Abstract
Step length is a key indicator of gait efficiency and mobility in older adults, closely associated with fall risk, frailty, and overall health. However, most available prediction equations are based solely on height or have not undergone empirical validation, which limits their precision and applicability in aging populations. PURPOSE: This study aimed to cross-validate the newly developed Healthy Step Length Equation, which incorporates age, sex, height, weight, and walking speed, by comparing it with three commonly used height-based models to evaluate its predictive accuracy, and clinical relevance in older adults. METHODS: A total of 174 healthy, community-dwelling adults aged 65 years and older who were capable of independent ambulation and had no history of falls were included. Gait parameters were obtained using the IB-GAIT system (InBody, Seoul, Korea), which measures spatiotemporal characteristics over a 9-meter walkway under standardized conditions. Each participant performed a continuous walking trial on the walkway after a brief practice to ensure a natural and steady gait pattern. Predicted values from four equations were compared with observed measurements: (1) height × 0.45, (2) height × 0.37, (3) height – 100, and (4) the Healthy Step Length Equation (–16.14 – 0.06·Age + 0.31·Height – 0.04·Weight – 0.02·Sex + 0.30·Walking speed). Model accuracy and agreement were assessed using root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), coefficient of determination (R²), and Lin’s concordance correlation coefficient (CCC). REDULTS: The Healthy Step Length Equation demonstrated the best overall performance, showing the lowest prediction error (RMSE = 3.59 cm, MAE = 2.68 cm, MAPE = 4.19%) and the highest explanatory power and concordance (R² = 0.83, CCC = 0.90). In contrast, height-based models exhibited limited predictive capability (R² ≤ 0.18; CCC ≤ 0.33), indicating their restricted clinical utility. CONCLUSION: Integrating age, sex, body size, and walking speed markedly improves step length prediction in older adults. The Healthy Step Length Equation offers a validated and practical reference for clinical gait assessment and fall-risk screening, with potential applications in digital health and wearable monitoring.
Recommended Citation
lee, jungyu; Han, Ho; Kim, Heontae; and Diaz-Vega, Diego
(2026)
"Cross-Validating the Healthy Step Length Equation: Evaluating Prediction Accuracy in Community-Dwelling Older Adults,"
International Journal of Exercise Science: Conference Proceedings: Vol. 2:
Iss.
18, Article 36.
Available at:
https://digitalcommons.wku.edu/ijesab/vol2/iss18/36