Multilevel Analysis of the Patterns of Physical-Mental Multimorbidity in General Population of São Paulo Metropolitan Area, Brazil

Regular source of primary care and health services utilisation among Brazilian elderly with mental-physical multimorbidity

BACKGROUND

In ageing populations, multimorbidity is a complex challenge to health systems, especially when the individuals have both mental and physical morbidities. Although a regular source of primary care (RSPC) is associated with better health outcomes, its relation with health service utilisation in elderly patients with mental-physical multimorbidity (MP-MM) is scarce.

OBJECTIVE

This study explored the relations among health service utilisation, presence of RSPC and MP-MM among elderly Brazilians.

METHODS

A national cross-sectional study performed with data from national representative samples from the Brazilian National Health Research (PNS, in Portuguese; Pesquisa Nacional de Saúde) carried out in 2013 with 11,177 elderly Brazilian people. MP-MM was defined as the presence of two or more morbidities, including at least one mental morbidity, and was evaluated using a list of 16 physical and mental morbidities. The RSPC was analysed by the presence of regular font of care in primary care and health service utilisation according to the demand for health services ≤ 15 days, medical consultation ≤ 12 months, and hospitalisation ≤ 1 year. Frequency description of variables and bivariate association were performed using Stata v.15.2 software.

RESULTS

The majority of individuals was female (56.4%), and their mean age was 69.8 years. The observed prevalence of MP-MM was 12.2%. Individuals with MP-MM had higher utilisation of health services when compared to those without MP-MM. RSPC was present at 36.5% and was higher in women (37.8% vs. 34.9%). There was a lower occurrence of hospitalisation ≤ 1 year among MP-MM individuals with RSPC and without a private plan of health.

CONCLUSION

Our findings demonstrate that RSPC can be an important component of care in elderly individuals with MP-MM because it was associated with lower occurrence of hospitalisation, mainly in those that have not a private plan of health. Longitudinal studies are necessary to confirm these findings.

A scoping review finds a growing trend in studies validating multimorbidity patterns and identifies five broad types of validation methods

OBJECTIVES

Multimorbidity, the presence of two or more long-term conditions, is a growing public health concern. Many studies use analytical methods to discover multimorbidity patterns from data. We aimed to review approaches used in published literature to validate these patterns.

STUDY DESIGN AND SETTING

We systematically searched PubMed and Web of Science for studies published between July 2017 and July 2023 that used analytical methods to discover multimorbidity patterns.

RESULTS

Out of 31,617 studies returned by the searches, 172 were included. Of these, 111 studies (64%) conducted validation, the number of studies with validation increased from 53.13% (17 out of 32 studies) to 71.25% (57 out of 80 studies) in 2017-2019 to 2022-2023, respectively. Five types of validation were identified: assessing the association of multimorbidity patterns with clinical outcomes (n = 79), stability across subsamples (n = 26), clinical plausibility (n = 22), stability across methods (n = 7) and exploring common determinants (n = 2). Some studies used multiple types of validation.

CONCLUSION

The number of studies conducting a validation of multimorbidity patterns is clearly increasing. The most popular validation approach is assessing the association of multimorbidity patterns with clinical outcomes. Methodological guidance on the validation of multimorbidity patterns is needed.

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.

Discovery and classification of complex multimorbidity patterns: unravelling chronicity networks and their social profiles

Multimorbidity can be defined as the presence of two or more chronic diseases in an individual. This condition is associated with reduced quality of life, increased disability, greater functional impairment, increased health care utilisation, greater fragmentation of care and complexity of treatment, and increased mortality. Thus, understanding its epidemiology and inherent complexity is essential to improve the quality of life of patients and to reduce the costs associated with multi-pathology. In this paper, using data from the European Health Survey, we explore the application of Mixed Graphical Models and its combination with social network analysis techniques for the discovery and classification of complex multimorbidity patterns. The results obtained show the usefulness and versatility of this approach for the study of multimorbidity based on the use of graphs, which offer the researcher a holistic view of the relational structure of data with variables of different types and high dimensionality.

Patterns of multimorbidity and some psychiatric disorders: A systematic review of the literature

Objective

The presence of two or more chronic diseases results in worse clinical outcomes than expected by a simple combination of diseases. This synergistic effect is expected to be higher when combined with some conditions, depending on the number and severity of diseases. Multimorbidity is a relatively new term, with the first fundamental definitions appearing in 2015. Studies usually define it as the presence of at least two chronic medical illnesses. However, little is known regarding the relationship between mental disorders and other non-psychiatric chronic diseases. This review aims at investigating the association between some mental disorders and non-psychiatric diseases, and their pattern of association.

Methods

We performed a systematic approach to selecting papers that studied relationships between chronic conditions that included one mental disorder from 2015 to 2021. These were processed using Covidence, including quality assessment.

Results

This resulted in the inclusion of 26 papers in this study. It was found that there are strong associations between depression, psychosis, and multimorbidity, but recent studies that evaluated patterns of association of diseases (usually using clustering methods) had heterogeneous results. Quality assessment of the papers generally revealed low quality among the included studies.

Conclusions

There is evidence of an association between depressive disorders, anxiety disorders, and psychosis with multimorbidity. Studies that tried to examine the patterns of association between diseases did not find stable results.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021216101, identifier: CRD42021216101.

Cohort profile: Bandar Kong prospective study of chronic non-communicable diseases

Chronic non-communicable diseases (NCDs), are the leading causes of death among adults worldwide. It is projected that half of the NCDs could be avoided by preventing measures. Under the prospective epidemiological research studies in Iran (PERSIAN), we established a prospective population-based cohort study in southern Iran. The present study was designed to observe changing pattern of lifestyle transition over time and investigate the incidence and prevalence of regional modifiable risk factors as well as their associations with major NCDs. At baseline, 4063 participants aged 35-70 years were recruited on Oct, 2016and planned to get re-evaluated every 5 years along with annual follow-up. Data using validated electronic questionnaire comprising 55 questions and 482 items including general, medical and nutrition queries was collected. Blood, hair, nails, urine specimens and anthropometric measurements were taken. The response rate was 99%. In the results; male and female participants were 42.5% and 57.5%, respectively. Of note, 30.4% of women and 16.1% of men were obese. The prevalence of hypertension in men and women was 14.6% and 21%; however, diabetic men and women were 17.4% and 12.4%, respectively. Living in rural areas increased the odds of having hypertension by 1.33 (AOR = 1.33, 95% CI:1-09, 1.61). Noteworthy, logistic regression displayed that aging could predispose individuals to be more overweight, hypertensive and diabetic. The prevalence of multimorbidity of 3 or more NCDs were 8% (No. 326) and 6% (No.240), respectively. Intake of fruits, vegetables and dairy was less than two servings per day in 9.2%, 13% and 58.3% of the participants. Lower cardiovascular diseases and serum level of FBS and higher HDL level in sailors/fishermen compared to other job groups were significant (p-value <0.001). The second annual follow-up was completed and now at the end of the third wave. Findings of the present study signified the high prevalence of behavioral risk factors and their associations with respective NCDs. Subsequently, it is essential to keep track lifestyle variations, the modifiable risk factors and NCDs trends by prospective population-based cohort studies.

Longitudinal patterns of comorbidity between anxiety, depression and binge eating symptoms among patients with obesity: A path analysis

BACKGROUND

Depression, anxiety, and binge eating are common psychiatric symptoms among people with obesity. Although many studies seek to understand the mechanisms of association between these psychiatric symptoms, there is no still consensus about the longitudinal association.

METHODS

155 patients (124 women) were recruited from a university-based bariatric center and evaluated over three waves (T0-T1-T2). In the last period the sample comprised 126 (104 women) participants. Trained clinicians assessed psychiatric symptoms by telephone interview using measurement scales. Partial Least Squares (PLS) was applied to investigate the path effects between anxiety, depression and binge eating symptoms over time.

RESULTS

The results of path coefficients (β) showed that the effect of anxiety on depression was constantly significant in all periods T0 (β = 0.74), T1 (β = 0.71), and T2 (β = 0.67). Anxiety had an effect on binge eating in T0 (β = 0.39) and T2 (β = 0.26) but not in T1. Binge eating affected depressive symptoms only in T2 (β = 0.22). Two carry-over-effects were significant binge eating in T0-T1 (β = 0.41) and T1-T2 (β = 0.19).

LIMITATIONS

Telephone interviews, social isolation due to the pandemic and the social desirability may have contributed to collection and information biases.

CONCLUSION

Anxiety has significant path effects on depression and binge eating. Binge eating was shown to be the most unstable symptom over time. The time factor seems to contribute to path effects between the psychiatric symptoms. The results draw attention to the fact that psychiatric symptoms must be evaluated and treated in association with each other, and investigated over time.

The moderating effects of social support and depressive symptoms on pain among elderly multimorbid patients-data from the multicentre, prospective, observational cohort study MultiCare

OBJECTIVES

Depressive symptoms and chronic pain are common among patients with multimorbidity creating a complex medical condition for both the patient and the general practitioner. Perceived social support may function as a protective measure.

To examine the impact of perceived social support as a potential moderator between depressive symptoms and pain intensity and pain disability in daily activities in multimorbid patients aged 75+.

METHOD

Data from 3,189 patients of the German longitudinal cohort study MultiCare were obtained at baseline and follow-ups during 5 years. Multilevel linear mixed-effects analyses were conducted for pain intensity (model 1) and pain disability in daily activities (model 2). The interaction term social support by depression score was included to test for moderation.

RESULTS

The interaction between social support and depressive symptoms was significantly associated with the pain intensity score 0.41 (SE=.17; 95-CI[.08;.74]) but not with the pain disability score 0.35 (SE=.19; 95-CI[-.01;.72]). Additionally, men and individuals with medium or higher educational level showed reduced pain intensity and disability scores. Pain disability scores increased with age and depressive symptoms. Increased pain scores were also found for body mass index and burden of multimorbidity.

CONCLUSION

Perceived social support amplified the association of depressive symptoms on pain intensity and did not show a protective function. The high scores of perceived social support among the participants may point to the practice of secondary gain due to the patients immense health burden.

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.

Comorbidities in dementia during the last years of life: a register study of patterns and time differences in Finland

BACKGROUND

Comorbidities have major implications for the care of people with dementia.

AIM

To investigate the patterns of comorbidities in dementia in the last five years of life and how these patterns differed between three cohorts.

METHODS

The study included people who died at age 70 and above in 2001 (n = 13,717), 2007 (n = 34,750) and 2013 (n = 38,087) in Finland. ICD-10 morbidity data for a five-year period prior to death were extracted from national registers. Principal component analysis was employed to identify patterns for several morbidities. The associations of principal component scores with dementia were analysed using binary logistic regression. Linear regression was used to examine changes in the number of morbidities in patterns over time.

RESULTS

The morbidity patterns identified in the last years of life were (1) cardiometabolic disorders, (2) neurological, (3) cerebrovascular diseases and (4) musculoskeletal, thyroid and psychiatric disorders. Among the patterns, neurological and musculoskeletal, thyroid and psychiatric disorders were associated with dementia. The number of diagnoses in the cerebrovascular pattern increased and those in the musculoskeletal, thyroid and psychiatric pattern decreased over time.

DISCUSSION

Comorbidity patterns identified in this nationwide register study are largely in line with previous evidence. Time difference in these patterns provide crucial information for service planning.

CONCLUSIONS

Comorbidities in dementia in the last years of life occur in patterns and change over time. More systematic monitoring and updated clinical guidelines are needed for the care of comorbidities with dementia.

Multimorbidity in Latin America and the Caribbean: a systematic review and meta-analysis

OBJECTIVE

To estimate the pooled prevalence of multimorbidity (≥2 non-communicable diseases in the same individual) among adults of the general population of Latin American and the Caribbean (LAC).

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

MEDLINE, Embase, Global Health, Scopus and LILACS up to 1 July 2020.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

The outcome was the prevalence of multimorbidity. Reports were selected whether they enrolled adult individuals (age ≥18 years) from the general population.

DATA EXTRACTION AND SYNTHESIS

Reviewers extracted relevant data and assessed risk of bias independently. A random-effects meta-analysis was conducted to report pooled prevalence estimates of multimorbidity; pooled estimates by pre-specified subgroups (eg, national studies) were also pursued.

RESULTS

From 5830 results, we selected 28 reports, mostly from Brazil and 16 were based on a nationally representative sample. From the 28 selected reports, 26 were further included in the meta-analysis revealing a pooled multimorbidity prevalence of 43% (95% CI: 35% to 51%; I²: 99.9%). When only reports with a nationally representative sample were combined, the pooled prevalence was 37% (95% CI: 27% to 47%; I²: 99.9%). When the ascertainment of multimorbidity was based on self-reports alone, the pooled prevalence was 40% (95% CI: 31% to 48%; I²: 99.9%); this raised to 52% (95% CI: 33% to 70%; I²: 99.9%) for reports including self-reported and objective diagnosis.

CONCLUSIONS

Our results complement and advance those from global efforts by incorporating much more reports from LAC. We revealed a larger presence of multimorbidity in LAC than previously reported.

PROSPERO REGISTRATION NUMBER

CRD42020196177.

"I don't need any treatment" - barriers to mental health treatment in the general population of a megacity

Objective:

Most countries fail to treat individuals with psychopathologies. Investigating treatment barriers and reasons for dropout are key elements to overcoming this scenario.

Methods:

A representative sample of 2,942 urban-dwelling adults was interviewed face-to-face within a cross-sectional, stratified, multistage probability survey of the general population. Psychiatric diagnosis, severity level, use of services, reasons for not seeking treatment, and treatment dropout were investigated.

Results:

Only 23% of individuals with a psychopathology of any severity level in the last 12 months received treatment. Low perceived need for treatment (56%) was the most common reason for not seeking treatment. The most visited settings were psychiatric, other mental health care, and general medical care. Among those with a perceived need for treatment (44%), psychological barriers were the most common reason for not seeking it. Treatment dropout was more prevalent among those who visited a general medical care setting. Among individuals still in treatment, human services and psychiatric care were the most common types. Female sex was associated with structural barriers (OR = 2.1). Disorder severity was negatively associated with need barriers (OR = 0.4), and positively associated with structural barriers (OR = 2.5) and psychological barriers (OR = 2.5).

Conclusion:

Despite the need for treatment and better services, psychological barriers were the major reason for not seeking treatment. Apart from providing more specialists, investing in awareness, de-stigmatization, and information is the ultimate strategy for improving psychiatric care.

Does socioeconomic inequality occur in the multimorbidity among Brazilian adults?

OBJECTIVE

To assess the prevalence of multimorbidity among Brazilian adults and its association with socioeconomic indicators.

METHODS

Cross-sectional study that used data from the Pesquisa Nacional Sobre Acesso, Utilização e Promoção do Uso Racional de Medicamentos no Brasil (PNAUM - Brazilian National Survey on Access, Use and Promotion of Rational Use of Medicines), carried out between 2013 and 2014. The definition of multimorbidity was the coexistence, in a single individual, of two or more chronic diseases, measured through a list of 14 morbidities (self-reported medical diagnosis throughout life). Economic status and educational level were the socioeconomic indicators used, being the inequalities assessed through the Slope Index of Inequality (SII) and the Concentration Index, stratified by gender.

RESULTS

The study comprehended 23,329 adults (52.8% of which were women), with an average age of 37.9 years. Hypertension and high cholesterol levels were the most prevalent conditions. The prevalence of multimorbidity was of 10.9% (95%CI 10.1-11.7) representing nearly 11 million individuals in Brazil, of which 14.5% (95%CI 13.5-15.4) were women and 6.8% (95%CI 5.9-7.8) were men. The occurrence of multimorbidity was similar according to the socioeconomic indicators. In the inequality analysis, we observed absolute and relative differences in men with a higher purchasing power (SII = 3.7; 95%CI 0.3-7.0) and higher educational level (CIX = 7.1; 95%CI 0.9-14.7), respectively.

CONCLUSIONS

The frequency of comorbidities in Brazilian adults is high, especially in absolute terms. We only observed socioeconomic inequalities in multimorbidities among men.

Assessing the Quality of Life Among Productive Age in the General Population: A Cross-Sectional Study of Family Life Survey in Indonesia

A large number of productive age populations in Indonesia are tagged reliable human resources, assuming they have a good quality of life (QoL). This study aims to examine the determinant factors related to QoL based on the 2014 Indonesia Family Life Survey. This is a population-based cross-sectional study comprising 13 368 participants aged 15 to 64 years from 23 provinces. The analysis was carried out to construct a composite indicator of QoL. The result showed that the low prevalence of 54% among the general population needs to be ameliorated. Demographic factors (e.g. age, marital status, and education), primary activities, pain, and chronic illnesses were significantly related to QoL and used to provide supporting information.

Untangling the complexity of multimorbidity with machine learning

The prevalence of multimorbidity has been increasing in recent years, posing a major burden for health care delivery and service. Understanding its determinants and impact is proving to be a challenge yet it offers new opportunities for research to go beyond the study of diseases in isolation. In this paper, we review how the field of machine learning provides many tools for addressing research challenges in multimorbidity. We highlight recent advances in promising methods such as matrix factorisation, deep learning, and topological data analysis and how these can take multimorbidity research beyond cross-sectional, expert-driven or confirmatory approaches to gain a better understanding of evolving patterns of multimorbidity. We discuss the challenges and opportunities of machine learning to identify likely causal links between previously poorly understood disease associations while giving an estimate of the uncertainty on such associations. We finally summarise some of the challenges for wider clinical adoption of machine learning research tools and propose some solutions.

The patterns of Non-communicable disease Multimorbidity in Iran: A Multilevel Analysis

The prevalence of non-communicable diseases is increasing worldwide. Multimorbidity and long-term medical conditions is common among these patients. This study aimed to investigate the patterns of non-communicable disease multimorbidity and their risk factors at the individual and aggregated level. Data was inquired from the nationwide survey performed in 2011, according to the WHO stepwise approach on NCD risk factors. A latent class analysis on multimorbidity components (11 chronic diseases) was performed and the association of some individual and aggregated risk factors (urbanization) with the latent subclasses was accessed using multilevel multinomial logistic regression. Latent class analysis revealed four distinct subclasses of multimorbidity among the Iranian population (10069 participants). Musculoskeletal diseases and asthma classes were seen in both genders. In males, the odds of membership in the diabetes class was 41% less by increasing physical activity; but with increased BMI, the odds of membership in the diabetes class was 1.90 times higher. Tobacco smoking increased the odds of membership in the musculoskeletal diseases class, 1.37 and 2.30 times for males and females, respectively. Increased BMI and low education increased the chances of females' membership in all subclasses of multimorbidity. At the province level, with increase in urbanization, the odds of membership in the diabetes class was 1.28 times higher among males (P = 0.027). Increased age, higher BMI, tobacco smoking and low education are the most important risk factors associated with NCD multimorbidity among Iranians. Interventions and policies should be implemented to control these risk factors.

Multimorbidity of chronic non-communicable diseases in low- and middle-income countries: A scoping review

BACKGROUND

Multimorbidity is rising in low- and middle-income countries (LMICs). However, the evidence on its epidemiology from LMICs settings is limited and the available literature has not been synthesized as yet.

OBJECTIVES

To review the available evidence on the epidemiology of multimorbidity in LMICs.

METHODS

PubMed, Scopus, PsycINFO and Grey literature databases were searched. We followed the PRISMA-ScR reporting guideline.

RESULTS

Of 33, 110 articles retrieved, 76 studies were eligible for the epidemiology of multimorbidity. Of these 76 studies, 66 (86.8%) were individual country studies. Fifty-two (78.8%) of which were confined to only six middle-income countries: Brazil, China, South Africa, India, Mexico and Iran. The majority (n = 68, 89.5%) of the studies were crosssectional in nature. The sample size varied from 103 to 242, 952. The largest proportion (n = 33, 43.4%) of the studies enrolled adults. Marked variations existed in defining and measuring multimorbidity. The prevalence of multimorbidity in LMICs ranged from 3.2% to 90.5%.

CONCLUSION AND RECOMMENDATIONS

Studies on the epidemiology of multimorbidity in LMICs are limited and the available ones are concentrated in few countries. Despite variations in measurement and definition, studies consistently reported high prevalence of multimorbidity. Further research is urgently required to better understand the epidemiology of multimorbidity and define the best possible interventions to improve outcomes of patients with multimorbidity in LMICs.