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Metabolic syndrome in fixed-shift workers

OBJECTIVE: To analyze if metabolic syndrome and its altered components are associated with demographic, socioeconomic and behavioral factors in fixed-shift workers. METHODS: A cross-sectional study was conducted on a sample of 902 shift workers of both sexes in a poultry processing plant in Southern...

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Detalles Bibliográficos
Autores principales: Canuto, Raquel, Pattussi, Marcos Pascoal, Macagnan, Jamile Block Araldi, Henn, Ruth Liane, Olinto, Maria Teresa Anselmo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Faculdade de Saúde Pública da Universidade de São Paulo 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4544368/
https://www.ncbi.nlm.nih.gov/pubmed/26061455
http://dx.doi.org/10.1590/S0034-8910.2015049005524
Descripción
Sumario:OBJECTIVE: To analyze if metabolic syndrome and its altered components are associated with demographic, socioeconomic and behavioral factors in fixed-shift workers. METHODS: A cross-sectional study was conducted on a sample of 902 shift workers of both sexes in a poultry processing plant in Southern Brazil in 2010. The diagnosis of metabolic syndrome was determined according to the recommendations from Harmonizing the Metabolic Syndrome. Its frequency was evaluated according to the demographic (sex, skin color, age and marital status), socioeconomic (educational level, income and work shift), and behavioral characteristics (smoking, alcohol intake, leisure time physical activity, number of meals and sleep duration) of the sample. The multivariate analysis followed a theoretical framework for identifying metabolic syndrome in fixed-shift workers. RESULTS: The prevalence of metabolic syndrome in the sample was 9.3% (95%CI 7.4;11.2). The most frequently altered component was waist circumference (PR 48.4%; 95%CI 45.5;51.2), followed by high-density lipoprotein. Work shift was not associated with metabolic syndrome and its altered components. After adjustment, the prevalence of metabolic syndrome was positively associated with women (PR 2.16; 95%CI 1.28;3.64), workers aged over 40 years (PR 3.90; 95%CI 1.78;8.93) and those who reported sleeping five hours or less per day (PR 1.70; 95%CI 1.09;2.24). On the other hand, metabolic syndrome was inversely associated with educational level and having more than three meals per day (PR 0.43; 95%CI 0.26;0.73). CONCLUSIONS: Being female, older and deprived of sleep are probable risk factors for metabolic syndrome, whereas higher educational level and higher number of meals per day are protective factors for metabolic syndrome in fixed-shift workers.