = 40). Clinic-based counseling consists of 15 group and four individual lifestyle counseling sessions provided by health educators targeting behavior change in physical activity and dietary practices. Community health worker support includes seven home visits aimed at practical implementation of weight loss strategies within the person's home and neighborhood. The interventions use a framework based on Social Cognitive Theory, the Transtheoretical Model of behavior change, and techniques from previously tested lifestyle interventions. Application of the framework was culturally tailored based on past interventions in the same community and elsewhere, as well as a community needs and assets assessment. The interventions include a 12-month intensive phase followed by a 12-month maintenance phase. Participants are obese Spanish-speaking adults with at least one cardiovascular risk factor recruited from a community health center in a low-income neighborhood of San Mateo County, California. Follow-up assessments occur at 6, 12, and 24 months for the primary outcome of percent change in body mass index at 24 months. Secondary outcomes include specific cardiovascular risk factors, particularly blood pressure and fasting glucose levels.

Discussion and conclusions: If successful, this study will provide evidence for broad implementation of obesity interventions in minority populations and guidance about the selection of strategies involving clinic-based case management and community-based community health worker support.

Clinical trial registration: ClinicalTrials.gov: NCT01242683.

Figures

Figure 1
Figure 1
Schedule of data collection and intervention visits. All participants receive data collection visits. Case management visits are provided to participants in the case management and case management plus community health worker arms. Home visits are provided by community health workers to participants in the case management plus community health worker arm.

References

    1. Baskin ML, Ard J, Franklin F, Allison DB. Prevalence of obesity in the United States. Obes Rev. 2005;6(1):5–7. doi: 10.1111/j.1467-789X.2005.00165.x.
    1. Flegal KM, Carroll MD, Ogden CL, Johnson CL. Prevalence and trends in obesity among US adults, 1999-2000. JAMA. 2002;288(14):1723–1727. doi: 10.1001/jama.288.14.1723.
    1. Flegal KM, Carroll MD, Ogden CL, Curtin LR. Prevalence and trends in obesity among US adults, 1999-2008. JAMA. 2010;303(3):235–241. doi: 10.1001/jama.2009.2014.
    1. Finkelstein EA, Trogdon JG, Cohen JW, Dietz W. Annual medical spending attributable to obesity: payer-and service-specific estimates. Health Aff (Millwood) 2009;28(5):w822–831. doi: 10.1377/hlthaff.28.5.w822.
    1. Peeters A, Barendregt JJ, Willekens F, Mackenbach JP, Al Mamun A, Bonneux L. Obesity in adulthood and its consequences for life expectancy: a life-table analysis. Ann Intern Med. 2003;138(1):24–32.
    1. Bray GA. Risks of obesity. Endocrinol Metab Clin North Am. 2003;32(4):787–804. doi: 10.1016/S0889-8529(03)00067-7. viii.
    1. Wing RR, Jeffery RW. Effect of modest weight loss on changes in cardiovascular risk factors: are there differences between men and women or between weight loss and maintenance? Int J Obes Relat Metab Disord. 1995;19(1):67–73.
    1. Stevens VJ, Obarzanek E, Cook NR, Lee IM, Appel LJ, Smith West D, Milas NC, Mattfeldt-Beman M, Belden L, Bragg C. et al.Long-term weight loss and changes in blood pressure: results of the Trials of Hypertension Prevention, phase II. Ann Intern Med. 2001;134(1):1–11.
    1. Yancy CW, Benjamin EJ, Fabunmi RP, Bonow RO. Discovering the full spectrum of cardiovascular disease: Minority Health Summit 2003: executive summary. Circulation. 2005;111(10):1339–1349. doi: 10.1161/01.CIR.0000157740.93598.51.
    1. Lillie-Blanton M, Maddox TM, Rushing O, Mensah GA. Disparities in cardiac care: rising to the challenge of Healthy People 2010. J Am Coll Cardiol. 2004;44(3):503–508. doi: 10.1016/j.jacc.2004.04.043.
    1. French SA, Story M, Jeffery RW. Environmental influences on eating and physical activity. Annu Rev Public Health. 2001;22:309–335. doi: 10.1146/annurev.publhealth.22.1.309.
    1. Beaulac J, Kristjansson E, Cummins S. A systematic review of food deserts, 1966-2007. Prev Chronic Dis. 2009;6(3):A105.
    1. Walker RE, Keane CR, Burke JG. Disparities and access to healthy food in the United States: A review of food deserts literature. Health Place. 2010;16(5):876–884. doi: 10.1016/j.healthplace.2010.04.013.
    1. Popkin BM, Duffey K, Gordon-Larsen P. Environmental influences on food choice, physical activity and energy balance. Physiol Behav. 2005;86(5):603–613. doi: 10.1016/j.physbeh.2005.08.051.
    1. Wang MC, Kim S, Gonzalez AA, MacLeod KE, Winkleby MA. Socioeconomic and food-related physical characteristics of the neighbourhood environment are associated with body mass index. J Epidemiol Community Health. 2007;61(6):491–498. doi: 10.1136/jech.2006.051680.
    1. Christian JG, Bessesen DH, Byers TE, Christian KK, Goldstein MG, Bock BC. Clinic-based support to help overweight patients with type 2 diabetes increase physical activity and lose weight. Arch Intern Med. 2008;168(2):141–146. doi: 10.1001/archinternmed.2007.13.
    1. McTigue KM, Hess R, Ziouras J. Obesity in older adults: a systematic review of the evidence for diagnosis and treatment. Obesity (Silver Spring) 2006;14(9):1485–1497. doi: 10.1038/oby.2006.171.
    1. The Diabetes Prevention Program (DPP): description of lifestyle intervention. Diabetes Care. 2002;25(12):2165–2171. doi: 10.2337/diacare.25.12.2165.
    1. Knowler WC, Barrett-Connor E, Fowler SE, Hamman RF, Lachin JM, Walker EA, Nathan DM. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med. 2002;346(6):393–403. doi: 10.1056/NEJMoa012512.
    1. McTigue KM, Conroy MB, Bigi L, Murphy C, McNeil M. Weight loss through living well: translating an effective lifestyle intervention into clinical practice. Diabetes Educ. 2009;35(2):199–204. doi: 10.1177/0145721709332815. 208.
    1. Ackermann RT, Finch EA, Brizendine E, Zhou H, Marrero DG. Translating the Diabetes Prevention Program into the community. The DEPLOY Pilot Study. Am J Prev Med. 2008;35(4):357–363. doi: 10.1016/j.amepre.2008.06.035.
    1. Amundson HA, Butcher MK, Gohdes D, Hall TO, Harwell TS, Helgerson SD, Vanderwood KK. Translating the diabetes prevention program into practice in the general community: findings from the Montana Cardiovascular Disease and Diabetes Prevention Program. Diabetes Educ. 2009;35(2):209–210. doi: 10.1177/0145721709333269. 213-204, 216-220 passim.
    1. Ma J, Lee KV, Berra K, Stafford RS. Implementation of case management to reduce cardiovascular disease risk in the Stanford and San Mateo Heart to Heart randomized controlled trial: study protocol and baseline characteristics. Implement Sci. 2006;1:21. doi: 10.1186/1748-5908-1-21.
    1. Hebert JR, Ebbeling CB, Ockene IS, Ma Y, Rider L, Merriam PA, Ockene JK, Saperia GM. A dietitian-delivered group nutrition program leads to reductions in dietary fat, serum cholesterol, and body weight: the Worcester Area Trial for Counseling in Hyperlipidemia (WATCH) J Am Diet Assoc. 1999;99(5):544–552. doi: 10.1016/S0002-8223(99)00136-4.
    1. Befort CA, Donnelly JE, Sullivan DK, Ellerbeck EF, Perri MG. Group versus individual phone-based obesity treatment for rural women. Eat Behav. 2010;11(1):11–17. doi: 10.1016/j.eatbeh.2009.08.002.
    1. Kramer MK, Kriska AM, Venditti EM, Miller RG, Brooks MM, Burke LE, Siminerio LM, Solano FX, Orchard TJ. Translating the Diabetes Prevention Program: a comprehensive model for prevention training and program delivery. Am J Prev Med. 2009;37(6):505–511. doi: 10.1016/j.amepre.2009.07.020.
    1. Avenell A, Broom J, Brown TJ, Poobalan A, Aucott L, Stearns SC, Smith WC, Jung RT, Campbell MK, Grant AM. Systematic review of the long-term effects and economic consequences of treatments for obesity and implications for health improvement. Health Technol Assess. 2004;8(21):iii–iv. 1-182.
    1. Gary TL, Bone LR, Hill MN, Levine DM, McGuire M, Saudek C, Brancati FL. Randomized controlled trial of the effects of nurse case manager and community health worker interventions on risk factors for diabetes-related complications in urban African Americans. Prev Med. 2003;37(1):23–32. doi: 10.1016/S0091-7435(03)00040-9.
    1. Gorin A, Phelan S, Tate D, Sherwood N, Jeffery R, Wing R. Involving support partners in obesity treatment. J Consult Clin Psychol. 2005;73(2):341–343. doi: 10.1037/0022-006X.73.2.341.
    1. Frank LD, Andresen MA, Schmid TL. Obesity relationships with community design, physical activity, and time spent in cars. Am J Prev Med. 2004;27(2):87–96. doi: 10.1016/j.amepre.2004.04.011.
    1. Balcazar HG, de Heer H, Rosenthal L, Aguirre M, Flores L, Puentes FA, Cardenas VM, Duarte MO, Ortiz M, Schulz LO. A promotores de salud intervention to reduce cardiovascular disease risk in a high-risk Hispanic border population, 2005-2008. Prev Chronic Dis. 2010;7(2):A28.
    1. Joshu CE, Rangel L, Garcia O, Brownson CA, O'Toole ML. Integration of a promotora-led self-management program into a system of care. Diabetes Educ. 2007;33(Suppl 6):151S–158S. doi: 10.1177/0145721707304076.
    1. Balcazar HG, Byrd TL, Ortiz M, Tondapu SR, Chavez M. A randomized community intervention to improve hypertension control among Mexican Americans: using the promotoras de salud community outreach model. J Health Care Poor Underserved. 2009;20(4):1079–1094. doi: 10.1353/hpu.0.0209.
    1. Brownstein JN, Cheal N, Ackermann SP, Bassford TL, Campos-Outcalt D. Breast and cervical cancer screening in minority populations: a model for using lay health educators. J Cancer Educ. 1992;7(4):321–326. doi: 10.1080/08858199209528189.
    1. Culica D, Walton JW, Harker K, Prezio EA. Effectiveness of a community health worker as sole diabetes educator: comparison of CoDE with similar culturally appropriate interventions. J Health Care Poor Underserved. 2008;19(4):1076–1095. doi: 10.1353/hpu.0.0076.
    1. Berra K, Ma J, Klieman L, Hyde S, Monti V, Guardado A, Rivera S, Stafford RS. Implementing cardiac risk-factor case management: lessons learned in a county health system. Crit Pathw Cardiol. 2007;6(4):173–179.
    1. Stafford RS, Berra K. Critical factors in case management: practical lessons from a cardiac case management program. Dis Manag. 2007;10(4):197–207. doi: 10.1089/dis.2007.103624.
    1. 2004 American Community Survey-Data Profile: San Mateo County, California. U.S. Census Bureau; 2004.
    1. SMC H. 2004 Community Assessment: Health and Quality of Life in San Mateo County. 2005.
    1. 2008 Community Assessment: Health & Quality of Life in San Mateo County. San Mateo, CA: Healthy Community Collaborative of San Mateo County; 2008. Professional Research Consultants I.
    1. Karlsson J, Taft C, Sjostrom L, Torgerson JS, Sullivan M. Psychosocial functioning in the obese before and after weight reduction: construct validity and responsiveness of the Obesity-related Problems scale. Int J Obes Relat Metab Disord. 2003;27(5):617–630. doi: 10.1038/sj.ijo.0802272.
    1. Carpenter JS, Andrykowski MA, Wilson J, Hall LA, Rayens MK, Sachs B, Cunningham LL. Psychometrics for two short forms of the Center for Epidemiologic Studies-Depression Scale. Issues Ment Health Nurs. 1998;19(5):481–494. doi: 10.1080/016128498248917.
    1. Blumberg SJ, Bialostosky K, Hamilton WL, Briefel RR. The effectiveness of a short form of the Household Food Security Scale. Am J Public Health. 1999;89(8):1231–1234. doi: 10.2105/AJPH.89.8.1231.
    1. Buysse DJ, Reynolds CF, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry Res. 1989;28(2):193–213. doi: 10.1016/0165-1781(89)90047-4.
    1. Sherman AC, Simonton S, Adams DC, Latif U, Plante TG, Burns SK, Poling T. Measuring religious faith in cancer patients: reliability and construct validity of the Santa Clara Strength of Religious Faith questionnaire. Psychooncology. 2001;10(5):436–443. doi: 10.1002/pon.523.
    1. CDC. Behavioral Risk Factor Surveillance System Survey Questionnaire. Atlanta, Georgia: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention; 2006.
    1. Block G, Hartman AM, Naughton D. A reduced dietary questionnaire: development and validation. Epidemiology. 1990;1(1):58–64. doi: 10.1097/00001648-199001000-00013.
    1. A B. Social Foundations of Thought and Action: A Social Cognitive Theory. Englewood Cliffs, NJ: Prentice Hall; 1986.
    1. Prochaska JO, Velicer WF. The transtheoretical model of health behavior change. Am J Health Promot. 1997;12(1):38–48.
    1. Thomas S, Reading J, Shephard RJ. Revision of the Physical Activity Readiness Questionnaire (PAR-Q) Can J Sport Sci. 1992;17(4):338–345.
    1. Holm S. A Simple Sequentially Rejective Multiple Test Procedure. Scandinavian Journal of Statistics. 1979;6:6.
    1. Proschan M. A Multiple Comparison Procedure for Three- and Four-armed Controlled Clinical Trials. Statistics in Medicine. 1999;18:12. doi: 10.1002/(SICI)1097-0258(19990415)18:7<787::AID-SIM77>;2-M.
    1. Califf RM, Armstrong PW, Carver JR, D'Agostino RB, Strauss WE. 27th Bethesda Conference: matching the intensity of risk factor management with the hazard for coronary disease events. Task Force 5. Stratification of patients into high, medium and low risk subgroups for purposes of risk factor management. J Am Coll Cardiol. 1996;27(5):1007–1019. doi: 10.1016/0735-1097(96)87733-3.
    1. D'Agostino RB Sr, Grundy S, Sullivan LM, Wilson P. Validation of the Framingham coronary heart disease prediction scores: results of a multiple ethnic groups investigation. JAMA. 2001;286(2):180–187.
    1. Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42(2):377–381. doi: 10.1016/j.jbi.2008.08.010.
    1. Screening for obesity in adults: recommendations and rationale. Ann Intern Med. 2003;139(11):930–932.

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