Combinations Of Chronic Conditions Research Articles

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

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. 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. 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. 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). 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.

Cultivating informatics capacity for multimorbidity: A learning health systems use case.

BackgroundThe aim of this study was to characterize patterns of multimorbidity across patients and identify opportunities to strengthen the informatics capacity of learning health systems that are used to characterize multimorbidity across patients.MethodsElectronic health record (EHR) data on 225,710 multimorbidity patients were extracted from the Arkansas Clinical Data Repository as a use case. Hierarchical cluster analysis identified the most frequently occurring combinations of chronic conditions within the learning health system’s captured data.ResultsResults revealed multimorbidity was highest among patients ages 60 to 74, Caucasians, females, and Medicare payors. The largest numbers of chronic conditions occurred in the smallest numbers of patients (i.e., 70,262 (31%) patients with two conditions, two (<1%) patients with 22 chronic conditions). The results revealed urgent needs to improve EHR systems and processes that collect and manage multimorbidity data (e.g., creating new, multimorbidity-centric data elements in EHR systems, detailed longitudinal tracking of compounding disease diagnoses).ConclusionsWithout additional capacity to collect and aggregate large-scale data, multimorbidity patients cannot benefit from the recent advancements in informatics (i.e., clinical data registries, emerging data standards) that are abundantly working to improve the outcomes of patients with single chronic conditions. Additionally, robust socio-technical system studies of clinical workflows are needed to assess the feasibility of integrating the collection of risk factor data elements (i.e., psycho-social, cultural, ethnic, and socioeconomic attributes of populations) into primary care encounters. These approaches to advancing learning health systems for multimorbidity could substantially reduce the constraints of current technologies, data, and data-capturing processes.

Combinations of chronic conditions, functional limitations and geriatric syndromes associated with periodontal disease

ObjectiveTo identify complex multimorbid conditions, including chronic conditions, functional limitations and geriatric syndromes, associated with the presence and severity of periodontal disease (PD), after accounting for a series of demographic...

Identifying Factors Associated with Periodontal Disease Using Machine Learning.

This study aimed to identify combinations of chronic conditions associated with the presence and severity of periodontal disease (PD) after accounting for a series of demographic and behavioral characteristics in a nationally representative sample of US adults. A cross-sectional study of the 2013-2014 National Health and Nutrition Examination Survey (n = 4555). Outcome measure: PD using clinical attachment loss (measured as none, mild, moderate, or severe). The main independent variables were self-reported chronic conditions, while other covariates included demographic and behavioral variables. Classification and regression tree analysis was used to identify combinations of specific chronic conditions associated with PD and PD with higher severity. Random forest was used to identify the most important variables associated with the presence and severity of PD. The prevalence of PD was 77% among the study population. The percentage of those with PD was higher among younger and middle-aged (< 61 years old) than older (> 61 years old) adults. Age and education level were the two most important predictors for the presence and severity of PD. Other significant factors included alcohol use, type of medical insurance, sex, and non-white race. Accounting for only chronic conditions, hypertension and diabetes were the two chronic conditions associated with the presence and severity of PD. Sociodemographic and behavioral factors emerged as more strongly associated with the presence and severity of PD than chronic conditions. Accounting for the co-occurrence for sociodemographic and behavioral factors will be informative for identifying people vulnerable to the development of PD.

Multiple Chronic Condition Combinations, Affect, and Memory Among Black and White Older Adults

Research demonstrates the adverse effects of coexisting multiple chronic conditions (MCCs) on older adults’ health and wellbeing. While most research relies on total counts of chronic conditions, little work explores how specific MCC combinations may have compounding effects on depression and memory. Furthermore, no published research explores differences in the prevalence and correlates of MCC combinations between Black and White older adults. The current study assesses within- and between-group heterogeneity in the prevalence and correlates of MCC combinations to advance health equity research. We utilize a sample of 16,757 Black and White older adults drawn from the 2014 wave of the Health and Retirement Study. Respondents were categorized into one of 32 MCC combination groups. Depressive symptoms and self-rated memory were calculated separately for Black and White respondents across each of the 32 groups. Chi-square tests, t-tests, and ANCOVAs were used to compare differences. Black and White respondents differed significantly in the prevalence of 14 out of 32 MCC combinations. Within-group differences were found such that 45% of Black respondents experiencing only Lung Disease met criteria for clinical depression; this rate is similar to Black respondents experiencing Diabetes + Heart Condition + Hypertension + Lung Disease (44.5%). Between-group differences revealed that Black respondents experiencing Arthritis + Diabetes + Hypertension had worse self-rated memory than White counterparts (MB = 3.24, MW = 3.13; two sample t[1139]= -2.04, p < .05; Cohen’s d = 0.13). Additional findings are presented, and theoretical and practical implications for this work are discussed.

Multiple Chronic Condition Combinations and Cognitive Task Performance

A growing body of literature describes important advances in the study of chronic conditions, most notably a paradigm shift from the study of individual chronic conditions to the study of multiple chronic conditions (MCCs). Despite these advances, little research has explored MCC combinations, and almost no published research has explored how MCC combinations are related to cognitive outcomes in older adult populations. Using data from the Health and Retirement Study, we categorized 17,349 older adults into one of 32 groups using self-reports of five of the most commonly diagnosed conditions. These included arthritis, diabetes, heart problems, hypertension, and respiratory problems. We utilized ANOVA to examine the associations between combinations of MCCs and performance on two cognitive tasks associated with executive function and fluid intelligence: verbal fluency and verbal analogies. Results demonstrated that older adults with a greater number of health conditions performed more poorly on both the verbal fluency (p<.0001) and analogies (p<.0001) tasks than those with fewer conditions. Some MCC combinations were associated with poorer cognitive task performance than other combinations: for example, older adults in the Heart-Hypertension-Respiratory group had an average score of 488.73 (SD=24.96) on the verbal analogies task and 14.06 (SD=7.06) on the verbal fluency task. Conversely, adults in the Arthritis-Heart-Respiratory group had average scores of 503.69 (SD=27.89) and 16.45 (SD=7.03), respectively, suggesting differential additive effects of MCCs. These findings demonstrate the complex associations of specific MCC combinations with cognitive performance and highlight the importance of better understanding the unique needs of older people with MCCs.

Diabetes multimorbidity combinations and disability in the Mexican Health and Aging Study, 2012–2015

PurposeThe aim of this study was to investigate the relationship between specific combinations of chronic conditions and disability in Mexican older adults with diabetes. MethodsThis was a prospective cohort study of Mexican adults (n = 2558) with diabetes and aged 51 or older that used data from the 2012 and 2015 waves of the Mexican Health and Aging Study. The main outcome was an index that measured ability to perform activities of daily living and instrumental activities of daily living. The main independent variables were diabetes multimorbidity combinations, defined as diabetes and at least one other chronic condition. The authors calculated the prevalence of each multimorbidity combination present in the sample in 2012 and used negative binomial regression models to estimate the association of the most prevalent of these combinations with disability incidence in 2015. ResultsThe three most prevalent combinations were: 1) diabetes-hypertension (n = 637, 31.9%) 2) diabetes-hypertension-depression (n = 388, 19.4%) and 3) diabetes-depression (n = 211, 10.6%). In fully adjusted models comparing participants with specific multimorbidity combinations to participants with diabetes alone, the combinations that had an increased association with disability were diabetes-hypertension-depression, diabetes-depression and diabetes-hypertension-arthritis-depression. In nested models, the addition of arthritis to combinations including depression increased this association. ConclusionsConsistent with prior studies, multimorbidity combinations including depression were associated with increased risk of disability. However, the effect size of this relationship was lower than what had been previously been reported internationally. This highlights the need for globally oriented multimorbidity research.

Association between chronic diseases and falls among a sample of older people in Finland

BackgroundFalls are a major problem for older people and recurrent fallers are especially prone to severe consequences due to falls. This study investigated the association between chronic conditions and falls.MethodsResponses from 872 older persons (age 65–98) to a health questionnaire were used in the analyses. Characteristics and disease prevalence between recurrent fallers, one-time fallers and non-fallers were compared. A hierarchical clustering method was applied to find combinations of chronic conditions that were associated with recent recurrent falling.ResultsThe results showed that recurrent fallers had a higher number of diseases (median 4, interquartile range, IQR = 2.0–5.0) compared to non-fallers (median 2, IQR = 1.0–3.0). Eight clusters were formed based on the data. The participants in the low chronic disease cluster were younger, more physically active, not frail, and had fewer geriatric conditions. Multiple chronic disease cluster participants were older, less physically active, overweight (body mass index, BMI > 30), at risk of malnutrition, and had more geriatric conditions. Significantly increased risk of recurrent falls relative to the low chronic cluster was found for respondents in the osteoporosis cluster and multiple chronic disease cluster (OR = 5.65, 95% confidence interval CI: 1.23–25.85, p = 0.026, and OR = 13.42, 95% CI: 2.47–72.96, p = 0.002, respectively). None of the clusters were associated with increased risk of one-time falling.ConclusionsThe results implicate that the number of chronic diseases is related with risk of recurrent falling. Furthermore, the results implicate the potential of identifying certain combinations of chronic diseases that increase fall risk by analyzing health record data, although further studies are needed with a larger population sample.

Prevalence of Multimorbidity among Asian Indian, Chinese, and Non-Hispanic White Adults in the United States.

Asian Americans are the fastest-growing minority group in the United States, yet little is known about their multimorbidity. This study examined the association of Asian Indians, Chinese and non-Hispanic whites (NHWs) to multimorbidity, defined as the concurrent presence of two or more chronic conditions in the same individual. We used a cross-sectional design with data from the National Health Interview Survey (2012–2017) of Asian Indians, Chinese, and NHWs (N = 132,666). Logistic regressions were used to examine the adjusted association of race/ethnicity to multimorbidity. There were 1.9% Asian Indians, 1.8% Chinese, and 96.3% NHWs. In unadjusted analyses (p < 0.001), 17.1% Asian Indians, 17.9% Chinese, and 39.0% NHWs had multimorbidity. Among the dyads, high cholesterol and hypertension were the most common combination of chronic conditions among Asian Indians (32.4%), Chinese (41.0%), and NHWs (20.6%). Asian Indians (AOR = 0.73, 95% CI = (0.61, 0.89)) and Chinese (AOR = 0.63, 95% CI = (0.53, 0.75)) were less likely to have multimorbidity compared to NHWs, after controlling for age, sex, and other risk factors. However, Asian Indians and Chinese were more likely to have high cholesterol and hypertension, risk factors for diabetes and heart disease.

Individual and population level impact of chronic conditions on functional disability in older adults

BackgroundIt is unknown if the relationship between multimorbidity and disability differs by combinations of chronic conditions. The objective of our study was to elucidate how joint effect of different combinations of chronic conditions impact the five year risk of functional disability at the population level.MethodsParticipants ≥65 years from the Canadian Study of Health and Aging were assessed for functional disability measured using activities of daily living (ADL) and instrumental ADL (IADL), and the presence of conditions in five disease domains; cardiometabolic, neurological, sensory, musculoskeletal, and respiratory. Logistic regression was used to assess the relationship between each disease domain and incident ADL and IADL measured at five years of follow up and population attributable risk (PAR) was modeled for diseases domains that were significantly associated with disability. Results were stratified by sex and age (65–74 years, ≥75 years).ResultsThere were 6272 participants free of ADL disability and 4571 participants free from IADL disability at baseline. For incident ADL, the greatest PAR values were 21.3 (9.8–32.8) for the cardiometabolic domain in males 65–74 years, 22.7 (4.7–40.8) for the musculoskeletal domain for females aged 65–74 years, and 11.2 (2.8–19.7) for the musculoskeletal domain in males ≥75 years. The PAR for the musculoskeletal, sensory, and neurological domains were similar in females ≥75 years(9.3–9.9). PAR values were lower but followed similar patterns for IADL disability.ConclusionThe chronic disease domains which most strongly predicted incident ADLs and IADLs did not account for the greatest amount of disability at the population level.

Association Between Chronic Health Conditions and Quality of Life in Rural Teachers.

AimThe school teacher profession has been reported to be associated with an increased rate of health problems that can affect the quality of life (QoL) of teachers. However, there is little information about rural teachers.ObjectiveTo investigate the associations of obesity, abdominal obesity, and hypertension with the perception of QoL in rural teachers.Materials and MethodsThis cross-sectional study included a representative sample of teachers from eight rural schools in the Valparaíso Region of Chile. Obesity was evaluated by the percentages of fat mass (% FM) and abdominal obesity, and hypertension was recorded. The Short Form-36 Health Survey was administered to subjects to evaluate QoL. A logistic regression adjusted for age and gender was used to associate QoL with chronic health conditions.ResultsEighty-five percent of teachers presented abdominal obesity, 56% presented obesity evaluated by % FM and 33% presented hypertension. Thirty percent of teachers in the ≥45-year-old age group presented all three chronic conditions simultaneously. Teachers presenting abdominal obesity in the ≤44-year-old age group had lower scores in the mental health component (MCS) (p < 0.05) of the survey than the teachers in the ≥45-year-old age group. In addition, teachers in the ≤44-year-old age group who presented obesity scored lower in the MCS than those in the same age group without obesity (p = 0.004). The occurrence simultaneous of two and three chronic health conditions increased the risk of reduced MCS significantly (p = 0.015, OR 17.0, 95% CI: 1.741–165.90 and p = 0.003, OR 82.6, 95% CI: 4.58–1490.70, respectively). In addition, ages under 45 years old were associated with low score of MCS (OR 8.8, 95% CI: 1.565–49.698).ConclusionA combination of chronic conditions affects the mental health (MH) of rural teachers. Although the association does not imply causation, these findings support the notion that teachers present early MH problems. This suggests that resources must be made available to detect early mental and chronic health conditions of rural teachers.

Nutrition Label Use Is Related to Chronic Conditions among Mexicans: Data from the Mexican National Health and Nutrition Survey 2016

BackgroundNon-communicable diseases, such as obesity, diabetes, and hypertension, can be prevented and treated through a balanced nutrient-rich diet. Nutrition labels have been recognized as crucial to preventing obesity and non-communicable diseases through a healthier diet. ObjectiveOur aim was to examine the association between nutrition label use and chronic conditions (overweight, obesity, previously diagnosed diabetes, and hypertension) among an adult Mexican population. DesignThis was a cross-sectional study that used data from the Mexican National Health and Nutrition Survey of 2016 (ENSANUT MC 2016). Participants/settingThe participants were 5,013 adults aged 20 to 70 years old. Older adults (>70 years), illiterate participants, pregnant women, and participants with implausible blood pressure data were excluded from the sample. The survey was conducted from May to August 2016 in the participants’ households. Main outcome measuresWe measured chronic conditions (overweight, obesity, previously diagnosed diabetes, and hypertension). Statistical analyses performedPearson χ2 test was used to examine the associations among the use of nutrition labels and sociodemographic characteristics and chronic conditions. Multiple logistic regression was used to determine the association between nutrition label use and chronic conditions adjusting for the effect of confounding variables like sex, age, body mass index, education level, marital status, ethnicity, residence area, region, and socioeconomic status. ResultsFrom the total sample, 40.9% (95% CI 38.4% to 43.8%) reported using nutrition labeling. Respondents with overweight or obesity were less likely to use nutrition labels (odds ratio 0.74; P<0.05). Participants who self-reported diabetes had significantly lower odds of nutrition label use than participants who did not report to have diabetes (odds ratio 0.66; P<0.05). Participants having 3 chronic conditions had lower odds of nutrition label use (odds ratio 0.34; P<0.01) relative to having zero chronic conditions. ConclusionsThis study suggests an association between nutrition label use and chronic conditions (obesity and diabetes). These findings demonstrate that people with obesity, diabetes, and a combination of chronic conditions were less likely to use nutrition labels than people without these conditions.

Quality-adjusted Life Years (QALY) for 15 Chronic Conditions and Combinations of Conditions Among US Adults Aged 65 and Older.

Although the life expectancy for the US population has increased, a high proportion of this population has lived with ≥1 chronic conditions. We have quantified the burden of disease associated with 15 chronic conditions and combinations of conditions by estimating quality-adjusted life years (QALYs) for older US adults. Data were from the Medicare Health Outcomes Survey Cohort 15 (baseline survey in 2012, follow-up survey 2014, with mortality follow-up through January 31, 2015). We included individuals aged 65 years and older (n=96,481). We estimated mean QALY throughout the remainder of the lifetime according to the occurrence of these conditions. The age-adjusted QALY was 5.8 years for men and 7.8 years for women. Over 90% respondents reported at least 1 condition and 72% reported multiple conditions. Respondents with depression and congestive heart failure had the lowest age-adjusted QALY (1.1-1.5 y for men and 1.5-2.2 y for women), whereas those with hypertension, arthritis, and sciatica had higher QALY (4.2-5.4 and 6.4-7.2 y, respectively). Having either depression or congestive heart failure and any 1 or 2 of the other 13 conditions was associated with the lowest QALY among the possible dyads and triads of chronic conditions. Dyads and triads with hypertension or arthritis were more prevalent, but had higher QALY. Understanding the burden of disease for common chronic conditions and for combinations of these conditions is useful for delivering high-quality primary care that could be tailored for individuals with combinations of chronic conditions.

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.

Prevalence of multimorbidity in the Brazilian adult population according to socioeconomic and demographic characteristics.

Knowledge on the occurrence of multimorbidity is important from the viewpoint of public policies, as this condition increases the consumption of medicines as well as the utilization and expenses of health services, affecting life quality of the population. The objective of this study was to estimate prevalence of self-reported multimorbidity in Brazilian adults (≥18 years old) according to socioeconomic and demographic characteristics. A descriptive study is presented herein, based on data from the National Health Survey, which was a household-based survey carried out in Brazil in 2013. Data on 60,202 adult participants over the age of 18 were included. Prevalences and its respective confidence intervals (95%) were estimated according to sex, age, education level, marital status, self-reported skin color, area of residence, occupation and federative units (states). Poisson regression models univariate and multivariate were used to evaluate the association between socioeconomic and demographic variables with multimorbidity. To observe the combinations of chronic conditions the most common groups in pairs, trios, quartets and quintets of chronic diseases were observed. The prevalence of multimorbidity was 23.6% and was higher among women, in individuals over 60 years of age, people with low educational levels, people living with partner, in urban areas and among unemployed persons. The states of the South and Southeast regions presented higher prevalence. The most common groups of chronic diseases were metabolic and musculoskeletal diseases. The results demonstrated high prevalence of multimorbidity in Brazil. The study also revealed that a considerable share of the economically active population presented two or more chronic diseases. Data of this research indicated that socioeconomic and demographic aspects must be considered during the planning of health services and development of prevention and treatment strategies for chronic diseases, and consequently, multimorbidity.

Identifying Specific Combinations of Multimorbidity that Contribute to Health Care Resource Utilization: An Analytic Approach.

Multimorbidity affects the majority of elderly adults and is associated with higher health costs and utilization, but how specific patterns of morbidity influence resource use is less understood. The objective was to identify specific combinations of chronic conditions, functional limitations, and geriatric syndromes associated with direct medical costs and inpatient utilization. Retrospective cohort study using the Health and Retirement Study (2008-2010) linked to Medicare claims. Analysis used machine-learning techniques: classification and regression trees and random forest. A population-based sample of 5771 Medicare-enrolled adults aged 65 and older in the United States. Main covariates: self-reported chronic conditions (measured as none, mild, or severe), geriatric syndromes, and functional limitations. Secondary covariates: demographic, social, economic, behavioral, and health status measures. Medicare expenditures in the top quartile and inpatient utilization. Median annual expenditures were $4354, and 41% were hospitalized within 2 years. The tree model shows some notable combinations: 64% of those with self-rated poor health plus activities of daily living and instrumental activities of daily living disabilities had expenditures in the top quartile. Inpatient utilization was highest (70%) in those aged 77-83 with mild to severe heart disease plus mild to severe diabetes. Functional limitations were more important than many chronic diseases in explaining resource use. The multimorbid population is heterogeneous and there is considerable variation in how specific combinations of morbidity influence resource use. Modeling the conjoint effects of chronic conditions, functional limitations, and geriatric syndromes can advance understanding of groups at greatest risk and inform targeted tailored interventions aimed at cost containment.

Chronic Pain: How Challenging Are DDIs in the Analgesic Treatment of Inpatients with Multiple Chronic Conditions?

BackgroundChronic pain is common in multimorbid patients. However, little is known about the implications of chronic pain and analgesic treatment on multimorbid patients. This study aimed to assess chronic pain therapy with regard to the interaction potential in a sample of inpatients with multiple chronic conditions.Methods and FindingsWe conducted a retrospective study with all multimorbid inpatients aged ≥18 years admitted to the Department of Internal Medicine of University Hospital Zurich in 2011 (n = 1,039 patients). Data were extracted from the electronic health records and reviewed. We identified 433 hospitalizations of patients with chronic pain and analyzed their combinations of chronic conditions (multimorbidity). We then classified all analgesic prescriptions according to the World Health Organization (WHO) analgesic ladder. Furthermore, we used a Swiss drug-drug interactions knowledge base to identify potential interactions between opioids and other drug classes, in particular coanalgesics and other concomitant drugs. Chronic pain was present in 38% of patients with multimorbidity. On average, patients with chronic pain were aged 65.7 years and had a mean number of 6.6 diagnoses. Hypertension was the most common chronic condition. Chronic back pain was the most common painful condition. Almost 90% of patients were exposed to polypharmacotherapy. Of the chronic pain patients, 71.1% received opioids for moderate to severe pain, 43.4% received coanalgesics. We identified 3,186 potential drug-drug interactions, with 17% classified between analgesics (without coanalgesics).ConclusionsAnalgesic drugs-related DDIs, in particular opioids, in multimorbid patients are often complex and difficult to assess by using DDI knowledge bases alone. Drug-multimorbidity interactions are not sufficiently investigated and understood. Today, the scientific literature is scarce for chronic pain in combination with multiple coexisting medical conditions and medication regimens. Our work may provide useful information to enable further investigations in multimorbidity research within the scope of potential interactions and chronic pain.

Multimorbidity as specific disease combinations, an important predictor factor for mortality in octogenarians: the Octabaix study.

BackgroundThe population is aging and multimorbidity is becoming a common problem in the elderly.ObjectiveTo explore the effect of multimorbidity patterns on mortality for all causes at 3- and 5-year follow-up periods.Materials and methodsA prospective community-based cohort (2009–2014) embedded within a randomized clinical trial was conducted in seven primary health care centers, including 328 subjects aged 85 years at baseline. Sociodemographic variables, sensory status, cardiovascular risk factors, comorbidity, and geriatric tests were analyzed. Multimorbidity patterns were defined as combinations of two or three of 16 specific chronic conditions in the same individual.ResultsOf the total sample, the median and interquartile range value of conditions was 4 (3–5). The individual morbidities significantly associated with death were chronic obstructive pulmonary disease (COPD; hazard ratio [HR]: 2.47; 95% confidence interval [CI]: 1.3; 4.7), atrial fibrillation (AF; HR: 2.41; 95% CI: 1.3; 4.3), and malignancy (HR: 1.9; 95% CI: 1.0; 3.6) at 3-year follow-up; whereas dementia (HR: 2.04; 95% CI: 1.3; 3.2), malignancy (HR: 1.84; 95% CI: 1.2; 2.8), and COPD (HR: 1.77; 95% CI: 1.1; 2.8) were the most associated with mortality at 5-year follow-up, after adjusting using Barthel functional index (BI). The two multimorbidity patterns most associated with death were AF, chronic kidney disease (CKD), and visual impairment (HR: 4.19; 95% CI: 2.2; 8.2) at 3-year follow-up as well as hypertension, CKD, and malignancy (HR: 3.24; 95% CI: 1.8; 5.8) at 5 years, after adjusting using BI.ConclusionMultimorbidity as specific combinations of chronic conditions showed an effect on mortality, which would be higher than the risk attributable to individual morbidities. The most important predicting pattern for mortality was the combination of AF, CKD, and visual impairment after 3 years. These findings suggest that a new approach is required to target multimorbidity in octogenarians.

Stratifying Patients with Diabetes into Clinically Relevant Groups by Combination of Chronic Conditions to Identify Gaps in Quality of Care.

To find clinically relevant combinations of chronic conditions among patients with diabetes and to examine their relationships with six diabetes quality metrics. Twenty-nine thousand five hundred and sixty-two adult patients with diabetes seen at eight Midwestern U.S. health systems during 2010-2011. We retrospectively evaluated the relationship between six diabetes quality metrics and patients' combinations of chronic conditions. We analyzed 12 conditions that were concordant with diabetes care to define five mutually exclusive combinations of conditions ("classes") based on condition co-occurrence. We used logistic regression to quantify the relationship between condition classes and quality metrics, adjusted for patient demographics and utilization. We extracted electronic health record data using a standardized algorithm. We found the following condition classes: severe cardiac, cardiac, noncardiac vascular, risk factors, and no concordant comorbidities. Adjusted odds ratios and 95 percent confidence intervals for glycemic control were, respectively, 1.95 (1.7-2.2), 1.6 (1.4-1.9), 1.3 (1.2-1.5), and 1.3 (1.2-1.4) compared to the class with no comorbidities. Results showed similar patterns for other metrics. Patients had distinct quality metric achievement by condition class, and those in less severe classes were less likely to achieve diabetes metrics.

Functional disability and social participation restriction associated with chronic conditions in middle-aged and older adults

BackgroundWe examine the population impact on functional disability and social participation of physical and mental chronic conditions individually and in combination.MethodsCross-sectional, population-based data from community-dwelling people aged 45 years and...