[Purpose] This study evaluated the predictive power of Body Mass Index (BMI) for metabolic syndrome in older adults across pre-, during-, and post-COVID-19 periods, and examined the effects of metabolic syndrome factors on BMI by income level, aiming to inform elderly health management and crisis-related policies. [Methods] Data from 6,242 older adults (aged 65–80) were drawn from the 2019–2022 Korea National Health and Nutrition Examination Survey. Income was divided into quartiles, and time was segmented into pre-, during-, and post-pandemic periods. Multiple linear regression was used to assess the effects of metabolic syndrome factors (diabetes, abdominal obesity, low HDL, hypertension, hypertriglyceridemia) on BMI by income and period. Receiver Operating Characteristic (ROC) analysis evaluated BMI’s predictive power for metabolic syndrome. Significance was set at .05. [Results] Abdominal obesity and low HDL consistently influenced BMI across all groups. In the lowest income group, hypertension increasingly affected BMI during and after the pandemic. BMI Area Under the Curve (AUC) values peaked during the pandemic in this group, while the highest income group showed stable predictive power. [Conclusion] The COVID-19 pandemic had a differential impact on the association between BMI and metabolic syndrome among older adults according to income level. In low-income older adults, the predictive power of BMI for metabolic syndrome increased during the mid-pandemic period, while it remained stable across all periods in high-income groups. Systematic health management programs and policy interventions targeting low-income older adults are required to reduce health disparities during public health crises.
