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Rev Saude Publica ; 58: 13, 2024.
Article in English, Portuguese | MEDLINE | ID: mdl-38695442

ABSTRACT

OBJECTIVE: To analyze the distribution and association of sociodemographic and occupational factors with self-reported work accidents (WA) in a representative sample of the Brazilian population, with emphasis on occupational class, and to examine gender differences in this distribution. METHODS: A population-based cross-sectional study, using data from the 2019 National Health Survey (PNS), analyzed the responses of a sample of adults aged 18 or over. Factors associated with WA were investigated using binary logistic regression and hierarchical analysis using blocks (sociodemographic and occupational variables). The final model was adjusted by variables from all blocks, adopting a significance level of 5%. The values of odds ratios (OR) and respective confidence intervals were obtained. RESULTS: Among the participants, 2.69% reported having suffered a WA, with a higher prevalence in men (3.37%; 95%CI 2.97-3.82%) than in women (1.86%; 95%CI 1.55-2.23%). The analysis identified that age group, night work, working hours, and exposure to occupational risks were associated with WA, with emphasis on gender differences. The class of manual workers, both qualified (ORwomen = 2.87; 95%CI 1.33-6.21 and ORmen = 2.46; 95%CI 1.37-4.40) and unskilled (ORwomen = 2.55; 95%CI 1.44-4.50 and ORmen = 3.70; 95%CI 1.95-7.03), had a higher chance of WA than the class of managers/professionals. CONCLUSION: Occupational factors contributed significantly to the increase in the probability of WA for men and women, with greater magnitude among those positioned in the lower strata of the occupational structure. The results obtained are clues for working out WA prevention actions.


Subject(s)
Accidents, Occupational , Socioeconomic Factors , Humans , Brazil/epidemiology , Male , Female , Adult , Cross-Sectional Studies , Accidents, Occupational/statistics & numerical data , Middle Aged , Young Adult , Sex Factors , Adolescent , Risk Factors , Sex Distribution , Health Surveys , Occupations/statistics & numerical data , Occupations/classification , Prevalence , Sociodemographic Factors , Self Report
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