Prevalence and associated socioeconomic factors of multimorbidity in 10 regions of China: an analysis of 0.5 million adults

Individual and joint exposure to air pollutants and patterns of multiple chronic conditions

Existing research on the detrimental effects of air pollution and its mixture on multiple chronic conditions (MCC) is not yet fully recognized. Our objective was to examine if individual and joint exposure to air pollution is associated with the incidence and patterns of MCC. Totally 10,231 CHARLS 2015 participants aged over 45 years and 1,938 without MCC were followed up in 2018 and 2020. Residential-levelcumulative personal exposure concentrations of PM1, PM10, PM2.5, CO, O3, NO2, SO2, NO3-, Cl-, NH4+, and SO42- at the residential level were determined utilizing a spatio-temporal random forest model with a spatial resolution of 0.1° × 0.1°. In the cross-sectional and longitudinal research, logistic regression, cox regression analysis, and quantile g-computation were utilized to estimate the single and joint effect with MCC and its patterns, respectively. Interaction analyses and stratified analyses were also performed. A correlation was observed between the prevalence of cardiovascular illnesses and the presence of all 11 major air pollutants. PM2.5, PM10, NH4+, NO3-, CO, and SO42- are associated with an increased frequency of respiratory disorders. An increase of PM2.5, PM1, PM10, NO2, and SO2 (a 10 µg/m3 rise), CO (a 0.1 mg/m3 rise), and PMCs (Cl-, NH4+, NO3-, and SO42-) (a 1 µg/m3 rise) corresponded to the HRs (95% CI) for developing MCC of 1.194 (95% CI: 1.043, 1.367), 1.362 (95% CI: 1.073, 1.728), 1.115 (95% CI: 1.026, 1.212), 1.443 (95% CI: 1.151, 1.808), 3.175 (95% CI: 2.291, 4.401), 1.272 (95% CI: 1.149,1.410), 1.382 (95% CI: 1.011, 1.888), 1.107 (95% CI: 1.003, 1.222), 1.035 (95% CI: 0.984, 1.088), and 1.122 (95% CI: 1.086, 1.160), respectively. SO2 was the predominant contributor to the combined effect (HR: 2.083, 95% CI: 1.659-2.508). Gender, age, drinking, and health status could modify the effects of air pollutants on MCC patterns. Long-term exposure to air pollution is correlated to the incidence and patterns of MCC in middle-aged and elderly Chinese individuals. Preventive methods are essential to safeguarding those susceptible to MCC.

Socioeconomic, Health Services, and Multimorbidity Disparities in Chinese Older Adults

INTRODUCTION

As one of the world's most populous countries, China persistently confronts a significant multimorbidity burden. This study aimed to elucidate the multimorbidity burden experienced by Chinese older adults, explore its interplay with socioeconomic disparity, and investigate potential correlations between these provincial disparities and health services availability.

METHODS

The fourth wave of China's national Urban and Rural Elderly Population study, conducted in 2015, was used to construct a multimorbidity index and elucidate the geographic differences in the multimorbidity burden. Incorporating macrolevel indicators about socioeconomic and health services availability, quantile regression and Spearman correlation analyses were employed to investigate the relationship between multimorbidity and socioeconomic disparities and examine the potential linkages between these provincial disparities and health services availability. Analyses were performed in 2023.

RESULTS

The final analysis included a total of 213,857 older adults. At the provincial level, significant geographic disparities in multimorbidity burden were identified. After adjusting for individual social determinants of health, an independent association was found between the human development index and a higher multimorbidity index (coefficient= -0.22; 95% CI= -0.24, -0.19). Furthermore, a significant positive correlation emerged between human development index and both population and geographic densities of health services availability. Notably, geographic density displayed greater inequality (Gini coefficients=0.45-0.48) than population density (Gini coefficients=0.03-0.10).

CONCLUSIONS

This study demonstrates that multimorbidity burden in China is linked to provincial socioeconomic disparities and that inequality in health services availability may account for this, which would advocate for a need to reduce disparities in health services availability.

Prevalence and patterns of multimorbidity in China during 2002-2022: A systematic review and meta-analysis

BACKGROUND

Multimorbidity is common, particularly among elderly people. Restructuring health service systems to better manage this public health issue requires knowledge regarding disease prevalence and patterns. We quantified the epidemiology characteristics of multimorbidity among adults in China to inform policy-making and resource allocation.

METHODS

We searched 10 databases for studies (January 2000-October 2023) reporting primary epidemiological multimorbidity data for adults in China. We included observational studies; we excluded duplicate publications and studies investigating a single comorbidity pattern, focused on specific population categories, using medical insurance reimbursement data, and with unclear/incomplete data. We assessed risk of bias using the STROBE checklist and estimated heterogeneity among studies. The prevalence was pooled using the random-effects method and sample size as weight.

FINDINGS

Of 13,998 records retrieved, 67 studies (30 in English, 37 in Chinese) were included. The prevalence (95% confidence interval) of multimorbidity was 25.4% (15.1%, 35.7%) among Chinese adults. Among 42 studies reporting age-specific prevalence, multimorbidity prevalence increased rapidly with age: 3.3% (0%, 15.2%) for age 18-29 years, 5.9% (0%, 12.9%) for 30-44 years, 17.6% (6.1%, 29.1%) for 45-59 years, 32.4% (16.1%, 48.7%) for 60-69 years, 38.5% (23.6%, 53.4%) for 70-79 years, and 40.2% (20.8%, 59.6%) for age ≥ 80 years. Overall prevalence of multimorbidity has increased in recent years, with regional disparity. The most common patterns included hypertension with hearing impairment (10.4% [95% CI: 4.3%, 16.5%]), dyslipidemia (8.9% [4.1%, 13.6%]), and diabetes (8.7% [3.7%, 13.8%]).

CONCLUSION

Multimorbidity was present nearly one in four Chinese adults, with hypertensive diseases and other comorbidities being the most-observed pattern; the prevalence increased rapidly with increased age. There is huge variation in the prevalence of multimorbidity across China. Coordinated, comprehensive strategies are urgently needed to control the ongoing impact of multimorbidity.

Association of smoking status and nicotine dependence with multi-morbidity in China: A nationally representative crosssectional study

INTRODUCTION

Multi-morbidity is a public health priority as it is associated with an increased risk of mortality and a substantial healthcare burden. Smoking is considered a predisposing factor for multi-morbidity, but evidence for an association between multi-morbidity and nicotine dependence is insufficient. This study aimed to explore the association between smoking status, nicotine dependence, and multi-morbidity in China.

METHODS

We recruited 11031 Chinese citizens from 31 provinces in 2021 using a multistage stratified cluster sampling strategy to ensure the study population represented national population characteristics. The association between smoking status and multi-morbidity was analyzed using binary logistic regression and multinomial logit regression models. We then analyzed the associations between four kinds of smoking status (age at smoking initiation, cigarette consumption per day, smoking when ill in bed, and inability to control smoking in public places), nicotine dependence, and multi-morbidity among participants who were current smokers.

RESULTS

Compared with non-smokers, the odds of multi-morbidity were higher among ex-smokers (adjusted odd ratio, AOR=1.40, 95% CI: 1.07-1.85). The risk of multi-morbidity was greater in participants who were underweight/overweight/obese (AOR=1.90; 95% CI: 1.60-2.26) compared with those who were normal weight. and also greater for drinkers (AOR=1.34; 95% CI: 1.09-1.63) than non-drinkers. Compared with children who began smoking at the age of <15 years, participants aged >18 years had a lower likelihood of multi-morbidity (AOR=0.52; 95% CI: 0.32-0.83). People who consumed ≥31 cigarettes per day (AOR=3.77; 95% CI: 1.47-9.68) and those who smoked when ill in bed (AOR=1.70; 95% CI: 1.10-2.64) were more likely to have multi-morbidity.

CONCLUSIONS

Our findings show that smoking behavior, including initiation age, frequency of daily smoking, and still smoking during illness or in public, is a critical risk factor for multi-morbidity, especially when combined with alcohol consumption, physical inactivity, and abnormal weight (underweight, overweight, or obese). This highlights the crucial effect of smoking cessation in the prevention and control of multi-morbidity, especially in patients with three or more diseases. Implementing smoking and lifestyle interventions to promote health would both benefit adults and prevent the next generation from initiating habits that increase the risk of multi-morbidity.

Prevalence and factors associated with multimorbidity in adults in Brazil, according to sex: a population-based cross-sectional survey

Introduction

Multimorbidity, defined as the coexistence of two or more chronic diseases in the same individual, represents a significant health challenge. However, there is limited evidence on its prevalence and associated factors in developing countries, such as Brazil, especially stratified by sex. Thus, this study aims to estimate the prevalence and analyze the factors associated with multimorbidity in Brazilian adults according to sex.

Methods

Cross-sectional population-based household survey carried out with Brazilian adults aged 18 years or older. The sampling strategy consisted of a three-stage conglomerate plan. The three stages were performed through simple random sampling. Data were collected through individual interviews. Multimorbidity was classified based on a list of 14 self-reported chronic diseases/conditions. Poisson regression analysis was performed to estimate the magnitude of the association between sociodemographic and lifestyle factors with the prevalence of multimorbidity stratified by sex.

Results

A total of 88,531 individuals were included. In absolute terms, the prevalence of multimorbidity was 29.4%. The frequency in men and women was 22.7 and 35.4%, respectively. Overall, multimorbidity was more prevalent among women, the older people, residents of the South and Southeast regions, urban area residents, former smokers, current smokers, physically inactive, overweight, and obese adults. Individuals with complete high school/incomplete higher education had a lower prevalence of multimorbidity than those with higher educational level. The associations between education and multimorbidity differed between sexes. In men, multimorbidity was inversely associated with the strata of complete middle school/incomplete high school and complete high school/incomplete higher education, while in women, the association between these variables was not observed. Physical inactivity was positively associated with a higher prevalence of multimorbidity only in men. An inverse association was verified between the recommended fruit and vegetable consumption and multimorbidity for the total sample and both sexes.

Conclusion

One in four adults had multimorbidity. Prevalence increased with increasing age, among women, and was associated with some lifestyles. Multimorbidity was significantly associated with educational level and physical inactivity only in men. The results suggest the need to adopt integrated strategies to reduce the magnitude of multimorbidity, specific by gender, including actions for health promotion, disease prevention, health surveillance and comprehensive health care in Brazil.

Social inequalities in all-cause mortality among adults with multimorbidity: a 10-year prospective study of 0.5 million Chinese adults

BACKGROUND

Chinese individuals face an increase in multimorbidity, but little is known about the mortality gradients of multimorbid people in different socio-economic groups. This study measures relative and absolute socio-economic inequality in mortality among multimorbid Chinese.

METHODS

For this study, the prospective China Kadoorie Biobank (CKB) enrolled 512 712 participants ages 30-79 y from 10 areas of China between 25 June 2004 and 15 July 2008. All-cause mortality was accessed with a mean follow-up period of 10 y (to 31 December 2016). Associations between multimorbidity and mortality were assessed using Cox proportional hazards models, with the relative index of inequality (RII) and slope index of inequality (SII) in mortality calculated to measure disparities.

RESULTS

Mortality risk was highest for those who had not attended formal school and with four or more long-term conditions (LTCs) (hazard ratio 3.11 [95% confidence interval {CI} 2.75 to 3.51]). Relative educational inequality was lower in participants with four or more LTCs (RII 1.92 [95% CI 1.60 to 2.30]), especially in rural areas. Absolute disparities were greater in adults with more LTCs (SII 0.18 [95% CI 0.14 to 0.21] for rural participants with three LTCs).

CONCLUSIONS

Whereas the relative inequality in all-cause mortality was lower among multimorbid people, absolute inequality was greater among multimorbid men, especially in rural areas.

Analysis of Hospitalization Costs in Patients Suffering from Cerebral Infarction along with Varied Comorbidities

OBJECTIVE

This study aimed to study the influence of comorbidities on hospitalization costs for inpatients with cerebral infarction.

METHODS

The data from the medical records pertaining to 76,563 inpatients diagnosed with cerebral infarction were collected from public hospital records for the period between 1 January 2020 and 30 December 2020 in Gansu Province. EpiData 3.1 software was used for data collation, and SPSS 25.0 was used for data analysis. Numbers and percentages were calculated for categorical variables, the chi-squared test was used to compare differences between groups, and multiple independent-sample tests (Kruskal-Wallis H test, test level α = 0.05) and multiple linear regression were used to analyze the influence of different types of comorbidity on hospitalization costs.

RESULTS

Among the 76,563 cerebral infarction inpatients, 41,400 were male (54.07%); the average age of the inpatients was 67.68 ± 10.75 years (the 60~80-year-old group accounted for 65.69%). Regarding the incidence of varied chronic disease comorbidities concomitant with cerebral infarction, hypertension was reported as the most frequent, followed by heart disease and chronic pulmonary disease. The average hospitalization cost of cerebral infarction inpatients is US $1219.66; the hospitalization cost increases according to the number of comorbidities with which a patient suffers (H = 404.506, p < 0.001); Regarding the types of comorbidities, the hospitalization cost of cancer was the highest, at US $1934.02, followed by chronic pulmonary disease (US $1533.02). Regarding the cost of hospitalization for combinations of comorbidities, cerebral infarction + chronic pulmonary disease was the most costly (US $1718.90), followed by cerebral infarction + hypertension + chronic pulmonary disease (US $1530.60). In the results of multiple linear regression analysis, cerebral infarction with chronic pulmonary disease had significant effects on hospitalization costs (β = 0.181, p < 0.001), drug costs (β = 0.144, p < 0.001) and diagnosis costs (β = 0.171, p < 0.001).

CONCLUSIONS

Comorbidities are significantly associated with high hospitalization costs for cerebral infarction patients. Furthermore, relevant health departments should build preventative and control systems to reduce the risk of comorbidities, as well as to improve hospital clinical pathway management and to strengthen and refine the cost-control management of cerebral infarction from the perspective of comorbidities.

The impact of socioeconomic status and sleep quality on the prevalence of multimorbidity in older adults

Introduction

Multimorbidity has become a global public health concern that can cause serious damage to the health status of older adults. This study aimed to investigate the impact of socioeconomic status (SES) and sleep quality on the prevalence of multimorbidity in older adults, thus providing a reference for reducing the risk of the prevalence of multimorbidity and improving the health of older adults.

Methods

A multi-stage random sampling method was used to conduct a questionnaire survey on 3,250 older adults aged 60 years and above in Shanxi Province, China. The chi-square test and multiple logistic regression models were used to analyze the association of SES and sleep quality with the prevalence of multimorbidity of older adults.

Results

The prevalence of multimorbidity was 30.31% in older adults aged 60 years and above in Shanxi Province, China. After adjusting for confounders, very low SES (OR = 1.440, 95% CI: 1.083-1.913) and poor sleep quality (OR = 2.445, 95% CI: 2.043-2.927) were associated with the prevalence of multimorbidity. Older adults with low SES and poor sleep quality had the highest risk of the prevalence of multimorbidity (OR = 3.139, 95% CI: 2.288-4.307).

Conclusions

SES and sleep quality are associated with the prevalence of multimorbidity in older adults, and older adults with lower SES and poorer sleep quality are at higher risk for the prevalence of multimorbidity.

Association of multimorbidity patterns with incident disability and recovery of independence among middle-aged and older adults

OBJECTIVE

to identify multimorbidity patterns among middle-aged and older adults in China and examine how these patterns are associated with incident disability and recovery of independence.

METHODS

data were from The China Health and Retirement Longitudinal Study. We included 14,613 persons aged ≥45 years. Latent class analysis (LCA) was conducted to identify multimorbidity patterns with clinical meaningfulness. Multinomial logistic models were used to determine the adjusted association between multimorbidity patterns and incident disability and recovery of independence.

RESULTS

we identified four multimorbidity patterns: 'low morbidity' (67.91% of the sample), 'pulmonary-digestive-rheumatic' (17.28%), 'cardiovascular-metabolic-neuro' (10.77%) and 'high morbidity' (4.04%). Compared to the 'low morbidity' group, 'high morbidity' (OR = 2.63, 95% CI = 1.97-3.51), 'pulmonary-digestive-rheumatic' (OR = 1.89, 95% CI = 1.63-2.21) and 'cardiovascular-metabolic-neuro' pattern (OR = 1.61, 95% CI = 1.31-1.97) had higher odds of incident disability in adjusted multinomial logistic models. The 'cardiovascular-metabolic-neuro' (OR = 0.60, 95% CI = 0.44-0.81), 'high morbidity' (OR = 0.68, 95% CI = 0.47-0.98) and 'pulmonary-digestive-rheumatic' group (OR = 0.75, 95% CI = 0.60-0.95) had lower odds of recovery from disability than the 'low morbidity' group. Among people without disability, the 'cardiovascular-endocrine-neuro' pattern was associated with the highest 2-year mortality (OR = 2.42, 95% CI = 1.56-3.72).

CONCLUSIONS

multimorbidity is complex and heterogeneous, but our study demonstrates that clinically meaningful patterns can be obtained using LCA. We highlight four multimorbidity patterns with differential effects on incident disability and recovery from disability. These studies suggest that targeted prevention and treatment approaches are needed for people with multimorbidity.

Prevalence and patterns of multimorbidity in chronic diseases in Guangzhou, China: a data mining study in the residents' health records system among 31 708 community-dwelling elderly people

OBJECTIVES

Examination of the prevalence, influence factors and patterns of multimorbidity among the elderly people in Guangzhou, China.

DESIGN

Cross-sectional study.

PARTICIPANTS

31 708 community-dwelling elderly people aged 65 and over.

PRIMARY AND SECONDARY OUTCOME MEASURES

Prevalence, influence factors and patterns of multimorbidity in seven chronic conditions among the participants. A multistage, stratified random sampling was adopted for selection of health records in the residents' health records system of Guangzhou. Data mining by association rule mining analysis was used to explore the correlations and multimorbidity patterns between seven chronic diseases.

RESULTS

The prevalence of morbidity was 55.0% (95% CI 40.1% to 60.1%) and the multimorbidity was 15.2% (95% CI 12.4% to 18.4%) among the participants. Elderly, women, higher education level, being single, living in urban areas and having medical insurance were more likely to have chronic diseases and multimorbidity. Data mining by association rule mining analysis reveals patterns of multimorbidity among the participants, including coexistence of hypertension and diabetes (support: 12.5%, confidence: 17.6%), hypertension and coronary heart disease (support: 4.4%, confidence: 5.7%), diabetes and coronary heart disease (support: 1.6%, confidence: 5.7%), diabetes, coronary heart disease and hypertension (support: 1.4%, confidence: 4.4%).

CONCLUSIONS

A high prevalence of morbidity (especially on hypertension and diabetes) and a relatively low multimorbidity of chronic diseases exist in elderly people. Data mining of residents' health records will help for strengthening the management of residents' health records in community health service centres of Guangzhou, China.

Frequency and types of clusters of major chronic diseases in 0.5 million adults in urban and rural China

Background

Little is known about the frequency and types of disease clusters involving major chronic diseases that contribute to multimorbidity in China. We examined the frequency of disease clusters involving major chronic diseases and their relationship with age and socioeconomic status in 0.5 million Chinese adults.

Methods

Multimorbidity was defined as the presence of at least two or more of five major chronic diseases: stroke, ischaemic heart disease (IHD), diabetes, chronic obstructive pulmonary disease (COPD) and cancer. Multimorbid disease clusters were estimated using both self-reported doctor-diagnosed diseases at enrolment and incident cases during 10-year follow-up. Frequency of multimorbidity was assessed overall and by age, sex, region, education and income. Association rule mining (ARM) and latent class analysis (LCA) were used to assess clusters of the five major diseases.

Results

Overall, 11% of Chinese adults had two or more major chronic diseases, and the frequency increased with age (11%, 24% and 33% at age 50-59, 60-69 and 70-79 years, respectively). Multimorbidity was more common in men than women (12% vs 11%) and in those living in urban than in rural areas (12% vs 10%), and was inversely related to levels of education. Stroke and IHD were the most frequent combinations, followed by diabetes and stroke. The patterns of self-reported disease clusters at baseline were similar to those that were recorded during the first 10 years of follow-up.

Conclusions

Cardiometabolic and cardiorespiratory diseases were most common disease clusters. Understanding the nature of such clusters could have implications for future prevention strategies.

Theoretical explanations for socioeconomic inequalities in multimorbidity: a scoping review

OBJECTIVE

To document socioepidemiological theories used to explain the relationship between socioeconomic disadvantage and multimorbidity.

DESIGN

Scoping review.

METHODS

A search strategy was developed and then applied to multiple electronic databases including Medline, Embase, PsychInfo, Web of Science, Scielo, Applied Social Sciences, ERIC, Humanities Index and Sociological Abstracts. After the selection of studies, data were extracted using a data charting plan. The last search was performed on the 28 September 2021. Extracted data included: study design, country, population subgroups, measures of socioeconomic inequality, assessment of multimorbidity and conclusion on the association between socioeconomic variables and multimorbidity. Included studies were further assessed on their use of theory, type of theories used and context of application. Finally, we conducted a meta-narrative synthesis to summarise the results.

RESULTS

A total of 64 studies were included in the review. Of these, 33 papers included theories as explanations for the association between socioeconomic position and multimorbidity. Within this group, 16 explicitly stated those theories and five tested at least one theory. Behavioural theories (health behaviours) were the most frequently used, followed by materialist (access to health resources) and psychosocial (stress pathways) theories. Most studies used theories as post hoc explanations for their findings or for study rationale. Supportive evidence was found for the role of material, behavioural and life course theories in explaining the relationship between social inequalities and multimorbidity.

CONCLUSION

Given the widely reported social inequalities in multimorbidity and its increasing public health burden, there is a critical gap in evidence on pathways from socioeconomic disadvantage to multimorbidity. Generating evidence of these pathways will guide the development of intervention and public policies to prevent multimorbidity among people living in social disadvantage. Material, behavioural and life course pathways can be targeted to reduce the negative effect of low socioeconomic position on multimorbidity.

The association between educational level and multimorbidity among adults in Southeast Asia: A systematic review

BACKGROUND

In Southeast Asia, the prevalence of multimorbidity is gradually increasing. This paper aimed to investigate the association between educational level and multimorbidity among over 15-years old adults in Southeast Asia.

METHODS

We conducted a systematic review of published observational studies. Studies were selected according to eligibility criteria of addressing definition and prevalence of multimorbidity and associations between level of education and multimorbidity in Southeast Asia. The Newcastle-Ottawa Scale (NOS) was used to measure the quality and risk of bias. The methodology has been published in PROSPERO with registered number ID: CRD42021259311.

RESULTS

Eighteen studies were included in the data synthesis. The results are presented using narrative synthesis due to the heterogeneity of differences in exposures, outcomes, and methodology. The prevalence of multimorbidity ranged from 1.7% to 72.6% among over 18 years-old adults and from 1.5% to 51.5% among older people (≥ 60 years). There were three association patterns linking between multimorbidity and education in these studies: (1) higher education reducing odds of multimorbidity, (2) higher education increasing odds of multimorbidity and (3) education having no association with multimorbidity. The association between educational attainment and multimorbidity also varies widely across countries. In Singapore, three cross-sectional studies showed that education had no association with multimorbidity among adults. However, in Indonesia, four cross-sectional studies found higher educated persons to have higher odds of multimorbidity among over 40-years-old persons.

CONCLUSIONS

Published studies have shown inconsistent associations between education and multimorbidity because of different national contexts and the lack of relevant research in the region concerned. Enhancing objective data collection such as physical examinations would be necessary for studies of the connection between multimorbidity and education. It can be hypothesised that more empirical research would reveal that a sound educational system can help people prevent multimorbidity.

Urban-Rural Differences in Patterns and Associated Factors of Multimorbidity Among Older Adults in China: A Cross-Sectional Study Based on Apriori Algorithm and Multinomial Logistic Regression

Introduction: Multimorbidity has become one of the key issues in the public health sector. This study aimed to explore the urban–rural differences in patterns and associated factors of multimorbidity in China and to provide scientific reference for the development of health management strategies to reduce health inequality between urban and rural areas.

Methods: A cross-sectional study, which used a multi-stage random sampling method, was conducted effectively among 3,250 participants in the Shanxi province of China. The chi-square test was used to compare the prevalence of chronic diseases among older adults with different demographic characteristics. The Apriori algorithm and multinomial logistic regression were used to explore the patterns and associated factors of multimorbidity among older adults, respectively.

Results: The findings showed that 30.3% of older adults reported multimorbidity, with significantly higher proportions in rural areas. Among urban older adults, 10 binary chronic disease combinations with strong association strength were obtained. In addition, 11 binary chronic disease combinations and three ternary chronic disease combinations with strong association strength were obtained among rural older adults. In rural and urban areas, there is a large gap in patterns and factors associated with multimorbidity.

Conclusions: Multimorbidity was prevalent among older adults, which patterns mainly consisted of two or three chronic diseases. The patterns and associated factors of multimorbidity varied from urban to rural regions. Expanding the study of urban–rural differences in multimorbidity will help the country formulate more reasonable public health policies to maximize the benefits of medical services for all.