Skip to main content

Advertisement

Springer Nature Link
Log in

Application of Latent Class Analysis to Identify Behavioral Patterns of Response to Behavioral Lifestyle Interventions in Overweight and Obese Adults

  • Published:
International Journal of Behavioral Medicine Aims and scope Submit manuscript

Abstract

Background

Examining responders and non-responders to behavioral lifestyle interventions among overweight/obese adults with additional comorbidities may aid in refining and tailoring obesity treatment.

Purpose

The purpose of this study is to demonstrate the use of latent class analysis to identify patterns of response to behavioral lifestyle interventions based on adherence to diet and exercise recommendations.

Method

Repeated measures latent class analysis was applied to two clinical trial datasets, combination of two active interventions in the PREMIER Trial (n = 501) and phase 1 of the Weight Loss Maintenance Trial (WLM; n = 1685), to identify patterns of response to behavioral lifestyle interventions. Treatment response was based on adherence to daily recommendations for fruit/vegetable, fat, saturated fat, sodium, and exercise at baseline and 6 months.

Results

In PREMIER, three distinct latent classes emerged: responders (45.9 %), non-responders (23.6 %), and early adherers (30.5 %). Responders and Early Adherers had greater weight loss at 6 and 18 months and were more likely to meet behavioral recommendations at 18 months than Non-responders. For WLM, there were four latent classes: partial responders (16 %), non-responders (40 %), early adherers (2 %), and fruit/veggie only responders (41 %). Non-responders in WLM had significantly less weight loss at 6 months compared to that of the other three latent classes.

Conclusion

Latent class analysis is a useful method to apply to clinical trial data to identify distinct patterns of response to behavioral interventions. Overweight/ obese participants who respond to behavioral lifestyle treatment (i.e., meet behavioral recommendations) have significantly greater weight loss than that of participants who do not make behavioral changes.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Explore related subjects

Discover the latest articles and news from researchers in related subjects, suggested using machine learning.

References

  1. Butryn ML, Webb V, Wadden TA. Behavioral treatment of obesity. Psychiatr Clin North Am. 2011;34(4):841–59.

    Article  PubMed Central  PubMed  Google Scholar 

  2. Wadden TA, Webb VL, Moran CH, Bailer BA. Lifestyle modification for obesity: new developments in diet, physical activity, and behavior therapy. Circulation. 2012;125(9):1157–70.

    Article  PubMed Central  PubMed  Google Scholar 

  3. Kong W, Langlois MF, Kamga-Ngande C, Gagnon C, Brown C, Baillargeon JP. Predictors of success to weight-loss intervention program in individuals at high risk for type 2 diabetes. Diabetes Res Clin Pract. 2010;90(2):147–53.

    Article  PubMed  Google Scholar 

  4. Teixeira PJ, Going SB, Houtkooper LB, Cussler EC, Metcalfe LL, Blew RM, et al. Pretreatment predictors of attrition and successful weight management in women. Int J Obes Relat Metab Disord. 2004;28(9):1124–33.

    Article  CAS  PubMed  Google Scholar 

  5. Collins LM, Lanza ST. Latent class and latent transition analysis: with applications in the social, behavioral, and health sciences. New Jersey: Wiley; 2010.

    Google Scholar 

  6. Lanza ST, Rhoades BL. Latent class analysis: an alternative perspective on subgroup analysis in prevention and treatment. Prev Sci. 2013;14(2):157–68.

    Article  PubMed Central  PubMed  Google Scholar 

  7. Appel LJ, Champagne CM, Harsha DW, Cooper LS, Obarzanek E, Elmer PJ, et al. Effects of comprehensive lifestyle modification on blood pressure control: main results of the PREMIER clinical trial. JAMA. 2003;289(16):2083–93.

    PubMed  Google Scholar 

  8. Elmer PJ, Obarzanek E, Vollmer WM, Simons-Morton D, Stevens VJ, Rohm Young D, et al. Effects of comprehensive lifestyle modification on diet, weight, physical fitness, and blood pressure control: 18-month results of a randomized trial. Ann Intern Med. 2006;144(7):485–95.

    Article  PubMed  Google Scholar 

  9. Svetkey LP, Stevens VJ, Brantley PJ, et al. Comparison of strategies for sustaining weight loss: the Weight Loss Maintenance randomized controlled trial. JAMA. 2008;299(10):1139–48.

    Article  CAS  PubMed  Google Scholar 

  10. Jones LR, Wilson CI, Wadden TA. Lifestyle modification in the treatment of obesity: an educational challenge and opportunity. Clin Pharmacol Ther. 2007;81(5):776–9.

    Article  CAS  PubMed  Google Scholar 

  11. Funk KL, Elmer PJ, Stevens VJ, Harsha DW, Craddick SR, Lin PH, et al. PREMIER—a trial of lifestyle interventions for blood pressure control: intervention design and rationale. Health Promot Pract. 2008;9(3):271–80.

    Article  PubMed  Google Scholar 

  12. Appel LJ, Moore TJ, Obarzanek E, Vollmer WM, Svetkey LP, Sacks FM, et al. A clinical trial of the effects of dietary patterns on blood pressure. DASH collaborative research group. N Engl J Med. 1997;336(16):1117–24.

    Article  CAS  PubMed  Google Scholar 

  13. Karanja NM, Obarzanek E, Lin PH, McCullough ML, Phillips KM, Swain JF, et al. Descriptive characteristics of the dietary patterns used in the dietary approaches to stop hypertension trial. DASH collaborative research group. J Am Diet Assoc. 1999;99(8 Suppl):S19–27.

    Article  CAS  PubMed  Google Scholar 

  14. Hollis JF, Gullion CM, Stevens VJ, et al. Weight loss during the intensive intervention phase of the Weight Loss Maintenance Trial. Am J Prev Med. 2008;35(2):118–26.

    Article  PubMed Central  PubMed  Google Scholar 

  15. Blair SN, Haskell WL, Po H, Paffenbarger RS, Vranizan KM, Farquhar JW, et al. Assessment of habitual physical activity methodology by a seven-day recall in a community survey and controlled experiments. Am J Epidemiol. 1986;122:794–804.

    Google Scholar 

  16. Sallis JF, Haskell WL, Wood PD, Fortmann SP, Rogers T, Blair SN, et al. Physical activity assessment methodology in the five-city project. Am J Epidemiol. 1985;121(1):91–106.

    CAS  PubMed  Google Scholar 

  17. Harlan LC, Block G. Use of adjustment factors with a brief food frequency questionnaire to obtain nutrient values. Epidemiology. 1990;1(3):224–31.

    Article  CAS  PubMed  Google Scholar 

  18. US Department of Agriculture. The food guide pyramid. Vol Home and Garden Bulletin No. 252. Washington, D.C.: US Department of Agriculture; 1992.

  19. Akaike H. Factor analysis and AIC. Psychometrika. 1987;52:317–32.

    Article  Google Scholar 

  20. Sclove L. Application of model-selection criteria to some problems in multivariate analysis. Psychometrika. 1987;52:333–43.

    Article  Google Scholar 

  21. Nylund KL, Asparouhov T, Muthen B. Deciding on the number of classes in latent class analysis and growth mixture modeling: a Monte Carlo simulation study. Struct Equ Model: Multidiscip J. 2007;14:535–69.

    Article  Google Scholar 

  22. Wang C, Brown CH, Bandeen-Roche K. Residual diagnostics for growth mixture models: examining the impact of a preventive intervention on multiple trajectories of aggressive behavior. J Am Stat Assoc. 2005;100(3):1054–76.

    Article  CAS  Google Scholar 

  23. Knowler WC, Barrett-Connor E, Fowler SE, et al. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med. 2002;346(6):393–403.

    Article  CAS  PubMed  Google Scholar 

  24. Look AHEAD Research Group, Wing RR. Long-term effects of a lifestyle intervention on weight and cardiovascular risk factors in individuals with type 2 diabetes mellitus: four-year results of the Look AHEAD trial. Arch Intern Med. 2010;170(17):1566–75.

    Google Scholar 

  25. World Health Organization. Obesity: preventing and managing the global epidemic. Report of a WHO consultation on obesity, Geneva, June 3–5, 1997. 1998; Publication No. WHO/NUT/NCD/98.1.

  26. Subar AF, Thompson FE, Kipnis V, Midthune D, Hurwitz P, McNutt S, et al. Comparative validation of the Block, Willett, and National Cancer Institute Food Frequency Questionnaires. Am J Epidemiol. 2001;154(12):1089–99.

    Article  CAS  PubMed  Google Scholar 

  27. Sloane R, Clutter Snyder D, Demark-Wahnefried W, Lobach D, Kraus WE. Comparing the 7-day PAR with a triaxial accelerometer for measuring time in exercise. Med Sci Sports Exerc. 2009;41(6):1334–40.

    Article  PubMed Central  PubMed  Google Scholar 

  28. de Vries H, Van’t Riet J, Spigt M, Metsemakers J, van den Akker M, Vermunt JK, et al. Clusters of lifestyle behaviors: results from the Dutch SMILE study. Prev Med. 2008;46(3):203–8.

    Article  PubMed  Google Scholar 

  29. BeLue R, Lanza ST, Figaro MK. Lifestyle therapy changes and hypercholesterolemia: Identifying risk groups in a community sample of Blacks and Whites. Ethn Dis. 2009;19(2):142–7.

    PubMed Central  PubMed  Google Scholar 

  30. Ogden LG, Stroebele N, Wyatt HR, Catenacci VA, Peters JC, Stuht J, et al. Cluster analysis of the national weight control registry to identify distinct subgroups maintaining successful weight loss. Obesity (Silver Spring). 2012;20(10):2039–47.

    Article  Google Scholar 

  31. Trivedi RB, Ayotte BJ, Thorpe CT, Edelman D, Bosworth HB. Is there a nonadherent subtype of hypertensive patient? A latent class analysis approach. Patient Prefer Adherence. 2010;4:255–62.

    Article  PubMed Central  PubMed  Google Scholar 

  32. Lanza ST, Collins LM. A mixture model of discontinuous development in heavy drinking from ages 18 to 30: the role of college enrollment. J Stud Alcohol. 2006;67(4):552–61.

    Article  PubMed  Google Scholar 

  33. Espeland MA, Bray GA, Neiberg R, et al. Describing patterns of weight changes using principal components analysis: results from the action for health in diabetes (Look AHEAD) research group. Ann Epidemiol. 2009;19(10):701–10.

    Article  PubMed Central  PubMed  Google Scholar 

  34. Neiberg RH, Wing RR, Bray GA, et al. Patterns of weight change associated with long-term weight change and cardiovascular disease risk factors in the Look AHEAD study. Obesity (Silver Spring). 2012;20(10):2048–56.

    Article  CAS  Google Scholar 

  35. Vermunt JK, Magidson J. Latent class cluster analysis. In: Hagenaars JA, McCutcheon AL, eds. Applied latent class analysis. Cambridge University Press:; 2002:89–106.

  36. Fitzpatrick SL, Lai BS, Brancati FL, Golden SH, Hill-Briggs F. Metabolic syndrome risk profiles among African American adolescents: National Health and Nutrition Examination Survey, 2003–2010. Diabetes Care. 2013;36(2):436–42.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  37. Lei H, Nahum-Shani I, Lynch K, Oslin D, Murphy SA. A “SMART” design for building individualized treatment sequences. Annu Rev Clin Psychol. 2012;8:21–48.

    Article  CAS  PubMed  Google Scholar 

  38. Almirall D, Nahum-Shani I, Sherwood NE, Murphy SA. Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research. Translational Behavioral Medicine. Published online: 06 May 2014.

Download references

Conflict of Interest

Lawrence Appel, Janelle Coughlin, Arlene Dalcin, and Gerald Jerome have an institutional (Johns Hopkins University) conflict of interest with Healthways, Inc.

Author information

Authors and Affiliations

  1. Department of Preventive Medicine, Rush University Medical Center, 1700 W. Van Buren St., Room 478A, Chicago, IL, 60607, USA

    Stephanie L. Fitzpatrick

  2. Department of Psychiatry & Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA

    Janelle W. Coughlin

  3. Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA

    Lawrence J. Appel, Gerald J. Jerome, Arlene Dalcin & Felicia Hill-Briggs

  4. Department of Medicine, Duke University, Durham, NC, USA

    Crystal Tyson

  5. Center for Health Research, Kaiser Permanente Northwest, Portland, OR, USA

    Victor J. Stevens

  6. Pennington Biomedical Research Center, Louisiana State University, Baton Rouge, LA, USA

    Phillip J. Brantley

Authors
  1. Stephanie L. Fitzpatrick
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Janelle W. Coughlin
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Lawrence J. Appel
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Crystal Tyson
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Victor J. Stevens
    View author publications

    You can also search for this author inPubMed Google Scholar

  6. Gerald J. Jerome
    View author publications

    You can also search for this author inPubMed Google Scholar

  7. Arlene Dalcin
    View author publications

    You can also search for this author inPubMed Google Scholar

  8. Phillip J. Brantley
    View author publications

    You can also search for this author inPubMed Google Scholar

  9. Felicia Hill-Briggs
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to Stephanie L. Fitzpatrick.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fitzpatrick, S.L., Coughlin, J.W., Appel, L.J. et al. Application of Latent Class Analysis to Identify Behavioral Patterns of Response to Behavioral Lifestyle Interventions in Overweight and Obese Adults. Int.J. Behav. Med. 22, 471–480 (2015). https://doi.org/10.1007/s12529-014-9446-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12529-014-9446-y

Keywords