Patterns and impact of comorbidity and multimorbidity among community-resident American Indian elders

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.

Multimorbidity patterns and the association with health status of the oldest-old in long-term care facilities in China: a two-step analysis

BACKGROUND

The increasing prevalence of multimorbidity has created a serious global public health problem in aging populations. Certain multimorbidity patterns across different age ranges and their association with health status remain unclear. The main aim of this study is to identify multimorbidity patterns discrepancies and associated health status between younger-old and oldest-old.

METHODS

The Ethics Committee of Nanjing Medical University approved the study protocol (No.2019-473). Convenience sampling method was used to recruit older adults aged ≥ 60 years with multimorbidity from July to December 2021 from 38 Landsea long-term care facilities in China. The multimorbidity patterns were analyzed using network analysis and two-step cluster analysis. One-Way ANOVA was utilized to explore their association with health status including body function, activity of daily living, and social participation. A Sankey diagram visualized the flow of health status within different multimorbidity patterns. This study is reported following the STROBE guidelines.

RESULTS

A total of 214 younger-old (60-84 years) and 173 oldest-old (≥ 85 years) were included. Leading coexisting diseases were cardiovascular disease (CD), metabolic and endocrine disease (MED), neurological disease (ND), and orthopedic disease (OD). Cluster 1 (53, 24.8%) of CD-ND (50, 94.3%; 31, 58.8%), cluster 2 (39, 18.2%) of MED-ND-CD (39, 100%; 39, 100%; 37, 94.9%), cluster 3 (37, 17.3%) of OD-CD-MED-ND (37, 100%; 33, 89.2%; 27, 73.0%; 16, 43.2%), and cluster 4 (34, 15.9%) of CD-MED (34, 100%; 34, 100%) were identified in the younger-old. In the oldest-old, the primary multimorbidity patterns were: cluster 1 (33, 19.1%) of CD-respiratory disease-digestive disease-urogenital disease (CD-RD-DSD-UD) (32, 97.0%; 9, 27.3%; 8, 24.2%; 7, 21.2%), cluster 2 (42, 24.3%) of ND-CD-MED (42, 100%; 35, 83.3%; 14, 33.3%), cluster 3 (28, 16.2%) of OD-CD-MED (28, 100%; 25, 89.3%; 18, 64.3%), and cluster 4 (35, 20.2%) of CD-MED (35, 100%; 35, 100%). Younger-old with CD-ND or MED-ND-CD, and oldest-old with ND-CD-MED have worse health status compared with other multimorbidity patterns (e.g., CD-MED and OD-CD-MED).

CONCLUSION

Discrepancies in common patterns of multimorbidity across age groups suggest that caregivers in long-term care facilities should consider changes in multimorbidity patterns with ageing when developing prevention plans for individualized management. Neurological disease concurrent with other diseases was the major determinant of health status, especially for the oldest-old. Interventions targeting multimorbidity need to be focused, yet generic. It is essential to assess complex needs and health outcomes that arise from different multimorbidity patterns and manage them through an interdisciplinary approach and consider their priorities to gain high-quality primary care for older adults living in long-term care facilities.

Clustering of comorbidities and associated outcomes in people with osteoarthritis - A UK Clinical Practice Research Datalink study

OBJECTIVE

To examine the clusters of chronic conditions present in people with osteoarthritis and the associated risk factors and health outcomes.

METHODS

Clinical Practice Research Datalink (CPRD) GOLD was used to identify people diagnosed with incident osteoarthritis (n = 221,807) between 1997 and 2017 and age (±2 years), gender, and practice matched controls (no osteoarthritis, n = 221,807) from UK primary care. Clustering of people was examined for 49 conditions using latent class analysis. The associations between cluster membership and covariates were quantified by odds ratios (OR) using multinomial logistic regression. General practice (GP) consultations, hospitalisations, and all-cause mortality rates were compared across the clusters identified at the time of first diagnosis of osteoarthritis (index date).

RESULTS

In both groups, conditions largely grouped around five clusters: relatively healthy; cardiovascular (CV), musculoskeletal-mental health (MSK-MH), CV-musculoskeletal (CV-MSK) and metabolic (MB). In the osteoarthritis group, compared to the relatively healthy cluster, strong associations were seen for 1) age with all clusters; 2) women with the MB cluster (OR 5.55: 5.14-5.99); 3) obesity with the CV-MSK (OR 2.11: 2.03-2.20) and CV clusters (OR 2.03: 1.97-2.09). The CV-MSK cluster in the osteoarthritis group had the highest number of GP consultations and hospitalisations, and the mortality risk was 2.45 (2.33-2.58) times higher compared to the relatively healthy cluster.

CONCLUSIONS

Of the five identified clusters, CV-MSK, CV, and MSK-MH are more common in OA and CV-MSK cluster had higher health utilisation. Further research is warranted to better understand the mechanistic pathways and clinical implications.

Comorbidities in osteoarthritis (ComOA): a combined cross-sectional, case-control and cohort study using large electronic health records in four European countries

INTRODUCTION

Osteoarthritis (OA) is one of the leading chronic conditions in the older population. People with OA are more likely to have one or more other chronic conditions than those without. However, the temporal associations, clusters of the comorbidities, role of analgesics and the causality and variation between populations are yet to be investigated. This paper describes the protocol of a multinational study in four European countries (UK, Netherlands, Sweden and Spain) exploring comorbidities in people with OA.

METHODS AND ANALYSIS

This multinational study will investigate (1) the temporal associations of 61 identified comorbidities with OA, (2) the clusters and trajectories of comorbidities in people with OA, (3) the role of analgesics on incidence of comorbidities in people with OA, (4) the potential biomarkers and causality between OA and the comorbidities, and (5) variations between countries.A combined case-control and cohort study will be conducted to find the temporal association of OA with the comorbidities using the national or regional health databases. Latent class analysis will be performed to identify the clusters at baseline and joint latent class analysis will be used to examine trajectories during the follow-up. A cohort study will be undertaken to evaluate the role of non-steroidal anti-inflammatory drugs (NSAIDs), opioids and paracetamol on the incidence of comorbidities. Mendelian randomisation will be performed to investigate the potential biomarkers for causality between OA and the comorbidities using the UK Biobank and the Rotterdam Study databases. Finally, a meta-analyses will be used to examine the variations and pool the results from different countries.

ETHICS AND DISSEMINATION

Research ethics was obtained according to each database requirement. Results will be disseminated through the FOREUM website, scientific meetings, publications and in partnership with patient organisations.

An exploration of the sociodemographic and health conditions associated with self-rated wellbeing for Aboriginal and Torres Strait Islander adults

Objective

To identify sociodemographic factors and health conditions associated with self-rated wellbeing for Aboriginal and Torres Strait Islander adults. Participants were recruited via investigator networks and an online panel provider with an established nationwide panel of Aboriginal and Torres Strait Islander adults. Those interested were invited to complete a survey that included an assessment of wellbeing using a visual analogue scale. Data was collected from October–November 2019 and August–September 2020. Exploratory analyses were conducted to ascertain factors associated with self-rated wellbeing for Aboriginal and Torres Strait Islander adults.

Results

Having more than enough money to last until next pay day, full-time employment, completion of grade 12, having a partner, and living with others were significantly associated with higher wellbeing among Aboriginal and Torres Strait Islander adults. A self-reported history of depression, anxiety, other mental health conditions, heart disease, or disability were associated with lower self-rated wellbeing scores. Our findings indicate a need for further investigation among these socioeconomic and patient groups to identify how to improve and support the wellbeing of Aboriginal and Torres Strait Islander adults.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13104-021-05794-3.

Regulation of Long-Term Care Homes for Older Adults in India

The rising aging population in India has led to an increased caregiving burden, and accordingly, the number of residential care facilities is also burgeoning. There is no regulatory framework or registration authority specifically for residential care homes in India. The article's objective is to understand the need for a regulatory framework in India in the context of historic and global experiences in the UK, USA, and Europe. Although there is a lack of literature comparing the community home-based care and residential care, one study reported a preference for home-based care in the South Asian context. Elder abuse and deprivation of rights of seniors are common, and there is a need to bring in more safeguards to prevent these from the perspective of the older adults, their family members, the care providers, and the state. While the main priority of meeting care needs in long-term care is a challenge given the lack of trained care staff, the quality control mechanisms also need to evolve. A review of adverse incidents, complaints, and litigations also highlights the need for regulation to improve the standards and quality of care. The article explores lacunae of residential care facilities in the Indian context and provides recommendatory parameters for evaluating the quality of care provided. Relevant sections of the statutory new Mental Healthcare Act of 2017 in India could provide a regulatory framework ensuring rights and liberties of the residents are upheld. The authors propose a state-run model for elderly care homes and commencement of framing regulations appropriate to the Indian context.

Clustering of comorbidities

Within the last decade, clustering of comorbidities has become an increasing health problem on a global scale and will continue to challenge healthcare professionals in the coming years. People with multiple diseases find difficulties in managing their daily lives due to the implications each disease brings; attending and keeping up to date with hospital appointments, being prescribed and taking various medications, the effects of mental health and quality of life, and the impact it has on their families. Most research in clinical trials often exclude individuals with multimorbidity and observational studies mainly focus on single disease outcomes, therefore there is an opportunity to encourage future research in an area which could help prevent further cases and improve the lives of those already living with multimorbidity. This review aims to summarise the rising prevalence and most common clusters, highlight the challenges faced in healthcare, and explore ways to improve future research.

Common Comorbidities of Stroke in the Canadian Population

OBJECTIVES

Although comorbidity increases the health care and community support needs for patients, and the burden for the health care system, there are few population-based studies on comorbidity in patients with stroke. This study aims to evaluate the occurrence of important comorbidities among stroke patients in the Canadian population.

METHODS

Data from the population-based 2011-2012 Canadian Community Health Survey containing responses from 124,929 participants covering about 98% of the Canadian population when weighted were examined and analyzed by means of logistic regression models.

RESULTS

There was a statistically significant association between stroke history and multiple comorbid risk factors. Stroke prevalence increased in individuals with heart disease (odds ratio (OR): 3.80, 95% confidence interval (CI): 3.77-3.84), hypertension (OR: 1.97, 95% CI: 1.95-1.99), diabetes (OR: 1.74, 95% CI: 1.72-1.75), mood disorder (OR: 2.14, 95% CI: 2.12-2.17), and chronic obstructive pulmonary disease (COPD) (OR: 1.46, 95% CI: 1.44-1.48) compared to others without the condition. Of 2067 participants with stroke, 1680 (81.3%) had one or more comorbid conditions (heart disease, hypertension, diabetes, mood disorder, or COPD) that coexist with stroke and 48% had two or more. Comorbidity increased with age, and two-thirds of stroke patients with comorbid medical conditions were 60 years of age or older.

CONCLUSION

This population-based study provides evidence of comorbidity between stroke and other conditions that include heart disease, hypertension, diabetes, mood disorder, and COPD. Canadian individuals with stroke have a high burden of comorbidity. Health care systems need to recognize and respond to the strong association of comorbidity and stroke occurrence. This key factor should be considered when allocating resources.

Health Care Access and Utilization for American Indian Elders: A Concept-Mapping Study

OBJECTIVES

Inequities in access to and utilization of health care greatly influence the health and quality of life of American Indian elders (AIEs). This study explores the importance and perceived prevalence of factors affecting health care use within this population and assesses the changeability of these factors to produce a list of action items that are timely and relevant to improving health care access and utilization.

METHOD

Concept mapping was conducted with AIEs (n = 65) and professional stakeholders (n = 50), including tribal leaders, administrators of public-sector health systems, outreach workers, and health care providers. Data were analyzed using multidimensional scaling and cluster analyses.

RESULTS

The final concept-map model comprised nine thematic clusters related to factors affecting elder health care: Difficulties Obtaining and Using Insurance; Insecurity from Lack of Knowledge; Limited Availability of Services; Scheduling Challenges; Provider Issues and Relationships; Family and Emotional Challenges; Health-Related Self-Efficacy and Knowledge; Accessibility and Transportation Barriers; and Tribal/National Policy.

DISCUSSION

Findings suggest that improvements in access to and utilization of health care among AIEs will require actions across multiple domains, including health system navigation services, workforce improvements, and tribal, state, and federal policy. A multilevel socioecological approach is necessary to organize and undertake these actions.

Comorbidity Patterns of Older Lung Cancer Patients in Northeast China: An Association Rules Analysis Based on Electronic Medical Records

Purposes: This study aims to identify the comorbidity patterns of older men with lung cancer in China. Methods: We analyzed the electronic medical records (EMRs) of lung cancer patients over age 65 in the Jilin Province of China. The data studied were obtained from 20 hospitals of Jilin Province in 2018. In total, 1510 patients were identified. We conducted a rank–frequency analysis and social network analysis to identify the predominant comorbidities and comorbidity networks. We applied the association rules to mine the comorbidity combination with the values of confidence and lift. A heatmap was utilized to visualize the rules. Results: Our analyses discovered that (1) there were 31 additional medical conditions in older patients with lung cancer. The most frequent comorbidities were pneumonia, cerebral infarction, and hypertension. (2) The network-based analysis revealed seven subnetworks. (3) The association rules analysis provided 41 interesting rules. The results revealed that hypertension, ischemic cardiomyopathy, and pneumonia are the most frequent comorbid combinations. Heart failure may not have a strong implicating role in these comorbidity patterns. Cerebral infarction was rarely combined with other diseases. In addition, glycoprotein metabolism disorder comorbid with hyponatremia or hypokalemia increased the risk of anemia by more than eight times in older lung cancer patients. Conclusions: This study provides evidence on the comorbidity patterns of older men with lung cancer in China. Understanding the comorbidity patterns of older patients with lung cancer can assist clinicians in their diagnoses and contribute to developing healthcare policies, as well as allocating resources.

Prevalence and Patterns of Multimorbidity Among Rural Elderly: Findings of the AHSETS Study

Introduction: In India, the proportion of older population is projected to increase from 8% in 2015 to 19% in 2050 and a third of the country's population will be older adults by end of the century. Multimorbidity is common among the elderly and the prevalence increases with age. Chronic conditions are most often present as clusters and it's critical to explore the prevalent pattern of clustering for better public health strategies. Method: A cross-sectional study was conducted among 725 rural older adults (>60 years) in Tigiria block of Odisha, India. Multimorbidity status was assessed using the prior validated MAQ-PC tool. Survey was conducted using android tablets installed with open data kit software. While Euclidean distances using K-means clustering algorithm were used to estimate the similarity or dissimilarity of observations. The optimum numbers of clusters were determined using silhouette method. Data were analyzed using multiple open source packages of R statistical programming software ver-3.6.3. Result: The overall prevalence of multimorbidity was 48.8% of which dyads (25%) were the most common form, followed by triads (15.2%). The prevalence of multimorbidity was higher in females (50.4%) than males (47.4%). The optimal number of clusters was found to be 3. While arthritis alone was a separate cluster, hypertension and acid peptic disease were in another cluster and all the rest conditions were included in the third cluster. Conclusion: The cluster analysis to measure of proximity suggested arthritis, hypertension, and acid peptic disease are the diseases that occur mostly in isolation with the other chronic conditions in the rural elderly.

Patterns of multimorbidity in medical inpatients: a multinational retrospective cohort study

Multimorbidity is frequent and represents a significant burden for patients and healthcare systems. However, there are limited data on the most common combinations of comorbidities in multimorbid patients. We aimed to describe and quantify the most common combinations of comorbidities in multimorbid medical inpatients. We used a large retrospective cohort of adults discharged from the medical department of 11 hospitals across 3 countries (USA, Switzerland, and Israel) between 2010 and 2011. Diseases were classified into acute versus chronic. Chronic diseases were grouped into clinically meaningful categories of comorbidities. We identified the most prevalent combinations of comorbidities and compared the observed and expected prevalence of the combinations. We assessed the distribution of acute and chronic diseases and the median number of body systems in relationship to the total number of diseases. Eighty-six percent (n = 126,828/147,806) of the patients were multimorbid (≥ 2 chronic diseases), with a median of five chronic diseases; 13% of the patients had ≥ 10 chronic diseases. Among the most frequent combinations of comorbidities, the most prevalent comorbidity was chronic heart disease. Other high prevalent comorbidities included mood disorders, arthropathy and arthritis, and esophageal disorders. The ratio of chronic versus acute diseases was approximately 2:1. Multimorbidity affected almost 90% of patients, with a median of five chronic diseases. Over 10% had ≥ 10 chronic diseases. This identification and quantification of frequent combinations of comorbidities among multimorbid medical inpatients may increase awareness of what should be taken into account when treating such patients, a growth in the need for special care considerations.

The Relationship between Physical-Mental Comorbidity and Subjective Well-Being among Older Adults

OBJECTIVES

The present study examined the relationship between types and severity of physical-mental comorbidity and subjective well-being (SWB) among older adults.

METHODS

The sample was drawn from the National Health and Aging Trends Study (NHATS) collected in 2011. A total of 6,945 older adults aged 65 to 105 were categorized into four groups using 16 common physical health conditions and two mental health problems: no chronic health condition (n = 562, referent), physical health condition (n = 4,946), mental health problem (n = 56), and physical-mental comorbidity (n = 1,380). Outcome variable was self-reported SWB measured with 11 items. Analyses of covariance (ANCOVAs) were used to assess the relationship between types and severity of physical-mental comorbidity and SWB.

RESULTS

After adjusting for covariates, older adults with a mental health problem or physical-mental comorbidity reported lower SWB compared to the no chronic health condition group. Physical-mental comorbidity was associated with lower SWB compared to the physical health condition group. Higher severity level of physical-mental comorbidity was associated with decreased SWB.

DISCUSSION

Findings suggest that mental health problem and physical-mental comorbidity negatively associated with SWB among older adults.

CLINICAL IMPLICATIONS

Integrative interventions should be developed to target mental health issues and comorbid physical-mental health conditions in the older populations.

Comorbidity status in hospitalized elderly in Japan: Analysis from National Database of Health Insurance Claims and Specific Health Checkups

The detailed comorbidity status of hospitalized elderly patients throughout Japan has remained largely unknown; therefore, our goal was to rigorously explore this situation and its implications as of the 2015 fiscal year (from April 2015 to March 2016). This study was based on a health insurance claims database, covering all insured policy holders in Japan aged ≥60 years (male: n = 2,135,049, female: 1,969,019) as of the 2015 fiscal year. Comorbidity status was identified by applying principal factor analysis to the database. The factors identified in male patients were [1] myocardial infarction, hypertension, dyslipidemia, and diabetes mellitus; [2] congestive heart failure (CHF), cardiac arrhythmia, and renal failure; [3] Parkinson’s disease, dementia, cerebrovascular disease, and pneumonia; [4] cancer and digestive disorders; and [5] rheumatoid arthritis and hip fracture. However, in female patients, the results obtained for the quaternary and quinary factors were the opposite of those obtained in male patients. In superelderly patients, dementia, cerebrovascular disease, and pneumonia appeared as the tertiary factor, and hip fracture and osteoporosis appeared as the quaternary factor. The comorbidities in the elderly patients suggest the importance of coronary heart disease and its related metabolic disorders; in superelderly patients, fracture and osteoporosis appeared as factors, in addition to dementia and pneumonia.

Use of latent class analysis to identify multimorbidity patterns and associated factors in Korean adults aged 50 years and older

Introduction

Multimorbidity associated with significant disease and economic burdens is common among the aged. We identified chronic disease multimorbidity patterns in Koreans 50 years of age or older, and explored whether such patterns were associated with particular sociodemographic factors and health-related quality-of-life.

Methods

The multimorbidity patterns of 10 chronic diseases (hypertension, dyslipidemia, stroke, osteoarthritis, tuberculosis, asthma, allergic rhinitis, depression, diabetes mellitus, and thyroid disease) were identified via latent class analysis of data on 8,370 Korean adults aged 50+ years who participated in the sixth Korean National Health and Nutrition Examination Survey (2013–2015). The associations between multimorbidity patterns, and sociodemographic factors and health-related quality of life, were subjected to regression analysis.

Results

Three patterns of multimorbidity were identified: 1) a relatively healthy group (60.4% of the population); 2) a ‘cardiometabolic conditions’ group (27.8%); and, 3) an ‘arthritis, asthma, allergic rhinitis, depression, and thyroid disease’ group (11.8%). The female (compared to male) gender was associated with an increased likelihood of membership of the cardiometabolic conditions group (odds ratio [OR] = 1.32, 95% confidence interval [CI] = 1.15–1.51) and (to a much greater extent) the arthritis, asthma, allergy, depression, and thyroid disease group (OR = 4.32, 95% CI = 3.30–5.66). Low socioeconomic status was associated with membership of the two multimorbidity classes. Membership of the arthritis, asthma, allergy, depression, and thyroid disease group was associated with a significantly poorer health-related quality-of-life than was membership of the other two groups.

Conclusion

The co-occurrence of chronic diseases was not attributable to chance. Multimorbidity patterns were associated with sociodemographic factors and quality-of-life. Our results suggest that targeted, integrated public health and clinical strategies dealing with chronic diseases should be based on an understanding of multimorbidity patterns; this would improve the quality-of-life of vulnerable multimorbid adults.

Do replicable profiles of multimorbidity exist? Systematic review and synthesis

This systematic review aimed to synthesise multimorbidity profiling literature to identify replicable and clinically meaningful groupings of multimorbidity. We searched six electronic databases (Medline, EMBASE, PsycINFO, CINAHL, Scopus, and Web of Science) for articles reporting multimorbidity profiles. The identified profiles were synthesised with multidimensional scaling, stratified by type of statistical analysis used in the derivation of profiles. The 51 studies that met inclusion criteria reported results of 98 separate analyses of multimorbidity profiling, with a total of 407 multimorbidity profiles identified. The statistical techniques used to identify multimorbidity profiles were exploratory factor analysis, cluster analysis of diseases, cluster analysis of people, and latent class analysis. Reporting of methodological details of statistical methods was often incomplete. The discernible groupings of multimorbidity took the form of both discrete categories and continuous dimensions. Mental health conditions and cardio-metabolic conditions grouped along identifiable continua in the synthesised results of all four methods. Discrete groupings of chronic obstructive pulmonary disease with asthma, falls and fractures with sensory deficits and of Parkinson's disease and cognitive decline where partially replicable (identifiable in the results of more than one method), while clustering of musculoskeletal conditions and clustering of reproductive systems were each observed only in one statistical approach. The two most replicable multimorbidity profiles were mental health conditions and cardio-metabolic conditions. Further studies are needed to understand aetiology and evolution of these multimorbidity groupings. Guidelines for strengthening the reporting of multimorbidity profiling studies are proposed.

Differences in function and recovery profiles between patterns of multimorbidity among older medical patients the first year after an acute admission-An exploratory latent class analysis

INTRODUCTION

Multimorbidity is common among older people and may contribute to adverse health effects, such as functional limitations. It may help stratify rehabilitation of older medical patients, if we can identify differences in function under and after an acute medical admission, among patient with different patterns of multimorbidity.

AIM

To investigate differences in function and recovery profiles among older medical patients with different patterns of multimorbidity the first year after an acute admission.

METHODS

Longitudinal prospective cohort study of 369 medical patients (77.9 years, 62% women) acutely admitted to the Emergency Department. During the first 24 h after admission, one month and one year after discharge we assessed mobility level using the de Morton Mobility Index. At baseline and one-year we assessed handgrip strength, gait speed, Barthel20, and the New Mobility Score. Information about chronic conditions was collected by national registers. We used Latent Class Analysis to determine differences among patterns of multimorbidity based on 22 chronic conditions.

RESULTS

Four distinct patterns of multimorbidity were identified (Minimal chronic disease; Degenerative, lifestyle, and mental disorders; Neurological, functional and sensory disorders; and Metabolic, pulmonary and cardiovascular disorders). The "Neurological, functional and sensory disorders"-pattern showed significant lower function than the "Minimal chronic disease"-pattern in all outcome measures. There were no differences in recovery profile between patients in the four patterns.

CONCLUSION

The results support that patients with different patterns of multimorbidity among acutely hospitalized older medical patients differ in function, which suggests a differentiated approach towards treatment and rehabilitation warrants further studies.

Personalized and typical concurrent risk of limitations in social activity and mobility in older persons with multiple chronic conditions and polypharmacy

PURPOSE

We define personalized concurrent risk (PCR) as the subject-specific probability of an index outcome within a defined interval of time, while currently at risk for a separate outcome, where the outcomes are not mutually exclusive and can be jointly modeled with a shared random intercept. We further define typical concurrent risk as the risk obtained by setting the random intercept to null.

METHODS

Drawing data from the Medical Expenditure Panel Survey (cohorts 2008-2013), we jointly model limitations in social activity and mobility over two years among older community-dwelling persons with both hypertension and chronic obstructive pulmonary disease. The joint model uses inverse probability of treatment weighting based on each participant's baseline propensity of polypharmacy (≥5 classes of medication).

RESULTS

Even among participants with the same covariates, older persons with multiple chronic conditions exhibit wide-ranging heterogeneity of the treatment effect from polypharmacy, a risk factor for negative health outcomes among older persons. The magnitude of the PCRs is dominated by the value of the subject-specific random effect.

CONCLUSIONS

Estimates of PCR and typical concurrent risk can be calculated from national or institutional data sets and may facilitate the practice of personalized care for older patients with multiple chronic conditions.

Patterns of multimorbid health conditions: a systematic review of analytical methods and comparison analysis

Background

The latest review of studies on multimorbidity patterns showed high heterogeneity in the methodology for identifying groups of multimorbid conditions. However, it is unclear how analytical methods used influence the identified multimorbidity patterns.

Methods

We undertook a systematic review of analytical methods used to identify multimorbidity patterns in PubMed and EMBASE from their inception to January 2017. We conducted a comparison analysis to assess the effect the analytical methods had on the multimorbidity patterns identified, using the Australian National Health Survey (NHS) 2007-08 data.

Results

We identified 13 194 studies and excluded 13 091 based on titles/abstracts. From the full-text reviews of the 103 remaining publications, we identified 41 studies that used five different analytical methods to identify multimorbid conditions in the studies. Thirty-seven studies (90%) adopted either the factor-analysis or hierarchical-clustering methods, but heterogeneity arises for the use of different proximity measures within each method to form clusters. Our comparison analysis showed the variation in identified groups of multimorbid conditions when applying the methods to the same NHS data. We extracted main similarities among the groupings obtained by the five methods: (i) cardiovascular and metabolic diseases, (ii) mental health problems and (iii) allergic diseases.

Conclusion

We showed the extent of effects for heterogeneous analytical methods on identification of multimorbidity patterns. However, more work is needed to guide investigators for choosing the best analytical method to improve the validity and generalizability of findings. Investigators should also attempt to compare results obtained by various methods for a consensus grouping of multimorbid conditions.

Medical diagnoses showed low relatedness in an explorative mutual information analysis of 190,837 inpatient cases

OBJECTIVES

We aimed to quantify the shared information between medical diagnoses of an adult inpatient population to explore both multimorbidity patterns and vice versa the unrelatedness of medical diagnoses.

STUDY DESIGN AND SETTING

This was a cross-sectional study, performed at a tertiary care center in Switzerland. Diagnoses were routinely coded using the International Classification of Diseases, 10th revision.

RESULTS

Among 190,837 inpatient cases, 7,994 unique diagnoses were coded. There were 31.9 million possible diagnosis pairs; the respective mutual information scores in diagnosis pairs were low (range, 10^-7 to 0.237). There were 148 pairs of diagnoses with a mutual information score higher than 0.01, which formed several clinically plausible disease clusters; 27.2% of cases did not have a diagnosis that belonged to one of the morbidity clusters.

CONCLUSION

In an explorative analysis, we observed a high unrelatedness of diagnoses in a tertiary-care inpatient population. This finding indicates that although multimorbidity patterns can be observed, inpatient cases frequently have further, unrelated diagnoses, which share little information with specific other diagnoses. Therefore, management of multimorbid patients should be individualized and may not be generalized based on a few multimorbidity patterns or clusters.

Characterization of indigenous community engagement in arthritis studies conducted in Canada, United States of America, Australia and New Zealand

BACKGROUND

Research adhering to community engagement processes leads to improved outcomes. The level of Indigenous communities' engagement in rheumatology research is unknown.

OBJECTIVE

To characterize the frequency and level of community engagement reporting in arthritis studies conducted in Australia (AUS), Canada (CAN), New Zealand (NZ) and the United States of America (USA).

METHODS

Studies identified through systematic reviews on topics of arthritis epidemiology, disease phenotypes and outcomes, health service utilization and mortality in Indigenous populations of AUS, CAN, NZ and USA, were evaluated for their descriptions of community engagement. The level of community engagement during inception, data collection and results interpretation/dissemination stages of research was evaluated using a custom-made instrument, which ranked studies along the community engagement spectrum (i.e. inform-consult-involve-collaborate-empower). Meaningful community engagement was defined as involving, collaborating or empowering communities. Descriptive analyses for community engagement were performed and secondary non-parametric inferential analyses were conducted to evaluate the possible associations between year of publication, origin of the research idea, publication type and region of study; and meaningful community engagement.

RESULTS

Only 34% (n = 69) of the 205 studies identified reported community engagement at ≥ 1 stage of research. Nearly all studies that engaged communities (99% (n = 68)) did so during data collection, while only 10% (n = 7) did so at the inception of research and 16% (n = 11) described community engagement at the results' interpretation/dissemination stage. Most studies provided community engagement descriptions that were assessed to be at the lower end of the spectrum. At the inception of research stage, 3 studies reported consulting communities, while 42 studies reported community consultation at data collection stage and 4 studies reported informing or consulting communities at the interpretation/dissemination of results stage. Only 4 studies described meaningful community engagement through all stages of the research. Inferential statistics identified that studies with research ideas that originated from the Indigenous communities involved were significantly more associated with achieving meaningful community engagement.

CONCLUSIONS

The reporting of Indigenous community engagement in published arthritis studies is limited in frequency and is most frequently described at the lower end of the community engagement spectrum. Processes that support meaningful community engagement are to be promoted.

Review of chronic non-cancer pain research among Aboriginal people in Canada

Purpose

Aboriginal people in Canada are disproportionately affected by chronic illnesses, compared to non-Aboriginal Canadians. The purpose of this review was to determine whether differences exist between the two groups with respect to chronic non-cancer pain (CNCP) in order to better inform clinical practice and to identify research gaps.

Data sources

Four electronic databases were searched for the period of 1990-2015.

Study selection

Only English and French language original studies that examined CNCP prevalence, assessment tools and beliefs among Aboriginal people in Canada were considered.

Data extraction

Data extracted included Aboriginal group, geographic location, study setting and pain definition (for prevalence studies only).

Results of data synthesis

A total of 11 studies matched the selection criteria: 10 reported estimates of chronic pain prevalence among Aboriginal people in Canada, 1 was about a culturally adapted pain assessment tool, and no study was found about CNCP beliefs within Aboriginal people.

Conclusion

CNCP among Aboriginal people is still a largely unexplored research field. The limited evidence available so far does not allow us to conclude that CNCP affects a higher proportion of Aboriginal than non-Aboriginal people in Canada. However, arthritis, a specific condition associated with chronic pain, is more prevalent in Aboriginal than non-Aboriginal people. Additional research is needed on other CNCP types and conditions. Furthermore, pain assessment tools are not culturally adapted and clinicians should inquire more about the beliefs of Aboriginal patients to make them feel safer and to better target interventions.

Physical-psychiatric comorbidity: patterns and explanations for ethnic group differences

OBJECTIVE

This paper examines ethnic differences in the co-occurrence of physical and psychiatric health problems (physical-psychiatric comorbidity) for women and men. The following ethnic groups are included: Non-Latino Whites, African Americans, Caribbean Blacks, Spanish Caribbean Blacks, Mexicans, Cubans, Puerto Ricans, Other Latinos, Chinese, Filipinos, Vietnamese, and Other Asian Americans. In addition, the study assesses the extent to which social factors (socioeconomic status, stress exposure, social support) account for ethnic differences in physical-psychiatric comorbidity (PPC).

DESIGN

This study uses data from the Collaborative Psychiatric Epidemiology Surveys (CPES) (N = 12,787). Weighted prevalence rates of physical-psychiatric comorbidity (PPC) - the co-occurrence of physical and psychiatric health problems - are included to examine ethnic group differences among women and men. Multinomial logistic regression analysis was used to determine group differences in PPC before and after adjusting for social factors.

RESULTS

Puerto Rican men have significantly higher risk of PPC in comparison to Non-Latino White men. Among women, Blacks and Cubans were more likely than Non-Latino Whites to experience PPC as opposed to 'Psychiatric Only' health problems. Social factors account for the Puerto Rican/Non-Latino White difference in comorbid health among men, but have little explanatory power for understanding ethnic differences in comorbidity among women.

CONCLUSION

These findings have implications for medical care and can guide intervention programs in targeting a specific constellation of co-occurring physical and psychiatric health problems for diverse ethnic groups in the United States. As comorbidity rates increase, it is crucial to identify the myriad factors that give rise to ethnic group differences therein.

Patterns of Multimorbidity in Middle-Aged and Older Adults: An Analysis of the UK Biobank Data

OBJECTIVE

To assess the prevalence, disease clusters, and patterns of multimorbidity using a novel 2-stage approach in middle-aged and older adults from the United Kingdom.

PATIENTS AND METHODS

Data on 36 chronic conditions from 502,643 participants aged 40 to 69 years with baseline measurements between March 13, 2006, and October 1, 2010, from the UK Biobank were extracted. We combined cluster analysis and association rule mining to assess patterns of multimorbidity overall and by age, sex, and ethnicity. A maximum of 3 clusters and 30 disease patterns were mined. Comparisons were made using lift as the main measure of association.

RESULTS

Ninety-five thousand seven hundred-ten participants (19%) had 2 or more chronic conditions. The first cluster included only myocardial infarction and angina (lift=13.3), indicating that the likelihood of co-occurrence of these conditions is 13 times higher than in isolation. The second cluster consisted of 26 conditions, including cardiovascular, musculoskeletal, respiratory, and neurodegenerative diseases. The strongest association was found between heart failure and atrial fibrillation (lift=23.6). Diabetes was at the center of this cluster with strong associations with heart failure, chronic kidney disease, liver failure, and stroke (lift>2). The third cluster contained 8 highly prevalent conditions, including cancer, hypertension, asthma, and depression, and the strongest association was observed between anxiety and depression (lift=5.0).

CONCLUSION

Conditions such as diabetes, hypertension, and asthma are the epicenter of disease clusters for multimorbidity. A more integrative multidisciplinary approach focusing on better management and prevention of these conditions may help prevent other conditions in the clusters.

[The problem of multiple somatic and/or psychiatric pathology basic concepts and prevalence]

The literature of the last decades shows the growing interest to multiple pathologies in medicine including psychiatry and neurology. Multiple pathology is often determined as multimorbidity or comorbidity. Multiple pathology is a common phenomenon, which is the rule rather than the exception. In the medical care system, it is burden for the patient and for the physician in clinical, organizational and economic aspects. The review addresses all these issues in the aspect of terminology and prevalence.

Comparative analysis of methods for identifying multimorbidity patterns: a study of 'real-world' data

OBJECTIVE

The aim was to compare multimorbidity patterns identified with the two most commonly used methods: hierarchical cluster analysis (HCA) and exploratory factor analysis (EFA) in a large primary care database. Specific objectives were: (1) to determine whether choice of method affects the composition of these patterns and (2) to consider the potential application of each method in the clinical setting.

DESIGN

Cross-sectional study. Diagnoses were based on the 263 corresponding blocks of the International Classification of Diseases version 10. Multimorbidity patterns were identified using HCA and EFA. Analysis was stratified by sex, and results compared for each method.

SETTING AND PARTICIPANTS

Electronic health records for 408 994 patients with multimorbidity aged 45-64 years in 274 primary health care teams from 2010 in Catalonia, Spain.

RESULTS

HCA identified 53 clusters for women, with just 12 clusters including at least 2 diagnoses, and 15 clusters for men, all of them including at least two diagnoses. EFA showed 9 factors for women and 10 factors for men. We observed differences by sex and method of analysis, although some patterns were consistent. Three combinations of diseases were observed consistently across sex groups and across both methods: hypertension and obesity, spondylopathies and deforming dorsopathies, and dermatitis eczema and mycosis.

CONCLUSIONS

This study showed that multimorbidity patterns vary depending on the method of analysis used (HCA vs EFA) and provided new evidence about the known limitations of attempts to compare multimorbidity patterns in real-world data studies. We found that EFA was useful in describing comorbidity relationships and HCA could be useful for in-depth study of multimorbidity. Our results suggest possible applications for each of these methods in clinical and research settings, and add information about some aspects that must be considered in standardisation of future studies: spectrum of diseases, data usage and methods of analysis.

Multimorbidity and Decision-Making Preferences Among Older Adults

PURPOSE

Understanding individuals' preferences for participating in health care decisions is foundational to delivering person-centered care. We aimed to (1) explore preferences for health care decision making among older adults, and (2) identify multimorbidity profiles associated with preferring less active, ie, passive, participation among older US adults.

METHOD

Ours was a cross-sectional, nationally representative study of 2,017 National Health and Aging Trends Study respondents. Passive decision-making preference was defined as preferring to leave decisions to physicians. Multimorbidity profiles, based on 13 prevalent chronic conditions, were examined as (1) presence of 2 or more conditions, (2) a simple conditions count, and (3) a condition clusters count. Multiple logistic regression was used with adjustment for age, sex, education, English proficiency, and mobility limitation.

RESULTS

Most older adults preferred to participate actively in making health care decisions. Older adults with 4 or more conditions, however, and those with multiple condition clusters are relatively less likely to prefer active decision making.

CONCLUSIONS

Primary care physicians should initiate a shared decision-making process with older adults with 4 or more conditions or multiple condition clusters. Physicians should anticipate variation in decision-making preferences among older adults and adapt a decision-making process that suits individuals' preferences for participation to ensure person-centered care delivery.

Latent class analysis of multimorbidity patterns and associated outcomes in Spanish older adults: a prospective cohort study

Background

This study sought to identify multimorbidity patterns and determine the association between these latent classes with several outcomes, including health, functioning, disability, quality of life and use of services, at baseline and after 3 years of follow-up.

Methods

We analyzed data from a representative Spanish cohort of 3541 non-institutionalized people aged 50 years old and over. Measures were taken at baseline and after 3 years of follow-up. Latent Class Analysis (LCA) was conducted using eleven common chronic conditions. Generalized linear models were conducted to determine the adjusted association of multimorbidity latent classes with several outcomes.

Results

63.8% of participants were assigned to the “healthy” class, with minimum disease, 30% were classified under the “metabolic/stroke” class and 6% were assigned to the “cardiorespiratory/mental/arthritis” class. Significant cross-sectional associations were found between membership of both multimorbidity classes and poorer memory, quality of life, greater burden and more use of services. After 3 years of follow-up, the “metabolic/stroke” class was a significant predictor of lower levels of verbal fluency while the two multimorbidity classes predicted poor quality of life, problems in independent living, higher risk of hospitalization and greater use of health services.

Conclusions

Common chronic conditions in older people cluster together in broad categories. These broad clusters are qualitatively distinct and are important predictors of several health and functioning outcomes. Future studies are needed to understand underlying mechanisms and common risk factors for patterns of multimorbidity and to propose more effective treatments.

Electronic supplementary material

The online version of this article (doi:10.1186/s12877-017-0586-1) contains supplementary material, which is available to authorized users.

Association Between Lifestyle Factors and the Incidence of Multimorbidity in an Older English Population

Background

Evidence on the role of lifestyle factors in relation to multimorbidity, especially in elderly populations, is scarce. We assessed the association between five lifestyle factors and incident multimorbidity (presence of ≥2 chronic conditions) in an English cohort aged ≥50 years.

Methods

We used data from waves 4, 5, and 6 of the English Longitudinal Study of Ageing. Data on smoking, alcohol consumption, physical activity, fruit and vegetable consumption, and body mass index were extracted and combined to generate a sum of unhealthy lifestyle factors for each individual. We examined whether these lifestyle factors individually or in combination predicted multimorbidity during the subsequent wave. We used marginal structural Cox proportional hazard models, adjusted for both time-constant and time-varying factors.

Results

A total of 5,476 participants contributed 232,749 person-months of follow-up during which 1,156 cases of incident multimorbidity were recorded. Physical inactivity increased the risk of multimorbidity by 33% (adjusted hazard ratio [aHR]: 1.33, 95% confidence interval [CI]: 1.03-1.73). The risk was about two to three times higher when inactivity was combined with obesity (aHR: 2.87, 95% CI: 1.55-5.31) or smoking (aHR: 2.35, 95% CI: 1.36-4.08) and about four times when combined with both (aHR: 3.98, 95% CI: 1.02-17.00). Any combination of 2, 3, and 4 or more unhealthy lifestyle factors significantly increased the multimorbidity hazard, compared with none, from 42% to 116%.

Conclusion

This study provides evidence of a temporal association between combinations of different unhealthy lifestyle factors with multimorbidity. Population level interventions should include reinforcing positive lifestyle changes in the population to reduce the risk of developing multimorbidity.

Determinants of Health-Related Quality of Life Among Older American Indians and Alaska Natives

During the past decade, health-related quality of life (HRQoL) has been recognized in both clinical and community health research as an important health outcome and a needed supplement to conventional health outcomes. The authors provide a profile of HRQoL and examine its determinants among American Indians and Alaska Natives aged 50 or older. Multivariate analyses of cross-sectional survey data from the 1996-1998 Centers for Disease Control Behavioral Risk Factor Surveillance System were conducted. Thirty-four percent of the sample reported fair or poor self-rated health. The mean number of poor health days in the past month ranged from 4 to 6 on different measures. Age, sex, education, annual household income, employment status, hypertension, and obesity were associated with aspects of HRQoL. Further research aimed at eliminating health disparities among this population should focus on identifying additional indicators of poor HRQoL and on understanding variables that mediate the relationship between disease and HRQoL.

Patterns and Consequences of Multimorbidity in the General Population: There is No Chronic Disease Management Without Rheumatic Disease Management

OBJECTIVE

To identify empirical model-based patterns of multimorbidity from chronic noncommunicable diseases in the general population, with a focus on the contribution of rheumatic and musculoskeletal diseases (RMDs), and to quantify their association with adverse health outcomes.

METHODS

Cross-sectional data from the Portuguese Fourth National Health Survey were analyzed (n = 23,754). Latent class analysis was used to identify patterns of coexistence of 11 chronic noncommunicable diseases (RMDs, diabetes mellitus, hypertension, chronic obstructive pulmonary disease, stroke, depression, myocardial infarction, cancer, osteoporosis, asthma, and renal failure). Based on the Outcome Measures in Rheumatology, filter 2.0, health outcomes included life impact, pathophysiologic manifestations, and resource use. We assessed the association between patterns and adverse health outcomes, through sex-, age-, and body mass index-adjusted prevalence ratios with 95% confidence intervals, obtained using Poisson regression.

RESULTS

Four patterns of chronic noncommunicable diseases co-occurrence were identified and labeled as low disease probability, cardiometabolic conditions, respiratory conditions, and RMDs and depression. RMDs were highly prevalent in patients with chronic diseases (from 38.6% in cardiometabolic conditions to 66.7% in RMDs and depression). While negative self-rated health, short-term disability, and chronic pain were more strongly associated with cardiometabolic conditions and respiratory conditions, all multimorbidity patterns were similarly associated with long-term disability, frequent health care utilization, and out-of-pocket health care expenses.

CONCLUSION

Our study emphasizes RMDs as a major presence in multimorbidity in the general population. All multimorbidity patterns were associated with a wide set of adverse health outcomes. Management strategies for the patient with chronic cardiometabolic, respiratory, or depressive conditions should also target RMDs.

Individualized Absolute Risk Calculations for Persons with Multiple Chronic Conditions: Embracing Heterogeneity, Causality, and Competing Events

Approximately 75% of adults over the age of 65 years are affected by two or more chronic medical conditions. We provide a conceptual justification for individualized absolute risk calculators for competing patient-centered outcomes (PCO) (i.e. outcomes deemed important by patients) and patient reported outcomes (PRO) (i.e. outcomes patients report instead of physiologic test results). The absolute risk of an outcome is the probability that a person receiving a given treatment will experience that outcome within a pre-defined interval of time, during which they are simultaneously at risk for other competing outcomes. This allows for determination of the likelihood of a given outcome with and without a treatment. We posit that there are heterogeneity of treatment effects among patients with multiple chronic conditions (MCC) largely depends on those coexisting conditions. We outline the development of an individualized absolute risk calculator for competing outcomes using propensity score methods that strengthen causal inference for specific treatments. Innovations include the key concept that any given outcome may or may not concur with any other outcome and that these competing outcomes do not necessarily preclude other outcomes. Patient characteristics and MCC will be the primary explanatory factors used in estimating the heterogeneity of treatment effects on PCO and PRO. This innovative method may have wide-spread application for determining individualized absolute risk calculations for competing outcomes. Knowing the probabilities of outcomes in absolute terms may help the burgeoning population of patients with MCC who face complex treatment decisions.

Long terms trends of multimorbidity and association with physical activity in older English population

Background

Multimorbidity has become one of the main challenges in the recent years for patients, health care providers and the health care systems globally. However, literature describing the burden of multimorbidity in the elderly population, especially longitudinal trends is very limited. Physical activity is recommended as one of the main lifestyle changes in the prevention and management of multiple chronic diseases worldwide; however, the evidence on its association with multimorbidity remains inconclusive. Therefore, we aimed to assess the longitudinal trends of multimorbidity and the association between multimorbidity and physical activity in a nationally representative cohort of the English population aged ≥50 years between 2002 and 2013.

Methods

We used data on 15,688 core participants from six waves of the English Longitudinal Study of Ageing, with complete information on physical activity. Self-reported physical activity was categorised as inactive, mild, moderate and vigorous levels of physical activity. We calculated the number of morbidities and the prevalence of multimorbidity (more than 2 chronic conditions) between 2002 and 2013 overall and by levels of self-reported physical activity. We estimated the odds ratio (OR) and 95 % confidence intervals (CI) for multimorbidity by each category of physical activity, adjusting for potential confounders.

Results

There was a progressive decrease over time in the proportion of participants without any chronic conditions (33.9 % in 2002/2003 vs. 26.8 % in 2012/2013). In contrast, the prevalence of multimorbidity steadily increased over time (31.7 % in 2002/2003 vs. 43.1 % in 2012/2013). Compared to the physically inactive group, the OR for multimorbidity was 0.84 (95 % CI 0.78 to 0.91) in mild, 0.61 (95 % CI 0.56 to 0.66) in moderate and 0.45 (95 % CI 0.41 to 0.49) in the vigorous physical activity group.

Conclusion

This study demonstrated an inverse dose-response association between levels of physical activity and multimorbidity, however, given the increasing prevalence of multimorbidity over time, there is a need to explore causal associations between physical activity and multimorbidity and its impact as a primary prevention strategy to prevent the occurrence of chronic conditions later in life and reduce the burden of multimorbidity.

Electronic supplementary material

The online version of this article (doi:10.1186/s12966-016-0330-9) contains supplementary material, which is available to authorized users.

Deconstructing Complex Multimorbidity in the Very Old: Findings from the Newcastle 85+ Study

Objectives. To examine the extent and complexity of the morbidity burden in 85-year-olds; identify patterns within multimorbidity; and explore associations with medication and healthcare use. Participants. 710 men and women; mean (SD) age 85.5 (0.4) years. Methods. Data on 20 chronic conditions (diseases and geriatric conditions) ascertained from general practice records and participant assessment. Cluster analysis within the multimorbid sample identified subgroups sharing morbidity profiles. Clusters were compared on medication and healthcare use. Results. 92.7% (658/710) of participants had multimorbidity; median number of conditions: 4 (IQR 3–6). Cluster analysis (multimorbid sample) identified five subgroups sharing similar morbidity profiles; 60.0% (395/658) of participants belonged to one of two high morbidity clusters, with only 4.9% (32/658) in the healthiest cluster. Healthcare use was high, with polypharmacy (≥5 medications) in 69.8% (459/658). Between-cluster differences were found in medication count (p = 0.0001); hospital admissions (p = 0.022); and general practitioner (p = 0.034) and practice nurse consultations (p = 0.011). Morbidity load was related to medication burden and use of some, but not all, healthcare services. Conclusions. The majority of 85-year-olds had extensive and complex morbidity. Elaborating participant clusters sharing similar morbidity profiles will help inform future healthcare provision and the identification of common underlying biological mechanisms.

Gifted students with a coexisting disability: The twice exceptional

The twice exceptional are students who have both high ability and a disability or disorder. The ability can be in any culturally-valued domain, including high intelligence, academics, the visual or performing arts, and athletics. The co-existing disability can be physical, medical, or psychological. There is a growing literature of scholarly opinion about twice exceptionality; however, there are few well-designed empirical investigations of gifted students with anxiety, depression, bipolar disorder, attention-deficit/hyperactivity disorder, eating disorders, conduct problems, or medical, physical or sensory disabilities. This article examines a few key issues about the twice exceptional student and then discusses what we know about the gifted students with attention-deficit hyperactivity disorder and gifted students with learning disabilities. The article also provides a brief discussion on suicide and the gifted student.

Prevalence and Patterns of Chronic Disease Pairs and Multimorbidity among Older Chinese Adults Living in a Rural Area

Background

The burden of chronic diseases in China is substantial now. Data on patterns of chronic diseases and multimorbidity among older adults, especially among those living in rural areas, are sparse.

Objective

We aim to investigate the prevalence and patterns of chronic disease pairs and multimorbidity in elderly people living in rural China.

Methods

This population-based study included 1480 adults aged 60 years and over (mean age 68.5 years, 59.4% women) living in a rural community. Data were derived from the Confucius Hometown Aging Project in Shandong, China (June 2010-July 2011). Chronic diseases were diagnosed through face-to-face interviews, clinical examinations, and laboratory tests. Patterns of chronic disease pairs and multimorbidity were explored using logistic regression and exploratory factor analyses.

Results

The prevalence of individual chronic diseases ranged from 3.0% for tumor to 76.4% for hypertension, and each disease was often accompanied with three or more other chronic diseases. The observed prevalence of pairs of chronic conditions exceeded the expected prevalence for several conditions, such as cardiovascular diseases and metabolic disorders, as well as pulmonary diseases and degenerative disorders. Chronic multimorbidity (≥2 chronic diseases) affected more than 90% of subjects, and two patterns of chronic multimorbidity were identified: cardiopulmonary-mental-degenerative disorder pattern (overall prevalence, 58.2%), and cerebrovascular-metabolic disorder pattern (62.6%). Prevalence of the cardiopulmonary-mental-degenerative disorder pattern increased with age, and was higher in men than women; whereas prevalence of the cerebrovascular-metabolic disorder pattern was higher in women than in men but did not vary by age.

Conclusion

Chronic multimorbidity was highly prevalent among older Chinese adults living in rural areas, and there were specific patterns of the co-occurrence of chronic diseases. Effort is needed to identify possible preventative strategies based on the potential clustering of chronic diseases.

Multimorbidity Patterns in Hospitalized Older Patients: Associations among Chronic Diseases and Geriatric Syndromes

BACKGROUND/OBJECTIVES

The clinical status of older individuals with multimorbidity can be further complicated by concomitant geriatric syndromes. This study explores multimorbidity patterns, encompassing both chronic diseases and geriatric syndromes, in geriatric patients attended in an acute hospital setting.

DESIGN

Retrospective observational study.

SETTING

Unit of Social and Clinical Assessment (UVSS), Miguel Servet University Hospital (HUMS), Zaragoza (Spain). Year, 2011.

PARTICIPANTS

A total of 924 hospitalized patients aged 65 years or older.

MEASUREMENTS

Data on patients' clinical, functional, cognitive and social statuses were gathered through comprehensive geriatric assessments. To identify diseases and/or geriatric syndromes that cluster into patterns, an exploratory factor analysis was applied, stratifying by sex. The factors can be interpreted as multimorbidity patterns, i.e., diseases non-randomly associated with each other within the study population. The resulting patterns were clinically assessed by several physicians.

RESULTS

The mean age of the study population was 82.1 years (SD 7.2). Multimorbidity burden was lower in men under 80 years, but increased in those over 80. Immobility, urinary incontinence, hypertension, falls, dementia, cognitive decline, diabetes and arrhythmia were among the 10 most frequent health problems in both sexes, with prevalence rates above 20%. Four multimorbidity patterns were identified that were present in both sexes: Cardiovascular, Induced Dependency, Falls and Osteoarticular. The number of conditions comprising these patterns was similar in men and women.

CONCLUSION

The existence of specific multimorbidity patterns in geriatric patients, such as the Induced Dependency and Falls patterns, may facilitate the early detection of vulnerability to stressors, thus helping to avoid negative health outcomes such as functional disability.

Risk and protective factors for depressive symptoms among American Indian older adults: adverse childhood experiences and social support

OBJECTIVES

Despite efforts to promote health equity, many American Indian and Alaska Native (AI/AN) populations, including older adults, experience elevated levels of depression. Although adverse childhood experiences (ACE) and social support are well-documented risk and protective factors for depression in the general population, little is known about AI/AN populations, especially older adults. The purpose of this study was to examine factors related to depression among a sample of AI older adults in the midwest.

METHOD

Data were collected using a self-administered survey completed by 233 AIs over the age of 50. The survey included standardized measures such as the Geriatric Depression Scale-Short Form, ACE Questionnaire, and the Multidimensional Scale of Perceived Social Support. Hierarchical multivariate regression analyses were conducted to evaluate the main hypotheses of the study.

RESULTS

Two dimensions of ACE (i.e., childhood neglect, household dysfunction) were positively associated with depressive symptoms; social support was negatively associated with depressive symptoms. Perceived health and living alone were also significant predictors.

CONCLUSION

ACE may play a significant role in depression among AI/AN across the life course and into old age. Social support offers a promising mechanism to bolster resilience among AI/AN older adults.

Association of depressive symptomatology with receipt of informal caregiving among older American Indians: the native elder care study

OBJECTIVE

Our study objectives were to identify the primary sources of informal caregiving and to examine the association of depressive symptomatology with receipt of informal caregiving among a sample of community-dwelling older American Indians.

DESIGN

We conducted a cross-sectional study of older American Indians.

PARTICIPANTS

Community-dwelling adults aged 55 years and older who are members of a federally recognized American Indian tribe in the Southeast United States.

MEASUREMENTS

We collected information on the participant's primary caregiver, number of informal care hours received in the past week, depressive symptomatology, demographic characteristics, physical health status, and assistance need.

RESULTS

Daughters, spouses, and sons were the most common informal primary caregivers with distinct differences by sex of those receiving care. Compared with participants with lower levels, those with a high level of depressive symptomatology received substantially greater hours of informal care (33.4 versus 11.5 hours per week).

CONCLUSION

Older American Indians with higher levels of depressive symptomatology received more informal caregiving than those with lower depressive symptomatology. The burden of caregiving of older adults is primarily shouldered by spouses and children with those who care for older adults with depressive symptomatology likely experiencing an even greater burden of care.

Stressors, Coping Resources, and Depressive Symptoms among Rural American Indian Older Adults

The purpose of this study was to examine the associations of physical health stressors and coping resources with depressive symptoms among American Indian older adults age 50 years or older. The study used a convenience sample of 227 rural American Indian older adults. A hierarchical multiple regression tested three sets of predictors on depressive symptoms: (a) sociodemographics, (b) physical health stressors (functional disability and chronic medical conditions), and (c) coping resources (social support and spirituality). Most participants reported little difficulty in performing daily activities (e.g., eating, dressing, traveling, and managing money), while presenting over two types of chronic medical conditions. Depressive symptoms were predicted by higher scores on perceived social support and lower scores on functional disability; women and those having no health insurance also had higher levels of depressive symptoms. Findings suggest that social work practitioners should engage family and community support, advocate for access to adequate health care, and attend to women's unique circumstances and needs when working with American Indian older adults.

Impact of changes in medical condition burden index and stress on absenteeism among employees of a US utility company

Purpose

– The purpose of this paper is to investigate the impact of changes of medical condition burden index (MCBI) and stress on absenteeism and discuss implications for policy/program design.

Design/methodology/approach

– Sample: US utility employees that participated in Health Risk Appraisals (HRA) during 2009 and 2010 (n=3,711). Methods: the MCBI was created by summing number of medical conditions. Absenteeism was measured from administrative records. Change in MCBI and stress and impact on absenteeism was assessed according to incremental change, by low/high categorizations, and by using multivariate regression.

Findings

– Incrementally, greater changes in MCBI or stress generally resulted in corresponding absenteeism change. For both MCBI and stress, high categories were associated with greater absenteeism compared to those in low categories. Those remaining in the low MCBI category decreased absenteeism (−0.10 days/year; p=0.01). Changes from low to high MCBI resulted in increased absenteeism (+0.12 days/year; p=0.04. Changes in stress from low to high or from high to low categories resulted in concurrent changes in absenteeism (+0.21 days/year; p=0.04 and −0.31 days/year; p=0.01, respectively). Regression analyses indicated the interaction between stress and MCBI as a significant contributor to absenteeism change.

Research limitations/implications

– Conclusions: MCBI, stress and their interaction appear to be direct determinants of absenteeism. Companies should consider both physical and emotional health simultaneously in program interventions in order to reduce absenteeism.

Originality/value

– Unlike most studies illustrating cross-sectional relationships, this study shows how changes in stress and medical conditions relate to changes in absenteeism. The interaction between MCBI and stress in this context is also a novel addition.

An Examination of the Disablement Process Among Older American Indians: The Native Elder Care Study

PURPOSE OF THE STUDY

Older American Indians disproportionately suffer from poorer physical and mental health and have greater disability compared to their racial and ethnic counterparts. The purpose of this study was to examine the disablement process among older American Indians.

DESIGN AND METHODS

Data analyzed were from the Native Elder Care Study, which included in-person interviews with 505 community-dwelling American Indians aged ≥55 years. We used structural equation modeling to examine the contributive direct and indirect effects of health, demographic, and psychosocial risk factors on disability.

RESULTS

Pathology had direct and indirect effects through social support and depressive symptoms on chronic pain intensity. Pathology also had direct and indirect effects on disability. Chronic pain intensity was a significant mediator between pathology and functional limitations. With contributive effects of older age and female sex, greater functional limitations were associated with increased disability.

IMPLICATIONS

Our results support the theorized main pathway of the Disablement Process Model with our sample of older American Indians. Our findings support the importance of taking into account intra and extraindividual factors in assessing the prevalence and incidence of disability for older American Indians.

A comparison of GP and GDS diagnosis of depression in late life among multimorbid patients - results of the MultiCare study

BACKGROUND

The objective of the study was to compare General Practitioners׳ (GPs) diagnosis of depression and depression diagnosis according to Geriatric Depression Scale (GDS) and to identify potential factors associated with both depression diagnosis methods.

METHODS

The data were derived from the baseline wave of the German MultiCare1 study, which is a multicentre, prospective, observational cohort study of 3177 multimorbid patients aged 65+ randomly selected from 158 GP practices. Data were collected in GP interviews and comprehensive patient interviews. Depressive symptoms were assessed with a short version of the Geriatric Depression Scale (15 items, cut-off 6). Cohen׳s kappa was used to assess agreement of GP and GDS diagnoses. To identify factors that might have influenced GP and GDS diagnoses of depression, binary logistic regression analyses were performed.

RESULTS

Depressive symptoms according to GDS were diagnosed in 12.6% of the multimorbid subjects, while 17.8% of the patients received a depression diagnosis by their GP. The agreement between general practitioners and GDS diagnosis was poor. To summarize we find that GPs and the GDS have different perspectives on depression. To GPs somatic and psychological comorbid conditions carry weight when diagnosing depression, while cognitive impairment in form of low verbal fluency, pain and comorbid somatic conditions are relevant for a depression diagnosis by GDS.

CONCLUSIONS

Each depression diagnosing method is influenced by different variables and therefore, has advantages and limitations. Possibly, the application of both, GP and GDS diagnoses of depression, could provide valuable support in combining the different perspectives of depression and contribute to a comprehensive view on multimorbid elderly in primary care setting.

Distinct trajectories of multimorbidity in primary care were identified using latent class growth analysis

Objectives

To investigate the use of latent class growth analysis (LCGA) in understanding onset and changes in multimorbidity over time in older adults.

Study Design and Setting

This study used primary care consultations for 42 consensus-defined chronic morbidities over 3 years (2003–2005) by 24,615 people aged >50 years at 10 UK general practices, which contribute to the Consultations in Primary Care Archive database. Distinct groups of people who had similar progression of multimorbidity over time were identified using LCGA. These derived trajectories were tested in another primary care consultation data set with linked self-reported health status.

Results

Five clusters of people representing different trajectories were identified: those who had no recorded chronic problems (40%), those who developed a first chronic morbidity over 3 years (10%), a developing multimorbidity group (37%), a group with increasing number of chronic morbidities (12%), and a multi-chronic group with many chronic morbidities (1%). These trajectories were also identified using another consultation database and associated with self-reported physical and mental health.

Conclusion

There are distinct trajectories in the development of multimorbidity in primary care populations, which are associated with poor health. Future research needs to incorporate such trajectories when assessing progression of disease and deterioration of health.

Impact of multimorbidity: acute morbidity, area of residency and use of health services across the life span in a region of south Europe

Background

Concurrent diseases, multiple pathologies and multimorbidity patterns are topics of increased interest as the world’s population ages. To explore the impact of multimorbidity on affected patients and the consequences for health services, we designed a study to describe multimorbidity by sex and life-stage in a large population sample and to assess the association with acute morbidity, area of residency and use of health services.

Methods

A cross-sectional study was conducted in Catalonia (Spain). Participants were 1,749,710 patients aged 19+ years (251 primary care teams). Primary outcome: Multimorbidity (≥2 chronic diseases). Secondary outcome: Number of new events of each acute disease. Other variables: number of acute diseases per patient, sex, age group (19–24, 25–44, 45–64, 65–79, and 80+ years), urban/rural residence, and number of visits during 2010.

Results

Multimorbidity was present in 46.8% (95% CI, 46.7%-46.8%) of the sample, and increased as age increased, being higher in women and in rural areas. The most prevalent pair of chronic diseases was hypertension and lipid disorders in patients older than 45 years. Infections (mainly upper respiratory infection) were the most common acute diagnoses. In women, the highest significant RR of multimorbidity vs. non-multimorbidity was found for teeth/gum disease (aged 19–24) and acute upper respiratory infection. In men, this RR was only positive and significant for teeth/gum disease (aged 65–79). The adjusted analysis showed a strongly positive association with multimorbidity for the oldest women (80+ years) with acute diseases and women aged 65–79 with 3 or more acute diseases, compared to patients with no acute diseases (OR ranged from 1.16 to 1.99, p < 0.001). Living in a rural area was significantly associated with lower probability of having multimorbidity. The odds of multimorbidity increased sharply as the number of visits increased, reaching the highest probability in those aged 65–79 years.

Conclusions

Multimorbidity is related to greater use of health care services and higher incidence of acute diseases, increasing the burden on primary care services. The differences related to sex and life-stage observed for multimorbidity and acute diseases suggest that further research on multimorbidity should be stratified according to these factors.

Multimorbidity patterns: a systematic review

OBJECTIVES

The aim of this review was to identify studies on patterns of associative multimorbidity, defined as the nonrandom association between diseases, focusing on the main methodological features of the studies and the similarities among the detected patterns.

STUDY DESIGN AND SETTING

Studies were identified through MEDLINE and EMBASE electronic database searches from their inception to June 2012 and bibliographies.

RESULTS

The final 14 articles exhibited methodological heterogeneity in terms of the sample size, age and recruitment of study participants, the data source, the number of baseline diseases considered, and the statistical procedure used. A total of 97 patterns composed of two or more diseases were identified. Among these, 63 patterns were composed of three or more diseases. Despite the methodological variability among studies, this review demonstrated relevant similarities for three groups of patterns. The first one comprised a combination of cardiovascular and metabolic diseases, the second one was related with mental health problems, and the third one with musculoskeletal disorders.

CONCLUSION

The existence of associations beyond chance among the different diseases that comprise these patterns should be considered with the aim of directing future lines of research that measure their intensity, clarify their nature, and highlight the possible causal underlying mechanisms.