Evidence on multimorbidity from definition to intervention: An overview of systematic reviews

Adverse childhood experiences with physical, depressive, and cognitive multimorbidity among Chinese adults and the mediating role of loneliness

Little is known about the associations between adverse childhood experiences (ACES) and physical, depressive, and cognitive (PDC) disorders and their multimorbidity. Moreover, no study has assessed whether loneliness mediates any such associations. Using a nationally population-based study in China, we aimed to investigate the associations between ACES and PDC disorders and their multimorbidity among 11,124 middle-aged and older adults. Eight categories of outcomes including no disorders, physical disorder, depressive symptoms, cognitive disorder, and their four combinations were assessed. Twelve ACES indicators were measured using a validated questionnaire. Multivariate logistic regression and stratification analyses were performed to explore the association between ACES and PDC disorders and their multimorbidity, as well as potential modifiers. Mediate analyses were applied to examine the potential pathways via loneliness. Of the 11,124 individuals (45.8 % women, mean [SD] age: 60.1 [8.9] years), 79.3 % had at least one ACE. Compared with individuals without ACES, those who had four or more ACES had elevated risks of PDC disorders and their multimorbidity. The estimated odds ratios (OR) were 2.95 (95 % CI: 2.46-3.54) for physical-depressive multimorbidity, 1.59 (1.28-1.98) for physical-cognitive multimorbidity, 2.58 (2.01-3.31) for depressive-cognitive multimorbidity, and 2.91 (2.15-3.96) for PDC multimorbidity, respectively. There is an exposure-response relationship between cumulative ACES with different outcomes. These associations were mediated by loneliness, with a mediation proportion varying from 8.7 % to 32.5 %. However, no significant modification was observed by sex, age, educational level, and childhood economic status. Our findings provided important insights for reducing childhood adversity to prevent chronic multimorbidity.

Health and social care staff's experiences working with adults with complex needs - a focus group study

BACKGROUND

Multimorbidity is increasing globally, affecting over one-third of the population. Adults with complex needs often experience physical, mental, and cognitive disorders, leading to increased healthcare utilization, reduced quality of life, and social challenges. The frequent co-occurrence of psychiatric conditions, substance abuse, addiction, and homelessness highlights the complexity of these needs. Collaboration between healthcare and social services is essential for delivering integrated care but is often hindered by legislative constraints and difficulties in coordinating care. Although integrated care has been shown to improve outcomes, persistent challenges affect staff in their daily work with adults with complex needs. Therefore, the aim was to describe health and social care staff's experiences working with adults with complex needs, with a focus on what promotes or hinders collaboration and the individual's participation.

METHODS

This study employed a descriptive qualitative design. Data were collected through four focus group interviews with 17 health and social care staff members and analyzed using qualitative content analysis.

RESULTS

Data analysis resulted in three generic categories: (i) collaboration between authorities is complex, (ii) challenges working according to the person's needs, and (iii) participation under difficult conditions.

CONCLUSIONS

This study highlights both challenges and facilitators in working with adults with complex needs. Collaboration was hindered by legislative, financial, and organizational disparities but facilitated by interprofessional forums and collaborative meetings. Establishing trusting relationships free from bureaucratic constraints was important for providing person-centered care. However, fostering meaningful participation remains challenging because of the individual's limited capacity to engage and the complexities that staff face in balancing respect for autonomy with acting in the person's best interest. Further research incorporating perspectives from adults with complex needs, their relatives, and management could enhance the understanding of how collaboration, participation, and organizational barriers impact the provision of integrated healthcare and social services.

Multimorbidity and risk of dementia: A systematic review and meta-analysis of longitudinal cohort studies

BACKGROUND

Chronic diseases (e.g., hypertension, diabetes, and heart diseases) have been proposed as marked predictors of incident dementia. However, synthesised evidence on the effect of multimorbidity on dementia is still lacking. We aim to summarise the association between multimorbidity and risk of dementia in longitudinal cohorts.

METHODS

In this systematic review and meta-analysis, we conducted a systematic search in PubMed, Web of Science and Embase from inception to Dec 14, 2024, to identify longitudinal cohort studies reporting the association between multimorbidity or multimorbidity patterns and risk of dementia. Information of included studies were extracted by three reviewers (YaZ, YY and YuZ), and the quality assessment was conducted using the Newcastle-Ottawa Scale. The inverse-variance weighted random effects meta-analysis was performed to obtain the pooled hazard ratios (HRs) and 95 % confidence intervals (CIs) for dementia associated with multimorbidity and cardiometabolic multimorbidity (CMM). Cochran's Q test and the I2 statistic were used to indicate heterogeneity among the studies. Meta-regression analysis, subgroup analysis and sensitivity analysis were conducted to determine any valid sources of heterogeneity. This study was registered with PROSPERO (CRD42023403684).

RESULTS

We included 17 longitudinal cohort studies (2262,885 middle-aged and older participants) in the systematic review, of which seven were included in meta-analysis. All studies presented moderate to high methodological quality. Meta-analysis showed a positive association between multimorbidity and incident dementia (HR=1.53, 95 % CI=1.12 to 2.09), with substantial heterogeneity (I2=95.2 %). Studies using health records to measure dementia tend to find a stronger positive relationship between multimorbidity and risk of dementia than those using self-report (HRhealth records=1.94, 95 % CI=1.35 to 2.78, I2=94 %; HRself-report=1.17, 95 % CI=1.07 to 1.28, I2=0 %). The impacts of CMM were also observed, and the HRs for dementia ranged from 2.49 (combination of heart diseases and stroke: 95 % CI=1.64 to 3.78) to 3.77 (combination of diabetes, heart diseases and stroke: 95 % CI=2.02 to 7.02). The heterogeneity was moderate, with I2 ranging from 46.9 % (p for heterogeneity=0.152) to 84.1 % (p for heterogeneity=0.002). The impacts of number of diseases, multimorbidity clusters, and multimorbidity trajectory on risk of dementia were narratively summarised due to lacking comparable studies. Limited evidence (only one study) precluded quantitative synthesis for the association of physical and psychological multimorbidity with dementia.

CONCLUSION

Multimorbidity and CMM pattern were significantly associated with risk of dementia, while the effect of physical and psychological multimorbidity remain inconclusive. Individuals affected by multimorbidity should be prioritised in risk factor modification and dementia prevention. Preventing the development of multimorbidity is also crucial-particularly those who already have one chronic disease-in order to maintain cognitive health.

Risk prediction models for mortality in patients with multimorbidity: a systematic review and meta-analysis

Background

Multimorbidity is a major aging and public health problem that has a significant burden on a global scale. The number of risk prediction models for mortality in patients with multimorbidity is increasing; however, the quality and applicability of these prediction models in clinical practice and future research remain uncertain.

Objective

To systematically review published studies on risk prediction models for mortality in patients with multimorbidity.

Methods

The Wanfang, China National Knowledge Infrastructure, China Science and Technology Journal (VIP), PubMed, SinoMed, Cochrane Library, Web of Science, Embase, and Cumulative Index to Nursing and Allied Health Literature databases were searched from inception until May 30, 2024. Two independent reviewers performed study selection, data extraction, and quality assessment. The Prediction Model Risk of Bias Assessment Tool (PROBAST) checklist was utilized to assess the risk of bias and applicability.

Results

Overall, 18 studies with 21 prediction models were included in this review. Logistic regression was used for model development in 12 studies, Cox regression in four, a parametric Weibull regression in one, and machine learning in one study. The incidence of mortality in patients with multimorbidity ranged from 7.6-50.0%. The most frequently used predictors were age and body mass index. The reported area under the receiver operating characteristic curve (AUC) and C-index values ranged from 0.700-0.907. Three studies were rated as having a low risk of bias, 11 as high, and four as unclear, primarily owing to poor reporting of the analysis domain. The pooled AUC value of the seven validated models was 0.81, with a 95% confidence interval ranging from 0.77-0.86, signifying a fair level of discrimination.

Conclusion

The included studies revealed a degree of discriminatory ability in predicting mortality in patients with multimorbidity; however, they all demonstrated significant risks of bias based on the PROBAST checklist assessment. Future researchers should prioritize the development of new models that incorporate rigorous study designs and multicenter external validation, which may improve the precision of risk predictions and help the development of global strategies for this significant public health problem.

Registration

The study protocol was registered in PROSPERO (registration number: CRD42024543170).

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO/recorddashboard, PROSPERO CRD42024543170.

Association of possible Sarcopenia, Sarcopenia and sarcopenic obesity with multimorbidity among middle-aged and older adults: findings from the China health and retirement longitudinal study

BACKGROUND AND OBJECTIVES

The association between possible sarcopenia, sarcopenia and sarcopenic obesity on multimorbidity risk remains poorly investigating. We aimed to evaluate the associations between possible sarcopenia, sarcopenia and sarcopenic obesity on multimorbidity prevalence and incidence among middle-aged and older Chinese population.

METHODS

A total of 13,036 participants from the China Health and Retirement Longitudinal Study 2011 were included in cross-sectional analyses. 5771 participants were including in longitudinal analyses and were followed up in 2018. Sarcopenia status was defined according to the Asian Working Group for Sarcopenia 2019 (AWGS 2019) criteria. Obesity was defined according to body mass index.

RESULTS

In cross-sectional analyses, possible sarcopenia, sarcopenia and sarcopenic obesity were significantly associated with higher multimorbidity prevalence. During the 7 years of follow-up, 2295(39.77%) participants with new-onset multimorbidity were identified. Compared with participants without sarcopenia or obesity, a greater increase in the risk of multimorbidity incidence was found among participants with obesity only (OR = 1.39, 1.21-1.59), sarcopenia only (OR = 1.45, 1.35-1.58) and sarcopenic obesity (OR = 2.42, 2.03-2.89). Both pre-sarcopenia, sarcopenia and sarcopenic obesity were positively related to an increased number of morbidities.

CONCLUSION

Pre-sarcopenia, sarcopenia and sarcopenic obesity were associated with higher multimorbidity prevalence and incidence. Our findings provide important implications for screening and preventing possible sarcopenia, sarcopenia and obesity, which may be beneficial in reducing chronic disease burden.

Multimorbid life expectancy across race, socio-economic status, and sex in South Africa

Multimorbidity is increasing globally as populations age. However, it is unclear how long individuals live with multimorbidity and how it varies by social and economic factors. We investigate this in South Africa, whose apartheid history further complicates race, socio-economic, and sex inequalities. We introduce the term 'multimorbid life expectancy' (MMLE) to describe the years lived with multimorbidity. Using data from the South African National Income Dynamics Study (2008-17) and incidence-based multistate Markov modelling, we find that females experience higher MMLE than males (17.3 vs 9.8 years), and this disparity is consistent across all race and education groups. MMLE is highest among Asian/Indian people and the post-secondary educated relative to other groups and lowest among African people. These findings suggest there are associations between structural inequalities and MMLE, highlighting the need for health-system and educational policies to be implemented in a way proportional to each group's level of need.

Quadratic associations between sleep and multimorbidity among the older population in China: Evidence from CLHLS 2011 to 2018

OBJECTIVES

To investigate the relationship between sleep and multimorbidity, including the associations between sleep duration and multimorbidity, as well as between sleep quality and multimorbidity.

METHODS

Using data from the three latest waves of the Chinese Longitudinal Health Longevity Study (2011, 2014, and 2018), a binary panel regression was conducted to investigate the quadratic relationship between sleep duration and multimorbidity. Subsequently, quadratic fitting and robustness analysis were further utilized to strengthen the verification of this relationship.

RESULTS

From 2011 to 2018, the prevalence of multimorbidity increased, with average rates of 0.309, 0.345, and 0.367, respectively. Meanwhile, sleep duration was 7.45, 7.34, and 7.39, but sleep quality showed a declining trend with scores of 3.70, 3.63, and 3.47, respectively. Furthermore, the regression analysis revealed that the odds ratios (OR) for the relationship between sleep duration and multimorbidity, and between the square of sleep duration and multimorbidity were 0.734, with 95 % CI = [0.6272, 0.8582] and 1.016, with 95 % CI = [1.0058, 1.0262], respectively. From the quadratic relationship, it is evident that the multimorbidity among older Chinese adults initially decreases and then increases with long sleep durations.

CONCLUSIONS

The multimorbidity was significantly different among individuals with different sleep duration. A U-shaped relationship was observed between sleep duration and multimorbidity, whereby both short and excessive sleep durations were associated with higher rates of multimorbidity. Additionally, a negative association was found between sleep quality and multimorbidity, indicating that higher sleep quality was linked to lower rates of multimorbidity.

Health beliefs mediates the association between the number of non-communicable diseases and preventive behaviors in middle-aged and older adults in southern China

BACKGROUND

The triadic relationship among the number of NCDs, preventive behaviors and health beliefs has not been fully explored, especially the role of health beliefs.

AIMS

To explore the association between the number of NCDs and preventive behaviors, as well as the mediating effect of health beliefs and its dimensions among middle-aged and older adults. Provide scientific evidence for developing targeted behavior intervention.

METHODS

Data from 2095 middle-aged and older adults who completed demographic information, health beliefs and preventive behaviors questionnaire. Mediation analysis was used to explore the association of health beliefs and its dimensions between the number of NCDs and preventive behaviors.

RESULTS

Health beliefs and self-efficacy positively impacted preventive behaviors, whereas perceived severity, while perceived barriers had negative effects. Health beliefs (β = - 0.1809, 95% CI - 0.2658 to - 0.0960) and its dimensions(Perceived barriers:β = - 0.0881, 95% CI - 0.1533 to - 0.0232, self-efficacy: β = - 0.2706, 95% CI - 0.3592 to - 0.1892) partially mediated the associations between the number of NCDs and preventive behaviors. The negative mediation effects indicates that as the number of NCDs increases, preventive behaviors decrease, partly due to a decline in health beliefs and self-efficacy, as well as an increase in perceived barriers (scored inversely, meaning higher barriers). These mediation pathways exhibited modest strength, highlighting the importance of health beliefs on behavior change.

CONCLUSIONS

An increasing number of NCDs is associated with reduced engagement in preventive behaviors. Health beliefs and its dimensions play a partial mediating role in this relationship. Effective intervention targeting health beliefs may help promote positive behavioral changes.

Effect of PM2.5 and its constituents on hospital admissions for cardiometabolic multimorbidity in Urumqi, China

Cardiometabolic multimorbidity (CMM) is caused by two or more of the diseases ischemic heart disease (CVD), type 2 diabetes mellitus (T2DM), and stroke, and therefore requires more hospitalization and healthcare costs. However, few studies have investigated fine particulate matter (PM2.5) and its constituents and the risk of hospital admissions for CMM. We aimed to study these associations in Urumqi, a representative area in northwest China. The effect of PM2.5 and its constituents on the hospital admissions for CMM was determined using the quantile-based g-computation (QBGC) and bayesian kernel machine regression (BKMR) method, in which the constituents with the greatest effect on the hospital admissions for CMM were ranked as NO3- > SO42- > NH4+ > BC > OM. Among all constituents, NO3- presented the highest risk, with the largest effect observed at lag 21-day at the maximum concentration (RR = 2.079, 95% CI: 1.396-3.097). Per IQR increase in NO3- had the significantly effect on hospital admissions for IHD (RR = 1.079, 95% CI: 1.028-1.132) and on hospital admissions for CMM (RR = 1.094, 95% CI: 1.039-1.152). Female patients hospitalized for CMM indicated heightened sensitivity to elevated NO3- levels (RR = 1.170, 95% CI: 1.077-1.271). The interaction between the high concentrations of PM2.5 and its constituents with low temperature, high relative humidity (RH), and low sunshine duration (SSD) significantly affected hospital admissions for CMM. Additionally, cold waves, defined as the minimum temperature of below P2.5 and sustained for 5 days (CW5), intensified the interaction with PM2.5 and its constituents.

Barriers to Implementing Effective Healthcare Practices for the Aging Population: Approaches to Identification and Management

The aging population presents a growing challenge to healthcare systems, necessitating urgent adaptations to meet the complex needs of older adults. Existing healthcare models often lack integration and fail to provide patient-centered care, leading to fragmented services, suboptimal outcomes, increased hospitalizations, and escalating healthcare costs. This narrative review aims to systematically identify and categorize the key barriers to effective healthcare implementation for the elderly, evaluate current healthcare models and their limitations, and explore evidence-based strategies to improve care delivery. A comprehensive literature search was conducted in PubMed, MEDLINE, Scopus, and Web of Science for studies published from 2000 to October 2024. The identified barriers span multiple domains, including patient-related challenges such as low health literacy and socioeconomic disparities, disease-specific factors like frailty and multimorbidity, provider-related constraints such as inadequate geriatric training, and system-wide deficiencies in primary care infrastructure and policy support. To address these challenges, this review explores emerging solutions, including risk stratification tools, integrated healthcare models, digital health innovations, and artificial intelligence-driven interventions. By providing a structured analysis of barriers and solutions, this review aims to inform policy and healthcare practices that enhance elderly care, reduce hospital readmissions, and optimize resource utilization in aging populations.

Analytical approaches to evaluate risk factors of multimorbidity: a systematic scoping review protocol

INTRODUCTION

Understanding causal risk factors that contribute to the development of multimorbidity is essential for designing and targeting effective preventive strategies. Despite a large body of research in this field, there has been little critical discussion about the appropriateness of the various analytical approaches used. This proposed scoping review aims to summarise and appraise the analytical approaches used in the published literature that evaluated risk factors of multimorbidity and to provide guidance for researchers conducting analyses in this field.

METHODS AND ANALYSIS

We will systematically search three electronic databases-Embase, Global Health and MEDLINE, as well as the reference lists of identified relevant review articles, from inception to September 2024. We will screen titles and abstracts using the artificial intelligence-aided software ASReview, followed by screening for eligible articles in full text and extracting data. We will then categorise the analytical approaches used across studies, provide a comprehensive overview of the methodology and discuss the potential strengths and limitations of each analytical approach.

ETHICS AND DISSEMINATION

We will undertake a secondary analysis of published literature; therefore, ethical approval is not required. The results will be disseminated through an open-access, peer-reviewed publication. This systematic scoping review will serve as a guide for researchers in selecting analytical approaches for aetiological multimorbidity research, thereby improving the quality and comparability of research in this field.

Multimorbidity patterns and function among adults in low- and middle-income countries: a scoping review

OBJECTIVES

To map the scope of available evidence on relationships between multimorbidity patterns and functioning among adults in low- and middle-income countries (LMICs), and describe methods used.

DESIGN

Scoping review guided by a five-step methodological framework and Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews reporting guidelines.

DATA SOURCES

PubMed/MEDLINE, Scopus, EBSCOhost (CINAHL) and Cochrane databases were searched from January 1976 to March 2023, plus reference lists of included studies.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

Peer-reviewed full-text articles or conference proceedings of any design, published in English or Afrikaans, involving adults (>18 years) with multimorbidity living in LMICs. Studies had to refer to associations between multimorbid patterns of co-occurrence and functioning. Multimorbidity was defined as the coexistence of ≥2 diseases, including any combination of non-communicable, infectious and mental health conditions.

DATA EXTRACTION AND SYNTHESIS

Data were extracted independently by two reviewers using a piloted form. Findings were synthesised according to methodological approaches, multimorbidity-pattern epidemiology, evidence gaps/limitations and recommendations for future research. The International Classification of Functioning, Disability and Health framework was used to classify functional problems.

RESULTS

Nine studies (total sample size: 62 003) were included, mainly from upper-middle-income Asian countries. Key methodological inconsistencies were identified in defining and operationalising multimorbidity, conditions included in determining patterns, statistical methods for pattern determination and functioning outcome measures. Five main multimorbidity pattern domains emerged: Cardio-Metabolic and Coronary Atherosclerotic, Musculoskeletal, Respiratory and Digestive/Visceral, Degenerative, and Mental Health-Related. Mobility limitations, instrumental activities of daily living, self-care and bowel/bladder problems were consistently linked to all pattern domains.

CONCLUSIONS

The limited and geographically skewed body of literature, along with methodological inconsistencies, hampers a comprehensive understanding of multimorbidity patterns and associations with functioning in LMICs. Future research should explore context-specific multimorbidity definitions, employ transparent methodologies, use standardised measures and incorporate diverse samples to inform tailored interventions and policies.

Postpartum depression in relation to chronic diseases and multimorbidity in women's mid-late life: a prospective cohort study of UK Biobank

BACKGROUND

Maternal short-term outcomes of postpartum depression (PPD) were widely examined, but little is known about its long-term association with multiple chronic diseases (multimorbidity) in women's later life. This study aims to assess the association of PPD with chronic diseases and multimorbidity in women's mid-late life.

METHODS

This prospective cohort study included female participants in UK Biobank who attended online follow-up assessment and reported their history of PPD. A total of 36 chronic diseases were assessed and multimorbidity was defined as the co-existence of two or more of these diseases. Participants were followed from the baseline recruitment to the onset of two or more chronic diseases, death, or the end of follow-up (2023). Logistic regression models, Cox proportional hazard models, quasi-Poisson mixed effects models, and linear mixed models were conducted to examine the association of PPD with chronic diseases and multimorbidity at baseline and during follow-up.

RESULTS

Among all 54,885 participants, 5106 (9.3%) participants experienced PPD, 13,928 (25.4%) participants had multimorbidity at baseline, and 14,135 (25.8%) participants developed two or more diseases during a median follow-up of 15 years. Women with a PPD history had higher odds of having multimorbidity at baseline (odds ratio = 1.35, 95% confidence interval [CI] = 1.27-1.44) and higher risk of developing multimorbidity during follow-up (hazard ratio = 1.13, 95% CI = 1.08-1.20). PPD was associated with increased number of chronic diseases, with the relatively new-onset number of diseases during follow-up being 8% higher for those with PPD (relative risk = 1.08, 95% CI = 1.05-1.12). Chronic diseases also accumulated at a faster annual rate for women with a history of PPD (b = 0.009, 95% CI = 0.007-0.011), compared to those without. We observed no interaction or mediation effects of physical activity, smoking, alcohol drinking, and dietary factors on the association between PPD and multimorbidity; however, women's body mass index at baseline contributed to the association, with the mediation proportion of 6.38% (2.56-10.20%).

CONCLUSIONS

PPD was associated with higher risks of chronic diseases and multimorbidity in women's mid-late life. This finding supports the importance of perinatal and postpartum mental health care, and its role in the prevention of chronic diseases and multimorbidity throughout women's life course.

Integrating general practitioners' and patients' perspectives in the development of a digital tool supporting primary care for older patients with multimorbidity: a focus group study

Introduction

The web application gp-multitool.de is based on the German clinical practice guideline "multimorbidity" and supports mutual prioritisation of treatments by GPs (general practitioners) and patients. The application facilitates sending hyperlinks to standardized assessments by email, which can be completed by patients on any suitable digital device. GPs can document clinical decisions. The tool also supports a structured medication review. Aims of this study were to consider needs and wants of the target groups in implementing the "multimorbidity" clinical practice guideline in a digital tool, and to examine themes of discussions in order to identify which aspects were considered most important for customising a digital tool.

Materials and methods

We conducted six focus groups with 32 GPs and six focus groups with 33 patients. Eight groups were conducted alongside the programming of the web application and four after finishing a prototype. GPs were recruited by mail and asked to invite up to six eligible patients from their practice to participate. Focus groups were based on semi-structured interview guides and discussed assessments, functionalities, usability and reliability of gp-multitool.de. Discussions were transcribed verbatim and analysed using content analysis.

Results

GPs wanted to avoid unnecessary and time-consuming functions and did not want to explore problems that they could not provide solutions for. For some assessments, GPs suggested simplifying scales or including residual categories. GPs and patients also addressed possible misunderstandings due to wording and discussed if some items might be too intimate or overtax patients intellectually. In most cases, participants confirmed usability, but they suggested changes in default settings and pointed out a few minor bugs that needed to be fixed. While some GPs considered data security an important topic, most patients were unconcerned with this issue and open to share their data.

Conclusion

Our study indicates that focus groups can be used to customize a digital tool according to the needs and wants of target groups and thus, improve content, functionality, usability, and reliability of digital tools. However, digital tools still need to be piloted and evaluated in everyday care. In our focus groups, study participants confirmed that gp-multitool.de can be a relevant approach for overcoming deficits in the information needed for mutual prioritisation of treatments by GPs and patients.

The co-occurrence of multimorbidity and polypharmacy among middle-aged and older adults in Canada: A cross-sectional study using the Canadian Longitudinal Study on Aging (CLSA) and the Canadian Primary Care Sentinel Surveillance Network (CPCSSN)

BACKGROUND

There is an increasing prevalence of multiple conditions (multimorbidity) and multiple medications (polypharmacy) across many populations. Previous literature has focused on the prevalence and impact of these health states separately, but there is a need to better understand their co-occurrence.

METHODS AND FINDINGS

This study reported on multimorbidity and polypharmacy among middle-aged and older adults in two national datasets: the Canadian Longitudinal Study on Aging (CLSA) and the Canadian Primary Care Sentinel Surveillance Network (CPCSSN). Using consistent methodology, we conducted a cross-sectional analysis of CLSA participants and CPCSSN patients aged 45 to 85 years as of 2015. When multimorbidity was defined as two or more conditions, the prevalence was 66.7% and 52.0% in the CLSA and CPCSSN cohorts, respectively. The prevalence of polypharmacy was 14.9% in the CLSA cohort and 22.6% in the CPCSSN cohort when defined as five or more medications. Using the same cut-points, the co-occurrence of multimorbidity and polypharmacy was similar between the two cohorts (CLSA: 14.3%; CPCSSN: 13.5%). Approximately 20% of older adults (65 to 85 years) were living with both multimorbidity and polypharmacy (CLSA: 21.4%; CPCSSN: 18.3%), as compared to almost 10% of middle-aged adults (45 to 64 years) living with this co-occurrence (CLSA: 9.2%; CPCSSN: 9.9%). Across both cohorts and age groups, females had consistently higher estimates of multimorbidity, polypharmacy and the co-occurrence of multimorbidity and polypharmacy.

CONCLUSIONS

This study found that multimorbidity and polypharmacy are not interchangeable in understanding population health needs. Approximately one in five older adults in the CLSA and CPCSSN cohorts were living with both multimorbidity and polypharmacy, double the proportion in the younger cohorts. This has implications for future research, as well as health policy and clinical practice, that aim to reduce the occurrence and impact of multimorbidity and unnecessary polypharmacy to enhance the well-being of aging populations.

Exploring Self-Management Behavior Profiles in Patients with Multimorbidity: A Sequential, Explanatory Mixed-Methods Study

Purpose

This study aims to identify self-management behavior profiles in multimorbid patients, and explore how workload, capacity, and their interactions influence these profiles.

Patients and Methods

A sequential explanatory mixed-methods design was employed. In the quantitative phase (August 2022 to May 2023), data were collected from 1,920 multimorbid patients across nine healthcare facilities in Zhejiang Province. Latent Profile Analysis (LPA) was used to identify distinct self-management behavior profiles. Multinomial logistic regression was then used to assess the influence of workload and capacity dimensions (independent variables in Model 1), as well as their interaction (independent variables in Model 2), on these profiles (dependent variables in two models). The qualitative phase (May to August 2023) included semi-structured interviews with 16 participants, and the Giorgi analysis method was used for data categorization and coding.

Results

Quantitative analysis revealed three self-management behavior profiles: Symptom-driven Profile (8.0%), Passive-engagement Profile (29.5%), and Active-cooperation Profile (62.5%). Compared to the Active-cooperation Profile, both the Symptom-driven and Passive-engagement Profiles were associated with a higher workload (OR > 1, P < 0.05) and lower capacity (OR < 1, P < 0.05). An interaction of the overall workload and capacity showed a synergistic effect in the Passive-engagement Profile (OR = 1.08, 95% CI = 1.03-1.13, P < 0.05). Qualitative analysis identified six workload themes, and related coping strategies of three self-management behavior profiles. The integrated results highlighted distinct characteristics: Symptom-driven Profile patients exhibited reactive behaviors with limited health awareness, Passive-engagement Profile patients reduced engagement once symptoms stabilized, while Active-cooperation Profile patients proactively managed their conditions.

Conclusion

Identifying three distinct self-management behavior profiles and their relationship with workload and capacity provides valuable insights into multimorbid patients' experiences, emphasizing the need for tailored interventions targeting workload and capacity to improve health outcomes.

Socioeconomic inequality in the multimorbidity trajectories of middle-aged and older adults in China: A prospective cohort study

OBJECTIVE

The prevalence of multimorbidity is socially patterned, but little is known about how socioeconomic inequality might affect the long-term progression of multimorbidity. This study aimed to identify multimorbidity trajectories and to examine their association with socioeconomic status (SES) among middle-aged and older Chinese adults.

METHODS

A total of 3837 middle-aged and older participants were included from the dynamic cohort of the China Health and Retirement Longitudinal Study, 2011-2018. Multimorbidity trajectories were assessed using the Chinese Multimorbidity-Weighted Index (CMWI), which covers 14 chronic conditions. Group-based trajectory modeling was used to identify multimorbidity developmental trajectories. Education, working status, and total household income were used to construct SES scores. The associations between SES and CMWI trajectories were estimated using multinomial logistic regression models adjusting for sociodemographic and lifestyle factors.

RESULTS

Four distinct CMWI trajectories were identified: 'no multimorbidity' (16.8 %), 'new-onset multimorbidity' (48.7 %), 'slowly increasing multimorbidity' (24.3 %), and 'rapidly increasing multimorbidity' (10.2 %). Lower SES was associated with higher odds of experiencing the 'rapidly increasing' trajectory (P trend < 0.01); for example, compared with the 'no multimorbidity' group, participants with low SES had a 96 % (OR, 1.96; 95 % CI, 1.29 to 2.98) increased odds of belonging to the 'rapidly increasing' group.

CONCLUSION

Socioeconomic inequalities were observed in the CMWI trajectories of multimorbidity in middle-aged and older Chinese adults. The findings suggest effective strategies for preventing and controlling multimorbidity should be made from a long-term perspective, especially for those of lower SES.

Reciprocal Relations of Social Isolation and Multimorbidity in Chinese Elderly

INTRODUCTION

This study aims to investigate the bidirectional associations between social isolation (SI) and multimorbidity among Chinese older adults.

METHODS

Data from six waves of the Chinese Longitudinal Healthy Longevity Survey spanning from 2002 to 2018 were analyzed. A General Cross-Lagged Model was employed in 2023 to investigate the temporal interrelationships between SI and multimorbidity among individuals aged 65 years and older.

RESULTS

In the short-term, significant bidirectional associations between SI and multimorbidity were found. Higher levels of SI at a given time point were associated with increased multimorbidity scores in the future, while greater levels of multimorbidity at a given time were associated with higher future SI scores. In the long-term, it is more likely that initial multimorbidity affect SI rather than initial SI affecting multimorbidity.

CONCLUSIONS

This study contributes to the understanding of the bidirectional associations between SI and multimorbidity among Chinese older adults, highlighting that initial multimorbidity was associated with future SI.

Association of multimorbidity with working life expectancy among adults aged 50 years and older: Findings from two prospective cohort studies

Background

Individual diseases are important risk factors for early exit from the labour force among older adults, but the contribution of multimorbidity to working life expectancy (WLE) is unclear.

Methods

We used data from two prospective cohort studies: Finnish Public Sector study (FPS) and Health and Social Support Study (HeSSup). Multimorbidity at baseline was ascertained from a combination of self-reported, physician-diagnosed chronic diseases, and nationwide cancer and medication reimbursement registers. WLE from age 50 up to 68 years was ascertained utilising linked data from a nationwide register of pensionable earnings. WLE was estimated utilising a multi-state models in R.

Results

Our findings were based on data from 56,079 women and 17,078 men aged ≥50 years. In FPS, women and men with two chronic diseases could expect to work about 9 months less and those with three or more chronic diseases could expect to work about a year less than those with no chronic disease. In HeSSup, women and men with three or more diseases had about 2-3 years shorter WLEs than those with no disease. In both studies participants with physical-mental multimorbidity had 3-12 months shorter WLEs and individuals with multimorbidity comprising two physical diseases had 8-10 months shorter WLEs than those with no chronic disease. The patterns were similar across the socioeconomic positions.

Conclusion

Women and men with multiple chronic diseases could expect to work ∼1 year less than those with no chronic disease. The differences in WLE can have important economic implications to individuals, health services and society.

The Cross-Sectional Association Between Multimorbidity and Sleep Quality and Duration Among the Elderly Community Dwellers in Northwest China

Background

Multimorbidity, defined as the coexistence of two or more chronic diseases, is highly prevalent among the elderly population and is associated with adverse outcomes. However, little is known about its relationship with sleep issues, particularly in this demographic. Therefore, this study aimed to investigate its association with sleep quality and duration among the elderly.

Methods

This cross-sectional study was conducted in Emin County, Xinjiang, China, which included a population aged 60 years and above. We employed the Pittsburgh Sleep Quality Index (PSQI) score to assess sleep quality and duration. Multimorbidity was determined through self-reports, physical examination, blood tests, and imaging. Logistic regression analyses were used to explore the association between multimorbidity and sleep patterns, adjusting for confounders.

Results

A total of 8205 elderly participants were included, of whom 66.8% suffered from multimorbidity. Participants with multimorbidity exhibited higher total PSQI scores [6 (3,9)], and a higher percentage of poor sleep quality (50.6%), compared to those without multimorbidity. Multimorbidity was significantly associated with the presence of poor sleep quality (OR = 1.27, 95% CI: 1.14-1.41, P < 0.001) before and after adjusting for confounders. The risk of having poor sleep quality significantly increased as the number of multimorbidities increased. The OR (95% CI) values were 1.16 (1.02,1.32) for two diseases, 1.54 (1.26,1.90) for ≥5 diseases. In the adjusted model for total participants, having four diseases (OR = 1.26, 95% CI: 1.05-1.51, p = 0.013) and five or more diseases (OR = 1.29, 95% CI: 1.03-1.61, p = 0.029) were associated with shorter sleep duration. Furthermore, those with five or more diseases associated with longer sleep duration (OR = 1.40, 95% CI: 1.00-1.95, p = 0.057).

Conclusion

There is a significant association between multimorbidity and poor sleep quality in older community dwellers, which may provide clues for disease prevention.

The Attitudes Toward Polypharmacy and Willingness to Deprescribe Among Patients with Multimorbidity in Rural Areas of Shandong Province in China: A Cross-Sectional Study

Purpose

Multimorbidity and polypharmacy have emerged as significant global issues, heightening the risks of potentially inappropriate medications (PIMs). This necessitates medication optimization through deprescribing. Understanding patients' decision-making preferences regarding medication cessation is crucial for mitigating medication-related risks. This study aims to capture the attitude of patients with multimorbidity towards deprescribing in rural China and to ascertain whether individual characteristics were linked to these attitudes.

Patient and Methods

A cross-sectional study employing the validated Patients' Attitudes Towards Deprescribing (PATD) questionnaire was performed in rural regions of Eastern China. The PATD Questionnaire was utilized to investigate patients' attitudes towards the concurrent use of multiple medications, with response elicited on a 5-point Likert scale. Utilizing multistage random sampling, a total of 560 participants with multimorbidity were randomly selected from two counties in Shandong Province. Descriptive statistics were reported on participant characteristics. Binary logistic regression analysis was conducted to identify the factors that influenced participants' willingness to discontinue or reduce their medication.

Results

The median age of patients was 69.5 years (SD=8.2 years), and 314 were female. Nearly one in four patients experienced polypharmacy, while 42.2% had two chronic diseases. More than half of the participants (55.2%) reported that they would be willing to stop one or more medications if their physicians agreed, and 52.9% of participants agreed to reduce the medications taken. Participants with two chronic conditions (OR=3.038, 95% CI=1.342-6.881), taking less than 10 tablets (OR=2.994, 95% CI=1.113-8.054), having their own source of healthcare expenditure (OR=0.639, 95% CI=0.432-0.945), and hospitalization in the prior year (OR=0.636, 95% CI=0.429-0.944) were significantly associated with patients' attitudes toward deprescribing.

Conclusion

Over half of patients with multimorbidity expressed a willingness to have one or more of their medicines deprescribed. Physicians can be trained in the integrated care of chronic diseases and encouraged to engage in discussions about deprescribing with patients having multimorbidity and polypharmacy during their routine practice.

How the development of chronic morbidity and multimorbidity depends on natural age of menopause: Results from nationally representative cross-sectional Indian study

Background

Multimorbidity development is linked with the age at menopause. Fewer studies are available to support the findings. This study was conducted to find, how multimorbidity is associated with the natural age of menopause.

Methodology

LASI-1, a longitudinal study, collected detailed information on the psychological, social, economic, and health aspects of aging in India. Wave-1 data collection was done in all 35 states and union territories in India. Baseline data was collected from year 2017-2019. As the current study was a secondary data analysis to find the association between multimorbidity and age of menopause, only eligible women's relevant data was analyzed.

Results

A total of 25,256 women were analyzed, 67.8% of participants had at least one comorbidity. The mean age was 58.5 ± 10.17 years. 57.04% and 13.45% women had optimal or suboptimal menopause, while 7.4%, 17.5%, and 4.4% had premature, early, and delayed menopause. A significant association was found for the presence of multimorbidity and premature (AOR 1.19 (1.07-1.32)), early menopause (AOR 1.18 (1.10-1.27)), and optimal age of menopause (AOR 0.83 (0.78-0.88)).

Conclusion

There is a high burden of multimorbidity and it is associated with the natural age of menopause. This study would be helpful for effective policymaking and a better primary healthcare approach to deal with the condition.

Adverse childhood experiences and multimorbidity among middle-aged and older adults: Evidence from China

BACKGROUND

Associations between adverse childhood experiences (ACEs) and multimorbidity among middle-aged and older Chinese individuals have not been well documented.

OBJECTIVE

We aimed to examine the associations of ACEs and different multimorbidity measures among Chinese middle-aged and older adults.

PARTICIPANTS AND SETTING

The study population included 6428 participants aged 45 years or older who were obtained from the China Health and Retirement Longitudinal Study (CHARLS).

METHODS

Multimorbidity was assessed by the number of self-reported physician diagnoses of 14 chronic diseases, the Chinese multimorbidity-weighted index (CMWI), multimorbidity trajectories and multimorbidity patterns. ACEs were measured retrospectively by whether the individuals having physical abuse, emotional neglect, household substance abuse, household mental illness, domestic violence, incarcerated household member, parental separation or divorce, unsafe neighborhood, bullying, parental death, sibling death, and parental disability or not, which were characterized by the binarized presence or absence of any ACE. We estimated the associations between ACEs and multimorbidity using a mixed-effects model. Latent growth curve modelling was used to investigate the trajectory of multimorbidity by ACEs. Both models Adjusted for sociodemographic and other health risk factors. Patterns of multimorbidity by ACEs were explored using hierarchical cluster analysis.

RESULTS

Of the 6428 individuals included (mean [SD] age, 56.67 [8.00] years; 6181 [45.29 %] were females), 81.16 % had experienced ACEs at baseline. ACEs were associated with an increased number of chronic diseases (β = 0.30; 95 % CI, 0.21 to 0.40) and the lower CMWI (β = -0.49; 95 % CI, -0.64 to -0.33). ACEs were associated with an increased number of chronic diseases at the baseline (intercept: 0.28, 95%CI: 0.20 to 0.36) and a more rapid increase in the number of chronic diseases over 7 years (intercept: 0.03, 95%CI: 0.01 to 0.05). The results of continuous variables (the number of ACEs) were consistent with those of binary variables (ACEs). ACEs were associated with lower scores at the baseline (intercept: -0.46, 95%CI: -0.60 to -0.33) but weren't related to a faster decrease (intercept: -0.04, 95%CI: -0.07 to 0.00). The number of ACEs was associated with the lower scores of CMWI at baseline and the faster the decrease in CMWI scores (intercept: -0.17, 95%CI: -0.21 to -0.14; slope: -0.03, 95%CI: -0.04 to -0.02). The above results varied among different types of ACEs. The binary multimorbidity pattern (arthritis and stomach/digestive disease) had the highest prevalence (15.50 %) in the participants with ACEs. There were differences in multimorbidity patterns between individuals exposed to ACE or not. The liver-kidney cluster more likely clustered with the arthritis-stomach cluster in individuals without ACE, but with the cancer-psych cluster in counterparts with ACEs.

CONCLUSIONS

There was an association between ACEs and multimorbidity with its trajectories and patterns after age 45. This study encourages a comprehensive life-course perspective to better understand and potentially prevent multimorbidity.

Musculoskeletal Multimorbidity Burden and Trajectory in Relation to Later-Life Holistic Well-Being Among Middle-Aged and Elderly Individuals: A Prospective Study

OBJECTIVES

Understanding the patterns and implications of coexisting musculoskeletal conditions is crucial for developing effective management strategies and improving care for older adults. This study aimed to examine the associations between musculoskeletal multimorbidity burden and trajectory and holistic well-being among middle-aged and older adults.

METHODS

This prospective study employed data from nine consecutive waves of the English Longitudinal Study of Aging (ELSA), spanning 2002-2018. We used latent class trajectory models (LCTM) to identify groups based on changes in musculoskeletal multimorbidity status. Subsequently, we employed linear mixed models to investigate the associations between musculoskeletal disease burden, trajectory groups, and seven dimensions of holistic well-being: Activities of Daily Living (ADLs), Instrumental Activities of Daily Living (IADLs), depression, memory, loneliness, social interactions, and life satisfaction.

RESULTS

In total, 5272 participants (mean age: 71.9 years; SD: 8.9) were included in the final analysis. Four distinct trajectories were identified: a low-burden group (48.37%), an emerging group (14.76%), a moderate-burden group (26.00%), and a persistent burden group (10.87%). After adjustment, the findings demonstrate that the musculoskeletal disorder burden significantly impacts ADLs, depression, memory, social interactions, and life satisfaction in middle-aged and older adults, with minor effects on IADLs and loneliness. Moreover, with the escalation of the burden, its impact significantly intensifies (p for trend is < 0.001). Compared with the low-burden group, participants in both the moderate and persistent burden groups exhibited significantly lower capabilities in ADLs, poorer memory, increased social interactions, and lower life satisfaction. The emerging group displayed a similar trend, though without statistically significant results.

CONCLUSIONS

Our study suggests that the extent and persistence of musculoskeletal disease burden can significantly affect holistic well-being among middle-aged and older individuals.

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 reproductive lifespan and multimorbidity among Chinese postmenopausal women

OBJECTIVE

Although menopause is considered a risk factor for multimorbidity, few studies have explored the association between reproductive lifespan and multimorbidity. This study aimed to explore the association between reproductive lifespan and multimorbidity in postmenopausal Chinese women.

METHODS

This cross-sectional study selected postmenopausal women as study participants. The reproductive lifespan refers to the interval between menarche and menopause. Multimorbidity refers to having two or more self-reported chronic diseases. We used a logistic regression model to explore potential associations based on the adjustment of a set of covariates.

RESULTS

In total, 1,310 postmenopausal women with an average reproductive lifespan of 34 years were included in this study. The prevalence of multimorbidity was 22.2% (291/1,310) in postmenopausal women. Our findings showed that compared with postmenopausal women with the Q1 of reproductive lifespan (≤32 reproductive years), those with Q3 (35-37 reproductive years) and Q4 (≥38 reproductive years) were less likely to have multimorbidity (OR Q3 = 0.529, 95% CI Q3 = 0.347-0.805, OR Q4 = 0.510, 95% CI Q4 = 0.308-0.842), whereas those with Q2 (33-34 reproductive years) were not (OR = 0.700, 95% CI = 0.446-1.098). This study also revealed a linear trend in the association between the reproductive lifespan and multimorbidity; that is, the longer the reproductive lifespan, the lower the risk of multimorbidity.

CONCLUSIONS

In postmenopausal Chinese women, a longer reproductive lifespan was associated with a lower prevalence of multimorbidity. This study suggests that for the prevention and intervention of multimorbidity in postmenopausal women, healthcare professionals should screen and assess reproductive factors to identify high-risk individuals.

Integrating VAI-Assisted Quantified CXRs and Multimodal Data to Assess the Risk of Mortality

To address the unmet need for a widely available examination for mortality prediction, this study developed a foundation visual artificial intelligence (VAI) to enhance mortality risk stratification using chest X-rays (CXRs). The VAI employed deep learning to extract CXR features and a Cox proportional hazard model to generate a hazard score ("CXR-risk"). We retrospectively collected CXRs from patients visited outpatient department and physical examination center. Subsequently, we reviewed mortality and morbidity outcomes from electronic medical records. The dataset consisted of 41,945, 10,492, 31,707, and 4441 patients in the training, validation, internal test, and external test sets, respectively. During the median follow-up of 3.2 (IQR, 1.2-6.1) years of both internal and external test sets, the "CXR-risk" demonstrated C-indexes of 0.859 (95% confidence interval (CI), 0.851-0.867) and 0.870 (95% CI, 0.844-0.896), respectively. Patients with high "CXR-risk," above 85th percentile, had a significantly higher risk of mortality than those with low risk, below 50th percentile. The addition of clinical and laboratory data and radiographic report further improved the predictive accuracy, resulting in C-indexes of 0.888 and 0.900. The VAI can provide accurate predictions of mortality and morbidity outcomes using just a single CXR, and it can complement other risk prediction indicators to assist physicians in assessing patient risk more effectively.

Multimorbidity among the Indigenous population: A systematic review and meta-analysis

BACKGROUND

Multimorbidity, the concurrent presence of multiple chronic health conditions in an individual, represents a mounting public health challenge. Chronic illnesses are prevalent in the Indigenous populations, which contributes to multimorbidity. However, the epidemiology of multimorbidity in this population is not well studied. This review aimed to elucidate the extent, determinants, consequences, and prevention of multimorbidity within Indigenous populations globally, contrasting findings with non-Indigenous populations.

METHODS

Adhering to the PRISMA guidelines, this systematic review assimilated peer-reviewed articles and grey literature, focusing on the prevalence, determinants, implications, and preventive strategies of multimorbidity in global Indigenous populations. Emphasis was given to original, English-language, full-text articles, excluding editorials, and conference abstracts.

FINDINGS

Of the 444 articles identified, 13 met the inclusion criteria. Five studies are from Australia, and the rest are from the USA, Canada, New Zealand, and India. The study indicated a higher multimorbidity prevalence among Indigenous populations, with consistent disparities observed across various age groups. Particularly, Indigenous individuals exhibited a 2-times higher likelihood of multimorbidity compared to non-Indigenous populations. Noteworthy findings underscored the elevated severity of certain comorbid conditions, especially strokes, within Indigenous groups, with further revelations highlighting their significant pairing with conditions such as heart diseases and diabetes.

INTERPRETATION

The findings affirm the elevated burden of multimorbidity among Indigenous populations. Prevalence and risk of developing multimorbidity are significantly higher in this population compared to their non-Indigenous counterparts. Future research should prioritize harmonized research methodologies, fostering insights into the multimorbidity landscape, and promoting strategies to address health disparities in Indigenous populations.

Registered nurse case managers' work experiences with a person-centered collaborative healthcare model: an interview study

BACKGROUND

Multimorbidity is increasingly acknowledged as a significant health concern, particularly among older individuals. It is associated with a decline in quality of life and psychosocial well-being as well as an increased risk of being referred to multiple healthcare providers, including more frequent admissions to emergency departments. Person-centered care interventions tailored to individuals with multimorbidity have shown promising results in improving patient outcomes. Research is needed to explore how work practices within integrated care models are experienced from Registered Nurse Case Managers' (RNCMs) perspective to identify areas of improvement. Therefore, the aim of this study was to describe RNCMs' work experience with a person-centered collaborative healthcare model (PCCHCM).

METHODS

This study used an inductive design. The data were collected through individual interviews with 11 RNCMs and analyzed using qualitative content analysis.

RESULTS

Data analysis resulted in four generic categories: 'Being a detective, 'Being a mediator', 'Being a partner', and 'Being a facilitator of development' which formed the basis of the main category 'Tailoring healthcare, and social services to safeguard the patient's best.' The findings showed that RNCMs strive to investigate, identify, and assess older persons' needs for coordinated care. They worked closely with patients and their relatives to engage them in informed decision-making and to implement those decisions in a personalized agreement that served as the foundation for the care and social services provided. Additionally, the RNCMs acted as facilitators of the development of the PCCHCM, improving collaboration with other healthcare professionals and enhancing the possibility of securing the best care for the patient.

CONCLUSIONS

The results of this study demonstrated that RNCMs tailor healthcare and social services to provide care in various situations, adhering to person-centered care principles and continuity of care. The findings underline the importance of implementing integrated care models that consider the unique characteristics of each care context and adapt different case managers' roles based on the patient's individual needs as well as on the specific needs of the local setting. More research is needed from the patients' and their relatives' perspectives to deepen the understanding of the PCCHCM concerning its ability to provide involvement, security, and coordination of care.

Key needs, quality performance indicators and outcomes for patients with atrial fibrillation and multimorbidity: The AFFIRMO study

BACKGROUND

Patients with atrial fibrillation (AF) often have concomitant long-term conditions that negatively impact their quality of life and the clinical management they receive. The AFFIRMO study aimed to identify the needs, quality performance indicators (QPIs), and outcomes relevant to patients, caregivers and healthcare professionals (HCPs) to improve the care of patients with AF.

METHODS

An on-line survey to collect the key needs, QPIs, and outcomes relevant to patients with AF, their caregivers and HCPs, was distributed between May 2022 and January 2023 in five countries (UK, Italy, Denmark, Romania and Spain). Results from the on-line survey were discussed in a three-round Delphi process with international representatives of patients with AF, caregivers, and HCPs to determine the key needs, QPIs and outcomes for the management of patients with AF and multimorbidity.

RESULTS

659 patients (47.2% males, mean (SD) age 70.9 (10.2) years), 201 caregivers (26.9% males, mean (SD) age: 58.3 (SD 15.2) years), and 445 HCPs (57.8% males, mean (SD) age 47.4 (10.6) years) participated in the survey. An initial list of 27 needs, 9 QPIs, and 17 outcomes were identified. Eight patients, two caregivers, and 11 HCPs participated in the Delphi process. Nineteen (70%) needs, 8 (89%) QPIs, and 13 (76%) outcomes reached "consensus in", and were included in the final list.

CONCLUSIONS

The final key needs, QPIs and outcomes obtained from the Delphi process will inform the AFFIRMO clinical trial, which aims to test the iABC app which incorporates an empowerment toolbox for patients and their caregivers, providing information to improve patient engagement and empowerment to help improve the clinical and self-management of patients with AF in the context of multimorbidity.

[Multimorbidity and utilization of health services in the city of São Paulo, Brazil: prevalence and associated factors]

The scope of this paper was to estimate the prevalence of multimorbidity in the city of São Paulo and to verify the factors associated with the utilization of the health services. It involved a population based cross-sectional study based on data from the Health Survey in the city of São Paulo, in which descriptive analysis was conducted, and logistic regression models were developed using multimorbidity and sociodemographic independent variables, living conditions and use of health services as the outcome. A total of 3,184 individuals aged 20 years or older participated, with a mean age of 43.8 years. The prevalence of multimorbidity was 50.7% among women, 62.5% among those who reported some health problem and 55.1% among those who had recourse to health services in the last 2 weeks. A higher prevalence was identified among those who used the health service due to a mental health problem (66.1%), and in those who reported higher health expenditures in the preceding month (55.4%). Multimorbidity was more frequently associated with aging, in the population with a higher economic status, with worse self-rated health, who frequented health services for 6 months or less, who reported a health problem, or who had a health plan and opted for polypharmacy.

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.

Multimorbidity patterns and associated factors in a megacity: a cross-sectional study

OBJECTIVE

To identify empirical patterns of multimorbidity and quantify their associations with socioeconomic, behavioral characteristics, and health outcomes in the megacity of São Paulo.

METHODS

This was a cross-sectional study conducted through household interviews with residents aged 20 years or older in urban areas (n = 3,184). Latent class analysis was used to identify patterns among the co-existence of 22 health conditions. Age-adjusted prevalence ratios were estimated using Poisson regression.

RESULTS

The analysis of latent classes showed 4 patterns of multimorbidity, whereas 58.6% of individuals were classified in the low disease probability group, followed by participants presenting cardiovascular conditions (15.9%), respiratory conditions (12.8%), and rheumatic, musculoskeletal, and emotional conditions (12.8%). Older individuals, with lower schooling and lower household income, presented higher multimorbidity prevalence in cardiovascular, respiratory, rheumatic, musculoskeletal, and emotional conditions patterns compared with the low disease probability pattern.

CONCLUSION

The results showed four distinct patterns of multimorbidity in the megacity population, and these patterns are clinically recognizable and theoretically plausible. The identification of trends between patterns would make it feasible to estimate the magnitude of the challenge for the organization of health care policies.

Choices of measures of association affect the visualisation and composition of the multimorbidity networks

BACKGROUND

Network analysis, commonly used to describe the patterns of multimorbidity, uses the strength of association between conditions as weight to classify conditions into communities and calculate centrality statistics. Our aim was to examine the robustness of the results to the choice of weight.

METHODS

Data used on 27 chronic conditions listed on Australian death certificates for women aged 85+. Five statistics were calculated to measure the association between 351 possible pairs: odds ratio (OR), lift, phi correlation, Salton cosine index (SCI), and normalised-joint frequency of pairs (NF). Network analysis was performed on the 10% of pairs with the highest weight according to each definition, the 'top pairs'.

RESULTS

Out of 56 'top pairs' identified, 13 ones were consistent across all statistics. In networks of OR and lift, three of the conditions which did not join communities were among the top five most prevalent conditions. Networks based on phi and NF had one or two conditions not part of any community. For the SCI statistics, all three conditions which did not join communities had prevalence below 3%. Low prevalence conditions were more likely to have high degree in networks of OR and lift but not SCI.

CONCLUSION

Use of different statistics to estimate weights leads to different networks. For exploratory purposes, one may apply alternative weights to identify a large list of pairs for further assessment in independent studies. However, when the aim is to visualise the data in a robust and parsimonious network, only pairs which are selected by multiple statistics should be visualised.

The impact of discharge letter content on unplanned hospital readmissions within 30 and 90 days in older adults with chronic illness - a mixed methods study

BACKGROUND

Care transitions are high-risk processes, especially for people with complex or chronic illness. Discharge letters are an opportunity to provide written information to improve patients' self-management after discharge. The aim of this study is to determine the impact of discharge letter content on unplanned hospital readmissions and self-rated quality of care transitions among patients 60 years of age or older with chronic illness.

METHODS

The study had a convergent mixed methods design. Patients with chronic obstructive pulmonary disease or congestive heart failure were recruited from two hospitals in Region Stockholm if they were living at home and Swedish-speaking. Patients with dementia or cognitive impairment, or a "do not resuscitate" statement in their medical record were excluded. Discharge letters from 136 patients recruited to a randomised controlled trial were coded using an assessment matrix and deductive content analysis. The assessment matrix was based on a literature review performed to identify key elements in discharge letters that facilitate a safe care transition to home. The coded key elements were transformed into a quantitative variable of "SAFE-D score". Bivariate correlations between SAFE-D score and quality of care transition as well as unplanned readmissions within 30 and 90 days were calculated. Lastly, a multivariable Cox proportional hazards model was used to investigate associations between SAFE-D score and time to readmission.

RESULTS

All discharge letters contained at least five of eleven key elements. In less than two per cent of the discharge letters, all eleven key elements were present. Neither SAFE-D score, nor single key elements correlated with 30-day or 90-day readmission rate. SAFE-D score was not associated with time to readmission when adjusted for a range of patient characteristics and self-rated quality of care transitions.

CONCLUSIONS

While written summaries play a role, they may not be sufficient on their own to ensure safe care transitions and effective self-care management post-discharge.

TRIAL REGISTRATION

Clinical Trials. giv, NCT02823795, 01/09/2016.

Adiposity indicators exhibit depot- and sex-specific associations with multimorbidity onset: A cohort study of the UK Biobank

AIM

This study investigated the depot- and sex-specific associations of adiposity indicators with incident multimorbidity and comorbidity pairs.

MATERIALS AND METHODS

We selected 382 678 adults without multimorbidity (≥2 chronic diseases) at baseline from the UK Biobank. General obesity, abdominal obesity and body fat percentage indices were measured.

RESULTS

Cox proportional hazard regression analyses of general obesity indices revealed that for every one-unit increase in body mass index, the risk of incident multimorbidity increased by 5.2% (95% confidence interval 5.0%-5.4%). A dose-response relationship was observed between general obesity degrees and incident multimorbidity. The analysis of abdominal obesity indices showed that for every 0.1 increment in waist-to-height ratio and waist-to-hip ratio, the risk of incident multimorbidity increased by 42.0% (37.9%-46.2%) and 27.9% (25.7%-30.0%), respectively. Central obesity, as defined by waist circumference, contributed to a 23.2% increased risk of incident multimorbidity. Hip circumference and hip-to-height ratio had protective effects on multimorbidity onset. Consistent findings were observed for males and females. Body fat percentage elevated 3% (0.2%-5.9%) and 5.3% (1.1%-9.7%) risks of incident multimorbidity in all adults and females, respectively. Arm fat percentages elevated 5.3% (0.8%-9.9%) and 19.4% (11.0%-28.5%) risks of incident multimorbidity in all adults and males, respectively. The general obesity indices, waist circumference, waist-to-height ratio, waist-to-hip ratio and central obesity increased the onset of comorbidity pairs, whereas hip circumference and hip-to-height ratio decreased the onset of comorbidity pairs. These adiposity indicators mainly affect diabetes mellitus-related comorbidity onset in males and hypertensive-related comorbidity onset in females.

CONCLUSIONS

Adiposity indicators are predictors of multimorbidity and comorbidity pairs and represent a promising approach for intervention.

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.

Prevalence of multimorbidity in people with and without severe mental illness: a systematic review and meta-analysis

BACKGROUND

People with severe mental illness, such as schizophrenia-spectrum disorder and bipolar disorder, face poorer health outcomes from multiple chronic illnesses. Physical multimorbidity, the coexistence of two or more chronic physical conditions, and psychiatric multimorbidity, the coexistence of three or more psychiatric disorders, are both emerging concepts useful in conceptualising disease burden. However, the prevalence of physical and psychiatric multimorbidity in this cohort is unknown. This study aimed to estimate the absolute prevalence of both physical and psychiatric multimorbidity in people with severe mental illness, and also compare the odds of physical multimorbidity prevalence against people without severe mental illness.

METHODS

We searched CINAHL, EMBASE, PubMed, and PsycINFO from inception until Feb 15, 2024, for observational studies that measured multimorbidity prevalence. To be included, studies had to have an observational study design, be conducted in an adult population (mean age ≥18 years) diagnosed with either schizophrenia-spectrum disorder or bipolar disorder, and include a measurement of occurrence of either physical multimorbidity (≥2 physical health conditions) or psychiatric multimorbidity (≥3 psychiatric conditions total, including the severe mental illness). From control studies, a random-effects meta-analysis compared odds of physical multimorbidity between people with and without severe mental illness. Absolute prevalence of physical and psychiatric multimorbidity in people with severe mental illness was also calculated. Sensitivity and meta-regression analyses tested an array of demographic, diagnostic, and methodological variables.

FINDINGS

From 11 144 citations we included 82 observational studies featuring 1 623 773 individuals with severe mental illness (specifically schizophrenia-spectrum disorder or bipolar disorder), of which 21 studies featured 13 235 882 control individuals without severe mental illness (descriptive data for the entire pooled cohorts were not available for numbers of males and females, age, and ethnicity). This study did not feature involvement of people with lived experience. The odds ratio (OR) of physical multimorbidity between people with and without severe mental illness was 2·40 (95% CI 1·57-3·65, k=11, p=0·0009). This ratio was higher in younger severe mental illness populations (mean age ≤40 years, OR 3·99, 95% CI 1·43-11·10) compared with older populations (mean age >40 years, OR 1·55, 95% CI 0·96-2·51; subgroup differences p=0·0013). For absolute prevalence, 25% of those with severe mental illness have physical multimorbidity (95% CI 0·19-0·32, k=29) and 14% have psychiatric multimorbidity (95% CI 0·08-0·23, k=21).

INTERPRETATION

This is the first meta-analysis to estimate physical alongside psychiatric multimorbidity prevalence, showing that these are common in people with schizophrenia-spectrum disorder and bipolar disorder. The greater burden of physical multimorbidity in people with severe mental illness compared with those without is higher for younger cohorts, reflecting a need for earlier intervention. Our findings speak to the utility of multimorbidity for characterising the disease burden associated with severe mental illness, and the importance of facilitating integrated physical and mental health care.

FUNDING

None.

The diabetes mellitus multimorbidity network in hospitalized patients over 50 years of age in China: data mining of medical records

OBJECTIVE

Many diabetes mellitus (DM) patients suffer from multimorbidity. Understanding the DM multimorbidity network should be given priority. The purpose of this study is characterize the DM multimorbidity network in people over 50 years.

METHODS

Data on 75 non-communicable diseases (NCDs) were extracted from electronic medical records of 309,843 hospitalized patients older than 50 years who had at least one NCD. The association rules analysis was used as a novel classification method and combined with the Chi-square tests to identify associations between NCDs and DM.

RESULT

A total of 12 NCDs were closely related to DM, {cholelithiasis, DM} was an unexpected combination. {dyslipidemia, DM} and {gout, DM} had the largest lift in the male and female groups, respectively. The negative related group included 7 NCDs. There were 9 NCDs included in the strong association rules. Most combinations were different by age and sex. In males, the strongest rule was {peripheral vascular disease (PVD), dyslipidemia, DM}, while {hypertension, dyslipidemia, chronic liver disease (CLD), DM} was the strongest in females. In patients younger than 70 years, hypertension, CLD, and dyslipidemia were the most dominant NCDs in the DM multimorbidity network. In patients 70 years or older, chronic kidney disease (CKD), CVD, CHD, and heart disease (HD) frequently co-occurred with DM.

CONCLUSION

Future primary healthcare policies for DM should be formulated based on age and sex. In patients younger than 70 years, more attention to hypertension, CLD, and dyslipidemia is required, while attention to CKD, CVD, CHD and HD is needed in patients older than 70 years.

Mobile Health Apps, Family Caregivers, and Care Planning: Scoping Review

BACKGROUND

People living with multiple chronic conditions (MCCs) face substantial challenges in planning and coordinating increasingly complex care. Family caregivers provide important assistance for people with MCCs but lack sufficient support. Caregiver apps have the potential to help by enhancing care coordination and planning among the health care team, including patients, caregivers, and clinicians.

OBJECTIVE

We aim to conduct a scoping review to assess the evidence on the development and use of caregiver apps that support care planning and coordination, as well as to identify key factors (ie, needs, barriers, and facilitators) related to their use and desired caregiver app functionalities.

METHODS

Papers intersecting 2 major domains, mobile health (mHealth) apps and caregivers, that were in English and published from 2015 to 2021 were included in the initial search from 6 databases and gray literature and ancestry searches. As per JBI (Joanna Briggs Institute) Scoping Review guidelines and PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews), 2 authors independently screened full texts with disagreements resolved by a third author. Working in pairs, the authors extracted data using a pilot-tested JBI extraction table and compared results for consensus.

RESULTS

We identified 34 papers representing 25 individual studies, including 18 (53%) pilot and feasibility studies, 13 (38%) qualitative studies, and 2 experimental or quasi-experimental studies. None of the identified studies assessed an intervention of a caregiver app for care planning and coordination for people with MCCs. We identified important caregiver needs in terms of information, support, and care coordination related to both caregiving and self-care. We compiled desired functionalities and features enabling apps to meet the care planning and care coordination needs of caregivers, in particular, the integration of caregiver roles into the electronic health record.

CONCLUSIONS

Caregiver needs identified through this study can inform developers and researchers in the design and implementation of mHealth apps that integrate with the electronic health record to link caregivers, patients, and clinicians to support coordinated care for people with MCCs. In addition, this study highlights the need for more rigorous research on the use of mHealth apps to support caregivers in care planning and coordination.

Genetic effects and causal association analyses of 14 common conditions/diseases in multimorbidity patterns

BACKGROUND

Multimorbidity has become an important health challenge in the aging population. Accumulated evidence has shown that multimorbidity has complex association patterns, but the further mechanisms underlying the association patterns are largely unknown.

METHODS

Summary statistics of 14 conditions/diseases were available from the genome-wide association study (GWAS). Linkage disequilibrium score regression analysis (LDSC) was applied to estimate the genetic correlations. Pleiotropic SNPs between two genetically correlated traits were detected using pleiotropic analysis under the composite null hypothesis (PLACO). PLACO-identified SNPs were mapped to genes by Functional Mapping and Annotation of Genome-Wide Association Studies (FUMA), and gene set enrichment analysis and tissue differential expression were performed for the pleiotropic genes. Two-sample Mendelian randomization analyses assessed the bidirectional causality between conditions/diseases.

RESULTS

LDSC analyses revealed the genetic correlations for 20 pairs based on different two-disease combinations of 14 conditions/diseases, and genetic correlations for 10 pairs were significant after Bonferroni adjustment (P<0.05/91 = 5.49E-04). Significant pleiotropic SNPs were detected for 11 pairs of correlated conditions/diseases. The corresponding pleiotropic genes were differentially expressed in the brain, nerves, heart, and blood vessels and enriched in gluconeogenesis and drug metabolism, biotransformation, and neurons. Comprehensive causal analyses showed strong causality between hypertension, stroke, and high cholesterol, which drive the development of multiple diseases.

CONCLUSIONS

This study highlighted the complex mechanisms underlying the association patterns that include the shared genetic components and causal effects among the 14 conditions/diseases. These findings have important implications for guiding the early diagnosis, management, and treatment of comorbidities.

Complex multimorbidity in hemodialysis patients: Study in a metropolitan region in Brazil

The objective of this article was to analyze the factors associated with complex multimorbidity (CMM) among hemodialysis patients in a metropolitan region in southeastern Brazil. To this end, a cross-sectional epidemiological survey was carried out with 1,024 individuals in the year 2019. CMM data were collected through the application of a questionnaire to hemodialysis patients. The binary logistic regression model was used to estimate odds ratios (OR) and 95% confidence intervals (95%CI) between independent variables and CMM. The prevalence of CMM was 81% and the results indicated that: living in cities with a low rate of general mortality (OR = 0.395, 95%CI = 0.179-0.870), being aged between 18 and 29 (OR = 0.402, 95%CI = 0.196-0.825), having an elementary education (OR = 0.536, 95%CI = 0.290-0.966) and assessing health as good/very good (OR = 0.446, 95%CI = 0.301-0.661) are factors that reduced the chances of having CMM, whereas a longer period of hemodialysis (OR = 1.779 and 95%CI = 1.057-2.997) increased the chances of CMM. The findings show that characteristics of the social and individual context are associated with CMM in hemodialysis patients, signaling the need for public health policies that include monitoring the complex multimorbidity condition among individuals undergoing hemodialysis treatment.

The effect of multimorbidity patterns on physical and cognitive function in diabetes patients: a longitudinal cohort of middle-aged and older adults in China

Background

The prevalence of diabetes has increased rapidly, and comorbid chronic conditions are common among diabetes patients. However, little is known about the pattern of multimorbidity in diabetes patients and the effect on physical and cognitive function. This study aimed to assess the disease clusters and patterns of multimorbidity in diabetes patients using a novel latent class analysis (LCA) approach in middle-aged and older adults and explore the association between different clusters of multimorbidity in diabetes and the effect on physical and cognitive function.

Methods

This national observational study included 1,985 diabetes patients from the four waves of the China Health and Retirement Longitudinal Study (CHARLS) in 2011 to 2018. Thirteen chronic diseases were used in latent class analysis to identify the patterns of multimorbidity in diabetes, which span the cardiovascular, physical, psychological, and metabolic systems. Cognitive function is assessed via a structured questionnaire in three domains: memory, executive function, and orientation. We combined activities of daily living (ADL) with instrumental activities of daily living (IADL) to measure physical function. Linear mixed models and negative binomial regression models were used to analyze the association between patterns of multimorbidity in diabetes and the effect on cognitive function and disability, respectively.

Results

A sample of 1,985 diabetic patients was identified, of which 1,889 (95.2%) had multimorbidity; their average age was 60.6 years (standard deviation (SD) = 9.5), and 53.1% were women. Three clusters were identified: "cardio-metabolic" (n = 972, 51.5%), "mental-dyslipidemia-arthritis" (n = 584, 30.9%), and "multisystem morbidity" (n = 333, 17.6%). Compared with diabetes alone, the "multisystem morbidity" class had an increased association with global cognitive decline. All patterns of multimorbidity were associated with an increased risk of memory decline and disability; however, the "multisystem morbidity" group also had the strongest association and presented a higher ADL-IADL disability (ratio = 4.22, 95% CI = 2.52, 7.08) and decline in memory Z scores (β = -0.322, 95% CI = -0.550, -0.095, p = 0.0058).

Conclusion

Significant longitudinal associations between different patterns of multimorbidity in diabetes patients and memory decline and disability were observed in this study. Future studies are needed to understand the underlying mechanisms and common risk factors for multimorbidity in diabetes patients and to propose treatments that are more effective.

Clinical phenotypes of comorbidities in end-stage knee osteoarthritis: a cluster analysis

OBJECTIVES

Comorbidities, as components of these heterogeneous features, often coexist with knee osteoarthritis, and are particularly prevalent in end-stage knee osteoarthritis. Here, we attempted to identify the different clinical phenotypes of comorbidities in patients with end-stage knee osteoarthritis by cluster analysis.

METHODS

A total of 421 inpatients diagnosed with end-stage knee osteoarthritis who underwent inpatient surgery were included in this cross-sectional study. 23 demographic, comorbidity, inflammatory immune and evaluation scale variables were collected. Systematic clustering after factor analysis and separate two-step cluster analysis were performed for individual comorbidity variables and all variables, respectively, to objectively identify the different clinical phenotypes of the study patients.

RESULTS

Four clusters were finally identified. Cluster 1 had the largest proportion of obese patients (93.8%) and hypertension was common (71.2%). Almost all patients in cluster 2 were depressed (95.8%) and anxiety disorders (94.7%). Cluster 3 combined patients with isolated end-stage knee osteoarthritis and a few comorbidities. Cluster 4 had the highest proportion of patients with rheumatoid arthritis (58.8%).

CONCLUSIONS

Patients with end-stage knee osteoarthritis may be classified into four different clinical phenotypes: "isolated end-stage knee osteoarthritis"; "obesity + hypertension"; "depression + anxiety"; and "rheumatoid arthritis", which may help guide individualized patient care and treatment strategies.

Patterns and Predictors of HIV Comorbidity among Adolescents and Young Adults in South Africa

Adolescents and young adults (AYA) are identified as a high-risk group for HIV acquisition. However, health services are generally not sensitive to the needs of this priority population. In addition, multimorbidity (having more than one disease in an individual) is not well studied among AYA, as it is typically associated with older individuals. This paper reports on commonly co-occurring disease conditions and disease patterns in AYA, aged 15-24 years, who took part in the 2016 South African Demographic and Health Survey. Chi-squared tests and logistic regression were used to examine the weighted prevalence of disease among those with/without HIV, and the risk factors associated with HIV. Latent class analysis (LCA) was conducted to identify common co-occurring diseases. Of the 1787 individuals included in our analysis, the weighted prevalence of HIV was 8.7%. Hypertension (30.5%), anaemia (35.8%) and diabetes (2.0%) were more prevalent among those with HIV. HIV and anaemia, hypertension and anaemia, and HIV and hypertension comprise the largest disease burden of co-occurring diseases. Co-morbidity was high among those with HIV, emphasizing the need for integrated care of HIV and non-communicable diseases.

The Impact of Multimorbidity Patterns on Changes in Physical Activity and Physical Capacity Among Older Adults Participating in a Year-Long Exercise Intervention

This study investigated the impact of multimorbidity patterns on physical activity and capacity outcomes over the course of a year-long exercise intervention, and on physical activity 1 year later. Participants were 314 physically inactive community-dwelling men and women aged 70-85 years, with no contraindications for exercise at baseline. Physical activity was self-reported. Physical capacity measurements included five-time chair-stand time, 6-minute walking distance, and maximal isometric knee-extension strength. The intervention included supervised and home-based strength, balance, and walking exercises. Multimorbidity patterns comprised physician-diagnosed chronic disease conditions as a predictor cluster and body mass index as a measure of obesity. Multimorbidity patterns explained 0%-12% of baseline variance and 0%-3% of the change in outcomes. The magnitude and direction of the impact of unique conditions varied by outcome, time point, and sex. Multimorbid older adults with no contraindications for exercise may benefit from multimodal physical training.

Prevalence of multimorbidity and polypharmacy among adults and older adults: a systematic review

Multimorbidity (multiple conditions) and polypharmacy (multiple medications) are increasingly common, yet there is a need to better understand the prevalence of co-occurrence. In this systematic review, we examined the prevalence of multimorbidity and polypharmacy among adults (≥18 years) and older adults (≥65 years) in clinical and community settings. Six electronic databases were searched, and 87 studies were retained after two levels of screening. Most studies focused on adults 65 years and older and were done in population-based community settings. Although the operational definitions of multimorbidity and polypharmacy varied across studies, consistent cut-points (two or more conditions and five or more medications) were used across most studies. In older adult samples, the prevalence of multimorbidity ranged from 4·8% to 93·1%, while the prevalence of polypharmacy ranged from 2·6% to 86·6%. High heterogeneity between studies indicates the need for more consistent reporting of specific lists of conditions and medications used in operational definitions.

The Effect of Coordinating the Outpatient Treatment across Medical Specialities for Patients With Multimorbidity

Introduction

Patients with multimorbidity attend multiple outpatient clinics. We assessed the effects on hospital use of scheduling several outpatient appointments to same-day visits in a multidisciplinary outpatient pathway (MOP).

Methods

This study used a quasi-experimental design. Eligible patients had multimorbidity, were aged ≥18 years and attended ≥2 outpatient clinics in five different specialties. Patients were identified through forthcoming appointments from August 2018 to March 2020 and divided into intervention group (alignment of appointments) and comparison group (no alignment). We used patient questionnaires and paired analyses to study care integration and treatment burden. Using negative binomial regression, we estimated healthcare utilisation as incidence rates ratios (IRRs) at one year before and one year after baseline for both groups and compared IRR ratios (IRRRs).

Results

Intervention patients had a 19% reduction in hospital visits (IRRR: 0.81, 95% CI: 0.70-0.96) and a 17% reduction in blood samples (IRRR: 0.83, 0.73-0.96) compared to comparison patients. No effects were found for care integration, treatment burden, outpatient contacts, terminated outpatient trajectories, hospital admissions, days of admission or GP contacts.

Conclusion

The MOP seemed to reduce the number of hospital visits and blood samples. These results should be further investigated in studies exploring the coordination of outpatient care for multimorbidity.

Research question

Can an intervention of coordinating outpatient appointments to same-day visits combined with a multidisciplinary conference influence the utilisation of healthcare services and the patient-assessed integration of healthcare services and treatment burden among patients with multimorbidity?

Prevalence of and factors associated with multimorbidity among adults in Kuwait

BACKGROUND

This cross-sectional study aimed to assess the prevalence of morbidity i.e., one morbidity and multimorbidity (≥ 2 morbid conditions) among adults in Kuwait and to examine the sociodemographic and lifestyle factors associated with morbidity as a multinomial outcome in the study population.

METHODS

The data were collected from January 26, 2021, to February 3, 2021, using an electronic questionnaire, which was distributed on social media platforms. The consent form was attached with the questionnaire and the participants were requested to sign the consent form before completing the questionnaire. The prevalences (%) of each morbidity and multimorbidity were computed. Multivariable polychotomous logistic regression analysis was used to evaluate the association between the demographic and lifestyle factors with morbidity as a multinomial outcome.

RESULTS

Of 3572 respondents included, 89% were Kuwaiti, 78.3% females and 66% were 21- 40 years old. The prevalence of multimorbidity and one morbidity respectively was 27.4% and 29.7%. The prevalence of multimorbidity with two, three, four or five ill-health conditions were 14.3%, 7.4%, 3.5%, and 1.2%, respectively. A higher prevalence of multimorbidity was among respondents over 60 years of age (71%) and Kuwaiti nationals (28.9%). The final multivariable polychotomous logistic regression model revealed that age, sex, nativity, sedentary lifestyle, smoking, and alcohol drinking were significantly (p < 0.05) associated with multimorbidity. However, age and alcohol drinking were significant (p < 0.05) predictors of one morbidity.

CONCLUSION

This study provides evidence that multimorbidity is more prevalent among the elderly, females, and Kuwaiti nationals. Sedentary behaviour, smoking and alcohol consumption were significantly and independently associated with multimorbidity. These findings highlight the burden of multimorbidity and should be considered in the development of future prevention programs.