Stephanie L Fitzpatrick1, Lawrence J Appel2,3,4, Bethany Bray5, Neon Brooks1, Victor J Stevens1. 1. 1 Kaiser Permanente Center for Health Research, Portland, OR, USA. 2. 2 Johns Hopkins University School of Medicine, Baltimore, MD, USA. 3. 3 Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA. 4. 4 The Welch Center for Prevention, Epidemiology & Clinical Research, Baltimore, MD, USA. 5. 5 Pennsylvania State University, University Park, PA, USA.
Abstract
BACKGROUND: We have demonstrated previously that patterns of behavioral adherence in the first 6 months of behavioral lifestyle interventions were associated with significant weight loss at 18 months. In this article, we extend this work to examine patterns of behavioral adherence over 18 months and to explore baseline demographic and psychosocial predictors. METHOD: Latent class analysis was applied separately to the Weight Loss Maintenance and PREMIER trials data to examine patterns of adherence to the following recommendations: (1) consuming ≥9 servings of fruits and vegetables per day, (2) ≤25% of energy from total fat, (3) ≤7% energy from saturated fat, and (4) ≥180 minutes of moderate-to-vigorous physical activity per week. Multinomial logistic regression was used to test demographic and psychosocial predictors of latent class membership. RESULTS: Four distinct subgroups with common patterns of behavioral adherence were identified in each trial including, Behavioral Maintainers, who maintained adherence to all behavioral recommendations for 1 year, Nonresponders, who did not adhere to the recommendations at any time point, and latent classes that reflected patterns of adherence to one or two behaviors or behavioral relapse. A significantly higher proportion of Behavioral Maintainers sustained ≥5% weight loss for 1 year compared with Nonresponders. Participants with higher vitality scores at baseline were more likely to belong to a latent class with long-term adherence to one or more recommendations than the Nonresponders class. CONCLUSIONS: Regular assessment of health behaviors and psychosocial measures such as vitality may help identify nonresponders and inform treatment tailoring to improve long-term behavioral and weight outcomes.
BACKGROUND: We have demonstrated previously that patterns of behavioral adherence in the first 6 months of behavioral lifestyle interventions were associated with significant weight loss at 18 months. In this article, we extend this work to examine patterns of behavioral adherence over 18 months and to explore baseline demographic and psychosocial predictors. METHOD: Latent class analysis was applied separately to the Weight Loss Maintenance and PREMIER trials data to examine patterns of adherence to the following recommendations: (1) consuming ≥9 servings of fruits and vegetables per day, (2) ≤25% of energy from total fat, (3) ≤7% energy from saturated fat, and (4) ≥180 minutes of moderate-to-vigorous physical activity per week. Multinomial logistic regression was used to test demographic and psychosocial predictors of latent class membership. RESULTS: Four distinct subgroups with common patterns of behavioral adherence were identified in each trial including, Behavioral Maintainers, who maintained adherence to all behavioral recommendations for 1 year, Nonresponders, who did not adhere to the recommendations at any time point, and latent classes that reflected patterns of adherence to one or two behaviors or behavioral relapse. A significantly higher proportion of Behavioral Maintainers sustained ≥5% weight loss for 1 year compared with Nonresponders. Participants with higher vitality scores at baseline were more likely to belong to a latent class with long-term adherence to one or more recommendations than the Nonresponders class. CONCLUSIONS: Regular assessment of health behaviors and psychosocial measures such as vitality may help identify nonresponders and inform treatment tailoring to improve long-term behavioral and weight outcomes.
Entities:
Keywords:
adherence; behavior change; latent class analysis; psychosocial predictors; treatment response; weight loss maintenance
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