Association between allergic rhinitis and metabolic conditions: a nationwide survey in Korea View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2016-12

AUTHORS

In Cheol Hwang, Yong Joo Lee, Hong Yup Ahn, Sang Min Lee

ABSTRACT

BACKGROUND: Accumulating evidence indicates a strong correlation between allergic disease and cardiovascular risks. In spite of this, the data concerning the association between allergic rhinitis (AR) and cardiovascular risks is sparse and conflicting. This study aimed to investigate the association between AR prevalence and metabolic syndrome (MetS) in a large-scale, population-based survey, while considering the relevant risk factors. METHODS: A nationwide cross-sectional study was conducted based on data from 30,590 subjects aged 19 years and older, from the Korean National Health and Nutrition Survey 2007-2013. The odds ratios (ORs) and 95 % confidence intervals (CIs) of AR prevalence, based on MetS status and the presence of any MetS component, were calculated using multiple logistic regression analyses. RESULTS: Regarding the characteristics of patients with AR and/or MetS, some variables had significant associations with disease in inverse directions for AR and MetS. Multivariate logistic analysis, with adjustments for demographic variables and health habits, indicated that AR prevalence was significantly lower in subjects with MetS (OR 0.84; 95 % CI 0.76-0.93), high blood pressure (OR 0.85; 95 % CI 0.77-0.94), or impaired fasting glucose (OR 0.81; 95 % CI 0.73-0.89). Furthermore, high blood pressure and impaired fasting glucose were significant predictors for reduced AR prevalence, independently of other MetS components. CONCLUSION: In this population, AR was diagnosed less frequently in subjects with metabolic conditions. Well-designed prospective studies allowing for medical service utilization and collaborative basic research are warranted to elucidate the mechanism responsible for this inverse relationship. More... »

PAGES

5

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s13223-015-0108-7

DOI

http://dx.doi.org/10.1186/s13223-015-0108-7

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1043288407

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/26807136


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/2008/1117", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Public Health and Health Services", 
        "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": "Gachon University Gil Medical Center", 
          "id": "https://www.grid.ac/institutes/grid.411653.4", 
          "name": [
            "Department of Family Medicine, Gachon University Gil Medical Center, Incheon, Republic of Korea"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hwang", 
        "givenName": "In Cheol", 
        "id": "sg:person.01165746746.79", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01165746746.79"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Catholic University of Korea", 
          "id": "https://www.grid.ac/institutes/grid.411947.e", 
          "name": [
            "Department of Family Medicine, Seoul St. Mary\u2019s Hospital, The Catholic University College of Medicine, 222 Banpo-daero, Seocho-gu, 137-701, Seoul, Republic of Korea"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Lee", 
        "givenName": "Yong Joo", 
        "id": "sg:person.0656757343.28", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0656757343.28"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Dongguk University", 
          "id": "https://www.grid.ac/institutes/grid.255168.d", 
          "name": [
            "Department of Statistics, Dongguk University, Seoul, Republic of Korea"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ahn", 
        "givenName": "Hong Yup", 
        "id": "sg:person.0662273421.52", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0662273421.52"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Gachon University Gil Medical Center", 
          "id": "https://www.grid.ac/institutes/grid.411653.4", 
          "name": [
            "Division of Allergy, Department of Internal Medicine, Gil Medical Center, Incheon, Republic of Korea"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Lee", 
        "givenName": "Sang Min", 
        "id": "sg:person.01315300754.59", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01315300754.59"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1046/j.1365-2222.2002.01311.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000177707"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jaci.2004.08.044", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006482889"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1291/hypres.26.961", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008106205", 
          "https://doi.org/10.1291/hypres.26.961"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3122/jabfm.2008.03.070273", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013515293"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1365-2222.2007.02695.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015656589"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.diabres.2006.04.013", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016027000"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1172/jci46028", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019674574"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jaci.2003.09.051", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023957359"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/jaha.113.000650", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024217156"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.4082/kjfm.2015.36.2.60", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025485108"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1056/nejmcp1412282", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027588010"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1503/cmaj.050584", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028648737"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1503/cmaj.050584", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028648737"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1467-789x.2009.00663.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030572079"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1467-789x.2009.00663.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030572079"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2337/dc08-2228", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033715228"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/00004872-200405000-00008", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036337502"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/00004872-200405000-00008", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036337502"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2337/dc10-1338", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037744292"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circulationaha.111.075424", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040993620"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1161/circulationaha.111.075424", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040993620"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1136/oem.2006.031542", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045575254"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1136/oem.2006.031542", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045575254"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.pcad.2013.03.006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050682645"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/qjmed/hcv104", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1059986316"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.12998/wjcc.v3.i3.285", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064867829"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1076819420", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1078328347", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1078513180", 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2016-12", 
    "datePublishedReg": "2016-12-01", 
    "description": "BACKGROUND: Accumulating evidence indicates a strong correlation between allergic disease and cardiovascular risks. In spite of this, the data concerning the association between allergic rhinitis (AR) and cardiovascular risks is sparse and conflicting. This study aimed to investigate the association between AR prevalence and metabolic syndrome (MetS) in a large-scale, population-based survey, while considering the relevant risk factors.\nMETHODS: A nationwide cross-sectional study was conducted based on data from 30,590 subjects aged 19\u00a0years and older, from the Korean National Health and Nutrition Survey 2007-2013. The odds ratios (ORs) and 95\u00a0% confidence intervals (CIs) of AR prevalence, based on MetS status and the presence of any MetS component, were calculated using multiple logistic regression analyses.\nRESULTS: Regarding the characteristics of patients with AR and/or MetS, some variables had significant associations with disease in inverse directions for AR and MetS. Multivariate logistic analysis, with adjustments for demographic variables and health habits, indicated that AR prevalence was significantly lower in subjects with MetS (OR 0.84; 95\u00a0% CI 0.76-0.93), high blood pressure (OR 0.85; 95\u00a0% CI 0.77-0.94), or impaired fasting glucose (OR 0.81; 95\u00a0% CI 0.73-0.89). Furthermore, high blood pressure and impaired fasting glucose were significant predictors for reduced AR prevalence, independently of other MetS components.\nCONCLUSION: In this population, AR was diagnosed less frequently in subjects with metabolic conditions. Well-designed prospective studies allowing for medical service utilization and collaborative basic research are warranted to elucidate the mechanism responsible for this inverse relationship.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1186/s13223-015-0108-7", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1035225", 
        "issn": [
          "1710-1484", 
          "1710-1492"
        ], 
        "name": "Allergy, Asthma & Clinical Immunology", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "12"
      }
    ], 
    "name": "Association between allergic rhinitis and metabolic conditions: a nationwide survey in Korea", 
    "pagination": "5", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "ce32b6e99a5812ca7fda4e63d81e6e7e4b482fbfb5a57ce84c209f3d0c1908e5"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "26807136"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "101244313"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1186/s13223-015-0108-7"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1043288407"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1186/s13223-015-0108-7", 
      "https://app.dimensions.ai/details/publication/pub.1043288407"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T15:08", 
    "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_8663_00000551.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1186%2Fs13223-015-0108-7"
  }
]
 

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/s13223-015-0108-7'

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/s13223-015-0108-7'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s13223-015-0108-7'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s13223-015-0108-7'


 

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

167 TRIPLES      21 PREDICATES      53 URIs      21 LITERALS      9 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1186/s13223-015-0108-7 schema:about anzsrc-for:11
2 anzsrc-for:1117
3 schema:author N2fdc36e34467474cb8dd23ba409b0eac
4 schema:citation sg:pub.10.1291/hypres.26.961
5 https://app.dimensions.ai/details/publication/pub.1076819420
6 https://app.dimensions.ai/details/publication/pub.1078328347
7 https://app.dimensions.ai/details/publication/pub.1078513180
8 https://doi.org/10.1016/j.diabres.2006.04.013
9 https://doi.org/10.1016/j.jaci.2003.09.051
10 https://doi.org/10.1016/j.jaci.2004.08.044
11 https://doi.org/10.1016/j.pcad.2013.03.006
12 https://doi.org/10.1046/j.1365-2222.2002.01311.x
13 https://doi.org/10.1056/nejmcp1412282
14 https://doi.org/10.1093/qjmed/hcv104
15 https://doi.org/10.1097/00004872-200405000-00008
16 https://doi.org/10.1111/j.1365-2222.2007.02695.x
17 https://doi.org/10.1111/j.1467-789x.2009.00663.x
18 https://doi.org/10.1136/oem.2006.031542
19 https://doi.org/10.1161/circulationaha.111.075424
20 https://doi.org/10.1161/jaha.113.000650
21 https://doi.org/10.1172/jci46028
22 https://doi.org/10.12998/wjcc.v3.i3.285
23 https://doi.org/10.1503/cmaj.050584
24 https://doi.org/10.2337/dc08-2228
25 https://doi.org/10.2337/dc10-1338
26 https://doi.org/10.3122/jabfm.2008.03.070273
27 https://doi.org/10.4082/kjfm.2015.36.2.60
28 schema:datePublished 2016-12
29 schema:datePublishedReg 2016-12-01
30 schema:description BACKGROUND: Accumulating evidence indicates a strong correlation between allergic disease and cardiovascular risks. In spite of this, the data concerning the association between allergic rhinitis (AR) and cardiovascular risks is sparse and conflicting. This study aimed to investigate the association between AR prevalence and metabolic syndrome (MetS) in a large-scale, population-based survey, while considering the relevant risk factors. METHODS: A nationwide cross-sectional study was conducted based on data from 30,590 subjects aged 19 years and older, from the Korean National Health and Nutrition Survey 2007-2013. The odds ratios (ORs) and 95 % confidence intervals (CIs) of AR prevalence, based on MetS status and the presence of any MetS component, were calculated using multiple logistic regression analyses. RESULTS: Regarding the characteristics of patients with AR and/or MetS, some variables had significant associations with disease in inverse directions for AR and MetS. Multivariate logistic analysis, with adjustments for demographic variables and health habits, indicated that AR prevalence was significantly lower in subjects with MetS (OR 0.84; 95 % CI 0.76-0.93), high blood pressure (OR 0.85; 95 % CI 0.77-0.94), or impaired fasting glucose (OR 0.81; 95 % CI 0.73-0.89). Furthermore, high blood pressure and impaired fasting glucose were significant predictors for reduced AR prevalence, independently of other MetS components. CONCLUSION: In this population, AR was diagnosed less frequently in subjects with metabolic conditions. Well-designed prospective studies allowing for medical service utilization and collaborative basic research are warranted to elucidate the mechanism responsible for this inverse relationship.
31 schema:genre research_article
32 schema:inLanguage en
33 schema:isAccessibleForFree true
34 schema:isPartOf N1f7a9c0c964c40e19379c22da72f65b7
35 N4a8b252ee7964281a379d963a01eaa45
36 sg:journal.1035225
37 schema:name Association between allergic rhinitis and metabolic conditions: a nationwide survey in Korea
38 schema:pagination 5
39 schema:productId N2e25957b1add48869b12d569efa55882
40 N3485ff088c9249309b4e1441b1e65be2
41 N481904739d62476c8166c78425dacf9e
42 Na924af3b18b44c168124c170cf874033
43 Neae8da1218c24f64a3d7440b9e0eae42
44 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043288407
45 https://doi.org/10.1186/s13223-015-0108-7
46 schema:sdDatePublished 2019-04-10T15:08
47 schema:sdLicense https://scigraph.springernature.com/explorer/license/
48 schema:sdPublisher N7c7a2e00921544fe8a651676b4839a04
49 schema:url http://link.springer.com/10.1186%2Fs13223-015-0108-7
50 sgo:license sg:explorer/license/
51 sgo:sdDataset articles
52 rdf:type schema:ScholarlyArticle
53 N0ef16bcfbfde4f32b209e246dda22c3a rdf:first sg:person.0662273421.52
54 rdf:rest N6bc5c98ad2bb4511a24aefaede58eda7
55 N1f7a9c0c964c40e19379c22da72f65b7 schema:volumeNumber 12
56 rdf:type schema:PublicationVolume
57 N2e25957b1add48869b12d569efa55882 schema:name readcube_id
58 schema:value ce32b6e99a5812ca7fda4e63d81e6e7e4b482fbfb5a57ce84c209f3d0c1908e5
59 rdf:type schema:PropertyValue
60 N2fdc36e34467474cb8dd23ba409b0eac rdf:first sg:person.01165746746.79
61 rdf:rest Naa5dbe7a4dce4316bcd8c1abf08e355a
62 N3485ff088c9249309b4e1441b1e65be2 schema:name dimensions_id
63 schema:value pub.1043288407
64 rdf:type schema:PropertyValue
65 N481904739d62476c8166c78425dacf9e schema:name doi
66 schema:value 10.1186/s13223-015-0108-7
67 rdf:type schema:PropertyValue
68 N4a8b252ee7964281a379d963a01eaa45 schema:issueNumber 1
69 rdf:type schema:PublicationIssue
70 N6bc5c98ad2bb4511a24aefaede58eda7 rdf:first sg:person.01315300754.59
71 rdf:rest rdf:nil
72 N7c7a2e00921544fe8a651676b4839a04 schema:name Springer Nature - SN SciGraph project
73 rdf:type schema:Organization
74 Na924af3b18b44c168124c170cf874033 schema:name pubmed_id
75 schema:value 26807136
76 rdf:type schema:PropertyValue
77 Naa5dbe7a4dce4316bcd8c1abf08e355a rdf:first sg:person.0656757343.28
78 rdf:rest N0ef16bcfbfde4f32b209e246dda22c3a
79 Neae8da1218c24f64a3d7440b9e0eae42 schema:name nlm_unique_id
80 schema:value 101244313
81 rdf:type schema:PropertyValue
82 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
83 schema:name Medical and Health Sciences
84 rdf:type schema:DefinedTerm
85 anzsrc-for:1117 schema:inDefinedTermSet anzsrc-for:
86 schema:name Public Health and Health Services
87 rdf:type schema:DefinedTerm
88 sg:journal.1035225 schema:issn 1710-1484
89 1710-1492
90 schema:name Allergy, Asthma & Clinical Immunology
91 rdf:type schema:Periodical
92 sg:person.01165746746.79 schema:affiliation https://www.grid.ac/institutes/grid.411653.4
93 schema:familyName Hwang
94 schema:givenName In Cheol
95 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01165746746.79
96 rdf:type schema:Person
97 sg:person.01315300754.59 schema:affiliation https://www.grid.ac/institutes/grid.411653.4
98 schema:familyName Lee
99 schema:givenName Sang Min
100 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01315300754.59
101 rdf:type schema:Person
102 sg:person.0656757343.28 schema:affiliation https://www.grid.ac/institutes/grid.411947.e
103 schema:familyName Lee
104 schema:givenName Yong Joo
105 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0656757343.28
106 rdf:type schema:Person
107 sg:person.0662273421.52 schema:affiliation https://www.grid.ac/institutes/grid.255168.d
108 schema:familyName Ahn
109 schema:givenName Hong Yup
110 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0662273421.52
111 rdf:type schema:Person
112 sg:pub.10.1291/hypres.26.961 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008106205
113 https://doi.org/10.1291/hypres.26.961
114 rdf:type schema:CreativeWork
115 https://app.dimensions.ai/details/publication/pub.1076819420 schema:CreativeWork
116 https://app.dimensions.ai/details/publication/pub.1078328347 schema:CreativeWork
117 https://app.dimensions.ai/details/publication/pub.1078513180 schema:CreativeWork
118 https://doi.org/10.1016/j.diabres.2006.04.013 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016027000
119 rdf:type schema:CreativeWork
120 https://doi.org/10.1016/j.jaci.2003.09.051 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023957359
121 rdf:type schema:CreativeWork
122 https://doi.org/10.1016/j.jaci.2004.08.044 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006482889
123 rdf:type schema:CreativeWork
124 https://doi.org/10.1016/j.pcad.2013.03.006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050682645
125 rdf:type schema:CreativeWork
126 https://doi.org/10.1046/j.1365-2222.2002.01311.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1000177707
127 rdf:type schema:CreativeWork
128 https://doi.org/10.1056/nejmcp1412282 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027588010
129 rdf:type schema:CreativeWork
130 https://doi.org/10.1093/qjmed/hcv104 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059986316
131 rdf:type schema:CreativeWork
132 https://doi.org/10.1097/00004872-200405000-00008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036337502
133 rdf:type schema:CreativeWork
134 https://doi.org/10.1111/j.1365-2222.2007.02695.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1015656589
135 rdf:type schema:CreativeWork
136 https://doi.org/10.1111/j.1467-789x.2009.00663.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1030572079
137 rdf:type schema:CreativeWork
138 https://doi.org/10.1136/oem.2006.031542 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045575254
139 rdf:type schema:CreativeWork
140 https://doi.org/10.1161/circulationaha.111.075424 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040993620
141 rdf:type schema:CreativeWork
142 https://doi.org/10.1161/jaha.113.000650 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024217156
143 rdf:type schema:CreativeWork
144 https://doi.org/10.1172/jci46028 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019674574
145 rdf:type schema:CreativeWork
146 https://doi.org/10.12998/wjcc.v3.i3.285 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064867829
147 rdf:type schema:CreativeWork
148 https://doi.org/10.1503/cmaj.050584 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028648737
149 rdf:type schema:CreativeWork
150 https://doi.org/10.2337/dc08-2228 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033715228
151 rdf:type schema:CreativeWork
152 https://doi.org/10.2337/dc10-1338 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037744292
153 rdf:type schema:CreativeWork
154 https://doi.org/10.3122/jabfm.2008.03.070273 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013515293
155 rdf:type schema:CreativeWork
156 https://doi.org/10.4082/kjfm.2015.36.2.60 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025485108
157 rdf:type schema:CreativeWork
158 https://www.grid.ac/institutes/grid.255168.d schema:alternateName Dongguk University
159 schema:name Department of Statistics, Dongguk University, Seoul, Republic of Korea
160 rdf:type schema:Organization
161 https://www.grid.ac/institutes/grid.411653.4 schema:alternateName Gachon University Gil Medical Center
162 schema:name Department of Family Medicine, Gachon University Gil Medical Center, Incheon, Republic of Korea
163 Division of Allergy, Department of Internal Medicine, Gil Medical Center, Incheon, Republic of Korea
164 rdf:type schema:Organization
165 https://www.grid.ac/institutes/grid.411947.e schema:alternateName Catholic University of Korea
166 schema:name Department of Family Medicine, Seoul St. Mary’s Hospital, The Catholic University College of Medicine, 222 Banpo-daero, Seocho-gu, 137-701, Seoul, Republic of Korea
167 rdf:type schema:Organization
 




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


...