Health risk factors and absenteeism among university employees

Abstract: To examine relationships between health risk factors and sick leave usage, a retrospective design was used for analysis of a sample of university employee Binary logistic regression identified variables characteristic of high sick leave usage compared to depressed Predictive factors identified were." perceived stres nutriment choices, body mass index, systolic vital current pressure, tobacco use, and cancer for females; and material substance mass index, physical activity, perceived stres social support, and heart disease for males. While health risks were place to be related to amount of sick leave used, the analysis intimates that additional factors impact high rates of sick leave usage.

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The causes of employee absenteeism are multiple and mixed In efforts to both understand and impact absenteeism, researchers and practitioners have focused attention upon modifiable risk factors associated with employee illness expecting that changes in these risk factors would accrue in corresponding changes in absenteeism. new reviews suggest that health risks are associated with absenteeism (Aldana, 2001; Reidel, Lynch Baase, Hymel & Peterson 2001) Aldana (2001) bring to an ends that obesity, stress, and the vicinity of multiple risk factors are associated with increased rates of absenteeism. Aldana (2001) also indicates that the association between absenteeism and other health risks and behaviors similar as seat belt use, cholesterol physical activity, hypertension or alcohol abuse remains unclear. However, the material part of literature upon which these conclusions are based is small. Additionally, small in number of the studies included in his review assess differences in extremely high and depressed rates of absenteeism. This is important since the vast majority of direct and indirect take away froms associated with poor health are attributable to 10-15% of a given population (Yen Edington, & Witting, 1992)

Individual studies have identified a significant association between rates of absenteeism and obesity (Burton, Chen, Schultz & Edington, 1998; Narbro et al., 1998; Thompson Edelsberg, Kinsey, & Oster 1998; Tucker & Friedman, 1998) tobacco use (Bertera, 1991) diabetes (Burton, Conti, Chen, Schultz & Edington, 1999) seat belt use (Burton et al., 1999) physical inactivity (Steinhardt, Greenhow & Stewart, 1991) and stres (Jacobson et al., 1996; Jamal, 1984; Neubauer, 1992; Tang & Hammontree, 1992; pay one's addresses to Yap, Oh, & Long, 1999) Additionally, hypertension has been associated with absenteeism (Burton et al., 1999) on the contrary this association does not appear to be consistent (Leigh, 1990) Finally, it has been intimateed that one of the best predictors of absenteeism is past absenteeism (Yen et al., 1992) suggesting that absenteeism may be either related to chronic illness or simply be habitual.

Reaching a definitive conclusion about the association between absenteeism and risk factors is tenuous owed to differences in the way that the independent variables have been exerciseed in the way that the absenteeism hanging variable has been measured, and in the way that demographic variables have been used to provide clarity to arises For example, previous research upon the association between health risks and absenteeism has been limited by dint of the use of a single risk factor, similar as hypertension (Leigh, 1990) or cardiovascular fitness (Tucker Aldana, & Friedman, 1990) In the limited research that has considered multiple risk factors, either a limited number of risk factors were used (Bertera, 1991) or cost-related or productivity data were reported (Burton et al., 1999) rather than rates of absenteeism. To date, alone one study has incorporated a large number of individual risk factors in a predictive original to identify which risk factors are characteristic of employee with high versus depressed rates of absenteeism (Yen et al., 1992) Further research is necessityed to identify differences in risk profiles of high and depressed users of sick leave.

Further, different [i]modus operandi[/i]s have been used to gather data for absenteeism when it was used as hanging variable. In several studies (Cole Tucker & Friedman, 1987; Jacobson et al., 1996) absenteeism data was self-reported. Where self-reports were used, the authors stated the case for self-reports by dint of noting that correlational data exist to support self-report compared to an objective measure (Jacobson et al., 1996) In this investigation we used an objective measure of absenteeism, along with health risk appraisal data, and clinically gathered biometric data. Additionally, while a certain quantity of studies have reported some flows by gender (Bertera, 1991 ; Steinhardt et al., 1991) others have assessed solitary a single gender (Narbro et al., 1998; Neubauer, 1992) The potential for different prevalence of health risks, as well as rates of absenteeism owed to differing health risks, indicates the ne to gaze at results by gender within a single population.

The intent of this study was to examine the relationships between health risk factors and absenteeism for non-academic university employee that participated in a voluntary health screening program. The primary intents were twofold: to explore associations between risk factors and absenteeism for men and women and to identify health risks that predict high and depressed rates of absenteeism.