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时间动作分析作为一种评估环境热暴露对农业工人劳动力损失影响的新方法。

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

作者信息

Ioannou Leonidas G, Tsoutsoubi Lydia, Samoutis George, Bogataj Lucka Kajfez, Kenny Glen P, Nybo Lars, Kjellstrom Tord, Flouris Andreas D

机构信息

FAME Laboratory, School of Exercise Science, University of Thessaly, Thessaly, Greece.

Medical School, University of Nicosia, Nicosia, Cyprus.

出版信息

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

DOI:10.1080/23328940.2017.1338210
PMID:28944274
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5605156/
Abstract

: 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. : Seven grape-picking workers were assessed during the summer and/or autumn via video throughout four work shifts. : 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) were associated with changes in mean skin temperature (1.7 ± 1.8°C) ( < 0.05). Time-motion analysis showed that 12.4% (summer 15.3% vs. autumn 10.0%; < 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 ( < 0.01). Seasonal changes in UTCI explained 64.0% of the seasonal changes in WTL ( = 0.017). Productivity explained 36.6% of the variance in WTL ( < 0.001), while the vineyard manager's WTL estimate was too optimistic ( < 0.001) and explained only 2.8% of the variance in the true WTL ( = 0.456). : 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.

摘要

在本研究中,我们:(i) 引入了时间动作分析,以评估工作场所高温对葡萄采摘工人从事劳动的轮班时间(WTL)的影响;(ii) 研究季节性环境差异是否会影响他们的WTL;(iii) 调查是否可以通过监测生产率或葡萄园经理对WTL的估计来评估他们的WTL。在夏季和/或秋季,通过视频对7名葡萄采摘工人的4个轮班进行了评估。气温(26.8±4.8°C)、湿球黑球温度(WBGT;25.2±4.1°C)、通用热气候指数(UTCI;35.2±6.7°C)和太阳辐射(719.1±187.5 W/m)与平均皮肤温度变化(1.7±1.8°C)相关(P<0.05)。时间动作分析表明,总轮班时间的12.4%(夏季为15.3%,秋季为10.0%;P<0.001)用于非规律性休息(WTB)。温度、WBGT、UTCI和平均皮肤温度每升高1摄氏度,每小时的WTB分别增加0.8%、0.8%、0.6%和2.1%(P<0.01)。UTCI的季节性变化解释了WTL季节性变化的64.0%(P=0.017)。生产率解释了WTL方差的36.6%(P<0.001),而葡萄园经理对WTL的估计过于乐观(P<0.001),仅解释了真实WTL方差的2.8%(P=0.456)。时间动作分析准确地评估了WTL,评估了每个工人在每个轮班期间花费的每一秒。所研究的葡萄采摘工人经历了工作场所高温增加,导致了显著的劳动力损失。监测生产率或葡萄园经理对每个工人WTL的估计并不能完全反映这些葡萄采摘工人的真实WTL。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7469/5605156/4073697f6348/ktmp-04-03-1338210-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7469/5605156/23cb2149428d/ktmp-04-03-1338210-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7469/5605156/444507c55a45/ktmp-04-03-1338210-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7469/5605156/5c1981e8b19a/ktmp-04-03-1338210-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7469/5605156/bfb10da67361/ktmp-04-03-1338210-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7469/5605156/4acbe03e44f3/ktmp-04-03-1338210-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7469/5605156/4073697f6348/ktmp-04-03-1338210-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7469/5605156/23cb2149428d/ktmp-04-03-1338210-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7469/5605156/444507c55a45/ktmp-04-03-1338210-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7469/5605156/5c1981e8b19a/ktmp-04-03-1338210-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7469/5605156/bfb10da67361/ktmp-04-03-1338210-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7469/5605156/4acbe03e44f3/ktmp-04-03-1338210-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7469/5605156/4073697f6348/ktmp-04-03-1338210-g006.jpg

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