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Physical activity, sedentary behaviors, and sleep are often associated with cardiometabolic biomarkers commonly found in metabolic syndrome. These relationships are well studied, and yet there are still questions on how each activity may affect cardiometabolic biomarkers. The objective of this study was to examine data from the BeWell24 studies to

Physical activity, sedentary behaviors, and sleep are often associated with cardiometabolic biomarkers commonly found in metabolic syndrome. These relationships are well studied, and yet there are still questions on how each activity may affect cardiometabolic biomarkers. The objective of this study was to examine data from the BeWell24 studies to evaluate the relationship between objectively measured physical activity and sedentary behaviors and cardiometabolic biomarkers in middle age adults, while also determining if sleep quality and duration mediates this relationship. A group of inactive participants (N = 29, age = 52.1 ± 8.1 years, 38% female) with increased risk for cardiometabolic disease were recruited to participate in BeWell24, a trial testing the impact of a lifestyle-based, multicomponent smartphone application targeting sleep, sedentary, and more active behaviors. During baseline, interim (4 weeks), and posttest visits (8 weeks), biomarker measurements were collected for weight (kg), waist circumference (cm), glucose (mg/dl), insulin (uU/ml), lipids (mg/dl), diastolic and systolic blood pressures (mm Hg), and C reactive protein (mg/L). Participants wore validated wrist and thigh sensors for one week intervals at each time point to measure sedentary behavior, physical activity, and sleep outcomes. Long bouts of sitting time (>30 min) significantly affected triglycerides (beta = .15 (±.07), p<.03); however, no significant mediation effects for sleep quality or duration were present. No other direct effects were observed between physical activity measurements and cardiometabolic biomarkers. The findings of this study suggest that reductions in long bouts of sitting time may support reductions in triglycerides, yet these effects were not mediated by sleep-related improvements.
ContributorsLanich, Boyd (Author) / Buman, Matthew (Thesis advisor) / Ainsworth, Barbara (Committee member) / Huberty, Jennifer (Committee member) / Arizona State University (Publisher)
Created2017
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"Globesity," as defined by the World Health Organization, describes obesity as a pandemic affecting at least 400 million people worldwide. The prevalence of obesity is higher among women than men; and in non-Hispanic black and Hispanic populations. Obesity has been significantly associated with increased all-cause mortality, and mortality from cardiovascular

"Globesity," as defined by the World Health Organization, describes obesity as a pandemic affecting at least 400 million people worldwide. The prevalence of obesity is higher among women than men; and in non-Hispanic black and Hispanic populations. Obesity has been significantly associated with increased all-cause mortality, and mortality from cardiovascular disease, obesity-related cancers, diabetes and kidney disease. Current strategies to curb obesity rates often use an ecological approach, suggesting three main factors: biological, behavioral, and environmental. This approach was used to develop four studies of obesity. The first study assessed dietary quality, using the Healthy Eating Index (HEI)-2005, among premenopausal Hispanic and non-Hispanic white women, and found that Hispanic women had lower total HEI-2005 scores, and lower scores for total vegetables, dark green and orange vegetables and legumes, and sodium. Markers of obesity were negatively correlated with total HEI-2005 scores. The second study examined the relationship between reported screen time and markers of obesity among premenopausal women and found that total screen time, TV, and computer use were positively associated with markers of obesity. Waist/height ratio, fat mass index, and leptin concentrations were significantly lower among those who reported the lowest screen time versus the moderate and high screen time categories. The third study examined the relationship between screen time and dietary intake and found no significant differences in absolute dietary intake by screen time category. The fourth study was designed to test a brief face-to-face healthy shopping intervention to determine whether food purchases of participants who received the intervention differed from those in the control group; and whether purchases differed by socioeconomic position. Participants in the intervention group purchased more servings of fruit when compared to the control group. High-income participants purchased more servings of dark green/deep yellow vegetables compared to those in the low-income group. Among those who received the intervention, low-income participants purchased foods of lower energy density, and middle-income participants purchased food of higher fat density. The findings of these studies support policy changes to address increasing access and availability of fruits and vegetables, and support guidelines to limit screen time among adults.
ContributorsMilliron, Brandy-Joe (Author) / Woolf, Kathleen (Thesis advisor) / Vaughan, Linda (Committee member) / Ainsworth, Barbara (Committee member) / Wharton, Chris (Committee member) / Der Ananian, Cheryl (Committee member) / Appelhans, Bradley (Committee member) / Arizona State University (Publisher)
Created2010