OBJECTIVE: To determine the relationship between metabolic syndrome (MS) and socioeconomic level, life style, health status, family history of morbidity, and residence areas. METHODS: This is a cross-sectional cohort study. The random sample consisted of users of two primary health care units (Unidades Básicas de Saúde--UBSs) in the city of São Paulo--Jardim Comercial (UBS1), and Jardim Germânia (UBS2), a total of 452 subjects. The NCEP ATP IIIcriterion was used to diagnose MS. Weight, height, abdominal and hip circumferences were measured for the anthropometric evaluation. A general questionnaire was used to obtain sociodemographic and socioeconomic data; family history; medical history; behavioral habits such as smoking, drinking, and physical activity. Multivariate logistic regression was used to establish the association between explanatory variables of interest and MS. RESULTS: At UBS1, MS percentage was 56.1%; at UBS2, 34.0%. There was a direct and significant association between MS and age, female gender, race, smoking, drinking, physical activity level, stress, and family history of heart disease and diabetes mellitus. Education level showed an inverse association. Subjects living in a lower socioeconomic level neighborhood had a higher MS risk. CONCLUSION: The results suggest that the morbidities that compose MS are a serious publichealth problem in that population.
OBJECTIVE: To determine the relationship between metabolic syndrome (MS) and socioeconomic level, life style, health status, family history of morbidity, and residence areas. METHODS: This is a cross-sectional cohort study. The random sample consisted of users of two primary health care units (Unidades Básicas de Saúde--UBSs) in the city of São Paulo--Jardim Comercial (UBS1), and Jardim Germânia (UBS2), a total of 452 subjects. The NCEP ATP IIIcriterion was used to diagnose MS. Weight, height, abdominal and hip circumferences were measured for the anthropometric evaluation. A general questionnaire was used to obtain sociodemographic and socioeconomic data; family history; medical history; behavioral habits such as smoking, drinking, and physical activity. Multivariate logistic regression was used to establish the association between explanatory variables of interest and MS. RESULTS: At UBS1, MS percentage was 56.1%; at UBS2, 34.0%. There was a direct and significant association between MS and age, female gender, race, smoking, drinking, physical activity level, stress, and family history of heart disease and diabetes mellitus. Education level showed an inverse association. Subjects living in a lower socioeconomic level neighborhood had a higher MS risk. CONCLUSION: The results suggest that the morbidities that compose MS are a serious publichealth problem in that population.
Authors: Anh D Ngo; Catherine Paquet; Natasha J Howard; Neil T Coffee; Robert Adams; Anne Taylor; Mark Daniel Journal: BMC Public Health Date: 2013-07-25 Impact factor: 3.295
Authors: Anh D Ngo; Catherine Paquet; Natasha J Howard; Neil T Coffee; Anne W Taylor; Robert J Adams; Mark Daniel Journal: Int J Environ Res Public Health Date: 2014-01-08 Impact factor: 3.390
Authors: Amália Ivine Costa Santana; Magno Conceição das Merces; Lucélia Batista Neves Cunha Magalhães; André Luiz Brandão Costa; Argemiro D'Oliveira Journal: Rev Bras Med Trab Date: 2020-12-11
Authors: Marina Zamuner; Walker Wendell Laranja; João Carlos Cardoso Alonso; Fabiano A Simões; Ronald F Rejowski; Leonardo O Reis Journal: Adv Urol Date: 2014-01-23