Relationship between energy expenditure and productivity of sugar cane cutters and stackers.
The main aim of this study was to measure the energy expenditure of sugar cane cutters and stackers during a normal working day and to relate this to their productivity (tonnes of cane cut or stacked per day). A secondary aim of the study was to relate the food and fluid ingestion of the workers during the day to energy expenditure, productivity and changes in body mass. Cutters (n = 12) and stackers (n = 12), who were randomly selected from all the workers (n = 50) on a Natal sugar estate in South Africa, wore heart rate monitors for the entire working day (7 h +/- 30 min). On a separate occasion, all subjects underwent treadmill exercise tests in which oxygen consumption (VO2) and heart rate (HR) were measured simultaneously. A VO2-HR regression equation was calculated for each subject. Based on this regression equation, energy expenditure (kJ) for the working day was calculated for each subject. There was no difference in the mean productivity of the cutters (9.0 +/- 0.7 tonnes) compared to the stackers (9.0 +/- 0.5 tonnes). Both groups expended a large and similar amount of energy during the working day (cutters = 11,695 +/- 1288 kJ; stackers 14,127 +/- 1710 kJ). They ingested similar amounts of energy while working (cutters = 5179 +/- 161 kJ; stackers = 5281 +/- 324 kJ). The best predictor of productivity was the length of the working day (r = 0.63), followed by the energy expended (r = 0.60). Despite the large amount of fluid ingested (up to 6.0 litres/day), some workers lost more than 3% of their body weight.(ABSTRACT TRUNCATED AT 250 WORDS)
Lambert
M I
MI
MRC/UCT Bioenergetics of Exercise Research Unit, University of Cape Town Medical School, Observatory, South Africa.
Cheevers
E J
EJ
Coopoo
Y
Y
D000328:Adult; D000383:Agriculture; D001835:Body Weight; D004326:Drinking; D004435:Eating; D004526:Efficiency; D004734:Energy Metabolism; D006801:Humans; D008297:Male; D016272:Occupational Health; D011897:Random Allocation; D012044:Regression Analysis