(1) Background: Metabolic syndrome is associated with cardiovascular complications. Therefore, this study aims to establish cut points for the conicity index based on the components of metabolic syndrome and to associate it with characteristic sociodemographic, food consumption and occupational factors in Brazilian rural workers; (2) Methods: A cross-sectional study carried out with farmers. The receiver operating characteristic curve was calculated and the cut-off points for the conicity index were identified by the area under the curve, sensitivity and specificity. The variables included in the binary logistic regression analysis were selected by considering p < 0.20 in the bivariate test; (3) Results: The cut points were similar in females according to both criteria, resulting in a single cut-off of 1.269. In males, the cut points showed differences, resulting in 1.272 according to the NCEP-ATP III and 1.252 according to the IDF. We have shown that younger people, those who work more than 40 h a week and the lowest contribution of culinary ingredients are associated with increased odds of abdominal obesity, while the consumption of the products they sell or produce decreases these chances; (4) Conclusions: The conicity index showed high discriminatory power for the identification of abdominal obesity in rural workers. Therefore, there is a need to improve eating habits and promote healthier eating environments for individuals, respecting traditional food culture, mainly to contain the advance of MS in rural areas.
Background The conicity index is indicated as a tool for assessing the nutritional status of renal individuals undergoing hemodialysis. Thus, this study aimed to estimate the prevalence of abdominal obesity using the conicity index in individuals with chronic kidney disease undergoing hemodialysis to verify its association with sociodemographic, clinical, and lifestyle factors. Materials and methods This is a cross-sectional study with 941 individuals undergoing hemodialysis in a metropolitan area in southeastern Brazil. The conicity index was estimated and cutoffs of 1.275 and 1.285 for men and women, respectively, were used. For the analysis of the results, binary logistic regression was performed and the odds ratio (OR) was estimated with their respective confidence intervals (95% CI). Results The conicity index was high in 56.54% of men (95% CI: 34.34–70.16) and 43.46% of women (95% CI: 38.45–55.20). We found that both adult men (OR = 3.71; 95% CI: 2.27–6.07) and adult women (OR = 4.06; 95% CI: 2.41–6.84) were more likely to have abdominal obesity, as well as self-declared mixed-raced (OR: 1.74; 95% CI: 1.01–3.00) and single men (OR: 1.64; 95% CI: 1.00–2.68). Conclusions The conicity index is an important anthropometric indicator to estimate abdominal obesity in individuals with chronic kidney disease on hemodialysis.
Introduction Part of the patients infected by COVID-19 have at least one lasting sequel of the disease and may be framed in the concept of long Covid. These sequelae can compromise the quality of life, increase dependence on other people for personal care, impair the performance of activities of daily living, thus compromising work activities and harming the health of the worker. This protocol aims to critically synthesize the scientific evidence on the effects of Covid-19 among workers and its impact on their health status and professional life. Method Searches will be performed in MEDLINE via PubMed, EMBASE, Cochrane Library Central, Web of Science, Scopus, LILACS and Epistemonikos. Included studies will be those that report the prevalence of long-term signs and symptoms in workers and/or the impact on their health status and work performance, which may be associated with Covid-19 infection. Data extraction will be conducted by 3 reviewers independently. For data synthesis, a results report will be carried out, based on the main outcome of this study. Discussion This review will provide evidence to support health surveillance to help decision makers (i.e. healthcare providers, stakeholders and governments) regarding long-term Covid. Trial registration PROSPERO registration number: CRD42021288120. https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021288120.
Background Self-rated health status can be considered a good predictor of morbidity and mortality and has been used due to its easy assessment and applicability. The instrument is efficient for understanding sociodemographic, environmental and clinical conditions that may be related to the self-rated health status. Thus, this study aims to analyze the self-assessment of health status in rural workers and its association with socioeconomic characteristics, lifestyle, clinical condition and work characteristics. Methods This is a cross-sectional study carried out with 787 male and female rural reporting agriculture as their main source of income in the municipality of Santa Maria de Jetibá. A simple and direct question was used “In general, compared to people your age, how do you rate your own state of health?” to see how rural workers rate their current health status. The independent variables analyzed were socioeconomic, clinical, health and work conditions. The magnitude of the associations was evaluated by means of hierarchical logistic regression. Results It was found that 42.1% of rural workers self-rated their health status as regular or poor. Belonging to socioeconomic classes C (OR = 1.937; 95% CI = 1.009–3.720) or D/E (OR = 2.280; 95% CI = 1.178–4.415), being overweight (or having excess weight) (OR = 1.477; 95% CI = 1.086–2.008), multimorbidity (OR = 1.715; 95% CI = 1.201–2.447) and complex multimorbidity (OR = 1.738; 95% CI = 1.097–2.751) were risk factors for worse self-rated health. Conclusion It was concluded that chronic diseases, socioeconomic status and overweight are risk factors for negative self-rated health. The identification of these determinants through self-rated status can support the planning of actions aimed at improving the health of the rural population. Trial registration This study was approved by the Research Ethics Committee of the Health Sciences Center of the Federal University of Espírito Santo (Protocol No. 2091172; CAAE No. 52839116.3.0000.5060). All research participants gave their informed consent.
No abstract
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.