Evidence map›Paper›PMID 41183114›Full record

ArticlePloS one2025

Investigating multimorbidity patterns and associated risk factors in the fasa adults cohort study (FACS): A latent class analysis.

Mehdi Sharafi, Najibullah Baeradeh, Mohammad Ali Mohsenpour, Sima Afrashteh, Pezhman Bagheri, Omid Keshavarzian, Mohammad Amin Annabi, Fatemeh Nekouei, Mojtaba Farjam

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Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Mehdi SharafiCellular and Molecular Research Center, Gerash University of Medical Sciences, Gerash, Iran.ORCID https://orcid.org/0000-0002-6505-9463
Najibullah BaeradehDepartment of Public Health, Ferdows Faculty of Medical Sciences, Birjand University of Medical Sciences, Birjand, Iran.
Mohammad Ali MohsenpourNutrition Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.
Sima AfrashtehDepartment of Biostatistics and Epidemiology, Faculty of Health and Nutrition, Bushehr University of Medical Sciences, Bushehr, Iran.ORCID https://orcid.org/0000-0002-4276-2084
Pezhman BagheriNoncommunicable Diseases Research Center, Fasa University of Medical Sciences, Fasa, Iran.
Omid KeshavarzianTransplant Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.
Mohammad Amin AnnabiSchool of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran.
Fatemeh NekoueiSchool of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran.
Mojtaba FarjamNoncommunicable Diseases Research Center, Fasa University of Medical Sciences, Fasa, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMultimorbidity, defined as the co-occurrence of multiple health conditions, is a major global public health concern. This study aimed to identify latent classes of multimorbidity and associated risk factors in Iranian adults.

methodThis cross-sectional study analyzed baseline data from 10,131 adults who participated in the Fasa Adults Cohort Study (FACS) in southern Iran. Multimorbidity was defined as the presence of two or more of 11 chronic diseases, including hypertension, dyslipidemia, stroke, osteoarthritis, depression, type two diabetes mellitus, obesity, osteoporosis, cardiovascular disease, thyroid disease, and respiratory disease. Latent class analysis (LCA) was used for cluster participants, and multinomial logistic regression was conducted to investigate the association between age, sex, education level, socioeconomic status, daily sleep duration, physical activity, and multimorbidity.

resultThe prevalence of multimorbidity was 40.3%. Three latent classes were identified: healthy (66.8%), dyslipidemia (14.1%), and cardio-metabolic conditions (19.1%). Older age increased the odds of belonging to dyslipidemia (odds ratio (OR) = 1.04 [95% confidence interval (CI): 1.03-1.05]) and cardio-metabolic conditions (OR = 1.10 [95% CI: 1.09-1.11]) classes. Similarly, women were at higher odds than men of being in dyslipidemia (OR = 2.49 [95% CI: 2.05-3.02]) and cardio-metabolic conditions (OR = 3.35, 95% CI: 2.79-4.03]) classes. Employed participants showed decreased odds of having cardio-metabolic conditions (OR = 0.66 [95% CI: 0.55-0.80]). However, very high socioeconomic status was a risk factor for cardio-metabolic conditions (OR = 1.44 [95% CI: 1.16-1.78]) and dyslipidemia (OR = 1.35 [95% CI: 1.10-1.65]). Higher physical activity and sleeping for 8 hours or more were protective factors against cardio-metabolic conditions (OR = 0.74 [95% CI: 0.63-0.87]). Moreover, medium or high dietary intake increased the odds of belonging to the dyslipidemia class (OR = 1.46 [95% CI: 1.09-1.94] and OR = 1.57 [95% CI: 1.16-2.11], respectively).

conclusionUsing LCA, we identified distinct subgroups of chronic diseases, showing hidden patterns of multimorbidity associated with several risk factors. This approach offers deeper knowledge of disease clustering, contributes to a more comprehensive understanding of multimorbidity, and shows the importance of regional health challenges in designing targeted public health interventions.

Indexed as

MultimorbidityAdultAgedChronic DiseaseCohort StudiesCross-Sectional StudiesDyslipidemiasFemaleHumansIranLatent Class AnalysisMaleMiddle AgedPrevalenceRisk Factors

Identifiers

PMID41183114
PMCPMC12582492

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.