Walking into aging: real-world mobility patterns and digital benchmarks from the InCHIANTI Study.

Area of Science:

• Gerontology
• Biomedical Engineering
• Public Health

Background:

• Mobility is essential for health and quality of life in older adults.
• Digital mobility outcomes (DMOs) from real-world walking data provide insights into functional status and early mobility decline.
• Understanding normative values and demographic influences on DMOs is crucial for clinical applications.

Purpose of the Study:

• To establish reference values for walking activity, pace, rhythm, and gait variability in community-dwelling older adults.
• To evaluate the effects of age, sex, height, and weight on these digital mobility outcomes.
• To identify age-related non-linear trends in mobility metrics.

Main Methods:

• Utilized data from 200 older adults (aged 65-94 years) from the InCHIANTI Study.
• Applied the Mobilise-D computational pipeline to analyze a week of real-world walking data.
• Performed statistical analyses to assess the impact of age, sex, height, and weight on mobility parameters.

Main Results:

• Significant differences in walking activity and gait parameters were observed between sexes and across age groups.
• Males exhibited higher walking activity in younger age groups (65-74 and 75-84 years) but not in the oldest group (85-94 years).
• Non-linear age-related trends in mobility metrics were identified, suggesting accelerated decline in specific age ranges.

Conclusions:

• Real-world walking data and DMOs provide valuable benchmarks for assessing mobility in older adults.
• Monitoring DMOs can help pinpoint critical periods of mobility decline, enabling targeted interventions.
• This research supports the use of DMOs in clinical practice and future research for understanding and managing age-related mobility changes.