The problem of population aging is serious in China, and chronic diseases comorbidity is becoming more and more common.

Based on the health ecology model, to systematically understand the main influencing factors of chronic disease comorbidity among the elderly in China, and to provide scientific reference for the prevention and control of chronic disease comorbidity among the elderly in China.

Based on the follow-up data of China Health and Retirement Longitudinal Study (CHARLS) 2018, a total of 10 779 samples aged ≥60 years were selected in March 2021. After excluding the samples with missing data and unqualified data, a total of 7 354 samples was included in this study. With the occurrence of chronic comorbidities (having ≥2 chronic conditions) as the dependent variable and the inclusion of independent variables according to the 5 dimensions of the health ecology model, a multivariate Logistic regression model was used to analyze the influencing factors of chronic disease comorbidity in the elderly.

Among the elderly≥60 years old in China, the comorbidity rate of chronic diseases was 65.16% (4 792/7 354) , with 32.16% (1 541/4 792) patients suffered from two kinds of chronic diseases, and the diseases with the largest combination of two comorbidities were hypertension with arthritis or rheumatism〔16.42% (253/1 541) 〕. The results of the multivariate Logistic analysis showed that for the risk of comorbidities of chronic diseases in the elderly, females were higher than that in males〔OR (95%CI) =1.371 (1.177, 1.596) 〕, those over 70 years old were higher than those aged 60-70 years old〔OR (95%CI) =1.189 (1.061, 1.333) 〕, those who slept for 6-8 hours or more than 8 hours at night were lower than those who slept for less than 6 hours at night〔OR (95%CI) =0.759 (0.678, 0.850) , OR (95%CI) =0.686 (0.572, 0.821) 〕, those who took nap time of 0.5-1.0 h and over 1.0 h were higher than those of less than 0.5 h 〔OR (95%CI) =1.238 (1.102, 1.391) , OR (95%CI) =1.219 (1.604, 1.396) 〕, those who felt general and less satisfied with their health were higher than those who were very satisfied〔OR (95%CI) =1.755 (1.537, 2.004) , OR (95%CI) =5.890 (4.930, 7.037) 〕, those who registered in urban areas were higher than those in the rural areas〔OR (95%CI) =1.167 (1.036, 1.315) 〕, those living in the central and western regions were higher than those in the eastern region〔OR (95%CI) =1.311 (1.158, 1.483) , OR (95%CI) =1.491 (1.315, 1.692) 〕, those who were working were lower than those who had worked〔OR (95%CI) =0.768 (0.680, 0.866) 〕, and those with annual income > 50 000 per capita were higher than that of less than 20 000 yuan〔OR (95%CI) =1.413 (1.009, 1.978) 〕.

The incidence of chronic diseases comorbidity is higher in the elderly in China. The influencing factors of comorbidity of chronic diseases are multi-level and multi-dimensional. There are complex relationships between different influencing factors, which suggest strengthening multi-dimensional intervention and management of chronic diseases from individual to environment, so as to improve the health level of the population.

When insomnia and obstructive sleep apnea (OSA) coexist, it is referred to as comorbid insomnia and obstructive sleep apnea (COMISA). The prevalence of COMISA in the general population ranges from 0.6% to 19.3%. It is primarily characterized by difficulty falling asleep, frequent nighttime awakenings, early morning awakening, poor sleep quality, snoring or apnea during sleep, unrefreshing or nonrestorative sleep, excessive daytime sleepiness, fatigue, attention impairment, memory impairment, emotional disorders, and impaired quality of life. COMISA can lead to adverse outcomes in multiple systems and increase all-cause mortality. Therefore, it is significant to establish a guidline for the diagnosis, differential diagnosis, and standardized treatment of COMISA. The guideline was organized by the Chinese Academy Society of Sleep Medicine, Chinese Medical Doctor Association and Sleep Medicine Group, China Neurologist Association. It was formed by reviewing domestic and international COMISA diagnosis and treatment practices, through literature evidence review, and after extensive discussion. The guideline summarized the epidemiology, etiology and risk factors, pathophysiological mechanisms, clinical manifestations, assessment methods, diagnosis, differential diagnosis, and treatment studies of COMISA, providing a basis for decision-making in the diagnosis and treatment of COMISA for clinician.

The challenge of aging is becoming increasingly severe in China. Understanding the trends in chronic disease prevalence and comorbidity spectrum among the elderly is crucial for primary healthcare.

To analyze the prevalence and comorbidity patterns of chronic diseases among the elderly in China based on data from the China Health and Retirement Longitudinal Study (CHARLS) .

Participants aged ≥60 years from the 2011 (Wave 1) and 2015 (Wave 3) CHARLS dataset were selected. Their physical examination data and self-reported disease conditions, as well as the questionnaire data were extracted for descriptive statistical analysis of chronic disease and comorbidity prevalence, comparing changes over time. Latent class analysis (LCA) was employed to identify common clusters of comorbidities in the elderly and to assess their impact on daily living activities (evaluated using the Activities of Daily Living Scale, ADL) .

A total of 7 290 individuals in 2011 and 9 845 in 2015, all aged≥60 years, were included in the study. The prevalence of chronic disease comorbidity increased from 85.96% in 2011 to 92.24% in 2015, indicating a significant rise (χ²=109.65, P<0.05). Except for pain and oral diseases, the prevalence of all other chronic diseases increased in 2015 (P<0.05). Combining self-reported diseases and laboratory results, the prevalence of overweight or obesity increased from 39.53% in 2011 to 42.88% in 2015 (χ²=35.12, P<0.01), and abdominal obesity from 45.37% to 47.99% (χ²=18.09, P<0.01). The prevalence of cardiovascular-metabolic disease comorbidity increased from 52.75% in 2011 to 60.49% in 2015 (χ²=64.39, P<0.01), becoming the primary form of chronic disease comorbidity in this population. The LCA categorized the elderly population into five comorbidity patterns in the elderly, with the "cardiovascular-metabolic + musculoskeletal diseases" pattern showing higher ADL scores compared to the "cardiovascular-metabolic diseases""musculoskeletal diseases""respiratory diseases" and "nonspecific comorbidities" patterns.

According to CHARLS data from 2011 and 2015, there is a high prevalence (85.96% in 2011 and 92.24% in 2015) and increasing trend in chronic disease comorbidity among Chinese individuals aged ≥60. Cardiovascular-metabolic comorbidity pattern is the most common, with many cases undetected, and the combination of cardiovascular-metabolic and musculoskeletal diseases has the most significant impact on the daily living abilities of the elderly.

The estimation of the prevalence of multimorbidity and identification of high-risk populations can directly affect the corresponding rational allocation of public health resources.

To comprehensively describe the prevalence trends and population characteristics of multimorbidity among residents in mainland China from 1998-2019 through Meta-analysis.

The databases including Web of Science, PubMed, CNKI, Wanfang Data Knowledge Service Platform and VIP were searched for journal literature relevant to the prevalence of multimorbidity in mainland China from inception to 2022-04-30. Data extraction and quality evaluation were performed on the literature and meta-analysis was performed using Stata 14.0 software. The pooled prevalence of multimorbidity was calculated by using random effects model, and subgroup analysis of the prevalence of multimorbidity was conducted based on survey time (before 2004, 2004-2013, since 2014), gender, region (urban, rural), geographical area (east, central, west, northeast), education level (uneducated, primary school, secondary school and above), marital status (married, others), and research quality (low, medium, high) .

A total of 123 papers were included into analysis with a total sample size of 7 714 313 cases. There was significant heterogeneity among studies (I²=100.0%, P<0.001), and the prevalence of multimorbidity was 36.3%〔95%CI (32.8%, 39.9%) 〕. Meta-linear regression model showed a non-linear increasing trend in the prevalence of multimorbidity from 1998 to 2019〔β=0.013, 95%CI (0.006, 0.019) 〕. The results of the subgroup analysis showed that the prevalence of multimorbidity was higher since 2014〔40.4%, 95%CI (33.0%, 47.8%) 〕 than before 2004〔14.5%, 95%CI (12.5%, 16.5%) 〕 and 2004-2013〔35.2%, 95%CI (32.2%, 38.2%) 〕 (P<0.001) ; the prevalence of multimorbidity was higher among those aged 60-79 years〔38.1%, 95%CI (34.6%, 41.5%) 〕 than those aged ≥80 years〔36.6%, 95%CI (32.5%, 40.8%) 〕, 40-59 years〔27.7%, 95%CI (24.4%, 31.1%) 〕, and <40 years〔10.6%, 95%CI (9.0%, 12.3%) 〕 (P<0.001). There was no significant difference in the subgroup analysis of gender, education level, marital status, region, geographical area, type of chronic disease, quality of research, and the comparison of the prevalence of multimorbidity (P>0.05) .

The prevalence of multimorbidity among residents in mainland China was 36.3% from 1998 to 2019 with a rising trend and significant differences in age, therefore, attention should be paid to the early screening of high-risk population, active and effective strategies for prevention and control should be adopted.

Middle-aged and elderly ischemic stroke patients suffer from multiple co-morbid chronic diseases, and this co-morbidity status has a great impact on the patients' healthy living standard. Currently, there are few studies on the current status of ischemic stroke co-morbidities and the analysis of co-morbidity patterns.

To understand the current status of ischemic stroke co-morbidities in middle-aged and elderly people in Henan Province, and explore the association between ischemic stroke co-morbidities, so as to provide a reference basis for the management of ischemic stroke co-morbidities, as well as the preventive and control measures.

Ischemic stroke patients over 45 years of age attending Henan Provincial People's Hospital from January 2021 to December 2022 were selected for the study, with their chronic disease prevalence counted, the status of ischemic stroke co-morbidities was compared by different demographic characteristics, and the co-morbidity patterns of ischemic stroke in the middle-aged and elderly population were investigated using cluster analysis.

A total of 1 685 middle-aged and elderly ischemic stroke patients were enrolled in this study, of whom 90.0% (1 516/1 685) had at least 1 co-morbid chronic disease; 13.6% (230/1 685) had 2 co-morbid chronic diseases, 26.9% (454/1 685) had 3 co-morbid chronic diseases, and 49.4% (832/1 685) had 4 or more co-morbid chronic diseases. The chronic diseases with high prevalence were hypertension in 1 047 cases (62.1%) and dyslipidemia in 755 cases (44.8%). Among ischemic stroke patients, the prevalence of co-morbidities was higher in females compared with males (χ²=14.516, P<0.05) ; the prevalence of co-morbidities tended to increase with age (χ²_trend=148.889, P<0.001) ; and the prevalence of co-morbidities tended to decrease with higher education (χ²_trend=30.890, P<0.001). Cluster analysis showed four patterns of co-morbidity, which were cardiovascular-metabolic patterns (hypertension, dyslipidemia, heart attack, and diabetes mellitus), patterns characterized by hepato-pulmonary-gastrointestinal-urinary disorders (chronic lung disease, renal disease, hepatic disease, gastrointestinal disorders, and urinary disorders), psychiatric-degenerative patterns (neurological or psychiatric problems, arthritis or rheumatism, disorders related to memory), and cancer.

The prevalence of co-morbidities of ischemic stroke in middle-aged and elderly people in Henan province is high, and their co-morbidity patterns include cardiovascular-metabolic patterns, patterns characterized by hepato-pulmonary-gastrointestinal-urinary disorders, psychiatric-degenerative patterns, and cancers, among which cardiovascular-metabolic patterns are more associated with ischemic stroke, and the screening and prevention of which should be better controlled.

With the rapid progression of aging in China, the challenge of multimorbidity has become a significant concern for both public health and clinical practice. Nocturnal sleep status, including sleep duration and quality, is crucial for regulating body metabolism and physiological functions in the elderly. However, current research on the relationship between nocturnal sleep status and multimorbidity was limited to specific regions or the middle-aged population. The association between nocturnal sleep status and prevalence of multimorbidity among community-dwelling older adults remains ambiguous.

To investigate the association between nocturnal sleep status and prevalence of multimorbidity among community-dwelling older adults.

In April 2023, a total of 11 917 community-dwelling older adults from the Chinese Longitudinal Healthy Longevity and Happy Family Study (CLHLS-HF, wave 2018) were selected as the participants. Multivariate Logistic regression was used to explore the association of sleep duration and sleep quality with the prevalence of multimorbidity, represented by odds ratios (OR) and 95% confidence intervals (95%CI). Additionally, restrictive cubic splines (RCS) based on Logistic regression analysis were utilized to analyze the dose-response relationship between sleep duration and prevalence of multimorbidity.

Of the 11 917 community-dwelling older adults, with an average age of (84.4±11.4) years ranged from 65.0 to 117.0 years, 6 477 were females (54.35%) and 5 440 were males (45.65%). Multivariate Logistic regression results after adjusting for covariates such as gender, age, region, and years of education, indicated that compared to those with 6-8 h of nocturnal sleep duration, older adults with shorter sleep duration (<6 h) had a higher prevalence of multimorbidity (OR=1.51, 95%CI=1.36-1.67, P<0.05) ; compared to those with good sleep quality, individuals with fair sleep quality (OR=1.34, 95%CI=1.22-1.46, P<0.05) and poor sleep quality (OR=2.14, 95%CI=1.91-2.40, P<0.05) were associated with higher prevalence of multimorbidity. RCS plots revealed a "U" -shaped nonlinear association between sleep duration and prevalence of multimorbidity, with an optimal sleep duration of approximately 7 hours.

Community-dwelling older adults with sleep durations less than 6 hours, fair or poor sleep quality, are associated with an increased prevalence of multimorbidity. The optimal sleep duration for community-dwelling older adults is approximately 7 hours. Normal sleep duration and good sleep quality are important for the prevention of multimorbidity.

The high prevalence of multimorbidity among middle-aged and older adults has become a serious issue needing to be addressed by China's healthcare system. The number of chronic diseases is related to health service utilization and medical costs, but there is still a lack of relevant national surveys in China.

To understand the prevalence and features of multimorbidity and to examine its associations with health service utilization and medical costs among middle-aged and older Chinese adults.

Data were collected from the 2018 wave of China Health and Retirement Longitudinal Study (CHARLS) during April to October 2021, involving 16 674 Chinese adults (≥45 years old) . Multimorbidity was defined as the coexistence of two or more of the self-reported 14 chronic conditions. Health service utilization was measured using inpatient service utilization in the past year and outpatient service utilization in the past month. Medical costs were measured using total inpatient cost and out-of-pocket (OOP) cost for inpatient care in the past one year, total outpatient costs and OOP cost for outpatient care in the past one month. Logistic regression was used to estimate the association between the number of chronic diseases and health service utilization. Quantile regression was adopted to estimate the association between the number of chronic diseases and medical costs.

Of all participants, 9 561 (57.34%) had multimorbidity. 2 624 (15.74%) had utilized inpatient services in the past year, and 2 588 (15.52%) used outpatient services in the past one month. Inpatient service utilization, outpatient service utilization, total inpatient cost, OOP cost for inpatient care, total outpatient cost, and OOP cost for outpatient care varied significantly by the number of chronic diseases (P<0.05) . Multivariate Logistic regression analysis indicated that the number of chronic diseases was associated with inpatient service utilization (P<0.05) . Suffering from 1, 2, 3, 4 and ≥5 chronic diseases was associated with 1.882 times〔95%CI (1.547, 2.290) 〕, 2.939 times〔95%CI (2.429, 3.555) 〕, 4.231 times〔95%CI (3.490, 5.130) 〕, 5.723 times〔95%CI (4.680, 7.000) 〕, and 8.671 times〔95%CI (7.173, 10.482) 〕 higher rate of inpatient service utilization, respectively. Having 1, 2, 3, 4 and ≥5 chronic diseases was associated with 1.684 times〔95%CI (1.421, 1.995) 〕, 2.481 times〔95%CI (2.101, 2.931) 〕, 3.691 times〔95%CI (3.115, 4.374) 〕, 3.774 times〔95%CI (3.134, 4.544) 〕, and 5.577 times〔95%CI (4.698, 6.620) 〕 higher rate of outpatient service utilization, respectively. Each increased chronic disease was associated with an increase in both total inpatient costs and OOP for inpatient care at the upper and middle (50, 75 and 90 percentiles) percentile levels, with larger effects on the upper percentile 〔90th percentile Coeff (95%CI) =1 248.43 (219.20, 2 277.66) for total hospital costs; 90th percentile Coeff (95%CI) =706.36 (266.87, 1 145.86) for OOP for inpatient care〕. Each increased chronic disease was also associated with an increase in both total outpatient costs and OOP for outpatient care, and the effects on the upper percentiles were larger〔90th percentile Coeff (95%CI) =196.33 (31.06, 361.61) for total outpatient costs; 90th percentile Coeff (95%CI) =128.56 (26.83, 230.28) for OOP for outpatient care〕.

In middle-aged and older Chinese adults, multimorbidity was highly prevalent, and the increase in the number of coexisted chronic diseases was associated with higher rate of health service utilization and medical costs. The government should pay more attention on primary care to manage the demand for health services and medical costs associated with multimorbidity.

Osteoporosis (OP) and lumbar disc herniation (LDH) are two common orthopedic diseases encountered clinically, which are closely related and often coexisted, causing great suffering to middle-aged and elderly people along with the accelerated process of population aging.

To perform a cross-sectional survey on the prevalence and associated factors of LDH in OP in community-dwelling middle-aged and elderly people in Beijing, providing a reference for clinical prevention and treatment of this disease.

From November 2017 to July 2018, 1 540 residents with complete demographics and bone mass measurement data who lived in 10 communities in Chaoyang District and Fengtai District of Beijing were selected. A survey was conducted with the residents for understanding their data collected on-site, including demographics, fracture history, fall history, history of hereditary disease, bone mineral density, EuroQol Health Utility score, then those with OP were further selected and divided into two groups by the prevalence of LDH. Multivariate Logistic regression analysis was used to explore the influencing factors of LDH in OP.

A total of 521 cases of OP attended the survey, except for one with missing information of LDH, the other 520 cases (80 with LDH, and 440 without LDH) were included for final analysis. Multivariate Logistic regression analysis indicated that after controlling for age and BMI, falls〔OR=1.96, 95%CI (1.02, 3.78) , P=0.044〕, fracture〔OR=1.80, 95%CI (1.04, 3.12) , P=0.035〕and pain/discomfort〔OR=2.43, 95%CI (1.41, 4.18) , P=0.001〕were independently associated with LDH in OP.

The coexistence of LDH and OP was common in this population. Falls, fractures, and pain/discomfort may be influencing factors of LDH in OP.

The cases of multiple chronic conditions are increasing yearly, yet their medication adherence is unsatisfactory though taking medication as prescribed is recognized as the most effective measure to manage chronic diseases. To improve the prevention and control of chronic diseases, it is crucial to identify the causes and influencing factors of non-compliance in multiple chronic conditions patients.

To classify the medication adherence and to identify the associated factors of each class of medication adherence in multiple chronic conditions patients.

This investigation was conducted between July and September 2021 with a convenience sample of 267 inpatients from two tertiary A general hospitals of Henan Province using the Chinese version of Beliefs about Medicines (BMQ-C) , the Chinese version of 8-item Morisky Medication Adherence Scale (MMAS-8-C) , and the Medication Knowledge Scale (MKS) . Latent class analysis was used to classify the medication adherence. Demographic characteristics, medication use, medication knowledge and medication beliefs were compared by the class of medication adherence. Multiple Logistic regression was used to explore the associated factors of each class of medication adherence.

The medication adherence of the participants was divided into three latent classes, namely subjective poor medication adherence, overall poor medication adherence, and overall good medication adherence, and the prevalence of the three classes was 18.0%, 34.4% and 47.6%, respectively. The education level, occupational status after an illness, living situation, household monthly income per person, financial resources, prevalence of having pharmacist guidance, number of medications, frequency of taking medication, years of taking medication, the BMQ-C score, and MKS score in the participants differed significantly by the class of medication adherence (P<0.05) . By multiple Logistic regression analysis, compared with patients with subjective poor medication adherence, those with overall good medication adherence had higher prevalence of having pharmacist guidance, and higher average scores of BMQ-C and MKS, and lower prevalence of retirement due to illness and offspring's support as the only financial resource (P<0.05) . Compared with those with overall poor medication adherence, those with overall good medication adherence had higher prevalence of retirees, taking medication once a day, and having pharmacist guidance, as well as higher average scores of BMQ-C and MKS (P<0.05) .

The medication adherence in these multiple chronic conditions patients could be classified into three latent classes. More attention should be given to those who were retired due to illness or financially supported by their children, because they were prone to having poor medication adherence. Those who had lower frequency of medication use, medication guidance from a pharmacist, and higher levels of medication knowledge and beliefs were prone to having good medication adherence.

Subjective cognitive decline (SCD) is a target for early prevention of Alzheimer's disease (AD). AD is closely related to multimorbidity, but the correlation of SCD with multimorbidity has not been well defined.

To investigate the correlation between SCD and multimorbidity in the elderly, providing a theoretical basis for early prevention and intervention of AD.

From January 2021 to June 2022, 612 elderly people aged≥60 years were sampled by convenience sampling method in urban communities and elderly care institutions in Guangzhou. The objective cognitive function was assessed using the Chinese version of Montreal Cognitive Assessment-Basic (MoCA-BC), Chinese version of Clinical Dementia Rating Scale (CDR-C), and Chinese version of Hachinski Ischemic Scale (HIS-C). SCD was diagnosed using the conceptual framework proposed by the working group of the Subjective Cognitive Decline Initiative and Chinese version of Subjective Cognitive Decline-Questionnaire 9 (SCD-Q9-C). Then according to the assessment results, participants were divided into SCD group (having normal overall objective cognitive function, SCD and SCD-Q9-C score≥5) and normal cognitive (NC) group (having normal overall objective cognitive function, and SCD-Q9-C score<5). A general information questionnaire to collect socio-demographics〔gender, age, place of residence (community or elderly care institution), years of education, marital status, type of occupation before retirement, monthly income〕and health-related information〔body mass index, waist circumference, habits of smoking, alcohol consumption and drinking tea, exercise frequency, habit and average duration of siesta, sleep quality assessed using the Chinese version of Pittsburgh Sleep Quality Index (PSQI-C), depressive symptoms assessed using the Chinese version of Patient Health Questionnaire (PHQ-9-C), anxiety symptoms assessed using the Chinese version of Generalized Anxiety Disorder Scale-7 (GAD-7-C), and activities of daily living (ADLs) assessed using the ADL Scale for Chinese Adults〕. Besides, another questionnaire to collect the history of chronic illness. The level of multimorbidity was classified into three categories〔no multimorbidity (0-1), low multimorbidity (2-4) and high multimorbidity (≥5) 〕by the number of chronic conditions. A binary Logistic regression analysis was used to explore the effect of multimorbidity on the SCD.

The mean SCD-Q9-C score was (4.20±1.95) in 612 elderly people in this survey. Two hundred and fifty cases (40.8%) and 362 cases (59.2%) were assigned to the SCD group, and NC group, respectively. Univariate analysis showed statistically significant differences in gender, age, years of education, type of occupation before retirement, monthly income, tea drinking habits, sleep quality, depressive symptoms, anxiety symptoms and ADL scores between SCD and NC groups (P<0.05). Five hundred and seventy-four cases (93.8%) had chronic diseases, and 475 (77.6%) of them had multimorbidity, including 352 (57.5%) with low multimorbidity level and 123 (20.1%) with high multimorbidity level. The differences in multimorbidity prevalence, multimorbidity level, diabetes, arthritis and osteoporosis between SCD and NC groups were statistically significant (P<0.05). Binary Logistic regression analysis showed that older age, poor sleep quality, presence of anxiety symptoms, poor ADLs, and high level of multimorbidity were statistically significant risk factors for SCD (P<0.05), with the risk of SCD being 1.826〔95%CI (1.037, 3.216) 〕times higher for high multimorbidity level than for no multimorbidity (P<0.05). Longer years of education was a protective factor for SCD (P<0.05) .

High multimorbidity level is associated with increased risk of SCD. Community and elderly care providers can use multimorbidity as an assessment indicator of cognitive decline, and collaboratively implement management of multimorbidity and related factors to actively identify and intervene in SCD in order to delay the development of AD in older adults and promote healthy ageing.

With the acceleration of population aging, the health problems of middle-aged and elderly people are prominent. Multimorbidity seriously threaten the health and quality of life of middle-aged and elderly people, and hinder the progress of Healthy China Initiative. It is of positive significance to explore the relationship between multimorbidity and social determinants of health.

To understand the multimorbidity and social determinants of health among the middle-aged and elderly people in Ningxia, and analyze the relationship between the social determinants of health and multimorbidity, so as to provide reference for the health management and intervention strategies for middle-aged and elderly people.

A multi-stage stratified random sampling method was used to investigate the health related data of 1 997 middle-aged and elderly people in 10 districts/counties of Shizuishan City, Yinchuan City, and Guyuan City in Ningxia from June 27, 2022 to August 27, 2022. The Apriori algorithm was used to analyze the comorbidity patterns of middle-aged and elderly people in Ningxia, and unconditional Logistic regression analysis was used to explore the correlation between multimorbidity and social determinants of health among middle-aged and elderly people in Ningxia.

There were 418 middle-aged and elderly people in Ningxia with a comorbidity rate of 20.9%; the results of association rules showed 14 comorbidity patterns, of which 11 were related to coronary heart disease, 9 to hypertension, and 9 to diabetes; the results of unconditional Logistic regression analysis showed that middle-aged and elderly people aged ≥60 years, with 2-3 children, established family archives, retired or unemployed work status, and resident pension insurance had a higher incidence of multimorbidity (P<0.05), while middle-aged and elderly people with nighttime sleep duration of 7-8 hours and more than 8 hours, and education level of college or above had a lower incidence of multimorbidity (P<0.05). Conclusion The factors influencing the comorbidity of chronic diseases in middle aged and elderly people involve individual, community and social aspects. It is recommended to intervene in chronic comorbidity patients from a multidimensional perspective with a view to improving the health of the population.

As the aging society develops, multimorbidity is increasingly prevalent in an increased number of older adults, which imposes a heavy treatment burden on the group, but the composition of treatment burden of elderly patients with chronic comorbidity in China is not clear.

To understand the real experience of treatment burden in elderly patients with multimorbidity, providing a theoretical basis for promoting the research on treatment burden in China.

By use of purposive sampling, 21 older inpatients with multimorbidity were selected from three hospitals (one is primary level, another is secondary and another is tertiary) in Chengdu from January to June 2021. Individual, face-to-face, in-depth, semi-structured interviews were utilized to collect their experiences of treatment burden, and the data were recorded, and analyzed using Colaizzi's method of data analysis.

Of the participants, eight were women, and 13 were men; 10 were selected from the tertiary hospital, seven from the secondary hospital, and four from the primary hospital. Six themes were summarized: economic burden, drug burden, self-management burden, medical service burden, social burden and psychological burden.

Taken overall, the treatment burden was relatively heavy in older inpatients with multimorbidity. To reduce the treatment burden and improve the efficacy in this group, it is recommended that medical workers should pay attention to their treatment burden, and formulate individualized treatment plan for them.

Cognitive frailty is a cognitive impairment state between normal aging and dementia. Cognitive frailty is associated with higher possibility of negative clinical events than simple frailty or cognitive impairment in older people. As cognitive frailty could be reversible toa certain degree, early identification of high-risk groups and timely intervention are particularly important in reducing adverse prognoses and improving the quality of life of elderly patients in their later years.

To investigate the prevalence and influencing factors of cognitive frailty, and its relationship with two-year post-discharge mortality in hospitalized elderly patients with comorbidities.

The data were collected from part of the project "Research and Demonstration of Clinical Management and Community-based Continuing Care Models for Older People with Comorbidities", involving a cluster sample of older inpatients with comorbidity aged≥60 years recruited from Department of Gerontology, Chengdu Fifth People's Hospital from November 2015 to January 2018. Demographics, chronic disease prevalence, and comprehensive geriatric assessment results were collected. Cognitive frailty was assessed by the FRAIL scale and Mini-Mental State Examination. Binary Logistic regression was used to analyze the influencing factors of cognitive frailty. The survival status was investigated at the end of a two-year follow-up after discharge. Cox regression was used to analyze the relationship of cognitive frailty with two-year post-discharge mortality.

A total of 554 cases were included, and 15.9% (88/554) of them had cognitive frailty. Compared with non-cognitive frailty group, cognitive frailty group had older average age, lower prevalence of high school education or above, lower average family care score, higher prevalence of malnutrition, depression, dependence in activities of daily living and balance dysfunction (P<0.05) . Binary Logistic regression analysis showed that malnutrition, balance dysfunction, and family care disorder were independent factors of cognitive frailty. During the follow-up period, 456 patients (82.3%) survived, 81 (14.6%) died, and 17 (3.1%) were lost to follow-up. After controlling for confounding factors, Cox regression analysis indicated that, the risk of two-year post-discharge mortality in cognitive frailty group was 2.039〔95%CI (1.060, 3.922) 〕times higher than that of those with normal cognitive function and non-frailty, and was 5.266〔95%CI (3.159, 8.778) 〕times higher than that of those with simple cognitive frailty (P<0.05) .

Cognitive frailty is common among elderly inpatients with comorbid conditions, and it can increase the relative risk of two-year post-discharge mortality. Clinical medical workers should pay more attention to this group to identify high-risk individuals of cognitive frailty as soon as possible and give them preventive interventionsin time.

In the context of aging society in China, the prevalence of Alzheimer's disease increases and multimorbidity becomes more common with years. However, the extensive investigations of Alzheimer's disease in Hunan province have not been reported adequately and the multimorbidity relationship between relevant diseases remains unclear.

To completely understand the prevalence of Alzheimer's disease in residents aged 65 or above in Hunan and analyze its multimorbidity relationships with 11 common chronic diseases.

The residents aged 65 years and above in 30 districts (counties), 60 streets (townships), and 180 neighborhood (village) committees in Hunan Province were randomly selected between April and May 2021 by using stratified multistage sampling method. Alzheimer's disease was diagnosed by a neurologist or psychiatrist using the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA), after using the Community Screening Interview for Dementia (CSI-D) or the 8-item ascertain dementia (AD8) as the screening tools. In addition, all respondents were investigated for the prevalence of hypertension, cerebrovascular disease, ischemic heart disease, rheumatoid arthritis, intervertebral disc disease, diabetes, gastroenteritis, chronic obstructive pulmonary disease, calculous cholecystitis, peptic ulcer and cancer.

A total of 5 979 residents were sampled, 5 616 of them completed the examinations and 785 (13.98%) were diagnosed with Alzheimer's disease. There were significant differences in the prevalence of Alzheimer's disease among respondents with different regions, gender, age, smoking history and presence of other chronic diseases (P<0.05). The total number of patients with other chronic diseases among all respondents was 5 606, with the top five diseases of hypertension〔2 205 (39.33%) 〕, intervertebral disc disease〔553 (9.86%) 〕, diabetes 〔526 (9.38%) 〕, cerebrovascular disease〔492 (8.78%) 〕, and ischemic heart disease〔467 (8.33%) 〕. The top five diseases in the dementia patients were hypertension〔325 (41.40%) 〕, cerebrovascular disease〔111 (14.14%) 〕, ischemic heart disease〔91 (11.59%) 〕, rheumatoid arthritis 〔89 (11.33%) 〕, and intervertebral disc disease〔81 (10.31%) 〕. The prevalence of dementia in patients with no chronic disease, with 1, 2, 3 or more types of other chronic diseases was 11.46% (214/1 867), 13.66% (309/2 262), 17.50% (176/1 006), and 18.26% (86/471), respectively. There were statistically significant differences in the prevalence of Alzheimer's disease between the subjects with and without gastroenteritis, rheumatoid arthritis, cerebrovascular disease, chronic obstructive pulmonary disease, and ischemic heart disease, respectively (P<0.05). Binary Logistic regression analysis showed that living in rural areas〔OR=2.048, 95%CI (1.655, 2.536) 〕, female〔OR=1.388, 95%CI (1.163, 1.655) 〕, aging〔OR=1.348, 95%CI (1.270, 1.431) 〕, and suffering from other chronic diseases〔OR=1.195, 95%CI (1.101, 1.297) 〕 were risk factors for the development of Alzheimer's disease in residents aged 65 years and above (P<0.05). The investigation results of timely medication taking in the patients with Alzheimer's disease showed that 12.79% (99/774) reported difficulties, 6.59% (51/774) needed help, and 2.97% (23/774) were unable to complete independently.

The prevalence of Alzheimer's disease in residents aged 65 years and above in Hunan Province increases with the number of other chronic diseases and correlates with multiple diseases. Great attention should be paid on the self-care ability and family care burden of Alzheimer's disease by society. The prevalence and multimorbidity of Alzheimer's disease were basically grasped by the investigation, in order to provide an objective basis for the formulation of policies on its prevention and treatment.

In China, as population aging quickens, multimorbidity has become a major public health problem threatening the health of elderly people. Multimorbidity has a negative impact on mental health, but there is a lack of research on its association with anxiety symptoms in elderly people.

To investigate the influence of multimorbidity on anxiety symptoms among Chinese elderly people, so as to provide references for improving mental health for older people with multimorbidity.

We selected 6 854 older adults (≥65 years old) from the participants of the Chinese Longitudinal Healthy Longevity Survey 2018 from December 2022 to February 2023. The 7-item Generalized Anxiety Disorder Scale was used to assess symptoms of anxiety. Multimorbidity was defined as having two or more coexisting chronic conditions, while non-multimorbidity was defined as having only one or no chronic condition. Propensity score matching (PSM) was used tomatch individuals with and without multimorbidity. The association of multimorbidity with anxiety symptoms was analyzed by univariate and multivariate Logistic regression analyses.

Among the 6 854 cases, the prevalence of multimorbidity and anxiety symptoms was 38.04% (2 607/6 854), and 10.53% (722/6 854), respectively. There were 4 247 cases (61.96%) without multimorbidity, of whom 2 102 (30.67%) had no chronic disease, and 2 145 (31.29%) had one chronic disease. A total of 2 282 pairs of multimorbidity and non-multimorbidity (4 564 cases altogether) were obtained after matching. Multivariate Logistic regression analysis showed that multimorbidity was the risk factor of anxiety symptoms〔OR=1.399, 95%CI (1.166, 1.679), P<0.001〕. Besides that, gender, ability to perform activities of daily living and receiving a pension were also related to anxiety symptoms (P<0.05). Five hundred and twenty-two pairs (1 044 cases altogether) were obtained after matching the subjects with multimorbidity and those with one chronic disease using PSM, and the analysis found that those with one chronic disease had higher prevalence of anxiety symptoms〔64.76% (215/332) vs 43.12% (307/712) 〕 (P<0.001) .

Compared with their counterparts without multimorbidity, elderly people with multimorbidity had higher risk of anxiety symptoms, so more attentions should be paid to the mental health of these people.

As population ageing accelerates and life expectancy increases, multimorbidity and disability pose challenges to health and social care systems worldwide. Although multimorbidity is closely related to disability, there is still a lack of research on the impact of multimorbidity on disability in rural middle-aged and elderly people.

To evaluate the influence of multimorbidity on disability in rural middle-aged and elderly people using the propensity-score matching (PSM) , providing a reference for formulating strategies for the management of multimorbidity and disability in this population.

The data of 11 088 rural middle-aged and elderly people (≥45 years old) were collected from the 2018 China Health and Retirement Longitudinal Study in March 2022, including demographics, chronic disease prevalence, and disability measured by activities of daily living (ADLs) , and instrumental activities of daily living (IADLs) . Participants were divided into multimorbidity and non-multimorbidity groups by the prevalence of multimorbidity (defined as having ≥2 chronic conditions) , and then matched using PSM with a 1∶1 ratio. Conditional Logistic regression model for paired binary data was used to assess the impact of multimorbidity on ADL disability and IADL disability.

Of 11 088 ural middle-aged and elderly people with chronic diseases, 2 711 (24.45%) had ADL disability, 4 216 (38.02%) had IADL disability, and 7 673 (69.20%) were multimorbidity patients. The prevalence of ADL disability or IADL disability differed significantly by gender, age, marital status, education level, sleep duration, smoking, drinking, disability status, participation in social activities, and prevalence of multimorbidity (P<0.05) . There were statistically significant differences in gender, age, marital status, education level, sleep duration, smoking, drinking, disability status, and participation in social activities between the two groups before matching (P<0.05) . A total of 3 391 pairs were derived after PSM with matched covariates. Logistic regression analysis showed that multimorbidity prevalence increased the risk of ADL disability by a factor of 2.25〔OR (95%CI) =2.25 (1.96, 2.59) , P<0.001〕 and elevated the risk of IADL disability by a factor of 1.52〔OR (95%CI) =1.52 (1.36, 1.71) , P<0.001〕.

PSM is beneficial for reducing confounding bias in study groups. Multimorbidity would increase the risk of disability in rural middle-aged and elderly people. It is suggested to value the government input on resources and policies to strengthen the prevention and management of multimorbidity and disability in this group of people.

The number of elderly comorbidity patients in our country is continuously increasing. With the accumulation of chronic diseases, older adults experience varying degrees of health loss. Currently, there is a lack of research analyzing the multi-level factors influencing the number of chronic conditions in elderly comorbidity patients.

To explore the factors influencing the number of chronic conditions in elderly patients from different levels combining with the etiology and characteristics of chronic diseases based on the health ecology model, so as to provide evidence for the management and prevention of chronic diseases in community-dwelling elderly comorbidity patients in our country.

In February 2023, a multi-stage stratified cluster random sampling method was used to select community-dwelling elderly (≥60 years old) comorbidity patients in Guangdong province as the survey subjects. A face-to-face interview was conducted using the "Survey Questionnaire on the Status and Influencing Factors of Elderly Patients with Multiple Chronic Conditions", which was based on the health ecology model and included five levels of individual trait, behavioral characteristic, interpersonal relationship, living and working conditions, and policy environment. The number of chronic conditions in elderly comorbidity patients was considered as the dependent variable, and an unordered multivariate Logistic regression analysis was conducted by incorporating independent variables according to the five levels.

A total of 1 000 questionnaires were distributed, and 987 valid questionnaires were collected, with a recovery rate of 98.7%. Among the 987 elderly comorbidity patients, 346 (35.1%) had two concurrent chronic diseases, 456 (46.2%) had three concurrent chronic diseases, and 185 (18.7%) had more than three concurrent chronic diseases. The results of unordered multivariate logistic regression analysis showed that, compared to elderly patients with two concurrent chronic diseases, disease duration less than 6 years and 6-10 years, local urban household were risk factors for elderly patients with three concurrent chronic diseases (P<0.05), with OR (95%CI) values of 2.100 (1.284-3.435), 1.948 (1.201-3.158), and 4.103 (1.496-11.250), respectively. Having at least 6 hours of sleep daily, self-rating good health status, taking 1-3 types of medication daily, regularly participating in social activities, level of junior high school or below and high school/secondary school, and having urban employee medical insurance/rural resident medical insurance were protective factors for elderly patients with three concurrent chronic diseases (P<0.05), with OR (95%CI) values of 0.528 (0.322-0.867), 0.570 (0.325-0.998), 0.385 (0.261-0.569), 0.348 (0.208-0.582), 0.412 (0.175-0.972), 0.486 (0.298-0.790), and 0.392 (0.242-0.634), respectively. Being male, exercising less than 3 times a week were risk factors for elderly patients with more than three concurrent chronic diseases (P<0.05), with OR (95%CI) values of 2.563 (1.634-4.021), 2.990 (1.429-6.256), respectively. Having at least 6 hours of sleep daily, self-rating good and fair health status, taking 1-3 types of medication daily, having an annual average income below ≤30 000 and >30 000-50 000 yuan, and having urban employee medical insurance/rural resident medical insurance were protective factors for elderly patients with more than three concurrent chronic diseases (P<0.05), with OR (95%CI) values of 0.300 (0.159-0.565), 0.247 (0.125-0.487), 0.448 (0.240-0.837), 0.288 (0.178-0.467), 0.318 (0.155-0.654), 0.489 (0.293-0.816), and 0.416 (0.229-0.755), respectively.

The proportion of elderly comorbidity patients having 2-3 types of chronic diseases is relatively high in Guangdong province, accounting for over 80%. The factors influencing the number of chronic conditions in elderly comorbidity patients are complex, including gender, duration of disease, physical activity, sleep quality, self-rated health status, medication adherence, household registration type, supervision by children or family members in medication adherence or exercise, income level, educational level, and type of medical insurance. Moreover, there are significant differences in the risk factors across different comorbidity counts. Therefore, corresponding intervention measures should be implemented at different levels to reduce the number of chronic conditions in elderly comorbidity patients and improve their overall health level.

Multimorbidity increases the burden of disease and treatment for patients, which is becoming an essential research issue in the field of public health and primary care. As medical research advances, the understanding of how to deal with the challenge of multimorbidity is undergoing a profound shift, the most significant of which is the focus on the potential influence of social and environmental factors on disease clustering and development. Syndemic theory provides a new perspective for exploring the clustering of multiple conditions, as well as their interaction with social and environmental factors, which is of great significance for analyzing the interaction of chronic comorbidities at the social and environmental levels, and contributing to improve health outcomes of vulnerable populations. However, there is a lack of introduction and research on this theory in China. This article mainly reviews the basic concepts and viewpoints of the syndemic theory, as well as the classical models proposed by foreign scholars, analyzes the common disease synergistic factors with previous research findings, and puts forwards suggestions and countermeasures for general practitioners in China to improve the quality of managing multimorbidity.

Multimorbidity accelerates cognitive decline and leads to an increased risk of cognitive impairment. However, existing studies have mainly explored the cognitive status of patients with a single or specific chronic disease, and the patient with multimorbidity remains to be urgently explored. The present study describes the epidemiological characteristics of cognitive impairment in multimorbidity, summarizes the influencing factors, organizes the association patterns between multimorbidity and cognitive impairment, elucidates the mechanisms underlying their occurrence, and finally proposes preventive and control strategies. The findings of this study are intended to serve as a valuable reference for future efforts in preventing and treating cognitive impairment in multimorbidity.

The prevalence of comorbidity in the elderly is showing a rising trend year by year with the acceleration of population aging. Comorbidity is a key risk factor for frailty in the elderly. Then frailty only increases the risk of adverse health outcomes for patients with comorbidity, but also significantly increases their family medical expenses. It has a certain guiding value for the management of comorbidity to identify the frailty conditions of elderly patients with comorbidity as early as possible.

To systematically review the prevalence of frailty in elderly patients with comorbidity.

CNKI, VIP, CBM, WanFang, PubMed, EmBase, Web of Science and Cochrane Library were searched in December 2021 for the investigation studies on the current status of frailty in elderly patients with comorbidity published from inception to December 4, 2021. Two researchers performed literature screening and data extraction independently. The cross-sectional study quality rating scale and Newcastle-Ottawa Scale (NOS) recommended by Agency for Healthcare Research and Quality (AHRQ) were used to assess the risk of bias of the included studies and Stata 14.0 was adopted for meta-analysis.

A total of 25 studies involving 16 062 elderly patients with comorbidity were included. Meta-analysis results showed that the prevalence of frailty and pre-frailty in elderly patients with comorbidity was 26.7%〔95%CI (21.9%, 31.5%) 〕and 47.7%〔95%CI (43.9%, 51.4%) 〕. Subgroup analysis showed that the prevalence of frailty in older adults with≥2, ≥3, ≥4, and≥5 chronic diseases was 25.1%〔95%CI (19.3%, 30.8%) 〕, 27.4%〔95%CI (13.7%, 41.0%) 〕, 60.7%〔95%CI (29.0%, 92.4%) 〕, and 23.5%〔95%CI (8.6%, 38.5%) 〕, respectively. The prevalence of frailty in elderly patients with comorbidity in Oceania (52.1%) and Asia (31.3%) were significantly higher than Europe (16.9%) and South America (13.2%) . The prevalence of frailty in elderly patients with comorbidity in hospital (26.2%) was significantly higher than community (23.2%) . The prevalence of frailty in elderly patients with comorbidity screened by Clinical Frailty Scale (CFS) , Fried frailty phenotype scale and FRAIL Scale was 42.8%〔95%CI (38.4%, 47.1%) 〕, 22.2%〔95%CI (17.8%, 26.7%) 〕and 8.5%〔95%CI (6.3%, 10.6%) 〕, respectively. The prevalence of frailty in elderly patients surveyed in 2001—2010, 2011—2015, and 2016—2020 was 21.0%〔95%CI (13.2%, 28.8%) 〕, 19.0%〔95%CI (13.1%, 24.8%) 〕and 37.7%〔95%CI (22.6%, 52.9%) 〕, respectively.

The prevalence of frailty in elderly patients with comorbidity is gradually increasing, with differences by number of co-morbidities, continents, assessment tools and study sites. Therefore, relevant personnel should pay attention to early screening of frailty in elderly patients with comorbidity and take timely measures to prevent the development of frailty in elderly patients with comorbidity.

In the context of increasing population aging, maintaining the health of the elderly is the key to successful aging. Multimorbidity is an important factor threatening the health of the elderly, and its relationship with the health promotion behaviors of the elderly has been rarely reported.

To understand the multimorbidity patterns and distribution of health promotion behaviors among the elderly in Ningxia, analyze the relationship between multimorbidity patterns and health promotion behaviors in the elderly, so as to provide a reference for the development of management and intervention strategies for the health of elderly.

The population aged 65 years and above in Ningxia were selected as study subjects by using random cluster sampling method from January 2021 to July 2021, and surveyed by self-designed questionnaire〔including general information questionnaire, patient health questionnaire-9 (PHQ-9) , mini-mental state examination (MMSE) , health promoting lifestyle profile-Chinese version (HPLP-C) 〕. Multimorbidity patterns of the elderly was analyzed by association rules of Apriori algorithm, the correlation between multimorbidity and health promotion behaviors of the elderly was analyzed by multivariable Logistic regression analysis.

A total of 2 010 older adults aged 65 years and above were included, with the multimorbidity rate of 31.00% (623/2 010) . The most common binary multimorbidity pattern was coronary heart disease and hypertension〔25.36% (158/623) 〕, the most common ternary multimorbidity pattern was hypertension, coronary heart disease and stroke〔4.49% (28/623) 〕. The association rules revealed 16 patterns of multimorbidity, 15 of which were related to hypertension, 10 were related to coronary heart disease, and 7 were related to asthma. The multivariate Logistic regression analysis showed that compared with older adults with poor health promotion behaviors, those with general〔OR (95%CI) =0.364 (0.185, 0.714) 〕, good〔OR (95%CI) =0.488 (0.251, 0.948) 〕, excellent〔OR (95%CI) =0.426 (0.213, 0.853) 〕health promotion behaviors had a lower risk of multimorbidity (P<0.05) . HPLP-C physical activity〔OR (95%CI) =0.960 (0.925, 0.997) 〕and stress management〔OR (95%CI) =0.963 (0.938, 0.989) 〕dimension scores in older adults were negatively associated with the occurrence of multimorbidity; HPLP-C health responsibility〔OR (95%CI) =1.038 (1.013, 1.063) 〕dimension score was positively associated with the occurrence of multimorbidity.

The multimorbidity patterns of the elderly in Ningxia are complex, and there is an association between health promotion behaviors and occurrence of multimorbidity. The risk of multimorbidity can be reduced by interventions such as encouraging the elderly to practice health promotion behaviors and improve their lifestyles.

Cardiovascular disease is the leading cause of death among Chinese residents, hypertension, hyperglycemia and hyperlipidemia are important risk factors for cardiovascular disease. Therefore, China proposes to implement the co-management of these three diseases. At present, there is a lack of relevant research on the three diseases comorbidities of the Kazakhs in Xinjiang.

To investigate the prevalence and status of dyslipidemia, hypertension and diabetes comorbidities among Kazakhs, and explore the related factors.

Kazakh residents over 18 years old from Dure Town and Tuerhong Township with large populations mainly consist of Kazakh in Fuyun County, Altay Prefecture, Xinjiang from March to June in 2022 were selected to conduct the cross-sectional study. Patient information was collected through questionnaires (general information, history of smoking, alcohol consumption, and diseases), physical examination (waist circumference, hip circumference, height, weight, blood pressure, heart rate, etc.), and laboratory tests (total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, triacylglycerol, and fasting blood glucose, etc.). Multivariate Logistic regression analysis was used to explore the factors related to dyslipidemia, hypertension and diabetes comorbidities among Kazakhs.

A total of 4 835 Kazakh residents were included, 48.2% (2 231/4 835) and 51.8% (2 504/4 835) were male and female respectively, with an average age of (45.8±12.7) years. The standardized prevalence of dyslipidemia, hypertension and diabetes mellitus were 37.9%, 21.1% and 4.0%, respectively. The standardized prevalence of hypercholesterolemia, high low-density lipoprotein cholesterol, low high-density lipoprotein cholesterol and hypertriacylglycerolemia in the dyslipidemic population was 24.1%, 24.8%, 10.0% and 7.3%, respectively. The standardized prevalence of comorbidities was 11.8%. Univariate Logistic regression analysis showed that gender, age, BMI, waist circumference, hip circumference, heart rate, marital status, and education level were correlated with the comorbidities (P<0.05). Multivariate Logistic regression analysis showed that gender, age, marital status, BMI and heart rate were correlated with three diseases comorbidities (P<0.05) .

The prevalence of dyslipidemia is higher than that of hypertension and diabetes, and dyslipidemia is dominated by hypercholesterolemia. The comorbidities of dyslipidemia and hypertension are the most common among the three diseases comorbidities, and the elderly, males and people with high BMI should be prioritized for the three diseases co-management.

The continuous increase in the prevalence of comorbidities has severe challenges to population health management, and the World Health Organization (WHO) recommends the development of integrated medical care models to cope with the pressure of health management of patients with comorbidities. In this paper, we constructed an integrated management model for geriatric comorbidities under medical association based on PDSA theory, in order to continuously improve the management ability and effect in the reciprocal cycle of "plan-execute-research-act". The model consists of four key elements, including management team, management process, management tools and management effect. Based on previous intervention research, the model integrates patient-centered care, multidisciplinary team, patient self-management and other intervention methods, and relies on big data technology to establish a decision support platform, thus realizing the whole life cycle health management of patients with comorbidities.

Chronic obstructive pulmonary disease (COPD) patients often present with multiple comorbidities, which increase the complexity of treatment and the healthcare of burden. While comorbidities significantly impact the management of COPD patients, existing research primarily focuses on individual comorbidities, lacking systematic analysis of multiple comorbidity patterns and hospitalization costs.

To investigate the comorbidity characteristics and patterns in patients with COPD, analyzing how different features and comorbidity patterns affect hospitalization costs. The findings will provide a basis for personalized health management and resource allocation for COPD patients.

A retrospective analysis was conducted on 5 061 inpatients diagnosed with COPD at the First Affiliated Hospital, Guangzhou Medical University from 2020 to 2023. Systematic clustering analysis was employed to construct dendrograms, identifying comorbidity patterns among COPD patients. Multiple group comparisons were performed to assess the basic characteristics of these patterns, then multiple linear regression analysis was utilized to evaluate the impact of each comorbidity pattern on total hospitalization costs, western medicine costs, and antibacterial medication costs.

There are a total of 4 343 patients with COPD, and the comorbidity was 85.81%. Systematic clustering analysis identified six comorbidity patterns among COPD patients: cardiovascular and metabolic diseases, hepatorenal diseases, digestive system diseases, arthropathy diseases, cancer and respiratory system diseases. There were significant differences in sex, age, BMI and smoking history among patients with 6 comorbidity models (P<0.05). Multiple linear regression analysis revealed that BMI, cancer pattern, and respiratory system diseases pattern all had impacts on total hospitalization costs, western medicine costs and antibacterial medication costs (P<0.05), with the respiratory system diseases pattern having the most substantial impact on total hospitalization costs (β=0.125, P<0.001) .

Comorbidity patterns in COPD can be categorized into six clusters. BMI, cancer pattern and respiratory system diseases pattern are the primary factors influencing hospitalization costs.