Waist-to-height ratio, a simple and practical index for assessing central fat distribution and metabolic risk in Japanese men and women View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2003-04-17

AUTHORS

S D Hsieh, H Yoshinaga, T Muto

ABSTRACT

OBJECTIVE: The normal body mass index (BMI) range, as defined by the World Health Organization (WHO), is quite wide, and some people within this range may have excessive central fat accumulation and elevated metabolic risks. We hypothesize that the waist-to-height ratio (W/Ht), an effective index for assessing central fat distribution among Japanese people, can be used to identify subjects who are at higher metabolic risk within the normal as well as the overweight range.METHODS: We investigated: (1) the values of BMI, waist circumference, and W/Ht in 6141 men and 2137 women at various age intervals and calculated gender (female to male) ratios for all these anthropometric indices; (2) the relation between age and each anthropometric index, between age and morbidity index for coronary risk factors (sum of the scores for hyperglycemia, hypertension, hypertriglyceridemia, hypercholesterolemia, and low HDL cholesterol; one point for each condition if present), and between morbidity index for coronary risk factors and each anthropometric index; (3) the distributions of the subjects, using various proposed indices of waist circumference (those suggested by WHO, the Japan Society for the Study of Obesity, and the Asia-Pacific perspective), and our proposed boundary value, W/Ht 0.5, among the WHO categories based on BMI; (4) the metabolic risks (coronary risk factors, hyperuricemia, high γ-glutamyltransferase, and fatty liver diagnosed by ultrasonography), and exercise habits among normal-weight subjects with W/Ht<0.5 or ≥0.5.RESULTS: (1) For the various anthropometric indices in all age groups, the gender ratio for W/Ht was closest to 1, indicating that a single set of values for W/Ht can be used for men and women. (2) Height correlated negatively with age. Among the anthropometric indices, only W/Ht correlated positively with age for both men and women, while age and all anthropometric indices, except height, correlated positively with the morbidity index for coronary risk factors. For both men and women, the highest correlation coefficient was between W/Ht and the morbidity index for coronary risk factors. (3) Nearly all overweight men and women (BMI≥25) had W/Ht≥0.5 (98.5% of men and 97.5% of women). None of the underweight subjects had W/Ht≥0.5. However, 45.5% of men and 28.3% of women of normal weight (BMI 18.5–<25) had W/Ht≥0.5. W/Ht, of all the indices investigated, was the best index for signaling metabolic risk in the normal-weight subjects as well as the overweight subjects. (4) Age- and BMI-adjusted odds ratios for multiple metabolic risks, and history of no habitual exercise were significantly higher in normal-weight men and women with W/Ht≥0.5 than in others of normal weight.CONCLUSIONS: Waist circumference is improved by relating it to height to categorized fat distribution of different genders and ages. W/Ht is a simple and practical anthropometric index to identify higher metabolic risks in normal and overweight Japanese men and women. More... »

PAGES

610-616

References to SciGraph publications

  • 2000-03. Health risks among Japanese men with moderate body mass index in INTERNATIONAL JOURNAL OF OBESITY
  • 1997-08. Association of anthropometric indices with elevated blood pressure in British adults in INTERNATIONAL JOURNAL OF OBESITY
  • <error retrieving object. in <ERROR RETRIEVING OBJECT
  • 2000-11-17. Waist circumference and waist-to-height ratio are better predictors of cardiovascular disease risk factors in children than body mass index in INTERNATIONAL JOURNAL OF OBESITY
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/sj.ijo.0802259

    DOI

    http://dx.doi.org/10.1038/sj.ijo.0802259

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1026699560

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/12704405


    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/2008/11", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Medical and Health Sciences", 
            "type": "DefinedTerm"
          }, 
          {
            "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"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Abdomen", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Adult", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Age Distribution", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Aged", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Body Height", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Body Mass Index", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Body Weight", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Energy Metabolism", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Female", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Humans", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Male", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Middle Aged", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Obesity", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Risk Factors", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "Medical Center of Health Science, Toranomon Hospital, Tokyo, Japan", 
              "id": "http://www.grid.ac/institutes/grid.410813.f", 
              "name": [
                "Medical Center of Health Science, Toranomon Hospital, Tokyo, Japan"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Hsieh", 
            "givenName": "S D", 
            "id": "sg:person.012116044212.03", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012116044212.03"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Department of Internal Medicine, Ebina General Hospital, Kanagawa, Japan", 
              "id": "http://www.grid.ac/institutes/grid.459497.2", 
              "name": [
                "Department of Internal Medicine, Ebina General Hospital, Kanagawa, Japan"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Yoshinaga", 
            "givenName": "H", 
            "id": "sg:person.01306237377.05", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01306237377.05"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Department of Public Health, Dokkyo University, School of Medicine, Tochigi, Japan", 
              "id": "http://www.grid.ac/institutes/grid.412039.d", 
              "name": [
                "Department of Public Health, Dokkyo University, School of Medicine, Tochigi, Japan"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Muto", 
            "givenName": "T", 
            "id": "sg:person.01201574117.36", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01201574117.36"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "sg:pub.10.1038/sj.ijo.0800459", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1031445973", 
              "https://doi.org/10.1038/sj.ijo.0800459"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/sj.ijo.0800651", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1018852292", 
              "https://doi.org/10.1038/sj.ijo.0800651"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/sj.ijo.0801157", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040914071", 
              "https://doi.org/10.1038/sj.ijo.0801157"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/sj.ijo.0801401", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1031785071", 
              "https://doi.org/10.1038/sj.ijo.0801401"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2003-04-17", 
        "datePublishedReg": "2003-04-17", 
        "description": "OBJECTIVE: The normal body mass index (BMI) range, as defined by the World Health Organization (WHO), is quite wide, and some people within this range may have excessive central fat accumulation and elevated metabolic risks. We hypothesize that the waist-to-height ratio (W/Ht), an effective index for assessing central fat distribution among Japanese people, can be used to identify subjects who are at higher metabolic risk within the normal as well as the overweight range.METHODS: We investigated: (1) the values of BMI, waist circumference, and W/Ht in 6141 men and 2137 women at various age intervals and calculated gender (female to male) ratios for all these anthropometric indices; (2) the relation between age and each anthropometric index, between age and morbidity index for coronary risk factors (sum of the scores for hyperglycemia, hypertension, hypertriglyceridemia, hypercholesterolemia, and low HDL cholesterol; one point for each condition if present), and between morbidity index for coronary risk factors and each anthropometric index; (3) the distributions of the subjects, using various proposed indices of waist circumference (those suggested by WHO, the Japan Society for the Study of Obesity, and the Asia-Pacific perspective), and our proposed boundary value, W/Ht 0.5, among the WHO categories based on BMI; (4) the metabolic risks (coronary risk factors, hyperuricemia, high \u03b3-glutamyltransferase, and fatty liver diagnosed by ultrasonography), and exercise habits among normal-weight subjects with W/Ht<0.5 or \u22650.5.RESULTS: (1) For the various anthropometric indices in all age groups, the gender ratio for W/Ht was closest to 1, indicating that a single set of values for W/Ht can be used for men and women. (2) Height correlated negatively with age. Among the anthropometric indices, only W/Ht correlated positively with age for both men and women, while age and all anthropometric indices, except height, correlated positively with the morbidity index for coronary risk factors. For both men and women, the highest correlation coefficient was between W/Ht and the morbidity index for coronary risk factors. (3) Nearly all overweight men and women (BMI\u226525) had W/Ht\u22650.5 (98.5% of men and 97.5% of women). None of the underweight subjects had W/Ht\u22650.5. However, 45.5% of men and 28.3% of women of normal weight (BMI 18.5\u2013<25) had W/Ht\u22650.5. W/Ht, of all the indices investigated, was the best index for signaling metabolic risk in the normal-weight subjects as well as the overweight subjects. (4) Age- and BMI-adjusted odds ratios for multiple metabolic risks, and history of no habitual exercise were significantly higher in normal-weight men and women with W/Ht\u22650.5 than in others of normal weight.CONCLUSIONS: Waist circumference is improved by relating it to height to categorized fat distribution of different genders and ages. W/Ht is a simple and practical anthropometric index to identify higher metabolic risks in normal and overweight Japanese men and women.", 
        "genre": "article", 
        "id": "sg:pub.10.1038/sj.ijo.0802259", 
        "isAccessibleForFree": false, 
        "isPartOf": [
          {
            "id": "sg:journal.1035838", 
            "issn": [
              "0307-0565", 
              "1476-5497"
            ], 
            "name": "International Journal of Obesity", 
            "publisher": "Springer Nature", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "5", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "27"
          }
        ], 
        "keywords": [
          "coronary risk factors", 
          "high metabolic risk", 
          "central fat distribution", 
          "metabolic risk", 
          "normal-weight subjects", 
          "anthropometric indices", 
          "morbidity index", 
          "risk factors", 
          "waist circumference", 
          "fat distribution", 
          "World Health Organization", 
          "normal weight", 
          "Japanese men", 
          "normal body mass index (BMI) range", 
          "body mass index range", 
          "elevated metabolic risk", 
          "multiple metabolic risks", 
          "overweight Japanese men", 
          "central fat accumulation", 
          "normal-weight men", 
          "values of BMI", 
          "gender ratio", 
          "overweight men", 
          "overweight subjects", 
          "overweight range", 
          "habitual exercise", 
          "WHO categories", 
          "exercise habits", 
          "odds ratio", 
          "fat accumulation", 
          "underweight subjects", 
          "age groups", 
          "height ratio", 
          "BMI", 
          "Health Organization", 
          "women", 
          "age", 
          "circumference", 
          "men", 
          "risk", 
          "age intervals", 
          "subjects", 
          "waist", 
          "good index", 
          "index", 
          "different genders", 
          "factors", 
          "Japanese people", 
          "practical index", 
          "correlation coefficient", 
          "weight", 
          "exercise", 
          "gender", 
          "people", 
          "group", 
          "habits", 
          "ratio", 
          "HT", 
          "interval", 
          "history", 
          "accumulation", 
          "values", 
          "high correlation coefficient", 
          "categories", 
          "height", 
          "index range", 
          "range", 
          "distribution", 
          "relation", 
          "organization", 
          "effective index", 
          "single set", 
          "coefficient", 
          "set", 
          "boundary values"
        ], 
        "name": "Waist-to-height ratio, a simple and practical index for assessing central fat distribution and metabolic risk in Japanese men and women", 
        "pagination": "610-616", 
        "productId": [
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1026699560"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1038/sj.ijo.0802259"
            ]
          }, 
          {
            "name": "pubmed_id", 
            "type": "PropertyValue", 
            "value": [
              "12704405"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1038/sj.ijo.0802259", 
          "https://app.dimensions.ai/details/publication/pub.1026699560"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2022-08-04T16:55", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-springernature-scigraph/baseset/20220804/entities/gbq_results/article/article_377.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "https://doi.org/10.1038/sj.ijo.0802259"
      }
    ]
     

    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.10.1038/sj.ijo.0802259'

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

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/sj.ijo.0802259'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/sj.ijo.0802259'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/sj.ijo.0802259'


     

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

    228 TRIPLES      21 PREDICATES      118 URIs      106 LITERALS      21 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1038/sj.ijo.0802259 schema:about N2b1f53906f0f47f1b9f624f2a2d3b523
    2 N31531512817f4e3f9744b59a71820859
    3 N32afb7deae59452db82ac8b7985a3edd
    4 N3313b7d13d9d45198aae264d0b6af7e4
    5 N4a06e9145301430e9959e6e5e0fa0255
    6 N641748d0f56444faa7facfe59bf9bd21
    7 N7f1d6037347c48ac8aac87ef314b52a8
    8 N971b37bd02134914b9421d62cb8bac2c
    9 Na17816021fa74abd92f652ba9d049abd
    10 Nb76f631ecd7f4bbdb2dee34abfeb762b
    11 Nc3ae903be12347dc852343c1f3028046
    12 Nd94ed85feee44725ba56ec5e3869ec55
    13 Ne009ee21b93b459dbac46565ccaac850
    14 Nf8006518f62d47f09b76290d16bcd3ba
    15 anzsrc-for:11
    16 anzsrc-for:1117
    17 schema:author N76838b82ffaf4734ad46253333f29075
    18 schema:citation sg:pub.10.1038/sj.ijo.0800459
    19 sg:pub.10.1038/sj.ijo.0800651
    20 sg:pub.10.1038/sj.ijo.0801157
    21 sg:pub.10.1038/sj.ijo.0801401
    22 schema:datePublished 2003-04-17
    23 schema:datePublishedReg 2003-04-17
    24 schema:description OBJECTIVE: The normal body mass index (BMI) range, as defined by the World Health Organization (WHO), is quite wide, and some people within this range may have excessive central fat accumulation and elevated metabolic risks. We hypothesize that the waist-to-height ratio (W/Ht), an effective index for assessing central fat distribution among Japanese people, can be used to identify subjects who are at higher metabolic risk within the normal as well as the overweight range.METHODS: We investigated: (1) the values of BMI, waist circumference, and W/Ht in 6141 men and 2137 women at various age intervals and calculated gender (female to male) ratios for all these anthropometric indices; (2) the relation between age and each anthropometric index, between age and morbidity index for coronary risk factors (sum of the scores for hyperglycemia, hypertension, hypertriglyceridemia, hypercholesterolemia, and low HDL cholesterol; one point for each condition if present), and between morbidity index for coronary risk factors and each anthropometric index; (3) the distributions of the subjects, using various proposed indices of waist circumference (those suggested by WHO, the Japan Society for the Study of Obesity, and the Asia-Pacific perspective), and our proposed boundary value, W/Ht 0.5, among the WHO categories based on BMI; (4) the metabolic risks (coronary risk factors, hyperuricemia, high γ-glutamyltransferase, and fatty liver diagnosed by ultrasonography), and exercise habits among normal-weight subjects with W/Ht<0.5 or ≥0.5.RESULTS: (1) For the various anthropometric indices in all age groups, the gender ratio for W/Ht was closest to 1, indicating that a single set of values for W/Ht can be used for men and women. (2) Height correlated negatively with age. Among the anthropometric indices, only W/Ht correlated positively with age for both men and women, while age and all anthropometric indices, except height, correlated positively with the morbidity index for coronary risk factors. For both men and women, the highest correlation coefficient was between W/Ht and the morbidity index for coronary risk factors. (3) Nearly all overweight men and women (BMI≥25) had W/Ht≥0.5 (98.5% of men and 97.5% of women). None of the underweight subjects had W/Ht≥0.5. However, 45.5% of men and 28.3% of women of normal weight (BMI 18.5–<25) had W/Ht≥0.5. W/Ht, of all the indices investigated, was the best index for signaling metabolic risk in the normal-weight subjects as well as the overweight subjects. (4) Age- and BMI-adjusted odds ratios for multiple metabolic risks, and history of no habitual exercise were significantly higher in normal-weight men and women with W/Ht≥0.5 than in others of normal weight.CONCLUSIONS: Waist circumference is improved by relating it to height to categorized fat distribution of different genders and ages. W/Ht is a simple and practical anthropometric index to identify higher metabolic risks in normal and overweight Japanese men and women.
    25 schema:genre article
    26 schema:isAccessibleForFree false
    27 schema:isPartOf N1927b6e4829d49b9ac7d23c6f4661874
    28 Nf315ef7d8e3d46e68693447b8932a66c
    29 sg:journal.1035838
    30 schema:keywords BMI
    31 HT
    32 Health Organization
    33 Japanese men
    34 Japanese people
    35 WHO categories
    36 World Health Organization
    37 accumulation
    38 age
    39 age groups
    40 age intervals
    41 anthropometric indices
    42 body mass index range
    43 boundary values
    44 categories
    45 central fat accumulation
    46 central fat distribution
    47 circumference
    48 coefficient
    49 coronary risk factors
    50 correlation coefficient
    51 different genders
    52 distribution
    53 effective index
    54 elevated metabolic risk
    55 exercise
    56 exercise habits
    57 factors
    58 fat accumulation
    59 fat distribution
    60 gender
    61 gender ratio
    62 good index
    63 group
    64 habits
    65 habitual exercise
    66 height
    67 height ratio
    68 high correlation coefficient
    69 high metabolic risk
    70 history
    71 index
    72 index range
    73 interval
    74 men
    75 metabolic risk
    76 morbidity index
    77 multiple metabolic risks
    78 normal body mass index (BMI) range
    79 normal weight
    80 normal-weight men
    81 normal-weight subjects
    82 odds ratio
    83 organization
    84 overweight Japanese men
    85 overweight men
    86 overweight range
    87 overweight subjects
    88 people
    89 practical index
    90 range
    91 ratio
    92 relation
    93 risk
    94 risk factors
    95 set
    96 single set
    97 subjects
    98 underweight subjects
    99 values
    100 values of BMI
    101 waist
    102 waist circumference
    103 weight
    104 women
    105 schema:name Waist-to-height ratio, a simple and practical index for assessing central fat distribution and metabolic risk in Japanese men and women
    106 schema:pagination 610-616
    107 schema:productId N231e5773af8643ffbe85c457741b9278
    108 N71588702efe8485b8c615f8c31186a5b
    109 Necaf8da400f04b33bb31345b4b1bff8c
    110 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026699560
    111 https://doi.org/10.1038/sj.ijo.0802259
    112 schema:sdDatePublished 2022-08-04T16:55
    113 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    114 schema:sdPublisher N1fbfb601e19a4943adf175c6fd4b9bfe
    115 schema:url https://doi.org/10.1038/sj.ijo.0802259
    116 sgo:license sg:explorer/license/
    117 sgo:sdDataset articles
    118 rdf:type schema:ScholarlyArticle
    119 N11f686ee62784cbabad899763f926765 rdf:first sg:person.01306237377.05
    120 rdf:rest Nc01390680582429784df06c9ca9544cf
    121 N1927b6e4829d49b9ac7d23c6f4661874 schema:issueNumber 5
    122 rdf:type schema:PublicationIssue
    123 N1fbfb601e19a4943adf175c6fd4b9bfe schema:name Springer Nature - SN SciGraph project
    124 rdf:type schema:Organization
    125 N231e5773af8643ffbe85c457741b9278 schema:name doi
    126 schema:value 10.1038/sj.ijo.0802259
    127 rdf:type schema:PropertyValue
    128 N2b1f53906f0f47f1b9f624f2a2d3b523 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    129 schema:name Middle Aged
    130 rdf:type schema:DefinedTerm
    131 N31531512817f4e3f9744b59a71820859 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    132 schema:name Abdomen
    133 rdf:type schema:DefinedTerm
    134 N32afb7deae59452db82ac8b7985a3edd schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    135 schema:name Age Distribution
    136 rdf:type schema:DefinedTerm
    137 N3313b7d13d9d45198aae264d0b6af7e4 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    138 schema:name Body Mass Index
    139 rdf:type schema:DefinedTerm
    140 N4a06e9145301430e9959e6e5e0fa0255 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    141 schema:name Adult
    142 rdf:type schema:DefinedTerm
    143 N641748d0f56444faa7facfe59bf9bd21 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    144 schema:name Body Height
    145 rdf:type schema:DefinedTerm
    146 N71588702efe8485b8c615f8c31186a5b schema:name pubmed_id
    147 schema:value 12704405
    148 rdf:type schema:PropertyValue
    149 N76838b82ffaf4734ad46253333f29075 rdf:first sg:person.012116044212.03
    150 rdf:rest N11f686ee62784cbabad899763f926765
    151 N7f1d6037347c48ac8aac87ef314b52a8 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    152 schema:name Risk Factors
    153 rdf:type schema:DefinedTerm
    154 N971b37bd02134914b9421d62cb8bac2c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    155 schema:name Obesity
    156 rdf:type schema:DefinedTerm
    157 Na17816021fa74abd92f652ba9d049abd schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    158 schema:name Aged
    159 rdf:type schema:DefinedTerm
    160 Nb76f631ecd7f4bbdb2dee34abfeb762b schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    161 schema:name Humans
    162 rdf:type schema:DefinedTerm
    163 Nc01390680582429784df06c9ca9544cf rdf:first sg:person.01201574117.36
    164 rdf:rest rdf:nil
    165 Nc3ae903be12347dc852343c1f3028046 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    166 schema:name Female
    167 rdf:type schema:DefinedTerm
    168 Nd94ed85feee44725ba56ec5e3869ec55 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    169 schema:name Male
    170 rdf:type schema:DefinedTerm
    171 Ne009ee21b93b459dbac46565ccaac850 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    172 schema:name Body Weight
    173 rdf:type schema:DefinedTerm
    174 Necaf8da400f04b33bb31345b4b1bff8c schema:name dimensions_id
    175 schema:value pub.1026699560
    176 rdf:type schema:PropertyValue
    177 Nf315ef7d8e3d46e68693447b8932a66c schema:volumeNumber 27
    178 rdf:type schema:PublicationVolume
    179 Nf8006518f62d47f09b76290d16bcd3ba schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    180 schema:name Energy Metabolism
    181 rdf:type schema:DefinedTerm
    182 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
    183 schema:name Medical and Health Sciences
    184 rdf:type schema:DefinedTerm
    185 anzsrc-for:1117 schema:inDefinedTermSet anzsrc-for:
    186 schema:name Public Health and Health Services
    187 rdf:type schema:DefinedTerm
    188 sg:journal.1035838 schema:issn 0307-0565
    189 1476-5497
    190 schema:name International Journal of Obesity
    191 schema:publisher Springer Nature
    192 rdf:type schema:Periodical
    193 sg:person.01201574117.36 schema:affiliation grid-institutes:grid.412039.d
    194 schema:familyName Muto
    195 schema:givenName T
    196 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01201574117.36
    197 rdf:type schema:Person
    198 sg:person.012116044212.03 schema:affiliation grid-institutes:grid.410813.f
    199 schema:familyName Hsieh
    200 schema:givenName S D
    201 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012116044212.03
    202 rdf:type schema:Person
    203 sg:person.01306237377.05 schema:affiliation grid-institutes:grid.459497.2
    204 schema:familyName Yoshinaga
    205 schema:givenName H
    206 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01306237377.05
    207 rdf:type schema:Person
    208 sg:pub.10.1038/sj.ijo.0800459 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031445973
    209 https://doi.org/10.1038/sj.ijo.0800459
    210 rdf:type schema:CreativeWork
    211 sg:pub.10.1038/sj.ijo.0800651 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018852292
    212 https://doi.org/10.1038/sj.ijo.0800651
    213 rdf:type schema:CreativeWork
    214 sg:pub.10.1038/sj.ijo.0801157 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040914071
    215 https://doi.org/10.1038/sj.ijo.0801157
    216 rdf:type schema:CreativeWork
    217 sg:pub.10.1038/sj.ijo.0801401 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031785071
    218 https://doi.org/10.1038/sj.ijo.0801401
    219 rdf:type schema:CreativeWork
    220 grid-institutes:grid.410813.f schema:alternateName Medical Center of Health Science, Toranomon Hospital, Tokyo, Japan
    221 schema:name Medical Center of Health Science, Toranomon Hospital, Tokyo, Japan
    222 rdf:type schema:Organization
    223 grid-institutes:grid.412039.d schema:alternateName Department of Public Health, Dokkyo University, School of Medicine, Tochigi, Japan
    224 schema:name Department of Public Health, Dokkyo University, School of Medicine, Tochigi, Japan
    225 rdf:type schema:Organization
    226 grid-institutes:grid.459497.2 schema:alternateName Department of Internal Medicine, Ebina General Hospital, Kanagawa, Japan
    227 schema:name Department of Internal Medicine, Ebina General Hospital, Kanagawa, Japan
    228 rdf:type schema:Organization
     




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


    ...