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Heat Strain and Hydration of Japanese Construction Workers during Work in Summer

Heat Strain and Hydration of Japanese Construction Workers during Work in Summer Abstract Objectives The aim was to ascertain hydration and heat strain of construction workers in Japan during the summer who are at the highest risk of heat-related disorders. Methods The subjects were 23 construction workers, whose average age was 41, average weight was 69 kg, and average height was 170 cm. We measured thermal working conditions with a wet bulb globe temperature (WBGT) measurement instrument affixed to the helmet of each worker, at fixed points outdoors in the sun and indoors. Heat strain was evaluated for water intake, urine specific gravity (Usg), urine temperature (UT), heart rate (HR), and body weight during work. Results The average WBGT measured on the worker helmets over 3 consecutive days was 28.0 ± 0.7, 27.6 ± 0.8, and 27.6 ± 1.1°C. The average water intake was 2.6 l during a work shift. The average Usg, UT, and % HR reserve were the highest in the first half of afternoon work. Seventy-eight percent of the subjects exceeded at least one of the ACGIH TLV physiological guidelines for heat strain in terms of HR and weight loss or a clinically dehydrated level of Usg. Conclusions Heat strain was the highest in the first half of afternoon work. The number of dehydrated workers increased during this shift because of insufficient water intake. Adequate hydration is required to decrease the risk of heat-related disorders among construction workers in the summer. construction, deep body temperature, dehydration, heat stress, urine specific gravity Introduction Higher heat stress in the work environment associated with climate change has increased the risk of heat-related disorders for workers in construction, agriculture, forestry, and other outdoor occupations (NIOSH, 2016). Epidemiological data (Adelakun et al., 1999; Bonauto et al., 2007; Lin and Chan, 2009; Jackson and Rosenberg, 2010) have indicated that the construction industry had the highest percentage of work-related heat disorders. Japan’s Ministry of Health, Labour and Welfare (2016) has announced that construction work accounted for 40.0% of casualties from heat stroke between 2011 and 2015, the largest industry of all Japanese industries. The construction industry accounts for 7.8% of all employment in Japan (Ministry of Internal Affairs and Communication, 2016). Construction is the highest-risk industry in terms of work-related heat disorders. Ambient temperature (Ta), humidity, radiation, air velocity, metabolic rate, and clothing are used to calculate the heat exchange between the human body and the environment in the thermal model of ISO7933 (ISO, 2004b) and ISO7730 (ISO, 2005). For construction workers, high Ta, direct sunlight, radiation from the heated ground or building, weakened air velocity, strenuous workload, and protective clothing with high thermal insulation and vapor resistance contribute to increased heat strain in workers. In summer, the daily maximum temperature of Ta in Japan is often over 35°C, according to the Japan Meteorological Agency (2017). On a construction site, Ta would be higher than the temperature indicated by the weather stove, which is measured at more than 1.5 m above lawn where natural wind is not disturbed (Japan Meteorological Agency, 1998). When Ta is higher than skin temperature, convective heat is transferred to the body from the environment. Sweat evaporation is the main way for heat to dissipate from the body to the environment. To maintain body temperature, construction workers sweat heavily, leading to dehydration and hyponatremia. Furthermore, the protective clothing worn by construction workers prevents the sweat on the skin from evaporating and promotes even heavier sweating and dehydration. This depletion of water and electrolytes decreases the blood volume, extracellular fluid volume, and amount of sweating (Sawka et al., 1989), thus making heat dissipation even more difficult. Dehydration exceeding 2% body weight has been reported to decrease aerobic (Cheuvront et al., 2010) and cognitive performance (Hancock and Vasmatzidis, 2003). Thus, dehydration increases not only the risk of heat stroke, but also the likelihood of accidents. Dehydration was found in 17% of all cases of heat stroke reported in the US Army over a 22-year period (Carter et al., 2005). Previous studies (Bates and Schneider, 2008; Bates et al., 2010; Montazer et al., 2013) of hydration in construction workers have been inconsistent. UAE construction workers (Bates and Schneider, 2008; Bates et al., 2010) were reported to be well hydrated during work, but construction workers (Montazer et al., 2013) in Iran were inadequately hydrated from before to the end of work. Thus, it is important to ascertain the hydration of construction workers. In terms of workload, some studies reported an average heart rate (HR) during work as 90–100 beats per minute (bpm) (Bates and Schneider, 2008; Miller et al., 2011), while others reported 110 bpm (Chang et al., 2009; Wong et al., 2014). Construction workers engage in strenuous physical activity even in very hot environments. A field study in a tropical region found that self-pacing is a protective response to working under such conditions (Miller et al., 2011). However, construction workers in Japan are liable to be required to finish their tasks on time despite the heat. Time constraints could increase the risk of heat strain among construction workers. According to the Monthly Labour Survey by the Ministry of Health, Labour and Welfare Japan (2017), in 2016 the average construction worker clocked 171.3 h of work a month, which was the longest in all industries. Most previous studies were conducted in tropical or subtropical regions (Yoopat et al., 2002; Bates and Schneider, 2008; Chang et al., 2009; Bates et al., 2010; Miller et al., 2011; Montazer et al., 2013; Wong et al., 2014), and few were done in temperate regions. There is a great need for comprehensive field studies of construction workers in temperate regions during the summer. The aim of this field study was to ascertain hydration and heat strain of construction workers in summer in a temperate zone. These data would inform the planning of effective steps to decrease the incidence of heat stroke among construction workers. Materials and methods This field study was conducted at a worksite of Aichi prefecture in Japan. Aichi prefecture in central Japan is one of the hottest regions in the country. The average daily maximum temperature and relative humidity (RH) in August from 1990 to 2005 were registered at 32.9°C and 70%, respectively. Aichi was selected for this study because it is one of the largest prefectures in Japan with a large number of ambulance transports due to heat disorders (Ministry of Internal Affairs and Communications, 2008). The daily maximum temperature of the nearest meteorological observatory had been over 30°C for 2 weeks before the study. The subjects were assumed to be acclimatized to heat. The construction workers on the site were renovating a building to increase earthquake resistance. Observations were made for 3 consecutive days in August 2009. Subjects Twenty-three male construction workers (age: 41 ± 15 years; weight: 68 ± 10 kg; height: 170 ± 6 cm; body mass index: 24 ± 3) participated in the study. The breakdown of the subjects was as follows: seven were plumbers, three were demolition workers, two were cleaning workers, steel-frame workers, heat insulation workers and chipping workers, and five were others. They were engaged in various types of work: worksite supervision, cutting metal rods with an electric saw while on a stepladder, peeling off tile and carrying it out, installing a curing seat, wrapping pipes with insulation while on a stepladder, etc. Some subjects worked indoors and others outdoors or both. Moreover, most subjects worked at different places between A.M. and P.M. Work started at around 9:00 A.M. and finished around 4:30 P.M. during the study days. There was a scheduled 30-min break in the morning (10:00 A.M.–10:30 A.M.), an hour for lunch (Noon–1:00 P.M.) and a second 30-min break in the afternoon (3:00 P.M.–3:30 P.M.). The purpose and study procedures were explained to the participants before they gave their written informed consent. The Review Board of National Institute of Occupational Safety and Health, Japan approved this study. This study was conducted according to the Declaration of Helsinki. A medical doctor and a health care worker joined this study. Environmental conditions Environmental conditions were measured inside the building and outside the building in the sun using a wet bulb globe temperature (WBGT) monitor (3M QUESTemp°36) at a resolution of 0.1°C, respectively. For the indoor WBGT monitor, there was no direct sunlight to the monitor in a room on the first floor of the construction building with the windows open. For the outdoor WBGT monitor in the sun, there was direct sunlight to the WBGT monitor on the ground of the construction site. Buildings were not located near the outdoor monitor. Both WBGT monitors were placed at fixed points. The monitors had been calibrated by the manufacturer before use. Digital data for natural wet bulb temperature, dry bulb temperature (Ta), wind speed, and globe temperature (Tg) were recorded every minute. In addition, portable rod-like WBGT monitors (WBGT-213B, Kyoto Electronics Manufacturing) were used to record the digital data of Ta, Tg, and RH around each worker every 2 min. The monitor, which was 24 cm in length and 110 g in weight, was attached to the side of each worker’s helmet above the ear position with adhesive tape. The portable monitors were used just after being purchased from the manufacturer. We checked that the fixed-position WBGT monitors and portable WBGT monitors showed the same values before the study. The sizes of the globe sensor of both WBGT instruments were smaller than a standard size of 15 cm in diameter for convenience in measurement. The calibration algorithm to fit the size of the globe sensor to a standard size was a black box. Physiological conditions The physiological conditions of workers were monitored by HR, weight loss, and urine specific gravity. R-R interval (the inter-beat intervals using R-wave peak) was measured with a data logger (ActiHR, CamNTech Ltd) from the start to the end of the shift. Average HR for each minute was calculated from R-R interval. Heart rate reserve (%HRR) was calculated by using the following equation: %HRR=(HR–resting HR)/(maximal HR – resting HR)×100 (1) where maximal HR was estimated by the following equation (Tanaka et al., 2001): Maximal HR=208–0.7×age (2) Resting HR was estimated by the stable minimal HR during the shift. Most of the resting HR were registered at lunch, morning break, before work, or after work. The average resting HR was 75 bpm, which was close to the experimental average resting HR of 71–73 bpm (Isaka et al., 1990). Subject weight was measured six times [at the start of the work shift (SW), morning break (MB), before lunch (BL), after lunch (AL), afternoon break (AB), and at end of the work shift (EW)] with only their shorts with an accuracy of 20 g (FG-150 KBM, AND). At measurement, subjects wiped their sweat off their skin. Sublingual temperature was measured by an electronic thermometer with a predictive function of equilibrium temperature (ET-C502, Terumo) within about 90 s with a precision of 0.05°C at a resolution of 0.01°C. When the prediction was finished, a thermometer bell rings. The subjects were asked to put the thermometer under their tongue until the bell rings. The thermometers were assigned the personal identification numbers and distributed to the corresponding subjects only at measurement to maintain sanitary conditions. Urine was sampled six times at SW, MB, BL, AL, AB, and EW to measure urinary volume, urine specific gravity (Usg), urine osmolality (Uosm), urine sodium (Uso), and urine creatinine. Urine temperature (UT) was measured during urination by a thermistor (LT-ST08-00, Gram) as a reference of core temperature. The temperature sensor was set at the bottom of the cup for collecting urine. The maximum temperature of the sensor was recorded as UT. Usg was measured with a refractometer (Pal-09S, Atago). Urine samples were dispensed to a 5 ml cryo-tube that was frozen via dry ice and transferred to a measurement firm (SRL, Inc., Tokyo) that measured urine content. Hydration Fluid consumption was measured by subtracting the remaining weight of a water bottle from the weight of a water bottle before the measurement at MB, BL, AL, AB, and EW by an electric weight scale with an accuracy of 1 g. In this study, sweating was estimated by the following equation (3), Sweating=Body weight loss+water intake−urine volume (3) Water loss through respiration was included in sweating. Results Ten, nine, and four male subjects participated in this study on the first, second, and third days of the field study, respectively. No subject participated on more than one day. The average time length for first half (w1), break (b1) and second half (w2) in the morning, lunch (b2), and the first half (w3), break (b3) and second half (w4) in the afternoon were 83, 21, 90, 53, 115, 25, and 84 min, respectively. The mean outdoor WBGT of the first day from 10:40 to 16:30 was 32.2°C. The mean outdoor WBGT of the second and third day from 10:40 to 16:30 were 30.0 and 30.4°C, respectively (Fig. 1). Mean WBGT inside the building was 27.4°C (first day), 26.5°C (second day), and 26.6°C (third day). Air conditioners were not installed inside the building. Stationary measurement of WBGT, Ta, Tg, Tnw, and RH for indoor and outdoor in the sun from the first to the third day are shown together in Fig. 1. Average WBGT recorded by portable WBGT instruments attached to the helmet of each subject during work was 28.0 ± 0.7°C (first day), 27.6 ± 0.8°C (second day), and 27.6 ± 1.1°C (third day). Since the average WBGTs on the helmets were not significantly different over the 3 days of field study, we clustered the data for the analysis. The average personal monitoring WBGTs, Ta, Tg, and RH are shown in Fig. 2A–D, respectively. The average personal WBGT values were 27.4, 28.0, 28.5, and 27.3°C for w1, w2, w3, and w4, respectively. Figure 1. View largeDownload slide Time course of fixed WBGT monitors for indoor (In) and outdoor in the sun (Out). RH: relative humidity; Tw: wet bulb temperature; Ta: ambient temperature; Tg: globe temperature. The data of WBGT monitors of outdoor in the sun were missing in the first half of the morning work in the first day. Figure 1. View largeDownload slide Time course of fixed WBGT monitors for indoor (In) and outdoor in the sun (Out). RH: relative humidity; Tw: wet bulb temperature; Ta: ambient temperature; Tg: globe temperature. The data of WBGT monitors of outdoor in the sun were missing in the first half of the morning work in the first day. Figure 2. View largeDownload slide Thermal working environment of construction workers. (A) WBGT, (B) dry bulb temperature, (C) globe temperature, (D) RH. Pers: average value measured by WBGT monitor fixed on workers’ helmet; Out: average value measured by WBGT monitor set at standpoint in outdoor in the sun; In: average value measured by WBGT monitor set at standpoint in outdoor in the sun; w1: first half of morning work; w2: second half of morning work; w3: first half of afternoon work; w4: second half of the afternoon work. The error bars represent SD. From Fig. 2A–D, w1 showed the average of second and third day. W2, w3, and w4 showed the average of first to third day. Figure 2. View largeDownload slide Thermal working environment of construction workers. (A) WBGT, (B) dry bulb temperature, (C) globe temperature, (D) RH. Pers: average value measured by WBGT monitor fixed on workers’ helmet; Out: average value measured by WBGT monitor set at standpoint in outdoor in the sun; In: average value measured by WBGT monitor set at standpoint in outdoor in the sun; w1: first half of morning work; w2: second half of morning work; w3: first half of afternoon work; w4: second half of the afternoon work. The error bars represent SD. From Fig. 2A–D, w1 showed the average of second and third day. W2, w3, and w4 showed the average of first to third day. Average UT increased from SW to AB and average UT at AB was significantly higher than the others (Fig. 3A, Table 1). The UT of more than half of the workers was more than 37.5°C at AB. The average %HRR of w3 was significantly higher than those at other times (Fig. 3B). The average body weight relative to initial body weight decreased during morning work, increased at lunch, and decreased during afternoon work (Fig. 3C). Average body weight decreased by 1.3% at EW. Body weight decreased more than 2.0% for five workers at EW. In Fig. 3D, sweat rate, water intake, and urine rate are shown per 1 h per 70 kg body weight. For 16 subjects, whose water intake data were completely registered at six measuring times, water intake was 0.84 l h−1 70 kg−1 at lunch (Fig. 3D), and total water intake during shift including lunch was 2.6 l. During lunch, the sweat rate was not shown due to unavailability of lunch weight. Sweat rate in the afternoon was a little larger than in the morning but was not significant. Two subjects defecated between the morning break and lunch. There were no other subjects who defecated during work hours. Thus, the error in sweating rate resulting from defecation that was calculated by equation (3) was negligible. During the work shift, the ratios of fluid intake to water loss (sweat loss + urine) were 56% at w1, 52% at w2, 37% at w3, 74% at w4 (Fig. 3D), and 52% at work shift except for lunch. Table 1. Urine biochemical measurements of the subjects. Time of measurement SW MB BL AL AB EW Urine temperature (°C) Average 36.74 36.99 37.26 36.97 37.47 37.25 SD 0.30 0.40 0.33 0.33 0.28 0.27 Urine osmolality (mOsm kg−1 H2O) Average 723 689 748 779 765 787 SD 2709 243 273 289 308 291 Urine specific gravity (g ml−1) Average 1.019 1.019 1.02 1.022 1.024 1.024 SD 0.008 0.009 0.009 0.009 0.011 0.009 Urine Na corrected by Cr (mEQ mg−1) Average 0.180 0.121 0.114 0.119 0.074 0.091 SD 0.084 0.073 0.075 0.063 0.048 0.05 Time of measurement SW MB BL AL AB EW Urine temperature (°C) Average 36.74 36.99 37.26 36.97 37.47 37.25 SD 0.30 0.40 0.33 0.33 0.28 0.27 Urine osmolality (mOsm kg−1 H2O) Average 723 689 748 779 765 787 SD 2709 243 273 289 308 291 Urine specific gravity (g ml−1) Average 1.019 1.019 1.02 1.022 1.024 1.024 SD 0.008 0.009 0.009 0.009 0.011 0.009 Urine Na corrected by Cr (mEQ mg−1) Average 0.180 0.121 0.114 0.119 0.074 0.091 SD 0.084 0.073 0.075 0.063 0.048 0.05 The values which are significantly larger or smaller than the other value by Student’s t-test (P < 0.05) are marked in bold. View Large Table 1. Urine biochemical measurements of the subjects. Time of measurement SW MB BL AL AB EW Urine temperature (°C) Average 36.74 36.99 37.26 36.97 37.47 37.25 SD 0.30 0.40 0.33 0.33 0.28 0.27 Urine osmolality (mOsm kg−1 H2O) Average 723 689 748 779 765 787 SD 2709 243 273 289 308 291 Urine specific gravity (g ml−1) Average 1.019 1.019 1.02 1.022 1.024 1.024 SD 0.008 0.009 0.009 0.009 0.011 0.009 Urine Na corrected by Cr (mEQ mg−1) Average 0.180 0.121 0.114 0.119 0.074 0.091 SD 0.084 0.073 0.075 0.063 0.048 0.05 Time of measurement SW MB BL AL AB EW Urine temperature (°C) Average 36.74 36.99 37.26 36.97 37.47 37.25 SD 0.30 0.40 0.33 0.33 0.28 0.27 Urine osmolality (mOsm kg−1 H2O) Average 723 689 748 779 765 787 SD 2709 243 273 289 308 291 Urine specific gravity (g ml−1) Average 1.019 1.019 1.02 1.022 1.024 1.024 SD 0.008 0.009 0.009 0.009 0.011 0.009 Urine Na corrected by Cr (mEQ mg−1) Average 0.180 0.121 0.114 0.119 0.074 0.091 SD 0.084 0.073 0.075 0.063 0.048 0.05 The values which are significantly larger or smaller than the other value by Student’s t-test (P < 0.05) are marked in bold. View Large Figure 3. View largeDownload slide Average physiological indexes of construction workers during shift. (A) Urine and sublingual temperature, (B) HRR, (C) relative body weight difference, (D) sweat rate, water intake, urine volume per 1 h on assumption of the weight of 70 kg. Sweat rate in lunch was not calculated due to unavailability of weight of lunch. AB: afternoon break; AL: after lunch; BL: before lunch; EW: end of the work shift; MB: morning break; SW: start of the work shift; w1: first half of the morning work; w2: second half of the morning work; b2: lunch time; w3: first half of the afternoon work; w4: second half of afternoon work. *The values are significantly different by Student’s t-test (P < 0.05). The error bars represent SD. Figure 3. View largeDownload slide Average physiological indexes of construction workers during shift. (A) Urine and sublingual temperature, (B) HRR, (C) relative body weight difference, (D) sweat rate, water intake, urine volume per 1 h on assumption of the weight of 70 kg. Sweat rate in lunch was not calculated due to unavailability of weight of lunch. AB: afternoon break; AL: after lunch; BL: before lunch; EW: end of the work shift; MB: morning break; SW: start of the work shift; w1: first half of the morning work; w2: second half of the morning work; b2: lunch time; w3: first half of the afternoon work; w4: second half of afternoon work. *The values are significantly different by Student’s t-test (P < 0.05). The error bars represent SD. Nineteen subjects had urine samples collected at six measurement times (SW, MB, BL, AL, AB, EW). The urine biochemical data were analyzed. Average Uosm was larger in the afternoon, but not significant. Usg increased from SW (1.019 g ml−1) to AB (1.024 g ml−1). Usg of AB was significantly higher than SW, MB, and BL (P < 0.05) and Usg of EW was larger than that of SW and BL (P < 0.05) (Table 1). The ratio of workers whose Usg was above the clinically dehydrated level of 1.030 g ml−1 was 5, 16, 11, 21, 26, and 21% at SW, MB, BL, AL, AB, and EW, respectively. The correlation between Usg and Uosm was very high (R = 0.87). Urine sodium concentration corrected by creatinine was significantly lower in AB than samples collected at other shifts and urine sodium concentration corrected by creatinine at SW were significantly larger than those of the other times (Table 1). Discussion The physiological effects of heat stress were monitored for construction workers in Japan during the summer. The average personal WBGT were 27.4, 28.0, 28.5, and 27.3°C for w1, w2, w3, and w4, respectively. Body weight decreased by 1.3% at EW. Average water intake was 52% compared with water loss during work excluding lunch time. UT and Usg were highest in AB. Urine sodium corrected by creatinine decreased significantly from SW to AB. Heat stress As far as we know, this is the first study to measure the thermal work environmental conditions around workers by WBGT monitor. The average outside WBGT in the sun over 3 days of 30.9°C was close to that in studies of other construction workers [31°C (Montazer et al., 2013), 31.4°C (Chang et al., 2009), 30.1°C (Morioka et al., 2006)]. Since the other studies did not measure the environment around workers, it is possible that the measured environmental data did not accurately reflect the work environment. Some subjects would work in the sun, some subjects work in the shade or inside, and others work in both. Measured Ta, Tg, RH, and WBGT by a personal WBGT monitoring instrument were between those of a stationary WBGT placed indoors and outdoors in the sun (Fig. 2). The WBGT of workers in direct sunlight was close to those in a sunny area, and the WBGT in indoor workers was close to that in indoor settings. The differences between maximum and minimum average personal WBGT were 3.1, 3.0, 4.9, and 3.4°C for w1, w2, w3, and w4, respectively, which were not negligible. These data showed that personal monitoring of thermal environmental conditions during work was needed. Heat strain HR is a suitable single index of heat strain (Goldman, 1988), since it reflects the combination of physical work, heat elimination difficulty, and psychological stress. According to ISO 8996 (ISO, 2004a), the contributing factors to a change in HR is dynamic muscular load, static muscular work, heat stress, mental load, and other factors, such as respiratory effects, circadian rhythms, and dehydration (ISO, 2004). To regulate body temperature in a hot work environment, the autonomic nervous system increases blood flow from the core to the skin and triggers sweating. Both the demand of blood flow to muscle by work and to the skin by body temperature regulation increases HR. In this study, the average HR of construction workers in w3 was 112 bpm, significantly higher than average HR at other times in the shift. %HRR, which removed inter-subject variability by age or resting HR from original HR, was also highest in w3. One reason for this is that higher environmental heat stress in afternoon work could activate the autonomic nervous system and HR would increase. Dimri et al. (1980) showed that total metabolic rate increases in high heat stress conditions at the same work output. Ueno et al. (2014) also reported increased metabolic rate by higher Ta. A higher metabolic rate increases body temperature, activates the autonomic system, and increases HR. Another factor is food intake, which is also a contributing factor to increase HR. Sidery and Macdonald reported that HR increased by 5–10 bpm after food intake and lasted for about 2 h (Sidery and Macdonald, 1994). Considering the effect of food, average HR in w3 was at the same level as the other work times. A field study (Bates and Schneider, 2008) of UAE construction workers reported that average HR during work was about 90 bpm in a thermal environment of WBGT over 27.5°C. It is suggested that low humidity, adequate water intake, and self-paced work would help to keep the HR at a safe level despite the high Ta and radiant temperature of the work environment. A field study of construction workers in Taiwan (Chang et al., 2009) and Hong Kong (Wong et al., 2014) found that the average HR of scaffolders (Chang et al., 2009) was 120 bpm and that of bar benders (Wong et al., 2014) was 114 bpm. Our results were close to those of Chang et al. (2009) and Wong et al., (2014). For miners, Kalkowsky and Kampmann (2006) reported that HR exceeded a limit of ‘200-age’ in 61 out of 125 shifts. The World Health Organization (WHO) recommends that a maximum allowable average HR as 110 bpm (WHO, 1969). Our results of construction workers’ HR showed that cardiovascular strain exceeded the WHO limit. The subjects in our study were allocated a designated amount of work that they had to complete by a certain time. Core body temperature was measured by UT and sublingual temperature. In our data, average UT increased significantly by 0.73°C from the start of work to the afternoon break (Fig. 3A, Table 1). According to ACGIH TLV (2017) for heat stress and strain, the limits on core temperature are determined by a maximum temperature of 38°C for unacclimatized workers and 38.5°C for acclimatized workers. In this study, none of the UT samples were over 38.0°C. The average largest increase of the UT from the start of work to the first half of the afternoon work was 0.8°C. Due to circadian rhythms, body temperature differs diurnally by 1°C or more, with the lowest at 4:00 A.M. and highest at 6:00 P.M. Since the work time was approximately from 9:00 A.M. to 5:00 P.M., the amplitude of the diurnal core temperature would be close to 1°C. Some part of the UT change could be explained by circadian rhythm. The next contributing factor is food intake. A large meal was reported to increase core body temperature by 0.3°C (Nielsen, 1987). Furthermore, a hot work environment could increase metabolic rate (Dimri et al., 1980; Ueno et al., 2014) and consequently increase UT (Fig. 3A). Another factor is physical work. The decrease of UT after lunch and a sharp increase after the first half of the afternoon work would be caused by rest and physical work in a hot work environment. UT has been used as an index of body core temperature (Fox et al., 1975; Samples and Abrams, 1984). Fox et al. showed that rectal temperature was higher than UT by 0.33°C. Since the ambient temperature in our study was closer to body temperature than their condition (20°C) and because we used a quicker temperature response thermistor, the measured UT would not be as decreased after urination as in Fox’s study. Since the difference between rectal and measured UT was estimated to be smaller than 0.33°C, UT was a reliable index of core temperature in our study. Samples and Abrams also provided data that the maximum temperature of the voided UT records was close to vaginal temperature. Bates and Schneider (2008) reported that the mean aural temperature of construction workers during work as shown in Fig. 2 in their paper was 36.5°C, though it increased slightly in the afternoon, suggesting that worker heat strain was not severe. Nag et al.’s (2013) field study on body temperature of construction workers in India by using oral temperature showed that 90% of workers were under 38°C and 4% were over 39°C. Nag et al. concluded that the workers regulated their core temperature by pacing themselves. Our research showed the same results as those found by Bates and Schneider (2008) and Nag et al. (2013). On the contrary, Kalkowsky and Kampmann (2006) reported that maximum rectal temperature (Tre) measured by rectal thermal probe exceeded 38.0°C for most miners during work. Brake and Bates (2002) showed field research data about miners whose average maximum core temperature was 38.9°C. Severe heat stress and the heavy physical workload led miners to have a higher core temperature than construction workers. Hydration Hydration status is an important determinant of a person’s heat tolerance. In this study, water intake, body weight loss, Usg, and Uosm were measured as parameters for hydration status. Since the weight of bowel movements was not measured and there were only two occurrences for all subjects, we did not take bowel movements into account. On average, body weight decreased by 1.3% at EW compared to SW. Body weight decreased by more than 2.0% for five workers. Dehydration over 2% of body weight decreases aerobic (Cheuvront et al., 2010) and cognitive performance (Hancock and Vasmatzidis, 2003). A previous study (Peiffer and Abbiss, 2013) showed that 2–4% dehydration by weight loss reduces maximum aerobic power. Physical work capacity has also been reported to decrease with 1–2% dehydration, reducing work performance (Armstrong et al., 1985). Moreover, dehydration decreases the sweating rate (Sawka et al., 1989) and skin blood flow due to reduced blood volume. Decreased heat dissipation from the skin due to dehydration would increase the core temperature of workers (Montain et al., 1995) and elevate the risk of heat stroke. The low rate of fluid intake to water loss during morning work was partly compensated by fluid intake during lunch (Fig. 3D). The average fluid intake during lunch was 0.84 l h−1 70 kg−1, which was four times larger than that of w3. The rate of fluid intake to water loss during the shift would be a little higher than that excluding lunch of 52%. In this study, participant fluid intake was insufficient. To prevent dehydration, it is necessary to drink water frequently during work and also replenish water during lunch. The other hydration indices we used in this study were Usg and Uosm. The mean Usg of 19 subjects whose samples were collected and measured six times in a day increased from 1.019 g ml−1 at SW to 1.024 g ml−1 at EW. In this study, the percentage of hydrated subjects (Usg < 1.020 g ml−1) (Oppliger et al., 2005) of 47% at SW decreased to 21% at EW. A study of miners (Polkinghorne et al., 2013) found that 41% of subjects were hydrated before work and 42% were hydrated after work. The average rate of water intake compared to water loss during work time was about 52% in our study, which could cause a decreased level of hydration in the afternoon. In this field study, we measured physiological indexes without intervention. Since voluntary drinking was reported to lead to insufficient water intake, workers without knowledge of the importance of hydration or instruction to drink water could become dehydrated (Greenleaf and Sargent, 1965). Some previous studies reported on the hydration of construction workers in hot environments. Bates and Schneider (2008) reported that Usg of UAE construction workers was about 1.012 mg ml−1 in the morning, 1.013 at midday, and 1.012 in the afternoon, which meant that workers were slightly overhydrated (Usg < 1.015 g ml−1). The subjects of Bates and Schneider (2008) drank 5.4 l of water during a 12-h shift compared to the 2.6 l that workers in our study drank in an 8-h shift. Miller and Bates (2007) presented data on construction workers whose Usg was 1.018 mg ml−1 in pre-shift, 1.018 mg ml−1 in mid-shift, and 1.018 mg ml−1 in post-shift. Their fluid intake was 1.04 l h−1 and sweat rate was 1.03 l h−1, which maintained a fluid balance. The unchanged Usg of workers in their study (Miller and Bates, 2007; Bates and Schneider, 2008) showed that water intake was comparable to water loss. ACGIH TLV standard of drinking a cup of cool water (about 235 ml) every 20 min during work in a hot environment to prevent heat illness would not be enough for a sweat rate of over 1 l h−1 in a hot environment. Another study of construction workers in Iran (Montazer et al., 2013) reported that average Usg was 1.026 g ml−1 at the start of the workday, 1.027 g ml−1 in the middle, and 1.025 g ml−1 at the end. Usg stayed constant from the beginning to the end. In the paper (Montazer et al., 2013), the workers were asked to drink a specific amount of water during their shift. Similarly, a field study of miners (Brake and Bates, 2003) showed that Usg was kept constant at about 1.025 g ml−1 from the start of work to the end with an average fluid intake at 6.5 l for 10–12.5 h. High Usg at the beginning of work would be caused by insufficient water intake outside of work. Thus, to keep workers adequately hydrated, lost fluid during the shift would have to be replaced and hydration at the start of work would have to be increased. To study the reliability of Usg as a hydration index, Oppliger et al. (2005) compared the criteria of dehydration of Usg over 1.020 g ml−1 and plasma osmolality (Posm) over 290 mOsm kg−1, and found high sensitivity (80% subjects whose Usg was over 1.020 had Posm > 290), but low specificity (31.3% subjects whose Usg was under 1.020 had Posm < 290). Their study showed that workers with a high Usg had a high probability of dehydration, but that low Usg does not guarantee euhydration. Uosm is considered a better index than Usg, because osmotic pressure is not influenced by the dissolved substances in urine. However, analysis of Uosm requires an osmometer installed in a laboratory, making it unsuited for use in the field. On the other hand, Usg can be measured quickly with a portable refractometer. For the collected urine from the subjects in this study, there was a high correlation (R = 0.87) between Uosm and Usg. The mean Uosm of 19 subjects who had all of their samples collected at each measurement increased from 682 mOsm kg−1 to 804 mOsm kg−1. Since the cutoff value of euhydration for Uosm is considered as 700 mOsm kg−1 (Kenefick et al., 2012), the average Uosm showed that the subjects were euhydrated at the start of work and hypohydrated at the end of work. Every urine sample more than 1.030 g ml−1 in Usg was more than 1000 mOsm kg−1 in Uosm. However, there are also limitations in Uosm. Oppliger et al. (2005) reported that Uosm has poor association with body weight loss or Posm. Moreover, Usg or Uosm lags behind Posm during acute dehydration (Popowski et al., 2001). This lagging would reflect the fact that urine indices were the average of previous urination and present urinations. Hyponatremia Hyponatremia, which arises due to loss of sodium by heavy sweating coupled with an intake of a large amount of water or other low sodium drink, sometimes causes severe conditions, including pulmonary edema, respiratory arrest, coma, or death. In this field study, the possibility of hyponatremia for the subjects would be low due to a low intake of beverage and maintenance of the Uso level during work. However, creatinine-adjusted sodium concentration (Vought et al., 1963) in urine decreased significantly during work (Table 1), suggesting a sign of decreased sodium. A mean body weight loss under 0.9% of body weight at the end of work and ample salt intake from food or drink during work would prevent hyponatremia (Hew-Butler et al., 2008). Heat stress standards We referred to the physiological heat strain recommendations proposed by ACGIH TLV guidelines (2017) for cardiac strain of sustained HR in excess of 180 bpm minus the individual’s age, body core temperature of 38.5°C for a medically selected and acclimatized person, and weight loss over a shift of 1.5% of body weight. In addition to ACGIH TLV guidelines, a clinical guideline of Usg over 1.030 mg ml−1, which is used as a criterion of clinical dehydration by the Australian Pathology Association (Bates and Schneider, 2008), was included. Among four referred heat strain recommendations, no subjects were over the body core temperature of 38.5°C. Therefore, a Venn diagram was drawn for 23 subjects based on three recommendations, excluding body temperature, to clarify the relationships among the recommendations (Fig. 4). Six of the 23 workers exceeded the recommendations for HR, 11 exceeded body weight loss, and 8 exceeded Usg. Only four workers were under the limits for all the four recommendations. There were no subjects whose physiological indexes exceeded all the four recommendations. These results showed that heat strain of the subjects in this study was not severe. Figure 4 shows that gold heat strain recommendations which include all recommendations did not exist. Although weight loss and Usg are classified under the same hydration recommendations, only two subjects overlapped. It also could be considered that not exceeding one criterion of heat strain does not guarantee that there is little risk of a heat-related disorder. Examining more than one physiological parameter is needed to identify workers at risk of heat stroke and ensure adequate protection. Figure 4. View largeDownload slide Venn diagram of the overlap of physiological guidelines limiting the heat strain by ACGIH of weight loss, HR, and clinically dehydrated urine specific gravity for 23 subjects. (I) The subjects whose heart rate was over 180—age for more than 3 min, (II) those whose weight decreased more than 1.5% in the shift, (III) those whose urine specific gravity was over 1.030 mg ml−1 were counted. The number in the figure stands for the subject’s number corresponding to each area of Venn diagram. Figure 4. View largeDownload slide Venn diagram of the overlap of physiological guidelines limiting the heat strain by ACGIH of weight loss, HR, and clinically dehydrated urine specific gravity for 23 subjects. (I) The subjects whose heart rate was over 180—age for more than 3 min, (II) those whose weight decreased more than 1.5% in the shift, (III) those whose urine specific gravity was over 1.030 mg ml−1 were counted. The number in the figure stands for the subject’s number corresponding to each area of Venn diagram. Limitations The use of UT as a measure of deep body temperature can be constrained as urination times can be limited. This makes it difficult to detect quick changes of body temperature. However, the results of this study showed that UT was sensitive to body temperature changes (Fig. 3A). The benefit of estimating body core temperature by UT is to free the subjects from the stress of restrictions imposed by body temperature measurement. An instrument to measure UT in a toilet would provide a good tool to allow workers to check deep body temperature on their own. An additional limitation was that we did not have a chance to measure the weight of a lunch meal. If the weight of the lunch that the subjects ate was available, it would be possible to calculate the sweat rate during lunch time (Fig. 3D). Conclusions In Japan, the number of construction workers who died from heat stroke during summer work was the largest in all kinds of industry. To survey the heat strain of construction workers, environmental conditions, HR, water intake, body weight, UT, urine specific gravity (Usg), urine osmolality (Uosm), urine sodium (Uso), and urine creatinine were measured. The heat strain of subjects was highest in the first half of afternoon work (w3). The average work environment, measured on the helmet of each subject, was 28.5°C in w3. The rate of water intake to water loss excluding lunch time was 52%. The average UT, Usg, %HRR, and sweat rate were 37.5°C, 1.024 g ml−1, 35%, and 0.55 l h−1 70 kg−1, respectively, in w3. Average Usg increased during the shift, reflecting the low rate of fluid replacement. Compared with ACGIH TLV physiological recommendations for HR, weight loss, core temperature, and clinical limit for Usg, 19 out of 23 subjects were over at least one of these recommendations (Fig. 4). No subjects exceeded the core temperature recommendation of 38.0°C. A gold-standard heat strain recommendations that include all recommendations does not exist (Fig. 4). Therefore, to prevent heat-related disorders in construction workers, many physiological indexes about heat strain should be checked. Additionally, workers should be encouraged to drink enough water and salt and pace themselves when working in a hot environment. Funding Funding for this project (principal investigator: Dr Shin-ichi Sawada) was provided by Ministry of Health, Labour and Welfare. Acknowledgements The authors declare no conflict of interest relating to the material presented in this article. Its contents, including any opinions and/or conclusions expressed, are solely those of the authors. 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Int J Occup Saf Ergon ; 8 : 83 – 93 . Google Scholar CrossRef Search ADS PubMed © The Author(s) 2018. Published by Oxford University Press on behalf of the British Occupational Hygiene Society. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Annals of Work Exposures and Health (formerly Annals Of Occupational Hygiene) Oxford University Press

Heat Strain and Hydration of Japanese Construction Workers during Work in Summer

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Abstract

Abstract Objectives The aim was to ascertain hydration and heat strain of construction workers in Japan during the summer who are at the highest risk of heat-related disorders. Methods The subjects were 23 construction workers, whose average age was 41, average weight was 69 kg, and average height was 170 cm. We measured thermal working conditions with a wet bulb globe temperature (WBGT) measurement instrument affixed to the helmet of each worker, at fixed points outdoors in the sun and indoors. Heat strain was evaluated for water intake, urine specific gravity (Usg), urine temperature (UT), heart rate (HR), and body weight during work. Results The average WBGT measured on the worker helmets over 3 consecutive days was 28.0 ± 0.7, 27.6 ± 0.8, and 27.6 ± 1.1°C. The average water intake was 2.6 l during a work shift. The average Usg, UT, and % HR reserve were the highest in the first half of afternoon work. Seventy-eight percent of the subjects exceeded at least one of the ACGIH TLV physiological guidelines for heat strain in terms of HR and weight loss or a clinically dehydrated level of Usg. Conclusions Heat strain was the highest in the first half of afternoon work. The number of dehydrated workers increased during this shift because of insufficient water intake. Adequate hydration is required to decrease the risk of heat-related disorders among construction workers in the summer. construction, deep body temperature, dehydration, heat stress, urine specific gravity Introduction Higher heat stress in the work environment associated with climate change has increased the risk of heat-related disorders for workers in construction, agriculture, forestry, and other outdoor occupations (NIOSH, 2016). Epidemiological data (Adelakun et al., 1999; Bonauto et al., 2007; Lin and Chan, 2009; Jackson and Rosenberg, 2010) have indicated that the construction industry had the highest percentage of work-related heat disorders. Japan’s Ministry of Health, Labour and Welfare (2016) has announced that construction work accounted for 40.0% of casualties from heat stroke between 2011 and 2015, the largest industry of all Japanese industries. The construction industry accounts for 7.8% of all employment in Japan (Ministry of Internal Affairs and Communication, 2016). Construction is the highest-risk industry in terms of work-related heat disorders. Ambient temperature (Ta), humidity, radiation, air velocity, metabolic rate, and clothing are used to calculate the heat exchange between the human body and the environment in the thermal model of ISO7933 (ISO, 2004b) and ISO7730 (ISO, 2005). For construction workers, high Ta, direct sunlight, radiation from the heated ground or building, weakened air velocity, strenuous workload, and protective clothing with high thermal insulation and vapor resistance contribute to increased heat strain in workers. In summer, the daily maximum temperature of Ta in Japan is often over 35°C, according to the Japan Meteorological Agency (2017). On a construction site, Ta would be higher than the temperature indicated by the weather stove, which is measured at more than 1.5 m above lawn where natural wind is not disturbed (Japan Meteorological Agency, 1998). When Ta is higher than skin temperature, convective heat is transferred to the body from the environment. Sweat evaporation is the main way for heat to dissipate from the body to the environment. To maintain body temperature, construction workers sweat heavily, leading to dehydration and hyponatremia. Furthermore, the protective clothing worn by construction workers prevents the sweat on the skin from evaporating and promotes even heavier sweating and dehydration. This depletion of water and electrolytes decreases the blood volume, extracellular fluid volume, and amount of sweating (Sawka et al., 1989), thus making heat dissipation even more difficult. Dehydration exceeding 2% body weight has been reported to decrease aerobic (Cheuvront et al., 2010) and cognitive performance (Hancock and Vasmatzidis, 2003). Thus, dehydration increases not only the risk of heat stroke, but also the likelihood of accidents. Dehydration was found in 17% of all cases of heat stroke reported in the US Army over a 22-year period (Carter et al., 2005). Previous studies (Bates and Schneider, 2008; Bates et al., 2010; Montazer et al., 2013) of hydration in construction workers have been inconsistent. UAE construction workers (Bates and Schneider, 2008; Bates et al., 2010) were reported to be well hydrated during work, but construction workers (Montazer et al., 2013) in Iran were inadequately hydrated from before to the end of work. Thus, it is important to ascertain the hydration of construction workers. In terms of workload, some studies reported an average heart rate (HR) during work as 90–100 beats per minute (bpm) (Bates and Schneider, 2008; Miller et al., 2011), while others reported 110 bpm (Chang et al., 2009; Wong et al., 2014). Construction workers engage in strenuous physical activity even in very hot environments. A field study in a tropical region found that self-pacing is a protective response to working under such conditions (Miller et al., 2011). However, construction workers in Japan are liable to be required to finish their tasks on time despite the heat. Time constraints could increase the risk of heat strain among construction workers. According to the Monthly Labour Survey by the Ministry of Health, Labour and Welfare Japan (2017), in 2016 the average construction worker clocked 171.3 h of work a month, which was the longest in all industries. Most previous studies were conducted in tropical or subtropical regions (Yoopat et al., 2002; Bates and Schneider, 2008; Chang et al., 2009; Bates et al., 2010; Miller et al., 2011; Montazer et al., 2013; Wong et al., 2014), and few were done in temperate regions. There is a great need for comprehensive field studies of construction workers in temperate regions during the summer. The aim of this field study was to ascertain hydration and heat strain of construction workers in summer in a temperate zone. These data would inform the planning of effective steps to decrease the incidence of heat stroke among construction workers. Materials and methods This field study was conducted at a worksite of Aichi prefecture in Japan. Aichi prefecture in central Japan is one of the hottest regions in the country. The average daily maximum temperature and relative humidity (RH) in August from 1990 to 2005 were registered at 32.9°C and 70%, respectively. Aichi was selected for this study because it is one of the largest prefectures in Japan with a large number of ambulance transports due to heat disorders (Ministry of Internal Affairs and Communications, 2008). The daily maximum temperature of the nearest meteorological observatory had been over 30°C for 2 weeks before the study. The subjects were assumed to be acclimatized to heat. The construction workers on the site were renovating a building to increase earthquake resistance. Observations were made for 3 consecutive days in August 2009. Subjects Twenty-three male construction workers (age: 41 ± 15 years; weight: 68 ± 10 kg; height: 170 ± 6 cm; body mass index: 24 ± 3) participated in the study. The breakdown of the subjects was as follows: seven were plumbers, three were demolition workers, two were cleaning workers, steel-frame workers, heat insulation workers and chipping workers, and five were others. They were engaged in various types of work: worksite supervision, cutting metal rods with an electric saw while on a stepladder, peeling off tile and carrying it out, installing a curing seat, wrapping pipes with insulation while on a stepladder, etc. Some subjects worked indoors and others outdoors or both. Moreover, most subjects worked at different places between A.M. and P.M. Work started at around 9:00 A.M. and finished around 4:30 P.M. during the study days. There was a scheduled 30-min break in the morning (10:00 A.M.–10:30 A.M.), an hour for lunch (Noon–1:00 P.M.) and a second 30-min break in the afternoon (3:00 P.M.–3:30 P.M.). The purpose and study procedures were explained to the participants before they gave their written informed consent. The Review Board of National Institute of Occupational Safety and Health, Japan approved this study. This study was conducted according to the Declaration of Helsinki. A medical doctor and a health care worker joined this study. Environmental conditions Environmental conditions were measured inside the building and outside the building in the sun using a wet bulb globe temperature (WBGT) monitor (3M QUESTemp°36) at a resolution of 0.1°C, respectively. For the indoor WBGT monitor, there was no direct sunlight to the monitor in a room on the first floor of the construction building with the windows open. For the outdoor WBGT monitor in the sun, there was direct sunlight to the WBGT monitor on the ground of the construction site. Buildings were not located near the outdoor monitor. Both WBGT monitors were placed at fixed points. The monitors had been calibrated by the manufacturer before use. Digital data for natural wet bulb temperature, dry bulb temperature (Ta), wind speed, and globe temperature (Tg) were recorded every minute. In addition, portable rod-like WBGT monitors (WBGT-213B, Kyoto Electronics Manufacturing) were used to record the digital data of Ta, Tg, and RH around each worker every 2 min. The monitor, which was 24 cm in length and 110 g in weight, was attached to the side of each worker’s helmet above the ear position with adhesive tape. The portable monitors were used just after being purchased from the manufacturer. We checked that the fixed-position WBGT monitors and portable WBGT monitors showed the same values before the study. The sizes of the globe sensor of both WBGT instruments were smaller than a standard size of 15 cm in diameter for convenience in measurement. The calibration algorithm to fit the size of the globe sensor to a standard size was a black box. Physiological conditions The physiological conditions of workers were monitored by HR, weight loss, and urine specific gravity. R-R interval (the inter-beat intervals using R-wave peak) was measured with a data logger (ActiHR, CamNTech Ltd) from the start to the end of the shift. Average HR for each minute was calculated from R-R interval. Heart rate reserve (%HRR) was calculated by using the following equation: %HRR=(HR–resting HR)/(maximal HR – resting HR)×100 (1) where maximal HR was estimated by the following equation (Tanaka et al., 2001): Maximal HR=208–0.7×age (2) Resting HR was estimated by the stable minimal HR during the shift. Most of the resting HR were registered at lunch, morning break, before work, or after work. The average resting HR was 75 bpm, which was close to the experimental average resting HR of 71–73 bpm (Isaka et al., 1990). Subject weight was measured six times [at the start of the work shift (SW), morning break (MB), before lunch (BL), after lunch (AL), afternoon break (AB), and at end of the work shift (EW)] with only their shorts with an accuracy of 20 g (FG-150 KBM, AND). At measurement, subjects wiped their sweat off their skin. Sublingual temperature was measured by an electronic thermometer with a predictive function of equilibrium temperature (ET-C502, Terumo) within about 90 s with a precision of 0.05°C at a resolution of 0.01°C. When the prediction was finished, a thermometer bell rings. The subjects were asked to put the thermometer under their tongue until the bell rings. The thermometers were assigned the personal identification numbers and distributed to the corresponding subjects only at measurement to maintain sanitary conditions. Urine was sampled six times at SW, MB, BL, AL, AB, and EW to measure urinary volume, urine specific gravity (Usg), urine osmolality (Uosm), urine sodium (Uso), and urine creatinine. Urine temperature (UT) was measured during urination by a thermistor (LT-ST08-00, Gram) as a reference of core temperature. The temperature sensor was set at the bottom of the cup for collecting urine. The maximum temperature of the sensor was recorded as UT. Usg was measured with a refractometer (Pal-09S, Atago). Urine samples were dispensed to a 5 ml cryo-tube that was frozen via dry ice and transferred to a measurement firm (SRL, Inc., Tokyo) that measured urine content. Hydration Fluid consumption was measured by subtracting the remaining weight of a water bottle from the weight of a water bottle before the measurement at MB, BL, AL, AB, and EW by an electric weight scale with an accuracy of 1 g. In this study, sweating was estimated by the following equation (3), Sweating=Body weight loss+water intake−urine volume (3) Water loss through respiration was included in sweating. Results Ten, nine, and four male subjects participated in this study on the first, second, and third days of the field study, respectively. No subject participated on more than one day. The average time length for first half (w1), break (b1) and second half (w2) in the morning, lunch (b2), and the first half (w3), break (b3) and second half (w4) in the afternoon were 83, 21, 90, 53, 115, 25, and 84 min, respectively. The mean outdoor WBGT of the first day from 10:40 to 16:30 was 32.2°C. The mean outdoor WBGT of the second and third day from 10:40 to 16:30 were 30.0 and 30.4°C, respectively (Fig. 1). Mean WBGT inside the building was 27.4°C (first day), 26.5°C (second day), and 26.6°C (third day). Air conditioners were not installed inside the building. Stationary measurement of WBGT, Ta, Tg, Tnw, and RH for indoor and outdoor in the sun from the first to the third day are shown together in Fig. 1. Average WBGT recorded by portable WBGT instruments attached to the helmet of each subject during work was 28.0 ± 0.7°C (first day), 27.6 ± 0.8°C (second day), and 27.6 ± 1.1°C (third day). Since the average WBGTs on the helmets were not significantly different over the 3 days of field study, we clustered the data for the analysis. The average personal monitoring WBGTs, Ta, Tg, and RH are shown in Fig. 2A–D, respectively. The average personal WBGT values were 27.4, 28.0, 28.5, and 27.3°C for w1, w2, w3, and w4, respectively. Figure 1. View largeDownload slide Time course of fixed WBGT monitors for indoor (In) and outdoor in the sun (Out). RH: relative humidity; Tw: wet bulb temperature; Ta: ambient temperature; Tg: globe temperature. The data of WBGT monitors of outdoor in the sun were missing in the first half of the morning work in the first day. Figure 1. View largeDownload slide Time course of fixed WBGT monitors for indoor (In) and outdoor in the sun (Out). RH: relative humidity; Tw: wet bulb temperature; Ta: ambient temperature; Tg: globe temperature. The data of WBGT monitors of outdoor in the sun were missing in the first half of the morning work in the first day. Figure 2. View largeDownload slide Thermal working environment of construction workers. (A) WBGT, (B) dry bulb temperature, (C) globe temperature, (D) RH. Pers: average value measured by WBGT monitor fixed on workers’ helmet; Out: average value measured by WBGT monitor set at standpoint in outdoor in the sun; In: average value measured by WBGT monitor set at standpoint in outdoor in the sun; w1: first half of morning work; w2: second half of morning work; w3: first half of afternoon work; w4: second half of the afternoon work. The error bars represent SD. From Fig. 2A–D, w1 showed the average of second and third day. W2, w3, and w4 showed the average of first to third day. Figure 2. View largeDownload slide Thermal working environment of construction workers. (A) WBGT, (B) dry bulb temperature, (C) globe temperature, (D) RH. Pers: average value measured by WBGT monitor fixed on workers’ helmet; Out: average value measured by WBGT monitor set at standpoint in outdoor in the sun; In: average value measured by WBGT monitor set at standpoint in outdoor in the sun; w1: first half of morning work; w2: second half of morning work; w3: first half of afternoon work; w4: second half of the afternoon work. The error bars represent SD. From Fig. 2A–D, w1 showed the average of second and third day. W2, w3, and w4 showed the average of first to third day. Average UT increased from SW to AB and average UT at AB was significantly higher than the others (Fig. 3A, Table 1). The UT of more than half of the workers was more than 37.5°C at AB. The average %HRR of w3 was significantly higher than those at other times (Fig. 3B). The average body weight relative to initial body weight decreased during morning work, increased at lunch, and decreased during afternoon work (Fig. 3C). Average body weight decreased by 1.3% at EW. Body weight decreased more than 2.0% for five workers at EW. In Fig. 3D, sweat rate, water intake, and urine rate are shown per 1 h per 70 kg body weight. For 16 subjects, whose water intake data were completely registered at six measuring times, water intake was 0.84 l h−1 70 kg−1 at lunch (Fig. 3D), and total water intake during shift including lunch was 2.6 l. During lunch, the sweat rate was not shown due to unavailability of lunch weight. Sweat rate in the afternoon was a little larger than in the morning but was not significant. Two subjects defecated between the morning break and lunch. There were no other subjects who defecated during work hours. Thus, the error in sweating rate resulting from defecation that was calculated by equation (3) was negligible. During the work shift, the ratios of fluid intake to water loss (sweat loss + urine) were 56% at w1, 52% at w2, 37% at w3, 74% at w4 (Fig. 3D), and 52% at work shift except for lunch. Table 1. Urine biochemical measurements of the subjects. Time of measurement SW MB BL AL AB EW Urine temperature (°C) Average 36.74 36.99 37.26 36.97 37.47 37.25 SD 0.30 0.40 0.33 0.33 0.28 0.27 Urine osmolality (mOsm kg−1 H2O) Average 723 689 748 779 765 787 SD 2709 243 273 289 308 291 Urine specific gravity (g ml−1) Average 1.019 1.019 1.02 1.022 1.024 1.024 SD 0.008 0.009 0.009 0.009 0.011 0.009 Urine Na corrected by Cr (mEQ mg−1) Average 0.180 0.121 0.114 0.119 0.074 0.091 SD 0.084 0.073 0.075 0.063 0.048 0.05 Time of measurement SW MB BL AL AB EW Urine temperature (°C) Average 36.74 36.99 37.26 36.97 37.47 37.25 SD 0.30 0.40 0.33 0.33 0.28 0.27 Urine osmolality (mOsm kg−1 H2O) Average 723 689 748 779 765 787 SD 2709 243 273 289 308 291 Urine specific gravity (g ml−1) Average 1.019 1.019 1.02 1.022 1.024 1.024 SD 0.008 0.009 0.009 0.009 0.011 0.009 Urine Na corrected by Cr (mEQ mg−1) Average 0.180 0.121 0.114 0.119 0.074 0.091 SD 0.084 0.073 0.075 0.063 0.048 0.05 The values which are significantly larger or smaller than the other value by Student’s t-test (P < 0.05) are marked in bold. View Large Table 1. Urine biochemical measurements of the subjects. Time of measurement SW MB BL AL AB EW Urine temperature (°C) Average 36.74 36.99 37.26 36.97 37.47 37.25 SD 0.30 0.40 0.33 0.33 0.28 0.27 Urine osmolality (mOsm kg−1 H2O) Average 723 689 748 779 765 787 SD 2709 243 273 289 308 291 Urine specific gravity (g ml−1) Average 1.019 1.019 1.02 1.022 1.024 1.024 SD 0.008 0.009 0.009 0.009 0.011 0.009 Urine Na corrected by Cr (mEQ mg−1) Average 0.180 0.121 0.114 0.119 0.074 0.091 SD 0.084 0.073 0.075 0.063 0.048 0.05 Time of measurement SW MB BL AL AB EW Urine temperature (°C) Average 36.74 36.99 37.26 36.97 37.47 37.25 SD 0.30 0.40 0.33 0.33 0.28 0.27 Urine osmolality (mOsm kg−1 H2O) Average 723 689 748 779 765 787 SD 2709 243 273 289 308 291 Urine specific gravity (g ml−1) Average 1.019 1.019 1.02 1.022 1.024 1.024 SD 0.008 0.009 0.009 0.009 0.011 0.009 Urine Na corrected by Cr (mEQ mg−1) Average 0.180 0.121 0.114 0.119 0.074 0.091 SD 0.084 0.073 0.075 0.063 0.048 0.05 The values which are significantly larger or smaller than the other value by Student’s t-test (P < 0.05) are marked in bold. View Large Figure 3. View largeDownload slide Average physiological indexes of construction workers during shift. (A) Urine and sublingual temperature, (B) HRR, (C) relative body weight difference, (D) sweat rate, water intake, urine volume per 1 h on assumption of the weight of 70 kg. Sweat rate in lunch was not calculated due to unavailability of weight of lunch. AB: afternoon break; AL: after lunch; BL: before lunch; EW: end of the work shift; MB: morning break; SW: start of the work shift; w1: first half of the morning work; w2: second half of the morning work; b2: lunch time; w3: first half of the afternoon work; w4: second half of afternoon work. *The values are significantly different by Student’s t-test (P < 0.05). The error bars represent SD. Figure 3. View largeDownload slide Average physiological indexes of construction workers during shift. (A) Urine and sublingual temperature, (B) HRR, (C) relative body weight difference, (D) sweat rate, water intake, urine volume per 1 h on assumption of the weight of 70 kg. Sweat rate in lunch was not calculated due to unavailability of weight of lunch. AB: afternoon break; AL: after lunch; BL: before lunch; EW: end of the work shift; MB: morning break; SW: start of the work shift; w1: first half of the morning work; w2: second half of the morning work; b2: lunch time; w3: first half of the afternoon work; w4: second half of afternoon work. *The values are significantly different by Student’s t-test (P < 0.05). The error bars represent SD. Nineteen subjects had urine samples collected at six measurement times (SW, MB, BL, AL, AB, EW). The urine biochemical data were analyzed. Average Uosm was larger in the afternoon, but not significant. Usg increased from SW (1.019 g ml−1) to AB (1.024 g ml−1). Usg of AB was significantly higher than SW, MB, and BL (P < 0.05) and Usg of EW was larger than that of SW and BL (P < 0.05) (Table 1). The ratio of workers whose Usg was above the clinically dehydrated level of 1.030 g ml−1 was 5, 16, 11, 21, 26, and 21% at SW, MB, BL, AL, AB, and EW, respectively. The correlation between Usg and Uosm was very high (R = 0.87). Urine sodium concentration corrected by creatinine was significantly lower in AB than samples collected at other shifts and urine sodium concentration corrected by creatinine at SW were significantly larger than those of the other times (Table 1). Discussion The physiological effects of heat stress were monitored for construction workers in Japan during the summer. The average personal WBGT were 27.4, 28.0, 28.5, and 27.3°C for w1, w2, w3, and w4, respectively. Body weight decreased by 1.3% at EW. Average water intake was 52% compared with water loss during work excluding lunch time. UT and Usg were highest in AB. Urine sodium corrected by creatinine decreased significantly from SW to AB. Heat stress As far as we know, this is the first study to measure the thermal work environmental conditions around workers by WBGT monitor. The average outside WBGT in the sun over 3 days of 30.9°C was close to that in studies of other construction workers [31°C (Montazer et al., 2013), 31.4°C (Chang et al., 2009), 30.1°C (Morioka et al., 2006)]. Since the other studies did not measure the environment around workers, it is possible that the measured environmental data did not accurately reflect the work environment. Some subjects would work in the sun, some subjects work in the shade or inside, and others work in both. Measured Ta, Tg, RH, and WBGT by a personal WBGT monitoring instrument were between those of a stationary WBGT placed indoors and outdoors in the sun (Fig. 2). The WBGT of workers in direct sunlight was close to those in a sunny area, and the WBGT in indoor workers was close to that in indoor settings. The differences between maximum and minimum average personal WBGT were 3.1, 3.0, 4.9, and 3.4°C for w1, w2, w3, and w4, respectively, which were not negligible. These data showed that personal monitoring of thermal environmental conditions during work was needed. Heat strain HR is a suitable single index of heat strain (Goldman, 1988), since it reflects the combination of physical work, heat elimination difficulty, and psychological stress. According to ISO 8996 (ISO, 2004a), the contributing factors to a change in HR is dynamic muscular load, static muscular work, heat stress, mental load, and other factors, such as respiratory effects, circadian rhythms, and dehydration (ISO, 2004). To regulate body temperature in a hot work environment, the autonomic nervous system increases blood flow from the core to the skin and triggers sweating. Both the demand of blood flow to muscle by work and to the skin by body temperature regulation increases HR. In this study, the average HR of construction workers in w3 was 112 bpm, significantly higher than average HR at other times in the shift. %HRR, which removed inter-subject variability by age or resting HR from original HR, was also highest in w3. One reason for this is that higher environmental heat stress in afternoon work could activate the autonomic nervous system and HR would increase. Dimri et al. (1980) showed that total metabolic rate increases in high heat stress conditions at the same work output. Ueno et al. (2014) also reported increased metabolic rate by higher Ta. A higher metabolic rate increases body temperature, activates the autonomic system, and increases HR. Another factor is food intake, which is also a contributing factor to increase HR. Sidery and Macdonald reported that HR increased by 5–10 bpm after food intake and lasted for about 2 h (Sidery and Macdonald, 1994). Considering the effect of food, average HR in w3 was at the same level as the other work times. A field study (Bates and Schneider, 2008) of UAE construction workers reported that average HR during work was about 90 bpm in a thermal environment of WBGT over 27.5°C. It is suggested that low humidity, adequate water intake, and self-paced work would help to keep the HR at a safe level despite the high Ta and radiant temperature of the work environment. A field study of construction workers in Taiwan (Chang et al., 2009) and Hong Kong (Wong et al., 2014) found that the average HR of scaffolders (Chang et al., 2009) was 120 bpm and that of bar benders (Wong et al., 2014) was 114 bpm. Our results were close to those of Chang et al. (2009) and Wong et al., (2014). For miners, Kalkowsky and Kampmann (2006) reported that HR exceeded a limit of ‘200-age’ in 61 out of 125 shifts. The World Health Organization (WHO) recommends that a maximum allowable average HR as 110 bpm (WHO, 1969). Our results of construction workers’ HR showed that cardiovascular strain exceeded the WHO limit. The subjects in our study were allocated a designated amount of work that they had to complete by a certain time. Core body temperature was measured by UT and sublingual temperature. In our data, average UT increased significantly by 0.73°C from the start of work to the afternoon break (Fig. 3A, Table 1). According to ACGIH TLV (2017) for heat stress and strain, the limits on core temperature are determined by a maximum temperature of 38°C for unacclimatized workers and 38.5°C for acclimatized workers. In this study, none of the UT samples were over 38.0°C. The average largest increase of the UT from the start of work to the first half of the afternoon work was 0.8°C. Due to circadian rhythms, body temperature differs diurnally by 1°C or more, with the lowest at 4:00 A.M. and highest at 6:00 P.M. Since the work time was approximately from 9:00 A.M. to 5:00 P.M., the amplitude of the diurnal core temperature would be close to 1°C. Some part of the UT change could be explained by circadian rhythm. The next contributing factor is food intake. A large meal was reported to increase core body temperature by 0.3°C (Nielsen, 1987). Furthermore, a hot work environment could increase metabolic rate (Dimri et al., 1980; Ueno et al., 2014) and consequently increase UT (Fig. 3A). Another factor is physical work. The decrease of UT after lunch and a sharp increase after the first half of the afternoon work would be caused by rest and physical work in a hot work environment. UT has been used as an index of body core temperature (Fox et al., 1975; Samples and Abrams, 1984). Fox et al. showed that rectal temperature was higher than UT by 0.33°C. Since the ambient temperature in our study was closer to body temperature than their condition (20°C) and because we used a quicker temperature response thermistor, the measured UT would not be as decreased after urination as in Fox’s study. Since the difference between rectal and measured UT was estimated to be smaller than 0.33°C, UT was a reliable index of core temperature in our study. Samples and Abrams also provided data that the maximum temperature of the voided UT records was close to vaginal temperature. Bates and Schneider (2008) reported that the mean aural temperature of construction workers during work as shown in Fig. 2 in their paper was 36.5°C, though it increased slightly in the afternoon, suggesting that worker heat strain was not severe. Nag et al.’s (2013) field study on body temperature of construction workers in India by using oral temperature showed that 90% of workers were under 38°C and 4% were over 39°C. Nag et al. concluded that the workers regulated their core temperature by pacing themselves. Our research showed the same results as those found by Bates and Schneider (2008) and Nag et al. (2013). On the contrary, Kalkowsky and Kampmann (2006) reported that maximum rectal temperature (Tre) measured by rectal thermal probe exceeded 38.0°C for most miners during work. Brake and Bates (2002) showed field research data about miners whose average maximum core temperature was 38.9°C. Severe heat stress and the heavy physical workload led miners to have a higher core temperature than construction workers. Hydration Hydration status is an important determinant of a person’s heat tolerance. In this study, water intake, body weight loss, Usg, and Uosm were measured as parameters for hydration status. Since the weight of bowel movements was not measured and there were only two occurrences for all subjects, we did not take bowel movements into account. On average, body weight decreased by 1.3% at EW compared to SW. Body weight decreased by more than 2.0% for five workers. Dehydration over 2% of body weight decreases aerobic (Cheuvront et al., 2010) and cognitive performance (Hancock and Vasmatzidis, 2003). A previous study (Peiffer and Abbiss, 2013) showed that 2–4% dehydration by weight loss reduces maximum aerobic power. Physical work capacity has also been reported to decrease with 1–2% dehydration, reducing work performance (Armstrong et al., 1985). Moreover, dehydration decreases the sweating rate (Sawka et al., 1989) and skin blood flow due to reduced blood volume. Decreased heat dissipation from the skin due to dehydration would increase the core temperature of workers (Montain et al., 1995) and elevate the risk of heat stroke. The low rate of fluid intake to water loss during morning work was partly compensated by fluid intake during lunch (Fig. 3D). The average fluid intake during lunch was 0.84 l h−1 70 kg−1, which was four times larger than that of w3. The rate of fluid intake to water loss during the shift would be a little higher than that excluding lunch of 52%. In this study, participant fluid intake was insufficient. To prevent dehydration, it is necessary to drink water frequently during work and also replenish water during lunch. The other hydration indices we used in this study were Usg and Uosm. The mean Usg of 19 subjects whose samples were collected and measured six times in a day increased from 1.019 g ml−1 at SW to 1.024 g ml−1 at EW. In this study, the percentage of hydrated subjects (Usg < 1.020 g ml−1) (Oppliger et al., 2005) of 47% at SW decreased to 21% at EW. A study of miners (Polkinghorne et al., 2013) found that 41% of subjects were hydrated before work and 42% were hydrated after work. The average rate of water intake compared to water loss during work time was about 52% in our study, which could cause a decreased level of hydration in the afternoon. In this field study, we measured physiological indexes without intervention. Since voluntary drinking was reported to lead to insufficient water intake, workers without knowledge of the importance of hydration or instruction to drink water could become dehydrated (Greenleaf and Sargent, 1965). Some previous studies reported on the hydration of construction workers in hot environments. Bates and Schneider (2008) reported that Usg of UAE construction workers was about 1.012 mg ml−1 in the morning, 1.013 at midday, and 1.012 in the afternoon, which meant that workers were slightly overhydrated (Usg < 1.015 g ml−1). The subjects of Bates and Schneider (2008) drank 5.4 l of water during a 12-h shift compared to the 2.6 l that workers in our study drank in an 8-h shift. Miller and Bates (2007) presented data on construction workers whose Usg was 1.018 mg ml−1 in pre-shift, 1.018 mg ml−1 in mid-shift, and 1.018 mg ml−1 in post-shift. Their fluid intake was 1.04 l h−1 and sweat rate was 1.03 l h−1, which maintained a fluid balance. The unchanged Usg of workers in their study (Miller and Bates, 2007; Bates and Schneider, 2008) showed that water intake was comparable to water loss. ACGIH TLV standard of drinking a cup of cool water (about 235 ml) every 20 min during work in a hot environment to prevent heat illness would not be enough for a sweat rate of over 1 l h−1 in a hot environment. Another study of construction workers in Iran (Montazer et al., 2013) reported that average Usg was 1.026 g ml−1 at the start of the workday, 1.027 g ml−1 in the middle, and 1.025 g ml−1 at the end. Usg stayed constant from the beginning to the end. In the paper (Montazer et al., 2013), the workers were asked to drink a specific amount of water during their shift. Similarly, a field study of miners (Brake and Bates, 2003) showed that Usg was kept constant at about 1.025 g ml−1 from the start of work to the end with an average fluid intake at 6.5 l for 10–12.5 h. High Usg at the beginning of work would be caused by insufficient water intake outside of work. Thus, to keep workers adequately hydrated, lost fluid during the shift would have to be replaced and hydration at the start of work would have to be increased. To study the reliability of Usg as a hydration index, Oppliger et al. (2005) compared the criteria of dehydration of Usg over 1.020 g ml−1 and plasma osmolality (Posm) over 290 mOsm kg−1, and found high sensitivity (80% subjects whose Usg was over 1.020 had Posm > 290), but low specificity (31.3% subjects whose Usg was under 1.020 had Posm < 290). Their study showed that workers with a high Usg had a high probability of dehydration, but that low Usg does not guarantee euhydration. Uosm is considered a better index than Usg, because osmotic pressure is not influenced by the dissolved substances in urine. However, analysis of Uosm requires an osmometer installed in a laboratory, making it unsuited for use in the field. On the other hand, Usg can be measured quickly with a portable refractometer. For the collected urine from the subjects in this study, there was a high correlation (R = 0.87) between Uosm and Usg. The mean Uosm of 19 subjects who had all of their samples collected at each measurement increased from 682 mOsm kg−1 to 804 mOsm kg−1. Since the cutoff value of euhydration for Uosm is considered as 700 mOsm kg−1 (Kenefick et al., 2012), the average Uosm showed that the subjects were euhydrated at the start of work and hypohydrated at the end of work. Every urine sample more than 1.030 g ml−1 in Usg was more than 1000 mOsm kg−1 in Uosm. However, there are also limitations in Uosm. Oppliger et al. (2005) reported that Uosm has poor association with body weight loss or Posm. Moreover, Usg or Uosm lags behind Posm during acute dehydration (Popowski et al., 2001). This lagging would reflect the fact that urine indices were the average of previous urination and present urinations. Hyponatremia Hyponatremia, which arises due to loss of sodium by heavy sweating coupled with an intake of a large amount of water or other low sodium drink, sometimes causes severe conditions, including pulmonary edema, respiratory arrest, coma, or death. In this field study, the possibility of hyponatremia for the subjects would be low due to a low intake of beverage and maintenance of the Uso level during work. However, creatinine-adjusted sodium concentration (Vought et al., 1963) in urine decreased significantly during work (Table 1), suggesting a sign of decreased sodium. A mean body weight loss under 0.9% of body weight at the end of work and ample salt intake from food or drink during work would prevent hyponatremia (Hew-Butler et al., 2008). Heat stress standards We referred to the physiological heat strain recommendations proposed by ACGIH TLV guidelines (2017) for cardiac strain of sustained HR in excess of 180 bpm minus the individual’s age, body core temperature of 38.5°C for a medically selected and acclimatized person, and weight loss over a shift of 1.5% of body weight. In addition to ACGIH TLV guidelines, a clinical guideline of Usg over 1.030 mg ml−1, which is used as a criterion of clinical dehydration by the Australian Pathology Association (Bates and Schneider, 2008), was included. Among four referred heat strain recommendations, no subjects were over the body core temperature of 38.5°C. Therefore, a Venn diagram was drawn for 23 subjects based on three recommendations, excluding body temperature, to clarify the relationships among the recommendations (Fig. 4). Six of the 23 workers exceeded the recommendations for HR, 11 exceeded body weight loss, and 8 exceeded Usg. Only four workers were under the limits for all the four recommendations. There were no subjects whose physiological indexes exceeded all the four recommendations. These results showed that heat strain of the subjects in this study was not severe. Figure 4 shows that gold heat strain recommendations which include all recommendations did not exist. Although weight loss and Usg are classified under the same hydration recommendations, only two subjects overlapped. It also could be considered that not exceeding one criterion of heat strain does not guarantee that there is little risk of a heat-related disorder. Examining more than one physiological parameter is needed to identify workers at risk of heat stroke and ensure adequate protection. Figure 4. View largeDownload slide Venn diagram of the overlap of physiological guidelines limiting the heat strain by ACGIH of weight loss, HR, and clinically dehydrated urine specific gravity for 23 subjects. (I) The subjects whose heart rate was over 180—age for more than 3 min, (II) those whose weight decreased more than 1.5% in the shift, (III) those whose urine specific gravity was over 1.030 mg ml−1 were counted. The number in the figure stands for the subject’s number corresponding to each area of Venn diagram. Figure 4. View largeDownload slide Venn diagram of the overlap of physiological guidelines limiting the heat strain by ACGIH of weight loss, HR, and clinically dehydrated urine specific gravity for 23 subjects. (I) The subjects whose heart rate was over 180—age for more than 3 min, (II) those whose weight decreased more than 1.5% in the shift, (III) those whose urine specific gravity was over 1.030 mg ml−1 were counted. The number in the figure stands for the subject’s number corresponding to each area of Venn diagram. Limitations The use of UT as a measure of deep body temperature can be constrained as urination times can be limited. This makes it difficult to detect quick changes of body temperature. However, the results of this study showed that UT was sensitive to body temperature changes (Fig. 3A). The benefit of estimating body core temperature by UT is to free the subjects from the stress of restrictions imposed by body temperature measurement. An instrument to measure UT in a toilet would provide a good tool to allow workers to check deep body temperature on their own. An additional limitation was that we did not have a chance to measure the weight of a lunch meal. If the weight of the lunch that the subjects ate was available, it would be possible to calculate the sweat rate during lunch time (Fig. 3D). Conclusions In Japan, the number of construction workers who died from heat stroke during summer work was the largest in all kinds of industry. To survey the heat strain of construction workers, environmental conditions, HR, water intake, body weight, UT, urine specific gravity (Usg), urine osmolality (Uosm), urine sodium (Uso), and urine creatinine were measured. The heat strain of subjects was highest in the first half of afternoon work (w3). The average work environment, measured on the helmet of each subject, was 28.5°C in w3. The rate of water intake to water loss excluding lunch time was 52%. The average UT, Usg, %HRR, and sweat rate were 37.5°C, 1.024 g ml−1, 35%, and 0.55 l h−1 70 kg−1, respectively, in w3. Average Usg increased during the shift, reflecting the low rate of fluid replacement. Compared with ACGIH TLV physiological recommendations for HR, weight loss, core temperature, and clinical limit for Usg, 19 out of 23 subjects were over at least one of these recommendations (Fig. 4). No subjects exceeded the core temperature recommendation of 38.0°C. A gold-standard heat strain recommendations that include all recommendations does not exist (Fig. 4). Therefore, to prevent heat-related disorders in construction workers, many physiological indexes about heat strain should be checked. Additionally, workers should be encouraged to drink enough water and salt and pace themselves when working in a hot environment. Funding Funding for this project (principal investigator: Dr Shin-ichi Sawada) was provided by Ministry of Health, Labour and Welfare. Acknowledgements The authors declare no conflict of interest relating to the material presented in this article. Its contents, including any opinions and/or conclusions expressed, are solely those of the authors. 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Int J Occup Saf Ergon ; 8 : 83 – 93 . Google Scholar CrossRef Search ADS PubMed © The Author(s) 2018. Published by Oxford University Press on behalf of the British Occupational Hygiene Society. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices)

Journal

Annals of Work Exposures and Health (formerly Annals Of Occupational Hygiene) – Oxford University Press

Published: Mar 24, 2018

References

  • Occupational heat exposure
    Adelakun