Impact of multimorbidity and complex multimorbidity on mortality among older Australians aged 45 years and over: a large population-based record linkage study

Multimorbidity patterns and trajectories in young and middle-aged adults: a large-scale population-based cohort study

Introduction

The presence of multiple chronic conditions, also referred to as multimorbidity, is a common finding in adults. Epidemiologic research can help identify groups of individuals with similar clinical profiles who could benefit from similar interventions. Many cross-sectional studies have revealed the existence of different multimorbidity patterns. Most of these studies were focused on the older population. However, multimorbidity patterns begin to form at a young age and can evolve over time following distinct multimorbidity trajectories with different impact on health. In this study, we aimed to identify multimorbidity patterns and trajectories in adults 18-65 years old.

Methods

We conducted a retrospective longitudinal epidemiologic study in the EpiChron Cohort, which includes all inhabitants of Aragón (Spain) registered as users of the Spanish National Health System, linking, at the patient level, information from electronic health records from both primary and specialised care. We included all 293,923 patients 18-65 years old with multimorbidity in 2011. We used cluster analysis at baseline (2011) and in 2015 and 2019 to identify multimorbidity patterns at four and eight years of follow-up, and we then created alluvial plots to visualise multimorbidity trajectories. We performed age- and sex-adjusted logistic regression analysis to study the association of each pattern with four- and eight-year mortality.

Results

We identified three multimorbidity patterns at baseline, named dyslipidaemia & endocrine-metabolic, hypertension & obesity, and unspecific. The hypertension & obesity pattern, found in one out of every four patients was associated with a higher likelihood of four- and eight-year mortality (age- and sex-adjusted odds ratio 1.11 and 1.16, respectively) compared to the unspecific pattern. Baseline patterns evolved into different patterns during the follow-up.

Discussion

Well-known preventable cardiovascular risk factors were key elements in most patterns, highlighting the role of hypertension and obesity as risk factors for higher mortality. Two out of every three patients had a cardiovascular profile with chronic conditions like diabetes and obesity that are linked to low-grade systemic chronic inflammation. More studies are encouraged to better characterise the relatively large portion of the population with an unspecific disease pattern and to help design and implement effective and comprehensive strategies towards healthier ageing.

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.

Impact of multimorbidity and complex multimorbidity on healthcare utilisation in older Australian adults aged 45 years or more: a large population-based cross-sectional data linkage study

OBJECTIVES

As life expectancy increases, older people are living longer with multimorbidity (MM, co-occurrence of ≥2 chronic health conditions) and complex multimorbidity (CMM, ≥3 chronic conditions affecting ≥3 different body systems). We assessed the impacts of MM and CMM on healthcare service use in Australia, as little was known about this.

DESIGN

Population-based cross-sectional data linkage study.

SETTING

New South Wales, Australia.

PARTICIPANTS

248 496 people aged ≥45 years who completed the Sax Institute's 45 and Up Study baseline questionnaire.

PRIMARY OUTCOME

High average annual healthcare service use (≥2 hospital admissions, ≥11 general practice visits and ≥2 emergency department (ED) visits) during the 3-year baseline period (year before, year of and year after recruitment).

METHODS

Baseline questionnaire data were linked with hospital, Medicare claims and ED datasets. Poisson regression models were used to estimate adjusted and unadjusted prevalence ratios for high service use with 95% CIs. Using a count of chronic conditions (disease count) as an alternative morbidity metric was requested during peer review.

RESULTS

Prevalence of MM and CMM was 43.8% and 15.5%, respectively, and prevalence increased with age. Across three healthcare settings, MM was associated with a 2.02-fold to 2.26-fold, and CMM was associated with a 1.83-fold to 2.08-fold, increased risk of high service use. The association was higher in the youngest group (45-59 years) versus the oldest group (≥75 years), which was confirmed when disease count was used as the morbidity metric in sensitivity analysis.When comparing impact using three categories with no overlap (no MM/CMM, MM with no CMM, and CMM), CMM had greater impact than MM across all settings.

CONCLUSION

Increased healthcare service use among older adults with MM and CMM impacts on the demand for primary care and hospital services. Which of MM or CMM has greater impact on risk of high healthcare service use depends on the analytic method used. Ageing populations living longer with increasing burdens of MM and CMM will require increased Medicare funding and provision of integrated care across the healthcare system to meet their complex needs.

Multimorbidity and adverse longitudinal outcomes among patients attending chronic outpatient medical care in Bahir Dar, Northwest Ethiopia

Background

Multimorbidity is becoming more prevalent in low-and middle-income countries (LMICs). However, the evidence base on the burden and its longitudinal outcomes are limited. This study aimed to determine the longitudinal outcomes of patients with multimorbidity among a sample of individuals attending chronic outpatient non communicable diseases (NCDs) care in Bahir Dar, northwest Ethiopia.

Methods

A facility-based longitudinal study was conducted among 1,123 participants aged 40+ attending care for single NCD (n = 491) or multimorbidity (n = 633). Data were collected both at baseline and after 1 year through standardized interviews and record reviews. Data were analyzed using Stata V.16. Descriptive statistics and longitudinal panel data analyzes were run to describe independent variables and identify factors predicting outcomes. Statistical significance was considered at p-value <0.05.

Results

The magnitude of multimorbidity has increased from 54.8% at baseline to 56.8% at 1 year. Four percent (n = 44) of patients were diagnosed with one or more NCDs and those having multimorbidity at baseline were more likely than those without multimorbidity to develop new NCDs. In addition, 106 (9.4%) and 22 (2%) individuals, respectively were hospitalized and died during the follow up period. In this study, about one-third of the participants had higher quality of life (QoL), and those having higher high activation status were more likely to be in the higher versus the combined moderate and lower QoL [AOR1 = 2.35, 95%CI: (1.93, 2.87)] and in the combined higher and moderate versus lower level of QoL [AOR2 = 1.53, 95%CI: (1.25, 1.88)].

Conclusion

Developing new NCDs is a frequent occurrence and the prevalence of multimorbidity is high. Living with multimorbidity was associated with poor progress, hospitalization and mortality. Patients having a higher activation level were more likely than those with low activation to have better QoL. If health systems are to meet the needs of the people with chronic conditions and multimorbidity, it is essential to understand diseases trajectories and of impact of multimorbidity on QoL, and determinants and individual capacities, and to increase their activation levels for better health improve outcomes through education and activation.