Obesity and Its Relationship with Occupational Injury in the Canadian Workforce

Janssen, Ian; Bacon, Eric; Pickett, William

doi:10.1155/2011/531403

Cited by 38 publications

(36 citation statements)

References 18 publications

(22 reference statements)

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“…Although shorter sleep durations or higher BMI have been generally associated with increased work-related injury risk (Chau et al, 2004;Janssen et al, 2011;Kling et al, 2010;Lombardi et al, 2010;Pollack & Cheskin, 2007;Schulte et al, 2008), this is the first large US population-based study that has examined these two risk factors simultaneously to determine if they affect injury risk independently (e.g., additive effect) or if BMI modifies the effects of short sleep (or vice versa) on injury risk (e.g., interactive effect). Although we found no statistically significant interactive effect among sleep duration and BMI, their individual associations with injury risk are generally consistent with the findings of previously published studies that examined these factors separately (Chau et al, 2004;Connor et al, 2001;Dembe et al, 2005;Folkard et al, 2005;Janssen et al, 2011;Lombardi et al, 2010;Melamed & Oksenberg, 2002;Pollack & Cheskin, 2007;Schulte et al, 2008;Teran-Santos et al, 1999;Virtanen et al, 2009;Williamson et al, 2011).…”

Section: Discussionmentioning

confidence: 96%

“…Additionally, Schmier et al (2006) demonstrated that overweight or obese employees had not only a higher injury risk, but also higher sick leave or disability use, and health care costs, based on claims data analyses. In a population study of Canadian workers, obese workers were found to have injury risks that were 40-49% higher than normal-weight workers (Janssen et al, 2011), and the effect was strongest among sedentary workers, women, and those ≥40 yrs of age. However, a review by Pollack and Cheskin (2007) points out the need to further examine the association between obesity and traumatic injury risk using studies with sufficient sample size that control for confounding variables.…”

Section: Introductionmentioning

confidence: 98%

“…Higher BMI and obesity have been shown to increase injury risk in vehicle drivers (Whitlock et al, 2003) and occupational settings (Chau et al, 2004;Janssen et al, 2011;Pollack & Cheskin, 2007;Schulte et al, 2008). Compared to workers with healthy weight, obese workers (BMI ≥30) were reported to have a higher risk of falls, sprains, and strains, and general occupational injury (Chau et al, 2004).…”

Section: Introductionmentioning

confidence: 99%

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Independent Effects of Sleep Duration and Body Mass Index on the Risk of a Work-Related Injury: Evidence From the US National Health Interview Survey (2004–2010)

Lombardi

Wirtz²,

Willetts

et al. 2012

Chronobiology International

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Fatigue has been linked to adverse safety outcomes, and poor quality or decreased sleep has been associated with obesity (higher body mass index, BMI). Additionally, higher BMI is related to an increased risk for injury; however, it is unclear whether BMI modifies the effect of short sleep or has an independent effect on work-related injury risk. To answer this question, the authors examined the risk of a work-related injury as a function of total daily sleep time and BMI using the US National Health Interview Survey (NHIS). The NHIS is an in-person household survey using a multistage, stratified, clustered sample design representing the US civilian population. Data were pooled for the 7-yr survey period from 2004 to 2010 for 101 891 "employed" adult subjects (51.7%; 41.1 ± yrs of age [mean ± SEM]) with data on both sleep and BMI. Weighted annualized work-related injury rates were estimated across a priori defined categories of BMI: healthy weight (BMI: <25), overweight (BMI: 25-29.99), and obese (BMI: ≥30) and also categories of usual daily sleep duration: <6, 6-6.99, 7-7.99, 8-8.99, and ≥9 h. To account for the complex sampling design, including stratification, clustering, and unequal weighting, weighted multiple logistic regression was used to estimate the risk of a work-related injury. The initial model examined the interaction among daily sleep duration and BMI, controlling for weekly working hours, age, sex, race/ethnicity, education, type of pay, industry, and occupation. No significant interaction was found between usual daily sleep duration and BMI (p = .72); thus, the interaction term of the final logistic model included these two variables as independent predictors of injury, along with the aforementioned covariates. Statistically significant covariates (p ≤ .05) included age, sex, weekly work hours, occupation, and if the worker was paid hourly. The lowest categories of usual sleep duration (<6 and 6-6.9 h) showed significantly (p ≤ .05) elevated injury risks than the referent category (7-8 h sleep), whereas sleeping >7-8 h did not significantly elevate risk. The adjusted injury risk odds ratio (OR) for a worker with a usual daily sleep of <6 h was 1.86 (95% confidence interval [CI]: 1.37-2.52), and for 6-6.9 h it was 1.46 (95% CI: 1.18-1.80). With regards to BMI, the adjusted injury risk OR comparing workers who were obese (BMI: ≥30) to healthy weight workers (BMI: <25) was 1.34 (95% CI: 1.09-1.66), whereas the risk in comparing overweight workers (BMI: 25-29.99) to healthy weight risk was elevated, but not statistically significant (OR = 1.08; 95% CI: .88-1.33). These results from a large representative sample of US workers suggest increase in work-related injury risk for reduced sleep regardless of worker's body mass. However, being an overweight worker also increases work-injury risk regardless of usual daily sleep duration. The independent additive risk of these factors on work-related injury suggests a substantial, but at least partially preventable, risk.

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Section: Discussionmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

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Independent Effects of Sleep Duration and Body Mass Index on the Risk of a Work-Related Injury: Evidence From the US National Health Interview Survey (2004–2010)

Lombardi

Wirtz²,

Willetts

et al. 2012

Chronobiology International

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“…Obese workers are often less productive at work 2) , and have increased absenteeism 3) , occupational injuries 4) , morbidity and use of health services 5) . In recent decades, the prevalence of obesity has been increasing worldwide 6) .…”

mentioning

confidence: 99%

Long Work Hours and Obesity in Korean Adult Workers

Jang

Kim

Lee

et al. 2013

Journal of Occupational Health

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25 or over 64 years, pregnant women, part-time workers, soldiers, housewives and students were excluded. The total number of individuals included in the analysis was 8,889 (5,241 male and 3,648 female subjects). The outcome variable was obesity, defined as body mass index ≥25 kg/m 2 . Variables considered in the model were age, education, income, marital status, alcohol drinking, smoking, daily energy intake, physical activity, sleep hours per day, the type of job, work hours, and work schedule. Work hours were categorized as <40, 40−48 (reference), 49−60, and >60 hours per week. Results: In the multiple SURVEYLOGISTIC regression analyses, the adjusted odds ratio of obesity for long work hours (>60 hours per week) in male manual workers was 1.647 (95% confidence interval 1.262−2.151). Long work hours did not significantly increase the odds ratio for obesity in male nonmanual workers and female manual and nonmanual workers. Conclusions: More than 60 work hours per week increased the risk of obesity in Korean male manual workers. This result might be helpful in preventing obesity in Korean adult workers, especially male manual workers. (J Occup Health 2013; 55: 359-366)

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“…General and postpartum stress as causes of obesity: Physical and mental stress have been implicated as potential causes of obesity [156,157]. Job strain and job related stress have also been implicated in the causes of obesity and overweight [158,159]. Postpartum stress is also implicated as causes of maternal weight retention and obesity [157].…”

Section: N Lower Basal Metabolic Rate (Bmr) As a Cause Of Obesitymentioning

confidence: 99%

Assessment of Obesity, Presumed and Proven Causes and Prevention Strategies: A Review

Uzogara¹

2016

AOWMC

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The obesity epidemic has been widespread in many countries, and has several adverse consequences. So many factors, some probable, others verified and documented, are known to contribute to the obesity problem in developed and developing countries. Nutritionists and other health professionals need to be skilled in understanding these various causes and their health implications. They should also be able to assess excessive body weight in clinical and other settings. Armed with this knowledge, health professionals should therefore be able to advise consumers and clients struggling with weight management on cost-effective preventive strategies to prevent or reduce incidence of obesity. In addition, nutritionists should be able to advise food manufacturers to make and market healthy food products. This paper will address the growing concern on obesity epidemic by reviewing the presumed and published or proven causes of obesity and the various methods for measurement of obesity. Strategies for preventing obesity will also be discussed. Such strategies would include health education, lifestyle changes, physical activity, diet and behaviour modifications as well as reading food labels and proper food selection. Preventive strategies for obesity and overweight when properly implemented are very cost effective especially at personal and community levels and will ensure good health and wellness in many populations. Keywords IntroductionObesity and overweight trends have reached epidemic proportions in many countries [1][2][3][4][5][6][7][8], and have serious health and socio-economic consequences. In addition, obesity has negative medical, psychological and quality of life consequences, drains health care resources and reduces life expectancy. The International Obesity Task Force (IOTF) and WHO project that obesity rates worldwide would increase very significantly by 2025 unless appropriate intervention is taken [8,9]. In the USA, between 2011 & 2012, the percent of US adults aged 20 years and above who are obese was reported to be 35.1 %, while the percent of US adults who had excess body weight (overweight and obesity)in the same period was 69.0% according to published reports [2,10]. Obesity and related chronic diseases are no longer a problem of affluent countries alone, as poor developing countries, middle income countries or countries undergoing economic transition, are also affected by the epidemic [4,[6][7][8]. Global, national and state public health agencies as well as their nutritionists, researchers and educators have raised awareness or taken immediate action to arrest the increasing weight trends and obesity in adults, the youth and children [11][12][13][14][15][16]. Despite the high prevalence of obesity in many parts of the world, segments of populations (such as geriatric, very sick people, preschool children, pregnant & lactating women) suffer from underweight [7,[17][18][19]. In some developing countries, various types of unhealthy weight such as obesity, overweight and underweight, can coexist...

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Obesity and Its Relationship with Occupational Injury in the Canadian Workforce

Cited by 38 publications

References 18 publications

Independent Effects of Sleep Duration and Body Mass Index on the Risk of a Work-Related Injury: Evidence From the US National Health Interview Survey (2004–2010)

Independent Effects of Sleep Duration and Body Mass Index on the Risk of a Work-Related Injury: Evidence From the US National Health Interview Survey (2004–2010)

Long Work Hours and Obesity in Korean Adult Workers

Assessment of Obesity, Presumed and Proven Causes and Prevention Strategies: A Review

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