Multimorbidity Patterns and 5-Year Mortality in Institutionalized Older Adults

Prevalence of rheumatic and musculoskeletal diseases (RMDs) in nursing home residents: a systematic literature review

PURPOSE

The objective of this systematic literature review was to: (1) estimate the prevalence of (symptoms of) rheumatic and musculoskeletal diseases (RMDs) and (2) explore how (symptoms of) RMDs are identified and documented in studies among nursing home residents.

METHODS

Prevalence data of (symptoms of) RMDs in permanently admitted nursing home residents ≥ 60 years were included. Data extraction, data synthesis and risk of bias assessment were performed by two reviewers independently. Included studies were categorized based on case ascertainment and case definition comprising: (location of) musculoskeletal pain, general terms for RMDs or a specific type of RMD. Results were summarized descriptively.

RESULTS

Out of 6900 records, 53 studies were included. Case ascertainment comprised databases (n = 5), physical examination (n = 1), self-report questionnaires (n = 14), review of medical charts (n = 23) and self-report questionnaires combined with review of medical charts (n = 10). Prevalence ranged between 0.9 and 77.0% for (localized) musculoskeletal pain (n = 19) and between 0.6 and 67.5% for RMDs in general (n = 39). Prevalence rates of specific type of RMDs ranged between 0.7 and 47.5% for gout, between 3.3 and 11.0% for rheumatoid arthritis and between 2.8 and 75.4% for osteo-arthritis (n = 14). Heterogeneity with regard to documentation of (symptoms of) RMDs in medical data of nursing home residents was high.

CONCLUSION

The overall prevalence of (symptoms of) RMDs varied to a great extent. This was mainly due to large heterogeneity in documentation of (symptoms of) RMDs. Establishing agreement on a useful and practical classification may ultimately increase identification of RMDs in the nursing home setting.

The regional disparities in liver disease comorbidity among elderly Chinese based on a health ecological model: the China Health and Retirement Longitudinal Study

PURPOSE

This study aimed to investigate the risk factors for liver disease comorbidity among older adults in eastern, central, and western China, and explored binary, ternary and quaternary co-morbid co-causal patterns of liver disease within a health ecological model.

METHOD

Basic information from 9,763 older adults was analyzed using data from the China Health and Retirement Longitudinal Study (CHARLS). LASSO regression was employed to identify significant predictors in eastern, central, and western China. Patterns of liver disease comorbidity were studied using association rules, and spatial distribution was analyzed using a geographic information system. Furthermore, binary, ternary, and quaternary network diagrams were constructed to illustrate the relationships between liver disease comorbidity and co-causes.

RESULTS

Among the 9,763 elderly adults studied, 536 were found to have liver disease comorbidity, with binary or ternary comorbidity being the most prevalent. Provinces with a high prevalence of liver disease comorbidity were primarily concentrated in Inner Mongolia, Sichuan, and Henan. The most common comorbidity patterns identified were "liver-heart-metabolic", "liver-kidney", "liver-lung", and "liver-stomach-arthritic". In the eastern region, important combination patterns included "liver disease-metabolic disease", "liver disease-stomach disease", and "liver disease-arthritis", with the main influencing factors being sleep duration of less than 6 h, frequent drinking, female, and daily activity capability. In the central region, common combination patterns included "liver disease-heart disease", "liver disease-metabolic disease", and "liver disease-kidney disease", with the main influencing factors being an education level of primary school or below, marriage, having medical insurance, exercise, and no disabilities. In the western region, the main comorbidity patterns were "liver disease-chronic lung disease", "liver disease-stomach disease", "liver disease-heart disease", and "liver disease-arthritis", with the main influencing factors being general or poor health satisfaction, general or poor health condition, severe pain, and no disabilities.

CONCLUSION

The comorbidities associated with liver disease exhibit specific clustering patterns at both the overall and local levels. By analyzing the comorbidity patterns of liver diseases in different regions and establishing co-morbid co-causal patterns, this study offers a new perspective and scientific basis for the prevention and treatment of liver diseases.

Multimorbidity, consisting of a combination of chronic diseases and geriatric syndromes, predicts the risk of difficulty in discharge home in older patients admitted to acute care hospital

AIM

To determine whether multimorbidity, consisting of chronic diseases and geriatric syndromes, is associated with home discharge difficulties in older patients.

METHODS

A total of 522 older adults (mean age: 85 ± 7 years) who were admitted to an acute care hospital were enrolled. Multimorbidity was assessed by calculating the number of 16 chronic conditions (CCs): 8 chronic diseases (cardiac diseases, diabetes mellitus, chronic kidney disease, respiratory diseases, gastrointestinal diseases, anemia, dementia, and Parkinson disease) and 8 geriatric syndromes (depression, constipation, chronic pain, polypharmacy, dysphagia, underweight, hypoalbuminemia, and functional limitations). The patients were divided into four groups based on the number of CCs. The outcome was difficulty in discharging home (transfer to other facilities or in-hospital death). Multivariate logistic regression analysis was performed to assess independent associations between four CC groups and failure to discharge home after adjusting for age, sex, living alone, and Barthel index and odds ratio (OR) and 95% confidence interval (CI) were calculated.

RESULTS

Of the 522 patients, 18.8% were transferred to other facilities or died. The proportion of poor outcome in those with 0-2, 3-4, 5-6, and ≥7 CCs was 4.4%, 14.8%, 25.5%, and 37.5%, respectively. Logistic regression analysis after adjusting for covariates revealed that multimorbidity increased the risk of difficulty in discharging home (OR, 2.9 [95% CI, 1.1-8.0] for 3-4 CCs; OR, 4.9 [95% CI, 1.8-13.5] for 5-6 CCs; OR, 8.7 [95% CI, 3.1-24.6] for ≥7 CCs).

CONCLUSION

Multimorbidity, consisting of chronic diseases and geriatric syndromes, predicted difficulty in discharge home in older patients. Geriatr Gerontol Int 2024; 24: 300-305.

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.

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.

Longer Multimorbidity Intervals Are Associated With Lower Mortality in Diabetes: A Whole-Population Nested Case-Control Study

BACKGROUND

Approximately two-thirds of diabetes patients develop multimorbidity, which is associated with increased mortality. We aimed to examine whether, and to what extent, the time interval between pre-existing diabetes and a second chronic disease may be associated with the risk of mortality.

METHODS

We carried out a territory-wide nested case-control study using incidence density sampling, utilizing electronic health records from Hong Kong's public healthcare facilities. Among 158 732 patients first diagnosed with diabetes from January 1, 2010 to December 31, 2012 and subsequently developed multimorbidity as of December 31, 2019, we extracted those who died before December 31, 2019 as case participants. For each participant, we randomly matched with up to 4 people of the same sex, multimorbidity age, and second chronic condition who had not died after going through the same survival period of the case participant. Multimorbidity interval was included as a continuous variable. We used conditional logistic regression to estimate adjusted odds ratios (aOR) for mortality.

RESULTS

In total, 3508 case participants were matched with 14 032 control participants. Conditional logistic regression showed there were 19%-reduced odds of mortality following the extension of multimorbidity interval by 1 year. Similar associations were observed in men, women, people aged 64 years or younger, and older people aged 65 years or more.

CONCLUSIONS

Delayed multimorbidity among patients living with diabetes may be related to a lower risk of mortality. This study suggests that we should focus on mitigating and lowering the risk of multimorbidity in clinical management of diabetes to reduce further complication and mortality.

Latent class analyses of multimorbidity and all-cause mortality: A prospective study in Chilean adults

Multimorbidity patterns can lead to differential risks for all-cause mortality. Within the Chilean context, research on morbidity and mortality predominantly emphasizes individual diseases or combinations thereof, rather than specific disease clusters. This study aimed to identify multimorbidity patterns, along with their associations with mortality, within a representative sample of the Chilean population. 3,701 participants aged ≥18 from the Chilean National Health Survey 2009-2010 were included in this prospective study. Multimorbidity patterns were identified from 16 chronic conditions and then classified using latent class analyses. All-cause mortality data were extracted from the Chilean Civil Registry. The association of classes with all-cause mortality was carried out using Cox proportional regression models, adjusting by sociodemographic and lifestyle variables. Three classes were identified: a) Class 1, the healthiest (72.1%); b) Class 2, the depression/cardiovascular disease/cancer class (17.5%); and c) Class 3, hypertension/chronic kidney disease class (10.4%). Classes 2 and 3 showed higher mortality risk than the healthiest class. After adjusting, Class 2 showed 45% higher mortality risk, and Class 3 98% higher mortality risk, compared with the healthiest class. Hypertension appeared to be a critical underlying factor of all-cause morbidity. Particular combinations of chronic diseases have a higher excess risk of mortality than others.

Association of multimorbidity patterns with motoric cognitive risk syndrome among older adults: Evidence from a China longitudinal study

OBJECTIVES

Motoric cognitive risk syndrome (MCR), a pre-dementia syndrome, is characterized by slow gait and subjective cognitive complaints among older adults. This study assessed the relationship between multimorbidity, its patterns, and MCR.

METHODS

Data for this study were obtained from three waves (2011, 2013, and 2015) of the China Health and Retirement Longitudinal Study. Participants who were aged 60 years and older and had complete data at baseline as well as complete data about MCR at follow-up were selected. Patients without MCR at baseline were selected for further analyses. Longitudinal associations between multimorbidity, its patterns, and MCR were examined using a Cox proportional hazards model. Multimorbidity patterns were classified using latent class analysis.

RESULTS

A total of 4923 respondents were included at baseline, 43.47% of whom had multimorbidity. Additionally, the prevalence of MCR at baseline was 12.61%. After adjusting for covariates, multimorbidity was positively associated with MCR (hazard ratio [HR] = 1.33, 95% confidence interval [CI] = 1.06-1.68). A higher number of multimorbidity was also significantly associated with an increased risk of developing MCR (HR = 1.10, 95% CI = 1.02-1.19). Three multimorbidity patterns were selected: relatively healthy pattern, respiratory pattern, and cardiovascular pattern. Older adults with the cardiovascular pattern were 1.57 times more likely to develop MCR than those with the relatively healthy pattern (HR = 1.57, 95% CI = 1.16-2.13). There was no significant difference between the relatively healthy pattern and the respiratory pattern (HR = 1.31, 95% CI = 0.91-1.92).

CONCLUSIONS

MCR is highly prevalent among older Chinese adults. MCR may be exacerbated by multimorbidity. For older adults with multimorbidity (especially cardiovascular multimorbidity), attention should be paid to MCR to achieve early detection, diagnosis, and treatment.

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.

Optimising the care for older persons with complex chronic conditions in home care and nursing homes: design and protocol of I-CARE4OLD, an observational study using real-world data

INTRODUCTION

In ageing societies, the number of older adults with complex chronic conditions (CCCs) is rapidly increasing. Care for older persons with CCCs is challenging, due to interactions between multiple conditions and their treatments. In home care and nursing homes, where most older persons with CCCs receive care, professionals often lack appropriate decision support suitable and sufficient to address the medical and functional complexity of persons with CCCs. This EU-funded project aims to develop decision support systems using high-quality, internationally standardised, routine care data to support better prognostication of health trajectories and treatment impact among older persons with CCCs.

METHODS AND ANALYSIS

Real-world data from older persons aged ≥60 years in home care and nursing homes, based on routinely performed comprehensive geriatric assessments using interRAI systems collected in the past 20 years, will be linked with administrative repositories on mortality and care use. These include potentially up to 51 million care recipients from eight countries: Italy, the Netherlands, Finland, Belgium, Canada, USA, Hong Kong and New Zealand. Prognostic algorithms will be developed and validated to better predict various health outcomes. In addition, the modifying impact of pharmacological and non-pharmacological interventions will be examined. A variety of analytical methods will be used, including techniques from the field of artificial intelligence such as machine learning. Based on the results, decision support tools will be developed and pilot tested among health professionals working in home care and nursing homes.

ETHICS AND DISSEMINATION

The study was approved by authorised medical ethical committees in each of the participating countries, and will comply with both local and EU legislation. Study findings will be shared with relevant stakeholders, including publications in peer-reviewed journals and presentations at national and international meetings.

Association between sleep problems and multimorbidity patterns in older adults

BACKGROUND

Sleep problems are frequent in older adults and are associated with chronic diseases. However, the association with multimorbidity patterns is still unknown. Considering the negative impacts that multimorbidity patterns can have on older adults' life, knowledge of this association can help in the screening and early identification of older adults with sleep problems. The objective was to verify the association between sleep problems and multimorbidity patterns in older Brazilian adults.

METHODS

This was a cross-sectional study conducted with data from 22,728 community-dwelling older adults from the 2019 National Health Survey. The exposure variable was self-reported sleep problems (yes/no). The study outcomes were: multimorbidity patterns, analyzed by self-report of the coexistence of two or more chronic diseases with similar clinical characteristics: (1) cardiopulmonary; (2) vascular-metabolic; (3) musculoskeletal; (4) coexisting patterns.

RESULTS

Older adults with sleep problems had 1.34 (95%CI: 1.21; 1.48), 1.62 (95%CI: 1.15; 2.28), 1.64 (95%CI: 1.39; 1.93), and 1.88 (95%CI: 1.52; 2.33) greater odds of presenting vascular-metabolic, cardiopulmonary, musculoskeletal, and coexisting patterns, respectively.

CONCLUSIONS

These results suggest that public health programs aimed at preventing sleep problems in older adults are essential to reduce possible adverse health outcomes, including multimorbidity patterns and their negative consequences for older adults' health.

Frailty, multimorbidity patterns and mortality in institutionalized older adults in Italy

Background

Little is known on how frailty influences clinical outcomes in persons with specific multimorbidity patterns.

Aims

To investigate the interplay between multimorbidity and frailty in the association with mortality in older individuals living in nursing homes (NH).

Methods

We considered 4,131 NH residents aged 60 years and over, assessed through the interRAI LTCF instrument between 2014 and 2018. Follow-up was until 2019. Considering four multimorbidity patterns identified via principal component analysis, subjects were stratified in tertiles (T) with respect to their loading values. Frailty Index (FI) considered 23 variables and a cut-off of 0.24 distinguished between high and low frailty levels. For each pattern, all possible combinations of tertiles and FI were evaluated. Their association (Hazard Ratio [HR] and 95% confidence interval) with mortality was tested in Cox regression models.

Results

In the heart diseases and dementia and sensory impairments patterns, the hazard of death increases progressively with patterns expression and frailty severity (being HR T3 vs. T1 = 2.36 [2.01–2.78]; HR T3 vs. T1 = 2.12 [1.83–2.47], respectively). In heart, respiratory and psychiatric diseases and diabetes, musculoskeletal and vascular diseases patterns, frailty seems to have a stronger impact on mortality than patterns’ expression.

Discussion

Frailty increases mortality risk in all the patterns and provides additional prognostic information in NH residents with different multimorbidity patterns.

Conclusions

These findings support the need to routinely assess frailty. Older people affected by specific groups of chronic diseases need a specific care approach and have high risk of negative health outcomes.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40520-022-02269-8.