Trevor Simper

Nutritional Peak Week and Competition Day Strategies of Competitive Natural Bodybuilders

Bodybuilders utilize peaking strategies in a bid to fine-tune their aesthetics for competition day. The most prevalent peaking strategies utilized by natural bodybuilders are unreported in the current literature. Eighty-one (M-59, F-22) natural bodybuilders were recruited from competitions during the 2016 and 2017 British Natural Bodybuilder Federation seasons. Competitors completed a 34-item questionnaire designed to investigate peaking and contest day strategies. The questionnaire listed commonly utilized peaking strategies and provided additional space for qualitative information. Analysis of the data indicated that carbohydrate (CHO), water, and sodium manipulation were the most commonly utilized peaking strategies. The consumption of high glycemic index CHO was the most common competition day strategy. Only 6.2% of competitors reported following their regular diet the week prior to competition. The CHO manipulation strategies followed were similar to classical CHO loading, whereby bodybuilders attempt to maximize muscle glycogen concentrations. Furthermore, bodybuilders attempted to remove superfluous water by exploiting the diuretic/polyuria effect associated with water loading/restriction. The potentially deleterious effects of peaking on bodybuilders’ health is considered and the efficacy of these strategies to enhance appearance is discussed. The findings of the present investigation are likely to be of interest to bodybuilders and their coaches.

Citrulline malate has no effect on German Volume Training Protocol - abstract only

Total energy expenditure (TEE) has been quantified in elite senior rugby league (RL) and rugby union (RU) players using multiple measures, with criterion measures lacking in RU and academy players. Robust measures of TEE are required as prediction equations used to estimate energy requirements are often unsuitable for athletes. This study quantified TEE of 27 elite male English academy (U16 and U20) and senior (U24) RL and RU players during a 14-day in-season period using doubly labelled water (DLW). Resting metabolic rate (RMR), using indirect calorimetry, and physical activity level (PAL) was also measured (TEE:RMR). Predicted TEE, determined by published equations, was compared to measured TEE by age group. Differences in TEE (RL, 4369 ± 979; RU, 4365 ± 1122; U16, 4010 ± 744; U20, 4414 ± 688; U24, 4761 ± 1523 Kcal.day-1) and PAL (overall mean 2.0 ± 0.4) were unclear. RMR was very likely greater for RL (2366 ± 296 Kcal.day-1) than RU players (2123 ± 269 Kcal.day-1). Relative RMR for U16, U20 and U24 (27 ± 4, 23 ± 3 and 26 ± 5 Kcal.Kg-1.day-1) was very likely greater for U20 than U24 players. Differences in TEE estimated by the Schofield, Cunningham and Harris-Benedict equations compared with DLW were unclear, likely and unclear for U16 (187 ± 614; -489 ± 564 and -90 ± 579 Kcal.day-1), likely, very likely and likely for U20 (-449 ± 698; -785 ± 650 and -452 ± 684 Kcal.day-1) and all unclear for U24 players (-428 ± 1292; -605 ± 1493 and -461 ± 1314 Kcal.day-1). Due to large variability between individuals, negligible differences in TEE were observed by code, and ~350-400 Kcal.day-1 differences between consecutive age groups were unclear. Differences in RMR may be due to training exposure and match play. The remaining components of TEE (i.e. thermic effect of feeding and activity thermogenesis) may reflect the differences in contact demands between codes, as RU players typically engage in more static exertions than RL players during match play. Prediction equations are currently insufficient to differentiate between individual variability in TEE. The importance of practitioners providing individual support for the elite rugby player is highlighted. Finally, the TEE measured in this study using the gold standard DLW method can be used as reference data for elite rugby players of different codes and ages, during an in-season training period.

Dietary strategies of elite natural bodybuilders - abstract only

Total energy expenditure (TEE) has been quantified in elite senior rugby league (RL) and rugby union (RU) players using multiple measures, with criterion measures lacking in RU and academy players. Robust measures of TEE are required as prediction equations used to estimate energy requirements are often unsuitable for athletes. This study quantified TEE of 27 elite male English academy (U16 and U20) and senior (U24) RL and RU players during a 14-day in-season period using doubly labelled water (DLW). Resting metabolic rate (RMR), using indirect calorimetry, and physical activity level (PAL) was also measured (TEE:RMR). Predicted TEE, determined by published equations, was compared to measured TEE by age group. Differences in TEE (RL, 4369 ± 979; RU, 4365 ± 1122; U16, 4010 ± 744; U20, 4414 ± 688; U24, 4761 ± 1523 Kcal.day-1) and PAL (overall mean 2.0 ± 0.4) were unclear. RMR was very likely greater for RL (2366 ± 296 Kcal.day-1) than RU players (2123 ± 269 Kcal.day-1). Relative RMR for U16, U20 and U24 (27 ± 4, 23 ± 3 and 26 ± 5 Kcal.Kg-1.day-1) was very likely greater for U20 than U24 players. Differences in TEE estimated by the Schofield, Cunningham and Harris-Benedict equations compared with DLW were unclear, likely and unclear for U16 (187 ± 614; -489 ± 564 and -90 ± 579 Kcal.day-1), likely, very likely and likely for U20 (-449 ± 698; -785 ± 650 and -452 ± 684 Kcal.day-1) and all unclear for U24 players (-428 ± 1292; -605 ± 1493 and -461 ± 1314 Kcal.day-1). Due to large variability between individuals, negligible differences in TEE were observed by code, and ~350-400 Kcal.day-1 differences between consecutive age groups were unclear. Differences in RMR may be due to training exposure and match play. The remaining components of TEE (i.e. thermic effect of feeding and activity thermogenesis) may reflect the differences in contact demands between codes, as RU players typically engage in more static exertions than RL players during match play. Prediction equations are currently insufficient to differentiate between individual variability in TEE. The importance of practitioners providing individual support for the elite rugby player is highlighted. Finally, the TEE measured in this study using the gold standard DLW method can be used as reference data for elite rugby players of different codes and ages, during an in-season training period.

Weight locus of control' and weight management in an urban population.

This manuscript relates to weight locus of control in an urban population; essentially analysing the relationship between Body Mass Index and the perception of to what degree control over bodyweight is internally or externally controlled.

Dietary Strategies of Elite Natural Bodybuilders

Introduction The British Natural Bodybuilding Federation UK finals provided an opportunity to study the dietary and training practices of elite natural bodybuilders. To prepare for competition bodybuilders utilise a combination of resistance and cardiovascular exercise, calorie reduction, supplement regimes and peaking strategies(1). Although recommendations exist(2,3), and there is a paucity of applied research in this area (4,5). Here we report the results of a recent cross-sectional study investigating the preparation strategies of natural bodybuilders.

Responses to oral glucose challenge differ by physical activity volume and intensity: A pilot study

Background One-hour postprandial hyperglycemia is associated with increased risk of type 2 diabetes and cardiovascular disease. Physical activity (PA) has short-term beneficial effects on post-meal glucose response. This study compared the oral glucose tolerance test results of 3 groups of people with habitually different levels of PA. Methods Thirty-one adults without diabetes (age 25.9 ± 6.6 years; body mass index 23.8 ± 3.8 kg/m2; mean ± SD) were recruited and divided into 3 groups based on self-reported PA volume and intensity: low activity < 30 min/day of moderate-intensity activity (n = 11), moderately active ≥ 30 min/day of moderate-intensity PA (n = 10), and very active ≥ 60 min/day of PA at high intensity (n = 10). Participants completed an oral glucose tolerance test (50 g glucose) with capillary blood samples obtained at baseline, 15 min, 30 min, 45 min, 60 min, 90 min, and 120 min post-ingestion. Results There were no significant differences between groups for age or body fat percentage or glycated hemoglobin (p > 0.05). The groups were significantly different in terms of baseline glucose level (p = 0.003) and, marginally, for gender (p = 0.053) and BMI (p = 0.050). There was a statistically significant effect of PA on the 1-h postprandial glucose results (p = 0.029), with differences between very active and low activity groups (p = 0.008) but not between the moderately active and low activity groups (p = 0.360), even when baseline glucose level and gender differences were accounted for. For incremental area under the curve there was no significant effect of activity group once gender and body fat percentage had been accounted for (p = 0.401). Those in the low activity group took 15 min longer to reach peak glucose level than those in the very active group (p = 0.012). Conclusion The results suggest that high levels of PA have a beneficial effect on postprandial blood glucose profiles when compared to low and moderate levels of activity.

Comparison of responses to oral glucose challenge by physical activity duration and intensity

The glycaemic response to an oral glucose tolerance test (OGTT) can be used to predict risk of development of type 2 diabetes mellitus. Low habitual physical activity is associated with undiagnosed impaired glucose tolerance and type 2 diabetes, and OGTT response is inversely related to physical activity levels in a population at risk of T2D development. However the relationship between habitual physical activity and OGTT response in a low-risk population is not as well understood. The study was approved by the Ethics Committee of Sheffield Hallam University and all participants provided written informed consent. Thirty-one non-diabetic adults (25·9yrs ±6·6; 23·8 kg/m ±3·8) participated. An OGTT was performed: capillary blood samples were obtained and analysed for blood glucose at baseline, 15, 30, 45, 60, 90 and 120 minutes after ingestion of 50 g of glucose. Participants were categorised into 3 groups based on self-reported physical activity levels: Sedentary (< 30 min.day−1 ‘moderate’ intensity activity, n= 11), Active (⩾ 30 min.day−1 of ‘moderate’ intensity physical activity, n= 10) and Very Active (⩾ 60 min.day−1 of ‘intense’ physical activity (n= 10). There were no significant differences between groups for age or percentage body fat (P> 0·05); however, there was a significant difference between groups for BMI (P= 0·043). Area under the curve (AUC) was significantly impacted by the intensity and duration of physical activity (P= 0·049) with the AUC of the very active group being significantly lower than that of the sedentary and active groups (P= 0·027 and P = 0·041 respectively). There was no significant difference between the active and sedentary groups (P= 0·844).

Small-group weight management programme using self selected goals improves General Well Being scores

Background: normal weight obesity (NWO) is defined as an excessive body fat associated with a normal body mass index (BMI<25 kg/m2), but its prevalence in the general population is unknown. Objective: to assess the prevalence of NWO in Switzerland according to different cut points used to define excess body fat. Design: cross-sectional study including 3,213 women and 2,912 men aged 35-75 years. Body fat was assessed by bioimpedance and prevalence of NWO was assessed using four previously published definitions for excess body fat. Results: % body fat increased with age: in men, the values (mean SD) were 20.2 5.4, 23.0 5.4, 26.3 5.2 and 28.2 4.6 for age groups [35 - 44], [45 - 54], [55 - 64] and [65 - 75] years, respectively; the corresponding values for women were 29.9 7.8, 33.1 7.4, 36.7 7.5 and 39.6 6.9. In men, prevalence of NWO was <1% irrespective of the definition used. Conversely, in women, a one to twenty fold difference (from 1.4% to 27.8%) in NWO prevalence was found. The prevalence of NWO increased with age when age-independent cut points were used in women, but not in men. Conclusions: prevalence of NWO is low in the general population and higher in women than in men. The prevalence is highly dependent on the criteria used to define excess body fat, namely in women. The use of gender- and age-specific cut points to define excess body fat is better than fixed or gender-specific only cut points.Background and Aims: normal weight obesity (NWO) has been defined as an excessive body fat (BF) associated with a normal body mass index (BMI). Little is known regarding its prevalence in the general population or which cut-offs for BF should be used. Methods: convenience sample of 1,523 Portuguese adults. BF was measured by validated hand-held bioimpedance. NWO was defined as a BMI 30%, along other published criteria. Results: prevalence of NWO was 10.1% in women and 3.2% in men. In women, prevalence of NWO increased considerably with age, and virtually all women aged over 55 with a BMI<25 kg/m2 were actually considered as NWO. Using gender specific cut-offs for BF (29.1% in men and 37.2% in women) led to moderately lower of NWO in women. Using gender- and age-specific cut-points for %BF considerably decreased the prevalence of NWO in women (0.5 to 2.5% depending on the criterion) but not in men (1.9 to 3.4%). Conclusions: gender- and age- specific or at least gender-specific, instead of single cut-offs for %BF, should be used to characterize and study NWO.