2017
DOI: 10.1016/j.shaw.2016.05.005
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Beating Obesity: Factors Associated with Interest in Workplace Weight Management Assistance in the Mining Industry

Abstract: BackgroundRates of overweight and obese Australians are high and continue to rise, putting a large proportion of the population at risk of chronic illness. Examining characteristics associated with preference for a work-based weight-loss program will enable employers to better target programs to increase enrolment and benefit employees' health and fitness for work.MethodsA cross-sectional survey was undertaken at two Australian mining sites. The survey collected information on employee demographics, health cha… Show more

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Cited by 14 publications
(16 citation statements)
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“…The prevalence of overweight and obesity in the general population is 67%, with 36% being overweight and 31% obese (Australian Bureau of Statistics, 2019). Similar levels of overweight and obesity, 40% and 28%, respectively, have been reported in the Australian mining industry (Street and Thomas, 2017). Therefore, we anticipate similar levels of overweight and obesity in this study.…”
Section: Bodyweightsupporting
confidence: 85%
“…The prevalence of overweight and obesity in the general population is 67%, with 36% being overweight and 31% obese (Australian Bureau of Statistics, 2019). Similar levels of overweight and obesity, 40% and 28%, respectively, have been reported in the Australian mining industry (Street and Thomas, 2017). Therefore, we anticipate similar levels of overweight and obesity in this study.…”
Section: Bodyweightsupporting
confidence: 85%
“…These results illustrate the systemic nature of overweight and obesity within the NSW coal mining industry; and identify potential factors, whether it be workplace, diet or exercise that may compound this issue. Whilst the results are alarming, this trend has been previously documented both in the Australian mining industry [ 13 , 29 ], as well as other blue-collar male dominated employment sectors (construction and manufacturing) in Australia [ 30 , 31 ].…”
Section: Discussionmentioning
confidence: 91%
“…The factors that contribute for obesity are reduced exercise, dietary intake, overindulgence in energydense, dietary composition and changing lifestyle. Prediction of Women obesity [2] at early age will reduce the risk of being obese. The objective of this work is to propose a framework for predicting obesity in women and the framework uses Naïve Baye's algorithm for prediction.…”
Section: Introductionmentioning
confidence: 99%