Does Weight Loss And Exercise Training Alter Hormone Levels In Older Obese And Overweight Adults?

2005 ◽  
Vol 37 (Supplement) ◽  
pp. S353
Author(s):  
Michelle J. Steiner ◽  
Gary D. Miller ◽  
Cralen C. Davis ◽  
Barbara J. Nicklas ◽  
Stephen P. Messier
2005 ◽  
Vol 37 (Supplement) ◽  
pp. S353
Author(s):  
Michelle J. Steiner ◽  
Gary D. Miller ◽  
Cralen C. Davis ◽  
Barbara J. Nicklas ◽  
Stephen P. Messier

2018 ◽  
Vol 43 (4) ◽  
pp. 363-370 ◽  
Author(s):  
Matthew Jackson ◽  
Fardin Fatahi ◽  
Kholoud Alabduljader ◽  
Charlotte Jelleyman ◽  
Jonathan P. Moore ◽  
...  

Individuals show high variability in body weight responses to exercise training. Expectations and motivation towards effects of exercise on body weight might influence eating behaviour and could conceal regulatory mechanisms. We conducted 2 single-blind exercise trials (4 weeks (study 1) and 8 weeks (study 2)) with concealed objectives and exclusion of individuals with weight loss intention. Circuit exercise training programs (3 times a week (45–90 min), intensity 50%–90% peak oxygen uptake for 4 and 8 weeks) were conducted. Thirty-four females finished the 4-week intervention and 36 females the 8-week intervention. Overweight/obese (OV/OB) and lean female participants’ weight/body composition responses were assessed and fasting and postprandial appetite hormone levels (PYY, insulin, amylin, leptin, ghrelin) were measured before and after the intervention for understanding potential contribution to individuals’ body weight response to exercise training (study 2). Exercise training in both studies did not lead to a significant reduction of weight/body mass index (BMI) in the participants’ groups; however, lean participants gained muscle mass. Appetite hormones levels were significantly (p < 0.05) altered in the OV/OB group, affecting fasting (−24%) and postprandial amylin (−14%) levels. Investigation of individuals’ BMI responses using multiple regression analysis revealed that levels of fasting leptin, postprandial amylin increase, and BMI were significant predictors of BMI change, explaining about 43% of the variance. In conclusion, tested exercise training did not lead to weight loss in female participants, while a considerable proportion of variance in body weight response to training could be explained by individuals’ appetite hormone levels and BMI.


2019 ◽  
Vol 26 (1) ◽  
pp. 10-20
Author(s):  
Maija Huttunen-Lenz ◽  
Sylvia Hansen ◽  
Thomas Meinert Larsen ◽  
Pia Christensen ◽  
Mathijs Drummen ◽  
...  

Abstract. Individuals at risk of Type 2 Diabetes are advised to change health habits. This study investigated how the PREMIT behavior modification intervention and its association with socio-economic variables influenced weight maintenance and habit strength in the PREVIEW study. Overweight adults with pre-diabetes were enrolled ( n = 2,224) in a multi-center RCT including a 2-month weight-loss phase and a 34-month weight-maintenance phase for those who lost ≥ 8% body weight. Initial stages of the PREMIT covered the end of weight-loss and the beginning of weight-maintenance phase (18 weeks). Cross-sectional and longitudinal data were explored. Frequent PREMIT sessions attendance, being female, and lower habit strength for poor diet were associated with lower weight re-gain. Being older and not in employment were associated with lower habit strength for physical inactivity. The PREMIT appeared to support weight loss maintenance. Younger participants, males, and those in employment appeared to struggle more with inactivity habit change and weight maintenance.


Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 2062-P
Author(s):  
JOSIANE L. BROUSSARD ◽  
DARCY E. KAHN ◽  
SEAN A. NEWSOM ◽  
JOSEPH T. BROZINICK ◽  
HAI BUI ◽  
...  

Circulation ◽  
2015 ◽  
Vol 131 (suppl_1) ◽  
Author(s):  
Christopher E Kline ◽  
Patrick J Strollo ◽  
Eileen R Chasens ◽  
Bonny Rockette-Wagner ◽  
Andrea Kriska ◽  
...  

Background: Sleep is emerging as an important factor that impacts dietary habits, physical activity, and metabolism. However, minimal attention is typically given to sleep in traditional lifestyle interventions. The purpose of these analyses was to examine baseline associations between sleep and physical activity and perceived barriers to healthy eating, which are two common lifestyle intervention targets, in a sample of apparently healthy adults enrolled in a behavioral weight loss intervention study. Methods: 150 overweight adults (51.1±10.2 y; 91% female; 79% Caucasian) participated in a 12-month lifestyle intervention that featured adaptive ecological momentary assessment. Sleep, physical activity, barriers to healthy eating and body habitus/composition were assessed prior to the intervention. Objective sleep was estimated with 7 days of wrist-worn actigraphy (Philips Actiwatch 2); sleep onset latency (SOL; the amount of time it takes to fall asleep after going to bed), sleep efficiency (SE; the percentage of time in bed that is spent asleep), and total sleep time (TST; total time spent asleep) served as the primary actigraphic sleep variables. Subjective sleep quality was assessed with the Pittsburgh Sleep Quality Index (PSQI). Physical activity was assessed with 7 days of waist-worn accelerometry (ActiGraph GT3x). Perceived barriers to healthy eating were assessed with the Barriers to Healthy Eating questionnaire. Body mass index (BMI) served as the measure of body habitus, and body fat was assessed with bioelectrical impedance. Results: Mean BMI and body fat for the sample were 34.0±4.6 kg/m2 and 43.7±5.5%, respectively. Mean TST was 6.6±0.8 h/night; approximately 23% of the sample averaged less than 6 hours of sleep. Mean SOL and SE for the sample were 15.3±16.2 min and 85.7±6.1%, respectively. Based on the PSQI, 52.0% of the sample had poor sleep quality. Following adjustment for age, sex, and race, longer SOL was associated with fewer steps/day (β=-.19, p=.02) and less time spent in moderate to vigorous physical activity (MVPA; β=-.16, p=.03), and lower SE was related to less MVPA (β=.15, p=.04). Shorter TST was associated with greater barriers to healthy eating (β=-.16, p=.05). Longer SOL was associated with higher BMI (β=.16, p=.05) and body fat % (β=.15, p=.03), and lower SE was related to higher body fat % (β=-.13, p=.06). Conclusions: Short sleep duration and sleep disturbance were highly prevalent in this sample of overweight adults. Significant associations were observed between sleep and measures of body habitus/composition and eating and physical activity habits. Efforts to improve sleep during a behavioral intervention for weight loss may reduce barriers to healthy eating and improve physical activity habits as well as weight loss outcomes.


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