Obesity- and Lipid-Related Parameters in the Identification of Older Adults with a High Risk of Prediabetes According to the American Diabetes Association: An Analysis of the 2015 Health, Well-Being, and Aging Study
This study evaluated the predictive ability of 11 obesity- and lipid-related parameters, including body mass index (BMI), waist circumference (WC), waist-to-height ratio (WtHR), body roundness index (BRI), "A" body-shape index (ABSI), conicity index (CI), visceral adiposity index (VAI), tr...
Gespeichert in:
| Veröffentlicht in: | Nutrients 2019-11, Vol.11 (11), p.2654 |
|---|---|
| Hauptverfasser: | , , , , , , , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | |
|---|---|
| container_issue | 11 |
| container_start_page | 2654 |
| container_title | Nutrients |
| container_volume | 11 |
| creator | Ramírez-Vélez, Robinson Pérez-Sousa, Miguel Ángel González-Ruíz, Katherine Cano-Gutierrez, Carlos A Schmidt-RioValle, Jacqueline Correa-Rodríguez, María Izquierdo, Mikel Romero-García, Jesús Astolfo Campos-Rodríguez, Adriana Yolanda Triana-Reina, Héctor Reynaldo González-Jiménez, Emilio |
| description | This study evaluated the predictive ability of 11 obesity- and lipid-related parameters, including body mass index (BMI), waist circumference (WC), waist-to-height ratio (WtHR), body roundness index (BRI), "A" body-shape index (ABSI), conicity index (CI), visceral adiposity index (VAI), triglyceride-to-glucose fasting index (TyG), triglyceride-to-glucose fasting related to BMI (TyG-BMI), triglyceride-to-glucose fasting related to WC (TyG-WC), and triglyceride-to-glucose fasting related to WtHR (TyG-WtHR), to identify patients from an elderly Colombian population with a high risk of prediabetes according to the 2016 American Diabetes Association criteria. The data were obtained from the 2015 Colombian Health and Wellbeing and Aging Survey. A total of 3307 elderly Colombian individuals (aged over 60 years) were included. Anthropometric data, fasting plasma glucose, blood lipid profiles, family history, and health-related behaviors were assessed, and prediabetes was defined as a fasting plasma glucose of 100 to 125 mg/dL. The areas under the receiver operating characteristic (ROC) curves (AUCs) were calculated for each anthropometric indicator, using the prediabetes classification to identify their sensitivity and specificity, and these indicated that the prevalence of prediabetes was 25.3% in this population. After adjusting for potential confounding factors, the TyG index was strongly associated with the odds of having prediabetes in both sexes, and multivariate logistic regression analysis showed that the ORs for prediabetes increased across quartiles (
< 0.001). The TyG index was best able to identify prediabetes in either sex (AUC and optimal cut-off = 0.700 and 8.72, and 0.695 and 8.92 for men and women, respectively), suggesting that compared to the other parameters, the TyG index has the best discriminative power to predict prediabetes in the whole population. Thus, we propose the TyG index be used as a complementary marker for assessing prediabetes in older adults. |
| doi_str_mv | 10.3390/nu11112654 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_6893527</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2400479317</sourcerecordid><originalsourceid>FETCH-LOGICAL-c439t-6dffc58785c22a9762f45d3a0feb88bfcc381098b3571bd51b95f1757e1df7893</originalsourceid><addsrcrecordid>eNqNkltrFDEUgAdRbKl98QdIwBeRjuYymUx8EMZ62cLClqr4OGRy2UmdTdYko-wv9e-Y2da1-uQhkEC-fJxzcoriMYIvCOHwpZtQDlzT6l5xjCHDZV1X5P6d81FxGuM1nINBVpOHxRFBdcM5Y8fFz1Wvo027EginwNJurSqv9CiSVuBSBLHRSYcIrANp0OBCaZessVIk6x3wBqxGpQNo1TSmCH7YNAABFnY9gCsbv87AZdDKij5rImil9EFZtwbJ733tRocsc-DtAYnRS7vXvwKty0uMu2jjrJpfYIgoWGgxpuEMfNHjWL7RWXi2T79dz-6PaVK7R8UDI8aoT2_3k-Lz-3efzhflcvXh4rxdlrIiPJW1MkbShjVUYiw4q7GpqCICGt03TW-kJA2CvOkJZahXFPWcGsQo00gZ1nByUry-8W6nfqOVzP0JYuy2wW5E2HVe2O7vG2eHbu2_d_kDCMUsC57dCoL_NumYuo2NMhcmnPZT7HAFYcU4Qf-BEoQpRRWrMvr0H_TaTyH3ck_RquE1nYXPbygZfIxBm0PeCHbzdHV_pivDT-5WekB_zxL5BZAZywc</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2315489657</pqid></control><display><type>article</type><title>Obesity- and Lipid-Related Parameters in the Identification of Older Adults with a High Risk of Prediabetes According to the American Diabetes Association: An Analysis of the 2015 Health, Well-Being, and Aging Study</title><source>MDPI - Multidisciplinary Digital Publishing Institute</source><source>MEDLINE</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>PubMed Central</source><source>PubMed Central Open Access</source><creator>Ramírez-Vélez, Robinson ; Pérez-Sousa, Miguel Ángel ; González-Ruíz, Katherine ; Cano-Gutierrez, Carlos A ; Schmidt-RioValle, Jacqueline ; Correa-Rodríguez, María ; Izquierdo, Mikel ; Romero-García, Jesús Astolfo ; Campos-Rodríguez, Adriana Yolanda ; Triana-Reina, Héctor Reynaldo ; González-Jiménez, Emilio</creator><creatorcontrib>Ramírez-Vélez, Robinson ; Pérez-Sousa, Miguel Ángel ; González-Ruíz, Katherine ; Cano-Gutierrez, Carlos A ; Schmidt-RioValle, Jacqueline ; Correa-Rodríguez, María ; Izquierdo, Mikel ; Romero-García, Jesús Astolfo ; Campos-Rodríguez, Adriana Yolanda ; Triana-Reina, Héctor Reynaldo ; González-Jiménez, Emilio</creatorcontrib><description>This study evaluated the predictive ability of 11 obesity- and lipid-related parameters, including body mass index (BMI), waist circumference (WC), waist-to-height ratio (WtHR), body roundness index (BRI), "A" body-shape index (ABSI), conicity index (CI), visceral adiposity index (VAI), triglyceride-to-glucose fasting index (TyG), triglyceride-to-glucose fasting related to BMI (TyG-BMI), triglyceride-to-glucose fasting related to WC (TyG-WC), and triglyceride-to-glucose fasting related to WtHR (TyG-WtHR), to identify patients from an elderly Colombian population with a high risk of prediabetes according to the 2016 American Diabetes Association criteria. The data were obtained from the 2015 Colombian Health and Wellbeing and Aging Survey. A total of 3307 elderly Colombian individuals (aged over 60 years) were included. Anthropometric data, fasting plasma glucose, blood lipid profiles, family history, and health-related behaviors were assessed, and prediabetes was defined as a fasting plasma glucose of 100 to 125 mg/dL. The areas under the receiver operating characteristic (ROC) curves (AUCs) were calculated for each anthropometric indicator, using the prediabetes classification to identify their sensitivity and specificity, and these indicated that the prevalence of prediabetes was 25.3% in this population. After adjusting for potential confounding factors, the TyG index was strongly associated with the odds of having prediabetes in both sexes, and multivariate logistic regression analysis showed that the ORs for prediabetes increased across quartiles (
< 0.001). The TyG index was best able to identify prediabetes in either sex (AUC and optimal cut-off = 0.700 and 8.72, and 0.695 and 8.92 for men and women, respectively), suggesting that compared to the other parameters, the TyG index has the best discriminative power to predict prediabetes in the whole population. Thus, we propose the TyG index be used as a complementary marker for assessing prediabetes in older adults.</description><identifier>ISSN: 2072-6643</identifier><identifier>EISSN: 2072-6643</identifier><identifier>DOI: 10.3390/nu11112654</identifier><identifier>PMID: 31689977</identifier><language>eng</language><publisher>Switzerland: MDPI AG</publisher><subject>adiposity ; adults at risk ; Aged ; Aging ; blood glucose ; blood lipids ; blood plasma ; body mass index ; Body measurements ; Cardiovascular disease ; Diabetes mellitus ; Diabetes Mellitus - prevention & control ; Diagnostic systems ; elderly ; fasting ; Female ; Glucose ; health behavior ; Humans ; Hyperglycemia ; Insulin ; Insulin resistance ; lipid composition ; Lipid Metabolism ; Lipids ; Lipids - blood ; Male ; men ; Metabolic disorders ; Metabolic syndrome ; Middle Aged ; Minority & ethnic groups ; Obesity ; Older people ; Parameter estimation ; patients ; Prediabetic State - diagnosis ; regression analysis ; Risk Factors ; surveys ; waist circumference ; waist-to-height ratio ; women</subject><ispartof>Nutrients, 2019-11, Vol.11 (11), p.2654</ispartof><rights>2019. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2019 by the authors. 2019</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c439t-6dffc58785c22a9762f45d3a0feb88bfcc381098b3571bd51b95f1757e1df7893</citedby><cites>FETCH-LOGICAL-c439t-6dffc58785c22a9762f45d3a0feb88bfcc381098b3571bd51b95f1757e1df7893</cites><orcidid>0000-0003-2775-0058 ; 0000-0002-1506-4272 ; 0000-0002-6334-7082 ; 0000-0003-3075-6960 ; 0000-0001-9165-4349 ; 0000-0001-5680-7880 ; 0000-0003-4392-6850 ; 0000-0001-5103-6028</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6893527/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6893527/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,27901,27902,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31689977$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Ramírez-Vélez, Robinson</creatorcontrib><creatorcontrib>Pérez-Sousa, Miguel Ángel</creatorcontrib><creatorcontrib>González-Ruíz, Katherine</creatorcontrib><creatorcontrib>Cano-Gutierrez, Carlos A</creatorcontrib><creatorcontrib>Schmidt-RioValle, Jacqueline</creatorcontrib><creatorcontrib>Correa-Rodríguez, María</creatorcontrib><creatorcontrib>Izquierdo, Mikel</creatorcontrib><creatorcontrib>Romero-García, Jesús Astolfo</creatorcontrib><creatorcontrib>Campos-Rodríguez, Adriana Yolanda</creatorcontrib><creatorcontrib>Triana-Reina, Héctor Reynaldo</creatorcontrib><creatorcontrib>González-Jiménez, Emilio</creatorcontrib><title>Obesity- and Lipid-Related Parameters in the Identification of Older Adults with a High Risk of Prediabetes According to the American Diabetes Association: An Analysis of the 2015 Health, Well-Being, and Aging Study</title><title>Nutrients</title><addtitle>Nutrients</addtitle><description>This study evaluated the predictive ability of 11 obesity- and lipid-related parameters, including body mass index (BMI), waist circumference (WC), waist-to-height ratio (WtHR), body roundness index (BRI), "A" body-shape index (ABSI), conicity index (CI), visceral adiposity index (VAI), triglyceride-to-glucose fasting index (TyG), triglyceride-to-glucose fasting related to BMI (TyG-BMI), triglyceride-to-glucose fasting related to WC (TyG-WC), and triglyceride-to-glucose fasting related to WtHR (TyG-WtHR), to identify patients from an elderly Colombian population with a high risk of prediabetes according to the 2016 American Diabetes Association criteria. The data were obtained from the 2015 Colombian Health and Wellbeing and Aging Survey. A total of 3307 elderly Colombian individuals (aged over 60 years) were included. Anthropometric data, fasting plasma glucose, blood lipid profiles, family history, and health-related behaviors were assessed, and prediabetes was defined as a fasting plasma glucose of 100 to 125 mg/dL. The areas under the receiver operating characteristic (ROC) curves (AUCs) were calculated for each anthropometric indicator, using the prediabetes classification to identify their sensitivity and specificity, and these indicated that the prevalence of prediabetes was 25.3% in this population. After adjusting for potential confounding factors, the TyG index was strongly associated with the odds of having prediabetes in both sexes, and multivariate logistic regression analysis showed that the ORs for prediabetes increased across quartiles (
< 0.001). The TyG index was best able to identify prediabetes in either sex (AUC and optimal cut-off = 0.700 and 8.72, and 0.695 and 8.92 for men and women, respectively), suggesting that compared to the other parameters, the TyG index has the best discriminative power to predict prediabetes in the whole population. Thus, we propose the TyG index be used as a complementary marker for assessing prediabetes in older adults.</description><subject>adiposity</subject><subject>adults at risk</subject><subject>Aged</subject><subject>Aging</subject><subject>blood glucose</subject><subject>blood lipids</subject><subject>blood plasma</subject><subject>body mass index</subject><subject>Body measurements</subject><subject>Cardiovascular disease</subject><subject>Diabetes mellitus</subject><subject>Diabetes Mellitus - prevention & control</subject><subject>Diagnostic systems</subject><subject>elderly</subject><subject>fasting</subject><subject>Female</subject><subject>Glucose</subject><subject>health behavior</subject><subject>Humans</subject><subject>Hyperglycemia</subject><subject>Insulin</subject><subject>Insulin resistance</subject><subject>lipid composition</subject><subject>Lipid Metabolism</subject><subject>Lipids</subject><subject>Lipids - blood</subject><subject>Male</subject><subject>men</subject><subject>Metabolic disorders</subject><subject>Metabolic syndrome</subject><subject>Middle Aged</subject><subject>Minority & ethnic groups</subject><subject>Obesity</subject><subject>Older people</subject><subject>Parameter estimation</subject><subject>patients</subject><subject>Prediabetic State - diagnosis</subject><subject>regression analysis</subject><subject>Risk Factors</subject><subject>surveys</subject><subject>waist circumference</subject><subject>waist-to-height ratio</subject><subject>women</subject><issn>2072-6643</issn><issn>2072-6643</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><recordid>eNqNkltrFDEUgAdRbKl98QdIwBeRjuYymUx8EMZ62cLClqr4OGRy2UmdTdYko-wv9e-Y2da1-uQhkEC-fJxzcoriMYIvCOHwpZtQDlzT6l5xjCHDZV1X5P6d81FxGuM1nINBVpOHxRFBdcM5Y8fFz1Wvo027EginwNJurSqv9CiSVuBSBLHRSYcIrANp0OBCaZessVIk6x3wBqxGpQNo1TSmCH7YNAABFnY9gCsbv87AZdDKij5rImil9EFZtwbJ733tRocsc-DtAYnRS7vXvwKty0uMu2jjrJpfYIgoWGgxpuEMfNHjWL7RWXi2T79dz-6PaVK7R8UDI8aoT2_3k-Lz-3efzhflcvXh4rxdlrIiPJW1MkbShjVUYiw4q7GpqCICGt03TW-kJA2CvOkJZahXFPWcGsQo00gZ1nByUry-8W6nfqOVzP0JYuy2wW5E2HVe2O7vG2eHbu2_d_kDCMUsC57dCoL_NumYuo2NMhcmnPZT7HAFYcU4Qf-BEoQpRRWrMvr0H_TaTyH3ck_RquE1nYXPbygZfIxBm0PeCHbzdHV_pivDT-5WekB_zxL5BZAZywc</recordid><startdate>20191104</startdate><enddate>20191104</enddate><creator>Ramírez-Vélez, Robinson</creator><creator>Pérez-Sousa, Miguel Ángel</creator><creator>González-Ruíz, Katherine</creator><creator>Cano-Gutierrez, Carlos A</creator><creator>Schmidt-RioValle, Jacqueline</creator><creator>Correa-Rodríguez, María</creator><creator>Izquierdo, Mikel</creator><creator>Romero-García, Jesús Astolfo</creator><creator>Campos-Rodríguez, Adriana Yolanda</creator><creator>Triana-Reina, Héctor Reynaldo</creator><creator>González-Jiménez, Emilio</creator><general>MDPI AG</general><general>MDPI</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7TS</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>7S9</scope><scope>L.6</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0003-2775-0058</orcidid><orcidid>https://orcid.org/0000-0002-1506-4272</orcidid><orcidid>https://orcid.org/0000-0002-6334-7082</orcidid><orcidid>https://orcid.org/0000-0003-3075-6960</orcidid><orcidid>https://orcid.org/0000-0001-9165-4349</orcidid><orcidid>https://orcid.org/0000-0001-5680-7880</orcidid><orcidid>https://orcid.org/0000-0003-4392-6850</orcidid><orcidid>https://orcid.org/0000-0001-5103-6028</orcidid></search><sort><creationdate>20191104</creationdate><title>Obesity- and Lipid-Related Parameters in the Identification of Older Adults with a High Risk of Prediabetes According to the American Diabetes Association: An Analysis of the 2015 Health, Well-Being, and Aging Study</title><author>Ramírez-Vélez, Robinson ; Pérez-Sousa, Miguel Ángel ; González-Ruíz, Katherine ; Cano-Gutierrez, Carlos A ; Schmidt-RioValle, Jacqueline ; Correa-Rodríguez, María ; Izquierdo, Mikel ; Romero-García, Jesús Astolfo ; Campos-Rodríguez, Adriana Yolanda ; Triana-Reina, Héctor Reynaldo ; González-Jiménez, Emilio</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c439t-6dffc58785c22a9762f45d3a0feb88bfcc381098b3571bd51b95f1757e1df7893</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>adiposity</topic><topic>adults at risk</topic><topic>Aged</topic><topic>Aging</topic><topic>blood glucose</topic><topic>blood lipids</topic><topic>blood plasma</topic><topic>body mass index</topic><topic>Body measurements</topic><topic>Cardiovascular disease</topic><topic>Diabetes mellitus</topic><topic>Diabetes Mellitus - prevention & control</topic><topic>Diagnostic systems</topic><topic>elderly</topic><topic>fasting</topic><topic>Female</topic><topic>Glucose</topic><topic>health behavior</topic><topic>Humans</topic><topic>Hyperglycemia</topic><topic>Insulin</topic><topic>Insulin resistance</topic><topic>lipid composition</topic><topic>Lipid Metabolism</topic><topic>Lipids</topic><topic>Lipids - blood</topic><topic>Male</topic><topic>men</topic><topic>Metabolic disorders</topic><topic>Metabolic syndrome</topic><topic>Middle Aged</topic><topic>Minority & ethnic groups</topic><topic>Obesity</topic><topic>Older people</topic><topic>Parameter estimation</topic><topic>patients</topic><topic>Prediabetic State - diagnosis</topic><topic>regression analysis</topic><topic>Risk Factors</topic><topic>surveys</topic><topic>waist circumference</topic><topic>waist-to-height ratio</topic><topic>women</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ramírez-Vélez, Robinson</creatorcontrib><creatorcontrib>Pérez-Sousa, Miguel Ángel</creatorcontrib><creatorcontrib>González-Ruíz, Katherine</creatorcontrib><creatorcontrib>Cano-Gutierrez, Carlos A</creatorcontrib><creatorcontrib>Schmidt-RioValle, Jacqueline</creatorcontrib><creatorcontrib>Correa-Rodríguez, María</creatorcontrib><creatorcontrib>Izquierdo, Mikel</creatorcontrib><creatorcontrib>Romero-García, Jesús Astolfo</creatorcontrib><creatorcontrib>Campos-Rodríguez, Adriana Yolanda</creatorcontrib><creatorcontrib>Triana-Reina, Héctor Reynaldo</creatorcontrib><creatorcontrib>González-Jiménez, Emilio</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Physical Education Index</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><collection>AGRICOLA</collection><collection>AGRICOLA - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Nutrients</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ramírez-Vélez, Robinson</au><au>Pérez-Sousa, Miguel Ángel</au><au>González-Ruíz, Katherine</au><au>Cano-Gutierrez, Carlos A</au><au>Schmidt-RioValle, Jacqueline</au><au>Correa-Rodríguez, María</au><au>Izquierdo, Mikel</au><au>Romero-García, Jesús Astolfo</au><au>Campos-Rodríguez, Adriana Yolanda</au><au>Triana-Reina, Héctor Reynaldo</au><au>González-Jiménez, Emilio</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Obesity- and Lipid-Related Parameters in the Identification of Older Adults with a High Risk of Prediabetes According to the American Diabetes Association: An Analysis of the 2015 Health, Well-Being, and Aging Study</atitle><jtitle>Nutrients</jtitle><addtitle>Nutrients</addtitle><date>2019-11-04</date><risdate>2019</risdate><volume>11</volume><issue>11</issue><spage>2654</spage><pages>2654-</pages><issn>2072-6643</issn><eissn>2072-6643</eissn><abstract>This study evaluated the predictive ability of 11 obesity- and lipid-related parameters, including body mass index (BMI), waist circumference (WC), waist-to-height ratio (WtHR), body roundness index (BRI), "A" body-shape index (ABSI), conicity index (CI), visceral adiposity index (VAI), triglyceride-to-glucose fasting index (TyG), triglyceride-to-glucose fasting related to BMI (TyG-BMI), triglyceride-to-glucose fasting related to WC (TyG-WC), and triglyceride-to-glucose fasting related to WtHR (TyG-WtHR), to identify patients from an elderly Colombian population with a high risk of prediabetes according to the 2016 American Diabetes Association criteria. The data were obtained from the 2015 Colombian Health and Wellbeing and Aging Survey. A total of 3307 elderly Colombian individuals (aged over 60 years) were included. Anthropometric data, fasting plasma glucose, blood lipid profiles, family history, and health-related behaviors were assessed, and prediabetes was defined as a fasting plasma glucose of 100 to 125 mg/dL. The areas under the receiver operating characteristic (ROC) curves (AUCs) were calculated for each anthropometric indicator, using the prediabetes classification to identify their sensitivity and specificity, and these indicated that the prevalence of prediabetes was 25.3% in this population. After adjusting for potential confounding factors, the TyG index was strongly associated with the odds of having prediabetes in both sexes, and multivariate logistic regression analysis showed that the ORs for prediabetes increased across quartiles (
< 0.001). The TyG index was best able to identify prediabetes in either sex (AUC and optimal cut-off = 0.700 and 8.72, and 0.695 and 8.92 for men and women, respectively), suggesting that compared to the other parameters, the TyG index has the best discriminative power to predict prediabetes in the whole population. Thus, we propose the TyG index be used as a complementary marker for assessing prediabetes in older adults.</abstract><cop>Switzerland</cop><pub>MDPI AG</pub><pmid>31689977</pmid><doi>10.3390/nu11112654</doi><orcidid>https://orcid.org/0000-0003-2775-0058</orcidid><orcidid>https://orcid.org/0000-0002-1506-4272</orcidid><orcidid>https://orcid.org/0000-0002-6334-7082</orcidid><orcidid>https://orcid.org/0000-0003-3075-6960</orcidid><orcidid>https://orcid.org/0000-0001-9165-4349</orcidid><orcidid>https://orcid.org/0000-0001-5680-7880</orcidid><orcidid>https://orcid.org/0000-0003-4392-6850</orcidid><orcidid>https://orcid.org/0000-0001-5103-6028</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 2072-6643 |
| ispartof | Nutrients, 2019-11, Vol.11 (11), p.2654 |
| issn | 2072-6643 2072-6643 |
| language | eng |
| recordid | cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_6893527 |
| source | MDPI - Multidisciplinary Digital Publishing Institute; MEDLINE; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central; PubMed Central Open Access |
| subjects | adiposity adults at risk Aged Aging blood glucose blood lipids blood plasma body mass index Body measurements Cardiovascular disease Diabetes mellitus Diabetes Mellitus - prevention & control Diagnostic systems elderly fasting Female Glucose health behavior Humans Hyperglycemia Insulin Insulin resistance lipid composition Lipid Metabolism Lipids Lipids - blood Male men Metabolic disorders Metabolic syndrome Middle Aged Minority & ethnic groups Obesity Older people Parameter estimation patients Prediabetic State - diagnosis regression analysis Risk Factors surveys waist circumference waist-to-height ratio women |
| title | Obesity- and Lipid-Related Parameters in the Identification of Older Adults with a High Risk of Prediabetes According to the American Diabetes Association: An Analysis of the 2015 Health, Well-Being, and Aging Study |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-02T13%3A51%3A40IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Obesity-%20and%20Lipid-Related%20Parameters%20in%20the%20Identification%20of%20Older%20Adults%20with%20a%20High%20Risk%20of%20Prediabetes%20According%20to%20the%20American%20Diabetes%20Association:%20An%20Analysis%20of%20the%202015%20Health,%20Well-Being,%20and%20Aging%20Study&rft.jtitle=Nutrients&rft.au=Ram%C3%ADrez-V%C3%A9lez,%20Robinson&rft.date=2019-11-04&rft.volume=11&rft.issue=11&rft.spage=2654&rft.pages=2654-&rft.issn=2072-6643&rft.eissn=2072-6643&rft_id=info:doi/10.3390/nu11112654&rft_dat=%3Cproquest_pubme%3E2400479317%3C/proquest_pubme%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2315489657&rft_id=info:pmid/31689977&rfr_iscdi=true |