The Effect of Varying Fatty Acid Composition on Postprandial Airway Inflammation, Pulmonary Function, and Airway Resistance in Healthy, Young Adults.

OBJECTIVE: To examine the effect of varying fatty acid composition in a HFM on eNO, pulmonary function, and airway resistance. METHODS: Fifteen individuals [6 M/9 F; 21.9 ± 1.5 years old] each completed three HFM conditions {SF, O6FA, and O3FA; 12 kcal/kg body weight, 63% total fat, and 0.72 g/kg sugar smoothies} in random order separated by at least 48 h. Airway inflammation assessed via eNO, pulmonary function measured using the maximum flow volume loop (MFVL) and airway resistance measured using impulse oscillometry (iOS) were taken at baseline, 2h and 4h postprandially. RESULTS: There was no difference in eNO or iOS across time in any condition or between conditions (p > 0.05). There was a significant time by condition effect for FEV1 post-HFM in the SF and O6FA conditions (p < 0.05). CONCLUSION: Different fatty acid compositions do not increase eNO or iOS in healthy, college-aged participants after consumption of a HFM, though the minimally processed meals with fruit added may contribute to these findings.

Body composition measured by multi-frequency bioelectrical impedance following creatine supplementation.

BACKGROUND: Acute fluid ingestion increases estimated body fat percentage (BF%) measurements by single frequency (SF-BIA) and multi-frequency bioelectrical impedance (MF-BIA). It is unknown if MF-BIA accurately measures total BF% and total body water (TBW) after creatine supplementation, which causes fluid retention, and resultant increases in fat-free mass and TBW. The purpose of this study was to analyze the effect of creatine supplementation on body composition and TBW measured through a popular MF-BIA device (InBody 770). METHODS: Thirteen male and 14 female subjects (18-22 years) completed one week of creatine monohydrate (0.3 g/kg body weight) or maltodextrin. Pre- and post-supplementation body composition measurements included dual-energy X-ray absorptiometry (DEXA), SF-BIA measured by an Omron HBF-306C device, and MF-BIA measured by an InBody 770 device to measure BF%, fat free mass (FFM), and fat mass (FM). Additionally, intracellular water (ICW), extracellular water (ECW), and TBW were estimated by MF- BIA. RESULTS: FFM increased more in the creatine group than the placebo group measured by all body composition modes (1.2 kg, 1.9 kg, and 1.1 kg increase for SF-BIA, MF-BIA, and DEXA respectively, P<0.05). Creatine supplementation resulted in a 2% increase (P<0.05) in TBW measured by MF-BIA (40.4±9.5 to 41.2±9.6 kg). CONCLUSIONS: One week of creatine supplementation increased TBW as detected by the InBody 770 device. Changes in body composition that occurred due to the increase in TBW were detected as an increase in FFM measured by SF-BIA, MF-BIA, and DEXA.

ß-Cell function during a high-fat meal in young versus old adults: role of exercise.

The acute effect of exercise on ß-cell function during a high-fat meal (HFM) in young adults (YA) versus old adults (OA) is unclear. In this randomized crossover trial, YA (n = 5 M/7 F, 23.3 ± 3.9 yr) and OA (n = 8 M/4 F, 67.7 ± 6.0 yr) underwent a 180-min HFM (12 kcal/kg body wt; 57% fat, 37% CHO) after a rest or exercise [∼65% heart rate peak (HRpeak)] condition ∼12 h earlier. After an overnight fast, plasma lipids, glucose, insulin, and free fatty acid (FFA) were determined to estimate peripheral, or skeletal muscle, insulin sensitivity (Matsuda index) as well as hepatic [homeostatic model assessment of insulin resistance (HOMA-IR)] and adipose insulin resistance (adipose-IR). ß-Cell function was derived from C-peptide and defined as early-phase (0-30 min) and total-phase (0-180 min) disposition index [DI, glucose-stimulated insulin secretion (GSIS) adjusted for insulin sensitivity/resistance]. Hepatic insulin extraction (HIE), body composition [dual-energy X-ray absorptiometry (DXA)], and peak oxygen consumption (V̇o2peak) were also assessed. OA had higher total cholesterol (TC), LDL, HIE, and DI across organs as well as lower adipose-IR (all, P < 0.05) and V̇o2peak (P = 0.056) despite similar body composition and glucose tolerance. Exercise lowered early-phase TC and LDL in OA versus YA (P < 0.05). However, C-peptide area under the curve (AUC), total phase GSIS, and adipose-IR were reduced postexercise in YA versus OA (P < 0.05). Skeletal muscle DI increased in YA and OA after exercise (P < 0.05), whereas adipose DI tended to decline in OA (P = 0.06 and P = 0.08). Exercise-induced skeletal muscle insulin sensitivity (r = -0.44, P = 0.02) and total-phase DI (r = -0.65, P = 0.005) correlated with reduced glucose AUC180min. Together, exercise improved skeletal muscle insulin sensitivity/DI in relation to glucose tolerance in YA and OA, but only raised adipose-IR and reduced adipose-DI in OA.NEW & NOTEWORTHY High-fat diets may induce ß-cell dysfunction. This study compared how young and older adults responded to a high-fat meal with regard to ß-cell function and whether exercise comparably impacted glucose regulation. Older adults secreted more insulin during the high-fat meal than younger adults. Although exercise increased ß-cell function adjusted for skeletal muscle insulin sensitivity in relation to glucose tolerance, it raised adipose insulin resistance and reduced pancreatic ß-cell function relative to adipose tissue in older adults. Additional work is needed to discern nutrient-exercise interactions across age to mitigate chronic disease risk.

Saturated Fatty Acids Consumed in Smoothies Increase Glucose and Metabolic Load Index in Young Adults Compared to Polyunsaturated Omega-3-Fatty Acids.

Introduction: Chronic diets high in saturated fat (SF) and omega-6-fatty acids (O6FAs) elevate fasting triglycerides (TRGs) and glucose (GLU). Postprandial TRGs, GLU, and Metabolic Load Index (MLI) are better predictors of disease risk compared to fasting levels alone. Conversely, diets high in omega-3 fatty acids (O3FAs) may be cardioprotective. Unfortunately, many existing postprandial studies are not standardized to body weight and given in an amount individuals would typically consume in their daily lives; the MLI is not calculated, and varying types of fat content are not examined. Therefore, we sought to determine whether SF, O3FAs, or O6FAs altered postprandial TRGs, GLU, and MLI from a standardized mixed meal. Methods: Fifteen individuals (6 M and 9 F) visited the laboratory three times, separated by at least 48 h, to consume HFM smoothies with varying FA composition (SF, high O6FAs, and high O3FAs). The smoothies were standardized to 12 kcal/kg body weight, 63% total fat, and 0.72 g/kg sugar. TRGs and GLU were collected at baseline and at 2 h and 4 h postprandially; the MLI was calculated by summing the TRG and GLU responses at each time point. Results: There was a significant increase in TRGs across time points (p < 0.001). For TRGs, there was a trend toward a significant interaction between smoothie type and time (p = 0.06) due to the increase in TRGs in the SF compared to the O3FA smoothie. There was an increase in postprandial GLU that varied across smoothie types (p = 0.036). Taken together, the MLI was elevated in the SF smoothie compared to the O3FAs at 2 h (p = 0.041). Conclusion: A SF smoothie in the morning elevated the metabolic load compared to an O3FA smoothie. Mechanisms of action in the competing clearance of TRGs and GLU warrant further investigation.

Acute Exercise and the Systemic and Airway Inflammatory Response to a High-Fat Meal in Young and Older Adults.

The purpose of the present study was to determine fasting and high-fat meal (HFM)-induced post-prandial systemic inflammation and airway inflammation (exhaled nitric oxide (eNO)) in older adults (OAs) compared to younger adults (YAs) before and after acute exercise. Twelve YAs (23.3 ± 3.9 y n = 5 M/7 F) and 12 OAs (67.7 ± 6 y, n = 8 M/4 F) completed two HFM challenges. After an overnight fast, participants underwent an HFM session or pre-prandial exercise (EX, 65% VO2Peak to expend 75% of the caloric content of the HFM) plus HFM (EX + HFM) in a randomized order. Systemic inflammatory cytokines were collected at 0, 3, and 6 h, while eNO was determined at 0, 2, and 4 h after the HFM (12 kcal/kg body weight: 61% fat, 35% CHO, 4% PRO). TNF-α was higher in OAs compared to YAs (p = 0.005) and decreased across time from baseline to 6 h post-HFM (p = 0.007). In response to the HFM, IL-6 decreased from 0 to 3 h but increased at 6 h regardless of age or exercise (p = 0.018). IL-8 or IL-1ß did not change over the HFM by age or exercise (p > 0.05). eNO was also elevated in OAs compared to YAs (p = 0.003) but was not altered by exercise (p = 0.108). There was a trend, however, towards significance post-prandially in OAs and YAs from 0 to 2 h (p = 0.072). TNF-α and eNO are higher in OAs compared to YAs but are not elevated more in OAs post-prandially compared to YAs. Primary systemic inflammatory cytokines and eNO were not modified by acute exercise prior to an HFM.

Acute exercise improves glucose and TAG metabolism in young and older adults following high-fat, high-carbohydrate meal intake.

A single high-fat, high-carbohydrate meal (HFHC) results in elevated postprandial glucose (GLU), triglycerides (TAG) and metabolic load index (MLI; TAG (mg/dl) + GLU (mg/dl)) that contributes to chronic disease risk. While disease risk is higher in older adults (OA) compared to younger adults (YA), the acute effects of exercise on these outcomes in OA is understudied. Twelve YA (age 23.3 ± 3.9 yrs, n = 5 M/7 F) and 12 OA (age 67·7 ± 6.0 yrs, n = 8 M/4 F) visited the laboratory in random order to complete a HFHC with no exercise (NE) or acute exercise (EX) condition. EX was performed 12 hours prior to HFHC at an intensity of 65 % of maximal heart rate to expend 75 % of the kcals consumed in HFHC (Marie Callender's Chocolate Satin Pie; 12 kcal/kgbw; 57 % fat, 37 % CHO). Blood samples were taken at 0, 30, 60, 90 minutes, and then every hour until 6 hours post-meal. TAG levels increased to a larger magnitude in OA (Δ∼61 ± 31 %) compared to YA (Δ∼37 ± 34 %, P < 0·001), which were attenuated in EX compared to NE (P < 0·05) independent of age. There was no difference in GLU between OA and YA after the HFM, however, EX had attenuated GLU independent of age (NE: Δ∼21 ± 26 %; EX: Δ∼12 ± 18 %, P = 0·027). MLI was significantly lower after EX compared to NE in OA and YA (P < 0·001). Pre-prandial EX reduced TAG, GLU and MLI post-HFHC independent of age.

The impact of the COVID-19 pandemic on physical activity habits at a residential university.

OBJECTIVE: To assess changes in physical activity (PA) after a COVID-19 shutdown on a primarily residential university campus. METHODS: Eighty students, faculty, and staff (FS) of a university (age: 32.2 ± 13.6 yr) who wore a consumer wearable technology (CWT) device completed an anonymous survey by inputting data for 30 days prior to- and 30 days following an academic break in 2020, in which the university transitioned to remote learning. RESULTS: Steps decreased after spring break in all subjects (p < .001), but steps were impacted to a greater extent in students. 30-day, weekday, and weekend step averages all decreased in students (p < .001). FS were able to maintain their weekend step averages. CONCLUSIONS: PA decreased in a university community after the COVID-19 shutdown. Students, no longer active transport for campus life, saw a greater impact on their PA. These changes could have an impact on health status.

Markers of poor sleep quality increase sedentary behavior in college students as derived from accelerometry.

PURPOSE: Sleep is essential for overall health and can impact academic performance. Prior research reports reduced sleep time in college students. Poor sleep may impact physical activity (PA) and sedentary behavior, or vice versa, but has not been examined extensively in this population. Therefore, the purpose of this study was to examine markers of sleep quality, PA, and sedentary behavior in college students using objective means. METHODS: A convenience sample of college students underwent body composition analysis and 7-day objective PA and sleep assessment via accelerometry. RESULTS: Among 81 college students (53 women), there was no association between total sleep time (TST) and weekly average PA. TST was negatively associated with sedentary minutes per day, sedentary bouts per day, and total time in sedentary bouts per day. Greater sedentary bouts per day and average sedentary minutes per day were seen in those with a TST < 6 h, with no difference in body composition. Further, TST was negatively associated with sedentary minutes accumulated on the subsequent day, for all 7 days. CONCLUSION: In a primarily residential college student cohort, poor sleep is associated with sedentary behavior more than PA. These students, who require a high amount of transport PA to and from campus during the week, are compensating by sleeping more and moving less on the weekend.

Combining supervised run interval training or moderate-intensity continuous training with the diabetes prevention program on clinical outcomes.

PURPOSE: The present study was designed to evaluate the 16 weeks diabetes prevention program (DPP) combined with instructed run sprint interval training (INT) or moderate-intensity continuous training (MICT) on glycemic control, body composition, fitness, exercise adherence, and perceived exercise enjoyment in sedentary, adults with prediabetes. METHODS: Participants completed three weekly supervised sessions of INT (4-10 bouts of 30 s maximal sprints followed by a 4 min active recovery) or MICT (30-60 min at 45-55% HRR) exercise coupled with the DPP for 16 weeks. At baseline, 8 and 16 weeks, participants completed fitness and clinical assessments as well as questionnaires to assess group and time differences. RESULTS: Twenty-nine study participants (INT n = 17, MICT n = 12) were randomized, however, significantly (p = 0.024) more participants withdrew from the INT (n = 11) than MICT (n = 4) treatment. There was no significant difference between groups in perceived exercise enjoyment, but, the MICT group significantly improved their perceived exercise enjoyment (10.8 ± 14.2; p = 0.021) from baseline to 16 weeks. Both INT and MICT groups decreased their body weight (2.0 ± 0.8 vs. - 5.5 ± 1.4 kg; p < 0.001), BMI (- 0.6 ± 0.3 vs. - 2.1 ± 0.5 kg/m2; p < 0.001), body fat mass (1.4 ± 0.6 vs. - 4.2 ± 1.0 kg; p < 0.001), fasting glucose (- 0.09 ± 0.01 vs. - 0.18 ± 0.02 mmol/L; p = 0.020), and HbA1c (- 0.21 ± 0.09 vs. - 0.12 ± 0.12%; p = 0.001), respectively, however, the MICT had greater reductions (GxT: p ≤ 0.05) in body weight, BMI, and body fat than the INT group. CONCLUSION: Sixteen weeks of MICT is adhered to better and elicits greater improvements in body composition than INT. Nevertheless, both interventions similarly reduced fasting glucose and HbA1c in adults with prediabetes, suggesting either treatment could be effective for T2D prevention.

Loading and concurrent synchronous whole-body vibration interaction increases oxygen consumption during resistance exercise.

Exercise is commonly used as an intervention to increase caloric output and positively affect body composition. A major challenge is the low compliance often seen when the prescribed exercise is associated with high levels of exertion. Whole-body vibration (WBV) may allow increased caloric output with reduced effort; however, there is limited information concerning the effect of WBV on oxygen consumption (VO2). Therefore, this study assessed the synergistic effects of resistance training and WBV on VO2. We examined VO2 at different loads (0%, 20%, and 40% body weight (BW)) and vibration intensities (No vibration (NV), 35HZ, 2-3mm (35L), 50Hz, 57mm (50H)) in ten men (26.5 ± 5.1 years). Data were collected during different stages (rest, six 30s sets of squatting, and recovery). Repeated measures ANOVA showed a stage x load x vibration interaction. Post hoc analysis revealed no differences during rest; however, a significant vibration x load interaction occurred during exercise. Both 35L and 50H produced greater VO2 than NV at a moderate load of 20%BW. Although 40%BW produced greater VO2 than 20%BW or 0%BW using NV, no significant difference in VO2 was seen among vibratory conditions at 40%BW. Moreover, no significant differences were seen between 50H and 35L at 20%BW and NV at 40%BW. During recovery there was a main effect for load. Post hoc analyses revealed that VO2 at 40%BW was significantly higher than 20%BW or 0%BW, and 20%BW produced higher VO2 than no load. Minute-by-minute analysis revealed a significant impact on VO2 due to load but not to vibratory condition. We conclude that the synergistic effect of WBV and active squatting with a moderate load is as effective at increasing VO2 as doubling the external load during squatting without WBV. Key PointsSynchronous whole body vibration in conjunction with moderate external loading (app 20% BW) can increase oxygen consumption to the same extent as heavier loading (40% BW) during performance of the parallel squat.While the application of synchronous whole body vibration had no effect on recovery oxygen, under bot vibratory and non-vibratory conditions, the heavier the external load the greater the recovery oxygen consumption levels.Regardless of vibratory condition, during the squatting exercise bout 40% BW produced higher heart rates than 20%BW or 0% BW, and 20% BW produced higher heart rates than 0% BW.There were strong trends toward higher heart rates in both vibratory conditions (50 Hz, 5-6mm; 35 Hz, 2-3 mm) than in the non-vibratory condition regardless of external loading.

Association between sleep disorders, obesity, and exercise: a review.

Decreased sleep duration and quality is associated with an increase in body weight and adiposity. Insomnia, obstructive sleep apnea, and restless legs syndrome are three of the most prevalent types of sleep disorder that lead to an increased risk for numerous chronic health conditions. Various studies have examined the impact of these sleep disorders on obesity, and are an important link in understanding the relationship between sleep disorders and chronic disease. Physical activity and exercise are important prognostic tools in obesity and chronic disease, and numerous studies have explored the relationship between obesity, sleep disorders, and exercise. As such, this review will examine the relationship between sleep disorders and obesity. In addition, how sleep disorders may impact the exercise response and how exercise may impact patient outcomes with regard to sleep disorders will also be reviewed.