Individual Heat Stress Response ISBN: 90-9010979-X Cover design: George Havenith / Walter van Dijk: false colour infra-red image of TNO colleagues. Printer: Ponsen en Looijen BV copyright: The copyright for the published papers belongs to Springer Verlag, Heidelberg (reprinted with permission). All other copyright belongs to the author. Nothing from this thesis is to be used or reproduced without prior permission of respective copyright holders. Individual Heat Stress Response Een wetenschappelijke proeve op het gebied van de Medische Wetenschappen Proefschrift ter verkrijging van de graad van doctor aan de Katholieke Universiteit Nijmegen, volgens besluit van het College van Decanen in het openbaar te verdedigen op dinsdag 4 November 1997 des namiddags om 3:30 uur precies door George Havenith geboren op 25 september 1956 te Heerlen Promotor: prof. dr. R.A. Binkhorst Co-promotor: dr. W.A. Lötens (TNO-TM) - Manuscriptcommissie: prof. dr. A. van Oosterom, voorzitter dr. M.A. van 't Hof prof. dr. H. Kuipers (UM) The research presented in this thesis was performed at the TNO Human Factors Research Institute, Soesterberg, The Netherlands and at Noll, physiological Research Center, University Park, PA, USA. The research was financed by the Netherlands Council for Defence Research. CONTENTS List of abbreviations ii 1 Introduction 1 1.1 General introduction 1.2 Background 1.3 Methodology 1.4 Outline 2 Age predicts cardiovascular, but not thermoregulatory, 23 responses to humid heat stress 3 The relative influence of body characteristics on humid heat 45 stress response 4 The influence of individual characteristics on physiological 67 response during relative load exercise in different climates 5 The relevance of individual characteristics for human heat 81 stress response is dependent on work intensity and climate type 6 Thermal modelling of individual characteristics 107 6.1 Introduction 6.2 The necessity of individualization 6.3 The model 6.4 Validation 6.5 Conclusion 7 Example simulations 143 8 Summary and suggestions for future research 155 9 Samenvatting en aanbevelingen voor verder onderzoek 163 Program listing, Appendix 1 171 Bibliography, Appendix 2 179 Acknowledgements 185 Curriculum Vitae 189 Abbreviations o = relative size of skin compartment ABS = absolute workload (60W) Acclim = acclimation ACSM = American college of sports medicine ACTIV = daily activity score AD = body surface area A /mass = body surface area to mass ratio D ASHRAE = American Society of Heating Refrigerating and Air Conditioning Engineers BF = blood flow Cp = specific heat of body tissue CEN = Centre Européen de Normalisation CO = cool climate (21 °C, 50% r.h.) Dbody = density of body tissue diast = diastolic blood pressure DRY = dry heat loss (radiative+convective+conductive) ET = Effective Temperature EVAP = evaporative heat loss %fat = body fat percentage FBF = forearm blood flow FVC = forearm vascular conductance GXT = graded exercise test Heap = heat capacity HD = hot dry climate (45°C, 20% r.h.) HR = heart rate HST = heat stress test l = clothing insulation cl ISO = International Standardization Organization LBM = lean body mass MAP = mean arterial pressure mass = body mass MSBF = maximal skin blood flow MS R = maximal sweat rate n = number of datapoints (subjects) P = ambient water vapour pressure a p = statistical significance level r = correlation coefficient r2 = explained variance rad = added radiation (above normal at T ) a RC = regression coefficient R = clothing vapour resistance e Ref = reference temperature (setpoint/threshold) REL = workload relative to individual Vo 2 max RESP = respiratory heat exchange r.h. = relative humidity SD = standard deviation Ill SE = Standard error SF = sum of 7 skinfolds shiver = shivering metabolic rate sk = skin SKBF = skin blood flow STORE = body heat storage sw = sweating syst = systolic blood pressure T = ambient temperature a = mean body temperature 'body = body core temperature = oesophageal temperature = rectal temperature = mean skin temperature 'sk = wind speed V V0 = minute oxygen consumption 2 V0 = maximal oxygen uptake 2max Vo ff = maximal oxygen uptake per kg fat free body mass 2max %V0 = work load as % of maximal oxygen uptake 2max WBGT = wet bulb globe temperature WBT = Wet Bulb Temperature WH = warm humid climate (35°C, 80% r.h.) Introduction Introduction Chapter 1 INTRODUCTION 1.1 General introduction The aim of this thesis is to contribute to the improvement of the quality of heat strain prediction in healthy humans. Heat strain prediction is possible using thermal indices or models. In this prediction several parameters are of importance: the type of index or model, the climate, the task which has to be performed, the clothing worn, and the characteristics of the person involved. These parameters will be described below. The characteristics of the individual have hardly been incorporated in heat stress modelling. The emphasis of this thesis will therefore be the role of individual charac- teristics in heat stress response. 1.1.1 Thermal indices and models Empirical indices Heat strain determination and prediction is a subject which importance was recog- nized in industry early this century, when people began to pay more attention to work conditions. This interest, also coming from the indoor-climate control industry, led to first attempts to define heat stress by a single index value, like the Wet Bulb Temper- ature (WBT, Haldane, 1905) or the Effective Temperature (ET, Houghton and Ya- glou, 1923). Research on this subject was boosted when military interest in the subject increased. In the United States, with the involvement in World War II, recruits from all parts of the US were trained in the Southern States, with their warm, humid summers. The high incidence of heat exhaustion and heat stroke during military training pointed out the need for instruments or methods to determine the risks involved with exercise in such stressful climates. Adolph (1947), published a book reviewing a number of studies performed with military personnel during and after the war, dealing with risks of heat exposure and ways to reduce these risks. Schickele (1947) published data on the relation of the occurrence of heat stroke with climatic factors. Later these findings were incorporated in the design of a measuring device which was used to determine a heat stress index, the Wet Bulb Globe Temperature (WBGT1, Yaglou and Minard; 1957). This device allowed management of training sessions and work duration in relation to the climatic stress. Individual variations in 1Wet Bulb Globe Temperature: Climate Index, which Is based on measurement of natural wet bulb temperature, air temperature and globe temperature, indicating the level of heat stress in a single value. Climates with equal WBGT are supposed to induce equal stress on a subject. Chapter 1 response were not accounted for by these indices. Only in the interpretation, different tables were e.g. used for acclimated and non-acclimated subjects Analytical indices The applicability of all these indices however, as their relation with heat strain was determined empirically and only based on climatic parameters, was limited to situations which were studied before. Especially changes in metabolic rate or in clothing, produced discrepancies between observed and predicted strain. This led to the development of analytical indices, dealing with actual heat and mass transfer between human skin and environment. Two examples of such indices, which really are based on the human heat balance equation2, are the Heat Stress Index (Belding and Hatch, 1955) and the Required Sweat Rate Index (ISO 7933, 1989). These improved strain prediction, and widened the range of applicability of indices. Some basic individual characteristics related to the anthropometry and acclimation were introduced in some of these models, but their impact was hardly validated. Physiological models Around 1970, when substantial data on thermoregulatory control functions became available in the literature, and with the increasing availability of computers, the development of physiological simulation models started. These models combined physics of internal and external heat flow with internal body temperature regulation. The most well known physiological models of human thermorégulation were initiated by research for space travel. Stolwijk (1971) published a 25 compartment thermoreg- ulatory model, incorporating control functions for blood flow, sweating and metabo- lism for use by NASA. He was followed by many other authors who published relatively simple (Gagge et al., 1971, 1986) to more complex (Wissler, 1964, 1982; Werner, 1989; Werner and Webb, 1993) physiological models. These models all allowed the introduction of anthropométrie data, and some acclimation, but these parameters were hardly validated for work in the heat. Clothing Once the physiological part of these models was developed, researchers started to improve the description of the interface between man and environment in these models: the air layers at the skin, at and within the clothing, and the clothing itself. Basic data for this purpose were gathered in the 1940-1960 period already (for a historical review see Gagge, 1983). Originally, people worked with static data on 2The heat balance equation defines the balance of the rates of heat production and heat losses. Rates of metabolic heat production at thermal equilibrium equal the sum of the rates of external work, respiratory-, convective-, radiative- and evaporative heat gains or losses. If not, this implies that heat is stored in the body. Positive storage leads to body temperature increase, negative storage to a decrease.