Longitudinal and age trends of metabolic syndrome and its risk factors: The Family Heart Study View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2006-12

AUTHORS

Aldi T Kraja, Ingrid B Borecki, Kari North, Weihong Tang, Richard H Myers, Paul N Hopkins, Donna Arnett, Jonathan Corbett, Avril Adelman, Michael A Province

ABSTRACT

BACKGROUND: We report longitudinal changes in the metabolic syndrome (MetS) in 2,458 participants from 480 families in the Family Heart Study. Participants were examined between 1994-96 (FHS-T1) and 2002-03 (FHS-T2), about 7.4 years apart. Additionally, the impact of medication on estimates of MetS prevalence, and associations of MetS with prevalent coronary heart disease (CHD) and type 2 diabetes (T2D) were studied. METHODS: Three definitions for MetS prevalence were considered. One represented the original (o) National Cholesterol Education Program (NCEP) MetS criteria. Two others considered the confounding of medications effects, respectively (m) lipid medications constituted a categorical diagnostic criterion for lipids variables, and (c) lipids and blood pressure variables were corrected with average clinical trials medications effects. Logistic regression of MetS on CHD and T2D, as well as the trend analysis of MetS by age, were performed. RESULTS: MetS increased from 17.1% in FHS-T1(o) to 28.8% in FHS-T2(o); from 19.7% in FHS-T1(m) to 42.5% in FHS-T2(m); and from 18.4% in FHS-T1(c) to 33.6% in FHS-T2(c). While we observed adverse changes in all risk factors, the greatest increase was for waist circumference (25%). The percentages of MetS were about 2 to almost 3 times higher in ages 50 years and older than in younger ages. The odds of having prevalent CHD were about 2.5 times higher in the subjects classified with MetS than without. CONCLUSION: MetS percentages increased noticeably longitudinally and cross-sectionally with older age. These conclusions were reached with and without considering medication use, but correcting risk factors for medications use affects the MetS prevalence estimates. As found in other studies, MetS was associated with increased odds for prevalent CHD. More... »

PAGES

41

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/1743-7075-3-41

DOI

http://dx.doi.org/10.1186/1743-7075-3-41

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1014105373

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/17147796


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1103", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Clinical Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/11", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Medical and Health Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Washington University in St. Louis", 
          "id": "https://www.grid.ac/institutes/grid.4367.6", 
          "name": [
            "From the Division of Statistical Genomics, Washington University School of Medicine, Saint Louis, MO, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kraja", 
        "givenName": "Aldi T", 
        "id": "sg:person.01260600634.53", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01260600634.53"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Washington University in St. Louis", 
          "id": "https://www.grid.ac/institutes/grid.4367.6", 
          "name": [
            "From the Division of Statistical Genomics, Washington University School of Medicine, Saint Louis, MO, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Borecki", 
        "givenName": "Ingrid B", 
        "id": "sg:person.01117564210.02", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01117564210.02"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of North Carolina System", 
          "id": "https://www.grid.ac/institutes/grid.410711.2", 
          "name": [
            "Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "North", 
        "givenName": "Kari", 
        "id": "sg:person.011405001662.87", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011405001662.87"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Minnesota", 
          "id": "https://www.grid.ac/institutes/grid.17635.36", 
          "name": [
            "Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Tang", 
        "givenName": "Weihong", 
        "id": "sg:person.014304652012.83", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014304652012.83"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Boston Medical Center", 
          "id": "https://www.grid.ac/institutes/grid.239424.a", 
          "name": [
            "Department of Neurology, Boston University Medical Center, MA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Myers", 
        "givenName": "Richard H", 
        "id": "sg:person.010442405757.16", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010442405757.16"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Utah", 
          "id": "https://www.grid.ac/institutes/grid.223827.e", 
          "name": [
            "Department of Internal Medicine, University of Utah Health Sciences Center, Salt Lake City, UT, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hopkins", 
        "givenName": "Paul N", 
        "id": "sg:person.013107363662.75", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013107363662.75"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Alabama at Birmingham", 
          "id": "https://www.grid.ac/institutes/grid.265892.2", 
          "name": [
            "Department of Epidemiology, University of Alabama School of Public Health, Birmingham, AL, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Arnett", 
        "givenName": "Donna", 
        "id": "sg:person.01351132756.07", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01351132756.07"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Washington University in St. Louis", 
          "id": "https://www.grid.ac/institutes/grid.4367.6", 
          "name": [
            "From the Division of Statistical Genomics, Washington University School of Medicine, Saint Louis, MO, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Corbett", 
        "givenName": "Jonathan", 
        "id": "sg:person.01074103705.27", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01074103705.27"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Washington University in St. Louis", 
          "id": "https://www.grid.ac/institutes/grid.4367.6", 
          "name": [
            "From the Division of Statistical Genomics, Washington University School of Medicine, Saint Louis, MO, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Adelman", 
        "givenName": "Avril", 
        "id": "sg:person.01273571054.08", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01273571054.08"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Washington University in St. Louis", 
          "id": "https://www.grid.ac/institutes/grid.4367.6", 
          "name": [
            "From the Division of Statistical Genomics, Washington University School of Medicine, Saint Louis, MO, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Province", 
        "givenName": "Michael A", 
        "id": "sg:person.014223302737.04", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014223302737.04"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.2337/diacare.26.11.3153", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008158915"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2337/diacare.26.3.575", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009237000"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1001/jama.288.21.2709", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009474275"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/(sici)1096-9136(199705)14:5<370::aid-dia363>3.0.co;2-j", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012343972"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2337/diabetes.53.4.1166", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012389495"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1159/000077545", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014777995"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2337/diabetes.52.5.1210", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018914258"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/oxfordjournals.aje.a008709", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019620955"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/1098-2272(200012)19:4<395::aid-gepi10>3.0.co;2-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020020594"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/01.hyp.35.5.1032", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020974870"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/01.cir.0000081777.17879.85", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026999290"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2337/diabetes.52.11.2840", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029210705"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.amjcard.2005.01.046", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030415876"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circulationaha.105.169404", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030755840"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/sj.ijo.0802422", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031545457", 
          "https://doi.org/10.1038/sj.ijo.0802422"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/sj.ijo.0802422", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031545457", 
          "https://doi.org/10.1038/sj.ijo.0802422"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2337/diacare.28.3.675", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033919261"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11936-005-0007-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036123485", 
          "https://doi.org/10.1007/s11936-005-0007-1"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.amjcard.2003.09.028", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038812186"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/gepi.10288", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040608932"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s1056-8727(00)00125-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041618859"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/01.hyp.0000184249.20016.bb", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047949139"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/01.hyp.0000184249.20016.bb", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047949139"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/01.hyp.0000184249.20016.bb", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047949139"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/01.cir.0000140677.20606.0e", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048457740"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1046/j.1464-5491.2003.01068.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050344057"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.amjhyper.2005.01.011", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1054726957"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1075127455", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circ.106.25.3143", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1075204771"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1055/s-0037-1613555", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1075222203"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1076958963", 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2006-12", 
    "datePublishedReg": "2006-12-01", 
    "description": "BACKGROUND: We report longitudinal changes in the metabolic syndrome (MetS) in 2,458 participants from 480 families in the Family Heart Study. Participants were examined between 1994-96 (FHS-T1) and 2002-03 (FHS-T2), about 7.4 years apart. Additionally, the impact of medication on estimates of MetS prevalence, and associations of MetS with prevalent coronary heart disease (CHD) and type 2 diabetes (T2D) were studied.\nMETHODS: Three definitions for MetS prevalence were considered. One represented the original (o) National Cholesterol Education Program (NCEP) MetS criteria. Two others considered the confounding of medications effects, respectively (m) lipid medications constituted a categorical diagnostic criterion for lipids variables, and (c) lipids and blood pressure variables were corrected with average clinical trials medications effects. Logistic regression of MetS on CHD and T2D, as well as the trend analysis of MetS by age, were performed.\nRESULTS: MetS increased from 17.1% in FHS-T1(o) to 28.8% in FHS-T2(o); from 19.7% in FHS-T1(m) to 42.5% in FHS-T2(m); and from 18.4% in FHS-T1(c) to 33.6% in FHS-T2(c). While we observed adverse changes in all risk factors, the greatest increase was for waist circumference (25%). The percentages of MetS were about 2 to almost 3 times higher in ages 50 years and older than in younger ages. The odds of having prevalent CHD were about 2.5 times higher in the subjects classified with MetS than without.\nCONCLUSION: MetS percentages increased noticeably longitudinally and cross-sectionally with older age. These conclusions were reached with and without considering medication use, but correcting risk factors for medications use affects the MetS prevalence estimates. As found in other studies, MetS was associated with increased odds for prevalent CHD.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1186/1743-7075-3-41", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.2691540", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.2691546", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.2691543", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.2691541", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.2404655", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.2691542", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.2691545", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.2439022", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.2691544", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": [
      {
        "id": "sg:journal.1034448", 
        "issn": [
          "1743-7075"
        ], 
        "name": "Nutrition & Metabolism", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "3"
      }
    ], 
    "name": "Longitudinal and age trends of metabolic syndrome and its risk factors: The Family Heart Study", 
    "pagination": "41", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "433261a9150ee8a741e593b357a53519ad2259f7d27d95169b3557b6c74fa219"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "17147796"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "101231644"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1186/1743-7075-3-41"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1014105373"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1186/1743-7075-3-41", 
      "https://app.dimensions.ai/details/publication/pub.1014105373"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T15:58", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8664_00000549.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1186%2F1743-7075-3-41"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/1743-7075-3-41'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/1743-7075-3-41'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/1743-7075-3-41'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/1743-7075-3-41'


 

This table displays all metadata directly associated to this object as RDF triples.

248 TRIPLES      21 PREDICATES      57 URIs      21 LITERALS      9 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1186/1743-7075-3-41 schema:about anzsrc-for:11
2 anzsrc-for:1103
3 schema:author Nc8d45458cd3341b484e53feb655ee284
4 schema:citation sg:pub.10.1007/s11936-005-0007-1
5 sg:pub.10.1038/sj.ijo.0802422
6 https://app.dimensions.ai/details/publication/pub.1075127455
7 https://app.dimensions.ai/details/publication/pub.1076958963
8 https://doi.org/10.1001/jama.288.21.2709
9 https://doi.org/10.1002/(sici)1096-9136(199705)14:5<370::aid-dia363>3.0.co;2-j
10 https://doi.org/10.1002/1098-2272(200012)19:4<395::aid-gepi10>3.0.co;2-3
11 https://doi.org/10.1002/gepi.10288
12 https://doi.org/10.1016/j.amjcard.2003.09.028
13 https://doi.org/10.1016/j.amjcard.2005.01.046
14 https://doi.org/10.1016/j.amjhyper.2005.01.011
15 https://doi.org/10.1016/s1056-8727(00)00125-2
16 https://doi.org/10.1046/j.1464-5491.2003.01068.x
17 https://doi.org/10.1055/s-0037-1613555
18 https://doi.org/10.1093/oxfordjournals.aje.a008709
19 https://doi.org/10.1159/000077545
20 https://doi.org/10.1161/01.cir.0000081777.17879.85
21 https://doi.org/10.1161/01.cir.0000140677.20606.0e
22 https://doi.org/10.1161/01.hyp.0000184249.20016.bb
23 https://doi.org/10.1161/01.hyp.35.5.1032
24 https://doi.org/10.1161/circ.106.25.3143
25 https://doi.org/10.1161/circulationaha.105.169404
26 https://doi.org/10.2337/diabetes.52.11.2840
27 https://doi.org/10.2337/diabetes.52.5.1210
28 https://doi.org/10.2337/diabetes.53.4.1166
29 https://doi.org/10.2337/diacare.26.11.3153
30 https://doi.org/10.2337/diacare.26.3.575
31 https://doi.org/10.2337/diacare.28.3.675
32 schema:datePublished 2006-12
33 schema:datePublishedReg 2006-12-01
34 schema:description BACKGROUND: We report longitudinal changes in the metabolic syndrome (MetS) in 2,458 participants from 480 families in the Family Heart Study. Participants were examined between 1994-96 (FHS-T1) and 2002-03 (FHS-T2), about 7.4 years apart. Additionally, the impact of medication on estimates of MetS prevalence, and associations of MetS with prevalent coronary heart disease (CHD) and type 2 diabetes (T2D) were studied. METHODS: Three definitions for MetS prevalence were considered. One represented the original (o) National Cholesterol Education Program (NCEP) MetS criteria. Two others considered the confounding of medications effects, respectively (m) lipid medications constituted a categorical diagnostic criterion for lipids variables, and (c) lipids and blood pressure variables were corrected with average clinical trials medications effects. Logistic regression of MetS on CHD and T2D, as well as the trend analysis of MetS by age, were performed. RESULTS: MetS increased from 17.1% in FHS-T1(o) to 28.8% in FHS-T2(o); from 19.7% in FHS-T1(m) to 42.5% in FHS-T2(m); and from 18.4% in FHS-T1(c) to 33.6% in FHS-T2(c). While we observed adverse changes in all risk factors, the greatest increase was for waist circumference (25%). The percentages of MetS were about 2 to almost 3 times higher in ages 50 years and older than in younger ages. The odds of having prevalent CHD were about 2.5 times higher in the subjects classified with MetS than without. CONCLUSION: MetS percentages increased noticeably longitudinally and cross-sectionally with older age. These conclusions were reached with and without considering medication use, but correcting risk factors for medications use affects the MetS prevalence estimates. As found in other studies, MetS was associated with increased odds for prevalent CHD.
35 schema:genre research_article
36 schema:inLanguage en
37 schema:isAccessibleForFree true
38 schema:isPartOf N520b34bc6d9646869ec9cf4027d8b40a
39 Ndb20347b541443d5b592708adcf882c8
40 sg:journal.1034448
41 schema:name Longitudinal and age trends of metabolic syndrome and its risk factors: The Family Heart Study
42 schema:pagination 41
43 schema:productId N14c5342da0124b1c8ccd73a4c1cc0604
44 N4fefe3375f92413882cd83c5333a05bf
45 N732f97ba3e88438d8f6ae0ed96d40a3d
46 N98cefb51033c4d4aa3d4b961a44aee07
47 Naeb5f8ea05424107bb53773e0c60f550
48 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014105373
49 https://doi.org/10.1186/1743-7075-3-41
50 schema:sdDatePublished 2019-04-10T15:58
51 schema:sdLicense https://scigraph.springernature.com/explorer/license/
52 schema:sdPublisher Nb9b495dcb6fd4f0abcadbcd0f8fe38bc
53 schema:url http://link.springer.com/10.1186%2F1743-7075-3-41
54 sgo:license sg:explorer/license/
55 sgo:sdDataset articles
56 rdf:type schema:ScholarlyArticle
57 N026666d9e5894a81bba4bd70583ab259 rdf:first sg:person.014304652012.83
58 rdf:rest Nc6798d5919ca4471a4be74535c493c81
59 N06c30fe7c529434dab8191febdaef47b rdf:first sg:person.013107363662.75
60 rdf:rest N565a986f6006409ea7208cb1b4d10303
61 N14c5342da0124b1c8ccd73a4c1cc0604 schema:name pubmed_id
62 schema:value 17147796
63 rdf:type schema:PropertyValue
64 N4fefe3375f92413882cd83c5333a05bf schema:name readcube_id
65 schema:value 433261a9150ee8a741e593b357a53519ad2259f7d27d95169b3557b6c74fa219
66 rdf:type schema:PropertyValue
67 N520b34bc6d9646869ec9cf4027d8b40a schema:issueNumber 1
68 rdf:type schema:PublicationIssue
69 N5573cd79f86e4bc09de3bf65cb2a634e rdf:first sg:person.01117564210.02
70 rdf:rest Nc00fc9627807407aac2caa87e4b4090d
71 N565a986f6006409ea7208cb1b4d10303 rdf:first sg:person.01351132756.07
72 rdf:rest Nc35bcce810714602824aadcadfe72933
73 N732f97ba3e88438d8f6ae0ed96d40a3d schema:name nlm_unique_id
74 schema:value 101231644
75 rdf:type schema:PropertyValue
76 N7763d6b26ad74be89e09326c29414771 rdf:first sg:person.01273571054.08
77 rdf:rest Nb20b44d1e484474893128b856675e626
78 N98cefb51033c4d4aa3d4b961a44aee07 schema:name dimensions_id
79 schema:value pub.1014105373
80 rdf:type schema:PropertyValue
81 Naeb5f8ea05424107bb53773e0c60f550 schema:name doi
82 schema:value 10.1186/1743-7075-3-41
83 rdf:type schema:PropertyValue
84 Nb20b44d1e484474893128b856675e626 rdf:first sg:person.014223302737.04
85 rdf:rest rdf:nil
86 Nb9b495dcb6fd4f0abcadbcd0f8fe38bc schema:name Springer Nature - SN SciGraph project
87 rdf:type schema:Organization
88 Nc00fc9627807407aac2caa87e4b4090d rdf:first sg:person.011405001662.87
89 rdf:rest N026666d9e5894a81bba4bd70583ab259
90 Nc35bcce810714602824aadcadfe72933 rdf:first sg:person.01074103705.27
91 rdf:rest N7763d6b26ad74be89e09326c29414771
92 Nc6798d5919ca4471a4be74535c493c81 rdf:first sg:person.010442405757.16
93 rdf:rest N06c30fe7c529434dab8191febdaef47b
94 Nc8d45458cd3341b484e53feb655ee284 rdf:first sg:person.01260600634.53
95 rdf:rest N5573cd79f86e4bc09de3bf65cb2a634e
96 Ndb20347b541443d5b592708adcf882c8 schema:volumeNumber 3
97 rdf:type schema:PublicationVolume
98 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
99 schema:name Medical and Health Sciences
100 rdf:type schema:DefinedTerm
101 anzsrc-for:1103 schema:inDefinedTermSet anzsrc-for:
102 schema:name Clinical Sciences
103 rdf:type schema:DefinedTerm
104 sg:grant.2404655 http://pending.schema.org/fundedItem sg:pub.10.1186/1743-7075-3-41
105 rdf:type schema:MonetaryGrant
106 sg:grant.2439022 http://pending.schema.org/fundedItem sg:pub.10.1186/1743-7075-3-41
107 rdf:type schema:MonetaryGrant
108 sg:grant.2691540 http://pending.schema.org/fundedItem sg:pub.10.1186/1743-7075-3-41
109 rdf:type schema:MonetaryGrant
110 sg:grant.2691541 http://pending.schema.org/fundedItem sg:pub.10.1186/1743-7075-3-41
111 rdf:type schema:MonetaryGrant
112 sg:grant.2691542 http://pending.schema.org/fundedItem sg:pub.10.1186/1743-7075-3-41
113 rdf:type schema:MonetaryGrant
114 sg:grant.2691543 http://pending.schema.org/fundedItem sg:pub.10.1186/1743-7075-3-41
115 rdf:type schema:MonetaryGrant
116 sg:grant.2691544 http://pending.schema.org/fundedItem sg:pub.10.1186/1743-7075-3-41
117 rdf:type schema:MonetaryGrant
118 sg:grant.2691545 http://pending.schema.org/fundedItem sg:pub.10.1186/1743-7075-3-41
119 rdf:type schema:MonetaryGrant
120 sg:grant.2691546 http://pending.schema.org/fundedItem sg:pub.10.1186/1743-7075-3-41
121 rdf:type schema:MonetaryGrant
122 sg:journal.1034448 schema:issn 1743-7075
123 schema:name Nutrition & Metabolism
124 rdf:type schema:Periodical
125 sg:person.010442405757.16 schema:affiliation https://www.grid.ac/institutes/grid.239424.a
126 schema:familyName Myers
127 schema:givenName Richard H
128 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010442405757.16
129 rdf:type schema:Person
130 sg:person.01074103705.27 schema:affiliation https://www.grid.ac/institutes/grid.4367.6
131 schema:familyName Corbett
132 schema:givenName Jonathan
133 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01074103705.27
134 rdf:type schema:Person
135 sg:person.01117564210.02 schema:affiliation https://www.grid.ac/institutes/grid.4367.6
136 schema:familyName Borecki
137 schema:givenName Ingrid B
138 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01117564210.02
139 rdf:type schema:Person
140 sg:person.011405001662.87 schema:affiliation https://www.grid.ac/institutes/grid.410711.2
141 schema:familyName North
142 schema:givenName Kari
143 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011405001662.87
144 rdf:type schema:Person
145 sg:person.01260600634.53 schema:affiliation https://www.grid.ac/institutes/grid.4367.6
146 schema:familyName Kraja
147 schema:givenName Aldi T
148 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01260600634.53
149 rdf:type schema:Person
150 sg:person.01273571054.08 schema:affiliation https://www.grid.ac/institutes/grid.4367.6
151 schema:familyName Adelman
152 schema:givenName Avril
153 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01273571054.08
154 rdf:type schema:Person
155 sg:person.013107363662.75 schema:affiliation https://www.grid.ac/institutes/grid.223827.e
156 schema:familyName Hopkins
157 schema:givenName Paul N
158 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013107363662.75
159 rdf:type schema:Person
160 sg:person.01351132756.07 schema:affiliation https://www.grid.ac/institutes/grid.265892.2
161 schema:familyName Arnett
162 schema:givenName Donna
163 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01351132756.07
164 rdf:type schema:Person
165 sg:person.014223302737.04 schema:affiliation https://www.grid.ac/institutes/grid.4367.6
166 schema:familyName Province
167 schema:givenName Michael A
168 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014223302737.04
169 rdf:type schema:Person
170 sg:person.014304652012.83 schema:affiliation https://www.grid.ac/institutes/grid.17635.36
171 schema:familyName Tang
172 schema:givenName Weihong
173 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014304652012.83
174 rdf:type schema:Person
175 sg:pub.10.1007/s11936-005-0007-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036123485
176 https://doi.org/10.1007/s11936-005-0007-1
177 rdf:type schema:CreativeWork
178 sg:pub.10.1038/sj.ijo.0802422 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031545457
179 https://doi.org/10.1038/sj.ijo.0802422
180 rdf:type schema:CreativeWork
181 https://app.dimensions.ai/details/publication/pub.1075127455 schema:CreativeWork
182 https://app.dimensions.ai/details/publication/pub.1076958963 schema:CreativeWork
183 https://doi.org/10.1001/jama.288.21.2709 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009474275
184 rdf:type schema:CreativeWork
185 https://doi.org/10.1002/(sici)1096-9136(199705)14:5<370::aid-dia363>3.0.co;2-j schema:sameAs https://app.dimensions.ai/details/publication/pub.1012343972
186 rdf:type schema:CreativeWork
187 https://doi.org/10.1002/1098-2272(200012)19:4<395::aid-gepi10>3.0.co;2-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020020594
188 rdf:type schema:CreativeWork
189 https://doi.org/10.1002/gepi.10288 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040608932
190 rdf:type schema:CreativeWork
191 https://doi.org/10.1016/j.amjcard.2003.09.028 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038812186
192 rdf:type schema:CreativeWork
193 https://doi.org/10.1016/j.amjcard.2005.01.046 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030415876
194 rdf:type schema:CreativeWork
195 https://doi.org/10.1016/j.amjhyper.2005.01.011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1054726957
196 rdf:type schema:CreativeWork
197 https://doi.org/10.1016/s1056-8727(00)00125-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041618859
198 rdf:type schema:CreativeWork
199 https://doi.org/10.1046/j.1464-5491.2003.01068.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1050344057
200 rdf:type schema:CreativeWork
201 https://doi.org/10.1055/s-0037-1613555 schema:sameAs https://app.dimensions.ai/details/publication/pub.1075222203
202 rdf:type schema:CreativeWork
203 https://doi.org/10.1093/oxfordjournals.aje.a008709 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019620955
204 rdf:type schema:CreativeWork
205 https://doi.org/10.1159/000077545 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014777995
206 rdf:type schema:CreativeWork
207 https://doi.org/10.1161/01.cir.0000081777.17879.85 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026999290
208 rdf:type schema:CreativeWork
209 https://doi.org/10.1161/01.cir.0000140677.20606.0e schema:sameAs https://app.dimensions.ai/details/publication/pub.1048457740
210 rdf:type schema:CreativeWork
211 https://doi.org/10.1161/01.hyp.0000184249.20016.bb schema:sameAs https://app.dimensions.ai/details/publication/pub.1047949139
212 rdf:type schema:CreativeWork
213 https://doi.org/10.1161/01.hyp.35.5.1032 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020974870
214 rdf:type schema:CreativeWork
215 https://doi.org/10.1161/circ.106.25.3143 schema:sameAs https://app.dimensions.ai/details/publication/pub.1075204771
216 rdf:type schema:CreativeWork
217 https://doi.org/10.1161/circulationaha.105.169404 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030755840
218 rdf:type schema:CreativeWork
219 https://doi.org/10.2337/diabetes.52.11.2840 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029210705
220 rdf:type schema:CreativeWork
221 https://doi.org/10.2337/diabetes.52.5.1210 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018914258
222 rdf:type schema:CreativeWork
223 https://doi.org/10.2337/diabetes.53.4.1166 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012389495
224 rdf:type schema:CreativeWork
225 https://doi.org/10.2337/diacare.26.11.3153 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008158915
226 rdf:type schema:CreativeWork
227 https://doi.org/10.2337/diacare.26.3.575 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009237000
228 rdf:type schema:CreativeWork
229 https://doi.org/10.2337/diacare.28.3.675 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033919261
230 rdf:type schema:CreativeWork
231 https://www.grid.ac/institutes/grid.17635.36 schema:alternateName University of Minnesota
232 schema:name Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN, USA
233 rdf:type schema:Organization
234 https://www.grid.ac/institutes/grid.223827.e schema:alternateName University of Utah
235 schema:name Department of Internal Medicine, University of Utah Health Sciences Center, Salt Lake City, UT, USA
236 rdf:type schema:Organization
237 https://www.grid.ac/institutes/grid.239424.a schema:alternateName Boston Medical Center
238 schema:name Department of Neurology, Boston University Medical Center, MA, USA
239 rdf:type schema:Organization
240 https://www.grid.ac/institutes/grid.265892.2 schema:alternateName University of Alabama at Birmingham
241 schema:name Department of Epidemiology, University of Alabama School of Public Health, Birmingham, AL, USA
242 rdf:type schema:Organization
243 https://www.grid.ac/institutes/grid.410711.2 schema:alternateName University of North Carolina System
244 schema:name Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
245 rdf:type schema:Organization
246 https://www.grid.ac/institutes/grid.4367.6 schema:alternateName Washington University in St. Louis
247 schema:name From the Division of Statistical Genomics, Washington University School of Medicine, Saint Louis, MO, USA
248 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...