The Detection of Heat Stress by Assessing Individual Body Responses to Heat (Heat Strain) in Young and Healthy Non-athlete Participants (HEATSTAR)

HEAT Stress Detection From Personally STandARdized Heat Strain Measurements - The HEATSTAR Pilot Trial

• This study investigates and compares the within and in-between variances of the body responses to different heat stressors in a controlled lab-setting. The participants will be exposed to different heat sources while a variety of physiological heat strain reactions such as heartrate, sweat rate, and core body temperature are recorded using on- and in-body devices. For the participant monitoring during the study, medical grade devices such as a certified ECG and a swallowable sensor-pill to continuously monitor the core body temperature will be applied. A one-for-all wearable device is additionally applied for physiological validation. Further, sweat will be collected to assess (i) the local sweat rate and (ii) the appearance of different heat stress associated molecular markers in this non-invasively collectable biofluid. As a secondary aim, a model will be developed that will enable to predict the different heat stress sources out of the heat strain measurements.

Study Overview

• Status: Completed
• Conditions: Heat Stress
• Intervention / Treatment: Other: Elevated ambient heat; Other: Elevated relative humidity; Other: Exertion

• Study Type: Observational
• Enrollment (Actual): 23

Contacts and Locations

Study Locations

• Switzerland
  • Andere (Nicht USA-Länder)
    • Zurich, Andere (Nicht USA-Länder), Switzerland, 8093
      • ETH Zurich

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years to 40 years (ADULT)
• Accepts Healthy Volunteers: Yes
• Genders Eligible for Study: All

• Sampling Method: Non-Probability Sample

Study Population

Participants will be recruited through Swiss Universities and Swiss Universities of Applied Science. The institutions host a broad range of students that are likely to match the inclusion criteria.

Description

Inclusion Criteria:

• Healthy participant, able to give consent
• Age 18-40 years
• Non-athlete (<4h sport/week)
• BMI<30 (non-obese)
• German speaking, or fluent in German

Exclusion Criteria:

• Pregnancy (urine pregnancy test), and breastfeeding
• Regular medication intake (excluding birth control pill)
• Intake of drugs and/or daily alcohol consumption
• Fever or symptoms of an acute infection (cough, shortness of breath, sore throat, taste loss)
• Active smoking or history of smoking <9 months ago
• Mobility impairment
• Traveled (<1 month ago) to a warm/hot temperature zone and stayed for >6 days
• Any chronic conditions such as: high blood pressure, diabetes mellitus, immuno-deficiencies, sweat disorders such as anhidrosis
• Color blindness (STROOP test)
• Weight <40 kg (e-Celsius pill)
• Diverticulum or obstructions of the gastrointestinal tract (including motility disorders, swallowing disorders) as well as major abdominal surgery (e-Celsius pill)
• Need of exposure to strong electromagnetic fields during study participation, above all MRI examinations (e-Celsius pill)

Study Plan

How is the study designed?

Design Details

• Observational Models: Other
• Time Perspectives: Cross-Sectional

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort

Intervention / Treatment

Healthy participants; Age of the participants is between 18-40 years, females and males equally distributed

Other: Elevated ambient heat; Temporary exposure to increased ambient temperature +10°C (the effect of the intervention is fully and spontaneously reversible); Other: Elevated relative humidity; Temporary exposure to increased ambient relative humidity +40% (max. 90%) (the effect of the intervention is fully and spontaneously reversible); Other: Exertion; Temporary exertion on an ergometer (1W/kg body weight) (the effect of the intervention is fully and spontaneously reversible)

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
The within and between subject heat strain marker variability in relation to specific heat stress sources (ambient heat, ambient humidity, exertion, and clothing)	The primary endpoint is the within- and between- subject heat strain marker variability of HR, CBT, WSR, and LSR in relation to various heat stress sources (increased ambient temperature, increased relative humidity, and exertion, all without and with additional clothing.	Max. 7 days

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Accuracy to detect the specific heat stress source (such as ambient heat, relative humidity) from different on- and in-body measurements	The models for the primary endpoints will be extended to explore the relationships between heat strain parameters, heat stress sources, as well as personal characteristics. Additionally, prediction of heat stress source will be explored.	Max. 7 days
Assessment of short-term heart rate variability in context to each heat stressor.	Short-term HRV with a repeating time frame of 5min. Root mean square of successive RR interval (RMSSD; in [ms]) and the Standard-deviation of RR intervals (SDRR; in [ms]) will be computed with respect to each heat stress source.	Max. 7 days
Temperature [°C] and relative humidity [%] of the microenvironment as an additional source of information for patterns to detect heat stressors	Features of temperature [°C] and relative humidity [%] of the microenvironment as additional model predictors.	Max. 7 days

Other Outcome Measures

Outcome Measure	Measure Description	Time Frame
The relation between cognitive assessment and skin temperature	Correlation between subjective heat comfort (Visual Analog Scale, where +1 is comfortable and +4 is very uncomfortable) and baseline differential stress inventory (causes of stress, symptoms of stress, coping, stress stabilization) in relation to skin temperature [°C]	Max. 7 days
The relation between STROOP assessment and different heat stressors	Correlation between changes in the STROOP assessment outcome (number of errors and time of decision [ms], between beginning and end of heat stress exposure) in context to the various heat stress sources, skin temperature, and thermal comfort.	Max. 7 days
Novel Sweat Biomarkers for heat stress detection	Descriptive statistics for novel non-invasive biomarkers from sweat analysis with respect to heat stress source, including between- and within-subject variability	Max. 7 days
Recording heat strain parameters with an all-for-one device	The 'reliability' (missing data per minute ([%]) and the 'accuracy' (HR [bpm] with 95% confidence intervals), CBT (in [°C] with 95% confidence intervals), and local sweat rate measurements (in [g/h] with 95% confidence intervals) of the wearable device in recording vital parameters.	Max. 7 days

Collaborators and Investigators

• Sponsor: ETH Zurich
• Collaborators: Swiss Federal Office of Sports (BASPO); Functional Genomics Center, ETH Zurich/University of Zurich; Center for Chronobiology, Psychiatric University Clinics, Basel; epyMetrics; Swiss Federal Railways; Innosuisse - Swiss Innovation Agency

Publications and helpful links

General Publications

• Watts N, Amann M, Ayeb-Karlsson S, Belesova K, Bouley T, Boykoff M, Byass P, Cai W, Campbell-Lendrum D, Chambers J, Cox PM, Daly M, Dasandi N, Davies M, Depledge M, Depoux A, Dominguez-Salas P, Drummond P, Ekins P, Flahault A, Frumkin H, Georgeson L, Ghanei M, Grace D, Graham H, Grojsman R, Haines A, Hamilton I, Hartinger S, Johnson A, Kelman I, Kiesewetter G, Kniveton D, Liang L, Lott M, Lowe R, Mace G, Odhiambo Sewe M, Maslin M, Mikhaylov S, Milner J, Latifi AM, Moradi-Lakeh M, Morrissey K, Murray K, Neville T, Nilsson M, Oreszczyn T, Owfi F, Pencheon D, Pye S, Rabbaniha M, Robinson E, Rocklov J, Schutte S, Shumake-Guillemot J, Steinbach R, Tabatabaei M, Wheeler N, Wilkinson P, Gong P, Montgomery H, Costello A. The Lancet Countdown on health and climate change: from 25 years of inaction to a global transformation for public health. Lancet. 2018 Feb 10;391(10120):581-630. doi: 10.1016/S0140-6736(17)32464-9. Epub 2017 Oct 30. No abstract available. Erratum In: Lancet. 2017 Nov 23;: Lancet. 2020 Jun 6;395(10239):1762.
• Varghese BM, Hansen A, Bi P, Pisaniello D. Are workers at risk of occupational injuries due to heat exposure? A comprehensive literature review. Safety Science. 2018;110:380-92.
• Davey SL, Downie V, Griggs K, Havenith G. The physiological strain index does not reliably identify individuals at risk of reaching a thermal tolerance limit. Eur J Appl Physiol. 2021 Jun;121(6):1701-1713. doi: 10.1007/s00421-021-04642-3. Epub 2021 Mar 7.
• Nunes MJ, Cordas CM, Moura JJG, Noronha JP, Branco LC. Screening of Potential Stress Biomarkers in Sweat Associated with Sports Training. Sports Med Open. 2021 Jan 22;7(1):8. doi: 10.1186/s40798-020-00294-3.
• Flores M, Glusman G, Brogaard K, Price ND, Hood L. P4 medicine: how systems medicine will transform the healthcare sector and society. Per Med. 2013;10(6):565-576. doi: 10.2217/pme.13.57.

Study record dates

Study Major Dates

• Study Start (ACTUAL): November 2, 2022
• Primary Completion (ACTUAL): January 31, 2023
• Study Completion (ACTUAL): February 10, 2023

Study Registration Dates

• First Submitted: November 11, 2022
• First Submitted That Met QC Criteria: November 11, 2022
• First Posted (ACTUAL): November 18, 2022

Study Record Updates

• Last Update Posted (ACTUAL): February 13, 2023
• Last Update Submitted That Met QC Criteria: February 10, 2023
• Last Verified: February 1, 2023

More Information

Terms related to this study

• Keywords: Wearable; Heat Strain; Sweat Analysis
• Additional Relevant MeSH Terms: Wounds and Injuries; Heat Stress Disorders
• Other Study ID Numbers: EKNZ ID: 2022 - 01325

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No