A comparison of the correlation between heat stress indices (UTCI, WBGT, WBDT, TSI) and physiological parameters of workers in Iran

Shirvan, Hossein Elahi; Hemmatjo, Rasoul; Nadri, Farshad; Jahani, Yunes; Jamshidzadeh, Kobra; Paydar, Parisa

doi:10.1016/j.wace.2019.100213

Cited by 55 publications

(26 citation statements)

References 15 publications

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“…Stress causes several adverse symptoms such as insomnia, headache, fatigue, anxiety, gastrointestinal upset and decreased immunity, as well as increased family conflicts, decreased quality of work, interpersonal disorders and other negative effects 20 , 21 . Furthermore, Harmful factors in the workplace, such as noise and heat, cause stress and the release of stress hormones in the body 22 , 23 , 24 . Medical staffs especially that work in hospitals that provide primary care to patients with COVID-19 are not only at higher risk of infection but also more vulnerable to mental health.…”

Section: Introductionmentioning

confidence: 99%

Occupational stress assessment of health care workers (HCWs) facing COVID-19 patients in Kerman province hospitals in Iran

dameneh

Esmaeili

Kazemi

et al. 2021

Heliyon

Self Cite

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Section: Introductionmentioning

confidence: 99%

Occupational stress assessment of health care workers (HCWs) facing COVID-19 patients in Kerman province hospitals in Iran

dameneh

Esmaeili

Kazemi

et al. 2021

Heliyon

Self Cite

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“…For TEMP max , WBGT max , and UTCI max , seven, ten, and eight prefectures among the top ten belonged to the regions of Kinki and westward, with values ranging from 31.5 to 32.1 • C, 28.6 to 30.1 • C, and 39.5 to 40.2 • C, respectively. These ranges in the WBGT and UTCI correspond to 'very hot or danger' (28-31 • C) and 'very strong heat stress' (38-46 • C), respectively [39,40]. This indicates the significant increase in heatstroke risk in spite of the three-month (July-September) average of the daily maximum value; as the UTCI can be regarded as a 'feels like' temperature, residents were exposed to dangerous conditions in the summer climate in many prefectures of western Japan.…”

Section: Decade Distributions In 47-prefecture Scalementioning

confidence: 99%

Assessing the Climatological Relationship between Heatstroke Risk and Heat Stress Indices in 47 Prefectures in Japan

Iwamoto

Ohashi

2021

GeoHazards

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This study provides a decade-long link between summer heatstroke incidence and certain heat stress indices in 47 prefectures of Japan. The results for each prefecture were determined from the age-adjusted heatstroke incidence rate (TRadj) with heatstroke patients transported by ambulance, as well as from the daily maximum temperature (TEMPmax), maximum wet-bulb globe temperature (WBGTmax), and maximum universal thermal climate index (UTCImax) recorded from July to September of 2010–2019. The UTCImax relatively increased the vulnerability in many prefectures of northern Japan more distinctly than the other indices. In the following analysis, the ratio of the TRadj of the hottest to coolest months using the UTCImax was defined as the heatstroke risk of the hottest to coolest (HRHC). Overall, the HRHC varied approximately from 20 to 40 in many prefectures in the past decade. In contrast, for the same analysis performed in each month, HRHC ratios in July and August fell within 2–4 in many prefectures, whereas in September, the average and maximum HRHC ratios for all prefectures were 7.0 and 32.4, respectively. This difference can be related to the large difference in UTCImax between the maximum and minimum for a decade.

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“…Therefore, the Comfort Index should be able to present changes in human sensory experience according to changes in values. Based on these conditions, Daylight Glare Probability (DGP) and Predicted Mean Vote (PMV) techniques were finally selected [14][15][16][17].…”

Section: Analysis Evaluation Indices Of Ks a 6300mentioning

confidence: 99%

Applicability of Assessment Indices for Hanok-User Sensory Comfort Based on Visual and Tactile Comfort Evaluation Indicators

Choe

Han

2021

Sustainability

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This study aimed to present an evaluation system to assess comfort that reflects the unique value of vernacular architecture. For this purpose, the background, purpose, evaluation items, and evaluation methods of Korean Standard-Basic Part: 6300-1, 2 (KS A 6300) were analyzed. As a result, the weakness was found in the KS system that there was no method to evaluate the user’s human sensory comfort. To overcome this problem, the contents of KS A 6300-1, 2 were analyzed, and evaluation indices were categorized to assess the comfort of human sensory experience. A comfort assessment index was then derived to evaluate the visual and tactile comfort of the Korean traditional house by analyzing previous research and systems. To assess the possibility of using the Hanok evaluation system for the derived comfort indices, the actual building environmental and user data were collected for one year. Based on the previous step, Predicted Mean Vote (PMV) and Daylight Glare Probability (DGP) were calculated, and at the same time, a comparative analysis was conducted with the collected user data. As a result, DGP showed a tendency of changing user comfort and an error of 7 to 8% regardless of region, while PMV showed a tendency similar to the change in user discomfort response rate. Accordingly, it was concluded that each evaluation index could be used for the comfort evaluation of Hanok.

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A comparison of the correlation between heat stress indices (UTCI, WBGT, WBDT, TSI) and physiological parameters of workers in Iran

Cited by 55 publications

References 15 publications

Occupational stress assessment of health care workers (HCWs) facing COVID-19 patients in Kerman province hospitals in Iran

Occupational stress assessment of health care workers (HCWs) facing COVID-19 patients in Kerman province hospitals in Iran

Assessing the Climatological Relationship between Heatstroke Risk and Heat Stress Indices in 47 Prefectures in Japan

Applicability of Assessment Indices for Hanok-User Sensory Comfort Based on Visual and Tactile Comfort Evaluation Indicators

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