Purpose: To assess the dietary intake and body composition of recreational and competitive female athletes, for the purpose of analyzing the relationships between macronutrient intake and body composition.. The main aim was to determine the relationship between caloric intake, carbohydrate (CHO) intake and protein intake with body fat percentage in active females. Methods: Using an IRB approved protocol, 44 volunteer female recreational and competitive athletes 18 years of age or older were recruited. Interviews were conducted to gather information on within day energy balance by assessing the time and amount of foods/beverages consumed, and the duration and intensity (using a Rating of Perceived Exertion scale) of activity performed on the day of assessment. All analyses were performed using Nutritiming™ (Calorie and Pulse Technologies, Atlanta, GA) to assess energy surpluses, energy deficits, and end of day energy balance. Information on date of birth, race/ethnicity, menstrual status, sleep and wake times, and prior diagnoses of metabolic disease and/or eating disorders were collected at the time of the interview. Height was assessed using a standard stadiometer. Weight and body composition were assessed via Bioelectrical Impedance Analysis (BIA) using InBody 230 (BioSpace Co. USA). The BIA assessment was performed to determine body fat percentage, Basal Metabolic Rate (BMR), Body Mass Index (BMI), segmental body composition, and fat and lean mass in kilograms. Nutrient data were derived using an interviewer-led, 24-hour recall. Results: CHO intake/kg total mass was significantly and inversely correlated with body fat percentage and BMI, (p=0.018 and p=0.001 respectively). Protein intake/kg total mass was also inversely and significantly correlated with body fat percentage (p=0.006). Fat intake was not significantly associated with BMI, body fat percent, or lean mass in kilograms. Total energy intake/kg total mass was inversely associated with BMI (p=0.001), with fat mass (p=0.001), and with body fat percentage, (p=0.001). CHO intake/kg total mass was positively associated with the total number of hours spent in an anabolic (i.e., EB>0) state (p=0.001), and was inversely associated with the total number of hours spent in a catabolic (i.e., EB < 0) state (p=0.001). CHO intake/kg total mass was the only substrate to be significantly correlated with the number of hours spent ± 400 kcal EB over a 24 hour period (p=0.001). Z-scores were created to establish categories of body composition and energy balance values. Utilizing Chi-Square tests, it was determined that more hours spent in an energy surplus (> 400kcal) was associated with higher body fat percent (p=0.042). Conclusions: CHO restriction, whether done intentionally or as a function of an energy restrictive intake, was commonly observed in this subject pool. Of the females surveyed, 79% did not meet their daily energy needs and, on average, consumed 49% of the recommended daily intake of CHO established for active people. The findings that subjects with lower CHO intakes had higher body fat levels, and that CHO was associated with improved maintenance of energy balance, which was also associated with lower body fat percent, suggest that physically active women should not restrict CHO to achieve a desired body composition. It was also observed that end-of-day energy balance was not associated with either energy substrate consumption or body composition.

The topic of my master thesis is monitoring of carbohydrate intake in sportsmen's diet. In the thesis, intake of carbohydrates as well as other macronutrients is monitored in order to evaluate, if athletes prefer other energy sources to carbohydrates and if their total energy intake is sufficient. If athletes prefer easily digestible carbohydrates or if they follow recommendation for healthy diet and increase their intake of whole foods, legumes, fruits and vegetables can be evaluated by monitoring fiber and sugar intake. All the monitored data are compared with non-athletes in order to see, in which field their diets vary. In the theoretical part, principles of sports nutrition are defined, basics of population recommendations are mentioned and methods of nutritional assessment and energy expenditure estimation are explained. In the practical part, five-day food-diaries of athletes and non-athletes are evaluated by NutriPro Expert software. Five-day physical activity diaries recorded during the same days are evaluated by using the Compendium of Physical Activities. All the studied values (energy intake, energy expenditure, carbohydrate, fat, protein, sugar, fiber and alcohol intake) were compared to recommended values for athletes and non- athletes and further compared among these two groups. The...

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Adiponectin is an adipose-derived protein (adipocytokine) that is secreted by adipose tissue. It has insulin-sensitizing, anti-inflammatory and cardio-protective properties, and is thought to be protective against obesity-related diseases such as type 2 diabetes. Humans and cats are two species that commonly develop type 2 diabetes associated with insulin resistance, impaired beta cell function and spontaneous islet amyloid deposition. The domestic cat (Felis catus) has recently been proposed as an animal model for human type 2 diabetes. However, little is known about the physiology of adiponectin in cats. Therefore, we set out to investigate the association of adiponectin profiles with dietary carbohydrate intake, feeding, body weight, fat mass, and insulin sensitivity in healthy young adult cats (n=32; 2-4 years old; gender ratio 1:1; body condition 4-5/9). Cats were fed a moderate carbohydrate diet (37% ME) at maintenance energy requirements for four weeks. Cats were then assigned to either receive a low (19% ME) or high (52% ME) carbohydrate diet and fed at maintenance energy requirements for another four weeks, followed by ad-libitum feeding for eight weeks to facilitate weight gain. Adiponectin profiles including total circulating adiponectin and its distribution [low molecular weight (LMW) and high molecular weight (HMW) adiponectin], and proportion of adiponectin that is HMW (SA) were measured by ELISA and velocity sedimentation using sucrose gradients, followed by Western blotting, respectively. We demonstrated inter-animal variation in total adiponectin concentration at baseline (0.6 to 15.0 g/mL), with the adiponectin present in both LMW and HMW forms. Feeding with a high carbohydrate diet for four weeks at maintenance energy requirements resulted in increased total adiponectin concentration, which was associated with an increased concentration of LMW adiponectin. In contrast, feeding with a low carbohydrate diet for four weeks at maintenance energy requirements resulted in increased concentration of HMW adiponectin, decreased LMW adiponectin concentration, and increased SA, without a change in total adiponectin concentration. In cats fed the high carbohydrate diet, total adiponectin and HMW adiponectin concentrations become lower at six hours after feeding, as compared to the fasting concentrations. This phenomenon was not observed in cats fed a low carbohydrate diet, indicating a diet-dependent postprandial effect. There was no effect of gender on any of the adiponectin profiles in cats. Unlike other studies in humans and mice in which adiponectin concentrations decreased as fat mass increased, our data indicate that a moderate weight gain achieved by ad libitum feeding of a low carbohydrate diet for eight weeks correlated with increased adiponectin concentrations. Total adiponectin concentration (mirrored by HMW adiponectin) was positively correlated with body weight gain and fat mass gain (but not absolute fat mass) in our overweight cats. Furthermore, the fat mass-related increases in plasma adiponectin over eight weeks correlated with insulin sensitivity (higher adiponectin concentration corresponded to greater insulin sensitivity in overweight cats). These data hint at the possibility that in overweight animals, adiponectin is similar to other adipokines that rise concomitantly with increased of moderate fat mass gain and thus increases insulin sensitivity. Overall, the knowledge in this study therefore provides useful information to veterinarians and cat food manufacturers, and forms a foundation for future studies to extend our knowledge of adiponectin in cats. Data gathered in cats may also be applicable to humans and could therefore inform research using cats as an animal model of human obesity and type 2 diabetes.

Adiponectin is an adipose-derived protein (adipocytokine) that is secreted by adipose tissue. It has insulin-sensitizing, anti-inflammatory and cardio-protective properties, and is thought to be protective against obesity-related diseases such as type 2 diabetes. Humans and cats are two species that commonly develop type 2 diabetes associated with insulin resistance, impaired beta cell function and spontaneous islet amyloid deposition. The domestic cat (Felis catus) has recently been proposed as an animal model for human type 2 diabetes. However, little is known about the physiology of adiponectin in cats. Therefore, we set out to investigate the association of adiponectin profiles with dietary carbohydrate intake, feeding, body weight, fat mass, and insulin sensitivity in healthy young adult cats (n=32; 2-4 years old; gender ratio 1:1; body condition 4-5/9). Cats were fed a moderate carbohydrate diet (37% ME) at maintenance energy requirements for four weeks. Cats were then assigned to either receive a low (19% ME) or high (52% ME) carbohydrate diet and fed at maintenance energy requirements for another four weeks, followed by ad-libitum feeding for eight weeks to facilitate weight gain. Adiponectin profiles including total circulating adiponectin and its distribution [low molecular weight (LMW) and high molecular weight (HMW) adiponectin], and proportion of adiponectin that is HMW (SA) were measured by ELISA and velocity sedimentation using sucrose gradients, followed by Western blotting, respectively. We demonstrated inter-animal variation in total adiponectin concentration at baseline (0.6 to 15.0 g/mL), with the adiponectin present in both LMW and HMW forms. Feeding with a high carbohydrate diet for four weeks at maintenance energy requirements resulted in increased total adiponectin concentration, which was associated with an increased concentration of LMW adiponectin. In contrast, feeding with a low carbohydrate diet for four weeks at maintenance energy requirements resulted in increased concentration of HMW adiponectin, decreased LMW adiponectin concentration, and increased SA, without a change in total adiponectin concentration. In cats fed the high carbohydrate diet, total adiponectin and HMW adiponectin concentrations become lower at six hours after feeding, as compared to the fasting concentrations. This phenomenon was not observed in cats fed a low carbohydrate diet, indicating a diet-dependent postprandial effect. There was no effect of gender on any of the adiponectin profiles in cats. Unlike other studies in humans and mice in which adiponectin concentrations decreased as fat mass increased, our data indicate that a moderate weight gain achieved by ad libitum feeding of a low carbohydrate diet for eight weeks correlated with increased adiponectin concentrations. Total adiponectin concentration (mirrored by HMW adiponectin) was positively correlated with body weight gain and fat mass gain (but not absolute fat mass) in our overweight cats. Furthermore, the fat mass-related increases in plasma adiponectin over eight weeks correlated with insulin sensitivity (higher adiponectin concentration corresponded to greater insulin sensitivity in overweight cats). These data hint at the possibility that in overweight animals, adiponectin is similar to other adipokines that rise concomitantly with increased of moderate fat mass gain and thus increases insulin sensitivity. Overall, the knowledge in this study therefore provides useful information to veterinarians and cat food manufacturers, and forms a foundation for future studies to extend our knowledge of adiponectin in cats. Data gathered in cats may also be applicable to humans and could therefore inform research using cats as an animal model of human obesity and type 2 diabetes.

L’activité physique (AP) est liée à plusieurs bénéfices pour la santé chez les personnes atteintes de diabète de type 1 (DT1), mais elles sont peu actives dû à la peur des hypoglycémies liée à l’AP. Un apport en glucides est souvent requis pour prévenir les hypoglycémies lors d’une AP, mais il y a un manque de connaissances quant à la quantité à consommer et la distribution temporelle idéales des glucides. Notre objectif est de comparer l’efficacité de 2 stratégies de collation pour maintenir la glycémie dans les cibles (4,0 - 10,0 mmol/L) lors d’une AP chez les adolescents et adultes avec le DT1. Les participants (N=33) ont effectué 2 interventions durant lesquelles une heure d’ergocycle à intensité moyenne a été réalisée. Ils consommaient un apport en glucides de 0,5g/kg du poids corporel et cet apport était aléatoirement consommé en une prise unique (PU) avant l’AP ou en une prise répartie (PR) avant et pendant l’AP. La GC était mesurée toutes les 10 minutes durant l’AP. Quatre participants ont eu une hypoglycémie durant l’AP avec la PU comparativement à 6 participants pour la PR (P=0,42). Il n’y avait pas de différence significative pour le pourcentage de temps passé dans les cibles entre les deux stratégies (PU : 75 ± 35%; PR : 87 ± 26%; P=0,12). Nos résultats suggèrent qu’un apport en glucide de 0.5g/kg du poids corporel est une option raisonnable pour une AP d’intensité moyenne d’une heure. Les deux stratégies sont similaires pour prévenir les hypoglycémies lors de l’AP. / Physical activity (PA) is associated to many health benefits in people living with type 1 diabetes (T1D), but these patients are not very active due to the fear of PA-related hypoglycemia. Carbohydrate intake is often required to prevent hypoglycemia during PA, but there is a lack of knowledge about the ideal amount to consume and the timing distribution of carbohydrates. Our objective is to compare the efficacy of two snack strategies to maintain glucose levels in the target range (4.0 – 10.0 mmol/L) during PA in adolescents and adults living with T1D. The participants (N = 33) took part in 2 interventions during which one hour of moderate intensity ergocycle was performed. They consumed a carbohydrate intake of 0.5g/kg of body weight and this intake was randomly consumed in a single intake (SI) before PA or in a distributed intake (DI) before and during PA. Capillary blood glucose was measured every 10 minutes during PA. Hypoglycemia occurred in 4 participants with SI compared to 6 participants for DI (P = 0.42). There was no significant difference in the percentage of time spent in the target range between the two strategies (SCI: 75 ± 35%; DCI: 87 ± 26%; P = 0.12). Our results suggest that a carbohydrate intake of 0.5g/kg of body weight is a reasonable option for one hour of moderate PA. The two snack strategies are similar to prevent hypoglycemia during PA.