Time-motion analysis as a novel approach for evaluating the impact of environmental heat exposure on labor loss in agriculture workers

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Time-motion analysis as a novel approach for evaluating the impact of environmental heat exposure on labor loss in agriculture workers. / Ioannou, Leonidas G; Tsoutsoubi, Lydia; Samoutis, George; Bogataj, Lucka Kajfez; Kenny, Glen P; Nybo, Lars; Kjellstrom, Tord; Flouris, Andreas D.

I: Temperature, Bind 4, Nr. 3, 2017, s. 330-340.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Harvard

Ioannou, LG, Tsoutsoubi, L, Samoutis, G, Bogataj, LK, Kenny, GP, Nybo, L, Kjellstrom, T & Flouris, AD 2017, 'Time-motion analysis as a novel approach for evaluating the impact of environmental heat exposure on labor loss in agriculture workers', Temperature, bind 4, nr. 3, s. 330-340. https://doi.org/10.1080/23328940.2017.1338210

APA

Ioannou, L. G., Tsoutsoubi, L., Samoutis, G., Bogataj, L. K., Kenny, G. P., Nybo, L., Kjellstrom, T., & Flouris, A. D. (2017). Time-motion analysis as a novel approach for evaluating the impact of environmental heat exposure on labor loss in agriculture workers. Temperature, 4(3), 330-340. https://doi.org/10.1080/23328940.2017.1338210

Vancouver

Ioannou LG, Tsoutsoubi L, Samoutis G, Bogataj LK, Kenny GP, Nybo L o.a. Time-motion analysis as a novel approach for evaluating the impact of environmental heat exposure on labor loss in agriculture workers. Temperature. 2017;4(3):330-340. https://doi.org/10.1080/23328940.2017.1338210

Author

Ioannou, Leonidas G ; Tsoutsoubi, Lydia ; Samoutis, George ; Bogataj, Lucka Kajfez ; Kenny, Glen P ; Nybo, Lars ; Kjellstrom, Tord ; Flouris, Andreas D. / Time-motion analysis as a novel approach for evaluating the impact of environmental heat exposure on labor loss in agriculture workers. I: Temperature. 2017 ; Bind 4, Nr. 3. s. 330-340.

Bibtex

@article{3d3de9e73c0244469b33d18d814659fc,
title = "Time-motion analysis as a novel approach for evaluating the impact of environmental heat exposure on labor loss in agriculture workers",
abstract = "Introduction: In this study we (i) introduced time-motion analysis for assessing the impact of workplace heat on the work shift time spent doing labor (WTL) of grape-picking workers, (ii) examined whether seasonal environmental differences can influence their WTL, and (iii) investigated whether their WTL can be assessed by monitoring productivity or the vineyard manager's estimate of WTL. Methods: Seven grape-picking workers were assessed during the summer and/or autumn via video throughout four work shifts. Results: Air temperature (26.8 ± 4.8°C), wet bulb globe temperature (WBGT; 25.2 ± 4.1°C), universal thermal climate index (UTCI; 35.2 ± 6.7°C), and solar radiation (719.1 ± 187.5 W/m(2)) were associated with changes in mean skin temperature (1.7 ± 1.8°C) (p < 0.05). Time-motion analysis showed that 12.4% (summer 15.3% vs. autumn 10.0%; p < 0.001) of total work shift time was spent on irregular breaks (WTB). There was a 0.8%, 0.8%, 0.6%, and 2.1% increase in hourly WTB for every degree Celsius increase in temperature, WBGT, UTCI, and mean skin temperature, respectively (p < 0.01). Seasonal changes in UTCI explained 64.0% of the seasonal changes in WTL (p = 0.017). Productivity explained 36.6% of the variance in WTL (p < 0.001), while the vineyard manager's WTL estimate was too optimistic (p < 0.001) and explained only 2.8% of the variance in the true WTL (p = 0.456). Conclusion: Time-motion analysis accurately assesses WTL, evaluating every second spent by each worker during every work shift. The studied grape-picking workers experienced increased workplace heat, leading to significant labor loss. Monitoring productivity or the vineyard manager's estimate of each worker's WTL did not completely reflect the true WTL in these grape-picking workers.",
keywords = "Europe, Heat strain, Heat stress, Irregular work break, Productivity, WBGT, UTCI",
author = "Ioannou, {Leonidas G} and Lydia Tsoutsoubi and George Samoutis and Bogataj, {Lucka Kajfez} and Kenny, {Glen P} and Lars Nybo and Tord Kjellstrom and Flouris, {Andreas D}",
note = "CURIS 2017 NEXS 254",
year = "2017",
doi = "10.1080/23328940.2017.1338210",
language = "English",
volume = "4",
pages = "330--340",
journal = "Temperature",
issn = "2332-8940",
publisher = "Taylor & Francis",
number = "3",

}

RIS

TY - JOUR

T1 - Time-motion analysis as a novel approach for evaluating the impact of environmental heat exposure on labor loss in agriculture workers

AU - Ioannou, Leonidas G

AU - Tsoutsoubi, Lydia

AU - Samoutis, George

AU - Bogataj, Lucka Kajfez

AU - Kenny, Glen P

AU - Nybo, Lars

AU - Kjellstrom, Tord

AU - Flouris, Andreas D

N1 - CURIS 2017 NEXS 254

PY - 2017

Y1 - 2017

N2 - Introduction: In this study we (i) introduced time-motion analysis for assessing the impact of workplace heat on the work shift time spent doing labor (WTL) of grape-picking workers, (ii) examined whether seasonal environmental differences can influence their WTL, and (iii) investigated whether their WTL can be assessed by monitoring productivity or the vineyard manager's estimate of WTL. Methods: Seven grape-picking workers were assessed during the summer and/or autumn via video throughout four work shifts. Results: Air temperature (26.8 ± 4.8°C), wet bulb globe temperature (WBGT; 25.2 ± 4.1°C), universal thermal climate index (UTCI; 35.2 ± 6.7°C), and solar radiation (719.1 ± 187.5 W/m(2)) were associated with changes in mean skin temperature (1.7 ± 1.8°C) (p < 0.05). Time-motion analysis showed that 12.4% (summer 15.3% vs. autumn 10.0%; p < 0.001) of total work shift time was spent on irregular breaks (WTB). There was a 0.8%, 0.8%, 0.6%, and 2.1% increase in hourly WTB for every degree Celsius increase in temperature, WBGT, UTCI, and mean skin temperature, respectively (p < 0.01). Seasonal changes in UTCI explained 64.0% of the seasonal changes in WTL (p = 0.017). Productivity explained 36.6% of the variance in WTL (p < 0.001), while the vineyard manager's WTL estimate was too optimistic (p < 0.001) and explained only 2.8% of the variance in the true WTL (p = 0.456). Conclusion: Time-motion analysis accurately assesses WTL, evaluating every second spent by each worker during every work shift. The studied grape-picking workers experienced increased workplace heat, leading to significant labor loss. Monitoring productivity or the vineyard manager's estimate of each worker's WTL did not completely reflect the true WTL in these grape-picking workers.

AB - Introduction: In this study we (i) introduced time-motion analysis for assessing the impact of workplace heat on the work shift time spent doing labor (WTL) of grape-picking workers, (ii) examined whether seasonal environmental differences can influence their WTL, and (iii) investigated whether their WTL can be assessed by monitoring productivity or the vineyard manager's estimate of WTL. Methods: Seven grape-picking workers were assessed during the summer and/or autumn via video throughout four work shifts. Results: Air temperature (26.8 ± 4.8°C), wet bulb globe temperature (WBGT; 25.2 ± 4.1°C), universal thermal climate index (UTCI; 35.2 ± 6.7°C), and solar radiation (719.1 ± 187.5 W/m(2)) were associated with changes in mean skin temperature (1.7 ± 1.8°C) (p < 0.05). Time-motion analysis showed that 12.4% (summer 15.3% vs. autumn 10.0%; p < 0.001) of total work shift time was spent on irregular breaks (WTB). There was a 0.8%, 0.8%, 0.6%, and 2.1% increase in hourly WTB for every degree Celsius increase in temperature, WBGT, UTCI, and mean skin temperature, respectively (p < 0.01). Seasonal changes in UTCI explained 64.0% of the seasonal changes in WTL (p = 0.017). Productivity explained 36.6% of the variance in WTL (p < 0.001), while the vineyard manager's WTL estimate was too optimistic (p < 0.001) and explained only 2.8% of the variance in the true WTL (p = 0.456). Conclusion: Time-motion analysis accurately assesses WTL, evaluating every second spent by each worker during every work shift. The studied grape-picking workers experienced increased workplace heat, leading to significant labor loss. Monitoring productivity or the vineyard manager's estimate of each worker's WTL did not completely reflect the true WTL in these grape-picking workers.

KW - Europe

KW - Heat strain

KW - Heat stress

KW - Irregular work break

KW - Productivity

KW - WBGT

KW - UTCI

U2 - 10.1080/23328940.2017.1338210

DO - 10.1080/23328940.2017.1338210

M3 - Journal article

C2 - 28944274

VL - 4

SP - 330

EP - 340

JO - Temperature

JF - Temperature

SN - 2332-8940

IS - 3

ER -

ID: 183762562