Search

Objective: Public health surveillance is an important aspect of outbreak early warning based on prediction models. The present study compares a hybrid model based on discrete wavelet transform (DWT) and ARIMA (Autoregressive Integrated Moving Average) for predicting incidence cases due to COVID-19., Methods: In the current cross-sectional stuady based on time-series data, the incidence data for confirmed daily cases of COVID-19 from February 26, 2019, to April 25, 2022, were used. A hybrid model based on DWT and ARIMA and a pure ARIMA model were used to predict the trend. All analyzes were performed by MATLAB 2018, stata 2015, and Excel 2013 computer software., Results: Compared to the ARIMA model, the prediction results of the hybrid model were closer to the actual number of incident cases. The correlation between predicted values by the hybrid model with real data was higher than the correlation between predicted values by the ARIMA model with actual data., Conclusions: Discreet Wavelet decomposition of the dataset was combined with an ARIMA model and showed better performance in predicting the future trend., Competing Interests: None of the authors have any conflict of interest to declare., (© 2024 The Authors. Published by Elsevier Ltd.)

Background & Aim: Whey protein (WP) is one of the well-known dairy driven products to help people to change their weight and body composition (BC). This study aimed to investigate the effect of WP on weight and BC on every published RCT on all populations., Methods: A systematic review of the literature was undertaken to identify RCTs that examined the effect of WP on weight, body fat, lean body mass, fat-free mass, and waist circumference. To create weighted-group-mean differences for within- and between-group comparisons, random effects models were used. Subgroup analyses were also done to determine the effect of potential sources of heterogeneity., Results: Thirty-five RCTs, with a total of 1902 adult participants were included in pooled analysis. The effect of WP supplementation on BMI (-0.156, 95% CI: -0.31, 0.00, P < 0.05), body fat mass (-0.144, 95% CI: -0.28, 0.00, P < 0.05), and waist circumference (-0.448, 95% CI: -0.86, -0.03, P < 0.05) in within group analysis, and BMI (-0.769, 95% CI: -1.54, 0.00, P < 0.05) and lean body mass (0.741, 95% CI: 0.07, 1.41, P < 0.05) in the between group analysis was indicated. Resistance training, WP dosage, sex, age group, the type of control group (placebo, different proteins, etc.), the control group dosage, and energy intake before and during the trial, as well as between the WP and control groups, were recognized as the main sources of heterogeneity., Conclusion: The data from trials currently available supports the use of WP to improve BC indicators. The benefits of WP on BC are expected to be greatest when combined with resistance training and a reduction in overall calorie consumption., Competing Interests: Declaration of competing interest The authors declare no conflict of interest., (Copyright © 2022 European Society for Clinical Nutrition and Metabolism. Published by Elsevier Ltd. All rights reserved.)

Background: The risk of developing chronic diseases such as diabetes, cardiovascular disease, dyslipidemia, and stroke is increased following an outbreak of metabolic syndrome. Whey protein can play a major role in preventing metabolic syndrome., Objective: This study was conducted to systematically evaluate the effect of whey protein on the components of metabolic syndrome in overweight and obesity patients., Methods: This systematic review and meta-analysis was conducted on RCTs (PROSPERO registration number: CDR42019114794). Published articles of controlled trials between 1 January 2000 to 30 May 2019 indexed in PubMed, Scopus, Web of Science and Cochrane Library were reviewed. Keywords were Whey Protein, Metabolic Syndrome, HDL Lipoprotein, Blood Pressure, Triglyceride, Fasting Blood Glucose, Waist Circumference, Overweight and Obesity or a combination of them in the title/abstracts. The mean difference was extracted for each study. All analyses performed using STATA version 11., Results: There were 2344 individuals reviewed in this systematic review of 37 published articles., Conclusion: According to the results, whey supplementation significantly reduced the SBP, DBP, HDL, waist circumference, TG and FBS in intervention groups in comparing to control groups., (Copyright © 2019 Diabetes India. Published by Elsevier Ltd. All rights reserved.)