Cardiovascular and thermal strain during 3-4 days of a metabolically demanding cold-weather military operation

BACKGROUND

Cardiovascular (CV) and thermal responses to metabolically demanding multi-day military operations in extreme cold-weather environments are not well described. Characterization of these operations will provide greater insights into possible performance capabilities and cold injury risk.

METHODS

Soldiers from two cold-weather field training exercises (FTX) were studied during 3-day (study 1, n = 18, age: 20 ± 1 year, height: 182 ± 7 cm, mass: 82 ± 9 kg) and 4-day (study 2, n = 10, age: 20 ± 1 year, height: 182 ± 6 cm, mass: 80.7 ± 8.3 kg) ski marches in the Arctic. Ambient temperature ranged from -18 to -4 °C during both studies. Total daily energy expenditure (TDEE, from doubly labeled water), heart rate (HR), deep body (T_pill), and torso (T_torso) skin temperature (obtained in studies 1 and 2) as well as finger (T_fing), toe (T_toe), wrist, and calf temperatures (study 2) were measured.

RESULTS

TDEE was 6821 ± 578 kcal day^-1 and 6394 ± 544 for study 1 and study 2, respectively. Mean HR ranged from 120 to 140 bpm and mean T_pill ranged between 37.5 and 38.0 °C during skiing in both studies. At rest, mean T_pill ranged from 36.0 to 36.5 °C, (lowest value recorded was 35.5 °C). Mean T_fing ranged from 32 to 35 °C during exercise and dropped to 15 °C during rest, with some T_fing values as low as 6-10 °C. T_toe was above 30 °C during skiing but dropped to 15-20 °C during rest.

CONCLUSIONS

Daily energy expenditures were among the highest observed for a military training exercise, with moderate exercise intensity levels (~65% age-predicted maximal HR) observed. The short-term cold-weather training did not elicit high CV and T_pill strain. T_fing and T_toe were also well maintained while skiing, but decreased to values associated with thermal discomfort at rest.

Effects of winter military training on energy balance, whole-body protein balance, muscle damage, soreness, and physical performance

Physiological consequences of winter military operations are not well described. This study examined Norwegian soldiers (n = 21 males) participating in a physically demanding winter training program to evaluate whether short-term military training alters energy and whole-body protein balance, muscle damage, soreness, and performance. Energy expenditure (D218O) and intake were measured daily, and postabsorptive whole-body protein turnover ([15N]-glycine), muscle damage, soreness, and performance (vertical jump) were assessed at baseline, following a 4-day, military task training phase (MTT) and after a 3-day, 54-km ski march (SKI). Energy intake (kcal·day−1) increased (P < 0.01) from (mean ± SD (95% confidence interval)) 3098 ± 236 (2985, 3212) during MTT to 3461 ± 586 (3178, 3743) during SKI, while protein (g·kg−1·day−1) intake remained constant (MTT, 1.59 ± 0.33 (1.51, 1.66); and SKI, 1.71 ± 0.55 (1.58, 1.85)). Energy expenditure increased (P < 0.05) during SKI (6851 ± 562 (6580, 7122)) compared with MTT (5480 ± 389 (5293, 5668)) and exceeded energy intake. Protein flux, synthesis, and breakdown were all increased (P < 0.05) 24%, 18%, and 27%, respectively, during SKI compared with baseline and MTT. Whole-body protein balance was lower (P < 0.05) during SKI (–1.41 ± 1.11 (–1.98, –0.84) g·kg−1·10 h) than MTT and baseline. Muscle damage and soreness increased and performance decreased progressively (P < 0.05). The physiological consequences observed during short-term winter military training provide the basis for future studies to evaluate nutritional strategies that attenuate protein loss and sustain performance during severe energy deficits.

Validation of equations used to predict plasma osmolality in a healthy adult cohort

BACKGROUND

Plasma osmometry and the osmol gap have long been used to provide clinicians with important diagnostic and prognostic patient information.

OBJECTIVE

We compared different equations used for predicting plasma osmolality when its direct measurement was not practical or an osmol gap was of interest and identified the best performers.

DESIGN

The osmolality of plasma was measured by using freezing point depression by microosmometer and osmolarity calculated from biosensor measures of select analytes according to the dictates of each formula tested. After a rigid analytic prescreen of 36 originally published equations, a bootstrap regression analysis was used to compare shrinkage and model agreement.

RESULTS

Sixty healthy volunteers provided 163 plasma samples for analysis. Of 36 equations considered, 11 equations met the prescreen variables for the bootstrap regression analysis. Of the 11 equations, 8 equations met shrinkage and apparent model error thresholds, and 5 equations were deemed optimal with an original model osmol gap <5 mmol.

CONCLUSIONS

The use of bootstrap regression provides a unique insight for osmolality prediction equation performance from a very large theoretical population of healthy people. Of the original 36 equations evaluated, 5 equations appeared optimal for the prediction of osmolality when its direct measurement was not practical or an osmol gap was of interest. Note that 4 of 5 optimal equations were derived from a nonhealthy population.

A comparison of whole blood and plasma osmolality and osmolarity

BACKGROUND

Substituting whole blood osmolality for plasma osmolality could expedite treatments otherwise delayed by the time required to separate erythrocytes from plasma. The purpose of this study was to compare the measured osmolality (mmol/kg) and calculated osmolarity (mmol/l) of whole blood and plasma.

METHODS

The osmolality of whole blood and plasma was measured using freezing point depression by micro-osmometer and osmolarity calculated from biosensor measures of sodium, glucose, and blood urea nitrogen. The influence of sample volume was also investigated post hoc by comparing measured osmolality at 20 and 250 μl.

RESULTS

Sixty-two volunteers provided 168 paired whole blood and plasma samples for analysis. The mean difference (whole blood - plasma; ±standard deviation) in osmolality was 10 ± 3 mmol/kg. Whole blood was greater than plasma in 168 of 168 cases (100%) and data distributions overlapped by 27%. The mean difference in osmolarity was 0 ± 2 mmol/l. Whole blood was greater than plasma in 90 of 168 cases (56%) and data distributions overlapped by 90%. The osmol gap (osmolality - osmolarity) was 16 ± 6 mmol for whole blood and 7 ± 5 mmol for plasma. Ten volunteers were tested on one occasion post hoc to investigate the potential effects of sample volume. The difference between whole blood and plasma was reduced to 3 ± 2 mmol/kg with a larger (250 μl vs. 20 μl) sample volume.

CONCLUSIONS

This investigation provides strong evidence that whole blood and plasma osmolality are not interchangeable measurements when a 20 μl sample is used.

Effects of a 7-day military training exercise on inflammatory biomarkers, serum hepcidin, and iron status

BACKGROUND

Hepcidin, a peptide that is released into the blood in response to inflammation, prevents cellular iron export and results in declines in iron status. Elevated serum and urinary levels of hepcidin have been observed in athletes following exercise, and declines in iron status have been reported following prolonged periods of training. The objective of this observational study was to characterize the effects of an occupational task, military training, on iron status, inflammation, and serum hepcidin.

FINDINGS

Volunteers (n = 21 males) included Norwegian Soldiers participating in a 7-day winter training exercise that culminated in a 3-day, 54 km ski march. Fasted blood samples were collected at baseline, on day 4 (PRE, prior to the ski march), and again on day 7 (POST, following the ski march). Samples were analyzed for hemoglobin, serum ferritin, soluble transferrin receptor (sTfR), interleukin-6 (IL-6), and serum hepcidin. Military training affected inflammation and serum hepcidin levels, as IL-6 and hepcidin concentrations increased (P < 0.05) from the baseline to POST (mean ± SD, 9.1 ± 4.9 vs. 14.5 ± 8.4 pg/mL and 6.5 ± 3.5 vs. 10.2 ± 6.9 ng/mL, respectively). Iron status was not affected by the training exercise, as sTfR levels did not change over the course of the 7-day study.

CONCLUSIONS

Military training resulted in significant elevations in IL-6 and serum hepcidin. Future studies should strive to identify the role of hepcidin in the adaptive response to exercise, as well as countermeasures for the prevention of chronic or repeated elevations in serum hepcidin due to exercise or sustained occupational tasks which may result in longer term decrements in iron status.

The effects of elapsed time after warm-up on subsequent exercise performance in a cold environment

Athletes often compete in cold environments and may face delays because of weather or race logistics between performance of a warm-up and the start of the race. This study sought to determine, (a) whether a delay after warm-up affects subsequent time trial (TT) performance and (b) if exposure to a cold environment has an additive effect. We hypothesized that after a warm-up, 30 minutes of rest in a cold environment would negatively affect subsequent rowing and running performance. In a temperate (temp; 24° C) or cold (cold; 5° C) environment, 5 rowers (33 ± 10 years; 83 ± 12 kg) and 5 runners (23 ± 2 years; 65 ± 8 kg) performed a 15-minute standardized warm-up followed by a 5- or 30-minute rest and then performed a 2-km rowing or 2.4 km running TT. The 5-minute rest following warm-up in the temperate environment (5Temp) served as the control trial to which the other experimental trials (5Cold; 30Temp; and 30Cold) were compared. Heart rate, lactate, and esophageal (Tes) and skin (Tsk) temperatures were measured throughout. Postrest and post-TT, Tes, and Tsk were lowest in the 30Cold trials. The greatest decrement in TT performance vs. 5Temp occurred in 30Cold (-4.0%; difference of 20 seconds). This difference is considered to have practical importance, as it was greater than the reported day-to-day variation for events of this type. We conclude that longer elapsed time following warm-up, combined with cold air exposure, results in potentially important reductions in exercise performance. Athletes should consider the appropriate timing of warm-up. In addition, performance may be preserved by maintaining skin and core temperatures following a warm-up, via clothing or other means.

Assessment of extracellular dehydration using saliva osmolality

INTRODUCTION

When substantial solute losses accompany body water an isotonic hypovolemia (extracellular dehydration) results. The potential for using blood or urine to assess extracellular dehydration is generally poor, but saliva is not a simple ultra-filtrate of plasma and the autonomic regulation of salivary gland function suggests the possibility that saliva osmolality (Sosm) may afford detection of extracellular dehydration via the influence of volume-mediated factors.

PURPOSE

This study aimed to evaluate the assessment of extracellular dehydration using Sosm. In addition, two common saliva collection methods and their effects on Sosm were compared.

METHODS

Blood, urine, and saliva samples were collected in 24 healthy volunteers during paired euhydration and dehydration trials. Furosemide administration and 12 h fluid restriction were used to produce extracellular dehydration. Expectoration and salivette collection methods were compared in a separate group of eight euhydrated volunteers. All comparisons were made using paired t-tests. The diagnostic potential of body fluids was additionally evaluated.

RESULTS

Dehydration (3.1 ± 0.5% loss of body mass) decreased PV (-0.49 ± 0.12 L; -15.12 ± 3.94% change), but Sosm changes were marginal (<10 mmol/kg) and weakly correlated with changes in absolute or relative PV losses. Overall diagnostic accuracy was poor (AUC = 0.77-0.78) for all body fluids evaluated. Strong agreement was observed between Sosm methods (Expectoration: 61 ± 10 mmol/kg, Salivette: 61 ± 8 mmol/kg, p > 0.05).

CONCLUSIONS

Extracelluar dehydration was not detectable using plasma, urine, or saliva measures. Salivette and expectoration sampling methods produced similar, consistent results for Sosm, suggesting no methodological influence on Sosm.