Relationship between multimorbidity, demographic factors and mortality: findings from the UK Biobank cohort

Workload-capacity imbalances and their impact on self-management complexity in patients with multimorbidity: a multicenter cross-sectional study

INTRODUCTION

Multimorbidity is increasing globally, emphasizing the need for effective self-management strategies. The Cumulative Complexity Model (CuCoM) offers a unique perspective on understanding self-management based on workload and capacity. This study aims to validate the CuCoM in multimorbid patients and identify tailored predictors of self-management.

METHODS

This multicenter cross-sectional survey recruited 1920 multimorbid patients in five primary health centres and four hospitals in China. The questionnaire assessed workload (drug intake, doctor visits and follow-up, disruption in life, and health problems), capacity (social, environmental, financial, physical, and psychological), and self-management. Data were analyzed using latent profile analysis, chi-square, multivariate linear regression, and network analysis.

RESULTS

d Patients were classified into four profiles: low workload-low capacity (10.2%), high workload-low capacity (7.5%), low workload-high capacity (64.6%), and high workload-high capacity (17.7%). Patients with low workload and high capacity exhibited better self-management (β = 0.271, p < 0.001), while those with high workload and low capacity exhibited poorer self-management (β=-0.187, p < 0.001). Social capacity was the strongest predictor for all profiles. Environmental capacity ranked second for 'high workload-high capacity' (R² = 3.26) and 'low workload-low capacity' (R² = 5.32) profiles. Financial capacity followed for the 'low workload-high capacity' profile (R² = 5.40), while psychological capacity was key in the 'high workload-low capacity' profile (R² = 6.40). In the network analysis, socioeconomic factors exhibited the central nodes (p < 0.05).

CONCLUSIONS

Personalized interventions designed to increase capacity and reduce workload are essential for improving self-management in multimorbid patients. Upstream policies promoting health equity are also crucial for better self-management outcomes.

Multimorbidity and analgesic-related harms: a systematic review

BACKGROUND

Multimorbidity is the presence of two or more long-term medical conditions. Chronic pain affects more than half of people with multimorbidity, and optimal treatment strategies are unknown. We aimed to quantify the risk of adverse outcomes from the following analgesics: opioids, nonsteroidal anti-inflammatory drugs (NSAIDs), and gabapentinoids in adults with multimorbidity.

METHOD

The review was registered on PROSPERO (CRD42023462592). We searched Medline, CINAHL, Web of Science, Embase, and CENTRAL for studies reporting analgesic-related harms in people with multimorbidity or the impact of multimorbidity on harms in adults exposed to analgesics. Two researchers independently screened titles/abstracts, completed full-text reviews, extracted data, and assessed risk of bias using the Newcastle-Ottawa scale. Studies were synthesised narratively, grouping by analgesic class and direction of effect.

RESULTS

We screened 6690 records and 344 full texts, with 27 studies included (n=2 671 958 patients). Studies were heterogenous, with variable quality (high risk of bias, n=11). Most studies on opioids reported adverse outcomes (12/16). Opioid use compared with non-use was associated with increased mortality in adults with multimorbidity. Multimorbidity was associated with opioid overdose and death among adults prescribed opioids for pain. Half of studies of NSAIDs reported adverse outcomes (6/11) including gastrointestinal bleeding. Only one study assessed gabapentinoids which found an association with delirium and pneumonia, but not mortality in people with multimorbidity.

CONCLUSIONS

There is evidence of harms associated with opioids in adults with multimorbidity, including overdose and increased mortality. There is a lack of evidence on gabapentinoids. Further research is required to understand optimal analgesic management in people with multimorbidity.

SYSTEMATIC REVIEW PROTOCOL

PROSPERO (CRD42023462592).

Development and evaluation of an integrated multispecialty clinic for people with multiple long-term conditions

Introduction

The number of people with multiple long-term conditions (MLTC) is increasing. People with MLTC experience fragmentation of care due to single-disease-orientated healthcare organisation and have increased morbidity and mortality. We developed an innovative clinic model whereby people with MLTC are assessed by a team of specialists together in one appointment to form a consensus management plan in real time. We report the outcomes together with patient and clinician feedback.

Methods

A multispecialty clinic was established to assess adults referred from the community or secondary care with MLTC. Patients were seen together by three or more relevant specialists and a coordinated plan was developed. To evaluate the clinic, we collected patient outcomes and obtained feedback from patients and clinicians in the clinic and from primary care clinicians.

Results

Twenty seven patients were assessed in the multispecialty clinic with a mean age of 64.6 years; 89% had diabetes, 70.4% hypertension, 63% CKD stages 3-5, and 51.9% had heart failure. Patients were taking a mean of 10 medications. Referrals were from primary care (51.9%) and secondary care, with the commonest reason being fluid overload (29.6%). On average, 1.7 medication changes were made per patient. Compared to the 6-month period before the clinic, in the 6 months after the clinic there was a significant reduction in interactions of patients with the acute hospital services (emergency department, same-day emergency care unit and acute inpatient medicine service). In a survey of 11 patients, all reported high satisfaction with the novel clinic format. A survey of seven clinicians, including a pharmacist and trainee doctor, demonstrated positive experiences of the clinic, confidence in the clinical decision making and enhanced learning. Primary care physicians also appreciated the coordinated plan across several specialties.

Discussion

In our pilot multispecialty clinic, people with MLTC were able to develop a real-time consensus plan with a group of specialists. Our approach was associated with fewer unscheduled healthcare interactions after the clinic. Our after-clinic survey showed positive responses from patients and clinicians. Future studies could examine how such a service could be rolled out to a wider group of people effectively and efficiently.

Heterogeneity in mortality risk prediction: a study of vulnerable adults in the Canadian longitudinal study on aging

BACKGROUND

Mortality prediction models are essential for clinical decision-making, but their performance may vary across patient subgroups. This study aimed to evaluate how a general mortality prediction model performs across subgroups defined by vulnerability factors and to test whether model improvements could improve prediction accuracy.

METHODS

We analyzed data from 49,266 participants in the Canadian Longitudinal Study on Aging. A general mortality prediction model (Model A) was developed using Cox proportional hazard regression with LASSO, incorporating variables spanning sociodemographic factors, lifestyle habits, comorbidities, and physical/cognitive function measures. Performance was evaluated across subgroups defined by age, frailty, multimorbidity, cognitive function, and functional impairment using discrimination (c-index), calibration, and Brier scores. We tested two additional strategies: incorporating subgroup-specific variables (Model B) and developing tailored models for different mortality risk categories (Models C1, C2, C3).

RESULTS

Over a median 6-year follow-up, 7.5% (3672) participants died. The general model performed well overall (c-index: 0.82, 95% CI 0.80-0.84; Brier: 0.036, 95% CI 0.032-0.040), but performance varied across subgroups. It was lower in frail individuals (c-index: 0.73, 95% CI 0.71-0.75; Brier: 0.12, 95% CI 0.11-0.13) and those with multiple chronic conditions (c-index: 0.76, 95% CI 0.75-0.78; Brier: 0.08, 95% CI 0.07-0.08), with risk underestimated in these groups. Neither incorporating subgroup variables nor developing risk-stratified models significantly improved performance.

CONCLUSION

Important variability in performance, particularly in vulnerable groups, highlights the limitations of a one-size-fits-all and underscores the need for more granular predictive models that account for subpopulation-specific characteristics to enhance mortality risk prediction.

Patterns of comorbidities differentially impact on in-hospital outcomes in heart failure patients

BACKGROUND

Cardiac and non-cardiac comorbidities are highly prevalent in patients with heart failure (HF). The aim of the present study was to describe their selective impact on in-hospital outcomes (length of hospitalization and mortality) of HF patients hospitalized in an Internal Medicine Unit.

METHODS

Between January 2017 and December 2022, 12,435 (6146 F, 6289 M) inpatients were hospitalized in our Internal Medicine Unit. HF was defined according to the International Statistical Classification of Diseases and Related Health Problems (ICD) version 9 codes 428, 402.01, 402.11, 402.91, 404.11, 404.13, 404.91, 404.93. Patients were classified by burden of overall, cardiac, and of non-cardiac comorbidities (0, 1, 2, 3 +). Multivariable regression models were used to assess associations between comorbidity burden and length of stay (linear regression) or in-hospital mortality (logistic regression).

RESULTS

HF patients (1481, or 11.9% of all hospitalizations during the observation period) had on average comorbidity count of 1.6. An increasing number of comorbidities was associated with longer duration of hospitalization and mortality. Non-cardiac, but not cardiac, comorbidities were associated with significantly higher length of stay (beta coefficient 2.86 ± 0.27) and in-hospital mortality (OR 1.90, 95% confidence interval (CI) 1.60-2.23; p < 0.0001).

CONCLUSIONS

Cardiac and non-cardiac comorbidities differentially impact on in-hospital outcomes of older HF patients hospitalized in an Internal Medicine unit. Their more precise management will allow a reduction of avoidable hospitalization in HF patients.

Association between systemic inflammation biomarkers and incident cardiovascular disease in 423,701 individuals: evidence from the UK biobank cohort

BACKGROUND

The associations between systemic inflammation biomarkers and cardiovascular disease (CVD) remain not well explored. This study aimed to investigate associations between different systemic inflammation biomarkers and incident CVD and main CVD subtypes - ischaemic heart disease (IHD), stroke, and heart failure - explore dose-response relationships, and compare their predictive performance.

METHODS

This prospective cohort study included 423,701 UK Biobank participants free of CVD at baseline. Baseline neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), and system inflammation response index (SIRI) were derived. Cox-proportional regression models were used to investigate the associations.

RESULTS

NLR, PLR, SII, and SIRI was positively and LMR was negatively associated with all four of the outcomes investigated. The relationships were non-linear for all biomarkers with CVD and were linear for NLR, SII, and SIRI and non-linear for LMR and PLR with IHD, stroke and heart failure. Compared with the more established biomarkers, all four of the novel biomarkers had statistically superior predictive performance for three of the outcomes investigated (CVD, IHD and heart failure) and three of them were superior at predicting stroke. Compared to a model of CVD prediction with classical risk factors (C-index = 0.702), discrimination was improved on the addition of inflammation markers for CVD (C-index change 0.0069, 95% CI 0.0033 to 0.0107), IHD (C-index change 0.0054, 95% CI 0.0013 to 0.0095), and heart failure (C-index change 0.0153, 95% CI 0.0089 to 0.0218).

CONCLUSIONS

There were independent and dose-response relationships between the novel systemic inflammation biomarkers and CVD outcomes. Addition of the inflammation biomarkers including novel inflammation biomarkers showed improved discrimination of the traditional risk prediction model. With accumulated evidence, these biomarkers should be considered for inclusion in risk tools and prevention.

Knee and hip osteoarthritis increase the risk of cardiovascular disease: A national registry-based longitudinal cohort study

OBJECTIVE

Osteoarthritis and cardiovascular disease are major public health challenges. We aimed to estimate the average sex-specific effects of knee and hip osteoarthritis on the risk of cardiovascular disease.

METHODS

We used 2001-2015 Danish national health registry data to identify all adults with knee or hip osteoarthritis and an age-, sex-, and education-matched group without osteoarthritis. Cardiovascular disease outcomes were identified with relevant ICD-10 codes. The effects of osteoarthritis were estimated with sex-stratified multivariable Cox regression models, accounting for multiple sources of confounding determined a priori with a directed acyclic graph. Results were reported with cumulative incidence curves and hazard ratios (HR) conditioned on age, sex, education, and obesity diagnosis. Sensitivity analyses explored the potential impacts of bias owing to outcome misclassification and unmeasured confounding.

RESULTS

We analysed data from 1,838,434 adults, including 290,781 people with knee or hip osteoarthritis and 1,547,653 age-, sex-, and education-matched controls. Women with knee or hip osteoarthritis had a 44% increased hazard of cardiovascular disease (HR [95% CI] =  1.44 [1.43 to 1.46]), while men with knee or hip osteoarthritis had a 24% increased hazard of subsequent cardiovascular disease (HR[95% CI] =  1.24 [1.23 to 1.26]) compared to people without osteoarthritis. These results were confirmed by sensitivity analyses.

CONCLUSION

The apparent effect of osteoarthritis on cardiovascular disease was stronger in women than in men. Clinicians who care for patients with osteoarthritis should be aware of cardiovascular disease risk when selecting therapies and consider behavioural approaches to improving health-related physical activity behaviour in this population.

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.

Multimorbidity Patterns and In-Hospital Outcomes in Chinese Young Women (Aged <55 Years) Presenting with ST-Segment-Elevation Myocardial Infarction

BACKGROUND

Recent evidence highlights an increasing incidence of myocardial infarction in young women. Identifying clinical multimorbidity patterns in this population may improve therapeutic strategies and clinical care.

METHODS AND RESULTS

We identified multimorbidity patterns in 9570 young women with ST-segment-elevation myocardial infarction (median age, 50 years [range, 47.0-53.0 years]) admitted to the China Chest Pain Center Database between 2016 and 2021. Hierarchical clustering of 15 medical conditions was performed to derive multimorbidity patterns. The primary outcome was a composite of in-hospital adverse events. Associations between multimorbidity patterns and outcomes were evaluated using multivariable-adjusted logistic regression models. Among 9570 patients, 50% (n=4789) had multimorbidity. Six multimorbidity patterns were identified, including 4 specific patterns: (1) pattern 1, cerebrovascular cluster (histories of cerebrovascular disease and hypertension); (2) pattern 2, traditional cardiovascular disease risk factors cluster (histories of hyperlipidemia, obesity, and diabetes, and family history of cardiovascular disease and smoking); (3) pattern 3, coronary-heart failure cluster (histories of heart failure, coronary artery disease, peripheral arterial disease, and thyroid dysfunction); and (4) pattern 4, anemia-renal dysfunction cluster (histories of atrial fibrillation, anemia, chronic kidney disease, and peptic ulcer). Compared with patients without multimorbidity, those with pattern 1 (odds ratio [OR], 2.29 [95% CI, 1.49-3.52]), pattern 2 (OR, 1.52 [95% CI, 1.24-1.86]), and pattern 4 (OR, 2.25 [95% CI, 1.10-4.61]) exhibited higher risks for composite outcomes.

CONCLUSIONS

Specific multimorbidity patterns in young women with ST-segment-elevation myocardial infarction were associated with distinct in-hospital outcomes in a nationwide registry, providing proof-of-concept evidence to guide future therapeutic approaches.

Understanding hospital activity and outcomes for people with multimorbidity using electronic health records

As the prevalence of multimorbidity grows, provision of effective healthcare is more challenging. Both multimorbidity and complexity in healthcare delivery may be associated with worse outcomes. We studied consecutive, unique emergency non-surgical hospitalisations for patients over 50 years old to three hospitals in Scotland, UK between 2016 and 2024 using linked primary care and hospital records to define multimorbidity (2 + long-term conditions), and timestamped hospital electronic health record (EHR) contacts with nursing and rehabilitation providers to describe intensity of inpatient care. The primary outcome was emergency hospital readmission within 30 days of discharge, analysed using multivariable logistic regression. Across 98,242 consecutive admissions, 84% of the study population had multimorbidity, 50% had 4 + long-term conditions, and 37% had both physical and mental health conditions. Both higher condition count and contacts (nursing and rehabilitation) were independently associated with the primary outcome in fully adjusted models (example adjusted odds ratio [aOR] 1.62, 95% CI 1.52 to 1.73 for 4 + conditions compared to no multimorbidity, p < 0.001; aOR 1.35, 95% CI 1.28 to 1.42 for > 8 nursing contacts compared to 1-3, p < 0.001). While multimorbidity was associated with longer hospital stays with more nursing and rehabilitation contacts, the distribution of contacts and activity did not differ by multimorbidity or subsequent emergency readmission status. Higher count multimorbidity was associated with an increased risk of readmission, but we observed uniformity in care despite differential outcomes across multimorbidity groups. This may suggest that EHR data-driven approaches could inform person-centred care and improve hospital resource allocation.

Association between physical multimorbidity in middle adulthood and mortality: findings from two large cohort studies in Japan

BACKGROUND

While previous literature suggests that multimorbidity is linked to a higher risk of mortality, evidence is scarce among individuals in middle adulthood. We aimed to examine the association between physical multimorbidity and all-cause mortality among individuals aged 40-64 years at baseline in Japan.

METHODS

Data were obtained from two cohort studies, the Japan Public Health Center-based Prospective Study (JPHC) and the Japan Epidemiology Collaboration on Occupational Health Study (J-ECOH). The study participants were 144,774 individuals aged 40-64 years at baseline who were followed up for a maximum of 29 and 10 years in the JPHC and J-ECOH, respectively. Multimorbidity was defined as the presence of ≥ 2 of 10 morbidities or conditions based on self-reported information. A Cox proportional hazards model was used to examine the association in relation to all-cause mortality. We calculated pooled hazard ratios (HR) and corresponding 95% confidence intervals (CI) using a random-effects meta-analysis model. Cause-specific analysis was performed using the JPHC dataset, which provided a sufficient number of events for mortality due to physical disorders, mental disorders/suicide, and unintentional injuries.

RESULTS

During a follow-up of 2,304,375 person-years in the JPHC and 311,637 person-years in the J-ECOH, 23,611 and 275 deaths were recorded, respectively. Participants with vs. without physical multimorbidity at baseline were more likely to die prematurely in both cohorts with a pooled HR of 1.61 (95%CI = 1.29-2.01). Cause-specific analyses among the JPHC participants revealed that physical multimorbidity at baseline was linked with mortality due to physical disorders, mortality due to mental disorders/suicide, and mortality due to unintentional injuries.

CONCLUSIONS

Physical multimorbidity in middle adulthood is associated with an increased risk of all-cause mortality in Japan.

Multimorbidity clusters and their associations with health-related quality of life in two UK cohorts

BACKGROUND

Identifying clusters of multiple long-term conditions (MLTCs), also known as multimorbidity, and their associated burden may facilitate the development of effective and cost-effective targeted healthcare strategies. This study aimed to identify clusters of MLTCs and their associations with long-term health-related quality of life (HRQoL) in two UK population-based cohorts.

METHODS

Age-stratified clusters of MLTCs were identified at baseline in UK Biobank (n = 502,363, 54.6% female) and UKHLS (n = 49,186, 54.8% female) using latent class analysis (LCA). LCA was applied to people who self-reported ≥ 2 LTCs (from n = 43 LTCs [UK Biobank], n = 13 LTCs [UKHLS]) at baseline, across four age-strata: 18-36, 37-54, 55-73, and 74 + years. Associations between MLTC clusters and HRQoL were investigated using tobit regression and compared to associations between MLTC counts and HRQoL. For HRQoL, we extracted EQ-5D index data from UK Biobank. In UKHLS, SF-12 data were extracted and mapped to EQ-5D index scores using a standard preference-based algorithm. HRQoL data were collected at median 5 (UKHLS) and 10 (UK Biobank) years follow-up. Analyses were adjusted for available sociodemographic and lifestyle covariates.

RESULTS

LCA identified 9 MLTC clusters in UK Biobank and 15 MLTC clusters in UKHLS. Clusters centred around pulmonary and cardiometabolic LTCs were common across all age groups. Hypertension was prominent across clusters in all ages, while depression featured in younger groups and painful conditions/arthritis were common in clusters from middle-age onwards. MLTC clusters showed different associations with HRQoL. In UK Biobank, clusters with high prevalence of painful conditions were consistently associated with the largest deficits in HRQoL. In UKHLS, clusters of cardiometabolic disease had the lowest HRQoL. Notably, negative associations between MLTC clusters containing painful conditions and HRQoL remained significant even after adjusting for number of LTCs.

CONCLUSIONS

While higher LTC counts remain important, we have shown that MLTC cluster types also have an impact on HRQoL. Health service delivery planning and future intervention design and risk assessment of people with MLTCs should consider both LTC counts and MLTC clusters to better meet the needs of specific populations.

Impact of adverse childhood experiences on sensory thresholds in adults living with multimorbidity and chronic pain (the ACE-MAP study): protocol for an observational feasibility study

INTRODUCTION

Exposure to adverse childhood experiences (ACEs) is associated with a range of poor long-term health outcomes, including multimorbidity and chronic pain. Epidemiological evidence underpins much of this relationship; however, psychophysical testing methods, such as quantitative sensory testing (QST), may provide valuable insights into potential mechanisms. Previous studies have shown inconsistent links between ACEs and QST, but the QST profiles of people with multimorbidity have not been reported. We hypothesise that exposure to ACEs is associated with lowered QST thresholds (ie, experience of pain with milder stimuli) and that this association is stronger in adults with multimorbidity and/or chronic pain. The ACE-MAP study is a cross-sectional feasibility study with the primary aim of assessing the feasibility and acceptability of the proposed study procedures. The secondary aim is to generate preliminary data to understand the impact of ACEs on QST thresholds.

METHODS AND ANALYSIS

We plan to recruit 40 participants, with 10 in each of the following groups: (1) chronic pain with multimorbidity; (2) chronic pain without multimorbidity; (3) multimorbidity without chronic pain; and (4) controls. Participants will complete a series of questionnaires (including on ACEs, chronic pain and long-term conditions) and will then take part in QST assessments. The primary study outcomes will include measures of feasibility and acceptability of the proposed study design. The secondary study outcomes will include exploratory analysis on the relationship between ACEs and QST thresholds.

ETHICS AND DISSEMINATION

The study was approved by the Scotland B Research Ethics Committee (reference: 24/SS/0031). Results from the study will be presented at scientific conferences, published in a peer-reviewed journal and shared with patients and members of the public through other media streams.

TRIAL REGISTRATION NUMBER

ISRCTN10049430.

GWAShug: a comprehensive platform for decoding the shared genetic basis between complex traits based on summary statistics

The shared genetic basis offers very valuable insights into the etiology, diagnosis and therapy of complex traits. However, a comprehensive resource providing shared genetic basis using the accessible summary statistics is currently lacking. It is challenging to analyze the shared genetic basis due to the difficulty in selecting parameters and the complexity of pipeline implementation. To address these issues, we introduce GWAShug, a platform featuring a standardized best-practice pipeline with four trait level methods and three molecular level methods. Based on stringent quality control, the GWAShug resource module includes 539 high-quality GWAS summary statistics for European and East Asian populations, covering 54 945 pairs between a measurement-based and a disease-based trait and 43 902 pairs between two disease-based traits. Users can easily search for shared genetic basis information by trait name, MeSH term and category, and access detailed gene information across different trait pairs. The platform facilitates interactive visualization and analysis of shared genetic basic results, allowing users to explore data dynamically. Results can be conveniently downloaded via FTP links. Additionally, we offer an online analysis module that allows users to analyze their own summary statistics, providing comprehensive tables, figures and interactive visualization and analysis. GWAShug is freely accessible at http://www.gwashug.com.

Multimorbidity latent classes in relation to 11-year mortality, risk factors and health-related quality of life in Malaysia: a prospective health and demographic surveillance system study

BACKGROUND

We aimed to identify specific multimorbidity latent classes among multi-ethnic community-dwelling adults aged ≥ 18 years in Malaysia. We further explored the risk factors associated with these patterns and examined the relationships between the multimorbidity patterns and 11-year all-cause mortality risk, as well as health-related quality of life (HRQoL).

METHODS

Using data from 18,101 individuals (aged 18-97 years) from the baseline Census 2012, Health Round 2013, and Verbal Autopsies 2012-2023 of the South East Asia Community Observatory (SEACO) health and demographic surveillance system, latent class analysis was performed on 13 chronic health conditions to identify statistically and clinically meaningful groups. Multinomial logistic regression and Cox proportional hazards regression models were conducted to investigate the adjusted association of multimorbidity patterns with the risk factors and mortality, respectively. HRQoL was analyzed by linear contrasts in conjunction with ANCOVA adjusted for baseline confounders.

RESULTS

Four distinct multimorbidity latent classes were identified: (1) relatively healthy (n = 10,640); (2) cardiometabolic diseases (n = 2428); (3) musculoskeletal, mobility and sensory disorders (n = 2391); and (4) complex multimorbidity (a group with more severe multimorbidity with combined profiles of classes 2 and 3) (n = 699). Significant variations in associations between socio-demographic characteristics and multimorbidity patterns were discovered, including age, sex, ethnicity, education level, marital status, household monthly income and employment status. The complex multimorbidity group had the lowest HRQoL across all domains compared to other groups (p < 0.001), including physical health, psychological, social relationships and environment. This group also exhibited the highest mortality risk over 11 years even after adjustment of confounders (age, sex, ethnicity, education and employment status), with a hazard of death of 1.83 (95% CI 1.44-2.33), followed by the cardiometabolic group (HR 1.42, 95% CI 1.18-1.70) and the musculoskeletal, mobility and sensory disorders group (HR 1.29, 95% CI 1.04-1.59).

CONCLUSIONS

Our study advances the understanding of the complexity of multimorbidity and its implications for health outcomes and healthcare delivery. The findings suggest the need for integrated healthcare approaches that account for the clusters of multiple conditions and prioritize the complex multimorbidity cohort. Further longitudinal studies are warranted to explore the underlying mechanisms and evolution of multimorbidity patterns.

Child Maltreatment Characteristics and Adult Physical Multimorbidity in Germany

Importance

Associations between child maltreatment (CM) and health have been studied broadly, but most studies focus on multiplicity (number of experienced subtypes of CM). Studies assessing multiple CM characteristics are scarce, partly due to methodological challenges, and were mostly conducted in patient samples.

Objective

To determine the importance of CM characteristics in association with physical multimorbidity in adulthood for women and men in a German representative sample.

Design, Setting, and Participants

This survey study used data from a representative sample of the German population between July and October 2021. Households were randomly selected within regional areas by a German demographic consultation company, and the Kish-Grid method was applied to ensure random participation. Reasons for nonparticipation were refusal of the selected household or target person to participate and failure to contact a household after 4 visits. Analyses took place between June 2023 and July 2024.

Exposure

Characteristics of CM, including subtypes of CM, multiplicity, age at time of maltreatment (timing), number of years of experienced maltreatment (duration), frequency, and subjective severity (measured with the ISPCAN Child Abuse Screening Tools Retrospective version questionnaire).

Main Outcomes and Measures

The main outcome was physical multimorbidity, defined as the sum score of lifetime leading morbidity and mortality causes in Western countries (obesity, diabetes, cancer, hypertension, myocardial infarction, chronic obstructive pulmonary disease, and incident stroke). Conditioned random forest regression analyses (a machine learning regression technique) were conducted to examine what characteristics of CM were most importantly associated with physical multimorbidity in adulthood while considering all other variables in the model.

Results

Of 5908 individuals invited, the study sample included 2514 participants (response rate, 42.6%), with 1297 (51.6%) women (mean [SD] age, 50.6 [17.9] years) and 1217 (48.4%) men (mean [SD] age, 49.5 [18.2] years). Duration of CM was the most important factor for physical multimorbidity in adulthood for both women (importance = 0.595; 95% CI, 0.599-0.601) and men (importance = 1.389; 95% CI, 1.386-1.394). Duration and timing variables were more importantly associated with outcomes than multiplicity in women and men. For women, severity and experiencing CM at age 4 years was significantly associated with physical multimorbidity in adulthood. For men, experiencing CM at age 11 years was most importantly associated with physical multimorbidity in adulthood.

Conclusions and Relevance

In this survey study, conditioned random forest regression analyses were applied to provide insights in the importance of duration and timing of CM for physical health in addition to the frequently studied multiplicity. These findings suggest that CM assessments should be considered in diagnostics of individuals with physical health conditions and may also inform strategies to mitigate the risk.

Beyond the underlying cause of death: an algorithm to study multi-morbidity at death

BACKGROUND

In countries with high life expectancy, a growing share of the population is living with several diseases, a situation referred to as multi-morbidity. In addition to health data, cause-of-death data, based on the information reported on death certificates, can help monitor and characterize this situation. This requires going beyond the underlying cause of death and accounting for all causes on the death certificates which may have played various roles in the morbid process, depending on how they relate to each other.

METHODS

Apart from the underlying cause, the cause-of death data available in vital registration systems do not differentiate all other causes. We developed an algorithm based on the WHO rules that assigns a "role" to each entry on the death certificate. We distinguish between the following roles: originating (o), when the condition has initiated a sequence of events leading directly to death; precipitating (p), when it was caused by an originating condition or one of its consequences; associated (a), when it contributed to death but was not part of the direct sequence leading to death; ill-defined (i), i.e., conditions such as symptoms or signs or poorly informative causes. We applied this algorithm to all death records in four countries (Italy, France, Spain and the US) in 2017.

RESULTS

The average number of originating causes is similar in the four countries. The proportion of death certificates with more than one originating cause-a situation typical of multi-morbidity-ranges from 10% in the US to 18% in Spain. All ages combined, the proportion of deaths with at least one associated cause is higher in Italy (41%) and in the US (42%) than in France (29%) and in Spain (27%). It is especially high in the US at all adult ages. Variations in the average number of causes between the four countries are mainly due to precipitating and ill-defined causes.

CONCLUSIONS

The output of our algorithm sheds light on cross-country differences in the average number of causes on death certificates. It also opens the door for improvements in the methods used for multiple cause-of-death analysis.

Beyond Index Conditions: Applying a Multimorbidity Approach to Renal Cancer Nursing

OBJECTIVE

This article aims to describe the key components of renal cancer nursing and multimorbidity nursing, and reflects on how adopting a multimorbidity approach to renal cancer nursing can help nurses provide holistic patient care.

METHODS

This is a discussion paper drawing on relevant evidence and theory.

RESULTS

Renal cancer nurses have a highly specialised knowledge base and are able to use this expertise to deliver excellent care to people with cancer. However, lots of people with cancer have other conditions as well. Adopting a multimorbidity approach to nursing care provides a more holistic framework for care delivery.

CONCLUSIONS

Cancer nurses are ideally placed to support patients in this way, so they are able to deliver care which accounts for factors such as treatment burden and how this impacts on patients and carers.

IMPLICATIONS FOR NURSING PRACTICE

Nurses who care for people with renal cancer should view their patients through the lens of multimorbidity. This involves screening for other chronic conditions, considering polypharmacy, providing emotional support and continuity of care, and coordinating care in a way that accounts for the potentially burdensome nature of the patient's interactions with health care.

Ultra-processed food, genetic risk, and the risk of cardiometabolic diseases and cardiometabolic multimorbidity: A prospective study

BACKGROUND AND AIMS

This study aims to evaluate the impact of ultra-processed food (UPF) on type 2 diabetes (T2D), cardiovascular disease (CVD), hypertension, and cardiometabolic multimorbidity (CMM), and to explore the role of genetic susceptibility in these associations.

METHODS AND RESULTS

90 631 participants from the UK Biobank were included (collected between 2006 and 2010). The outcomes assessed included T2D, CVD, hypertension and CMM. The Cox proportional hazards model was used to evaluate their associations and the potential modification by genetic risk, which was estimated using the polygenic risk score (PRS). Participants with high UPF consumption had a higher risk of T2D, CVD, and CMM, with the adjusted hazard ratio (HR) of 1.36 (95 % confidence interval [CI]: 1.15, 1.61), 1.13 (95%CI: 1.03, 1.23), and 1.14 (95%CI: 1.05, 1.24), respectively. Those with high UPF consumption and high PRS for T2D, CVD, and hypertension had the highest risk of T2D (HR: 4.01; 95%CI: 2.83, 5.69), CVD (HR: 2.18; 95%CI: 1.86, 2.56), and hypertension (HR: 1.79; 95%CI: 1.61, 1.99), respectively. In participants with one cardiometabolic disease (CMD), those with high UPF consumption and high PRST2D or PRSCVD had the highest risk of developing CMM. A significant additive interaction was observed between PRST2D and UPF consumption on the risk of T2D.

CONCLUSION

Our study underscored the importance of identifying individuals with high UPF consumption for targeted dietary interventions to mitigate the risk of CMDs and CMM, particularly among those with a high genetic risk of CMDs.

Combinations of multiple long term conditions and risk of hospital admission or death during winter 2021-22 in England: population based cohort study

Objective

To describe which combinations of long term conditions were associated with a higher risk of hospital admission or death during winter 2021-22 (the third wave of the covid-19 pandemic) in adults in England.

Design

Population based cohort study.

Setting

Linked primary and secondary care data from the General Practice Extraction Service Data for Pandemic Planning and Research (GDPPR) database, Hospital Episode Statistics, and Office for National Statistics death registry, comprising pseudoanonymised routinely collected electronic medical records from the whole population of England registered at a general practice, 1 December 2021 to 31 March 2022.

Participants

48 253 125 individuals, registered in GDPPR in England, aged ≥18 years, and alive on 1 December 2021.

Main outcomes measures

All cause hospital admissions and deaths associated with combinations of multiple long term conditions compared with those with no long term conditions, during the winter season (1 December 2021 to 31 March 2022). Overdispersed Poisson regression models were used to estimate the incidence rate ratios after adjusting for age, sex, ethnic group, and index of multiple deprivation.

Results

Complete data were available for 48 253 125 adults, of whom 15 million (31.2%) had multiple long term conditions. Rates of hospital admissions and deaths among individuals with no long term conditions were 96.3 and 0.8 per 1000 person years, respectively. Compared with those with no long term conditions, the adjusted incidence rate ratio of hospital admissions were 11.0 (95% confidence interval (CI) 9.4 to 12.7) for those with a combination of cancer, chronic kidney disease, cardiovascular disease, and type 2 diabetes mellitus; 9.8 (8.3 to 11.4) for those with cancer, chronic kidney disease, cardiovascular disease, and osteoarthritis; and 9.6 (8.6 to 10.7) for those with cancer, chronic kidney disease, and cardiovascular disease. Compared with those with no long term conditions, the adjusted rate ratio of death was 21.4 (17.5 to 26.0) for those with chronic kidney disease, cardiovascular disease, and dementia; 23.2 (17.5 to 30.3) for those with cancer, chronic kidney disease, cardiovascular disease, and dementia; and 24.3 (19.1 to 30.4) for those with chronic kidney disease, cardiovascular disease, dementia, and osteoarthritis. Cardiovascular disease with dementia appeared in all of the top five combinations of multiple long term conditions for mortality, and this two disease combination was associated with a substantially higher rate of death than many three, four, and five disease combinations.

Conclusions

In this study, rates of hospital admission and death varied by combinations of multiple long term conditions and were substantially higher in those with than in those without any long term conditions. High risk combinations for prioritisation and preventive action by policy makers were highlighted to help manage the challenges imposed by winter pressures on the NHS.

Classification of long-term disease patterns in inflammatory bowel disease and analysis of their associations with adverse health events

BACKGROUND

With existing researches identifying an increased rate of long-term conditions (LTCs) among Inflammatory Bowel Disease (IBD) patients, yet there is a lack of exploration into the patterns of comorbidity and prognostic rates for IBD patients with multiple morbidities.

METHODS

The study included 8,305 participants who self-reported having IBD, comprising ulcerative colitis (UC) and Crohn's disease (CD). Latent class analysis (LCA) was utilized to create optimal categories of LTC combinations for UC and CD patients with additional long-term conditions. Using Cox proportional hazards models, we compared the all-cause mortality rates over a 16-year follow-up among UC and CD patients within different LTC categories, both without LTCs and with the addition of one LTC, the probability of major adverse cardiovascular events (MACE), and the rates of IBD-related surgeries.

RESULTS

A total of 5,617 participants reported having two or more LTCs, with the LCA method identifying three prevalence categories among CD patients, and four prevalence categories among UC patients. The highest mortality rate among CD patients was found in category 3: (HR 1.789, 95% CI (1.439-2.224)), and the highest rates of MACE were also in category 3: (HR 11.432, 95% CI (9.332-14.005)), with hypertension being the distinguishing characteristic of this category, and the highest rates of IBD-related surgeries being associated with pain in category 1: (HR 1.217, 95% CI (0.983-1.506)). Among UC patients, the highest mortality rate was in category 3: (HR 2.221, 95% CI (1.837-2.684)), with the highest MACE rates found in category 3: (HR 6.422, 95% CI (5.659-7.288)), and the highest rates of IBD-related surgeries being associated with pain, also in category 3: (HR 1.218, 95% CI (1.041-1.425)).

CONCLUSION

The rates of adverse health outcomes in IBD patients is closely associated with multimorbidity patterns, underscoring the need to fully consider multimorbidity patterns in the assessment, management, and treatment strategies for IBD.

Association between single and multiple cardiometabolic diseases and all-cause mortality among Chinese older adults: A prospective, nationwide cohort study

BACKGROUND AND AIM

Cardiometabolic diseases (CMDs) are leading causes of death and disability, but little is known about the additive mortality effects of multiple CMDs. This study aimed to examine the association between single and multiple CMDs and all-cause mortality among older Chinese population.

METHODS AND RESULTS

Using the Chinese Longitudinal Healthy Longevity Survey (CLHLS) database, we analyzed data from 2008 to 2018 to assess the relationship between CMDs and mortality. Cox regression models estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for single and multiple CMDs. At baseline, 11,351 participants (56.9% female) aged 60 years or older were included. 11.91% of participants had a single CMD, 1.51% had two CMDs, and 0.22% had three CMDs. Over a decade follow-up, 8992 deaths (79.2%) were recorded. A dose-response relationship was observed, with the mortality risk increasing by 17% for each additional disease. The fully-adjusted HRs for all-cause mortality were 1.16, 1.36, and 2.03 for one, two, and three CMDs, respectively. Larger effects of single and multiple CMDs were observed in the male group (P = 0.015) and the younger senior group (P < 0.001).

CONCLUSIONS

This large-scale study found that CMDs multiply mortality risks, especially in younger seniors and males. The risk is highest when heart disease and stroke coexist, and diabetes further increases it. Public health efforts should prioritize evidence-based management and prevention of CMDs.

Reporting of pre-existing multiple long-term conditions in physical rehabilitation for long COVID: a scoping review

BACKGROUND

Physical rehabilitation may improve health and wellbeing outcomes for some adults living with long COVID. However, individuals living with pre-existing multiple long-term conditions (MLTCs) and long COVID may have additional rehabilitation challenges. This scoping review aims to identify the available evidence describing physical rehabilitation interventions for adults living with long COVID, to systematically map the reporting of pre-existing MLTCs, and to describe the characteristics of physical rehabilitation interventions used in adults with both pre-existing long-term conditions (LTCs) and long COVID.

METHODS

MEDLINE, CINAHL, Scopus, APA PsycInfo, medRxiv, OpenGrey and MedNar were searched from January 2020 to July 2023. Eligibility criteria included adults with long COVID, rehabilitation interventions including a physical component in any setting and any study design investigating interventions or intervention content except case series/reports.

RESULTS

Of 5326 unique records, 50 articles met the inclusion criteria, of which 25 (50%) made reference to pre-existing LTCs. These articles included four protocols and one consensus statement. Four of the remaining 20 studies (20%) reported the number of pre-existing LTCs, enabling the differentiation of individuals with MLTCs. One study reported outcomes of individuals with MLTCs separately to those without. The interventions described (k=24) typically consisted of combined aerobic and strength exercises (k=17 (71%)) in an outpatient setting (k=13 (54%)).

CONCLUSIONS

There is limited and inconsistent reporting of the presence of MLTCs in studies of physical rehabilitation for adults with long COVID. Clarity and consistency of reporting of MLTCs is required to enable evaluation and adaptation of interventions to improve health and wellbeing for this population.

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.

Association of serum calcium, vitamin D, and C-reactive protein with all-cause and cause-specific mortality in an osteoarthritis population in the UK: a prospective cohort study

BACKGROUND

Osteoarthritis is a prevalent musculoskeletal condition, but the role of specific serum biomarkers, such as calcium, vitamin D, and C-reactive protein (CRP), in predicting mortality among individuals with osteoarthritis remains unclear.

METHODS

This observational study analyzed longitudinal data from over 500,000 participants in the UK Biobank, identifying those with osteoarthritis using ICD-9/10 codes or self-reported history. We performed multivariable cox-regression and flexible parametric survival model (FPSM) for survival analysis, with adjustments made through the inverse probability of treatment weight (IPTW) for baseline covariates identified by directed acyclic graphs (DAGs).

RESULTS

Of the 49,082 osteoarthritis population, the average age was 60.69 years, with 58.7% being female. During the follow-up period exceeding 15 years, a total of 5,522 people with osteoarthritis died. High serum calcium levels, compared to normal serum calcium levels, were significantly associated with all-cause mortality (hazard ratio (HR) 1.33, 95% confidence interval (CI) 1.11, 1.59), cardiovascular diseases (CVD)-related deaths (HR 1.55, 95% CI 1.05, 2.29), and other deaths (HR 1.59, 95% CI 1.20, 2.11). Low serum calcium levels, compared to normal serum calcium levels, was linked with CVD-related deaths (HR 2.06, 95% CI 1.02, 4.14). Vitamin D insufficiency, compared to sufficient vitamin D levels, was correlated with all-cause mortality (HR 1.22, 95% CI 1.13, 1.33), CVD-related deaths (HR 1.43, 95% CI 1.20, 1.72), and other deaths (HR 1.26, 95% CI 1.09, 1.45) but not with cancer-related deaths. High serum CRP levels, compared to normal CRP levels, were associated with all outcomes (all-cause mortality: HR 1.22, 95% CI 1.12, 1.33; CVD-related death: HR 1.24, 95%CI 1.03, 1.49; cancer-related death: HR 1.23, 95% CI 1.09, 1.40; other deaths: HR 1.19, 95%CI 1.03, 1.38).

CONCLUSIONS

Both high and low serum calcium levels, elevated CRP, and vitamin D insufficiency are potential predictors of increased mortality risk in the osteoarthritis population. These findings emphasize the importance of monitoring and possibly addressing these serum biomarkers in osteoarthritis populations to improve long-term outcomes. Further studies are needed to understand the underlying mechanisms and to propose therapeutic interventions.

Multimorbidity and adverse outcomes following emergency department attendance: population based cohort study

ABSTRACT

Objectives

To describe the effect of multimorbidity on adverse patient centred outcomes in people attending emergency department.

Design

Population based cohort study.

Setting

Emergency departments in NHS Lothian in Scotland, from 1 January 2012 to 31 December 2019.

Participants

Adults (≥18 years) attending emergency departments.

Data sources

Linked data from emergency departments, hospital discharges, and cancer registries, and national mortality data.

Main outcome measures

Multimorbidity was defined as at least two conditions from the Elixhauser comorbidity index. Multivariable logistic or linear regression was used to assess associations of multimorbidity with 30 day mortality (primary outcome), hospital admission, reattendance at the emergency department within seven days, and time spent in emergency department (secondary outcomes). Primary analysis was stratified by age (<65 v ≥65 years).

Results

451 291 people had 1 273 937 attendances to emergency departments during the study period. 43 504 (9.6%) had multimorbidity, and people with multimorbidity were older (median 73 v 43 years), more likely to arrive by emergency ambulance (57.8% v 23.7%), and more likely to be triaged as very urgent (23.5% v 9.2%) than people who do not have multimorbidity. After adjusting for other prognostic covariates, multimorbidity, compared with no multimorbidity, was associated with higher 30 day mortality (8.2% v 1.2%, adjusted odds ratio 1.81 (95% confidence interval (CI) 1.72 to 1.91)), higher rate of hospital admission (60.1% v 20.5%, 1.81 (1.76 to 1.86)), higher reattendance to an emergency department within seven days (7.8% v 3.5%, 1.41 (1.32 to 1.50)), and longer time spent in the department (adjusted coefficient 0.27 h (95% CI 0.26 to 0.27)). The size of associations between multimorbidity and all outcomes were larger in younger patients: for example, the adjusted odds ratio of 30 day mortality was 3.03 (95% CI 2.68 to 3.42) in people younger than 65 years versus 1.61 (95% CI 1.53 to 1.71) in those 65 years or older.

Conclusions

Almost one in ten patients presenting to emergency department had multimorbidity using Elixhauser index conditions. Multimorbidity was strongly associated with adverse outcomes and these associations were stronger in younger people. The increasing prevalence of multimorbidity in the population is likely to exacerbate strain on emergency departments unless practice and policy evolve to meet the growing demand.

Association of Depression With the Progression of Multimorbidity in Older Adults: A Population-Based Cohort Study

BACKGROUND

The relationship between depression and the risk of multimorbidity progression has rarely been studied in older adults. This study was aimed to determine whether depression is associated with progression in the severity and complexity of multimorbidity, considering the influence of depression's severity and subtype.

METHODS

As a part of the Korean Longitudinal Study on Cognitive Aging and Dementia, this population-based cohort study followed a random sample of community-dwelling Koreans aged 60 and older for 8 years at 2-year intervals starting in 2010. Participants included those who completed mood and multimorbidity assessments and did not exhibit complex multimorbidity at the study's outset. Depression was assessed using the Geriatric Depression Scale, while multimorbidity was evaluated using the Cumulative Illness Rating Scale. The study quantified multimorbidity complexity by counting affected body systems and measured multimorbidity severity by averaging scores across 14 body systems.

FINDINGS

The 2,486 participants (age = 69.1 ± 6.5 years, 57.6% women) were followed for 5.9 ± 2.4 years. Linear mixed models revealed that participants with depression had a faster increase in multimorbidity complexity score (β = .065, SE = 0.019, p = 0.001) than those without depression, but a comparable increase in multimorbidity severity score (β = .001, SE = .009, p = 0.870) to those without depression. Cox proportional hazard models revealed that depression was associated with the risk of developing highly complex multimorbidity affecting five or more body systems, particularly in severe or anhedonic depression.

INTERPRETATION

Depression was associated with the worsening of multimorbidity in Korean older adults, particularly when severe or anhedonic. Early screening and management of depression may help to reduce the burden of multimorbidity in older adults.

Association of latent class analysis-derived multimorbidity clusters with adverse health outcomes in patients with multiple long-term conditions: comparative results across three UK cohorts

Background

It remains unclear how to meaningfully classify people living with multimorbidity (multiple long-term conditions (MLTCs)), beyond counting the number of conditions. This paper aims to identify clusters of MLTCs in different age groups and associated risks of adverse health outcomes and service use.

Methods

Latent class analysis was used to identify MLTCs clusters in different age groups in three cohorts: Secure Anonymised Information Linkage Databank (SAIL) (n = 1,825,289), UK Biobank (n = 502,363), and the UK Household Longitudinal Study (UKHLS) (n = 49,186). Incidence rate ratios (IRR) for MLTC clusters were computed for: all-cause mortality, hospitalisations, and general practice (GP) use over 10 years, using <2 MLTCs as reference. Information on health outcomes and service use were extracted for a ten year follow up period (between 01st Jan 2010 and 31st Dec 2019 for UK Biobank and UKHLS, and between 01st Jan 2011 and 31st Dec 2020 for SAIL).

Findings

Clustering MLTCs produced largely similar results across different age groups and cohorts. MLTC clusters had distinct associations with health outcomes and service use after accounting for LTC counts, in fully adjusted models. The largest associations with mortality, hospitalisations and GP use in SAIL were observed for the "Pain+" cluster in the age-group 18-36 years (mortality IRR = 4.47, hospitalisation IRR = 1.84; GP use IRR = 2.87) and the "Hypertension, Diabetes & Heart disease" cluster in the age-group 37-54 years (mortality IRR = 4.52, hospitalisation IRR = 1.53, GP use IRR = 2.36). In UK Biobank, the "Cancer, Thyroid disease & Rheumatoid arthritis" cluster in the age group 37-54 years had the largest association with mortality (IRR = 2.47). Cardiometabolic clusters across all age groups, pain/mental health clusters in younger groups, and cancer and pulmonary related clusters in older age groups had higher risk for all outcomes. In UKHLS, MLTC clusters were not significantly associated with higher risk of adverse outcomes, except for the hospitalisation in the age-group 18-36 years.

Interpretation

Personalising care around MLTC clusters that have higher risk of adverse outcomes may have important implications for practice (in relation to secondary prevention), policy (with allocation of health care resources), and research (intervention development and targeting), for people living with MLTCs.

Funding

This study was funded by the National Institute for Health and Care Research (NIHR; Personalised Exercise-Rehabilitation FOR people with Multiple long-term conditions (multimorbidity)-NIHR202020).

Relationship between 2nd-generation angiotensin receptor blockers and the risk of hypotension in COVID-19 patients admitted to hospital

It has not yet been established whether angiotensin II receptor blockers (ARB), statins, and multiple drugs affect the severity of COVID-19. Therefore, we herein performed an observational study on the effects of 1st- and 2nd-generation ARB, statins, and multiple drugs, on COVID-19 in patients admitted to 15 Japanese medical facilities. The results obtained showed that ARB, statins, and multiple drugs were not associated with the primary outcome (odds ratio: 1.040, 95% confidence interval: 0.688-0.571; 0.696, 0.439-1.103; 1.056, 0.941-1.185, respectively), each component of the primary outcome (in-hospital death, ventilator support, extracorporeal membrane oxygenation support, and admission to the intensive care unit), or the secondary outcomes (oxygen administration, disturbed consciousness, and hypotension, defined as systolic blood pressure ≤90 mmHg). ARB were divided into 1st- and 2nd-generations based on their approval for use (before 2000 and after 2001), with the former consisting of losartan, candesartan, and valsartan, and the latter of telmisartan, olmesartan, irbesartan, and azilsartan. The difference of ARB generation was not associated with the primary outcome (odds ratio with 2nd-generation ARB relative to 1st-generation ARB: 1.257, 95% confidence interval: 0.613-2.574). The odd ratio for a hypotension as one of the secondary outcomes with 2nd-generation ARB was 1.754 (95% confidence interval: 1.745-1.763) relative to 1st-generation ARB. These results suggest that patients taking 2nd-generation ARB may be at a higher risk of hypotension than those taking 1st-generation ARB and also that careful observations are needed. Further studies are continuously needed to support decisions to adjust medications for co-morbidities.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Correlation of cardiometabolic index and sarcopenia with cardiometabolic multimorbidity in middle-aged and older adult: a prospective study

Background

Research has demonstrated that sarcopenia and visceral obesity are significant risk factors for chronic disease in middle-aged and older adults. However, the relationship between sarcopenia, the cardiac metabolic index (CMI), a novel measure of visceral obesity, and cardiometabolic multimorbidity (CMM) remains unclear. In this study, data from the China Longitudinal Study of Health and Retirement (CHARLS) were analyzed to investigate the association between sarcopenia and CMI with CMM in the middle-aged and older adult population.

Methods

The study included 4,959 participants aged 45 and over. Sarcopenia was defined using the criteria of the Asian Sarcopenia Working Group 2019. CMM is defined as having two or more of the following conditions: physician-diagnosed heart disease, diabetes, stroke, and/or hypertension. CMI was calculated using the formula: CMI = (TG/HDL-C) × WHtR. To explore the association between CMI and sarcopenia and CMM, cox proportional risk regression models were used.

Results

The median age of all participants was 57 years, with 47.1% being male. Over the 8-year follow-up, 1,362 individuals developed CMM. The incidence of CMM was 8.7/1,000 person-years in the group without sarcopenia or high CMI, 17.37/1,000 person-years in those with high CMI, 14.22/1,000 person-years in the sarcopenia group, and 22.34/1,000 person-years in the group with both conditions. After adjusting for covariates, the group with both sarcopenia and high CMI had a significantly increased risk of CMM (HR 2.48, 95% CI 1.12-5.51) and heart disease (HR 2.04, 95% CI 1.05-3.98). Among those over 65 years, sarcopenia was discovered to be associated with an increased risk of CMM [HR (95% CI: 4.83 (1.22, 19.06)]. The risk of CMM was further increased to 7.31-fold (95% CI:1.72, 31.15) when combined with high CMI.

Conclusions

The combination of sarcopenia and high CMI is associated with an increased risk of developing CMM. Early identification and intervention of sarcopenia and CMI not only enable the development of targeted therapeutic strategies but also provide potential opportunities to reduce the morbidity and mortality of CMM.

Temporal change in multimorbidity prevalence, clustering patterns, and the association with mortality: findings from the China Kadoorie Biobank study in Jiangsu Province

Objectives

The characteristics of multimorbidity in the Chinese population are currently unclear. We aimed to determine the temporal change in multimorbidity prevalence, clustering patterns, and the association of multimorbidity with mortality from all causes and four major chronic diseases.

Methods

This study analyzed data from the China Kadoorie Biobank study performed in Wuzhong District, Jiangsu Province. A total of 53,269 participants aged 30-79 years were recruited between 2004 and 2008. New diagnoses of 15 chronic diseases and death events were collected during the mean follow-up of 10.9 years. Yule's Q cluster analysis method was used to determine the clustering patterns of multimorbidity. A Cox proportional hazards model was used to estimate the associations of multimorbidity with mortalities.

Results

The overall multimorbidity prevalence rate was 21.1% at baseline and 27.7% at the end of follow-up. Multimorbidity increased more rapidly during the follow-up in individuals who had a higher risk at baseline. Three main multimorbidity patterns were identified: (i) cardiometabolic multimorbidity (diabetes, coronary heart disease, stroke, and hypertension), (ii) respiratory multimorbidity (tuberculosis, asthma, and chronic obstructive pulmonary disease), and (iii) mental, kidney and arthritis multimorbidity (neurasthenia, psychiatric disorders, chronic kidney disease, and rheumatoid arthritis). There were 3,433 deaths during the follow-up. The mortality risk increased by 24% with each additional disease [hazard ratio (HR) = 1.24, 95% confidence interval (CI) = 1.20-1.29]. Compared with those without multimorbidity at baseline, both cardiometabolic multimorbidity and respiratory multimorbidity were associated with increased mortality from all causes and four major chronic diseases. Cardiometabolic multimorbidity was additionally associated with mortality from cardiovascular diseases and diabetes, with HRs of 2.64 (95% CI = 2.19-3.19) and 28.19 (95% CI = 14.85-53.51), respectively. Respiratory multimorbidity was associated with respiratory disease mortality, with an HR of 9.76 (95% CI = 6.22-15.31).

Conclusion

The prevalence of multimorbidity has increased substantially over the past decade. This study has revealed that cardiometabolic multimorbidity and respiratory multimorbidity have significantly increased mortality rates. These findings indicate the need to consider high-risk populations and to provide local evidence for intervention strategies and health management in economically developed regions.

Personalised Exercise-Rehabilitation FOR people with Multiple long-term conditions (PERFORM): protocol for a randomised feasibility trial

INTRODUCTION

Personalised Exercise-Rehabilitation FOR people with Multiple long-term conditions (PERFORM) is a research programme that seeks to develop and evaluate a comprehensive exercise-based rehabilitation intervention designed for people with multimorbidity, the presence of multiple long-term conditions (MLTCs). This paper describes the protocol for a randomised trial to assess the feasibility and acceptability of the PERFORM intervention, study design and processes.

METHODS AND ANALYSIS

A multicentre, parallel two-group randomised trial with individual 2:1 allocation to the PERFORM exercise-based intervention plus usual care (intervention) or usual care alone (control). The primary outcome of this feasibility trial will be to assess whether prespecified progression criteria (recruitment, retention, intervention adherence) are met to progress to the full randomised trial. The trial will be conducted across three UK sites and 60 people with MLTCs, defined as two or more LTCs, with at least one having evidence of the beneficial effect of exercise. The PERFORM intervention comprises an 8-week (twice a week for 6 weeks and once a week for 2 weeks) supervised rehabilitation programme of personalised exercise training and self-management education delivered by trained healthcare professionals followed by two maintenance sessions. Trial participants will be recruited over a 4.5-month period, and outcomes assessed at baseline (prerandomisation) and 3 months postrandomisation and include health-related quality of life, psychological well-being, symptom burden, frailty, exercise capacity, physical activity, sleep, cognition and serious adverse events. A mixed-methods process evaluation will assess acceptability, feasibility and fidelity of intervention delivery and feasibility of trial processes. An economic evaluation will assess the feasibility of data collection and estimate the costs of the PERFORM intervention.

ETHICS AND DISSEMINATION

The trial has been given favourable opinion by the West Midlands, Edgbaston Research Ethics Service (Ref: 23/WM/0057). Participants will be asked to give full, written consent to take part by trained researchers. Findings will be disseminated via journals, presentations and targeted communications to clinicians, commissioners, service users and patients and the public.

TRIAL REGISTRATION NUMBER

ISRCTN68786622.

PROTOCOL VERSION

2.0 (16 May 2023).

Developing SysteMatic: Prevention, precision and equity by design for people living with multiple long-term conditions

Background

The number of individuals living with multiple (≥2) long term conditions (MLTCs) is a growing global challenge. People with MLTCs experience reduced life expectancy, complex healthcare needs, higher healthcare utilisation, increased burden of treatment, poorer quality of life and higher mortality. Evolving technologies including artificial intelligence (AI) could address some of these challenges by enabling more preventive and better integrated care, however, they may also exacerbate inequities.

Objective

We aim to deliver an equity focused, action-ready plan for transforming MLTC prevention and care, co-designed by people with lived experience of MLTCs and delivered through an Innovation Hub: SysteMatic.

Design

Our Hub is being co-designed by people with lived experience of MLTCs, practitioners, academics and industry partners in Liverpool and Glasgow, UK. This work builds on research into mental-physical health interdependence across the life-course, and on mobilisation of large-scale quantitative data and technology validation in health and care systems serving deprived populations in Glasgow and Liverpool. We work with 3 population segments: 1) Children & Families: facing psychosocial and environmental challenges with lifetime impacts; 2). Working Life: people with poorly integrated mental, physical and social care; and 3) Pre-Frailty: older people with MLTCs. We aim to understand their experiences and in parallel look at routinely collected health data on people with MLTCs to help us identify targets for intervention. We are co-identifying opportunities for systems transformation with our patient partners, healthcare professionals and through discussion with companies and public-sector organisations. We are co-defining 3/5/7-year MLTC innovation/transition targets and sustainable learning approaches.

Discussion

SysteMatic will deliver an actionable MLTC Innovation Hub strategic plan, with investment from the UK National Health Service, civic health and care partners, universities, and industry, enabling feedback of well-translated, patient and public prioritised problems into the engineering, physical, health and social sciences to underpin future equitable innovation delivery.

Ethnic differences in multimorbidity after accounting for social-economic factors, findings from The Health Survey for England

BACKGROUND

Social-economic factors and health behaviours may be driving variation in ethnic health inequalities in multimorbidity including among distinct ethnic groups.

METHODS

Using the cross-sectional nationally representative Health Surveys for England 2011-18 (N = 54 438, aged 16+), we performed multivariable logistic regression on the odds of having general multimorbidity (≥2 longstanding conditions) by ethnicity [British White (reference group), White Irish, Other White, Indian, Pakistani, Bangladeshi, Chinese, African, Caribbean, White mixed, Other Mixed], adjusting for age, sex, education, area deprivation, obesity, smoking status and survey year. This was repeated for cardiovascular multimorbidity (N = 37 148, aged 40+: having ≥2 of the following: self-reported diabetes, hypertension, heart attack or stroke) and multiple cardiometabolic risk biomarkers (HbA1c ≥6.5%, raised blood pressure, total cholesterol ≥5mmol/L).

RESULTS

Twenty percent of adults had general multimorbidity. In fully adjusted models, compared with the White British majority, Other White [odds ratio (OR) = 0.63; 95% confidence interval (CI) 0.53-0.74], Chinese (OR = 0.58, 95% CI 0.36-0.93) and African adults (OR = 0.54, 95% CI 0.42-0.69), had lower odds of general multimorbidity. Among adults aged 40+, Pakistani (OR = 1.27, 95% CI 0.97-1.66; P = 0.080) and Bangladeshi (OR = 1.75, 95% CI 1.16-2.65) had increased odds, and African adults had decreased odds (OR = 0.63, 95% CI 0.47-0.83) of general multimorbidity. Risk of cardiovascular multimorbidity was higher among Indian (OR = 3.31, 95% CI 2.56-4.28), Pakistani (OR = 3.48, 95% CI 2.52-4.80), Bangladeshi (OR = 3.67, 95% CI 1.98-6.78), African (OR = 1.61, 95% CI 1.05-2.47), Caribbean (OR = 2.18, 95% CI 1.59-2.99) and White mixed (OR = 1.98, 95% CI 1.14-3.44) adults. Indian adults were also at risk of having multiple cardiometabolic risk biomarkers.

CONCLUSION

Ethnic inequalities in multimorbidity are independent of social-economic factors. Ethnic minority groups are particularly at risk of cardiovascular multimorbidity, which may be exacerbated by poorer management of cardiometabolic risk requiring further investigation.

Multimorbidity and 11-year mortality in adults: a prospective analysis using the Chilean National Health Survey

Research on morbidity and mortality often emphasizes individual diseases over the cumulative effects of multimorbidity, especially in low- and middle-income countries. This study aimed to analyze the association between multimorbidity and all-cause mortality in a representative sample of the Chilean population. This longitudinal study used data from 3701 subjects aged ≥15 years who participated in the Chilean National Health Survey conducted between 2009 and 2010. We included 16 self-reported highly prevalent morbidities. All-cause mortality data from an 11-year follow-up were collected from the Chilean Civil Registry. The Cox proportional hazard model, adjusted for confounders, determined the association between multimorbidity categories and all-cause mortality. Of the total sample, 24.3% reported no morbidity, while 50.4% two or more. After adjustment, participants with four or more morbidities had a 1.66 times higher mortality risk [95% confidence interval (CI): 1.03-2.67] than those without morbidities. The mortality risk increased by 10% for each additional morbidity [HR: 1.09 (CI: 1.04-1.16)]. Multimorbidity was common in the Chilean population and increased the mortality risk, which greatly challenges the health system to provide an integral and coordinated approach to healthcare.

Personalised lung cancer risk stratification and lung cancer screening: do general practice electronic medical records have a role?

BACKGROUND

In the United Kingdom (UK), cancer screening invitations are based on general practice (GP) registrations. We hypothesize that GP electronic medical records (EMR) can be utilised to calculate a lung cancer risk score with good accuracy/clinical utility.

METHODS

The development cohort was Secure Anonymised Information Linkage-SAIL (2.3 million GP EMR) and the validation cohort was UK Biobank-UKB (N = 211,597 with GP-EMR availability). Fast backward method was applied for variable selection and area under the curve (AUC) evaluated discrimination.

RESULTS

Age 55-75 were included (SAIL: N = 574,196; UKB: N = 137,918). Six-year lung cancer incidence was 1.1% (6430) in SAIL and 0.48% (656) in UKB. The final model included 17/56 variables in SAIL for the EMR-derived score: age, sex, socioeconomic status, smoking status, family history, body mass index (BMI), BMI:smoking interaction, alcohol misuse, chronic obstructive pulmonary disease, coronary heart disease, dementia, hypertension, painful condition, stroke, peripheral vascular disease and history of previous cancer and previous pneumonia. The GP-EMR-derived score had AUC of 80.4% in SAIL and 74.4% in UKB and outperformed ever-smoked criteria (currently the first step in UK lung cancer screening pilots).

DISCUSSION

A GP-EMR-derived score may have a role in UK lung cancer screening by accurately targeting high-risk individuals without requiring patient contact.

Social connection and mortality in UK Biobank: a prospective cohort analysis

BACKGROUND

Components of social connection are associated with mortality, but research examining their independent and combined effects in the same dataset is lacking. This study aimed to examine the independent and combined associations between functional and structural components of social connection and mortality.

METHODS

Analysis of 458,146 participants with full data from the UK Biobank cohort linked to mortality registers. Social connection was assessed using two functional (frequency of ability to confide in someone close and often feeling lonely) and three structural (frequency of friends/family visits, weekly group activities, and living alone) component measures. Cox proportional hazard models were used to examine the associations with all-cause and cardiovascular disease (CVD) mortality.

RESULTS

Over a median of 12.6 years (IQR 11.9-13.3) follow-up, 33,135 (7.2%) participants died, including 5112 (1.1%) CVD deaths. All social connection measures were independently associated with both outcomes. Friends/family visit frequencies < monthly were associated with a higher risk of mortality indicating a threshold effect. There were interactions between living alone and friends/family visits and between living alone and weekly group activity. For example, compared with daily friends/family visits-not living alone, there was higher all-cause mortality for daily visits-living alone (HR 1.19 [95% CI 1.12-1.26]), for never having visits-not living alone (1.33 [1.22-1.46]), and for never having visits-living alone (1.77 [1.61-1.95]). Never having friends/family visits whilst living alone potentially counteracted benefits from other components as mortality risks were highest for those reporting both never having visits and living alone regardless of weekly group activity or functional components. When all measures were combined into overall functional and structural components, there was an interaction between components: compared with participants defined as not isolated by both components, those considered isolated by both components had higher CVD mortality (HR 1.63 [1.51-1.76]) than each component alone (functional isolation 1.17 [1.06-1.29]; structural isolation 1.27 [1.18-1.36]).

CONCLUSIONS

This work suggests (1) a potential threshold effect for friends/family visits, (2) that those who live alone with additional concurrent markers of structural isolation may represent a high-risk population, (3) that beneficial associations for some types of social connection might not be felt when other types of social connection are absent, and (4) considering both functional and structural components of social connection may help to identify the most isolated in society.

Severe and common mental disorders and risk of emergency hospital admissions for ambulatory care sensitive conditions among the UK Biobank cohort

BACKGROUND

People with mental disorders have worse physical health compared with the general population, which could be attributable to receiving poorer quality healthcare.

AIMS

To examine the relationship between severe and common mental disorders and risk of emergency hospital admissions for ambulatory care sensitive conditions (ACSCs), and factors associated with increased risk.

METHOD

Baseline data for England (N = 445 814) were taken from UK Biobank, which recruited participants aged 37-73 years during 2006-2010, and linked to hospital admission records up to 31 December 2019. Participants were grouped into those with a history of either schizophrenia, bipolar disorder, depression or anxiety, or no mental disorder. Survival analysis was used to assess the risk of hospital admission for ACSCs among those with mental disorders compared with those without, adjusting for factors in different domains (sociodemographic, socioeconomic, health and biomarkers, health-related behaviours, social isolation and psychological).

RESULTS

People with schizophrenia had the highest (unadjusted) risk of hospital admission for ACSCs compared with those with no mental disorder (hazard ratio 4.40, 95% CI 4.04-4.80). People with bipolar disorder (hazard ratio 2.48, 95% CI 2.28-2.69) and depression or anxiety (hazard ratio 1.76, 95% CI 1.73-1.80) also had higher risk. Associations were more conservative when including all admissions, as opposed to first admissions only. The observed associations persisted after adjusting for a range of factors.

CONCLUSIONS

People with severe mental disorders have the highest risk of preventable hospital admissions. Ensuring people with mental disorders receive adequate ambulatory care is essential to reduce the large health inequalities they experience.

Childhood adversity and COVID-19 outcomes in the UK Biobank

OBJECTIVES

This study aims to investigate the association between childhood adversity and COVID-19-related hospitalisation and COVID-19-related mortality in the UK Biobank.

DESIGN

Cohort study.

SETTING

UK.

PARTICIPANTS

151 200 participants in the UK Biobank cohort who had completed the Childhood Trauma Screen were alive at the start of the COVID-19 pandemic (January 2020) and were still active in the UK Biobank when hospitalisation and mortality data were most recently updated (November 2021).

MAIN OUTCOME MEASURES

COVID-19-related hospitalisation and COVID-19-related mortality.

RESULTS

Higher self-reports of childhood adversity were related to greater likelihood of COVID-19-related hospitalisation in all statistical models. In models adjusted for age, ethnicity and sex, childhood adversity was associated with an odds ratio (OR) of 1.227 of hospitalisation (95% CI 1.153 to 1.306, childhood adversity z=6.49, p<0.005) and an OR of 1.25 of a COVID-19-related death (95% CI 1.11 to 1.424, childhood adversity z=3.5, p<0.005). Adjustment for potential confounds attenuated these associations, although associations remained statistically significant.

CONCLUSIONS

Childhood adversity was significantly associated with COVID-19-related hospitalisation and COVID-19-related mortality after adjusting for sociodemographic and health confounders. Further research is needed to clarify the biological and psychosocial processes underlying these associations to inform public health intervention and prevention strategies to minimise COVID-19 disparities.

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

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

Cardiometabolic risk in people under 40 years with severe mental illness: reading between the guidelines

People with severe mental illness (SMI) have a shorter life expectancy than the rest of the population. Multimorbidity and poorer physical health contribute to this health inequality. Cardiometabolic multimorbidity confers a significant mortality risk in this population. Multimorbidity is not restricted to older people and people with SMI present with multimorbidity earlier in life. Despite this, most screening, prevention and treatment strategies target older people. People under 40 years with SMI are underserved by current guidelines for cardiovascular risk assessment and reduction. Research is needed to develop and implement interventions to reduce cardiometabolic risk in this population.

Association of ultra-processed food consumption with incident depression and anxiety: a population-based cohort study

Background: Global ultra-processed food (UPF) consumption has risen rapidly. The development and prognosis of depression and anxiety remain unclarified. Herein, we aimed to examine the association between UPF consumption and the incidence and progression trajectory of depression and anxiety. Methods: In our study, participants were recruited between 2006 and 2010. UPF consumption was expressed as UPF servings, energy ratio, and weight ratio. The relationships between UPF consumption and depression or anxiety were assessed using the Cox proportional hazards model. Multi-state models were used to explore the association between UPF consumption and the risks of all transitions from a healthy state to depression or anxiety and then to all-cause mortality. Results: Among the 183 474 participants, 5453 were diagnosed with depression and 6763 with anxiety during the follow-up of 13.1 years. The participants in the highest quartile (Q4) of UPF servings, energy ratio, and weight ratio had an increased risk of depression compared to those in the lowest quartile (Q1), with hazard ratios (HRs) and 95% confidence intervals [CIs] of 1.22 (1.13-1.31), 1.13 (1.05-1.22), and 1.26 (1.17-1.36), respectively. Similarly, participants in Q4 of UPF consumption had a higher risk of anxiety, with HRs (95% CIs) of 1.13 (1.06-1.21), 1.13 (1.05-1.21), and 1.11 (1.04-1.19), compared to those in Q1. The study also found a significant association between UPF consumption and all-cause mortality, which disappeared for participants with depression or anxiety. Conclusions: Our findings revealed that UPF consumption is associated with depression or anxiety.

Global perspectives on heart disease rehabilitation and secondary prevention: a scientific statement from the Association of Cardiovascular Nursing and Allied Professions, European Association of Preventive Cardiology, and International Council of Cardiovascular Prevention and Rehabilitation

Cardiovascular disease is a leading cause of death, morbidity, disability, and reduced health-related quality of life, as well as economic burden worldwide, with some 80% of disease burden occurring in the low- and middle-income country (LMIC) settings. With increasing numbers of people living longer with symptomatic disease, the effectiveness and accessibility of secondary preventative and rehabilitative health services have never been more important. Whilst LMICs experience the highest prevalence and mortality rates, the global approach to secondary prevention and cardiac rehabilitation, which mitigates this burden, has traditionally been driven from clinical guidelines emanating from high-income settings. This state-of-the art review provides a contemporary global perspective on cardiac rehabilitation and secondary prevention, contrasting the challenges of and opportunities for high vs. lower income settings. Actionable solutions to overcome system, clinician, programme, and patient level barriers to cardiac rehabilitation access in LMICs are provided.

Effects of multimorbidity coexistence on the risk of mortality in the older adult population in China

Background

Multimorbidity coexistence is a serious public health issue affecting a significant number of older adults worldwide. However, associations between multimorbidity and mortality are rarely studied in China. We assessed the effects of multimorbidity coexistence on mortality among a nationwide sample of older adults from China.

Objective

We analyzed 10-year (2008-2018) longitudinal data of 12,337 individuals who took part in China, a nationwide survey of people aged 65 years and above. We used the Cox proportional hazard model to determine the effects of multimorbidity on the all-cause mortality risk. We also examined mortality risk between sex and age obtained through differential analysis.

Results

At baseline, 30.2, 29.9, and 39.9% of participants had 0, 1, and 2 or more diseases, respectively. The cumulative follow-up of this study was 27,428 person-years (median follow-up = 2.7 years; range, 0.01-11.3 years), with 8297 deaths. The HRs (95% CIs) for all-cause mortality in participants with 1, and 2 or more conditions compared with those with none were 1.04 (0.98, 1.10) and 1.12 (1.06, 1.18), respectively. The heterogeneity analysis indicated that, the mortality risk for 80-94 years and 95-104 years group with multimorbidity coexistence is 1.12 (1.05-1.21) and 1.11 (1.01-1.23), respectively, but the mortality risk for 65-79 years group with multimorbidity coexistence was not statistically significant. The heterogeneity analysis indicated that, the mortality risk for men and women in older adults with multimorbidity coexistence is 1.15 (1.06, 1.25) and 1.08 (1.01, 1.17), respectively.

Conclusion

Multimorbidity coexistence is associated with an increase in an increased risk of death in older individuals, with the effect being relatively significant in those aged 80-94 years.

Identifying the potential causal role of insomnia symptoms on 11,409 health-related outcomes: a phenome-wide Mendelian randomisation analysis in UK Biobank

BACKGROUND

Insomnia symptoms are widespread in the population and might have effects on many chronic conditions and their risk factors but previous research has focused on select hypothesised associations/effects rather than taking a systematic hypothesis-free approach across many health outcomes.

METHODS

We performed a Mendelian randomisation (MR) phenome-wide association study (PheWAS) in 336,975 unrelated white-British UK Biobank participants. Self-reported insomnia symptoms were instrumented by a genetic risk score (GRS) created from 129 single-nucleotide polymorphisms (SNPs). A total of 11,409 outcomes from UK Biobank were extracted and processed by an automated pipeline (PHESANT) for the MR-PheWAS. Potential causal effects (those passing a Bonferroni-corrected significance threshold) were followed up with two-sample MR in MR-Base, where possible.

RESULTS

Four hundred thirty-seven potential causal effects of insomnia symptoms were observed for a diverse range of outcomes, including anxiety, depression, pain, body composition, respiratory, musculoskeletal and cardiovascular traits. We were able to undertake two-sample MR for 71 of these 437 and found evidence of causal effects (with directionally concordant effect estimates across main and sensitivity analyses) for 30 of these. These included novel findings (by which we mean not extensively explored in conventional observational studies and not previously explored using MR based on a systematic search) of an adverse effect on risk of spondylosis (OR [95%CI] = 1.55 [1.33, 1.81]) and bronchitis (OR [95%CI] = 1.12 [1.03, 1.22]), among others.

CONCLUSIONS

Insomnia symptoms potentially cause a wide range of adverse health-related outcomes and behaviours. This has implications for developing interventions to prevent and treat a number of diseases in order to reduce multimorbidity and associated polypharmacy.

Association between multimorbidity patterns and incident depression among older adults in Taiwan: the role of social participation

Background

Previous research has found different multimorbidity patterns that negatively affects health outcomes of older adults. However, there is scarce evidence, especially on the role of social participation in the association between multimorbidity patterns and depression. Our study aimed to explore the relationship between multimorbidity patterns and depression among older adults in Taiwan, including the social participation effect on the different multimorbidity patterns.

Methods

Data were retracted from the Taiwan longitudinal study on ageing (TLSA) for this population-based cohort study. 1,975 older adults (age > 50) were included and were followed up from 1996 to 2011. We used latent class analysis to determine participants’ multimorbidity patterns in 1996, whereas their incident depression was determined in 2011 by CES-D. Multivariable logistic regression was used to analyse the relationship between multimorbidity patterns and depression.

Results

The participants’ average age was 62.1 years in 1996. Four multimorbidity patterns were discovered through latent class analysis, as follows: (1) Cardiometabolic group (n = 93), (2) Arthritis-cataract group (n = 105), (3) Multimorbidity group (n = 128) and (4) Relatively healthy group (n = 1649). Greater risk of incident depression was found among participants in the Multimorbidity group (OR: 1.62; 95% CI: 1.02–2.58) than the Relatively healthy group after the multivariable analysis. Compare to participants in the relatively healthy group with social participation, participants in the arthritis-cataract group without social participation (OR: 2.22, 95% CI: 1.03–4.78) and the multimorbidity group without social participation (OR: 2.21, 95% CI: 1.14–4.30) had significantly increased risk of having depression.

Conclusion

Distinct multimorbidity patterns among older adults in Taiwan are linked with the incident depression during later life, and social participation functioned as a protective factor.

Socioeconomic gradient in mortality of working age and older adults with multiple long-term conditions in England and Ontario, Canada

BACKGROUND

There is currently mixed evidence on the influence of long-term conditions and deprivation on mortality. We aimed to explore whether number of long-term conditions contribute to socioeconomic inequalities in mortality, whether the influence of number of conditions on mortality is consistent across socioeconomic groups and whether these associations vary by working age (18-64 years) and older adults (65 + years). We provide a cross-jurisdiction comparison between England and Ontario, by replicating the analysis using comparable representative datasets.

METHODS

Participants were randomly selected from Clinical Practice Research Datalink in England and health administrative data in Ontario. They were followed from 1 January 2015 to 31 December 2019 or death or deregistration. Number of conditions was counted at baseline. Deprivation was measured according to the participant's area of residence. Cox regression models were used to estimate hazards of mortality by number of conditions, deprivation and their interaction, with adjustment for age and sex and stratified between working age and older adults in England (N = 599,487) and Ontario (N = 594,546).

FINDINGS

There is a deprivation gradient in mortality between those living in the most deprived areas compared to the least deprived areas in England and Ontario. Number of conditions at baseline was associated with increasing mortality. The association was stronger in working age compared with older adults respectively in England (HR = 1.60, 95% CI 1.56,1.64 and HR = 1.26, 95% CI 1.25,1.27) and Ontario (HR = 1.69, 95% CI 1.66,1.72 and HR = 1.39, 95% CI 1.38,1.40). Number of conditions moderated the socioeconomic gradient in mortality: a shallower gradient was seen for persons with more long-term conditions.

CONCLUSIONS

Number of conditions contributes to higher mortality rate and socioeconomic inequalities in mortality in England and Ontario. Current health care systems are fragmented and do not compensate for socioeconomic disadvantages, contributing to poor outcomes particularly for those managing multiple long-term conditions. Further work should identify how health systems can better support patients and clinicians who are working to prevent the development and improve the management of multiple long-term conditions, especially for individuals living in socioeconomically deprived areas.

Multimorbidity in People with Epilepsy

Multimorbidity is an emerging priority in healthcare due to associations with the ageing population, frailty, polypharmacy, health and social care demands. It affects 60-70% of adults and 80% of children with epilepsy. Neurodevelopmental conditions are commonly seen in children with epilepsy, while cancer, cardiovascular and neurodegenerative conditions often afflict older people with epilepsy. Mental health problems are common across the lifespan. Genetic, environmental, social and lifestyle factors contribute to multimorbidity and its consequences. Multimorbid people with epilepsy (PWE) are at higher risk of depression and suicide, premature death, suffer lower health-related quality of life, and require more hospital admissions and health care costs. The best management of multimorbid PWE requires a paradigm shift from the traditional single disease-single comorbidity approach and a refocus on a person-centred approach. Improvements in health care must be informed by assessing the burden of multimorbidity associated with epilepsy, delineating disease clusters, and measuring the effects on health outcomes.