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Weight change and workplace absenteeism in the HealthWorks study.

ABSTRACT: Little is known about the relationship between weight change and workplace absenteeism. The purpose of this study was to examine the degree to which weight change predicted 2-year absenteeism.A longitudinal analysis of 1,228 employees enrolled in a worksite-randomized controlled trial was performed. Participants were all working adults in the Minneapolis, MN, area (USA).The final model indicated a significant interaction between weight change and baseline BMI. The difference in absenteeism ranged from (mean ± SE) 3.2 ± 1.2 days among healthy weight employees who maintained their weight to 6.6 ± 1.1 days among obese employees who gained weight (and slightly higher among healthy weight employees who lost weight). The adjusted model also indicated that participants who were male, not depressed, nonsmokers, and had lower baseline absenteeism had significantly less workplace absenteeism relative to participants who were female, depressed, smokers, and had higher baseline absenteeism.Absenteeism was generally low in this sample, but healthy weight employees who maintained their body weight over 2 years had the fewest number of sick days. More research is needed in this area, but future workforce attendance interventions may be improved by focusing on the primary prevention of weight gain in healthy weight employees.

SUBMITTER: VanWormer JJ

PROVIDER: S-EPMC4032064 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Weight change and workplace absenteeism in the HealthWorks study.

VanWormer Jeffrey J JJ Linde Jennifer A JA Harnack Lisa J LJ Stovitz Steven D SD Jeffery Robert W RW

Obesity facts 20121024 5

<h4>Objective</h4>Little is known about the relationship between weight change and workplace absenteeism. The purpose of this study was to examine the degree to which weight change predicted 2-year absenteeism.<h4>Methods</h4>A longitudinal analysis of 1,228 employees enrolled in a worksite-randomized controlled trial was performed. Participants were all working adults in the Minneapolis, MN, area (USA).<h4>Results</h4>The final model indicated a significant interaction between weight change and ...[more]

PMID: 23108493

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Project description:BACKGROUND:Excess weight can increase absenteeism of workers and can have a negative influence on their productivity. Current evidence on this association is mostly based on cross-sectional data and there is little evidence concerning the longitudinal relationship between obesity, and disability with workplace absenteeism. Further, gender differences in this association have often ignored in the existing literature. OBJECTIVES:This study aims to examine gender differences in the longitudinal association between obesity, and disability with absenteeism in the workplace. METHODS:Data from thirteen waves (2006 to 2018) of the Household, Income and Labour Dynamics in Australia (HILDA) survey were pooled, resulting in 117,769 observations for 19,851 adult employees. The Zero-Inflated Negative Binomial (ZINB) regression model was deployed to investigate the links between obesity, and disability with workplace absenteeism for the total sample and stratified by gender. RESULTS:The findings showed that overweight (Incidence Rate Ratio [IRR]: 1.23, 95% confidence interval [CI]: 1.02-1.47), obesity (IRR: 1.35, 95% CI: 1.12-1.64) and disability (IRR: 2.83, 95% CI: 2.36-3.38) were associated with prolonged workplace absenteeism irrespective of gender. This study found that the multiplicative interaction between weight status and gender is significantly associated with absenteeism. The results reveal that the rate of absenteeism was 2.79 times (IRR: 2.79, 95% CI: 1.96-3.97) and 1.73 times (IRR: 1.73, 95% CI: 1.20-2.48) higher among overweight and obese women than male counterparts, respectively. Moreover, this study found that the weight status of male workers is not associated with absenteeism. However, disability (IRR: 3.14, 95% CI: 2.43-4.05) is positively associated with longer days of absence among male workers. Finally, the study results showed that the rate of absenteeism is 1.82 (IRR: 1.82, 95% CI: 1.36-2.44), 1.61 (IRR: 1.61, 95% CI: 1.21-2.13), and 2.63 (IRR: 2.63, 95% CI: 1.99-3.48) times higher among overweight, obese, and female workers with a disability, respectively, compared with their lower weight counterparts. CONCLUSIONS:Workplace absenteeism is significantly associated with overweight and obesity among Australian workers. An active workplace health promotion program is very important for weight management of overweight and obese workers and thus to reduce workplace absenteeism. For example, employers may provide incentives for maintaining recommended body weights, encourage exercise, and promote healthy diets amongst their workers.

Project description:ImportanceAlcohol use disorder (AUD) is common and associated with increased morbidity. The degree to which AUD currently factors into workplace absenteeism needs further characterization in the US.ObjectiveTo examine the association between AUD and workplace absenteeism in a nationally representative sample.Design, setting, and participantsThis cross-sectional study used data from a nationally representative sample of noninstitutionalized US residents from the 2015-2019 National Survey on Drug Use and Health to examine the association of AUD with workplace absenteeism. Eligible respondents were aged 18 years and older who reported full-time employment. Data were analyzed from March to September 2021.Main outcomes and measuresPrimary outcomes were markers of workplace absenteeism as defined by the number of days missed from work because of illness or injury and days skipped from work in the last 30 days. Descriptive statistics, prevalence ratios, and logistic regression analyses were performed to assess the association between AUD and absenteeism.ResultsA total of 110 701 adults aged 18 years and older reported current full-time employment (58 948 [53.2%] men, 51 753 [46.8%] women; 12 776 [11.5%] Black, 18 096 [16.3%] Hispanic, and 69 506 [62.8%] White respondents). Weighted prevalence of AUD in this sample of working adults was 9.3% (95% CI, 9.0%-9.5%); 6.2% (95% CI, 6.0%-6.4%) of respondents met criteria for mild AUD, 1.9% (95% CI, 1.7%-2.0%) for moderate AUD, and 1.2% (95% CI, 1.1%-1.3%) for severe AUD. Mean days missed from work annually increased in a stepwise fashion with increasing AUD severity (no AUD, 13.0 days; 95% CI, 12.7-13.2 days; mild AUD, 17.7 days; 95% CI, 16.4-19.1 days; moderate AUD, 23.6 days; 95% CI, 21.5-25.7 days; severe AUD, 32.3 days; 95% CI, 27.5-37.0 days). People with AUD represented 9.3% of the full-time workforce and contributed to 14.1% of total reported workplace absences.Conclusions and relevanceIn this cross-sectional study, AUD was disproportionately associated with an increased prevalence of workplace absenteeism, with individuals with AUD contributing over 232 million missed workdays annually. These results provide economic incentive for increased investment in AUD prevention and treatment, both for employers and policy makers.

Project description:Introduction:Organizational readiness to change may be a key determinant of implementation success and a mediator of the effectiveness of implementation interventions. If organizational readiness can be reliably and validly assessed at the outset of a change initiative, it could be used to assess the effectiveness of implementation-support activities by measuring changes in readiness factors over time. Methods:We analyzed two waves of readiness-to-change survey data collected as part of a three-arm, randomized controlled trial to implement evidence-based health promotion practices in small worksites in low-wage industries. We measured five readiness factors: context (favorable broader conditions); change valence (valuing health promotion); information assessment (demands and resources to implement health promotion); change commitment (an intention to implement health promotion); and change efficacy (a belief in shared ability to implement health promotion). We expected commitment and efficacy to increase at intervention sites along with their self-reported effort to implement health promotion practices, termed wellness-program effort. We compared means between baseline and 15?months, and between intervention and control sites. We used linear regression to test whether intervention and control sites differed in their change-readiness scores over time. Results:Only context and change commitment met reliability thresholds. Change commitment declined significantly for both control (-0.39) and interventions sites (-0.29) from baseline to 15?months, while context did not change for either. Only wellness program effort at 15?months, but not at baseline, differed significantly between control and intervention sites (1.20 controls, 2.02 intervention). Regression analyses resulted in two significant differences between intervention and control sites in changes from baseline to 15?months: (1) intervention sites exhibited significantly smaller change in context scores relative to control sites over time and (2) intervention sites exhibited significantly higher changes in wellness program effort relative to control sites. Discussion:Contrary to our hypothesis, change commitment declined significantly at both Healthlinks and control sites, even as wellness-program effort increased significantly at HealthLinks sites. Regression to the mean may explain the decline in change commitment. Future research needs to assess whether baseline commitment is an independent predictor of wellness-program effort or an effect modifier of the HealthLinks intervention.

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Weight change and workplace absenteeism in the HealthWorks study.

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Weight change and workplace absenteeism in the HealthWorks study.

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