Automated Author ProfileElyssia Karine Nunes Mendonça Ramires
Elyssia Karine Nunes Mendonça Ramires
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 0.7 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Abstract Background: In Brazil, population-based researches analyzing prevalence and factors associated with metabolic syndrome (MS), a recognized predictor of cardiovascular diseases (CVD), and an important cause of disability and death in the country are scarce. Objective: To evaluate prevalence of MS and its associated factors in Brazilian population. Methods: Secondary analysis of the 2013 National Health Survey, a cross-sectional survey with national representativeness of Brazilian adult population (n = 59,402). MS was the outcome variable, defined from harmonization of cardiology international consensus as load ≥ 3 of the following components: self-reported diabetes and hypercholesterolemia, high blood pressure and high waist circumference. Analysis were stratified by sex and prevalence ratios, with their respective 99% confidence intervals (PR [CI 99%]) calculated by simple and multiple Poisson regression models. Results: MS prevalence was 8.9%, being significantly higher among women compared to men; in general, this pattern was maintained in relation to exposure variables studied. Additionally, less than 25% of population did not present any MS component. In final multiple models, sociodemographic, behavioral and comorbidity variables were associated with MS, however, while low schooling (1.46 [1.23-1.74], cerebrovascular accident (1.36 [1], 00] (1.28 [1.03-1.62]) were associated among women, chronic renal failure (1.85 [2.23-2.76]) was associated exclusively among men. Conclusion: We identified MS high prevalence in Brazilian population; on the other hand, factors associated with this condition were different depending on sex.
Authors
- Elyssia Karine Nunes Mendonça Ramires ;
- Risia Cristina Egito De Menezes ;
- Giovana Longo-Silva ;
- Taíse Gama Dos Santos ;
- Marinho, Patrícia De Menezes ;
- Silveira, Jonas Augusto Cardoso Da
Abstract Background: In Brazil, population-based researches analyzing prevalence and factors associated with metabolic syndrome (MS), a recognized predictor of cardiovascular diseases (CVD), and an important cause of disability and death in the country are scarce. Objective: To evaluate prevalence of MS and its associated factors in Brazilian population. Methods: Secondary analysis of the 2013 National Health Survey, a cross-sectional survey with national representativeness of Brazilian adult population (n = 59,402). MS was the outcome variable, defined from harmonization of cardiology international consensus as load ≥ 3 of the following components: self-reported diabetes and hypercholesterolemia, high blood pressure and high waist circumference. Analysis were stratified by sex and prevalence ratios, with their respective 99% confidence intervals (PR [CI 99%]) calculated by simple and multiple Poisson regression models. Results: MS prevalence was 8.9%, being significantly higher among women compared to men; in general, this pattern was maintained in relation to exposure variables studied. Additionally, less than 25% of population did not present any MS component. In final multiple models, sociodemographic, behavioral and comorbidity variables were associated with MS, however, while low schooling (1.46 [1.23-1.74], cerebrovascular accident (1.36 [1], 00] (1.28 [1.03-1.62]) were associated among women, chronic renal failure (1.85 [2.23-2.76]) was associated exclusively among men. Conclusion: We identified MS high prevalence in Brazilian population; on the other hand, factors associated with this condition were different depending on sex.
Authors
- Elyssia Karine Nunes Mendonça Ramires ;
- Risia Cristina Egito De Menezes ;
- Giovana Longo-Silva ;
- Taíse Gama Dos Santos ;
- Marinho, Patrícia De Menezes ;
- Silveira, Jonas Augusto Cardoso Da