Clustering of cardiometabolic risk factors in Mexican pre-adolescents
To examine clustering of cardiometabolic markers in Mexican children at age 11 years and compare a metabolic syndrome (MetS) score to an exploratory cardiometabolic health (CMH) score. We used data from children enrolled in the POSGRAD birth cohort with cardiometabolic data available (n = 413). We u...
Gespeichert in:
Veröffentlicht in: | Diabetes research and clinical practice 2023-08, Vol.202, p.110818-110818, Article 110818 |
---|---|
Hauptverfasser: | , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 110818 |
---|---|
container_issue | |
container_start_page | 110818 |
container_title | Diabetes research and clinical practice |
container_volume | 202 |
creator | Wimalasena, Sonia Tandon Ramirez Silva, Claudia Ivonne Sun, Yan V. Stein, Aryeh D. Rivera, Juan A. Ramakrishnan, Usha |
description | To examine clustering of cardiometabolic markers in Mexican children at age 11 years and compare a metabolic syndrome (MetS) score to an exploratory cardiometabolic health (CMH) score.
We used data from children enrolled in the POSGRAD birth cohort with cardiometabolic data available (n = 413). We used principal component analysis (PCA) to derive a Metabolic Syndrome (MetS) score and an exploratory cardiometabolic health (CMH) score, which additionally included adipokines, lipids, inflammatory markers, and adiposity. We assessed reliability of individual cardiometabolic risk as defined by MetS and CMH by calculating % agreement and Cohen’s kappa statistic.
At least one cardiometabolic risk factor was present in 42 % of study participants; the most common risk factors were low High-Density Lipoprotein (HDL) cholesterol (31.9 %) and elevated triglycerides (18.2 %). Measures of adiposity and lipids explained the most variation in cardiometabolic measures for both MetS and CMH scores. Two-thirds of individuals were categorized in the same risk category by both MetS and CMH scores (κ = 0.42).
MetS and CMH scores capture a similar amount of variation. Additional follow-up studies comparing predictive abilities of MetS and CMH scores may enable improved identification of children at risk for cardiometabolic disease. |
doi_str_mv | 10.1016/j.diabres.2023.110818 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2835280483</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0168822723005818</els_id><sourcerecordid>2835280483</sourcerecordid><originalsourceid>FETCH-LOGICAL-c365t-a2b6541347a284e99127f352c2157a7d42db24c96142f91783abc634585dc6ae3</originalsourceid><addsrcrecordid>eNqFkLtOwzAUhi0EoqXwCKCMLAm-xXEmhKpykYpYYLYc-wS5JHGxEwRvT0oKK9M5w_efy4fQOcEZwURcbTLrdBUgZhRTlhGCJZEHaE5kQVNJaXGI5iMnf_oZOolxgzEWjOfHaMYKTikRYo5Wy2aIPQTXvSa-TowO1vkWel35xpkkuPiW1Nr0PsTEdckjfDqju2QbINXWNxANdH08RUe1biKc7esCvdyunpf36frp7mF5s04NE3mfalqJnBPGC00lh7IktKhZTg0leaELy6mtKDelIJzWJSkk05XZnSxza4QGtkCX09xt8O8DxF61brygaXQHfoiKynGaxFyyEc0n1AQfY4BabYNrdfhSBKudQbVRe4NqZ1BNBsfcxX7FULVg_1K_ykbgegJgfPTDQVDROOgMWBfA9Mp698-Kb9B2g1U</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2835280483</pqid></control><display><type>article</type><title>Clustering of cardiometabolic risk factors in Mexican pre-adolescents</title><source>Elsevier ScienceDirect Journals</source><creator>Wimalasena, Sonia Tandon ; Ramirez Silva, Claudia Ivonne ; Sun, Yan V. ; Stein, Aryeh D. ; Rivera, Juan A. ; Ramakrishnan, Usha</creator><creatorcontrib>Wimalasena, Sonia Tandon ; Ramirez Silva, Claudia Ivonne ; Sun, Yan V. ; Stein, Aryeh D. ; Rivera, Juan A. ; Ramakrishnan, Usha</creatorcontrib><description>To examine clustering of cardiometabolic markers in Mexican children at age 11 years and compare a metabolic syndrome (MetS) score to an exploratory cardiometabolic health (CMH) score.
We used data from children enrolled in the POSGRAD birth cohort with cardiometabolic data available (n = 413). We used principal component analysis (PCA) to derive a Metabolic Syndrome (MetS) score and an exploratory cardiometabolic health (CMH) score, which additionally included adipokines, lipids, inflammatory markers, and adiposity. We assessed reliability of individual cardiometabolic risk as defined by MetS and CMH by calculating % agreement and Cohen’s kappa statistic.
At least one cardiometabolic risk factor was present in 42 % of study participants; the most common risk factors were low High-Density Lipoprotein (HDL) cholesterol (31.9 %) and elevated triglycerides (18.2 %). Measures of adiposity and lipids explained the most variation in cardiometabolic measures for both MetS and CMH scores. Two-thirds of individuals were categorized in the same risk category by both MetS and CMH scores (κ = 0.42).
MetS and CMH scores capture a similar amount of variation. Additional follow-up studies comparing predictive abilities of MetS and CMH scores may enable improved identification of children at risk for cardiometabolic disease.</description><identifier>ISSN: 0168-8227</identifier><identifier>EISSN: 1872-8227</identifier><identifier>DOI: 10.1016/j.diabres.2023.110818</identifier><identifier>PMID: 37422166</identifier><language>eng</language><publisher>Ireland: Elsevier B.V</publisher><subject>Biomarkers ; Cardiometabolic risk ; Mexican population ; Pre-adolescence</subject><ispartof>Diabetes research and clinical practice, 2023-08, Vol.202, p.110818-110818, Article 110818</ispartof><rights>2023</rights><rights>Copyright © 2023. Published by Elsevier B.V.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c365t-a2b6541347a284e99127f352c2157a7d42db24c96142f91783abc634585dc6ae3</citedby><cites>FETCH-LOGICAL-c365t-a2b6541347a284e99127f352c2157a7d42db24c96142f91783abc634585dc6ae3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.diabres.2023.110818$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,777,781,3537,27905,27906,45976</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37422166$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Wimalasena, Sonia Tandon</creatorcontrib><creatorcontrib>Ramirez Silva, Claudia Ivonne</creatorcontrib><creatorcontrib>Sun, Yan V.</creatorcontrib><creatorcontrib>Stein, Aryeh D.</creatorcontrib><creatorcontrib>Rivera, Juan A.</creatorcontrib><creatorcontrib>Ramakrishnan, Usha</creatorcontrib><title>Clustering of cardiometabolic risk factors in Mexican pre-adolescents</title><title>Diabetes research and clinical practice</title><addtitle>Diabetes Res Clin Pract</addtitle><description>To examine clustering of cardiometabolic markers in Mexican children at age 11 years and compare a metabolic syndrome (MetS) score to an exploratory cardiometabolic health (CMH) score.
We used data from children enrolled in the POSGRAD birth cohort with cardiometabolic data available (n = 413). We used principal component analysis (PCA) to derive a Metabolic Syndrome (MetS) score and an exploratory cardiometabolic health (CMH) score, which additionally included adipokines, lipids, inflammatory markers, and adiposity. We assessed reliability of individual cardiometabolic risk as defined by MetS and CMH by calculating % agreement and Cohen’s kappa statistic.
At least one cardiometabolic risk factor was present in 42 % of study participants; the most common risk factors were low High-Density Lipoprotein (HDL) cholesterol (31.9 %) and elevated triglycerides (18.2 %). Measures of adiposity and lipids explained the most variation in cardiometabolic measures for both MetS and CMH scores. Two-thirds of individuals were categorized in the same risk category by both MetS and CMH scores (κ = 0.42).
MetS and CMH scores capture a similar amount of variation. Additional follow-up studies comparing predictive abilities of MetS and CMH scores may enable improved identification of children at risk for cardiometabolic disease.</description><subject>Biomarkers</subject><subject>Cardiometabolic risk</subject><subject>Mexican population</subject><subject>Pre-adolescence</subject><issn>0168-8227</issn><issn>1872-8227</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNqFkLtOwzAUhi0EoqXwCKCMLAm-xXEmhKpykYpYYLYc-wS5JHGxEwRvT0oKK9M5w_efy4fQOcEZwURcbTLrdBUgZhRTlhGCJZEHaE5kQVNJaXGI5iMnf_oZOolxgzEWjOfHaMYKTikRYo5Wy2aIPQTXvSa-TowO1vkWel35xpkkuPiW1Nr0PsTEdckjfDqju2QbINXWNxANdH08RUe1biKc7esCvdyunpf36frp7mF5s04NE3mfalqJnBPGC00lh7IktKhZTg0leaELy6mtKDelIJzWJSkk05XZnSxza4QGtkCX09xt8O8DxF61brygaXQHfoiKynGaxFyyEc0n1AQfY4BabYNrdfhSBKudQbVRe4NqZ1BNBsfcxX7FULVg_1K_ykbgegJgfPTDQVDROOgMWBfA9Mp698-Kb9B2g1U</recordid><startdate>20230801</startdate><enddate>20230801</enddate><creator>Wimalasena, Sonia Tandon</creator><creator>Ramirez Silva, Claudia Ivonne</creator><creator>Sun, Yan V.</creator><creator>Stein, Aryeh D.</creator><creator>Rivera, Juan A.</creator><creator>Ramakrishnan, Usha</creator><general>Elsevier B.V</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>20230801</creationdate><title>Clustering of cardiometabolic risk factors in Mexican pre-adolescents</title><author>Wimalasena, Sonia Tandon ; Ramirez Silva, Claudia Ivonne ; Sun, Yan V. ; Stein, Aryeh D. ; Rivera, Juan A. ; Ramakrishnan, Usha</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c365t-a2b6541347a284e99127f352c2157a7d42db24c96142f91783abc634585dc6ae3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Biomarkers</topic><topic>Cardiometabolic risk</topic><topic>Mexican population</topic><topic>Pre-adolescence</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wimalasena, Sonia Tandon</creatorcontrib><creatorcontrib>Ramirez Silva, Claudia Ivonne</creatorcontrib><creatorcontrib>Sun, Yan V.</creatorcontrib><creatorcontrib>Stein, Aryeh D.</creatorcontrib><creatorcontrib>Rivera, Juan A.</creatorcontrib><creatorcontrib>Ramakrishnan, Usha</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Diabetes research and clinical practice</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wimalasena, Sonia Tandon</au><au>Ramirez Silva, Claudia Ivonne</au><au>Sun, Yan V.</au><au>Stein, Aryeh D.</au><au>Rivera, Juan A.</au><au>Ramakrishnan, Usha</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Clustering of cardiometabolic risk factors in Mexican pre-adolescents</atitle><jtitle>Diabetes research and clinical practice</jtitle><addtitle>Diabetes Res Clin Pract</addtitle><date>2023-08-01</date><risdate>2023</risdate><volume>202</volume><spage>110818</spage><epage>110818</epage><pages>110818-110818</pages><artnum>110818</artnum><issn>0168-8227</issn><eissn>1872-8227</eissn><abstract>To examine clustering of cardiometabolic markers in Mexican children at age 11 years and compare a metabolic syndrome (MetS) score to an exploratory cardiometabolic health (CMH) score.
We used data from children enrolled in the POSGRAD birth cohort with cardiometabolic data available (n = 413). We used principal component analysis (PCA) to derive a Metabolic Syndrome (MetS) score and an exploratory cardiometabolic health (CMH) score, which additionally included adipokines, lipids, inflammatory markers, and adiposity. We assessed reliability of individual cardiometabolic risk as defined by MetS and CMH by calculating % agreement and Cohen’s kappa statistic.
At least one cardiometabolic risk factor was present in 42 % of study participants; the most common risk factors were low High-Density Lipoprotein (HDL) cholesterol (31.9 %) and elevated triglycerides (18.2 %). Measures of adiposity and lipids explained the most variation in cardiometabolic measures for both MetS and CMH scores. Two-thirds of individuals were categorized in the same risk category by both MetS and CMH scores (κ = 0.42).
MetS and CMH scores capture a similar amount of variation. Additional follow-up studies comparing predictive abilities of MetS and CMH scores may enable improved identification of children at risk for cardiometabolic disease.</abstract><cop>Ireland</cop><pub>Elsevier B.V</pub><pmid>37422166</pmid><doi>10.1016/j.diabres.2023.110818</doi><tpages>1</tpages></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0168-8227 |
ispartof | Diabetes research and clinical practice, 2023-08, Vol.202, p.110818-110818, Article 110818 |
issn | 0168-8227 1872-8227 |
language | eng |
recordid | cdi_proquest_miscellaneous_2835280483 |
source | Elsevier ScienceDirect Journals |
subjects | Biomarkers Cardiometabolic risk Mexican population Pre-adolescence |
title | Clustering of cardiometabolic risk factors in Mexican pre-adolescents |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-18T04%3A08%3A43IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Clustering%20of%20cardiometabolic%20risk%20factors%20in%20Mexican%20pre-adolescents&rft.jtitle=Diabetes%20research%20and%20clinical%20practice&rft.au=Wimalasena,%20Sonia%20Tandon&rft.date=2023-08-01&rft.volume=202&rft.spage=110818&rft.epage=110818&rft.pages=110818-110818&rft.artnum=110818&rft.issn=0168-8227&rft.eissn=1872-8227&rft_id=info:doi/10.1016/j.diabres.2023.110818&rft_dat=%3Cproquest_cross%3E2835280483%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2835280483&rft_id=info:pmid/37422166&rft_els_id=S0168822723005818&rfr_iscdi=true |