Predictors of low bone mass in postmenopausal Japanese women: a questionnaire-based study View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2009-02

AUTHORS

Fumihiro Omasu, Jun Kitagawa, Nobuyuki Ushiki, Kazuo Yamakami, Yutaka Sakurai, Yoshibumi Nakahara

ABSTRACT

The burgeoning costs of nursing care and medical treatment have become a serious problem for Japan, a country with an aging population and declining birthrate. Disease prevention and control of runaway health care costs are two important issues. We are interested in osteoporosis in the elderly. Thus, we aimed to establish predictive factors of low bone mass or fracture in postmenopausal elderly women by means of a simple questionnaire. Subjects were 107 postmenopausal Japanese women. All data in the present study were collected in 2006. The calcaneus stiffness index (SI) was determined by ultrasound bone densitometry. Urinary deoxypyridinoline (DPD), a marker of bone resorption, was measured. Factors related to bone loss and fracture were investigated by means of a questionnaire and tested by regression analysis and analysis of variance. The SI correlated significantly with age, years since menopause, weight, and the DPD level. Change in body weight did not influence the SI, but lumbar pain, height loss, and stoop did influence the SI. The SI was significantly low in subjects who had already suffered a fracture. Body mass index (BMI) was the strongest predictor of the SI. Low bone mass or fracture may be predicted in part with a simple questionnaire that addresses personal factors related to bone health. More... »

PAGES

61

References to SciGraph publications

  • 2006-06. Bone mineral density and estimated height loss based on patients’ recalls in OSTEOPOROSIS INTERNATIONAL
  • 2003-03. Effect of daily walking steps on ultrasound parameters of the calcaneus in elderly Japanese women in OSTEOPOROSIS INTERNATIONAL
  • 2003-07. Clinical usefulness of measurements of urinary deoxypyridinoline (DPD) in patients with postmenopausal osteoporosis receiving intermittent cyclical etidronate: advantage of free form of DPD over total DPD in predicting treatment efficacy in JOURNAL OF BONE AND MINERAL METABOLISM
  • 2007-05. Identifying osteoporosis in a primary care setting with quantitative ultrasound: relationship to anthropometric and lifestyle factors in JOURNAL OF BONE AND MINERAL METABOLISM
  • 2007-03. Biochemical markers of bone turnover may predict progression to osteoporosis in osteopenic women: the JPOS Cohort Study in JOURNAL OF BONE AND MINERAL METABOLISM
  • 2007-01. Use of clinical risk factors to identify postmenopausal women with vertebral fractures in OSTEOPOROSIS INTERNATIONAL
  • 2003-04. Rapid suppression of bone resorption and parathyroid hormone secretion by acute oral administration of calcium in healthy adult men in JOURNAL OF ENDOCRINOLOGICAL INVESTIGATION
  • 2007-01. Quantitative Ultrasound in Adults with Cystic Fibrosis: Correlation with Bone Mineral Density and Risk of Vertebral Fractures in CALCIFIED TISSUE INTERNATIONAL
  • 2004-11. The serum level of bone-specific alkaline phosphatase activity is associated with aortic calcification in osteoporosis patients in JOURNAL OF BONE AND MINERAL METABOLISM
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s10389-008-0216-7

    DOI

    http://dx.doi.org/10.1007/s10389-008-0216-7

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1039219767


    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": "National Defense Medical College", 
              "id": "https://www.grid.ac/institutes/grid.416614.0", 
              "name": [
                "Department of Preventive Medicine and Public Health, National Defense Medical College, 3-2 Namiki, 359-8513, Tokorozawa, Saitama, Japan"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Omasu", 
            "givenName": "Fumihiro", 
            "id": "sg:person.0731243426.67", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0731243426.67"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Tokyo Institute of Technology", 
              "id": "https://www.grid.ac/institutes/grid.32197.3e", 
              "name": [
                "Department of Human System Science, Graduate School of Decision Science and Technology, Tokyo Institute of Technology, 2-12-1-W9-7 Ohokayama, 152-8552, Tokyo, Meguro, Japan"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Kitagawa", 
            "givenName": "Jun", 
            "id": "sg:person.016053363621.22", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016053363621.22"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "name": [
                "Ushiki Women\u2019s Clinic, 2-3-79-5 Honcho, 189-0014, Tokyo, Higashimurayama, Japan"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Ushiki", 
            "givenName": "Nobuyuki", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "National Defense Medical College", 
              "id": "https://www.grid.ac/institutes/grid.416614.0", 
              "name": [
                "Department of Preventive Medicine and Public Health, National Defense Medical College, 3-2 Namiki, 359-8513, Tokorozawa, Saitama, Japan"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Yamakami", 
            "givenName": "Kazuo", 
            "id": "sg:person.01272132535.71", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01272132535.71"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "National Defense Medical College", 
              "id": "https://www.grid.ac/institutes/grid.416614.0", 
              "name": [
                "Department of Preventive Medicine and Public Health, National Defense Medical College, 3-2 Namiki, 359-8513, Tokorozawa, Saitama, Japan"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Sakurai", 
            "givenName": "Yutaka", 
            "id": "sg:person.01211254076.28", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01211254076.28"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Wayo Women's University", 
              "id": "https://www.grid.ac/institutes/grid.443771.2", 
              "name": [
                "Department of Health and Nutrition, School of Home Economics, Wayo Women\u2019s University, 2-3-1 Kohnodai, 272-8533, Chiba, Ichikawa, Japan"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Nakahara", 
            "givenName": "Yoshibumi", 
            "id": "sg:person.010101303261.13", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010101303261.13"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "https://doi.org/10.1359/jbmr.040818", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008076540"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/bf03345184", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1009198453", 
              "https://doi.org/10.1007/bf03345184"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1359/jbmr.060607", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1012085288"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.bone.2007.01.008", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1015427344"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/jcla.20166", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1015471887"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.jocd.2006.11.001", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1017413824"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.jbspin.2006.04.008", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019585684"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00223-006-0117-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021026559", 
              "https://doi.org/10.1007/s00223-006-0117-0"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1136/ard.2002.002287", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022332089"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00198-006-0209-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024399390", 
              "https://doi.org/10.1007/s00198-006-0209-8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00198-006-0209-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024399390", 
              "https://doi.org/10.1007/s00198-006-0209-8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1210/jc.2005-0086", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024680081"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00774-006-0741-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1026635834", 
              "https://doi.org/10.1007/s00774-006-0741-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00774-006-0741-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1026635834", 
              "https://doi.org/10.1007/s00774-006-0741-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.maturitas.2004.02.017", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1029726709"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00198-005-0046-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1034168988", 
              "https://doi.org/10.1007/s00198-005-0046-1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00198-005-0046-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1034168988", 
              "https://doi.org/10.1007/s00198-005-0046-1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.2114/jpa.23.49", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1034816049"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00774-004-0528-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1035120832", 
              "https://doi.org/10.1007/s00774-004-0528-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00774-006-0736-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036780160", 
              "https://doi.org/10.1007/s00774-006-0736-6"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00774-006-0736-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036780160", 
              "https://doi.org/10.1007/s00774-006-0736-6"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.4065/81.5.662", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037054673"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ypmed.2004.04.010", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1038633707"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.clinbiochem.2005.09.002", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045280543"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.clinbiochem.2005.09.002", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045280543"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1359/jbmr.061112", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1048583944"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00198-002-1339-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1050524528", 
              "https://doi.org/10.1007/s00198-002-1339-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0168-8227(02)00097-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1050532640"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1210/jc.2005-2818", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1064289030"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1210/jc.2006-0572", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1064289207"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00774-003-0412-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1075301967", 
              "https://doi.org/10.1007/s00774-003-0412-z"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://app.dimensions.ai/details/publication/pub.1077171271", 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/jn/136.6.1453", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1077241462"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://app.dimensions.ai/details/publication/pub.1077410547", 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2009-02", 
        "datePublishedReg": "2009-02-01", 
        "description": "The burgeoning costs of nursing care and medical treatment have become a serious problem for Japan, a country with an aging population and declining birthrate. Disease prevention and control of runaway health care costs are two important issues. We are interested in osteoporosis in the elderly. Thus, we aimed to establish predictive factors of low bone mass or fracture in postmenopausal elderly women by means of a simple questionnaire. Subjects were 107 postmenopausal Japanese women. All data in the present study were collected in 2006. The calcaneus stiffness index (SI) was determined by ultrasound bone densitometry. Urinary deoxypyridinoline (DPD), a marker of bone resorption, was measured. Factors related to bone loss and fracture were investigated by means of a questionnaire and tested by regression analysis and analysis of variance. The SI correlated significantly with age, years since menopause, weight, and the DPD level. Change in body weight did not influence the SI, but lumbar pain, height loss, and stoop did influence the SI. The SI was significantly low in subjects who had already suffered a fracture. Body mass index (BMI) was the strongest predictor of the SI. Low bone mass or fracture may be predicted in part with a simple questionnaire that addresses personal factors related to bone health.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1007/s10389-008-0216-7", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": false, 
        "isPartOf": [
          {
            "id": "sg:journal.1107285", 
            "issn": [
              "2198-1833", 
              "1613-2238"
            ], 
            "name": "Journal of Public Health", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "1", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "17"
          }
        ], 
        "name": "Predictors of low bone mass in postmenopausal Japanese women: a questionnaire-based study", 
        "pagination": "61", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "bad255bbb77d46755367df0f86788899140fefd7a34311173683e13096edf544"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/s10389-008-0216-7"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1039219767"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1007/s10389-008-0216-7", 
          "https://app.dimensions.ai/details/publication/pub.1039219767"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-11T14:31", 
        "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/v90/0000000373_0000000373/records_13096_00000001.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "http://link.springer.com/10.1007%2Fs10389-008-0216-7"
      }
    ]
     

    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.10.1007/s10389-008-0216-7'

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

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s10389-008-0216-7'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s10389-008-0216-7'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s10389-008-0216-7'


     

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

    197 TRIPLES      21 PREDICATES      56 URIs      19 LITERALS      7 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/s10389-008-0216-7 schema:about anzsrc-for:11
    2 anzsrc-for:1103
    3 schema:author N8174bbd189164e019c2d5d34e9b9f441
    4 schema:citation sg:pub.10.1007/bf03345184
    5 sg:pub.10.1007/s00198-002-1339-2
    6 sg:pub.10.1007/s00198-005-0046-1
    7 sg:pub.10.1007/s00198-006-0209-8
    8 sg:pub.10.1007/s00223-006-0117-0
    9 sg:pub.10.1007/s00774-003-0412-z
    10 sg:pub.10.1007/s00774-004-0528-9
    11 sg:pub.10.1007/s00774-006-0736-6
    12 sg:pub.10.1007/s00774-006-0741-9
    13 https://app.dimensions.ai/details/publication/pub.1077171271
    14 https://app.dimensions.ai/details/publication/pub.1077410547
    15 https://doi.org/10.1002/jcla.20166
    16 https://doi.org/10.1016/j.bone.2007.01.008
    17 https://doi.org/10.1016/j.clinbiochem.2005.09.002
    18 https://doi.org/10.1016/j.jbspin.2006.04.008
    19 https://doi.org/10.1016/j.jocd.2006.11.001
    20 https://doi.org/10.1016/j.maturitas.2004.02.017
    21 https://doi.org/10.1016/j.ypmed.2004.04.010
    22 https://doi.org/10.1016/s0168-8227(02)00097-9
    23 https://doi.org/10.1093/jn/136.6.1453
    24 https://doi.org/10.1136/ard.2002.002287
    25 https://doi.org/10.1210/jc.2005-0086
    26 https://doi.org/10.1210/jc.2005-2818
    27 https://doi.org/10.1210/jc.2006-0572
    28 https://doi.org/10.1359/jbmr.040818
    29 https://doi.org/10.1359/jbmr.060607
    30 https://doi.org/10.1359/jbmr.061112
    31 https://doi.org/10.2114/jpa.23.49
    32 https://doi.org/10.4065/81.5.662
    33 schema:datePublished 2009-02
    34 schema:datePublishedReg 2009-02-01
    35 schema:description The burgeoning costs of nursing care and medical treatment have become a serious problem for Japan, a country with an aging population and declining birthrate. Disease prevention and control of runaway health care costs are two important issues. We are interested in osteoporosis in the elderly. Thus, we aimed to establish predictive factors of low bone mass or fracture in postmenopausal elderly women by means of a simple questionnaire. Subjects were 107 postmenopausal Japanese women. All data in the present study were collected in 2006. The calcaneus stiffness index (SI) was determined by ultrasound bone densitometry. Urinary deoxypyridinoline (DPD), a marker of bone resorption, was measured. Factors related to bone loss and fracture were investigated by means of a questionnaire and tested by regression analysis and analysis of variance. The SI correlated significantly with age, years since menopause, weight, and the DPD level. Change in body weight did not influence the SI, but lumbar pain, height loss, and stoop did influence the SI. The SI was significantly low in subjects who had already suffered a fracture. Body mass index (BMI) was the strongest predictor of the SI. Low bone mass or fracture may be predicted in part with a simple questionnaire that addresses personal factors related to bone health.
    36 schema:genre research_article
    37 schema:inLanguage en
    38 schema:isAccessibleForFree false
    39 schema:isPartOf N9780bfc402fb45dc94d9dbd587540acc
    40 Nf599c5f1770440d09e89c382c63b3927
    41 sg:journal.1107285
    42 schema:name Predictors of low bone mass in postmenopausal Japanese women: a questionnaire-based study
    43 schema:pagination 61
    44 schema:productId N65055f1d391d4811b9459ff54d8be951
    45 Naf3478e7b58441b7aa9a7d234796f76f
    46 Nc5bff3fce7f14f5fb0dff20f5b2dd848
    47 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039219767
    48 https://doi.org/10.1007/s10389-008-0216-7
    49 schema:sdDatePublished 2019-04-11T14:31
    50 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    51 schema:sdPublisher Nedef2ca659254cea90bbd33305350f78
    52 schema:url http://link.springer.com/10.1007%2Fs10389-008-0216-7
    53 sgo:license sg:explorer/license/
    54 sgo:sdDataset articles
    55 rdf:type schema:ScholarlyArticle
    56 N1872d69fa7d34078a8f81f6beac136a5 rdf:first sg:person.010101303261.13
    57 rdf:rest rdf:nil
    58 N1a46a5949c2c42999c1a2c81e047a72b rdf:first sg:person.01272132535.71
    59 rdf:rest N5ecaef26d53d4d4dad93331f37e10d32
    60 N292b548a703c4379b5f024bb1b1bd4ec schema:affiliation N3960911f316a4b7ab3ff124cde054ecd
    61 schema:familyName Ushiki
    62 schema:givenName Nobuyuki
    63 rdf:type schema:Person
    64 N3960911f316a4b7ab3ff124cde054ecd schema:name Ushiki Women’s Clinic, 2-3-79-5 Honcho, 189-0014, Tokyo, Higashimurayama, Japan
    65 rdf:type schema:Organization
    66 N54f19a0689394797a5c95342369e7fab rdf:first N292b548a703c4379b5f024bb1b1bd4ec
    67 rdf:rest N1a46a5949c2c42999c1a2c81e047a72b
    68 N5ecaef26d53d4d4dad93331f37e10d32 rdf:first sg:person.01211254076.28
    69 rdf:rest N1872d69fa7d34078a8f81f6beac136a5
    70 N65055f1d391d4811b9459ff54d8be951 schema:name readcube_id
    71 schema:value bad255bbb77d46755367df0f86788899140fefd7a34311173683e13096edf544
    72 rdf:type schema:PropertyValue
    73 N8174bbd189164e019c2d5d34e9b9f441 rdf:first sg:person.0731243426.67
    74 rdf:rest N92cc0876e6f64188a0fba582dc9db1f3
    75 N92cc0876e6f64188a0fba582dc9db1f3 rdf:first sg:person.016053363621.22
    76 rdf:rest N54f19a0689394797a5c95342369e7fab
    77 N9780bfc402fb45dc94d9dbd587540acc schema:volumeNumber 17
    78 rdf:type schema:PublicationVolume
    79 Naf3478e7b58441b7aa9a7d234796f76f schema:name doi
    80 schema:value 10.1007/s10389-008-0216-7
    81 rdf:type schema:PropertyValue
    82 Nc5bff3fce7f14f5fb0dff20f5b2dd848 schema:name dimensions_id
    83 schema:value pub.1039219767
    84 rdf:type schema:PropertyValue
    85 Nedef2ca659254cea90bbd33305350f78 schema:name Springer Nature - SN SciGraph project
    86 rdf:type schema:Organization
    87 Nf599c5f1770440d09e89c382c63b3927 schema:issueNumber 1
    88 rdf:type schema:PublicationIssue
    89 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
    90 schema:name Medical and Health Sciences
    91 rdf:type schema:DefinedTerm
    92 anzsrc-for:1103 schema:inDefinedTermSet anzsrc-for:
    93 schema:name Clinical Sciences
    94 rdf:type schema:DefinedTerm
    95 sg:journal.1107285 schema:issn 1613-2238
    96 2198-1833
    97 schema:name Journal of Public Health
    98 rdf:type schema:Periodical
    99 sg:person.010101303261.13 schema:affiliation https://www.grid.ac/institutes/grid.443771.2
    100 schema:familyName Nakahara
    101 schema:givenName Yoshibumi
    102 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010101303261.13
    103 rdf:type schema:Person
    104 sg:person.01211254076.28 schema:affiliation https://www.grid.ac/institutes/grid.416614.0
    105 schema:familyName Sakurai
    106 schema:givenName Yutaka
    107 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01211254076.28
    108 rdf:type schema:Person
    109 sg:person.01272132535.71 schema:affiliation https://www.grid.ac/institutes/grid.416614.0
    110 schema:familyName Yamakami
    111 schema:givenName Kazuo
    112 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01272132535.71
    113 rdf:type schema:Person
    114 sg:person.016053363621.22 schema:affiliation https://www.grid.ac/institutes/grid.32197.3e
    115 schema:familyName Kitagawa
    116 schema:givenName Jun
    117 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016053363621.22
    118 rdf:type schema:Person
    119 sg:person.0731243426.67 schema:affiliation https://www.grid.ac/institutes/grid.416614.0
    120 schema:familyName Omasu
    121 schema:givenName Fumihiro
    122 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0731243426.67
    123 rdf:type schema:Person
    124 sg:pub.10.1007/bf03345184 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009198453
    125 https://doi.org/10.1007/bf03345184
    126 rdf:type schema:CreativeWork
    127 sg:pub.10.1007/s00198-002-1339-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050524528
    128 https://doi.org/10.1007/s00198-002-1339-2
    129 rdf:type schema:CreativeWork
    130 sg:pub.10.1007/s00198-005-0046-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034168988
    131 https://doi.org/10.1007/s00198-005-0046-1
    132 rdf:type schema:CreativeWork
    133 sg:pub.10.1007/s00198-006-0209-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024399390
    134 https://doi.org/10.1007/s00198-006-0209-8
    135 rdf:type schema:CreativeWork
    136 sg:pub.10.1007/s00223-006-0117-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021026559
    137 https://doi.org/10.1007/s00223-006-0117-0
    138 rdf:type schema:CreativeWork
    139 sg:pub.10.1007/s00774-003-0412-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1075301967
    140 https://doi.org/10.1007/s00774-003-0412-z
    141 rdf:type schema:CreativeWork
    142 sg:pub.10.1007/s00774-004-0528-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035120832
    143 https://doi.org/10.1007/s00774-004-0528-9
    144 rdf:type schema:CreativeWork
    145 sg:pub.10.1007/s00774-006-0736-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036780160
    146 https://doi.org/10.1007/s00774-006-0736-6
    147 rdf:type schema:CreativeWork
    148 sg:pub.10.1007/s00774-006-0741-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026635834
    149 https://doi.org/10.1007/s00774-006-0741-9
    150 rdf:type schema:CreativeWork
    151 https://app.dimensions.ai/details/publication/pub.1077171271 schema:CreativeWork
    152 https://app.dimensions.ai/details/publication/pub.1077410547 schema:CreativeWork
    153 https://doi.org/10.1002/jcla.20166 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015471887
    154 rdf:type schema:CreativeWork
    155 https://doi.org/10.1016/j.bone.2007.01.008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015427344
    156 rdf:type schema:CreativeWork
    157 https://doi.org/10.1016/j.clinbiochem.2005.09.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045280543
    158 rdf:type schema:CreativeWork
    159 https://doi.org/10.1016/j.jbspin.2006.04.008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019585684
    160 rdf:type schema:CreativeWork
    161 https://doi.org/10.1016/j.jocd.2006.11.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017413824
    162 rdf:type schema:CreativeWork
    163 https://doi.org/10.1016/j.maturitas.2004.02.017 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029726709
    164 rdf:type schema:CreativeWork
    165 https://doi.org/10.1016/j.ypmed.2004.04.010 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038633707
    166 rdf:type schema:CreativeWork
    167 https://doi.org/10.1016/s0168-8227(02)00097-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050532640
    168 rdf:type schema:CreativeWork
    169 https://doi.org/10.1093/jn/136.6.1453 schema:sameAs https://app.dimensions.ai/details/publication/pub.1077241462
    170 rdf:type schema:CreativeWork
    171 https://doi.org/10.1136/ard.2002.002287 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022332089
    172 rdf:type schema:CreativeWork
    173 https://doi.org/10.1210/jc.2005-0086 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024680081
    174 rdf:type schema:CreativeWork
    175 https://doi.org/10.1210/jc.2005-2818 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064289030
    176 rdf:type schema:CreativeWork
    177 https://doi.org/10.1210/jc.2006-0572 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064289207
    178 rdf:type schema:CreativeWork
    179 https://doi.org/10.1359/jbmr.040818 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008076540
    180 rdf:type schema:CreativeWork
    181 https://doi.org/10.1359/jbmr.060607 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012085288
    182 rdf:type schema:CreativeWork
    183 https://doi.org/10.1359/jbmr.061112 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048583944
    184 rdf:type schema:CreativeWork
    185 https://doi.org/10.2114/jpa.23.49 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034816049
    186 rdf:type schema:CreativeWork
    187 https://doi.org/10.4065/81.5.662 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037054673
    188 rdf:type schema:CreativeWork
    189 https://www.grid.ac/institutes/grid.32197.3e schema:alternateName Tokyo Institute of Technology
    190 schema:name Department of Human System Science, Graduate School of Decision Science and Technology, Tokyo Institute of Technology, 2-12-1-W9-7 Ohokayama, 152-8552, Tokyo, Meguro, Japan
    191 rdf:type schema:Organization
    192 https://www.grid.ac/institutes/grid.416614.0 schema:alternateName National Defense Medical College
    193 schema:name Department of Preventive Medicine and Public Health, National Defense Medical College, 3-2 Namiki, 359-8513, Tokorozawa, Saitama, Japan
    194 rdf:type schema:Organization
    195 https://www.grid.ac/institutes/grid.443771.2 schema:alternateName Wayo Women's University
    196 schema:name Department of Health and Nutrition, School of Home Economics, Wayo Women’s University, 2-3-1 Kohnodai, 272-8533, Chiba, Ichikawa, Japan
    197 rdf:type schema:Organization
     




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


    ...