Establishing public health benchmarks for physical activity programs.
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Biomedical subjects
Publications and source records attributed to Sarah Levin Martin.
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OBJECTIVE: To establish the feasibility and utility of a simple data collection methodology for dietary assessment. DESIGN: Using a cross-sectional design, trained data collectors approached adults (approximately 20 - 40 years of age) at local grocery stores and asked whether they would volunteer their grocery receipts and answer a few questions for a small stipend (dollar 1). METHODS: The grocery data were divided into 3 categories: "fats, oils, and sweets," "processed foods," and "low-fat/low-calorie substitutions" as a percentage of the total food purchase price. The questions assessed the shopper's general eating habits (eg, fast-food consumption) and a few demographic characteristics and health aspects (eg, perception of body size). Statistical Analyses Performed. Descriptive and analytic analyses using non-parametric tests were conducted in SAS. RESULTS: Forty-eight receipts and questionnaires were collected. Nearly every respondent reported eating fast food at least once per month; 27% ate out once or twice a day. Frequency of fast-food consumption was positively related to perceived body size of the respondent (p = 0.02). Overall, 30% of the food purchase price was for fats, oils, sweets, 10% was for processed foods, and almost 6% was for low-fat/low-calorie substitutions. Households where no one was perceived to be overweight spent a smaller proportion of their food budget on fats, oils, and sweets than did households where at least one person was perceived to be overweight (p = 0.10); household where the spouse was not perceived to be overweight spent less on fats, oils, and sweets (p = 0.02) and more on low-fat/low-calorie substitutions (p = 0.09) than did households where the spouse was perceived to be overweight; and, respondents who perceived themselves to be overweight spent more on processed foods than did respondents who did not perceive themselves to be overweight (p = 0.06). CONCLUSION: This simple dietary assessment method, although global in nature, may be a useful indicator of dietary practices as evidenced by its association with perceived weight status.
BACKGROUND: Physical activity (PA) is critical for children's normal growth and development. The purpose of this study was to assess potential correlates of physical activity in a US national sample of youth aged 9-13 years. METHODS: A nationally representative telephone survey of parent-child pairs was conducted from April through June 2002. The questions assessed organized and free-time physical activity behavior and psychosocial and environmental variables that are potentially related to youth physical activity. RESULTS: Children's positive outcome expectations or beliefs about the benefits of participating in physical activity and parent's beliefs that participating in physical activity is important were related to participation in both organized and free-time physical activity. Children's perception of parental support and parent's reports of direct support were strongly related to organized physical activity. Feeling safe, having lots of places to be active, and parental participation with their child were strongly related to free-time physical activity. CONCLUSIONS: Messages and interventions aiming to increase children and adolescent's participation in organized and free-time physical activity should continue to focus on promoting the benefits that are associated with being active, the importance of parental support, and the provision of safe and enjoyable opportunities to be active.
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PURPOSE: There is some speculation about geographic differences in physical activity (PA) levels. We examined the prevalence of physical inactivity (PIA) and whether U.S. citizens met the recommended levels of PA across the United States. In addition, the association between PIA/PA and degree of urbanization in the 4 main U.S. regions (Northeast, Midwest, South, and West) was determined. METHODS: Participants were 178,161 respondents to the 2000 Behavioral Risk Factor Surveillance System (BRFSS). Data from 49 states and the District of Columbia were included (excluding Alaska). States were categorized by urban status according to the U.S. Department of Agriculture. Physical activity variables were those commonly used in national surveillance systems (PIA = no leisure-time PA; and PA = meeting a PA recommendation). RESULTS: Nationally, PA levels were higher in urban areas than in rural areas; correspondingly, PIA levels were higher in rural areas than in urban areas. Regionally, the urban-rural differences were most striking in the South and were, in fact, often absent in other regions. Demographic factors appeared to modify the association. CONCLUSION: The association between PA and degree of urbanization is evident and robust in the South but cannot be generalized to all regions of the United States. For the most part, the Midwest and the Northeast do not experience any relationship between PA and urbanization, whereas, in the West, the trend appears to be opposite of that observed in the South.
OBJECTIVES: We evaluated lifestyle interventions for diabetic persons who live in rural communities. METHODS: We conducted a 12-month randomized clinical trial (n = 152) of "intensive-lifestyle" (modeled after the NIH Diabetes Prevention Program) and "reimbursable-lifestyle" (intensive-lifestyle intervention delivered in the time allotted for Medicare reimbursement for diabetes education related to nutrition and physical activity) interventions with usual care as a control. RESULTS: Modest weight loss occurred by 6 months among intensive-lifestyle participants and was greater than the weight loss among usual-care participants (2.6 kg vs 0.4 kg, P<.01). At 12 months, a greater proportion of intensive-lifestyle participants had lost 2 kg or more than usual-care participants (49% vs 25%, P<.05). No differences in weight change were observed between reimbursable-lifestyle and usual-care participants. Glycated hemoglobin was reduced among all groups (P<.05) but was not different between groups. CONCLUSIONS: Improvement in both weight and glycemia was attainable by lifestyle interventions designed for persons who had type 2 diabetes and lived in rural communities.