The challenge of assessing physical activity in an ageing population

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)

Newcastle 85+ Study

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.

The challenge of assessing physical activity in an ageing population

Paul Innerd

Clinical Exercise Physiologist

University of Sunderland