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Temperature (Austin). 2017 Jul 12;4(3):330-340. doi: 10.1080/23328940.2017.1338210. eCollection 2017.

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

Author information

1
FAME Laboratory, School of Exercise Science, University of Thessaly, Thessaly, Greece.
2
Medical School, University of Nicosia, Nicosia, Cyprus.
3
Biotehnical Faculty, University of Ljubljana, Ljubljana, Slovenia.
4
Human and Environmental Physiology Research Unit, School of Human Kinetics, University of Ottawa, Ottawa, ON, Canada.
5
Department of Nutrition, Exercise and Sports, University of Copenhagen, Copenhagen, Denmark.
6
Centre for Technology Research and Innovation (CETRI), Limassol, Cyprus.

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/m2) 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; UTCI; WBGT; heat strain; heat stress; irregular work break; productivity

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