Time-motion analysis as a novel approach for evaluating the impact of environmental heat exposure on labor loss in agriculture workers
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
Standard
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 tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
Harvard
APA
Vancouver
Author
Bibtex
}
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