4 research outputs found
A high protein diet (3.4 g/kg/d) combined with a heavy resistance training program improves body composition in healthy trained men and women - a follow-up investigation
Background The consumption of a high protein diet (\u3e4 g/kg/d) in trained men and women who did not alter their exercise program has been previously shown to have no significant effect on body composition. Thus, the purpose of this investigation was to determine if a high protein diet in conjunction with a periodized heavy resistance training program would affect indices of body composition, performance and health. Methods Forty-eight healthy resistance-trained men and women completed this study (meanβΒ±βSD; Normal Protein group [NP nβ=β17, four female and 13 male]: 24.8βΒ±β6.9 yr; 174.0βΒ±β9.5 cm height; 74.7βΒ±β9.6 kg body weight; 2.4βΒ±β1.7 yr of training; High Protein group [HP nβ=β31, seven female and 24 male]: 22.9βΒ±β3.1 yr; 172.3βΒ±β7.7 cm; 74.3βΒ±β12.4 kg; 4.9βΒ±β4.1 yr of training). Moreover, all subjects participated in a split-routine, periodized heavy resistance-training program. Training and daily diet logs were kept by each subject. Subjects in the NP and HP groups were instructed to consume their baseline (~2 g/kg/d) and \u3e3 g/kg/d of dietary protein, respectively. Results Subjects in the NP and HP groups consumed 2.3 and 3.4 g/kg/day of dietary protein during the treatment period. The NP group consumed significantly (pβ\u3cβ0.05) more protein during the treatment period compared to their baseline intake. The HP group consumed more (pβ\u3cβ0.05) total energy and protein during the treatment period compared to their baseline intake. Furthermore, the HP group consumed significantly more (pβ\u3cβ0.05) total calories and protein compared to the NP group. There were significant time by group (pββ€β0.05) changes in body weight (change: +1.3βΒ±β1.3 kg NP, β0.1βΒ±β2.5 HP), fat mass (change: β0.3βΒ±β2.2 kg NP, β1.7βΒ±β2.3 HP), and % body fat (change: β0.7βΒ±β2.8 NP, β2.4βΒ±β2.9 HP). The NP group gained significantly more body weight than the HP group; however, the HP group experienced a greater decrease in fat mass and % body fat. There was a significant time effect for FFM; however, there was a non-significant time by group effect for FFM (change: +1.5βΒ±β1.8 NP, +1.5βΒ±β2.2 HP). Furthermore, a significant time effect (pββ€β0.05) was seen in both groups vis a vis improvements in maximal strength (i.e., 1-RM squat and bench) vertical jump and pull-ups; however, there were no significant time by group effects (pββ₯β0.05) for all exercise performance measures. Additionally, there were no changes in any of the blood parameters (i.e., basic metabolic panel). Conclusion Consuming a high protein diet (3.4 g/kg/d) in conjunction with a heavy resistance-training program may confer benefits with regards to body composition. Furthermore, there is no evidence that consuming a high protein diet has any deleterious effects
The Effects of A High Protein Diet on Performance and Body Composition in Trained Men and Women
The effects of heavy resistance training and a high protein diet (3.4g/kg/d) on body composition, exercise performance and indices of health in resistance-trained individuals - a follow-up investigation
Mid-pregnancy sleep disturbances are not associated with mid-pregnancy maternal glycemia
Background: In pregnancy, epidemiological data have consistently shown strong associations between sleep quality and duration and maternal glycemia. However, other sleep disturbances such as difficulty falling asleep and staying asleep are common in pregnancy. They may contribute to impaired maternal glycemia through sympathetic nervous system activity, systemic inflammation, and hormonal pathways. However, there is little research examining associations between these specific sleep disturbances and maternal glycemia.
Objective: This study aimed to investigate the associations of sleep disturbances during mid-pregnancy and mid-pregnancy maternal glycemia and gestational diabetes subtypes.
Study design: This is a secondary data analysis of the Comparison of Two Screening Strategies for Gestational Diabetes trial. Participants (n = 828) self-reported the frequency of sleep disturbances (i.e., trouble falling asleep, trouble staying asleep, waking several times per night, and waking feeling tired or worn out) in mid-pregnancy. Gestational diabetes was diagnosed using either the International Associations of Diabetes and Pregnancy Study Groups or Carpenter-Coustan approach. We defined gestational diabetes subtypes based on the degree of insulin resistance and beta-cell dysfunction. We used multinomial logistic regression to examine associations of sleep disturbances with gestational diabetes status (i.e., normal, mild glycemic dysfunction, and gestational diabetes) and gestational diabetes subtypes (i.e., neither insulin resistance or beta-cell dysfunction, insulin resistance only, beta-cell dysfunction only, and insulin resistance and beta-cell dysfunction).
Results: A total of 665 participants (80%) had normal glycemia, 81 (10%) mild hyperglycemia, and 80 (10%) had gestational diabetes. Among participants with gestational diabetes, 62 (78%) had both insulin resistance and beta-cell dysfunction, 15 (19 %) had insulin resistance only, and 3 had beta-cell dysfunction only or neither insulin resistance nor beta-cell dysfunction. Sleep disturbance frequency was not associated with maternal glycemia or gestational diabetes subtypes.
Conclusions: Sleep disturbances in mid-pregnancy were not associated with maternal glycemia during mid-pregnancy. Future research should collect data on sleep disturbances at multiple time points in pregnancy and in combination with other sleep disturbances to determine whether sleep plays any role in maternal glycemic control