New directions in childhood obesity research: how a comprehensive biorepository will allow better prediction of outcomes.
BACKGROUND
Childhood obesity is associated with the early development of diseases such as type 2 diabetes and cardiovascular disease. Unfortunately, to date, traditional methods of research have failed to identify effective prevention and treatment strategies, and large numbers of children and adolescents continue to be at high risk of developing weight-related disease.


OBJECTIVE
To establish a unique 'biorepository' of data and biological samples from overweight and obese children, in order to investigate the complex 'gene × environment' interactions that govern disease risk.


METHODS
The 'Childhood Overweight BioRepository of Australia' collects baseline environmental, clinical and anthropometric data, alongside storage of blood samples for genetic, metabolic and hormonal profiles. Opportunities for longitudinal data collection have also been incorporated into the study design. National and international harmonization of data and sample collection will achieve required statistical power.


RESULTS
Ethical approval in the parent site has been obtained and early data indicate a high response rate among eligible participants (71%) with a high level of compliance for comprehensive data collection (range 56% to 97% for individual study components). Multi-site ethical approval is now underway.


CONCLUSIONS
In time, it is anticipated that this comprehensive approach to data collection will allow early identification of individuals most susceptible to disease, as well as facilitating refinement of prevention and treatment programs.
Sabin
Matthew A
MA
Clemens
Susan L
SL
Saffery
Richard
R
McCallum
Zoe
Z
Campbell
Michele W
MW
Kiess
Wieland
W
Crimmins
Nancy A
NA
Woo
Jessica G
JG
Leong
Gary M
GM
Werther
George A
GA
Ukoumunne
Obioha C
OC
Wake
Melissa A
MA
D000293:Adolescent; D001315:Australia; D035843:Biomedical Research; D002648:Child; D002675:Child, Preschool; D015897:Comorbidity; D003625:Data Collection; D016208:Databases, Factual; D006801:Humans; D009765:Obesity / Q000235:genetics; D050177:Overweight; D012307:Risk Factors; D015431:Weight Loss