Heat Stress Control and Heat Casualty Management

Sawka, Michael N.; Wenger, C. B.; Montain, Scott J.; Kolka, Margaret A.; Bettencourt, B. Ann; Flinn, Sean; Gardner, John; Matthew, William T.; Lovell, M.E.; Scott, Christine

doi:10.1037/e458312006-001

Cited by 22 publications

(12 citation statements)

References 3 publications

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“…The implications of these results are two-fold; firstly these data can be used to understand endurance time on lift and carry tasks and set appropriate work-rest tables, and secondly, we provide evidence for the use of a maximal lifting task to aid in predicting endurance time. Work-rest schedules are used in a variety of occupations to guide task duration depending on factors such as sleep loss [ 25 ] and heat stress [ 26 ]. By understanding individual variation in the time to exhaustion in repetitive tasks, the models that we report can be used to guide the development of specific work-rest tables in lift and carry tasks or the effect a change in item mass may make to the sustainable work time of a worker population or specific worker.…”

Section: Discussionmentioning

confidence: 99%

Predicting Endurance Time in a Repetitive Lift and Carry Task Using Linear Mixed Models

et al. 2016

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ObjectivesRepetitive manual handling tasks account for a substantial portion of work-related injuries. However, few studies report endurance time in repetitive manual handling tasks. Consequently, there is little guidance to inform expected work time for repetitive manual handling tasks. We aimed to investigate endurance time and oxygen consumption of a repetitive lift and carry task using linear mixed models.MethodsFourteen male soldiers (age 22.4 ± 4.5 yrs, height 1.78 ± 0.04 m, body mass 76.3 ± 10.1 kg) conducted four assessment sessions that consisted of one maximal box lifting session and three lift and carry sessions. The relationships between carry mass (range 17.5–37.5 kg) and the duration of carry, and carry mass and oxygen consumption, were assessed using linear mixed models with random effects to account for between-subject variation.ResultsResults demonstrated that endurance time was inversely associated with carry mass (R2 = 0.24), with significant individual-level variation (R2 = 0.85). Normalising carry mass to performance in a maximal box lifting test improved the prediction of endurance time (R2 = 0.40). Oxygen consumption presented relative to total mass (body mass, external load and carried mass) was not significantly related to lift and carry mass (β1 = 0.16, SE = 0.10, 95%CI: -0.04, 0.36, p = 0.12), indicating that there was no change in oxygen consumption relative to total mass with increasing lift and carry mass.ConclusionPractically, these data can be used to guide work-rest schedules and provide insight into methods assessing the physical capacity of workers conducting repetitive manual handling tasks.

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Section: Discussionmentioning

confidence: 99%

Predicting Endurance Time in a Repetitive Lift and Carry Task Using Linear Mixed Models

et al. 2016

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“…The additive impacts of heat and humidity extend beyond direct health outcomes to include reduced individual performance across a range of activities, as well as large-scale economic impacts (5)(6)(7). Heat-humidity effects have prompted decades of study in military, athletic, and occupational contexts (8,9). However, consideration of wet-bulb temperature (TW) from the perspectives of climatology and meteorology began more recently (10,11).…”

Section: Introductionmentioning

confidence: 99%

The emergence of heat and humidity too severe for human tolerance

2020

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Humans’ ability to efficiently shed heat has enabled us to range over every continent, but a wet-bulb temperature (TW) of 35°C marks our upper physiological limit, and much lower values have serious health and productivity impacts. Climate models project the first 35°C TW occurrences by the mid-21st century. However, a comprehensive evaluation of weather station data shows that some coastal subtropical locations have already reported a TW of 35°C and that extreme humid heat overall has more than doubled in frequency since 1979. Recent exceedances of 35°C in global maximum sea surface temperature provide further support for the validity of these dangerously high TW values. We find the most extreme humid heat is highly localized in both space and time and is correspondingly substantially underestimated in reanalysis products. Our findings thus underscore the serious challenge posed by humid heat that is more intense than previously reported and increasingly severe.

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“…21 Previous observations 11 have also noted that up to 40% of Army recruits with EHI were classified as RM cases during the initial 6 days of BCT. Despite implementation of heat illness mitigation strategies, [22][23][24][25] approximately 300% to 400% more ADA RM cases versus the civilian populace occurred between 2004 and 2006. 26 Moreover, incident cases of ADA RM were higher among: (1) men, (2) <25 years of age, (3) African Americans, (4) <90 days in the Army, (5) those with prior heat injury (PHI), and (6) those who never deployed. 26 More recently, there were 358 cases of RM among U.S. service members, mostly occurring in Marines (42.5 per 100,000 personyears) and Army Soldiers (32.5 per 100,000 person-years).…”

Section: Introductionmentioning

confidence: 99%

Risk Factors for Rhabdomyolysis in the U.S. Army

et al. 2017

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The standardized mortality rate of rhabdomyolysis (RM) in Active Duty U.S. Army Soldiers is considerably higher than in the civilian population. RM occurs when large amounts of intracellular contents from damaged skeletal muscle escape into circulation, leading to serious sequelae (e.g., acute renal failure, hyperkalemia, compartment syndrome). Extended physical exertion, especially in hot environments, and trauma can precipitate RM. The aim of this study was to identify RM risk factors among U.S. Active Duty Army (ADA) Soldiers. Methods: This nested case-control study used data from the Total Army Injury and Health Outcomes Database (years 2004Database (years -2006 to examine RM among ADA male Soldiers. Demographic and occupational variables were identified as potential risk factors. Each RM case was age and date-matched to 4 controls. Adjusted odds ratios (OR) were computed using conditional logistic regression analyses. (2) self-reported Black race, OR 2.56 (95% CI 2.2-3.0); and (3) length of service (0-90 days), OR 2.05 (95% CI 1.6-2.7). Conclusion: There is a substantially greater likelihood for male U.S. Army Soldiers to develop RM who: (1) have had a prior heat injury, (2) self-report in the Black racial category, and (3) who are within the initial 90 days of service. Greater awareness of the risk factors associated with RM may improve force health protection and readiness through targeted mitigation strategies.

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Heat Stress Control and Heat Casualty Management

Cited by 22 publications

References 3 publications

Predicting Endurance Time in a Repetitive Lift and Carry Task Using Linear Mixed Models

Predicting Endurance Time in a Repetitive Lift and Carry Task Using Linear Mixed Models

The emergence of heat and humidity too severe for human tolerance

Risk Factors for Rhabdomyolysis in the U.S. Army

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