Browsing by Author "Hamlin M"
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- ItemAdiposity in preadolescent children: Associations with cardiorespiratory fitness(Public Library of Science, 2022-10-26) Castro N; Bates LC; Zieff G; Pagan Lassalle P; Faulkner J; Lark S; Hamlin M; Skidmore P; Signal TL; Williams MA; Higgins S; Stoner LLifestyle factors contribute to childhood obesity risk, however it is unclear which lifestyle factors are most strongly associated with childhood obesity. The purpose of this cross-sectional study was to simultaneously investigate the associations among dietary patterns, activity behaviors, and physical fitness with adiposity (body fat %, fat mass, body mass index [BMI], and waist to hip ratio) in preadolescent children. Preadolescent children (N = 392, 50% female, age: 9.5 ± 1.1year, BMI: 17.9 ± 3.3 kg/m2) were recruited. Body fat (%) and fat mass (kg) were measured with bioelectrical impedance analysis. Cardiorespiratory fitness (VO2 max), muscular strength (hand-grip strength), activity, sleep, and dietary pattern was assessed. Multivariable analysis revealed that cardiorespiratory fitness associated most strongly with all four indicators of adiposity (body fat (%) (β = -0.2; p < .001), fat mass (β = -0.2; p < .001), BMI (β = -0.1; p < .001) and waist to hip ratio (β = -0.2; p < .001). Additionally, fruit and vegetable consumption patterns were associated with body fat percentage, but the association was negligible (β = 0.1; p = 0.015). Therefore, future interventions should aim to promote the use of cardiorespiratory fitness as a means of reducing the obesity epidemic in children.
- ItemSocial Jetlag and Cardiometabolic Risk in Preadolescent Children(Frontiers Media SA, 2021-10-07) Castro N; Diana J; Blackwell J; Faulkner J; Lark S; Skidmore P; Hamlin M; Signal L; Williams MA; Stoner L; Barseghian AObjective: Childhood cardiometabolic disease risk (CMD) has been associated with short sleep duration. Its relationship with other aspects of sleep should also be considered, including social jetlag (SJL) which represents the difference between a person's social rhythms and circadian clock. This study investigated whether childhood CMD risk is associated with sleep duration, sleep disturbances, and SJL. Study Design: The observational study included 332 children aged 8-10 years (48.5% female). The three independent variables were sleep duration, sleep disturbances, and SJL. SJL was calculated as the variation in hours between the midpoint of sleep during free (weekend) days and work/school days. Eleven cardiometabolic biomarkers were measured, including central blood pressure, lipids, glycated hemoglobin, arterial wave reflection, and glucose. Underlying CMD risk factors were identified using factor analysis. Results: Four underlying CMD risk factors were identified using factor analysis: blood pressure, cholesterol, vascular health, and carbohydrate metabolism. Neither sleep disturbances nor sleep duration were significantly associated with any of the four CMD factors following adjustments to potential confounders. However, SJL was significantly linked to vascular health (p = 0.027) and cholesterol (p = 0.025). Conclusion: These findings suggest that SJL may be a significant and measurable public health target for offsetting negative CMD trajectories in children. Further studies are required to determine biological plausibility.