Multimorbidity: constellations of conditions across subgroups of midlife and older individuals, and related Medicare expenditures

Multimorbidity clusters in adults 50 years or older with and without a history of cancer: National Health Interview Survey, 2018

BACKGROUND

Multimorbidity is increasing among adults in the United States. Yet limited research has examined multimorbidity clusters in persons aged 50 years and older with and without a history of cancer. An increased understanding of multimorbidity clusters may improve the cancer survivorship experience for survivors with multimorbidity.

METHODS

We identified 7580 adults aged 50 years and older with 2 or more diseases-including 811 adults with a history of primary breast, colorectal, cervical, prostate, or lung cancer-from the 2018 National Health Interview Survey. Exploratory factor analysis identified clusters of multimorbidity among cancer survivors and individuals without a history of cancer (controls). Frequency tables and chi-square tests were performed to determine overall differences in sociodemographic characteristics, health-related characteristics, and multimorbidity between groups.

RESULTS

Cancer survivors reported a higher prevalence of having 4 or more diseases compared to controls (57% and 38%, respectively). Our analysis identified 6 clusters for cancer survivors and 4 clusters for controls. Three clusters (pulmonary, cardiac, and liver) included the same diseases for cancer survivors and controls.

CONCLUSIONS

Diseases clustered differently across adults ≥ 50 years of age with and without a history of cancer. Findings from this study may be used to inform clinical care, increase the development and dissemination of multilevel public health interventions, escalate system improvements, and initiate innovative policy reform.

How do older adults with multimorbidity navigate healthcare?: a qualitative study in Singapore

BACKGROUND

Patients living with multimorbidity may require frequent visits to multiple healthcare institutions and to follow diverse medical regimens and advice. Older adults with multimorbidity could face additional challenges because of declining cognitive capability, frailty, increased complexity of diseases, as well as limited social and economic resources. Research on how this population navigates the healthcare system in Singapore also remains unknown. This study investigates the challenges older adults with multimorbidity face in navigating healthcare in Singapore.

METHODS

Twenty older adults with multimorbidity from a public primary care setting were purposively sampled. Interviews conducted inquired into their experiences of navigating the healthcare system with multiple conditions. Inductive thematic analysis was performed by independent coders who resolved differences through discussion.

RESULTS

Older adults with multimorbidity form a population with specific characteristics and challenges. Their ability to navigate the healthcare system well was influenced by these themes including patient-related factors (autonomy and physical mobility, literacy and technological literacy, social support network), healthcare system-related factors (communication and personal rapport, fragmented system, healthcare staff as advocate) and strategies for navigation (fitting in, asking for help, negotiating to achieve goals, managing the logistics of multimorbidity).

DISCUSSION

Older adults with multimorbidity should not be treated as a homogenous group but can be stratified according to those with less serious or disruptive conditions (less burden of illness and burden of treatment) and those with more severe conditions (more burden of illness and burden of treatment). Among the latter, some became navigational experts while others struggled to obtain the resources needed. The variations of navigational experiences of the healthcare system show the need for further study of the differential needs of older adults with multimorbidity. To be truly patient-centred, healthcare providers should consider factors such as the existence of family support networks, literacy, technological literacy and the age-related challenges older adults face as they interact with the healthcare system, as well as finding ways to improve healthcare systems through personal rapport and strategies for reducing unnecessary burden of treatment for patients with multimorbidity.

Estimating health spending associated with chronic multimorbidity in 2018: An observational study among adults in the United States

BACKGROUND

The rise in health spending in the United States and the prevalence of multimorbidity-having more than one chronic condition-are interlinked but not well understood. Multimorbidity is believed to have an impact on an individual's health spending, but how having one specific additional condition impacts spending is not well established. Moreover, most studies estimating spending for single diseases rarely adjust for multimorbidity. Having more accurate estimates of spending associated with each disease and different combinations could aid policymakers in designing prevention policies to more effectively reduce national health spending. This study explores the relationship between multimorbidity and spending from two distinct perspectives: (1) quantifying spending on different disease combinations; and (2) assessing how spending on a single diseases changes when we consider the contribution of multimorbidity (i.e., additional/reduced spending that could be attributed in the presence of other chronic conditions).

METHODS AND FINDINGS

We used data on private claims from Truven Health MarketScan Research Database, with 16,288,894 unique enrollees ages 18 to 64 from the US, and their annual inpatient and outpatient diagnoses and spending from 2018. We selected conditions that have an average duration of greater than one year among all Global Burden of Disease causes. We used penalized linear regression with stochastic gradient descent approach to assess relationship between spending and multimorbidity, including all possible disease combinations with two or three different conditions (dyads and triads) and for each condition after multimorbidity adjustment. We decomposed the change in multimorbidity-adjusted spending by the type of combination (single, dyads, and triads) and multimorbidity disease category. We defined 63 chronic conditions and observed that 56.2% of the study population had at least two chronic conditions. Approximately 60.1% of disease combinations had super-additive spending (e.g., spending for the combination was significantly greater than the sum of the individual diseases), 15.7% had additive spending, and 23.6% had sub-additive spending (e.g., spending for the combination was significantly less than the sum of the individual diseases). Relatively frequent disease combinations (higher observed prevalence) with high estimated spending were combinations that included endocrine, metabolic, blood, and immune disorders (EMBI disorders), chronic kidney disease, anemias, and blood cancers. When looking at multimorbidity-adjusted spending for single diseases, the following had the highest spending per treated patient and were among those with high observed prevalence: chronic kidney disease ($14,376 [12,291,16,670]), cirrhosis ($6,465 [6,090,6,930]), ischemic heart disease (IHD)-related heart conditions ($6,029 [5,529,6,529]), and inflammatory bowel disease ($4,697 [4,594,4,813]). Relative to unadjusted single-disease spending estimates, 50 conditions had higher spending after adjusting for multimorbidity, 7 had less than 5% difference, and 6 had lower spending after adjustment.

CONCLUSIONS

We consistently found chronic kidney disease and IHD to be associated with high spending per treated case, high observed prevalence, and contributing the most to spending when in combination with other chronic conditions. In the midst of a surging health spending globally, and especially in the US, pinpointing high-prevalence, high-spending conditions and disease combinations, as especially conditions that are associated with larger super-additive spending, could help policymakers, insurers, and providers prioritize and design interventions to improve treatment effectiveness and reduce spending.

Association rules analysis on patterns of multimorbidity in adults: based on the National Health and Nutrition Examination Surveys database

OBJECTIVE

To explore the prevalence and patterns of multimorbidity in population with different genders and age ranges.

DESIGN

A cross-sectional study.

SETTING

National Health and Nutrition Examination Surveys database.

PARTICIPANTS

12 576 patients.

PRIMARY AND SECONDARY OUTCOME MEASURES

The prevalence and patterns of multimorbidity.

RESULTS

High cholesterol had the highest prevalence in all population (33.4 (95% CI: 32.0 to 34.9)) and males. In females <65 years, the most prevalent disease was sleep disorder (32.1 (95% CI: 29.6 to 34.5)) while in females ≥65 years, hypertension was the most prevalent disease (63.9 (95% CI: 59.9 to 67.9)). Hypertension and high cholesterol were associated with the highest support (occur together most frequently) in all population regardless of genders. Hypertension displayed the highest betweenness centrality (mediating role in the network) followed by high cholesterol and arthritis in all population. For males aged <65 years, hypertension and high cholesterol presented the highest betweenness centrality. In males ≥65 years, hypertension, high cholesterol and arthritis were the top three diseases of degree centrality (direct association with other conditions). As for females ≥65 years, hypertension showed the highest betweenness centrality followed by high cholesterol and arthritis. The associations of hypertension, arthritis and one other item with high cholesterol presented the highest support in all population. In males, the associations of depression, hypertension with sleep disorders had the highest lift (the chance of co-occurrence of the conditions and significant association). Among females, the associations of depression, arthritis with sleep disorders had the highest lift.

CONCLUSION

Hypertension and high cholesterol were prevalent in all population, regardless of females and males. Hypertension and high cholesterol, arthritis and hypertension, and diabetes and hypertension were more likely to coexist. The findings of this study might help make plans for the management and primary care of people with one or more diseases.

Prevalence of multimorbidity combinations and their association with medical costs and poor health: A population-based study of U.S. adults

Background

Multimorbidity is common, but the prevalence and burden of the specific combinations of coexisting disease has not been systematically examined in the general U.S. adult population.

Objective

To identify and estimate the burden of highly prevalent combinations of chronic conditions that are treated among one million or more adults in the United States.

Methods

Cross-sectional analysis of U.S. households in the Medical Expenditure Panel Survey (MEPS), 2016-2019, a large nationally-representative sample of the community-dwelling population. Association rule mining was used to identify the most common combinations of 20 chronic conditions that have high relevance, impact, and prevalence in primary care. The main measures and outcomes were annual treated prevalence, total medical expenditures, and perceived poor health. Logistic regression models with poor health as the outcome and each multimorbidity combination as the exposure were used to calculate adjusted odds ratios and 95% confidence intervals.

Results

Frequent pattern mining yielded 223 unique combinations of chronic disease, including 74 two-way (dyad), 115 three-way (triad), and 34 four-way combinations that are treated in one million or more U.S. adults. Hypertension-hyperlipidemia was the most common two-way combination occurring in 30.8 million adults. The combination of diabetes-arthritis-cardiovascular disease was associated with the highest median annual medical expenditures ($23,850, interquartile range: $11,593-$44,616), and the combination of diabetes-arthritis-asthma/COPD had the highest age-race-sex adjusted odds ratio of poor self-rated health (adjusted odd ratio: 6.9, 95%CI: 5.4-8.8).

Conclusion

This study demonstrates that many multimorbidity combinations are highly prevalent among U.S. adults, yet most research and practice-guidelines remain single disease focused. Highly prevalent and burdensome multimorbidity combinations could be prioritized for evidence-based research on optimal prevention and treatment strategies.

Association of Complex Multimorbidity and Long-term Survival After Emergency General Surgery in Older Patients With Medicare

Importance

Although nearly 1 million older patients are admitted for emergency general surgery (EGS) conditions yearly, long-term survival after these acute diseases is not well characterized. Many older patients with EGS conditions have preexisting complex multimorbidity defined as the co-occurrence of at least 2 of 3 key domains: chronic conditions, functional limitations, and geriatric syndromes. The hypothesis was that specific multimorbidity domain combinations are associated with differential long-term mortality after patient admission with EGS conditions.

Objective

To examine multimorbidity domain combinations associated with increased long-term mortality after patient admission with EGS conditions.

Design, Setting, and Participants

This cohort study included community-dwelling participants aged 65 years and older from the Medicare Current Beneficiary Survey with linked Medicare data (January 1992 through December 2013) and admissions for diagnoses consistent with EGS conditions. Surveys on health and function from the year before EGS conditions were used to extract the 3 domains: chronic conditions, functional limitations, and geriatric syndromes. The number of domains present were summed to calculate a categorical rank: no multimorbidity (0 or 1), multimorbidity 2 (2 of the 3 domains present), and multimorbidity 3 (all 3 domains present). Whether operative treatment was provided during the admission was also identified. Data were cleaned and analyzed between January 16, 2020, and April 29, 2021.

Exposures

Mutually exclusive multimorbidity domain combinations (functional limitations and geriatric syndromes; functional limitations and chronic conditions; chronic conditions and geriatric syndromes; or functional limitations, geriatric syndromes, and chronic conditions).

Main Outcomes and Measures

Time to death (up to 3 years from EGS conditions admission) in patients with multimorbidity combinations was analyzed using a Cox proportional hazards model and compared with those without multimorbidity; hazard ratios (HRs) and 95% CIs are presented. Models were adjusted for age, sex, and operative treatment.

Results

Of 1960 patients (median [IQR] age, 79 [73-85] years; 1166 [59.5%] women), 383 (19.5%) had no multimorbidity, 829 (42.3%) had 2 multimorbidity domains, and 748 (38.2%) had all 3 domains present. A total of 376 (19.2%) were known to have died in the follow-up period, with a median (IQR) follow-up of 377 (138-621) days. Patients with chronic conditions and geriatric syndromes had a mortality risk similar to those without multimorbidity. However, all domain combinations with functional limitations were associated with significantly increased risk of death: functional limitations and chronic conditions (HR, 1.83; 95% CI, 1.03-3.23); functional limitations and geriatric syndromes (HR, 2.91; 95% CI, 1.37-6.18); and functional limitations, geriatric syndromes, and chronic conditions (HR, 2.08; 95% CI, 1.49-2.89).

Conclusions and Relevance

Findings of this study suggest that a patient's baseline complex multimorbidity level efficiently identifies risk stratification groups for long-term survival. Functional limitations are rarely considered in risk stratification paradigms for older patients with EGS conditions compared with chronic conditions and geriatric syndromes. However, functional limitations may be the most important risk factor for long-term survival.

Burden of Chronic and Acute Conditions and Symptoms in People With Epilepsy

BACKGROUND AND OBJECTIVES

People with epilepsy, one-third of whom in the United States are on Medicaid, experience a wide range of chronic and physical comorbidities that influence their care and outcomes. In this study, we examine the burden and racial/ethnic disparities of chronic and acute conditions, injuries, and symptoms in a large and diverse group of people with epilepsy on Medicaid.

METHODS

Using 5 years of Medicaid claims data, we identified adults with epilepsy and used all available claims and diagnoses to identify each person's Clinical Classification Codes groups diagnosed during the study period. Using association rule mining, we identified the top combinations of conditions and stratified these by race/ethnicity to identify potential prevalence disparities. We examined the top combinations of conditions in high utilizers; that is, individuals in the top quartile of hospitalizations and emergency department visits.

RESULTS

Among 81,963 patients, the most common conditions were anxiety and mood disorders (46.5%), hypertension (36.9%), back problems (35.2%), developmental disorders (31.6%), and headache (29.5%). When examining combinations of conditions, anxiety and mood disorders continued to have an outsized prevalence, appearing in nearly every combination. There were notable disparities in disease burden, with American Indians and Alaskan Natives having a substantially higher prevalence of developmental disorders, while Black individuals had a higher prevalence of hypertension. These disparities persisted to the higher-order combinations that included these conditions. High utilizers had a much higher disease burden, with 75.8% having an anxiety or mood disorder, as well as a higher burden of injuries.

DISCUSSION

This study shows a high prevalence of psychiatric and physical conditions and identifies racial and ethnic disparities affecting people with epilepsy. Targeting interventions to consider the comorbidities, race, and ethnicity has potential to improve clinical care and reduce disparities.

Race-Related Differences Between and Within Sex to Experimental Thermal Pain in Middle and Older Adulthood: An Exploratory Pilot Analysis

This brief report details a pilot analysis conducted to explore racial differences in pain sensitivity and unpleasantness between cognitively healthy Black and White adults, stratified by sex. A total of 24 cognitively healthy adults (12 Black and 12 White) from two completed studies were matched by age and sex, and divided into two groups based on race. Stratified analyses by sex demonstrated that Black females reported experiencing pain intensity ratings of all three intensity sensations at lower temperatures than White females. These findings will inform future research studies to determine if these results hold true in a fully-powered sample and should include mixed methodologies, incorporating neuroimaging data to further assess this phenomenon. Improving pain assessment and management across racial/ethnic groups will help healthcare providers such as nurses and physicians to ensure optimal quality of life for all.

Prevalence, pattern and determinants of chronic disease multimorbidity in Nepal: secondary analysis of a national survey

OBJECTIVES

To assess the prevalence, pattern and determinants of non-communicable diseases (NCDs) multimorbidity in Nepal.

DESIGN

Secondary analysis of the data from the NCD survey 2018, which was conducted between 2016 and 2018.

SETTING

The data belong to the nationally representative survey, that selected the study samples from throughout Nepal using multistage cluster sampling.

PARTICIPANTS

8931 participants aged 20 years and older were included in the study.

PRIMARY OUTCOMES

NCD multimorbidity (occurrence of two or more chronic conditions including hypertension, diabetes, chronic obstructive pulmonary disease, chronic kidney disease, coronary artery disease and cancer). Descriptive statistics, prevalence ratio and odds ratio were computed to assess pattern and determinants of multimorbidity.

RESULTS

Mean (SD) age was 46.7 years (14.9 years). The majority of the participants were women (57.8%), without formal education (53.4%) and from urban areas (51.5%). Multimorbidity was present in 13.96% (95% CI: 12.9% to 15.1%). Hypertension and diabetes coexisted in 5.7%. Age, alcohol consumption, body mass index, non-high-density lipoprotein (non-HDL) level and rural-urban setting were significantly associated with multimorbidity.

CONCLUSION

Multimorbidity was prevalent in particular groups or geographical areas in Nepal suggesting a need for coordinated and integrated NCD care approach for the management of multiplicative co-comorbid conditions.

Racial and Ethnic Differences in Multimorbidity Changes Over Time

BACKGROUND

Our understanding of how multimorbidity progresses and changes is nascent.

OBJECTIVES

Assess multimorbidity changes among racially/ethnically diverse middle-aged and older adults.

DESIGN, SETTING, AND PARTICIPANTS

Prospective cohort study using latent class analysis to identify multimorbidity combinations over 16 years, and multinomial logistic models to assess change relative to baseline class membership. Health and Retirement Study respondents (age 51 y and above) in 1998 and followed through 2014 (N=17,297).

MEASURES

Multimorbidity latent classes of: hypertension, heart disease, lung disease, diabetes, cancer, arthritis, stroke, high depressive symptoms.

RESULTS

Three latent classes were identified in 1998: minimal disease (45.8% of participants), cardiovascular-musculoskeletal (34.6%), cardiovascular-musculoskeletal-mental (19.6%); and 3 in 2014: cardiovascular-musculoskeletal (13%), cardiovascular-musculoskeletal-metabolic (12%), multisystem multimorbidity (15%). Remaining participants were deceased (48%) or lost to follow-up (12%) by 2014. Compared with minimal disease, individuals in cardiovascular-musculoskeletal in 1998 were more likely to be in multisystem multimorbidity in 2014 [odds ratio (OR)=1.78, P<0.001], and individuals in cardiovascular-musculoskeletal-mental in 1998 were more likely to be deceased (OR=2.45, P<0.001) or lost to follow-up (OR=3.08, P<0.001). Hispanic and Black Americans were more likely than White Americans to be in multisystem multimorbidity in 2014 (OR=1.67, P=0.042; OR=2.60, P<0.001, respectively). Black compared with White Americans were more likely to be deceased (OR=1.62, P=0.01) or lost to follow-up (OR=2.11, P<0.001) by 2014.

CONCLUSIONS AND RELEVANCE

Racial/ethnic older adults are more likely to accumulate morbidity and die compared with White peers, and should be the focus of targeted and enhanced efforts to prevent and/or delay progression to more complex multimorbidity patterns.

Mining Complex Genetic Patterns Conferring Multiple Sclerosis Risk

(1) Background: Complex genetic relationships, including gene-gene (G × G; epistasis), gene(n), and gene-environment (G × E) interactions, explain a substantial portion of the heritability in multiple sclerosis (MS). Machine learning and data mining methods are promising approaches for uncovering higher order genetic relationships, but their use in MS have been limited. (2) Methods: Association rule mining (ARM), a combinatorial rule-based machine learning algorithm, was applied to genetic data for non-Latinx MS cases (n = 207) and controls (n = 179). The objective was to identify patterns (rules) amongst the known MS risk variants, including HLA-DRB1*15:01 presence, HLA-A*02:01 absence, and 194 of the 200 common autosomal variants. Probabilistic measures (confidence and support) were used to mine rules. (3) Results: 114 rules met minimum requirements of 80% confidence and 5% support. The top ranking rule by confidence consisted of HLA-DRB1*15:01, SLC30A7-rs56678847 and AC093277.1-rs6880809; carriers of these variants had a significantly greater risk for MS (odds ratio = 20.2, 95% CI: 8.5, 37.5; p = 4 × 10⁻⁹). Several variants were shared across rules, the most common was INTS8-rs78727559, which was in 32.5% of rules. (4) Conclusions: In summary, we demonstrate evidence that specific combinations of MS risk variants disproportionately confer elevated risk by applying a robust analytical framework to a modestly sized study population.

Impact of Instrumental Activities of Daily Living Limitations on Hospital Readmission: an Observational Study Using Machine Learning

BACKGROUND

Limitations in instrumental activities of daily living (IADL) hinder a person's ability to live independently in the community and self-manage their conditions, but its impact on hospital readmission has not been firmly established.

OBJECTIVE

To test the importance of IADL dependency as a predictor of 30-day readmissions and quantify its impact relative to other morbidities.

DESIGN

A retrospective cohort study of the population-based Health and Retirement Study linked to Medicare claims data. Random forest was used to rank each predictor variable in terms of its ability to predict readmission. Classification and regression tree (CART) was used to identify complex multimorbidity combinations associated with high or low risk of readmission. Generalized linear regression was used to estimate the adjusted relative risk of readmission for IADL limitations.

SUBJECTS

Hospitalizations of adults age 65 and older (n = 20,007), from 6617 unique subjects.

MAIN MEASURES

The main outcome was 30-day all-cause unplanned readmission. The main predictor of interest was self-reported IADL limitation. Other key predictors were self-reported complex multimorbidity including chronic diseases, geriatric syndromes, and activities of daily living (ADL) limitations, along with demographic, socioeconomic, and behavioral factors.

KEY RESULTS

The overall 30-day readmission rate in the study was 16.4%. Random forest analysis ranked ADLs and IADL limitations as the two most important predictors of 30-day readmission. CART identified hospitalizations of patients with IADL limitations and diabetes as a subgroup at the highest risk of readmission (26% readmitted). Multivariable regression analyses showed that ADL limitations were associated with 1.17 (1.06-1.29) times higher risk of readmission even after adjusting for other patient covariates. Risk prediction was modest though for even the best model (AUC = 0.612).

CONCLUSIONS

IADL limitations are key predictors of 30-day readmission as demonstrated using several machine learning methods. Routine assessment of functional abilities in hospital settings could help identify those most at risk.

Multimorbidity of chronic non-communicable diseases and its models of care in low- and middle-income countries: a scoping review protocol

INTRODUCTION

Multimorbidity is the coexistence of two or more chronic non-communicable diseases (NCDs) in a given individual. Multimorbidity is increasing in low- and middle-income countries (LMICs) and challenging health systems. Individuals with multimorbidity are facing the risk of premature mortality, lower quality of life and greater use of healthcare services. However, despite the huge challenge multimorbidity brings in LMICs, gaps remain in mapping and synthesising the available knowledge on the issue. The focus of this scoping review will be to synthesise the extent, range and nature of studies on the epidemiology and models of multimorbidity care in LMICs.

METHODS

PubMed (MEDLINE) will be the main database to be searched. For articles that are not indexed in the PubMed, Scopus, PsycINFO and Cochrane databases will be searched. Grey literature databases will also be explored. There will be no restrictions on study setting or year of publication. Articles will be searched using key terms, including comorbidity, co-morbidity, multimorbidity, multiple chronic conditions and model of care. Relevant articles will be screened by two independent reviewers and data will be charted accordingly. The result of this scoping review will be presented using the Preferred Reporting Items for Systematic Review and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) checklist and reporting guideline.

ETHICS AND DISSEMINATION

This scoping review does not require ethical approval. Findings will be published in peer-reviewed journal and presented at scientific conferences.

Association Between Adverse Childhood Events and Multimorbidity in a Racial and Ethnic Diverse Sample of Middle-Aged and Older Adults

Background and Objectives

Adverse childhood events (ACEs) have been associated with increased health risks later in life. However, it is unclear whether ACEs may be associated with multimorbidity among diverse racial/ethnic middle-aged and older adults. We evaluated whether there were racial and ethnic differences in the association between ACEs and the number of somatic and psychiatric multimorbidity in a sample of U.S. middle-aged and older adults.

Research Design and Methods

Data from the 2012-2013 National Epidemiologic Survey on Alcohol and Related Conditions (N = 10,727; ≥55 years) were used to test whether the number of self-reported somatic conditions (i.e., heart disease, hypertension, stroke, diabetes, arthritis, cancer, osteoporosis, and chronic lung problems) as well as DSM-5 psychiatric disorders (i.e., depression) during the past 12 months differed by history of ACEs while stratifying by age (i.e., 55-64 or ≥65) and racial/ethnic group (i.e., non-Hispanic White [NHW; n = 7,457], non-Hispanic Black [NHB; n = 1,995], and Hispanic [n=1275]).

Results

The prevalence of reporting more than two somatic conditions and psychiatric disorders was 48.8% and 11.4% for those with a history of ACEs, and 41.1% and 3.3% for those without a history of ACEs. Adjusting for sociodemographic and other health risk factors, ACEs was significantly associated with greater numbers of somatic multimorbidity among racial and ethnic middle-aged adults but this was not the case for older adults.

Discussion and Implications

Our findings suggest that middle-aged adults with a history of ACEs are more likely to suffer from somatic and psychiatric multimorbidity, highlighting the importance of screening for ACEs in promoting healthy aging.

The Influence of Multimorbidity on Leading Causes of Death in Older Adults With Cognitive Impairment

Objective: The aim of this study is to evaluate the relationship of leading causes of death with gradients of cognitive impairment and multimorbidity. Method: This is a population-based study using data from the linked 1992-2010 Health and Retirement Study and National Death Index (n = 9,691). Multimorbidity is defined as a combination of chronic conditions, functional limitations, and geriatric syndromes. Regression trees and Random Forest identified which combinations of multimorbidity associated with causes of death. Results: Multimorbidity is common in the study population. Heart disease is the leading cause in all groups, but with a larger percentage of deaths in the mild and moderate/severe cognitively impaired groups than among the noncognitively impaired. The different "paths" down the regression trees show that the distribution of causes of death changes with different combinations of multimorbidity. Discussion: Understanding the considerable heterogeneity in chronic conditions, functional limitations, geriatric syndromes, and causes of death among people with cognitive impairment can target care management and resource allocation.

Increasing Burden of Complex Multimorbidity Across Gradients of Cognitive Impairment

INTRODUCTION

This study evaluates the burden of multimorbidity (MM) across gradients of cognitive impairment (CI).

METHODS

Using data from the 2010 Health and Retirement Study, we identified individuals with no CI, mild CI, and moderate/severe CI. In addition, we adopted an expansive definition of complex MM by accounting for the occurrence and co-occurrence of chronic conditions, functional limitations, and geriatric syndromes.

RESULTS

In a sample of 18 913 participants (weighted n = 87.5 million), 1.93% and 1.84% presented with mild and moderate/severe CI, respectively. The prevalence of most conditions constituting complex MM increased markedly across the spectrum of CI. Further, the percentage of individuals presenting with 10 or more conditions was 19.9%, 39.3%, and 71.3% among those with no CI, mild CI, and moderate/severe CI, respectively.

DISCUSSION

Greater CI is strongly associated with increased burden of complex MM. Detailed characterization of MM across CI gradients will help identify opportunities for health care improvement.