Coexistence Of Multiple Chronic Conditions Research Articles

A Narrative Review on Recombinant Human Bone Morphogenetic Protein 2: Where Are We Now?

Spinal fusion is a prevalent surgical intervention for degenerative spinal diseases, with increasing demand driven by ageing populations. The coexistence of multiple chronic conditions, termed multimorbidity, often complicates surgical outcomes, making advanced bone grafts crucial for successful fusions. This paper reviews the development, clinical application, and controversies surrounding the use of recombinant human bone morphogenetic protein-2 (rhBMP-2) in spinal fusion surgeries. A comprehensive narrative review was conducted, focusing on literature from January 1980 to January 2024, sourced from PubMed and Google Scholar. Studies included those examining rhBMP-2 specifically in spinal fusion contexts, excluding other bone morphogenetic proteins (BMPs) and non-spinal applications. This review presents an overarching synopsis of rhBMP-2, its development history and clinical efficacy, the emergence of side effects, and evolving patterns of clinical use. As discussed in this review, clinical practice has adjusted usage and dosages to mitigate adverse effects, yet the need for safer delivery mechanisms persists. rhBMP-2 remains a potent osteoinductive agent with comparable fusion success, as measured by radiographic fusion and good clinical outcomes, to autologous grafts but poses unique risks. This review sets out how further research is essential to optimise the delivery of rhBMP-2 to reduce side effects. Enhanced understanding and innovation of spatio-temporal presentation relative to endogenous BMP could significantly improve patient outcomes in spinal fusion surgeries. The review contributes to the growing body of literature on the use of rhBMP-2 in spine surgery and discusses changing patterns of clinical use over time.

Prevalence and determinants of multiple chronic conditions (MCC) among young adults in Indian households: an analysis of NFHS-5

BackgroundMultiple chronic conditions (MCC) are defined as the presence of two or more chronic conditions, that significantly impact health status, functional capacity, quality of life, and overall healthcare management. Despite the significant evidence on chronic disease burden, the co-existence of MCC within a household in low- and middle-income countries (LMICs) is less studied. This study therefore estimates the prevalence of MCC and its determinants among adults in the Indian households.MethodsData used in this study were drawn from the fifth round of the National Family Health Survey (NFHS) conducted in 2019–21. Data sets of men (15–54 years) and women (15–49 years) were used for the study. The total sample size of adults for this analysis was N = 239,848. The outcome variable of this study was multiple chronic conditions (MCC) in adults which included a total of nine chronic conditions (hypertension, diabetes, chronic respiratory diseases, chronic kidney disorders, cancer, thyroid disorders, obesity, and heart diseases, consuming alcohol, chewing tobacco, and smoking) documented in NFHS-5. Descriptive statistics and binary logistic regression analysis were used to quantify the results.ResultsA prevalence of 5.5% of MCC in adults emerged from our study. Logistic regression analysis identified that younger age, males (AOR 0.36 (0.33–0.39)), urban areas (AOR 1.11 (1.02–1.17)) as the place of residence, and participants representing SC (AOR 0.89 (0.81–0.97)), and ST (AOR 1.30 (1.17–1.45)), had a higher risk of MCC irrespective of level of education, type of occupation, marital status, or wealth index, and states from any category of social progress.ConclusionA 5% prevalence of MCC specifically obesity, substance use, and hypertension calls for integrated efforts aiming at behavior change, and regulatory efforts to prevent further increase of MCC among young adults in India.

Patterns of multimorbidity in primary care electronic health records: A systematic review.

Multimorbidity, the coexistence of multiple chronic conditions in an individual, is a complex phenomenon that is highly prevalent in primary care settings, particularly in older individuals. This systematic review summarises the current evidence on multimorbidity patterns identified in primary care electronic health record (EHR) data. Three databases were searched from inception to April 2022 to identify studies that derived original multimorbidity patterns from primary care EHR data. The quality of the included studies was assessed using a modified version of the Newcastle-Ottawa Quality Assessment Scale. Sixteen studies were included in this systematic review, none of which was of low quality. Most studies were conducted in Spain, and only one study was conducted outside of Europe. The prevalence of multimorbidity (i.e. two or more conditions) ranged from 14.0% to 93.9%. The most common stratification variable in disease clustering models was sex, followed by age and calendar year. Despite significant heterogeneity in clustering methods and disease classification tools, consistent patterns of multimorbidity emerged. Mental health and cardiovascular patterns were identified in all studies, often in combination with diseases of other organ systems (e.g. neurological, endocrine). These findings emphasise the frequent coexistence of physical and mental health conditions in primary care, and provide useful information for the development of targeted preventive and management strategies. Future research should explore mechanisms underlying multimorbidity patterns, prioritise methodological harmonisation to facilitate the comparability of findings, and promote the use of EHR data globally to enhance our understanding of multimorbidity in more diverse populations.

Integrated care models for older adults with depression and physical multimorbidity: a scoping review

Objective: Multimorbidity, the coexistence of multiple chronic conditions occurring in one person at the same time, where one is not a known complication of the other, is a growing challenge in the care for older people with mental illness. In order to address both physical and mental illnesses in older people, integrated care management is required. The purpose of this scoping review was to provide a comprehensive overview of integrated care models for older adults (60+) with depression and physical multimorbidity. We identified the core components of the examined integrated care models and mapped the reported outcomes and implementation strategies.
 Methods and analysis: We followed the methodology of Arksey and O’Malley’s. MEDLINE, EMBASE, CINAHL and Cochrane Library were searched independently by two reviewers from inception to May 2022. Studies composed in English or Dutch concerning integrated care interventions for older adults with major depression and physical multimorbidity were included. We used the micro-level SELFIE framework to map the core concepts of integrated care models. Outcomes were divided in person-centered and service themes.
 Results: After title and abstract and subsequent full-text screening, 38 studies were included describing 13 different care models. The majority (n=21) were randomized controlled trials, followed by observational studies (n=6), study protocols (n=5), qualitative studies (n=4), and feasibility studies (n=2). Studies were conducted in the North-America (n=28), Europe (n=6), Asia (n=3) and Australia (n=1). In all care models, a multidisciplinary team with a care coordinator was involved. Also treatment interaction, continuity of care, individualized care planning, tailored holistic assessment and self-management support were elements of all care models. Informal care giver involvement and shared decision making were less often described as core elements. Discrepancy was detected in the information systems and technology that different care models used. Only seven care models reported on financial aspects of the intervention, e.g. the reimbursement on participation or the provision of financial incentives.
 A total of 32 different outcomes were evaluated in the primary studies. Patient outcomes, e.g. functional status and depression symptoms, are well described by all care models. In contrast, little attention is paid to service outcomes such as emergency department visits or therapy attendance. Only two studies briefly described the implementation strategies used in the study.
 Conclusion: The core elements that comprise integrated care models are diverse. Future studies should focus more on implementation aspects of the intervention and describe financial parts, e.g. the cost of the intervention for the healthcare user, more transparently.
 Key words: Collaborative care, integrated care, psychosomatic medicine, geriatric psychiatry, care models

Sociodemographic characteristics and longitudinal progression of multimorbidity: A multistate modelling analysis of a large primary care records dataset in England.

Multimorbidity, characterised by the coexistence of multiple chronic conditions in an individual, is a rising public health concern. While much of the existing research has focused on cross-sectional patterns of multimorbidity, there remains a need to better understand the longitudinal accumulation of diseases. This includes examining the associations between important sociodemographic characteristics and the rate of progression of chronic conditions. We utilised electronic primary care records from 13.48 million participants in England, drawn from the Clinical Practice Research Datalink (CPRD Aurum), spanning from 2005 to 2020 with a median follow-up of 4.71 years (IQR: 1.78, 11.28). The study focused on 5 important chronic conditions: cardiovascular disease (CVD), type 2 diabetes (T2D), chronic kidney disease (CKD), heart failure (HF), and mental health (MH) conditions. Key sociodemographic characteristics considered include ethnicity, social and material deprivation, gender, and age. We employed a flexible spline-based parametric multistate model to investigate the associations between these sociodemographic characteristics and the rate of different disease transitions throughout multimorbidity development. Our findings reveal distinct association patterns across different disease transition types. Deprivation, gender, and age generally demonstrated stronger associations with disease diagnosis compared to ethnic group differences. Notably, the impact of these factors tended to attenuate with an increase in the number of preexisting conditions, especially for deprivation, gender, and age. For example, the hazard ratio (HR) (95% CI; p-value) for the association of deprivation with T2D diagnosis (comparing the most deprived quintile to the least deprived) is 1.76 ([1.74, 1.78]; p < 0.001) for those with no preexisting conditions and decreases to 0.95 ([0.75, 1.21]; p = 0.69) with 4 preexisting conditions. Furthermore, the impact of deprivation, gender, and age was typically more pronounced when transitioning from an MH condition. For instance, the HR (95% CI; p-value) for the association of deprivation with T2D diagnosis when transitioning from MH is 2.03 ([1.95, 2.12], p < 0.001), compared to transitions from CVD 1.50 ([1.43, 1.58], p < 0.001), CKD 1.37 ([1.30, 1.44], p < 0.001), and HF 1.55 ([1.34, 1.79], p < 0.001). A primary limitation of our study is that potential diagnostic inaccuracies in primary care records, such as underdiagnosis, overdiagnosis, or ascertainment bias of chronic conditions, could influence our results. Our results indicate that early phases of multimorbidity development could warrant increased attention. The potential importance of earlier detection and intervention of chronic conditions is underscored, particularly for MH conditions and higher-risk populations. These insights may have important implications for the management of multimorbidity.

Application of Machine Learning in Multimorbidity Research: Protocol for a Scoping Review.

Multimorbidity, defined as the coexistence of multiple chronic conditions, poses significant challenges to health care systems on a global scale. It is associated with increased mortality, reduced quality of life, and increased health care costs. The burden of multimorbidity is expected to worsen if no effective intervention is taken. Machine learning has the potential to assist in addressing these challenges since it offers advanced analysis and decision-making capabilities, such as disease prediction, treatment development, and clinical strategies. This paper represents the protocol of a scoping review that aims to identify and explore the current literature concerning the use of machine learning for patients with multimorbidity. More precisely, the objective is to recognize various machine learning models, the patient groups involved, features considered, types of input data, the maturity of the machine learning algorithms, and the outcomes from these machine learning models. The scoping review will be based on the guidelines of the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews). Five databases (PubMed, Embase, IEEE, Web of Science, and Scopus) are chosen to conduct a literature search. Two reviewers will independently screen the titles, abstracts, and full texts of identified studies based on predefined eligibility criteria. Covidence (Veritas Health Innovation Ltd) will be used as a tool for managing and screening papers. Only studies that examine more than 1 chronic disease or individuals with a single chronic condition at risk of developing another will be included in the scoping review. Data from the included studies will be collected using Microsoft Excel (Microsoft Corp). The focus of the data extraction will be on bibliographical information, objectives, study populations, types of input data, types of algorithm, performance, maturity of the algorithms, and outcome. The screening process will be presented in a PRISMA-ScR flow diagram. The findings of the scoping review will be conveyed through a narrative synthesis. Additionally, data extracted from the studies will be presented in more comprehensive formats, such as charts or tables. The results will be presented in a forthcoming scoping review, which will be published in a peer-reviewed journal. To our knowledge, this may be the first scoping review to investigate the use of machine learning in multimorbidity research. The goal of the scoping review is to summarize the field of literature on machine learning in patients with multiple chronic conditions, highlight different approaches, and potentially discover research gaps. The results will offer insights for future research within this field, contributing to developments that can enhance patient outcomes. PRR1-10.2196/53761.

The Association between Multimorbidity and Cognitive Decline: A Systematic Review

AbstractBackgroundThe worldwide population ageing is a major driver for the increasing prevalence of multimorbidity, which is the co‐occurrence/ coexistence of multiple chronic conditions in the same individual. Simultaneously, cognitive decline has become a worldwide burden. Previous research has shown that there might be an association between multimorbidity as a risk for cognitive decline but no systematic review has evaluated this association.ObjectiveTo quantify the association between multimorbidity and cognitive decline through a systematic review, defining cognitive decline as a change in neuropsychological test scores or clinical diagnosis of mild cognitive impairment or dementia.MethodWe followed the PRISMA guidelines. We searched Medline/Pubmed, EMBASE, PsychINFO, CINAHL, LILACS, Scopus and ProQuest for studies published between January 1996 and May 2021. We evaluated study references for additional studies. We selected studies with a clear definition of multimorbidity, and cognitive decline, defined as cognitive impairment, dementia, or change in cognitive test scores. With one exception, all data were from high‐income countries and largely Caucasian populations. We employed the critical appraisal tools from the Joanna Briggs Institute to assess the risk of bias. We present a narrative data synthesis from each study in conjunction with key design information. PROSPERO register (CRD42020167253).ResultWe initially identified 1433 references, of which 16 studies fulfilled inclusion criteria, and were included; we found three additional studies through studies references. These studies encompassed a total of 90606 participants. Thirteen studies were cohorts, four cross‐sectional and two case‐control designs. Ten studies were population registers, five memory clinics cohorts, two population‐based surveys and one from administrative data. We found a high degree of heterogeneity among studies, driven by the use of multiple definitions of multimorbidity and cognitive decline that precluded a meta‐analysis. In general, all studies noticed an increased risk of cognitive decline or diminishing test scores with increasing accumulation of chronic disease. Future research will need to address a standardized definition of multimorbidity and cognitive decline/scores as well as obtain and evaluate data from low‐ and middle‐income countries.ConclusionWe found an association between suffering multimorbidity and increasing risk of cognitive decline measured as cognitive test scores or diagnosis of MCI or dementia.

Culturally Competent Assessment of Neurocognitive Functioning in Latinos with Complex Multimorbidity: A Case Study.

Multimorbidity—the coexistence of multiple chronic conditions within an individual—is the new normal in hospital settings. Individuals with higher levels of multimorbidity require a multidisciplinary and holistic approach to meet their needs, though the complexity of their neurocognitive profiles is still poorly researched. This study reported on the neurocognitive profile of a 69-year-old, left-handed, Latino cisgender male with 10 years of education. He was deemed to have a short-term mortality in 2018, yet is still enjoying a good quality of life in 2022. This case report illustrated (a) a rather common neurocognitive profile of a patient with complex multimorbidity, (b) the advantages of being served in a center of excellence with linguistically and culturally appropriate services that evaluate patients’ cognitive functioning and inform and provide continuity of care, and (c) the benefits of a holistic and multidisciplinary approach to the care of the multimorbidity population.

Factors associated with family caregiver burden among frail older persons with multimorbidity

IntroductionSingapore is facing an ageing population and the care needs of the population will increase in tandem. A segment of this population would be living with multimorbidity and frailty. Frailty is defined as an age-related state characterised by reduced strength and physiologic malfunctioning. Multimorbidity refers to the coexistence of multiple chronic conditions in an individual. Older adults are more likely to have frailty and multimorbidity, and this would increase the burden of their caregiver. Our study aimed to determine the prevalence of caregiver burden for primary family caregivers of frail older adults with multimorbidity. We also investigated the factors that were associated with primary family caregiver burden.MethodsThis was an interviewer-administered, cross-sectional study of primary family caregivers of frail older patients with multimorbidity that was conducted in two National Healthcare Group polyclinics. Convenience sampling was used. The 12-item Zarit Burden Index (ZBI) was used to assess primary family caregiver burden. The scores of the ZBI range from 0 to 48, with a score of 10 or above indicating that the primary family caregiver perceives burden. Descriptive statistics were used to provide information regarding the caregivers and the care recipients. Multivariable logistic regression was used to investigate the factors affecting primary family caregiver burden.ResultsOne hundred eighty-eight family caregivers were interviewed and 71.8% of them perceived burden on the ZBI. 59.6% were caregivers to their parents and 18.1% of them had multimorbidity. Almost two-thirds of the caregivers interviewed were female. After adjusting for other factors via multivariable analysis, the ethnicity of the caregiver and the increase in time spent caregiving per week were the two factors positively associated with family caregiver burden. A Chinese primary family caregiver had almost three times the odds of perceiving burden when compared to a non-Chinese primary family caregiver.ConclusionCaregiver burden was high amongst primary family caregivers of frail older adults with multimorbidity. Being a Chinese primary family caregiver compared to non-Chinese ethnic groups as well as being a primary family caregiver who spent increased time caregiving per week were the two factors positively associated with family caregiver burden. Further exploratory, qualitative studies can be done to find out the reasons to Chinese primary family caregivers being more burdened compared to the non-Chinese primary family caregivers. In addition, the specific factors related to increased time caregiving per week and family caregiver burden can also be studied.

Impact of multimorbidity and frailty on adverse outcomes among older delayed discharge patients: Implications for healthcare policy

ObjectiveTo assess the impacts of multiple chronic conditions (MCC) and frailty on 30-day post-discharge readmission and mortality among older patients with delayed discharge. Data source/extractionWe used a retrospective cohort of older patients in the Discharge Abstract Database (DAD) between 2004 and 2017 in Ontario, Canada. We extracted data on patients aged ≥ 65 who experienced delayed discharge during hospitalization (N = 353,106). Study designWe measured MCC and frailty using the Elixhauser Comorbidity Index (ECI) and the Hospital Frailty Risk Score (HFRS), respectively. We used multinomial logistic regression to model the main and interactive effects of MCC and frailty on the adverse outcomes. Principal findingsAfter adjusting for sex, discharge destination, urban/rural residency, wait time for alternative care, and socioeconomic status, the coexistence of MCC and high frailty increased the relative risk of 30-day mortality and readmission when compared to the references group, i.e., non-MCC patients with low-to-moderate frailty. ConclusionsMultimorbidity and frailty each provide unique information about adverse outcomes among older patients with delayed discharge but are most informative when examined in unison. Implications for health policyTo minimize the risk of adverse outcomes among older delayed discharge patients, discharge planning must be tailored to their concurrent multimorbidity and frailty status.

Prevalence and patterns of multi-morbidity in the productive age group of 30-69 years: A cross-sectional study in Pathanamthitta District, Kerala.

Background: Multi-morbidity is the coexistence of multiple chronic conditions in individuals. With advancing epidemiological and demographic transitions, the burden of multi-morbidity is expected to increase India. Methods: A cross-sectional representative survey was conducted among 410 participants aged 30-69 years in Pathanamthitta District, Kerala to assess the prevalence of multi-morbidity. A multi-stage cluster sampling method was employed to identify households for the survey. We interviewed all eligible participants in the selected households. A structured interview schedule was used to assess socio-demographic variables, behavioral risk factors and prevailing clinical conditions. We used the PHQ-9 questionnaire for depression screening. Further, we conducted active measurements of both blood sugar and blood pressure. Multiple logistic regression was used to identify variables associated with multi-morbidity. Results: Overall, the prevalence of multi-morbidity was 45.4% (95% CI: 40.5-50.3%). Nearly a quarter of the study participants (25.4%) reported only one chronic condition (21.3-29.9%). Further, 30.7% (26.3-35.5), 10.7% (7.9-14.2), 3.7% (2.1-6.0) and 0.2% reported two, three, four and five chronic conditions, respectively. At least one person with multi-morbidity was present in around seven out of ten households (72%, 95% CI: 65-78%). Further, one in five households (22%, 95% CI: 16.7-28.9%) reported more than one person with multi-morbidity. Diabetes and hypertension was the most frequent dyad (30.9%, 95% CI: 26.5-35.7%), followed by hypertension and depression (7.8%, 95% CI: 5.5-10.9%). Diabetes, hypertension and ischemic heart disease was the common triad in males (8.5%, 95% CI: 4.8-14.1%), while it was diabetes, hypertension and depression (6.9%, 95% CI: 4.2-11.1%) in females. Age, sex, and employment status were associated with multi-morbidity. Conclusion: Multi-morbidity is prevalent in one of two participants in the productive age group of 30-69 years. Further, seven of ten households have at least one person with multi-morbidity. The high burden of multi-morbidity calls for integrated management strategies for multiple chronic conditions.

Prevalence and patterns of multi-morbidity in the productive age group of 30-69 years: A cross-sectional study in Pathanamthitta District, Kerala.

Background: Multi-morbidity is the coexistence of multiple chronic conditions in individuals. With advancing epidemiological and demographic transitions, the burden of multi-morbidity is expected to increase India. Methods: A cross-sectional representative survey was conducted among 410 participants aged 30-69 years in Pathanamthitta District, Kerala to assess the prevalence of multi-morbidity. A multi-stage cluster sampling method was employed to identify households for the survey. We interviewed all eligible participants in the selected households. A structured interview schedule was used to assess socio-demographic variables, behavioral risk factors and prevailing clinical conditions. We used the PHQ-9 questionnaire for depression screening. Further, we conducted active measurements of both blood sugar and blood pressure. Multiple logistic regression was used to identify variables associated with multi-morbidity. Results: Overall, the prevalence of multi-morbidity was 45.4% (95% CI: 40.5-50.3%). Nearly a quarter of the study participants (25.4%) reported only one chronic condition (21.3-29.9%). Further, 30.7% (26.3-35.5), 10.7% (7.9-14.2), 3.7% (2.1-6.0) and 0.2% reported two, three, four and five chronic conditions, respectively. At least one person with multi-morbidity was present in around seven out of ten households (72%, 95% CI: 65-78%). Further, one in five households (22%, 95% CI: 16.7-28.9%) reported more than one person with multi-morbidity. Diabetes and hypertension was the most frequent dyad (30.9%, 95% CI: 26.5-35.7%), followed by hypertension and depression (7.8%, 95% CI: 5.5-10.9%). Diabetes, hypertension and ischemic heart disease was the common triad in males (8.5%, 95% CI: 4.8-14.1%), while it was diabetes, hypertension and depression (6.9%, 95% CI: 4.2-11.1%) in females. Age, sex, and employment status were associated with multi-morbidity. Conclusion: Multi-morbidity is prevalent in one of two participants in the productive age group of 30-69 years. Further, seven of ten households have at least one person with multi-morbidity. The high burden of multi-morbidity calls for integrated management strategies for multiple chronic conditions.

Multimorbidity in cardiovascular disease and association with life satisfaction: a Chinese national cross-sectional study

BackgroundThe coexistence of multiple chronic conditions is very common in cardiovascular disease (CVD). However, the prevalence of CVD multimorbidity in China and its influence on life satisfaction have not been...

Video Consultations for Older Adults With Multimorbidity During the COVID-19 Pandemic: Protocol for an Exploratory Qualitative Study.

BackgroundMultimorbidity, the coexistence of multiple chronic conditions in an individual, is a growing public health challenge. Amidst the COVID-19 pandemic, physical distancing remains an indispensable measure to limit the spread of the virus. This pertains especially to those belonging to high-risk groups, namely older adults with multimorbidity. In-person visits are discouraged for this cohort; hence, there is a need for an alternative form of consultation such as video consultations to continue the provision of care.ObjectiveThe potential of video consultations has been explored in several studies. However, the emergence of COVID-19 presents us with an unprecedented opportunity to explore the use of this technological innovation in a time when physical distancing is imperative. This study will evaluate the sustainability of video consultations on a micro-, meso-, and macro-level by assessing the views of patients, physicians, and organizational and national policymakers, respectively.MethodsThe NASSS (nonadoption, abandonment, scale-up, spread, and sustainability) framework was designed as a guide for the development of health care technologies. In this study, the implementation of and experiences related to video consultations will be studied using the NASSS framework. Individual in-depth interviews or focus group discussions will be conducted with participants using the Zoom platform. Data will be analyzed by at least two investigators trained in qualitative methodology, organized thematically, and coded in two phases—an initial phase and a focused selective phase. All disagreements will be resolved by consulting the larger research team until consensus is reached.ResultsThis study was approved for funding from the Geriatric Education and Research Institute. Ethics approval was obtained from the National Healthcare Group Domain Specific Review Board (reference #2020/00760). Study recruitment commenced in July 2020. The results of the data analysis are expected to be available by the end of the year.ConclusionsThis study aims to evaluate the adoption and sustainability of video consultations for older adults with multimorbidity during the pandemic as well as post COVID-19. The study will yield knowledge that will challenge the current paradigm on how care is being delivered for community-dwelling older adults with multimorbidity. Findings will be shared with administrators in the health care sector in order to enhance the safety and quality of these video consultations to improve patient care for this group of population.International Registered Report Identifier (IRRID)DERR1-10.2196/22679

Prevalence and patterns of multi-morbidity in the productive age group of 30-69 years: A cross-sectional study in Pathanamthitta District, Kerala.

Background: Multi-morbidity is the coexistence of multiple chronic conditions in individuals and families. With advancing epidemiological and demographic transitions, the burden of multi-morbidity is expected to increase India. Methods: A cross-sectional representative survey was conducted among 410 participants aged 30-69 years in Pathanamthitta District, Kerala. A multi-stage cluster sampling method was employed to identify households for the survey. We interviewed all eligible participants in the selected households. A structured interview schedule was used to assess socio-demographic variables, behavioral risk factors and prevailing clinical conditions. We used the PHQ-9 questionnaire for depression screening. Further, we conducted active measurements of both blood sugar and blood pressure. Multiple logistic regression was used to identify variables associated with multi-morbidity. Results: Overall, the prevalence of multi-morbidity was 45.4% (95% CI: 40.5-50.3%). Nearly a quarter of the study participants (25.4%) reported only one chronic condition (21.3-29.9%). Further, 30.7% (26.3-35.5), 10.7% (7.9-14.2), 3.7% (2.1-6.0) and 0.2% reported two, three, four and five chronic conditions, respectively. At least one person with multi-morbidity was present in around seven out of ten households (72%, 95% CI: 65-78%). Further, one in five households (22%, 95% CI: 16.7-28.9%) reported more than one person with multi-morbidity. Diabetes and hypertension was the most frequent dyad (30.9%, 95% CI: 26.5-35.7%), followed by hypertension and depression (7.8%, 95% CI: 5.5-10.9%). Diabetes, hypertension and ischemic heart disease was the common triad in males (8.5%, 95% CI: 4.8-14.1%), while it was diabetes, hypertension and depression (6.9%, 95% CI: 4.2-11.1%) in females. Age, sex, and employment status were associated with multi-morbidity. Conclusion: Multi-morbidity is prevalent in one of two participants in the productive age group of 30-69 years. Further, seven of ten households have at least one person with multi-morbidity. The high burden of multi-morbidity calls for integrated preventive and management strategies for multiple chronic conditions.

Transition Experiences of Caregivers of Older Adults With Dementia and Multiple Chronic Conditions: An Interpretive Description Study.

IntroductionFamily caregivers provide most of the care for older persons living with dementia (PLWD) and multiple chronic conditions (MCCs) in the community. Caregivers experience transitions, such as changes to their health, roles, and responsibilities, during the process of caring. Transitions encompass a time when caregivers undergo stressful responses to change. However, we know little about the transition experiences of caregivers of persons living with both dementia and MCCs.ObjectiveThis qualitative study explored the transition experiences of caregivers of PLWD within the context of MCCs, from the perspective of both caregivers and practitioners. The research question was the following: What are the transition experiences of family caregivers in providing care to older PLWD and MCCs living in the community?MethodsThis study was conducted using an interpretive description approach. Semistructured interviews were conducted with 19 caregivers of older community-dwelling PLWD and MCCs and 7 health-care providers working with caregivers in Ontario, Canada. Concurrent data collection and inductive data analysis were used.ResultsCaregivers of older PLWD and MCCs experienced four key transitions: (a) taking on responsibility for managing multiple complex conditions, (b) my health is getting worse, (c) caregiving now defines my social life, and (d) expecting that things will change. Findings highlight how the coexistence of MCCs with dementia complicates caregiver transitions and the importance of social networks for facilitating transitions.ConclusionThe study provided insight on the transition experiences of caregivers of older PLWD and MCCs. MCCs increased the care load and further complicated caregivers’ transition experiences. Health-care providers, such as nurses, can play important roles in supporting caregivers during these transitions and engage them as partners in care.

Multimorbidity Development in Working People.

Multimorbidity is defined as the coexistence of multiple chronic conditions in one person. It affects the way people lead their lives and might be a heavy burden, especially for those with limited material resources. This study explores the prevalence of multimorbidity in the working population and discusses the distribution of multimorbidity in specific sub-groups. We conducted a longitudinal analysis of nationally representative data in South Korea (Korea Health Panel, 2010–2015). Generalized estimation models were applied to examine the individual effect of socioeconomic status (SES) and job-related variables. We found that about five percent of workers who initially had no or one chronic condition developed multimorbidity during within five years. About 20% of working women had multimorbidity at age 55, about 10 years earlier than working men. A higher prevalence appeared in working women with school-age children, non-standard employment, no autonomy at work, or unskilled occupation. SES was significantly associated with a higher prevalence of multimorbidity in both gender after controlling for the effect of age and other covariates. Multimorbidity is a major health concern in the working population and prevention and control should be promoted in the workplace.

Caring for Patients With Multiple Chronic Conditions.

Multimorbidity, the coexistence of multiple chronic conditions, is common among all adults receiving health care and the norm among older adults. The authors discuss the limitations of disease-focu...

An Official American Thoracic Society Workshop Report. A Framework for Addressing Multimorbidity in Clinical Practice Guidelines for Pulmonary Disease, Critical Illness, and Sleep Disorders.

Coexistence of multiple chronic conditions (i.e., multimorbidity) is the most common chronic health problem in adults. However, clinical practice guidelines have primarily focused on patients with a single disease, resulting in uncertainty about the care of patients with multimorbidity. The American Thoracic Society convened a workshop with the goal of establishing a strategy to address multimorbidity within clinical practice guidelines. In this Workshop Report, we describe a framework that addresses multimorbidity in each of the key steps of guideline development: topic selection, panel composition, identifying clinical questions, searching for and synthesizing evidence, rating the quality of that evidence, summarizing benefits and harms, formulating recommendations, and rating the strength of the recommendations. For the consideration of multimorbidity in guidelines to be successful and sustainable, the process must be both feasible and pragmatic. It is likely that this will be achieved best by the step-wise addition and refinement of the various components of the framework.

How do I best manage the care of older patients with cancer with multimorbidity?

The typical older patient with cancer presents with several other chronic conditions. The coexistence of multiple chronic conditions in one patient is best termed multimorbidity, and it affects a growing percentage of the population each year. In cancer care, as in much sub-specialty care, "other diseases" have been approached from a research and clinical standpoint as "comorbidities"--other age-associated diseases that are of secondary importance to cancer care. This is not the same as the newer concept of "multimorbidity", a situation in which several overlapping chronic conditions are managed as equally-important to patient quality of life and outcomes. In the absence of a substantial evidence base or clinical practice guidelines that are tailored for multimorbid patients, clinicians need practical guidance for a rational approach to care for these complex patients. We adapt the American Geriatrics Society's Guiding Principles as an excellent starting point for clinical decision-making and management. These Guiding Principles include: 1) assessing patient preferences, 2) interpreting the available evidence, 3) estimating prognosis, 4) considering treatment feasibility, and 5) optimizing therapies and care plans. We apply them to older patients with cancer. As the population of older adults with cancer and multimorbidity grows, understanding the impact of multimorbidity on the care of patients with cancer and developing a management approach for these vulnerable patients will be vital for oncology care.