File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: The discrimination of dyslipidaemia using anthropometric measures in ethnically diverse populations of the Asia-pacific region: The obesity in Asia collaboration

TitleThe discrimination of dyslipidaemia using anthropometric measures in ethnically diverse populations of the Asia-pacific region: The obesity in Asia collaboration
Authors
KeywordsDiagnosis
Lipids
Meta-analysis
Obesity
Issue Date2010
PublisherBlackwell Publishing Ltd. The Journal's web site is located at http://www.blackwellpublishing.com/journals/OBR
Citation
Obesity Reviews, 2010, v. 11 n. 2, p. 127-136 How to Cite?
AbstractDyslipidaemia is a major risk factor for cardiovascular disease and is only detectable through blood testing, which may not be feasible in resource-poor settings. As dyslipidaemia is commonly associated with excess weight, it may be possible to identify individuals with adverse lipid profiles using simple anthropometric measures. A total of 222 975 individuals from 18 studies were included as part of the Obesity in Asia Collaboration. Linear and logistic regression models were used to assess the association between measures of body size and dyslipidaemia. Body mass index, waist circumference, waist: hip ratio (WHR) and waist: height ratio were continuously associated with the lipid variables studied, but the relationships were consistently stronger for triglycerides and high-density lipoprotein cholesterol. The associations were similar between Asians and non-Asians, and no single anthropometric measure was superior at discriminating those individuals at increased risk of dyslipidaemia. WHR cut-points of 0.8 in women and 0.9 in men were applicable across both Asians and non-Asians for the discrimination of individuals with any form of dyslipidaemia. Measurement of central obesity may help to identify those individuals at increased risk of dyslipidaemia. WHR cut-points of 0.8 for women and 0.9 for men are optimal for discriminating those individuals likely to have adverse lipid profiles and in need of further clinical assessment. © 2009 International Association for the Study of Obesity.
Persistent Identifierhttp://hdl.handle.net/10722/129489
ISSN
2021 Impact Factor: 10.867
2020 SCImago Journal Rankings: 2.845
ISI Accession Number ID
Funding AgencyGrant Number
National Health and Medical Research Council of Australia
National Heart Foundation of Australia
Institut Servier, France
Assistance Publique-Hopitaux de Paris
Funding Information:

The authors would like to thank principal collaborators in OAC: John Adam, Fereidoun Azizi, Corazon Barba, Zhou Beifan, Chen Chunming, Stephen Colagiuri, Jeffery Cutter, Chee Weng Fong, Graham Giles, Kuo-Chin Huang, Edward Janus, Jae-Heon Kang, Gary Ko, Shinichi Kuriyama, Tai Hing Lam, Scott Lear, Viswanathan Mohan, Sang Woo Oh, Jeetesh Patel, Dorairaj Prabhakaran, Srinath Reddy, Jonathan Shaw, Piyamitr Sritara, Paibul Suriyawongpaisal, Tim Welborn, Paul Zimmet. The funding support is from National Health and Medical Research Council of Australia and National Heart Foundation of Australia. Sebastien Czernichow is supported by a research grant from Institut Servier, France and Assistance Publique-Hopitaux de Paris. R. Huxley is supported by a Career Development Award from the National Heart Foundation of Australia.

References

 

DC FieldValueLanguage
dc.contributor.authorBarzi, Fen_HK
dc.contributor.authorWoodward, Men_HK
dc.contributor.authorCzernichow, Sen_HK
dc.contributor.authorLee, CMYen_HK
dc.contributor.authorKang, JHen_HK
dc.contributor.authorJanus, Een_HK
dc.contributor.authorLear, Sen_HK
dc.contributor.authorPatel, Aen_HK
dc.contributor.authorCaterson, Ien_HK
dc.contributor.authorPatel, Jen_HK
dc.contributor.authorLam, THen_HK
dc.contributor.authorSuriyawongpaisal, Pen_HK
dc.contributor.authorHuxley, Ren_HK
dc.date.accessioned2010-12-23T08:37:53Z-
dc.date.available2010-12-23T08:37:53Z-
dc.date.issued2010en_HK
dc.identifier.citationObesity Reviews, 2010, v. 11 n. 2, p. 127-136en_HK
dc.identifier.issn1467-7881en_HK
dc.identifier.urihttp://hdl.handle.net/10722/129489-
dc.description.abstractDyslipidaemia is a major risk factor for cardiovascular disease and is only detectable through blood testing, which may not be feasible in resource-poor settings. As dyslipidaemia is commonly associated with excess weight, it may be possible to identify individuals with adverse lipid profiles using simple anthropometric measures. A total of 222 975 individuals from 18 studies were included as part of the Obesity in Asia Collaboration. Linear and logistic regression models were used to assess the association between measures of body size and dyslipidaemia. Body mass index, waist circumference, waist: hip ratio (WHR) and waist: height ratio were continuously associated with the lipid variables studied, but the relationships were consistently stronger for triglycerides and high-density lipoprotein cholesterol. The associations were similar between Asians and non-Asians, and no single anthropometric measure was superior at discriminating those individuals at increased risk of dyslipidaemia. WHR cut-points of 0.8 in women and 0.9 in men were applicable across both Asians and non-Asians for the discrimination of individuals with any form of dyslipidaemia. Measurement of central obesity may help to identify those individuals at increased risk of dyslipidaemia. WHR cut-points of 0.8 for women and 0.9 for men are optimal for discriminating those individuals likely to have adverse lipid profiles and in need of further clinical assessment. © 2009 International Association for the Study of Obesity.en_HK
dc.languageengen_US
dc.publisherBlackwell Publishing Ltd. The Journal's web site is located at http://www.blackwellpublishing.com/journals/OBRen_HK
dc.relation.ispartofObesity Reviewsen_HK
dc.subjectDiagnosis-
dc.subjectLipids-
dc.subjectMeta-analysis-
dc.subjectObesity-
dc.subject.meshAdulten_HK
dc.subject.meshAnthropometry - methodsen_HK
dc.subject.meshAsiaen_HK
dc.subject.meshBody Compositionen_HK
dc.subject.meshBody Weighten_HK
dc.subject.meshDyslipidemias - diagnosis - epidemiologyen_HK
dc.subject.meshFemaleen_HK
dc.subject.meshHumansen_HK
dc.subject.meshMaleen_HK
dc.subject.meshMiddle Ageden_HK
dc.subject.meshObesity - diagnosis - epidemiologyen_HK
dc.subject.meshOceaniaen_HK
dc.subject.meshPrevalenceen_HK
dc.subject.meshRegression Analysisen_HK
dc.subject.meshRisk Assessmenten_HK
dc.subject.meshWaist Circumferenceen_HK
dc.subject.meshWaist-Hip Ratioen_HK
dc.titleThe discrimination of dyslipidaemia using anthropometric measures in ethnically diverse populations of the Asia-pacific region: The obesity in Asia collaborationen_HK
dc.typeArticleen_HK
dc.identifier.emailLam, TH:hrmrlth@hkucc.hku.hken_HK
dc.identifier.authorityLam, TH=rp00326en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1111/j.1467-789X.2009.00605.xen_HK
dc.identifier.pmid19493299-
dc.identifier.scopuseid_2-s2.0-75149138986en_HK
dc.identifier.hkuros183384en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-75149138986&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume11en_HK
dc.identifier.issue2en_HK
dc.identifier.spage127en_HK
dc.identifier.epage136en_HK
dc.identifier.isiWOS:000273732700005-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridBarzi, F=7003545543en_HK
dc.identifier.scopusauthoridWoodward, M=7102510958en_HK
dc.identifier.scopusauthoridCzernichow, S=35229348600en_HK
dc.identifier.scopusauthoridLee, CMY=35262011100en_HK
dc.identifier.scopusauthoridKang, JH=20934732900en_HK
dc.identifier.scopusauthoridJanus, E=7006936536en_HK
dc.identifier.scopusauthoridLear, S=7003829555en_HK
dc.identifier.scopusauthoridPatel, A=7403524909en_HK
dc.identifier.scopusauthoridCaterson, I=7005056126en_HK
dc.identifier.scopusauthoridPatel, J=8562612200en_HK
dc.identifier.scopusauthoridLam, TH=7202522876en_HK
dc.identifier.scopusauthoridSuriyawongpaisal, P=7004837179en_HK
dc.identifier.scopusauthoridHuxley, R=6701828350en_HK
dc.identifier.issnl1467-7881-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats