Obesity-related patterns of multimorbidity and their association with health-related quality of life in Iranian adults: a cross-sectional study.
To identify patterns of non-communicable disease (NCD) multimorbidity among Iranian adults and assess their associations with sociodemographic factors and health-related quality of life (HRQOL).
Cross-sectional analysis using data from the 2021 Iranian STEPS Survey, which follows the WHO STEPwise approach to collecting information on NCD risk factors.
A community-based, nationally representative household survey conducted across Iran.
A total of 17 517 Iranian adults with complete survey data were included. Of these, 56.7% were women and 67.4% lived in urban areas.
Latent class analysis was used to identify multimorbidity clusters based on chronic disease profiles, including myocardial infarction, stroke, asthma/chronic obstructive pulmonary disease, cancer, obesity (abdominal and defined by the body mass index), hypertension, diabetes, chronic kidney disease and dyslipidaemia. Associations between cluster membership, demographic characteristics and HRQOL (measured using the EuroQol Visual Analogue Scale, EQ-VAS) were examined using multinomial logistic regression.
Four distinct multimorbidity clusters were identified: obesity with severe metabolic syndrome (OSMS, 13.0%), obesity with early metabolic syndrome (OEMS, 39.3%), low comorbidity (LC, 42.4%) and non-obese cardiometabolic multimorbidity (NOCM, 5.2%). Cluster membership varied significantly by sex, age, education, occupation and insurance status. Older age, female sex, lower education, unpaid work and urban residence were associated with OSMS and OEMS, while male sex, older age, retirement and complementary insurance were associated with NOCM. EQ-VAS scores were significantly lower in the OSMS (β = -8.5; 95% CI -10.1 to -6.9), OEMS (β = -2.1; 95% CI -3.2 to -1.1) and NOCM (β = -6.2; 95% CI -8.2 to -4.2) clusters compared with the LC cluster.
Multimorbidity clusters in Iran are heterogeneous and linked to demographic and socioeconomic factors. Obesity and social disadvantage strongly shape disease patterns and HRQOL. Findings highlight the need for integrated, equity-oriented policies addressing both clinical complexity and social determinants through prevention and coordinated care.
Cross-sectional analysis using data from the 2021 Iranian STEPS Survey, which follows the WHO STEPwise approach to collecting information on NCD risk factors.
A community-based, nationally representative household survey conducted across Iran.
A total of 17 517 Iranian adults with complete survey data were included. Of these, 56.7% were women and 67.4% lived in urban areas.
Latent class analysis was used to identify multimorbidity clusters based on chronic disease profiles, including myocardial infarction, stroke, asthma/chronic obstructive pulmonary disease, cancer, obesity (abdominal and defined by the body mass index), hypertension, diabetes, chronic kidney disease and dyslipidaemia. Associations between cluster membership, demographic characteristics and HRQOL (measured using the EuroQol Visual Analogue Scale, EQ-VAS) were examined using multinomial logistic regression.
Four distinct multimorbidity clusters were identified: obesity with severe metabolic syndrome (OSMS, 13.0%), obesity with early metabolic syndrome (OEMS, 39.3%), low comorbidity (LC, 42.4%) and non-obese cardiometabolic multimorbidity (NOCM, 5.2%). Cluster membership varied significantly by sex, age, education, occupation and insurance status. Older age, female sex, lower education, unpaid work and urban residence were associated with OSMS and OEMS, while male sex, older age, retirement and complementary insurance were associated with NOCM. EQ-VAS scores were significantly lower in the OSMS (β = -8.5; 95% CI -10.1 to -6.9), OEMS (β = -2.1; 95% CI -3.2 to -1.1) and NOCM (β = -6.2; 95% CI -8.2 to -4.2) clusters compared with the LC cluster.
Multimorbidity clusters in Iran are heterogeneous and linked to demographic and socioeconomic factors. Obesity and social disadvantage strongly shape disease patterns and HRQOL. Findings highlight the need for integrated, equity-oriented policies addressing both clinical complexity and social determinants through prevention and coordinated care.
Authors
Kheirabady Kheirabady, Masoumi Masoumi, Azizpour Azizpour, Kharaghani Kharaghani, Mirzad Mirzad, Bagherian Ghotbi Bagherian Ghotbi, Rezaei Rezaei, Golestani Golestani
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