Abstract
BackgroundObesity and long term health condition (LTHC) are major public health concerns that have an impact on productivity losses at work. Little is known about the longitudinal association between obesity and LTHC with impaired productivity.ObjectiveThis study aims to explore the longitudinal association between obesity and LTHC with presenteeism or working while sick.DesignLongitudinal research designSettingAustralian workplacesMethodsThis study pooled individual-level data of 111,086 employees collected in wave 6 through wave 18 from the Household, Income and Labour Dynamics in Australia (HILDA) survey. The study used a Generalized Estimating Equation (GEE) model with logistic link function to estimate the association.ResultsThe findings suggest that overweight (Odds Ratios [OR]: 1.09, 95% Confidence Interval [CI]: 1.05–1.14), obesity (OR: 1.38, 95% CI: 1.31–1.45), and LTHC (OR: 3.03, 95% CI: 2.90–3.16) are significantly positively associated with presenteeism.ConclusionsThe longitudinal association between obesity and LTHC with presenteeism among Australian employees implies that interventions to improve workers' health and well-being will reduce the risk of presenteeism at work.
Highlights
The global obesity prevalence has nearly tripled since 1975
The findings suggest that overweight (Odds Ratios [OR]: 1.09, 95% Confidence Interval [confidence intervals (CI)]: 1.05–1.14), obesity (OR: 1.38, 95% CI: 1.31–1.45), and long term health condition (LTHC) (OR: 3.03, 95% CI: 2.90–3.16) are significantly positively associated with presenteeism
Given the discrete nature of the dependent variable, presenteeism, the present study explores the association between obesity and LTHC with presenteeism using Generalized Estimating Equation (GEE) with a logistic link function
Summary
This study aims to explore the longitudinal association between obesity and LTHC with presenteeism or working while sick. Data Availability Statement: The authors completed and signed the Confidentiality Deed Poll and sent it to NCLD (ncldresearch@dss.gov.au) and ADA (ada@anu.edu.au) before the data applications’ approval. Datasets analyzed and/or generated during the current study are subject to the signed confidentiality deed. The present study used HILDA data set, which is a third-party data set and were collected by the Melbourne Institute of Applied Economic and Social Research. There are some formalities on accessing and legal restrictions on sharing this
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