This study investigated the effect of environmental heat stress on physiological and performance measures during a ~4 mi time trial (TT) mountain hike in the Phoenix metropolitan area. Participants (n = 12; 7M/5F; age 21.6 ± 2.47 [SD]) climbed ‘A’ mountain (~1 mi) four times on a hot day (HOT; wet bulb globe temperature [WBGT] = 31.6°C) and again on a moderate day (MOD; WBGT = 19.0°C). Physiological and performance measures were made before and throughout the course of each hike. Mean pre-hike hydration status (urine specific gravity [USG]) indicated that participants began both HOT and MOD trials in a euhydrated state (1.016 ± 0.010 and 1.010 ± 0.008, respectively) and means did not differ significantly between trials (p = .085). Time trial performance was impaired by -11% (11.1 minutes) in the HOT trial (105 ± 21.7 min), compared to MOD (93.9 ± 13.1 min) (p = .013). Peak core temperatures were significantly higher in HOT (38.5 ± 0.36°C) versus MOD (38.0 ± 0.30°C) with progressively increasing differences between trials over time (p < .001). Peak ratings of perceived exertion were significantly higher in HOT (14.2 ± 2.38) compared to MOD (11.9 ± 2.02) (p = .007). Relative intensity (percent of age-predicted maximal heart rate [HR]), estimated absolute intensity (metabolic equivalents [METs]), and estimated energy expenditure (MET-h) were all increased in HOT, but not significantly so. The HOT condition reduced predicted maximal aerobic capacity (CRFp) by 6% (p = .026). Sweat rates differed significantly between HOT (1.38 ± 0.53 L/h) and MOD (0.84 ± 0.27 L/h) (p = .01). Percent body mass loss (PBML) did not differ significantly between HOT (1.06 ± 0.95%) and MOD (0.98 ± 0.84%) (p = .869). All repeated measures variables showed significant between-subjects effects (p < .05), indicating individual differences in response to test conditions. Heat stress was shown to negatively affect physiological and performance measures in recreational mountain hikers. However, considerable variation exists between individuals, and the degree of physiological and performance impairment is probably due, in part, to differences in aerobic fitness and acclimatization status rather than pre- or during-performance hydration status.
Asymmetry scores were calculated for all three exercises. The exercise that produced the greatest absolute, average asymmetry score was the ab-slide using the roller device. The muscle that the greatest absolute asymmetry was found was the internal oblique. This means that during the three exercises and MVC, the greatest difference between right and left side pair muscles was observed in the internal obliques. The standard deviation of symmetry scores for all exercises and muscles was great as there was much variation in the skill levels in the participants of this study. Bilateral asymmetry was found by visually comparing the asymmetry scores. In conclusion, bilateral asymmetry was found in the core muscles of college-aged individuals during bilateral abdominal exercises.
Methods: There were 4 groups of participants: healthy younger adults (n=14)(21.74 ± 1.97), healthy older adults (n=12)(55-75), older adults (n=4)(55-75) with a partial-thickness rotator cuff tear, and older adults (n=4)(55-75) with a full-thickness rotator cuff tear (RCT). All four groups completed strength testing, horizontal drawing and pointing tasks, and three dimensional (3D) activities of daily living. Kinematic and kinetic variables of the arm were obtained during horizontal and 3D tasks using data from 12 reflective markers placed on the arm, 8 motion capture cameras, and Cortex motion capture software (Motion Analysis Corp., Santa Rosa, CA). Strength testing tasks were measured using a dynamometer. All strength testing and 3D tasks were completed for three trials and horizontal tasks were completed for two trials.
Results: Results of the younger adult participants showed that during the forward portion of seven 3D tasks, there were four phases of different joint control mechanics seen in a majority of the movements. These phases included active rotation of both the shoulder and the elbow joint, active rotation of the shoulder with passive rotation of the elbow, passive rotation of the shoulder with active rotation of the elbow, and passive rotation of both the shoulder and the elbow. Passive rotation during movements was a result of gravitational torque on the different segments of the arm and interaction torque caused as a result of the multi-joint structure of human limbs. The number of tested participants for the minor RCT, and RCT older adults groups is not yet high enough to produce significant results and because of this their results are not reported in this article. Between the older adult control group and the young adult control group in the tasks upward reach to eye height and hair comb there were significant differences found between the groups. The differences were found in shorter overall time and distance between the two groups in the upward eye task.
Discussion: Through the available results, multiple phases were found where one or both of the joints of the arm moved passively which further supports the LJH and extends it to include 3D movements. With available data, it can be concluded that healthy older adults use movement control strategies, such as shortening distance covered, decreasing time percentage in active joint phases, and increasing time percentage in passive joint phases, to account for atrophy along with other age-related declines in performance, such as a decrease in range of motion. This article is a part of a bigger project which aims to better understand how older adults with RCTs compensate for the decreased strength, the decreased range of motion, and the pain that accompany this type of injury. It is anticipated that the results of this experiment will lead to more research toward better understanding how to treat patients with RCTs.
Mental disorders are prevalent in young adults and frequently present between 12-24 years of age.4 The top five sources of stress reported by college students were changes in sleeping routines, changes in eating habits, increased amount of work, new responsibilities, and breaks/vacations.5 Overall, a total of 73% of college students report occasional difficulties sleeping, and 48% of students suffer from sleep deprivation, as self-reported.6,7
Lifestyle factors such as diet, exercise and sleep may influence symptoms related to stress and depression.8 Symptoms of depression include but are not limited to, persistent anxious or sad moods, feeling guilty or helpless, loss of interest in hobbies, irritability, and other behaviors that may interrupt daily living.9 Inadequate intake of folic acid from fruits and vegetables, and essential fatty acids in fish, may increase symptoms of depression.10 Unhealthy eating habits may be associated with increases in depression-like symptoms in women, supporting the notion that healthier eating habits may decrease major depression.11 Diet is only one component of how lifestyle may influence depression and stress in adults. Exercise may be another important component in decreasing depression-related symptoms due to the release of endorphins.12 It has been found that participating in regular physical activity may decrease tension levels, increase and stabilize mood, improve self-esteem, and lead to better sleeping patterns.13 It has been concluded that individuals who consume a healthy diet are less likely to experience depression whereas people eating unhealthy and processed diets are more likely to be depressed.14
Poor sleep quality as well as unstable sleeping patterns may lead to poor psychological and physical health.15 Poor sleep includes longer duration of sleep onset latency, which is defined as the amount of time it takes to fall asleep, waking up multiple times throughout the night, and not getting a restful sleep because of tossing and turning.16 In healthy adults, the short-term consequences of sleep disruption consist of somatic pain, emotional destress and mood disorders, reduced quality of life, and increased stress responsivity.17 Irregular sleep-wake patterns, defined as taking numerous naps within a 24 hour span and not having a main nighttime sleep experience, are present at alarming levels (more than a quarter) among college students.18 A study done with 2,000 college students concluded that more than a quarter of the students were at risk of a sleeping disorder.19 Therefore, college students who were classified as poor-quality sleepers, reported experiencing more psychological and physical health problems compared to their healthy counterparts. Perceived stress was also found to be a factor in lower sleep quality of young adults.20
The link between depression-like symptoms and sleep remains poorly understood. It is mentioned that there are risk factors of poor sleep, depression and anxiety among college students but this topic has not yet been heavily studied within this population.