Association between simple anthropometric indices and cardiovascular risk factors
To identify which of the three simple anthropometric indices, body mass index (BMI), waist-to-hip ratio (WHR) and waist circumference (WC), best predicts cardiovascular risk factors, and to determine if the association between the anthropometric indices and cardiovascular risk factors varies with ge...
Gespeichert in:
| Veröffentlicht in: | International Journal of Obesity 2001-11, Vol.25 (11), p.1689-1697 |
|---|---|
| Hauptverfasser: | , , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 1697 |
|---|---|
| container_issue | 11 |
| container_start_page | 1689 |
| container_title | International Journal of Obesity |
| container_volume | 25 |
| creator | HO, S. C CHEN, Y. M WOO, J. L. F LEUNG, S. S. F LAM, T. H JANUS, E. D |
| description | To identify which of the three simple anthropometric indices, body mass index (BMI), waist-to-hip ratio (WHR) and waist circumference (WC), best predicts cardiovascular risk factors, and to determine if the association between the anthropometric indices and cardiovascular risk factors varies with gender.
A cross-sectional population-based survey was carried out during 1995-1996. One thousand and ten Chinese people (500 men and 510 women) aged 25-74 y were recruited as subjects for the study. Metabolic profiles and anthropometric indices were measured.
Partial correlation and co-variance analyses showed that WC exhibited the highest degree of association with almost all of the studied metabolic profiles for both men and women. We observed significant gender differences in the association between central or general obesity with cardiovascular risk factors. BMI had an independent and significant association with metabolic risks in men, but not in women, whereas WHR was more strongly correlated with metabolic risks for women than for men. Logistic regression analysis further confirmed the magnitude of the association between the obesity indices and metabolic risks. Among the studied metabolic variables, serum insulin showed the highest degree of association with the obesity indices, followed by plasma glucose, triglyceride, HDL and blood pressure. Total cholesterol and LDL-cholesterol had a small but significant correlation with obesity. No threshold values in the relation between either the anthropometric indices and metabolic values, or with hypertension, diabetes and dislipidemia were observed.
The association of central or general obesity and metabolic syndrome varied with gender. In addition, the useful anthropometric predictors for cardiovascular risk factors were BMI and WC for men, and WC and WHR for women. |
| doi_str_mv | 10.1038/sj.ijo.0801784 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_219221667</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1011863021</sourcerecordid><originalsourceid>FETCH-LOGICAL-c423t-afa6f2e06c1efca09aed9a1bc522a6eddf3bf0738515a204c63ebec6896564bd3</originalsourceid><addsrcrecordid>eNpFkE1LxDAQhoMo7rp69ShF8NiajyZpj4v4BQsi6DlM0wRT26YmreK_t7KFPQ0Mz_sO8yB0SXBGMCtuY5O5xme4wEQW-RFak1yKlOelPEZrzLBMMRd8hc5ibDDGnGN6ilaESM54SdfodRuj1w5G5_ukMuOPMX0SXTe0JoF-_Ah-8J0Zg9OJ62unTZzXdaIh1M5_Q9RTCyEJLn4mFvToQzxHJxbaaC6WuUHvD_dvd0_p7uXx-W67S3VO2ZiCBWGpwUITYzXgEkxdAqk0pxSEqWvLKoslKzjhQHGuBTOV0aIoBRd5VbMNut73DsF_TSaOqvFT6OeTipKSUiKEnKFsD-ngYwzGqiG4DsKvIlj9C1SxUbNAtQicA1dL61R1pj7gi7EZuFmA-XlobYBeu3jgcsJlwQv2B5UAe88</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>219221667</pqid></control><display><type>article</type><title>Association between simple anthropometric indices and cardiovascular risk factors</title><source>MEDLINE</source><source>Springer Nature - Complete Springer Journals</source><source>Nature Journals Online</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><creator>HO, S. C ; CHEN, Y. M ; WOO, J. L. F ; LEUNG, S. S. F ; LAM, T. H ; JANUS, E. D</creator><creatorcontrib>HO, S. C ; CHEN, Y. M ; WOO, J. L. F ; LEUNG, S. S. F ; LAM, T. H ; JANUS, E. D</creatorcontrib><description>To identify which of the three simple anthropometric indices, body mass index (BMI), waist-to-hip ratio (WHR) and waist circumference (WC), best predicts cardiovascular risk factors, and to determine if the association between the anthropometric indices and cardiovascular risk factors varies with gender.
A cross-sectional population-based survey was carried out during 1995-1996. One thousand and ten Chinese people (500 men and 510 women) aged 25-74 y were recruited as subjects for the study. Metabolic profiles and anthropometric indices were measured.
Partial correlation and co-variance analyses showed that WC exhibited the highest degree of association with almost all of the studied metabolic profiles for both men and women. We observed significant gender differences in the association between central or general obesity with cardiovascular risk factors. BMI had an independent and significant association with metabolic risks in men, but not in women, whereas WHR was more strongly correlated with metabolic risks for women than for men. Logistic regression analysis further confirmed the magnitude of the association between the obesity indices and metabolic risks. Among the studied metabolic variables, serum insulin showed the highest degree of association with the obesity indices, followed by plasma glucose, triglyceride, HDL and blood pressure. Total cholesterol and LDL-cholesterol had a small but significant correlation with obesity. No threshold values in the relation between either the anthropometric indices and metabolic values, or with hypertension, diabetes and dislipidemia were observed.
The association of central or general obesity and metabolic syndrome varied with gender. In addition, the useful anthropometric predictors for cardiovascular risk factors were BMI and WC for men, and WC and WHR for women.</description><identifier>ISSN: 0307-0565</identifier><identifier>EISSN: 1476-5497</identifier><identifier>DOI: 10.1038/sj.ijo.0801784</identifier><identifier>PMID: 11753592</identifier><identifier>CODEN: IJOBDP</identifier><language>eng</language><publisher>Basingstoke: Nature Publishing</publisher><subject>Abdomen ; Adult ; Aged ; Anthropometry ; Biological and medical sciences ; Blood Glucose - metabolism ; Blood Pressure ; Body Constitution ; Body fat ; Body Mass Index ; Cardiovascular Diseases - diagnosis ; Cardiovascular Diseases - epidemiology ; Cholesterol ; Cholesterol, HDL - blood ; Cross-Sectional Studies ; Diabetes ; Female ; Gender differences ; Glucose ; Health risks ; Hong Kong - epidemiology ; Humans ; Hypertension ; Insulin - blood ; Kinases ; Low density lipoprotein ; Male ; Medical sciences ; Metabolic diseases ; Metabolic disorders ; Metabolic syndrome ; Middle Aged ; Obesity ; Plasma ; Predictive Value of Tests ; Regression analysis ; Risk Factors ; Sex Factors ; Triglycerides - blood ; Women</subject><ispartof>International Journal of Obesity, 2001-11, Vol.25 (11), p.1689-1697</ispartof><rights>2002 INIST-CNRS</rights><rights>Copyright Nature Publishing Group Nov 2001</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c423t-afa6f2e06c1efca09aed9a1bc522a6eddf3bf0738515a204c63ebec6896564bd3</citedby><cites>FETCH-LOGICAL-c423t-afa6f2e06c1efca09aed9a1bc522a6eddf3bf0738515a204c63ebec6896564bd3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=14157858$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/11753592$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>HO, S. C</creatorcontrib><creatorcontrib>CHEN, Y. M</creatorcontrib><creatorcontrib>WOO, J. L. F</creatorcontrib><creatorcontrib>LEUNG, S. S. F</creatorcontrib><creatorcontrib>LAM, T. H</creatorcontrib><creatorcontrib>JANUS, E. D</creatorcontrib><title>Association between simple anthropometric indices and cardiovascular risk factors</title><title>International Journal of Obesity</title><addtitle>Int J Obes Relat Metab Disord</addtitle><description>To identify which of the three simple anthropometric indices, body mass index (BMI), waist-to-hip ratio (WHR) and waist circumference (WC), best predicts cardiovascular risk factors, and to determine if the association between the anthropometric indices and cardiovascular risk factors varies with gender.
A cross-sectional population-based survey was carried out during 1995-1996. One thousand and ten Chinese people (500 men and 510 women) aged 25-74 y were recruited as subjects for the study. Metabolic profiles and anthropometric indices were measured.
Partial correlation and co-variance analyses showed that WC exhibited the highest degree of association with almost all of the studied metabolic profiles for both men and women. We observed significant gender differences in the association between central or general obesity with cardiovascular risk factors. BMI had an independent and significant association with metabolic risks in men, but not in women, whereas WHR was more strongly correlated with metabolic risks for women than for men. Logistic regression analysis further confirmed the magnitude of the association between the obesity indices and metabolic risks. Among the studied metabolic variables, serum insulin showed the highest degree of association with the obesity indices, followed by plasma glucose, triglyceride, HDL and blood pressure. Total cholesterol and LDL-cholesterol had a small but significant correlation with obesity. No threshold values in the relation between either the anthropometric indices and metabolic values, or with hypertension, diabetes and dislipidemia were observed.
The association of central or general obesity and metabolic syndrome varied with gender. In addition, the useful anthropometric predictors for cardiovascular risk factors were BMI and WC for men, and WC and WHR for women.</description><subject>Abdomen</subject><subject>Adult</subject><subject>Aged</subject><subject>Anthropometry</subject><subject>Biological and medical sciences</subject><subject>Blood Glucose - metabolism</subject><subject>Blood Pressure</subject><subject>Body Constitution</subject><subject>Body fat</subject><subject>Body Mass Index</subject><subject>Cardiovascular Diseases - diagnosis</subject><subject>Cardiovascular Diseases - epidemiology</subject><subject>Cholesterol</subject><subject>Cholesterol, HDL - blood</subject><subject>Cross-Sectional Studies</subject><subject>Diabetes</subject><subject>Female</subject><subject>Gender differences</subject><subject>Glucose</subject><subject>Health risks</subject><subject>Hong Kong - epidemiology</subject><subject>Humans</subject><subject>Hypertension</subject><subject>Insulin - blood</subject><subject>Kinases</subject><subject>Low density lipoprotein</subject><subject>Male</subject><subject>Medical sciences</subject><subject>Metabolic diseases</subject><subject>Metabolic disorders</subject><subject>Metabolic syndrome</subject><subject>Middle Aged</subject><subject>Obesity</subject><subject>Plasma</subject><subject>Predictive Value of Tests</subject><subject>Regression analysis</subject><subject>Risk Factors</subject><subject>Sex Factors</subject><subject>Triglycerides - blood</subject><subject>Women</subject><issn>0307-0565</issn><issn>1476-5497</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2001</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><recordid>eNpFkE1LxDAQhoMo7rp69ShF8NiajyZpj4v4BQsi6DlM0wRT26YmreK_t7KFPQ0Mz_sO8yB0SXBGMCtuY5O5xme4wEQW-RFak1yKlOelPEZrzLBMMRd8hc5ibDDGnGN6ilaESM54SdfodRuj1w5G5_ukMuOPMX0SXTe0JoF-_Ah-8J0Zg9OJ62unTZzXdaIh1M5_Q9RTCyEJLn4mFvToQzxHJxbaaC6WuUHvD_dvd0_p7uXx-W67S3VO2ZiCBWGpwUITYzXgEkxdAqk0pxSEqWvLKoslKzjhQHGuBTOV0aIoBRd5VbMNut73DsF_TSaOqvFT6OeTipKSUiKEnKFsD-ngYwzGqiG4DsKvIlj9C1SxUbNAtQicA1dL61R1pj7gi7EZuFmA-XlobYBeu3jgcsJlwQv2B5UAe88</recordid><startdate>20011101</startdate><enddate>20011101</enddate><creator>HO, S. C</creator><creator>CHEN, Y. M</creator><creator>WOO, J. L. F</creator><creator>LEUNG, S. S. F</creator><creator>LAM, T. H</creator><creator>JANUS, E. D</creator><general>Nature Publishing</general><general>Nature Publishing Group</general><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7T2</scope><scope>7TK</scope><scope>7TS</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>88G</scope><scope>8AO</scope><scope>8C1</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M2M</scope><scope>M7P</scope><scope>PHGZM</scope><scope>PHGZT</scope><scope>PJZUB</scope><scope>PKEHL</scope><scope>PPXIY</scope><scope>PQEST</scope><scope>PQGLB</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PSYQQ</scope><scope>Q9U</scope></search><sort><creationdate>20011101</creationdate><title>Association between simple anthropometric indices and cardiovascular risk factors</title><author>HO, S. C ; CHEN, Y. M ; WOO, J. L. F ; LEUNG, S. S. F ; LAM, T. H ; JANUS, E. D</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c423t-afa6f2e06c1efca09aed9a1bc522a6eddf3bf0738515a204c63ebec6896564bd3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2001</creationdate><topic>Abdomen</topic><topic>Adult</topic><topic>Aged</topic><topic>Anthropometry</topic><topic>Biological and medical sciences</topic><topic>Blood Glucose - metabolism</topic><topic>Blood Pressure</topic><topic>Body Constitution</topic><topic>Body fat</topic><topic>Body Mass Index</topic><topic>Cardiovascular Diseases - diagnosis</topic><topic>Cardiovascular Diseases - epidemiology</topic><topic>Cholesterol</topic><topic>Cholesterol, HDL - blood</topic><topic>Cross-Sectional Studies</topic><topic>Diabetes</topic><topic>Female</topic><topic>Gender differences</topic><topic>Glucose</topic><topic>Health risks</topic><topic>Hong Kong - epidemiology</topic><topic>Humans</topic><topic>Hypertension</topic><topic>Insulin - blood</topic><topic>Kinases</topic><topic>Low density lipoprotein</topic><topic>Male</topic><topic>Medical sciences</topic><topic>Metabolic diseases</topic><topic>Metabolic disorders</topic><topic>Metabolic syndrome</topic><topic>Middle Aged</topic><topic>Obesity</topic><topic>Plasma</topic><topic>Predictive Value of Tests</topic><topic>Regression analysis</topic><topic>Risk Factors</topic><topic>Sex Factors</topic><topic>Triglycerides - blood</topic><topic>Women</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>HO, S. C</creatorcontrib><creatorcontrib>CHEN, Y. M</creatorcontrib><creatorcontrib>WOO, J. L. F</creatorcontrib><creatorcontrib>LEUNG, S. S. F</creatorcontrib><creatorcontrib>LAM, T. H</creatorcontrib><creatorcontrib>JANUS, E. D</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health and Safety Science Abstracts (Full archive)</collection><collection>Neurosciences Abstracts</collection><collection>Physical Education Index</collection><collection>Agricultural Science Collection</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Psychology Database (Alumni)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Agricultural Science Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Psychology Database</collection><collection>Biological Science Database</collection><collection>ProQuest Central (New)</collection><collection>ProQuest One Academic (New)</collection><collection>ProQuest Health & Medical Research Collection</collection><collection>ProQuest One Academic Middle East (New)</collection><collection>ProQuest One Health & Nursing</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Applied & Life Sciences</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest One Psychology</collection><collection>ProQuest Central Basic</collection><jtitle>International Journal of Obesity</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>HO, S. C</au><au>CHEN, Y. M</au><au>WOO, J. L. F</au><au>LEUNG, S. S. F</au><au>LAM, T. H</au><au>JANUS, E. D</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Association between simple anthropometric indices and cardiovascular risk factors</atitle><jtitle>International Journal of Obesity</jtitle><addtitle>Int J Obes Relat Metab Disord</addtitle><date>2001-11-01</date><risdate>2001</risdate><volume>25</volume><issue>11</issue><spage>1689</spage><epage>1697</epage><pages>1689-1697</pages><issn>0307-0565</issn><eissn>1476-5497</eissn><coden>IJOBDP</coden><abstract>To identify which of the three simple anthropometric indices, body mass index (BMI), waist-to-hip ratio (WHR) and waist circumference (WC), best predicts cardiovascular risk factors, and to determine if the association between the anthropometric indices and cardiovascular risk factors varies with gender.
A cross-sectional population-based survey was carried out during 1995-1996. One thousand and ten Chinese people (500 men and 510 women) aged 25-74 y were recruited as subjects for the study. Metabolic profiles and anthropometric indices were measured.
Partial correlation and co-variance analyses showed that WC exhibited the highest degree of association with almost all of the studied metabolic profiles for both men and women. We observed significant gender differences in the association between central or general obesity with cardiovascular risk factors. BMI had an independent and significant association with metabolic risks in men, but not in women, whereas WHR was more strongly correlated with metabolic risks for women than for men. Logistic regression analysis further confirmed the magnitude of the association between the obesity indices and metabolic risks. Among the studied metabolic variables, serum insulin showed the highest degree of association with the obesity indices, followed by plasma glucose, triglyceride, HDL and blood pressure. Total cholesterol and LDL-cholesterol had a small but significant correlation with obesity. No threshold values in the relation between either the anthropometric indices and metabolic values, or with hypertension, diabetes and dislipidemia were observed.
The association of central or general obesity and metabolic syndrome varied with gender. In addition, the useful anthropometric predictors for cardiovascular risk factors were BMI and WC for men, and WC and WHR for women.</abstract><cop>Basingstoke</cop><pub>Nature Publishing</pub><pmid>11753592</pmid><doi>10.1038/sj.ijo.0801784</doi><tpages>9</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0307-0565 |
| ispartof | International Journal of Obesity, 2001-11, Vol.25 (11), p.1689-1697 |
| issn | 0307-0565 1476-5497 |
| language | eng |
| recordid | cdi_proquest_journals_219221667 |
| source | MEDLINE; Springer Nature - Complete Springer Journals; Nature Journals Online; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals |
| subjects | Abdomen Adult Aged Anthropometry Biological and medical sciences Blood Glucose - metabolism Blood Pressure Body Constitution Body fat Body Mass Index Cardiovascular Diseases - diagnosis Cardiovascular Diseases - epidemiology Cholesterol Cholesterol, HDL - blood Cross-Sectional Studies Diabetes Female Gender differences Glucose Health risks Hong Kong - epidemiology Humans Hypertension Insulin - blood Kinases Low density lipoprotein Male Medical sciences Metabolic diseases Metabolic disorders Metabolic syndrome Middle Aged Obesity Plasma Predictive Value of Tests Regression analysis Risk Factors Sex Factors Triglycerides - blood Women |
| title | Association between simple anthropometric indices and cardiovascular risk factors |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-20T21%3A18%3A44IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Association%20between%20simple%20anthropometric%20indices%20and%20cardiovascular%20risk%20factors&rft.jtitle=International%20Journal%20of%20Obesity&rft.au=HO,%20S.%20C&rft.date=2001-11-01&rft.volume=25&rft.issue=11&rft.spage=1689&rft.epage=1697&rft.pages=1689-1697&rft.issn=0307-0565&rft.eissn=1476-5497&rft.coden=IJOBDP&rft_id=info:doi/10.1038/sj.ijo.0801784&rft_dat=%3Cproquest_cross%3E1011863021%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=219221667&rft_id=info:pmid/11753592&rfr_iscdi=true |