Dataset Of Dietary Patterns, Anthropometric Indices, and Biochemical Markers in Adults with Non-Alcoholic Fatty Liver Disease: Insights for Metabolic Health Research
Description
This dataset, includes data from 280 adults (18–65 years) with NAFLD, recruited from Gonabad University of Medical Sciences, Iran, in 2024. It examines dietary patterns, anthropometric indices, biochemical markers, and NAFLD severity to inform nutritional interventions for metabolic health. Overview Embedded in the article, the dataset comprises three tables with raw and adjusted data (corrected for age, sex, physical activity). Collected via standardized methods (questionnaires, 24-hour dietary recalls, clinical measurements, ultrasonography), it includes demographic, anthropometric, dietary, physical activity, biochemical, and NAFLD severity data, supporting diverse statistical analyses. Tables Table 1: Participant CharacteristicsFor 280 participants: Demographic: Age (46.06 ± 12.37 years), sex (63.6% female), education (47.1% higher). Anthropometric: BMI (29.19 ± 4.14 kg/m²), waist circumference (100.99 ± 9.24 cm). Dietary: Energy intake (2899.61 ± 783.33 kcal) via three 24-hour recalls. Physical Activity: Levels (63.2% low, 30.7% moderate, 6.1% high). Biochemical: Triglycerides (186.32 ± 84.66 mg/dL), cholesterol (193.97 ± 37.65 mg/dL), LDL-C (113.74 ± 30.02 mg/dL), HDL-C (42.12 ± 11.68 mg/dL), glucose (95.35 ± 8.71 mg/dL), ALT (54.69 ± 32.35 U/L), AST (37.19 ± 19.06 U/L). NAFLD Severity: Grades (24.6% grade 1, 63.2% grade 2, 12.2% grade 3). Table 2: Food Groups and Factor LoadingsLists 23 food groups (e.g., vegetables, red meat) with factor loadings (>0.2) for healthy and unhealthy dietary patterns (KMO: 0.571; Bartlett’s: χ² = 1074.60, p < 0.001). Table 3: Associations with Metabolic FactorsShows dietary pattern associations with BMI, HDL-C, cholesterol, and NAFLD grades via regression (e.g., healthy pattern: lower BMI, p=0.041; higher HDL-C, p=0.040; unhealthy pattern: higher cholesterol, p=0.007). Data Collection Participants had NAFLD, no chronic diseases, special diets, smoking, or alcohol use. Methods: Demographic: Questionnaires. Anthropometric: Seca scale, wall-mounted tape. Dietary: 24-hour recalls. Physical Activity: IPAQ-SF. Biochemical: Blood analysis (Pars Azmoon kit). NAFLD: Samsung RS80A ultrasonography. Accessibility Available at https://data.mendeley.com/drafts/tgfp8r7d7g, with an SPSS output file for analysis. Supports exploratory analyses, interventions, meta-analyses, and policy development. Value From an underrepresented region, this dataset informs NAFLD research with reliable data, despite limitations (e.g., sampling bias, recall bias, cross-sectional design). Ethics Follows Declaration of Helsinki, with consent and approval (IR.TBZMED.REC.1402.750). Supported by Nutrition Research Center, Tabriz (ID: 73108). ***The dataset is also provided as an SPSS output file, facilitating direct statistical analysis for researchers using SPSS software.
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Steps to reproduce
To replicate this dataset, recruit 280 adults (18–65 years) with NAFLD from a clinical center in Gonabad, Iran, using convenience sampling via gastroenterologist referrals. Ensure inclusion criteria: NAFLD diagnosed by ultrasonography, no chronic diseases, special diets, smoking, alcohol use, or pregnancy/breastfeeding. Obtain ethics approval and informed consent (per Declaration of Helsinki). Collect data as follows: - Demographic: Use structured questionnaires for age, sex, marital status, education, and employment. - Anthropometric: Measure weight (Seca scale, 0.1 kg precision), height (wall-mounted tape, 0.5 cm accuracy), calculate BMI, and measure waist circumference at the midpoint between the lowest rib and iliac crest. - Dietary: Conduct three 24-hour dietary recalls (two weekdays, one weekend) using standard nutritional protocols. - Physical Activity: Administer the IPAQ-SF to categorize activity levels (low, moderate, high) in MET-min/week. - Biochemical: Collect blood after a 10–12-hour fast, analyze fasting glucose, triglycerides, total cholesterol, HDL-C, LDL-C (Friedewald equation), ALT, and AST using enzymatic colorimetric methods (Pars Azmoon kit). -NAFLD Severity: Perform liver ultrasonography (Samsung RS80A) to confirm diagnosis and grade severity (1–3). Analyze data using SPSS (Version 19) with linear and ordinal regression, adjusting for age, sex, and physical activity. Present results in three tables: participant characteristics, food group factor loadings, and associations with metabolic factors and NAFLD severity. Ensure data accessibility within the article.
Institutions
- Tabriz University of Medical SciencesEast Azerbaijan, Tabriz