Doroteia Aparecida Höfelmann1, Nelson Blank. 1. Programa de Pós-Graduação em Saúde Pública, Centro de Ciências da Saúde, Universidade Federal de Santa Catarina, Florianópolis, SC, Brasil. doroaph@yahoo.com.br
Abstract
OBJECTIVE: To analyze the prevalence of negative self-rated health and its factors associates among industrial workers. METHODS: Cross-sectional study with a probabilistic sample of 482 metal mechanic industrial workers of a city in Southern Brazil. Data was collected by means of self-administered questionnaire and anthropometric measures. The magnitude of the association between self-rated health and the study variables was estimated by odds ratio with 95% confidence intervals (95% CI). Multivariate logistic regression models were obtained using a theoretical hierarchical model. RESULTS: Response rate was 98.6%. Negative self-rated health was seen in 16.6% of the employees and most (84.8%) were males engaged in predominantly production activities (79.4%). The most common complaint was back pain (30.9%). After statistical modeling the following variables remained associated with negative self-rated health: females (OR=3.0 95% CI 1.5;6.2), physical inactivity (OR=1.8 95% CI 1.0;3.4), psychological stress (OR=3.0 95% CI 1.6;5.6), lack of control over life (OR=3.0 95% CI 1.5;6.1), reporting of one (OR=3.2 95% CI 1.4;7.2) or two or more chronic conditions (OR=7.7 95% CI 3.4;17.8), short-term medical leave (OR=2.9 95% CI 1.5;5.5), and incapacitating illness (OR=2.8 95% CI 1.2;6.6). CONCLUSIONS: The prevalence of negative self-rated health was associated with socioeconomic/demographic, lifestyle, psychosocial and health-related dimensions. The variable causing the greatest impact on the outcome was reporting of more than two chronic conditions.
OBJECTIVE: To analyze the prevalence of negative self-rated health and its factors associates among industrial workers. METHODS: Cross-sectional study with a probabilistic sample of 482 metal mechanic industrial workers of a city in Southern Brazil. Data was collected by means of self-administered questionnaire and anthropometric measures. The magnitude of the association between self-rated health and the study variables was estimated by odds ratio with 95% confidence intervals (95% CI). Multivariate logistic regression models were obtained using a theoretical hierarchical model. RESULTS: Response rate was 98.6%. Negative self-rated health was seen in 16.6% of the employees and most (84.8%) were males engaged in predominantly production activities (79.4%). The most common complaint was back pain (30.9%). After statistical modeling the following variables remained associated with negative self-rated health: females (OR=3.0 95% CI 1.5;6.2), physical inactivity (OR=1.8 95% CI 1.0;3.4), psychological stress (OR=3.0 95% CI 1.6;5.6), lack of control over life (OR=3.0 95% CI 1.5;6.1), reporting of one (OR=3.2 95% CI 1.4;7.2) or two or more chronic conditions (OR=7.7 95% CI 3.4;17.8), short-term medical leave (OR=2.9 95% CI 1.5;5.5), and incapacitating illness (OR=2.8 95% CI 1.2;6.6). CONCLUSIONS: The prevalence of negative self-rated health was associated with socioeconomic/demographic, lifestyle, psychosocial and health-related dimensions. The variable causing the greatest impact on the outcome was reporting of more than two chronic conditions.