Sickness absence is of considerable concern in both Norway and Denmark. Labour Force Surveys indicate that absence in Norway is about twice that in Denmark and twice that of the mean reported by the Organisation for Economic Co-operation and Development. This study compares absence patterns according to age, percentage of employment, and occupation between municipal employees in the health and care sectors in two municipalities in Norway and Denmark.
Data recorded in the personnel registers of the municipalities of Kristiansand, Norway and Aarhus, Denmark were extracted for the years 2004 and 2008, revealing 3498 and 7751 employee-years, respectively. We calculated absence rates together with number of sick leave episodes, and their association with the above-mentioned covariates. Gender-specific comparative descriptive statistics and negative binomial regression analysis were performed.
The sickness absence rate in women was 11.3% in Norway (95% confidence interval [CI] 11.2-11.4) and 7.0% in Denmark (95% CI 7.0-7.1) whereas mean number of sick leave episodes among women was 2.4 in Denmark, compared to 2.3 in Norway (p = 0.02). Young employees in Denmark had more sick leave episodes than in Norway. Proportion of absentees was higher in Denmark compared to Norway (p < 0.0001).
The finding of that more employees in Denmark have more frequent, but shorter sick leave episodes compared to Norway, for whatever reasons, may indicate that more frequent sick leaves episodes prevent higher sick leaves rates.
"The municipal health and care sectors include, for example, nursing homes, home care services, and day centers. This study is a part of a larger study where background variables, such as occupation, age, and percentage of employment, were investigated
. In this study, we focus on sickness absences patterns and trends over a 5-year period, overall and by age group. "
[Show abstract][Hide abstract] ABSTRACT: Background
Sickness absence is a growing public health problem in Norway and Denmark, with the highest absence rates being registered in Norway. We compared time trends in sickness absence patterns of municipal employees in the health and care sectors in Norway and Denmark.
Data from 2004 to 2008 were extracted from the personnel registers of the municipalities of Kristiansand, Norway, and Aarhus, Denmark, for 3,181 and 8,545 female employees, respectively. Age-specific comparative statistics on sickness absence rates (number of calendar days of sickness absence/possible working days) and number of sick leave episodes were calculated for each year of the study period.
There was an overall increasing trend in sickness absence rates in Denmark (P = 0.002), where rates were highest in the 20–29- (P = 0.01) and 50–59-year-old age groups (P = 0.03). Sickness absence rates in Norway were stable, except for an increase in the 20–29-year-old age group (P = 0.004). In both Norway and Denmark, the mean number of sick leave episodes increased (P <0.0001 and P <0.0001, respectively) in all age groups except for the 30–39- and 60–67-year-old age groups. The proportion of employees without sickness absence was higher in Norway than in Denmark. Both short-term and long-term absence increased in Denmark (P = 0.003 and P <0.0001, respectively), while in Norway, only short-term absence increased (P = 0.09).
We found an overall increase in sickness absence rates in Denmark, while the largest overall increase in sick leave episodes was found in Norway. In both countries, the largest increases were observed among young employees. The results indicate that the two countries are converging in regard to sickness absence measured as rates and episodes.
Human Resources for Health 07/2014; 12(1):37. DOI:10.1186/1478-4491-12-37 · 1.83 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Purpose:
To validate Dutch prognostic models including age, self-rated health and prior sickness absence (SA) for ability to predict high SA in Danish eldercare. The added value of work environment variables to the models' risk discrimination was also investigated.
2,562 municipal eldercare workers (95% women) participated in the Working in Eldercare Survey. Predictor variables were measured by questionnaire at baseline in 2005. Prognostic models were validated for predictions of high (≥30) SA days and high (≥3) SA episodes retrieved from employer records during 1-year follow-up. The accuracy of predictions was assessed by calibration graphs and the ability of the models to discriminate between high- and low-risk workers was investigated by ROC-analysis. The added value of work environment variables was measured with Integrated Discrimination Improvement (IDI).
1,930 workers had complete data for analysis. The models underestimated the risk of high SA in eldercare workers and the SA episodes model had to be re-calibrated to the Danish data. Discrimination was practically useful for the re-calibrated SA episodes model, but not the SA days model. Physical workload improved the SA days model (IDI = 0.40; 95% CI 0.19-0.60) and psychosocial work factors, particularly the quality of leadership (IDI = 0.70; 95% CI 053-0.86) improved the SA episodes model.
The prognostic model predicting high SA days showed poor performance even after physical workload was added. The prognostic model predicting high SA episodes could be used to identify high-risk workers, especially when psychosocial work factors are added as predictor variables.
[Show abstract][Hide abstract] ABSTRACT: Results: Four major significant themes were identified from the FGDs: a) sickness absence and sickness presenteeism, b) acceptable causes of sickness absence, c) job identity, and d) organization of work and physical aspects of the workplace. Our analyses showed that social commitment and loyalty to residents and colleagues was important for sickness absence and sickness presenteeism, as were perceived acceptable and non-acceptable reasons for sickness absence. Organization of work and physical aspects of the workplace were also found to have an influence on attitudes towards sickness absence.
BMC Public Health 08/2014; 14(1):880. DOI:10.1186/1471-2458-14-880 · 2.26 Impact Factor
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