Fasting insulin sensitivity indices are not better than routine clinical variables at predicting insulin sensitivity among Black Africans: a clamp study in sub-Saharan Africans
Identifieur interne : 001581 ( Pmc/Corpus ); précédent : 001580; suivant : 001582Fasting insulin sensitivity indices are not better than routine clinical variables at predicting insulin sensitivity among Black Africans: a clamp study in sub-Saharan Africans
Auteurs : Eugene Sobngwi ; Andre-Pascal Kengne ; Justin B. Echouffo-Tcheugui ; Simeon Choukem ; Joelle Sobngwi-Tambekou ; Eric V. Balti ; Mark S. Pearce ; Valentin Siaha ; Aissa S. Mamdjokam ; Valery Effoe ; Eric Lontchi-Yimagou ; Oliver T. Donfack ; Barbara Atogho-Tiedeu ; Philippe Boudou ; Jean-Francois Gautier ; Jean-Claude MbanyaSource :
- BMC Endocrine Disorders [ 1472-6823 ] ; 2014.
Abstract
We aimed to evaluate the predictive utility of common fasting insulin sensitivity indices, and non-laboratory surrogates [BMI, waist circumference (WC) and waist-to-height ratio (WHtR)] in sub-Saharan Africans without diabetes.
We measured fasting glucose and insulin, and glucose uptake during 80/mU/m2/min euglycemic clamp in 87 Cameroonians (51 men) aged (SD) 34.6 (11.4) years. We derived insulin sensitivity indices including HOMA-IR, quantitative insulin sensitivity check index (QUICKI), fasting insulin resistance index (FIRI) and glucose-to-insulin ratio (GIR). Indices and clinical predictors were compared to clamp using correlation tests, robust linear regressions and agreement of classification by sex-specific thirds.
The mean insulin sensitivity was M = 10.5 ± 3.2 mg/kg/min. Classification across thirds of insulin sensitivity by clamp matched with non-laboratory surrogates in 30-48% of participants, and with fasting indices in 27-51%, with kappa statistics ranging from −0.10 to 0.26. Fasting indices correlated significantly with clamp (/r/=0.23-0.30), with GIR performing less well than fasting insulin and HOMA-IR (both p < 0.02). BMI, WC and WHtR were equal or superior to fasting indices (/r/=0.38-0.43). Combinations of fasting indices and clinical predictors explained 25-27% of variation in clamp values.
Fasting insulin sensitivity indices are modest predictors of insulin sensitivity measured by euglycemic clamp, and do not perform better than clinical surrogates in this population.
Url:
DOI: 10.1186/1472-6823-14-65
PubMed: 25106496
PubMed Central: 4130121
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PMC:4130121Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Fasting insulin sensitivity indices are not better than routine clinical variables at predicting insulin sensitivity among Black Africans: a clamp study in sub-Saharan Africans</title><author><name sortKey="Sobngwi, Eugene" sort="Sobngwi, Eugene" uniqKey="Sobngwi E" first="Eugene" last="Sobngwi">Eugene Sobngwi</name><affiliation><nlm:aff id="I1">Department of Internal Medicine, Faculty of Medicine and Biomedical Sciences, University of Yaounde I, Yaounde, Cameroon</nlm:aff></affiliation><affiliation><nlm:aff id="I2">National Obesity Centre, Yaounde Central Hospital, Yaounde, Cameroon</nlm:aff></affiliation><affiliation><nlm:aff id="I12">Laboratory of Molecular Medicine and Metabolism, Biotechnology Centre, Nkolbisson, University of Yaounde 1, Yaounde, Cameroon</nlm:aff></affiliation></author><author><name sortKey="Kengne, Andre Pascal" sort="Kengne, Andre Pascal" uniqKey="Kengne A" first="Andre-Pascal" last="Kengne">Andre-Pascal Kengne</name><affiliation><nlm:aff id="I3">South African Medical Research Council & University of Cape Town, Cape Town, South Africa</nlm:aff></affiliation><affiliation><nlm:aff id="I4">The George Institute for Global Health, Sydney, Australia</nlm:aff></affiliation></author><author><name sortKey="Echouffo Tcheugui, Justin B" sort="Echouffo Tcheugui, Justin B" uniqKey="Echouffo Tcheugui J" first="Justin B" last="Echouffo-Tcheugui">Justin B. Echouffo-Tcheugui</name><affiliation><nlm:aff id="I5">Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA</nlm:aff></affiliation></author><author><name sortKey="Choukem, Simeon" sort="Choukem, Simeon" uniqKey="Choukem S" first="Simeon" last="Choukem">Simeon Choukem</name><affiliation><nlm:aff id="I6">Faculty of Health Sciences, University of Buea, Buea, Cameroon</nlm:aff></affiliation><affiliation><nlm:aff id="I7">Department of Internal Medicine, Douala General Hospital, Douala, Cameroon</nlm:aff></affiliation></author><author><name sortKey="Sobngwi Tambekou, Joelle" sort="Sobngwi Tambekou, Joelle" uniqKey="Sobngwi Tambekou J" first="Joelle" last="Sobngwi-Tambekou">Joelle Sobngwi-Tambekou</name><affiliation><nlm:aff id="I8">Centre of Higher Education in Health Sciences, Catholic University of Central Africa, Yaounde, Cameroon</nlm:aff></affiliation></author><author><name sortKey="Balti, Eric V" sort="Balti, Eric V" uniqKey="Balti E" first="Eric V" last="Balti">Eric V. Balti</name><affiliation><nlm:aff id="I2">National Obesity Centre, Yaounde Central Hospital, Yaounde, Cameroon</nlm:aff></affiliation><affiliation><nlm:aff id="I9">Diabetes Research Center, Brussels Free University-(VUB), Brussels, Belgium</nlm:aff></affiliation></author><author><name sortKey="Pearce, Mark S" sort="Pearce, Mark S" uniqKey="Pearce M" first="Mark S" last="Pearce">Mark S. Pearce</name><affiliation><nlm:aff id="I10">Institute of Health & Society, Newcastle University, Newcastle upon Tyne, UK</nlm:aff></affiliation></author><author><name sortKey="Siaha, Valentin" sort="Siaha, Valentin" uniqKey="Siaha V" first="Valentin" last="Siaha">Valentin Siaha</name><affiliation><nlm:aff id="I2">National Obesity Centre, Yaounde Central Hospital, Yaounde, Cameroon</nlm:aff></affiliation></author><author><name sortKey="Mamdjokam, Aissa S" sort="Mamdjokam, Aissa S" uniqKey="Mamdjokam A" first="Aissa S" last="Mamdjokam">Aissa S. Mamdjokam</name><affiliation><nlm:aff id="I2">National Obesity Centre, Yaounde Central Hospital, Yaounde, Cameroon</nlm:aff></affiliation></author><author><name sortKey="Effoe, Valery" sort="Effoe, Valery" uniqKey="Effoe V" first="Valery" last="Effoe">Valery Effoe</name><affiliation><nlm:aff id="I2">National Obesity Centre, Yaounde Central Hospital, Yaounde, Cameroon</nlm:aff></affiliation><affiliation><nlm:aff id="I11">Wake Forest Institute for Regenerative Medicine, Wake Forest University, Winston-Salem, North Carolina, USA</nlm:aff></affiliation></author><author><name sortKey="Lontchi Yimagou, Eric" sort="Lontchi Yimagou, Eric" uniqKey="Lontchi Yimagou E" first="Eric" last="Lontchi-Yimagou">Eric Lontchi-Yimagou</name><affiliation><nlm:aff id="I12">Laboratory of Molecular Medicine and Metabolism, Biotechnology Centre, Nkolbisson, University of Yaounde 1, Yaounde, Cameroon</nlm:aff></affiliation></author><author><name sortKey="Donfack, Oliver T" sort="Donfack, Oliver T" uniqKey="Donfack O" first="Oliver T" last="Donfack">Oliver T. Donfack</name><affiliation><nlm:aff id="I12">Laboratory of Molecular Medicine and Metabolism, Biotechnology Centre, Nkolbisson, University of Yaounde 1, Yaounde, Cameroon</nlm:aff></affiliation></author><author><name sortKey="Atogho Tiedeu, Barbara" sort="Atogho Tiedeu, Barbara" uniqKey="Atogho Tiedeu B" first="Barbara" last="Atogho-Tiedeu">Barbara Atogho-Tiedeu</name><affiliation><nlm:aff id="I12">Laboratory of Molecular Medicine and Metabolism, Biotechnology Centre, Nkolbisson, University of Yaounde 1, Yaounde, Cameroon</nlm:aff></affiliation></author><author><name sortKey="Boudou, Philippe" sort="Boudou, Philippe" uniqKey="Boudou P" first="Philippe" last="Boudou">Philippe Boudou</name><affiliation><nlm:aff id="I13">Unit of Transfer in Molecular Oncology and Hormonology, Saint-Louis University Hospital, Assistance Publique - Hôpitaux de Paris, Paris, France</nlm:aff></affiliation></author><author><name sortKey="Gautier, Jean Francois" sort="Gautier, Jean Francois" uniqKey="Gautier J" first="Jean-Francois" last="Gautier">Jean-Francois Gautier</name><affiliation><nlm:aff id="I14">Department of Diabetes and Endocrinology, Saint-Louis University Hospital, Assistance Publique - Hôpitaux de Paris, University Paris-Diderot Paris-7, Paris, France</nlm:aff></affiliation></author><author><name sortKey="Mbanya, Jean Claude" sort="Mbanya, Jean Claude" uniqKey="Mbanya J" first="Jean-Claude" last="Mbanya">Jean-Claude Mbanya</name><affiliation><nlm:aff id="I1">Department of Internal Medicine, Faculty of Medicine and Biomedical Sciences, University of Yaounde I, Yaounde, Cameroon</nlm:aff></affiliation><affiliation><nlm:aff id="I2">National Obesity Centre, Yaounde Central Hospital, Yaounde, Cameroon</nlm:aff></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">25106496</idno><idno type="pmc">4130121</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4130121</idno><idno type="RBID">PMC:4130121</idno><idno type="doi">10.1186/1472-6823-14-65</idno><date when="2014">2014</date><idno type="wicri:Area/Pmc/Corpus">001581</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">001581</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Fasting insulin sensitivity indices are not better than routine clinical variables at predicting insulin sensitivity among Black Africans: a clamp study in sub-Saharan Africans</title><author><name sortKey="Sobngwi, Eugene" sort="Sobngwi, Eugene" uniqKey="Sobngwi E" first="Eugene" last="Sobngwi">Eugene Sobngwi</name><affiliation><nlm:aff id="I1">Department of Internal Medicine, Faculty of Medicine and Biomedical Sciences, University of Yaounde I, Yaounde, Cameroon</nlm:aff></affiliation><affiliation><nlm:aff id="I2">National Obesity Centre, Yaounde Central Hospital, Yaounde, Cameroon</nlm:aff></affiliation><affiliation><nlm:aff id="I12">Laboratory of Molecular Medicine and Metabolism, Biotechnology Centre, Nkolbisson, University of Yaounde 1, Yaounde, Cameroon</nlm:aff></affiliation></author><author><name sortKey="Kengne, Andre Pascal" sort="Kengne, Andre Pascal" uniqKey="Kengne A" first="Andre-Pascal" last="Kengne">Andre-Pascal Kengne</name><affiliation><nlm:aff id="I3">South African Medical Research Council & University of Cape Town, Cape Town, South Africa</nlm:aff></affiliation><affiliation><nlm:aff id="I4">The George Institute for Global Health, Sydney, Australia</nlm:aff></affiliation></author><author><name sortKey="Echouffo Tcheugui, Justin B" sort="Echouffo Tcheugui, Justin B" uniqKey="Echouffo Tcheugui J" first="Justin B" last="Echouffo-Tcheugui">Justin B. Echouffo-Tcheugui</name><affiliation><nlm:aff id="I5">Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA</nlm:aff></affiliation></author><author><name sortKey="Choukem, Simeon" sort="Choukem, Simeon" uniqKey="Choukem S" first="Simeon" last="Choukem">Simeon Choukem</name><affiliation><nlm:aff id="I6">Faculty of Health Sciences, University of Buea, Buea, Cameroon</nlm:aff></affiliation><affiliation><nlm:aff id="I7">Department of Internal Medicine, Douala General Hospital, Douala, Cameroon</nlm:aff></affiliation></author><author><name sortKey="Sobngwi Tambekou, Joelle" sort="Sobngwi Tambekou, Joelle" uniqKey="Sobngwi Tambekou J" first="Joelle" last="Sobngwi-Tambekou">Joelle Sobngwi-Tambekou</name><affiliation><nlm:aff id="I8">Centre of Higher Education in Health Sciences, Catholic University of Central Africa, Yaounde, Cameroon</nlm:aff></affiliation></author><author><name sortKey="Balti, Eric V" sort="Balti, Eric V" uniqKey="Balti E" first="Eric V" last="Balti">Eric V. Balti</name><affiliation><nlm:aff id="I2">National Obesity Centre, Yaounde Central Hospital, Yaounde, Cameroon</nlm:aff></affiliation><affiliation><nlm:aff id="I9">Diabetes Research Center, Brussels Free University-(VUB), Brussels, Belgium</nlm:aff></affiliation></author><author><name sortKey="Pearce, Mark S" sort="Pearce, Mark S" uniqKey="Pearce M" first="Mark S" last="Pearce">Mark S. Pearce</name><affiliation><nlm:aff id="I10">Institute of Health & Society, Newcastle University, Newcastle upon Tyne, UK</nlm:aff></affiliation></author><author><name sortKey="Siaha, Valentin" sort="Siaha, Valentin" uniqKey="Siaha V" first="Valentin" last="Siaha">Valentin Siaha</name><affiliation><nlm:aff id="I2">National Obesity Centre, Yaounde Central Hospital, Yaounde, Cameroon</nlm:aff></affiliation></author><author><name sortKey="Mamdjokam, Aissa S" sort="Mamdjokam, Aissa S" uniqKey="Mamdjokam A" first="Aissa S" last="Mamdjokam">Aissa S. Mamdjokam</name><affiliation><nlm:aff id="I2">National Obesity Centre, Yaounde Central Hospital, Yaounde, Cameroon</nlm:aff></affiliation></author><author><name sortKey="Effoe, Valery" sort="Effoe, Valery" uniqKey="Effoe V" first="Valery" last="Effoe">Valery Effoe</name><affiliation><nlm:aff id="I2">National Obesity Centre, Yaounde Central Hospital, Yaounde, Cameroon</nlm:aff></affiliation><affiliation><nlm:aff id="I11">Wake Forest Institute for Regenerative Medicine, Wake Forest University, Winston-Salem, North Carolina, USA</nlm:aff></affiliation></author><author><name sortKey="Lontchi Yimagou, Eric" sort="Lontchi Yimagou, Eric" uniqKey="Lontchi Yimagou E" first="Eric" last="Lontchi-Yimagou">Eric Lontchi-Yimagou</name><affiliation><nlm:aff id="I12">Laboratory of Molecular Medicine and Metabolism, Biotechnology Centre, Nkolbisson, University of Yaounde 1, Yaounde, Cameroon</nlm:aff></affiliation></author><author><name sortKey="Donfack, Oliver T" sort="Donfack, Oliver T" uniqKey="Donfack O" first="Oliver T" last="Donfack">Oliver T. Donfack</name><affiliation><nlm:aff id="I12">Laboratory of Molecular Medicine and Metabolism, Biotechnology Centre, Nkolbisson, University of Yaounde 1, Yaounde, Cameroon</nlm:aff></affiliation></author><author><name sortKey="Atogho Tiedeu, Barbara" sort="Atogho Tiedeu, Barbara" uniqKey="Atogho Tiedeu B" first="Barbara" last="Atogho-Tiedeu">Barbara Atogho-Tiedeu</name><affiliation><nlm:aff id="I12">Laboratory of Molecular Medicine and Metabolism, Biotechnology Centre, Nkolbisson, University of Yaounde 1, Yaounde, Cameroon</nlm:aff></affiliation></author><author><name sortKey="Boudou, Philippe" sort="Boudou, Philippe" uniqKey="Boudou P" first="Philippe" last="Boudou">Philippe Boudou</name><affiliation><nlm:aff id="I13">Unit of Transfer in Molecular Oncology and Hormonology, Saint-Louis University Hospital, Assistance Publique - Hôpitaux de Paris, Paris, France</nlm:aff></affiliation></author><author><name sortKey="Gautier, Jean Francois" sort="Gautier, Jean Francois" uniqKey="Gautier J" first="Jean-Francois" last="Gautier">Jean-Francois Gautier</name><affiliation><nlm:aff id="I14">Department of Diabetes and Endocrinology, Saint-Louis University Hospital, Assistance Publique - Hôpitaux de Paris, University Paris-Diderot Paris-7, Paris, France</nlm:aff></affiliation></author><author><name sortKey="Mbanya, Jean Claude" sort="Mbanya, Jean Claude" uniqKey="Mbanya J" first="Jean-Claude" last="Mbanya">Jean-Claude Mbanya</name><affiliation><nlm:aff id="I1">Department of Internal Medicine, Faculty of Medicine and Biomedical Sciences, University of Yaounde I, Yaounde, Cameroon</nlm:aff></affiliation><affiliation><nlm:aff id="I2">National Obesity Centre, Yaounde Central Hospital, Yaounde, Cameroon</nlm:aff></affiliation></author></analytic><series><title level="j">BMC Endocrine Disorders</title><idno type="eISSN">1472-6823</idno><imprint><date when="2014">2014</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><sec><title>Background</title><p>We aimed to evaluate the predictive utility of common fasting insulin sensitivity indices, and non-laboratory surrogates [BMI, waist circumference (WC) and waist-to-height ratio (WHtR)] in sub-Saharan Africans without diabetes.</p></sec><sec><title>Methods</title><p>We measured fasting glucose and insulin, and glucose uptake during 80/mU/m<sup>2</sup>/min euglycemic clamp in 87 Cameroonians (51 men) aged (SD) 34.6 (11.4) years. We derived insulin sensitivity indices including HOMA-IR, quantitative insulin sensitivity check index (QUICKI), fasting insulin resistance index (FIRI) and glucose-to-insulin ratio (GIR). Indices and clinical predictors were compared to clamp using correlation tests, robust linear regressions and agreement of classification by sex-specific thirds.</p></sec><sec><title>Results</title><p>The mean insulin sensitivity was M = 10.5 ± 3.2 mg/kg/min. Classification across thirds of insulin sensitivity by clamp matched with non-laboratory surrogates in 30-48% of participants, and with fasting indices in 27-51%, with kappa statistics ranging from −0.10 to 0.26. Fasting indices correlated significantly with clamp (/r/=0.23-0.30), with GIR performing less well than fasting insulin and HOMA-IR (both p < 0.02). BMI, WC and WHtR were equal or superior to fasting indices (/r/=0.38-0.43). Combinations of fasting indices and clinical predictors explained 25-27% of variation in clamp values.</p></sec><sec><title>Conclusion</title><p>Fasting insulin sensitivity indices are modest predictors of insulin sensitivity measured by euglycemic clamp, and do not perform better than clinical surrogates in this population.</p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Danaei, G" uniqKey="Danaei G">G Danaei</name></author><author><name sortKey="Finucane, Mm" uniqKey="Finucane M">MM Finucane</name></author><author><name sortKey="Lu, Y" uniqKey="Lu Y">Y Lu</name></author><author><name sortKey="Singh, Gm" uniqKey="Singh G">GM Singh</name></author><author><name sortKey="Cowan, Mj" uniqKey="Cowan M">MJ Cowan</name></author><author><name sortKey="Paciorek, Cj" uniqKey="Paciorek C">CJ Paciorek</name></author><author><name sortKey="Lin, Jk" uniqKey="Lin J">JK Lin</name></author><author><name sortKey="Farzadfar, F" 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<front><journal-meta><journal-id journal-id-type="nlm-ta">BMC Endocr Disord</journal-id><journal-id journal-id-type="iso-abbrev">BMC Endocr Disord</journal-id><journal-title-group><journal-title>BMC Endocrine Disorders</journal-title></journal-title-group><issn pub-type="epub">1472-6823</issn><publisher><publisher-name>BioMed Central</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">25106496</article-id><article-id pub-id-type="pmc">4130121</article-id><article-id pub-id-type="publisher-id">1472-6823-14-65</article-id><article-id pub-id-type="doi">10.1186/1472-6823-14-65</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group></article-categories><title-group><article-title>Fasting insulin sensitivity indices are not better than routine clinical variables at predicting insulin sensitivity among Black Africans: a clamp study in sub-Saharan Africans</article-title></title-group><contrib-group><contrib contrib-type="author" corresp="yes" id="A1"><name><surname>Sobngwi</surname><given-names>Eugene</given-names></name><xref ref-type="aff" rid="I1">1</xref><xref ref-type="aff" rid="I2">2</xref><xref ref-type="aff" rid="I12">12</xref><email>sobngwieugene@yahoo.fr</email></contrib><contrib contrib-type="author" id="A2"><name><surname>Kengne</surname><given-names>Andre-Pascal</given-names></name><xref ref-type="aff" rid="I3">3</xref><xref ref-type="aff" rid="I4">4</xref><email>andre.kengne@mrc.ac.za</email></contrib><contrib contrib-type="author" id="A3"><name><surname>Echouffo-Tcheugui</surname><given-names>Justin B</given-names></name><xref ref-type="aff" rid="I5">5</xref><email>echouffotcheugui@yahoo.com</email></contrib><contrib contrib-type="author" id="A4"><name><surname>Choukem</surname><given-names>Simeon</given-names></name><xref ref-type="aff" rid="I6">6</xref><xref ref-type="aff" rid="I7">7</xref><email>sipic2@yahoo.com</email></contrib><contrib contrib-type="author" id="A5"><name><surname>Sobngwi-Tambekou</surname><given-names>Joelle</given-names></name><xref ref-type="aff" rid="I8">8</xref><email>jtambekou@yahoo.fr</email></contrib><contrib contrib-type="author" id="A6"><name><surname>Balti</surname><given-names>Eric V</given-names></name><xref ref-type="aff" rid="I2">2</xref><xref ref-type="aff" rid="I9">9</xref><email>ebaltivo@vub.ac.be</email></contrib><contrib contrib-type="author" id="A7"><name><surname>Pearce</surname><given-names>Mark S</given-names></name><xref ref-type="aff" rid="I10">10</xref><email>mark.pearce@ncl.ac.uk</email></contrib><contrib contrib-type="author" id="A8"><name><surname>Siaha</surname><given-names>Valentin</given-names></name><xref ref-type="aff" rid="I2">2</xref><email>valto_s2002@yahoo.fr</email></contrib><contrib contrib-type="author" id="A9"><name><surname>Mamdjokam</surname><given-names>Aissa S</given-names></name><xref ref-type="aff" rid="I2">2</xref><email>aissag7@yahoo.fr</email></contrib><contrib contrib-type="author" id="A10"><name><surname>Effoe</surname><given-names>Valery</given-names></name><xref ref-type="aff" rid="I2">2</xref><xref ref-type="aff" rid="I11">11</xref><email>valeffoe@gmail.com</email></contrib><contrib contrib-type="author" id="A11"><name><surname>Lontchi-Yimagou</surname><given-names>Eric</given-names></name><xref ref-type="aff" rid="I12">12</xref><email>lontchifrenzy@yahoo.fr</email></contrib><contrib contrib-type="author" id="A12"><name><surname>Donfack</surname><given-names>Oliver T</given-names></name><xref ref-type="aff" rid="I12">12</xref><email>tsainelafouine@yahoo.fr</email></contrib><contrib contrib-type="author" id="A13"><name><surname>Atogho-Tiedeu</surname><given-names>Barbara</given-names></name><xref ref-type="aff" rid="I12">12</xref><email>mma_tiedeu@yahoo.com</email></contrib><contrib contrib-type="author" id="A14"><name><surname>Boudou</surname><given-names>Philippe</given-names></name><xref ref-type="aff" rid="I13">13</xref><email>philippe.boudou@sls.ap-hop-paris.fr</email></contrib><contrib contrib-type="author" id="A15"><name><surname>Gautier</surname><given-names>Jean-Francois</given-names></name><xref ref-type="aff" rid="I14">14</xref><email>jean-francois.gautier@lrb.aphp.fr</email></contrib><contrib contrib-type="author" id="A16"><name><surname>Mbanya</surname><given-names>Jean-Claude</given-names></name><xref ref-type="aff" rid="I1">1</xref><xref ref-type="aff" rid="I2">2</xref><email>jcmbanya@yahoo.co.uk</email></contrib></contrib-group><aff id="I1"><label>1</label>Department of Internal Medicine, Faculty of Medicine and Biomedical Sciences, University of Yaounde I, Yaounde, Cameroon</aff><aff id="I2"><label>2</label>National Obesity Centre, Yaounde Central Hospital, Yaounde, Cameroon</aff><aff id="I3"><label>3</label>South African Medical Research Council & University of Cape Town, Cape Town, South Africa</aff><aff id="I4"><label>4</label>The George Institute for Global Health, Sydney, Australia</aff><aff id="I5"><label>5</label>Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA</aff><aff id="I6"><label>6</label>Faculty of Health Sciences, University of Buea, Buea, Cameroon</aff><aff id="I7"><label>7</label>Department of Internal Medicine, Douala General Hospital, Douala, Cameroon</aff><aff id="I8"><label>8</label>Centre of Higher Education in Health Sciences, Catholic University of Central Africa, Yaounde, Cameroon</aff><aff id="I9"><label>9</label>Diabetes Research Center, Brussels Free University-(VUB), Brussels, Belgium</aff><aff id="I10"><label>10</label>Institute of Health & Society, Newcastle University, Newcastle upon Tyne, UK</aff><aff id="I11"><label>11</label>Wake Forest Institute for Regenerative Medicine, Wake Forest University, Winston-Salem, North Carolina, USA</aff><aff id="I12"><label>12</label>Laboratory of Molecular Medicine and Metabolism, Biotechnology Centre, Nkolbisson, University of Yaounde 1, Yaounde, Cameroon</aff><aff id="I13"><label>13</label>Unit of Transfer in Molecular Oncology and Hormonology, Saint-Louis University Hospital, Assistance Publique - Hôpitaux de Paris, Paris, France</aff><aff id="I14"><label>14</label>Department of Diabetes and Endocrinology, Saint-Louis University Hospital, Assistance Publique - Hôpitaux de Paris, University Paris-Diderot Paris-7, Paris, France</aff><pub-date pub-type="collection"><year>2014</year></pub-date><pub-date pub-type="epub"><day>9</day><month>8</month><year>2014</year></pub-date><volume>14</volume><fpage>65</fpage><lpage>65</lpage><history><date date-type="received"><day>5</day><month>4</month><year>2014</year></date><date date-type="accepted"><day>1</day><month>8</month><year>2014</year></date></history><permissions><copyright-statement>Copyright © 2014 Sobngwi et al.; licensee BioMed Central Ltd.</copyright-statement><copyright-year>2014</copyright-year><copyright-holder>Sobngwi et al.; licensee BioMed Central Ltd.</copyright-holder><license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/4.0"><license-p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0">http://creativecommons.org/licenses/by/4.0</ext-link>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/publicdomain/zero/1.0/">http://creativecommons.org/publicdomain/zero/1.0/</ext-link>) applies to the data made available in this article, unless otherwise stated.</license-p></license></permissions><self-uri xlink:href="http://www.biomedcentral.com/1472-6823/14/65"></self-uri><abstract><sec><title>Background</title><p>We aimed to evaluate the predictive utility of common fasting insulin sensitivity indices, and non-laboratory surrogates [BMI, waist circumference (WC) and waist-to-height ratio (WHtR)] in sub-Saharan Africans without diabetes.</p></sec><sec><title>Methods</title><p>We measured fasting glucose and insulin, and glucose uptake during 80/mU/m<sup>2</sup>/min euglycemic clamp in 87 Cameroonians (51 men) aged (SD) 34.6 (11.4) years. We derived insulin sensitivity indices including HOMA-IR, quantitative insulin sensitivity check index (QUICKI), fasting insulin resistance index (FIRI) and glucose-to-insulin ratio (GIR). Indices and clinical predictors were compared to clamp using correlation tests, robust linear regressions and agreement of classification by sex-specific thirds.</p></sec><sec><title>Results</title><p>The mean insulin sensitivity was M = 10.5 ± 3.2 mg/kg/min. Classification across thirds of insulin sensitivity by clamp matched with non-laboratory surrogates in 30-48% of participants, and with fasting indices in 27-51%, with kappa statistics ranging from −0.10 to 0.26. Fasting indices correlated significantly with clamp (/r/=0.23-0.30), with GIR performing less well than fasting insulin and HOMA-IR (both p < 0.02). BMI, WC and WHtR were equal or superior to fasting indices (/r/=0.38-0.43). Combinations of fasting indices and clinical predictors explained 25-27% of variation in clamp values.</p></sec><sec><title>Conclusion</title><p>Fasting insulin sensitivity indices are modest predictors of insulin sensitivity measured by euglycemic clamp, and do not perform better than clinical surrogates in this population.</p></sec></abstract></article-meta></front><body><sec><title>Background</title><p>Type 2 diabetes mellitus (T2DM) and obesity, which are both associated with insulin resistance, are increasingly common worldwide, especially in developing countries including sub-Saharan African (SSA) [<xref ref-type="bibr" rid="B1">1</xref>,<xref ref-type="bibr" rid="B2">2</xref>]. Furthermore, the highest relative increases in diabetes (by 90%) prevalence by 2030 is projected to occur in SSA [<xref ref-type="bibr" rid="B3">3</xref>]. The experienced increasing trends of T2DM and obesity over the last two decades in SSA have revealed new challenges for diagnosis, prevention and treatment, as well as uncovering context specific causes and promoters of the conditions. Given the central role of insulin resistance in the pathogenesis of T2DM and obesity, measures of insulin sensitivity are very important diagnostic and research tools. The gold standard for assessing insulin sensitivity is the hyperinsulinemic-euglycemic clamp, which measures the in vivo rate of insulin-stimulated glucose uptake [<xref ref-type="bibr" rid="B4">4</xref>]. However, this method is invasive, costly, logistically challenging, technically demanding, and time consuming. Consequently, it is impractical and not applicable in large-scale epidemiological and intervention studies, especially in resource-poor settings of SSA. Surrogate indices of insulin sensitivity that can be used in large-scale studies have been developed [<xref ref-type="bibr" rid="B5">5</xref>], and validated in several populations [<xref ref-type="bibr" rid="B5">5</xref>], mainly Caucasians. However, there are suggestions that ethnicity may influence the performance of available surrogate indices of insulin sensitivity, particularly among populations with high prevalence of insulin resistance such as Africans [<xref ref-type="bibr" rid="B6">6</xref>,<xref ref-type="bibr" rid="B7">7</xref>]. This issue however, remains largely under-investigated and little is known on the diagnostic utility of common insulin sensitivity indices, and whether they even do better than non-laboratory-based determinants of insulin sensitivity, in SSA populations. We therefore assessed the performance of common fasting indices of insulin sensitivity and clinical surrogates of insulin resistance, against hyperinsulinemic-euglycemic clamp-measured insulin sensitivity, among non-diabetic Cameroonians adults with a wide range of insulin sensitivity/resistance profile.</p></sec><sec sec-type="methods"><title>Methods</title><sec><title>Study population</title><p>We recruited 87 non-diabetic volunteers of sub- Saharan African origin (51 men and 36 women) aged 21 to 61 years, from 2006 to 2008 in Cameroon. Eligible healthy subjects were recruited through the outpatient clinic of the National Obesity Center of the Yaounde Central Hospital [<xref ref-type="bibr" rid="B8">8</xref>]. Potential participants were screened by history, physical examination and biochemical tests. A fasting plasma glucose of ≥ 126 mg/dl (7 mmol/L) indicated diabetes [<xref ref-type="bibr" rid="B9">9</xref>]. Participants with serum creatinine concentrations >1.5 mg/dl, on medications that may impact on energy metabolism, with human immunodeficiency virus (HIV)-positive status, or with overt chronic liver, renal, or thyroid disease, active coronary artery disease, and smoking more than 20 cigarettes per day, were excluded.</p><p>All volunteers were examined on two consecutive days, each after 12-h overnight fast and controlled diet and activity for 7 days. Participants had a diet consisting of 50% carbohydrates, 30% lipids, and 20% proteins, and vigorous physical exercise was prohibited. On day 1, we performed anthropometric measurements and an oral glucose tolerance test (OGTT), and on day 2, we performed a euglycemic hyperinsulinemic clamp.</p></sec><sec><title>Anthropometric measurements</title><p>For all participants, we measured height to the nearest 0.5 cm, and weight in light clothes to the nearest 0.1 kg, and calculated the body mass index (BMI) as weight in kg/height<sup>2</sup> in m<sup>2</sup>. Individuals were categorized as lean (BMI < 25 kg/m<sup>2</sup>), overweight (BMI: 25–29.9 kg/m<sup>2</sup>) or obese (BMI ≥ 30 kg/m<sup>2</sup>). We measured waist and hip circumference to the nearest 0.5 cm and calculated the waist-to-hip ratio as well as waist-to-height ratio (WHtR). Total fat mass, fat-free mass, and percent fat were measured by dual energy X-ray absorptiometry (DEXA) with an absorptiometer (Hologic QDR-1000/W, Wilmington, MA, USA) with Whole Body V5.73 software (n = 19), or by bioimpedance (TANITA BC 420 MA, TANITA Corporation 1-14-2 Maeno-cho, Tabashi-ku, Tokyo-Japan) (n = 68).</p><p>Blood pressure was the mean of two measurements performed at least three minutes apart, in the right arm with the subject sited after a 15-min rest with an Omron recorder (manufacturer references).</p></sec><sec><title>Fasting measurements</title><sec><title>Oral glucose tolerance test</title><p>After a 12 h overnight fast, each participant underwent a 75-gram OGTT over 120 minutes. We collected whole blood samples from an antecubital vein at 0, 30, and 120 min for the determination of blood glucose, and serum insulin and the evaluation of glucose tolerance according to World Health Organization Criteria (WHO 1998 criteria) [<xref ref-type="bibr" rid="B9">9</xref>], and early phase insulin secretory response.</p></sec><sec><title>Euglycemic hyperinsulinemic clamp</title><p>Whole-body insulin sensitivity was evaluated with a 120-minute euglycemic hyperinsulinemic clamp technique [<xref ref-type="bibr" rid="B4">4</xref>]. After a 12-h overnight fast, at 8 am, a priming dose of insulin infusion (Actrapid 100 IU/ml; Novo Nordisk, Gentofte, Denmark) was administrated during the initial 10 minutes to acutely raise plasma insulin to the desired level, where it was maintained by a continuous insulin infusion at a rate of 80 mU/m<sup>2</sup> body surface area per minute. Blood glucose was clamped at 100 mg/dl (5.5 mmol/l) for 100 minutes by infusing 20% glucose at variable rates according to blood glucose measurements performed at 5-min intervals (mean coefficient of variation of blood glucose was <5%). The mean value for the period from 80 to 100 min was used to calculate the rates of whole body glucose uptake. In the fasting state and at 80, 90, and 100 min, arterialized blood samples for the measurement of plasma insulin were performed.</p></sec><sec><title>Biochemical assays</title><p>We performed all assays twice using the same batch of kits in each case. Glucose was measured by the glucose oxidase method, and we used immunoradiometric assays (Bi-insulin IRMA [Bio-Rad, Marnes la Coquette, France] to measure insulin. The intra-assay coefficient of variation was 1.8-3.8% and the inter-assay coefficient of variation was 2.6-8.0% for insulin. Serum total cholesterol, high-density lipoprotein (HDL)-cholesterol and triglycerides were measured by means of standard enzymatic techniques. Low-density lipoprotein (LDL)-cholesterol was calculated using Friedwald’s formula [<xref ref-type="bibr" rid="B10">10</xref>].</p></sec><sec><title>Calculations of clamp-derived and surrogate indices of insulin sensitivity</title><p>Insulin mediated glucose uptake (M value) was calculated from the glucose infusion rate during the final 20 min of the glucose clamp as the rate of exogenous glucose infusion divided by the steady-state clamp insulin concentration, after accounting for differences between individuals in glucose space (by dividing the average group steady-state glucose by the individual steady state glucose), and expressed in mg/min/kg of body fat-free mass [<xref ref-type="bibr" rid="B4">4</xref>].</p><p>Calculations of fasting-derived indices were made using the mean of two fasting glucose and insulin concentrations before the start of the euglycemic clamp. The fasting glucose to insulin ratio (Glucose/Insulin ratio), fasting insulin resistance index (FIRI = fasting glucose × fasting insulin/25) [<xref ref-type="bibr" rid="B11">11</xref>], the Homeostasis Model Assessment (HOMA) for insulin resistance (HOMA-IR) [<xref ref-type="bibr" rid="B12">12</xref>,<xref ref-type="bibr" rid="B13">13</xref>], and the quantitative insulin sensitivity check index (QUICKI) [<xref ref-type="bibr" rid="B14">14</xref>] were calculated according to established methods. Given that HOMA-IR and FIRI assess insulin resistance as opposed to sensitivity, negative correlations with euglycemic clamp measure of insulin sensitivity would be expected.</p></sec></sec><sec><title>Statistical analysis</title><p>Data are presented as mean (standard deviation, SD) for continuous variables and as count and percentage for categorical variables. We compared groups (BMI and gender) using the Kruskal-Wallis test for continuous variables, and assessed the heterogeneity across gender and BMI subgroups through interaction tests. Continuous associations between indices of insulin sensitivity was assessed graphically with the use of correlation matrix, applying the Box-Cox [<xref ref-type="bibr" rid="B15">15</xref>] power transformations to improve the shape of the associations; then the “<italic>Covariance Estimation for Multivariate t Distribution</italic>” [<xref ref-type="bibr" rid="B16">16</xref>] methods was used to derived the correlation coefficients, while minimising the potential effects of outliers. The Steiger t test was used to compare correlation coefficients among indices of insulin sensitivity. Regression coefficients to indicate the size of the association of each of the indices with euglycemic clamp was derived from robust multiple linear regressions model that included each of the indices of interest, waist circumference and sex as independent variables. Agreement was explored by examining the proportion of subjects correctly classified by surrogate indices of insulin sensitivity, within sex-specific thirds of clamp-derived measure of insulin sensitivity as the reference. This was supplemented by a formal statistical testing using the kappa test to compare the distribution of participants across increasing thirds of QUICKI and glucose/insulin ratio, or decreasing thirds of age, BMI, waist circumference, WHtR, fasting insulin HOMA-IR and FIRI, vs. increasing third of clamp derived insulin sensitivity. The 95% confidence interval around kappa estimates was from two-sided bootstrap methods, based on 1000 replications. Analyses were carried out using SPSS version 17.0 for Windows (SPSS Inc., Chicago, IL) and R statistical software version 2.13.0 [13-04-2011], (The R Foundation for Statistical Computing, Vienna, Austria). The significance level was set at 0.05.</p></sec></sec><sec sec-type="results"><title>Results</title><sec><title>Characteristics of the study population</title><p>The mean age (SD) was 34.6 (11.4) years and the mean BMI was 27.6 (6.5) kg/m<sup>2</sup>. Table <xref ref-type="table" rid="T1">1</xref> shows the general characteristics of the 87 study participants, across sex-specific BMI categories. In both men and women, there were significant differences in percent fat, waist circumference, hip circumference, WHtR and total-cholesterol across BMI categories, with always significant linear trends. Systolic and diastolic blood pressures, two-hour glucose and fasting insulin levels were significantly different in men (waist-to-hip ratio in women) across BMI categories, again, with significant linear trends, except for systolic blood pressure. In both genders, no significant differences across categories of BMI were noted for age, triglycerides, and cholesterol (HDL and LDL) levels. There was evidence of heterogeneity by sex and across BMI categories for waist-to-hip ratio (p = 0.04 for interaction) fasting and 2-hour glucose (both p ≤ 0.05), and marginally for fasting insulin (p = 0.06), but not for other characteristics (Table <xref ref-type="table" rid="T1">1</xref>).</p><table-wrap position="float" id="T1"><label>Table 1</label><caption><p>Characteristics of the subjects by sex and BMI categories</p></caption><table frame="hsides" rules="groups" border="1"><colgroup><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="right"></col><col align="right"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col></colgroup><thead valign="top"><tr><th align="center" valign="bottom"> <hr></hr></th><th colspan="5" align="center" valign="bottom"><bold>Men</bold><hr></hr></th><th colspan="5" align="center" valign="bottom"><bold>Women</bold><hr></hr></th><th rowspan="2" align="right"><bold>p gender and BMI interaction</bold></th></tr><tr><th align="center"> </th><th align="center"><bold>Lean</bold></th><th align="center"><bold>Overweight</bold></th><th align="center"><bold>Obese</bold></th><th align="right"><bold>p Kruskal Wallis</bold></th><th align="right"><bold>p linearity</bold></th><th align="center"><bold>Lean</bold></th><th align="center"><bold>Overweight</bold></th><th align="center"><bold>Obese</bold></th><th align="right"><bold>p Kruskal Wallis</bold></th><th align="right"><bold>p linearity</bold></th></tr></thead><tbody valign="top"><tr><td align="center" valign="bottom">N<hr></hr></td><td align="center" valign="bottom">23<hr></hr></td><td align="center" valign="bottom">18<hr></hr></td><td align="center" valign="bottom">10<hr></hr></td><td align="right" valign="bottom"> <hr></hr></td><td align="right" valign="bottom"> <hr></hr></td><td align="center" valign="bottom">14<hr></hr></td><td align="center" valign="bottom">9<hr></hr></td><td align="center" valign="bottom">13<hr></hr></td><td align="right" valign="bottom"> <hr></hr></td><td align="right" valign="bottom"> <hr></hr></td><td align="right" valign="bottom"> <hr></hr></td></tr><tr><td align="center" valign="bottom">Age (years)<hr></hr></td><td align="center" valign="bottom">33.1 ± 11.4<hr></hr></td><td align="center" valign="bottom">36.9 ± 9.3<hr></hr></td><td align="center" valign="bottom">38.3 ± 9.7<hr></hr></td><td align="right" valign="bottom">0.23<hr></hr></td><td align="right" valign="bottom">0.15<hr></hr></td><td align="center" valign="bottom">31.3 ± 12.9<hr></hr></td><td align="center" valign="bottom">35.3 ± 16.0<hr></hr></td><td align="center" valign="bottom">34.2 ± 10.7<hr></hr></td><td align="right" valign="bottom">0.70<hr></hr></td><td align="right" valign="bottom">0.56<hr></hr></td><td align="right" valign="bottom">0.91<hr></hr></td></tr><tr><td align="center" valign="bottom">BMI ( kg/m2)<hr></hr></td><td align="center" valign="bottom">22.1 ± 1.4<hr></hr></td><td align="center" valign="bottom">27.7 ± 1.7<hr></hr></td><td align="center" valign="bottom">35.3 ± 7.4<hr></hr></td><td align="right" valign="bottom"><0.001<hr></hr></td><td align="right" valign="bottom"><0.001<hr></hr></td><td align="center" valign="bottom">23.0 ± 1.4<hr></hr></td><td align="center" valign="bottom">27.7 ± 1.5<hr></hr></td><td align="center" valign="bottom">36.3 ± 5.9<hr></hr></td><td align="right" valign="bottom"><0.001<hr></hr></td><td align="right" valign="bottom"><0.001<hr></hr></td><td align="right" valign="bottom">0.86<hr></hr></td></tr><tr><td align="center" valign="bottom">Percent fat (%)<hr></hr></td><td align="center" valign="bottom">14.2 ± 3.6<hr></hr></td><td align="center" valign="bottom">23.2 ± 6.3<hr></hr></td><td align="center" valign="bottom">33.6 ± 9.6<hr></hr></td><td align="right" valign="bottom"><0.001<hr></hr></td><td align="right" valign="bottom"><0.001<hr></hr></td><td align="center" valign="bottom">26.6 ± 6.0<hr></hr></td><td align="center" valign="bottom">32.5 ± 8.0<hr></hr></td><td align="center" valign="bottom">40.8 ± 5.3<hr></hr></td><td align="right" valign="bottom"><0.001<hr></hr></td><td align="right" valign="bottom"><0.001<hr></hr></td><td align="right" valign="bottom">0.28<hr></hr></td></tr><tr><td align="center" valign="bottom">Waist circumference (cm)<hr></hr></td><td align="center" valign="bottom">76.0 ± 4.5<hr></hr></td><td align="center" valign="bottom">92.8 ± 8.4<hr></hr></td><td align="center" valign="bottom">109.0 ± 12.8<hr></hr></td><td align="right" valign="bottom"><0.001<hr></hr></td><td align="right" valign="bottom"><0.001<hr></hr></td><td align="center" valign="bottom">78.0 ± 6.7<hr></hr></td><td align="center" valign="bottom">85.4 ± 7.7<hr></hr></td><td align="center" valign="bottom">102.6 ± 11.4<hr></hr></td><td align="right" valign="bottom"><0.001<hr></hr></td><td align="right" valign="bottom"><0.001<hr></hr></td><td align="right" valign="bottom">0.09<hr></hr></td></tr><tr><td align="center" valign="bottom">Hip circumference (cm)<hr></hr></td><td align="center" valign="bottom">87.1 ± 5.9<hr></hr></td><td align="center" valign="bottom">97.2 ± 6.1<hr></hr></td><td align="center" valign="bottom">117.1 ± 15.1<hr></hr></td><td align="right" valign="bottom"><0.001<hr></hr></td><td align="right" valign="bottom"><0.001<hr></hr></td><td align="center" valign="bottom">92.0 ± 9.1<hr></hr></td><td align="center" valign="bottom">106.9 ± 9.7<hr></hr></td><td align="center" valign="bottom">119.8 ± 13.3<hr></hr></td><td align="right" valign="bottom"><0.001<hr></hr></td><td align="right" valign="bottom"><0.001<hr></hr></td><td align="right" valign="bottom">0.59<hr></hr></td></tr><tr><td align="center" valign="bottom">Waist-to-hip ratio<hr></hr></td><td align="center" valign="bottom">0.89 ± 0.03<hr></hr></td><td align="center" valign="bottom">0.93 ± 0.04<hr></hr></td><td align="center" valign="bottom">0.92 ± 0.05<hr></hr></td><td align="right" valign="bottom">0.12<hr></hr></td><td align="right" valign="bottom">0.10<hr></hr></td><td align="center" valign="bottom">0.85 ± 0.06<hr></hr></td><td align="center" valign="bottom">0.80 ± 0.04<hr></hr></td><td align="center" valign="bottom">0.88 ± 0.08<hr></hr></td><td align="right" valign="bottom">0.04<hr></hr></td><td align="right" valign="bottom">0.40<hr></hr></td><td align="right" valign="bottom">0.04<hr></hr></td></tr><tr><td align="center" valign="bottom">Waist-to-height ratio<hr></hr></td><td align="center" valign="bottom">0.44 ± 0.03<hr></hr></td><td align="center" valign="bottom">0.53 ± 0.05<hr></hr></td><td align="center" valign="bottom">0.63 ± 0.09<hr></hr></td><td align="right" valign="bottom"><0.001<hr></hr></td><td align="right" valign="bottom"><0.001<hr></hr></td><td align="center" valign="bottom">0.48 ± 0.05<hr></hr></td><td align="center" valign="bottom">0.52 ± 0.04<hr></hr></td><td align="center" valign="bottom">0.63 ± 0.07<hr></hr></td><td align="right" valign="bottom"><0.001<hr></hr></td><td align="right" valign="bottom"><0.001<hr></hr></td><td align="right" valign="bottom">0.10<hr></hr></td></tr><tr><td align="center" valign="bottom">Systolic blood pressure (mmHg)<hr></hr></td><td align="center" valign="bottom">122 ± 20<hr></hr></td><td align="center" valign="bottom">131 ± 21<hr></hr></td><td align="center" valign="bottom">129 ± 10<hr></hr></td><td align="right" valign="bottom">0.04<hr></hr></td><td align="right" valign="bottom">0.22<hr></hr></td><td align="center" valign="bottom">123 ± 22<hr></hr></td><td align="center" valign="bottom">117 ± 17<hr></hr></td><td align="center" valign="bottom">125 ± 6<hr></hr></td><td align="right" valign="bottom">0.29<hr></hr></td><td align="right" valign="bottom">0.91<hr></hr></td><td align="right" valign="bottom">0.34<hr></hr></td></tr><tr><td align="center" valign="bottom">Diastolic blood pressure (mmHg)<hr></hr></td><td align="center" valign="bottom">72 ± 9<hr></hr></td><td align="center" valign="bottom">76 ± 11<hr></hr></td><td align="center" valign="bottom">84 ± 6<hr></hr></td><td align="right" valign="bottom">0.006<hr></hr></td><td align="right" valign="bottom">0.002<hr></hr></td><td align="center" valign="bottom">75 ± 9<hr></hr></td><td align="center" valign="bottom">71 ± 6<hr></hr></td><td align="center" valign="bottom">77 ± 5<hr></hr></td><td align="right" valign="bottom">0.09<hr></hr></td><td align="right" valign="bottom">0.47<hr></hr></td><td align="right" valign="bottom">0.11<hr></hr></td></tr><tr><td align="center" valign="bottom">Total cholesterol (mg/L)<hr></hr></td><td align="center" valign="bottom">160 ± 43<hr></hr></td><td align="center" valign="bottom">210 ± 63<hr></hr></td><td align="center" valign="bottom">275 ± 45<hr></hr></td><td align="right" valign="bottom">0.002<hr></hr></td><td align="right" valign="bottom"><0.001<hr></hr></td><td align="center" valign="bottom">154 ± 61<hr></hr></td><td align="center" valign="bottom">182 ± 77<hr></hr></td><td align="center" valign="bottom">235 ± 55<hr></hr></td><td align="right" valign="bottom">0.02<hr></hr></td><td align="right" valign="bottom">0.009<hr></hr></td><td align="right" valign="bottom">0.67<hr></hr></td></tr><tr><td align="center" valign="bottom">Triglycerides (mg/L)<hr></hr></td><td align="center" valign="bottom">50 ± 17<hr></hr></td><td align="center" valign="bottom">57 ± 20<hr></hr></td><td align="center" valign="bottom">71 ± 47<hr></hr></td><td align="right" valign="bottom">0.42<hr></hr></td><td align="right" valign="bottom">0.17<hr></hr></td><td align="center" valign="bottom">54 ± 14<hr></hr></td><td align="center" valign="bottom">47 ± 15<hr></hr></td><td align="center" valign="bottom">71 ± 43<hr></hr></td><td align="right" valign="bottom">0.22<hr></hr></td><td align="right" valign="bottom">0.19<hr></hr></td><td align="right" valign="bottom">0.80<hr></hr></td></tr><tr><td align="center" valign="bottom">HDL cholesterol (mg/L)<hr></hr></td><td align="center" valign="bottom">48 ± 18<hr></hr></td><td align="center" valign="bottom">63 ± 21<hr></hr></td><td align="center" valign="bottom">70 ± 32<hr></hr></td><td align="right" valign="bottom">0.37<hr></hr></td><td align="right" valign="bottom">0.07<hr></hr></td><td align="center" valign="bottom">47 ± 20<hr></hr></td><td align="center" valign="bottom">39 ± 11<hr></hr></td><td align="center" valign="bottom">58 ± 23<hr></hr></td><td align="right" valign="bottom">0.10<hr></hr></td><td align="right" valign="bottom">0.22<hr></hr></td><td align="right" valign="bottom">0.37<hr></hr></td></tr><tr><td align="center" valign="bottom">LDL cholesterol (mg/L)<hr></hr></td><td align="center" valign="bottom">102 ± 40<hr></hr></td><td align="center" valign="bottom">136 ± 54<hr></hr></td><td align="center" valign="bottom">191 ± 80<hr></hr></td><td align="right" valign="bottom">0.02<hr></hr></td><td align="right" valign="bottom">0.006<hr></hr></td><td align="center" valign="bottom">96 ± 48<hr></hr></td><td align="center" valign="bottom">133 ± 81<hr></hr></td><td align="center" valign="bottom">163 ± 64<hr></hr></td><td align="right" valign="bottom">0.07<hr></hr></td><td align="right" valign="bottom">0.03<hr></hr></td><td align="right" valign="bottom">0.82<hr></hr></td></tr><tr><td align="center" valign="bottom">Fasting glucose (mmol/L)<hr></hr></td><td align="center" valign="bottom">4.56 ± 0.58<hr></hr></td><td align="center" valign="bottom">4.42 ± 0.55<hr></hr></td><td align="center" valign="bottom">4.93 ± 0.56<hr></hr></td><td align="right" valign="bottom">0.14<hr></hr></td><td align="right" valign="bottom">0.21<hr></hr></td><td align="center" valign="bottom">4.46 ± 0.50<hr></hr></td><td align="center" valign="bottom">4.85 ± 0.70<hr></hr></td><td align="center" valign="bottom">4.56 ± 043<hr></hr></td><td align="right" valign="bottom">0.20<hr></hr></td><td align="right" valign="bottom">0.61<hr></hr></td><td align="right" valign="bottom">0.04<hr></hr></td></tr><tr><td align="center" valign="bottom">2 h glucose (mmol/L)<hr></hr></td><td align="center" valign="bottom">5.46 ± 1.24<hr></hr></td><td align="center" valign="bottom">5.26 ± 1.00<hr></hr></td><td align="center" valign="bottom">8.17 ± 3.40<hr></hr></td><td align="right" valign="bottom">0.002<hr></hr></td><td align="right" valign="bottom">0.003<hr></hr></td><td align="center" valign="bottom">6.36 ± 1.21<hr></hr></td><td align="center" valign="bottom">6.67 ± 1.68<hr></hr></td><td align="center" valign="bottom">7.02 ± 1.14<hr></hr></td><td align="right" valign="bottom">0.48<hr></hr></td><td align="right" valign="bottom">0.25<hr></hr></td><td align="right" valign="bottom">0.05<hr></hr></td></tr><tr><td align="center" valign="bottom">Fasting insulin (mU/L)<hr></hr></td><td align="center" valign="bottom">4.66 ± 2.56<hr></hr></td><td align="center" valign="bottom">5.71 ± 4.39<hr></hr></td><td align="center" valign="bottom">8.95 ± 3.60<hr></hr></td><td align="right" valign="bottom">0.01<hr></hr></td><td align="right" valign="bottom">0.007<hr></hr></td><td align="center" valign="bottom">6.72 ± 2.69<hr></hr></td><td align="center" valign="bottom">9.56 ± 5.94<hr></hr></td><td align="center" valign="bottom">7.38 ± 3.26<hr></hr></td><td align="right" valign="bottom">0.44<hr></hr></td><td align="right" valign="bottom">0.59<hr></hr></td><td align="right" valign="bottom">0.06<hr></hr></td></tr><tr><td align="center" valign="bottom"><bold>Euglycaemic clamp</bold><hr></hr></td><td align="center" valign="bottom"> <hr></hr></td><td align="center" valign="bottom"> <hr></hr></td><td align="center" valign="bottom"> <hr></hr></td><td align="right" valign="bottom"> <hr></hr></td><td align="right" valign="bottom"> <hr></hr></td><td align="center" valign="bottom"> <hr></hr></td><td align="center" valign="bottom"> <hr></hr></td><td align="center" valign="bottom"> <hr></hr></td><td align="right" valign="bottom"> <hr></hr></td><td align="right" valign="bottom"> <hr></hr></td><td align="right" valign="bottom"> <hr></hr></td></tr><tr><td align="center" valign="bottom">M unadjusted (mg.min<sup>−1</sup>.kg<sup>−1</sup>)<hr></hr></td><td align="center" valign="bottom">10.0 ± 2.7<hr></hr></td><td align="center" valign="bottom">7.5 ± 2.4<hr></hr></td><td align="center" valign="bottom">5.2 ± 1.8<hr></hr></td><td align="right" valign="bottom"><0.001<hr></hr></td><td align="right" valign="bottom"><0.001<hr></hr></td><td align="center" valign="bottom">8.4 ± 2.2<hr></hr></td><td align="center" valign="bottom">7.6 ± 2.8<hr></hr></td><td align="center" valign="bottom">6.1 ± 1.7<hr></hr></td><td align="right" valign="bottom">0.02<hr></hr></td><td align="right" valign="bottom">0.01<hr></hr></td><td align="right" valign="bottom">0.13<hr></hr></td></tr><tr><td align="center" valign="bottom">M adjusted to lean mass (mg.min<sup>−1</sup>.kg<sup>−1</sup>)<hr></hr></td><td align="center" valign="bottom">11.6 ± 2.9<hr></hr></td><td align="center" valign="bottom">9.8 ± 3.3<hr></hr></td><td align="center" valign="bottom">7.8 ± 2.9<hr></hr></td><td align="right" valign="bottom">0.004<hr></hr></td><td align="right" valign="bottom">0.001<hr></hr></td><td align="center" valign="bottom">11.5 ± 2.7<hr></hr></td><td align="center" valign="bottom">11.1 ± 3.4<hr></hr></td><td align="center" valign="bottom">10.4 ± 3.1<hr></hr></td><td align="right" valign="bottom">0.70<hr></hr></td><td align="right" valign="bottom">0.35<hr></hr></td><td align="right" valign="bottom">0.27<hr></hr></td></tr><tr><td align="center" valign="bottom"><bold>Fasting indices</bold><hr></hr></td><td align="center" valign="bottom"> <hr></hr></td><td align="center" valign="bottom"> <hr></hr></td><td align="center" valign="bottom"> <hr></hr></td><td align="right" valign="bottom"> <hr></hr></td><td align="right" valign="bottom"> <hr></hr></td><td align="center" valign="bottom"> <hr></hr></td><td align="center" valign="bottom"> <hr></hr></td><td align="center" valign="bottom"> <hr></hr></td><td align="right" valign="bottom"> <hr></hr></td><td align="right" valign="bottom"> <hr></hr></td><td align="right" valign="bottom"> <hr></hr></td></tr><tr><td align="center" valign="bottom">Plasma insulin (mUI/mL)<hr></hr></td><td align="center" valign="bottom">4.7 ± 2.6<hr></hr></td><td align="center" valign="bottom">5.7 ± 4.4<hr></hr></td><td align="center" valign="bottom">8.9 ± 3.6<hr></hr></td><td align="right" valign="bottom">0.01<hr></hr></td><td align="right" valign="bottom">0.007<hr></hr></td><td align="center" valign="bottom">6.7 ± 2.7<hr></hr></td><td align="center" valign="bottom">9.6 ± 5.9<hr></hr></td><td align="center" valign="bottom">7.4 ± 3.3<hr></hr></td><td align="right" valign="bottom">0.44<hr></hr></td><td align="right" valign="bottom">0.59<hr></hr></td><td align="right" valign="bottom">0.06<hr></hr></td></tr><tr><td align="center" valign="bottom">Glucose/Insulin ratio (mmol/mUI)<hr></hr></td><td align="center" valign="bottom">25.5 ± 18.7<hr></hr></td><td align="center" valign="bottom">21.6 ± 13.3<hr></hr></td><td align="center" valign="bottom">11.6 ± 4.9<hr></hr></td><td align="right" valign="bottom">0.03<hr></hr></td><td align="right" valign="bottom">0.07<hr></hr></td><td align="center" valign="bottom">15.7 ± 12.0<hr></hr></td><td align="center" valign="bottom">13.6 ± 12.1<hr></hr></td><td align="center" valign="bottom">14.0 ± 6.8<hr></hr></td><td align="right" valign="bottom">0.50<hr></hr></td><td align="right" valign="bottom">0.69<hr></hr></td><td align="right" valign="bottom">0.30<hr></hr></td></tr><tr><td align="center" valign="bottom">HOMA-IR<hr></hr></td><td align="center" valign="bottom">0.95 ± 0.57<hr></hr></td><td align="center" valign="bottom">1.11 ± 0.89<hr></hr></td><td align="center" valign="bottom">2.00 ± 0.93<hr></hr></td><td align="right" valign="bottom">0.009<hr></hr></td><td align="right" valign="bottom">0.004<hr></hr></td><td align="center" valign="bottom">1.33 ± 0.56<hr></hr></td><td align="center" valign="bottom">2.08 ± 1.32<hr></hr></td><td align="center" valign="bottom">1.53 ± 0.65<hr></hr></td><td align="right" valign="bottom">0.34<hr></hr></td><td align="right" valign="bottom">0.47<hr></hr></td><td align="right" valign="bottom">0.02<hr></hr></td></tr><tr><td align="center" valign="bottom">FIRI<hr></hr></td><td align="center" valign="bottom">0.85 ± 0.51<hr></hr></td><td align="center" valign="bottom">1.01 ± 0.80<hr></hr></td><td align="center" valign="bottom">1.80 ± 0.84<hr></hr></td><td align="right" valign="bottom">0.009<hr></hr></td><td align="right" valign="bottom">0.004<hr></hr></td><td align="center" valign="bottom">1.20 ± 0.50<hr></hr></td><td align="center" valign="bottom">1.88 ± 1.19<hr></hr></td><td align="center" valign="bottom">1.37 ± 0.58<hr></hr></td><td align="right" valign="bottom">0.34<hr></hr></td><td align="right" valign="bottom">0.47<hr></hr></td><td align="right" valign="bottom">0.02<hr></hr></td></tr><tr><td align="center">QUICKI</td><td align="center">0.30 ± 0.15</td><td align="center">0.19 ± 0.10</td><td align="center">0.11 ± 0.03</td><td align="right">0.01</td><td align="right">0.10</td><td align="center">0.15 ± 0.08</td><td align="center">0.13 ± 0.08</td><td align="center">0.13 ± 0.03</td><td align="right">0.37</td><td align="right">0.46</td><td align="right">0.32</td></tr></tbody></table><table-wrap-foot><p>BMI: body mass index; HDL: high density lipoprotein cholesterol; LDL: low density lipoprotein cholesterol; HOMA-IR: Homeostasis Model Assessment for insulin resistance; FIRI: fasting insulin resistance index; QUICKI: quantitative insulin sensitivity check index.</p></table-wrap-foot></table-wrap></sec><sec><title>Insulin sensitivity across obesity categories</title><p>A total of 79 participants (47 men) had complete data on all variables of interest. Table <xref ref-type="table" rid="T1">1</xref> shows insulin sensitivity levels from various indices across BMI categories. The M-value was low in obese men and women, with significant differences across categories of BMI among men but not among women, with however no evidence of interaction (p = 0.27). Fasting plasma insulin, FIRI, HOMA-IR were highest in obese and lowest in lean men with significant differences across BMI categories, and in linear fashions (all p ≤ 0.01 for linear trends); whereas among women, these were highest in overweight and lowest among lean, with no significant difference or linear trends across BMI categories (all p ≥ 0.34); resulting in significant heterogeneity across sex and BMI categories (all p ≤ 0.06 for interaction, Table <xref ref-type="table" rid="T1">1</xref>). The glucose/insulin ratio was highest among lean men, without any trend in women (p =0.69 for linearity). The QUICKI index was lowest in obese men and women, and highest among lean men and women, with however, significant difference across BMI categories only in men (p =0.01), but not in a differential way (p = 0.32 for sex* and BMI interaction).</p></sec><sec><title>Correlation between fasting indices, clinical surrogates, and clamp measures</title><p>The correlation matrix of fasting indices and clinical surrogates of insulin sensitivity with clamp-derived index is described in Figure <xref ref-type="fig" rid="F1">1</xref>. In the overall sample, correlation coefficients (95% confidence interval) for fasting indices vs. clamp-derived index were −0.27 (−0.47 to −0.05) for fasting insulin, −0.30 (−0.49 to −0.09) for HOMA-IR, 0.29 (0.07 to 0.48) for QUICKI, −0.30 (−0.49 to −0.09) for FIRI and 0.23 (0.01 to 0.43) for glucose/insulin ratio. In analyses stratified by sex, the pattern was similar, with no difference by gender in the observed effects (all p > 0.60 for men vs. women comparisons). In the overall sample, correlations of fasting indices with clamp-derived index appeared to be significantly different for fasting insulin vs. QUICKI (p = 0.01) and glucose/insulin ratio (p = 0.03); HOMA-IR vs. QUICKI (p = 0.008) and glucose/insulin ratio (p = 0.02); QUICKI vs. FIRI (p = 0.008); and FIRI vs. glucose/insulin ratio (p = 0.02). The pattern was similar in men and women.</p><fig id="F1" position="float"><label>Figure 1</label><caption><p><bold>Correlation between clamp-derived insulin sensitivity index (M value), and fasting indices and clinical surrogates of insulin sensitivity overall and in men and women.</bold> Plots are based on the Box-Cox transformed values of insulin sensitivity of interest (x-axis) against the Box-Cox transformed M value (y-axis). Across figure panels, the filled circles are always for men and the point-up triangles for women. For each figure panel, the superimposed curves are the linear regression lines depicting the continuous association of indices of interest with M value overall (solid line) and for men (dotted lines) and women (broken lines). The accompanying correlation coefficient and 95% confidence intervals are also shown.</p></caption><graphic xlink:href="1472-6823-14-65-1"></graphic></fig><p>In the overall sample, correlation coefficients (95% confidence interval) clinical surrogates vs. clamp-derived index were −0.08 (−0.30 to 0.14) for age, −0.38 (−0.55 to −0.17) for BMI, −0.43 (−0.60 to −0.23) for waist circumference and −0.38 (−0.56 to −0.18) for WHtR. There was a trend toward stronger correlation in men than in women (Figure <xref ref-type="fig" rid="F1">1</xref> and Table <xref ref-type="table" rid="T2">2</xref>). The correlations of clamp with BMI, WC and WHtR were stronger than those with QUICKI, FIRI and glucose/insulin ratio (all p ≤ 0.0004), and not appreciably different to those with fasting insulin and HOMA-IR.</p><table-wrap position="float" id="T2"><label>Table 2</label><caption><p>Regression coefficients from multiple robust linear models for the prediction of clamp-derived index by fasting insulin sensitivity indices accounting for the potential effect of sex and adiposity</p></caption><table frame="hsides" rules="groups" border="1"><colgroup><col align="left"></col><col align="center"></col><col align="left"></col><col align="center"></col><col align="left"></col><col align="center"></col><col align="left"></col><col align="center"></col><col align="left"></col><col align="center"></col><col align="left"></col><col align="center"></col><col align="left"></col><col align="center"></col><col align="left"></col><col align="center"></col><col align="left"></col><col align="center"></col><col align="left"></col></colgroup><thead valign="top"><tr><th align="left" valign="bottom"> <hr></hr></th><th colspan="2" align="center" valign="bottom"><bold>BMI</bold><hr></hr></th><th colspan="2" align="center" valign="bottom"><bold>Waist</bold><hr></hr></th><th colspan="2" align="center" valign="bottom"><bold>WHtR</bold><hr></hr></th><th colspan="2" align="center" valign="bottom"><bold>BMI & WC</bold><hr></hr></th><th colspan="2" align="center" valign="bottom"><bold>Fasting insulin</bold><hr></hr></th><th colspan="2" align="center" valign="bottom"><bold>HOMA-IR</bold><hr></hr></th><th colspan="2" align="center" valign="bottom"><bold>QUICKI</bold><hr></hr></th><th colspan="2" align="center" valign="bottom"><bold>FIRI</bold><hr></hr></th><th colspan="2" align="center" valign="bottom"><bold>Glucose/insulin</bold><hr></hr></th></tr><tr><th align="left"> </th><th align="center"><bold>β</bold></th><th align="left"><bold>p</bold></th><th align="center"><bold>β</bold></th><th align="left"><bold>p</bold></th><th align="center"><bold>β</bold></th><th align="left"><bold>p</bold></th><th align="center"><bold>β</bold></th><th align="left"><bold>p</bold></th><th align="center"><bold>β</bold></th><th align="left"><bold>p</bold></th><th align="center"><bold>β</bold></th><th align="left"><bold>p</bold></th><th align="center"><bold>β</bold></th><th align="left"><bold>p</bold></th><th align="center"><bold>β</bold></th><th align="left"><bold>p</bold></th><th align="center"><bold>β</bold></th><th align="left"><bold>p</bold></th></tr></thead><tbody valign="top"><tr><td align="left" valign="bottom">Insuline sensitivity index<hr></hr></td><td align="center" valign="bottom">-<hr></hr></td><td align="left" valign="bottom">-<hr></hr></td><td align="center" valign="bottom">-<hr></hr></td><td align="left" valign="bottom">-<hr></hr></td><td align="center" valign="bottom">-<hr></hr></td><td align="left" valign="bottom">-<hr></hr></td><td align="center" valign="bottom">-<hr></hr></td><td align="left" valign="bottom">-<hr></hr></td><td align="center" valign="bottom">−1.472<hr></hr></td><td align="left" valign="bottom">0.01<hr></hr></td><td align="center" valign="bottom">−1.454<hr></hr></td><td align="left" valign="bottom">0.01<hr></hr></td><td align="center" valign="bottom">0.331<hr></hr></td><td align="left" valign="bottom">0.01<hr></hr></td><td align="center" valign="bottom">−1.454<hr></hr></td><td align="left" valign="bottom">0.01<hr></hr></td><td align="center" valign="bottom">1.761<hr></hr></td><td align="left" valign="bottom">0.03<hr></hr></td></tr><tr><td align="left" valign="bottom">Sex (female)<hr></hr></td><td align="center" valign="bottom">1.277<hr></hr></td><td align="left" valign="bottom">0.10<hr></hr></td><td align="center" valign="bottom">0.726<hr></hr></td><td align="left" valign="bottom">0.27<hr></hr></td><td align="center" valign="bottom">1.368<hr></hr></td><td align="left" valign="bottom">0.05<hr></hr></td><td align="center" valign="bottom">0.873<hr></hr></td><td align="left" valign="bottom">0.31<hr></hr></td><td align="center" valign="bottom">1.156<hr></hr></td><td align="left" valign="bottom">0.09<hr></hr></td><td align="center" valign="bottom">1.171<hr></hr></td><td align="left" valign="bottom">0.07<hr></hr></td><td align="center" valign="bottom">1.162<hr></hr></td><td align="left" valign="bottom">0.08<hr></hr></td><td align="center" valign="bottom">1.171<hr></hr></td><td align="left" valign="bottom">0.07<hr></hr></td><td align="center" valign="bottom">1.093<hr></hr></td><td align="left" valign="bottom">0.13<hr></hr></td></tr><tr><td align="left" valign="bottom">BMI<hr></hr></td><td align="center" valign="bottom">−200.3<hr></hr></td><td align="left" valign="bottom">0.0003<hr></hr></td><td align="center" valign="bottom">-<hr></hr></td><td align="left" valign="bottom">-<hr></hr></td><td align="center" valign="bottom">-<hr></hr></td><td align="left" valign="bottom">-<hr></hr></td><td align="center" valign="bottom">74.94<hr></hr></td><td align="left" valign="bottom">0.56<hr></hr></td><td align="center" valign="bottom">-<hr></hr></td><td align="left" valign="bottom">-<hr></hr></td><td align="center" valign="bottom">-<hr></hr></td><td align="left" valign="bottom">-<hr></hr></td><td align="center" valign="bottom">-<hr></hr></td><td align="left" valign="bottom">-<hr></hr></td><td align="center" valign="bottom">-<hr></hr></td><td align="left" valign="bottom">-<hr></hr></td><td align="center" valign="bottom">-<hr></hr></td><td align="left" valign="bottom">-<hr></hr></td></tr><tr><td align="left" valign="bottom">Waist<hr></hr></td><td align="center" valign="bottom">-<hr></hr></td><td align="left" valign="bottom">-<hr></hr></td><td align="center" valign="bottom">−8.964<hr></hr></td><td align="left" valign="bottom"><0.0001<hr></hr></td><td align="center" valign="bottom">-<hr></hr></td><td align="left" valign="bottom">-<hr></hr></td><td align="center" valign="bottom">6.130<hr></hr></td><td align="left" valign="bottom">0.30<hr></hr></td><td align="center" valign="bottom">−7.985<hr></hr></td><td align="left" valign="bottom">0.0002<hr></hr></td><td align="center" valign="bottom">−7.606<hr></hr></td><td align="left" valign="bottom">0.0004<hr></hr></td><td align="center" valign="bottom">−7.805<hr></hr></td><td align="left" valign="bottom">0.0002<hr></hr></td><td align="center" valign="bottom">−7.606<hr></hr></td><td align="left" valign="bottom">0.0004<hr></hr></td><td align="center" valign="bottom">−8.470<hr></hr></td><td align="left" valign="bottom">0.0002<hr></hr></td></tr><tr><td align="left" valign="bottom">WHtR<hr></hr></td><td align="center" valign="bottom"> <hr></hr></td><td align="left" valign="bottom"> <hr></hr></td><td align="center" valign="bottom"> <hr></hr></td><td align="left" valign="bottom"> <hr></hr></td><td align="center" valign="bottom">−8.1465<hr></hr></td><td align="left" valign="bottom">0.0002<hr></hr></td><td align="center" valign="bottom"> <hr></hr></td><td align="left" valign="bottom"> <hr></hr></td><td align="center" valign="bottom">-<hr></hr></td><td align="left" valign="bottom">-<hr></hr></td><td align="center" valign="bottom">-<hr></hr></td><td align="left" valign="bottom">-<hr></hr></td><td align="center" valign="bottom">-<hr></hr></td><td align="left" valign="bottom">-<hr></hr></td><td align="center" valign="bottom">-<hr></hr></td><td align="left" valign="bottom">-<hr></hr></td><td align="center" valign="bottom">-<hr></hr></td><td align="left" valign="bottom">-<hr></hr></td></tr><tr><td align="left">R<sup>2</sup></td><td colspan="2" align="center">0.179</td><td colspan="2" align="center">0.202</td><td colspan="2" align="center">0.177</td><td colspan="2" align="center">0.200</td><td colspan="2" align="center">0.261</td><td colspan="2" align="center">0.266</td><td colspan="2" align="center">0.263</td><td colspan="2" align="center">0.266</td><td colspan="2" align="center">0.248</td></tr></tbody></table><table-wrap-foot><p>BMI: body mass index; WHtR: waist-to-height ratio; β: standard regression coefficient; R<sup>2</sup>: coefficient of determination.</p></table-wrap-foot></table-wrap><p>The best fitting multivariable model containing sex and each of the clinical surrogates was achieved with waist circumference (R<sup>2</sup> = 0.202), in predicting clamp-derived index (Table <xref ref-type="table" rid="T2">2</xref>). Adding any of the other clinical surrogates did not improve the fit of the model. The effect of each of the fasting indices on clamp-derived value was only marginal in multivariable models (Table <xref ref-type="table" rid="T2">2</xref>). Altogether, each index, sex and waist circumference in the same model accounted for about 25 to 27% of the variability of clamp-derived measure of insulin sensitivity. Adding the interaction terms of indices with sex did not improve the fit of the models, while replacing WC with either BMI or WHtR resulted in less performing models. Across competing models (with each of the indices), WC was always the most significant and consistent determinant of clamp-derived index (Table <xref ref-type="table" rid="T2">2</xref>).</p></sec><sec><title>Classification agreement</title><p>The proportion of participants correctly ranked in cross-classification across thirds of clamp-derived and fasting insulin sensitivity indices and clinical surrogates is shown in Table <xref ref-type="table" rid="T3">3</xref>. This proportion ranged from 27% to 51% overall, 25% to 68% in men, and 25% to 47% in women based on fasting indices. Significant kappa statistic were observed in the overall sample and in men for QUICKI vs. Clamp [kappa 0.24 (95% CI: 0.09-0.42) and 0.27 (0.05-0.46)], and for glucose/insulin ratio vs. clamp [0.26 (0.09-0.42) and 0.30 (0.08-0.51)]; but not in women, or for other fasting indices (Table <xref ref-type="table" rid="T3">3</xref>). The best performing clinical surrogate was BMI [kappa 0.22 (0.05-0.38) in the overall sample and 0.36 (0.14-0.58) in men].</p><table-wrap position="float" id="T3"><label>Table 3</label><caption><p>Proportion of subjects correctly classified by each index using clamp-derived M thirds as reference insulin sensitivity categories</p></caption><table frame="hsides" rules="groups" border="1"><colgroup><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col><col align="center"></col></colgroup><thead valign="top"><tr><th align="center" valign="bottom"> <hr></hr></th><th colspan="5" align="center" valign="bottom"><bold>Men</bold><hr></hr></th><th colspan="5" align="center" valign="bottom"><bold>Women</bold><hr></hr></th><th colspan="5" align="center" valign="bottom"><bold>All subjects</bold><hr></hr></th></tr><tr><th align="center" valign="bottom"><bold>Insulin sensitivity category</bold><hr></hr></th><th align="center" valign="bottom"><bold> Low</bold><hr></hr></th><th align="center" valign="bottom"><bold> Medium</bold><hr></hr></th><th align="center" valign="bottom"><bold> High</bold><hr></hr></th><th align="center" valign="bottom"><bold> Total</bold><hr></hr></th><th align="center" valign="bottom"><bold> Kappa (95% CI)</bold><hr></hr></th><th align="center" valign="bottom"><bold> Low</bold><hr></hr></th><th align="center" valign="bottom"><bold> Medium</bold><hr></hr></th><th align="center" valign="bottom"><bold> High</bold><hr></hr></th><th align="center" valign="bottom"><bold> Total</bold><hr></hr></th><th align="center" valign="bottom"><bold> Kappa (95% CI)</bold><hr></hr></th><th align="center" valign="bottom"><bold> Low</bold><hr></hr></th><th align="center" valign="bottom"><bold> Medium</bold><hr></hr></th><th align="center" valign="bottom"><bold> High</bold><hr></hr></th><th align="center" valign="bottom"><bold> Total</bold><hr></hr></th><th align="center" valign="bottom"><bold> Kappa (95% CI)</bold><hr></hr></th></tr><tr><th align="center"><bold>Using clamp as reference</bold></th><th align="center"><bold>N = 15</bold></th><th align="center"><bold>N = 16</bold></th><th align="center"><bold>N = 16</bold></th><th align="center"><bold>N = 47</bold></th><th align="center"> </th><th align="center"><bold>N = 10</bold></th><th align="center"><bold>N = 11</bold></th><th align="center"><bold>N = 11</bold></th><th align="center"><bold>N = 32</bold></th><th align="center"> </th><th align="center"><bold>N = 25</bold></th><th align="center"><bold>N = 27</bold></th><th align="center"><bold>N = 27</bold></th><th align="center"><bold>N = 79</bold></th><th align="center"> </th></tr></thead><tbody valign="top"><tr><td align="center" valign="bottom">Fasting plasma insulin<hr></hr></td><td align="center" valign="bottom">20%<hr></hr></td><td align="center" valign="bottom">44%<hr></hr></td><td align="center" valign="bottom">25%<hr></hr></td><td align="center" valign="bottom">14/47<hr></hr></td><td align="center" valign="bottom">−0.05 (−0.25 to 0.14)<hr></hr></td><td align="center" valign="bottom">30%<hr></hr></td><td align="center" valign="bottom">36%<hr></hr></td><td align="center" valign="bottom">9%<hr></hr></td><td align="center" valign="bottom">8/32<hr></hr></td><td align="center" valign="bottom">−0.13 (−0.33 to 0.10)<hr></hr></td><td align="center" valign="bottom">24%<hr></hr></td><td align="center" valign="bottom">41%<hr></hr></td><td align="center" valign="bottom">18%<hr></hr></td><td align="center" valign="bottom">22/79<hr></hr></td><td align="center" valign="bottom">−0.08 (−0.22 to 0.08)<hr></hr></td></tr><tr><td align="center" valign="bottom">Glucose/Insulin ratio<hr></hr></td><td align="center" valign="bottom">53%<hr></hr></td><td align="center" valign="bottom">56%<hr></hr></td><td align="center" valign="bottom">50%<hr></hr></td><td align="center" valign="bottom">25/47<hr></hr></td><td align="center" valign="bottom">0.30 (0.08 to 0.51)<hr></hr></td><td align="center" valign="bottom">50%<hr></hr></td><td align="center" valign="bottom">45%<hr></hr></td><td align="center" valign="bottom">45%<hr></hr></td><td align="center" valign="bottom">15/32<hr></hr></td><td align="center" valign="bottom">0.20 (−0.08 to 0.47)<hr></hr></td><td align="center" valign="bottom">52%<hr></hr></td><td align="center" valign="bottom">52%<hr></hr></td><td align="center" valign="bottom">48%<hr></hr></td><td align="center" valign="bottom">40/79<hr></hr></td><td align="center" valign="bottom">0.26 (0.09 to 0.42)<hr></hr></td></tr><tr><td align="center" valign="bottom">HOMA-IR<hr></hr></td><td align="center" valign="bottom">20%<hr></hr></td><td align="center" valign="bottom">37%<hr></hr></td><td align="center" valign="bottom">19%<hr></hr></td><td align="center" valign="bottom">12/47<hr></hr></td><td align="center" valign="bottom">−0.12 (−0.30 to 0.06)<hr></hr></td><td align="center" valign="bottom">20%<hr></hr></td><td align="center" valign="bottom">45%<hr></hr></td><td align="center" valign="bottom">18%<hr></hr></td><td align="center" valign="bottom">9/32<hr></hr></td><td align="center" valign="bottom">−0.08 (−0.31 to 0.15)<hr></hr></td><td align="center" valign="bottom">20%<hr></hr></td><td align="center" valign="bottom">41%<hr></hr></td><td align="center" valign="bottom">18%<hr></hr></td><td align="center" valign="bottom">21/79<hr></hr></td><td align="center" valign="bottom">−0.10 (−0.24 to 0.04)<hr></hr></td></tr><tr><td align="center" valign="bottom">FIRI<hr></hr></td><td align="center" valign="bottom">20%<hr></hr></td><td align="center" valign="bottom">37%<hr></hr></td><td align="center" valign="bottom">19%<hr></hr></td><td align="center" valign="bottom">12/47<hr></hr></td><td align="center" valign="bottom">−0.12 (−0.30 to 0.08)<hr></hr></td><td align="center" valign="bottom">20%<hr></hr></td><td align="center" valign="bottom">45%<hr></hr></td><td align="center" valign="bottom">18%<hr></hr></td><td align="center" valign="bottom">9/32<hr></hr></td><td align="center" valign="bottom">−0.08 (−0.30 to 0.16)<hr></hr></td><td align="center" valign="bottom">20%<hr></hr></td><td align="center" valign="bottom">41%<hr></hr></td><td align="center" valign="bottom">18%<hr></hr></td><td align="center" valign="bottom">21/79<hr></hr></td><td align="center" valign="bottom">−0.10 (−0.24 to 0.04)<hr></hr></td></tr><tr><td align="center" valign="bottom">QUICKI<hr></hr></td><td align="center" valign="bottom">53%<hr></hr></td><td align="center" valign="bottom">50%<hr></hr></td><td align="center" valign="bottom">50%<hr></hr></td><td align="center" valign="bottom">24/47<hr></hr></td><td align="center" valign="bottom">0.27 (0.05 to 0.46)<hr></hr></td><td align="center" valign="bottom">50%<hr></hr></td><td align="center" valign="bottom">36%<hr></hr></td><td align="center" valign="bottom">54%<hr></hr></td><td align="center" valign="bottom">15/32<hr></hr></td><td align="center" valign="bottom">0.20 (−0.04 to 0.47)<hr></hr></td><td align="center" valign="bottom">52%<hr></hr></td><td align="center" valign="bottom">44%<hr></hr></td><td align="center" valign="bottom">52%<hr></hr></td><td align="center" valign="bottom">39/79<hr></hr></td><td align="center" valign="bottom">0.24 (0.09 to 0.42)<hr></hr></td></tr><tr><td align="center" valign="bottom">Age<hr></hr></td><td align="center" valign="bottom">27%<hr></hr></td><td align="center" valign="bottom">9%<hr></hr></td><td align="center" valign="bottom">56%<hr></hr></td><td align="center" valign="bottom">15/47<hr></hr></td><td align="center" valign="bottom">−0.02 (−0.22 to 0.18)<hr></hr></td><td align="center" valign="bottom">10%<hr></hr></td><td align="center" valign="bottom">45%<hr></hr></td><td align="center" valign="bottom">27%<hr></hr></td><td align="center" valign="bottom">9/32<hr></hr></td><td align="center" valign="bottom">−0.08 (−0.32 to 0.16)<hr></hr></td><td align="center" valign="bottom">20%<hr></hr></td><td align="center" valign="bottom">26%<hr></hr></td><td align="center" valign="bottom">44%<hr></hr></td><td align="center" valign="bottom">24/79<hr></hr></td><td align="center" valign="bottom">−0.04 (−0.19 to 0.11)<hr></hr></td></tr><tr><td align="center" valign="bottom">BMI<hr></hr></td><td align="center" valign="bottom">53%<hr></hr></td><td align="center" valign="bottom">56%<hr></hr></td><td align="center" valign="bottom">62%<hr></hr></td><td align="center" valign="bottom">27/47<hr></hr></td><td align="center" valign="bottom">0.36 (0.14 to 0.58)<hr></hr></td><td align="center" valign="bottom">50%<hr></hr></td><td align="center" valign="bottom">27%<hr></hr></td><td align="center" valign="bottom">27%<hr></hr></td><td align="center" valign="bottom">11/32<hr></hr></td><td align="center" valign="bottom">0.01 (−0.23 to 0.25)<hr></hr></td><td align="center" valign="bottom">52%<hr></hr></td><td align="center" valign="bottom">44%<hr></hr></td><td align="center" valign="bottom">48%<hr></hr></td><td align="center" valign="bottom">38/79<hr></hr></td><td align="center" valign="bottom">0.22 (0.05 to 0.38)<hr></hr></td></tr><tr><td align="center" valign="bottom">Waist<hr></hr></td><td align="center" valign="bottom">53%<hr></hr></td><td align="center" valign="bottom">31%<hr></hr></td><td align="center" valign="bottom">56%<hr></hr></td><td align="center" valign="bottom">21/47<hr></hr></td><td align="center" valign="bottom">0.20 (−0.02 to 0.40)<hr></hr></td><td align="center" valign="bottom">50%<hr></hr></td><td align="center" valign="bottom">27%<hr></hr></td><td align="center" valign="bottom">18%<hr></hr></td><td align="center" valign="bottom">10/32<hr></hr></td><td align="center" valign="bottom">−0.03 (−0.26 to 0.22)<hr></hr></td><td align="center" valign="bottom">52%<hr></hr></td><td align="center" valign="bottom">30%<hr></hr></td><td align="center" valign="bottom">41%<hr></hr></td><td align="center" valign="bottom">32/79<hr></hr></td><td align="center" valign="bottom">0.11 (−0.06 to 0.27)<hr></hr></td></tr><tr><td align="center">WHtR</td><td align="center">53%</td><td align="center">31%</td><td align="center">62%</td><td align="center">25/47</td><td align="center">0.23 (0.01 to 0.43)</td><td align="center">50%</td><td align="center">36%</td><td align="center">18%</td><td align="center">11/32</td><td align="center">0.01 (−0.22 to 0.25)</td><td align="center">52%</td><td align="center">33%</td><td align="center">44%</td><td align="center">34/79</td><td align="center">0.14 (−0.02 to 0.31)</td></tr></tbody></table><table-wrap-foot><p>HOMA-IR: Homeostasis Model Assessment for insulin resistance; FIRI: fasting insulin resistance index; QUICKI: quantitative insulin sensitivity check index;</p><p>BMI: body mass index; WHtR: waist-to-height ratio.</p></table-wrap-foot></table-wrap></sec></sec><sec sec-type="discussion"><title>Discussion</title><p>This study aimed to validate a wide-range of fasting indices of insulin sensitivity against hyperinsulinemic euglycemic clamp among non-diabetic sub-Saharan Africans. We found that, although fasting indices of insulin sensitivity were strongly correlated with each other, they only displayed weak associations with clamp-derived measure of insulin sensitive, and consistently among men and women. These associations were further attenuated after adjustment for clinical markers of adiposity, which appeared to be significant determinants of insulin sensitivity in this population. However, accounting for the effect of adiposity (via waist circumference), sex and fasting indices explained just about 25% of the variability of insulin sensitivity in our sample. Among participants ranked by thirds of fasting indices, less than half fall within the corresponding category based on thirds of clamp-derived measure. Similar results were obtained when using clinical surrogates of insulin sensitivity. Our results are of importance given the rapid ongoing changes in physical activity and nutritional behaviors, resulting in increasing insulin resistance and consequential escalating rates of diabetes and obesity in SSA. Addressing these challenges would require larger-scale studies of T2DM or obesity, in which the use of examined indices may prove beneficial.</p><p>The relatively low levels of correlations between indices and clamp measures may be the result of a higher basal insulin secretion in people of African ancestry [<xref ref-type="bibr" rid="B17">17</xref>], which may have clouded the relationship between these indices and clamp-derived measure. Although a direct comparison of our findings with what would be obtained in a Caucasian population is not possible, our results after adjusting for sex and adiposity are similar to those reported by Pisprasert et al. [<xref ref-type="bibr" rid="B7">7</xref>] who found similar coefficients of correlation between clamp-derived insulin sensitivity index and HOMA-IR (0.266 vs. 0.290) as well as QUICKI (0.263 vs. 0.265). In overweight African-American premenopausal women, Alvarez et al. [<xref ref-type="bibr" rid="B6">6</xref>] reported similar coefficients of correlation between insulin sensitivity index and Glucose/Insulin ratio while the coefficient was slightly higher for fasting insulin (0.261 vs. 0.308) and HOMA-IR (0.266 vs. 0.309), and lower for QUICKI (0.263 vs. 0.249). In all groups assessed in our study, fasting insulin had comparable correlations to those observed with the more complex indices of insulin resistance (HOMA-IR, QUICKI or FIRI) with clamp insulin sensitivity. Thus, HOMA-IR, QUICKI, and FIRI may not necessarily provide better estimation of insulin sensitivity than that obtained from fasting insulin alone in individuals of SSA origin.</p><p>Very few studies have examined surrogate indices against clamp-derived measures in population from SSA. Existing studies have mainly been from South Africa and were generally restricted to a limited number of indices, contrary to our investigation that comprehensively examined a wide range of indices. Ntyintyane et al. [<xref ref-type="bibr" rid="B18">18</xref>], reported significant correlations between clamp-derived insulin sensitivity and log HOMA-IR (r = −0.34) and QUICKI (r = 0.41) among Black South Africans; which in major ways were similar to those from our study. However, their study was based on a smaller and more heterogeneous group of participants including people with coronary heart disease and or diabetes mellitus [<xref ref-type="bibr" rid="B18">18</xref>]. Furthermore, they did not adjust clamp-derived M-values for lean body mass, and used lower insulin infusion rates (40 mU/m<sup>2</sup>/min), which may have resulted in incomplete suppression of hepatic glucose production (HGP) in participants with high BMI.</p><p>Our study has some limitations. Firstly, the study circumstances may not fully mimic real-life situation in the sense that participants were under controlled conditions before testing. Secondly, although we included more participants than any previous study from SSA, our sample size may still be small to uncover some significant associations. However, performing clamp studies in larger sample is logistically challenging in any setting. Thirdly, although we used a high-rate insulin infusion, in the absence of concomitant use of radiolabeled glucose tracer during the clamp studies, we are unable to confirm that we achieved total suppression of hepatic glucose production. Fourthly, we used two different methods (absorptiometry and bioimpedance) to measure fat body mass. This approach could possible induce differential measurement error, with possible, by likely marginal effect on the relationship of fasting indices and clamp-derived measures [<xref ref-type="bibr" rid="B19">19</xref>]. Lastly, we excluded heavy smokers (>20 cigarettes per day) from our sample. We made this choice because of uncertainties surrounding the association between smoking and insulin resistance from studies in Caucasians [<xref ref-type="bibr" rid="B20">20</xref>-<xref ref-type="bibr" rid="B22">22</xref>]. There have been suggestions that smoking 24 cigarettes per day increases energy expenditure by about 10% [<xref ref-type="bibr" rid="B23">23</xref>], which in turn could be associated with a lower body mass index, a key determinant of insulin resistance.</p><p>The strengths of our study relate primarily to our reliance on robust methods including: 1) the use of the reference method for estimating insulin sensitivity (hyperinsulinemic euglycemic clamp); the use of a systematic sequential- as opposed to a random approach to OGTT and the clamp studies; 3) the use of multiple and robust statistical approaches to assess the validity of surrogate indices. Furthermore, our cohort included a wide range of insulin sensitivity/BMI, as BMI is known to influence the relationship between surrogate indices and direct measurements of insulin sensitivity [<xref ref-type="bibr" rid="B24">24</xref>]. In the absence of established cut-off to diagnosed insulin resistance in this population, we purposefully refrained from assessing the predictive utility of indices based on arbitrary cut-offs derived from our sample.</p></sec><sec sec-type="conclusions"><title>Conclusions</title><p>In conclusion, fasting indices for insulin sensitivity are very modest determinants of clamp-derived measure of insulin sensitivity among non-diabetic sub-Saharan Africans. Furthermore, these indices appear not to perform better than common clinical measures of adiposity, nor to add significant predictive information to knowledge from non-invasive clinical measure in predicting insulin sensitivity. More research efforts are needed to identify in this setting to identify affordable fasting indicators which, singly or in combination may improve the accuracy of insulin sensitivity prediction. Predictive research in other settings has demonstrated the usefulness of routine clinical parameters in predicting the occurrence of diabetes mellitus or cardiovascular diseases, which are all long-term consequence of insulin resistance [<xref ref-type="bibr" rid="B25">25</xref>,<xref ref-type="bibr" rid="B26">26</xref>]. Adapting knowledge from those studies to the African setting will significantly improve the prevention and control of insulin resistance related status, without necessarily measuring insulin sensitivity, which at present appear to be unreliable using advocated fasting estimators.</p></sec><sec><title>Competing interests</title><p>The authors declare that they have no competing interests.</p></sec><sec><title>Authors’ contributions</title><p>ES, JFG and JCM: conceived the study and design study, data collection and analysis, and drafting of the manuscript. APK: analysis of data and drafting of the manuscript. JBE, SC, JST, EVB, MSP, VS, VE, EL, OTD, BAT: data interpretation, editing and reviewing the manuscript. ASM and PB: study design, data collection, editing and reviewing the manuscript. All authors read and approved the final manuscript.</p></sec><sec><title>Pre-publication history</title><p>The pre-publication history for this paper can be accessed here:</p><p><ext-link ext-link-type="uri" xlink:href="http://www.biomedcentral.com/1472-6823/14/65/prepub">http://www.biomedcentral.com/1472-6823/14/65/prepub</ext-link></p></sec></body><back><sec><title>Acknowledgments</title><p>This work was supported by Societe Francophone du Diabete, Paris France and by the North East Diabetes Trust, Newcastle upon Tyne, UK.</p><p>We acknowledge the contribution of all the participants to this study. 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|étape= Corpus
|type= RBID
|clé= PMC:4130121
|texte= Fasting insulin sensitivity indices are not better than routine clinical variables at predicting insulin sensitivity among Black Africans: a clamp study in sub-Saharan Africans
}}
Pour générer des pages wiki
HfdIndexSelect -h $EXPLOR_AREA/Data/Pmc/Corpus/RBID.i -Sk "pubmed:25106496" \
| HfdSelect -Kh $EXPLOR_AREA/Data/Pmc/Corpus/biblio.hfd \
| NlmPubMed2Wicri -a AustralieFrV1
| This area was generated with Dilib version V0.6.33. |  |