The challenge of assessing physical activity in an ageing
population
Paul Innerd
Clinical Exercise Physiologist
University of Sunderland
When carrying out measurement, it is essential that the researcher understands…
…what is being measured…
…and what factors may affect the accuracy of the method
Tait (2011)
“The progressive loss of function…risk of morbidity and mortality “.
Franco, Catt, Kirkwood. BMC Geriatrics 2007, 7:10
WHO: The World Health Report:2003: Shaping the future.
Metabolic control Proprioception
Insulin sensitivity
Physical function
Chronic disease A loss of ADL’s and IADL
Cognitive decline
Energy expenditure
Basal metabolic rate
Inflammatory factors
Sarcopenia
Immunity
Bone mineral density
The ageing population: a demographic shift
Christenson K. et al. Lancet 2009 3; 374(9696): 1196–1208
Until 1920s: Improvements in infant and childhood survival combating of infectious diseases at young ages Since 1950s: Improvements in clinical care
The ageing population: a demographic shift
Christenson K. et al. Lancet 2009 3; 374(9696): 1196–1208
Accelerometry
Use of raw accelerometry data
Standardised of analytical methods
Wijndaele et al . Utilization and Harmonization of Adult Accelerometry Data: Review and Expert Consensus. MedSciSpEx. 2015
The move toward raw accelerometry
Used in:
UKBiobank (n=250,000)
Whitehall II (n=3,975)
Newcastle 85+ (n=357)
Pelotas Birth Cohort (n=8,974)
Most commonly used to estimate activity intensity:
• Light
• Moderate
• Moderate to vigorous PA (MVPA)
Are specific cut-points needed for older people?
Does this differ according to body placement?
Paul Innerd, Vincent van Hees, Mike Catt, Mike Trenell MoveLab, Newcastle University
Age group comparison
Age 25-35 Age 65-75
12 activities of daily living (ADLs)
Accelerometer worn on
both wrists,
chest , waist,
both ankles
Cut-points for MVPA
Study Age Body placement
Cut-point (millig)
Hildebrand et al 8.9±0.9years Right wrist 191.6
Waist 152.8
Hildebrand et al 34 ±11years Right wrist 93.2
Waist 68.7
Innerd et al 28 ± 3 Right wrist 94.3
Waist 73.5
65 ± 9 Right wrist 72.3
Waist 42.9
Hildebrand et al. MedSciSpEx. 2014 What about the very old? Innerd et al (in preparation)
Thanks to…
Mike Trenell Professor of Movement and Metabolism
Dr Vincent van Hees
Dr Amanda West Associate Dean
Carol Jagger AXA Professor of Epidemiology of Ageing
Sir Professor Tom Kirkwood, Associate Dean for Ageing
Mike Catt Professor of Translational Research
Anne Crosland Professor of Nursing
Scott Wilkes Professor of General Practice and Primary Care
Amanda West Head of department Associate Dean
Conclusion
Age specific cut-points produce high levels of classification accuracy for MVPA
Children
Young
Old
We have used raw accelerometers to estimate physical activity, sedentary time, activity classification with the 85+ age group.