Sweat sodium composition and sweat loss estimation through wearable sensors and predictive equations in dry and humid hot conditions

TL;DR

This study compares wearable sensors and handheld analyzers for measuring sweat sodium and estimating sweat loss in hot conditions.

Contribution

The study introduces a wearable sweat sensor (S1) as a practical alternative for measuring sweat sodium and estimating sweat loss.

Findings

The S1 sensor provided sweat sodium measurements comparable to a handheld analyzer but lower than flame photometry.

The S1 sensor accurately estimated whole body sweat loss similar to scale measurements during cycling.

The sweat rate calculator underestimated fluid loss compared to the S1 and scale methods.

Abstract

Individualized sweat testing is essential for tailoring hydration and nutrition strategies, as water and sodium losses during exercise vary greatly across athletes. The validity of a wearable sweat sensor (S1, Flowbio) and a handheld analyzer (LAQUAtwin, Horiba Advanced Techno) for measuring sweat sodium concentration ([Na+]) was tested against flame photometry (FP). Additionally, whole body sweat loss (WBSL) estimated by the S1 and by a sweat rate calculator (SRC) was compared to the scale-based method.

Twenty-three recreationally active participants (11 males, 12 females) completed two sessions in hot and dry (40 °C, 36% rh) and hot and humid (30 °C, 81% rh) controlled environmental conditions on a cycling ergometer (74 ± 12 min, 1.9 ± 0.4 W/kg). Participants were instrumented with two S1 sensors and absorbent patches placed on each upper arm. Sweat was extracted from patches to measure [Na+] with LAQUAtwin and FP. Nude body mass was measured to the nearest 0.005 kg before and after exercise, with fluid intake monitored to determine WBSL. The influence of the method and the condition on the measure of sweat [Na+] and WBSL was investigated with linear mixed-effects models.

The estimated marginal means of sweat [Na+] in dry conditions for S1 and LAQUAtwin were equivalent (both 53 mmol/L, p = 0.952) and significantly lower than FP (63 mmol, both −10 mmol, p < 0.001). No significant interaction effects were observed between methods and conditions. For WBSL, the S1 estimation (1.479 kg) was not different than the scale measure (1.432 kg, 0.047, p = 0.624) while the SRC estimation (1.202 kg) was significantly lower than the scale and S1 (both p < 0.001), without interactions effects.

S1 offers equivalent and more practical collection of sweat [Na+] compared to the LAQUAtwin during indoor cycling ergometer exercise. However, measurements from both devices should currently be interpreted with caution and not considered equivalent to laboratory-grade analyses. Furthermore, S1 is an adequate tool during indoor cycling ergometer exercise to estimate WBSL when scale measurements are impractical, while SRC was found to underestimate fluid loss.

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