Identifying subgroups that succeed or fail with three levels of physical activity intervention: the Activity Counseling Trial

Department of Psychology, San Diego State University, San Diego, California, United States
Health Psychology (Impact Factor: 3.59). 06/2006; 25(3):336-47. DOI: 10.1037/0278-6133.25.3.336
Source: PubMed


The authors used recursive partitioning methods to identify combinations of baseline characteristics that predict 2-year physical activity success in each of 3 physical activity interventions delivered in the multisite Activity Counseling Trial. The sample consisted of 874 initially sedentary primary care patients, ages 35-75 years, who were at risk for cardiovascular disease. Predictors of 2-year success were specific to each intervention and represented a range of domains, including physiological, demographic, psychosocial, health-related, and environmental variables. The results indicate how specific patient subgroups (e.g., obese, unfit individuals; high-income individuals in stable health) may respond differently to varying levels and amounts of professional assistance and support. The methods used provide a practical first step toward identifying clinically meaningful patient subgroups for further systematic investigation.

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    • "As is typically performed with this type of recursive partitioning method[42,43,46], further descriptive analysis was conducted on the distinct subgroups identified through the age-stratified recursive partitioning analyses in order to better understand subgroup membership. All variables entered into the recursive partitioning analyses were evaluated, in addition to the initial screening variables for self-reported physical activity (CHAMPS questionnaire measuring total physical activity, total walking , and walking for errands variables[36]—the latter two variables being most typically associated with built environment features47484950), and lower-extremity function measured via the Short Physical Performance Battery (SPPB)[37]. "
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    ABSTRACT: Background: Obesity is an increasingly prevalent condition among older adults, yet relatively little is known about how built environment variables may be associated with obesity in older age groups. This is particularly the case for more vulnerable older adults already showing functional limitations associated with subsequent disability. Methods: The Lifestyle Interventions and Independence for Elders (LIFE) trial dataset (n = 1600) was used to explore the associations between perceived built environment variables and baseline obesity levels. Age-stratified recursive partitioning methods were applied to identify distinct subgroups with varying obesity prevalence. Results: Among participants aged 70-78 years, four distinct subgroups, defined by combinations of perceived environment and race-ethnicity variables, were identified. The subgroups with the lowest obesity prevalence (45.5-59.4 %) consisted of participants who reported living in neighborhoods with higher residential density. Among participants aged 79-89 years, the subgroup (of three distinct subgroups identified) with the lowest obesity prevalence (19.4 %) consisted of non-African American/Black participants who reported living in neighborhoods with friends or acquaintances similar in demographic characteristics to themselves. Overall support for the partitioned subgroupings was obtained using mixed model regression analysis. Conclusions: The results suggest that, in combination with race/ethnicity, features of the perceived neighborhood built and social environments differentiated distinct groups of vulnerable older adults from different age strata that differed in obesity prevalence. Pending further verification, the results may help to inform subsequent targeting of such subgroups for further investigation. Trial registration: Identifier = NCT01072500.
    Full-text · Article · Dec 2015 · International Journal of Behavioral Nutrition and Physical Activity
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    • "Overweight and obese people are more sedentary (they spend more hours sitting each day). In addition, they have shown poor rates of change and adherence to PA [28,29]. Thus, prevention and reduction of obesity should be a public health priority, and reducing SB could be an appropriate strategy [3]. "
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    ABSTRACT: There is growing evidence suggesting that prolonged sitting has negative effects on people's weight, chronic diseases and mortality. Interventions to reduce sedentary time can be an effective strategy to increase daily energy expenditure. The purpose of this study is to evaluate the effectiveness of a six-month primary care intervention to reduce daily of sitting time in overweight and mild obese sedentary patients. Method/Design The study is a randomized controlled trial (RCT). Professionals from thirteen primary health care centers (PHC) will randomly invite to participate mild obese or overweight patients of both gender, aged between 25 and 65 years old, who spend 6 hours at least daily sitting. A total of 232 subjects will be randomly allocated to an intervention (IG) and control group (CG) (116 individuals each group). In addition, 50 subjects with fibromyalgia will be included. Primary outcome is: (1) sitting time using the activPAL device and the Marshall questionnaire. The following parameters will be also assessed: (2) sitting time in work place (Occupational Sitting and Physical Activity Questionnaire), (3) health-related quality of life (EQ-5D), (4) evolution of stage of change (Prochaska and DiClemente's Stages of Change Model), (5) physical inactivity (catalan version of Brief Physical Activity Assessment Tool), (6) number of steps walked (pedometer and activPAL), (7) control based on analysis (triglycerides, total cholesterol, HDL, LDL, glycemia and, glycated haemoglobin in diabetic patients) and (8) blood pressure and anthropometric variables. All parameters will be assessed pre and post intervention and there will be a follow up three, six and twelve months after the intervention. A descriptive analysis of all variables and a multivariate analysis to assess differences among groups will be undertaken. Multivariate analysis will be carried out to assess time changes of dependent variables. All the analysis will be done under the intention to treat principle. If the SEDESTACTIV intervention shows its effectiveness in reducing sitting time, health professionals would have a low-cost intervention tool for sedentary overweight and obese patients management. Trial registration A service of the U.S. National Institutes of Health. Developed by the National Library of Medicine. NCT01729936 KEYWORDS: Sedentary behaviour, Sitting time, Primary care, Overweight, Obese patients.
    Full-text · Article · Mar 2014 · BMC Public Health
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    • "As reported in previous studies on PA determinants [15,16], men in our study achieved greater change in activity dose and were more likely to meet PA recommendations than women. Yet, in contrast to conclusions of other studies or systematic reviews in which no effect or positive effect for younger patients have been stated [9,14,18], patients aged ≥50 years showed greater improvements compared to younger patients in our study. "
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    ABSTRACT: Further research is needed to improve the evidence regarding determinants of physical activity (PA) as a crucial step to plan higher effective intervention strategies. The goal of the present study is to identify socio-demographic and clinical characteristics of primary care (PHC) insufficiently active patients that are associated with longitudinal changes in the level of physical activity. Longitudinal analysis of baseline socio-demographic and clinical predictors of physical activity change in insufficiently active PHC patients who participated in a PA-promoting multi-centre randomized clinical trial conducted from October 2003 through March 2006. The primary outcome measure was the self-reported physical activity assessed with the 7-day Physical Activity Recall (PAR), at baseline, 6, 12 and 24 months. Baseline covariates included sex, age, social class, anthropometric measures and other cardiovascular risk factors or associated diseases (Diabetes, HTA, tobacco use, etc.), and stage of readiness to change PA. Generalized linear mixed models were used to estimate longitudinal association of studied variables on PA change over the three follow-up measurements. A total of 3691 patients (85% of the 4317 recruited in the trial) with at least one follow-up measurement were included in the longitudinal analysis. At baseline, analysed patients (mean age: 50.6 years; 64.6% women) devoted 34.7 minutes and 2.36 metabolic equivalent hours per week (MET.h/week) to moderate and vigorous physical activity. Older age, male gender, higher social class, lower BMI, diagnosis of diabetes or hypertension, and measurement season were significant predictors of PA longitudinal change. The effect of baseline readiness to change on PA dose was modified by time, showing a positive gradient in favour of those with more readiness to change that increases significantly at 12 and 24 months (p-value interaction < .0001). Identified baseline characteristics such as readiness to change and risk factors can guide physicians to prioritize time and intervention efforts for maximizing their impact on insufficiently active PHC patients.
    Full-text · Article · Feb 2014 · BMC Public Health
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