Multimorbidity Patterns and Unplanned Hospitalisation in a Cohort of Older Adults

Associations between multimorbidity and kidney function decline in old age: A population-based cohort study

BACKGROUND

Individual chronic conditions have been linked to kidney function decline; however, the role of multimorbidity (the presence of ≥2 conditions) and multimorbidity patterns remains unclear.

METHODS

A total of 3094 individuals from the Swedish National study on Aging and Care in Kungsholmen (SNAC-K) were followed for 15 years. Multimorbidity was operationalized as the number of chronic conditions and multimorbidity patterns identified using latent class analysis (LCA). Joint models and Cox regression models were used to explore the associations between multimorbidity, and subsequent absolute and relative (≥25% decline from baseline) changes, respectively, in the estimated glomerular filtration rate (eGFR) calculated using the creatinine-based Berlin Initiative Study equation.

RESULTS

Mean age of the sample was 73.9, and 87% had multimorbidity. There was an independent dose-response relationship between the number of chronic conditions, and absolute (β [95% confidence interval, CI] = -0.05 [-0.07; -0.03]) and relative (hazard ratio, HR [95% CI] = 1.23 [1.17; 1.29]) declines in eGFR. Five patterns of multimorbidity were identified. The Unspecific, low burden pattern had the lowest morbidity burden and was used as the reference category. The Unspecific, high burden, and Cardiometabolic patterns showed accelerated absolute (β [95% CI] = -0.15 [-0.26; -0.05] and -0.77 [-0.98; -0.55], respectively) and relative (HR [95% CI] = 1.45 [1.09; 1.92] and 3.45 [2.27; 5.23], respectively) declines. Additionally, the Cognitive and Sensory pattern showed accelerated relative decline (HR [95% CI] = 1.53 [1.02; 2.31]). No associations were found for the Psychiatric and Respiratory pattern.

CONCLUSION

Multimorbidity is strongly associated with accelerated kidney function decline in older age. Individuals with cardiometabolic multimorbidity exhibit a particularly increased risk. Increased monitoring and timely interventions may preserve kidney function and reduce cardiovascular risks in individuals presenting with conditions that are characteristic of high-risk multimorbidity patterns.

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.

Multimorbidity patterns and trajectories in young and middle-aged adults: a large-scale population-based cohort study

Introduction

The presence of multiple chronic conditions, also referred to as multimorbidity, is a common finding in adults. Epidemiologic research can help identify groups of individuals with similar clinical profiles who could benefit from similar interventions. Many cross-sectional studies have revealed the existence of different multimorbidity patterns. Most of these studies were focused on the older population. However, multimorbidity patterns begin to form at a young age and can evolve over time following distinct multimorbidity trajectories with different impact on health. In this study, we aimed to identify multimorbidity patterns and trajectories in adults 18-65 years old.

Methods

We conducted a retrospective longitudinal epidemiologic study in the EpiChron Cohort, which includes all inhabitants of Aragón (Spain) registered as users of the Spanish National Health System, linking, at the patient level, information from electronic health records from both primary and specialised care. We included all 293,923 patients 18-65 years old with multimorbidity in 2011. We used cluster analysis at baseline (2011) and in 2015 and 2019 to identify multimorbidity patterns at four and eight years of follow-up, and we then created alluvial plots to visualise multimorbidity trajectories. We performed age- and sex-adjusted logistic regression analysis to study the association of each pattern with four- and eight-year mortality.

Results

We identified three multimorbidity patterns at baseline, named dyslipidaemia & endocrine-metabolic, hypertension & obesity, and unspecific. The hypertension & obesity pattern, found in one out of every four patients was associated with a higher likelihood of four- and eight-year mortality (age- and sex-adjusted odds ratio 1.11 and 1.16, respectively) compared to the unspecific pattern. Baseline patterns evolved into different patterns during the follow-up.

Discussion

Well-known preventable cardiovascular risk factors were key elements in most patterns, highlighting the role of hypertension and obesity as risk factors for higher mortality. Two out of every three patients had a cardiovascular profile with chronic conditions like diabetes and obesity that are linked to low-grade systemic chronic inflammation. More studies are encouraged to better characterise the relatively large portion of the population with an unspecific disease pattern and to help design and implement effective and comprehensive strategies towards healthier ageing.

Association of Comorbidity With Healthcare Utilization in People Living With Dementia, 2010-2019: A Population-Based Cohort Study

Evidence on the healthcare utilization associated with comorbidity in people with dementia is lacking in Chinese societies. This study aimed to quantify healthcare utilization associated with comorbidity that is common in people living with dementia. We conducted a cohort study using population-based data from Hong Kong public hospitals. Individuals aged 35+ with a dementia diagnosis between 2010 and 2019 were included. Among 88,151 participants, people with at least two comorbidities accounted for 81.2%. Estimates from negative binomial regressions showed that compared to those with one or no comorbid condition other than dementia, adjusted rate ratios of hospitalizations among individuals with six or seven and eight or more conditions were 1.97 [98.75% CI, 1.89-2.05] and 2.74 [2.63-2.86], respectively; adjusted rate ratios of Accident and Emergency department visits among individuals with six or seven and eight or more conditions were 1.53 [1.44-1.63] and 1.92 [1.80-2.05], respectively. Comorbid chronic kidney diseases were associated with the highest adjusted rate ratios of hospitalizations (1.81 [1.74-1.89]), whereas comorbid chronic ulcer of the skin was associated with the highest adjusted rate ratios of Accident and Emergency department visits (1.73 [1.61-1.85]). Healthcare utilization for individuals with dementia differed substantially by both the number of comorbid chronic conditions and the presence of some specific comorbid conditions. These findings further highlight the importance of taking account of multiple long-term conditions in tailoring the care approach and developing healthcare plans for people with dementia.

Somatic disease burden and depression risk in late life: a community-based study

AIMS

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.

METHODS

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.

RESULTS

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).

CONCLUSIONS

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.

Addressing health challenges in rural Japan: a thematic analysis of social isolation and community solutions

BACKGROUND

The establishment of sustainable connections between medical professionals and rural citizens is pivotal for effective community healthcare. Our study focuses on understanding and resolving health problems arising from social isolation, a critical barrier to achieving this goal, especially in the context of the coronavirus disease 2019(COVID-19) pandemic's impact on community dynamics respecting social cognitive theory. This study investigates the link between social isolation and rural community healthcare. We aim to develop methods that improve interaction and collaboration between healthcare providers and rural communities, ultimately enhancing the region's healthcare system.

METHODS

Employing thematic analysis based on social cognitive theory, we conducted semi-structured interviews with 57 community workers in rural communities. This qualitative approach enabled us to delve into the nuances of social isolation and its multifaceted impact on health and community well-being.

RESULTS

Our analysis revealed four key themes: the impact of aging on social dynamics, shifts in community relationships, unique aspects of rural community networking, and the role of these networks in driving community health. Notably, we identified specific challenges, such as the erosion of intergenerational interactions and the hesitancy to seek support, exacerbated by social isolation and negatively impacting community health.

CONCLUSIONS

Our study reveals the complex factors affecting rural community sustainability, particularly social isolation influenced by privacy concerns and changing social dynamics. Emphasizing the importance of social cognitive theory, it highlights the need for adaptable healthcare systems and strong community-medical collaborations. Future research should focus on developing culturally sensitive, practical strategies for enhancing these collaborations, especially involving physicians, to address rural communities' unique challenges.

Patterns of multimorbidity in primary care electronic health records: A systematic review

Background

Multimorbidity, the coexistence of multiple chronic conditions in an individual, is a complex phenomenon that is highly prevalent in primary care settings, particularly in older individuals. This systematic review summarises the current evidence on multimorbidity patterns identified in primary care electronic health record (EHR) data.

Methods

Three databases were searched from inception to April 2022 to identify studies that derived original multimorbidity patterns from primary care EHR data. The quality of the included studies was assessed using a modified version of the Newcastle-Ottawa Quality Assessment Scale.

Results

Sixteen studies were included in this systematic review, none of which was of low quality. Most studies were conducted in Spain, and only one study was conducted outside of Europe. The prevalence of multimorbidity (i.e. two or more conditions) ranged from 14.0% to 93.9%. The most common stratification variable in disease clustering models was sex, followed by age and calendar year. Despite significant heterogeneity in clustering methods and disease classification tools, consistent patterns of multimorbidity emerged. Mental health and cardiovascular patterns were identified in all studies, often in combination with diseases of other organ systems (e.g. neurological, endocrine).

Discussion

These findings emphasise the frequent coexistence of physical and mental health conditions in primary care, and provide useful information for the development of targeted preventive and management strategies. Future research should explore mechanisms underlying multimorbidity patterns, prioritise methodological harmonisation to facilitate the comparability of findings, and promote the use of EHR data globally to enhance our understanding of multimorbidity in more diverse populations.

A scoping review finds a growing trend in studies validating multimorbidity patterns and identifies five broad types of validation methods

OBJECTIVES

Multimorbidity, the presence of two or more long-term conditions, is a growing public health concern. Many studies use analytical methods to discover multimorbidity patterns from data. We aimed to review approaches used in published literature to validate these patterns.

STUDY DESIGN AND SETTING

We systematically searched PubMed and Web of Science for studies published between July 2017 and July 2023 that used analytical methods to discover multimorbidity patterns.

RESULTS

Out of 31,617 studies returned by the searches, 172 were included. Of these, 111 studies (64%) conducted validation, the number of studies with validation increased from 53.13% (17 out of 32 studies) to 71.25% (57 out of 80 studies) in 2017-2019 to 2022-2023, respectively. Five types of validation were identified: assessing the association of multimorbidity patterns with clinical outcomes (n = 79), stability across subsamples (n = 26), clinical plausibility (n = 22), stability across methods (n = 7) and exploring common determinants (n = 2). Some studies used multiple types of validation.

CONCLUSION

The number of studies conducting a validation of multimorbidity patterns is clearly increasing. The most popular validation approach is assessing the association of multimorbidity patterns with clinical outcomes. Methodological guidance on the validation of multimorbidity patterns is needed.

Multimorbidity patterns in COVID-19 patients and their relationship with infection severity: MRisk-COVID study

BACKGROUND

Several chronic conditions have been identified as risk factors for severe COVID-19 infection, yet the implications of multimorbidity need to be explored. The objective of this study was to establish multimorbidity clusters from a cohort of COVID-19 patients and assess their relationship with infection severity/mortality.

METHODS

The MRisk-COVID Big Data study included 14 286 COVID-19 patients of the first wave in a Spanish region. The cohort was stratified by age and sex. Multimorbid individuals were subjected to a fuzzy c-means cluster analysis in order to identify multimorbidity clusters within each stratum. Bivariate analyses were performed to assess the relationship between severity/mortality and age, sex, and multimorbidity clusters.

RESULTS

Severe infection was reported in 9.5% (95% CI: 9.0-9.9) of the patients, and death occurred in 3.9% (95% CI: 3.6-4.2). We identified multimorbidity clusters related to severity/mortality in most age groups from 21 to 65 years. In males, the cluster with highest percentage of severity/mortality was Heart-liver-gastrointestinal (81-90 years, 34.1% severity, 29.5% mortality). In females, the clusters with the highest percentage of severity/mortality were Diabetes-cardiovascular (81-95 years, 22.5% severity) and Psychogeriatric (81-95 years, 16.0% mortality).

CONCLUSION

This study characterized several multimorbidity clusters in COVID-19 patients based on sex and age, some of which were found to be associated with higher rates of infection severity/mortality, particularly in younger individuals. Further research is encouraged to ascertain the role of specific multimorbidity patterns on infection prognosis and identify the most vulnerable morbidity profiles in the community.

TRIAL REGISTRATION

NCT04981249. Registered 4 August 2021 (retrospectively registered).

Associations of hospitalisation - admission, readmission and length to stay - with multimorbidity patterns by age and sex in adults and older adults: the ELSI-Brazil study

BACKGROUND

Although the association between multimorbidity (MM) and hospitalisation is known, the different effects of MM patterns by age and sex in this outcome needs to be elucidated. Our study aimed to analyse the association of hospitalisations' variables (occurrence, readmission, length of stay) and patterns of multimorbidity (MM) according to sex and age.

METHODS

Data from 8.807 participants aged ≥ 50 years sourced from the baseline of the Brazilian Longitudinal Study of Ageing (ELSI-Brazil) were analysed. Multimorbidity was defined as ≥ 2 (MM2) and ≥ 3 (MM3) chronic conditions. Poisson regression was used to verify the association between the independent variables and hospitalisation according to sex and age group. Multiple linear regression models were constructed for the outcomes of readmission and length of stay. Ising models were used to estimate the networks of diseases and MM patterns.

RESULTS

Regarding the risk of hospitalisation among those with MM2, we observed a positive association with male sex, age ≥ 75 years and women aged ≥ 75 years. For MM3, there was a positive association with hospitalisation among males. For the outcomes hospital readmission and length of stay, we observed a positive association with male sex and women aged ≥ 75 years. Network analysis identified two groups that are more strongly associated with occurrence of hospitalisation: the cardiovascular-cancer-glaucoma-cataract group stratified by sex and the neurodegenerative diseases-renal failure-haemorrhagic stroke group stratified by age group.

CONCLUSION

We conclude that the association between hospitalisation, readmission, length of stay, and MM changes when sex and age group are considered. Differences were identified in the MM patterns associated with hospitalisation according to sex and age group.

Multimorbidity Patterns and Associations with Gait, Balance and Lower Extremity Muscle Function in the Elderly: A Cross-Sectional Study in Northwest China

Purpose

Fall is a common geriatric syndrome leading to various adverse outcomes in the elderly. Gait and balance disorders and decreased lower extremity muscle function are the major intrinsic risk factors of falls, and studies suggested that they were closely related to the underlying chronic conditions. This study aimed to explore the patterns of multimorbidity and determine the associations of these multimorbidity patterns with gait, balance and lower extremity muscle function.

Patients and Methods

A cross-sectional survey of 4803 participants aged ≥60 years in Shaanxi Province, China was conducted and the self-reported chronic conditions were investigated. The 6-m walk test, timed-up-and-go test (TUG) and 5-sit-to-stand test (5-STS) were conducted to evaluate gait, balance, and lower extremity muscle function respectively. Latent class analysis was used to explore patterns of multimorbidity, and multivariate regression analysis was used to determine the associations of multimorbidity patterns with gait, balance, and lower extremity muscle function.

Results

Five multimorbidity patterns were identified: Degenerative Disease Class, Cardio-metabolic Class, Stroke-Respiratory-Depression Class, Gastrointestinal Class, and Very sick Class, and they were differently associated with gait and balance disorders and decreased lower extremity muscle function. In particular, the multimorbidity patterns of Degenerative Disease Class and Stroke-Respiratory-Depression Class were closely associated with all the three risk factors of falls.

Conclusion

There are significant differences in the impact of different multimorbidity patterns on the major intrinsic risk factors of falls in the elderly population, and appropriate multimorbidity patterns are closely related to the prediction of falls and can help to develop fall prevention strategies in the elderly.

Sociodemographic and lifestyle determinants of multimorbidity among community-dwelling older adults: findings from 346,760 SHARE participants

BACKGROUND

This study aimed to investigate the prevalence of multimorbidity and its associated factors among the older population in China to propose policy recommendations for the management of chronic diseases in older adults.

METHODS

This study was conducted based on the 2021 Shenzhen Healthy Ageing Research (SHARE), and involved analysis of 346,760 participants aged 65 or older. Multimorbidity is defined as the presence of two or more clinically diagnosed or non self-reported chronic diseases among the eight chronic diseases surveyed in an individual. The Logistic analysis was adopted to explore the potential associated factors of multimorbidity.

RESULTS

The prevalences of obesity, hypertension, diabetes, anemia, chronic kidney disease, hyperuricemia, dyslipidemia and fatty liver disease were 10.41%, 62.09%, 24.21%, 12.78%, 6.14%, 20.52%, 44.32%, and 33.25%, respectively. The prevalence of multimorbidity was 63.46%. The mean count of chronic diseases per participant was 2.14. Logistic regression indicated that gender, age, marriage status, lifestyle (smoking status, drinking status, and physical activity), and socioeconomic status (household registration, education level, payment method of medical expenses) were the common predictors of multimorbidity for older adults, among which, being women, married, or engaged in physical activity was found to be a relative determinant as a protective factor for multimorbidity after the other covariates were controlled.

CONCLUSION

Multimorbidity is prevalent among older adults in Chinese. Guideline development, clinical management,and public intervention should target a group of diseases instead of a single condition.

Prevalence, patterns of multimorbidity and associations with health care utilization among middle-aged and older people in China

BACKGROUND

Multimorbidity has become one of the main challenges in health care system. The association between prevalence, patterns of multimorbidity and health care utilization is less often discussed in China. The purpose of this study is to examine this association among Chinese middle-aged and older adults and take into account different sociodemographic, behavioral and health characteristics. Based on this, implications of current evidence and effective intervention on multimorbidity and health care utilization can be identified and put into practice.

METHODS

The wave 4 in 2018 of the China Health and Retirement Longitudinal Study (CHARLS) was used in the study. Multimorbidity was defined as the co-occurrence of two or more chronic medical condition of a list of fourteen chronic diseases in one person. The presence of chronic diseases was assessed through self-report. Health care utilization include whether the respondents received outpatient service last month and inpatient service in the past year. Latent Class Analysis was conducted to identify the clustering pattern of chronic diseases. Logistic regressions were employed to explore the association between prevalence, patterns of multimorbidity and health care utilization. Analyses were weighted using individual sample weights, adjusted for non-response of individual and household.

RESULTS

Among 19,559 participants aged 45 and older, 23.10% were aged above 70 years and 52.42% were female. The prevalence of multimorbidity was 56.73%. Four patterns were identified: relatively healthy class, respiratory class, stomach-arthritis class and vascular class. Multimorbid individuals used more outpatient services (OR = 1.89, 95%CI = 1.65-2.17) and more inpatient services (OR = 2.52, 95%CI = 2.22-2.86) compared to their no-multimorbid counterparts. Compared to relatively healthy class, the respondents classified into respiratory class, stomach-arthritis class and vascular class used more outpatient services (OR = 1.90, 95%CI = 1.57-2.30; OR = 2.39, 95%CI = 2.06-2.78; OR = 1.53, 95%CI = 1.32-1.79 respectively) and more inpatient services (OR = 2.19, 95%CI = 1.83-2.62; OR = 2.93, 95%CI = 2.53-3.40; OR = 1.90, 95%CI = 1.65-2.19 respectively).

CONCLUSION

Our study provided evidence that multimorbidity is high among Chinese older adults and is associated substantially higher health care utilization in China. Four multimorbidity patters were identified. Policy should prioritize improving the management of individuals with multimorbidity to increase healthcare efficiency. Further research is necessary with special emphasis on the trajectory of multimorbidity and the role of health system in satisfying needs of multimorbid individuals.

Hospital length of stay and 30-day readmissions in older people: their association in a 20-year cohort study in Italy

BACKGROUND

There are conflicting data on whether hospital length of stay (LOS) reduction affects readmission rates in older adults. We explored 20-year trends of hospital LOS and 30-day rehospitalizations in a cohort of Italian older people, and investigated their association.

METHODS

Participants in the Pro.V.A. project (n = 3099) were followed-up from 1996 to 2018. LOS and 30-day rehospitalizations, i.e. new hospitalizations within 30 days from a previous discharge, were obtained from personal interviews and regional registers. Rehospitalizations in the 6 months before death were also assessed. Linear regressions evaluated the associations between LOS and the frequency of 30-day rehospitalizations, adjusting for the mean age of the cohort within each year.

RESULTS

Over 20 years, 2320 (74.9%) participants were hospitalized. Mean LOS gradually decreased from 17.3 days in 1996 to 11.3 days in 2018, while 30-day rehospitalization rates increased from 6.6% in 1996 to 13.6% in 2018. LOS was inversely associated with 30-day rehospitalizations frequency over time (β = -2.33, p = 0.01), similarly in men and women. A total of 1506 individuals was hospitalized within 6 months before death. The frequency of 30-day readmissions at the end of life increased from 1.4% in 1997 to 8.3% in 2017 and was associated with mean LOS (β = -1.17, p = 0.03).

CONCLUSIONS

The gradual LOS reduction observed in the latter decades is associated with higher 30-day readmission rates in older patients in Italy. This suggests that a careful pre-discharge assessment is warranted in older people, and that community healthcare services should be improved to reduce the risk of readmission.

Impact of a digital health literacy intervention and risk predictors for multimorbidity among poor women of reproductive years: Results of a randomized-controlled trial

Objective

The objective of this study was to deliver an intervention to improve health awareness for infection prevention, hygiene, and sanitation to assess its impact. Furthermore, it aimed to identify the risk of multimorbidity in women of reproductive years from low socio-economic background.

Methods

A randomized control trial was conducted in Pakistan among women aged 15–45 years. Overall, 820 women participated in the baseline survey; 388 women were part of the control group and 360 of the intervention group. A digital health literacy intervention was delivered by 91 trained community health workers. Data were analyzed using descriptive statistics and multivariate logistic regression.

Results

About 35.9% of women suffered from multimorbidity. The intervention group showed higher odds of confidence in managing health with respect to skill and technique acquisition (AOR = 2.21; 95% CI 1.01–4.84), self-monitoring and insight (AOR = 2.97; 95% CI 1.29–6.80) as well as sanitation and hygiene (AOR = 1.42; 95% CI 1.07–1.93). Two primary outcomes related to hand hygiene and protective behavior against infection did not show any significant improvement. The secondary outcomes of the study related to impact on overall health-related quality of life, social integration and support, and emotional well-being also did not show any significant improvement.

Conclusions

Digital health literacy interventions and multimorbidity management for women of reproductive years at the primary level are a way forward to alleviate communicable and non-communicable disease burden in developing countries like Pakistan. These efforts are also critical to improve maternal and child health in developing regions.

The association between social care expenditure and multiple-long term conditions: A population-based area-level analysis

Background

Multiple long-term health conditions (MLTCs) are common and increasing among older people, yet there is limited understanding of their prevalence and association with social care expenditure.

Aim

To estimate the prevalence of MTLCs and association with English social care expenditure.

Methods

Our study population included those aged ≥ 65 who died in England in the year 2018 with any of the following long-term conditions recorded on their death certificate: diabetes; cardiovascular diseases (CVDs) including hypertension; dementia; stroke; respiratory; and chronic kidney diseases (CKDs). Prevalence was based on the proportion of death reported for older people with MTLCs (≥ 2) in each of the 152 English Local Authorities (LAs). Ordinary least square regression (OLS) was used to assess the relationship between prevalence of MTLCs and adult social care expenditure, adjusting for LA characteristics.

Results

Of the 409551 deaths reported, 19.9% (n = 81395) had ≥ 2 MTLCs, of which the combination of CVDs-diabetes was the most prevalent. Hospitals were the leading place of death for those with MTLCs. Results from the OLS regression model showed that an increased prevalence of MLTCs is associated with higher LA social care expenditure. A percentage point increase in prevalence of MLTCs is associated with an increase of about £8.13 in per capita LA social care expenditure.

Conclusion

Our findings suggest that the increased prevalence of MTLCs is associated with increased LA social care expenditure. It is important for future studies to further explore the mechanisms or link between LA social care expenditure and the prevalence of MTLCs.

Gender and Socioeconomic Differences in the Prevalence and Patterns of Multimorbidity among Middle-Aged and Older Adults in China

BACKGROUND

Multimorbidity has become a global public health concern. Knowledge about the prevalence and patterns of multimorbidity will provide essential information for public intervention and clinical management. This study aimed to examine gender and socioeconomic differences in the prevalence and patterns of multimorbidity among a nationally representative sample of middle-aged and older Chinese individuals.

METHODS

Data were obtained from the 2018 wave of the China Health and Retirement Longitudinal Study. Latent class analysis was conducted to discriminate among the multimorbidity patterns. Multinomial logit analysis was performed to explore gender and socioeconomic factors associated with various multimorbidity patterns.

RESULTS

A total of 19,559 respondents over 45 years old were included in the study. The findings showed that 56.73% of the respondents reported multimorbidity, with significantly higher proportions among women. Four patterns, namely "relatively healthy class", "respiratory class", "stomach-arthritis class" and "vascular class", were identified. The women were more likely to be in the stomach-arthritis class. Respondents with a higher SES, including higher education, urban residence, higher consumption, and medical insurance, had a higher probability of being in the vascular class. Conclusions: Significant gender and socioeconomic differences were observed in the prevalence and patterns of multimorbidity. The examination of gender and socioeconomic differences for multimorbidity patterns has great implications for clinical practice and health policy. The results may provide insights to aid in the management of multimorbidity patients and improve health resource allocation.

Ageing people with intellectual disabilities and the association between frailty factors and social care: A Swedish national register study

The aim of this study was to describe the social care provided for different age groups of people with intellectual disability, 55 years or above, and to investigate the association between such care and frailty factors for those with diagnosed level of intellectual disabilities. Descriptive and logistic regression analyses were used. Commonest forms of social care among the 7936 people were Residential care, Daily activities and Contact person. Home help and Security alarm increased with age. The frailty factors significantly associated with increased social care were age, polypharmacy and severe levels of intellectual disabilities. Persons most likely to be in residential care were in the age group 65-79 with polypharmacy and severe disability. The results indicate a need for further research of how frailty factors are considered in social care and longstanding medication, especially then severe intellectual disability hinders communication. A national strategic plan for preventive interventions should be developed to ensure the best possible healthy ageing.

Derivation and validation of a 90-day unplanned hospital readmission score in older patients discharged form a geriatric ward

PURPOSE

To derive and validate a 90-day unplanned hospital readmission (UHR) score based on information available to non-hospital based care providers.

METHODS

Retrospective longitudinal study with cross-validation method. Participants were older adults (≥ 65 years) admitted to a geriatric short-stay department in a general hospital in France. Patients were split into a derivation cohort and a validation cohort. We recorded demographic information, medical history, and concurrent clinical characteristics. The main outcome was 90-day UHR. Data obtained from hospital discharge letters were used in a logistic regression model to construct a predictive score, and to identify risk groups for 90-day UHR.

RESULTS

In total, 750 and 250 aged adults were included in both the derivation and the validation cohorts. Mean age was 87.2 ± 5.2 years, most were women (68.1%). Independent risk factors for 90-day UHR were: use of mobility aids (p = .02), presence of dementia syndrome (p = .02), history of recent hospitalisation (p = .03), and discharge to domiciliary home (p = .005). From these four risk factors, three groups were determined: low-risk group (score < 4), medium-risk group (score between 4 and 6), and high-risk group (score ≥ 6). In the derivation cohort the 90-day UHR rates increased significantly across risk groups (14%, 22%, and 30%, respectively). The 90-day UHR score had the same discriminant power in the derivation cohort (c-statistic = 0.63) as in the validation cohort (c-statistic = 0.63).

CONCLUSIONS

This score makes it possible to identify aged adults at risk of 90-day UHR and to target multidisciplinary interventions to limit UHR for patients discharged from a Geriatric Short-Stay Unit.

The association between pain and central nervous system depressing medication among hospitalised Norwegian older adults

OBJECTIVES

Central nervous system depressant medications (CNSD) including benzodiazepines, z-hypnotics and opioids are regularly prescribed for the older patient. These medications are linked to dependence and associated with severe side effects in some older patients. Consensus recommendations for this group suggest limiting their use. We have recently described a high proportion of long-term CNSD use and dependence among older in-hospital patients. In this study, we aim to investigate factors associated with pain intensity and presentation of pain among older adults with long-term use of CNSDs compared to non-users.

METHODS

Two hundred and forty six elderly hospitalised patients were recruited consecutively in a cross-sectional study. Data was collected from patients and electronic health records (EHR). Independent variables were sex, age, education, emotional symptoms (hospital anxiety and depression scale [HADS]), cognitive function (Mini-mental State Examination test [MMSE]), comorbidity (cumulative illness rating score - geriatrics [CIRS-G]), loneliness (the six-item De Jong Gierveld Loneliness Scale) and prolonged (≥4 weeks) use of any CNSDs or prolonged use of opioids (≥4 weeks). All variables, including pain intensity, were collected at one time point consistent with the cross-sectional study design. Statistical analyses included descriptive statistics and linear regression models using the above mentioned variables and pain intensity (visual analogue scale for pain intensity [VAS] pain 0-100) as outcome. Additional information regarding pain presentation was extracted from the patients' EHR.

RESULTS

Mean pain intensity VAS (SD) was 35.2 (30.4) and 18.1 (24.2) respectively, for patients with vs. without prolonged use of CNSDs. In the multivariable linear regression analysis, prolonged use of CNSDs and opioids were positively associated with pain intensity (VAS) (regression coefficient (95% CI) 20.7 (11.0; 30.3), p<0.001, and 19.8 (5.7; 33.8), p=0.006, respectively), while sex, age, education, MMSE, HADS, CIRS-G and loneliness scores were not. Pain related to back (23.2%) and lower extremities (23.2%) were most common pain sites, and those with one or more pain sites reported overall higher pain intensity compared to those with no reported pain sites (p<0.006).

CONCLUSIONS

Prolonged use of CNSD medications as well as prolonged use of opioids are both positively associated with pain intensity. The results may have implications for treatment and long-term pain management for older patients.

Multimorbidity patterns and hospitalisation occurrence in adults and older adults aged 50 years or over

Multimorbidity is highly prevalent in older adults and can lead to hospitalisation. We investigate the prevalence, associated factors, and multimorbidity pattern associated to hospitalisation, readmission, and length of stay in the population aged 50 years and older. We analysed baseline data (2015–2016) from the ELSI-Brazil cohort, a representative sample of non-institutionalised Brazilians aged ≥ 50 years. In total, 8807 individuals aged ≥ 50 years were included. Poisson regression with robust variance adjusted for confounders was used to verify the associations with hospitalisation. Multiple linear regression was used to analyse the associations with readmission and length of stay. Network analysis was conducted using 19 morbidities and the outcome variables. In 8807 participants, the prevalence of hospitalisation was 10.0% (95% CI 9.1, 11), mean readmissions was 1.55 ± 1.191, and mean length of stay was 6.43 ± 10.46 days. Hospitalisation was positively associated with male gender, not living with a partner, not having ingested alcoholic beverages in the last month, and multimorbidity. For hospital readmission, only multimorbidity ≥ 3 chronic conditions showed a statistically significant association. Regarding the length of stay, the risk was positive for males and negative for living in rural areas. Five disease groups connected to hospitalisation, readmission and length of stay were identified. To conclude, sociodemographic variables, such as gender, age group, and living in urban areas, and multimorbidity increased the risk of hospitalisation, mean number of readmissions, and mean length of stay. Through network analysis, we identified the groups of diseases that increased the risk of hospitalisation, readmissions, and length of stay.

Comorbidity patterns in institutionalized older adults affected by dementia

Introduction

Dementia is common in nursing homes (NH) residents. Defining dementia comorbidities is instrumental to identify groups of persons with dementia that differ in terms of health trajectories and resources consumption. We performed a cross-sectional study to identify comorbidity patterns and their associated clinical, behavioral, and functional phenotypes in institutionalized older adults with dementia.

Methods

We analyzed data on 2563 Italian NH residents with dementia, collected between January 2014 and December 2018 using the multidimensional assessment instrument interRAI Long-Term Care Facility (LTCF). A standard principal component procedure was used to identify comorbidity patterns. Linear regression analyses were used to ascertain correlates of expression of the different patterns.

Results

Among NH residents with dementia, we identified three different comorbidity patterns: (1) heart diseases, (2) cardiovascular and respiratory diseases and sensory impairments, and (3) psychiatric diseases. Older age significantly related to increased expression of the first two patterns, while younger patients displayed increased expression of the third one. Recent hospital admissions were associated with increased expression of the heart diseases pattern (β = 0.028; 95% confidence interval [CI] 0.003 to 0.05). Depressive symptoms and delirium episodes increased the expression of the psychiatric diseases pattern (β = 0.130, 95% CI 0.10 to 0.17, and β 0.130, CI 0.10 to 0.17, respectively), while showed a lower expression of the heart diseases pattern.

Discussion

We identified different comorbidity patterns within NH residents with dementia that differ in term of clinical and functional profiles. The prompt recognition of health needs associated to a comorbidity pattern may help improve long-term prognosis and quality of life of these individuals.

Highlights

Defining dementia comorbidities patterns in institutionalized older adults is key.Institutionalized older adults with dementia express different care needs.Comorbidity patterns are instrumental to identify different patients' phenotypes.Phenotypes vary in terms of health trajectories and demand different care plans.Prompt recognition of phenotypes in nursing homes can positively impact on outcomes.

Multimorbidity patterns and association with mortality in 0.5 million Chinese adults

BACKGROUND

Few studies have assessed the relationship between multimorbidity patterns and mortality risk in the Chinese population. We aimed to identify multimorbidity patterns and examined the associations of multimorbidity patterns and the number of chronic diseases with the risk of mortality among Chinese middle-aged and older adults.

METHODS

We used data from the China Kadoorie Biobank and included 512,723 participants aged 30 to 79 years. Multimorbidity was defined as the presence of two or more of the 15 chronic diseases collected by self-report or physical examination at baseline. Multimorbidity patterns were identified using hierarchical cluster analysis. Cox regression was used to estimate the associations of multimorbidity patterns and the number of chronic diseases with all-cause and cause-specific mortality.

RESULTS

Overall, 15.8% of participants had multimorbidity. The prevalence of multimorbidity increased with age and was higher in urban than rural participants. Four multimorbidity patterns were identified, including cardiometabolic multimorbidity (diabetes, coronary heart disease, stroke, and hypertension), respiratory multimorbidity (tuberculosis, asthma, and chronic obstructive pulmonary disease), gastrointestinal and hepatorenal multimorbidity (gallstone disease, chronic kidney disease, cirrhosis, peptic ulcer, and cancer), and mental and arthritis multimorbidity (neurasthenia, psychiatric disorder, and rheumatoid arthritis). During a median of 10.8 years of follow-up, 49,371 deaths occurred. Compared with participants without multimorbidity, cardiometabolic multimorbidity (hazard ratios [HR] = 2.20, 95% confidence intervals [CI]: 2.14 - 2.26) and respiratory multimorbidity (HR = 2.13, 95% CI:1.97 - 2.31) demonstrated relatively higher risks of mortality, followed by gastrointestinal and hepatorenal multimorbidity (HR = 1.33, 95% CI:1.22 - 1.46). The mortality risk increased by 36% (HR = 1.36, 95% CI: 1.35 - 1.37) with every additional disease.

CONCLUSION

Cardiometabolic multimorbidity and respiratory multimorbidity posed the highest threat on mortality risk and deserved particular attention in Chinese adults.

The effect of social relationships on cognitive decline in older adults: an updated systematic review and meta-analysis of longitudinal cohort studies

Background

A previous meta-analysis (Kuiper et al., 2016) has shown that multiple aspects of social relationships are associated with cognitive decline in older adults. Yet, results indicated possible bias in estimations of statistical effects due to the heterogeneity of study design and measurements. We have updated this meta-analysis adding all relevant publications from 2012 to 2020 and performed a cumulative meta-analysis to map the evolution of this growing field of research (+80% of studies from 2012-2020 compared to the period considered in the previous meta-analysis).

Methods

Scopus and Web of Science were searched for longitudinal cohort studies examining structural, functional and combined effects of social relationships. We combined Odds Ratios (OR) with 95% confidence intervals (CI) using random effects meta-analysis and assessed sources of heterogeneity and the likelihood of publication bias. The risk of bias was evaluated with the Quality of Prognosis Studies in Systematic Reviews (QUIPS) tool.

Results

The review was prospectively registered on PROSPERO (ID: CRD42019130667). We identified 34 new articles published in 2012-2020. Poor social relationships were associated with cognitive decline with increasing precision of estimates compared to previously reviewed studies [(for structural, 17 articles, OR: 1.11; 95% CI: 1.08; 1.14) (for functional, 16 articles, OR: 1.12; 95% CI: 1.05; 1.20) (for combined, 5 articles, OR: 1.15; 95% CI: 1.06; 1.24)]. Meta-regression, risk and subgroup analyses showed that the precision of estimations improved in recent studies mostly due to increased sample sizes.

Conclusions

Our cumulative meta-analysis would confirm that multiple aspects of social relationships are associated with cognitive decline. Yet, there is still evidence of publication bias and relevant information on study design is often missing, which could lead to an over-estimation of their statistical effects.

Supplementary Information

The online version contains supplementary material available at (10.1186/s12889-022-12567-5).

Comportamento sedentário e associação com multimorbidade e padrões de multimorbidade em idosos brasileiros: dados da Pesquisa Nacional de Saúde de 2019

Resumo: O comportamento sedentário emerge como um importante determinante da saúde da pessoa idosa, no entanto, sua relação com a multimorbidade e seus padrões de acometimento em estudos epidemiológicos têm sido pouco explorados na população brasileira. Tais associações poderão auxiliar na elaboração de políticas públicas visando à modificação desse comportamento. Assim, o objetivo deste estudo foi avaliar a associação entre comportamento sedentário com multimorbidade e seus padrões em idosos brasileiros. Estudo transversal, com 43.554 idosos da Pesquisa Nacional de Saúde de 2019. O comportamento sedentário autorreferido foi categorizado em < 3; 3-6; e > 6 horas por dia. A presença de multimorbidade e seus padrões foram analisados pelo autorrelato da coexistência de duas ou mais doenças crônicas, sendo que os três padrões estabelecidos consideraram as doenças com características clínicas similares: (1) cardiopulmonar; (2) vascular-metabólico; e (3) mental-musculoesquelético. As associações foram realizadas pela regressão logística binária. Os idosos que despendiam 3-6 horas/dia em comportamento sedentário tiveram maiores chances (OR = 1,39; IC95%: 1,29; 1,50) de apresentar multimorbidade, padrão vascular-metabólico (OR = 1,39; IC95%: 1,29; 1,50) e mental-musculoesquelético (OR = 1,11; IC95%: 1,00; 1,24). Quando o comportamento sedentário foi > 6 horas/dia, houve maiores chances de multimorbidade (OR = 1,58; IC95%: 1,43; 1,74) e dos padrões cardiopulmonar (OR = 1,73; IC95%: 1,33; 2,27), vascular-metabólico (OR = 1,49; IC95%: 1,35; 1,64) e mental-musculoesquelético (OR = 1,15; IC95%: 1,01; 1,31), quando comparados àqueles que ficavam até 3 horas/dia. Dessa forma, evidenciou-se que tempos elevados em comportamento sedentário são fatores de risco relevantes para a ocorrência de multimorbidade e seus padrões em idosos.

Specific multimorbidity patterns modify the impact of an exercise intervention in older hospitalized adults

BACKGROUND

Different multimorbidity patterns present with different prognoses, but it is unknown to what extent they may influence the effectiveness of an individualized multicomponent exercise program offered to hospitalized older adults.

METHODS

This study is a secondary analysis of a randomized controlled trial conducted in the Department of Geriatric Medicine of a tertiary hospital. In addition to the standard care, an exercise-training multicomponent program was delivered to the intervention group during the acute hospitalization period. Multimorbidity patterns were determined through fuzzy c-means cluster analysis, over 38 chronic diseases. Functional, cognitive and affective outcomes were considered.

RESULTS

Three hundred and six patients were included in the analyses (154 control; 152 intervention), with a mean age of 87.2 years, and 58.5% being female. Four patterns of multimorbidity were identified: heart valves and prostate diseases (26.8%); metabolic diseases and colitis (20.6%); psychiatric, cardiovascular and autoimmune diseases (16%); and an unspecific pattern (36.6%). The Short Physical Performance Battery (SPPB) test improved across all patterns, but the intervention was most effective for patients in the metabolic/colitis pattern (2.48-point difference between intervention/control groups, 95% CI 1.60-3.35). Regarding the Barthel Index and the Mini Mental State Examination (MMSE), the differences were significant for all multimorbidity patterns, except for the psychiatric/cardio/autoimmune pattern. Differences concerning quality of life were especially high for the psychiatric/cardio/autoimmune pattern (16.9-point difference between intervention/control groups, 95% CI 4.04, 29.7).

CONCLUSIONS

Patients in all the analyzed multimorbidity patterns improved with this tailored program, but the improvement was highest for those in the metabolic pattern. Understanding how different chronic disease combinations are associated with specific functional and cognitive responses to a multicomponent exercise intervention may allow further tailoring such interventions to older patients' clinical profile.

Relationship between the Kihon Checklist and all-cause hospitalization among community-dwelling older adults

AIM

To examine the relationship between the Kihon Checklist (KCL) and incidence of hospitalization among community-dwelling older adults.

METHOD

We analyzed the cohort data of 2920 community-dwelling adults aged ≥65 years, who were living independently in a city in Shiga prefecture. We investigated the frailty status, instrumental activities of daily living, physical function, nutritional status, oral function, homebound status, cognitive function and mood using the KCL in the baseline survey. The outcome was incident all-cause hospitalization in the 2-year period. Logistic regression analysis was used to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) of the relationships between the frailty status and each domain of the KCL as well as all-cause hospitalization.

RESULTS

The prevalence of frailty, pre-frailty and robustness were 29.7%, 34.5% and 35.8%, respectively. During the 2-year follow-up period, 417 participants (14.3%) underwent an incident of all-cause hospitalization. The participants with frailty (adjusted OR 1.38, 95% CI 1.05-1.81) had a significantly elevated incidence of hospitalization according to the multivariate analysis compared with patients with robustness, but not in participants with pre-frailty (adjusted OR 1.07, 95% CI 0.82-1.40). Participants with low physical function (adjusted OR 1.45, 95% CI 1.12-1.87) and depressed mood (adjusted OR 1.35, 95% CI 1.08-1.70) had a significantly elevated incidence of hospitalization according to multivariate analysis compared with non-risk.

CONCLUSION

These results suggest that older adults with frailty are more likely to be hospitalized and that the KCL may be the screening tool to estimate the hospitalization risk. Geriatr Gerontol Int ••; ••: ••-•• Geriatr Gerontol Int 2021; ••: ••-••.

Associations between physical multimorbidity patterns and common mental health disorders in middle-aged adults: A prospective analysis using data from the UK Biobank

BACKGROUND

We aimed to identify specific patterns of physical multimorbidity, defined as the presence of two or more physical long-term conditions, and to examine the extent to which these specific patterns could predict future incident and persistent common mental health disorders (CMDs) in middle-aged adults enrolled in the UK Biobank.

METHODS

We assessed prospective associations between physical multimorbidity status at the baseline assessment (2006-2010) and depression and anxiety 'caseness' according to the Patient Health Questionnaire (PHQ)-9 and the Generalised Anxiety Disorder Assessment (GAD)-7 at the follow-up assessment (2016) in 154,367 middle-aged adults enrolled in the UK Biobank (median age: 57 years, interquartile range = 50-62 years, 56.5% female, mean duration of follow-up: 7.6 years, standard deviation = 0.87). Patterns of physical multimorbidity were identified using exploratory factor analysis. Logistic regression was used to assess prospective associations between physical multimorbidity patterns at baseline and both incident and persistent depression and anxiety at follow-up.

FINDINGS

Compared to those with no physical multimorbidity, having two (adjusted odds ratio (aOR) =1.41, 95%CI 1.32 to 1.53), three (aOR = 1.94, 95%CI 1.76 to 2.14), four (aOR = 2.38, 95%CI 2.07 to 2.74), and five or more (aOR = 2.89, 95%CI 2.42 to 3.45) physical conditions was prospectively associated with incident depression at follow-up in a dose response manner. Similar trends emerged for incident anxiety, persistent depression, and persistent anxiety, but associations were strongest for incident CMDs. Regarding specific patterns of physical MM, the respiratory pattern (aOR = 3.23, 95%CI 2.44 to 4.27) and the pain/gastrointestinal pattern (aOR = 2.19, 95%CI 1.92 to 2.50) emerged as the strongest predictors of incident depression. Similar results emerged for incident anxiety.

INTERPRETATION

These findings highlight patterns of physical multimorbidity with the poorest prognosis for both emerging and persisting depression and anxiety. These findings might have significant implications for the implementation of integrated mental and physical healthcare and facilitate the development of targeted preventative interventions and treatment for those with physical multimorbidity.

FUNDING

AR is supported by Guy's Charity grant number EIC180702; JAT is funded by Medical Research Council (MRC) number MR/SO28188/1; AD is funded by Guy's Charity grant number EIC180702 and MRC grant number MR/SO28188/1. JD is part supported by the ESRC Centre for Society and Mental Health at King's College London (ES/S012567/1), grants from the ESRC (ES/S002715/1), by the Health Foundation working together with the Academy of Medical Sciences, for a Clinician Scientist Fellowship, and by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London and the National Institute for Health Research (NIHR) Applied Research Collaboration South London (NIHR ARC South London) at King's College Hospital NHS Foundation Trust. The views expressed are those of the author[s] and not necessarily those of the ESRC, NIHR, the Department of Health and Social Care or King's College London.

Comorbidity status of deceased COVID-19 in-patients in Italy

Background

Most COVID-19-related deaths have occurred in older persons with comorbidities. Specific patterns of comorbidities related to COVID-19 deaths have not been investigated.

Methods

A random sample of 6085 individuals in Italy who died in-hospital with confirmed COVID-19 between February and December 2020 were included. Observed to expected (O/E) ratios of disease pairs were computed and logistic regression models were used to determine the association between disease pairs with O/E values ≥ 1.5.

Results

Six pairs of diseases exhibited O/E values ≥ 1.5 and statistically significant higher odds of co-occurrence in the crude and adjusted analyses: (1) ischemic heart disease and atrial fibrillation, (2) atrial fibrillation and heart failure, (3) atrial fibrillation and stroke, (4) heart failure and COPD, (5) stroke and dementia, and (6) type 2 diabetes and obesity.

Conclusion

In those deceased in-hospital due to COVID-19 in Italy, disease combinations defined by multiple cardio-respiratory, metabolic, and neuropsychiatric diseases occur more frequently than expected. This finding indicates a need to investigate the possible role of these clinical profiles in the chain of events that lead to death in individuals who have contracted SARS-CoV-2.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40520-021-01914-y.

Comprehensive Care through Family Medicine: Improving the Sustainability of Aging Societies

Comprehensive care through family medicine can enhance the approach to multimorbidity, interprofessional collaboration, and community care, and make medical care more sustainable for older people. This study investigated the effect of implementing family medicine and the comprehensiveness of medical care in one of the most rural communities. This implementation research used medical care data from April 2015 to March 2020. Patients' diagnoses were categorized according to the 10th revision of the International Statistical Classification of Disease and Related Health Problems (ICD-10). In 2016, family medicine was implemented in only one general hospital in Unnan. The comprehensiveness rate improved in all ICD-10 disease categories during the study period, especially in the following categories-infections; neoplasms; endocrine, nutritional, and metabolic diseases; mental disorders; nervous system; circulatory system; respiratory system; digestive system; skin and subcutaneous tissue; musculoskeletal system and connective tissue; and the genitourinary system. Implementing family medicine in rural Japanese communities can improve the comprehensiveness of medical care and resolve the issue of fragmentation of care by improving interprofessional collaboration and community care. It can be a solution for the aging of both patient and healthcare professionals. Future research can investigate the relationship between family medicine and patient health outcomes for improved healthcare sustainability.

AI and Big Data in Healthcare: Towards a More Comprehensive Research Framework for Multimorbidity

Multimorbidity refers to the coexistence of two or more chronic diseases in one person. Therefore, patients with multimorbidity have multiple and special care needs. However, in practice it is difficult to meet these needs because the organizational processes of current healthcare systems tend to be tailored to a single disease. To improve clinical decision making and patient care in multimorbidity, a radical change in the problem-solving approach to medical research and treatment is needed. In addition to the traditional reductionist approach, we propose interactive research supported by artificial intelligence (AI) and advanced big data analytics. Such research approach, when applied to data routinely collected in healthcare settings, provides an integrated platform for research tasks related to multimorbidity. This may include, for example, prediction, correlation, and classification problems based on multiple interaction factors. However, to realize the idea of this paradigm shift in multimorbidity research, the optimization, standardization, and most importantly, the integration of electronic health data into a common national and international research infrastructure is needed. Ultimately, there is a need for the integration and implementation of efficient AI approaches, particularly deep learning, into clinical routine directly within the workflows of the medical professionals.