Equilibrium of Dietary Patterns Between Alzheimer's Disease Patients and Healthy People: A Comprehensive Analysis Using Multiple Factor Analysis and Classification Modeling.

Abstract

Alzheimer's disease (AD) is a particular type of dementia that currently lacks a definitive treatment and cure. It is possible to reduce the risk of developing AD and mitigate its severity through modifications to one's lifestyle, regular diet, and alcohol-drinking habits. The objective of this study is to examine the daily dietary patterns of individuals with AD compared to healthy controls, with a focus on nutritional balance and its impact on AD. This study incorporated multiple-factor analysis (MFA) to evaluate dietary patterns and employed Random Forest (RF) classifier and Sparse Logistic Regression (SLR) for Variable Importance analysis to identify food items significantly associated with AD. MFA revealed trends in the data and a strong correlation (Lg = 0.92, RV = 0.65) between the daily consumption of processed food and meat items in AD patients. In contrast, no significant relationship was found for any daily consumed food categories within the healthy control (HC) group. Food items such as meat pie, hamburger, ham, sausages, beef, capsicum, and cabbage were identified as important variables associated with AD in RF and SLR analyses. The findings from MFA indicated that the diversity or equilibrium of daily diet might play a potential role in AD development. RF and SLR classifications exhibit among the processed foods, especially deli meats and food made with meat items, are associated with AD.