Physical Activity and Sleep SIG

SIG leaders

List of Investigators

Local

  • Professor Anne Smith, Curtin University
  • Professor Beth Hands, Notre Dame University
  • Dr Brennan Mils, Edith Cowan University
  • Dr Darren Beales, Curtin University
  • Professor David Hillman, Sir Charles Gardner Hospital
  • Dr Erin Howie, Curtin University
  • Professor Floran Zepf, University of Western Australia
  • Dr Jennifer Walsh, University of Western Australia
  • Dr Kath Maddison, University of Western Australia
  • Professor Leon Straker, Curtin University
  • Dr Manon Dontje, University of Western Australia
  • Professor Peter Eastwood, University of Western Australia
  • Dr Phillip Melton, University of Western Australia
  • Assoc/Professor Rae-Chi Huang, Telethon Kids Institute
  • Professor Romola Bucks, University of Western Australia
  • Stewart King
  • Professor Trevor Mori, University of Western Australia
  • Professor Cecilie Thorgenson, Ntoumanis
  • Dr Ben Jackson

National

  • Professor David Champion, Department of Anaesthesia and Pain Medicine NSW
  • Assoc/Professor Genevieve Healy, University of Queensland
  • Professor Emmanuel Stamatakis, University of Sydney

International

  • Dr Rebecca Meiring, University of Witwatersrand, South Africa
  • Dr Erin Howie, University of Arkansas, USA

Overview of the current data resources available in the SIG area

Generation 1

  • Polysomnographic (laboratory sleep study) measures 26 yr follow-up
  • Sleep-related Questionnaire measures [e.g., Common sleep disorders (OSA, Insomnia, RLS), sleepiness (Epworth), sleep behaviours (bed time etc), morningness-eveningness, disease specific quality of life (FOSQ-10), shift work, sleep and driving, family history of sleep disorders, Prospective and Retrospective Memory Questionnaire and the Revised Attention-related Cognitive Errors Scale]
  • Detailed questionnaire data on medical history (doctor diagnosed conditions) and medications
  • Actigraphy/sleep diary measures (1 week)
  • 3D-MD facial photograph
  • Neurocognitive assessments (‘Cogstate’ computer battery)
  • Actigraphy /sleep diary (1 week)

Generation 2

  • Polysomnographic (laboratory sleep study) measures at 22 yr follow-up
  • Sleep-related Questionnaire measures [e.g., Common sleep disorders (OSA, Insomnia, RLS), sleepiness (Epworth), sleep behaviours (bed time etc), morningness-eveningness, disease specific quality of life (FOSQ-10), shift work, sleep and driving, family history of sleep disorders, Prospective and Retrospective Memory Questionnaire and the Revised Attention-related Cognitive Errors Scale] at 22 yr follow-up
  • Actigraphy/sleep diary measures (1 week)3D-MD facial photograph at 22 year follow-up
  • Neurocognitive assessments (‘Cogstate’ computer battery) at 22 year follow-up
  • Sports participation (ages 5, 8, 10, 14, 17 and 20)
  • IPAQ (age 17, age 20, 22)
  • Pedometer & Multimedia Activity Recall for Children and Adolescents (MARCA) – age 14
  • Hip and Wrist Accelerometry (22 yr follow-up) (24hrs/day, 7 day week protocol) (Hip n = 774, Wrist n~800)

Generation 3

  • Hip accelerometry (data currently being collected as part of Autism Biobank study, Gen 3 – control arm)

Overview of current/recent SIG activity

Detailed sleep data of Generation 1 (26 yr follow-up) and Generation 2 (22 yr follow-up) is being analysed.

The Sleep and Activity SIG is currently developing algorithms for raw accelerometry data, and are developing user friendly processing software for accelerometry data, and are developing user friendly processing software for accelerometry data.  The algorithms and software will be further developed to analyse accelerometry data of Generation 1 and Generation 3 as well.

For both sleep and activity behaviours, analysis of contemporaneous factors and longitudinal predictors are being conducted.  For example:

  • Describing the prevalence of common sleep symptoms and sleep disorders in young adults
  • Describing the phenotypic characteristics of common sleep disorders (obstructive sleep apnoea, insomnia and restless legs syndrome) in young adults
  • Determining longitudinal predictors for the development of obstructive sleep apnoea in young adults, with a focus on obesity trajectories

Outline of SIG plans for next 5 years

The Sleep and Activity SIG will analyse prevalence, phenotype, associations between parental and offspring phenotype and discovery of genetic risk variants, assessing longitudinal relationships between sleep disorders and cardiovascular health.

The Sleep and Activity SIG will also be working on several other projects, such as:

  • To describe the prevalence and phenotype of middle-aged adult common sleep disorders
  • To determine the associations between Generation 1 and Generation 2 sleep phenotype and discovery of genetic risk variants
  • To assess the longitudinal relationships between sleep disorders in young adults and cardiovascular health
  • Assessing correlates of physical activity and sedentary time
  • Using a compositional data analysis approach to assess accelerometer measured physical activity and sedentary behaviour and cardio-metabolic biomarkers
  • Comparing 4 methods including visual inspection, PSG, actigraphy algorithm, and diary data to analyze physical activity and sleep data
  • Developing consensus terminology for sleep and activity behaviours
  • Identifying life course predictors of activity and inactivity
  • Analysing actigraphy data of Generation 1, 2 and 3 using novel approaches which consider the temporal relationship of 24 hour data
  • Associations between musculoskeletal pain and objectively measured physical activity and sedentary behaviour in middle-aged adults (Gen 1) of the Raine Study cohort
  • Lifecourse factors influencing the prevalence of knee and hip pain in middle and older aged adults from the Raine Study (Generation 1)
  • Physical activity and sedentary behaviour in children with Autistic Spectrum Disorder compared to typically developing children
  • Sleep trajectories from 5 to 17 years of age and mental health in young adulthood:  The Raine Study

Brief list of potential student/early career researcher projects

Please contact the Physical activity and Sleep SIG Leaders if you are interested in a research project incorporating Physical activity and Sleep data and they will coordinate whom to contact within the group.

Top 5-10 key findings (with reference)

  • There were strong associations found between reported musculoskeletal pain and restless legs syndrome in young adults.  (Hoogwout SJ, Paananen MV, Smith AJ, Beales DJ, O’Sullivan PB, Straker LM, Eastwood PR, McArdle N, Champion D. Musculoskeletal pain is associated with restless legs syndrome in young adults. BMC musculoskeletal disorders 2015;16:294). 
  • A trajectory characterized by less than 14 h/week TV viewing across childhood and adolescence predicts lower body fat in young adulthood.  (McVeigh JA, Smith A, Howie EK, Straker L. Trajectories of television watching from childhood to early adulthood and their association with body composition and mental health outcomes in young adults. PloS One 2016;11:e0152879.)
  • Trajectories characterized by participation in sports across childhood and adolescence predict better physical health in young adulthood.  (Howie EK, McVeigh JA, Smith AJ, Straker LM. Organized sport trajectories from childhood to adolescence and health associations. Med Sci Sports Exerc 2016;48:1331-39)-
  • Higher screen time exposure in early childhood predicts lower physical activity and higher BMI in later childhood but not in adolescence.  (Hands BP, Chivers PT, Parker HE, Beilin L, Kendall G, Larkin D. The associations between physical activity, screen time and weight from 6 to 14 yrs: The Raine Study. J Sci Med Sport 2011;14:397–403)
  • Less desirable correlates were associated with positive levels of activity in young Australian adult women and men. Howie EK, McVeigh JA,Winkler EAH, Healy GH, Bucks RS; Eastwood PR, Straker LM. Correlates of physical activity and sedentary time in young adults: The Western Australian Pregnancy Cohort (Raine) Study. BMC Public Health 2018 (In Press)
  • Five activity phenotypes were identified for each gender. Howie EK, McVeigh JA, Smith A, Straker LM. Accelerometer-derived activity phenotypes in young adults: A latent class analysis. International Journal of Behavioral Medicine 2018 (In press)

List of indicative recent publications

  • Hoogwout SJ, Paananen MV, Smith AJ, Beales DJ, O’Sullivan PB, Straker LM, Eastwood PR, McArdle N, Champion D. Musculoskeletal pain is associated with restless legs syndrome in young adults. BMC musculoskeletal disorders 2015;16:294.
  • Howie EK, McVeigh JA, Smith AJ, Straker LM. Organized sport trajectories from childhood to adolescence and health associations. Med Sci Sports Exerc 2016;48:1331-39.
  • McVeigh JA, Smith A, Howie EK, Straker L. Trajectories of television watching from childhood to early adulthood and their association with body composition and mental health outcomes in young adults. PloS One 2016;11:e0152879.
  • McVeigh JA, Winkler E, Healy G, Slater L, Eastwood P, Straker L. Validity of an automated algorithm to identify waking and in-bed wear time in hip-worn accelerometer data collected with a 24-hour wear protocol in young adults. Physiological Measurement 37: 1636-1652, 2016.
  • McVeigh JA, Winkler EAH, Howie EK, Tremblay MS, Smith A, Abbott RA, Eastwood PR, Healy GN, Straker LM. Objectively measured patterns of sedentary time and physical activity in          young adults of the Raine study cohort. International Journal of Behaviour Nutrition and Physical Activity 2016 (24): doi: 10.1186/s12966-016-0363-0.
  • McVeigh JA, Zhu K, Mountain J, Pennell CE, Lye SJ, Walsh JP, Straker LM. Longitudinal trajectories of television watching across childhood and adolescence predict bone mass at age 20    in the Raine Study. Journal of Bone and Mineral Research 2016 (31):2032-2040.
  • Hands BP, Chivers PT, Parker HE, Beilin L, Kendall G, Larkin D. The associations between physical activity, screen time and weight from 6 to 14 yrs: The Raine Study. J Sci Med Sport  2011;14:397–403).

List of current/recent grants

  • 2016-2018; A/Pr Ajmal Mian, Dr Nigel Mcardle, Prof David Hillman, Prof Peter Eastwood; Project grant Predicting Obstructive Sleep Apnoea using 3D Craniofacial Photography; NHMRC APP1109057.  $424,715.25
  • 2015-2017; Professor Peter Eastwood, Professor David Hillman, Professor Eric Moses, Doctor Nigel McArdle, Doctor Phillip Melton; Prevalence, phenotype and genotype of common sleep disorders. NHMRC Project grant APP1084947. $1,419,484.50
  • 2012-2014; Eastwood PR, Hillman DR, Smith A, McArdle N, Huang R-C; Childhood obesity and its relationship to adult sleep disordered breathing NHMRC.$843,060

Examples of recent media

“Children who watch lots of TV have weaker bones in adulthood”- released as a press release from Curtin based on (McVeigh JA, Zhu K, Mountain J, Pennell CE, Lye SJ, Walsh JP, Straker LM. Longitudinal trajectories of television watching across childhood and adolescence predict bone mass at age 20 in the Raine Study. Journal of Bone and Mineral Research 2016 (31):2032-2040)

Resulted in 10+ newspaper articles, 6 radio interviews and a slot in Today Tonight

Other data

The Raine Study has extensive data on genetics, phenotypes, behaviours, environment and social outcome that can be linked with Activity and Sleep data.