Nomogram for Predicting the Risk Factors for Falls in Older People: A Secondary Data Analysis Based on the 2021...

Area of Science:

• Gerontology
• Public Health
• Epidemiology

Background:

• Falls are a significant public health concern among older adults, leading to injuries and reduced quality of life.
• Identifying modifiable risk factors is crucial for developing effective fall prevention strategies in community-dwelling elderly populations.

Purpose of the Study:

• To identify risk factors associated with falls in community-dwelling older adults.
• To develop and validate a predictive nomogram for assessing fall risk in this demographic.

Main Methods:

• A large-scale cross-sectional study involving 74,492 Korean adults aged 65 and above from the 2021 Community Health Survey.
• Statistical analyses included Rao-Scott chi-square test, complex sample t-test, and complex binary logistic regression.
• A fall-risk prediction nomogram was constructed using logistic regression coefficients and validated with Receiver Operating Characteristic (ROC) curve analysis (Area Under the Curve - AUC).

Main Results:

• The overall fall incidence rate was 16.4%.
• Significant risk factors identified included advanced age (≥85 years), living alone, receiving basic welfare, poor subjective health status, obesity, severe depression, inadequate sleep, cognitive decline, and diabetes.
• The nomogram demonstrated moderate predictive accuracy with an AUC of 0.66, with depression score, subjective health, and cognitive decline being strong predictors.

Conclusions:

• A multifactorial approach considering physical, psychological, and social determinants is essential for effective fall prevention in older adults.
• The developed nomogram serves as a valuable tool for healthcare providers to assess fall risk and implement targeted interventions and educational programs.