Background: Acute effects of caffeinated and non-caffeinated cocoa on mood, motivation, and cognitive function are not well characterized. The current study examined the acute influence of brewed cocoa, alone and with supplemental caffeine, on attention, motivation to perform cognitive tasks and energy and fatigue mood states. Methods: A randomized, double-blinded, within-subjects crossover trial was conducted with four 473-milliliter brewed beverage treatments: cocoa, caffeinated cocoa (70 milligrams caffeine total), placebo (flavored and colored brewed water) and positive control (placebo plus 66 milligrams caffeine, "caffeine alone"). Participants (n = 24) were low consumers of polyphenols without elevated feelings of energy. Before and three times after beverage consumption, a 26-minute battery was used to assess motivation to perform cognitive tasks, mood and attention (serial subtractions of 3 and 7, the continuous performance task, and the Bakan dual task) with a 10-minute break between each postconsumption battery. The procedure was repeated with each beverage for each participant at least 48 h apart and ±30 min the same time of day. Data were evaluated using Treatment X Time analysis of covariance controlling for hours of prior night's sleep. Results: Compared to placebo, cocoa reduced overall false alarm errors progressively across time with 0.92, 1.44 and 2.35 fewer false alarms on average 22-48, 60-86 and 98-124 min post-consumption (η 2 = 0.08, p = 0.019). Caffeinated cocoa: (i) attenuated the anxiety-provoking effects of cognitive testing found after drinking caffeine alone (η 2 = 0.064, p = 0.038), and (ii) increased accuracy (η 2 = 0.085, p = 0.01) and reduced omission errors (η 2 = 0.077, p = 0.016) on the Bakan primary task compared to cocoa alone.
Background Until recently many researchers have examined energy and fatigue as opposite ends of a bipolar spectrum rather than two separate unipolar moods. Studies have also focused on a single variable to study these mood states rather than examining multiple variables simultaneously. Therefore, the purpose of this study was to identify factors predicting feelings of energy and fatigue while simultaneously examining multiple domains related to these mood states in graduate health sciences students. Methods Seventy‐seven subjects were recruited from a Physician Assistant, Physical Therapy and Occupational Therapy program at a small school in Northern New York. Subjects completed a series of surveys to measure mood, diet, mental work load intensity on school days and non‐school days, and physical activity. Subjects also completed the Trail‐making Test Part B task on an iPad and their Resting Metabolic Rate (RMR) and muscle oxygen consumption mVO2 was measured. A backwards linear regression was used to determine the relationship between energy, fatigue and multiple variables. Results The predictor variables accounted for 46.1% and 22.7% of the variance in fatigue and energy, respectively. More fatigue was associated with worse sleep quality, more time spent sitting and higher perceived intensity of mental workload on non‐school days. More energy was associated with better sleep quality, higher muscle oxygen saturation, lower RMR, and faster psychomotor performance. Conclusion The results of this study indicate that energy and fatigue are separate constructs that are predicted with different accuracy by different variables. Our results indicate that small lifestyle changes may be necessary to improve feelings of fatigue but comprehensive interventions may be necessary to improve feelings of energy. This study provides new insight into a multi‐domain approach to predicting energy and fatigue. Support or Funding Information There was no funding for this study This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.
The COVID-19 pandemic significantly altered much of US life with shifts to working-from-home and social distancing changing day-to-day behavior. We aimed to determine the self-reported prevalence of meeting US physical activity guidelines, stratified by sitting time during the early lockdown phase of COVID-19 in US adults. We conducted two cross-sectional internet-based studies April 3 rd -May 4 th , 2020 in convenience samples of US adults. Participants self-reported daily sitting time and weekly moderate-to-vigorous physical activity (MVPA) via questions from the International Physical Activity Questionnaire. A total of 5,036 US adults (65.3% women, 30.2% with chronic conditions) provided complete physical activity and sitting time data (80.3% of total). Overall, 42.6% of participants reported sitting for >8h/day (95% CI: 41.2%-44.0%) and 72.5% (71.2%-73.7%) reported being either sufficiently (150-300 MVPA minutes) or highly active (>300 minutes). The greatest proportion of people self-reported being highly active and sitting for >8h/day (24.0%; 22.8%-25.2%), followed by being highly active and sitting for 6-8h/day (20.9%; 19.8%-22.1%). Sitting and activity appeared similar between sexes, while there was evidence of some age differences. For example, more young adults (ages 18-34) appeared to self-report being inactive and more appeared to sit for >8h/day compared to older adults. High sitting time was reported by US adults (>40% sitting >8h/day) during April 2020. However, high levels of physical activity (>70% meeting guidelines) were also reported. Since physical activity cannot eliminate the negative health effects of sitting, maintaining activity and limiting sitting during periods of large workplace and societal shifts is encouraged.
The objective of this study was to identify the associations between trait energy and fatigue with state energy fatigue, as well as exploring if these relationships interacted with sex and/ or sleep quality. The study population included a convenience sample of adults and college students (n ranges from 687 to 694). Key measures were state and trait mental and physical energy and fatigue scales, PSQI (a measure of sleep quality), and sex. Multiple regression models included age, polyphenol consumption, POMS scores, physical activity, mental load, and caffeine consumption as covariates. Analyses yielded a strong (r = .65) positive association between each trait and state variable. Overall, several statistically significant interactions were identified. First, the relationship between state and trait physical fatigue was particularly strong for women with high trait scores. There were also interactions with sleep quality. In the case of physical fatigue, poor sleep quality magnified the association between physical fatigue trait and state among those with low trait physical fatigue, while sleep quality did not make a difference for those with high trait physical fatigue. Conversely, in the case of physical energy and mental fatigue, good sleep quality was associated with both higher "highs" and lower "lows" of their respective traits; both interactions were present only among males. Our analyses suggest that sleep quality and sex could influence the effects of trait physical and mental energy and fatigue on state. Findings were more complex than initially assumed, suggesting that the interrelationship between trait and state may be modified by how males and females react and adapt to their trait.
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