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Continuous Glucose Monitoring at High Altitude—Effects on Glucose Homeostasis

HILL, NEIL E.1,2; DEIGHTON, KEVIN3; MATU, JAMIE3; MISRA, SHIVANI4; OLIVER, NICK S.1,4; NEWMAN, CARRIE2; MELLOR, ADRIAN2,3; O’HARA, JOHN3; WOODS, DAVID2,3

Medicine & Science in Sports & Exercise: August 2018 - Volume 50 - Issue 8 - p 1679–1686
doi: 10.1249/MSS.0000000000001624
APPLIED SCIENCES
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Purpose Exposure to high altitude has been shown to enhance both glucose and lipid utilization depending on experimental protocol. In addition, high and low blood glucose levels have been reported at high altitude. We hypothesized that gradual ascent to high altitude results in changes in glucose levels in healthy young adults.

Methods Twenty-five adult volunteers, split into two teams, took part in the British Services Dhaulagiri Medical Research Expedition completing 14 d of trekking around the Dhaulagiri circuit in Nepal reaching a peak altitude of 5300 m on day 11 of the trek. Participants wore blinded continuous glucose monitors (CGM) throughout. Blood samples for C-peptide, proinsulin, and triacylglycerides were taken at sea level (United Kingdom) and in acclimatization camps at 3600, 4650, and 5120 m. Energy intake was determined from food diaries.

Results There was no difference in time spent in hypoglycemia stratified by altitude. Nocturnal CGM readings (2200–0600 h) were chosen to reduce the short-term effect of physical activity and food intake and showed a significant (P < 0.0001) increase at 3600 m (5.53 ± 0.22 mmol·L−1), 4650 m (4.77 ± 0.30 mmol·L−1), and 5120 m (4.78 ± 0.24 mmol·L−1) compared with baseline altitude 1100 m (vs 4.61 ± 0.25 mmol·L−1). Energy intake did not differ by altitude. Insulin resistance and beta-cell function, calculated by homeostatic model assessment, were reduced at 3600 m compared with sea level.

Conclusions We observed a significant increase in nocturnal CGM glucose at 3600 m and greater despite gradual ascent from 1100 m. Taken with the changes in insulin resistance and beta-cell function, it is possible that the stress response to high altitude dominates exercise-enhanced insulin sensitivity, resulting in relative hyperglycemia.

1Department of Diabetes and Endocrinology, Charing Cross Hospital, London, UNITED KINGDOM;

2Defence Medical Services, DMS Whittington, Lichfield, UNITED KINGDOM;

3Institute for Sport Physical Activity and Leisure, Leeds Beckett University, Leeds, UNITED KINGDOM;

4Diabetes, Endocrinology and Metabolic Medicine, Faculty of Medicine, Imperial College London, St. Mary’s Campus, London, UNITED KINGDOM

Address for correspondence: Neil E. Hill, M.R.C.P., Ph.D., Department of Diabetes and Endocrinology, Charing Cross Hospital, Fulham Palace Road, London, W6 8RF, United Kingdom; E-mail: n.hill@imperial.ac.uk.

Submitted for publication September 2017.

Accepted for publication February 2018.

Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s Web site (www.acsm-msse.org).

Ascent to high altitude (HA) is associated with significant risks, but despite this, mountaineering and HA trekking remain popular. In addition to environmental factors, such as temperature and wind, low barometric pressure combined with physical activity induces physiological changes that can result in impaired exercise capacity, a spectrum of altitude-related illnesses and even death (1).

To evaluate how harsh and inhospitable conditions affect people operating at HA, the Defence Medical Services have conducted a wide-ranging program of research investigating the effects of HA exposure (2–13). One area that remains relatively unexplored is how glucose homeostasis is affected by prolonged HA exposure. Exercise-induced hypoglcemia in nondiabetic subjects is recognized (14). At altitude, even mild neuroglycopenia could have serious repercussions, for example, loss of concentration or delayed recognition of imminent danger, and may exacerbate the effects of acute mountain sickness (AMS). A greater understanding of glucose flux at altitude may allow for appropriate prevention and management of both hypoglcemia and hyperglycemia, especially in conjunction with other life-threatening conditions such as HA pulmonary edema and HA cerebral edema.

Glucose is the most efficient fuel that the body can use, consuming less oxygen per unit of energy produced than either fat or protein (15). This is of relevance in hypoxic situations, such as those at HA. Sudden exposure to HA (4300 m) has been shown to lower blood glucose levels in the first 40 h (16). It has previously been postulated that hypoxemia may enhance utilization of glucose by mechanisms that are yet to be fully elucidated (17–19) and reduce reliance on fat as a substrate (20). However, we have recently shown that acute exposure to HA reduces carbohydrate oxidation and increases fat oxidation during walking (21) and prolonged cycling exercise (22). These contrasting results may be due to differences in energy consumption because the degree to which blood glucose increases on rapid ascent to 4300 m is higher if energy intake is adequate (23).

Loss of appetite is a near universal consequence of rapid ascent to HA and has a significant effect on the ability to maintain energy balance and, theoretically, glycemia. Anorexia may be mediated by hypothalamic mechanisms, but gastrointestinal signals causing nausea as part of the syndrome of AMS are a common exacerbating factor. It has been reported that soldiers participating in field exercises in mountainous terrain have consistently high rates of daily energy expenditure, but limited dietary energy intake (24). Increased energy requirements, reduced food intake, and factors driving muscle glucose uptake may therefore cause hypoglcemia, which has the potential to adversely affect performance at HA and even exacerbate AMS.

We hypothesized that ascent to HA results in a reduction in glucose levels and prolonged periods of hypoglycemia in healthy young adults. To investigate this, we undertook a novel observational study using continuous glucose monitoring (CGM) in volunteers undertaking a high-altitude expedition to the Himalayas in 2016.

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METHODS

Subjects

Participants (n = 25) were recruited from those taking part in the British Services Dhaulagiri Medical Research Expedition (BSDMRE) (25). The volunteers were divided into two teams (team 1 and team 2) and completed 14 d of trekking around the Dhaulagiri circuit in Nepal. Team 1 comprised 13 participants (10 male, 3 female) and team 2 had 12 volunteers (11 male, 1 female). Team 1 departed 14 d before team 2. Weather conditions and average temperatures were similar for both groups; at the time blood samples were collected (~0800 h), ambient temperatures in the research tents were 4.9°C, 1.2°C, and −6.4°C at 3600, 4650, and 5120 m, respectively. Both teams ascended to a peak altitude of 5300 m, with acclimatization days on days 7 and 10. In addition, team 1 had a further acclimatization day at 5120 m (details of altitudes and locations are in Table 1), whereas team 2 only stayed at this altitude for one night (due to several participants suffering from AMS who needed to descend on medical advice). Food (3 meals a day and afternoon tea) was provided by a support team of porters and chefs, accompanying each team separately. Thus, individuals within each team were offered the same type (and similar quantities) of food, but the food provision was not the same between each team. In general, the trekkers woke at 0600 h; after breakfast, trekking began at 0800 h and continued until ~1500 h (although this was variable depending on the distance and altitude covered). During the trek, regular breaks took place and lunch was taken at around noon. On arrival at the next camp, tea and biscuits were provided and little physical activity was undertaken. Supper was served at 1900 h and most people retired to their tents by 2100 h.

TABLE 1

TABLE 1

This study was conducted according to the guidelines laid down in the Declaration of Helsinki, and all procedures were approved by the Ethics Advisory Committee at Leeds Beckett University and the Ministry of Defence Research Ethics Committee (624/MODREC/14). All participants gave written informed consent.

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Study design

All participants wore blinded CGM throughout (Dexcom G4, San Diego, CA). CGM monitors were placed on the triceps area (participants were given the choice of triceps or abdominal wall) and replaced every 7 d. One CGM receiver stopped working after 5 d, and no further data were collected from that participant (male, team 1) and his/her results were excluded. Measurements of capillary blood glucose were also recorded twice each day using a Bayer Contour (Parsippany, NJ) glucometer using glucose dehydrogenase testing strips.

A priori, it was decided to focus on nocturnal (2200–0600 h) glucose measurements as the main outcome measurement to minimize the effects of food intake and physical activity on the glucose levels, thus hopefully allowing for clearer determination of the effects of altitude. CGM data were analyzed to identify the mean blood glucose during nighttime at Dharbang (1110 m) and on the night of arrival at each acclimatization camp (3600 m, Italian Base Camp; 4650 m, Dhaulagiri Base Camp; 5120 m, Hidden Valley) and each night of trekking. The overnight glycemic variability (measured by SD and coefficient of variation (CV)) was also assessed using EasyGV (Oxford, United Kingdom) software. Time spent in hypoglycemia (all readings) was determined at prespecified altitudes (<2000, 2000–3000, 3000–4000, and >4000 m). Three definitions of hypoglycemia were used: <3.9 mmol·L−1 (which correlates with the release of counterregulatory hormones), <3.3 mmol·L−1 (associated with the onset of neuroglycopenic and adrenergic symptoms), and <2.8 mmol·L−1 (the point at which cognitive dysfunction can occur) (26). All participants were asked to complete a standardized food intake diary, and daily energy intake was calculated using Nutritics dietary analysis software (v1.8 for Windows; Nutritics, Dublin). One day of food recording for one participant was excluded due to misrecording, and data were subsequently analyzed to include all remaining data (143 results) and also excluding days when participants had gastrointestinal illness affecting food intake (137 results).

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Blood sampling and assays

Venous blood samples were collected at sea level (in the United Kingdom) and at all research camps with participants in a fasted state. To prevent any extraneous influences from postural changes, all blood samples were collected after the participant had been seated for at least 5 min. One 5-mL precooled EDTA tube (Sarstedt, Leicester, United Kingdom) was used to obtain samples for the determination of C-peptide and proinsulin to investigate beta-cell function and insulin sensitivity. Immediately after filling, the tube was spun at 1500g for 10 min in a centrifuge (CompactStar CS4, VWR) and then immediately frozen at either −20°C in a freezer (for UK measurements) or within a dry shipper containing liquid nitrogen (at each fixed camp) before being transferred to −80°C and stored until analysis. C-peptide was measured on plasma samples using an automated chemiluminesent immunoassay (Abbott Architect, Abbott Park, IL) and proinsulin using a manual solid-phase two-site enzyme immunoassay (Mercodia Diagnostics, Upsalla, Sweden). To further understand the changes in overnight glucose observed at different altitudes, we calculated insulin resistance and beta-cell function using homeostatic model assessment (HOMA; http://www.dtu.ox.ac.uk/homacalculator/). We did not collect fasting plasma glucose and therefore used the mean CGM glucose between 5 AM and 6 AM on the day samples were taken. CGM glucose levels were used from the first morning of trekking (day 1) for the sea-level HOMA calculations. Plasma triacylglycerol concentration was determined spectrophotometrically using colorimetric analysis from a commercially available kit (Instrumentation Laboratory Company, Lexington, MA).

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Statistics

GraphPad Prism version 6.00 for Windows (GraphPad Software, La Jolla, CA; www.graphpad.com) was used for statistical analysis and graph creation. Data were checked for normality using the Shapiro–Wilk test. For unpaired data, one-way ANOVA was used with post hoc Dunnett’s multiple comparison test for parametric data, and the Kruskal–Wallis test with Dunn’s post hoc analysis for nonparametric data. Nonparametric repeated-measures data were analyzed using the Friedman test with Dunn’s post hoc analysis. To investigate differences between adjacent trek and rest days, data were analyzed by two-way ANOVA using Sidak’s multiple comparison test. Statistical significance was set at P < 0.05.

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RESULTS

Demographics

The mean age of the participants was 27.7 yr (range, 18–41 yr). Because of severe AMS, meaning that CGM sensors could not be replaced, data were not available for three participants at Hidden Valley (5120 m).

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Effects of altitude on hypoglycemia

There were no differences in percent time spent in hypoglycemia overnight (<3.9, <3.3, and <2.8 mmol·L−1) when the trekkers were at altitudes of less than 2000 m, between 2000 and 3000 m, and 3000–4000 m, or at more than 4000 m (Table 2).

TABLE 2

TABLE 2

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Effects of altitude on mean glucose levels and energy intake

There was a significant increase in mean nocturnal CGM glucose at Italian Base Camp (3600 m), Dhaulagiri Base Camp (4650 m), and Hidden Valley Camp (5120 m) compared with Dharbang (1110 m; 5.53 ± 0.22 vs 4.77 ± 0.30 vs 4.78 ± 0.24 vs 4.61 ± 0.25 mmol·L−1, respectively; P < 0.0001; Fig. 1). The mean nocturnal CGM glucose climbed steadily from Dharbang (4.61 ± 0.25 mmol·L−1) during the first week of the trek (Fig. 2A) peaking on the second night at Italian Base Camp (5.64 ± 0.25 mmol·L−1), then falling immediately to around 5 mmol·L−1 for the last 4 d. These results were largely replicated in both teams (Figs. 2B, C) despite them trekking at different times. The changes in CGM glucose were not obviously a reflection of the daily energy intake values. The mean daily energy intake immediately preceding the nocturnal glucose measurements did not differ between Dharbang and the three acclimatization camps (1968 ± 360 vs 2220 ± 558 vs 2354 ± 690 vs 2363 ± 434 kcal, P = 0.39) even when CGM glucose was most elevated (at the Italian Base Camp, 3600 m). Energy intake was lowest on the first 2 d of the trek when several participants were suffering from gastrointestinal illness (diarrhea and vomiting) resulting in reduced appetite independent of altitude (see Figure A, Supplemental Digital Content 1, Energy intake during the BSDMRE trek, http://links.lww.com/MSS/B249). When results of the effects of gastrointestinal disease were excluded, there were no changes in energy intake at any altitude (see Figure B, Supplemental Digital Content 1, Energy intake during the BSDMRE trek, http://links.lww.com/MSS/B249).

FIGURE 1

FIGURE 1

FIGURE 2

FIGURE 2

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Comparison of glucose levels on trekking and nontrekking (rest) days

There was a significantly higher mean nocturnal (2200–0600 h) CGM glucose at the Italian and Dhaulagiri Base Camps on rest days compared with the day before (when participants were trekking), but lower readings were recorded at Hidden Valley Camp on the rest day (Fig. 3A). Similarly, the mean daytime (0600–2200 h) CGM glucose levels were higher after a rest day at 3600 m (Italian Base Camp) and Hidden Valley Camp (5120 m), but not at Dhaulagiri (Fig. 3B). Energy intake was not different between trekking and rest days at any altitude (Fig. 3C).

FIGURE 3

FIGURE 3

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Effects of altitude on glycemic variability

Measures of glycemic variability were also examined. Nocturnal SD and mean amplitude of glycemia of CGM readings were not different significantly between Dharbang (1110 m), Italian Base Camp (3600 m), Dhaulagiri Base Camp (4650 m), and Hidden Valley (5120 m); however, there was a statistical difference in nocturnal percent CV (P = 0.02 by Kruskal–Wallis test). The difference between the median calibration capillary blood glucose and the temporally nearest CGM glucose reading did not change with altitude (−0.28 mmol·L−1 at <2000 m, −0.42 mmol·L−1 at 2000–3000 m, −0.33 mmol·L−1 at 3000–4000 m, −0.31 mmol·L−1 at 4000–5000 m, −0.25 mmol·L−1 at >5000 m; P = 0.79).

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Effects of altitude on beta-cell function and insulin resistance

There were significant reductions in C-peptide (P < 0.05) and proinsulin (P < 0.0001) levels between sea level (United Kingdom) and Italian Base Camp (3600 m) but no difference between sea level and Dhaulagiri Base Camp or Hidden Valley (Figs. 4A, B). Insulin resistance significantly differed with altitude (P = 0.04) and Holm–Sidak’s multiple comparisons showed a significant (P < 0.05) reduction in insulin resistance between sea level and Italian Base Camp, Dhaulagiri Base Camp, and Hidden Valley (Fig. 4C). Beta-cell function was also significantly different with altitude (P = 0.02), and Dunn’s multiple comparisons showed a significant (P < 0.05) reduction in beta-cell function between sea level and Italian Base Camp (Fig. 4D). The proinsulin/C-peptide ratio was not significantly altered by changes in altitude (P = 0.33; Fig. 4E). Triacylglycerol significantly increased with altitude (P < 0.0006; Fig. 4F).

FIGURE 4

FIGURE 4

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DISCUSSION

This is the first study to report the effects of gradual ascent to very HA on glucose levels measured by CGM in healthy volunteers. The participants, split into two groups, made it possible to compare whether the changes observed were reproducible in an environment where undertaking a controlled trial is not feasible. It is important to note that the ascent profile was carefully designed to minimize the risk of the participants developing AMS; thus, the daily ascent was rarely more than 500 m and the pace of walking set at that of the slowest team member. We believe that this means that the observed results reflect changes of acclimatization, rather than sudden exposure to HA.

The lack of differences in percentage time spent in hypoglcemia as the trekkers gained altitude is likely to reflect the gradual ascent profile and adaptation to HA. Strikingly, however, nocturnal glucose was significantly elevated, by around 0.8 mmol·L−1 at 3600 m compared with Dharbang (1100 m) and the higher camps (at 4650 and 5120 m). This was replicated in both team 1 and team 2. We interpret that the hyperglycemia and improved insulin sensitivity demonstrated at 3600 m to reflect parallel streams of adaptive physiology related to altitude (i.e., hypobaric hypoxia) and physical activity. A possible explanation is that physical activity pathway improves peripheral insulin sensitivity but the stress response to hypoxia dominates, raising blood glucose at the same time.

It has previously been shown (23) that acute (same day) ascent from sea level to 4300 m increases blood glucose on day 3 by 9.1%. Likewise, healthy volunteers exposed acutely to 3500-m altitude significantly increased plasma glucose from 4.59 mmol·L−1 at sea level to 5.53 mmol·L−1 (27). Interestingly, a study in which individuals were flown from Kathmandu (1300 m) to Namche (3500 m) then trekked to Everest Base Camp (5300 m) for 9 d showed no change in fasting glucose (or insulin sensitivity) until they had been at Base Camp for 6 wk (28). It is noteworthy that all these studies differ from ours because of their sudden exposure to HA. A reduction in the partial pressure of inspired oxygen is known to induce a stress response, which includes activation of the sympathetic nervous system and increased resting levels of normetanephrine at 3375 m (29). Increased catecholamines and sympathetic tone are associated with reduced insulin sensitivity at altitude (23,27,30,31), which would explain the observed hyperglycemia; however, our results show increased insulin sensitivity after gradual ascent to altitude. Others have shown no change during gradual acclimatization up to 5000 m (28) or increases in glucose utilization on acute exposure to 4300 m due to apparent increases in insulin action (19). The reasons for these divergent results are likely related to different study protocols, including rate of ascent and the complex mechanisms that underlie variations in glucose concentration at altitude, which include changes in beta-cell insulin secretion, hepatic glucose production, and tissue glucose uptake.

We further hypothesized that hypobaric hypoxia would result in beta-cell stress resulting in an increase in the proinsulin/C-peptide ratio at altitude (32). We observed no change in the proinsulin/C-peptide ratio with altitude; however, the reduced C-peptide and proinsulin levels at Italian Base Camp may indicate beta-cell stress and relative insulin deficiency. This provides a potential mechanism whereby reduced insulin secretion occurs in response to hypoxia. Increased insulin sensitivity, as seen at all altitudes above sea level in our study, which may be related to exercise (and possibly altitude induced), is, at least in part, due to up-regulation of skeletal muscle GLUT4 receptor translocation. In adult rats exposed to 9% inspired oxygen for 30 d, GLUT4 protein increased by 15%–20% compared with controls (33). Furthermore, in immature (21 d of age) and adult (6 months of age) rats exposed to a simulated altitude of 4878 m, there was increased leg muscle GLUT4 and reduced insulin receptor density after 7 d, but these changes disappeared by 28 d (34). These results could explain our observed increase in peripheral insulin sensitivity. Reduced insulin secretion also leads to increased hormone sensitive lipase activity with subsequent increased lipolysis and greater levels of circulating triglycerides, as we have shown and has been observed in response to simulated ascent to HA (35).

These results do not fit into a neat paradigm and the cellular mechanisms driving these findings are not known; thus, our proposed explanation (see Figure, Supplemental Digital Content 2, Proposed pathways influencing glucose levels during acclimatization to HA, http://links.lww.com/MSS/B250) is deliberately simplified to include the components that we measured. It should be noted that this description does not account for changes in multiple factors including the distribution and number of GLUT1 receptors, alterations in hypoxia-inducible factors (e.g., HIF1α), modulation of insulin receptor density, variations in rate-limiting enzymes such as glucokinase or glucose-6-phosphate, or the response of other hormones such as growth hormone, glucagon, and thyroxine to altitude exposure. Furthermore, we recognize that plasma levels of glucose and triacylglycerol do not reflect tissue uptake nor oxidation; thus reduced clearance, insulin resistance, and increased lipolysis may be important.

The absence of consistent changes in markers of glycemic variability implies that the increase in mean nocturnal glucose seen at Italian Base Camp (3600 m) was not due to greater glucose flux. The overall CV at all altitudes are all considered to reflect low levels of glycemic variability, which has previously been defined as a CV of <36% (36).

We suspected that increased food intake may play a role in the higher glucose readings seen on rest days; however, the results do not bear this out—there was no greater energy intake on rest days. Although food diaries are recognized to have limited reproducibility and accuracy (37), the energy intake in our study is within the levels expected for adults at altitude. The increased CGM glucose observed on some trekking days preceding rest days may reflect an exercise-mediated increase in insulin sensitivity and increases in non–insulin-mediated glucose uptake occurring on trekking days, and reduced physical activity on rest days; however, the lack of consistency in these findings warrants further investigation.

There were notable limitations to this study. The volunteers were nearly all white European young adults with reasonable levels of cardiovascular fitness, and therefore, the results may not be applicable to other populations. There was no standardized measurement of blood glucose (e.g., a YSI glucose meter), thus, the CGM calibration by fingerprick glucose meter may be subject to error (indeed this has been noted before) (38). In addition, only two calibration readings were taken each day (the minimum recommended). The altitude and cold temperatures may also have affected the CGM readings. CGM has been investigated in vitro in a hypobaric chamber using solutions containing 2.9, 4.9, and 11.3 mmol·L−1 glucose. Under conditions mimicking altitudes of 2500 and 5500 m, continuous readings were obtained; however, there was a significant difference in the CGM at the lower and higher glucose concentration compared with normobaric CGM (39,40). To mitigate against cold, the participants were encouraged to keep their CGM receivers inside their inner pockets. Reassuringly, the difference between CGM and calibration glucose measurements did not change significantly with increasing altitude, indicating that the CGM readings were at least consistent with those obtained from the fingerprick glucometers. Our sample size was too small to detect gender-based differences in glucose homeostasis, in particular the phase of menstrual cycle (greater insulin resistance typically occurs during the luteal phase) in female trekkers; this could be investigated in a larger group. Although this study lacks a control arm of people trekking under similar conditions at sea level, one of the strengths is that it was done in two different teams, and thus, the observed changes are independent of the time of trekking and other factors that might have affected a single group of people. Nevertheless, these results provide an insight into the changes in glucose homeostasis that occur as acclimatization to HA takes place.

In summary, we have shown a significant increase in nocturnal CGM glucose at 3600 m and greater than after gradual ascent from 1100 m. Taken with reduced insulin resistance and evidence of beta-cell dysfunction, it is possible that the stress response to HA leads to relative insulin deficiency and this effect is greater than exercise-induced increase in insulin sensitivity, resulting in relative hyperglycemia. Future studies could measure catecholamines, cortisol, and other stress markers as well as undertaking muscle biopsies to look at GLUT expression.

We are grateful to all the volunteers who took part in the study.

Dexcom provided the CGM kit. They had no role in study design, data analysis, or writing of this manuscript. This study has not been presented elsewhere.

This research was part of the British Services Dhaulagiri Medical Research Expedition, which was supported by the Royal Navy and Royal Marines Charity, the Defence Medical Services and Leeds Beckett University.

N. E. H. conceived the study, collected data, analyzed data, and wrote the manuscript. K. D. collected data and reviewed/edited the manuscript. S. M. analyzed samples, contributed to discussion, and reviewed/edited the manuscript. N. S. O. conceived the study and wrote the manuscript. C. N. collected data. A. M. conceived the study and reviewed/edited the manuscript. J. O. H. conceived the study and reviewed/edited the manuscript. D. W. conceived the study and wrote the manuscript.

N. E. H. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. The results of the present study do not constitute endorsement by the American College of Sports Medicine.

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REFERENCES

1. Barry PW, Pollard AJ. Altitude illness. BMJ. 2003;326:915–9.
2. Mellor AJ, Woods DR, O’Hara J, Howley M, Watchorn J, Boos C. Rating of perceived exertion and acute mountain sickness during a high-altitude trek. Aviat Space Environ Med. 2014;85:1214–6.
3. Mellor AJ, Boos CJ, Ball S, et al. Copeptin and arginine vasopressin at high altitude: relationship to plasma osmolality and perceived exertion. Eur J Appl Physiol. 2015;115:91–8.
4. Boos CJ, Holdsworth DA, Hall DP, Mellor A, O’Hara J, Woods DR. Comparison of two methods of assessing total body water at sea level and increasing high altitude. Clin Physiol Funct Imaging. 2014;34:478–84.
5. Mellor A, Boos C, Stacey M, et al. Neutrophil gelatinase-associated lipocalin: its response to hypoxia and association with acute mountain sickness. Dis Markers. 2013;35:537–42.
6. Woods DR, Mellor A, Begley J, et al. Brain natriuretic peptide and NT-proBNP levels reflect pulmonary artery systolic pressure in trekkers at high altitude. Physiol Res. 2013;62:597–603.
7. Boos CJ, Holdsworth DA, Woods DR, Green K, Naylor J, Mellor A. Cardiac biomarkers and high altitude pulmonary edema. Int J Cardiol. 2013;167:e65–6.
8. Boos CJ, Hodkinson P, Mellor A, Green NP, Woods DR. The effects of acute hypobaric hypoxia on arterial stiffness and endothelial function and its relationship to changes in pulmonary artery pressure and left ventricular diastolic function. High Alt Med Biol. 2012;13:105–11.
9. Woods DR, Davison A, Stacey M, et al. The cortisol response to hypobaric hypoxia at rest and post-exercise. Horm Metab Res. 2012;44:302–5.
10. Woods DR, Begley J, Stacey M, et al. Severe acute mountain sickness, brain natriuretic peptide and NT-proBNP in humans. Acta Physiol (Oxf). 2012;205:349–55.
11. Hill NE, Stacey MJ, Woods DR. Energy at high altitude. J R Army Med Corps. 2011;157(1):43–8.
12. Woods DR, Stacey M, Hill N, de Alwis N. Endocrine aspects of high altitude acclimatization and acute mountain sickness. J R Army Med Corps. 2011;157:33–7.
13. Woods DR, Allen S, Betts TR, et al. High altitude arrhythmias. Cardiology. 2008;111:239–46.
14. Brun JF, Dumortier M, Fedou C, Mercier J. Exercise hypoglycemia in nondiabetic subjects. Diabetes Metab. 2001;27:92–106.
15. Schippers MP, Ramirez O, Arana M, Pinedo-Bernal P, McClelland GB. Increase in carbohydrate utilization in high-altitude Andean mice. Curr Biol. 2012;22:2350–4.
16. Johnson HL, Consolazio CF, Burk RF, Daws TA. Glucose-14 C-UL metabolism in man after abrupt altitude exposure (4,300 m). Aerosp Med. 1974;45:849–54.
17. Brooks GA, Butterfield GE, Wolfe RR, et al. Increased dependence on blood glucose after acclimatization to 4,300 m. J Appl Physiol (1985). 1991;70:919–27.
18. Brooks GA, Wolfel EE, Groves BM, et al. Muscle accounts for glucose disposal but not blood lactate appearance during exercise after acclimatization to 4,300 m. J Appl Physiol (1985). 1992;72:2435–45.
19. Roberts AC, Reeves JT, Butterfield GE, et al. Altitude and beta-blockade augment glucose utilization during submaximal exercise. J Appl Physiol (1985). 1996;80:605–15.
20. Roberts AC, Butterfield GE, Cymerman A, Reeves JT, Wolfel EE, Brooks GA. Acclimatization to 4,300-m altitude decreases reliance on fat as a substrate. J Appl Physiol (1985). 1996;81:1762–71.
21. Matu J, Deighton K, Ispoglou T, Duckworth L. The effect of moderate versus severe simulated altitude on appetite, gut hormones, energy intake and substrate oxidation in men. Appetite. 2017;113:284–92.
22. O’Hara JP, Woods DR, Mellor A, et al. A comparison of substrate oxidation during prolonged exercise in men at terrestrial altitude and normobaric normoxia following the coingestion of 13C glucose and 13C fructose. Physiol Rep. 2017;5:e13101.
23. Barnholt KE, Hoffman AR, Rock PB, et al. Endocrine responses to acute and chronic high-altitude exposure (4,300 meters): modulating effects of caloric restriction. Am J Physiol Endocrinol Metab. 2006;290:E1078–88.
24. Hoyt RW, Jones TE, Baker-Fulco CJ, et al. Doubly labeled water measurement of human energy expenditure during exercise at high altitude. Am J Physiol. 1994;266:R966–71.
25. Mellor A, Bakker-Dyos J, Howard M, et al. The British Services Dhaulagiri Medical Research Expedition 2016: a unique military and civilian research collaboration. J R Army Med Corps. 2017;163:371–5.
26. International Hypoglycaemia Study Group. Glucose concentrations of less than 3.0 mmol/l (54 mg/dl) should be reported in clinical trials: a joint position statement of the American Diabetes Association and the European Association for the Study of Diabetes. Diabetes Care. 2017;40:155–7.
27. Sawhney RC, Malhotra AS, Singh T, Rai RM, Sinha KC. Insulin secretion at high altitude in man. Int J Biometeorol. 1986;30:231–8.
28. Siervo M, Riley HL, Fernandez BO, et al. Effects of prolonged exposure to hypobaric hypoxia on oxidative stress, inflammation and gluco-insular regulation: the not-so-sweet price for good regulation. PLoS One. 2014;9:e94915.
29. Woods DR, O’Hara JP, Boos CJ, et al. Markers of physiological stress during exercise under conditions of normoxia, normobaric hypoxia, hypobaric hypoxia, and genuine high altitude. Eur J Appl Physiol. 2017;117:893–900.
30. Braun B, Rock PB, Zamudio S, et al. Women at altitude: short-term exposure to hypoxia and/or alpha(1)-adrenergic blockade reduces insulin sensitivity. J Appl Physiol (1985). 2001;91:623–31.
31. Larsen JJ, Hansen JM, Olsen NV, Galbo H, Dela F. The effect of altitude hypoxia on glucose homeostasis in men. J Physiol. 1997;504:241–9.
32. Sato Y, Inoue M, Yoshizawa T, Yamagata K. Moderate hypoxia induces β-cell dysfunction with HIF-1–independent gene expression changes. PLoS One. 2014;9:e114868.
33. Xia Y, Warshaw JB, Haddad GG. Effect of chronic hypoxia on glucose transporters in heart and skeletal muscle of immature and adult rats. Am J Physiol. 1997;273:R1734–41.
34. Dill RP, Chadan SG, Li C, Parkhouse WS. Aging and glucose transporter plasticity in response to hypobaric hypoxia. Mech Ageing Dev. 2001;122:533–45.
35. Young PM, Rose MS, Sutton JR, Green HJ, Cymerman A, Houston CS. Operation Everest II: plasma lipid and hormonal responses during a simulated ascent of Mt. Everest. J Appl Physiol (1985). 1989;66:1430–5.
36. Monnier L, Colette C, Wojtusciszyn A, et al. Toward defining the threshold between low and high glucose variability in diabetes. Diabetes Care. 2017;40:832–8.
37. De Castro JM. Methodology, correlational analysis, and interpretation of diet diary records of the food and fluid intake of free-living humans. Appetite. 1994;23:179–92.
38. Oberg D, Ostenson CG. Performance of glucose dehydrogenase-and glucose oxidase-based blood glucose meters at high altitude and low temperature. Diabetes Care. 2005;28:1261.
39. de Mol P, Krabbe HG, de Vries ST, et al. Accuracy of handheld blood glucose meters at high altitude. PLoS One. 2010;5:e1548.
40. Adolfsson P, Ornhagen H, Eriksson BM, Gautham R, Jendle J. In-vitro performance of the Enlite Sensor in various glucose concentrations during hypobaric and hyperbaric conditions. J Diabetes Sci Technol. 2012;6:1375–82.
Keywords:

GLYCEMIC VARIABILITY; EXERCISE; TREKKING; INSULIN RESISTANCE; HYPOGLYCEMIA

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