ABSTRACT
The purpose of the cross-sectional study was to identify patterns of modifiable lifestyle behaviors and examine the relationship between sociodemographic characteristics and distinct lifestyle behaviors. The data were gathered from the National Health Survey 2019, a study that included adults with diabetes. Four domains of lifestyle behaviors were used to define these behaviors: smoking, alcohol consumption, physical activity, and diet. The association between patterns of lifestyle behaviors and variables of interest was assessed using multinomial regression analysis. The three lifestyle patterns identified were: Class 1, referred to as "unhealthy diet," comprised 17.0% of the sample and was characterized by unhealthy eating habits; Class 2 (less active and insufficient fruit and vegetable intake) represented 71.2% of the sample; Class 3 referred to as "low risk" (11.8%) is characterized by a lower probability of engaging in most risky behaviors. A person over 45 years of age with little or no education and no health care coverage was less likely to be a member of Class 1. Male individuals who do not attend a doctor regularly exhibited more chances of belonging to Class 2. Mixed-race individuals aged 45 years or more with a low level of education have a lower chance of belonging to this class.
Subject(s)
Diabetes Mellitus , Life Style , Adult , Humans , Male , Middle Aged , Latent Class Analysis , Brazil/epidemiology , Cross-Sectional Studies , Diet , Diabetes Mellitus/epidemiologyABSTRACT
Abstract The purpose of the cross-sectional study was to identify patterns of modifiable lifestyle behaviors and examine the relationship between sociodemographic characteristics and distinct lifestyle behaviors. The data were gathered from the National Health Survey 2019, a study that included adults with diabetes. Four domains of lifestyle behaviors were used to define these behaviors: smoking, alcohol consumption, physical activity, and diet. The association between patterns of lifestyle behaviors and variables of interest was assessed using multinomial regression analysis. The three lifestyle patterns identified were: Class 1, referred to as "unhealthy diet," comprised 17.0% of the sample and was characterized by unhealthy eating habits; Class 2 (less active and insufficient fruit and vegetable intake) represented 71.2% of the sample; Class 3 referred to as "low risk" (11.8%) is characterized by a lower probability of engaging in most risky behaviors. A person over 45 years of age with little or no education and no health care coverage was less likely to be a member of Class 1. Male individuals who do not attend a doctor regularly exhibited more chances of belonging to Class 2. Mixed-race individuals aged 45 years or more with a low level of education have a lower chance of belonging to this class.
Resumo Neste estudo de caráter transversal objetivou-se identificar os padrões de comportamento de estilo de vida e sua associação com características sociodemográficas. Utilizou-se como base de dados a Pesquisa Nacional de Saúde de 2019, com adultos (≥ 18 anos) diabéticos. Os padrões de saúde foram definidos pela Análise de Classes Latentes em quatro domínios: tabagismo, consumo de bebidas alcoólicas, atividade física e alimentação. Foi aplicada análise de regressão multinominal para identificar a associação entre os padrões de comportamento e as variáveis sociodemográficas de interesse. Identificou-se três padrões de comportamento: a Classe 1 corresponde a 17% da amostra e compreende indivíduos com maior probabilidade de comportamentos de risco ligados à alimentação; a Classe 2 (baixos nível de atividade física e consumo de frutas e hortaliças) compreende 71,2% da amostra; e a Classe 3 (11,8% da população) reúne os indivíduos com menor chance de desenvolver comportamentos de risco. Indivíduos com 45 anos ou mais, com baixa escolaridade e sem plano de saúde têm menos chances de pertencer à Classe 1. Homens, que não fazem visitas regulares ao médico têm maiores chances de pertencer à Classe 2, bem como aqueles com 45 anos ou mais, com baixa escolaridade.
ABSTRACT
OBJECTIVE: To analyze the relationship between parity, pre-pregnancy body mass index (BMI), and gestational weight gain (GWG). METHODS: This observational controlled study was conducted from November 2013 to April 2014, with postpartum women who started antenatal care up to 14 weeks and had full-term births. Data were collected from medical records and antenatal cards. Descriptive and bivariate analyses were performed. The significance level was 5%. RESULTS: Data were collected from 130 primiparous and 160 multiparous women. At the beginning of prenatal care, 54.62% of the primiparous were eutrophic, while the majority of multiparous were overweight or obese (62.51%). Multiparas are two times more likely to be obese at the beginning of their pregnancies, when compared to primiparas. The average pre-pregnancy weight and final pregnancy weight was significantly higher in multiparous, however, the mean GWG was higher among primiparous. CONCLUSION: We found an inverse correlation between parity and the total GWG, but initial BMI was significantly higher in multiparas. Nevertheless, monitoring of the GWG through actions that promote a healthier lifestyle is needed, regardless of parity and nutritional status, in order to prevent excessive GWG and postpartum weight retention and consequently inadequate pre-pregnancy nutritional status in future pregnancies.
