Latent Class Analysis of Stages of Change for Multiple Health Behaviors: Results from the Special Diabetes Program for Indians Diabetes Prevention Program
- 896 Downloads
This study sought to identify latent subgroups among American Indian and Alaska Native (AI/AN) patients with pre-diabetes based on their stages of change for multiple health behaviors. We analyzed baseline data from participants of the Special Diabetes Program for Indians Diabetes Prevention (SDPI-DP) Program, a lifestyle intervention program to prevent diabetes among AI/ANs. A total of 3,135 participants completed baseline questionnaires assessing stages of change for multiple health behaviors, specifically exercise, healthy eating, and weight loss. Latent class analysis was used to identify subgroups of people based on their answers to stages of change questions. Covariates were added to the latent class analyses to investigate how class membership was related to sociodemographic, behavioral, and psychosocial factors. Three classes were identified based on the distributions of the stages of change variables: Contemplation, Preparation, and Action/Maintenance classes. Male and retired participants were more likely to be in more advanced stages. Those who exercised more, ate healthier diets, and weighed less were significantly more likely to be in the Action/Maintenance class. Further, the participants who had higher self-efficacy, stronger family support, and better health-related quality of life had higher odds of being in the Action/Maintenance class. In conclusion, we found that stages of change for multiple behaviors can be summarized by a three-class model in this sample. Investigating the relationships between latent classes and intervention outcomes represents important next steps to extend the findings of the current study.
KeywordsTranstheoretical model Exercise Nutrition Weight management American Indian and Alaska natives
Funding for this project was provided by the Indian Health Service (HHSI242200400049C, S. Manson). We would like to express our gratitude to the Indian Health Service as well as tribal and urban Indian health programs and participants involved in the Special Diabetes Program for Indians Diabetes Prevention Program.
- Acton, K. J., Burrows, N. R., Geiss, L. S., & Thompson, T. (2003). Diabetes prevalence among American Indians and Alaska Natives and the overall population–United States, 1994–2002. Morbidity and Mortality Weekly Report, 52, 702–704.Google Scholar
- Acton, K. J., Burrows, N. R., Wang, J., & Geiss, L. S. (2006). Diagnosed diabetes among American Indian and Alaska Natives aged <35 years - United States, 1994–2004. Morbidity and Mortality Weekly Report, 55, 1201–1203.Google Scholar
- Adams, S. A., Matthews, C. E., Ebbeling, C. B., Moore, C. G., Cunningham, J. E., Fulton, J., et al. (2005). The effect of social desirability and social approval on self-reports of physical activity. American Journal of Epidemiology, 161, 389–398. doi: 10.1093/aje/kwi054.PubMedCrossRefGoogle Scholar
- BeLue, R., Lanza, S. T., & Figaro, M. K. (2009). Lifestyle therapy changes and hypercholesterolemia: Identifying risk groups in a community sample of Blacks and Whites. Ethnicity & Disease, 19, 142–147.Google Scholar
- CDC. (2011). 2011 National Diabetes Fact Sheet Retrieved from http://www.cdc.gov/diabetes/pibs/estimates11.htm.
- Collins, L. M., & Lanza, S. T. (2009). Latent class and latent transition analysis: With applications in the social, behavioral, and health sciences. Hoboken, NJ: Wiley.Google Scholar
- Evers, K. E., Prochaska, J. O., Johnson, J. L., Mauriello, L. A., Padula, J. A., & Prochaska, J. M. (2006). A randomized clinical trial of a population- and transtheoretical model-based stress-management intervention. Health Psychology, 25, 521–529. doi: 10.1037/0278-622.214.171.1241.PubMedCrossRefGoogle Scholar
- Greene, G. W., Fey-Yensan, N., Padula, C., Rossi, S., Rossi, J. S., & Clark, P. G. (2004). Differences in psychosocial variables by stage of change for fruits and vegetables in older adults. Journal of the American Dietetic Association, 104, 1236–1243. doi: 10.1016/j.jada.2004.05.205.PubMedCrossRefGoogle Scholar
- Guo, B. L., Aveyard, P., Fielding, A., & Sutton, S. (2009). Using latent class and latent transition analysis to examine the transtheoretical model staging algorithm and sequential stage transition in adolescent smoking. Substance Use & Misuse, 44, 2028–2042. doi: 10.3109/10826080902848665.CrossRefGoogle Scholar
- Johnson, S. S., Paiva, A. L., Cummins, C. O., Johnson, J. L., Dyment, S. J., Wright, J. A., et al. (2008). Transtheoretical model-based multiple behavior intervention for weight management: Effectiveness on a population basis. Preventive Medicine, 46, 238–246. doi: 10.1016/j.ypmed.2007.09.010.PubMedCrossRefGoogle Scholar
- Kavookjian, J., Berger, B. A., Grimley, D. M., Villaume, W. A., Anderson, H. M., & Barker, K. N. (2005). Patient decision making: Strategies for diabetes diet adherence intervention. Research in Social and Administrative Pharmacy, 1, 389–407. doi: 10.1016/j.sapharm.2005.06.006.PubMedCrossRefGoogle Scholar
- Marcus, B. H., Selby, V. C., Niaura, R. S., & Rossi, J. S. (1992b). Self-efficacy and the stages of exercise behavior change. Research Quarterly for Exercise and Sport, 63, 60–66.Google Scholar
- Mauriello, L. M., Ciavatta, M. M. H., Paiva, A. L., Sherman, K. J., Castle, P. H., Johnson, J. L., et al. (2010). Results of a multi-media multiple behavior obesity prevention program for adolescents. Preventive Medicine, 51, 451–456. doi: 10.1016/j.ypmed.2010.08.004.
- Muthén, L. K., & Muthén, B. O. (1998–2007). Mplus user's guide (5th ed.). Los Angeles: Authors.Google Scholar
- Prochaska, J. O., Velicer, W. F., Rossi, J. S., Redding, C. A., Greene, G. W., Rossi, S. R., et al. (2004). Multiple risk expert systems interventions: Impact of simultaneous stage-matched expert system interventions for smoking, high-fat diet, and sun exposure in a population of parents. Health Psychology, 23, 503–516. doi: 10.1037/0278-6126.96.36.1993.PubMedCrossRefGoogle Scholar
- Prochaska, J. O., Velicer, W. F., Redding, C., Rossi, J. S., Goldstein, M., DePue, J., et al. (2005). Stage-based expert systems to guide a population of primary care patients to quit smoking, eat healthier, prevent skin cancer, and receive regular mammograms. Preventive Medicine, 41, 406–416. doi: 10.1016/j.ypmed.2004.09.050.PubMedCrossRefGoogle Scholar
- Ruggiero, L., & Prochaska, J. O. (1993). Readiness for change: Application of the transtheoretical model to diabetes. Diabetes Spectrum, 6, 22–60.Google Scholar
- Scagliusi, F. B., Polacow, V. O., Artioli, G. G., Benatti, F. B., & Lancha, A. H. (2003). Selective underreporting of energy intake in women: Magnitude, determinants, and effect of training. Journal of the American Dietetic Association, 103, 1306–1313. doi: 10.1016/s0002-8223(03)01074-5.PubMedCrossRefGoogle Scholar
- Tuomilehto, J., Lindstrom, J., Eriksson, J. G., Valle, T. T., Hamalainen, H., Ilanne-Parikka, P., et al. (2001). Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance. The New England Journal of Medicine, 344, 1343–1350. doi: 10.1056/nejm200105033441801.PubMedCrossRefGoogle Scholar