Fatemeh Karimimanesh, Dr Mohammad Davarpanah Jazi, Dr Nooshin Mohammadifard,
Volume 5, Issue 2 (10-2017)
Abstract
Background & Objective: Health databases contain a large amount of clinical data. Investigating the relationships and patterns in these databases can lead to new medical knowledge. Nutrition indicators are designed to evaluate the dietary quality in communities. Metabolic syndrome is a set of risk factors which may increase the risk of heart disease. Inappropriate diet is one of the most important factors in the occurrence of metabolic syndrome. The health industry is constantly producing a large amount of data in medical areas which requires a technique to disclose useful information and important relationships. The aim of this study was to compare the dietary diversity score (DDS) with healthy eating index (HEI) in terms of nutrient intake and assessing the association with metabolic syndrome with the approach of data mining.
Methods: A total of 1019 teenagers between the ages of 11 to 18 years were enrolled in this study. Data were collected using a past 24-hour food frequency questionnaire (FFQ). Nutrition data collection and determination of anthropometric characteristics and medical examinations were performed in Isfahan Cardiovascular Institute. Data were analyzed by TANAGRA data mining tool.
Results: Statistical, regression and classification techniques were used for data exploration. The average score of DDS was 3.98 ± 1.10, while the HEI average was 59.23 ± 8.84 and the prevalence of metabolic syndrome was 17.39%. The average of DDS provided a better nutritional value in comparison to HEI. HEI was more robust in controlling received energy and carbohydrates. DDS was not significantly correlated with any of the components of metabolic syndrome, while HEI was weakly correlated with high waist circumference. High quartiles of HEI could predict a lower risk of metabolic syndrome, while high quartiles of DDS can predict higher risk of metabolic syndrome.
Conclusion: The findings of this study revealed that the DDS score may result in better nutrition uptake while adhering to the HEI was more effective in reducing the risk of metabolic syndrome.
Hamid Reza Zolfi, Amir Shakib, Zahra Niknam, Zhaleh Pashaei,
Volume 11, Issue 3 (12-2023)
Abstract
Background: Metabolic syndrome, a problem of the present age, is a combination of several medical issues, and miRNAs play important regulatory roles in metabolic syndrome. Many studies indicate that high-intensity interval training (HITT) may improve risk factors for metabolic syndrome.
This study aimed to investigate the effect of 8 weeks of HIIT training on the changes in miR-21, miR-122, alanine aminotransferase (ALT), aspartate aminotransferase (AST), low-density lipoprotein (LDL), lipid profile, and glucose.
Methods: In this quasi-experimental study, middle-aged male (n=19) volunteers with metabolic syndrome (body mass index (BMI)>30) were randomly assigned to the control (n=9) and training (n=10) groups. The training program consisted of 8 weeks of HIIT training with 4 sets of workouts with an intensity of 80-90% heart rate for the training group (3 sessions per week during the first 4 weeks and 4 sessions per week during the second 4 weeks). Blood samples were collected from the subjects 48 hours before and after the last training session to analyze miR-21, miR-122, ALT, AST, HDL, LDL, triglyceride, cholesterol, and glucose. The within-group and between-group differences of data were analyzed using the paired t-tests and analysis of covariance at a significance level of P˂0.05 in SPSS software.
Results: This study indicated that HIIT caused a significant decrease in miR-122, ALT, AST, triglyceride, cholesterol, glucose, body weight indicators, fat percentage, and BMI (P˂0.05). Also, a significant increase in miR-21 and HDL levels was observed following HIIT training (P˂0.05).
Conclusion: HIIT training seems essential in metabolic changes, such as reducing the lipid profile, decreasing glucose, and improving liver damage by affecting miR-21 and miR-122 indicators as small regulatory transcripts. However, more extensive studies are needed in this field.
