OBJECTIVE: To analyze factors associated with self-reported sickness absenteeism among nursing workers. METHODS: Cross-sectional study with 1,509 workers from three public hospitals in the city of Rio de Janeiro (Southeastern Brazil) in 2006. Absenteeism was classified in three levels: no day, a few days (1-9 days) and many days (> 10 days), based on the answer to a question of the work ability index questionnaire. The logistic regression analysis considered a conceptual model based on distal (socioeconomic status), intermediate I (occupational characteristics), intermediate II (lifestyle characteristics), and proximal (diseases and health conditions) determinants. RESULTS: The frequencies of sickness absenteeism were 20.3% and 16.6% for a few days and many days, respectively. Those who reported more than one job, musculoskeletal diseases and rated their health as poor or regular had higher odds of absenteeism. Compared to nurses, nursing assistants were less likely to mention a few days, and technicians were more likely to have many days of absence. Higher odds of mentioning many days of absence were observed among public servants, compared to contract workers (OR = 3.12; 95%CI 1.86;5.22), and among married (OR = 1.73; 95%CI 1.14;2.63) and separated, divorced and widowed individuals (OR = 2.06, 95%CI 1.27;3.35), compared to singles. CONCLUSIONS: Different variables were associated with the two forms of absenteeism, which suggests its multiple and complex determination related to factors from different levels that cannot be exclusively explained by health problems.
OBJECTIVE: To analyze factors associated with self-reported sickness absenteeism among nursing workers. METHODS: Cross-sectional study with 1,509 workers from three public hospitals in the city of Rio de Janeiro (Southeastern Brazil) in 2006. Absenteeism was classified in three levels: no day, a few days (1-9 days) and many days (> 10 days), based on the answer to a question of the work ability index questionnaire. The logistic regression analysis considered a conceptual model based on distal (socioeconomic status), intermediate I (occupational characteristics), intermediate II (lifestyle characteristics), and proximal (diseases and health conditions) determinants. RESULTS: The frequencies of sickness absenteeism were 20.3% and 16.6% for a few days and many days, respectively. Those who reported more than one job, musculoskeletal diseases and rated their health as poor or regular had higher odds of absenteeism. Compared to nurses, nursing assistants were less likely to mention a few days, and technicians were more likely to have many days of absence. Higher odds of mentioning many days of absence were observed among public servants, compared to contract workers (OR = 3.12; 95%CI 1.86;5.22), and among married (OR = 1.73; 95%CI 1.14;2.63) and separated, divorced and widowed individuals (OR = 2.06, 95%CI 1.27;3.35), compared to singles. CONCLUSIONS: Different variables were associated with the two forms of absenteeism, which suggests its multiple and complex determination related to factors from different levels that cannot be exclusively explained by health problems.
Authors: Marden Samir Santa-Marinha; Liliane Reis Teixeira; Elvira Maria Godinho de Seixas Maciel; Maria de Fatima Ramos Moreira Journal: Rev Bras Med Trab Date: 2020-04-24
Authors: Iara Bassi; Ada Ávila Assunção; Adriano Marçal Pimenta; Fernando G Benavides; Monica Ubalde-Lopez Journal: J Occup Health Date: 2016-03-24 Impact factor: 2.708
Authors: Fabiana Maluf Rabacow; Renata Bertazzi Levy; Paulo Rossi Menezes; Olinda do Carmo Luiz; Ana Maria Malik; Alex Burdorf Journal: BMC Public Health Date: 2014-04-06 Impact factor: 3.295