- A/Prof Nigel McArdle (Sleep) (McArdle@health.wa.gov.au)
- Dr Joanne McVeigh (Physical Activity/Sedentary Behaviour), Curtin University (email@example.com)
List of Investigators
- Anne Smith, School of Physiotherapy, Curtin University
- Beth Hands, Institute for Health Research, Notre Dame University
- Brennan Mils, School of Medical & Health Science, ECU
- Darren Beales, Pain Options, Curtin University
- David Hillman, Sir Charles Gardner Hospital, WA Sleep Disorders Research Institute
- Erin Howie, School of Physiotherapy & Exercise Science, Curtin University
- Floran Zepf, Pediatrics, UWA
- Jennifer Walsh, School of Human Sciences, UWA
- Kath Maddison, School of Human Sciences, UWA
- Leon Straker, School of Physiotherapy, Curtin University
- Manon Dontje, Raine Study, UWA
- Peter Eastwood, School of Human Sciences, UWA
- Phillip Melton, GOHaD, UWA
- Rae-Chi Huang, TKI
- Romola Bucks, School of Psychological Science, UWA
- Stewart King
- Trevor Mori, School of Biomedical Sciences, UWA
Overview of the current data resources available in the SIG area
Generation 2: (22 yr follow-up):
Sleep study (Laboratory PSG, n = 956)
Questionnaire: Sleep – Common sleep disorders (OSA, Insomnia, RLS), sleepiness, sleep behaviours (bed time etc), ‘morningness/eveningness’, accidents including motor vehicle
Actigraphy /sleep diary (1 week)
Sleep study (Laboratory PSG, n = 948)
Detailed questionnaire data on medical history (doctor diagnosed conditions) and medications
Actigraphy /sleep diary (1 week)
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)
Hip and Wrist Accelerometry (24hrs/day, 7 day week protocol) (Hip n ~ 1000, Wrist n~1000)
Hip accelerometry (data currently being collected as part of Autism Biobank study, Gen 3- control arm)
Overview of current/recent SIG activity
Sleep data of Generation 2 (22 yr follow-up) is being analysed. Preliminary data indicates common sleep disorders are prevalent in young adults (OSA= 21%, insomnia =17% , restless legs =3%), phenotype of young adults with OSA: similar risk factors to middle age (male, obesity, snoring) but asymptomatic. Longitudinal predictors of sleep disorders will be sought. Data collection of Generation 1 has been completed recently, the sleep data is currently being cleaned and analysed.
The Sleep and Activity SIG is currently working on processing and analysing the actigraphy data of Generation 2. They are developing algorithms for raw accelerometry data, and are developing user friendly processing software for acceleromtery data. The algorithms and software will be further developed to analyse accelerometry data of Generation 1 and 3 as well.
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. Generation 2 is currently undergoing a detailed assessment of cardiovascular health. The Sleep and Activity SIG will be assessing longitudinal relationships between sleep disorders and cardiovascular health.
The Sleep and Activity SIG will also be working on several other projects, such as:
- 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
- Identifying life course predictors of activity and inactivity
- Processing wrist actigraphy data
- Processing and analyzing actigraphy data of Generation 1 and 3
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)
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
- 2016-18; 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.
- 2015-17; CIA – Professor Peter Eastwood, CIB – Professor David Hillman, CIC – Professor Eric Moses , CID – Doctor Nigel McArdle , CIE – Doctor Phillip Melton; Prevalence, phenotype and genotype of common sleep disorders. NHMRC Project grant APP1084947.
- 2012-14; Eastwood PR, CIB Hillman DR, CIC Smith A, CID McArdle N, CIE Huang R-C; Childhood obesity and its relationship to adult sleep disordered breathing CIA NHMRC PROJECT GRANT.
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