Multimorbidity is increasingly common among older adults in Sub-Saharan Africa (SSA), yet the role of social determinants in shaping its prevalence and outcomes remains underexplored.

This review aimed to (a) identify the prevalence, types, and patterns of multimorbidity among older adults in SSA; (b) examine the influence of social determinants such as income, education, healthcare access, and geographic location; (c) evaluate current approaches for prevention and management; and (d) propose directions for future research.

A systematic search of six databases (PubMed, EMBASE, PsycINFO, Google Scholar, CINAHL, and Global Index Medicus) was conducted to identify quantitative studies published between 2000 and 2024 on adults aged 50 and above. Of 841 records screened, 16 studies met inclusion criteria and passed quality appraisal. The review protocol was registered in PROSPERO (CRD42024607875).

Multimorbidity ranged from 5.4% in Botswana to 71% in Nigeria. Cardiometabolic conditions often co-occurred with infectious and mental disorders. Poverty and low education significantly increased risk (OR: 1.44–7.44). Rural residents faced limited healthcare access, while urban dwellers had higher risks from lifestyle factors. Obesity and food insecurity further heightened vulnerability, especially among women and older adults.

Findings indicate that social determinants critically shape multimorbidity risk and outcomes in SSA. Integrated care models, targeted interventions, and policies addressing structural inequalities are urgently needed. Future research should apply longitudinal and qualitative approaches to clarify causal pathways and inform context-sensitive strategies.

The European General Practitioners Research Network (EGPRN) designed and validated a comprehensive definition of multimorbidity using a systematic literature review and qualitative research throughout Europe. This survey assessed which criteria in the EGPRN concept of multimorbidity could detect decompensating patients in residential care within a primary care cohort at a six-month follow-up.

Family physicians included all multimorbid patients encountered in their residential care homes from July to December 2014. Inclusion criteria were those of the EGPRN definition of multimorbidity. Exclusion criteria were patients under legal protection and those unable to complete the 2-year follow-up. Decompensation was defined as the occurrence of death or hospitalization for more than seven days. Statistical analysis was undertaken with uni- and multi-variate analysis at a six-month follow-up using a combination of approaches including both automatic classification and expert decision. A multiple correspondence analysis and a hierarchical clustering on principal components confirmed the consistency of the results. Finally, a logistic regression was performed to identify and quantify risk factors for decompensation.

Findings: About 12 family physicians participated in the study. In the study, 64 patients were analyzed. On analyzing the characteristics of the participants, two statistically significant variables between the two groups (decompensation and Nothing To Report): pain (p = 0.004) and the use of psychotropic drugs (p = 0.019) were highlighted. The final model of the logistic regression showed pain as the main decompensation risk factor.

Action should be taken by the health teams and their physicians to prevent decompensation in patients in residential care who are experiencing pain.

The European General Practitioners Research Network (EGPRN) designed and validated a comprehensive definition of multimorbidity using a systematic literature review and qualitative research throughout Europe. Identification of risk factors for decompensation would be an interesting challenge for family physicians (FPs) in the management of multimorbid patients. The aim was to assess which items from the EGPRN’s definition of multimorbidity could identify outpatients at risk of decompensation at 24 months.

A cohort study. About 120 multimorbid patients from Western Brittany, France, were included by general practitioners between 2014 and 2015. The status “decompensation” (hospitalization of at least 7 days or death) or “nothing to report (NTR)” was collected at 24 months of follow-up.

At 24 months, there were 44 patients (36.6%) in the decompensation group. Two variables were significant risk factors for decompensation: the number of visits to the FP per year (HR = 1.06 [95% CI 1.03–1.10], P < 0.001) and the total number of diseases (HR = 1.12 [95% CI 1.013–1.33], P = 0.039).

FPs should be warned that a high number of consultations and a high total number of diseases may predict death or hospitalization. These results need to be confirmed by large-scale cohorts in primary care.

Major depressive disorder (MDD) and insulin resistance-related conditions are major contributors to global disability. Their co-occurrence complicates clinical outcomes, increasing mortality and symptom severity.

In this study, we investigated the association of insulin resistance-related conditions and related polygenic scores (PGSs) with MDD clinical profile and treatment outcomes, using primary care records from UK Biobank.

We identified MDD cases and insulin resistance-related conditions, as well as measures of depression treatment outcomes (e.g. resistance) from the records. Clinical-demographic variables were derived from self-reports, and insulin resistance-related PGSs were calculated using PRS-CS. Univariable analyses were conducted to compare sociodemographic and clinical variables of MDD cases with (IR+) and without (IR−) lifetime insulin resistance-related conditions. Multiple regressions were performed to identify factors, including insulin resistance-related PGSs, potentially associated with treatment outcomes, adjusting for confounders.

Among 30 919 MDD cases, 51.95% were IR+. These had more antidepressant prescriptions and classes utilisation and longer treatment duration than patients without insulin resistance-related conditions (P < 0.001). IR+ participants showed distinctive depressive profiles, characterised by concentration issues, loneliness and inadequacy feelings, which varied according to the timing of MDD diagnosis relative to insulin resistance-related conditions. After adjusting for confounders, insulin resistance-related conditions (i.e. cardiovascular diseases, hypertension, non-alcoholic fatty liver disease, obesity/overweight, prediabetes and type 2 diabetes mellitus) were associated with antidepressant non-response/resistance and longer treatment duration, particularly when MDD preceded insulin resistance-related conditions. No significant PGS associations were found with antidepressant treatment outcomes.

Our findings support an integrated treatment approach, prioritising both psychiatric and metabolic health, and public health strategies aimed at early intervention and prevention of insulin resistance in MDD.

Multimorbidity, especially physical–mental multimorbidity, is an emerging global health challenge. However, the characteristics and patterns of physical–mental multimorbidity based on the diagnosis of mental disorders in Chinese adults remain unclear.

A cross-sectional study was conducted from November 2004 to April 2005 among 13,358 adults (ages 18–65years) residing in Liaoning Province, China, to evaluate the occurrence of physical–mental multimorbidity. Mental disorders were assessed using the Composite International Diagnostic Interview (version 1.0) with reference to the Diagnostic and Statistical Manual of Mental Disorders (3rd Edition Revised), while physical diseases were self-reported. Physical–mental multimorbidity was assessed based on a list of 16 physical and mental morbidities with prevalence ≥1% and was defined as the presence of one mental disorder and one physical disease. The chi-square test was used to calculate differences in the prevalence and comorbidity of different diseases between the sexes. A matrix heat map was generated of the absolute number of comorbidities for each disease. To identify complex associations and potential disease clustering patterns, a network analysis was performed, constructing a network to explore the relationships within and between various mental disorders and physical diseases.

Physical–mental multimorbidity was confirmed in 3.7% (498) of the participants, with a higher prevalence among women (4.2%, 282) than men (3.3%, 216). The top three diseases with the highest comorbidity rate and average number of comorbidities were dysphoric mood (86.3%; 2.86), social anxiety disorder (77.8%; 2.78) and major depressive disorder (77.1%; 2.53). A physical–mental multimorbidity network was visually divided into mental and physical domains. Additionally, four distinct multimorbidity patterns were identified: ‘Affective-addiction’, ‘Anxiety’, ‘Cardiometabolic’ and ‘Gastro-musculoskeletal-respiratory’, with the digestive-respiratory-musculoskeletal pattern being the most common among the total sample. The affective-addiction pattern was more prevalent in men and rural populations. The cardiometabolic pattern was more common in urban populations.

The physical–mental multimorbidity network structure and the four patterns identified in this study align with previous research, though we observed notable differences in the proportion of these patterns. These variations highlight the importance of tailored interventions that address specific multimorbidity patterns while maintaining broader applicability to diverse populations.

Involuntary treatment for patients with anorexia nervosa is common and lifesaving, but also highly intrusive. Understanding how morbidity patterns relate to involuntary treatment can help minimise its use.

We estimate the relative risk of involuntary treatment according to morbidity profiles in patients with anorexia nervosa.

This register-based cohort study included all individuals diagnosed with anorexia nervosa (ICD-10: F50.0, F50.1) between 1 January 2000 and 31 December 2016 in Denmark. Individuals were grouped by prior morbidities using latent class analysis (LCA). Cox proportional hazards regression estimated the relative risk of first involuntary treatment (e.g. involuntary admission, detention, locked wards) after a diagnosis with anorexia nervosa, regardless of the associated diagnosis. The relative risk of involuntary treatment was estimated with latent classes and the number of morbidities as exposure.

A total of 9892 individuals with anorexia nervosa were included (93.3% female), of which 821 (8.3%) individuals experienced at least one involuntary treatment event. The LCA produced six classes, with distinct morbidity profiles. The highest hazard ratio was observed for a group characterised by personality disorders, self-harm and substance misuse (hazard ratio 4.46, 95% CI: 3.43–5.79) followed by a high burden group with somatic and psychiatric disorders (hazard ratio 3.96, 95% CI: 2.81–5.59) and a group with developmental and behavioural disorders (hazard ratio 3.61, 95% CI: 2.54–5.11). The relative risk of involuntary treatment increased primarily with the number of psychiatric morbidities.

Specific morbidity groups are associated with highly elevated risk of involuntary treatment among patients with anorexia nervosa. Targeting preventive interventions to high-risk groups may help reduce the need for involuntary treatment.

This systematic review aimed to review therapeutic patient education (TPE) programmes in managing psychiatric disorders, considering the diversity in delivering agents, intervention formats, targeted skills, and therapeutic outcomes.

Comprehensive database searches, including Web of Science, PubMed, and COCHRANE, were conducted from September 2019 to January 2023, yielding 514 unique records, with 33 making it through rigorous evaluation for full-text review. Eleven studies met the inclusion criteria, focusing on various psychiatric disorders such as depression, bipolar disorder, psychosis, and multiple serious mental illnesses. A total of 38 studies were included from our previous review to supplement the current database search.

TPE programmes exhibited diversity in delivering agents and intervention formats, with a notable presence of multidisciplinary teams and various professionals. The interventions prioritized coping strategies and disease management techniques, though the extent varied based on the disorder. Effectiveness was heterogeneous across studies; some interventions showed significant benefits in areas such as symptom management, coping, and functional improvement, while others reported no significant outcomes.

The findings underscore the potential of TPE in psychiatric care, revealing its multifaceted nature and varied impact. TPE not only addresses deficits but also leverages patients’ existing strengths and capabilities. Despite the reported benefits, a portion of the interventions lacked statistical significance, indicating the necessity for continuous refinement and evaluation.

Multimorbidity, the presence of two or more health conditions, has been identified as a possible risk factor for clinical dementia. It is unclear whether this is due to worsening brain health and underlying neuropathology, or other factors. In some cases, conditions may reflect the same disease process as dementia (e.g. Parkinson's disease, vascular disease), in others, conditions may reflect a prodromal stage of dementia (e.g. depression, anxiety and psychosis).

To assess whether multimorbidity in later life was associated with more severe dementia-related neuropathology at autopsy.

We examined ante-mortem and autopsy data from 767 brain tissue donors from the UK, identifying physical multimorbidity in later life and specific brain-related conditions. We assessed associations between these purported risk factors and dementia-related neuropathological changes at autopsy (Alzheimer's-disease related neuropathology, Lewy body pathology, cerebrovascular disease and limbic-predominant age-related TDP-43 encephalopathy) with logistic models.

Physical multimorbidity was not associated with greater dementia-related neuropathological changes. In the presence of physical multimorbidity, clinical dementia was less likely to be associated with Alzheimer's disease pathology. Conversely, conditions which may be clinical or prodromal manifestations of dementia-related neuropathology (Parkinson's disease, cerebrovascular disease, depression and other psychiatric conditions) were associated with dementia and neuropathological changes.

Physical multimorbidity alone is not associated with greater dementia-related neuropathological change; inappropriate inclusion of brain-related conditions in multimorbidity measures and misdiagnosis of neurodegenerative dementia may better explain increased rates of clinical dementia in multimorbidity

Co-occurring somatic diseases exhibit complex clinical profiles, which can differentially impact the development of late-life depression. Within a community-based cohort, we aimed to explore the association between somatic disease burden, both in terms of the number of diseases and their patterns, and the incidence of depression in older people.

We analysed longitudinal data of depression- and dementia-free individuals aged 60+ years from the population-based Swedish National Study on Aging and Care in Kungsholmen. Depression diagnoses were clinically ascertained following the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition Text Revision over a 15-year follow-up. Somatic disease burden was assessed at baseline through a comprehensive list of chronic diseases obtained by combining information from clinical examinations, medication reviews and national registers and operationalized as (i) disease count and (ii) patterns of co-occurring diseases from latent class analysis. The association of somatic disease burden with depression incidence was investigated using Cox models, accounting for sociodemographic, lifestyle and clinical factors.

The analytical sample comprised 2904 people (mean age, 73.2 [standard deviation (SD), 10.5]; female, 63.1%). Over the follow-up (mean length, 9.6 years [SD, 4 years]), 225 depression cases were detected. Each additional disease was associated with the occurrence of any depression in a dose–response manner (hazard ratio [HR], 1.16; 95% confidence interval [CI]: 1.08, 1.24). As for disease patterns, individuals presenting with sensory/anaemia (HR, 1.91; 95% CI: 1.03, 3.53), thyroid/musculoskeletal (HR, 1.90; 95% CI: 1.06, 3.39) and cardiometabolic (HR, 2.77; 95% CI: 1.40, 5.46) patterns exhibited with higher depression hazards, compared to those without 2+ diseases (multimorbidity). In the subsample of multimorbid individuals (85%), only the cardiometabolic pattern remained associated with a higher depression hazard compared to the unspecific pattern (HR, 1.71; 95% CI: 1.02, 2.84).

Both number and patterns of co-occurring somatic diseases are associated with an increased risk of late-life depression. Mental health should be closely monitored among older adults with high somatic burden, especially if affected by cardiometabolic multimorbidity.

Multimorbidity, known as the co-occurrence of at least two chronic conditions, has become of increasing concern in the current context of ageing populations, though it affects all ages. Early life risk factors of multimorbidity include adverse childhood experiences (ACEs), particularly associated with psychological conditions and weight problems. Few studies have considered related mechanisms and focus on old age participants. We are interested in estimating, from young adulthood, the risk of overweight-depression comorbidity related to ACEs while adjusting for early life confounders and intermediate variables.

We used data from the 1958 National Child Development Study, a prospective birth cohort study (N = 18 558). A four-category outcome (no condition, overweight only, depression only and, overweight-depression comorbidity) was constructed at 23, 33, and 42 years. Multinomial logistic regression models adjusting for intermediate variables co-occurring with this outcome were created. ACEs and sex interaction on comorbidity risk was tested.

In our study sample (N = 7762), we found that ACEs were associated with overweight-depression comorbidity risk throughout adulthood (RRR [95% CI] at 23y = 3.80 [2.10–6.88]) though less overtime. Comorbidity risk was larger than risk of separate conditions. Intermediate variables explained part of the association. After full-adjustment, an association remained (RRR [95% CI] at 23y = 2.00 [1.08–3.72]). Comorbidity risk related to ACEs differed by sex at 42.

Our study provides evidence on the link and potential mechanisms between ACEs and the co-occurrence of mental and physical diseases throughout the life-course. We suggest addressing ACEs in intervention strategies and public policies to go beyond single disease prevention.

The association of COVID-19 with death in people with severe mental illness (SMI), and associations with multimorbidity and ethnicity, are unclear.

To determine all-cause mortality in people with SMI following COVID-19 infection, and assess whether excess mortality is affected by multimorbidity or ethnicity.

This was a retrospective cohort study using primary care data from the Clinical Practice Research Database, from February 2020 to April 2021. Cox proportional hazards regression was used to estimate the effect of SMI on all-cause mortality during the first two waves of the COVID-19 pandemic.

Among 7146 people with SMI (56% female), there was a higher prevalence of multimorbidity compared with the non-SMI control group (n = 653 024, 55% female). Following COVID-19 infection, the SMI group experienced a greater risk of death compared with controls (adjusted hazard ratio (aHR) 1.53, 95% CI 1.39–1.68). Black Caribbean/Black African people were more likely to die from COVID-19 compared with White people (aHR = 1.22, 95% CI 1.12–1.34), with similar associations in the SMI group and non-SMI group (P for interaction = 0.73). Following infection with COVID-19, for every additional multimorbidity condition, the aHR for death was 1.06 (95% CI 1.01–1.10) in the SMI stratum and 1.16 (95% CI 1.15–1.17) in the non-SMI stratum (P for interaction = 0.001).

Following COVID-19 infection, patients with SMI were at an elevated risk of death, further magnified by multimorbidity. Black Caribbean/Black African people had a higher risk of death from COVID-19 than White people, and this inequity was similar for the SMI group and the control group.

People with severe mental illness (SMI) die prematurely, mostly due to preventable causes.

To examine multimorbidity and mortality in people living with SMI using linked administrative datasets.

Analysis of linked electronically captured routine hospital administrative data from Northern Ireland (2010–2021). We derived sex-specific age-standardised rates for seven chronic life-limiting physical conditions (chronic kidney disease, malignant neoplasms, diabetes mellitus, chronic obstructive pulmonary disease, chronic heart failure, myocardial infarction, and stroke) and used logistic regression to examine the relationship between SMI, socio-demographic indicators, and comorbid conditions; survival models quantified the relationship between all-cause mortality and SMI.

Analysis was based on 929,412 hospital patients aged 20 years and above, of whom 10,965 (1.3%) recorded a diagnosis of SMI. Higher likelihoods of an SMI diagnosis were associated with living in socially deprived circumstances, urbanicity. SMI patients were more likely to have more comorbid physical conditions than non-SMI patients, and younger at referral to hospital for each condition, than non-SMI patients. Finally, in fully adjusted models, SMI patients had a twofold excess all-cause mortality.

Multiple morbidities associated with SMI can drive excess mortality. While SMI patients are younger at referral to treatment for these life-limiting conditions, their relatively premature death suggests that these conditions are also quite advanced. There is a need for a more aggressive approach to improving the physical health of this population.

People with severe mental illness (SMI) die earlier than the general population, primarily because of physical disorders.

We estimated the prevalence of physical health conditions, health risk behaviours, access to healthcare and health risk modification advice in people with SMI in Bangladesh, India and Pakistan, and compared results with the general population.

We conducted a cross-sectional survey in adults with SMI attending mental hospitals in Bangladesh, India and Pakistan. Data were collected on non-communicable diseases, their risk factors, health risk behaviours, treatments, health risk modification advice, common mental disorders, health-related quality of life and infectious diseases. We performed a descriptive analysis and compared our findings with the general population in the World Health Organization (WHO) ‘STEPwise Approach to Surveillance of NCDs’ reports.

We recruited 3989 participants with SMI, of which 11% had diabetes, 23.3% had hypertension or high blood pressure and 46.3% had overweight or obesity. We found that 70.8% of participants with diabetes, high blood pressure and hypercholesterolemia were previously undiagnosed; of those diagnosed, only around half were receiving treatment. A total of 47% of men and 14% of women used tobacco; 45.6% and 89.1% of participants did not meet WHO recommendations for physical activity and fruit and vegetable intake, respectively. Compared with the general population, people with SMI were more likely to have diabetes, hypercholesterolemia and overweight or obesity, and less likely to receive tobacco cessation and weight management advice.

We found significant gaps in detection, prevention and treatment of non-communicable diseases and their risk factors in people with SMI.