Does obesity contribute to non-fatal occupational injury? Evidence from the National Longitudinal Survey of Youth

Lin, Tin-Chi; Verma, Santosh K.; Courtney, Theodore K.

doi:10.5271/sjweh.3347

Cited by 28 publications

(25 citation statements)

References 50 publications

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“…Using the NLSY79 to assess injury risk among all workers, researchers have found an association between injuries and education, overtime, race/ethnicity, gender, marital status, and obesity. 5,6,18,21,37 Within construction, overtime and shift work were found to be associated with an increased risk of injury. 9 While these study designs may be sound, they were restricted to focus on one risk factor in one study.…”

Section: Introductionmentioning

confidence: 99%

Occupational and non-occupational factors associated with work-related injuries among construction workers in the USA

Dong

Wang

Largay

2015

International Journal of Occupational and Environmental Health

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Background: Many factors contribute to occupational injuries. However, these factors have been compartmentalized and isolated in most studies. Objective: To examine the relationship between work-related injuries and multiple occupational and nonoccupational factors among construction workers in the USA. Methods: Data from the 1988-2000 National Longitudinal Survey of Youth, 1979 cohort (N512,686) were analyzed. Job exposures and health behaviors were examined and used as independent variables in four multivariate logistic regression models to identify associations with occupational injuries. Results: After controlling for demographic variables, occupational injuries were 18% (95% CI: 1.04-1.34) more likely in construction than in non-construction. Blue-collar occupations, job physical efforts, multiple jobs, and long working hours accounted for the escalated risk in construction. Smoking, obesity/overweight, and cocaine use significantly increased the risk of work-related injury when demographics and occupational factors were held constant. Conclusions: Workplace injuries are better explained by simultaneously examining occupational and nonoccupational characteristics.

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Section: Introductionmentioning

confidence: 99%

Occupational and non-occupational factors associated with work-related injuries among construction workers in the USA

Dong

Wang

Largay

2015

International Journal of Occupational and Environmental Health

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“…21e23 This is also true within the civilian work force as worker compensations claims have been shown to be highest amongst those with higher BMI and in physically demanding jobs. 24,25 Another study looked at risk of falls and showed a linear relationship with higher obesity and increasing risk of fall-related injuries. 26 Fall/near fall injuries are a leading cause of hospitalization for injuries in military members.…”

Section: Discussionmentioning

confidence: 98%

Occupation and other risk factors for injury among enlisted U.S. Army Soldiers

et al. 2015

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“…Both analyses take account of repeated measurement of observations on the same individual. Random effect models describe subject-specific estimates, and GEE describes the population averaged estimates [35]. We conducted and compared the estimates for both methods.…”

Section: Methodsmentioning

confidence: 99%

Meal frequencies in early adolescence predict meal frequencies in late adolescence and early adulthood

2013

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BackgroundHealth and risk behaviours tend to be maintained from adolescence into adulthood. There is little knowledge on whether meal frequencies in adolescence are maintained into adulthood. We investigated whether breakfast, lunch and evening meal frequencies in early adolescence predicted meal frequencies in late adolescence and in early adulthood. Further, the modifying effect of gender and adolescent family structure were investigated.MethodsNational representative sample of 15-year-olds in Denmark with 4 and 12 year follow-up studies with measurement of breakfast, lunch and evening meal frequencies. A total of 561 persons completed questionnaires at age 15 years (baseline 1990, n=847, response rate 84.6%), age 19 years (n=729, response rate 73.2%) and age 27 years (n=614, response rate 61.6%).ResultsLow meal frequencies at age 15 years was a significant predictor for having low meal frequencies at age 19 years (odds ratio (OR, 95% CI)) varying between 2.11, 1.33-3.34 and 7.48, 3.64-15.41). Also, low meal frequencies at age 19 years predicted low meal frequencies at age 27 years (OR varying between 2.26, 1.30-3.91 and 4.38, 2.36-8.13). Significant predictions over the full study period were seen for low breakfast frequency and low lunch frequency (OR varying between 1.78, 1.13-2.81 and 2.58, 1.31-5.07). Analyses stratified by gender showed the same patterns (OR varying between 1.88, 1.13-3.14 and 8.30, 2.85-24.16). However, the observed predictions were not statistical significant among men between age 15 and 27 years. Analyses stratified by adolescent family structure revealed different lunch predictions in strata.ConclusionsHaving low meal frequencies in early adolescence predicted low meal frequencies in late adolescence and early adulthood. We propose that promotion of regular meals become a prioritised issue within health education.

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Does obesity contribute to non-fatal occupational injury? Evidence from the National Longitudinal Survey of Youth

Cited by 28 publications

References 50 publications

Occupational and non-occupational factors associated with work-related injuries among construction workers in the USA

Occupational and non-occupational factors associated with work-related injuries among construction workers in the USA

Occupation and other risk factors for injury among enlisted U.S. Army Soldiers

Meal frequencies in early adolescence predict meal frequencies in late adolescence and early adulthood

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