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

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TitleThe discrimination of dyslipidaemia using anthropometric measures in ethnically diverse populations of the Asia-pacific region: The obesity in Asia collaboration
AuthorsBarzi, F3
Woodward, M3
Czernichow, S3
Lee, CMY3
Kang, JH2
Janus, E1
Lear, S5
Patel, A3
Caterson, I3
Patel, J7
Lam, TH4
Suriyawongpaisal, P6
Huxley, R3
Issue Date2010
PublisherBlackwell Publishing Ltd. The Journal's web site is located at http://www.blackwellpublishing.com/journals/OBR
CitationObesity Reviews, 2010, v. 11 n. 2, p. 127-136 [How to Cite?]
DOI: http://dx.doi.org/10.1111/j.1467-789X.2009.00605.x
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.
ISSN1467-7881
2011 Impact Factor: 7.038
2011 SCImago Journal Rankings: 0.437
DOIhttp://dx.doi.org/10.1111/j.1467-789X.2009.00605.x
ISI Accession Number IDWOS:000273732700005
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.

ReferencesReferences in Scopus
DC Field
Value
dc.contributor.authorBarzi, F
dc.contributor.authorWoodward, M
dc.contributor.authorCzernichow, S
dc.contributor.authorLee, CMY
dc.contributor.authorKang, JH
dc.contributor.authorJanus, E
dc.contributor.authorLear, S
dc.contributor.authorPatel, A
dc.contributor.authorCaterson, I
dc.contributor.authorPatel, J
dc.contributor.authorLam, TH
dc.contributor.authorSuriyawongpaisal, P
dc.contributor.authorHuxley, R
dc.date.accessioned2010-12-23T08:37:53Z
dc.date.available2010-12-23T08:37:53Z
dc.date.issued2010
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.
dc.description.natureLink_to_subscribed_fulltext
dc.identifier.citationObesity Reviews, 2010, v. 11 n. 2, p. 127-136 [How to Cite?]
DOI: http://dx.doi.org/10.1111/j.1467-789X.2009.00605.x
dc.identifier.doihttp://dx.doi.org/10.1111/j.1467-789X.2009.00605.x
dc.identifier.epage136
dc.identifier.hkuros183384
dc.identifier.isiWOS:000273732700005
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.

dc.identifier.issn1467-7881
2011 Impact Factor: 7.038
2011 SCImago Journal Rankings: 0.437
dc.identifier.issue2
dc.identifier.pmid19493299
dc.identifier.scopuseid_2-s2.0-75149138986
dc.identifier.spage127
dc.identifier.urihttp://hdl.handle.net/10722/129489
dc.identifier.volume11
dc.languageeng
dc.publisherBlackwell Publishing Ltd. The Journal's web site is located at http://www.blackwellpublishing.com/journals/OBR
dc.publisher.placeUnited Kingdom
dc.relation.ispartofObesity Reviews
dc.relation.referencesReferences in Scopus
dc.subject.meshAdult
dc.subject.meshAnthropometry - methods
dc.subject.meshAsia
dc.subject.meshBody Composition
dc.subject.meshBody Weight
dc.subject.meshDyslipidemias - diagnosis - epidemiology
dc.subject.meshFemale
dc.subject.meshHumans
dc.subject.meshMale
dc.subject.meshMiddle Aged
dc.subject.meshObesity - diagnosis - epidemiology
dc.subject.meshOceania
dc.subject.meshPrevalence
dc.subject.meshRegression Analysis
dc.subject.meshRisk Assessment
dc.subject.meshWaist Circumference
dc.subject.meshWaist-Hip Ratio
dc.titleThe discrimination of dyslipidaemia using anthropometric measures in ethnically diverse populations of the Asia-pacific region: The obesity in Asia collaboration
dc.typeArticle
Author Affiliations
  1. Wimmera Health Care Group
  2. Inje University Paik Hospital
  3. University of Sydney
  4. The University of Hong Kong
  5. Simon Fraser University
  6. Mahidol University
  7. Sandwell General Hospital