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Table 1 Details of cohort characteristics, health measures and health assessments

From: Machine learning models for identifying pre-frailty in community dwelling older adults

Demographics, environment and social factors

Physiological measures

Medical history

•Age

•Audio test

•Current health conditions

•Community participation

•Balance (8 features)

•Distress (2 features)

•Education level

•Blood pressure (2 features)

•Emergency department visits

•Gender

•Cognition test

•History of falls

•Housing type

•Current pain

•Hospitalisations

•Employment status

•Dental health (4 features)

•Medications/supplements

•Income source

•Dexterity

•Near falls

•Living arrangements

•Dizziness

•Recent surgery

•Marital status/partnerships

•Fatigue

•Unintentional weight loss

•Pet ownership

•Foot sensation

Anthropometry

•Postcode

•Functional movement

•Body Mass Index (BMI)

•Mode of transport

•screening (6 features)

•Fat mass

Lifestyle factors

•Grip strength (3 features)

•Hip circumference

•Alcohol consumption (2 features)

•Reflex test

•Muscle mass

•Current smoking

•Hearing test

•Waist circumference

•Diet quality

•Lung health (2 features)

 

•Physical activity level (9 features)

•Pelvic floor health

 
 

•Sleep quality

 
 

•Stair climbing

 
 

•6 Minute Walk Test (6MWT)

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