Data mining approaches for type 2 diabetes mellitus prediction using anthropometric measurements.

BACKGROUND: The aim of this study was to evaluate the anthropometric measurements most associated with type 2 diabetes mellitus (T2DM) using machine learning approaches. METHODS: A prospective study was designed for a total population of 9354 (43% men and 57% women) aged 35-65. Anthropometric measurements include weight, height, demispan, Hip Circumference (HC), Mid-arm Circumference (MAC), Waist Circumference (WC), Body Roundness Index (BRI), Body Adiposity Index (BAI), A Body Shape Index (ABSI), Body Mass Index (BMI), Waist-to-height Ratio (WHtR), and Waist-to-hip Ratio (WHR) were completed for all participants. The association was assessed using logistic regression (LR) and decision tree (DT) analysis. Receiver operating characteristic (ROC) curve was performed to evaluate the DT's accuracy, sensitivity, and specificity using R software. RESULTS: Traditionally, 1461 women and 875 men with T2DM (T2DM group). According to the LR, in males, WC and BIA (p-value < 0.001) and in females, demispan and WC (p-value < 0.001) had the highest correlation with T2DM development risk. The DT indicated that WC has the most crucial effect on T2DM development risk, followed by HC, and BAI. CONCLUSIONS: Our results showed that in both men and women, WC was the most important anthropometric factor to predict T2DM.

Adherence to dietary approaches to stop hypertension (DASH) diet in relation to psychological function in recovered COVID-19 patients: a case-control study.

BACKGROUND: Follow-up of patients after recovery from coronavirus disease 2019 (COVID-19) and identifying the adverse effects of the disease in other organs is necessary. Psychiatric symptoms can persist after patients recover from the infection. AIM: We aimed to examine the adherence to the dietary approach to stop hypertension (DASH) diet in relation to psychological function in individuals who have recovered from COVID-19. METHOD: This case-control study was conducted on 246 eligible adults (123 cases and 123 controls). A valid and reliable food frequency questionnaire (FFQ) was used to determine dietary intake. Depression, anxiety and stress, insomnia, sleep quality, and quality of life of participants were evaluated using DASS, Insomnia Severity Index (ISI), Pittsburgh Sleep Quality Index (PSQI), and SF-36 questionnaires, respectively. RESULTS: There was a significant inverse correlation between total depression score with vegetables, depression, anxiety, and stress score and dietary intake of nuts, legumes, and whole grains (p < 0.05). There was a significant positive correlation between stress scores and the intake of red and processed meat (P < 0.05). In multivariate-adjusted regression model, a significant association was found between adherence to DASH diet and depression and stress only in case group (OR = 0.7863, 95% CI 0.746-0.997, p = 0.046 and OR = 0.876, 95% CI 0.771-0.995, p = 0.042, respectively). CONCLUSION: Adherence to a DASH diet might be associated with depression and stress reduction in recovered COVID-19 patients.