{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T18:02:02Z","timestamp":1785348122273,"version":"3.55.0"},"reference-count":83,"publisher":"Public Library of Science (PLoS)","issue":"7","license":[{"start":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T00:00:00Z","timestamp":1785283200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100017170","name":"Thailand Science Research and Innovation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100017170","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Sasin School of Management Research Grant"}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS One"],"abstract":"<jats:p>Multimorbidity, defined as the presence of two or more chronic conditions, is a growing public health concern. Understanding disease clustering and risk profiles is crucial for prevention and planning purposes. This study analyzed data from the National Health Survey in Thailand, which included 142,753 participants. Latent class analysis investigated nine non-communicable diseases, while multinomial logistic regression explored the characteristics associated with class membership. Four distinct classes were identified: low burden, hypertension\u2013metabolic, predominant hypertension, and high multimorbidity. Advancing age revealed an increased probability of membership in all multimorbidity classes. Females exhibited a higher propensity to belong to the hypertension\u2013metabolic and predominant hypertension classes. Urban residency was associated with an elevated probability of membership in the hypertension\u2013metabolic and high-multimorbidity classes. The body mass index displayed significant variations across classes. Overweight and obesity were linked to the hypertension\u2013metabolic and predominant hypertension classes, with obesity also associated with the high multimorbidity class. Underweight individuals demonstrated a reduced likelihood of membership in the hypertension\u2013metabolic class but an increased likelihood of membership in the predominant hypertension class. Smoking was correlated with a higher probability of membership across classes, particularly among current smokers. Dietary behaviors were distinctly associated across classes. Frequent consumption of high-fat and instant foods was linked to the hypertension\u2013metabolic class, whereas instant food consumption was also associated with the predominant hypertension class. Fruit consumption was correlated with a higher probability of membership in the hypertension\u2013metabolic class, whereas vegetable consumption was associated with a reduced likelihood of membership in the predominant hypertension class. Moderate consumption of non-alcoholic sugary drinks was associated with a lower probability of hypertension\u2013metabolic class membership. These findings underscore the heterogeneity of multimorbidity patterns in Thailand and delineate the demographic, behavioral, and residential profiles associated with non-communicable disease clustering.<\/jats:p>","DOI":"10.1371\/journal.pone.0354347","type":"journal-article","created":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T17:40:42Z","timestamp":1785346842000},"page":"e0354347","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["Multimorbidity patterns and their associations with demographic characteristics, behavioral factors, and urban\u2013rural residence: A latent class analysis in the Thai population"],"prefix":"10.1371","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1183-1427","authenticated-orcid":true,"given":"Pavitra","family":"Jindahra","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stefano","family":"Starita","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3219-9264","authenticated-orcid":true,"given":"Pinnaree","family":"Tea-makorn","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2026,7,29]]},"reference":[{"key":"pone.0354347.ref001","doi-asserted-by":"crossref","first-page":"776","DOI":"10.1186\/s12889-015-2008-7","article-title":"Multimorbidity and the inequalities of global ageing: a cross-sectional study of 28 countries using the World Health Surveys","volume":"15","author":"S Afshar","year":"2015","journal-title":"BMC Public Health"},{"key":"pone.0354347.ref002","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1186\/1475-9276-12-63","article-title":"The social determinants of multimorbidity in South Africa","volume":"12","author":"O Alaba","year":"2013","journal-title":"Int J Equity Health"},{"issue":"7","key":"pone.0354347.ref003","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0102149","article-title":"Prevalence, determinants and patterns of multimorbidity in primary care: a systematic review of observational studies","volume":"9","author":"C Violan","year":"2014","journal-title":"PLoS One"},{"issue":"2","key":"pone.0354347.ref004","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1089\/pop.2018.0069","article-title":"Recent patterns of multimorbidity among older adults in high-income countries","volume":"22","author":"R Ofori-Asenso","year":"2019","journal-title":"Popul Health Manag"},{"key":"pone.0354347.ref005","doi-asserted-by":"crossref","DOI":"10.1177\/2235042X20961919","article-title":"Multimorbidity of chronic non-communicable diseases in low- and middle-income countries: a scoping review","volume":"10","author":"F Abebe","year":"2020","journal-title":"J Comorb"},{"key":"pone.0354347.ref006","doi-asserted-by":"crossref","first-page":"26335565221106074","DOI":"10.1177\/26335565221106074","article-title":"Multimorbidity matters in low and middle-income countries","volume":"12","author":"A Basto-Abreu","year":"2022","journal-title":"J Multimorb Comorb"},{"key":"pone.0354347.ref007","doi-asserted-by":"crossref","first-page":"314","DOI":"10.1186\/s13104-016-2121-4","article-title":"Prevalence of self-reported multimorbidity in the general population and in primary care practices: a cross-sectional study","volume":"9","author":"N-M Mokraoui","year":"2016","journal-title":"BMC Res Notes"},{"issue":"6","key":"pone.0354347.ref008","doi-asserted-by":"crossref","DOI":"10.1136\/bmjopen-2016-013664","article-title":"Multimorbidity and patterns of chronic conditions in a primary care population in Switzerland: a cross-sectional study","volume":"7","author":"A D\u00e9ruaz-Luyet","year":"2017","journal-title":"BMJ Open"},{"issue":"2","key":"pone.0354347.ref009","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1093\/gerona\/glv128","article-title":"Global multimorbidity patterns: a cross-sectional, population-based, multi-country study","volume":"71","author":"N Garin","year":"2016","journal-title":"J Gerontol A Biol Sci Med Sci"},{"key":"pone.0354347.ref010","doi-asserted-by":"crossref","first-page":"245","DOI":"10.2147\/CLEP.S226586","article-title":"Patterns of multimorbidity and differences in healthcare utilization and complexity among acutely hospitalized medical patients (\u226565 years) - 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