Multimorbidity and Its Outcomes Among Patients Attending Psychiatric Care Settings: An Observational Study From Odisha, India

A longitudinal qualitative study on physician experience in managing multimorbidity across the COVID-19 pandemic in Odisha, India

While many studies have documented adverse impact of multiple chronic conditions or multimorbidity on COVID-19 outcomes in patients, there is scarcity of report on how physicians managed these patients. We investigated the experiences and challenges of clinicians in managing patients with multimorbidity throughout the COVID-19 pandemic in Odisha state, India. To understand the factors influencing illness management and the adaptive responses of physicians alongside the evolving pandemic, we followed a longitudinal qualitative study design. Twenty-three physicians comprising general practitioners, specialists, and intensivists, were telephonically interviewed in-depth. Saldana's longitudinal qualitative data analysis method was employed for data analysis. COVID-19 pandemic initially diverted the attention of health systems, resulting in reduced care. With time, the physicians overcame fear, anxiety, and feelings of vulnerability to COVID-19 and started prioritising patients with multimorbidity for treatment and vaccination. All physicians recommended teleconsultation and digital health records to benefit chronic illness care during future public health crises. The findings underscore the transformative potential of physician resilience and adaptation during the COVID-19 pandemic, emphasizing the importance of prioritizing patients with multimorbidity, incorporating teleconsultation, and implementing digital health records in healthcare systems to enhance chronic illness care and preparedness for future public health crises.

Interaction between depressive symptoms and obesity-related anthropometric measures on multimorbidity among community-dwelling older adults: evidence from India

BACKGROUND

This study aimed to examine the associations between depressive symptoms, body mass index (BMI), waist circumference, waist-hip ratio and multimorbidity among community-dwelling older adults. We also examine the interaction effects between depressive symptoms, BMI, waist circumference and waist-hip ratio on multimorbidity among older adults in India.

METHODS

A cross-sectional study was conducted, and the data were obtained from the Longitudinal Ageing Study in India (LASI) wave-1, with a sample of 31,464 older adults aged 60 years and above (men-15,098 and women-16,366). We used multinomial logistic regression to explore the independent associations between depressive symptoms, obesity-measures, and single and multimorbidity. We also estimated the interaction effects of depressive symptoms and obesity-measures on multimorbidity.

RESULTS

The prevalence of multimorbidity was higher among individuals with depressive symptoms (39.22%) than individuals with no depressive symptoms (29.94%). Adjusted models indicated that older adults with depressive symptoms had higher odds of single and multimorbidity [(AOR = 1.40, 95% CI: 1.17-1.68) and (AOR = 1.85, 95% CI: 1.58-2.16), respectively]. Similarly, in comparison to the normal BMI category, overweight and obese older adults were more likely to report single morbidity [(AOR = 1.62, 95% CI: 1.37-1.92 and (AOR = 2.14, 95% CI: 1.67-2.75), respectively] and multimorbidity [(AOR = 2.00, 95% CI: 1.72-2.33) and (AOR = 3.77, 95% CI: 2.94-4.82), respectively].

CONCLUSION

The findings revealed that the presence of depressive symptoms, overweight or obesity, and high-risk anthropometric measures such as high-risk waist circumference and high-risk waist to hip ratio significantly increased the risk of morbidity among older adults in India. Thus, it is suggested to adopt an integrated public health policy approach to control depressive symptoms and high-risk body composition to strategically prepare against the elevated risk of multimorbidity among ageing populations.

The moderating effect of mental health and health insurance ownership on the relationships between physical multimorbidity and healthcare utilisation and catastrophic health expenditure in India

BACKGROUND

The current demographic transition has resulted in the growth of the older population in India, a population group which has a higher chance of being affected by multimorbidity and its subsequent healthcare and economic consequences. However, little attention has been paid to the dual effect of mental health conditions and physical multimorbidity in India. The present study, therefore, aimed to analyse the moderating effects of mental health and health insurance ownership in the association between physical multimorbidity and healthcare utilisation and catastrophic health expenditure (CHE).

METHODS

We analysed the Longitudinal Aging Study in India, wave 1 (2017-2018). We determined physical multimorbidity by assessing the number of physical conditions. We built multivariable logistic regression models to determine the moderating effect of mental health and health insurance ownership in the association between the number of physical conditions and healthcare utilisation and CHE. Wald tests were used to evaluate if the estimated effects differ across groups defined by the moderating variables.

RESULTS

Overall, around one-quarter of adults aged 45 and above had physical multimorbidity, one-third had a mental health condition and 20.5% owned health insurance. Irrespective of having a mental condition and health insurance, physical multimorbidity was associated with increased utilisation of healthcare and CHE. Having an additional mental condition strengthened the adverse effect of physical multimorbidity on increased inpatient service use and experience of CHE. Having health insurance, on the other hand, attenuated the effect of experiencing CHE, indicating a protective effect.

CONCLUSIONS

The coexistence of mental health conditions in people with physical multimorbidity increases the demands of healthcare service utilisation and can lead to CHE. The findings point to the need for multidisciplinary interventions for individuals with physical multimorbidity, ensuring their mental health needs are also addressed. Our results urge enhancing health insurance schemes for individuals with mental and physical multimorbidity.

Epidemiology and impact of chronic disease multimorbidity in India: a systematic review and meta-analysis

Objectives

This is the first systematic review and meta-analysis of the prevalence of multimorbidity, its risk factors including socioeconomic factors, and the consequences of multimorbidity on health systems and broader society in India.

Methods

A systematic review of both published and grey literature from five databases (Medline, Embase, EBSCO, Scopus, and ProQuest) was conducted including original studies documenting prevalence or patient outcomes associated with multimorbidity among adults in India. We excluded studies that did not explicitly mention multimorbidity. Three independent reviewers did primary screening based on titles and abstracts followed by full-text review for potential eligibility. The risk of bias was independently assessed by two reviewers following the Appraisal Tool for Cross-Sectional Studies. We presented both qualitative and quantitative (through meta-analysis) summaries of the evidence. The protocol for this study was prospectively registered with PROSPERO (CRD42021257281).

Results

The review identified 5442 articles out of which 35 articles were finally included in this study. Twenty-three studies were based on the primary data while 12 used secondary data. Eleven studies were conducted in hospital/primary care setting while 24 were community-based. The pooled prevalence of multimorbidity based on (n=19) studies included for meta-analysis was 20% (95% CI: 19% to 20%). The most frequent outcomes were increased healthcare utilization, reduced health-related quality of life, physical and mental functioning.

Conclusion

We identified a wide variance in the magnitude of multimorbidity across age groups and regions with most of the studies from eastern India. Nation-wide studies, studies on vulnerable populations and interventions are warranted.

Making meaning of multimorbidity and severe mental illness: A viewpoint

People living with severe mental illness, such as schizophrenia and bipolar affective disorder, frequently experience poorer physical health compared to those without mental illness. This issue has hitherto been approached through the disease-centred construct of comorbidity, where subsequent conditions are viewed as secondary to an 'index condition'. In contrast, this Viewpoint sets out to explain why multimorbidity, a patient-centred concept that instead refers to the coexistence of multiple chronic illnesses, is a more versatile and robust framework for tackling the issue of poor physical health in people with severe mental illness. In establishing this argument, this Viewpoint has sought to address three key areas. First, this article will discuss the epidemiology of both physical and psychiatric multimorbidity, with respect to how they manifest at greater frequency and at younger ages in people with severe mental illness. Second, the profound consequences of this multimorbidity burden will be explored, with respect to the 'three D's' of death (premature mortality), disability (functional impacts) and deficit (health-economic impacts). Finally, the utility of multimorbidity as a framework will be illustrated through a proposal for a three-dimensional multimorbidity construct composed of (1) quantity, (2) severity and (3) duration of an individual's chronic illnesses. Consequently, this Viewpoint aims to capture why it is necessary for modern psychiatry to grasp the concept of multimorbidity to facilitate holistic healthcare for people living with severe mental illness.

Exploring multimorbidity clusters in relation to healthcare use and its impact on self-rated health among older people in India

The conventional definition of multimorbidity may not address the complex treatment needs resulting from interactions between multiple conditions, impacting self-rated health (SRH). In India, there is limited research on healthcare use and SRH considering diverse disease combinations in individuals with multimorbidity. This study aims to identify multimorbidity clusters related to healthcare use and determine if it improves the self-rated health of individuals in different clusters. This study extracted information from cross-sectional data of the first wave of the Longitudinal Ageing Study in India (LASI), conducted in 2017-18. The study participants were 31,373 people aged ≥ 60 years. A total of nineteen chronic diseases were incorporated to identify the multimorbidity clusters using latent class analysis (LCA) in the study. Multivariable logistic regression was used to examine the association between identified clusters and healthcare use. A propensity score matching (PSM) analysis was utilised to further examine the health benefit (i.e., SRH) of using healthcare in each identified cluster. LCA analysis identified five different multimorbidity clusters: relatively healthy' (68.72%), 'metabolic disorder (16.26%), 'hypertension-gastrointestinal-musculoskeletal' (9.02%), 'hypertension-gastrointestinal' (4.07%), 'complex multimorbidity' (1.92%). Older people belonging to the complex multimorbidity [aOR:7.03, 95% CI: 3.54-13.96] and hypertension-gastrointestinal-musculoskeletal [aOR:3.27, 95% CI: 2.74-3.91] clusters were more likely to use healthcare. Using the nearest neighbor matching method, results from PSM analysis demonstrated that healthcare use was significantly associated with a decline in SRH across all multimorbidity clusters. Findings from this study highlight the importance of understanding multimorbidity clusters and their implications for healthcare utilization and patient well-being. Our findings support the creation of clinical practice guidelines (CPGs) focusing on a patient-centric approach to optimize multimorbidity management in older people. Additionally, finding suggest the urgency of inclusion of counseling and therapies for addressing well-being when treating patients with multimorbidity.

Relationship between severe mental illness and physical multimorbidity: a meta-analysis and call for action

BACKGROUND

People with severe mental illness (SMI) have a higher prevalence of several chronic physical health conditions, and the prevalence of physical multimorbidity is expected to rise. The aim of this study was to assess the strength of the association between SMI and physical multimorbidity.

STUDY SELECTION AND ANALYSIS

We systematically searched PubMed/Medline, Scopus, Embase, Web of Science, PsycINFO and the behavioural sciences collection databases, from inception to 31 January 2023, for studies that investigated the association between SMI and physical multimorbidity. Humans of any age either clinically diagnosed and/or currently receiving treatment for SMI, specified as schizophrenia (and related psychotic disorders), bipolar disorder and psychotic depression, were eligible. Data from studies selected for inclusion were converted into ORs, with a subsequent meta-analysis conducted.

FINDINGS

We included 19 studies with a total of 194 123 patients with SMI with different diagnoses and drawn from the general population. The pooled OR for physical multimorbidity in people with versus without SMI was 1.84 (95% CI 1.33 to 2.54), with the analysis indicating a high level of heterogeneity (98.38%). The other 15 studies included in the systematic review for which it was not possible to conduct a meta-analysis showed strong associations between SMI and physical multimorbidity.

CONCLUSIONS

The current evidence highlights the link between SMI and physical multimorbidity. A multidisciplinary approach is now urgent to develop the best models of services tailored to patients with SMI with physical multimorbidities to improve physical, mental and social outcomes. PROSPERO registration number CRD42023395165.

Managing medical and psychiatric multimorbidity in older patients

Aging increases susceptibility both to psychiatric and medical disorders through a variety of processes ranging from biochemical to pharmacologic to societal. Interactions between aging-related brain changes, emotional and psychological symptoms, and social factors contribute to multimorbidity - the presence of two or more chronic conditions in an individual - which requires a more patient-centered, holistic approach than used in traditional single-disease treatment guidelines. Optimal treatment of older adults with psychiatric and medical multimorbidity necessitates an appreciation and understanding of the links between biological, psychological, and social factors - including trauma and racism - that underlie physical and psychiatric multimorbidity in older adults, all of which are the topic of this review.

Multimorbidity clusters and associated health care cost among patients attending psychiatric clinics in Odisha, India

Introduction

There is a dearth of data on common multimorbidity clusters and the healthcare costs for individuals with mental health disorders. This study aimed to identify clinically meaningful physical-mental multimorbidity clusters, frequently occurring clusters of conditions, and healthcare utilization patterns and expenditure among patients attending a psychiatric outpatient clinic.

Materials and Methods

Data were collected in the psychiatric outpatient department among patients aged 18 years and above in February-July 2019 (n = 500); follow-up data on non-communicable disease incidence were collected after 18 months. For analysis, morbidity clusters were defined using two approaches: 1) agglomerative hierarchical clustering method to identify clusters of diseases; and 2) non-hierarchical cluster k mean analysis to identify clusters of patients. Self-reported healthcare costs in these clusters were also calculated.

Result

Two disease clusters were identified: using the 1st approach were; 1) hypertension, diabetes, and mood disorder; 2) Neurotic, stress-related, and somatoform disorders, and acid peptic disease. Three clusters of patients identified using the 2nd approach were identified: 1) those with mood disorders and cardiometabolic, musculoskeletal, and thyroid diseases; 2) those with neurotic, substance use, and organic mental disorders, cancer, and epilepsy; and 3) those with Schizophrenia. Patients in Cluster 1 were taking more than six medicines and had more hospital visits. Within 18 months, 41 participants developed either one or two chronic conditions, most commonly diabetes, hypertension, or thyroid disease.

Conclusion

Cardiometabolic diseases are most commonly clustered with mood disorders. There is a need for blood pressure and sugar measurement in psychiatric clinics and mood disorder screening in cardiac, endocrinology, and primary care clinics.

Managing dementia care during COVID-19 pandemic: caregivers' experiences in Odisha, India

AIM

The present study explored the family caregivers' perspectives and elicited their experience while managing dementia care during the COVID-19 pandemic in Odisha, India.

BACKGROUND

The onset of the COVID-19 pandemic has diverted the attention of health systems away from chronic disease management and health services delivery. Psychiatric care particularly for dementia and the elderly is found to be more compromised in such situation.

METHODS

We adopted an inductive phenomenological approach to garner key insights into the care continuity for people living with dementia in the context of the COVID-19 pandemic. Telephonic in-depth interviews (IDIs) were carried out with 17 immediate caregivers. All IDIs were digitally recorded, transcribed, and analysed using a thematic approach.

FINDINGS

Caregivers did not perceive dementia as an overwhelming challenge; instead viewed it as a part of the ageing process. Caring for dementia was being done by family members as a collective responsibility with task-sharing. The caregivers primarily relied on their usual physician for the continuity of dementia care and took utmost precautions to prevent exposure to COVID-19 risk. However, they found it more challenging to ensure adequate care for the multiple illnesses (multimorbidity) coexisting with dementia. Towards this, they adopted all possible measures to keep the chronic conditions under control, lest the vulnerability to COVID-19 infection might heighten. The fear of visiting a hospital, prevailing restrictions in mobility, and diverted attention of health systems to pandemic containment created impediments towards maintaining multimorbidity care. The support of local administration, neighbourhood pharmacy and diagnostic laboratories and teleconsultation with the physicians were vital for care continuity. Caregivers adapted by reducing or deferring physical consultation and seeking treatment via telephonic advice of the treating physicians. Our findings suggest leveraging digitally enabled health care technology and augmenting caregiver activation for home-based dementia care to cruise through any similar catastrophic situations.

Patterns of multimorbidity among a community-based cohort in rural India

Background

Multimorbidity estimates are expected to increase in India primarily due to the population aging. However, there is a lack of research estimating the burden of multimorbidity in the Indian context using a validated tool. We estimated the prevalence and determinants of multimorbidity amongst the adult population of the rural Uddanam region, Andhra Pradesh.

Methods

This community-based cross-sectional study was conducted as a part of an ongoing research program. Multistage cluster sampling technique was used to select 2419 adult participants from 40 clusters. Multimorbidity was assessed using Multimorbidity Assessment Questionnaire for Primary Care (MAQ-PC) tool, collecting information on 13 chronic diseases. Patient Health Questionnaire (PHQ-12) was used to screen for depression. Multiple logistic regression was conducted to identify the strongest determinants of multimorbidity.

Results

Of the 2419 participants, 2289 completed the MAQ-PC tool. Mean age (standard deviation) of participants was 48.1 (13.1) years. The overall prevalence of multimorbidity was 58.5% (95% CI 56.5-60.6); with 30.7%, 15.6%, and 12.2% reporting two, three, and four chronic conditions, respectively. Acid peptic disease-musculoskeletal disease (44%) and acid peptic disease-musculoskeletal disease-hypertension (14.9%) were the most common dyad and triad. Among metabolic diseases, diabetes-hypertension (28.3%) and diabetes-hypertension-chronic kidney disease (7.6%) were the most common dyad and triad, respectively. Advancing age, female gender, and being obese were the strongest determinates of the presence of multimorbidity. Depression was highly prevalent among the study population, and participants with higher PHQ-12 score had 3.7 (2.5-5.4) greater odds of having multimorbidity.

Conclusions

Our findings suggest that six of 10 adults in rural India are affected with multimorbidity. We report a higher prevalence of multimorbidity as compared with other studies conducted in India. We also identified vulnerable groups which would guide policy makers in developing holistic care packages for individuals with multimorbidity.

Multimorbidity

Multimorbidity (two or more coexisting conditions in an individual) is a growing global challenge with substantial effects on individuals, carers and society. Multimorbidity occurs a decade earlier in socioeconomically deprived communities and is associated with premature death, poorer function and quality of life and increased health-care utilization. Mechanisms underlying the development of multimorbidity are complex, interrelated and multilevel, but are related to ageing and underlying biological mechanisms and broader determinants of health such as socioeconomic deprivation. Little is known about prevention of multimorbidity, but focusing on psychosocial and behavioural factors, particularly population level interventions and structural changes, is likely to be beneficial. Most clinical practice guidelines and health-care training and delivery focus on single diseases, leading to care that is sometimes inadequate and potentially harmful. Multimorbidity requires person-centred care, prioritizing what matters most to the individual and the individual's carers, ensuring care that is effectively coordinated and minimally disruptive, and aligns with the patient's values. Interventions are likely to be complex and multifaceted. Although an increasing number of studies have examined multimorbidity interventions, there is still limited evidence to support any approach. Greater investment in multimorbidity research and training along with reconfiguration of health care supporting the management of multimorbidity is urgently needed.

Multimorbidity Among Urban Poor in India: Findings From LASI, Wave-1

Background

Multimorbidity has become a norm in low-and middle-income countries such as India requiring notable health system improvements to combat. Urban population is a heterogeneous group where poor are at a risk of facing inequity in accessing healthcare services which can jeopardize our efforts to attain universal health coverage (UHC). We aimed to estimate the prevalence, assess correlates and patterns of multimorbidity among urban poor. Further, we assessed the outcomes of multimorbidity such as healthcare utilization, expenditure and self-rated health.

Methods

Longitudinal Aging Study in India (LASI), wave-1 is a nationally representative survey conducted amongst participants aged ≥45 years in 2017–18. We included 9,327 participants residing in urban areas, categorized as poor based on monthly per capita expenditure. Descriptive statistics computed prevalence with 95% uncertainty interval. Multivariable logistic regression was executed to assess the association between multimorbidity and various correlates, expressed as adjusted odds ratio. An ordinal regression model was run between self-rated health and number of chronic conditions.

Results

The prevalence of multimorbidity was 45.26% among the urban poor. Hypertension and oral morbidities were the most commonly observed dyad. Respondents who were poorer [AOR: 1.27 (1.06–1.51)] had higher chances of having multimorbidity than the poorest. Respondents with a health insurance [AOR: 1.40 (1.14–1.70)] had a higher risk of having multimorbidity. In-patient admission was significantly higher among participants having multimorbidity. Out of pocket expenditure increased while self-rated health deteriorated with each additional morbid condition.

Conclusion

Multimorbidity is found to be increasingly prevalent among urban poor and individuals having health insurance which demonstrates the need to expand healthcare insurance schemes such as Ayushman Bharat for urban poor to achieve UHC.

Emerging multimorbidity patterns and their links with selected health outcomes in a working-age population group

Background

The study aims to identify recurrent multimorbidity pattern among individuals in the age-group 15-64 years. Further, the study examines the association of these identified patterns with sociodemographic variables and selected health outcomes.

Methods

The study utilized data on 2912 individuals in the age-group 15-64 years collected under the burden of diseases study among patients attending public health care settings of Odisha. A latent class analysis was used to identify commonly occurring disease clusters.

Results

The findings suggested that 2.4% of the individuals were multimorbid. Two latent disease clusters were identified, low co-morbidity and Hypertension-Diabetes-Arthritis. Findings highlighted that age, belonging to a non-aboriginal ethnicity and urban area increased the risk of being in the 'Hypertension-Diabetes-Arthritis' group. Furthermore, 50% of the individual in the 'Hypertension-Diabetes-Arthritis' group reported poor quality of life, whereas 30% reported poor self-rated health compared to only 11% by their counterparts. Additionally, the mean health score reported by the individuals in the 'Hypertension-Diabetes-Arthritis' group was 39.9 compared to 46.9 by their counterparts.

Conclusions

The study findings hint towards increasing burden of multimorbidity among the working age population, which depicts a shift in causation of diseases as a result of which preventive measures also need to be taken much prior.

Metabolomics of Multimorbidity: Could It Be the Quo Vadis?

Multimorbidity, the simultaneous presence of two or more chronic diseases, affects the health care to a great extent. Its association with health care cost, more disability, and poor quality of life makes it a major public health risk. The matter of worry is that management of a multimorbid condition is complicated by the fact that multiple types of treatment may be required to treat different diseases at a time, and the interaction between some of the therapies can be detrimental. Understanding the causal factors of simultaneously occurring disease conditions and investigating the connected pathways involved in the whole process may resolve the complication. When different disease conditions present in an individual share common responsible factors, treatment strategies targeting at those common causes will certainly reduce the chance of development of multimorbidity occurring because of those factors. Metabolomics that can dig out the underlying metabolites/molecules of a medical condition is believed to be an effective technique for identification of biomarkers and intervention of effective treatment strategies for multiple diseases. We hypothesize that understanding the metabolic profile may shed light on targeting the common culprit for different/similar chronic diseases ultimately making the treatment strategy more effective with a combinatorial effect.

Exploring the Linkages Between Non-Communicable Disease Multimorbidity, Health Care Utilization and Expenditure Among Aboriginal Older Adult Population in India

Objective: The study investigates the magnitude and correlates of non-communicable disease multimorbidity and explores its linkages with health care utilization and out-of-pocket expenditure among aboriginal or tribal older adults.

Methods: The study employed data on 11,365 older adults from Scheduled Tribes from the Longitudinal Ageing Study in India, 2017-18. A disease score was computed integrating sixteen non-communicable diseases. Descriptive, bivariate, and multivariable analyses were performed to identify the magnitude and correlates of multimorbidity. The study further explored the linkages between selected diseases and multimorbidity with health care utilization and expenditure.

Results: The findings suggest that 27.1 and 14.5% of the aboriginal population lived with single or multiple disease, respectively. Hypertension and gastrointestinal disorders were frequent diseases. Higher age, Muslim religion, higher education, unemployment, and affluent background were the major correlates of multimorbidity. Health care utilization, mean expenditure on hospitalization, and outpatient visits increased significantly with multimorbidity.

Conclusion: Multimorbidity is emerging as a health care challenge among the aboriginal population. Measures need to be taken to assess the multimorbidity burden and reduce health care expenditure, ensuring health equity among country’s vulnerable population.

Patterns and predictors of non-communicable disease multimorbidity among older adults in India: evidence from longitudinal ageing study in India (LASI), 2017-2018

Escalating non-communicable disease multimorbidity rates among older adults is an emerging public health concern in India, but the literature sparsely addresses the epidemiology of multimorbidity. We explore levels, patterns, combinations and predictors of multimorbidity among older adults using information on 59,764 individuals, aged 45 years and older, from the first wave of Longitudinal Ageing Study in India (LASI), 2017-2018. We computed multimorbidity score for sixteen non-communicable diseases to identify frequently occurring morbidity patterns (dyads and triads) and assess the relationship between multimorbidity and selected background characteristics. Near third of the older adult population is affected by multimorbidity, with hypertension, gastrointestinal disorders, musculoskeletal disorders, diabetes and skin diseases being the most common. Policymakers should seek strategies to increase early detection and prevention of chronic diseases, delay the age at onset of disease for those who are not affected and improve management for those affected with multiple disease conditions.

Profile of multimorbidity in outpatients attending public healthcare settings: A descriptive cross-sectional study from Odisha, India

Background

Multimorbidity, the co-occurrence of two or more long-term conditions (LTC) in individuals, is associated with greater healthcare utilization, expenditure, and premature mortality, thus positing a challenge for patients and healthcare providers. Given its sparsely available epidemiological evidence, we aimed to describe the profile of multimorbidity in a representative sample of public healthcare outpatients in India.

Methods

A facility-based cross-sectional study was conducted from 1^st July to 31^st December 2015 in Odisha, India. Fifteen public healthcare facilities were selected by stratified random sampling. Data was collected from 1,870 adult outpatients attending these settings using Multimorbidity Assessment Questionnaire for Primary Care (MAQ-PC) tool.

Result

Nearly 3/4^th of both women and men outpatients were either obese or overweight. >1/2 had multimorbidity (≥2 LTC) while 1/3^rd had ≥3 LTC. Most prevalent condition was hypertension (63%), followed by chronic backache and arthritis. Cancer and psychiatric illness were least reported. Multimorbidity increased with age group, socioeconomic status, and education level. Females across all age groups had higher reported multimorbidity than males. Diabetes--hypertension was frequently occurring dyad. Both physical and mental component of quality of life was reduced in multimorbidity.

Conclusion

Multimorbidity is becoming a norm in healthcare practice with high prevalence in females and older adults. Health services for non-communicable diseases need to include commonly occurring dyads along with health promotion. Higher prevalence in females reinforces the need to incorporate gender differences while studying multimorbidity. Analysis of multimorbidity epidemiology through an equity lens could illuminate the underpinning complexities and heterogeneities of this phenomenon.

Do Community Free-Medication Service Policy Improve Patient Medication Adherence? A Cross-Sectional Study of Patients With Severe Mental Disorders in Beijing Community

Background: Nowadays, mental health problems have become a major concern affecting economic and social development, with severe mental health disorders being the top priority. In 2013, Beijing began to implement the Community Free-Medication Service policy (CFMS). This article aims to evaluate the effect of the policy on medication adherence.

Methods: In this study, multi-stage sampling was used to select representative patients as samples. Some of the baseline data were obtained by consulting the archives, and information about patient medication adherence measured by Brooks Medication Adherence Scale was obtained through face-to-face interviews. Logistic regression was used to examine the impact of the policy.

Results: Policy participation had a significant positive impact on medication adherence (OR = 1.557). The effect of policy participation on medication adherence in the Medication-only mode and Subsidy-only mode were highly significant, but it was not significant in the Mixed mode.

Conclusion: This study found that the CFMS in Beijing as an intervention is effective in improving the medication adherence of community patients. However, the impact of the policy is not consistent among service modes. Reinforcement magnitude and frequency should be considered when designing reinforcement interventions.

Managing Multimorbidity (Multiple Chronic Diseases) Amid COVID-19 Pandemic: A Community Based Study From Odisha, India

While most of the studies to date demonstrate the deleterious effect of multiple chronic diseases on COVID-19 risk and outcome, there is sparse information available on the effect of the pandemic on multimorbidity management, with no reports yet from India. We sought to explore the effect of COVID-19 pandemic on routine and emergency care for multimorbidity among community-dwelling adults in Odisha, India. A community-based cross-sectional study was undertaken pandemic lockdown, in Khurda district of Odisha, India. Around 600 individuals having at least one chronic disease residing in rural, urban residential and slums were interviewed using a specifically developed questionnaire MAQ COVID-19. The association of socio-demographic characteristics and multimorbidity with pandemic-related care challenges was examined by multiple logistic regression. Principal Component Analysis was employed to minimize the dimensionality of factors related to multimorbidity care. Multimorbidity was highly prevalent in younger age group (46-60 years) with cardio-metabolic clusters being dominant. Individuals with multimorbidity experienced significantly higher care challenges than those with single condition (AOR = 1.48, 95% CI = 1.01-2.05) with notable disruption in treatment and routine check-up. Most frequently cited concerns were-physician consultation (43%), diagnostic-services (26%), transport (33%), and mobility restrictions (21%). Multivariate analysis revealed older adults living alone in urban residence to have higher challenges than their rural counterparts. Patient activation for self-care, multimorbidity literacy, and technology-enabled tele-consultation could be explored as potential interventions. Future studies should qualitatively explore the challenges of physicians as well as garner an in-depth understanding of multimorbidity management in the vulnerable subgroups.

Temporal dynamics, patterns and correlates of single and multimorbidity in India, 1994-2018

OBJECTIVE

As a consequence of the epidemiological transition, multimorbidity has been identified as a critical public health challenge in India. The majority of the studies in the domain are grounded on hospital-based data or are based on small sample size, findings from which can only be generalized to a specific sub-group. These studies recommend exploring multimorbidity holistically at a national level to ensure adequate healthcare management in the country. Therefore, the present study examines the pattern and correlates of single and multimorbidity over the past two decades in India.

METHODS

The study utilized data on 397901, 257519, and 399705 individuals from 52nd (1994-1995), 60th (2004-2005), and 75th (2018) rounds of cross-sectional data from the National Sample Survey (NSS). Univariate, bivariate, and multivariable statistical methods were applied to draw inferences from the data. The findings depict an increase in single and multimorbidity burden over individuals' age and NSS rounds.

RESULTS

Hypertension and diabetes were the fastest-growing morbidities over time. Higher education, urban residence, and belonging to an affluent class were significantly associated with both single and multimorbidity occurrence over time.

CONCLUSION

The burden of single and multimorbidity increases over time among India's older adults. Therefore, there is an urgent need to recuperate chronic disease management strategies for older adults in the Indian healthcare infrastructure.