Journal of multimorbidity and comorbidity最新文献

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.

[This corrects the article DOI: 10.1177/26335565241258851.].

Background: Multimorbidity is rising in low-and middle-income countries such as Nepal, yet the research has not gained pace in this field. We aimed to systematically review the existing multimorbidity literature in Nepal and estimate the prevalence and map its risk factors and consequences.

Methods: We reviewed data collated from PubMed, Embase and CINAHL by including original studies that reported prevalence of multimorbidity in Nepal. The quality of included studies was assessed using the Appraisal Tool for Cross-sectional Studies. The summary of the review is presented both qualitatively as well as through meta-analysis to give pooled prevalence. We prospectively registered in PROSPERO (CRD42024499598).

Results: We identified 423 studies out of which seven were included in this review. All studies were conducted in a community setting except one which was hospital based. The prevalence reported across various studies ranged from 13.96% to 70.1%. The pooled prevalence of multimorbidity was observed to be 25.05% (95% CI: 16.99 to 34.09). The number of conditions used to assess multimorbidity ranged from four to nine. The major risk factors identified were increasing age, urban residence, and lower literacy rates.

Conclusion: A wide variance in the prevalence of multimorbidity was observed. Moreover, multimorbidity assessment tool/conditions considered for assessing multimorbidity were heterogeneous.

Objective: This investigation examines burden of comorbidity measured by the Charlson Comorbidity Index (CCI) and Elixhauser Comorbidity Index (ECI) among inpatients based on age, sex, and race.

Methods: Cross-sectional analysis of 2012-2018 US NIS datasets. Participants were inpatients 55y+. ICD-9/10 codes for admitting diagnoses were used to calculate disease burden using the CCI and ECI. Unweighted mean CCI and ECI scores were compared across demographic variables.

Results: An increase in mean CCI and ECI scores across age, sex, and races (p<.001) was identified. Compared to the youngest age group (55-59y), all age groups had higher mean CCI and ECI adjusting for time (p<.001). Increases were greatest in older age groups until age 80-84 for CCI and 85-89 for ECI. The female group had lower CCI adjusting for time (p<.001) compared to males. There was no difference between sex groups in mean ECI (p=.409). Compared with the White group, all other race groups had higher mean CCI adjusting for time (p<.001). Black inpatients had the highest CCI followed by Native American inpatients. Findings were similar for ECI, but with no difference between Hispanic and White groups (p=.434).

Conclusions: Growing multimorbidity burden among adult inpatients across age, sex, and race supports the continued need for programs for preventing and reducing multimorbidity, especially among communities that experience health inequity including older, Black, and Native American patients.

Objectives: This is the first systematic review and meta-analysis of the prevalence of multimorbidity, its risk factors including socioeconomic factors, and the consequences of multimorbidity on health systems and broader society in India.

Methods: A systematic review of both published and grey literature from five databases (Medline, Embase, EBSCO, Scopus, and ProQuest) was conducted including original studies documenting prevalence or patient outcomes associated with multimorbidity among adults in India. We excluded studies that did not explicitly mention multimorbidity. Three independent reviewers did primary screening based on titles and abstracts followed by full-text review for potential eligibility. The risk of bias was independently assessed by two reviewers following the Appraisal Tool for Cross-Sectional Studies. We presented both qualitative and quantitative (through meta-analysis) summaries of the evidence. The protocol for this study was prospectively registered with PROSPERO (CRD42021257281).

Results: The review identified 5442 articles out of which 35 articles were finally included in this study. Twenty-three studies were based on the primary data while 12 used secondary data. Eleven studies were conducted in hospital/primary care setting while 24 were community-based. The pooled prevalence of multimorbidity based on (n=19) studies included for meta-analysis was 20% (95% CI: 19% to 20%). The most frequent outcomes were increased healthcare utilization, reduced health-related quality of life, physical and mental functioning.

Conclusion: We identified a wide variance in the magnitude of multimorbidity across age groups and regions with most of the studies from eastern India. Nation-wide studies, studies on vulnerable populations and interventions are warranted.

Background: The co-occurrence of chronic diseases and acute infectious events exacerbates disability and diminishes quality of life, yet research in Low- and Middle-Income countries is scarce. We aimed to investigate the relationship between infectious events and multimorbidity in resource-constrained settings.

Methods: We conducted a sequential mixed-method study in Lima and Tumbes, Peru, with participants having multimorbidity from the CRONICAS Cohort Study. They completed a questionnaire on the occurrence, treatment, and health-seeking behaviour related to acute infectious events. Qualitative interviews explored the perceptions and links between multimorbidity and acute infectious events for a subgroup of participants.

Findings: Among individuals with multimorbidity, low awareness of chronic conditions and poor medication adherence. The cumulative incidence for respiratory and gastrointestinal infections, the most reported acute conditions, was 2.0 [95%CI: 1.8-2.2] and 1.6 [1.2-1.9] events per person per year, respectively. Individuals with cancer (6.4 [1.6-11.2] events per person per year) or gastrointestinal reflux (7.2 [4.4-10.1] events per person per year) reported higher cumulative incidence of infectious events than others, such as those with cardiovascular and metabolic conditions (5.2 [4.6-5.8] events per person per year). Those with three or more chronic conditions had a slightly higher cumulative incidence compared with individuals with two conditions (5.7 [4.4-7.0] vs 5.0 [4.4-5.6] events per person per year). Around 40% of individuals with multimorbidity sought healthcare assistance, while others chose drugstores or didn't seek help. Our qualitative analysis showed diverse perceptions among participants regarding the connections between chronic and acute conditions. Those who recognized a connection emphasized the challenges in managing these interactions.

Interpretation: Our study advances understanding of multimorbidity challenges in resource-limited settings, highlighting the impact of acute infections on patients' existing multimorbidity burden.

Background: Managing multimorbidity poses significant challenges for individuals, their families, and society due to issues with health information comprehension, communication with healthcare providers, and navigating the healthcare system. These challenges emphasise the critical need to prioritize individual and organisational health literacy. Multimorbidity is associated with a lack of social support for health; however, social networks and community dynamics can enhance health literacy. The "Co-designing municipal rehabilitation" (CURIA) project targets enhancing individual and organisational health literacy, and social networks for individuals with multimorbidity, with the overall aim of addressing health inequity through a collaborative local co-design process involving stakeholders.

Methods: The CURIA study employs a mixed-method approach that initially explores the health literacy experiences of individuals with multimorbidity participating in rehabilitation programs in selected Danish municipalities and the practices of professionals overseeing these programs. The subsequent co-design process will comprise individuals with multimorbidity, their relatives, municipalities, general practitioners, civil society, and knowledge institutions working together. This iterative and collaborative process involves tailoring and aligning health literacy needs with responsiveness within the context of local healthcare systems and developing supportive social networks.

Discussion: Given the increasing burden of multimorbidity, there is an urgent need to develop evidence-based practice for multimorbidity rehabilitation practices, developed in collaboration with municipalities and civil society. Emphasising self-care support for individuals, managing complex rehabilitation needs, and involving individuals in intervention prioritisation and customisation are crucial aspects addressed by CURIA to enhance health literacy and align municipal rehabilitation with identified needs.

Background: COVID-19's heavy toll on human health, and its concentration within specific at-risk groups including the socially vulnerable and individuals with comorbidities, has made it the focus of much syndemic discourse. Syndemic theory recognizes that social factors create the conditions that support the clustering of diseases and that these diseases interact in a manner that worsens health outcomes. Syndemics theory has helped to facilitate systems-level approaches to disease as a biosocial phenomenon and guide prevention and treatment efforts. Despite its recognized value, reviews of syndemics literature have noted frequent misuse of the concept limiting its potential in guiding appropriate interventions.

Objective: To review how the term 'syndemic' is defined and applied within peer-reviewed literature in relation to COVID-19.

Design: A scoping review of definitions within COVID-19 literature published between January 1, 2020 to May 15, 2023 was conducted. Searches took place across six databases: Academic Search Premier, CINAHL, JSTOR, MEDLINE/Pubmed, PsycINFO and Scopus. PRISMA-ScR guidelines were followed.

Results: Content analysis revealed that COVID-19 has varied clustered configurations of communicable-non-communicable diseases and novel communicable disease interactions. Spatial analysis was presented as a new strategy to evidence syndemic arrangements. However, syndemics continue to be regarded as universal, with continued misunderstanding and misapplication of the concept.

Conclusion: This review found that current applications of syndemics remain problematic. Recommendations are made on the design of syndemic studies. A syndemic framework offers an opportunity for systems-level thinking that considers the full complexity of human-disease interactions and is useful to inform future pandemic preparations and responses.

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

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

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

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

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

Background: Multimorbidity research has focused on the prevalence and consequences of multimorbidity in older populations. Less is known about the accumulation of chronic conditions earlier in the life course.

Methods: We identified patterns of longitudinal multimorbidity accumulation using 30 years of data from in-person exams, annual follow-ups, and adjudicated end-points among 4,945 participants of the Coronary Artery Risk Development in Young Adults (CARDIA) study. Chronic conditions included arthritis, asthma, atrial fibrillation, cancer, end stage renal disease, chronic obstructive pulmonary disease, coronary heart disease, diabetes, heart failure, hyperlipidemia, hypertension, and stroke. Trajectory patterns were identified using latent class growth curve models.

Results: Mean age (SD) at baseline (1985-6) was 24.9 (3.6), 55% were female, and 51% were Black. The median follow-up was 30 years (interquartile range 25-30). We identified six trajectory classes characterized by when conditions began to accumulate and the rapidity of accumulation: (1) early-fifties, slow, (2) mid-forties, fast, (3) mid-thirties, fast, (4) late-twenties, slow, (5) mid-twenties, slow, and (6) mid-twenties, fast. Compared with participants in the early-fifties, slow trajectory class, participants in mid-twenties, fast were more likely to be female, Black, and currently smoking and had a higher baseline mean waist circumference (83.6 vs. 75.6 cm) and BMI (27.0 vs. 23.4 kg/m²) and lower baseline physical activity (414.1 vs. 442.4 exercise units).

Conclusions: A life course approach that recognizes the heterogeneity in patterns of accumulation of chronic conditions from early adulthood into middle age could be helpful for identifying high risk subgroups and developing approaches to delay multimorbidity progression.