STATISTICAL AND MULTIVARIATE ANALYSIS OF DIETARY HABITS AND LIFESTYLE BEHAVIORS IN RELATION TO BODY WEIGHT

SALLAI MAZLLAMI, Valbona and Knights, Vesna and JANKULOSKA, Vezirka and UZUNOSKA, Zora and BLAZHEVSKA, Tatjana and VELKOVSKI, Valentina and GACOSKA, Kristina (2026) STATISTICAL AND MULTIVARIATE ANALYSIS OF DIETARY HABITS AND LIFESTYLE BEHAVIORS IN RELATION TO BODY WEIGHT. In: INTERNATIONAL CONFERENCE “FROM RESEARCH TO APPLICATION”, 20 May, 2026.

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Abstract

Dietary habits and lifestyle behaviors are important factors associated with body weight and metabolic health. Nut and seed consumption, cooking oil preference, sleep duration, and meal frequency may influence nutritional status and body-weight-related outcomes. This cross-sectional study presents a statistical analysis of dietary habits based on questionnaire responses collected from 22 participants. Descriptive statistics, Bayesian correlation, Bayesian regression, crosstab analysis, and Multiple Correspondence Analysis (MCA) were applied to investigate relationships among body weight, age, nut and seed consumption, bread intake, cooking oil usage, and lifestyle variables. The results showed an average body weight of 96.14 kg and an average age of 50.14 years among participants. Most participants reported irregular meal frequency, short sleep duration, and predominant use of sunflower oil. Bayesian analyses did not identify a reliable association between age and body weight or between meal frequency and body weight. MCA suggested that body weight, bread consumption, nut and seed intake, and cooking oil preference contributed most strongly to the latent variability structure of the dataset. The findings provide exploratory insight into dietary and lifestyle behaviors associated with body weight and may support future nutritional and public health investigations using larger population samples.

Item Type: Conference or Workshop Item (Paper)
Subjects: Q Science > Q Science (General)
Divisions: Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science
Depositing User: Unnamed user with email zshi@unite.edu.mk
Date Deposited: 23 Sep 2026 09:44
Last Modified: 23 Sep 2026 09:44
URI: http://eprints.unite.edu.mk/id/eprint/2468

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