Multimorbidity (MM), the presence of two or more chronic conditions, is increasingly common in clinical practice. Recent studies from India report a prevalence ranging from 28.3% to 45.4% across states at various stages of epidemiologic transition. MM is prevalent across different healthcare settings and income levels, particularly among the elderly. Cardiometabolic multimorbidity (CMM) refers to the coexistence of diabetes, heart disease, and stroke.The presence of multiple chronic conditions complicates MM care as it warrants polypharmacy, which increases the risk of drug interactions, side effects, and financial burden. This often leads to treatment fatigue, especially in elderly patients. Managing MM therefore poses significant challenges for clinicians, caregivers, patients, and health systems. Studies indicate that dyads or triads, such as diabetes and hypertension with heart disease, are the most common forms of CMM.Common pathways to metabolic multimorbidity include obesity, physical inactivity, unhealthy diets, and harmful behaviors like tobacco use and excessive alcohol intake. With this in mind, both pharmacological and non-pharmacological interventions can be used to manage CMM. Research from Canada and China highlights the strong association between socio-behavioral habits and CMM, suggesting that lifestyle changes and cessation programs could benefit CMM management.This Research Topic has three main focuses:1. The epidemiology and patterns of MM and CMM across different income brackets (e.g., LMICs like India and Colombia, MICs like Brazil, HICs like England and Australia), including common dyads and triads and gender differences. It will also examine the role of social determinants of health in MM/CMM.2. The pathophysiology and shared pathways of MM, and the cumulative morbidity measures of various MM dyads and triads.3. Therapeutic aspects of MM and CMM, management challenges, healthcare and economic burdens, continuum-of-care, and the role of digital technologies such as AI and machine learning in diagnosing and treating these conditions.With the epidemiologic transition and an aging population, MM is on the rise, presenting challenges to care at all levels. Intergenerational preventive strategies for primordial and primary prevention are urgently needed. Additionally, a syndromic approach tailored to individuals is crucial, given the common practice of polypharmacy in these patients.We encourage authors to submit papers focusing on, but not limited to:• The relevance, concept, history, and evolution of multimorbidity and cardiometabolic multimorbidity.• Epidemiology of multimorbidity in LMICs and different healthcare settings, including primary and tertiary care.• Common upstream pathways to multimorbidity and cardiometabolic multimorbidity.• Implications of multimorbidity for treating clinicians.• A syndromic approach to therapy for multimorbidity.• Care delivery pathways in multimorbidity and the role of digital technology in improving these pathways.• Social determinants in multimorbidity and cardiometabolic multimorbidity.• The role of artificial intelligence and machine learning in predicting and risk stratifying multimorbidity.• The economics of multimorbidity and the urgent need for preventive measures.
Multimorbidity (MM), the presence of two or more chronic conditions, is increasingly common in clinical practice. Recent studies from India report a prevalence ranging from 28.3% to 45.4% across states at various stages of epidemiologic transition. MM is prevalent across different healthcare settings and income levels, particularly among the elderly. Cardiometabolic multimorbidity (CMM) refers to the coexistence of diabetes, heart disease, and stroke.The presence of multiple chronic conditions complicates MM care as it warrants polypharmacy, which increases the risk of drug interactions, side effects, and financial burden. This often leads to treatment fatigue, especially in elderly patients. Managing MM therefore poses significant challenges for clinicians, caregivers, patients, and health systems. Studies indicate that dyads or triads, such as diabetes and hypertension with heart disease, are the most common forms of CMM.Common pathways to metabolic multimorbidity include obesity, physical inactivity, unhealthy diets, and harmful behaviors like tobacco use and excessive alcohol intake. With this in mind, both pharmacological and non-pharmacological interventions can be used to manage CMM. Research from Canada and China highlights the strong association between socio-behavioral habits and CMM, suggesting that lifestyle changes and cessation programs could benefit CMM management.This Research Topic has three main focuses:1. The epidemiology and patterns of MM and CMM across different income brackets (e.g., LMICs like India and Colombia, MICs like Brazil, HICs like England and Australia), including common dyads and triads and gender differences. It will also examine the role of social determinants of health in MM/CMM.2. The pathophysiology and shared pathways of MM, and the cumulative morbidity measures of various MM dyads and triads.3. Therapeutic aspects of MM and CMM, management challenges, healthcare and economic burdens, continuum-of-care, and the role of digital technologies such as AI and machine learning in diagnosing and treating these conditions.With the epidemiologic transition and an aging population, MM is on the rise, presenting challenges to care at all levels. Intergenerational preventive strategies for primordial and primary prevention are urgently needed. Additionally, a syndromic approach tailored to individuals is crucial, given the common practice of polypharmacy in these patients.We encourage authors to submit papers focusing on, but not limited to:• The relevance, concept, history, and evolution of multimorbidity and cardiometabolic multimorbidity.• Epidemiology of multimorbidity in LMICs and different healthcare settings, including primary and tertiary care.• Common upstream pathways to multimorbidity and cardiometabolic multimorbidity.• Implications of multimorbidity for treating clinicians.• A syndromic approach to therapy for multimorbidity.• Care delivery pathways in multimorbidity and the role of digital technology in improving these pathways.• Social determinants in multimorbidity and cardiometabolic multimorbidity.• The role of artificial intelligence and machine learning in predicting and risk stratifying multimorbidity.• The economics of multimorbidity and the urgent need for preventive measures.