A data-driven, meaningful, easy to interpret, standardised accelerometer outcome variable for global surveillance

Alex Rowlands, Lauren B. Sherar, Stuart J. Fairclough, Tom Yates, Charlotte L. Edwardson, Deirdre M. Harrington, Melanie J. Davies, Fehmidah Munir, Kamlesh Khunti, Victoria H. Stiles

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Objectives: Our aim is to demonstrate how a data-driven accelerometer metric, the acceleration above which a person's most active minutes are accumulated, can (a) quantify the prevalence of meeting current physical activity guidelines for global surveillance and (b) moving forward, could inform accelerometer-driven physical activity guidelines. Unlike cut-point methods, the metric is population-independent (e.g. age) and potentially comparable across datasets. Design: Cross-sectional, secondary data analysis. Methods: Analyses were carried out on five datasets using wrist-worn accelerometers: children (N = 145), adolescent girls (N = 1669), office workers (N = 114), pre- (N = 1218) and post- (N = 1316) menopausal women, and adults with type 2 diabetes (N = 475). Open-source software (GGIR) was used to generate the magnitude of acceleration above which a person's most active 60, 30 and 2 min are accumulated: M60ACC; M30ACC and M2ACC, respectively. Results: The proportion of participants with M60ACC (children) and M30ACC (adults) values higher than accelerations representative of brisk walking (i.e., moderate-to-vigorous physical activity) ranged from 17 to 68% in children and 15 to 81% in adults, tending to decline with age. The proportion of pre-and post-menopausal women with M2ACC values meeting thresholds for bone health ranged from 6 to 13%. Conclusions: These metrics can be used for global surveillance of physical activity, including assessing prevalence of meeting current physical activity guidelines. As accelerometer and corresponding health data accumulate it will be possible to interpret the metrics relative to age- and sex- specific norms and derive evidence-based physical activity guidelines directly from accelerometer data for use in future global surveillance. This is where the potential advantages of these metrics lie.
Original languageEnglish
Pages (from-to)1132-1138
Number of pages6
JournalJournal of Science and Medicine in Sport
Early online date1 Jul 2019
DOIs
Publication statusPublished - 1 Oct 2019

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Exercise
Guidelines
Health
Wrist
Type 2 Diabetes Mellitus
Walking
Software
Bone and Bones
Population
Datasets

Keywords

  • Acceleration
  • Measurement
  • Physical activity
  • Population
  • Research-grade accelerometer
  • Wrist-worn

Cite this

Rowlands, Alex ; Sherar, Lauren B. ; Fairclough, Stuart J. ; Yates, Tom ; Edwardson, Charlotte L. ; Harrington, Deirdre M. ; Davies, Melanie J. ; Munir, Fehmidah ; Khunti, Kamlesh ; Stiles, Victoria H. / A data-driven, meaningful, easy to interpret, standardised accelerometer outcome variable for global surveillance. In: Journal of Science and Medicine in Sport. 2019 ; pp. 1132-1138.
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abstract = "Objectives: Our aim is to demonstrate how a data-driven accelerometer metric, the acceleration above which a person's most active minutes are accumulated, can (a) quantify the prevalence of meeting current physical activity guidelines for global surveillance and (b) moving forward, could inform accelerometer-driven physical activity guidelines. Unlike cut-point methods, the metric is population-independent (e.g. age) and potentially comparable across datasets. Design: Cross-sectional, secondary data analysis. Methods: Analyses were carried out on five datasets using wrist-worn accelerometers: children (N = 145), adolescent girls (N = 1669), office workers (N = 114), pre- (N = 1218) and post- (N = 1316) menopausal women, and adults with type 2 diabetes (N = 475). Open-source software (GGIR) was used to generate the magnitude of acceleration above which a person's most active 60, 30 and 2 min are accumulated: M60ACC; M30ACC and M2ACC, respectively. Results: The proportion of participants with M60ACC (children) and M30ACC (adults) values higher than accelerations representative of brisk walking (i.e., moderate-to-vigorous physical activity) ranged from 17 to 68{\%} in children and 15 to 81{\%} in adults, tending to decline with age. The proportion of pre-and post-menopausal women with M2ACC values meeting thresholds for bone health ranged from 6 to 13{\%}. Conclusions: These metrics can be used for global surveillance of physical activity, including assessing prevalence of meeting current physical activity guidelines. As accelerometer and corresponding health data accumulate it will be possible to interpret the metrics relative to age- and sex- specific norms and derive evidence-based physical activity guidelines directly from accelerometer data for use in future global surveillance. This is where the potential advantages of these metrics lie.",
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author = "Alex Rowlands and Sherar, {Lauren B.} and Fairclough, {Stuart J.} and Tom Yates and Edwardson, {Charlotte L.} and Harrington, {Deirdre M.} and Davies, {Melanie J.} and Fehmidah Munir and Kamlesh Khunti and Stiles, {Victoria H.}",
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A data-driven, meaningful, easy to interpret, standardised accelerometer outcome variable for global surveillance. / Rowlands, Alex; Sherar, Lauren B.; Fairclough, Stuart J.; Yates, Tom; Edwardson, Charlotte L.; Harrington, Deirdre M.; Davies, Melanie J.; Munir, Fehmidah; Khunti, Kamlesh; Stiles, Victoria H.

In: Journal of Science and Medicine in Sport, 01.10.2019, p. 1132-1138.

Research output: Contribution to journalArticleResearchpeer-review

TY - JOUR

T1 - A data-driven, meaningful, easy to interpret, standardised accelerometer outcome variable for global surveillance

AU - Rowlands, Alex

AU - Sherar, Lauren B.

AU - Fairclough, Stuart J.

AU - Yates, Tom

AU - Edwardson, Charlotte L.

AU - Harrington, Deirdre M.

AU - Davies, Melanie J.

AU - Munir, Fehmidah

AU - Khunti, Kamlesh

AU - Stiles, Victoria H.

PY - 2019/10/1

Y1 - 2019/10/1

N2 - Objectives: Our aim is to demonstrate how a data-driven accelerometer metric, the acceleration above which a person's most active minutes are accumulated, can (a) quantify the prevalence of meeting current physical activity guidelines for global surveillance and (b) moving forward, could inform accelerometer-driven physical activity guidelines. Unlike cut-point methods, the metric is population-independent (e.g. age) and potentially comparable across datasets. Design: Cross-sectional, secondary data analysis. Methods: Analyses were carried out on five datasets using wrist-worn accelerometers: children (N = 145), adolescent girls (N = 1669), office workers (N = 114), pre- (N = 1218) and post- (N = 1316) menopausal women, and adults with type 2 diabetes (N = 475). Open-source software (GGIR) was used to generate the magnitude of acceleration above which a person's most active 60, 30 and 2 min are accumulated: M60ACC; M30ACC and M2ACC, respectively. Results: The proportion of participants with M60ACC (children) and M30ACC (adults) values higher than accelerations representative of brisk walking (i.e., moderate-to-vigorous physical activity) ranged from 17 to 68% in children and 15 to 81% in adults, tending to decline with age. The proportion of pre-and post-menopausal women with M2ACC values meeting thresholds for bone health ranged from 6 to 13%. Conclusions: These metrics can be used for global surveillance of physical activity, including assessing prevalence of meeting current physical activity guidelines. As accelerometer and corresponding health data accumulate it will be possible to interpret the metrics relative to age- and sex- specific norms and derive evidence-based physical activity guidelines directly from accelerometer data for use in future global surveillance. This is where the potential advantages of these metrics lie.

AB - Objectives: Our aim is to demonstrate how a data-driven accelerometer metric, the acceleration above which a person's most active minutes are accumulated, can (a) quantify the prevalence of meeting current physical activity guidelines for global surveillance and (b) moving forward, could inform accelerometer-driven physical activity guidelines. Unlike cut-point methods, the metric is population-independent (e.g. age) and potentially comparable across datasets. Design: Cross-sectional, secondary data analysis. Methods: Analyses were carried out on five datasets using wrist-worn accelerometers: children (N = 145), adolescent girls (N = 1669), office workers (N = 114), pre- (N = 1218) and post- (N = 1316) menopausal women, and adults with type 2 diabetes (N = 475). Open-source software (GGIR) was used to generate the magnitude of acceleration above which a person's most active 60, 30 and 2 min are accumulated: M60ACC; M30ACC and M2ACC, respectively. Results: The proportion of participants with M60ACC (children) and M30ACC (adults) values higher than accelerations representative of brisk walking (i.e., moderate-to-vigorous physical activity) ranged from 17 to 68% in children and 15 to 81% in adults, tending to decline with age. The proportion of pre-and post-menopausal women with M2ACC values meeting thresholds for bone health ranged from 6 to 13%. Conclusions: These metrics can be used for global surveillance of physical activity, including assessing prevalence of meeting current physical activity guidelines. As accelerometer and corresponding health data accumulate it will be possible to interpret the metrics relative to age- and sex- specific norms and derive evidence-based physical activity guidelines directly from accelerometer data for use in future global surveillance. This is where the potential advantages of these metrics lie.

KW - Acceleration

KW - Measurement

KW - Physical activity

KW - Population

KW - Research-grade accelerometer

KW - Wrist-worn

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U2 - https://doi.org/10.1016/j.jsams.2019.06.016

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