Validation of Core, Rectal and Skin Temperature Predictions of a Free Web-Based Predictive Heat Strain Software Based on the ISO 7933:2023 Standard in Recreational Athletes

Konstantinos Mantzios, Leonidas G. Ioannou, Eftihia Nikolaki, Paraskevi Gkiata, Georgia Charachousou, Lydia Tsoutsoubi, Petros C. Dinas, Andreas D. Flouris

Journal of Science in Sport and Exercise ›› 2024, Vol. 6 ›› Issue (3) : 303-314. DOI: 10.1007/s42978-024-00309-5
Original Article

Validation of Core, Rectal and Skin Temperature Predictions of a Free Web-Based Predictive Heat Strain Software Based on the ISO 7933:2023 Standard in Recreational Athletes

Author information +
History +

Abstract

We previously developed the FAME Lab PHS software (PHSFL), a free offline software to calculate the predicted heat strain for a group of individuals based on the ISO 7933. The objectives of this study were to: upgrade the PHSFL from an offline (desktop-version) tool to a web-based platform, as well as assess its validity in recreational athletes in different forms of exercise and across various temperature recording methodologies and environmental conditions. The web PHSFL was developed as browser-based software developed using HTML, CSS, and JavaScript, and included several updates from the previous offline version. Its validity was assessed in 83 healthy non-smoking males and females during rest, exercise, and post-exercise recovery in 165 trials (cycling: 97; running: 68). Trials were performed in an environmental chamber under varying environmental conditions: 19.1 to 40.6 °C air temperature, 30.0% to 60.0% relative humidity, 0.1 to 0.5 m/s wind speed, and 0 or 800 W/m2 solar radiation. Comparison of actual vs. predicted core body temperature showed 0.85 Willmott’s Index of Agreement, 0.76 (P < 0.001) correlation coefficient, and 95% limits of agreement of 0.16 ± 0.83 °C (mean difference ± 95% limits). Results for rectal temperature showed 0.79 Willmott’s Index of Agreement, 0.68 (P < 0.001) correlation coefficient, and 95% limits of agreement of 0.18 ± 0.76 °C. Results for skin temperature showed 0.77 Willmott’s Index of Agreement, 0.75 (P < 0.001) correlation coefficient, and 95% limits of agreement of − 0.24 ± 2.28 °C. We conclude that the web PHSFL provides acceptably accurate predictions of core body temperature and skin temperature to be used as indicators of physiological heat strain.

Keywords

Simulation / Exercise / Hyperthermia / Body temperature / Thermoregulation

Cite this article

Download citation ▾
Konstantinos Mantzios, Leonidas G. Ioannou, Eftihia Nikolaki, Paraskevi Gkiata, Georgia Charachousou, Lydia Tsoutsoubi, Petros C. Dinas, Andreas D. Flouris. Validation of Core, Rectal and Skin Temperature Predictions of a Free Web-Based Predictive Heat Strain Software Based on the ISO 7933:2023 Standard in Recreational Athletes. Journal of Science in Sport and Exercise, 2024, 6(3): 303‒314 https://doi.org/10.1007/s42978-024-00309-5

References

[1]
Ainsworth BE, Haskell WL, Whitt MC, Irwin ML, Swartz AM, Strath SJ, O’Brien WL, Bassett DR Jr, Schmitz KH, Emplaincourt PO, Jacobs DR Jr, Leon AS. Compendium of physical activities: an update of activity codes and MET intensities. Med Sci Sports Exerc, 2000, 32(9 Suppl): S498-504,
CrossRef Google scholar
[2]
Ainsworth BE, Haskell WL, Herrmann SD, Meckes N, Bassett DR Jr, Tudor-Locke C, Greer JL, Vezina J, Whitt-Glover MC, Leon AS. 2011 Compendium of Physical Activities: a second update of codes and MET values. Med Sci Sports Exerc, 2011, 43(8): 1575-81,
CrossRef Google scholar
[3]
American College of Sports Medicine. ACSM guidelines for exercise testing and prescription. New York City; Wolters Kluwer. 2019.
[4]
Allnutt MF, Allan JR. The effects of core temperature elevation and thermal sensation on performance. Ergonomics, 1973, 16(2): 189-96,
CrossRef Google scholar
[5]
Buller MJ, Tharion WJ, Cheuvront SN, Montain SJ, Kenefick RW, Castellani J, Latzka WA, Roberts WS, Richter M, Jenkins OC, Hoyt RW. Estimation of human core temperature from sequential heart rate observations. Physiol Meas, 2013, 34(7): 781-98,
CrossRef Google scholar
[6]
Campbell-Staton SC, Walker RH, Rogers SA, De León J, Landecker H, Porter W, Mathewson PD, Long RA. Physiological costs of undocumented human migration across the southern United States border. Science, 2021, 374(6574): 1496-500,
CrossRef Google scholar
[7]
Casa DJ, Becker SM, Ganio MS, Brown CM, Yeargin SW, Roti MW, Siegler J, Blowers JA, Glaviano NR, Huggins RA, Armstrong LE, Maresh CM. Validity of devices that assess body temperature during outdoor exercise in the heat. J Athl Train, 2007, 42(3): 333-42
[8]
Cushman DM, Markert M, Rho M. Performance trends in large 10-km road running races in the United States. J Strength Cond Res, 2014, 28(4): 892-901,
CrossRef Google scholar
[9]
Eggenberger P, MacRae BA, Kemp S, Burgisser M, Rossi RM, Annaheim S. Prediction of core body temperature based on skin temperature, heat flux, and heart rate under different exercise and clothing conditions in the heat in young adult males. Front Physiol, 2018, 9: 1780,
CrossRef Google scholar
[10]
Ely MR, Cheuvront SN, Roberts WO, Montain SJ. Impact of weather on marathon-running performance. Med Sci Sports Exerc, 2007, 39(3): 487-93,
CrossRef Google scholar
[11]
Ely BR, Cheuvront SN, Kenefick RW, Sawka MN. Aerobic performance is degraded, despite modest hyperthermia, in hot environments. Med Sci Sports Exerc, 2010, 42(1): 135-41,
CrossRef Google scholar
[12]
Fiala D. . Dynamic simulation of human heat transfer and thermal comfort, 1998 Leicester De Montfort University Leicester
[13]
Flouris AD, Schlader ZJ. Human behavioral thermoregulation during exercise in the heat. Scand J Med Sci Sports, 2015, 25(Suppl 1): 52-64,
CrossRef Google scholar
[14]
Flouris AD, Dinas PC, Ioannou LG, Nybo L, Havenith G, Kenny GP, Kjellstrom T. Workers’ health and productivity under occupational heat strain: a systematic review and meta-analysis. Lancet Planet Health, 2018, 2(12): e521-31,
CrossRef Google scholar
[15]
Glass S, Dwyer GB A. C. o. S. Medicine. . ACSM’s metabolic calculations handbook, 2007 Philadelphia Lippincott Williams & Wilkins
[16]
Hamatani T, Uchiyama A, Higashino T. Estimating core body temperature based on human thermal model using wearable sensors. Proceedings of the 30th Annual ACM Symposium on Applied Computing. 2015;521–26. https://doi.org/10.1145/2695664.2695765.
[17]
Hardy JD, Dubois EF. The technique of measuring radiation and convection. J Nutr, 1938, 15: 461-475,
CrossRef Google scholar
[18]
El Helou N, Tafflet M, Berthelot G, Tolaini J, Marc A, Guillaume M, Hausswirth C, Toussaint JF. Impact of environmental parameters on marathon running performance. PLoS ONE, 2012, 7(5): e37407,
CrossRef Google scholar
[19]
Hunt AP, Brearley M, Hall A, Pope R. Climate change effects on the predicted heat strain and labour capacity of outdoor workers in Australia. Int J Environ Res Public Health, 2023, 20(9): 5675,
CrossRef Google scholar
[20]
Ioannou LG, Tsoutsoubi L, Samoutis G, Bogataj LK, Kenny GP, Nybo L, Kjellstrom T, Flouris AD. Time-motion analysis as a novel approach for evaluating the impact of environmental heat exposure on labor loss in agriculture workers. Temperature, 2017, 4: 1-11,
CrossRef Google scholar
[21]
Ioannou LG, Tsoutsoubi L, Mantzios K, Flouris AD. A free software to predict heat strain according to the ISO 7933:2018. Ind Health, 2019, 57(6): 711-20,
CrossRef Google scholar
[22]
Ioannou LG, Mantzios K, Tsoutsoubi L, Notley SR, Dinas PC, Brearley M, Epstein Y, Havenith G, Sawka MN, Brode P, Mekjavic IB, Kenny GP, Bernard TE, Nybo L, Flouris AD. Indicators to assess physiological heat strain—Part 1: systematic review. Temperature (Austin), 2022, 9(3): 227-62,
CrossRef Google scholar
[23]
Ioannou LG, Ciuha U, Fisher JT, Tsoutsoubi L, Tobita K, Bonell A, Cotter JD, Kenny GP, Flouris AD, Mekjavic IB. Novel technological advances to protect people who exercise or work in thermally stressful conditions: a transition to more personalized guidelines. Appl Sci, 2023, 13(15): 8561,
CrossRef Google scholar
[24]
Ioannou LG, Tsoutsoubi L, Gkiata P, Brown HA, Periard JD, Mekjavic IB, Kenny GP, Nybo L, Flouris AD. Effect of sportswear on performance and physiological heat strain during prolonged running in moderately hot conditions. Scand J Med Sci Sports, 2024, 34(1): e14520,
CrossRef Google scholar
[25]
ISO 7730. Moderate thermal environments—determination of the PMV and PPD indices and specification of the conditions for thermal comfort (International Standard). 1994.
[26]
ISO 7726. Ergonomics of the thermal environment—Instruments for measuring physical quantities (International Standard). 1998.
[27]
ISO 8996. Determination of metabolic rate (International Standard). 2004
[28]
ISO/DIS 7933. . Ergonomics of the thermal environment—analytical determination and interpretation of heat stress using the predicted heat strain model, 2018 Geneva International Organization for Standardization
[29]
ISO/DIS 7933. . Ergonomics of the thermal environment—analytical determination and interpretation of heat stress using calculation of the predicted heat strain, 2023 Geneva International Organization for Standardization
[30]
Ji L, Laouadi A, Shu C, Wang L, Lacasse MA. Evaluation and improvement of the thermoregulatory system for the two-node bioheat model. Energy Build, 2021, 249: 111235,
CrossRef Google scholar
[31]
Karvonen MJ, Kentala E, Mustala O. The effects of training on heart rate; a longitudinal study. Ann Med Exp Biol Fenn, 1957, 35(3): 307-15
[32]
Laouadi A, Gaur A, Lacasse MA, Bartko M, Armstrong M. Development of reference summer weather years for analysis of overheating risk in buildings. J Build Perform Simul, 2020, 13(3): 301-19,
CrossRef Google scholar
[33]
Lefrant JY, Muller L, de La Coussaye JE, Benbabaali M, Lebris C, Zeitoun N, Mari C, Saïssi G, Ripart J, Eledjam JJ. Temperature measurement in intensive care patients: comparison of urinary bladder, oesophageal, rectal, axillary, and inguinal methods versus pulmonary artery core method. Intensive Care Med, 2003, 29(3): 414-8,
CrossRef Google scholar
[34]
Liljegren JC, Carhart RA, Lawday P, Tschopp S, Sharp R. Modeling the wet bulb globe temperature using standard meteorological measurements. J Occup Environ Hyg, 2008, 5(10): 645-55,
CrossRef Google scholar
[35]
Liu W, Lian Z, Deng Q, Liu Y. Evaluation of calculation methods of mean skin temperature for use in thermal comfort study. Build Environ, 2011, 46(2): 478-88,
CrossRef Google scholar
[36]
MacRae BA, Annaheim S, Spengler CM, Rossi RM. Skin temperature measurement using contact thermometry: a systematic review of setup variables and their effects on measured values. Front Physiol, 2018, 9: 29,
CrossRef Google scholar
[37]
Malchaire J, Piette A, Kampmann B, Mehnert P, Gebhardt H, Havenith G, den Hartog E, Holmer I, Parsons K, Alfano G, Griefahn B. Development and validation of the predicted heat strain model. Ann Occup Hyg, 2001, 45(2): 123-35,
CrossRef Google scholar
[38]
Mantzios K, Ioannou LG, Panagiotaki Z, Ziaka S, Periard JD, Racinais S, Nybo L, Flouris AD. Effects of weather parameters on endurance running performance: discipline-specific analysis of 1258 races. Med Sci Sports Exerc, 2022, 54(1): 153-61,
CrossRef Google scholar
[39]
McCann DJ, Adams WC. Wet bulb globe temperature index and performance in competitive distance runners. Med Sci Sports Exerc, 1997, 29(7): 955-61,
CrossRef Google scholar
[40]
McCullough EA, Jones BW, Huck J. A comprehensive data base for estimating clothing insulation. Ashrae Trans, 1985, 91(2): 29-47
[41]
Meade RD, Akerman AP, Notley SR, Kirby NV, Sigal RJ, Kenny GP. Effects of daylong exposure to indoor overheating on thermal and cardiovascular strain in older adults: a randomized crossover trial. Environ Health Perspect, 2024, 132(2): 27003,
CrossRef Google scholar
[42]
Misailidi M, Mantzios K, Papakonstantinou C, Ioannou LG, Flouris AD. Environmental and psychophysical heat stress in adolescent tennis athletes. Int J Sports Physiol Perform, 2021, 16(12): 1895-900,
CrossRef Google scholar
[43]
Mora-Rodriguez R, Ortega JF, Hamouti N. In a hot–dry environment racewalking increases the risk of hyperthermia in comparison to when running at a similar velocity. Eur J Appl Physiol, 2011, 111(6): 1073-80,
CrossRef Google scholar
[44]
National Weather Service. Vapor pressure. 2018. https://www.weather.gov/media/epz/wxcalc/vaporPressure.pdf. Accessed 12 Feb 2018.
[45]
Nie J, Zhang Q, Xu R, Gong M, Mao R, Cui J, Chen W, Pei B, Ding L. Improvement and validation of the Tanabe model to simulate human thermal behaviors in hot environments at high altitudes. Int J Therm Sci, 2023, 193: 108522,
CrossRef Google scholar
[46]
Nybo L, Rasmussen P, Sawka MN. Performance in the heat-physiological factors of importance for hyperthermia-induced fatigue. Compr Physiol, 2014, 4(2): 657-89,
CrossRef Google scholar
[47]
Periard JD, Racinais S, Sawka MN. Adaptations and mechanisms of human heat acclimation: applications for competitive athletes and sports. Scand J Med Sci Sports, 2015, 25(Suppl 1): 20-38,
CrossRef Google scholar
[48]
Piil JF, Lundbye-Jensen J, Christiansen L, Ioannou L, Tsoutsoubi L, Dallas CN, Mantzios K, Flouris AD, Nybo L. High prevalence of hypohydration in occupations with heat stress-perspectives for performance in combined cognitive and motor tasks. PLoS ONE, 2018, 13(10): e0205321,
CrossRef Google scholar
[49]
Potter AW, Hunt AP, Cadarette BS, Fogarty A, Srinivasan S, Santee WR, Blanchard LA, Looney DP. Heat Strain Decision Aid (HSDA) accurately predicts individual-based core body temperature rise while wearing chemical protective clothing. Comput Biol Med, 2019, 107: 131-136,
CrossRef Google scholar
[50]
Potter AW, Yermakova II, Hunt AP, Hancock JW, Oliveira AVM, Looney DP, Montgomery LD. Comparison of two mathematical models for predicted human thermal responses to hot and humid environments. J Therm Biol, 2021, 97: 102902,
CrossRef Google scholar
[51]
Poulianiti K, Havenith G, Flouris A. Metabolic energy cost of workers in agriculture, construction, manufacturing, tourism, and transportation industries. Ind Health, 2018, 57: 283,
CrossRef Google scholar
[52]
Racinais S, Moussay S, Nichols D, Travers G, Belfekih T, Schumacher YO, Periard JD. Core temperature up to 41.5 masculineC during the UCI Road Cycling World Championships in the heat. Br J Sports Med, 2019, 53(7): 426-9,
CrossRef Google scholar
[53]
Ramanathan NL. A new weighting system for mean surface temperature of the human body. J Appl Physiol, 1964, 19(3): 531-3,
CrossRef Google scholar
[54]
Roberts WO. Determining a “do not start” temperature for a marathon on the basis of adverse outcomes. Med Sci Sports Exerc, 2010, 42(2): 226-32,
CrossRef Google scholar
[55]
Sharma M, Suri NM, Kant S. Analysing metabolic heat among metal casting workers using different body surface area estimates: a comparative study. Singapore: Springer; 2022.
[56]
Smith KR, Woodward A, Lemke B, Otto M, Chang CJ, Mance AA, Balmes J, Kjellstrom T. The last Summer Olympics? Climate change, health, and work outdoors. Lancet, 2016, 388(10045): 642-44,
CrossRef Google scholar
[57]
Thorsson S, Rayner D, Palm G, Lindberg F, Carlstrom E, Borjesson M, Nilson F, Khorram-Manesh A, Holmer B. Is Physiological equivalent temperature (PET) a superior screening tool for heat stress risk than Wet-Bulb Globe Temperature (WBGT) index? Eight years of data from the Gothenburg half marathon. Br J Sports Med, 2021, 55(15): 825-30,
CrossRef Google scholar
[58]
Vihma T. Effects of weather on the performance of marathon runners. Int J Biometeorol, 2010, 54(3): 297-306,
CrossRef Google scholar
[59]
Waldock KAM, Lee BJ, Powell S, Wardle SL, Blacker SD, Myers SD, Maroni TD, Walker FS, Looney DP, Greeves JP, Potter AW. Field validation of The Heat Strain Decision Aid during military load carriage. Comput Biol Med, 2021, 134: 104506,
CrossRef Google scholar
[60]
Willmott CJ. On the validation of models. Phys Geogr, 1981, 2(2): 184-94,
CrossRef Google scholar
[61]
Willmott CJ, Robeson SM, Matsuura K. A refined index of model performance. Int J Climatol, 2012, 32(13): 2088-94,
CrossRef Google scholar
[62]
World Health Organization. WHO guidelines on physical activity and sedentary behaviour; at a galance. Geneva: World Health Organization; 2020.

Accesses

Citations

Detail

Sections
Recommended

/