Personal, Family, and Peer Correlates of General and Sport Physical Activity among African American, Latino, and White Girls

This study examined associations between personal, family, and peer variables on objectively measured physical activity (PA), and sports participation, of African American, Latino, and white girls. Specific variables included barriers efficacy, parent PA, parent support of PA, the home exercise environment, friends’ PA, and friends’ support of PA. The sample comprised 372 girls (mean age = 12.03 years; SD = 1.81; n = 128 African American, n = 120 Latino, and n = 124 white). Data were analyzed using multiple-sample structural equation models (by ethnicity), controlling for age, household income, body mass index, and physical development. Girls’ moderate to vigorous PA (MVPA) was positively related to friends’ support for all groups, and to parent PA only for African American girls. For sports, greater parental support related to more participation across ethnic/racial groups, whereas friends’ support was important only for African American girls. Age and physical development were negatively related to MVPA, and higher income was associated with greater sports participation. Numerous significant correlations emerged between the independent variables, with some differences across racial/ethnic groups. Findings highlight the role of parent and friends’ support for both MVPA and sports participation of early adolescent girls, as well as the importance of determining PA correlates among different ethnic/racial subgroups

Reliability of pedometer data in samples of youth and older women

BACKGROUND: Pedometers offer researchers a convenient and inexpensive tool for objective measurement of physical activity. However, many unanswered questions remain about expected values for steps/day for different populations, sources of variation in the data, and reliability of pedometer measurements. METHODS: This study documented and compared mean steps/day, demographic predictors of steps/day, and pedometer reliability in two longitudinal investigations, one involving a population-based youth sample (N = 367) and the other targeting postmenopausal women with type 2 diabetes (N = 270). Individuals were asked to wear pedometers (Yamax model SW-701) at the waist for 7 days and record steps/per day. They were also asked to record daily physical activities, duration, and perceived intensity (1 = low/light, 2 = medium/moderate, 3 = high/hard) for the same 7 days. In addition, survey data regarding usual physical activity was collected. Analyses of variance (ANOVA) were conducted to determine whether there were significant differences in pedometer results according to sex, age, and body mass index. Repeated measures ANOVAs were used to examine potential differences in results among differing numbers of days. RESULTS: Mean steps/day were 10,365 steps in the youth sample and 4,352 steps in the sample of older women. Girls took significantly fewer steps than boys, older women took fewer steps than younger women, and both youth and women with greater body mass took fewer steps than those with lower body mass. Reliability coefficients of .80 or greater were obtained with 5 or more days of data collection in the youth sample and 2 or more days in the sample of older women. Youth and older women were more active on weekdays than on weekends. Low but significant associations were found between step counts and self-report measures of physical activity in both samples. CONCLUSION: Mean steps/day and reliability estimates in the two samples were generally consistent with previously published studies of pedometer use. Based on these two studies, unsealed pedometers were found to offer an easy-to-use and cost-effective objective measure of physical activity in both youth and older adult populations

Long-term effects of the Mediterranean lifestyle program: a randomized clinical trial for postmenopausal women with type 2 diabetes

BACKGROUND: Multiple-risk-factor interventions offer a promising means for addressing the complex interactions between lifestyle behaviors, psychosocial factors, and the social environment. This report examines the long-term effects of a multiple-risk-factor intervention. METHODS: Postmenopausal women (N = 279) with type 2 diabetes participated in the Mediterranean Lifestyle Program (MLP), a randomized, comprehensive lifestyle intervention study. The intervention targeted healthful eating, physical activity, stress management, smoking cessation, and social support. Outcomes included lifestyle behaviors (i.e., dietary intake, physical activity, stress management, smoking cessation), psychosocial variables (e.g., social support, problem solving, self-efficacy, depression, quality of life), and cost analyses at baseline, and 6, 12, and 24 months. RESULTS: MLP participants showed significant 12- and 24-month improvements in all targeted lifestyle behaviors with one exception (there were too few smokers to analyze tobacco use effects), and in psychosocial measures of use of supportive resources, problem solving, self-efficacy, and quality of life. CONCLUSION: The MLP was more effective than usual care over 24 months in producing improvements on behavioral and psychosocial outcomes. Directions for future research include replication with other populations

A multilevel approach to youth physical activity research.

A multilevel approach to youth physical activity research. Exerc. Sport Sci. Rev., Vol. 32, No. 3, pp. 95-99, 2004. Social environment factors are hypothesized to interact with individual-level factors to influence youth physical activity. Multilevel analytic approaches are ideal for examining the influence of the social environment on youth physical activity as they allow examination of research questions across multiple contexts and levels (e.g., individual, family, and neighborhood levels)

Adapting and RE-AIMing a heart disease prevention program for older women with diabetes

Coronary heart disease is a pervasive public health problem with a heavy burden among older women. There is a need for developing effective interventions for addressing this problem and for evaluating the dissemination potential of such interventions. A multiple-behavior-change program originally designed for men with heart disease was adapted for women at high risk of heart disease in two randomized clinical trials—the Mediterranean Lifestyle Program and ¡Viva Bien!. Results from these two trials, including readiness for dissemination, are evaluated using the RE-AIM framework in terms of Reach, Effectiveness, Adoption, Implementation, and Maintenance. Program adaptations produced relative high reach as well as consistent and replicated effectiveness and maintenance, and were adopted by a high percentage of primary care offices and clinicians approached. We discuss key findings, lessons learned, future directions for related research, and use of RE-AIM for program development, adaptation, scale-up, and evaluation.Ye

The relationship between diabetes distress and clinical depression with glycemic control among patients with type 2 diabetes.

ObjectiveTo clarify previous findings that diabetes distress is related to glycemic control and self-management whereas measures of depression are not, using both binary and continuous measures of depression.Research design and methodsFour hundred and sixty-three type 2 patients completed measures of diabetes distress (Diabetes Distress Scale [DDS]) and clinical depression (Patient Health Questionnaire 8 [PHQ8]). PHQ8 was employed as either a binary (>or=10) or continuous variable. Dependent variables were A1C, diet, physical activity (PA), and medication adherence (MA).ResultsThe inclusion of a binary or continuous PHQ8 score yielded no differences in any equation. DDS was significantly associated with A1C and PA, whereas PHQ8 was not; both DDS and PHQ8 were significantly and independently associated with diet and MA.ConclusionsThe lack of association between depression and glycemic control is not due to the use of a binary measure of depression. Findings further clarify the significant association between distress and A1C

An introduction to latent variable growth curve modeling : concepts, issues, and applications. /

This book provides a comprehensive introduction to latent variable growth curve modeling (LGM) for analyzing repeated measures. It presents the statistical basis for LGM and its various methodological extensions, including a number of practical examples of its use. It is designed to take advantage of the reader's familiarity with analysis of variance and structural equation modeling (SEM) in introducing LGM techniques. Sample data, syntax, input and output, are provided for EQS, Amos, LISREL, and Mplus on the book's CD. Throughout the book, the authors present a variety of LGM techniques that are useful for many different research designs, and numerous figures provide helpful diagrams of the examples. Updated throughout, the second edition features three new chapters& growth modeling with ordered categorical variables, growth mixture modeling, and pooled interrupted time series LGM approaches. Following a new organization, the book now covers the development of the LGM, followed by chapters on multiple-group issues (analyzing growth in multiple populations, accelerated designs, and multi-level longitudinal approaches), and then special topics such as missing data models, LGM power and Monte Carlo estimation, and latent growth interaction models. The model specifications previously included in the appendices are now available on the CD so the reader can more easily adapt the models to their own research. This practical guide is ideal for a wide range of social and behavioral researchers interested in the measurement of change over time, including social, developmental, organizational, educational, consumer, personality and clinical psychologists, sociologists, and quantitative methodologists, as well as for a text on latent variable growth curve modeling or as a supplement for a course on multivariate statistics. A prerequisite of graduate level statistics is recommended.Rev. ed. of: An introduction to latent variable growth curve modeling / Terry E. Duncan ... [et al.]. 1999.Includes bibliographical references (p. 233-248) and indexes.This book provides a comprehensive introduction to latent variable growth curve modeling (LGM) for analyzing repeated measures. It presents the statistical basis for LGM and its various methodological extensions, including a number of practical examples of its use. It is designed to take advantage of the reader's familiarity with analysis of variance and structural equation modeling (SEM) in introducing LGM techniques. Sample data, syntax, input and output, are provided for EQS, Amos, LISREL, and Mplus on the book's CD. Throughout the book, the authors present a variety of LGM techniques that are useful for many different research designs, and numerous figures provide helpful diagrams of the examples. Updated throughout, the second edition features three new chapters& growth modeling with ordered categorical variables, growth mixture modeling, and pooled interrupted time series LGM approaches. Following a new organization, the book now covers the development of the LGM, followed by chapters on multiple-group issues (analyzing growth in multiple populations, accelerated designs, and multi-level longitudinal approaches), and then special topics such as missing data models, LGM power and Monte Carlo estimation, and latent growth interaction models. The model specifications previously included in the appendices are now available on the CD so the reader can more easily adapt the models to their own research. This practical guide is ideal for a wide range of social and behavioral researchers interested in the measurement of change over time, including social, developmental, organizational, educational, consumer, personality and clinical psychologists, sociologists, and quantitative methodologists, as well as for a text on latent variable growth curve modeling or as a supplement for a course on multivariate statistics. A prerequisite of graduate level statistics is recommended