Community prevalence and dyad disease pattern of multimorbidity in China and India: a systematic review

A model-based approach to estimating the prevalence of disease combinations in South Africa

BACKGROUND

The development of strategies to better detect and manage patients with multiple long-term conditions requires estimates of the most prevalent condition combinations. However, standard meta-analysis tools are not well suited to synthesising heterogeneous multimorbidity data.

METHODS

We developed a statistical model to synthesise data on associations between diseases and nationally representative prevalence estimates and applied the model to South Africa. Published and unpublished data were reviewed, and meta-regression analysis was conducted to assess pairwise associations between 10 conditions: arthritis, asthma, chronic obstructive pulmonary disease (COPD), depression, diabetes, HIV, hypertension, ischaemic heart disease (IHD), stroke and tuberculosis. The national prevalence of each condition in individuals aged 15 and older was then independently estimated, and these estimates were integrated with the ORs from the meta-regressions in a statistical model, to estimate the national prevalence of each condition combination.

RESULTS

The strongest disease associations in South Africa are between COPD and asthma (OR 14.6, 95% CI 10.3 to 19.9), COPD and IHD (OR 9.2, 95% CI 8.3 to 10.2) and IHD and stroke (OR 7.2, 95% CI 5.9 to 8.4). The most prevalent condition combinations in individuals aged 15+ are hypertension and arthritis (7.6%, 95% CI 5.8% to 9.5%), hypertension and diabetes (7.5%, 95% CI 6.4% to 8.6%) and hypertension and HIV (4.8%, 95% CI 3.3% to 6.6%). The average numbers of comorbidities are greatest in the case of COPD (2.3, 95% CI 2.1 to 2.6), stroke (2.1, 95% CI 1.8 to 2.4) and IHD (1.9, 95% CI 1.6 to 2.2).

CONCLUSION

South Africa has high levels of HIV, hypertension, diabetes and arthritis, by international standards, and these are reflected in the most prevalent condition combinations. However, less prevalent conditions such as COPD, stroke and IHD contribute disproportionately to the multimorbidity burden, with high rates of comorbidity. This modelling approach can be used in other settings to characterise the most important disease combinations and levels of comorbidity.

Chronic diseases spectrum and multimorbidity in elderly inpatients based on a 12-year epidemiological survey in China

BACKGROUND

The number and proportion of the elderly population have been continuously increasing in China, leading to the elevated prevalence of chronic diseases and multimorbidity, which ultimately brings heavy burden to society and families. Meanwhile, the status of multimorbidity tends to be more complex in elderly inpatients than community population. In view of the above concerns, this study was designed to investigate the health status of elderly inpatients by analyzing clinical data in Chinese People's Liberation Army (PLA) General Hospital from 2008 to 2019, including the constitution of common diseases, comorbidities, the status of multimorbidity, in-hospital death and polypharmacy among elderly inpatients, so as to better understand the diseases spectrum and multimorbidity of elderly inpatients and also to provide supporting evidence for targeted management of chronic diseases in the elderly.

METHODS

A clinical inpatients database was set up by collecting medical records of elderly inpatients from 2008 to 2019 in Chinese PLA General Hospital, focusing on diseases spectrum and characteristics of elderly inpatients. In this study, we collected data of inpatients aged ≥ 65 years old, and further analyzed the constitution of diseases, multimorbidity rates and mortality causes in the past decade. In addition, the prescriptions were also analyzed to investigate the status of polypharmacy in elderly inpatients.

RESULTS

A total of 210,169 elderly patients were hospitalized from January 1st, 2008 to December 31st, 2019. The corresponding number of hospitalizations was 290,833. The average age of the study population was 72.67 years old. Of the total population, 73,493 elderly patients were re-admitted within one year, with the re-hospitalization rate of 25.27%. Malignant tumor, hypertension, ischemic heart disease, diabetes mellitus and cerebrovascular disease were the top 5 diseases. Among the study population, the number of patients with two or more long-term health conditions was 267,259, accounting for 91.89%, with an average of 4.68 diseases. In addition, the average number of medications taken by the study population was 5.4, among which, the proportion of patients taking more than 5 types of medications accounted for 55.42%.

CONCLUSIONS

By analyzing the constitution of diseases and multimorbidity, we found that multimorbidity has turned out to be a prominent problem in elderly inpatients, greatly affecting the process of healthy aging and increasing the burden on families and society. Therefore, multidisciplinary treatment should be strengthened to make reasonable preventive and therapeutic strategies to improve the life quality of the elderly. Meanwhile, more attention should be paid to reasonable medications for elderly patients with multimorbidity to avoid preventable side effects caused by irrational medication therapy.

Exploring multimorbidity clusters in relation to healthcare use and its impact on self-rated health among older people in India

The conventional definition of multimorbidity may not address the complex treatment needs resulting from interactions between multiple conditions, impacting self-rated health (SRH). In India, there is limited research on healthcare use and SRH considering diverse disease combinations in individuals with multimorbidity. This study aims to identify multimorbidity clusters related to healthcare use and determine if it improves the self-rated health of individuals in different clusters. This study extracted information from cross-sectional data of the first wave of the Longitudinal Ageing Study in India (LASI), conducted in 2017-18. The study participants were 31,373 people aged ≥ 60 years. A total of nineteen chronic diseases were incorporated to identify the multimorbidity clusters using latent class analysis (LCA) in the study. Multivariable logistic regression was used to examine the association between identified clusters and healthcare use. A propensity score matching (PSM) analysis was utilised to further examine the health benefit (i.e., SRH) of using healthcare in each identified cluster. LCA analysis identified five different multimorbidity clusters: relatively healthy' (68.72%), 'metabolic disorder (16.26%), 'hypertension-gastrointestinal-musculoskeletal' (9.02%), 'hypertension-gastrointestinal' (4.07%), 'complex multimorbidity' (1.92%). Older people belonging to the complex multimorbidity [aOR:7.03, 95% CI: 3.54-13.96] and hypertension-gastrointestinal-musculoskeletal [aOR:3.27, 95% CI: 2.74-3.91] clusters were more likely to use healthcare. Using the nearest neighbor matching method, results from PSM analysis demonstrated that healthcare use was significantly associated with a decline in SRH across all multimorbidity clusters. Findings from this study highlight the importance of understanding multimorbidity clusters and their implications for healthcare utilization and patient well-being. Our findings support the creation of clinical practice guidelines (CPGs) focusing on a patient-centric approach to optimize multimorbidity management in older people. Additionally, finding suggest the urgency of inclusion of counseling and therapies for addressing well-being when treating patients with multimorbidity.

Incidence, prevalence and characteristics of multimorbidity in different age groups among urban hospitalized patients in China

The aim of the study was to investigate the incidence, prevalence and characteristics of multimorbidity in urban inpatients of different age groups. This study used data from the National Insurance Claim for Epidemiology Research (NICER) to calculate the overall incidence, prevalence, geographic and age distribution patterns, health care burden, and multimorbidity patterns for multimorbidity in 2017. According to our study, the overall prevalence of multimorbidity was 6.68%, and the overall prevalence was 14.87% in 2017. The prevalence of multimorbidity increases with age. The pattern of the geographic distribution of multimorbidity shows that the prevalence of multimorbidity is relatively high in South East China. The average annual health care expenditure of patients with multimorbidity increased with age and rose rapidly, especially among older patients. Patients with cancer and chronic kidney disease have higher treatment costs. Patients with hypertension or ischemic heart disease had a significantly higher relative risk of multimorbidity than other included noncommunicable diseases (NCDs). Hyperlipidemia has generated the highest number of association rules, which may suggest that hyperlipidemia may be both a risk factor for other NCDs and an outcome of them.

Prevalence of polypharmacy among older adults in Ethiopia: a systematic review and meta-analysis

Polypharmacy is a significant concern for older adults. Taking multiple medicines to prevent and treat comorbidities is very common in older adults, potentially leading to polypharmacy. Polypharmacy is associated with the development of geriatric syndromes, including cognitive impairment, delirium, falls, frailty, urinary incontinence, and weight loss. The prevalence of polypharmacy varies according to the literature. There is a paucity of data regarding the prevalence of polypharmacy among older adults. Therefore, this study aimed to estimate the pooled prevalence of polypharmacy among older adults in Ethiopia. A comprehensive search of databases, including PubMed, MEDLINE, EMBASE, Hinari, Cumulative Index to Nursing and Allied Health Literature, International Scientific Indexing, Cochrane library and Web of Science, and Google Scholar, was conducted. STATA statistical software (version 17) was used to analyze the data. Forest plot and I2 heterogeneity test were computed to examine the existence of heterogeneity. Subgroup analysis and sensitivity analysis were done to explore the source of heterogeneity. Publication bias was evaluated by using funnel plots and Egger's test. A random effect model was used to determine the pooled prevalence of polypharmacy. After reviewing 123 studies, 13 studies with a total of 3547 older adults fulfilled the inclusion criteria and were included in this meta-analysis. The result from 13 studies revealed that the pooled prevalence of polypharmacy among older adults in Ethiopia was 37.10% (95CI: 28.28-45.91). A Subgroup Meta-analysis showed that the heterogeneity level was slightly lower among studies done in Oromia region (I2 = 46.62, P-value = 0.154). Higher pooled polypharmacy prevalence was found among older adults with cardiovascular disorders (42.7%) and admitted patients (51.4%). In general, it was found that the pooled prevalence of polypharmacy among older adults in Ethiopia was high. More than one in three older adults take five or more medications at a time. Thus, intervention focusing on rational geriatric pharmacotherapy is significant to prevent unnecessary pill burden, adverse drug events, medical costs, geriatric morbidity, and mortality. Furthermore, enhancing pharmacist roles towards medication therapy management and safety monitoring in older adults is also indicated.

Additive effect of frailty with distinct multimorbidity patterns on mortality amongst middle-aged and older adults in Taiwan: A 16-year population-based study

AIM

This study aimed to explore the association between multimorbidity patterns with/without frailty and future mortality among Taiwanese middle-aged and older adults through a population-based cohort study design.

METHODS

Data were collected from the Taiwan Longitudinal Study on Aging. The data were obtained from Wave 3, with the multimorbidity patterns in the years of 1996 being analyzed through latent class analysis. Frailty was defined using the modified Fried criteria. The association between each disease group with/without frailty and mortality was examined using logistic regression, with the reference group as the Relatively healthy group without frailty. Survival analysis was performed using Cox regression, and the follow-up period of mortality was from 1 January 1996 to 31 December 2012.

RESULTS

A total of 4748 middle-aged and older adults with an average age of 66.3 years (SD: 9.07 years) were included. Four disease patterns were identified in 1996, namely the Cardiometabolic (21.0%), Arthritis-cataract (11.9%), Relatively healthy (61.6%), and Multimorbidity (5.5%) groups. After adjusting for all covariates, the Relatively healthy group with frailty showed the highest risk for mortality (odds ratio: 3.66, 95% confidence interval [95% CI]: 2.24-5.95), followed by the Cardiometabolic group with frailty (odds ratio: 3.58, 95% CI: 1.96-6.54), Multimorbidity group with frailty (odds ratio: 2.28, 95% CI: 1.17-4.44), Multimorbidity group without frailty (odds ratio: 1.44, 95% CI: 1.01-2.04), and the Cardiometabolic group without frailty (odds ratio: 1.24, 95% CI: 1.04-1.49).

CONCLUSIONS

Frailty plays an important role in mortality among middle-aged and older adults with distinct multimorbidity patterns. Middle-aged and older adults with a relatively healthy multimorbidity pattern or a cardiometabolic multimorbidity pattern with frailty encountered dismal outcomes. Geriatr Gerontol Int 2023; 23: 684-691.

Identification of status quo and association rules for chronic comorbidity among Chinese middle-aged and older adults rural residents

Background

Chronic comorbidity has become a major challenge in chronic disease prevention and control. This issue is particularly pronounced in rural areas of developing countries, where the prevalence of chronic disease comorbidity is high, especially among middle-aged and older adults populations. However, the health status of middle-aged and older adults individuals in rural areas of China has received inadequate attention. Therefore, it is crucial to investigate the correlation among chronic diseases to establish a reference basis for adjusting health policies aimed at promoting the prevention and management of chronic diseases among middle-aged and older adults individuals.

Methods

This study selected 2,262 middle-aged and older adults residents aged 50 years or older in Shangang Village, Jiangsu Province, China, as the study population. To analyze the chronic comorbidity of middle-aged and older adults residents with different characteristics, we used the χ² test with SPSS statistical software. Data analysis was conducted using the Apriori algorithm of Python software, set to mine the strong association rules of positive correlation between chronic disease comorbidities of middle-aged and older adults residents.

Results

The prevalence of chronic comorbidity was 56.6%. The chronic disease comorbidity group with the highest prevalence rate was the lumbar osteopenia + hypertension group. There were significant differences in the prevalence of chronic disease comorbidity among middle-aged and older adults residents in terms of gender, BMI, and chronic disease management. The Apriori algorithm was used to screen 15 association rules for the whole population, 11 for genders, and 15 for age groups. According to the order of support, the most common association rules of comorbidity of three chronic diseases were: {lumbar osteopenia} → {hypertension} (support: 29.22%, confidence: 58.44%), {dyslipidemia} → {hypertension} (support: 19.14%, confidence: 65.91%) and {fatty liver} → {hypertension} (support: 17.82%, confidence: 64.17%).

Conclusion

The prevalence of chronic comorbidity among middle-aged and older adults rural residents in China is relatively high. We identified many association rules among chronic diseases, dyslipidemia is mostly the antecedent, and hypertension is primarily the result. In particular, the majority of comorbidity aggregation patterns consisted of hypertension and dyslipidemia. By implementing scientifically-proven prevention and control strategies, the development of healthy aging can be promoted.

Associations among socioeconomic status, multimorbidity of non-communicable diseases, and the risk of household catastrophic health expenditure in China: a population-based cohort study

BACKGROUND

Multimorbidity of non-communicable diseases (NCDs) is increasingly prevalent among older adults around the world, leading a higher risk of household catastrophic health expenditure (CHE). As current powerful evidence was insufficient, we aimed to estimate the association between multimorbidity of NCDs and the risk of CHE in China.

METHODS

We designed a cohort study using data investigated in 2011-2018 from the China Health and Retirement Longitudinal Study, which is a nationally-representative study covering 150 counties of 28 provinces in China. We used mean ± standard deviation (SD) and frequencies and percentages to describe baseline characteristics. Person χ2 test was employed to compare the differences of baseline characteristics between households with and without multimorbidity. Lorenz curve and concentration index were used to measure the socioeconomic inequalities of CHE incidence. Cox proportional hazards models were applied to estimate adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs) for the association between multimorbidity and CHE.

RESULTS

Among 17,708 participants, 17,182 individuals were included for the descriptive analysis of the prevalence of multimorbidity in 2011, and 13,299 individuals (8029 households) met inclusion criteria and were included in the final analysis with a median of 83 (interquartile range: 25-84) person-months of follow-up. 45.1% (7752/17,182) individuals and 56.9% (4571/8029) households had multimorbidity at baseline. Participants with higher family economic level (aOR = 0.91, 95% CI: 0.86-0.97) had lower multimorbidity prevalence than those with lowest family economic level. 82.1% of participants with multimorbidity did not make use of outpatient care. The CHE incidence was more concentrated among participants with higher socioeconomic status (SES) with a concentration index of 0.059. The risk of CHE was 19% (aHR = 1.19, 95% CI: 1.16-1.22) higher for each additional NCD.

CONCLUSIONS

Approximately half of middle-aged and older adults in China had multimorbidity, causing a 19% higher risk of CHE for each additional NCD. Early interventions for preventing multimorbidity among people with low SES could be intensified to protect older adults from financial hardship. In addition, concerted efforts are needed to increase patients' rational healthcare utilization and strengthen current medical security for people with high SES to reduce economic disparities in CHE.

Global and regional prevalence of multimorbidity in the adult population in community settings: a systematic review and meta-analysis

BACKGROUND

Knowing the prevalence of multimorbidity among adults across continents is a crucial piece of information for achieving Sustainable Development Goal 3.4, which calls for reducing premature death due to non-communicable diseases. A high prevalence of multimorbidity indicates high mortality and increased healthcare utilization. We aimed to understand the prevalence of multimorbidity across WHO geographic regions among adults.

METHODS

We performed a systematic review and meta-analysis of surveys designed to estimate the prevalence of multimorbidity among adults in community settings. We searched PubMed, ScienceDirect, Embase and Google Scholar databases for studies published between January 1, 2000, and December 31, 2021. The random-effects model estimated the pooled proportion of multimorbidity in adults. Heterogeneity was quantified using I² statistics. We performed subgroup analyses and sensitivity analyses based on continents, age, gender, multimorbidity definition, study periods and sample size. The study protocol was registered with PROSPERO (CRD42020150945).

FINDINGS

We analyzed data from 126 peer-reviewed studies that included nearly 15.4 million people (32.1% were male) with a weighted mean age of 56.94 years (standard deviation of 10.84 years) from 54 countries around the world. The overall global prevalence of multimorbidity was 37.2% (95% CI = 34.9-39.4%). South America (45.7%, 95% CI = 39.0-52.5) had the highest prevalence of multimorbidity, followed by North America (43.1%, 95% CI = 32.3-53.8%), Europe (39.2%, 95% CI = 33.2-45.2%), and Asia (35%, 95% CI = 31.4-38.5%). The subgroup study highlights that multimorbidity is more prevalent in females (39.4%, 95% CI = 36.4-42.4%) than males (32.8%, 95% CI = 30.0-35.6%). More than half of the adult population worldwide above 60 years of age had multimorbid conditions (51.0%, 95% CI = 44.1-58.0%). Multimorbidity has become increasingly prevalent in the last two decades, while the prevalence appears to have stayed stable in the recent decade among adults globally.

INTERPRETATION

The multimorbidity patterns by geographic regions, time, age, and gender suggest noticeable demographic and regional differences in the burden of multimorbidity. According to insights about prevalence among adults, priority is required for effective and integrative interventions for older adults from South America, Europe, and North America. A high prevalence of multimorbidity among adults from South America suggests immediate interventions are needed to reduce the burden of morbidity. Furthermore, the high prevalence trend in the last two decades indicates that the global burden of multimorbidity continues at the same pace. The low prevalence in Africa suggests that there may be many undiagnosed chronic illness patients in Africa.

FUNDING

None.

Correlations between comorbidities in trials and the community: An individual-level participant data meta-analysis

Background

People with comorbidities are under-represented in randomised controlled trials, and it is unknown whether patterns of comorbidity are similar in trials and the community.

Methods

Individual-level participant data were obtained for 83 clinical trials (54,688 participants) for 16 index conditions from two trial repositories: Yale University Open Data Access (YODA) and the Centre for Global Clinical Research Data (Vivli). Community data (860,177 individuals) were extracted from the Secure Anonymised Information Linkage (SAIL) databank for the same index conditions. Comorbidities were defined using concomitant medications. For each index condition, we estimated correlations between comorbidities separately in trials and community data. For the six commonest comorbidities we estimated all pairwise correlations using Bayesian multivariate probit models, conditioning on age and sex. Correlation estimates from trials with the same index condition were combined into a single estimate. We then compared the trial and community estimates for each index condition.

Results

Despite a higher prevalence of comorbidities in the community than in trials, the correlations between comorbidities were mostly similar in both settings. On comparing correlations between the community and trials, 21% of correlations were stronger in the community, 10% were stronger in the trials and 68% were similar in both. In the community, 5% of correlations were negative, 21% were null, 56% were weakly positive and 18% were strongly positive. Equivalent results for the trials were 11%, 33%, 45% and 10% respectively.

Conclusions

Comorbidity correlations are generally similar in both the trials and community, providing some evidence for the reporting of comorbidity-specific findings from clinical trials.