Multimorbidity and mortality in older adults: A systematic review and meta-analysis

Implications and hidden toxicity of cardiometabolic syndrome and early-stage heart failure in carfilzomib-induced cardiotoxicity

BACKGROUND AND PURPOSE

Cancer therapy-related cardiovascular adverse events (CAEs) in presence of comorbidities, are in the spotlight of the cardio-oncology guidelines. Carfilzomib (Cfz), indicated for relapsed/refractory multiple myeloma (MM), presents with serious CAEs. MM is often accompanied with co-existing comorbidities. However, Cfz use in MM patients with cardiometabolic syndrome (CMS) or in heart failure with reduced ejection fraction (HFrEF), is questionable.

EXPERIMENTAL APPROACH

ApoE-/- and C57BL6/J male mice received 14 weeks Western Diet (WD) (CMS models). C57BL6/J male mice underwent permanent LAD ligation for 14 days (early-stage HFrEF model). CMS- and HFrEF-burdened mice received Cfz for two consecutive or six alternate days. Daily metformin and atorvastatin administrations were performed additionally to Cfz, as prophylactic interventions. Mice underwent echocardiography, while proteasome activity, biochemical and molecular analyses were conducted.

KEY RESULTS

CMS did not exacerbate Cfz left ventricular (LV) dysfunction, whereas Cfz led to metabolic complications in both CMS models. Cfz induced autophagy and Ca2+ homeostasis dysregulation, whereas metformin and atorvastatin prevented Cfz-mediated LV dysfunction and molecular deficits in the CMS-burdened myocardium. Early-stage HFrEF led to depressed LV function and increased protein phosphatase 2A (PP2A) activity. Cfz further increased myocardial PP2A activity, inflammation and Ca2+-cycling dysregulation. Metformin co-administration exerted an anti-inflammatory potential on the myocardium without improving LV function.

CONCLUSION AND IMPLICATIONS

CMS and HFrEF seem to exacerbate Cfz-induced CAEs, by presenting metabolism-related hidden toxicity and PP2A-related cardiac inflammation, respectively. Metformin retains its prophylactic potential in the presence of CMS, while mitigating inflammation and Ca2+ signalling dysregulation in the HFrEF myocardium.

Effectiveness of post-COVID-19 primary care attendance in improving survival in very old patients with multimorbidity: a territory-wide target trial emulation

OBJECTIVES

Older individuals with multimorbidity are at an elevated risk of infection and complications from COVID-19. Effectiveness of post-COVID-19 interventions or care models in reducing subsequent adverse outcomes in these individuals have rarely been examined. This study aims to examine the effectiveness of attending general outpatient within 30 days after discharge from COVID-19 on 1-year survival among older adults aged 85 years or above with multimorbidity.

DESIGN

Retrospective cohort study emulating a randomised target trial using electronic health records.

SETTING

We used data from the Hospital Authority and the Department of Health in Hong Kong, which provided comprehensive electronic health records, COVID-19 confirmed case data, population-based vaccination records and other individual characteristics for the study.

PARTICIPANTS

Adults aged 85 years or above with multimorbidity who were discharged after hospitalisation for COVID-19 between January 2020 and August 2022.

INTERVENTIONS

Attending a general outpatient within 30 days of last COVID-19 discharge defined the exposure, compared to no outpatient visit.

MAIN OUTCOME MEASURES

Primary outcome was all-cause mortality within one year. Secondary outcomes included mortality from respiratory, cardiovascular and cancer causes.

RESULTS

A total of 6183 eligible COVID-19 survivors were included in the analysis. The all-cause mortality rate following COVID-19 hospitalisation was lower in the general outpatient visit group (17.1 deaths per 100 person-year) compared with non-visit group (42.8 deaths per 100 person-year). After adjustment, primary care consultations within 30 days after discharge were associated with a significantly greater 1-year survival (difference in 1-year survival: 11.2%, 95% CI 8.1% to 14.4%). We also observed significantly better survival from respiratory diseases in the general outpatient visit group (difference in 1-year survival: 6.3%, 95% CI 3.5% to 8.9%). In a sensitivity analysis for different grace period lengths, we found that the earlier participants had a general outpatient visit after COVID-19 discharge, the better the survival.

CONCLUSIONS

Timely primary care consultations after COVID-19 hospitalisation may improve survival following COVID-19 hospitalisation among older adults aged 85 or above with multimorbidity. Expanding primary care services and implementing follow-up mechanisms are crucial to support this vulnerable population's recovery and well-being.

Trajectories in long-term condition accumulation and mortality in older adults: a group-based trajectory modelling approach using the English Longitudinal Study of Ageing

OBJECTIVES

To classify older adults into clusters based on accumulating long-term conditions (LTC) as trajectories, characterise clusters and quantify their associations with all-cause mortality.

DESIGN

We conducted a longitudinal study using the English Longitudinal Study of Ageing over 9 years (n=15 091 aged 50 years and older). Group-based trajectory modelling was used to classify people into clusters based on accumulating LTC over time. Derived clusters were used to quantify the associations between trajectory memberships, sociodemographic characteristics and all-cause mortality by conducting regression models.

RESULTS

Five distinct clusters of accumulating LTC trajectories were identified and characterised as: 'no LTC' (18.57%), 'single LTC' (31.21%), 'evolving multimorbidity' (25.82%), 'moderate multimorbidity' (17.12%) and 'high multimorbidity' (7.27%). Increasing age was consistently associated with a larger number of LTCs. Ethnic minorities (adjusted OR=2.04; 95% CI 1.40 to 3.00) were associated with the 'high multimorbidity' cluster. Higher education and paid employment were associated with a lower likelihood of progression over time towards an increased number of LTCs. All the clusters had higher all-cause mortality than the 'no LTC' cluster.

CONCLUSIONS

The development of multimorbidity in the number of conditions over time follows distinct trajectories. These are determined by non-modifiable (age, ethnicity) and modifiable factors (education and employment). Stratifying risk through clustering will enable practitioners to identify older adults with a higher likelihood of worsening LTC over time to tailor effective interventions to prevent mortality.

Multimorbidity and patient experience with general practice: A national cross-sectional survey in Norway

BACKGROUND

Patient experience is an important indicator of the quality of healthcare. Patients with multimorbidity often face adverse health outcomes and increased healthcare utilisation. General practitioners play a crucial role in managing these patients. The main aim of our study was to perform an in-depth assessment of differences in patient-reported experience with general practice between patients living with chronic conditions and multimorbidity, and those with no chronic conditions.

METHODS

We performed secondary analyses of a national survey of patient experience with general practice in 2021 (response rate 41.9%, n = 7,912). We described the characteristics of all survey respondents with no, one, two, and three or more self-reported chronic conditions. We assessed patient experience using four scales from the Norwegian patient experience with GP questionnaire (PEQ-GP). These scales were used as dependent variables in bivariate and multivariate analyses and for testing the measurement model, including confirmatory factor analysis and a multigroup CFA to assess measurement invariance. Sentiment and content analysis of free-text comments was also performed.

RESULTS

Patients with chronic conditions consistently reported lower scores on the GP and GP practice experience scales, compared to those without chronic conditions. This pattern persisted even after adjustment for patient background variables. The strongest associations were found for the scale of "Enablement", followed by the scales of "GP" and "Practice". The subscale "Accessibility" did not correlate statistically significantly with any number of chronic conditions. The analysis of free-text comments echoed the quantitative results. Patients with multimorbidity stressed the importance of time spent on consultations, meeting the same GP, follow-up and relationship more often than patients with no chronic conditions. Our study also confirmed measurement invariance across patients with no chronic conditions and patients with multimorbidity, indicating that the observed differences in patient experience were a result of true differences, rather than artifacts of measurement bias.

CONCLUSIONS

The findings highlight the need for the healthcare system to provide customised support for patients with chronic conditions and multimorbidity. Addressing the specific needs of patients with multimorbidity is a critical step towards enhancing patient experience and the quality of care in general practice.

Multimorbidity and associated informal care receiving characteristics for US older adults: a latent class analysis

BACKGROUND

Older adults with varying patterns of multimorbidity may require distinct types of care and rely on informal caregiving to meet their care needs. This study aims to identify groups of older adults with distinct, empirically-determined multimorbidity patterns and compare characteristics of informal care received among estimated classes.

METHODS

Data are from the 2011 National Health and Aging Trends Study (NHATS). Ten chronic conditions were included to estimate multimorbidity patterns among 7532 individuals using latent class analysis. Multinomial logistic regression model was estimated to examine the association between sociodemographic characteristics, health status and lifestyle variables, care-receiving characteristics and latent class membership.

RESULTS

A four-class solution identified the following multimorbidity groups: some somatic conditions with moderate cognitive impairment (30%), cardiometabolic (25%), musculoskeletal (24%), and multisystem (21%). Compared with those who reported receiving no help, care recipients who received help with household activities only (OR = 1.44, 95% CI 1.05-1.98), mobility but not self-care (OR = 1.63, 95% CI 1.05-2.53), or self-care but not mobility (OR = 2.07, 95% CI 1.29-3.31) had greater likelihood of being in the multisystem group versus the some-somatic group. Having more caregivers was associated with higher odds of being in the multisystem group compared with the some-somatic group (OR = 1.09, 95% CI 1.00-1.18), whereas receiving help from paid helpers was associated with lower odds of being in the multisystem group (OR = 0.36, 95% CI 0.19-0.77).

CONCLUSIONS

Results highlighted different care needs among persons with distinct combinations of multimorbidity, in particular the wide range of informal needs among older adults with multisystem multimorbidity. Policies and interventions should recognize the differential care needs associated with multimorbidity patterns to better provide person-centered care.

Twenty-year trajectories of morbidity in individuals with and without osteoarthritis

OBJECTIVES

To identify multimorbidity trajectories over 20 years among incident osteoarthritis (OA) individuals and OA-free matched references.

METHODS

Cohort study using prospectively collected healthcare data from the Skåne region, Sweden (~1.4 million residents). We extracted diagnoses for OA and 67 common chronic conditions. We included individuals aged 40+ years on 31 December 2007, with incident OA between 2008 and 2009. We selected references without OA, matched on birth year, sex, and year of death or moving outside the region. We employed group-based trajectory modelling to capture morbidity count trajectories from 1998 to 2019. Individuals without any comorbidity were included as a reference group but were not included in the model.

RESULTS

We identified 9846 OA cases (mean age: 65.9 (SD 11.7), female: 58%) and 9846 matched references. Among both cases and references, 1296 individuals did not develop chronic conditions (no-chronic-condition class). We identified four classes. At the study outset, all classes exhibited a low average number of chronic conditions (≤1). Class 1 had the slowest progression towards multimorbidity, which increased progressively in each class. Class 1 had the lowest count of chronic conditions at the end of the follow-up (mean: 2.9 (SD 1.7)), while class 4 had the highest (9.6 (2.6)). The presence of OA was associated with a 1.29 (1.12, 1.48) adjusted relative risk of belonging to class 1 up to 2.45 (2.12, 2.83) for class 4.

CONCLUSIONS

Our findings suggest that individuals with OA face an almost threefold higher risk of developing severe multimorbidity.

The number of comorbidities as an important cofactor to ASA class in predicting postoperative outcome: An international multicentre cohort study

BACKGROUND

Multimorbidity is a growing burden in our ageing society and is associated with perioperative morbidity and mortality. Despite several modifications to the ASA physical status classification, multimorbidity as such is still not considered. Thus, the aim of this study was to quantify the burden of comorbidities in perioperative patients and to assess, independent of ASA class, its potential influence on perioperative outcome.

METHODS

In a subpopulation of the prospective ClassIntra® validation study from eight international centres, type and severity of anaesthesia-relevant comorbidities were additionally extracted from electronic medical records for the current study. Patients from the validation study were of all ages, undergoing any type of in-hospital surgery and were followed up until 30 days postoperatively to assess perioperative outcomes. Primary endpoint was the number of comorbidities across ASA classes. The associated postoperative length of hospital stay (pLOS) and Comprehensive Complication Index (CCI®) were secondary endpoints. On a scale from 0 (no complication) to 100 (death) the CCI® measures the severity of postoperative morbidity as a weighted sum of all postoperative complications.

RESULTS

Of 1421 enrolled patients, the mean number of comorbidities significantly increased from 1.5 in ASA I (95% CI, 1.1-1.9) to 10.5 in ASA IV (95% CI, 8.3-12.7) patients. Furthermore, independent of ASA class, postoperative complications measured by the CCI® increased per each comorbidity by 0.81 (95% CI, 0.40-1.23) and so did pLOS (geometric mean ratio, 1.03; 95% CI, 1.01-1.06).

CONCLUSIONS

These data quantify the high prevalence of multimorbidity in the surgical population and show that the number of comorbidities is predictive of negative postoperative outcomes, independent of ASA class.

Association between profiles of accelerometer-measured daily movement behaviour and mortality risk: a prospective cohort study of British older adults

Objectives

We identified profiles of wake-time movement behaviours (sedentary behaviours, light intensity physical activity and moderate-to-vigorous physical activity) based on accelerometer-derived features among older adults and then examined their association with all-cause mortality.

Methods

Data were drawn from a prospective cohort of 3991 Whitehall II accelerometer substudy participants aged 60-83 years in 2012-2013. Daily movement behaviour profiles were identified using k-means cluster analysis based on 13 accelerometer-assessed features characterising total duration, frequency, bout duration, timing and activity intensity distribution of movement behaviour. Cox regression models were used to assess the association between derived profiles and mortality risk.

Results

Over a mean follow-up of 8.1 (SD 1.3) years, a total of 410 deaths were recorded. Five distinct profiles were identified and labelled as 'active' (healthiest), 'active sitters', 'light movers', 'prolonged sitters', and 'most sedentary' (most deleterious). In model adjusted for sociodemographic, lifestyle, and health-related factors, compared with the 'active' profile, 'active sitters' (HR 1.57, 95% CI 1.01 to 2.44), 'light movers' (HR 1.75, 95% CI 1.17 to 2.63), 'prolonged sitters' (HR 1.67, 95% CI 1.11 to 2.51), 'most sedentary' (HR 3.25, 95% CI 2.10 to 5.02) profiles were all associated with a higher risk of mortality.

Conclusion

Given the threefold higher mortality risk among those with a 'most sedentary' profile, public health interventions may target this group wherein any improvement in physical activity and sedentary behaviour might be beneficial.

When the Going Gets Tough: Multimorbidity and Heavy and Binge Drinking Among Adults

INTRODUCTION

Multimorbidity, the presence of two or more long-term health conditions in the same individual, is an emerging epidemic associated with increased morbidity and mortality. Continued drinking concurrent with alcohol-related chronic conditions, particularly with multimorbidity, is likely to further elevate health risk. This study aimed to examine the associations of multimorbidity among diabetes, hypertension, heart disease, and cancer with drinking, and moderation of these associations by age.

METHODS

Logistic regression modeling was performed in 2023 using a nationally representative sample of U.S. adults from the 2015-19 National Survey on Drug Use and Health. Multimorbidity was assessed using (1) a count of these conditions and (2) disease-specific categories. The outcomes were past month heavy drinking (7+/14+ drinks weekly) and binge drinking (4+/5+ drinks per occasion) for women and men.

RESULTS

A pattern of reduced odds for drinking outcomes associated with a greater degree of multimorbidity was found. This pattern was more apparent in models using the continuous measure of multimorbidity than in those using the categorical measure, and more consistent for binge drinking than for heavy drinking and for women than for men. Significant age interactions were found: the log odds of heavy drinking and binge drinking for both men and women decreased as the number of conditions increased, and more steeply for those ages 50+ than the younger. The log odds of heavy drinking varied little among men under age 50 regardless of multimorbidity.

CONCLUSIONS

Alcohol interventions to reduce drinking with multimorbidity, particularly among heavy-drinking men under age 50, are warranted.

Effectiveness of complex behaviour change interventions tested in randomised controlled trials for people with multiple long-term conditions (M-LTCs): systematic review with meta-analysis

INTRODUCTION

The prevalence of multiple long-term conditions (M-LTCs) increases as adults age and impacts quality of life and health outcomes. To help people manage these conditions, complex behaviour change interventions are used, often based on research conducted in those with single LTCs. However, the needs of those with M-LTCs can differ due to complex health decision-making and engagement with multiple health and care teams.

OBJECTIVES

The aim of this review is to identify whether current interventions are effective for people living with M-LTCs, and which outcomes are most appropriate to detect this change.

METHODS

Five databases (MEDLINE, Embase, PsycINFO, CINAHL and Web of Science) were systematically searched, between January 1999 and January 2022, to identify randomised controlled trials evaluating effectiveness of behaviour change interventions in people with M-LTCs. Intervention characteristics, intervention effectiveness and outcome measures were meta-analysed and narratively synthesised.

RESULTS

53 eligible articles were included. Emotional well-being and psychological distress (depression and anxiety) outcomes were most amenable to change (emotional well-being: standardised mean difference (SMD) 0.31 (95% CI 0.04 to 0.58); depression psychological distress: SMD -0.45 (95% CI -0.73 to -0.16); anxiety psychological distress: SMD -0.14 (95% CI -0.28 to 0.00)), particularly for interventions with a collaborative care approach. Interventions targeting those with a physical and mental health condition and those with cognitive and/or behavioural activation approach saw larger reductions in psychological distress outcomes. Interventions that lasted for longer than 6 months significantly improved the widest variety of outcomes.

CONCLUSION

Complex interventions can be successfully delivered to those with M-LTCs. These are most effective at reducing psychological distress in those with physical and mental LTCs. Further research is needed to identify the effective components of interventions for people with two or more physical LTCs and which outcome is most appropriate for detecting this change.

Age-specific Multimorbidity Patterns and Burden on All-Cause Mortality and Public Direct Medical Expenditure: A Retrospective Cohort Study

OBJECTIVE

To evaluate age-specific multimorbidity patterns and morbidity burden on mortality and healthcare expenditure across age groups.

PATIENTS AND METHODS

Retrospective observational study between January 1, 2009 to December 31, 2017 using electronic health records in Hong Kong: Individuals were stratified by age (< 50, 50-64, 65-79, ≥ 80), and sub-classified by number of morbidities (0, 1, 2, 3, ≥ 4) out of 21 common chronic conditions. Clustering analyses were conducted to identify specific patterns of multimorbidity. Association between the number as well as combinations of morbidities and all-cause mortality and public expenditure was examined.

RESULTS

4,562,832 individuals with a median follow-up of 7 years were included. Mental disorders were the top morbidities among young individuals, while cardiovascular diseases were prevalent in the elderly. An increased number of morbidities was associated with a greater relative risk for mortality and medical expenditure, and this relationship was stronger among younger patients. Compared to individuals in the same age group without morbidity, the hazard ratios (HR; 95% CI) of all-cause mortality in patients aged < 50 and ≥ 80 with two comorbidities 3.81 (3.60-4.03) and 1.38 (1.36-1.40), respectively, which increased to 14.22 (9.87-20.47) and 2.20 (2.13-2.26), respectively, as the number of morbidities increased to ≥ 4. The stroke-hypertension cluster was shown to be associated with the highest HR of mortality 2.48 (2.43-2.53) among all identified clusters arising from the clustering analysis.

CONCLUSION

Given the stronger association between multimorbidity and all-cause mortality and greater opportunity costs in younger populations, prevention and management of early-onset multimorbidity are warranted. (248 words).

Racial inequalities in the development of multimorbidity of chronic conditions: results from a Brazilian prospective cohort

BACKGROUND

The occurrence of multimorbidity and its impacts have differentially affected population subgroups. Evidence on its incidence has mainly come from high-income regions, with limited exploration of racial disparities. This study investigated the association between racial groups and the development of multimorbidity and chronic conditions in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil).

METHODS

Data from self-reported white, brown (pardos or mixed-race), and black participants at baseline of ELSA-Brasil (2008-2010) who were at risk for multimorbidity were analysed. The development of chronic conditions was assessed through in-person visits and self-reported diagnosis via telephone until the third follow-up visit (2017-2019). Multimorbidity was defined when, at the follow-up visit, the participant had two or more morbidities. Cumulative incidences, incidence rates, and adjusted incidence rate ratios (IRRs) were estimated using Poisson models.

RESULTS

Over an 8.3-year follow-up, compared to white participants: browns had a 27% greater incidence of hypertension and obesity; and blacks had a 62% and 45% greater incidence, respectively. Blacks also had 58% more diabetes. The cancer incidence was greater among whites. Multimorbidity affected 41% of the participants, with a crude incidence rate of 57.5 cases per 1000 person-years (ranging from 56.3 for whites to 63.9 for blacks). Adjusted estimates showed a 20% higher incidence of multimorbidity in black participants compared to white participants (IRR: 1.20; 95% CI: 1.05-1.38).

CONCLUSIONS

Significant racial disparities in the risk of chronic conditions and multimorbidity were observed. Many associations revealed a gradient increase in illness risk according to darker skin tones. Addressing fundamental causes such as racism and racial discrimination, alongside considering social determinants of health, is vital for comprehensive multimorbidity care. Intersectoral, equitable policies are essential for ensuring health rights for historically marginalized groups.

Intrinsic capacity and multimorbidity predicting incident disability-Insights from the I-Lan Longitudinal Aging Study

OBJECTIVES

This longitudinal cohort study aimed to examine the effect of intrinsic capacity (IC) and multimorbidity on the development of new disabilities.

METHODS

The study utilized data from 1,009 participants without disabilities from the I-Lan Longitudinal Aging Study. Multivariable logistic regressions were employed to assess the predictive capability of IC (ranging from 0 to 100) and multimorbidity for incident disability over a 7-year follow-up period.

RESULTS

Both low IC (OR 4.9, 95 % CI 2.1-11.1, p < 0.001) and multimorbidity (OR 4.5, 95 % CI 2.2-9.2, p < 0.001) significantly predicted incident disability over the 7-year period. A one-point increase in IC reduced the risk of incident disability by 10 % (OR 0.9, 95 % CI 0.8-0.9, p < 0.001). Among IC subdomains, both better locomotion (OR 0.96, 95 % CI 0.94-0.99, p = 0.014) and psychology (OR 0.97, 95 %CI 0.94-1.00, p = 0.049) significantly reduced the risk of incident disability. Rapid declines in IC significantly predicted incident disability (OR 4.1, 95 % CI 1.8-9.3, p = 0.001), whereas the onset of new multimorbidity or changes in the number of chronic conditions did not demonstrate a significant association with incident disability. The interaction terms between IC and multimorbidity, both categorically (low IC * multimorbidity, p = 0.959) and numerically (IC (per point) * multimorbidity, p = 0.660) were all statistically insignificant.

CONCLUSIONS

IC exhibited better predictive capacity for 7-year incident disability compared to multimorbidity, so health care services targeting older adults should adopt an integrated care approach that combines both function- and disease-centric strategies.

Identifying multi-resolution clusters of diseases in ten million patients with multimorbidity in primary care in England

BACKGROUND

Identifying clusters of diseases may aid understanding of shared aetiology, management of co-morbidities, and the discovery of new disease associations. Our study aims to identify disease clusters using a large set of long-term conditions and comparing methods that use the co-occurrence of diseases versus methods that use the sequence of disease development in a person over time.

METHODS

We use electronic health records from over ten million people with multimorbidity registered to primary care in England. First, we extract data-driven representations of 212 diseases from patient records employing (i) co-occurrence-based methods and (ii) sequence-based natural language processing methods. Second, we apply the graph-based Markov Multiscale Community Detection (MMCD) to identify clusters based on disease similarity at multiple resolutions. We evaluate the representations and clusters using a clinically curated set of 253 known disease association pairs, and qualitatively assess the interpretability of the clusters.

RESULTS

Both co-occurrence and sequence-based algorithms generate interpretable disease representations, with the best performance from the skip-gram algorithm. MMCD outperforms k-means and hierarchical clustering in explaining known disease associations. We find that diseases display an almost-hierarchical structure across resolutions from closely to more loosely similar co-occurrence patterns and identify interpretable clusters corresponding to both established and novel patterns.

CONCLUSIONS

Our method provides a tool for clustering diseases at different levels of resolution from co-occurrence patterns in high-dimensional electronic health records, which could be used to facilitate discovery of associations between diseases in the future.

Trends in prevalence of multimorbidity for chronic diseases in China: serial cross-sectional surveys from 2009 to 2018

BACKGROUND

Multimorbidity, individuals suffering from two or more chronic diseases, has become a major health challenge worldwide, especially in populous and prosperous cities, where studies of this phenomenon in China are limited. We examined the prevalence, trends, patterns, and associated factors of multimorbidity from 2009 to 2018 among community-dwelling adults in Guangzhou, China.

METHODS

We conducted serial cross-sectional surveys for chronic diseases in Guangzhou, China, in 2009, 2013, and 2018. General and stratified prevalence were standardized using demographic data. Multivariable logistic regression and hierarchical cluster analysis were applied to identify associated factors and to assess the correlations and patterns of multimorbidity, respectively.

RESULTS

This study included 23,284 adults aged 18 and over in 2009, 18,551 in 2013, and 15,727 in 2018. The standardized prevalence of multimorbidity increased substantially, with 12.69% (95% CI: 10.45-15.33) in 2009, 25.44% (95% CI: 23.47-27.52) in 2013, and 35.13% (95% CI:32.64-37.70) in 2018 (P for trend <0.001). The highest bi- and triple-conditions of multimorbidity were dyslipidemia (DP) and overweight or obesity (OO) (12.54%, 95% CI: 11.68-13.46), and DP, OO, and Hypertension (HT) (3.99%, 95% CI: 3.47-4.58) in 2018. From 2009 to 2018, (1) The majority of multimorbidity patterns showed a high prevalence; (2) The percentage of participants with only one chronic condition was found lower, while the percentage with multiple conditions was higher.

CONCLUSIONS

The prevalence of chronic disease multimorbidity in Guangzhou China, has increased substantially among adults. Effective policies targeting multimorbidity are urgently needed, especially for the health management of primary medical institutions.

Study protocol for two stepped-wedge interventional trials evaluating the effects of holistic information technology-based patient-oriented management in older multimorbid patients with cancer: The GERONTE trials

INTRODUCTION

Current hospital-based care pathways are generally single-disease centred. As a result, coexisting morbidities are often suboptimally evaluated and managed, a deficiency becoming increasingly apparent among older patients who exhibit heterogeneity in health status, functional abilities, frailty, and other geriatric impairments. To address this issue, our study aims to assess a newly developed patient-centred care pathway for older patients with multimorbidity and cancer. The new care pathway was based on currently available evidence and co-designed by end-users including health care professionals, patients, and informal caregivers. Within this care pathway, all healthcare professionals involved in the care of older patients with multimorbidity and cancer will form a Health Professional Consortium (HPC). The role of the HPC will be to centralise oncologic and non-oncologic treatment recommendations in accordance with the patient's priorities. Moreover, an Advanced Practice Nurse will act as case-manager by being the primary point of contact for the patient, thus improving coordination between specialists, and by organising and leading the consortium. Patient monitoring and the HPC collaboration will be facilitated by digital communication tools designed specifically for this purpose, with the added benefit of being customisable for each patient.

MATERIALS AND METHODS

The GERONTE study is a prospective international, multicentric study consisting of two stepped-wedge trials performed at 16 clinical sites across three European countries. Each trial will include 720 patients aged 70 years and over with a new or progressive cancer (breast, lung, colorectal, prostate) and at least one moderate or severe multimorbidity. The patients in the intervention group will receive the new care pathway whereas patients in the control group will receive usual oncologic care.

DISCUSSION

GERONTE will evaluate whether this kind of holistic, patient-oriented healthcare management can improve quality of life (primary outcome) and other valuable endpoints in older patients with multimorbidity and cancer. An ancillary study will assess in depth the socio-economic impact of the intervention and deliver concrete implementation guidelines for the GERONTE intervention care pathway.

TRIAL REGISTRATION

FRONE: NCT05720910 TWOBE: NCT05423808.

Longitudinal Patterns of Multimorbidity in Gulf War Era Veterans With and Without Gulf War Illness

Objectives: To examine whether severe Gulf War illness (SGWI) case status was associated with longitudinal multimorbidity patterns. Methods: Participants were users of the Veteran Health Administration Health Care System drawn from the Gulf War Era Cohort and Biorepository (n = 840). Longitudinal measures of multimorbidity were constructed using (1) electronic health records (Charlson Comorbidity Index; Elixhauser; and Veterans Affairs Frailty Index) from 10/1/1999 to 6/30/2023 and (2) self-reported medical conditions (Deficit Accumulation Index) since the war until the survey date. Accelerated failure time models examined SGWI case status as a predictor of time until threshold level of multimorbidity was reached, adjusted for age and sociodemographic and military characteristics. Results: Models, adjusted for covariates, revealed that (1) relative to the SWGI- group, the SGWI+ group was associated with an accelerated time for reaching each threshold and (2) the relationship between SGWI and each threshold was not moderated by age. Discussion: Findings suggest that veterans with SGWI experienced accelerated aging.

Nutrient intake and risk of multimorbidity: a prospective cohort study of 25,389 women

BACKGROUND

Multimorbidity is becoming an increasingly serious public health challenge in the aging population. The impact of nutrients on multimorbidity remains to be determined and was explored using data from a UK cohort study.

METHOD

Our research analysis is mainly based on the data collected by the United Kingdom Women's Cohort Study (UKWCS), which recruited 35,372 women aged 35-69 years at baseline (1995 to 1998), aiming to explore potential associations between diet and chronic diseases. Daily intakes of energy and nutrients were estimated using a validated 217-item food frequency questionnaire at recruitment. Multimorbidity was assessed using the Charlson comorbidity index (CCI) through electronic linkages to Hospital Episode Statistics up to March 2019. Cox's proportional hazards models were used to estimate associations between daily intakes of nutrients and risk of multimorbidity. Those associations were also analyzed in multinomial logistic regression as a sensitivity analysis. In addition, a stratified analysis was conducted with age 60 as the cutoff point.

RESULTS

Among the 25,389 participants, 7,799 subjects (30.7%) were confirmed with multimorbidity over a median follow-up of 22 years. Compared with the lowest quintile, the highest quintile of daily intakes of energy and protein were associated with 8% and 12% increased risk of multimorbidity respectively (HR 1.08 (95% CI 1.01, 1.16), p-linearity = 0.022 for energy; 1.12 (1.04, 1.21), p-linearity = 0.003 for protein). Higher quintiles of daily intakes of vitamin C and iron had a slightly lowered risk of multimorbidity, compared to the lowest quintile. A significantly higher risk of multimorbidity was found to be linearly associated with higher intake quintiles of vitamin B12 and vitamin D (p-linearity = 0.001 and 0.002, respectively) in Cox models, which became insignificant in multinomial logistic regression. There was some evidence of effect modification by age in intakes of iron and vitamin B1 associated with the risk of multimorbidity (p-interaction = 0.006 and 0.025, respectively).

CONCLUSIONS

Our findings highlight a link between nutrient intake and multimorbidity risk. However, there is uncertainty in our results, and more research is needed before definite conclusions can be reached.

Association of multimorbidity with mortality after stroke stratified by age, severity, etiology, and prior disability

BACKGROUND

Multimorbidity is common in patients with stroke and is associated with increased medium- to long-term mortality, but its value for clinical decision-making and case-mix adjustment will depend on other factors, such as age, stroke severity, etiological subtype, prior disability, and vascular risk factors.

AIMS

In the absence of previous studies, we related multimorbidity to long-term post-stroke mortality with stratification by these factors.

METHODS

In patients ascertained in a population-based stroke incidence study (Oxford Vascular Study; 2002-2017), we related pre-stroke multimorbidity (weighted/unweighted Charlson comorbidity index (CCI)) to all-cause/vascular/non-vascular mortality (1/5/10 years) using regression models adjusted/stratified by age, sex, predicted early outcome (THRIVE score), stroke severity (NIH stroke scale (NIHSS)), etiology (Trial of Org 10172 in Acute Stroke Treatment (TOAST)), premorbid disability (modified Rankin Scale (mRS)), and non-CCI risk factors (hypertension, hyperlipidemia, atrial fibrillation, smoking, deprivation, anxiety/depression).

RESULTS

Among 2454 stroke patients (M/SD age: 74.1/13.9 years; 48.9% male; M/SD NIHSS: 5.7/7.0), 1375/56.0% had ⩾ 1 CCI comorbidity and 685/27.9% had ⩾ 2. After age/sex adjustment, multimorbidity (unweighted CCI ⩾ 2 vs 0) predicted (all ps < 0.001) mortality at 1 year (aHR = 1.57, 95% CI = 1.38-1.78), 5 years (aHR = 1.73, 95% CI = 1.53-1.96), and 10 years (aHR = 1.79, 95% CI = 1.58-2.03). Although multimorbidity was independently associated with premorbid disability (mRS > 2: aOR = 2.76, 2.13-3.60) and non-CCI risk factors (hypertension: 1.56, 1.25-1.95; hyperlipidemia: 2.58, 2.03-3.28; atrial fibrillation: 2.31; 1.78-2.98; smoking: 1.37, 1.01-1.86), it predicted death after adjustment for all measured confounders (10-year-aHR = 1.56, 1.37-1.78, p < 0.001), driven mainly by non-vascular death (aHR = 1.89, 1.55-2.29). Predictive value for 10-year all-cause death was greatest in patients with lower expected early mortality: lower THRIVE score (pint < 0.001), age < 75 years (aHR = 2.27, 1.71-3.00), NIHSS < 5 (1.84, 1.53-2.21), and lacunar stroke (3.56, 2.14-5.91). Results were similar using the weighted CCI.

CONCLUSION

Pre-stroke multimorbidity is highly prevalent and is an independent predictor of death after stroke, supporting its inclusion in case-mix adjustment models and in informing decision-making by patients, families, and carers. Prediction in younger patients and after minor stroke, particularly for non-vascular death, suggests potential clinical utility in targeting interventions that require survival for 5-10 years to achieve a favorable risk/benefit ratio.

DATA ACCESS STATEMENT

Data requests will be considered by the Oxford Vascular Study (OXVASC) Study Director (P.M.R.-peter.rothwell@ndcn.ox.ac.uk).

Adverse childhood experiences and trajectories of multimorbidity in individuals aged over 50: Evidence from the English Longitudinal Study of Ageing

BACKGROUND

Adverse childhood experiences (ACE) are important for chronic diseases yet their association with multimorbidity remains understudied. Few studies consider the complexity of multimorbidity or observe multimorbidity development over time.

OBJECTIVE

We investigated whether ACE were associated with multimorbidity at baseline and over a 12-year follow-up period.

PARTICIPANTS AND SETTING

5326 participants aged over 50 were obtained from the English Longitudinal Study of Ageing (ELSA).

METHODS

An ACE summary score was derived using eight ACE items measuring abuse, social care, and household dysfunction. From repeated measurements of 29 chronic conditions over a 12-year period (2008-2019) we derived two multimorbidity measures: number of chronic diseases and number of chronic disease categories. We used multinomial logistic regression to assess associations between ACE and both measures. Mixed effects models were estimated to examine trajectories of multimorbidity by ACE over time.

RESULTS

Graded associations between ACE and multimorbidity were observed. Compared to those without ACE, participants with ≥3 ACE had three times the risk of having ≥3 chronic diseases (RRR 3.06, 95 % CI 1.85-5.05) and falling into ≥3 chronic disease categories (RRR 2·93 95 % CI 1·74-4·95). Graded associations persisted during 12-year follow-up, though differences in multimorbidity between those with ≥3 ACE and those without ACE remained constant (B 0.02, 95 % CI 0·01-0·03, and B -0·01, 95 % CI -0·02-0·00, number of chronic conditions and chronic condition categories respectively).

CONCLUSION

ACE are associated with multimorbidity risk and complexity, associations arising before the age of 50. Early intervention amongst those with ACE could attenuate this association.

Development and implementation of the Specialist Palliative Care in Aged Care (SPACE) Project across Queensland

There is an urgent and unmet need for specialist palliative care services in residential aged care. The Specialist Palliative Care in Aged Care (SPACE) Project aimed to improve palliative and end-of-life care for older people living in residential aged care facilities in Queensland. A representative working group developed a series of service principles around palliative care practice in aged care (comprehensive resident-focused care, streamlined service, and capacity building). Funding was allocated by population to the health services in Queensland to adapt and implement models of care aligned with these principles. SPACE successfully implemented a variety of decentralised models of care across Queensland. The critical elements for the success of SPACE were the use of an expert working group to define the core innovation, networking and implementation support from the central project team and community of practice, and adaptable models of care led by local facilitators. Lessons learned from this real-world case study could be adopted to guide and ensure the successful implementation and sustainability of future complex interventions in healthcare settings, both nationally and internationally.

Multimorbidity, consisting of a combination of chronic diseases and geriatric syndromes, predicts the risk of difficulty in discharge home in older patients admitted to acute care hospital

AIM

To determine whether multimorbidity, consisting of chronic diseases and geriatric syndromes, is associated with home discharge difficulties in older patients.

METHODS

A total of 522 older adults (mean age: 85 ± 7 years) who were admitted to an acute care hospital were enrolled. Multimorbidity was assessed by calculating the number of 16 chronic conditions (CCs): 8 chronic diseases (cardiac diseases, diabetes mellitus, chronic kidney disease, respiratory diseases, gastrointestinal diseases, anemia, dementia, and Parkinson disease) and 8 geriatric syndromes (depression, constipation, chronic pain, polypharmacy, dysphagia, underweight, hypoalbuminemia, and functional limitations). The patients were divided into four groups based on the number of CCs. The outcome was difficulty in discharging home (transfer to other facilities or in-hospital death). Multivariate logistic regression analysis was performed to assess independent associations between four CC groups and failure to discharge home after adjusting for age, sex, living alone, and Barthel index and odds ratio (OR) and 95% confidence interval (CI) were calculated.

RESULTS

Of the 522 patients, 18.8% were transferred to other facilities or died. The proportion of poor outcome in those with 0-2, 3-4, 5-6, and ≥7 CCs was 4.4%, 14.8%, 25.5%, and 37.5%, respectively. Logistic regression analysis after adjusting for covariates revealed that multimorbidity increased the risk of difficulty in discharging home (OR, 2.9 [95% CI, 1.1-8.0] for 3-4 CCs; OR, 4.9 [95% CI, 1.8-13.5] for 5-6 CCs; OR, 8.7 [95% CI, 3.1-24.6] for ≥7 CCs).

CONCLUSION

Multimorbidity, consisting of chronic diseases and geriatric syndromes, predicted difficulty in discharge home in older patients. Geriatr Gerontol Int 2024; 24: 300-305.

Characterizing Aging-Related Health in Older Women with a History of Incarceration: Multimorbidity, Polypharmacy, Mortality, Frailty, and Depression

OBJECTIVE

To characterize aging-related health in women with past CLSI and compare with women with no-CLSI.

METHOD

Health and Retirement Study Wave 11 and 12 data from women age >50 with CLSI were compared with data from women age >50 with no-CLSI. Generalized linear models were estimated for aging-related health outcomes.

RESULTS

The group with CLSI (n = 230) was significantly younger than the no-CLSI group (n = 8035) yet had more physical, functional, and mental health challenges and fewer resources. Incarceration significantly predicted aging-related outcomes of multimorbidity, polypharmacy, mortality, frailty, and depression.

DISCUSSION

Earlier onset of physical and functional health conditions in women with past CLSI has implications for health education and promotion, clinical practice, and intervention design.

Association between Multimorbidity and Psychological Distress among Older Adults in India: The Moderating Role of Elder Abuse

OBJECTIVES

In this study, we examine the association between multimorbidity and psychological distress and to what extent elder abuse mediates the association.

METHODS

We analyzed cross-sectional nationally representative data from the "Building Knowledge Base on Population Ageing in India (BKPAI)." Multivariate logistic regression was used to understand the association between multimorbidity and psychological distress. We used Karlson-Holm- Breen (KHB) method to understand the role of elder abuse in mediating the association between multimorbidity and psychological distress.

RESULTS

Older adults who ever experienced abuse (OR = 1.92 95%CI = 1.62, 2.26, p < .001) or in last one month (OR = 2.09 95%CI = 1.65, 2.64, p < .001) reported higher odds of psychological distress. Further, older adults with four or more chronic diseases are thrice more likely to report psychological distress (OR = 3.03 95%CI = 2.38, 3.82, p < .001). The results further suggest the mediating role of abuse on the association between multimorbidity and psychological distress.

CONCLUSIONS

The results suggest the role of elder abuse on the association between multimorbidity and psychological distress among older population in India.

CLINICAL IMPLICATIONS

Creating an environment to reduce the abuse among older adults who have multimorbidity will be essential to reducing the psychological distress among older adults in India.

Associations of individual chronic diseases and multimorbidity with multidimensional frailty

OBJECTIVE

To examine the associations between individual chronic diseases and multidimensional frailty comprising physical, psychological, and social frailty.

METHODS

Dutch individuals (N = 47,768) age ≥ 65 years completed a general health questionnaire sent by the Public Health Services (response rate of 58.5 %), including data concerning self-reported chronic diseases, multidimensional frailty, and sociodemographic characteristics. Multidimensional frailty was assessed with the Tilburg Frailty Indicator (TFI). Total frailty and each frailty domain were regressed onto background characteristics and the six most prevalent chronic diseases: diabetes mellitus, cancer, hypertension, arthrosis, urinary incontinence, and severe back disorder. Multimorbidity was defined as the presence of combinations of these six diseases.

RESULTS

The six chronic diseases had medium and strong associations with total ((f2 = 0.122) and physical frailty (f2 = 0.170), respectively, and weak associations with psychological (f2 = 0.023) and social frailty (f2 = 0.008). The effects of the six diseases on the frailty variables differed strongly across diseases, with urinary incontinence and severe back disorder impairing frailty most. No synergetic effects were found; the effects of a disease on frailty did not get noteworthy stronger in the presence of another disease.

CONCLUSIONS

Chronic diseases, in particular urinary incontinence and severe back disorder, were associated with frailty. We thus recommend assigning different weights to individual chronic diseases in a measure of multimorbidity that aims to examine effects of multimorbidity on multidimensional frailty. Because there were no synergetic effects of chronic diseases, the measure does not need to include interactions between diseases.

Determinants of multimorbidity in low- and middle-income countries: A systematic review of longitudinal studies and discovery of evidence gaps

Multimorbidity-the coexistence of at least two chronic health conditions within the same individual-is an important global health challenge. In high-income countries (HICs), multimorbidity is dominated by non-communicable diseases (NCDs); whereas, the situation may be different in low- and middle-income countries (LMICs), where chronic communicable diseases remain prominent. The aim of this systematic review was to identify determinants (including risk and protective factors) and potential mechanisms underlying multimorbidity from published longitudinal studies across diverse population-based or community-dwelling populations in LMICs. We systematically searched three electronic databases (Medline, Embase, and Global Health) using pre-defined search terms and selection criteria, complemented by hand-searching. All titles, abstracts, and full texts were independently screened by two reviewers from a pool of four researchers. Data extraction and reporting were according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Methodological quality and risk of bias assessment was performed using the Newcastle-Ottawa Scale for cohort studies. Data were summarized using narrative synthesis. The search yielded 1782 records. Of the 52 full-text articles included for review, 8 longitudinal population-based studies were included for final data synthesis. Almost all studies were conducted in Asia, with only one from South America and none from Africa. All studies were published in the last decade, with half published in the year 2021. The definitions used for multimorbidity were heterogeneous, including 3-16 chronic conditions per study. The leading chronic conditions were heart disease, stroke, and diabetes, and there was a lack of consideration of mental health conditions (MHCs), infectious diseases, and undernutrition. Prospectively evaluated determinants included socio-economic status, markers of social inequities, childhood adversity, lifestyle behaviors, obesity, dyslipidemia, and disability. This review revealed a paucity of evidence from LMICs and a geographical bias in the distribution of multimorbidity research. Longitudinal research into epidemiological aspects of multimorbidity is warranted to build up scientific evidence in regions beyond Asia. Such evidence can provide a detailed picture of disease development, with important implications for community, clinical, and interventions in LMICs. The heterogeneity in study designs, exposures, outcomes, and statistical methods observed in the present review calls for greater methodological standardisation while conducting epidemiological studies on multimorbidity. The limited evidence for MHCs, infectious diseases, and undernutrition as components of multimorbidity calls for a more comprehensive definition of multimorbidity globally.

Identifying patients in need of palliative care: Adaptation of the Necesidades Paliativas CCOMS-ICO© (NECPAL) screening tool for use in Israel

OBJECTIVES

The Necesidades Paliativas CCOMS-ICO© (NECPAL) screening tool was developed to identify patients in need of palliative care and has been used in Israel without formal translation, reliability testing, or validation. Because cultural norms significantly affect subscales such as social vulnerability and health-care delivery, research is needed to comprehensively assess the NECPAL's components, adapt it, and validate it for an Israeli health-care setting. This study linguistically and culturally translated the NECPAL into Hebrew to examine cultural and contextual acceptability for use in the Israeli geriatric health sector. The newly adapted tool was measured for itemized and scale-level content validity, inter-rater reliability (IRR), and construct validity.

METHODS

The NECPAL was back-translated and its content validated by a 5-member expert panel for clarity and relevance, forming the Israeli-NECPAL (I-NECPAL). Six health-care professionals used the I-NECPAL with 25 post-acute geriatric patients to measure IRR. For construct validity, the known-groups method was used, as there is no "gold standard" method for identifying palliative needs for comparison with the NECPAL. The known groups were 2 fictitious cases, predetermined of palliative need. Thirty health-care professionals, blinded to the predetermined palliative status, used the I-NECPAL to determine whether a patient needs a palliative-centered plan of care.

RESULTS

The findings point to acceptable content and construct validity as well as IRR of the I-NECPAL for potential inclusion as a tool for identifying geriatric patients in need of palliative care. Content-validity assessment brought linguistic changes and the exclusion of the frailty parameter from the annex of chronic diseases. The kappa-adjusted scale-level content-validity index indicated a high level of content validity (0.96). IRR indicated a high level of agreement (all parameters with an "excellent-good" agreement level). The sensitivity (0.93), specificity (0.17), positive predictive value (0.53), and negative predictive value (0.71) revealed how heavily the scale weighed upon the surprise question. These metrics are improved when removing the surprise question from the instrument.

SIGNIFICANCE OF RESULTS

Similar to other countries, the Israeli health-care system is regulated by policies that portray the local beliefs and culture as well as evidence-based practice. The decision about when to switch a patient to a palliative-centered plan of care is one such example. It is thus of utmost importance that only locally adapted and vigorously tested screening tools be offered to health-care providers to assist in this decision. The I-NECPAL is the first psychometrically tested palliative needs identification tool for use in the geriatric population in Israel, on both a scale and an itemized level. The results indicate that it can immediately replace the current unvalidated version in use. Further research is needed to determine whether all parts of the scale are relevant for this patient population.

Applying precision medicine principles to the management of multimorbidity: the utility of comorbidity networks, graph machine learning, and knowledge graphs

The current management of patients with multimorbidity is suboptimal, with either a single-disease approach to care or treatment guideline adaptations that result in poor adherence due to their complexity. Although this has resulted in calls for more holistic and personalized approaches to prescribing, progress toward these goals has remained slow. With the rapid advancement of machine learning (ML) methods, promising approaches now also exist to accelerate the advance of precision medicine in multimorbidity. These include analyzing disease comorbidity networks, using knowledge graphs that integrate knowledge from different medical domains, and applying network analysis and graph ML. Multimorbidity disease networks have been used to improve disease diagnosis, treatment recommendations, and patient prognosis. Knowledge graphs that combine different medical entities connected by multiple relationship types integrate data from different sources, allowing for complex interactions and creating a continuous flow of information. Network analysis and graph ML can then extract the topology and structure of networks and reveal hidden properties, including disease phenotypes, network hubs, and pathways; predict drugs for repurposing; and determine safe and more holistic treatments. In this article, we describe the basic concepts of creating bipartite and unipartite disease and patient networks and review the use of knowledge graphs, graph algorithms, graph embedding methods, and graph ML within the context of multimorbidity. Specifically, we provide an overview of the application of graph theory for studying multimorbidity, the methods employed to extract knowledge from graphs, and examples of the application of disease networks for determining the structure and pathways of multimorbidity, identifying disease phenotypes, predicting health outcomes, and selecting safe and effective treatments. In today's modern data-hungry, ML-focused world, such network-based techniques are likely to be at the forefront of developing robust clinical decision support tools for safer and more holistic approaches to treating older patients with multimorbidity.

Multimorbidity clusters in adults 50 years or older with and without a history of cancer: National Health Interview Survey, 2018

BACKGROUND

Multimorbidity is increasing among adults in the United States. Yet limited research has examined multimorbidity clusters in persons aged 50 years and older with and without a history of cancer. An increased understanding of multimorbidity clusters may improve the cancer survivorship experience for survivors with multimorbidity.

METHODS

We identified 7580 adults aged 50 years and older with 2 or more diseases-including 811 adults with a history of primary breast, colorectal, cervical, prostate, or lung cancer-from the 2018 National Health Interview Survey. Exploratory factor analysis identified clusters of multimorbidity among cancer survivors and individuals without a history of cancer (controls). Frequency tables and chi-square tests were performed to determine overall differences in sociodemographic characteristics, health-related characteristics, and multimorbidity between groups.

RESULTS

Cancer survivors reported a higher prevalence of having 4 or more diseases compared to controls (57% and 38%, respectively). Our analysis identified 6 clusters for cancer survivors and 4 clusters for controls. Three clusters (pulmonary, cardiac, and liver) included the same diseases for cancer survivors and controls.

CONCLUSIONS

Diseases clustered differently across adults ≥ 50 years of age with and without a history of cancer. Findings from this study may be used to inform clinical care, increase the development and dissemination of multilevel public health interventions, escalate system improvements, and initiate innovative policy reform.

Assigning disease clusters to people: A cohort study of the implications for understanding health outcomes in people with multiple long-term conditions

Background

Identifying clusters of co-occurring diseases may help characterise distinct phenotypes of Multiple Long-Term Conditions (MLTC). Understanding the associations of disease clusters with health-related outcomes requires a strategy to assign clusters to people, but it is unclear how the performance of strategies compare.

Aims

First, to compare the performance of methods of assigning disease clusters to people at explaining mortality, emergency department attendances and hospital admissions over one year. Second, to identify the extent of variation in the associations with each outcome between and within clusters.

Methods

We conducted a cohort study of primary care electronic health records in England, including adults with MLTC. Seven strategies were tested to assign patients to fifteen disease clusters representing 212 LTCs, identified from our previous work. We tested the performance of each strategy at explaining associations with the three outcomes over 1 year using logistic regression and compared to a strategy using the individual LTCs.

Results

6,286,233 patients with MLTC were included. Of the seven strategies tested, a strategy assigning the count of conditions within each cluster performed best at explaining all three outcomes but was inferior to using information on the individual LTCs. There was a larger range of effect sizes for the individual LTCs within the same cluster than there was between the clusters.

Conclusion

Strategies of assigning clusters of co-occurring diseases to people were less effective at explaining health-related outcomes than a person's individual diseases. Furthermore, clusters did not represent consistent relationships of the LTCs within them, which might limit their application in clinical research.

Long-term multimorbidity trajectories in older adults: The role of cancer, demographics, and health behaviors

BACKGROUND

Multimorbidity is associated with premature mortality and excess health care costs. The burden of multimorbidity is highest among patients with cancer, yet trends and determinants of multimorbidity over time are poorly understood.

METHODS

Via Medicare claims linked to Cancer Prevention Study II data, group-based trajectory modeling was used to compare National Cancer Institute comorbidity index score trends for cancer survivors and older adults without a cancer history. Among cancer survivors, multinomial logistic regression analyses evaluated associations between demographics, health behaviors, and comorbidity trajectories.

RESULTS

In 82,754 participants (mean age, 71.6 years [SD, 5.1 years]; 56.9% female), cancer survivors (n = 11,265) were more likely than older adults without a cancer history to experience the riskiest comorbidity trajectories: (1) steady, high comorbidity scores (remain high; odds ratio [OR], 1.36; 95% CI, 1.29-1.45), and (2) high scores that increased over time (start high and increase; OR, 1.51; 95% CI, 1.38-1.65). Cancer survivors who were physically active postdiagnosis were less likely to fall into these two trajectories (OR, 0.73; 95% CI, 0.64-0.84, remain high; OR, 0.42; 95% CI, 0.33-0.53, start high and increase) compared to inactive survivors. Cancer survivors with obesity were more likely to have a trajectory that started high and increased (OR, 2.83; 95% CI, 2.32-3.45 vs. normal weight), although being physically active offset some obesity-related risk. Cancer survivors who smoked postdiagnosis were also six times more likely to have trajectories that started high and increased (OR, 6.86; 95% CI, 4.41-10.66 vs. never smokers).

CONCLUSIONS

Older cancer survivors are more likely to have multiple comorbidities accumulated at a faster pace than older adults without a history of cancer. Weight management, physical activity, and smoking avoidance postdiagnosis may attenuate that trend.

The association between stress and multiple long-term conditions: A cohort study

BACKGROUND

Stress is an important predictor of long-term conditions. We examine whether hair cortisol (a biomarker of stress) is associated with incidence and accumulation of multiple long-term conditions (MLTC).

METHODS

We included data from 4295 individuals aged ≥50 years within the English Longitudinal Study of Ageing dataset with data on hair cortisol, sociodemographic and health behaviour variables. Cox proportional hazards models were used to quantify the association between hair cortisol at baseline and accumulation of MLTC between 2012/2013 and 2018/2019, both for individuals with and without MLTC at baseline.

RESULTS

Our cohort included 1458 (34.0%) individuals who accumulated MLTC between 2012/2013 and 2018/2019. The proportion of individuals with zero, 1, and ≥ 2 conditions at baseline who accumulated MLTC were 12.0% (n = 127), 40.4% (n = 520), and 41.7% (n = 811), respectively. Higher cortisol levels were associated with higher risk of accumulation of MLTC in both unadjusted [HR:1.15(1.05-1.25)] and models adjusted for sociodemographic and health behaviours [HR:1.12(1.02-1.22)]. For individuals without MLTC at baseline, higher cortisol levels were significantly associated with higher risk of developing MLTC in unadjusted [HR: 1.20(1.05-1.36)] and adjusted models [HR: 1.16(1.02-1.32)].

CONCLUSION

The study provides the first evidence of the role of stress in the development and accumulation of MLTC. This modifiable risk factor could be targeted to reduce the risk of MLTC. However, further work is needed to better understand the mechanisms and pathways that link stress and accumulation of MLTC.

Variation in multimorbidity by sociodemographics and social drivers of health among patients seen at community-based health centers

Purpose

Understanding variation in multimorbidity across sociodemographics and social drivers of health is critical to reducing health inequities.

Methods

From the multi-state OCHIN network of community-based health centers (CBHCs), we identified a cross-sectional cohort of adult (> 25 years old) patients who had a visit between 2019-2021. We used generalized linear models to examine the relationship between the Multimorbidity Weighted Index (MWI) and sociodemographics and social drivers of health (Area Deprivation Index [ADI] and social risks [e.g., food insecurity]). Each model included an interaction term between the primary predictor and age to examine if certain groups had a higher MWI at younger ages.

Results

Among 642,730 patients, 28.2% were Hispanic/Latino, 42.8% were male, and the median age was 48. The median MWI was 2.05 (IQR: 0.34, 4.87) and was higher for adults over the age of 40 and American Indians and Alaska Natives. The regression model revealed a higher MWI at younger ages for patients living in areas of higher deprivation. Additionally, patients with social risks had a higher MWI (3.16; IQR: 1.33, 6.65) than those without (2.13; IQR: 0.34, 4.89) and the interaction between age and social risk suggested a higher MWI at younger ages.

Conclusions

Greater multimorbidity at younger ages and among those with social risks and living in areas of deprivation shows possible mechanisms for the premature aging and disability often seen in community-based health centers and highlights the need for comprehensive approaches to improving the health of vulnerable populations.

Recruiting general practitioners and older patients with multimorbidity to randomized trials

BACKGROUND

Older patients with multimorbidity are under-represented in experimental research.

OBJECTIVE

To explore the barriers and facilitators to general practitioner (GP) and older patient recruitment and retention in a cluster randomized controlled trial (RCT).

METHOD

This descriptive study uses qualitative and quantitative data from a cluster RCT, designed to evaluate the effectiveness of a medicines optimization intervention. The SPPiRE cluster RCT enrolled 51 general practices and 404 patients aged ≥65 years and prescribed ≥15 medicines. Quantitative data were collected from all recruited practices and 32 additional practices who were enrolled, but unable to recruit sufficient participants. Qualitative data were collected from purposive samples of intervention GPs (18/26), patients (27/208), and researcher logs and analysed thematically using inductive coding.

RESULTS

Enrolment rates for practices and patients were 37% and 25%, respectively. Barriers to GP recruitment were lack of resources and to patient recruitment were difficulty understanding trial material and concern about medicines being taken away. GPs' primary motivation was perceived importance of the research question, whereas patients' primary motivation was trust in their GP. All general practices were retained. Thirty-five patients (8.6%) were lost to follow-up for primary outcomes, mainly because they had died and 45% did not return patient-reported outcome measures (PROMs).

CONCLUSION

Patient retention for the primary outcome was high, as it was collected directly from patient records. Patient completion of PROM data was poor, reflecting difficulty in understanding trial material. Recruiting older patients with multimorbidity to clinical trials is possible but requires significant resource and planning.

TRIAL REGISTRATION

ISRCTN Registry ISRCTN12752680.

Hepatocyte steatosis activates macrophage inflammatory response accelerating atherosclerosis development

OBJECTIVES

To investigate the mechanism of comorbidity between non-alcoholic fatty liver disease (NAFLD) and atherosclerosis (AS) based on metabolomics and network pharmacology.

METHODS

Six ApoE－/－ mice were fed with a high-fat diet for 16 weeks as a comorbid model of NAFLD and AS (model group). Normal diet was given to 6 wildtype C57BL/6J mice (control group). Serum samples were taken from both groups for a non-targeted metabolomics assay to identify differential metabolites. Network pharmacology was applied to explore the possible mechanistic effects of differential metabolites on AS and NAFLD. An in vitro comorbid cell model was constructed using NCTC1469 cells and RAW264.7 macrophage. Cellular lipid accumulation, cell viability, morphology and function of mitochondria were detected with oil red O staining, CCK-8 assay, transmission electron microscopy and JC-1 staining, respectively.

RESULTS

A total of 85 differential metabolites associated with comorbidity of NAFLD and AS were identified. The top 20 differential metabolites were subjected to network pharmacology analysis, which showed that the core targets of differential metabolites related to AS and NAFLD were STAT3, EGFR, MAPK14, PPARG, NFKB1, PTGS2, ESR1, PPARA, PTPN1 and SCD. The Kyoto Encyclopedia of Genes and Genomes showed the top 10 signaling pathways were PPAR signaling pathway, AGE-RAGE signaling pathway in diabetic complications, alcoholic liver disease, prolactin signaling pathway, insulin resistance, TNF signaling pathway, hepatitis B, the relax in signaling pathway, IL-17 signaling pathway and NAFLD. Experimental validation showed that lipid metabolism-related genes PPARG, PPARA, PTPN1, and SCD were significantly changed in hepatocyte models, and steatotic hepatocytes affected the expression of macrophage inflammation-related genes STAT3, NFKB1 and PTGS2; steatotic hepatocytes promoted the formation of foam cells and exacerbated the accumulation of lipids in foam cells; the disrupted morphology, impaired function, and increased reactive oxygen species production were observed in steatotic hepatocyte mitochondria, while the formation of foam cells aggravated mitochondrial damage.

CONCLUSIONS

Abnormal lipid metabolism and inflammatory response are distinctive features of comorbid AS and NAFLD. Hepatocyte steatosis causes mitochondrial damage, which leads to mitochondrial dysfunction, increased reactive oxygen species and activation of macrophage inflammatory response, resulting in the acceleration of AS development.

Application of machine learning in measurement of ageing and geriatric diseases: a systematic review

BACKGROUND

As the ageing population continues to grow in many countries, the prevalence of geriatric diseases is on the rise. In response, healthcare providers are exploring novel methods to enhance the quality of life for the elderly. Over the last decade, there has been a remarkable surge in the use of machine learning in geriatric diseases and care. Machine learning has emerged as a promising tool for the diagnosis, treatment, and management of these conditions. Hence, our study aims to find out the present state of research in geriatrics and the application of machine learning methods in this area.

METHODS

This systematic review followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and focused on healthy ageing in individuals aged 45 and above, with a specific emphasis on the diseases that commonly occur during this process. The study mainly focused on three areas, that are machine learning, the geriatric population, and diseases. Peer-reviewed articles were searched in the PubMed and Scopus databases with inclusion criteria of population above 45 years, must have used machine learning methods, and availability of full text. To assess the quality of the studies, Joanna Briggs Institute's (JBI) critical appraisal tool was used.

RESULTS

A total of 70 papers were selected from the 120 identified papers after going through title screening, abstract screening, and reference search. Limited research is available on predicting biological or brain age using deep learning and different supervised machine learning methods. Neurodegenerative disorders were found to be the most researched disease, in which Alzheimer's disease was focused the most. Among non-communicable diseases, diabetes mellitus, hypertension, cancer, kidney diseases, and cardiovascular diseases were included, and other rare diseases like oral health-related diseases and bone diseases were also explored in some papers. In terms of the application of machine learning, risk prediction was the most common approach. Half of the studies have used supervised machine learning algorithms, among which logistic regression, random forest, XG Boost were frequently used methods. These machine learning methods were applied to a variety of datasets including population-based surveys, hospital records, and digitally traced data.

CONCLUSION

The review identified a wide range of studies that employed machine learning algorithms to analyse various diseases and datasets. While the application of machine learning in geriatrics and care has been well-explored, there is still room for future development, particularly in validating models across diverse populations and utilizing personalized digital datasets for customized patient-centric care in older populations. Further, we suggest a scope of Machine Learning in generating comparable ageing indices such as successful ageing index.

Systematic review and meta-analysis of disease clustering in multimorbidity: a study protocol

INTRODUCTION

Multimorbidity is defined as the presence of two or more chronic diseases. Co-occurring diseases can have synergistic negative effects, and are associated with significant impacts on individual health outcomes and healthcare systems. However, the specific effects of diseases in combination will vary between different diseases. Identifying which diseases are most likely to co-occur in multimorbidity is an important step towards population health assessment and development of policies to prevent and manage multimorbidity more effectively and efficiently. The goal of this project is to conduct a systematic review and meta-analysis of studies of disease clustering in multimorbidity, in order to identify multimorbid disease clusters and test their stability.

METHODS AND ANALYSIS

We will review data from studies of multimorbidity that have used data clustering methodologies to reveal patterns of disease co-occurrence. We propose a network-based meta-analytic approach to perform meta-clustering on a select list of chronic diseases that are identified as priorities for multimorbidity research. We will assess the stability of obtained disease clusters across the research literature to date, in order to evaluate the strength of evidence for specific disease patterns in multimorbidity.

ETHICS AND DISSEMINATION

This study does not require ethics approval as the work is based on published research studies. The study findings will be published in a peer-reviewed journal and disseminated through conference presentations and meetings with knowledge users in health systems and public health spheres.

PROSPERO REGISTRATION NUMBER

CRD42023411249.

Multimorbidity in African ancestry populations: a scoping review

OBJECTIVES

Multimorbidity (MM) is a growing concern linked to poor outcomes and higher healthcare costs. While most MM research targets European ancestry populations, the prevalence and patterns in African ancestry groups remain underexplored. This study aimed to identify and summarise the available literature on MM in populations with African ancestry, on the continent, and in the diaspora.

DESIGN

A scoping review was conducted in five databases (PubMed, Web of Science, Scopus, Science Direct and JSTOR) in July 2022. Studies were selected based on predefined criteria, with data extraction focusing on methodology and findings. Descriptive statistics summarised the data, and a narrative synthesis highlighted key themes.

RESULTS

Of the 232 publications on MM in African-ancestry groups from 2010 to June 2022-113 examined continental African populations, 100 the diaspora and 19 both. Findings revealed diverse MM patterns within and beyond continental Africa. Cardiovascular and metabolic diseases are predominant in both groups (80% continental and 70% diaspora). Infectious diseases featured more in continental studies (58% continental and 16% diaspora). Although many papers did not specifically address these features, as in previous studies, older age, being women and having a lower socioeconomic status were associated with a higher prevalence of MM, with important exceptions. Research gaps identified included limited data on African-ancestry individuals, inadequate representation, under-represented disease groups, non-standardised methodologies, the need for innovative data strategies, and insufficient translational research.

CONCLUSION

The growing global MM prevalence is mirrored in African-ancestry populations. Recognising the unique contexts of African-ancestry populations is essential when addressing the burden of MM. This review emphasises the need for additional research to guide and enhance healthcare approaches for African-ancestry populations, regardless of their geographic location.

Clustering by multiple long-term conditions and social care needs: a cross-sectional study among 10 026 older adults in England

BACKGROUND   : People with multiple long-term conditions (MLTC) face health and social care challenges. This study aimed to classify people by MLTC and social care needs (SCN) into distinct clusters and quantify the association between derived clusters and care outcomes. METHODS : A cross-sectional study was conducted using the English Longitudinal Study of Ageing, including people with up to 10 MLTC. Self-reported SCN was assessed through 13 measures of difficulty with activities of daily living, 10 measures of mobility difficulties and whether health status was limiting earning capability. Latent class analysis was performed to identify clusters. Multivariable logistic regression quantified associations between derived MLTC/SCN clusters, all-cause mortality and nursing home admission. RESULTS: Our study included 9171 people at baseline with a mean age of 66.3 years; 44.5% were men. Nearly 70.8% had two or more MLTC, the most frequent being hypertension, arthritis and cardiovascular disease. We identified five distinct clusters classified as high SCN/MLTC through to low SCN/MLTC clusters. The high SCN/MLTC included mainly women aged 70-79 years who were white and educated to the upper secondary level. This cluster was significantly associated with higher nursing home admission (OR=8.71; 95% CI: 4.22 to 18). We found no association between clusters and all-cause mortality. CONCLUSIONS: We have highlighted those at risk of worse care outcomes, including nursing home admission. Distinct clusters of individuals with shared sociodemographic characteristics can help identify at-risk individuals with MLTC and SCN at primary care level.

The association between dietary intake of macro- and micronutrients and multimorbidity: a cross-sectional study in Cyprus

Research on the link between diet and multimorbidity is scarce, despite significant studies investigating the relationship between diet and individual chronic conditions. This study examines the association of dietary intake of macro- and micronutrients with multimorbidity in Cyprus's adult population. It was conducted as a cross-sectional study, with data collected using a standardised questionnaire between May 2018 and June 2019. The questionnaire included sociodemographic information, anthropometrics, medical history, dietary habits, sleep quality, smoking habits, and physical activity. The participants were selected using a stratified sampling method from adults residing in the five government-controlled municipalities of the Republic of Cyprus. The study included 1137 adults with a mean age of 40⋅8 years, of whom 26 % had multimorbidity. Individuals with multimorbidity consumed higher levels of sodium (P = 0⋅009) and vitamin A (P = 0⋅010) compared to those without multimorbidity. Additionally, higher fibre and sodium intake were also observed in individuals with at least one chronic disease of the circulatory system or endocrine system, compared to those with no chronic diseases in these systems (P < 0⋅05). Logistic regression models revealed that individuals with ≥2 chronic diseases compared to 0 or 1 chronic disease had higher fat intake (OR = 1⋅06, 95 % CI: 1⋅02, 1⋅10), higher iron intake (OR = 1⋅05, 95 % CI: 1⋅01, 1⋅09), lower mono-unsaturated fat intake (OR = 0⋅91, 95 % CI: 0⋅86, 0⋅96), and lower zinc intake (OR = 0⋅98, 95 % CI: 0⋅96, 0⋅99). Future research should replicate these results to further explore the intricate relationships between nutrient intake and multimorbidity. Our study's findings suggest that specific dietary components may contribute to preventing and managing multimorbidity.

Multimorbidity in systemic lupus erythematosus in a population-based cohort: the lupus Midwest network

OBJECTIVES

To assess the prevalence and incidence of multimorbidity and the association with the SLICC/ACR damage index (SDI) among patients with systemic lupus erythematosus (SLE).

METHODS

Using prevalent and incident population-based cohorts of patients with SLE and their matched comparators, we assessed 57 chronic conditions. Chronic conditions were categorized as SDI-related or SDI-unrelated. Multimorbidity was defined as the presence of 2+ chronic conditions. Multimorbidity at prevalence and incidence/index was compared between cohorts using logistic regression. Cox models were used to examine development of multimorbidity after SLE incidence.

RESULTS

The prevalent cohort included 449 patients with established SLE on January 1, 2015. They were three times more likely to have multimorbidity compared with non-SLE comparators (OR 2.98, 95% CI 2.18-4.11). The incident cohort included 270 patients with new-onset SLE. At SLE incidence, patients with SLE were more likely to have multimorbidity than comparators (OR 2.27, 95% CI 1.59-3.27). After incidence, the risk of developing multimorbidity was 2-fold higher among patients with SLE than comparators (hazard ratio (HR) 2.11, 95% CI 1.59-2.80). Development of multimorbidity was higher in patients with SLE based on SDI-related (HR 2.91, 95% CI 2.17-3.88) and SDI-unrelated conditions (HR 1.73, 95% CI, 1.32-2.26).

CONCLUSION

Patients with SLE have a higher burden of multimorbidity, even before the onset of the disease. The risk disparity continues after SLE classification and is also seen in a prevalent SLE cohort. Multimorbidity is driven both by SDI-related and unrelated conditions.

Beyond MACE: a multidimensional approach to outcomes in clinical trials for older adults with stable ischemic heart disease

The global population of older adults is expanding rapidly resulting in a shift towards managing multiple chronic diseases that coexist and may be exacerbated by cardiovascular illness. Stable ischemic heart disease (SIHD) is a predominant contributor to morbidity and mortality in the older adult population. Although results from clinical trials demonstrate that chronological age is a predictor of poor health outcomes, the current management approach remains suboptimal due to insufficient representation of older adults in randomized trials and the inadequate consideration for the interaction between biological aging, concurrent geriatric syndromes, and patient preferences. A shift towards a more patient-centered approach is necessary for appropriately and effectively managing SIHD in the older adult population. In this review, we aim to demonstrate the distinctive needs of older adults who prioritize holistic health outcomes like functional capacity, cognitive abilities, mental health, and quality of life alongside the prevention of major adverse cardiovascular outcomes reported in cardiovascular clinical trials. An individualized, patient-centered approach that involves shared decision-making regarding outcome prioritization is needed when any treatment strategy is being considered. By prioritizing patients and addressing their unique needs for successful aging, we can provide more effective care to a patient population that exhibits the highest cardiovascular risks.

Needs of multimorbid heart failure patients and their carers: a qualitative interview study and the creation of personas as a basis for a blended collaborative care intervention

Introduction

Involving patients and carers in the development of blended collaborative care (BCC) interventions for multimorbid heart failure (HF) patients is recommended but rarely practised, and research on the patient perspective is scarce. The aim of this study is to investigate patients' and carers' care-related needs and preferences to better customize a novel international BCC intervention.

Methods

A qualitative study design using framework analysis was employed. The study was performed in accordance with the EQUATOR standards for reporting qualitative research (SRQR). Patients aged at least 65 years with HF and at least two other physical diseases as well as their carers completed semistructured interviews in Germany, Italy, and Denmark. Based on these interviews, personas (prototype profiles of patients and carers) were created.

Results

Data from interviews with 25 patients and 17 carers were analysed. Initially, seven country-specific personas were identified, which were iteratively narrowed down to a final set of 3 personas: (a) the one who needs and wants support, (b) the one who has accepted their situation with HF and reaches out when necessary, and (c) the one who feels neglected by the health care system. Carers identifying with the last persona showed high levels of psychological stress and a high need for support.

Discussion

This is the first international qualitative study on patients' and carers' needs regarding a BCC intervention using the creation of personas. Across three European countries, data from interviews were used to develop three contrasting personas. Instead of providing "one size fits all" interventions, the results indicate that BCC interventions should offer different approaches based on the needs of individual patients and carers. The personas will serve as a basis for the development of a novel BCC intervention as part of the EU project ESCAPE (Evaluation of a patient-centred biopSychosocial blended collaborative CAre Pathway for the treatment of multimorbid Elderly patients).

Impact of Vaccination on the Course and Outcome of COVID-19 in Patients with Multimorbidity

Vaccination is the most cost-effective method of preventing COVID-19; however, data on its effect on patients with multimorbidity is limited. The aim was to evaluate the effect of vaccination against new coronavirus infection (NCI) in patients with multimorbid pathology in hospital treatment on the outcome of COVID-19 disease. An analysis was carried out of 1832 records of patients in one of the COVID-19 hospitals in Moscow for 2020-2022. Statistical analysis was carried out using the StatTech v. 3.1.3 software, and the binary logistic regression (BLR) method was used to obtain prognostic models. The median age of patients was 69 years, and 76% of them had received two vaccine doses. To assess the outcome of the disease, two prognostic models were obtained depending on the presence of a multimorbidity in patients: cardiovascular pathology and/or atherosclerosis and/or type 2 diabetes mellitus (Model 1) or atherosclerosis and/or type 2 diabetes mellitus and/or encephalopathy (Model 2), against the background of the presence or absence of vaccination against NCI. When assessing the outcome of NCI in Model 1, the odds of death decreased by 3.228 times with two doses of Sputnik V in patients with multimorbidity. According to Model 2, for patients with multimorbidity, the chances of death decreased by 3.281 times with two doses of Sputnik V. The presence of two doses of Sputnik V increased the likelihood of recovery in patients with multimorbidity by more than three times.

Sociodemographic characteristics and longitudinal progression of multimorbidity: A multistate modelling analysis of a large primary care records dataset in England

BACKGROUND

Multimorbidity, characterised by the coexistence of multiple chronic conditions in an individual, is a rising public health concern. While much of the existing research has focused on cross-sectional patterns of multimorbidity, there remains a need to better understand the longitudinal accumulation of diseases. This includes examining the associations between important sociodemographic characteristics and the rate of progression of chronic conditions.

METHODS AND FINDINGS

We utilised electronic primary care records from 13.48 million participants in England, drawn from the Clinical Practice Research Datalink (CPRD Aurum), spanning from 2005 to 2020 with a median follow-up of 4.71 years (IQR: 1.78, 11.28). The study focused on 5 important chronic conditions: cardiovascular disease (CVD), type 2 diabetes (T2D), chronic kidney disease (CKD), heart failure (HF), and mental health (MH) conditions. Key sociodemographic characteristics considered include ethnicity, social and material deprivation, gender, and age. We employed a flexible spline-based parametric multistate model to investigate the associations between these sociodemographic characteristics and the rate of different disease transitions throughout multimorbidity development. Our findings reveal distinct association patterns across different disease transition types. Deprivation, gender, and age generally demonstrated stronger associations with disease diagnosis compared to ethnic group differences. Notably, the impact of these factors tended to attenuate with an increase in the number of preexisting conditions, especially for deprivation, gender, and age. For example, the hazard ratio (HR) (95% CI; p-value) for the association of deprivation with T2D diagnosis (comparing the most deprived quintile to the least deprived) is 1.76 ([1.74, 1.78]; p < 0.001) for those with no preexisting conditions and decreases to 0.95 ([0.75, 1.21]; p = 0.69) with 4 preexisting conditions. Furthermore, the impact of deprivation, gender, and age was typically more pronounced when transitioning from an MH condition. For instance, the HR (95% CI; p-value) for the association of deprivation with T2D diagnosis when transitioning from MH is 2.03 ([1.95, 2.12], p < 0.001), compared to transitions from CVD 1.50 ([1.43, 1.58], p < 0.001), CKD 1.37 ([1.30, 1.44], p < 0.001), and HF 1.55 ([1.34, 1.79], p < 0.001). A primary limitation of our study is that potential diagnostic inaccuracies in primary care records, such as underdiagnosis, overdiagnosis, or ascertainment bias of chronic conditions, could influence our results.

CONCLUSIONS

Our results indicate that early phases of multimorbidity development could warrant increased attention. The potential importance of earlier detection and intervention of chronic conditions is underscored, particularly for MH conditions and higher-risk populations. These insights may have important implications for the management of multimorbidity.

Association between multimorbidity and informal long-term care use in China: a nationwide cohort study

BACKGROUND

The impact of multimorbidity on long-term care (LTC) use is understudied, despite its well-documented negative effects on functional disabilities. The current study aims to assess the association between multimorbidity and informal LTC use in China. We also explored the socioeconomic and regional disparities.

METHODS

The study included 10,831 community-dwelling respondents aged 45 years and older from the China Health and Retirement Longitudinal Study in 2011, 2015, and 2018 for analysis. We used a two-part model with random effects to estimate the association between multimorbidity and informal LTC use. Heterogeneity of the association by socioeconomic position (education and income) and region was explored via a subgroup analysis. We further converted the change of informal LTC hours associated with multimorbidity into monetary value and calculated the 95% uncertainty interval (UI).

RESULTS

The reported prevalence of multimorbidity was 60·0% (95% CI: 58·9%, 61·2%) in 2018. We found multimorbidity was associated with an increased likelihood of receiving informal LTC (OR = 2·13; 95% CI: 1·97, 2·30) and more hours of informal LTC received (IRR = 1·20; 95% CI: 1·06, 1·37), ceteris paribus. Participants in the highest income quintile received more hours of informal LTC care (IRR = 1·62; 95% CI: 1·31, 1·99). The estimated monetary value of increased informal LTC hours among participants with multimorbidity was equivalent to 3·7% (95% UI: 2·2%, 5·4%) of China's GDP in 2018.

CONCLUSION

Our findings substantiate the threat of multimorbidity to LTC burden. It is imperative to strengthen LTC services provision, especially among older adults with multimorbidity and ensure equal access among those with lower income.

Healthcare for Older Adults with Multimorbidity: A Scoping Review of Reviews

Purpose

To summarize adverse healthcare outcomes experienced by older adults with multimorbidity and barriers perceived by stakeholders regarding the healthcare systems primarily designed to address individual health conditions. Healthcare elements that aim to provide coordinated, continuous, and comprehensive services for this population were also identified.

Patients and Methods

We applied the methodology framework developed by Arksey and O'Malley to guide the review. The three-step search strategy was used to identify relevant English reviews that focused on adverse healthcare outcomes and barriers encountered by older adults with multimorbidity and other stakeholders regarding the single-disease-focused healthcare systems, as well as those concentrated on healthcare elements that aim to provide coordinated, continuous, and comprehensive services for older adults with multimorbidity. Five electronic databases, including PubMed/Medline, CINAHL, Web of Science Core Collection, Cochrane Library, and Embase, were systematically searched from database inception to February 2022. A standardized table was used to extract data. Thematic analysis was then conducted under the guidance of the Rainbow Model of Integrated Care and the Chronic Care Model.

Results

Twenty reviews were included in this study. Therapeutic competitions, high healthcare service utilization, and high healthcare costs were three adverse healthcare outcomes experienced by patients. Both patients and healthcare professionals faced various barriers. Other stakeholders, including informal caregivers, healthcare managers, and policymakers, also perceived several barriers. Numerous healthcare elements were identified that may contribute to optimized services. The elements most frequently mentioned included the implementation of shared decision-making, comprehensive geriatric assessments, and individual care plans.

Conclusion

This study conducted a comprehensive overview of the current knowledge related to healthcare for older adults with multimorbidity. In the future, it is necessary to develop more coordinated, continuous, and comprehensive healthcare service delivery models based on the healthcare needs of older adults with multimorbidity and the specific characteristics of different countries.

The Impact of Multimorbidity on All-Cause Mortality: A Longitudinal Study of 87,151 Thai Adults

Objectives: To investigate associations between multimorbidity, socio-demographic and health behaviour factors, and their interactions (multimorbidity and these factors) with all-cause mortality among Thai adults. Methods: Associations between multimorbidity (coexistence of two + chronic diseases) and mortality between 2005 and 2019 were investigated among Thai Cohort Study (TCS) participants (n = 87,151). Kaplan-Meier survival curves estimated and compared survival times. Multivariate Cox proportional hazards models examined associations between risk factors, and interactions between multimorbidity, these factors, and survival. Results: 1,958 cohort members died between 2005 and 2019. The risk of death was 43% higher for multimorbid people. In multivariate Cox proportional hazard models, multimorbidity/number of chronic conditions, age, long sleep duration, smoking and drinking were all independent factors that increased mortality risk. Women, urbanizers, university education, over 20,000-baht personal monthly income and soybean products consumption lowered risk. The interactions between multimorbidity and these variables (except for female, urbanizers and soybeans intake) also had significant (p < 0.05) impact on all-cause mortality. Conclusion: The results emphasise the importance of healthy lifestyle and reduced intake of alcohol and tobacco, in reducing premature mortality, especially when suffering from multimorbidity.