Time-motion analysis as a novel approach for evaluating the impact of environmental heat exposure on labor loss in agriculture workers. Issue 3 (3rd July 2017)

• Record Type: Journal Article
• Authors: Ioannou, Leonidas G.; Tsoutsoubi, Lydia; Samoutis, George; Bogataj, Lucka Kajfez; Kenny, Glen P.; Nybo, Lars; Kjellstrom, Tord; Flouris, Andreas D.
• Is Part Of: Temperature. Volume 4:Issue 3(2017)
• Page Start: 330
• Page End: 340
• Publication Date: 2017-07-03
• Subjects: Europe -- heat strain -- heat stress -- irregular work break -- productivity -- WBGT -- UTCI; Thermobiology -- Periodicals; Thermotherapy -- Periodicals; Body temperature -- Regulation -- Periodicals; Body temperature -- Regulation; Thermobiology; Thermotherapy; Periodicals; 571.46
• DOI: 10.1080/23328940.2017.1338210
• Languages: English
• ISSNs: 2332-8940

Abstract

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.