The multimorbidity in the elderly has become an important issue that needs urgent attention in the field of public health. Therefore, it is of great significance to explore the influencing factors of multimorbidity in the elderly.
To investigate the prevalence of multimorbidity and related influencing factors in the elderly population in northern and southern China, in order to better manage and intervene the development and prognosis of multimorbidity in the elderly in different regions.
PubMed, Embase, Web of Science, Cochrane Library, Scopus, China Biology Medicine Disc, China National Knowledge Infrastructure, Wanfang Data Knowledge service platform were searched for relevant studies on influencing factors of multimorbidity in the elderly. Two researchers independently searched, screened, extracted data, and cross-checked. Any disagreements were resolved through consultation with a third researcher for arbitration. The search time limit was from the establishment of the database to July 2024. Stata 18.0 software was used for meta-analysis.
The research incorporated 10 articles from the southern region and 10 from the northern region, with sample sizes of 2 342 507 and 75 871 cases, respectively. The prevalence of multimorbidity among elderly patients in the southern and northern regions was 34% (95%CI=29%-38%, P<0.001) and 36% (95%CI=22%-50%, P<0.001), respectively. Among them, the influencing factors of elderly patients with multimorbidity in southern China were age (OR=1.92, 95%CI=1.26-2.94, P=0.003), gender (OR=1.51, 95%CI=1.03-2.21, P=0.034), and household per capita monthly income (OR=1.62, 95%CI=1.03-2.54, P=0.036), education level (OR=1.47, 95%CI=1.25-1.73, P<0.001), BMI (OR=1.72, 95%CI=1.52-1.96, P<0.001), smoking (OR=1.53, 95%CI=1.11-2.11, P=0.009), drinking (OR=1.39, 95%CI=1.26-1.54, P<0.001), regular physical exercise (OR=0.67, 95%CI=0.55-0.80, P<0.001) ; age (OR=1.67, 95%CI=1.00-2.79, P=0.048), BMI (OR=2.39, 95%CI=1.80-3.18, P<0.001), drinking (OR=1.63, 95%CI=1.32-2.02, P<0.001), regular physical exercise (OR=0.84, 95%CI=0.71-0.99, P<0.037) were the influencing factors of elderly patients with multimorbidity in northern China. Sensitivity analysis showed that the results of Meta-analysis were stable, and Egger's test (multimorbidity prevalence: P=0.826; influencing factors: P=0.841) suggested that the risk of publication bias of the included literature was not significant.
The prevalence of multimorbidity among the elderly was relatively high in both the northern and southern regions. The risk factors for multimorbidity in both regions included: age≥70 years, overweight or obese BMI status, and alcohol consumption. Conversely, regular physical exercise served as a protective factor. In southern China, male sex, household per capita monthly income≥¥2 000, education below college level, and smoking were the risk factors for multimorbidity. These disparities may stem from dietary habits, economic levels, lifestyle pace, and uneven medical resource distribution. Enhancing inter-regional medical resource coordination and sharing is advised to improve health equity and resource balance, boosting elderly health overall. Additionally, healthcare providers should tailor interventions based on these factors to optimize disease management in elderly with multimorbidity.
Currently, the prevalence of multimorbidity among patients with chronic diseases in China is increasing, resulting in a growing burden of disease. However, research on complex multimorbidity is relatively limited in China, underscoring an urgent need for a substantial body of evidence to inform the development of comprehensive and coordinated strategies for the control of persistent impacts of multimorbidity and complex multimorbidity.
The present study aims to investigate the prevalence of, and patterns of, multimorbidity and complex multimorbidity among patients with chronic diseases in Urumqi City between 2016 and 2022.
In June 2023, a comprehensive data set encompassing general demographic information and the prevalence of chronic diseases among patients with 27 chronic diseases was retrieved from the Urumqi City Public Health Surveillance Database and Electronic Medical Record Information Database from 2016 to 2022. The prevalence trends of multimorbidity (suffering from≥2 chronic diseases) and complex multimorbidity (suffering from ≥3 chronic diseases) in patients with chronic diseases were analyzed. Multifactorial logistic regression was used to This analysis sought to elucidate the factors that influence the occurrence of both chronic disease multimorbidity and complex multimorbidity. Additionally, the Apriori association rule algorithm was employed to identify the common patterns underlying chronic disease multimorbidity and complex multimorbidity.
A total of 45 150 cases of study subjects were included during the seven-year period, comprising 12 969 (28.72%) cases of patients with a single chronic disease and 27 992 (62.00%) cases of patients with Additionally, 4 189 cases (9.28%) were identified as patients with complex multimorbidity, and the mean number of concomitant diseases per patient increased from (1.73±0.86) to (2.56±1.15). The results of the multifactorial Logistic regression analysis indicated that advancing age, male gender, and urban residence were significant risk factors for the development of comorbidities and complex multimorbidity in patients with chronic diseases. Of the 27 chronic diseases included in the study, the top three chronic disease prevalence rates were 33 675 cases of hypertension (74.58%), 32 942 cases of dyslipidemia (72.96%) and 12 408 cases of diabetes mellitus (27.48%). The most common binary co-morbidity patterns were "dyslipidemia+hypertension" "diabetes+hypertension" and "diabetes+dyslipidemia". The most common ternary co-morbidity patterns were "dyslipidemia+diabetes mellitus+hypertension" "oronary heart disease+dyslipidemia+hypertension" and "dyslipidemia+renal cyst+hypertension". Coronary heart disease was the preceding disease in all directional association rules. All rules appeared as antecedent diseases. The circulatory system was the most common co-occurring system, and the antecedents of several association rules directed to the circulatory system were all related to the endocrine system.
The prevalence of chronic disease multimorbidity and complex multimorbidity in Urumqi City has been increasing annually, with age, gender, and urban/rural differences playing a significant role. Hypertension, dyslipidemia, and diabetes mellitus are the most prevalent multimorbidity, while the most affected organ systems are the circulatory, digestive, and endocrine systems. The most common aggregation pattern is cardiometabolic disease.
The prevalence of hypertension is high and the control rate is low. It is also a basic disease of comorbidity in the elderly. However, previous studies have mainly focused on the comorbidity of the elderly, and less consideration has been given to studying the comorbidity based on hypertension. Therefore, understanding the comorbidity of hypertension in urban and rural elderly is of great significance for the management of elderly patients with hypertension at the grass-roots level.
In order to understand the current situation and influencing factors of comorbidity in urban and rural elderly hypertension patients in Anshun City, and to improve the management strategy for elderly hypertension patients comorbidity in urban and rural areas.
The elderly hypertension patients who participated in physical examination in primary medical and health institutions in Anshun City in 2023 were selected as the research objects. After variable screening and transformation, missing values and outliers processing, 44 571 samples were finally included in the analysis. Demographic characteristics were selected from the basic information of elderly hypertension patients, including age, gender, marital status, etc. Behavioral habits and existing major health problems were collected from physical examination data. Apriori algorithm was used to mine common comorbidity patterns, and multi-classification Logistic regression analysis was used to explore the influencing factors.
A total of 44 571 valid samples were included, including 19 270 (43.23%) in urban and 25 301 (56.77%) in rural areas. There were statistically significant differences in the number of comorbidities among elderly hypertension patients in urban and rural areas, different genders, age groups, exercise status, smoking status, drinking status, medication status, medication compliance, and different educational levels (P<0.001). The comorbidity rate of elderly hypertensive patients in Anshun City was 70.44% (31 397 cases), of which the urban comorbidity rate was 74.45% (14 346 cases) and the rural comorbidity rate was 67.39% (17 051 cases). The co-morbidity patterns of urban and rural males and females were mainly "obesity + hypertension, dyslipidemia + hypertension, obesity + dyslipidemia + hypertension". The support of "obesity + hypertension" in urban areas is much higher than that in rural areas, while the support of "anemia + hypertension" in urban areas is lower than that in rural areas. There were strong association rules of "kidney disease + hypertension" in urban and rural males. Male medication in urban and rural areas, high school education and above, and women 's medication in urban and rural areas were all related to the coexistence of one disease (P<0.05). The age and exercise of women in urban and rural areas, the medication of men in urban and rural areas, and the education level of high school and above were related to the coexistence of the two diseases (P<0.05). The age, exercise status, medication status of urban males and urban and rural females, and the education level of high school and above of urban and rural males were all related to the coexistence of three or more diseases (P<0.05) .
The comorbidity rate of elderly hypertensive patients in urban areas was higher than that in rural areas in Anshun city. The main comorbidity mode was "obesity+dyslipidemia / diabetes+hypertension". Age, medication, exercise and d education level are the influencing factors of hypertension comorbidity in the elderly. Strengthen the health monitoring of elderly patients with hypertension, strengthen the patient 's awareness of comorbidities, implement urban and rural differentiated comorbidity prevention strategies and measures, and improve the level of comorbidity prevention and treatment.
