Evaluation of a culturally-adapted lifestyle intervention to treat elevated cardiometabolic risk of Latino adults in primary care (Vida Sana): A randomized controlled trial

Contemporary Clinical Trials

Volumn 48, Issue , 2016, Pages 30-40

  Rosas, Lisa G ^a   Lv, Nan ^a   Xiao, Lan ^a   Lewis, Megan A ^b   Zavella, Patricia ^c   Kramer, M Kaye ^d   Luna, Veronica ^a   Ma, Jun ^a,e  

^a PALO ALTO MEDICAL FOUNDATION RESEARCH INSTITUTE   (United States)

^b RTI INTERNATIONAL   (United States)

^c UNIVERSITY OF CALIFORNIA   (United States)

^d UNIVERSITY OF PITTSBURGH   (United States)

^e UNIVERSITY OF ILLINOIS AT CHICAGO   (United States)

Author keywords

Behavioral intervention; Cultural adaptation; Latinos; Obesity; Primary care; Weight loss

Indexed keywords

ADULT; ARTICLE; BEHAVIOR CHANGE; BLOOD PRESSURE MEASUREMENT; BODY MASS; BODY WEIGHT; CARDIOMETABOLIC RISK; CLINICAL EFFECTIVENESS; CLINICAL EVALUATION; CLINICAL PRACTICE; CONTROLLED STUDY; CULTURAL ANTHROPOLOGY; DIABETES MELLITUS; FEMALE; FOLLOW UP; GROUP PRACTICE; HEALTH CARE PLANNING; HISPANIC; HOSPITAL SERVICE; HUMAN; INTERMETHOD COMPARISON; LIFESTYLE MODIFICATION; MAJOR CLINICAL STUDY; MALE; MEDICAL HISTORY; METABOLIC SYNDROME X; MOBILE APPLICATION; OBESITY; OUTCOME ASSESSMENT; PATIENT SAFETY; PHYSICAL ACTIVITY; PREGNANCY DIABETES MELLITUS; PRIMARY MEDICAL CARE; PROTOCOL COMPLIANCE; QUALITY CONTROL; RANDOMIZED CONTROLLED TRIAL; SELF MONITORING; SOCIAL PSYCHOLOGY; UNITED STATES; WAIST CIRCUMFERENCE; WEIGHT LOSS PROGRAM; WEIGHT REDUCTION; YOUNG ADULT; CALIFORNIA; CALORIC RESTRICTION; EXERCISE; IMPAIRED GLUCOSE TOLERANCE; LIFESTYLE; NON INSULIN DEPENDENT DIABETES MELLITUS; PRIMARY HEALTH CARE; PROCEDURES; TRANSCULTURAL CARE;

CALIFORNIA; CALORIC RESTRICTION; CULTURALLY COMPETENT CARE; DIABETES MELLITUS, TYPE 2; EXERCISE; HISPANIC AMERICANS; HUMANS; LIFE STYLE; METABOLIC SYNDROME; PREDIABETIC STATE; PRIMARY HEALTH CARE; WEIGHT REDUCTION PROGRAMS;

EID: 84961918681     PISSN: 15517144     EISSN: 15592030     Source Type: Journal    
DOI: 10.1016/j.cct.2016.03.003     Document Type: Article

References (124)

1. Census Bureau U.S. Annual estimates of the resident population by sex, age, race, and Hispanic origin for the United States and States: April 1, 2010 to July 1, 2014 (Accessed July 31, 2015). http://factfinder.census.gov/faces/tableservices/jsf/pages/productview.xhtml?pid=PEP_2013_PEPASR6H&prodType=table.
2. Ogden C.L., Carroll M.D., Kit B.K., Flegal K.M. Prevalence of childhood and adult obesity in the United States, 2011-2012. J. Am. Med. Assoc. 2014, 311(8):806-814.
3. Flegal K.M., Carroll M.D., Kit B.K., Ogden C.L. Prevalence of obesity and trends in the distribution of body mass index among US adults, 1999-2010. J. Am. Med. Assoc. 2012, 307(5):491-497.
4. Ogden C.L., Carroll M.D., Kit B.K., Flegal K.M. Prevalence of obesity and trends in body mass index among US children and adolescents, 1999-2010. J. Am. Med. Assoc. 2012, 307(5):483-490.
5. Mozumdar A., Liguori G. Persistent increase of prevalence of metabolic syndrome among U.S. adults: NHANES III to NHANES 1999-2006. Diabetes Care 2011, 34(1):216-219.
6. Roger V.L., Go A.S., Lloyd-Jones D.M., et al. Heart disease and stroke statistics-2012 update: a report from the American Heart Association. Circulation 2012, 125(1):e2-e220.
7. Daviglus M.L., Talavera G.A., Aviles-Santa M.L., et al. Prevalence of major cardiovascular risk factors and cardiovascular diseases among Hispanic/Latino individuals of diverse backgrounds in the United States. J. Am. Med. Assoc. 2012, 308(17):1775-1784.
8. Wadden T.A., Butryn M.L., Hong P.S., Tsai A.G. Behavioral treatment of obesity in patients encountered in primary care settings: a systematic review. J. Am. Med. Assoc. 2014, 312(17):1779-1791.
9. Aguiar E.J., Morgan P.J., Collins C.E., Plotnikoff R.C., Callister R. Efficacy of interventions that include diet, aerobic and resistance training components for type 2 diabetes prevention: a systematic review with meta-analysis. Int. J. Behav. Nutr. Phys. Act. 2014, 11:2.
10. Ali M.K., Echouffo-Tcheugui J., Williamson D.F. How effective were lifestyle interventions in real-world settings that were modeled on the diabetes prevention program?. Health Aff. (Millwood) 2012, 31(1):67-75.
11. Whittemore R. A systematic review of the translational research on the Diabetes Prevention Program. Transl. Behav. Med. 2011, 1(3):480-491.
12. Knowler W.C., Barrett-Connor E., Fowler S.E., et al. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N. Engl. J. Med. 2002, 346(6):393-403.
13. Knowler W.C., Fowler S.E., Hamman R.F., et al. 10-year follow-up of diabetes incidence and weight loss in the Diabetes Prevention Program outcomes study. Lancet 2009, 374(9702):1677-1686.
14. Kramer M.K., Kriska A.M., Venditti E.M., et al. Translating the Diabetes Prevention Program: a comprehensive model for prevention training and program delivery. Am. J. Prev. Med. 2009, 37(6):505-511.
15. Kramer M.K., Kriska A.M., Venditti E.M., et al. A novel approach to diabetes prevention: evaluation of the Group Lifestyle Balance program delivered via DVD. Diabetes Res. Clin. Pract. 2010, 90(3):e60-e63.
16. Diabetes Prevention Support Center Group Lifestyle Balance materials. A Modification of the Diabetes Prevention Program's Lifestyle Change Program 2011, University of Pittsburgh, Pittsburgh, PA, (Accessed October 19, 2015). http://www.diabetesprevention.pitt.edu/index.php/for-the-public/group-lifestyle-balance-materials/.
17. Centers for Disease Control and Prevention (CDC Centers for Disease Control and Prevention Diabetes Prevention Recognition Program Standards and Operating Procedures 2011, Centers for Disease Control and Prevention, Atlanta, Georgia.
18. Greenwood D.A., Kramer M.K., Hankins A.I., Parise C.A., Fox A., Buss K.A. Adapting the Group Lifestyle Balance program for weight management within a large health care system Diabetes Education Program. Diabetes Educ. 2014, 40(3):299-307.
19. Kramer M.K., Miller R., Venditti E., TO Orchard Group lifestyle intervention for diabetes prevention in those with metabolic syndrome in primary care practice. Diabetes Care 2006, 55. (suppl).
20. McTigue K.M., Conroy M.B., 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. 208.
21. Kramer M.K., McWilliams J.R., Chen H.Y., Siminerio L.M. A community-based diabetes prevention program: evaluation of the Group Lifestyle Balance program delivered by diabetes educators. Diabetes Educ. 2011, 37(5):659-668.
22. Kramer M.K., Molenaar D.M., Arena V.C., et al. Improving employee health: evaluation of a worksite lifestyle change program to decrease risk factors for diabetes and cardiovascular disease. J. Clin. Occup. Environ. Med./Am. Coll. Occu. Enviro. Med. 2015, 57(3):284-291.
23. Sevick M.A., Zickmund S., Korytkowski M., et al. Design, feasibility, and acceptability of an intervention using personal digital assistant-based self-monitoring in managing type 2 diabetes. Contemp Clin Trials. 2008, 29(3):396-409.
24. Burke L.E., Conroy M.B., Sereika S.M., et al. The effect of electronic self-monitoring on weight loss and dietary intake: a randomized behavioral weight loss trial. Obesity (Silver Spring) 2011, 19(2):338-344.
25. Neuhausera L., Kreps G.L. eHealth communication and behavior change: promise and performance. Soc. Semiot. 2010, 20(1):9-27.
26. Krukowski R.A., Harvey-Berino J., West D.S. Obesity. Using Technology to Support Evidence-based Behavioral Health Practices: A Clinician's Guide 2009, Routledge, New York. M.A. Cucciare, K.R. Weingardt (Eds.).
27. Krebs P., Prochaska J.O., Rossi J.S. A meta-analysis of computer-tailored interventions for health behavior change. Prev. Med. 2010, 51(3-4):214-221.
28. Neve M., Morgan P.J., Jones P.R., Collins C.E. Effectiveness of web-based interventions in achieving weight loss and weight loss maintenance in overweight and obese adults: a systematic review with meta-analysis. Obes. Rev. 2010, 11(4):306-321.
29. Arem H., Irwin M. A review of web-based weight loss interventions in adults. Obes. Rev. 2011, 12(5):e236-e243.
30. Manzoni G.M., Pagnini F., Corti S., Molinari E., Castelnuovo G. Internet-based behavioral interventions for obesity: an updated systematic review. Clinical Practice and Epidemiology in Mental Health: CP & EMH 2011, 7:19-28.
31. Spring B., Duncan J.M., Janke E.A., et al. Integrating technology into standard weight loss treatment: a randomized controlled trial. JAMA Intern. Med. 2013, 173(2):105-111.
32. Burke L.E., Ma J., Azar K.M., et al. Current science on consumer use of mobile health for cardiovascular disease prevention: a scientific statement from the American Heart Association. Circulation 2015, 132(12):1157-1213.
33. Ma J., King A.C., Wilson S.R., Xiao L., Stafford R.S. Evaluation of lifestyle interventions to treat elevated cardiometabolic risk in primary care (E-LITE): a randomized controlled trial. BMC Fam. Pract. 2009, 10:71.
34. Yank V., Stafford R.S., Rosas L.G., Ma J. Baseline reach and adoption characteristics in a randomized controlled trial of two weight loss interventions translated into primary care: a structured report of real-world applicability. Contemp. Clin. Trials 2013, 34(1):126-135.
35. Ma J., Xiao L., Blonstein A. Measurement of self-monitoring web technology acceptance and use in an eHealth weight-loss trial. Telemed eHealth. 2013, (in press).
36. Blonstein A.C., Yank V., Stafford R.S., Wilson S.R., Rosas L.G., Ma J. Translating an evidence-based lifestyle intervention program into primary care: lessons learned. Health Promot. Pract. 2013, 14(4):491-497.
37. Ma J., Yank V., Xiao L., et al. Translating the Diabetes Prevention Program lifestyle intervention for weight loss into primary care: a randomized trial. JAMA Intern. Med. 2013, 173(2):113-121.
38. Xiao L., Yank V., Wilson S.R., Lavori P.W., Ma J. Two-year weight-loss maintenance in primary care-based Diabetes Prevention Program lifestyle interventions. Nutr. Diab. 2013, 3.
39. Appel L.J., Clark J.M., Yeh H.C., et al. Comparative effectiveness of weight-loss interventions in clinical practice. N. Engl. J. Med. 2011, 365(21):1959-1968.
40. Wadden T.A., Volger S., Sarwer D.B., et al. A two-year randomized trial of obesity treatment in primary care practice. N. Engl. J. Med. 2011, 365(21):1969-1979.
41. Riley W.T., Rivera D.E., Atienza A.A., Nilsen W., Allison S.M., Mermelstein R. Health behavior models in the age of mobile interventions: are our theories up to the task?. Transl. Behav. Med. 2011, 1(1):53-71.
42. Rosas L.G., Lv N., Azar K., Xiao L., Yank V., Ma J. Applying the Pragmatic-Explanatory Continuum Indicator Summary model in a primary care-based lifestyle intervention trial. Am. J. Prev. Med. 2015, 49(3 Suppl. 2):S208-S214.
43. Sommers B.D., Gunja M.Z., Finegold K., Musco T. Changes in self-reported insurance coverage, access to care, and health under the Affordable Care Act. J. Am. Med. Assoc. 2015, 314(4):366-374.
44. Ferguson W.J., Candib L.M. Culture, language, and the doctor-patient relationship. FMCH Publ. Presentations 2002, 61.
45. Flores G. Culture and the patient-physician relationship: achieving cultural competency in health care. J. Pediatr. 2000, 136(1):14-23.
46. Control CfD Prevention. Building our understanding: culture insights. Communicating with Hispanic/Latinos 2013.
47. Glasgow R.E., McKay H.G., Piette J.D., Reynolds K.D. The RE-AIM framework for evaluating interventions: what can it tell us about approaches to chronic illness management?. Patient Educ. Couns. 2001, 44(2):119-127.
48. Poston L., Harthoorn L.F., Van Der Beek E.M. Obesity in pregnancy: implications for the mother and lifelong health of the child. A consensus statement. Pediatr. Res. 2011, 69(2):175-180.
49. Grundy S.M., Cleeman J.I., Daniels S.R., et al. Diagnosis and management of the metabolic syndrome: an American Heart Association/National Heart, Lung, and Blood Institute scientific statement. Circulation 2005, 112(17):2735-2752.
50. NIH and National Heart Lung Blood Institute Clinical Guidelines on the Identification, Evaluation, and Treatment of Overweight and Obesity in Adults: The Evidence Report 1998, DHHS, Public Health Service, Rockville, MD, (October. NIH Publication No. 00-4084).
51. Pickering T.G., Hall J.E., Appel L.J., et al. Recommendations for blood pressure measurement in humans and experimental animals: part 1: blood pressure measurement in humans: a statement for professionals from the Subcommittee of Professional and Public Education of the American Heart Association Council on High Blood Pressure Research. Hypertension 2005, 45(1):142-161.
52. Measures from the PhenX Toolkit version February 4, 2011, Ver 4.2 (). (PhenX (consensus measures of Phenotypes and eXposures) is supported by NHGRI award No. U01 HG004597. Accessed January 15, 2015). http://www.phenxtoolkit.org.
53. Xiao L., Lavori P.W., Wilson S.R., Ma J. Comparison of dynamic block randomization and minimization in randomized trials: a simulation study. Clin. Trials 2011, 8(1):59-69.
54. Ma J., Strub P., Xiao L., et al. Behavioral weight loss and physical activity intervention in obese adults with asthma. A randomized trial. Ann. Am. Thorac. Soc. 2015, 12(1):1-11.
55. Ma J., Strub P., Camargo C.A., et al. The Breathe Easier through Weight Loss Lifestyle (BE WELL) intervention: a randomized controlled trial. BMC Pulm. Med. 2010, 10:16.
56. Marín G. Issues in the measurement of acculturation among Hispanics. Psychological Testing of Hispanics 1992, 235-251. American Psychological Association, Washington, DC. K.F. Geisinger (Ed.).
57. Marin G., Gamba R.J. A new measurement of acculturation for Hispanics: the Bidimensional Acculturation Scale for Hispanics (BAS). Hisp. J. Behav. Sci. 1996, 18:297-316.
58. Prochaska J.O., DiClemente C.C. Stages and processes of self-change of smoking: toward an integrative model of change. J. Consult. Clin. Psychol. 1983, 51(3):390-395.
59. Bandura A. Social Foundations of Thought and Action: A Social Cognitive Theory 1986, Prentice Hall, Englewood Cliffs, N.J.
60. Winett R.A., Tate D.F., Anderson E.S., Wojcik J.R., Winett S.G. Long-term weight gain prevention: a theoretically based internet approach. Prev. Med. 2005, 41(2):629-641.
61. U.S. Department of Agriculture. MyPlate. (Accessed March 8, 2016). http://www.choosemyplate.gov/MyPlate.
62. Burke L.E., Wang J., Sevick M.A. Self-monitoring in weight loss: a systematic review of the literature. J. Am. Diet. Assoc. 2011, 111(1):92-102.
63. Perrin A., Duggan M. Americans' Internet Access: 2000-2015 2015, Pew Research Center, Washington.
64. Bellg A.J., Borrelli B., Resnick B., et al. Enhancing treatment fidelity in health behavior change studies: best practices and recommendations from the NIH Behavior Change Consortium. Health Psychol. 2004, 23(5):443-451.
65. Ma J., Strub P., Lavori P.W., et al. DASH for asthma: a pilot study of the DASH diet in not-well-controlled adult asthma. Contemp. Clin. Trials 2013, 35(2):55-67.
66. Ma J., Yank V., Lv N., et al. Research aimed at improving both mood and weight (RAINBOW) in primary care: a type 1 hybrid design randomized controlled trial. Contemp. Clin. Trials. 2015, 43:260-278.
67. Ma J., Strub P., Lv N., et al. Pilot randomized trial of a healthy eating behavioural intervention in uncontrolled asthma. Eur. Respir. J. 2015, (accepted for publication).
68. Rosas L.G., Thiyagarajan S., Goldstein B.A., et al. The effectiveness of two community-based weight loss strategies among obese, low-income US Latinos. J. Acad. Nutr. Diet. 2015, 115(4):537-550.
69. Ma J., Berra K., Haskell W.L., et al. Case management to reduce risk of cardiovascular disease in a county health care system. Arch. Intern. Med. 2009, 169(21):1988-1995.
70. Moshfegh A.J., Goldman J., Lacomb R., Perloff B., Cleveland L. Research results using the new USDA automated multiple-pass method. FASEB J. 2001, 15(4). (abstr).
71. Conway J.M., Ingwersen L.A., Vinyard B.T., Moshfegh A.J. Effectiveness of the US Department of Agriculture 5-step multiple-pass method in assessing food intake in obese and nonobese women. Am. J. Clin. Nutr. 2003, 77(5):1171-1178.
72. Conway J.M., Ingwersen L.A., Moshfegh A.J. Accuracy of dietary recall using the USDA five-step multiple-pass method in men: an observational validation study. J. Am. Diet. Assoc. 2004, 104(4):595-603.
73. Blair S.N., Haskell W.L., Ho P., et al. Assessment of habitual physical activity by a seven-day recall in a community survey and controlled experiments. Am. J. Epidemiol. 1985, 122(5):794-804.
74. Badia X., Schiaffino A., Alonso J., Herdman M. Using the EuroQoI 5-D in the Catalan general population: feasibility and construct validity. Qual. Life Res. 1998, 7(4):311-322.
75. Karlsson J., Taft C., Sjostrom L., Torgerson J.S., 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.
76. Spitzer R.L., Kroenke K., Williams J.B. Validation and utility of a self-report version of PRIME-MD: the PHQ primary care study. Primary Care Evaluation of Mental Disorders. Patient Health Questionnaire. J. Am. Med. Assoc. 1999, 282(18):1737-1744.
77. Kroenke K., Spitzer R.L., Williams J.B. The PHQ-9: validity of a brief depression severity measure. J. Gen. Intern. Med. 2001, 16(9):606-613.
78. Yu L., Buysse D.J., Germain A., et al. Development of short forms from the PROMIS sleep disturbance and sleep-related impairment item banks. Behav. Sleep Med. 2011, 10(1):6-24.
79. United States Department of Agriculture U.S. Household Food Security Survey Module (Accessed September 23, 2015). http://www.ers.usda.gov/topics/food-nutrition-assistance/food-security-in-the-us/survey-tools.aspx#Spanish.
80. Marín G., Sabogal F., VanOss Marín B., Otero-Sabogal F., Pérez-Stable E.J. Development of a short acculturation scale for Hispanics. Hisp. J. Behav. Sci. 1987, 9:183-205.
81. Lee S.Y., Stucky B.D., Lee J.Y., Rozier R.G., Bender D.E. Short Assessment of Health Literacy-Spanish and English: a comparable test of health literacy for Spanish and English speakers. Health Serv. Res. 2010, 45(4):1105-1120.
82. VM Ruiz, Berrocal C., AE López, Rivas T. Factor analysis of the Spanish version of the Weight Efficacy Life-Style Questionnaire. Educ. Psychol. Meas. 2002, 62(3):539-555.
83. Sallis J.F., Pinski R.B., Grossman R.M., Patterson T.L., Nader P.R. The development of self-efficacy scales for health-related diet and exercise behaviors. Health Educ. Res. 1988, 3:283-292.
84. Sallis J.F., Grossman R.M., Pinski R.B., Patterson T.L., Nader P.R. The development of scales to measure social support for diet and exercise behaviors. Prev. Med. 1987, 16(6):825-836.
85. Curran G.M., Bauer M., Mittman B., Pyne J.M., Stetler C. Effectiveness-implementation hybrid designs: combining elements of clinical effectiveness and implementation research to enhance public health impact. Med. Care 2012, 50(3):217-226.
86. Glasgow R.E., Vogt T.M., Boles S.M. Evaluating the public health impact of health promotion interventions: the RE-AIM framework. Am. J. Public Health 1999, 89(9):1322-1327.
87. Glasgow R.E., Klesges L.M., Dzewaltowski D.A., Bull S.S., Estabrooks P. The future of health behavior change research: what is needed to improve translation of research into health promotion practice?. Ann. Behav. Med. 2004, 27(1):3-12.
88. Kessler R.S., Purcell E.P., Glasgow R.E., Klesges L.M., Benkeser R.M., Peek C.J. What does it mean to "employ" the RE-AIM model?. Eval. Health Prof. 2013, 36(1):44-66.
89. Ma J., Yank V., Lv N., et al. Research Aimed at Improving Both Mood and Weight (RAINBOW) in primary care: a type 1 hybrid design randomized controlled trial. Contemp. Clin. Trials 2015.
90. Littell R.C., Milliken G.A. SAS System for Mixed Models 1996, SAS Institute Inc., Cary, NC.
91. Brown H., Prescott R. Applied Mixed Models in Medicine 1999, John Wiley & Sons, Inc., Chichester, England.
92. Verbeke G., Molenberghs G. Linear Mixed Models for Longitudinal Data 2000, Springer-Verlag, New York.
93. Shao J., Yu X., Zhong B. A theory for testing hypotheses under covariate-adaptive randomization. Biometrika 2010, 97(2):347-360.
94. Lavori P.W., Dawson R., Shera D. A multiple imputation strategy for clinical trials with truncation of patient data. Stat. Med. 1995, 14(17):1913-1925.
95. Schafer J.L. Analysis of Incomplete Multivariate Data 1997, Chapman and Hall, New York.
96. Tang L., Duan N., Klap R., Asarnow J.R., Belin T.R. Applying permutation tests with adjustment for covariates and attrition weights to randomized trials of health-services interventions. Stat. Med. 2009, 28(1):65-74.
97. DiCiccio T.J., Efron B. Bootstrap confidence intervals. Stat. Sci. 1996, 11(3):189-228.
98. MacKinnon D.P., Lockwood C.M., Hoffman J.M., West S.G., Sheets V. A comparison of methods to test mediation and other intervening variable effects. Psychol. Methods 2002, 7(1):83-104.
99. MacKinnon D.P., Fritz M.S., Williams J., Lockwood C.M. Distribution of the product confidence limits for the indirect effect: program PRODCLIN. Behav. Res. Methods 2007, 39(3):384-389.
100. ATLAS.ti Version 7.5. [computer program] 2014, Scientific Software Development, Berlin, Germany.
101. Elo S., Kyngas H. The qualitative content analysis process. J. Adv. Nurs. 2008, 62(1):107-115.
102. Patton M.Q. Qualitative Research and Evaluation Methods 2002, Sage Publications, San Francisco.
103. Kraemer H.C. To increase power in randomized clinical trials without increasing sample size. Psychopharmacol. Bull. 1991, 27(3):217-224.
104. Thomas P.R. Weighing the Options: Criteria for Evaluating Weight-Management Programs 1995, Committee to Develop Criteria for Evaluating the Outcomes of Approaches to Prevent and Treat Obesity, Institute of Medicine, Washington, DC.
105. Stevens J., Truesdale K.P., McClain J.E., Cai J. The definition of weight maintenance. Int. J. Obes. 2006, 30(3):391-399.
106. ICH Harmonised Tripartite Guideline Statistical principles for clinical trials. International Conference on Harmonisation E9 Expert Working Group. Stat. Med. 1999, 18(15):1905-1942.
107. Bender R., Lange S. Adjusting for multiple testing-when and how?. J. Clin. Epidemiol. 2001, 54(4):343-349.
108. Harris P.A., Taylor R., Thielke R., Payne J., Gonzalez N., Conde J.G. Research electronic data capture (REDCap)-ametadata-driven methodology and workflow process for providing translational research informatics support. J. Biomed. Inform. 2009, 42(2):377-381.
109. Shaibi G.Q., Greenwood-Ericksen M.B., Chapman C.R., Konopken Y., Ertl J. Development, implementation, and effects of community-based Diabetes Prevention Program for obese Latino youth. J. Prim. Care Community Health 2010, 1(3):206-212.
110. Ruggiero L., Oros S., Choi Y.K. Community-based translation of the Diabetes Prevention Program's lifestyle intervention in an underserved Latino population. Diabetes Educ. 2011, 37(4):564-572.
111. Merriam P.A., Tellez T.L., Rosal M.C., et al. Methodology of a diabetes prevention translational research project utilizing a community-academic partnership for implementation in an underserved Latino community. BMC Med. Res. Methodol. 2009, 9:20.
112. Ockene I.S., Tellez T.L., Rosal M.C., et al. Outcomes of a Latino community-based intervention for the prevention of diabetes: the Lawrence Latino Diabetes Prevention Project. Am. J. Public Health 2012, 102(2):336-342.
113. Hall D.L., Lattie E.G., McCalla J.R., Saab P.G. Translation of the Diabetes Prevention Program to ethnic communities in the United States. J. Immigr. Minor. Health/Center Minority Public Health 2015.
114. Roger V.L., Go A.S., Lloyd-Jones D.M., et al. Heart disease and stroke statistics-2012 update: a report from the American Heart Association. Circulation 2012, 125(1):e2-e220.
115. Rosas L.G., Thiyagarajan S., Goldstein B.A., et al. The effectiveness of two community-based weight loss strategies among obese, low-income US Latinos. J. Acad. Nutr. Diet. 2015.
116. Krukowski R.A., West D.S., Harvey-Berino J. Recent advances in internet-delivered, evidence-based weight control programs for adults. J. Diabetes Sci. Technol. 2009, 3(1):184-189.
117. Spring B., Duncan J.M., Janke E.A., et al. Integrating technology into standard weight loss treatment: a randomized controlled trial. Arch. Intern. Med. 2012, 1-7.
118. Lopez M.H., Gonzalez-Barrera A., Patten E. Closing the digital divide: Latinos and technology adoption. Religion 2014.
119. Sarasohn-Kahn J. How Smartphones are Changing Health Care for Consumers and Providers 2010, California HealthCare Foundation.
120. Smith A. U.S. smartphone use in 2015 (Accessed March 2, 2016). http://www.pewinternet.org/2015/04/01/us-smartphone-use-in-2015/.
121. Horrigan J.B., Duggan M. Home Broadband 2015 (Accessed March 8, 2016). http://www.pewinternet.org/2015/12/21/home-broadband-2015/.
122. Anderson M. Racial and ethnic differences in how people use mobile technology (Accessed March 8, 2016). http://www.pewresearch.org/fact-tank/2015/04/30/racial-and-ethnic-differences-in-how-people-use-mobile-technology/.
123. King A.C., Bickmoreb T.W., Camperoc M.I., Pruittc L.A., Yin J.L. Employing virtual advisors in preventive care for underserved communities: results from the COMPASS study. J. Health Commun. 2013.
124. Winter S.J., Goldman Rosas L., Padilla Romero P., et al. Using citizen scientists to gather, analyze, and disseminate information about neighborhood features that affect active living. J. Immigr. Minor. Health 2015.