Increased core body temperature in astronauts during long-duration space missions

Abstract

Humans' core body temperature (CBT) is strictly controlled within a narrow range. Various studies dealt with the impact of physical activity, clothing, and environmental factors on CBT regulation under terrestrial conditions. However, the effects of weightlessness on human thermoregulation are not well understood. Specifically, studies, investigating the effects of long-duration spaceflight on CBT at rest and during exercise are clearly lacking. We here show that during exercise CBT rises higher and faster in space than on Earth. Moreover, we observed for the first time a sustained increased astronauts' CBT also under resting conditions. This increase of about 1 °C developed gradually over 2.5 months and was associated with augmented concentrations of interleukin-1 receptor antagonist, a key anti-inflammatory protein. Since even minor increases in CBT can impair physical and cognitive performance, both findings have a considerable impact on astronauts' health and well-being during future long-term spaceflights. Moreover, our findings also pinpoint crucial physiological challenges for spacefaring civilizations, and raise questions about the assumption of a thermoregulatory set point in humans, and our evolutionary ability to adapt to climate changes on Earth.

Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Figure 1

Changes in core body temperature at rest (left panel, a and c) and after exercise (right panel, b and d) during long-duration spaceflight. Grey shaded area shows time during space. Upper panels (a and b) show marginal means and 95% CI from mixed model treating time as a fixed factor. Significant levels are indicated by asterisks. Pre refers to preflight data collection. 15, 45, 75, 105, 135 and 165 indicate flight day during mission. +1, +10 and +30 correspond to the number of days when data were collected after return to Earth. Lower panels (c and d) show marginal means and 95% CI as well as individual (dotted lines) and overall (solid lines) trajectories for changes of CBT over time, resulting from mixed models treating time as a covariate (for details see methods). n = 11, missing data are detailed in Tables S1 and S2. ***P < 0.001, **P < 0.01, *P < 0.05.

Figure 2

Changes of increase in core body temperature during exercise (left panel, a and c) and IL-1ra (right panel, b and d) at rest during long-duration spaceflight. Grey shaded area shows time during space. Panel a and b show marginal means and 95% CI from mixed model treating time as a fixed factor the slope of CBT during exercise and IL-1ra, respectively. Significant levels are indicated by asterisks. Pre refers to preflight data collection. 15, 45, 75, 105, 135 and 165 indicate flight day during mission. +1, +10 and +30 correspond to the number of days when data were collected after return to Earth. Panel c and d show marginal means and 95% CI as well as individual (dotted lines) and overall trajectories (solid lines) for changes of increases in CBT and IL-1ra over time, respectively, resulting from mixed models treating time as a covariate (for details see methods). Panel c shows a single subject with an unusual response, which was also confirmed by influential diagnostics (highest Cook’s D). The model was therefore rerun excluding these data, which, however, did not alter the inferential statistics, i.e. both the linear and quadratic component remained highly significant (p ***P < 0.001, **P < 0.01, *P < 0.05.

Figure 3

Repeated measures correlation between IL-1ra and core body temperature at rest (a) and after exercise (b) during long-duration spaceflight, to assess whether an increase in IL-1ra was associated with an increase in CBT within the individual. Dots are actual data values and grouped by subjects (each color summarizing one subject, n = 7 see also Table S4). By removing measured variance between-participants using analysis of covariance (ANCOVA), the repeated measures correlation provides the best linear fit for each participant using parallel regression lines. Solid colored lines show the repeated measures correlation model fit. Note that the availability of data points varies for individuals, reflecting different length of model fits. The multilevel model fit (dashed line) is also shown for the conditional effect (intervention, i.e. spaceflight).