Multimorbidity patterns and their relationship to mortality in the US older adult population

Temporal change in multimorbidity prevalence, clustering patterns, and the association with mortality: findings from the China Kadoorie Biobank study in Jiangsu Province

Objectives

The characteristics of multimorbidity in the Chinese population are currently unclear. We aimed to determine the temporal change in multimorbidity prevalence, clustering patterns, and the association of multimorbidity with mortality from all causes and four major chronic diseases.

Methods

This study analyzed data from the China Kadoorie Biobank study performed in Wuzhong District, Jiangsu Province. A total of 53,269 participants aged 30-79 years were recruited between 2004 and 2008. New diagnoses of 15 chronic diseases and death events were collected during the mean follow-up of 10.9 years. Yule's Q cluster analysis method was used to determine the clustering patterns of multimorbidity. A Cox proportional hazards model was used to estimate the associations of multimorbidity with mortalities.

Results

The overall multimorbidity prevalence rate was 21.1% at baseline and 27.7% at the end of follow-up. Multimorbidity increased more rapidly during the follow-up in individuals who had a higher risk at baseline. Three main multimorbidity patterns were identified: (i) cardiometabolic multimorbidity (diabetes, coronary heart disease, stroke, and hypertension), (ii) respiratory multimorbidity (tuberculosis, asthma, and chronic obstructive pulmonary disease), and (iii) mental, kidney and arthritis multimorbidity (neurasthenia, psychiatric disorders, chronic kidney disease, and rheumatoid arthritis). There were 3,433 deaths during the follow-up. The mortality risk increased by 24% with each additional disease [hazard ratio (HR) = 1.24, 95% confidence interval (CI) = 1.20-1.29]. Compared with those without multimorbidity at baseline, both cardiometabolic multimorbidity and respiratory multimorbidity were associated with increased mortality from all causes and four major chronic diseases. Cardiometabolic multimorbidity was additionally associated with mortality from cardiovascular diseases and diabetes, with HRs of 2.64 (95% CI = 2.19-3.19) and 28.19 (95% CI = 14.85-53.51), respectively. Respiratory multimorbidity was associated with respiratory disease mortality, with an HR of 9.76 (95% CI = 6.22-15.31).

Conclusion

The prevalence of multimorbidity has increased substantially over the past decade. This study has revealed that cardiometabolic multimorbidity and respiratory multimorbidity have significantly increased mortality rates. These findings indicate the need to consider high-risk populations and to provide local evidence for intervention strategies and health management in economically developed regions.

Social Determinants of Health and Multimorbidity Among Adults 50 Years and Older in the United States

BACKGROUND

Living with two or more chronic conditions simultaneously-known as multimorbidity-has become increasingly prevalent as the aging population continues to grow. However, the factors that influence the development of multimorbidity are still not fully understood.

OBJECTIVES

The purpose of this study was to investigate the prevalence of multimorbidity among U.S. adults 50 years and older and identify associated factors with multimorbidity.

METHODS

We used data from four cycles from the National Health and Nutrition Examination Survey (2011-2018) to examine the associations between social determinants of health and multimorbidity among American adults aged 50 years and older. A set of variables on socioeconomic status and health behaviors was chosen based on the social determinants of health conceptual framework developed by the World Health Organization. In our study, 4,552 participants were included. All analyses were accounted for a complex survey design and the use of survey weights. Multiple logistic regression analyses were performed to examine the associated factors with multimorbidity.

RESULTS

The average age was 63.1 years, and 52.9% were female. The average number of chronic conditions was 2.27. The prevalence of multimorbidity was 63.8%, with high cholesterol and hypertension being the most prevalent conditions. In the adjusted model, age, gender, household income, citizenship status, health insurance, healthcare access, body mass index, and smoking status were found to be associated with living with multimorbidity.

DISCUSSION

Our results indicate that continued efforts aimed at promoting smoking cessation and maintaining a healthy weight will be beneficial in preventing the onset of chronic conditions. Additional research is warranted to gain a deeper understanding of the interrelationships between gender, race/ethnicity, household income, citizenship status, health insurance, and healthcare access as social determinants of health in the context of multimorbidity. Further research will help us develop targeted interventions and policies to address disparities and improve health outcomes for individuals with multimorbidity.

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.

Spanish version of the Maastricht Personal Autonomy Questionnaire: A validation study among community-dwelling older adults with chronic multimorbidity

BACKGROUND

Loss of personal autonomy in older adults with chronic multimorbidity is associated with worsened biopsychosocial health. In order to facilitate the standardised assessment of personal autonomy in older adults with chronic conditions, nurses could use the Maastricht Personal Autonomy Questionnaire (MPAQ).

OBJECTIVE

To translate, culturally adapt and psychometrically assess the Spanish version of the MPAQ in community-dwelling older adults with chronic multimorbidity (MPAQ-Sp).

METHODS

Observational cross-sectional study. A convenience sample of 884 community-dwelling older adults was recruited from 10 community centres in five health districts in southeastern Spain. Data were collected between January 2021 and September 2022. The study was completed in four phases. Phase 1: The MPAQ was translated into Spanish. Phase 2: A pilot test of reliability and content validity was conducted. Phase 3: To test the dimensionality of the tool, an exploratory factor analysis (EFA) was conducted. Phase 4: a final validation study was conducted which included a confirmatory factor analysis (CFA) and assessed the validity (content, criterion and construct), reliability and readability of the MPAQ-Sp.

RESULTS

The average age of the sample was 75.89 years (SD = ±8.04). Their mean number of chronic conditions was 4.84 (SD = ±2.19) and 67% were women. The MPAQ-Sp is comprised of 16 items distributed in four subscales: [1] the 'Degree of autonomy' scale, [2] the 'Working on autonomy' scale, [3] the 'Dilemmas: health over preferences' scale and [4] the 'Dilemmas: preferences over health' scale.

CONCLUSIONS

The Spanish version of the MPAQ-Sp is a valid and reliable instrument to assess personal autonomy in Spanish-speaking, community-dwelling older adults with chronic multimorbidity.

IMPLICATIONS FOR PRACTICE

The use of the MPAQ-Sp would allow researchers and healthcare professionals to identify a loss of personal autonomy among Spanish-speaking community-dwelling older adults with chronic multimorbidity.

The effects of community interventions on unplanned healthcare use in patients with multimorbidity: a systematic review

OBJECTIVES

To summarise the impact of community-based interventions for multimorbid patients on unplanned healthcare use. The prevalence of multimorbidity (co-existence of multiple chronic conditions) is rapidly increasing and affects one-third of the global population. Patients with multimorbidity have complex healthcare needs and greater unplanned healthcare usage. Community-based interventions allow for continued care of patients outside hospitals, but few studies have explored the effects of these interventions on unplanned healthcare usage.

DESIGN

A systematic review was conducted. MEDLINE, EMBASE, PsychINFO and Cochrane Library online databases were searched. Studies were screened and underwent risk of bias assessment. Data were synthesised using narrative synthesis.

SETTING

Community-based interventions.

PARTICIPANTS

Patients with multimorbidity.

MAIN OUTCOME MEASURES

Unplanned healthcare usage.

RESULTS

Thirteen studies, including a total of 6148 participants, were included. All included studies came from high-income settings and had elderly populations. All studies measured emergency department attendances as their primary outcome. Risk of bias was generally low. Most community interventions were multifaceted with emphasis on education, self-monitoring of symptoms and regular follow-ups. Four studies looked at improved care coordination, advance care planning and palliative care. All 13 studies found a decrease in emergency department visits post-intervention with risk reduction ranging from 0 (95% confidencec interval [CI]: -0.37 to 0.37) to 0.735 (95% CI: 0.688-0.785).

CONCLUSIONS

Community-based interventions have potential to reduce emergency department visits in patients with multimorbidity. Identification of specific successful components of interventions was challenging given the overlaps between interventions. Policymakers should recognise the importance of community interventions and aim to integrate aspects of these into existing healthcare structures. Future research should investigate the impact of such interventions with broader participant characteristics.

Epidemiology, mortality, and health service use of local-level multimorbidity patterns in South Spain

Multimorbidity -understood as the occurrence of chronic diseases together- represents a major challenge for healthcare systems due to its impact on disability, quality of life, increased use of services and mortality. However, despite the global need to address this health problem, evidence is still needed to advance our understanding of its clinical and social implications. Our study aims to characterise multimorbidity patterns in a dataset of 1,375,068 patients residing in southern Spain. Combining LCA techniques and geographic information, together with service use, mortality, and socioeconomic data, 25 chronicity profiles were identified and subsequently characterised by sex and age. The present study has led us to several findings that take a step forward in this field of knowledge. Specifically, we contribute to the identification of an extensive range of at-risk groups. Moreover, our study reveals that the complexity of multimorbidity patterns escalates at a faster rate and is associated with a poorer prognosis in local areas characterised by lower socioeconomic status. These results emphasize the persistence of social inequalities in multimorbidity, highlighting the need for targeted interventions to mitigate the impact on patients' quality of life, healthcare utilisation, and mortality rates.

Multimorbidity patterns in the German general population aged 40 years and over

AIM

The aim of this study was to identify and describe multimorbidity patterns among middle-aged and older community-dwelling individuals in Germany. Moreover, we aimed to determine potential gender differences in multimorbidity patterns.

METHODS

We analysed data from the most recent (sixth) wave (2017) of the large nationally representative German Ageing Survey (DEAS). Altogether n = 6,554 individuals participated, mean age was 62.0 (ranging from 43 to 92 years). Latent Class Analysis was performed to identify multimorbidity patterns, based on 13 chronic conditions and diseases. Multimorbidity was defined as the presence of at least two chronic conditions.

RESULTS

Altogether, 53.3% of individuals were multimorbid. We identified and clinically described five multimorbidity patterns: the relatively healthy class (45.1%), the high morbidity class (10.8%), the arthrosis/inflammatory/mental illnesses class (20.6%), the hypertension-metabolic illness class (21.7%), and the cardiovascular/cancer class (1.7%). Our analysis revealed that women compared to men have higher relative risk (IRR = 1.61, 95% CI 1.25-2.06) of being in the arthrosis/inflammatory/mental illnesses class, compared to the relatively healthy class. Furthermore, we found that, depending on which multimorbidity pattern individuals belong to, they differ greatly in terms of socio-demographic factors, health behaviour, and lifestyle factors.

CONCLUSIONS

We showed that the many chronic diseases cluster in a non-random way. Five clinically meaningful multimorbidity patterns were identified. Gender differences were apparent only in one class, namely in the arthrosis/inflammatory/mental illnesses class.

Characteristics Associated with Multimorbidity among Older United States Adult Opioid Users with Pain

The objective of this study was to investigate the variables associated with multimorbidity status among older United States (US) adults with self-reported pain and opioid use. This study used a cross-sectional retrospective database design that included US adults aged ≥50 years with self-reported pain who used an opioid in 2019 in the Medical Expenditure Panel Survey data. Multivariable logistic regression models, weighted to produce nationally representative estimates, were used to determine variables significantly associated with multimorbidity status (≥2 versus <2 chronic conditions). Significance was determined using an a priori alpha level of 0.05. In the adjusted logistic regression analysis, those aged 50-64 (vs. ≥65 years), Hispanic (vs. non-Hispanic), employed (vs. unemployed), and who performed frequent exercise (vs. no frequent exercise) were associated with lower odds of having multimorbidity. In conclusion, these characteristics may be targets for pain management and opioid use interventions among older US adults. Further research is needed to investigate the variables associated with multimorbidity in greater detail.

Additive effect of frailty with distinct multimorbidity patterns on mortality amongst middle-aged and older adults in Taiwan: A 16-year population-based study

AIM

This study aimed to explore the association between multimorbidity patterns with/without frailty and future mortality among Taiwanese middle-aged and older adults through a population-based cohort study design.

METHODS

Data were collected from the Taiwan Longitudinal Study on Aging. The data were obtained from Wave 3, with the multimorbidity patterns in the years of 1996 being analyzed through latent class analysis. Frailty was defined using the modified Fried criteria. The association between each disease group with/without frailty and mortality was examined using logistic regression, with the reference group as the Relatively healthy group without frailty. Survival analysis was performed using Cox regression, and the follow-up period of mortality was from 1 January 1996 to 31 December 2012.

RESULTS

A total of 4748 middle-aged and older adults with an average age of 66.3 years (SD: 9.07 years) were included. Four disease patterns were identified in 1996, namely the Cardiometabolic (21.0%), Arthritis-cataract (11.9%), Relatively healthy (61.6%), and Multimorbidity (5.5%) groups. After adjusting for all covariates, the Relatively healthy group with frailty showed the highest risk for mortality (odds ratio: 3.66, 95% confidence interval [95% CI]: 2.24-5.95), followed by the Cardiometabolic group with frailty (odds ratio: 3.58, 95% CI: 1.96-6.54), Multimorbidity group with frailty (odds ratio: 2.28, 95% CI: 1.17-4.44), Multimorbidity group without frailty (odds ratio: 1.44, 95% CI: 1.01-2.04), and the Cardiometabolic group without frailty (odds ratio: 1.24, 95% CI: 1.04-1.49).

CONCLUSIONS

Frailty plays an important role in mortality among middle-aged and older adults with distinct multimorbidity patterns. Middle-aged and older adults with a relatively healthy multimorbidity pattern or a cardiometabolic multimorbidity pattern with frailty encountered dismal outcomes. Geriatr Gerontol Int 2023; 23: 684-691.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

TRIAL REGISTRATION

NCT04981249. Registered 4 August 2021 (retrospectively registered).

Relationship between Treatment Burden, Health Literacy, and Medication Adherence in Older Adults Coping with Multiple Chronic Conditions

A prospective study was conducted to investigate the impact of treatment burden and health literacy on medication adherence among older adults with multiple chronic conditions (MCC) and to explore the potential moderating effects of demographic and clinical factors. Face-to-face structured interviews were conducted among older adults aged 60 and above using the Burden of Treatment Questionnaire (TBQ-15), Short Form Health Literacy Questionnaire (HLS-SF12), and Malaysia Medication Adherence Assessment Tool (MyMAAT). This study included 346 older adults aged 60 years and above with two or more chronic conditions (n = 346). Hypertension (30.2%), hyperlipidemia (24.0%), and diabetes (18.0%) were the most reported chronic conditions among participants. The mean score of treatment burden was 53.4 (SD = 28.2), indicating an acceptable burden of treatment. The mean score of health literacy was 16.4 (SD = 12.6), indicating a limited health literacy level among participants; meanwhile, the mean score of medication adherence was 32.6 (SD = 12.3), indicating medication non-adherence among participants. Medication adherence was significantly correlated with treatment burden (r = -0.22, p < 0.0001), health literacy (r = 0.36, p < 0.0001), number of chronic conditions (r = -0.23, p < 0.0001), and age (r = -0.11, p < 0.05). The study findings emphasize that multimorbid older adults with high treatment burdens and low health literacy are more likely to have poor medication adherence. This underscores the importance for clinicians to address these factors in order to improve medication adherence among older adults with multiple chronic conditions (MCC).

Multimorbidity and social determinants of health in the US prior to the COVID-19 pandemic and implications for health outcomes: a cross-sectional analysis based on NHANES 2017-2018

Multimorbidity increases the risk of all-cause mortality, and along with age, is an independent risk factor for severe disease and mortality from COVID-19. Inequities in the social determinants of health contributed to increased mortality from COVID-19 among disadvantaged populations. This study aimed to evaluate the prevalence of multimorbid conditions and associations with the social determinants of health in the US prior to the pandemic.Methods Data from the 2017-18 cycle of NHANES were used to determine the prevalence of 13 chronic conditions, and the prevalence of having 0, 1, or 2 or more of those conditions, among the US adult population aged ≥ 20 years. Multimorbidity was defined as having 2 or more of these conditions. Data were stratified according to demographic, socioeconomic and indicators of health access, and analyses including logistic regression, performed to determine the factors associated with multimorbidity.Results The prevalence of multimorbidity was 58.4% (95% CI 55.2 to 61.7). Multimorbidity was strongly associated with age and was highly prevalent among those aged 20-29 years at 22.2% (95% CI 16.9 to 27.6) and continued to increase with older age. The prevalence of multimorbidity was highest in those defined as Other or multiple races (66.9%), followed in decreasing frequency by rates among non-Hispanic Whites (61.2%), non-Hispanic Blacks (57.4%), Hispanic (52.0%) and Asian (41.3%) groups.Logistic regression showed a statistically significant relationship between multimorbidity and age, as expected. Asian race was associated with a reduced likelihood of 2 or more chronic conditions (OR 0.4; 95% CI 0.35 to 0.57; P < 0.0001). Socioeconomic factors were related to multimorbidity. Being above the poverty level (OR 0.64; 95% CI 0.46 to 0.91, p = 0.013); and a lack of regular access to health care (OR 0.61 (95% CI 0.42 to 0.88, p = 0.008) were both associated with a reduced likelihood of multimorbidity. Furthermore, there was a borderline association between not having health insurance and reduced likelihood of multimorbidity (OR 0.63; 95% CI 0.40 to 1.0; p = 0.053).Conclusions There are high levels of multimorbidity in the US adult population, evident from young adulthood and increasing with age. Cardiometabolic causes of multimorbidity were highly prevalent, especially obesity, hyperlipidemia, hypertension, and diabetes; conditions subsequently found to be associated with severe disease and death from COVID-19. A lack of access to care was paradoxically associated with reduced likelihood of comorbidity, likely linked to underdiagnosis of chronic conditions. Obesity, poverty, and lack of access to healthcare are factors related to multimorbidity and were also relevant to the health impact of the COVID-19 pandemic, that must be addressed through comprehensive social and public policy measures. More research is needed on the etiology and determinants of multimorbidity, on those affected, patterns of co-morbidity, and implications for individual health and impact on health systems and society to promote optimal outcomes. Comprehensive public health policies are needed to tackle multimorbidity and reduce disparities in the social determinants of health, as well as to provide universal access to healthcare.

Social determinants of multimorbidity patterns: A systematic review

Social determinants of multimorbidity are poorly understood in clinical practice. This review aims to characterize the different multimorbidity patterns described in the literature while identifying the social and behavioral determinants that may affect their emergence and subsequent evolution. We searched PubMed, Embase, Scopus, Web of Science, Ovid MEDLINE, CINAHL Complete, PsycINFO and Google Scholar. In total, 97 studies were chosen from the 48,044 identified. Cardiometabolic, musculoskeletal, mental, and respiratory patterns were the most prevalent. Cardiometabolic multimorbidity profiles were common among men with low socioeconomic status, while musculoskeletal, mental and complex patterns were found to be more prevalent among women. Alcohol consumption and smoking increased the risk of multimorbidity, especially in men. While the association of multimorbidity with lower socioeconomic status is evident, patterns of mild multimorbidity, mental and respiratory related to middle and high socioeconomic status are also observed. The findings of the present review point to the need for further studies addressing the impact of multimorbidity and its social determinants in population groups where this problem remains invisible (e.g., women, children, adolescents and young adults, ethnic groups, disabled population, older people living alone and/or with few social relations), as well as further work with more heterogeneous samples (i.e., not only focusing on older people) and using more robust methodologies for better classification and subsequent understanding of multimorbidity patterns. Besides, more studies focusing on the social determinants of multimorbidity and its inequalities are urgently needed in low- and middle-income countries, where this problem is currently understudied.

Association between multimorbidity patterns and incident depression among older adults in Taiwan: the role of social participation

Background

Previous research has found different multimorbidity patterns that negatively affects health outcomes of older adults. However, there is scarce evidence, especially on the role of social participation in the association between multimorbidity patterns and depression. Our study aimed to explore the relationship between multimorbidity patterns and depression among older adults in Taiwan, including the social participation effect on the different multimorbidity patterns.

Methods

Data were retracted from the Taiwan longitudinal study on ageing (TLSA) for this population-based cohort study. 1,975 older adults (age > 50) were included and were followed up from 1996 to 2011. We used latent class analysis to determine participants’ multimorbidity patterns in 1996, whereas their incident depression was determined in 2011 by CES-D. Multivariable logistic regression was used to analyse the relationship between multimorbidity patterns and depression.

Results

The participants’ average age was 62.1 years in 1996. Four multimorbidity patterns were discovered through latent class analysis, as follows: (1) Cardiometabolic group (n = 93), (2) Arthritis-cataract group (n = 105), (3) Multimorbidity group (n = 128) and (4) Relatively healthy group (n = 1649). Greater risk of incident depression was found among participants in the Multimorbidity group (OR: 1.62; 95% CI: 1.02–2.58) than the Relatively healthy group after the multivariable analysis. Compare to participants in the relatively healthy group with social participation, participants in the arthritis-cataract group without social participation (OR: 2.22, 95% CI: 1.03–4.78) and the multimorbidity group without social participation (OR: 2.21, 95% CI: 1.14–4.30) had significantly increased risk of having depression.

Conclusion

Distinct multimorbidity patterns among older adults in Taiwan are linked with the incident depression during later life, and social participation functioned as a protective factor.

Multimorbidity patterns and mortality in older adults: Results from the KORA-Age study

The coexistence of several chronic diseases is very common in older adults, making it crucial to understand multimorbidity (MM) patterns and associated mortality. We aimed to determine the prevalence of MM and common chronic disease combinations, as well as their impact on mortality in men and women aged 65 years and older using the population-based KORA-Age study, based in South of Germany. The chronic disease status of the participants was determined in 2008/9, and mortality status was followed up until 2016. MM was defined as having at least two chronic diseases. We used Cox proportional hazard models to calculate the hazard ratios (HRs) and the 95% confidence intervals (CIs) for associations between MM and all-cause mortality. During the study period 495 men (24.6%) and 368 women (17.4%) died. Although the MM prevalence was almost the same in men (57.7%) and women (60.0%), the overall effect of MM on mortality was higher in men (HR: 1.81, 95% CI: 1.47–2.24) than in women (HR: 1.28, 95% CI: 1.01–1.64; p-value for interaction &lt;0.001). The type of disease included in the MM patterns had a significant impact on mortality risk. For example, when both heart disease and diabetes were included in the combinations of two and three diseases, the mortality risk was highest. The risk of premature death does not only depend on the number of diseases but also on the specific disease combinations. In this study, life expectancy depended strongly on a few diseases, such as diabetes, hypertension, and heart disease.

Association of Sleep Duration and Use of Sleeping Medication with Multimorbidity in Adults: Results from the PAMPA (Brazil) Cohort Study

Objective  To analyze the association of sleep duration and use of sleeping medication with multimorbidity. Materials and Methods  We conducted a cross-sectional study using data from the Prospective Study about Mental and Physical Health (PAMPA) cohort. Multimorbidity was defined as the presence of two or more conditions from a list of twelve health problems. Descriptive analyses were performed considering proportion and its 95% confidence interval (95%CI). We performed logistic regression (to obtain odds ratios, ORs) to estimate the associations, including models adjusted for confounding factors. Results  In total, 2,936 participants were included, 79,1% of them women, 54.2% aged between 18 and 39 years, and 88.9% with white skin color. Compared with regular sleep (seven to eight hours a day), five hours or less of sleep increased the odds of multimorbidity by 145% (95%CI: 1.90-3.14), and 9 hours or more of sleep increased the odds by 49% (95%CI: 1.14-1.95) for the crude model; the results remained significant even in the adjusted models. Discussion  Consumption of sleeping medication was associated with multimorbidity. Short and prolonged sleep duration increased the odds of multimorbidity, regardless of the sociodemographic and behavior characteristics. The regular use of sleeping medication was also associated with multimorbidity. The results of the present study are important but require caution due to reverse causality, and longitudinal studies are needed to confirm the findings.

Associations between multimorbidity and frailty transitions among older Americans

BACKGROUND

The associations of multimorbidity patterns with transitions between frailty states remain unclear in older individuals.

METHODS

We used data from the National Health and Aging Trends Study 2011-2019. Frailty was measured annually using the Fried frailty phenotype. Multimorbidity patterns at baseline were identified using latent class analysis based on 14 chronic conditions. We used the semi-Markov multi-state model to investigate the influences of multimorbidity characterized by condition counts and patterns on subsequent frailty transitions over follow-ups.

RESULTS

Among 9450 participants aged ≥65 years at baseline, 34.8% were non-frail, 48.1% were pre-frail and 17.0% were frail. Over a median follow-up of 4.0 years, 16 880 frailty transitions were observed, with 10 527 worsening and 6353 improving. For 7675 participants with multimorbidity, four multimorbidity patterns were identified: osteoarticular pattern (62.4%), neuropsychiatric-sensory pattern (17.2%), cardiometabolic pattern (10.3%) and complex multimorbidity pattern (10.1%). Compared with no disease, multimorbidity was significantly associated with an increased risk of worsening transitions, including from non-frail to pre-frail (hazard ratio [HR] = 1.35; 95% confidence interval [CI] = 1.21-1.52), from non-frail to frail (HR = 1.68; 95% CI = 1.04-2.73), from pre-frail to frail (HR = 2.19; 95% CI = 1.66-2.90) and from pre-frail to death (HR = 1.64; 95% CI = 1.11-2.41). Compared with the osteoarticular pattern, neuropsychiatric-sensory, cardiometabolic and complex multimorbidity patterns had a significantly higher risk of worsening frailty (all P < 0.05).

CONCLUSIONS

Multimorbidity was associated with dynamic transitions between frailty states and death among older American adults, and the associations varied across multimorbidity patterns. The findings could offer significant implications for public health policymakers in planning interventions and healthcare resources. They also might inform clinicians regarding providing targeted clinical treatment and health management based on multimorbidity patterns of older people.

Impact of multimorbidity patterns in hospital admissions: the case study of asthma

Most previous studies assessing multimorbidity in asthma assessed the frequency of individual comorbid diseases. We aimed to assess the frequency and clinical and economic impact of co-occurring groups of comorbidities (comorbidity patterns using the Charlson Comorbidity Index) on asthma hospitalizations. We assessed the dataset containing a registration of all Portuguese hospitalisations between 2011-2015. We applied three different approaches (regression models, association rule mining, and decision trees) to assess both the frequency and impact of comorbidities patterns in the length-of-stay, in-hospital mortality and hospital charges. For each approach, separate analyses were performed for episodes with asthma as main and as secondary diagnosis. Separate analyses were performed by participants' age group. We assessed 198340 hospitalizations in patients >18 years old. Both in hospitalizations with asthma as main or secondary diagnosis, combinations of diseases involving cancer, metastasis, cerebrovascular disease, hemiplegia/paraplegia, and liver disease displayed a relevant clinical and economic burden. In hospitalizations having asthma as a secondary diagnosis, we identified several comorbidity patterns involving asthma and associated with increased length-of-stay (average impact of 1.3-3.2 additional days), in-hospital mortality (OR range = 1.4-7.9) and hospital charges (average additional charges of 351.0 to 1025.8 Euro compared with hospitalizations without any registered Charlson comorbidity). Consistent results were observed with association rules mining and decision tree approaches. Our findings highlight the importance not only of a complete assessment of patients with asthma, but also of considering the presence of asthma in patients admitted by other diseases, as it may have a relevant impact on clinical and health services outcomes.

Multimorbidity combinations and their association with functional disabilities among Indian older adults: evidence from Longitudinal Ageing Study in India (LASI)

OBJECTIVE

This study aims to identify the unique multimorbidity combinations (MMCs) and their associations with the functional disability of Indian older adults. Moreover, the population attributable fractions (PAFs) were calculated to assess the potential impact of additional diseases in the nested groups on disability.

DESIGN

A cross-sectional data were analysed in this study.

SETTING AND PARTICIPANTS

The present study uses data from the first wave of the Longitudinal Ageing Study in India (2017-2018). The sample for the study consists of 27 753 aged 60 years and over.

PRIMARY AND SECONDARY OUTCOME MEASURES

The primary outcome variable was functional disability, measured by the combined activities of daily living (ADL)-instrumental activities of daily living (IADL) index.

RESULTS

Out of 197 uniquely identified MMCs, the combination of hypertension and high depressive symptoms (HDS) was the most prevalent (10.3%). Overall, all MMCs were associated with increased functional limitation. Specifically, the combination of hypertension, arthritis and HDS was associated with greater ADL-IADL disability than any other MMC. The addition of HDS in group 3 (hypertension and arthritis) (incidence rate ratios (IRR)=1.44; 95% CI 1.26 to 1.64) and the addition of arthritis in group 1 (hypertension, HDS) (IRR=1.48; 95% CI 1.28 to 1.71) and group 2 (hypertension, diabetes) (IRR=1.49; 95% CI 1.22 to 1.82) significantly increases the rates of ADL-IADL disability. The estimated PAFs of the group 1 (hypertension and HDS), group 3 (hypertension and arthritis) and group 4 (arthritis and HDS) for ADL-IADL disability were 22.5% (19.2-25.5), 21.6% (18.7-24.4) and 23.5% (20.6-26.3), respectively.

CONCLUSION

The findings from this study underscore the importance of addressing the morbidity combinations which are more disabling than the others in older adults. Understanding the somatic and psychological relevance of the morbidities in functional health is necessary and can help reduce disabilities among older adults.

Cross-sectional associations between body mass index, waist circumference, and multimorbidity: Pró-Saúde study

Background

This study aimed (1) To investigate the association between the Body Mass Index (BMI) and waist circumference (WC) with multimorbidity (MM), and (2) To identify patterns of MM and investigate the relationship between BMI and WC with specific combinations of MM (patterns of MM).

Methods

A cross-sectional study was conducted with 2,698 participants of the fourth phase of the Brazilian Longitudinal Study of Adult Health (Pró-Saúde Study). MM was defined by the presence of two or more morbidities. MM patterns were identified by exploratory factor analysis based on tetrachoric correlations. Logistic regression models were used to assess associations (odds ratios (OR) with the respective confidence intervals (CI)).

Results

Of the total number of participants, 39.5% were overweight and 30.0% were obese; 89.0% (n = 1,468) of women and 77.0% (n = 952) of men were abdominally obese. Indeed, 60.7% (n = 1,635) was identified with MM. For the category four or more morbidities, OR values of 5.98 (95% CI 4.84-7.13) and 7.48 (95% CI 6.14-8.18) were found for each point of increase in BMI, and 6.74 (95% CI 5.48-7.99) and 8.48 (95% CI 7.64-9.29) for each additional centimeter in the WC, for female and male, respectively. Five patterns of MM were identified: respiratory, osteoarticular, cardiometabolic, gastric, and thyroid diseases (56.4% of the total variance). Positive associations were found between BMI and patterns of cardiometabolic, osteoarticular, thyroid and gastric diseases (higher OR of 1.09 [95% CI 1.04-1.14]) and less pronounced between WC and patterns of cardiometabolic and osteoarticular (higher OR of 1.04 [95% CI 1.03-1.04]).

Conclusions

The results showed that an increase of both BMI and WC was associated with a higher number of morbidities and with patterns of cardiometabolic and osteoarticular diseases.

Outpatient Service Use in Korean Older Adult Women with Degenerative Arthritis Based on Andersen's Model

To ensure that older adults (aged 65 years or older) can experience a healthy life, they should use medical services that are appropriate, both quantitatively and qualitatively. This study aimed to identify the factors affecting outpatient service use by older adult women with degenerative arthritis using Andersen’s model. A survey was conducted among 232 older adult women with degenerative arthritis in two university hospitals in Seoul. The Korean Activities of Daily Living, Korean Instrumental Activities of Daily Living, and the Geriatric Depression Scale Short Form were used. Data were analyzed using descriptive statistics, χ2-test, t-test, and multiple logistic regression analysis. Among the participants, 69.8% used outpatient services and 30.2% did not. In the univariate analyses, age, marital status, residency, household income, chronic diseases, subjective health status, and disability were significant. Age (odds ratio [OR] = 5.53, p < 0.001), annual household income (OR = 5.64, p < 0.001), chronic diseases (OR = 11.06, p < 0.001), and disability (OR = 3.56, p = 0.016) significantly affected outpatient service use. The results suggest that health promotion interventions for Korean older adult women should focus on predicting outpatient service use according to the patient’s characteristics.

Quantifying care delivery team influences on the hospitalization outcomes of patients with multimorbidity: Implications for clinical informatics

The primary objective was to quantify the influences of care delivery teams on the outcomes of patients with multimorbidity. Electronic medical record data on 68,883 patient care encounters (i.e., 54,664 patients) were extracted from the Arkansas Clinical Data Repository. Social network analysis assessed the minimum care team size associated with improved care outcomes (i.e., hospitalizations, days between hospitalizations, and cost) of patients with multimorbidity. Binomial logistic regression further assessed the influence of the presence of seven specific clinical roles. When compared to patients without multimorbidity, patients with multimorbidity had a higher mean age (i.e., 47.49 v. 40.61), a higher mean dollar amount of cost per encounter (i.e., $3,068 v. $2,449), a higher number of hospitalizations (i.e., 25 v. 4), and a higher number of clinicians engaged in their care (i.e., 139,391 v. 7,514). Greater network density in care teams (i.e., any combination of two or more Physicians, Residents, Nurse Practitioners, Registered Nurses, or Care Managers) was associated with a 46-98% decreased odds of having a high number of hospitalizations. Greater network density (i.e., any combination of two or more Residents or Registered Nurses) was associated with 11-13% increased odds of having a high cost encounter. Greater network density was not significantly associated with having a high number of days between hospitalizations. Analyzing the social networks of care teams may fuel computational tools that better monitor and visualize real-time hospitalization risk and care cost that are germane to care delivery.

Towards Whole Health Toxicology: In-Silico Prediction of Diseases Sensitive to Multi-Chemical Exposures

Chemical exposures from diverse sources merge on a limited number of molecular pathways described as toxicity pathways. Changes in the same set of molecular pathways in different cell and tissue types may generate seemingly unrelated health conditions. Today, no approaches are available to predict in an unbiased way sensitivities of different disease states and their combinations to multi-chemical exposures across the exposome. We propose an inductive in-silico workflow where sensitivities of genes to chemical exposures are identified based on the overlap of existing genomic datasets, and data on sensitivities of individual genes is further used to sequentially derive predictions on sensitivities of molecular pathways, disease states, and groups of disease states (syndromes). Our analysis predicts that conditions representing the most significant public health problems are among the most sensitive to cumulative chemical exposures. These conditions include six leading types of cancer in the world (prostatic, breast, stomach, lung, colorectal neoplasms, and hepatocellular carcinoma), obesity, type 2 diabetes, non-alcoholic fatty liver disease, autistic disorder, Alzheimer's disease, hypertension, heart failure, brain and myocardial ischemia, and myocardial infarction. Overall, our predictions suggest that environmental risk factors may be underestimated for the most significant public health problems.

Use of fish oil and mortality of patients with cardiometabolic multimorbidity: A prospective study of UK biobank

BACKGROUND AND AIMS

Cardiometabolic multimorbidity (CMM) has risen as a global issue of public health, with an in-creasing prevalence and more severe clinical prognosis. This study aimed to estimate the association between use of fish oil and mortality among patients with CMM.

METHODS AND RESULTS

In this prospective study based on UK Biobank, participants with ≥2 of cardiometabolic diseases (CMDs, including coronary heart disease [CHD], diabetes, hypertension, and stroke in this study) at recruitment were included. Use of fish oil was derived from touchscreen questionnaires at baseline. All-cause and cardiovascular mortality were accessed via electronic health-related records. Kaplan-Meier curves and flexible parametric Royston-Parmar proportion-hazard models were fitted to assess the as-sociations of fish-oil use with all-cause, cardiovascular mortality, and related life expectancy alterations. Among 30 068 participants from UK Biobank (67.9% men; mean age 61.75 years), 5357 deaths were reported during 12.03 years of follow-up. For patients with CMM, use of fish oil was associated with a 17% lower risk of all-cause mortality (95% confidence interval [95% CI] 0.78-0.88, P < 0.001), and 19% lower risk of cardiovascular mortality (95% CI 0.72-0.90, P < 0.001) in multivariable-adjusted models. At 45 years old, using fish oil was associated with 1.66 years of life expectancy gained.

CONCLUSION

Among patients with CMM, use of fish oil was associated with a significantly reduced risk of all-cause, cardiovascular mortality, and prolonged life expectancy.

Comprehensive Multimorbidity Patterns in Older Patients Are Associated with Quality Indicators of Medication-MoPIM Cohort Study

Multimorbidity is increasing and poses a challenge to the clinical management of patients with multiple conditions and drug prescriptions. The objectives of this work are to evaluate if multimorbidity patterns are associated with quality indicators of medication: potentially inappropriate prescribing (PIP) or adverse drug reactions (ADRs). A multicentre prospective cohort study was conducted including 740 older (≥65 years) patients hospitalised due to chronic pathology exacerbation. Sociodemographic, clinical and medication related variables (polypharmacy, PIP according to STOPP/START criteria, ADRs) were collected. Bivariate analyses were performed comparing previously identified multimorbidity clusters (osteoarticular, psychogeriatric, minor chronic disease, cardiorespiratory) to presence, number or specific types of PIP or ADRs. Significant associations were found in all clusters. The osteoarticular cluster presented the highest prevalence of PIP (94.9%) and ADRs (48.2%), mostly related to anxiolytics and antihypertensives, followed by the minor chronic disease cluster, associated with ADRs caused by antihypertensives and insulin. The psychogeriatric cluster presented PIP and ADRs of neuroleptics and the cardiorespiratory cluster indicators were better overall. In conclusion, the associations that were found reinforce the existence of multimorbidity patterns and support specific medication review actions according to each patient profile. Thus, determining the relationship between multimorbidity profiles and quality indicators of medication could help optimise healthcare processes. Trial registration number: NCT02830425.

Association of multimorbidity patterns with incident disability and recovery of independence among middle-aged and older adults

OBJECTIVE

to identify multimorbidity patterns among middle-aged and older adults in China and examine how these patterns are associated with incident disability and recovery of independence.

METHODS

data were from The China Health and Retirement Longitudinal Study. We included 14,613 persons aged ≥45 years. Latent class analysis (LCA) was conducted to identify multimorbidity patterns with clinical meaningfulness. Multinomial logistic models were used to determine the adjusted association between multimorbidity patterns and incident disability and recovery of independence.

RESULTS

we identified four multimorbidity patterns: 'low morbidity' (67.91% of the sample), 'pulmonary-digestive-rheumatic' (17.28%), 'cardiovascular-metabolic-neuro' (10.77%) and 'high morbidity' (4.04%). Compared to the 'low morbidity' group, 'high morbidity' (OR = 2.63, 95% CI = 1.97-3.51), 'pulmonary-digestive-rheumatic' (OR = 1.89, 95% CI = 1.63-2.21) and 'cardiovascular-metabolic-neuro' pattern (OR = 1.61, 95% CI = 1.31-1.97) had higher odds of incident disability in adjusted multinomial logistic models. The 'cardiovascular-metabolic-neuro' (OR = 0.60, 95% CI = 0.44-0.81), 'high morbidity' (OR = 0.68, 95% CI = 0.47-0.98) and 'pulmonary-digestive-rheumatic' group (OR = 0.75, 95% CI = 0.60-0.95) had lower odds of recovery from disability than the 'low morbidity' group. Among people without disability, the 'cardiovascular-endocrine-neuro' pattern was associated with the highest 2-year mortality (OR = 2.42, 95% CI = 1.56-3.72).

CONCLUSIONS

multimorbidity is complex and heterogeneous, but our study demonstrates that clinically meaningful patterns can be obtained using LCA. We highlight four multimorbidity patterns with differential effects on incident disability and recovery from disability. These studies suggest that targeted prevention and treatment approaches are needed for people with multimorbidity.

Impact of multimorbidity and complex multimorbidity on mortality among older Australians aged 45 years and over: a large population-based record linkage study

OBJECTIVES

Multimorbidity (MM, co-occurrence of two or more chronic conditions) and complex multimorbidity (CMM, three or more chronic conditions affecting three or more different body systems) are used in the assessment of complex healthcare needs and their impact on health outcomes. However, little is known about the impacts of MM and CMM on mortality in Australia.

DESIGN

Community-based prospective cohort study.

SETTING

New South Wales, Australia.

PARTICIPANTS

People aged 45 years and over who completed the baseline survey of the 45 and Up Study.

MEASURES

Baseline survey data from the 45 and Up Study were linked with deaths registry data. Deaths that occurred within 8 years from the baseline survey date were the study outcome. Eleven self-reported chronic conditions (cancer, heart disease, diabetes, stroke, Parkinson's disease, depression/anxiety, asthma, allergic rhinitis, hypertension, thrombosis and musculoskeletal conditions) from the baseline survey were included in the MM and CMM classifications. Cox proportional hazard models were used to estimate adjusted and unadjusted 8-year mortality hazard ratios (HRs).

RESULTS

Of 251 689 people (53% female and 54% aged ≥60 years) in the cohort, 111 084 (44.1%) were classified as having MM and 39 478 (15.7%) as having CMM. During the 8-year follow-up, there were 25 891 deaths. Cancer (34.7%) was the most prevalent chronic condition and the cardiovascular system (50.9%) was the body system most affected by a chronic condition. MM and CMM were associated with a 37% (adjusted HR 1.36, 95% CI 1.32 to 1.40) and a 22% (adjusted HR 1.22, 95% CI 1.18 to 1.25) increased risk of death, respectively. The relative impact of MM and CMM on mortality decreased as age increased.

CONCLUSION

MM and CMM were common in older Australian adults; and MM was a better predictor of all-cause mortality risk than CMM. Higher mortality risk in those aged 45-59 years indicates tailored, person-centred integrated care interventions and better access to holistic healthcare are needed for this age group.

Temporal trajectories of important diseases in the life course and premature mortality in the UK Biobank

BACKGROUND

Little is known regarding life-course trajectories of important diseases. We aimed to identify diseases that were strongly associated with mortality and test temporal trajectories of these diseases before mortality.

METHODS

Our analysis was based on UK Biobank. Diseases were identified using questionnaires, nurses' interviews, or inpatient data. Mortality register data were used to identify mortality up to January 2021. The association between 60 individual diseases at baseline and in the life course and incident mortality was examined using Cox proportional regression models. Those diseases with great contribution to mortality were identified and disease trajectories in life course were then derived.

RESULTS

During a median follow-up of 11.8 years, 31,373 individuals (median age at death (interquartile range): 70.7 (65.3-74.8) years, 59.4% male) died of all-cause mortality (with complete data on diagnosis date of disease), with 16,237 dying with cancer and 6702 with cardiovascular disease (CVD). We identified 37 diseases including cancers and heart diseases that were associated with an increased risk of mortality independent of other diseases (hazard ratio ranged from 1.09 to 7.77). Among those who died during follow-up, 2.2% did not have a diagnosis of any disease of interest and 90.1% were diagnosed with two or more diseases in their life course. Individuals who were diagnosed with more diseases in their life course were more likely to have longer longevity. Cancer was more likely to be diagnosed following hypertension, hypercholesterolemia, CVD, or digestive disorders and more likely to be diagnosed ahead of CVD, chronic kidney disease (CKD), or digestive disorders. CVD was more likely to be diagnosed following hypertension, hypercholesterolemia, or digestive disorders and more likely to be diagnosed ahead of cancer or CKD. Hypertension was more likely to precede other diseases, and CKD was more likely to be diagnosed as the last disease before more mortality.

CONCLUSIONS

There are significant interplays between cancer and CVD for mortality. Cancer and CVD were frequently clustered with hypertension, CKD, and digestive disorders with CKD highly being diagnosed as the last disease in the life course. Our findings underline the importance of health checks among middle-aged adults for the prevention of premature mortality.

Associations between multiple long-term conditions and mortality in diverse ethnic groups

Background

Multiple conditions are more prevalent in some minoritised ethnic groups and are associated with higher mortality rate but studies examining differential mortality once conditions are established is US-based. Our study tested whether the association between multiple conditions and mortality varies across ethnic groups in England.

Methods and findings

A random sample of primary care patients from Clinical Practice Research Datalink (CPRD) was followed from 1^st January 2015 until 31^st December 2019. Ethnicity, usually self-ascribed, was obtained from primary care records if present or from hospital records. Long-term conditions were counted from a list of 32 that have previously been associated with greater primary care, hospital admissions, or mortality risk. Cox regression models were used to estimate mortality by count of conditions, ethnicity and their interaction, with adjustment for age and sex for 532,059 patients with complete data. During five years of follow-up, 5.9% of patients died. Each additional condition at baseline was associated with increased mortality. The direction of the interaction of number of conditions with ethnicity showed a statistically higher mortality rate associated with long-term conditions in Pakistani, Black African, Black Caribbean and Other Black ethnic groups. In ethnicity-stratified models, the mortality rate per additional condition at age 50 was 1.33 (95% CI 1.31,1.35) for White ethnicity, 1.43 (95% CI 1.26,1.61) for Black Caribbean ethnicity and 1.78 (95% CI 1.41,2.24) for Other Black ethnicity.

Conclusions

The higher mortality rate associated with having multiple conditions is greater in minoritised compared with White ethnic groups. Research is now needed to identify factors that contribute to these inequalities. Within the health care setting, there may be opportunities to target clinical and self-management support for people with multiple conditions from minoritised ethnic groups.

Multimorbidity Patterns in US Adults with Subjective Cognitive Decline and Their Relationship with Functional Difficulties

Objectives

This study identified different multimorbidity patterns among adults with subjective cognitive decline (SCD) and examined their association with SCD-related functional difficulties.

Methods

Data were obtained from the 2019 Behavioral Risk Factor Surveillance System. Latent class analysis was applied to identify different patterns of chronic conditions. Logistic regression was implemented to examine relationships between multimorbidity patterns and risk of SCD-related functional difficulties.

Results

Five multimorbidity patterns were identified: severely impaired (14.6%), respiratory/depression (18.2%), obesity/diabetes (18.6%), age-associated (22.3%), and minimal chronic conditions group (26.3%). Compared with minimal chronic conditions group, severely impaired group was most likely to report SCD-related functional difficulties, followed by respiratory/depression and obesity/diabetes group.

Discussions

Individuals in the three multimorbidity groups had elevated risk of SCD-related functional difficulties compared with minimal chronic conditions group. Characteristics of the high-risk groups identified in this study may help in development and implementation of interventions to prevent serious consequences of having multiple chronic conditions.

Multimorbidity patterns and association with mortality in 0.5 million Chinese adults

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Development and Validation of a Multimorbidity Index Predicting Mortality Among Older Chinese Adults

Objective

This study aimed to develop and validate a multimorbidity index using self-reported chronic conditions for predicting 5-year mortality risk.

Methods

We analyzed data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) and included 11,853 community-dwelling older adults aged 65–84 years. Restrictive association rule mining (ARM) was used to identify disease combinations associated with mortality based on 13 chronic conditions. Data were randomly split into the training (N = 8,298) and validation (N = 3,555) sets. Two multimorbidity indices with individual diseases only (MI) and disease combinations (MIDC) were developed using hazard ratios (HRs) for 5-year morality in the training set. We compared the predictive performance in the validation set between the models using condition count, MI, and MIDC by the concordance (C) statistic, the Integrated Discrimination Improvement (IDI), and the Net Reclassification Index (NRI).

Results

A total of 13 disease combinations were identified. Compared with condition count (C-statistic: 0.710), MIDC (C-statistic: 0.713) showed significantly better discriminative ability (C-statistic: p = 0.016; IDI: 0.005, p < 0.001; NRI: 0.038, p = 0.478). Compared with MI (C-statistic: 0.711), the C-statistic of the model using MIDC was significantly higher (p = 0.031), while the IDI was more than 0 but not statistically significant (IDI: 0.003, p = 0.090).

Conclusion

Although current multimorbidity status is commonly defined by individual chronic conditions, this study found that the multimorbidity index incorporating disease combinations showed supreme performance in predicting mortality among community-dwelling older adults. These findings suggest a need to consider significant disease combinations when measuring multimorbidity in medical research and clinical practice.

Similarities and differences between China and Sweden regarding the core features of palliative care for people aged 60 or older: a systematic scoping review

Background

Despite the increasing longevity of the world’s population, with an unprecedented rise in the number of people who need palliative care (PC), there has been sparse research regarding palliative care for older people, especially when it comes to comparison of PC between healthcare systems and cultures. The aim of this systematic scoping review was to identify the characteristics of the body of literature and to examine the knowledge gaps concerning PC research for older people (> 60 years) in two healthcare systems and cultures, mainland China and Sweden.

Methods

The guidelines PRISMA (Preferred Reporting Items for Systematic Reviews), and PICOS (Patient/population, Intervention, Comparison/control, and Outcome) were used. Empirical studies on patients 60 years or older, next of kin or staff participating in a palliative care intervention or setting were included. They were conducted in mainland China or in Sweden during 2007–2019, were published in English and were extracted from seven databases: Embase, PubMed, Scopus, Cinahl, PsycInfo, Academic Search Complete and Cochrane Library. Two independent researchers conducted the selection of studies, data extraction and methodological evaluation. Any disagreements were resolved in consultation with a third researcher. The analysis was manifest directed content analysis based on PICOS domains.

Results

Of the 15 studies, four were from mainland China and 11 from Sweden. Both countries included older patients with cancer but also other end-stage diseases such as heart failure and dementia. The studies differed in design, method and the content of the interventions. The study in China based on traditional Chinese medicine concerns traditional Chinese folk music. The six qualitative studies from Sweden were evaluations of five interventions.

Conclusions

Despite the high age of the participating patients, there was no focus on an ageing perspective concerning palliative care. To adapt to the changes taking place in most societies, future research should have increased focus on older persons’ need for palliative care and should take account of issues concerning research ethics, ethnicity and culture.

Registered in Prospero

CRD42020078685, available from.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12904-022-00906-7.

Trends of Multimorbidity Patterns over 16 Years in Older Taiwanese People and Their Relationship to Mortality

Understanding multimorbidity patterns is important in finding a common etiology and developing prevention strategies. Our aim was to identify the multimorbidity patterns of Taiwanese people aged over 50 years and to explore their relationship with health outcomes. This longitudinal cohort study used data from the Taiwan Longitudinal Study on Aging. The data were obtained from wave 3, and the multimorbidity patterns in 1996, 1999, 2003, 2007, and 2011 were analyzed separately by latent class analysis (LCA). The association between each disease group and mortality was examined using logistic regression. Four disease patterns were identified in 1996, namely, the cardiometabolic (18.57%), arthritis–cataract (15.61%), relatively healthy (58.92%), and multimorbidity (6.9%) groups. These disease groups remained similar in the following years. After adjusting all the confounders, the cardiometabolic group showed the highest risk for mortality (odds ratio: 1.237, 95% confidence interval: 1.040–1.472). This longitudinal study reveals the trend of multimorbidity among older adults in Taiwan for 16 years. Older adults with a cardiometabolic multimorbidity pattern had a dismal outcome. Thus, healthcare professionals should put more emphasis on the prevention and identification of cardiometabolic multimorbidity.

Factors associated to potentially inappropriate prescribing in older patients according to STOPP/START criteria: MoPIM multicentre cohort study

OBJECTIVES

The objectives of the present analyses are to estimate the frequency of potentially inappropriate prescribing (PIP) at admission according to STOPP/START criteria version 2 in older patients hospitalised due to chronic disease exacerbation as well as to identify risk factors associated to the most frequent active principles as potentially inappropriate medications (PIMs).

METHODS

A multicentre, prospective cohort study including older patients (≥65) hospitalized due to chronic disease exacerbation at the internal medicine or geriatric services of 5 hospitals in Spain between September 2016 and December 2018 was conducted. Demographic and clinical data was collected, and a medication review process using STOPP/START criteria version 2 was performed, considering both PIMs and potential prescribing omissions (PPOs). Primary outcome was defined as the presence of any most frequent principles as PIMs, and secondary outcomes were the frequency of any PIM and PPO. Descriptive and bivariate analyses were conducted on all outcomes and multilevel logistic regression analysis, stratified by participating centre, was performed on the primary outcome.

RESULTS

A total of 740 patients were included (mean age 84.1, 53.2% females), 93.8% of them presenting polypharmacy, with a median of 10 chronic prescriptions. Among all, 603 (81.5%) patients presented at least one PIP, 542 (73.2%) any PIM and 263 (35.5%) any PPO. Drugs prescribed without an evidence-based clinical indication were the most frequent PIM (33.8% of patients); vitamin D supplement in older people who are housebound or experiencing falls or with osteopenia was the most frequent PPO (10.3%). The most frequent active principles as PIMs were proton pump inhibitors (PPIs) and benzodiazepines (BZDs), present in 345 (46.6%) patients. This outcome was found significantly associated with age, polypharmacy and essential tremor in an explanatory model with 71% AUC.

CONCLUSIONS

PIMs at admission are highly prevalent in these patients, especially those involving PPIs or BZDs, which affected almost half of the patients. Therefore, these drugs may be considered as the starting point for medication review and deprescription.

TRIAL REGISTRATION NUMBER

NCT02830425.

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

Background

The 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.

Methods

Electronic 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.

Results

Results 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).

Conclusions

Without 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.

Associations of multiple (≥5) chronic conditions among a nationally representative sample of older United States adults with self-reported pain

OBJECTIVES

The association between an individuals' demographic and health characteristics and the presence of multiple chronic conditions is not well known among older United States (US) adults. This study aimed to identify the prevalence and associations of having multiple chronic conditions among older US adults with self-reported pain.

METHODS

This retrospective, cross-sectional study used data from the 2017 Medical Expenditure Panel Survey. Study subjects were aged ≥50 years and had self-reported pain in the past four weeks. The outcome variable was multiple (≥5) chronic conditions (vs. <5 chronic conditions). Hierarchical logistic regression models were used to identify significant associations between demographic and health characteristics and multiple chronic conditions with significance indicated at an a priori alpha level of 0.05. The complex survey design was accounted for when obtaining nationally-representative estimates.

RESULTS

The weighted population was 57,074,842 US older adults with pain, of which, 66.1% had ≥5 chronic conditions. In fully-adjusted analyses, significant associations of ≥5 comorbid chronic conditions included: age 50-64 vs. ≥65 years (adjusted odds ratio [AOR]=0.478, 95% confidence interval [CI]=0.391, 0.584); male vs. female gender (AOR=1.271, 95% CI=1.063, 1.519); white vs. other race (AOR=1.220, 95% CI=1.016, 1.465); Hispanic vs. non-Hispanic ethnicity (AOR=0.614, 95% CI=0.475, 0.793); employed vs. unemployed (AOR=0.591, 95% CI=0.476, 0.733); functional limitations vs. no functional limitations (AOR=1.862, 95% CI=1.510, 2.298); work limitations vs. no work limitations (AOR=1.588, 95% CI=1.275, 1.976); little/moderate vs. quite a bit/extreme pain (AOR=0.732, 95% CI=0.599, 0.893); and excellent/very good (AOR=0.375, 95% CI=0.294, 0.480) or good (AOR=0.661, 95% CI=0.540, 0.810) vs. fair/poor physical health.

CONCLUSIONS

Approximately 38 million of the 57 million US older adults with pain in this study had ≥5 chronic conditions in 2017. Several characteristics were associated with multiple chronic conditions, which may be important for health care professionals to consider when working with patients to manage their pain. This study was approved by The University of Arizona Institutional Review Board (2006721124, June 12, 2020).