scholarly journals The Prevalence and Severity of Sick Leave Due to Low Back Disorders among Workers in Slovenia: Analysis of National Data across Gender, Age and Classification of Economic Activities

2021 ◽  
Vol 19 (1) ◽  
pp. 131
Author(s):  
Dorjana Zerbo Šporin ◽  
Žiga Kozinc ◽  
Ticijana Prijon ◽  
Nejc Šarabon
Keyword(s):  
Sick Leave ◽  
Young Male ◽  
Health Condition ◽  
Low Back ◽  
National Data ◽  
Economic Activities ◽  
Back Disorders ◽  
Work Related ◽  
Depth Analysis ◽  
Low Back Disorders

Musculoskeletal disorders are the most common work-related health problems. As low back disorders (LBD) are the most problematic, the aim of this study was to provide an in-depth analysis of the nationwide data on sick leaves due to work-related LBDs among workers in Slovenia in 2015–2019 by gender, age and various economic activities (NACE Rev 2 classification). We retrospectively analyzed the Slovene national data for sick leave (SL) rates due to the LBDs between 2015 and 2019. The analyzed SL outcomes were (i) index of temporary disability as a diagnosis-specific loss of calendar days (all calendar days except Sundays) per employee, (ii) frequency of spells as the number of SL cases per 100 employees in one year and (iii) severity as the average duration of one absence from work due to a health condition. A high prevalence of sick leaves due to LBDs in Slovenia was present among young male workers in “mining and quarrying”. In the next age group (20.0–44.9 years), LBD is most frequent in “water supply; sewerage, waste management and remediation activities”. Particular attention should be paid to ‘’agriculture, forestry and fishing’’ which shows a large average sick leave duration and probably a more demanding course of LBDs.

Job exposures as correlates of recovery in population-based rehabilitation intervention for work-related low back disorders

2000 ◽  
Vol 10 (7) ◽  
pp. 481 ◽  
Author(s):  
DM Oleske ◽  
SA Lavender ◽  
GBJ Andersson ◽  
JJ Hahn ◽  
P Zold-Kilbourn ◽  
...  
Keyword(s):  
Population Based ◽  
Low Back ◽  
Back Disorders ◽  
Work Related ◽  
Rehabilitation Intervention ◽  
Low Back Disorders

Association Between Recovery Outcomes for Work-Related Low Back Disorders and Personal, Family, and Work Factors

Spine ◽  
2000 ◽  
Vol 25 (10) ◽  
pp. 1259-1265 ◽  
Author(s):  
Denise M. Oleske ◽  
Gunnar B. J. Andersson ◽  
Steven A. Lavender ◽  
Jerome J. Hahn
Keyword(s):  
Low Back ◽  
Back Disorders ◽  
Work Related ◽  
Work Factors ◽  
Low Back Disorders ◽  
Family And Work

Classification of jobs with risk of low back disorders by applying data mining techniques

2005 ◽  
Vol 4 (4) ◽  
pp. 291-305
Author(s):  
Jozef Zurada ◽  
Waldemar Karwowski ◽  
William Marras
Keyword(s):  
Data Mining ◽  
Neural Networks ◽  
Logistic Regression ◽  
Decision Tree ◽  
Low Back ◽  
Data Mining Techniques ◽  
Back Disorders ◽  
Work Related ◽  
Low Back Disorders

Work related low back disorders (LBDs) continue to pose significant occupational health problem that affects the quality of life of the industrial population. The main objective of this study was to explore the application of various data mining techniques, including neural networks, logistic regression, decision trees, memory-based reasoning, and the ensemble model, for classification of industrial jobs with respect to the risk of work-related LBDs. The results from extensive computer simulations using a 10-fold cross validation showed that memory-based reasoning and ensemble models were the best in the overall classification accuracy. The decision tree and memory-based reasoning models were the most accurate in classifying jobs with high risk of LBDs, whereas neural networks and logistic regression were the best in classifying jobs with low risk of LBDs. The decision tree model delivered the most stable results across 10 generations of different data sets randomly chosen for training, validation, and testing. The classification results generated by the decision tree were the easiest to interpret because they were given in the form of simple 'if-then' rules. These results produced by the decision tree method showed that the peak moment had the highest predictive power of LBDs.

Risk Factors for Recurrent Episodes of Work-Related Low Back Disorders in an Industrial Population

Spine ◽  
2006 ◽  
Vol 31 (7) ◽  
pp. 789-798 ◽  
Author(s):  
Denise M. Oleske ◽  
Steven A. Lavender ◽  
Gunnar B. J. Andersson ◽  
Mary J. Morrissey ◽  
Phyllis Zold-Kilbourn ◽  
...  
Keyword(s):  
Risk Factors ◽  
Low Back ◽  
Back Disorders ◽  
Work Related ◽  
Low Back Disorders

scholarly journals Assessing Work-Related Risk Factors on Low Back Disorders among Roofing Workers

2017 ◽  
Vol 143 (7) ◽  
pp. 04017026 ◽  
Author(s):  
Di Wang ◽  
Fei Dai ◽  
Xiaopeng Ning ◽  
Renguang G. Dong ◽  
John Z. Wu
Keyword(s):  
Risk Factors ◽  
Low Back ◽  
Back Disorders ◽  
Work Related ◽  
Related Risk ◽  
Low Back Disorders

Low Back Pain as a Predictor of Sickness Absence due to Low Back Disorders

2000 ◽  
Vol 44 (30) ◽  
pp. 5-581-5-583
Author(s):  
Marketta Häkkänen ◽  
Eira Viikari-Juntura ◽  
Rami Martikainen
Keyword(s):  
Low Back Pain ◽  
Back Pain ◽  
Sick Leave ◽  
Sickness Absence ◽  
Musculoskeletal Symptoms ◽  
Low Back ◽  
Linear Modeling ◽  
Back Disorders ◽  
Low Back Disorders ◽  
Potential Risk Factors

The objective of the study was to investigate two types of self-reported low back pain, sciatic and local, as predictors of sickness absence due to low back disorders. The study population comprised 4265 workers in a large forestry company. The workers filled out a self-administrative questionnaire on musculoskeletal symptoms and potential risk factors. Sickness absence was followed for subsequent 12 months via medical records. Log-linear modeling was used to investigate the associations between the predictors and the number of days lost due to low back disorders. Sciatic and local low back pain were predictors of future sick leaves. Furthermore, their effects on sick leave were different, sciatic pain increasing the risk of sick leave remarkably. Other predictors were self assessed ability to work during the coming five years, job category, average hours per day of transportation work, and average hours per day of working kneeling or squatted. Our results suggest that it is beneficial to differentiate between sciatic and local low back symptoms in health examinations of workers as well as in etiologic studies on low back disorders.

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