{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,26]],"date-time":"2026-09-26T17:35:53Z","timestamp":1790444153369,"version":"4.1.0"},"reference-count":36,"publisher":"SAGE Publications","issue":"5","license":[{"start":{"date-parts":[[2024,3,19]],"date-time":"2024-03-19T00:00:00Z","timestamp":1710806400000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["J Dent Res"],"published-print":{"date-parts":[[2024,5]]},"abstract":"<jats:p>Existing studies on multimorbidity have largely excluded oral diseases in multimorbidity prevalence estimates. The reason behind this is somewhat unclear, as chronic oral conditions are highly prevalent, affecting over half the global population. To address this gap, we examined the relationship between social disadvantage and multimorbidity, stratifying by the inclusion and exclusion of oral conditions. For participants aged 30 y and over ( n = 3,693), cross-sectional analysis was carried out using the US National Health and Nutrition Survey (2013\u20132014). Multimorbidity was defined as having 2 or more chronic conditions. Five medical conditions were examined: diabetes, asthma, arthritis, cardiovascular disease, and depression, as well as 4 oral health conditions: caries, periodontal disease, number of teeth, and edentulousness. Education and income poverty ratio were selected as measures of social disadvantage. Multimorbidity prevalence estimates according to social disadvantage were analyzed on an absolute and relative scale using inverse probability treatment weighting (IPTW), adjusting for age, sex, and ethnicity. The inclusion of oral health conditions in the assessment of multimorbidity increased the overall prevalence of multimorbidity from 20.8% to 53.4%. Findings from IPTW analysis demonstrated clear social gradients for multimorbidity estimates stratified by the exclusion of oral conditions. Upon inclusion of oral conditions, the prevalence of multimorbidity was higher across all social groups for both education and income. Stratifying by the inclusion of oral conditions, the mean probability of multimorbidity was 27% (95% confidence interval [CI], 23%\u201330%) higher in the low-education group compared to the high-education group. Similarly, the mean probability of multimorbidity was 44% (95% CI, 40%\u201348%) higher in the low-income group. On a relative scale, low education was associated with a 1.52 times (95% CI, 1.44\u20131.61) higher prevalence of multimorbidity compared to high education. Low income was associated with a 2.18 (95% CI, 1.99\u20132.39) higher prevalence of multimorbidity. This novel study strongly supports the impact of chronic oral conditions on multimorbidity prevalence estimates.<\/jats:p>","DOI":"10.1177\/00220345241228834","type":"journal-article","created":{"date-parts":[[2024,3,20]],"date-time":"2024-03-20T00:15:57Z","timestamp":1710893757000},"page":"477-483","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":17,"title":["Social Disadvantage and Multimorbidity Including Oral Conditions in the United States"],"prefix":"10.1177","volume":"103","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4794-5779","authenticated-orcid":false,"given":"A.","family":"Mirza","sequence":"first","affiliation":[{"name":"Department of Epidemiology and Public Health, University College London, London, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6229-8584","authenticated-orcid":false,"given":"R.G.","family":"Watt","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Public Health, University College London, London, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8188-5087","authenticated-orcid":false,"given":"A.","family":"Heilmann","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Public Health, University College London, London, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1731-9854","authenticated-orcid":false,"given":"M.","family":"Stennett","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Public Health, University College London, London, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1336-6493","authenticated-orcid":false,"given":"A.","family":"Singh","sequence":"additional","affiliation":[{"name":"Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Victoria, Australia"},{"name":"Melbourne Dental School, University of Melbourne, Melbourne, Victoria, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2024,3,19]]},"reference":[{"key":"bibr1-00220345241228834","unstructured":"Academy of Medical Sciences. 2018. 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