Diet Quality And Metabolic Syndrome In Adult Individuals: Evaluation Of Turkey Nutrition And Health Survey 2017

This study is a secondary analysis of the 2017 Turkey Nutrition and Health Survey (TNHS), which was conducted by the Ministry of Health to assess the health and nutritional status of the Turkish population. The objective of this cross-sectional observational study is to evaluate the relationship between diet quality and the presence of metabolic syndrome (MetS) among Turkish adults aged 19 years and older.

Diet quality will be assessed using several validated dietary indices, including the Healthy Eating Index-2015 (HEI-2015), the Dietary Inflammatory Index (DII), the modified Mediterranean Diet Score (MDS), and the DASH (Dietary Approaches to Stop Hypertension) score. These indices provide a comprehensive evaluation of overall dietary patterns and their potential impact on metabolic health.

Metabolic syndrome will be defined based on the Joint Interim Statement (2009) criteria. Participants will be classified as having metabolic syndrome if at least three of the following five components are present: abdominal obesity, elevated blood pressure or receiving antihypertensive treatment, reduced HDL cholesterol levels or receiving treatment for dyslipidemia, elevated triglyceride levels or receiving lipid-lowering therapy, and elevated fasting blood glucose or receiving treatment for hyperglycemia.

Statistical analysis will include descriptive statistics, t-tests or Mann-Whitney U tests for comparisons between MetS and non-MetS groups, and multivariate logistic regression analyses to determine the associations between dietary indices and the likelihood of having MetS, adjusting for relevant sociodemographic and lifestyle covariates.

Statistical analyses were conducted using SPSS version 22.0. Descriptive statistics included frequencies and percentages for categorical variables and means with standard deviations or medians with ranges for continuous variables, depending on the distribution. Normality was assessed using the Shapiro-Wilk test. Group comparisons were performed using the Mann-Whitney U test or Kruskal-Wallis test for non-normally distributed variables and the Chi-square test for categorical variables. Correlations between continuous variables were evaluated using Spearman's rank correlation coefficient. Binary logistic regression analysis was used to identify factors associated with the presence of metabolic syndrome. A p-value of <0.05 was considered statistically significant.