Sickness Absenteeism among Industrial Workers, Fourth Quarter of 1944, with a Note on Seasonal Variation

1945 ◽  
Vol 60 (22) ◽  
pp. 612 ◽  
Author(s):  
W. M. Gafafer
Keyword(s):  
Seasonal Variation ◽  
Fourth Quarter ◽  
Industrial Workers ◽  
Sickness Absenteeism

Seasonality of births in affective disorder in an Irish population

1998 ◽  
Vol 13 (7) ◽  
pp. 353-358 ◽  
Author(s):  
M Clarke ◽  
F Keogh ◽  
PT Murphy ◽  
M Morris ◽  
C Larkin ◽  
...  
Keyword(s):  
Seasonal Variation ◽  
Statistical Analysis ◽  
General Population ◽  
Affective Disorder ◽  
Fourth Quarter ◽  
Season Of Birth ◽  
Irish Population ◽  
Chi Square ◽  
Chi Square Test ◽  
Seasonality Of Births

SummarySeasonal variation in the births of patients with schizophrenia is a consistently replicated epidemiological finding. Few studies have investigated this phenomenon among patients with a diagnosis of affective disorder. The majority of season of birth studies have employed the chi square test for statistical analysis, a method that has been subject to some criticism. Using a Kolgomorov-Smirnov type statistic, the quarterly birth distribution of 6,646 patients with an ICD 9/10 diagnosis of affective disorder were compared to the general population. Only the births of those individuals with unipolar forms of affective disorder (n = 4,393) differed significantly from the general population, with significant excesses and deficits in the second quarter and fourth quarter respectively. These results were not altered by application of the displacement test. © 1998 Elsevier, Paris

Seasonal variation of hours worked in home-based industrial production: Evidence from Sweden 1912

2016 ◽  
Vol 40 (4) ◽  
pp. 838-866
Author(s):  
Malin Nilsson
Keyword(s):  
Seasonal Variation ◽  
Industrial Production ◽  
Supply And Demand ◽  
Principal Component ◽  
Industrial Workers ◽  
Seasonal Fluctuations ◽  
Hours Worked ◽  
Home Based ◽  
Flexible Segment ◽  
Means Of Production

This study investigates patterns of seasonal variation in hours worked by women employed in home-based industrial production in Sweden in the early 20th century. Previous studies often describe workers in this type of production as the most flexible segment of industrial workers, and highly dependent on seasonal fluctuations in supply and demand. However, few have studied this empirically. This study relies on data from interviews with home-based workers. Principal component analysis is used to identify seasonal patterns and OLS regressions to identify the factors driving these fluctuations. The results show surprisingly stable patterns in hours worked, most women worked 8–10 hours per day all year. Thus, while home-based workers were flexible in the sense that they all worked on piece-work contracts and provided their own means of production and place of work, their work was not essentially irregular or largely fluctuating by supply- or demand-driven seasonal variations.

scholarly journals Prevalence and Factors associated with sickness absenteeism among Pharmaceutical Industrial workers of Hyderabad, India

2021 ◽  
Vol 12 (1) ◽  
pp. 81-86
Author(s):  
Sudha Bala ◽  
Rajiv Kumar B ◽  
Harshal Pandve
Keyword(s):  
Health Care ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Mental Stress ◽  
Multinomial Logistic Regression ◽  
Pharmaceutical Manufacturing ◽  
Industrial Workers ◽  
Sickness Absenteeism ◽  
Multinomial Logistic Regression Analysis

Background: Sickness absenteeism is a potential epidemiological issue leading to loss of productivity in addition to increasing the cost of health care and provides a major tool in enhancing occupational health care preventive strategies. Aim and Objectives: To determine the prevalence of sickness absenteeism and their associated factors among Industrial Workers of Pharmaceutical Manufacturing industries in Hyderabad. Materials and Methods: A cross sectional study was taken up among 160 Workers at two Pharmaceutical Manufacturing companies in Hyderabad using simple random sampling technique. Data included Individual, Occupational and Organizational factors influencing their sickness absenteeism and general health conditions in the past six months through camp based approach. Data was analysed using descriptive statistics and multinomial logistic regression analysis to predict the variables associated with the outcome. Results: The prevalence of sickness absenteeism was found among 19% of the workers. Common causes were due to sickness among 25(84%) and social responsibilities among 5(16%). On multinomial logistic regression analysis- poor superior relationships, poor co-workers relationship and high mental stress were found to be significant. Conclusion: Sickness absenteeism was found to be high which can be reduced by improving relationships with superiors and co-workers and also by reducing mental stress among the workers.

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