The Relationship Between Family and Friend Social Support on Balance in Older Adults

The Relationship Between Family and Friend Social Support on Balance in Older Adults Moss K and Deo K Older adults are more likely to have longer hospital stays, health care utilization, increased medical prescriptions, and greater risk of falling as their age increases. Many of the injuries sustained in older adults can be attributed to poor balance; this can be improved with exercise. Despite the clear benefits to exercise many older adults still choose not to participate in exercise programs; or they do not participate in exercise activities on a consistent basis. Social support from family and friends could attribute to the likelihood that individuals will exercise regularly and see overall improvement in fitness. However, the effect of social support on these outcomes has not been well studied. The purpose of this study was to examine the relationship between social support from family and friends on balance improvements in older adults. Thirty-one participants total (age 75 + 4.7 yrs.) of the Center of Healthy Living and Longevity at UTA met the criteria to participate in this study. Each participant was asked to complete the Social Support Exercise Survey (measures family/friend support and discouragement), Revised Cheek and Buss Shyness Scale (RCBS); along with the Balance Efficiency Survey before the exercise sessions began and ended for the semester. Also, the participants’ balance was assessed using Sensory Organization Test (SOT) on the NeuroCom EquiTest before and after the intervention. In addition, the participants completed the Senior Fitness Test; that measures flexibility, agility, strength, and endurance. The exercise sessions were held three times a week for a total of 12 weeks. The exercises involved cardiovascular, balance, strength, and flexibility exercises. During each exercise session the participant’s attendance was taken. There was a marginally significant negative relationship between the participants change in shyness and their mean attendance percentage (r=0.31, p\u3c0.08). There was also a relationship between change in exercise related family punishment and change in performance on the two-minute step test (r=-0.49, p\u3c0.01). Also, there was a relationship between the change in friendship reward for exercise and change in visual scores on the SOT (r=0.415, p\u3c0.05); as well as for the change in peripheral balance (r=0.594, p\u3c0.001). The results of this study indicate that social support from friends and family can affect factors dealing with an individual’s overall fitness level. Social factors should be considered when designing group exercise interventions for older adults

Caffeine Supplementation Strategies Among Endurance Athletes

Caffeine is widely accepted as an endurance-performance enhancing supplement. Most scientific research studies use doses of 3–6 mg/kg of caffeine 60 min prior to exercise based on pharmacokinetics. It is not well understood whether endurance athletes employ similar supplementation strategies in practice. The purpose of this study was to investigate caffeine supplementation protocols among endurance athletes. A survey conducted on Qualtrics returned responses regarding caffeine supplementation from 254 endurance athletes (f = 134, m =120; age = 39.4 ± 13.9 y; pro = 11, current collegiate athlete = 37, recreational = 206; running = 98, triathlon = 83, cycling = 54, other = 19; training days per week = 5.4 ± 1.3). Most participants reported habitual caffeine consumption (85.0%; 41.2% multiple times daily). However, only 24.0% used caffeine supplements. A greater proportion of men (31.7%) used caffeine supplements compared with women (17.2%; p = 0.007). Caffeine use was also more prevalent among professional (45.5%) and recreational athletes (25.1%) than in collegiate athletes (9.4%). Type of sport (p = 0.641), household income (p = 0.263), education (p = 0.570) or working with a coach (p = 0.612) did not have an impact on caffeine supplementation prevalence. Of those reporting specific timing of caffeine supplementation, 49.1% and 34.9% reported consuming caffeine within 30 min of training and races respectively; 38.6 and 36.5% used caffeine 30–60 min before training and races. Recreational athletes reported consuming smaller amounts of caffeine before training (1.6 ± 1.0 mg/kg) and races (2.0 ± 1.2 mg/kg) compared with collegiate (TRG: 2.1 ± 1.2 mg/kg; RACE: 3.6 ± 0.2 mg/kg) and professional (TRG: 2.4 ± 1.1 mg/kg; RACE: 3.5 ± 0.6 mg/kg) athletes. Overall, participants reported minor to moderate perceived effectiveness of caffeine supplementation (2.31 ± 0.9 on a four-point Likert-type scale) with greatest effectiveness during longer sessions (2.8 ± 1.1). It appears that recreational athletes use lower caffeine amounts than what has been established as ergogenic in laboratory protocols; further, they consume caffeine closer to exercise compared with typical research protocols. Thus, better education of recreational athletes and additional research into alternative supplementation strategies are warranted

Caffeine Supplementation Strategies Among Endurance Athletes

Caffeine is widely accepted as an ergogenic aid for endurance performance. Many laboratory studies use doses of 3-6 mg/kg of caffeine 60 min prior to exercise. It is unclear if endurance athletes employ similar supplementation schemes in practice. Further, there is a paucity of data regarding caffeine consumption in this population. PURPOSE: The purpose of this study was to investigate caffeine supplementation strategies and consumption among endurance athletes. METHODS: A survey conducted on Qualtrics returned responses regarding caffeine supplementation from 247 endurance athletes (f = 129, m =118; age = 40.4 ± 18.4 y; pro = 11, current/former collegiate athlete = 67, recreational = 169; running = 95, triathlon = 80, cycling = 54, other = 18; training days per week = 5.4 ± 1.3). Descriptive statistics were calculated using SPSS V26. Pearson chi-square tests of independence were performed to investigate potential associations between a variety of grouping variables and caffeine use. Further, supplementation schemes were analyzed. Finally, athletes’ perception of the effectiveness of caffeine were examined. RESULTS: The majority of participants reported habitual caffeine consumption (84.2%; 34.8% multiple times daily). Yet, only 23.5% reported using caffeine supplements. A greater percentage of men (30.5%) used caffeine supplements compared with women (17.1%; p = .013). Athlete status was significantly associated with caffeine consumption (p = .004). Caffeine use was more prevalent among professional (36.4%) and recreational athletes (28.4%) compared with current/former collegiate athletes (9.0%). There were no significant differences in caffeine supplementation when comparing across type of sport (p = .505), household income (p = .191), education (p = .453) or working with a coach (p = .560). While not statistically significant (p = .064), 53.4% of those using caffeine supplements reported placing among the top 3 in their age group in the past year, compared with only 39.7% of those not using caffeine supplements. Sixty-eight athletes (27.5%) reported that they specifically timed caffeine supplementation around training (60.3% only before, 14.7% only during, 25.0% before and during sessions). Seventy-seven (31.2%) athletes reported timing caffeine intake around races (55.8% before, 13.0% during, 31.2% both). Of those reporting specific timing of caffeine use, 47.3% and 33.9% reported consuming caffeine within 30 min of training sessions and races respectively; 40.0% and 35.5% used caffeine 30-60 min before training and races; 12.7% and 36.6% reported taking caffeine \u3e60 min before training and races. The most frequently reported interval of supplementation during training (64.0%) and races (45.2%) was every 60-90 minutes. Those reporting specific amounts of caffeine consumed before training (n = 27) and races (n = 14), used 1.8 ± 1.0 mg/kg and 2.4 ± 1.3 mg/kg respectively. On average, 53.6% and 39.1% of athletes reported that caffeine exerted no effects to only minor effects during various types of training and racing respectively. A greater percentage of athletes reported moderate and major effects during more intense training as well as longer training sessions and races (52.7 - 72.7%). CONCLUSION: Most athletes in the present study did not follow typical laboratory protocols that have elicited ergogenic effects of caffeine. Better education among athletes and coaches or research into more diverse supplementation schemes are needed

The Impact of Dieting Culture Is Different Between Sexes In Endurance Athletes: A Cross-Sectional Analysis

Background: Frequent dieting is common in athletes attempting to achieve a body composition perceived to improve performance. Excessive dieting may indicate disordered eating (DE) behaviors and can result in clinical eating disorders. However, the current nutrition patterns that underly dieting culture are underexplored in endurance athletes. Therefore, the purpose of this study was to identify the sex differences in nutrition patterns among a group of endurance athletes. Methods: Two-hundred and thirty-one endurance athletes (females = 124) completed a questionnaire regarding their dieting patterns and associated variables. Results: The majority of athletes did not follow a planned diet (70.1%). For endurance athletes on planned diets (n = 69), males were more likely follow a balanced diet (p = 0.048) and females were more likely to follow a plant-based diet (p = 0.021). Female endurance athletes not on a planned diet (n = 162) were more likely to have attempted at least one diet (p \u3c 0.001). Male athletes attempted 2.0 ± 1.3 different diets on average compared to 3.0 ± 2.0 for females (p = 0.002). Female athletes were more likely to attempt ≥ three diets (p = 0.022). The most common diet attempts included carbohydrate/energy restrictive, plant-based, and elimination diets. Females were more likely to attempt ketogenic (p = 0.047), low-carbohydrate (p = 0.002), and energy restricted diets (p = 0.010). Females made up the entirety of those who attempted gluten-/dairy-free diets (F = 22.0%, M = 0.0%). Conclusions: Being a female athlete is a major determinant of higher dieting frequency and continual implementation of popular restrictive dietary interventions. Sports dietitians and coaches should prospectively assess eating behavior and provide appropriate programming, education, and monitoring of female endurance athletes

The Relationship Between Dietary Intake and Sleep Quality in Endurance Athletes

Many endurance athletes have poor sleep quality which may affect performance and health. It is unclear how dietary intake affects sleep quality among athletes. We examined if sleep quality in endurance athletes is associated with consumption of fruit, vegetables, whole grains, dairy milk, and caffeinated beverages. Two hundred thirty-four endurance athletes (39.5 ± 14.1 year) participated in a survey. Participants provided information on demographics, anthropometry, sleep behavior and quality, and dietary intake via questionnaires. Sleep quality was assessed using the Athlete Sleep Screening Questionnaire (ASSQ) with a global score (ASSQ-global) and subscales including sleep difficulty (ASSQ-SD), chronotype (ASSQ-C), and disordered breathing while sleeping (ASSQ-SDB). A general linear model (GLM), adjusted for age, body mass index, sleep discomfort, sleep behavior, gender, race, and ethnicity, showed that higher caffeinated beverage intake was related to poorer global sleep quality (p = 0.01) and increased risk for disordered breathing while sleeping (p = 0.03). Higher whole grain intake was associated with a morning chronotype and lower risk for sleep issues (p = 0.01). The GLM did not reveal a relationship between sleep quality and dairy milk, fruit, and vegetable intake. In conclusion, caffeinated beverages and whole grain intake may influence sleep quality. This relationship needs to be confirmed by further research

The Relationship between Dietary Intake and Sleep Quality in Endurance Athletes

Athletes have a high prevalence of poor sleep quality. It is unknown if dietary intake affects sleep quality in athletes. PURPOSE: To examine if sleep quality in endurance athletes is related to dietary intake. METHODS: Endurance athletes (n=187), 42.0±13.7 y, participated in the study. Participants completed questionnaires on demographics, dietary intake, and sleep quality. Sleep quality was assessed using the Athlete Sleep Screening Questionnaire (ASSQ), a validated tool, with scores ranging from 0-40 (higher scores indicate poorer sleep quality). The ASSQ subscales included sleep difficulty (SD), chronotype (C), and sleep disordered breathing (SDB). ASSQ-SD was categorized as having none (0-4), mild (5-7), moderate (8-10), and severe (11-17) SD. ASSQ-C was categorized as morning (\u3e4) or evening (higher risk for sleep issues) (≤4) type. ASSQ-SDB was categorized as difficulty breathing (\u3e1) or not ( RESULTS: ASSQ score was 22.3±3.96, indicating average sleep quality among athletes. ASSQ-SD score showed that 33.7% of athletes had no SD, and 38.5%, 21.9%, and 5.9% had mild, moderate, and severe SD, respectively. ASSQ-C score was 9.4±2.82, and 93% of athletes were morning type and 7% were evening type. ASSQ-SDB score indicated that 79.1% of athletes had normal and 20.9% had disordered breathing. Preliminary analyses revealed that ASSQ scores were significantly related to vegetable (p=.038) and caffeinated beverage (p=0.034) intake, but not to the other dietary variables. Significantly higher ASSQ score, (i.e., poorer sleep quality) was found in athletes who consumed ≥5 servings/d (24.0±4.0) of vegetables compared with \u3c1 \u3e(20.9±3.18, p=.011) or 1-2 (21.6±4.11, p=.030) servings/d. Athletes who drank \u3e2.5 cups/d of caffeinated beverages had higher ASSQ score or poorer sleep quality versus those who consumed 3 cups/d of milk had a higher disordered breathing score (.69±.947) versus those who drank 1-2 (.18±.521, p=.009) and \u3c1 \u3e(.30±.641, p=.016) cups/d. Athletes who consumed /d of whole grains had a higher ASSQ-DBS score (.48±.79) versus those who consumed 3-4 servings/d (.09±.401, p=.029). ASSQ-SD was not related to any of the dietary variables. CONCLUSIONS: Increased vegetable and caffeinated beverage consumption were associated with decreased sleep quality. Less whole grains and fruits were associated with evening chronotype. Athletes who consumed more milk and less whole grains had increased disordered breathing

Training Modifications in Endurance Athletes due to COVID-19 Restrictions

The COVID-19 pandemic created a situation that abruptly altered the life of nearly every individual, forcing them to adjust their daily habits. Adults who regularly engaged in daily physical activity, either as recreational, collegiate, or professional athletes prior to lockdowns had to subsequently adapt and change their training regimens. PURPOSE: To determine which characteristics (age, sex, education level, socioeconomic status, primary endurance sport, whether the athlete is being coached or following a training program, and prior competition medaling) of recreational, collegiate, and professional endurance athletes were associated with training changes due to COVID-19 safety restrictions. METHODS: A cross-sectional study design was used for this study. Personal and training related descriptive statistics were collected using a Qualtrics survey that was distributed to endurance athletes around the world from June 2020 – February 2021. Significant differences between athlete characteristics and change in training status were assessed using a Chi-squared test (significance pRESULTS: Approximately 2 out of every 3 (66.2%) of the 331 endurance athletes, 38.8±14.0y, changed their training due to restrictions. Significant group differences were found for age, sex, current collegiate athlete status, prior coaching status, prior use of a training program, and based on athlete primary sport compared to the whole sample. Athletes aged 18-30y changed their training at a higher portion (74.6%), while those 31-40y (56%) changed their training a lower portion. A significantly higher portion of female athletes changed their training compared to males (72.8% and 60.0%, respectively). A majority of collegiate athletes (83%), athletes who have previously worked with a coach (70.8%), athletes who have followed a training program previously (72.4%) changed their training. A significantly smaller proportion of athletes who chose running as their primary sport (55%) changed their training and a significantly larger portion of those who chose triathlon (82.1%) changed their training due to pandemic-related safety restrictions. CONCLUSION: The majority of athletes changed their training with COVID-19 safety restrictions, with significant differences based on personal and training characteristics. This data can be of use to safety policy makers, athletes, and coaches to consider for training approach and return to sport. Analysis of factors that allowed athletes to maintain their training and understanding the changes in athlete training can help minimize or prevent the effects of detraining for a greater portion of athletes

Nutrient Adequacy in Endurance Athletes

Adequate nutrition is critical to optimal performance in endurance athletes. However, it remains unclear if endurance athletes are consuming enough energy, macronutrients, and micronutrients. PURPOSE: The purpose of this study was to determine if endurance athletes are meeting their nutritional requirements and whether it varies by gender. METHODS: Endurance athletes (n=44), 39.0±14.2 y, participated in the study. Dietary intake was assessed using the five-step multiple-pass 24-hour recall method, a validated measure, that involved asking the participants to recall in detail the type and amount of foods and beverages they consumed the previous day. Energy, macronutrient, and micronutrient intakes were computed from the recalls using the ESHA Food Processor Diet Analysis Software. Nutritional adequacy was calculated by comparing the nutrient intakes of the participants with nutrient standards set by the Food and Nutrition Board, Institute of Medicine, the American College of Sports Medicine (ACSM), the Dietary Guidelines for Americans, and the American Heart Association (AHA). Fisher’s Exact test was used to compare the proportion of male and female endurance athletes that did not meet the requirements for energy, macronutrient, and micronutrient intakes. RESULTS: Over 50% of male athletes did not consume enough water, protein, carbohydrates, dietary fiber, linoleic acid, α-linolenic acid, eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA), vitamins D, E, and K, pantothenic acid, biotin, manganese, chromium, zinc, molybdenum, choline, potassium, and magnesium. More than 50% of female athletes did not consume enough protein, carbohydrates, linoleic acid, α-linolenic acid, EPA, DHA, vitamins D, E, and B12, pantothenic acid, thiamine, biotin, manganese, chromium, zinc, molybdenum, choline, and potassium. About 50% of male and female athletes consumed more than the recommended amount of total fat, saturated fat, cholesterol, and sodium. Many athletes (male: 20%; female: 8%) did not meet the energy requirements. A significantly higher portion of male athletes compared to female athletes did not meet the nutrient requirements for dietary fiber (70.0% and 24.0%, respectively; p ≤ 0.001), α-linolenic acid (90.0% and 60.0%, respectively; p = 0.04), and total water (75.0% and 40.0%, respectively; p = 0.03). CONCLUSION: Many endurance athletes are not meeting the nutrient requirements for energy, water, and several macronutrients and micronutrients, with some differences by gender. These results need to be confirmed by a larger study. Endurance athletes would benefit from dietary counseling by a registered dietitian

Chronic and Postprandial Metabolic Responses to a Ketogenic Diet Compared to High-Carbohydrate and Habitual Diets in Trained Competitive Cyclists and Triathletes: A Randomized Crossover Trial

Extreme carbohydrate deficits during a ketogenic diet (KD) may result in metabolic adaptations reflective of low energy availability; however, the manifestation of these adaptations outside of exercise have yet to be elucidated in cyclists and triathletes. The purpose of this study is to investigate the chronic and postprandial metabolic responses to a KD compared to a high-carbohydrate diet (HCD) and habitual diet (HD) in trained competitive cyclists and triathletes. For this randomized crossover trial, six trained competitive cyclist and triathletes (F: 4, M: 2) followed an ad libitum KD and HCD for 14 d each after their HD. Fasting energy expenditure (EE), respiratory exchange ratio (RER), and fat and carbohydrate oxidation (FatOx and CarbOx, respectively) were collected during their HD and after 14 d on each randomly assigned KD and HCD. Postprandial measurements were collected on day 14 of each diet following the ingestion of a corresponding test meal. There were no significant differences in fasting EE, RER, FatOx, or CarbOx among diet conditions (all p \u3e 0.050). Although postprandial RER and CarbOx were consistently lower following the KD meal, there were no differences in peak postprandial RER (p = 0.452), RER incremental area under the curve (iAUC; p = 0.416) postprandial FatOx (p = 0.122), peak FatOx (p = 0.381), or FatOx iAUC (p = 0.164) between the KD and HD meals. An ad libitum KD does not significantly alter chronic EE or substrate utilization compared to a HCD or HD; postprandial FatOx appears similar between a KD and HD; this is potentially due to the high metabolic flexibility of cyclists and triathletes and the metabolic adaptations made to habitual high-fat Western diets in practice. Cyclists and triathletes should consider these metabolic similarities prior to a KD given the potential health and performance impairments from severe carbohydrate restriction

Appetite Alterations in Endurance Athletes Following the Ketogenic Diet

Recently, endurance athletes have utilized a very low-carbohydrate diet, the ketogenic diet (KD), to improve performance in competition. The KD may be associated with diminished appetite, but this has not been explored in endurance athletes. PURPOSE: The purpose of this study was to evaluate the effects of a KD compared to a high-carbohydrate diet (HCD) and habitual diet (HD) on both subjective and objective measures of appetite in highly-trained cyclists and triathletes. METHODS: Following their HD, six highly-trained (≥80th percentile for V02max based on age and sex) cyclists and triathletes (male = 2, female = 4; age: 37.2 ± 12.2) consumed a KD and HCD, for two weeks each, in a random order. At the end of each diet, perceptions of fasting hunger, desire to eat (DTE), prospective consumption of food (PCF) and fullness, and serum total ghrelin (GHR) and glucagon-like-peptide-1 (GLP-1) were assessed. Immediately after collection of the fasting measures, a test meal containing an energy content that was 60% of measured resting metabolic rate was administered. The test meal composition corresponded with the participants diets (ketogenic meal after the KD, high-carbohydrate meal after the HCD, and a standard American meal after their HD). After ingestion of the test meal, postprandial appetite measures were collected for 3 h at 30, 60, 120, and 180 min. RESULTS: Repeated measures analysis showed that fasting GHR was significantly lower following the KD than the HD (p=0.001) and HCD (p=0.031) and fasting GLP-1 was significantly higher following the KD than the HD (p=0.041) and HCD (p=0.033). Fasting hunger was also significantly higher following the KD compared with the HD (p=0.042) and HCD (p=0.004) and PCF was higher for the KD versus HD (p=0.020). There were no differences between diets for fasting DTE and fullness. Postprandial GHR was significantly lower following consumption of the ketogenic test meal than the standard meal (p=0.007) and high-carbohydrate meal (p=0.031). Peak concentrations of postprandial GHR and incremental area under the curve (iAUC) for GHR were also significantly lower following the ketogenic meal than the standard meal (p=0.025; p=0.016, respectively) and the high-carbohydrate meal (p=0.044; p=0.045, respectively). Postprandial GLP-1 was significantly higher following consumption of the ketogenic test meal than the standard meal (p=0.006) and high-carbohydrate meal (p=0.003). Peak concentrations of postprandial GLP-1 and GLP-1 iAUC were also significantly higher following the ketogenic meal than the standard meal (p=0.009; p=0.004, respectively) and the high-carbohydrate meal (p=0.008; p=0.002, respectively). There were no differences in postprandial ratings of appetite between diets. CONCLUSIONS: Both fasting and postprandial concentrations of GHR were lower and GLP-1 were higher following the KD than the HC and HD in endurance athletes. Subjective ratings of appetite did not correspond with the objective measures of appetite, however. More research is needed to confirm our findings, and to understand the relationship between subjective and objective measures of appetite in endurance athletes