Coocorrência de fatores de risco à saúde em universitários de uma instituição de ensino superior brasileira

Sousa, Thiago Ferreira de; Loch, Mathias Roberto; Lima, Alexandre Justo de Oliveira; Franco, Dayana Chaves; Barbosa, Aline Rodrigues

doi:10.1590/1413-81232021262.07062019

Cited by 8 publications

(7 citation statements)

References 20 publications

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“…Students in the pre-clinical phase of medical education and in the 18-20 years age bracket presented with higher total Fantastic lifestyle scores when compared with students in later phases of medical education and in older age brackets. This corroborates previous data that state that as students age and progress further into higher-education, lifestyles have a propensity towards being augmented with risky behaviors [ 31 , 32 ]. Thus, the pre-clinical phase of medical education may present itself as a promising moment for lifestyle interventions focused on preventing such decline, but it is important to focus on interventions other than only formal education, as it alone appears to be ineffective in preventing worsening lifestyle behaviors over the course of time [ 33 ].…”

Section: Discussionsupporting

confidence: 91%

Associations between Lifestyle and Sociodemographic Factors in Medical Students: A Cross Sectional Study

Andraus,

Vieira,

Candido

et al. 2023

JLM

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Background Identifying lifestyle characteristics in higher education can lead to effective interventions that benefit both individuals and communities. Methods This cross-sectional survey-based study was conducted on medical students of a private university using the Fantastic Lifestyle Questionnaire (FLQ) to assess healthy lifestyles, as well as a custom sociodemographic questionnaire. Additionally, correlations among sociodemographic factors and alcohol intake, activity, tobacco and toxins, family and friends, insight, nutrition, type of behavior, career, sleep, seatbelt, stress, and safe sex domains were assessed. Results This study assessed 188 lifestyle profiles, of which 148 have complete data for evaluating the total FLQ score. The majority of evaluated lifestyles were characterized as “good (42.5%)” and “very good (35.8%)”, and correlations were identified between the total FLQ score and between the preclinical and later course phases, the 18-20 years and older age brackets, and any romantic relationship and being single. Additional associations were observed for the other domains with other sociodemographic factors. Conclusion Medical students frequently present with a lifestyle that may be improved through various targeted interventions.

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Section: Discussionsupporting

confidence: 91%

Associations between Lifestyle and Sociodemographic Factors in Medical Students: A Cross Sectional Study

Andraus,

Vieira,

Candido

et al. 2023

JLM

View full text Add to dashboard Cite

show abstract

“…However, the analysis of the sample power of this study demonstrates that between the categories of one and two risk behaviors there is an inadequately sample size to confirm such an association. Although this study did not find associations between one and two risk behaviors, in other studies these risk behaviors isolated 2,15 or combined into two variables 20,39,40 were described as health risk characteristics, which influence a negative SRH. Thus, it is suggested that the co-occurrence of two risk behaviors in health promotion at the university should not be disregarded, with a view to improving SRH.…”

Section: Discussioncontrasting

confidence: 65%

Prevalence of negative self-rated health in university students and its relationship with the co-occurrence of risk behaviors

et al. 2022

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The present study estimate the prevalence of negative self-rated health and to analyze its association with simultaneous risk behaviors (insufficient levels of physical activity, greater exposure to sedentary time and inappropriate sleep time) in students at a public university in the state from Minas Gerais, Brazil. It consists of cross-sectional study, with data collected through a questionnaire. The outcome variable was negative self-rated health. The independent variables were estimated by the questions related to the time spent on physical activity, sitting and sleep time, and these three behaviors were considered according to the risk criteria (none, one, two and three risk behaviors). The association was estimated by the Prevalence Ratios (PR), via Poisson regression. 1,110 students participated in the study. The prevalence of negative self-rated health among university students was 47.3%, and the prevalence of two risk behaviors and three risk behaviors were 41.3% and 11.3%, respectively. The simultaneous occurrence of three risk behaviors was associated with negative self-rated health in university students. The information in this study makes it possible to characterize the need for actions to promote health in the university environment.

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“…Evidence shows that the prevalence of simultaneous exposure to health risk behaviors increases with age, 9,46 since young people acquire greater autonomy and economic independence with advancing age. 9 However, this association has not been well established in the literature.…”

Section: Discussionmentioning

confidence: 99%

Age, skin color, self-rated health, and depression associated with co-occurrence of obesogenic behaviors in university students: a cross-sectional study

et al. 2023

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BACKGROUND: The university context plays an important role in the health-disease process since students are potentially vulnerable to obesogenic behaviors that can influence long-term health. OBJECTIVE: To estimate the prevalence of and factors associated with the co-occurrence of obesogenic behaviors among university students. DESIGN AND SETTING: This was a cross-sectional study at a Brazilian public university. METHODS: This study was conducted with all university students in the first and second semesters of 2019 at Universidade Federal de Ouro Preto, Minas Gerais, Brazil. Data were collected between April and September 2019, using a self-administered questionnaire. The outcome was the co-occurrence of obesogenic behaviors, measured as the sum of three risk behaviors: inadequate eating practices, leisure-time physical inactivity, and sedentary behavior. A Venn diagram was used to evaluate the simultaneous occurrence of risk behaviors. Pearson's chi-square test and multivariate logistic regression were used for statistical analyses. RESULTS: A total of 351 students participated in the study. Inadequate eating practices constituted the most prevalent isolated risk behavior (80.6%), which was also the most prevalent when combined with sedentary behavior (23.6%). University students aged 20 years or younger, with non-white skin color, poor self-rated health, and symptoms of depression had increased chances of simultaneous occurrence of obesogenic behaviors. CONCLUSION: These findings highlight the importance of developing and implementing actions to reduce combined obesogenic behaviors in the university environment. Institutions should focus on creating an environment that promotes health-protective behaviors such as physical activity and healthy eating.

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Coocorrência de fatores de risco à saúde em universitários de uma instituição de ensino superior brasileira

Cited by 8 publications

References 20 publications

Associations between Lifestyle and Sociodemographic Factors in Medical Students: A Cross Sectional Study

Associations between Lifestyle and Sociodemographic Factors in Medical Students: A Cross Sectional Study

Prevalence of negative self-rated health in university students and its relationship with the co-occurrence of risk behaviors

Age, skin color, self-rated health, and depression associated with co-occurrence of obesogenic behaviors in university students: a cross-sectional study

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