EFFECTS OF BODY MASS INDEX ON PHYSICAL ACTIVITY, ENERGY EXPENDITURE, SLEEP, AND FATIGUE IN MEN UNDERGOING RADIATION THERAPY FOR PROSTATE CANCER: A COHORT STUDY

2012 ◽  
Vol 30 (1) ◽  
pp. 28
Author(s):  
Jacqueline S. Drouin ◽  
Tracey L. Winkler ◽  
Nathan M. Kangas ◽  
Joshua J. Halas ◽  
Christina Mitchell ◽  
...  
2008 ◽  
Vol 33 (2) ◽  
pp. 309-314 ◽  
Author(s):  
Antony D. Karelis ◽  
Marie-Ève Lavoie ◽  
Virginie Messier ◽  
Diane Mignault ◽  
Dominique Garrel ◽  
...  

The purpose of this cross-sectional study was to examine the association between the metabolic syndrome (MetS) and physical activity energy expenditure (PAEE) in overweight and obese sedentary postmenopausal women. The study population consisted of 137 overweight and obese sedentary postmenopausal women (age, 57.7 ± 4.8 years; BMI, 32.4 ± 4.6 kg·m–2). Subjects had the MetS if 3 out of the following 5 criteria were met: visceral fat > 130 cm2, high-density lipoprotein (HDL) cholesterol < 1.29 mmol·L–1, fasting triglycerides ≥ 1.7 mmol·L–1, blood pressure ≥ 130/85 mmHg, and fasting glucose ≥5.6 mmol·L–1. We measured (i) body composition (by dual-energy X-ray absorptiometry); (ii) visceral fat (by computed tomography); (iii) insulin sensitivity (using the hyperinsulinemic-euglycemic clamp); (iv) plasma lipids, fasting glucose, and insulin, as well as 2 h glucose during an oral glucose tolerance test; (v) resting blood pressure; (vi) peak oxygen consumption (VO2 peak); (vii) PAEE (using doubly labeled water); and (viii) lower-body muscle strength (using weight-training equipment). Forty-two women (30.7%) had the MetS in our cohort. Individuals without the MetS had significantly higher levels of PAEE (962 ± 296 vs. 837 ± 271 kcal·d–1; p < 0.05), VO2 peak (18.2 ± 3.0 vs. 16.7 ± 3.2 mL·min–1·kg–1; p < 0.05), and insulin sensitivity, as well as significantly lower levels of 2 h glucose and central lean body mass. No differences in total energy expenditure, resting metabolic rate, and muscle strength between groups were observed. Logistic regression analysis showed that 2 h glucose (odds ratio (OR): 1.50 (95% CI 1.17–1.92)), central lean body mass (OR: 1.17 (95% CI 1.05–1.31)), and PAEE (OR: 0.998 (95% CI 0.997–1.000)), but not VO2 peak and (or) muscle strength, were independent predictors of the MetS. Lower levels of PAEE and higher levels of 2 h glucose, as well as central lean body mass, are independent determinants of the MetS in our cohort of overweight and obese postmenopausal women.


2010 ◽  
Vol 22 (1) ◽  
pp. 3 ◽  
Author(s):  
I Cook ◽  
M Alberts ◽  
EV Lambert

Objectives. We developed a novel approach to investigate patterns of pedometry-measured total weekly activity energy expenditure (EEAct) in rural black South Africans in the Limpopo Province. Design. We analysed 7-day pedometry data in 775 subjects (female: N=508; male: N=267). Variance components models for EEAct were used to estimate the variance explained by body mass (BM), total weekly steps (volume) and estimated intensity (kcal. kg-1.step-1). Univariate General Linear Models, adjusting for age, BM and physical activity (PA) volume, were used to determine if EEAct was primarily affected by volume or intensity. Results. BM (13.1%), PA intensity (24.4%) and PA volume (56.9%) explained 94.4% of the variance in EEAct. Adjusted EEAct did not differ between sexes (78 kcal.week-1, p =0.2552). There were no significant differences across activity categories (sedentary to very active) for adjusted EEAct (62 - 287 kcal.week-1, p>0.1). Adjusted EEAct for 6 - 7 days of compliance (≥10 000 steps.day-1) differed significantly from 1 - 2 days of compliance (266 - 419 kcal.week-1, p<0.04). Obese (body mass index ≥30 kg.m-2) and normal weight (body mass index 18.5 - 24.9 kg.m-2) women did not differ significantly across activity categories for EEAct (200 - 592 kcal.week-1, p>0.30). Conclusions. We have highlighted an intensity effect for days of compliance and at very active ambulatory levels (≥12 500 steps. day-1). A volume effect appeared to dominate between sexes, across activity categories and weight-by-activity categories. It is important that post hoc statistical adjustments be made for body mass and PA volume when comparing EEAct across groups.


2020 ◽  
Author(s):  
Harriet Carroll

Background: Variability in sweet preference between people is well established, with those who have a high preference colloquially identified as having a sweet tooth. Although characteristics have been described demonstrating key differences between those with and without a sweet tooth (such as differences in body mass index), it is less clear whether sweet preference moderates appetite and health responses to stimuli of different sweetness levels.Objective: To explore appetite and health responses to a sugar-sweetened (SWEET) and unsweetened (PLAIN) porridge-based breakfast, according to whether participants identified as having a sweet tooth or not. Methods: Secondary data analysis of a previously published randomised crossover trial in which n = 29 participants consumed an isocaloric PLAIN (~8 g sugar) and SWEET (~32 g sugar) porridge-based breakfast for three weeks each. Fasted pre- and post-intervention measures included blood biomarkers of health and appetite hormones, anthropometrics and metabolic rate, and a series of questionnaires assessing psychological appetite/approach to food. During each three week intervention, four days of lifestyle monitoring were conducted on days 1-4 and days 15-18, involving weighed food diaries, physical activity measurements (ActiHeart™), and visual analogue scales of appetite across the day. After study completion, participants were asked whether they believed they had a sweet tooth or not; n = 27 responded and were included in these analyses. Analyses were exploratory with no significance testing or a priori hypothesis. Results: 16 participants reported not having a sweet tooth. Average body mass index was higher in those without a sweet tooth (25.9 ± 6.0 kg/m2 versus 24.4 ± 4.3 kg/m2 for those with a sweet tooth), but waist-to-hip ratio was lower. Having a sweet tooth was associated with a higher desire for sweet across the day during both interventions compared to those without a sweet tooth, but also lower sugar intake. Sweet sensory-specific satiety was achieved in both groups post-breakfast during SWEET, whilst savoury sensory-specific satiety was achieved post-breakfast after both PLAIN and SWEET. Fasting plasma fibroblast growth factor 21 was higher in those with a sweet tooth, whilst fasting glucagon-like peptide-1 increased pre- to post-PLAIN (Δ 6.2, 95 % CI 1.1, 11.4 pmol∙L-1), but was otherwise similar across interventions and between groups. Those without a sweet tooth reduced their energy intake from week 1 to week 3 of PLAIN (Δ -152, 95 % CI -349, 45 kcal/d), whereas those with a sweet tooth (less reliably) increased their energy intake (Δ 131, 95 % CI -131, 395 kcal/d). No changes in energy intake were noted during SWEET. Physical activity energy expenditure largely remained consistent between groups and across interventions, though those without a sweet tooth increased their physical activity energy expenditure from week 1 to week 3 of SWEET (Δ 166, 95 % CI -8, 241 kcal/d).Conclusion: Having a sweet tooth was associated with distinct characteristics, such as lower body mass index and higher fasted plasma fibroblast growth factor 21 concentrations. Sweet preference may moderate biopsychological metabolic and appetitive responses to savoury or sweet primes. Due to the small sample size and other methodological features of these analyses, future work should establish the causality of these findings, and may need to consider sweet preference a priori when designing health and appetite research relating to sweetness.


Sensors ◽  
2015 ◽  
Vol 15 (3) ◽  
pp. 6133-6151 ◽  
Author(s):  
Mikkel Schneller ◽  
Mogens Pedersen ◽  
Nidhi Gupta ◽  
Mette Aadahl ◽  
Andreas Holtermann

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