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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Gender differences in the association between metabolic syndrome and periodontal disease: the Hisayama Study</title><author><name sortKey="Furuta, Michiko" sort="Furuta, Michiko" uniqKey="Furuta M" first="Michiko" last="Furuta">Michiko Furuta</name><affiliation><nlm:aff id="au1"><institution>Section of Preventive and Public Health Dentistry, Division of Oral Health, Growth and Development, Kyushu University Faculty of Dental Science</institution><addr-line>Fukuoka, Japan</addr-line></nlm:aff></affiliation></author><author><name sortKey="Shimazaki, Yoshihiro" sort="Shimazaki, Yoshihiro" uniqKey="Shimazaki Y" first="Yoshihiro" last="Shimazaki">Yoshihiro Shimazaki</name><affiliation><nlm:aff id="au1"><institution>Section of Preventive and Public Health Dentistry, Division of Oral Health, Growth and Development, Kyushu University Faculty of Dental Science</institution><addr-line>Fukuoka, Japan</addr-line></nlm:aff></affiliation></author><author><name sortKey="Takeshita, Toru" sort="Takeshita, Toru" uniqKey="Takeshita T" first="Toru" last="Takeshita">Toru Takeshita</name><affiliation><nlm:aff id="au1"><institution>Section of Preventive and Public Health Dentistry, Division of Oral Health, Growth and Development, Kyushu University Faculty of Dental Science</institution><addr-line>Fukuoka, Japan</addr-line></nlm:aff></affiliation></author><author><name sortKey="Shibata, Yukie" sort="Shibata, Yukie" uniqKey="Shibata Y" first="Yukie" last="Shibata">Yukie Shibata</name><affiliation><nlm:aff id="au1"><institution>Section of Preventive and Public Health Dentistry, Division of Oral Health, Growth and Development, Kyushu University Faculty of Dental Science</institution><addr-line>Fukuoka, Japan</addr-line></nlm:aff></affiliation></author><author><name sortKey="Akifusa, Sumio" sort="Akifusa, Sumio" uniqKey="Akifusa S" first="Sumio" last="Akifusa">Sumio Akifusa</name><affiliation><nlm:aff id="au2"><institution>Department of Health Management, School of Oral Health Science, Kyushu Dental College</institution><addr-line>Kitakyushu, Japan</addr-line></nlm:aff></affiliation></author><author><name sortKey="Eshima, Nobuoki" sort="Eshima, Nobuoki" uniqKey="Eshima N" first="Nobuoki" last="Eshima">Nobuoki Eshima</name><affiliation><nlm:aff id="au3"><institution>Department of Biostatistics, Faculty of Medicine, Oita University</institution><addr-line>Oita, Japan</addr-line></nlm:aff></affiliation></author><author><name sortKey="Kiyohara, Yutaka" sort="Kiyohara, Yutaka" uniqKey="Kiyohara Y" first="Yutaka" last="Kiyohara">Yutaka Kiyohara</name><affiliation><nlm:aff id="au4"><institution>Department of Environmental Medicine, Graduate School of Medical Sciences, Kyushu University</institution><addr-line>Fukuoka, Japan</addr-line></nlm:aff></affiliation></author><author><name sortKey="Ninomiya, Toshiharu" sort="Ninomiya, Toshiharu" uniqKey="Ninomiya T" first="Toshiharu" last="Ninomiya">Toshiharu Ninomiya</name><affiliation><nlm:aff id="au5"><institution>Department of Medicine and Clinical Science, Graduate School of Medical Sciences, Kyushu University</institution><addr-line>Fukuoka, Japan</addr-line></nlm:aff></affiliation></author><author><name sortKey="Hirakawa, Yoichiro" sort="Hirakawa, Yoichiro" uniqKey="Hirakawa Y" first="Yoichiro" last="Hirakawa">Yoichiro Hirakawa</name><affiliation><nlm:aff id="au4"><institution>Department of Environmental Medicine, Graduate School of Medical Sciences, Kyushu University</institution><addr-line>Fukuoka, Japan</addr-line></nlm:aff></affiliation></author><author><name sortKey="Mukai, Naoko" sort="Mukai, Naoko" uniqKey="Mukai N" first="Naoko" last="Mukai">Naoko Mukai</name><affiliation><nlm:aff id="au4"><institution>Department of Environmental Medicine, Graduate School of Medical Sciences, Kyushu University</institution><addr-line>Fukuoka, Japan</addr-line></nlm:aff></affiliation></author><author><name sortKey="Nagata, Masaharu" sort="Nagata, Masaharu" uniqKey="Nagata M" first="Masaharu" last="Nagata">Masaharu Nagata</name><affiliation><nlm:aff id="au4"><institution>Department of Environmental Medicine, Graduate School of Medical Sciences, Kyushu University</institution><addr-line>Fukuoka, Japan</addr-line></nlm:aff></affiliation></author><author><name sortKey="Yamashita, Yoshihisa" sort="Yamashita, Yoshihisa" uniqKey="Yamashita Y" first="Yoshihisa" last="Yamashita">Yoshihisa Yamashita</name><affiliation><nlm:aff id="au1"><institution>Section of Preventive and Public Health Dentistry, Division of Oral Health, Growth and Development, Kyushu University Faculty of Dental Science</institution><addr-line>Fukuoka, Japan</addr-line></nlm:aff></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">23829196</idno><idno type="pmc">3807558</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3807558</idno><idno type="RBID">PMC:3807558</idno><idno type="doi">10.1111/jcpe.12119</idno><date when="2013">2013</date><idno type="wicri:Area/Pmc/Corpus">003055</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">003055</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Gender differences in the association between metabolic syndrome and periodontal disease: the Hisayama Study</title><author><name sortKey="Furuta, Michiko" sort="Furuta, Michiko" uniqKey="Furuta M" first="Michiko" last="Furuta">Michiko Furuta</name><affiliation><nlm:aff id="au1"><institution>Section of Preventive and Public Health Dentistry, Division of Oral Health, Growth and Development, Kyushu University Faculty of Dental Science</institution><addr-line>Fukuoka, Japan</addr-line></nlm:aff></affiliation></author><author><name sortKey="Shimazaki, Yoshihiro" sort="Shimazaki, Yoshihiro" uniqKey="Shimazaki Y" first="Yoshihiro" last="Shimazaki">Yoshihiro Shimazaki</name><affiliation><nlm:aff id="au1"><institution>Section of Preventive and Public Health Dentistry, Division of Oral Health, Growth and Development, Kyushu University Faculty of Dental Science</institution><addr-line>Fukuoka, Japan</addr-line></nlm:aff></affiliation></author><author><name sortKey="Takeshita, Toru" sort="Takeshita, Toru" uniqKey="Takeshita T" first="Toru" last="Takeshita">Toru Takeshita</name><affiliation><nlm:aff id="au1"><institution>Section of Preventive and Public Health Dentistry, Division of Oral Health, Growth and Development, Kyushu University Faculty of Dental Science</institution><addr-line>Fukuoka, Japan</addr-line></nlm:aff></affiliation></author><author><name sortKey="Shibata, Yukie" sort="Shibata, Yukie" uniqKey="Shibata Y" first="Yukie" last="Shibata">Yukie Shibata</name><affiliation><nlm:aff id="au1"><institution>Section of Preventive and Public Health Dentistry, Division of Oral Health, Growth and Development, Kyushu University Faculty of Dental Science</institution><addr-line>Fukuoka, Japan</addr-line></nlm:aff></affiliation></author><author><name sortKey="Akifusa, Sumio" sort="Akifusa, Sumio" uniqKey="Akifusa S" first="Sumio" last="Akifusa">Sumio Akifusa</name><affiliation><nlm:aff id="au2"><institution>Department of Health Management, School of Oral Health Science, Kyushu Dental College</institution><addr-line>Kitakyushu, Japan</addr-line></nlm:aff></affiliation></author><author><name sortKey="Eshima, Nobuoki" sort="Eshima, Nobuoki" uniqKey="Eshima N" first="Nobuoki" last="Eshima">Nobuoki Eshima</name><affiliation><nlm:aff id="au3"><institution>Department of Biostatistics, Faculty of Medicine, Oita University</institution><addr-line>Oita, Japan</addr-line></nlm:aff></affiliation></author><author><name sortKey="Kiyohara, Yutaka" sort="Kiyohara, Yutaka" uniqKey="Kiyohara Y" first="Yutaka" last="Kiyohara">Yutaka Kiyohara</name><affiliation><nlm:aff id="au4"><institution>Department of Environmental Medicine, Graduate School of Medical Sciences, Kyushu University</institution><addr-line>Fukuoka, Japan</addr-line></nlm:aff></affiliation></author><author><name sortKey="Ninomiya, Toshiharu" sort="Ninomiya, Toshiharu" uniqKey="Ninomiya T" first="Toshiharu" last="Ninomiya">Toshiharu Ninomiya</name><affiliation><nlm:aff id="au5"><institution>Department of Medicine and Clinical Science, Graduate School of Medical Sciences, Kyushu University</institution><addr-line>Fukuoka, Japan</addr-line></nlm:aff></affiliation></author><author><name sortKey="Hirakawa, Yoichiro" sort="Hirakawa, Yoichiro" uniqKey="Hirakawa Y" first="Yoichiro" last="Hirakawa">Yoichiro Hirakawa</name><affiliation><nlm:aff id="au4"><institution>Department of Environmental Medicine, Graduate School of Medical Sciences, Kyushu University</institution><addr-line>Fukuoka, Japan</addr-line></nlm:aff></affiliation></author><author><name sortKey="Mukai, Naoko" sort="Mukai, Naoko" uniqKey="Mukai N" first="Naoko" last="Mukai">Naoko Mukai</name><affiliation><nlm:aff id="au4"><institution>Department of Environmental Medicine, Graduate School of Medical Sciences, Kyushu University</institution><addr-line>Fukuoka, Japan</addr-line></nlm:aff></affiliation></author><author><name sortKey="Nagata, Masaharu" sort="Nagata, Masaharu" uniqKey="Nagata M" first="Masaharu" last="Nagata">Masaharu Nagata</name><affiliation><nlm:aff id="au4"><institution>Department of Environmental Medicine, Graduate School of Medical Sciences, Kyushu University</institution><addr-line>Fukuoka, Japan</addr-line></nlm:aff></affiliation></author><author><name sortKey="Yamashita, Yoshihisa" sort="Yamashita, Yoshihisa" uniqKey="Yamashita Y" first="Yoshihisa" last="Yamashita">Yoshihisa Yamashita</name><affiliation><nlm:aff id="au1"><institution>Section of Preventive and Public Health Dentistry, Division of Oral Health, Growth and Development, Kyushu University Faculty of Dental Science</institution><addr-line>Fukuoka, Japan</addr-line></nlm:aff></affiliation></author></analytic><series><title level="j">Journal of Clinical Periodontology</title><idno type="ISSN">0303-6979</idno><idno type="eISSN">1600-051X</idno><imprint><date when="2013">2013</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p><bold>Aims</bold>: Periodontal disease and metabolic syndrome (MS) are more prevalent in males than in females. However, whether there is a gender difference in the association between these health conditions has not yet been investigated. This study examined the gender difference in this association, considering the definition of periodontal disease.</p><p><bold>Materials and Methods</bold>: We recruited 1040 males and 1330 females, aged ≥40 years, with at least ten teeth from subjects of the 2007 Hisayama health examination. We performed a logistic regression analysis with various definitions of periodontal disease the dependent variable and MS as the independent variable. Following the analysis, the data were reanalysed with the structural equations model.</p><p><bold>Results</bold>: The logistic regression analysis suggested a stronger association between periodontal disease and MS in females than that in males when periodontal disease was more severely defined. When we constructed the structural equations model in each gender, the model showed a good fit to the data of females, suggesting the association between periodontal disease and MS in females, but not in males.</p><p><bold>Conclusions</bold>: Gender differences seem to exist in the association between periodontal disease and MS; MS might show a stronger association with periodontal disease in females than in males.</p><p>Furuta M, Shimazaki Y, Takeshita T, Shibata Y, Akifusa S, Eshima N, Kiyohara Y, Ninomiya T, Hirakawa Y, Mukai N, Nagata M, Yamashita Y. Gender differences in the association between metabolic syndrome and periodontal disease: the Hisayama Study. J Clin Periodontol 2013; 40: 743–752. doi: <ext-link ext-link-type="doi" xlink:href="10.1111/jcpe.12119">10.1111/jcpe.12119</ext-link>.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Albandar, Jm" uniqKey="Albandar J">JM Albandar</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Alberti, Kg" uniqKey="Alberti K">KG Alberti</name></author><author><name sortKey="Eckel, Rh" uniqKey="Eckel R">RH Eckel</name></author><author><name sortKey="Grundy, Sm" uniqKey="Grundy S">SM Grundy</name></author><author><name sortKey="Zimmet, Pz" uniqKey="Zimmet P">PZ Zimmet</name></author><author><name sortKey="Cleeman, Ji" uniqKey="Cleeman J">JI Cleeman</name></author><author><name sortKey="Donato, Ka" uniqKey="Donato K">KA Donato</name></author><author><name sortKey="Fruchart, Jc" uniqKey="Fruchart J">JC Fruchart</name></author><author><name sortKey="James, Wp" uniqKey="James W">WP James</name></author><author><name 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<front><journal-meta><journal-id journal-id-type="nlm-ta">J Clin Periodontol</journal-id><journal-id journal-id-type="iso-abbrev">J. Clin. Periodontol</journal-id><journal-id journal-id-type="publisher-id">jcpe</journal-id><journal-title-group><journal-title>Journal of Clinical Periodontology</journal-title></journal-title-group><issn pub-type="ppub">0303-6979</issn><issn pub-type="epub">1600-051X</issn><publisher><publisher-name>Blackwell Publishing Ltd</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">23829196</article-id><article-id pub-id-type="pmc">3807558</article-id><article-id pub-id-type="doi">10.1111/jcpe.12119</article-id><article-categories><subj-group subj-group-type="heading"><subject>Periodontal Diseases</subject></subj-group></article-categories><title-group><article-title>Gender differences in the association between metabolic syndrome and periodontal disease: the Hisayama Study</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Furuta</surname><given-names>Michiko</given-names></name><xref ref-type="aff" rid="au1">1</xref></contrib><contrib contrib-type="author"><name><surname>Shimazaki</surname><given-names>Yoshihiro</given-names></name><xref ref-type="aff" rid="au1">1</xref></contrib><contrib contrib-type="author"><name><surname>Takeshita</surname><given-names>Toru</given-names></name><xref ref-type="aff" rid="au1">1</xref></contrib><contrib contrib-type="author"><name><surname>Shibata</surname><given-names>Yukie</given-names></name><xref ref-type="aff" rid="au1">1</xref></contrib><contrib contrib-type="author"><name><surname>Akifusa</surname><given-names>Sumio</given-names></name><xref ref-type="aff" rid="au2">2</xref></contrib><contrib contrib-type="author"><name><surname>Eshima</surname><given-names>Nobuoki</given-names></name><xref ref-type="aff" rid="au3">3</xref></contrib><contrib contrib-type="author"><name><surname>Kiyohara</surname><given-names>Yutaka</given-names></name><xref ref-type="aff" rid="au4">4</xref></contrib><contrib contrib-type="author"><name><surname>Ninomiya</surname><given-names>Toshiharu</given-names></name><xref ref-type="aff" rid="au5">5</xref></contrib><contrib contrib-type="author"><name><surname>Hirakawa</surname><given-names>Yoichiro</given-names></name><xref ref-type="aff" rid="au4">4</xref></contrib><contrib contrib-type="author"><name><surname>Mukai</surname><given-names>Naoko</given-names></name><xref ref-type="aff" rid="au4">4</xref></contrib><contrib contrib-type="author"><name><surname>Nagata</surname><given-names>Masaharu</given-names></name><xref ref-type="aff" rid="au4">4</xref></contrib><contrib contrib-type="author"><name><surname>Yamashita</surname><given-names>Yoshihisa</given-names></name><xref ref-type="corresp" rid="cor1"></xref><xref ref-type="aff" rid="au1">1</xref></contrib><aff id="au1"><label>1</label><institution>Section of Preventive and Public Health Dentistry, Division of Oral Health, Growth and Development, Kyushu University Faculty of Dental Science</institution><addr-line>Fukuoka, Japan</addr-line></aff><aff id="au2"><label>2</label><institution>Department of Health Management, School of Oral Health Science, Kyushu Dental College</institution><addr-line>Kitakyushu, Japan</addr-line></aff><aff id="au3"><label>3</label><institution>Department of Biostatistics, Faculty of Medicine, Oita University</institution><addr-line>Oita, Japan</addr-line></aff><aff id="au4"><label>4</label><institution>Department of Environmental Medicine, Graduate School of Medical Sciences, Kyushu University</institution><addr-line>Fukuoka, Japan</addr-line></aff><aff id="au5"><label>5</label><institution>Department of Medicine and Clinical Science, Graduate School of Medical Sciences, Kyushu University</institution><addr-line>Fukuoka, Japan</addr-line></aff></contrib-group><author-notes><corresp id="cor1">Address: Yoshihisa Yamashita, Section of Preventive and Public Health Dentistry, Division of Oral Health, Growth and Development, Kyushu University Faculty of Dental Science, 3-1-1 Maidashi, Higashi-ku Fukuoka 812-8582 Japan E-mail: <email>yoshi@dent.kyushu-u.ac.jp</email></corresp></author-notes><pub-date pub-type="ppub"><month>8</month><year>2013</year></pub-date><pub-date pub-type="epub"><day>08</day><month>7</month><year>2013</year></pub-date><volume>40</volume><issue>8</issue><fpage>743</fpage><lpage>752</lpage><history><date date-type="accepted"><day>01</day><month>5</month><year>2013</year></date></history><permissions><copyright-statement>Copyright © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd</copyright-statement><copyright-year>2013</copyright-year><license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/2.5/"><license-p>Re-use of this article is permitted in accordance with the Creative Commons Deed, Attribution 2.5, which does not permit commercial exploitation.</license-p></license></permissions><abstract><p><bold>Aims</bold>: Periodontal disease and metabolic syndrome (MS) are more prevalent in males than in females. However, whether there is a gender difference in the association between these health conditions has not yet been investigated. This study examined the gender difference in this association, considering the definition of periodontal disease.</p><p><bold>Materials and Methods</bold>: We recruited 1040 males and 1330 females, aged ≥40 years, with at least ten teeth from subjects of the 2007 Hisayama health examination. We performed a logistic regression analysis with various definitions of periodontal disease the dependent variable and MS as the independent variable. Following the analysis, the data were reanalysed with the structural equations model.</p><p><bold>Results</bold>: The logistic regression analysis suggested a stronger association between periodontal disease and MS in females than that in males when periodontal disease was more severely defined. When we constructed the structural equations model in each gender, the model showed a good fit to the data of females, suggesting the association between periodontal disease and MS in females, but not in males.</p><p><bold>Conclusions</bold>: Gender differences seem to exist in the association between periodontal disease and MS; MS might show a stronger association with periodontal disease in females than in males.</p><p>Furuta M, Shimazaki Y, Takeshita T, Shibata Y, Akifusa S, Eshima N, Kiyohara Y, Ninomiya T, Hirakawa Y, Mukai N, Nagata M, Yamashita Y. Gender differences in the association between metabolic syndrome and periodontal disease: the Hisayama Study. J Clin Periodontol 2013; 40: 743–752. doi: <ext-link ext-link-type="doi" xlink:href="10.1111/jcpe.12119">10.1111/jcpe.12119</ext-link>.</p></abstract><kwd-group><kwd>gender difference</kwd><kwd>metabolic syndrome</kwd><kwd>periodontal disease</kwd><kwd>structural equation model</kwd></kwd-group></article-meta></front><body><p>Recent epidemiological studies have revealed a significant association between periodontal disease and metabolic syndrome (MS) (<xref ref-type="bibr" rid="b45">Shimazaki et al. 2007</xref>, <xref ref-type="bibr" rid="b9">D’Aiuto et al. 2008</xref>, <xref ref-type="bibr" rid="b32">Morita et al. 2009</xref>, <xref ref-type="bibr" rid="b4">Andriankaja et al. 2010</xref>, <xref ref-type="bibr" rid="b7">Benguigui et al. 2010</xref>, <xref ref-type="bibr" rid="b50">Timonen et al. 2010</xref>, <xref ref-type="bibr" rid="b27">Kwon et al. 2011</xref>, <xref ref-type="bibr" rid="b21">Han et al. 2012</xref>). Much attention has been paid to this association because the rapidly increasing number of MS cases is a serious public health issue in most developed countries. Presently, it is unknown whether there is any causal relationship between the two health conditions; indeed, cohort study is only one (<xref ref-type="bibr" rid="b33">Morita et al. 2010</xref>) and interventional studies of the causal relationship are few.</p><p>On the other hand, using the National Cholesterol Education Programme Expert Panel Adult Treatment Panel III criteria (<xref ref-type="bibr" rid="b19">Grundy et al. 2004</xref>), the prevalence of MS was found to be higher in males than in females (<xref ref-type="bibr" rid="b36">Oh et al. 2004</xref>, <xref ref-type="bibr" rid="b40">Rutter et al. 2004</xref>, <xref ref-type="bibr" rid="b5">Arai et al. 2006</xref>). Among young and middle-aged adults, females have lower blood pressures and serum levels of triglycerides, higher insulin sensitivity, and less abdominal fat accumulation than males (<xref ref-type="bibr" rid="b14">Fernandez-Real et al. 1998</xref>, <xref ref-type="bibr" rid="b37">Razzouk & Muntner 2009</xref>). However, the protection conferred on females is not life-long and the prevalence of MS increases with age, especially after 50–60 years old (<xref ref-type="bibr" rid="b37">Razzouk & Muntner 2009</xref>). MS is a cluster of risk factors for the development of cardiovascular disease, including abdominal obesity, hypertension, insulin resistance, dyslipidaemia with high triglycerides and low high-density lipoprotein cholesterol (<xref ref-type="bibr" rid="b20">Grundy et al. 2005</xref>, <xref ref-type="bibr" rid="b2">Alberti et al. 2009</xref>). Several studies have revealed significant gender differences in cardiovascular disease incidence, showing a male-to- female ratio of 1.7–3.1 in subjects under 74 years of age (<xref ref-type="bibr" rid="b29">Lerner & Kannel 1986</xref>, <xref ref-type="bibr" rid="b24">Jousilahti et al. 1999</xref>, <xref ref-type="bibr" rid="b30">Levy et al. 2002</xref>) and the gender difference in MS is presumed to be one of the causes of that in cardiovascular disease (<xref ref-type="bibr" rid="b39">Regitz-Zagrosek et al. 2006</xref>).</p><p>A similar tendency of a higher incidence of disease in males than females is also the case for periodontal disease. In the Third National Health and Nutrition Examination Survey (NHANES III), the male-to-female prevalence ratios in adults were 1.1 for a probing depth of ≥3 mm, 1.4 for a probing depth of ≥4 mm, and 1.7 for a probing depth of ≥5 mm (<xref ref-type="bibr" rid="b1">Albandar 2002</xref>). Japanese (<xref ref-type="bibr" rid="b17">Furuta et al. 2010</xref>), Filipino (<xref ref-type="bibr" rid="b22">Horning et al. 1992</xref>), Brazilian (<xref ref-type="bibr" rid="b47">Susin et al. 2005</xref>) and Tanzanian surveys (<xref ref-type="bibr" rid="b34">Mumghamba et al. 1995</xref>) also showed that periodontal disease was more prevalent in males than in females.</p><p>It is clear that there is a gender difference in the prevalence of both MS and periodontal disease; thus, the association between periodontal disease and MS may also be expected to have a gender difference. However, most studies have not addressed this and did not use stratified analysis, which would allow determination of whether the relationship is unique to one gender, or even opposite in males and females. Moreover, in these cases, the overall analysis might reduce or compensate for actual differences between genders. To our knowledge, there are only two reports (<xref ref-type="bibr" rid="b4">Andriankaja et al. 2010</xref>, <xref ref-type="bibr" rid="b27">Kwon et al. 2011</xref>) of the relationship between MS and periodontal disease using stratified analyses. The results of these studies are contradictory; one showed a gender difference while the other did not. One reason for this discrepancy may be the different definition of periodontal disease. Thus, the purpose of this study was to explore the existence of a gender difference in the relationship between periodontal disease and MS in Japanese adults. We hypothesized that gender difference in this relationship might be affected by the definition of periodontal disease. Both multistep of dichotomous definition and continuous definition of periodontal disease were utilized to be clarified the above hypothesis in this study.</p><sec sec-type="materials|methods"><title>Materials and Methods</title><sec><title>Study population</title><p>This study was undertaken in 2007 in the town of Hisayama, which is a suburb of the Fukuoka metropolitan area in western Japan. The study population comprised 2861 participants aged 40–79 years (75.1% of all residents in that age group), who provided written consent to participate in the study, and underwent a comprehensive examination. Dental and medical examinations were performed on 2669 subjects, including edentulous individuals. In total, 299 subjects who had missing data or fewer than ten teeth were excluded, because it is difficult to assess their current periodontal health properly (<xref ref-type="bibr" rid="b41">Saito et al. 2004</xref>), and fewer teeth increase the variance of pocket depth (e.g. as the subjects have few teeth, the mean pocket depth deepens greatly on the number of teeth). Finally, 2370 subjects (1040 males, 1330 females) were used in this study.</p><p>The ethics committee of Kyushu University Faculty of Dental Science approved the study design, data collection methods and procedure for obtaining informed consent.</p></sec><sec><title>Oral examination</title><p>Periodontal status was assessed using pocket depth (PD) and clinical attachment loss (AL) on the mesio-buccal and mid-buccal sites for all teeth, except for third molars since these teeth when partially impacted frequently have pseudo-pockets, based on the NHANES III method. Because bleeding on probing (BOP) is a sensitive indicator of inflammation (<xref ref-type="bibr" rid="b18">Greenstein 1984</xref>), the percentage of teeth that bled on probing (%BOP) was also determined as an indicator for periodontal disease. Details of the periodontal examination have been described elsewhere (<xref ref-type="bibr" rid="b44">Shimazaki et al. 2011</xref>). Because the relationship with MS was similar in PD and clinical AL, but slightly stronger in PD than in clinical AL (<xref ref-type="bibr" rid="b45">Shimazaki et al. 2007</xref>), and there was a strong correlation between PD and clinical AL (Spearman correlation coefficient <italic>r</italic> = 0.85 for males and <italic>r</italic> = 0.87 for females), in this study, we used PD and %BOP as periodontal parameters to examine the association with MS.</p></sec><sec><title>General examination</title><p>Blood pressure was measured three consecutive times, after participants rested for at least 5 min., using a standard mercury sphygmomanometer, with the participants in the sitting position, and the average value was used for the analysis. A blood sample was collected from the antecubital vein in the morning after an overnight fast, and the serum cholesterol, triglycerides, and fasting plasma glucose levels were measured according to methods described previously (<xref ref-type="bibr" rid="b26">Kubo et al. 1999</xref>). Trained nurses measured the participants’ waist circumferences at the level of the umbilicus. MS was defined based on Joint Interim Societies (<xref ref-type="bibr" rid="b2">Alberti et al. 2009</xref>) and elevated waist circumference determination was based on the International Obesity Task Force central obesity criteria for Asians (<xref ref-type="bibr" rid="b52">World Health Organization 2000</xref>), according to the International Diabetes Federation’s suggestion that ethnic-specific cut-off values of waist circumference are appropriate for diagnosing MS (<xref ref-type="bibr" rid="b20">Grundy et al. 2005</xref>): elevated waist circumference (≥90 cm in males, and ≥80 cm in females), elevated triglycerides (≥150 mg/dl or drug treatment for elevated triglycerides), reduced HDL (<40 mg/dl in males and <50 mg/dl in females, or drug treatment for reduced HDL), elevated blood pressure (systolic blood pressure ≥130 mmHg or diastolic blood pressure ≥85 mmHg, or anti-hypertensive drug treatment) and elevated fasting glucose (≥100 mg/dl or drug treatment for elevated glucose).</p></sec><sec><title>Questionnaire</title><p>Information on smoking habits, alcohol intake, medication use and toothbrushing frequency was obtained using a self-administered questionnaire. Smoking habit was expressed as the Brinkman Index (number of cigarettes consumed per day multiplied by years of smoking) (<xref ref-type="bibr" rid="b8">Brinkman & Coates 1963</xref>). Alcohol intake was assessed on the basis of information about the usual weekly intake of alcoholic beverages, such as sake (rice wine), shochu (distilled liquor), beer or whisky. Moreover, alcohol intake was converted into a daily equivalent in terms of the number of <italic>go</italic>, a traditional Japanese unit of volume for <italic>sake</italic> (1 <italic>go</italic> = 0.18 l and contains 23 g of ethanol). In addition, subjects were asked about medication use, such anti-hypertensive, anti-hyperlipidemic and anti-diabetes drugs.</p></sec><sec><title>Statistical analysis</title><p>Although PD and MS components are continuous variables, to compare previous studies, the association between two variables was checked by categorized them. The chi-square test with significant level 0.05 was used for testing the differences in these variables between males and females. To illustrate the association between periodontal disease as dependent variable and MS components as independent variable when categorizing them in logistic regression analysis, the following criteria for periodontal disease were employed: mean PD cut-off values of ≥2.0, 2.5, 3.0 and 3.5 mm. In addition, we evaluated the interaction between gender and MS components with adjustment for age, smoking habits, alcohol intake, toothbrushing frequency and present number of teeth. We also tested for effect modification for periodontal disease by age, smoking habits and alcohol intake in each gender. Pearson’s correlation coefficient was used to assess the correlation among continuous PD, %BOP and MS component data. Of these, variables with high skewness or kurtosis (i.e. triglycerides and fasting glucose) were transformed with a natural log function. The SPSS software (ver. 19.0 for Windows; IBM SPSS Japan, Tokyo, Japan) was used for data analyses.</p><p>To examine quantitatively the association between periodontal disease and MS, we conducted structural equation modelling (SEM), using the M-plus statistical package. On the basis of our hypothesis, we examined the mutual relationship between periodontal disease and MS in SEM. SEM is a statistical method to analyse a correlation and causal relationship among a system of observed and latent variables. Latent variables are not directly observable, but are rather inferred its existence by properties of multiple observed variables.</p><p>First, we defined two latent variables in periodontal disease and MS (Model 1 in <xref ref-type="fig" rid="fig01">Fig. 1</xref>). The MS factor was represented by all MS components, and periodontal disease consisted of PD and %BOP. We used several variables, such as age, smoking habit, alcohol intake and toothbrushing frequency, as predictors of periodontal disease, the number of teeth and MS factors. The model included error terms which referred to all unobserved sources of variance, and residual terms which represented the variance not explained by the predictors. The correlation between residual terms describes the relationship between periodontal disease factor and MS factor while omitting the effects of the variables used as the predictors.</p><fig id="fig01" position="float"><label>Fig 1</label><caption><p>The metabolic syndrome (MS) single-factor model (Model 1). Rectangles indicate observed variables and ovals show latent constructs. Single-headed arrows indicate the directions of causal effects relating to the variables concerned, and the double-headed arrows imply the associations among the variables. The fit of Model 1 was <italic>χ</italic><sup>2</sup> (42) = 362.198; CFI = 0.807; RMSEA = 0.086 (0.078–0.094); SRMR = 0.055 in males and <italic>χ</italic><sup>2</sup> (42) = 358.831; CFI = 0.865; RMSEA = 0.075 (0.068–0.083); SRMR = 0.045 in females. The e1–e7 and r1–r3 designators refer to error terms and residual terms.</p></caption><graphic xlink:href="jcpe0040-0743-f1"></graphic></fig><p>Next, we tested an alternative MS factor structure. Because the MS components were highly inter-related, we used statistical analysis of clustering (factor analysis). Factor analysis is a technique for reducing the number of original variables into fewer summary factors. Absolute values of factor loadings ≥0.40 after orthogonal rotation of the correlation matrix minimizing the number of variables with high loading on each factor were commonly considered for factor interpretation. According to the results of the factor analysis, two latent factors in MS components, that is, MS factors (MSF) 1 and 2, could be identified. With regard to the medications variable, we used anti-hyperlipidemic drug use as “Medicine 1” and anti-hypertensive drug or anti-diabetes drug use as “Medicine 2.” We examined correlations among residual terms (r1–r4) in MSF 1, MSF2, periodontal disease factors and the number of teeth (<xref ref-type="fig" rid="fig02">Fig. 2</xref>).</p><fig id="fig02" position="float"><label>Fig 2</label><caption><p>The metabolic syndrome (MS) two-factor model (Model 2). MS factor 1 (MSF1) is represented by HDL and triglyceride (log TG), and MS factor 2 (MSF2) by waist circumstance (Waist), fasting glucose (log Glu) and systolic blood pressure (SBP). Periodontal disease is represented by mean PD and %BOP. “Medicine 1” indicates anti-hyperlipidemic drug use and “Medicine 2” is anti-hypertensive drug or anti-diabetes drug use. The e1–e7 and r1–r4 designators refer to error terms and residual terms.</p></caption><graphic xlink:href="jcpe0040-0743-f2"></graphic></fig><p>We used significance level 0.05 for the regression coefficients. The goodness-of-fit of the model used was assessed with a comparative fit index (CFI), a root-mean-square error of approximation (RMSEA), and the standardized root mean-square residual (SRMR). Values of close to 0.95 for the CFI, close to 0.06 for the RMSEA, and close to 0.08 for the SRMR are considered to indicate a good fit of the data to the model (<xref ref-type="bibr" rid="b23">Hu & Bentler 1999</xref>).</p></sec></sec><sec><title>Results</title><sec><title>Characteristics of subjects</title><p>Health characteristics of the subjects are summarized in <xref ref-type="table" rid="tbl1">Table 1</xref>. The overall mean PD was 2.5 ± 0.8 mm (mean ± SD) for males and 2.2 ± 0.7 mm for females. Females had a significantly lower mean PD (<italic>p</italic> < 0.001) and %BOP (<italic>p</italic> = 0.019) than males. There were significant differences in all MS components between males and females. There were 381 (36.6%) males with three or more of the five MS components and 451 (33.9%) females (<xref ref-type="table" rid="tbl1">Table 1</xref>).</p><table-wrap id="tbl1" position="float"><label>Table 1</label><caption><p>Demography of study subjects [<italic>n</italic> (%)]</p></caption><table frame="hsides" rules="groups"><thead><tr><th align="left" rowspan="1" colspan="1">Variable</th><th align="center" rowspan="1" colspan="1">Males (<italic>n</italic> = 1040)</th><th align="center" rowspan="1" colspan="1">Females (<italic>n</italic> = 1330)</th><th align="center" rowspan="1" colspan="1">All (<italic>n</italic> = 2370)</th><th align="right" rowspan="1" colspan="1"><italic>p</italic>-value</th></tr></thead><tbody><tr><td align="left" rowspan="1" colspan="1">%BOP<xref ref-type="table-fn" rid="tf1-1">*</xref></td><td align="center" rowspan="1" colspan="1">19.4 ± 20.9</td><td align="center" rowspan="1" colspan="1">17.5 ± 19.0</td><td align="center" rowspan="1" colspan="1">18.3 ± 19.9</td><td align="right" rowspan="1" colspan="1">0.019</td></tr><tr><td align="left" rowspan="1" colspan="1">Mean PD (mm)<xref ref-type="table-fn" rid="tf1-1">*</xref></td><td align="center" rowspan="1" colspan="1">2.5 ± 0.8</td><td align="center" rowspan="1" colspan="1">2.2 ± 0.7</td><td align="center" rowspan="1" colspan="1">2.3 ± 0.8</td><td align="right" rowspan="1" colspan="1"><0.001</td></tr><tr><td align="left" rowspan="1" colspan="1">High-density lipoprotein (HDL) (mg/dL)<xref ref-type="table-fn" rid="tf1-1">*</xref></td><td align="center" rowspan="1" colspan="1">61.0 ± 16.4</td><td align="center" rowspan="1" colspan="1">72.4 ± 17.7</td><td align="center" rowspan="1" colspan="1">67.4 ± 18.1</td><td align="right" rowspan="1" colspan="1"><0.001</td></tr><tr><td align="left" rowspan="1" colspan="1"> Normal (males ≥ 40, females ≥ 50)</td><td align="center" rowspan="1" colspan="1">979 (94.1)</td><td align="center" rowspan="1" colspan="1">1221 (91.8)</td><td align="center" rowspan="1" colspan="1">2200 (92.8)</td><td align="right" rowspan="1" colspan="1">0.029</td></tr><tr><td align="left" rowspan="1" colspan="1"> Reduced HDL (males < 40, females < 50)</td><td align="center" rowspan="1" colspan="1">61 (5.9)</td><td align="center" rowspan="1" colspan="1">109 (8.2)</td><td align="center" rowspan="1" colspan="1">170 (7.2)</td><td rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Triglycerides (mg/dl)<xref ref-type="table-fn" rid="tf1-1">*</xref></td><td align="center" rowspan="1" colspan="1">154.2 ± 140.0</td><td align="center" rowspan="1" colspan="1">107.5 ± 71.0</td><td align="center" rowspan="1" colspan="1">128.0 ± 109.3</td><td align="right" rowspan="1" colspan="1"><0.001</td></tr><tr><td align="left" rowspan="1" colspan="1"> Normal (<150)</td><td align="center" rowspan="1" colspan="1">628 (60.4)</td><td align="center" rowspan="1" colspan="1">962 (72.3)</td><td align="center" rowspan="1" colspan="1">1590 (67.1)</td><td align="right" rowspan="1" colspan="1"><0.001</td></tr><tr><td align="left" rowspan="1" colspan="1"> Elevated triglycerides (≥150)<xref ref-type="table-fn" rid="tf1-2">†</xref></td><td align="center" rowspan="1" colspan="1">412 (39.6)</td><td align="center" rowspan="1" colspan="1">368 (27.7)</td><td align="center" rowspan="1" colspan="1">780 (32.9)</td><td rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Systolic blood pressure (mmHg)<xref ref-type="table-fn" rid="tf1-1">*</xref></td><td align="center" rowspan="1" colspan="1">133.2 ± 17.7</td><td align="center" rowspan="1" colspan="1">127.9 ± 19.1</td><td align="center" rowspan="1" colspan="1">130.2 ± 18.7</td><td align="right" rowspan="1" colspan="1"><0.001</td></tr><tr><td align="left" rowspan="1" colspan="1">Diastolic blood pressure (mmHg)<xref ref-type="table-fn" rid="tf1-1">*</xref></td><td align="center" rowspan="1" colspan="1">82.3 ± 10.2</td><td align="center" rowspan="1" colspan="1">77.5 ± 10.8</td><td align="center" rowspan="1" colspan="1">79.6 ± 10.8</td><td align="right" rowspan="1" colspan="1"><0.001</td></tr><tr><td align="left" rowspan="1" colspan="1"> Normal (<130/<85)</td><td align="center" rowspan="1" colspan="1">381 (36.6)</td><td align="center" rowspan="1" colspan="1">648 (48.7)</td><td align="center" rowspan="1" colspan="1">1029 (43.4)</td><td align="right" rowspan="1" colspan="1"><0.001</td></tr><tr><td align="left" rowspan="1" colspan="1"> Elevated blood pressure (≥130/≥85)<xref ref-type="table-fn" rid="tf1-3">‡</xref></td><td align="center" rowspan="1" colspan="1">659 (63.4)</td><td align="center" rowspan="1" colspan="1">682 (51.3)</td><td align="center" rowspan="1" colspan="1">1341 (56.6)</td><td rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Waist circumference (cm)<xref ref-type="table-fn" rid="tf1-1">*</xref></td><td align="center" rowspan="1" colspan="1">86.8 ± 7.9</td><td align="center" rowspan="1" colspan="1">84.3 ± 10.2</td><td align="center" rowspan="1" colspan="1">85.4 ± 9.4</td><td align="right" rowspan="1" colspan="1"><0.001</td></tr><tr><td align="left" rowspan="1" colspan="1"> Normal (males < 90, females < 80)</td><td align="center" rowspan="1" colspan="1">671 (64.5)</td><td align="center" rowspan="1" colspan="1">442 (33.2)</td><td align="center" rowspan="1" colspan="1">1113 (47.0)</td><td align="right" rowspan="1" colspan="1"><0.001</td></tr><tr><td align="left" rowspan="1" colspan="1"> Elevated waist (males ≥ 90, females ≥ 80)</td><td align="center" rowspan="1" colspan="1">369 (35.5)</td><td align="center" rowspan="1" colspan="1">888 (66.8)</td><td align="center" rowspan="1" colspan="1">1257 (53.0)</td><td rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Fasting glucose (mg/dl)<xref ref-type="table-fn" rid="tf1-1">*</xref></td><td align="center" rowspan="1" colspan="1">108.6 ± 24.5</td><td align="center" rowspan="1" colspan="1">101.4 ± 19.4</td><td align="center" rowspan="1" colspan="1">104.5 ± 22.1</td><td align="right" rowspan="1" colspan="1"><0.001</td></tr><tr><td align="left" rowspan="1" colspan="1"> Normal (<100)</td><td align="center" rowspan="1" colspan="1">404 (38.8)</td><td align="center" rowspan="1" colspan="1">809 (60.8)</td><td align="center" rowspan="1" colspan="1">1213 (51.2)</td><td align="right" rowspan="1" colspan="1"><0.001</td></tr><tr><td align="left" rowspan="1" colspan="1"> Elevated fasting glucose (≥100)<xref ref-type="table-fn" rid="tf1-4">§</xref></td><td align="center" rowspan="1" colspan="1">636 (61.2)</td><td align="center" rowspan="1" colspan="1">551 (39.2)</td><td align="center" rowspan="1" colspan="1">1157 (48.8)</td><td rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Number of metabolic syndrome components</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"></td><td align="right" rowspan="1" colspan="1">0.033</td></tr><tr><td align="left" rowspan="1" colspan="1"> 0 component</td><td align="center" rowspan="1" colspan="1">127 (12.2)</td><td align="center" rowspan="1" colspan="1">211 (15.9)</td><td align="center" rowspan="1" colspan="1">338 (14.3)</td><td rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1"> 1 or 2 components</td><td align="center" rowspan="1" colspan="1">532 (51.2)</td><td align="center" rowspan="1" colspan="1">668 (50.2)</td><td align="center" rowspan="1" colspan="1">1200 (50.6)</td><td rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1"> ≥3 components (metabolic syndrome)</td><td align="center" rowspan="1" colspan="1">381 (36.6)</td><td align="center" rowspan="1" colspan="1">451 (33.9)</td><td align="center" rowspan="1" colspan="1">832 (35.1)</td><td rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Body mass index<xref ref-type="table-fn" rid="tf1-1">*</xref></td><td align="center" rowspan="1" colspan="1">23.7 ± 3.1</td><td align="center" rowspan="1" colspan="1">23.0 ± 3.6</td><td align="center" rowspan="1" colspan="1">23.3 ± 3.4</td><td align="right" rowspan="1" colspan="1"><0.001</td></tr><tr><td align="left" rowspan="1" colspan="1">Age</td><td align="center" rowspan="1" colspan="1">59.5 ± 10.1</td><td align="center" rowspan="1" colspan="1">59.5 ± 10.1</td><td align="center" rowspan="1" colspan="1">59.5 ± 10.1</td><td align="right" rowspan="1" colspan="1">0.972</td></tr><tr><td align="left" rowspan="1" colspan="1">Smoking habits (Brinkman index)</td><td align="center" rowspan="1" colspan="1">578.7 ± 511.6</td><td align="center" rowspan="1" colspan="1">44.6 ± 154.0</td><td align="center" rowspan="1" colspan="1">279.0 ± 445.4</td><td align="right" rowspan="1" colspan="1"><0.001</td></tr><tr><td align="left" rowspan="1" colspan="1">Alcohol intake (<italic>go</italic>/day)</td><td align="left" rowspan="1" colspan="1">1.5 ± 1.7</td><td align="left" rowspan="1" colspan="1">0.2 ± 0.5</td><td align="left" rowspan="1" colspan="1">0.8 ± 1.4</td><td align="left" rowspan="1" colspan="1"><0.001</td></tr><tr><td align="left" rowspan="1" colspan="1">Toothbrushing frequency per day</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"></td><td align="right" rowspan="1" colspan="1"><0.001</td></tr><tr><td align="left" rowspan="1" colspan="1"> No/1 time</td><td align="center" rowspan="1" colspan="1">484 (46.5)</td><td align="center" rowspan="1" colspan="1">271 (20.4)</td><td align="center" rowspan="1" colspan="1">755 (31.9)</td><td rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1"> 2 times</td><td align="center" rowspan="1" colspan="1">432 (41.5)</td><td align="center" rowspan="1" colspan="1">796 (59.8)</td><td align="center" rowspan="1" colspan="1">1228 (51.8)</td><td rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1"> More than 3 times</td><td align="center" rowspan="1" colspan="1">124 (11.9)</td><td align="center" rowspan="1" colspan="1">263 (19.8)</td><td align="center" rowspan="1" colspan="1">387 (16.3)</td><td rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1">Number of teeth present<xref ref-type="table-fn" rid="tf1-1">*</xref></td><td align="center" rowspan="1" colspan="1">24.6 ± 5.0</td><td align="center" rowspan="1" colspan="1">24.1 ± 4.8</td><td align="center" rowspan="1" colspan="1">24.3 ± 4.9</td><td align="right" rowspan="1" colspan="1">0.015</td></tr></tbody></table><table-wrap-foot><fn id="tf1-1"><label>*</label><p>Mean ± SD.</p></fn><fn id="tf1-2"><label>†</label><p>Triglycerides ≥ 150 mg/dl or drug treatment for dyslipidaemia.</p></fn><fn id="tf1-3"><label>‡</label><p>Systolic blood pressure ≥ 130 mmHg or diastolic blood pressure ≥ 85 mmHg, or anti-hypertensive drug treatment.</p></fn><fn id="tf1-4"><label>§</label><p>Fasting glucose ≥ 100 mg/dl or drug treatment for elevated glucose.</p></fn></table-wrap-foot></table-wrap></sec><sec><title>Logistic regression analysis</title><p>For the analysis technique, we need to determine the direction of the relationship in the logistic regression analysis. Therefore, we provisionally defined periodontal disease and MS as dependent and independent variables respectively. At first, we evaluated the effect of varying criteria of periodontitis (the mean PD ≥2.0, 2.5, 3.0 or 3.5 mm) on its association with MS. Setting the periodontal disease as a binary response variable, that is, 1 for positive and 0 for negative, a logistic regression analysis was performed, where explanatory variables are MS components, age, smoking habits, etc. The crude and adjusted odds ratios with respect to MS components for the above different criteria of periodontal diseases were estimated as in <xref ref-type="table" rid="tbl2">Table 2</xref>. In the results in females, three or more MS components were associated significantly with periodontal disease, defined by criteria mean PD ≥2.0, 2.5, 3.0 and 3.5 mm, compared with those with no MS components. In males, there was significant association between MS and periodontal disease, defined by criteria mean PD ≥2.0 and 2.5 mm. When we investigated the interaction between gender and MS components, the interaction term consisting of gender and three or more MS components was significant (<italic>p</italic> = 0.036) for periodontal disease defined by a mean PD ≥3.0 mm. In addition, in performing tests of interaction for periodontal disease among age, smoking habits and alcohol intake (interaction terms: age × smoking, age × alcohol, smoking × alcohol, age × smoking × alcohol), there was no statistically significant effects in each gender.</p><table-wrap id="tbl2" position="float"><label>Table 2</label><caption><p>Periodontal disease odds ratios according to mean PD cut-off value in males and females</p></caption><table frame="hsides" rules="groups"><thead><tr><th align="left" rowspan="2" colspan="1">Accumulation of metabolic components</th><th align="center" colspan="3" rowspan="1">Males</th><th align="center" colspan="3" rowspan="1">Females</th><th align="center" rowspan="2" colspan="1">Interaction for gender × metabolic component <italic>p</italic>-value<xref ref-type="table-fn" rid="tf2-2">†</xref></th></tr><tr><th align="left" rowspan="1" colspan="1">No. of subjects with periodontal disease</th><th align="center" colspan="2" rowspan="1">Crude OR (95% CI)</th><th align="center" colspan="2" rowspan="1">Adjusted OR<xref ref-type="table-fn" rid="tf2-1">*</xref> (95% CI)</th><th align="left" rowspan="1" colspan="1">No. of subjects with periodontal disease</th><th align="center" colspan="2" rowspan="1">Crude OR (95% CI)</th><th align="center" colspan="2" rowspan="1">Adjusted OR<xref ref-type="table-fn" rid="tf2-1">*</xref> (95% CI)</th></tr></thead><tbody><tr><td align="left" rowspan="1" colspan="1">Mean PD ≥ 2.0 mm</td><td align="char" char="." rowspan="1" colspan="1">788 (75.6)</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"></td><td align="char" char="." rowspan="1" colspan="1">782 (58.8)</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"></td></tr><tr><td align="left" colspan="12" rowspan="1"> Number of metabolic components</td></tr><tr><td align="left" rowspan="1" colspan="1"> 0 component</td><td align="char" char="." rowspan="1" colspan="1">86 (67.2)</td><td align="left" rowspan="1" colspan="1">1</td><td rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">1</td><td rowspan="1" colspan="1"></td><td align="char" char="." rowspan="1" colspan="1">99 (46.9)</td><td align="left" rowspan="1" colspan="1">1</td><td rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">1</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1"> 1 and 2 components</td><td align="char" char="." rowspan="1" colspan="1">392 (73.5)</td><td align="left" rowspan="1" colspan="1">1.36</td><td align="char" char="." rowspan="1" colspan="1">(0.90–2.06)</td><td align="left" rowspan="1" colspan="1">1.18</td><td align="char" char="." rowspan="1" colspan="1">(0.77–1.82)</td><td align="char" char="." rowspan="1" colspan="1">383 (57.2)</td><td align="left" rowspan="1" colspan="1">1.52</td><td align="char" char="." rowspan="1" colspan="1">(1.11–2.07)</td><td align="left" rowspan="1" colspan="1">1.28</td><td align="char" char="." rowspan="1" colspan="1">(0.93–1.78)</td><td align="char" char="." rowspan="1" colspan="1">0.553</td></tr><tr><td align="left" rowspan="1" colspan="1"> ≥3 components (metabolic syndrome)</td><td align="char" char="." rowspan="1" colspan="1">310 (81.4)</td><td align="left" rowspan="1" colspan="1">2.13</td><td align="char" char="." rowspan="1" colspan="1">(1.36–3.35)</td><td align="left" rowspan="1" colspan="1">1.64</td><td align="char" char="." rowspan="1" colspan="1">(1.02–2.64)</td><td align="char" char="." rowspan="1" colspan="1">300 (66.5)</td><td align="left" rowspan="1" colspan="1">2.25</td><td align="char" char="." rowspan="1" colspan="1">(1.61–3.14)</td><td align="left" rowspan="1" colspan="1">1.55</td><td align="char" char="." rowspan="1" colspan="1">(1.07–2.24)</td><td align="char" char="." rowspan="1" colspan="1">0.790</td></tr><tr><td align="left" rowspan="1" colspan="1">Mean PD ≥ 2.5 mm</td><td align="char" char="." rowspan="1" colspan="1">408 (39.2)</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"></td><td align="char" char="." rowspan="1" colspan="1">334 (25.1)</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"></td></tr><tr><td align="left" colspan="12" rowspan="1"> Number of metabolic components</td></tr><tr><td align="left" rowspan="1" colspan="1"> 0 component</td><td align="char" char="." rowspan="1" colspan="1">33 (25.8)</td><td align="left" rowspan="1" colspan="1">1</td><td rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">1</td><td rowspan="1" colspan="1"></td><td align="char" char="." rowspan="1" colspan="1">31 (14.7)</td><td align="left" rowspan="1" colspan="1">1</td><td rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">1</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1"> 1 and 2 components</td><td align="char" char="." rowspan="1" colspan="1">198 (37.1)</td><td align="left" rowspan="1" colspan="1">1.70</td><td align="char" char="." rowspan="1" colspan="1">(1.10–2.62)</td><td align="left" rowspan="1" colspan="1">1.41</td><td align="char" char="." rowspan="1" colspan="1">(0.90–2.22)</td><td align="char" char="." rowspan="1" colspan="1">155 (23.2)</td><td align="left" rowspan="1" colspan="1">1.75</td><td align="char" char="." rowspan="1" colspan="1">(1.15–2.67)</td><td align="left" rowspan="1" colspan="1">1.45</td><td align="char" char="." rowspan="1" colspan="1">(0.93–2.25)</td><td align="char" char="." rowspan="1" colspan="1">0.700</td></tr><tr><td align="left" rowspan="1" colspan="1"> ≥3 components (metabolic syndrome)</td><td align="char" char="." rowspan="1" colspan="1">177 (43.3)</td><td align="left" rowspan="1" colspan="1">2.50</td><td align="char" char="." rowspan="1" colspan="1">(1.60–3.90)</td><td align="left" rowspan="1" colspan="1">1.86</td><td align="char" char="." rowspan="1" colspan="1">(1.17–2.97)</td><td align="char" char="." rowspan="1" colspan="1">148 (32.8)</td><td align="left" rowspan="1" colspan="1">2.84</td><td align="char" char="." rowspan="1" colspan="1">(1.85–4.36)</td><td align="left" rowspan="1" colspan="1">1.87</td><td align="char" char="." rowspan="1" colspan="1">(1.17–2.98)</td><td align="char" char="." rowspan="1" colspan="1">0.640</td></tr><tr><td align="left" rowspan="1" colspan="1">Mean PD ≥ 3.0 mm</td><td align="char" char="." rowspan="1" colspan="1">225 (21.6)</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"></td><td align="char" char="." rowspan="1" colspan="1">137 (10.3)</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"></td></tr><tr><td align="left" colspan="12" rowspan="1"> Number of metabolic components</td></tr><tr><td align="left" rowspan="1" colspan="1"> 0 component</td><td align="char" char="." rowspan="1" colspan="1">19 (14.8)</td><td align="left" rowspan="1" colspan="1">1</td><td rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">1</td><td rowspan="1" colspan="1"></td><td align="char" char="." rowspan="1" colspan="1">9 (4.3)</td><td align="left" rowspan="1" colspan="1">1</td><td rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">1</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1"> 1 and 2 components</td><td align="char" char="." rowspan="1" colspan="1">117 (22.0)</td><td align="left" rowspan="1" colspan="1">1.60</td><td align="char" char="." rowspan="1" colspan="1">(0.94–2.72)</td><td align="left" rowspan="1" colspan="1">1.36</td><td align="char" char="." rowspan="1" colspan="1">(0.78–2.35)</td><td align="char" char="." rowspan="1" colspan="1">59 (8.8)</td><td align="left" rowspan="1" colspan="1">2.17</td><td align="char" char="." rowspan="1" colspan="1">(1.06–4.46)</td><td align="left" rowspan="1" colspan="1">2.00</td><td align="char" char="." rowspan="1" colspan="1">(0.95–4.21)</td><td align="char" char="." rowspan="1" colspan="1">0.303</td></tr><tr><td align="left" rowspan="1" colspan="1"> ≥3 components (metabolic syndrome)</td><td align="char" char="." rowspan="1" colspan="1">89 (23.4)</td><td align="left" rowspan="1" colspan="1">1.73</td><td align="char" char="." rowspan="1" colspan="1">(1.00–2.98)</td><td align="left" rowspan="1" colspan="1">1.32</td><td align="char" char="." rowspan="1" colspan="1">(0.75–2.34)</td><td align="char" char="." rowspan="1" colspan="1">69 (15.3)</td><td align="left" rowspan="1" colspan="1">4.05</td><td align="char" char="." rowspan="1" colspan="1">(1.98–8.29)</td><td align="left" rowspan="1" colspan="1">3.06</td><td align="char" char="." rowspan="1" colspan="1">(1.42–6.59)</td><td align="char" char="." rowspan="1" colspan="1">0.036</td></tr><tr><td align="left" rowspan="1" colspan="1">Mean PD ≥ 3.5 mm</td><td align="char" char="." rowspan="1" colspan="1">116 (11.1)</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"></td><td align="char" char="." rowspan="1" colspan="1">63 (4.7)</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"></td></tr><tr><td align="left" colspan="12" rowspan="1"> Number of metabolic components</td></tr><tr><td align="left" rowspan="1" colspan="1"> 0 component</td><td align="char" char="." rowspan="1" colspan="1">11 (8.6)</td><td align="left" rowspan="1" colspan="1">1</td><td rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">1</td><td rowspan="1" colspan="1"></td><td align="char" char="." rowspan="1" colspan="1">3 (1.4)</td><td align="left" rowspan="1" colspan="1">1</td><td rowspan="1" colspan="1"></td><td align="left" rowspan="1" colspan="1">1</td><td rowspan="1" colspan="1"></td><td rowspan="1" colspan="1"></td></tr><tr><td align="left" rowspan="1" colspan="1"> 1 and 2 components</td><td align="char" char="." rowspan="1" colspan="1">56 (10.5)</td><td align="left" rowspan="1" colspan="1">1.25</td><td align="char" char="." rowspan="1" colspan="1">(0.63–2.46)</td><td align="left" rowspan="1" colspan="1">1.03</td><td align="char" char="." rowspan="1" colspan="1">(0.51–2.07)</td><td align="char" char="." rowspan="1" colspan="1">28 (4.2)</td><td align="left" rowspan="1" colspan="1">3.03</td><td align="char" char="." rowspan="1" colspan="1">(0.91–10.06)</td><td align="left" rowspan="1" colspan="1">2.59</td><td align="char" char="." rowspan="1" colspan="1">(0.76–8.86)</td><td align="char" char="." rowspan="1" colspan="1">0.133</td></tr><tr><td align="left" rowspan="1" colspan="1"> ≥3 components (metabolic syndrome)</td><td align="char" char="." rowspan="1" colspan="1">49 (12.9)</td><td align="left" rowspan="1" colspan="1">1.57</td><td align="char" char="." rowspan="1" colspan="1">(0.79–3.12)</td><td align="left" rowspan="1" colspan="1">1.21</td><td align="char" char="." rowspan="1" colspan="1">(0.59–2.49)</td><td align="char" char="." rowspan="1" colspan="1">32 (7.1)</td><td align="left" rowspan="1" colspan="1">5.30</td><td align="char" char="." rowspan="1" colspan="1">(1.60–17.49)</td><td align="left" rowspan="1" colspan="1">3.60</td><td align="char" char="." rowspan="1" colspan="1">(1.03–12.61)</td><td align="char" char="." rowspan="1" colspan="1">0.066</td></tr></tbody></table><table-wrap-foot><fn><p>Logistic regression analysis with periodontal disease (mean PD cut-off value ≥2.0, 2.5, 3.0, 3.5 or 4.0 mm) as the dependent variable and accumulation of metabolic components as the independent variable.</p></fn><fn id="tf2-1"><label>*</label><p>Adjusted for age, smoking habits, alcohol intake, toothbrushing frequency and present number of teeth.</p></fn><fn id="tf2-2"><label>†</label><p><italic>p</italic>-value of the interaction term consisting of gender and MS components were calculated by using gender, MS components, age, smoking habits, alcohol intake, toothbrushing frequency and present number of teeth as explanatory variables. The interaction term was created by multiplying gender variable (0 = male, 1 = female) by MS components variable (0 = 0 component, 1 = 1 and 2 component, 2 = 3 or more components).</p></fn></table-wrap-foot></table-wrap><p>In this study, the percentage of subjects with elevated fasting glucose (i.e. fasting glucose ≥100 mg/dl or drug treatment for elevated glucose) were significantly higher in males than in females (61.2% males, 39.2% females). Since males were more likely to have drug treatment than females (9.0% males, 5.6% females), it was possible that drug treatment affected elevated fasting glucose as one of MS components. Therefore, we evaluated the effect of MS components on periodontal disease, while adjusting for drug treatment, age, smoking habits, etc., in Table S2. The result was similar to that previously adjusted for drug treatment.</p><p>We found gender difference in the association between MS and periodontal disease defined by a mean PD ≥3.0 or 3.5 mm, but not for periodontal disease defined by a mean PD ≥2.0 or 2.5 mm suggesting that the result from the logistic regression analysis depends on different categorical definition of periodontal disease (i.e. different mean PD cut-off values). Therefore, it is desirable to treat PD as a continuous variable and we utilized SEM, an analytical technique, for continuous variables to assess the association between periodontal disease and MS qualitatively.</p></sec><sec><title>Factor analysis of MS components and structural equation modelling</title><p>To examine the association between periodontal disease and MS, the correlation coefficients among the manifest variables for assessing them were estimated (Table S1). While all of the MS components were statistically correlated with PD and %BOP in females at the level of significant 0.05, some MS components were not in males. Systolic blood pressure was used as blood pressure in further analyses due to the strong correlation between systolic and diastolic blood pressure (Spearman correlation coefficient <italic>r</italic> = 0.87 for males and <italic>r</italic> = 0.89 for females). Although the correlation analysis was performed for the manifest variables concerning periodontal disease and MS, we regarded the states of them as latent variables, and to evaluate the correlations among the latent variables a SEM approach was carried out.</p><p>First, we considered the MS single-factor model (Model 1) shown in <xref ref-type="fig" rid="fig01">Fig. 1</xref>. This path system has two latent variables, that is, “MS factor” and “Periodontal disease.” Analysing the data of males and females, Model 1 did not show good fits to both of males and females data sets, that is, CFI = 0.807 for males and CFI = 0.865 for females.</p><p>Second, to construct an alternative MS factor structure, factor analysis of MS components was carried out. According to <xref ref-type="table" rid="tbl3">Table 3</xref>, the results in males and females are similar, and two factors, which are referred to as MSF1 and 2, were extracted from the male’s and female’s data respectively. Considering the factor loadings, MSF1 is related to HDL and log triglycerides, and MSF2 relates systolic blood pressure, waist and log fasting glucose.</p><table-wrap id="tbl3" position="float"><label>Table 3</label><caption><p>Factor analysis of metabolic components, factors and factor loadings</p></caption><table frame="hsides" rules="groups"><thead><tr><th rowspan="1" colspan="1"></th><th align="center" colspan="2" rowspan="1">Males</th><th align="center" colspan="2" rowspan="1">Females</th></tr><tr><th align="center" rowspan="1" colspan="1">MSF1</th><th align="center" rowspan="1" colspan="1">MSF2</th><th align="center" rowspan="1" colspan="1">MSF1</th><th align="center" rowspan="1" colspan="1">MSF2</th></tr></thead><tbody><tr><td align="left" rowspan="1" colspan="1">HDL</td><td align="char" char="." rowspan="1" colspan="1">0.99</td><td align="char" char="." rowspan="1" colspan="1">0.02</td><td align="char" char="." rowspan="1" colspan="1">0.95</td><td align="char" char="." rowspan="1" colspan="1">−0.10</td></tr><tr><td align="left" rowspan="1" colspan="1">Log triglycerides</td><td align="char" char="." rowspan="1" colspan="1">−0.47</td><td align="char" char="." rowspan="1" colspan="1">0.29</td><td align="char" char="." rowspan="1" colspan="1">−0.49</td><td align="char" char="." rowspan="1" colspan="1">0.36</td></tr><tr><td align="left" rowspan="1" colspan="1">Systolic blood pressure</td><td align="char" char="." rowspan="1" colspan="1">−0.02</td><td align="char" char="." rowspan="1" colspan="1">0.64</td><td align="char" char="." rowspan="1" colspan="1">−0.10</td><td align="char" char="." rowspan="1" colspan="1">0.63</td></tr><tr><td align="left" rowspan="1" colspan="1">Waist</td><td align="char" char="." rowspan="1" colspan="1">−0.35</td><td align="char" char="." rowspan="1" colspan="1">0.43</td><td align="char" char="." rowspan="1" colspan="1">−0.11</td><td align="char" char="." rowspan="1" colspan="1">0.52</td></tr><tr><td align="left" rowspan="1" colspan="1">Log fasting glucose</td><td align="char" char="." rowspan="1" colspan="1">−0.09</td><td align="char" char="." rowspan="1" colspan="1">0.37</td><td align="char" char="." rowspan="1" colspan="1">−0.20</td><td align="char" char="." rowspan="1" colspan="1">0.51</td></tr><tr><td align="left" rowspan="1" colspan="1">% Total variance</td><td align="char" char="." rowspan="1" colspan="1">38.2</td><td align="char" char="." rowspan="1" colspan="1">22.6</td><td align="char" char="." rowspan="1" colspan="1">42.70</td><td align="char" char="." rowspan="1" colspan="1">20.6</td></tr><tr><td align="left" rowspan="1" colspan="1">% Cumulative variance</td><td align="char" char="." rowspan="1" colspan="1">38.2</td><td align="char" char="." rowspan="1" colspan="1">60.8</td><td align="char" char="." rowspan="1" colspan="1">42.70</td><td align="char" char="." rowspan="1" colspan="1">63.3</td></tr></tbody></table><table-wrap-foot><fn><p>MSF, MS factor.</p></fn></table-wrap-foot></table-wrap><p>Third, according to factor analysis mentioned above, two latent variables for MS factors, that is, “MSF1” and “MSF2” were constructed in SEM (Model 2). The path diagram is shown in <xref ref-type="fig" rid="fig02">Fig. 2</xref>, and the estimates of the path coefficients in Model 2 are shown in <xref ref-type="table" rid="tbl4">Table 4</xref>. The latent variables “MSF1” and “MSF2” were represented by HDL and triglyceride, and by waist circumstance, fasting glucose and systolic blood pressure respectively. The latent variable “Periodontal disease” was represented by mean PD and %BOP. The correlations among “MSF1,” “MSF2,” “Periodontal disease” and “Teeth” in males and females are shown in <xref ref-type="fig" rid="fig03">Fig. 3</xref>. The correlation between residual terms indicates the relationship which was omitted the effects of several variables such as age, smoking habit, alcohol intake, medicine use and toothbrushing frequency. The effect of these variables on “MSF1,” “MSF2,” “Periodontal disease” and “Teeth” are also shown in <xref ref-type="fig" rid="fig03">Fig. 3</xref>. In females, Model 2 fits the data well [<italic>χ</italic><sup>2</sup> (35) = 118.504; CFI = 0.964; RMSEA = 0.042 (0.034–0.051); SRMR = 0.028]. In females, Model 2 showed that “Periodontal disease” correlated significantly with “MSF1” (the correlation coefficient = 0.08, <italic>p</italic> = 0.027), “MSF2” (the correlation coefficient = 0.18, <italic>p</italic> < 0.001), adjusted for several variables such as age, smoking habits. In males, Model 2 did not fit the observed data well [<italic>χ</italic><sup>2</sup> (35) = 238.203; CFI = 0.877; RMSEA = 0.075 (0.066–0.084); SRMR = 0.042]. The causal and correlation structure in males may be more complex than that in females.</p><table-wrap id="tbl4" position="float"><label>Table 4</label><caption><p>Maximum-likelihood parameter estimates for the structural regression model of periodontal disease and metabolic syndrome</p></caption><table frame="hsides" rules="groups"><thead><tr><th align="left" rowspan="2" colspan="1">Parameter</th><th align="center" colspan="3" rowspan="1">Males</th><th align="center" colspan="3" rowspan="1">Females</th></tr><tr><th align="center" rowspan="1" colspan="1"><italic>β</italic></th><th align="center" rowspan="1" colspan="1">SE</th><th align="center" rowspan="1" colspan="1"><italic>p</italic>-value</th><th align="center" rowspan="1" colspan="1"><italic>β</italic></th><th align="center" rowspan="1" colspan="1">SE</th><th align="center" rowspan="1" colspan="1"><italic>p</italic>-value</th></tr></thead><tbody><tr><td align="left" colspan="7" rowspan="1">Factor loadings</td></tr><tr><td align="left" rowspan="1" colspan="1"> Periodontal disease→PD</td><td align="char" char="." rowspan="1" colspan="1">0.941</td><td align="char" char="." rowspan="1" colspan="1">0.046</td><td align="char" char="." rowspan="1" colspan="1"><0.001</td><td align="char" char="." rowspan="1" colspan="1">0.809</td><td align="char" char="." rowspan="1" colspan="1">0.032</td><td align="char" char="." rowspan="1" colspan="1"><0.001</td></tr><tr><td align="left" rowspan="1" colspan="1"> Periodontal disease→%BOP</td><td align="char" char="." rowspan="1" colspan="1">0.670</td><td align="char" char="." rowspan="1" colspan="1">0.037</td><td align="char" char="." rowspan="1" colspan="1"><0.001</td><td align="char" char="." rowspan="1" colspan="1">0.744</td><td align="char" char="." rowspan="1" colspan="1">0.030</td><td align="char" char="." rowspan="1" colspan="1"><0.001</td></tr><tr><td align="left" rowspan="1" colspan="1"> MSF 1→Log TG</td><td align="char" char="." rowspan="1" colspan="1">0.787</td><td align="char" char="." rowspan="1" colspan="1">0.064</td><td align="char" char="." rowspan="1" colspan="1"><0.001</td><td align="char" char="." rowspan="1" colspan="1">0.881</td><td align="char" char="." rowspan="1" colspan="1">0.042</td><td align="char" char="." rowspan="1" colspan="1"><0.001</td></tr><tr><td align="left" rowspan="1" colspan="1"> MSF 1→HDL</td><td align="char" char="." rowspan="1" colspan="1">−0.581</td><td align="char" char="." rowspan="1" colspan="1">0.051</td><td align="char" char="." rowspan="1" colspan="1"><0.001</td><td align="char" char="." rowspan="1" colspan="1">−0.571</td><td align="char" char="." rowspan="1" colspan="1">0.033</td><td align="char" char="." rowspan="1" colspan="1"><0.001</td></tr><tr><td align="left" rowspan="1" colspan="1"> MSF 2→Waist</td><td align="char" char="." rowspan="1" colspan="1">0.587</td><td align="char" char="." rowspan="1" colspan="1">0.043</td><td align="char" char="." rowspan="1" colspan="1"><0.001</td><td align="char" char="." rowspan="1" colspan="1">0.531</td><td align="char" char="." rowspan="1" colspan="1">0.027</td><td align="char" char="." rowspan="1" colspan="1"><0.001</td></tr><tr><td align="left" rowspan="1" colspan="1"> MSF 2→Log Glu</td><td align="char" char="." rowspan="1" colspan="1">0.379</td><td align="char" char="." rowspan="1" colspan="1">0.037</td><td align="char" char="." rowspan="1" colspan="1"><0.001</td><td align="char" char="." rowspan="1" colspan="1">0.529</td><td align="char" char="." rowspan="1" colspan="1">0.027</td><td align="char" char="." rowspan="1" colspan="1"><0.001</td></tr><tr><td align="left" rowspan="1" colspan="1"> MSF 2→SBP</td><td align="char" char="." rowspan="1" colspan="1">0.493</td><td align="char" char="." rowspan="1" colspan="1">0.042</td><td align="char" char="." rowspan="1" colspan="1"><0.001</td><td align="char" char="." rowspan="1" colspan="1">0.635</td><td align="char" char="." rowspan="1" colspan="1">0.025</td><td align="char" char="." rowspan="1" colspan="1"><0.001</td></tr><tr><td align="left" colspan="7" rowspan="1">Covariance</td></tr><tr><td align="left" rowspan="1" colspan="1"> Periodontal disease↔MSF 1</td><td align="char" char="." rowspan="1" colspan="1">0.096</td><td align="char" char="." rowspan="1" colspan="1">0.041</td><td align="char" char="." rowspan="1" colspan="1">0.020</td><td align="char" char="." rowspan="1" colspan="1">0.083</td><td align="char" char="." rowspan="1" colspan="1">0.038</td><td align="char" char="." rowspan="1" colspan="1">0.027</td></tr><tr><td align="left" rowspan="1" colspan="1"> Periodontal disease↔MSF 2</td><td align="char" char="." rowspan="1" colspan="1">0.074</td><td align="char" char="." rowspan="1" colspan="1">0.050</td><td align="char" char="." rowspan="1" colspan="1">0.141</td><td align="char" char="." rowspan="1" colspan="1">0.182</td><td align="char" char="." rowspan="1" colspan="1">0.045</td><td align="char" char="." rowspan="1" colspan="1"><0.001</td></tr><tr><td align="left" rowspan="1" colspan="1"> Periodontal disease↔Teeth</td><td align="char" char="." rowspan="1" colspan="1">−0.309</td><td align="char" char="." rowspan="1" colspan="1">0.033</td><td align="char" char="." rowspan="1" colspan="1"><0.001</td><td align="char" char="." rowspan="1" colspan="1">−0.312</td><td align="char" char="." rowspan="1" colspan="1">0.029</td><td align="char" char="." rowspan="1" colspan="1"><0.001</td></tr><tr><td align="left" rowspan="1" colspan="1"> Teeth↔MSF 1</td><td align="char" char="." rowspan="1" colspan="1">−0.008</td><td align="char" char="." rowspan="1" colspan="1">0.038</td><td align="char" char="." rowspan="1" colspan="1">0.837</td><td align="char" char="." rowspan="1" colspan="1">−0.019</td><td align="char" char="." rowspan="1" colspan="1">0.031</td><td align="char" char="." rowspan="1" colspan="1">0.548</td></tr><tr><td align="left" rowspan="1" colspan="1"> Teeth↔MSF 2</td><td align="char" char="." rowspan="1" colspan="1">−0.056</td><td align="char" char="." rowspan="1" colspan="1">0.047</td><td align="char" char="." rowspan="1" colspan="1">0.233</td><td align="char" char="." rowspan="1" colspan="1">−0.079</td><td align="char" char="." rowspan="1" colspan="1">0.039</td><td align="char" char="." rowspan="1" colspan="1">0.045</td></tr><tr><td align="left" rowspan="1" colspan="1"> MSF 1↔MSF 2</td><td align="char" char="." rowspan="1" colspan="1">0.585</td><td align="char" char="." rowspan="1" colspan="1">0.061</td><td align="char" char="." rowspan="1" colspan="1"><0.001</td><td align="char" char="." rowspan="1" colspan="1">0.473</td><td align="char" char="." rowspan="1" colspan="1">0.047</td><td align="char" char="." rowspan="1" colspan="1"><0.001</td></tr><tr><td align="left" colspan="7" rowspan="1">Direct effect</td></tr><tr><td align="left" rowspan="1" colspan="1"> Age→Periodontal disease</td><td align="char" char="." rowspan="1" colspan="1">0.055</td><td align="char" char="." rowspan="1" colspan="1">0.033</td><td align="char" char="." rowspan="1" colspan="1">0.100</td><td align="char" char="." rowspan="1" colspan="1">0.222</td><td align="char" char="." rowspan="1" colspan="1">0.031</td><td align="char" char="." rowspan="1" colspan="1"><0.001</td></tr><tr><td align="left" rowspan="1" colspan="1"> Smoking→Periodontal disease</td><td align="char" char="." rowspan="1" colspan="1">0.176</td><td align="char" char="." rowspan="1" colspan="1">0.032</td><td align="char" char="." rowspan="1" colspan="1"><0.001</td><td align="char" char="." rowspan="1" colspan="1">0.068</td><td align="char" char="." rowspan="1" colspan="1">0.031</td><td align="char" char="." rowspan="1" colspan="1">0.027</td></tr><tr><td align="left" rowspan="1" colspan="1"> Toothbrushing→Periodontal disease</td><td align="char" char="." rowspan="1" colspan="1">−0.069</td><td align="char" char="." rowspan="1" colspan="1">0.035</td><td align="char" char="." rowspan="1" colspan="1">0.048</td><td align="char" char="." rowspan="1" colspan="1">−0.076</td><td align="char" char="." rowspan="1" colspan="1">0.031</td><td align="char" char="." rowspan="1" colspan="1">0.014</td></tr><tr><td align="left" rowspan="1" colspan="1"> Age→Teeth</td><td align="char" char="." rowspan="1" colspan="1">−0.329</td><td align="char" char="." rowspan="1" colspan="1">0.027</td><td align="char" char="." rowspan="1" colspan="1"><0.001</td><td align="char" char="." rowspan="1" colspan="1">−0.447</td><td align="char" char="." rowspan="1" colspan="1">0.022</td><td align="char" char="." rowspan="1" colspan="1"><0.001</td></tr><tr><td align="left" rowspan="1" colspan="1"> Smoking→Teeth</td><td align="char" char="." rowspan="1" colspan="1">−0.198</td><td align="char" char="." rowspan="1" colspan="1">0.028</td><td align="char" char="." rowspan="1" colspan="1"><0.001</td><td align="char" char="." rowspan="1" colspan="1">−0.071</td><td align="char" char="." rowspan="1" colspan="1">0.025</td><td align="char" char="." rowspan="1" colspan="1">0.004</td></tr><tr><td align="left" rowspan="1" colspan="1"> Toothbrushing→Teeth</td><td align="char" char="." rowspan="1" colspan="1">−0.011</td><td align="char" char="." rowspan="1" colspan="1">0.029</td><td align="char" char="." rowspan="1" colspan="1">0.713</td><td align="char" char="." rowspan="1" colspan="1">−0.012</td><td align="char" char="." rowspan="1" colspan="1">0.025</td><td align="char" char="." rowspan="1" colspan="1">0.617</td></tr><tr><td align="left" rowspan="1" colspan="1"> Age→MSF 1</td><td align="char" char="." rowspan="1" colspan="1">−0.245</td><td align="char" char="." rowspan="1" colspan="1">0.039</td><td align="char" char="." rowspan="1" colspan="1"><0.001</td><td align="char" char="." rowspan="1" colspan="1">0.205</td><td align="char" char="." rowspan="1" colspan="1">0.032</td><td align="char" char="." rowspan="1" colspan="1"><0.001</td></tr><tr><td align="left" rowspan="1" colspan="1"> Smoking→MSF 1</td><td align="char" char="." rowspan="1" colspan="1">0.230</td><td align="char" char="." rowspan="1" colspan="1">0.041</td><td align="char" char="." rowspan="1" colspan="1"><0.001</td><td align="char" char="." rowspan="1" colspan="1">0.132</td><td align="char" char="." rowspan="1" colspan="1">0.031</td><td align="char" char="." rowspan="1" colspan="1"><0.001</td></tr><tr><td align="left" rowspan="1" colspan="1"> Alcohol→MSF 1</td><td align="char" char="." rowspan="1" colspan="1">0.018</td><td align="char" char="." rowspan="1" colspan="1">0.053</td><td align="char" char="." rowspan="1" colspan="1">0.732</td><td align="char" char="." rowspan="1" colspan="1">0.009</td><td align="char" char="." rowspan="1" colspan="1">0.032</td><td align="char" char="." rowspan="1" colspan="1">0.785</td></tr><tr><td align="left" rowspan="1" colspan="1"> Medicine 1<xref ref-type="table-fn" rid="tf4-1">*</xref>→MSF 1</td><td align="char" char="." rowspan="1" colspan="1">0.057</td><td align="char" char="." rowspan="1" colspan="1">0.039</td><td align="char" char="." rowspan="1" colspan="1">0.144</td><td align="char" char="." rowspan="1" colspan="1">0.116</td><td align="char" char="." rowspan="1" colspan="1">0.032</td><td align="char" char="." rowspan="1" colspan="1"><0.001</td></tr><tr><td align="left" rowspan="1" colspan="1"> Medicine 2<xref ref-type="table-fn" rid="tf4-2">†</xref>→MSF 1</td><td align="char" char="." rowspan="1" colspan="1">0.103</td><td align="char" char="." rowspan="1" colspan="1">0.045</td><td align="char" char="." rowspan="1" colspan="1">0.022</td><td align="char" char="." rowspan="1" colspan="1">0.091</td><td align="char" char="." rowspan="1" colspan="1">0.034</td><td align="char" char="." rowspan="1" colspan="1">0.007</td></tr><tr><td align="left" rowspan="1" colspan="1"> Age→MSF 2</td><td align="char" char="." rowspan="1" colspan="1">−0.018</td><td align="char" char="." rowspan="1" colspan="1">0.050</td><td align="char" char="." rowspan="1" colspan="1">0.725</td><td align="char" char="." rowspan="1" colspan="1">0.340</td><td align="char" char="." rowspan="1" colspan="1">0.035</td><td align="char" char="." rowspan="1" colspan="1"><0.001</td></tr><tr><td align="left" rowspan="1" colspan="1"> Smoking→MSF 2</td><td align="char" char="." rowspan="1" colspan="1">0.121</td><td align="char" char="." rowspan="1" colspan="1">0.043</td><td align="char" char="." rowspan="1" colspan="1">0.004</td><td align="char" char="." rowspan="1" colspan="1">−0.031</td><td align="char" char="." rowspan="1" colspan="1">0.033</td><td align="char" char="." rowspan="1" colspan="1">0.346</td></tr><tr><td align="left" rowspan="1" colspan="1"> Alcohol→MSF 2</td><td align="char" char="." rowspan="1" colspan="1">0.113</td><td align="char" char="." rowspan="1" colspan="1">0.045</td><td align="char" char="." rowspan="1" colspan="1">0.012</td><td align="char" char="." rowspan="1" colspan="1">0.117</td><td align="char" char="." rowspan="1" colspan="1">0.033</td><td align="char" char="." rowspan="1" colspan="1"><0.001</td></tr><tr><td align="left" rowspan="1" colspan="1"> Medicine 1→MSF 2</td><td align="char" char="." rowspan="1" colspan="1">0.120</td><td align="char" char="." rowspan="1" colspan="1">0.044</td><td align="char" char="." rowspan="1" colspan="1">0.006</td><td align="char" char="." rowspan="1" colspan="1">0.109</td><td align="char" char="." rowspan="1" colspan="1">0.035</td><td align="char" char="." rowspan="1" colspan="1">0.002</td></tr><tr><td align="left" rowspan="1" colspan="1"> Medicine 2→MSF 2</td><td align="char" char="." rowspan="1" colspan="1">0.383</td><td align="char" char="." rowspan="1" colspan="1">0.045</td><td align="char" char="." rowspan="1" colspan="1"><0.001</td><td align="char" char="." rowspan="1" colspan="1">0.297</td><td align="char" char="." rowspan="1" colspan="1">0.035</td><td align="char" char="." rowspan="1" colspan="1"><0.001</td></tr><tr><td align="left" colspan="7" rowspan="1">Model fit index</td></tr><tr><td align="left" rowspan="1" colspan="1"> <italic>χ</italic>2</td><td align="char" char="." colspan="3" rowspan="1">265.469</td><td align="char" char="." colspan="3" rowspan="1">169.762</td></tr><tr><td align="left" rowspan="1" colspan="1"> df</td><td align="char" char="." colspan="3" rowspan="1">47</td><td align="char" char="." colspan="3" rowspan="1">47</td></tr><tr><td align="left" rowspan="1" colspan="1"> CFI</td><td align="char" char="." colspan="3" rowspan="1">0.876</td><td align="char" char="." colspan="3" rowspan="1">0.950</td></tr><tr><td align="left" rowspan="1" colspan="1"> RMSEA</td><td align="char" char="." colspan="3" rowspan="1">0.067 (0.059–0.075)</td><td align="char" char="." colspan="3" rowspan="1">0.044 (0.037–0.052)</td></tr><tr><td align="left" rowspan="1" colspan="1"> SRMR</td><td align="char" char="." colspan="3" rowspan="1">0.037</td><td align="char" char="." colspan="3" rowspan="1">0.030</td></tr></tbody></table><table-wrap-foot><fn><p>PD, pocket depth;%BOP, the percentage of teeth that bled on probing; Log TG, log triglycerides; Log Glu, log fasting glucose; SBP, systolic blood pressure; MSF, MS factor. <italic>β</italic>, standardized coefficient; SE, standard error.</p></fn><fn id="tf4-1"><label>*</label><p>Anti-hyperlipidemic drug use.</p></fn><fn id="tf4-2"><label>†</label><p>Anti-hypertensive drug or anti-diabetes drug use.</p></fn></table-wrap-foot></table-wrap><fig id="fig03" position="float"><label>Fig 3</label><caption><p>The metabolic syndrome (MS) two-factor model (Model 2) for males and females. Significant values are *<italic>p</italic> < 0.05, **<italic>p</italic> < 0.01, ***<italic>p</italic> < 0.001. The fit of Model 2 was <italic>χ</italic><sup>2</sup> (35) = 238.203; CFI = 0.877; RMSEA = 0.075 (0.066–0.084); SRMR = 0.042 in males and <italic>χ</italic><sup>2</sup> (35) = 118.504; CFI = 0.964; RMSEA = 0.042 (0.034–0.051); SRMR = 0.028 in females. The e1–e7 and r1–r4 designators refer to error terms and residual terms.</p></caption><graphic xlink:href="jcpe0040-0743-f3"></graphic></fig></sec></sec><sec><title>Discussion</title><p>In this study, a gender difference in the association between periodontal disease and MS components was identified by logistic regression analysis (<xref ref-type="table" rid="tbl2">Table 2</xref>). There was a significant association between periodontal disease and MS in females, but not in males, depending on the cut-off value of mean PD defined as periodontal disease. Our results were similar to those of <xref ref-type="bibr" rid="b4">Andriankaja et al. (2010)</xref> that females having three or more MS components had a stronger association with periodontal disease than those with no MS component; however, this was not seen in males. In contrast, <xref ref-type="bibr" rid="b27">Kwon et al. (2011)</xref> reported no gender difference in the relationship between periodontal diseases and MS, although the subjects in their and our studies were both Mongolians. The result of logistic regression analysis is generally affected by disease definition. Subjects in the study by <xref ref-type="bibr" rid="b27">Kwon et al. (2011)</xref> were assessed using the WHO community periodontal index (CPI) and the definition of periodontal disease was a CPI greater than or equal to “code 3” at least one site among those assessed. In contrast, we used the NHANES III criteria for periodontal assessment. This difference in the definition of periodontal disease may explain the discrepancy between the report by <xref ref-type="bibr" rid="b27">Kwon et al. (2011)</xref> and the present one. In fact, in our study the association between periodontal disease and MS statistically differed in several definitions of periodontal disease. In males, the association between MS and periodontal disease defined by a mean PD ≥2.0 or 2.5 mm was statistically significant, but not for periodontal disease defined by a mean PD ≥3.0 or 3.5 mm. Thus, the different mean PD cut-off values may derive different statistical results in the analysis of association between periodontal disease and MS, and it is possible to have a lack of consistency of results due to different definition of periodontal disease. This indicates a defect of the usual approach and a need to evaluate periodontal disease qualitatively.</p><p>To overcome the difficulty mentioned above, we treated periodontal disease as a continuous variable. The causal and correlation relationships among variables concerned were analysed SEM. As a result, the MS single-factor model (Model 1) failed to provide a good fit to the observed data. To construct an alternative MS factor structure, factor analysis of MS components was carried out. Factor analysis has been used to reduce inter-related variables into a smaller set of factors. As the MS components were high inter-related, factor analysis resulted in two summary factors. The variables with a factor loading 0.40 were commonly used for interpretation of factors. We found that triglycerides and HDL loaded on one factor, that is, MSF1, and waist circumferences, fasting glucose, and systolic blood pressure on another factor, MSF2. In male, although fasting glucose had loading 0.37 on MSF2, because of close to 0.40, we considered that fasting glucose loaded on MSF2. The present factor analysis identified two summary factors, and this result suggest that one MS component alone (e.g. fasting glucose) does not underlie all features of MS and that more than one pathophysiological mechanism are present for the full expression of MS (<xref ref-type="bibr" rid="b51">Wang et al. 2004)</xref>. Considering pathophysiologically, visceral obesity may be linked to decreased glucose tolerance with hyperinsulinemia, leading to reduced insulin-mediated glucose uptake (<xref ref-type="bibr" rid="b49">Timar et al. 2000</xref>). Indeed, obesity was associated with insulin resistance in previous studies (<xref ref-type="bibr" rid="b11">Edwards et al. 1994</xref>, <xref ref-type="bibr" rid="b28">Lempiainen et al. 1999</xref>). Insulin resistance with resulting compensatory hyperinsulinemia activates sympathetic activity that subsequently causes hypertension (<xref ref-type="bibr" rid="b38">Reaven et al. 1996</xref>). These interrelationships may explain why waist circumferences, fasting glucose and systolic blood pressure were related MSF2. On the other hand, in the pathophysiology of metabolic syndrome, increased triglyceride levels decrease the content of cholesterol HDL (<xref ref-type="bibr" rid="b10">Eckel et al. 2005</xref>); consequently, a cluster of triglycerides and HDL seems reasonable. As shown in factor analysis, it may be appropriate to assume two latent variables (i.e. factors) that explain the MS components in SEM.</p><p>According to the factor analysis, when an MS two-factor model was constructed for both genders, the model fitted female data well and but did not provide a good fit to the male data. This may suggest a gender difference in the association between periodontal disease and MS. There are several possible explanations for this gender difference. First, the different levels of MS inflammation in males and females may be related to differences in the association between periodontal disease and MS. Females with MS had higher levels of CRP than males (<xref ref-type="bibr" rid="b43">Saltevo et al. 2008</xref>), suggesting that the systemic inflammation level was higher in females than in males with MS. On the other hand, periodontal disease is associated with elevated CRP, but this has not been reported separately by gender (<xref ref-type="bibr" rid="b46">Slade et al. 2000</xref>, <xref ref-type="bibr" rid="b35">Noack et al. 2001</xref>). Because both periodontal disease and MS are associated with systemic inflammation, these health conditions are likely to be linked through a common pathophysiological pathway (<xref ref-type="bibr" rid="b9">D’Aiuto et al. 2008</xref>). The higher inflammation in females with MS could explain the stronger association of periodontal disease with MS in females than in males. In addition, our study showed that latent variable “Periodontal disease” was significantly related to “MSF2”, which was comprised of waist circumferences, fasting glucose and systolic blood pressure, in females, but not in males. Obesity is associated with systemic inflammation (<xref ref-type="bibr" rid="b48">Thorand et al. 2003</xref>) and periodontal disease (<xref ref-type="bibr" rid="b42">Saito et al. 2005</xref>). Because of higher inflammation in females with MS than in males, it is suggested that obesity-related factor is stronger associated with periodontal disease in females than in males. It is possible that males have a weak association between periodontal disease and MS; thus the male model did not fit the data well. Because the male model could not be explained using the observed variables, whether periodontal disease and MS are associated with factors or covariates not considered here should be investigated in future studies.</p><p>Another reason for the gender difference in the association between periodontal disease and MS may be the role played by sex hormones in the inflammatory process. Inflammatory cytokines decrease estradiol production by granulosa cells, suggesting that chronic inflammation may reduce the protective effect of oestrogen on body fat distribution and insulin action (<xref ref-type="bibr" rid="b3">Alpizar & Spicer 1994</xref>). Although oestrogen alone does not induce periodontal disease, it alters the periodontal tissue condition in response to the plaque microbiota (<xref ref-type="bibr" rid="b31">Mealey & Moritz 2003</xref>, <xref ref-type="bibr" rid="b15">Figuero et al. 2013</xref>).That is, systemic inflammation promoted by obesity could influence the production of oestrogen, which, in turn, affects insulin resistance and lipid metabolism and contributes to periodontal disease in females.</p><p>Considering the differences between males and females for biological factors as represented by sex hormones, gender difference in health status and disease condition is implied. As various aspects of gender differences have been recently studied (<xref ref-type="bibr" rid="b25">Klein et al. 2010</xref>, <xref ref-type="bibr" rid="b13">Eshima et al. 2011</xref>, <xref ref-type="bibr" rid="b12">2012</xref>, <xref ref-type="bibr" rid="b16">Flanagan et al. 2011</xref>), it is important to pay attention to gender differences in the association between periodontal disease and MS. Understanding gender differences may lead to studying common preventive approach and treatment strategy for periodontal disease and MS, and gender differential approaches may be established. Further studies are expected to identify a more detailed relationship structure between periodontal disease and MS.</p><p>This study has several limitations. We did not consider other factors that may be related to periodontal disease and MS, such as socioeconomic status, inflammation indices (e.g. CRP) or psychosocial factors. To get into a more detail investigation of the mechanism of the gender difference in the association between periodontal disease and MS, these factors should be treated in future studies. In addition, there is a room for consideration of a method of assessment of periodontal disease in this study, NHANES III method. Since this method does not include examination of lingual or palatal sites susceptible to periodontal disease, it is possible that the prevalence of periodontal disease was underestimated. If the prevalence of periodontal disease affects the association between periodontal disease and MS, our findings may have to be reconsidered. To our knowledge, there is no report of such an effect. We conducted multiple statistical tests such as the logistic regression analysis, the factor analysis, and the SEM. This may cause multiplicity problems (<xref ref-type="bibr" rid="b6">Bender & Lange 2001</xref>), which is derived from the limitation of the present statistical techniques.</p><p>In conclusion, our data suggest gender differences in the association between periodontal disease and MS in both the quantitative and qualitative sense. This gender difference should be considered when the association between periodontal disease and MS is evaluated.</p><p><boxed-text position="float"><sec><title>Clinical Relevance</title><p><italic>Scientific rationale for the study</italic>: Gender differences in the prevalence of periodontal disease and metabolic syndrome have been reported. However, the existence of a gender difference in the association between the two health conditions has not yet been determined.</p><p><italic>Principal findings</italic>: There was a gender difference in the association between periodontal disease and metabolic syndrome in both the quantitative and qualitative sense. The association in females was more consistent than that in males.</p><p><italic>Practical implications</italic>: To precisely evaluate the association between periodontal disease and factors of metabolic syndrome, the gender difference must be considered.</p></sec></boxed-text></p></sec><sec><title>Conflict of interest and source of funding statement</title><p>The authors have no conflicts of interest to declare. This study was supported by Grants-in-Aid of Scientific Research (22390401, 22406034 and 23390483) from the Ministry of Education, Science, Sports, and Culture of Japan, Tokyo, Japan and by Health and Labour Sciences Research Grants from the Japanese Ministry of Health, Labour and Welfare.</p></sec></body><back><ack><p>The authors thank Drs. 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(Accessed June 22, 2012)</comment></element-citation></ref></ref-list><sec sec-type="supplementary-material"><title>Supplementary material</title><p>Additional Supporting Information may be found in the online version of this article:</p><supplementary-material content-type="loca-data" id="SD1"><label>Table S1</label><caption><p>Pearson’s correlations between periodontal disease variables and the metabolic components examined.</p></caption><media mimetype="application/msword" mime-subtype="doc" xlink:href="jcpe0040-0743-sd1.doc" xlink:type="simple" id="d35e4373" position="anchor"></media></supplementary-material><supplementary-material content-type="loca-data" id="SD2"><label>Table S2</label><caption><p>Periodontal disease odds ratios adjusted for drug treatment for elevated glucose and confounding factor.</p></caption><media mimetype="application/msword" mime-subtype="doc" xlink:href="jcpe0040-0743-sd2.doc" xlink:type="simple" id="d35e4380" position="anchor"></media></supplementary-material></sec></back></pmc></record>Pour manipuler ce document sous Unix (Dilib)
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