'Multimorbidity' as the manifestation of network disturbances

Racial inequalities in the development of multimorbidity of chronic conditions: results from a Brazilian prospective cohort

BACKGROUND

The occurrence of multimorbidity and its impacts have differentially affected population subgroups. Evidence on its incidence has mainly come from high-income regions, with limited exploration of racial disparities. This study investigated the association between racial groups and the development of multimorbidity and chronic conditions in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil).

METHODS

Data from self-reported white, brown (pardos or mixed-race), and black participants at baseline of ELSA-Brasil (2008-2010) who were at risk for multimorbidity were analysed. The development of chronic conditions was assessed through in-person visits and self-reported diagnosis via telephone until the third follow-up visit (2017-2019). Multimorbidity was defined when, at the follow-up visit, the participant had two or more morbidities. Cumulative incidences, incidence rates, and adjusted incidence rate ratios (IRRs) were estimated using Poisson models.

RESULTS

Over an 8.3-year follow-up, compared to white participants: browns had a 27% greater incidence of hypertension and obesity; and blacks had a 62% and 45% greater incidence, respectively. Blacks also had 58% more diabetes. The cancer incidence was greater among whites. Multimorbidity affected 41% of the participants, with a crude incidence rate of 57.5 cases per 1000 person-years (ranging from 56.3 for whites to 63.9 for blacks). Adjusted estimates showed a 20% higher incidence of multimorbidity in black participants compared to white participants (IRR: 1.20; 95% CI: 1.05-1.38).

CONCLUSIONS

Significant racial disparities in the risk of chronic conditions and multimorbidity were observed. Many associations revealed a gradient increase in illness risk according to darker skin tones. Addressing fundamental causes such as racism and racial discrimination, alongside considering social determinants of health, is vital for comprehensive multimorbidity care. Intersectoral, equitable policies are essential for ensuring health rights for historically marginalized groups.

Tinkering with symptoms, causes and solutions: Tracing the enactments of multiple chronic illnesses in specialised outpatient check-ups

People living with multiple chronic illnesses and an increasing need for acute care is a global health challenge, which questions the conventional ways of managing illness. A central issue is how medical practices can become more patient-centred and aligned with the everyday life of patients. Communicative strategies for eliciting the patient's goals and preferences are often proposed. In this article, we draw on ethnographic data from fieldwork conducted during 2019-2020 in health-care settings and among people living with multiple chronic illness(es) and repeated acute admissions in Denmark. Inspired by science and technology studies of chronic illness and care, we trace the enactments of illness and illness work in a patient trajectory marked by persistent symptoms and medical complexity. We analyse three medical encounters, and we show how 'tinkering' with clinical signs and utterances in each encounter constantly enacts new versions, shaping how the patient could and should live with his illness. We argue that specialised outpatient check-ups for these patients must provide space for continuous tinkering with the concrete effects of illness in everyday life.

Multimorbidity in patients with atrial fibrillation

There is an escalating trend in both the incidence and prevalence of atrial fibrillation (AF). AF is linked to numerous other comorbidities, contributing to the emergence of multimorbidity. The sustained rise in multimorbidity and AF prevalences exerts a significant strain on healthcare systems globally. The understanding of the relation between multimorbidity and AF is essential to determine effective healthcare strategies, improve patient outcomes to adequately address the burden of AF. It not only begins with the accurate identification of comorbidities in the setting of AF. There is also the need to understand the pathophysiology of the different comorbidities and their common interactions, and how multimorbidity influences AF perpetuation. To manage the challenges that rise from the increasing incidence and prevalence of both multimorbidity and AF, such as adverse events and hospitalisations, the treatment of comorbidities in AF has already gained importance and will need to be a primary focus in the forthcoming years. There are numerous challenges to overcome in the treatment of multimorbidity in AF, whereby the identification of comorbidities is essential. Integrated care strategies focused on a comprehensive multimorbidity management with an individual-centred approach need to be determined to improve healthcare strategies and reduce the AF-related risk of frailty, cardiovascular diseases and improve patient outcomes.

The current state of complex systems research on socioeconomic inequalities in health and health behavior-a systematic scoping review

BACKGROUND

Interest in applying a complex systems approach to understanding socioeconomic inequalities in health is growing, but an overview of existing research on this topic is lacking. In this systematic scoping review, we summarize the current state of the literature, identify shared drivers of multiple health and health behavior outcomes, and highlight areas ripe for future research.

METHODS

SCOPUS, Web of Science, and PubMed databases were searched in April 2023 for peer-reviewed, English-language studies in high-income OECD countries containing a conceptual systems model or simulation model of socioeconomic inequalities in health or health behavior in the adult general population. Two independent reviewers screened abstracts and full texts. Data on study aim, type of model, all model elements, and all relationships were extracted. Model elements were categorized based on the Commission on Social Determinants of Health framework, and relationships between grouped elements were visualized in a summary conceptual systems map.

RESULTS

A total of 42 publications were included; 18 only contained a simulation model, 20 only contained a conceptual model, and 4 contained both types of models. General health outcomes (e.g., health status, well-being) were modeled more often than specific outcomes like obesity. Dietary behavior and physical activity were by far the most commonly modeled health behaviors. Intermediary determinants of health (e.g., material circumstances, social cohesion) were included in nearly all models, whereas structural determinants (e.g., policies, societal values) were included in about a third of models. Using the summary conceptual systems map, we identified 15 shared drivers of socioeconomic inequalities in multiple health and health behavior outcomes.

CONCLUSIONS

The interconnectedness of socioeconomic position, multiple health and health behavior outcomes, and determinants of socioeconomic inequalities in health is clear from this review. Factors central to the complex system as it is currently understood in the literature (e.g., financial strain) may be both efficient and effective policy levers, and factors less well represented in the literature (e.g., sleep, structural determinants) may warrant more research. Our systematic, comprehensive synthesis of the literature may serve as a basis for, among other things, a complex systems framework for socioeconomic inequalities in health.

Systematic review and meta-analysis of disease clustering in multimorbidity: a study protocol

INTRODUCTION

Multimorbidity is defined as the presence of two or more chronic diseases. Co-occurring diseases can have synergistic negative effects, and are associated with significant impacts on individual health outcomes and healthcare systems. However, the specific effects of diseases in combination will vary between different diseases. Identifying which diseases are most likely to co-occur in multimorbidity is an important step towards population health assessment and development of policies to prevent and manage multimorbidity more effectively and efficiently. The goal of this project is to conduct a systematic review and meta-analysis of studies of disease clustering in multimorbidity, in order to identify multimorbid disease clusters and test their stability.

METHODS AND ANALYSIS

We will review data from studies of multimorbidity that have used data clustering methodologies to reveal patterns of disease co-occurrence. We propose a network-based meta-analytic approach to perform meta-clustering on a select list of chronic diseases that are identified as priorities for multimorbidity research. We will assess the stability of obtained disease clusters across the research literature to date, in order to evaluate the strength of evidence for specific disease patterns in multimorbidity.

ETHICS AND DISSEMINATION

This study does not require ethics approval as the work is based on published research studies. The study findings will be published in a peer-reviewed journal and disseminated through conference presentations and meetings with knowledge users in health systems and public health spheres.

PROSPERO REGISTRATION NUMBER

CRD42023411249.

Association of cardiovascular health using Life's Essential 8 with noncommunicable disease multimorbidity

Cardiovascular health (CVH) is closely associated with various noncommunicable diseases (NCDs) and comorbidity; however, the influence of CVH on NCD multimorbidity was not fully elucidated. We aimed to examine the association between CVH using Life's Essential 8 (LE8) and NCD multimorbidity among adults, males, and females in the United States, conducting a cross-sectional analysis using data involving 24,445 participants from the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2018. LE8 was categorized into low, moderate, and high CVH groups. Multivariate logistic regressions and restricted cubic spline regressions were used to estimate the association between LE8 and NCD multimorbidity. Overall, 6162 participants had NCD multimorbidity, of which 1168 (43.5%), 4343 (25.9%), and 651 (13.4%) had low, moderate, and high CVH, separately. After multivariable adjustment, LE8 was negatively associated with NCD multimorbidity among adults (odds ratio (OR) for per 1 standard deviation (SD) increase in LE8 and 95% confidence interval (CI), 0.67 (0.64, 0.69)), and the top 3 NCDs associated with CVH were emphysema, congestive heart failure, stroke, and the dose-response relationships between LE8 and NCD multimorbidity were observed among adults (overall P < 0.001). Similar patterns were also identified among males and females. Higher CVH measured by the LE8 score was associated with lower odds of NCD multimorbidity among adults, males, and females.

Association between multimorbidity trajectories, healthcare utilization, and health expenditures among middle-aged and older adults: China Health and Retirement Longitudinal Study

BACKGROUND

To identify the latent groups of multimorbidity trajectories among middle-aged and older adults and examine their associations with healthcare utilization and health expenditures.

METHODS

We included adults aged ≥45 years who participated in the China Health and Retirement Longitudinal Study from 2011 to 2015 and were without multimorbidities (<2 chronic conditions) at baseline. Multimorbidity trajectories underlying 13 chronic conditions were identified using group-based multi-trajectory modeling based on the latent dimensions. Healthcare utilization included outpatient care, inpatient care, and unmet healthcare needs. Health expenditures included healthcare costs and catastrophic health expenditures (CHE). Random-effects logistic regression, random-effects negative binomial regression, and generalized linear regression models were used to examine the association between multimorbidity trajectories, healthcare utilization, and health expenditures.

RESULTS

Of the 5548 participants, 2407 developed multimorbidities during follow-up. Three trajectory groups were identified among those with new-onset multimorbidity according to the increasing dimensions of chronic diseases: "digestive-arthritic" (N = 1377, 57.21 %), "cardiometabolic/brain" (N = 834, 34.65 %), and "respiratory/digestive-arthritic" (N = 196, 8.14 %). All trajectory groups had a significantly increased risk of outpatient care, inpatient care, unmet healthcare needs, and higher healthcare costs than those without multimorbidities. Notably, participants in the "digestive-arthritic" trajectory group had a significantly increased risk of incurring CHE (OR = 1.70, 95%CI: 1.03-2.81).

LIMITATIONS

Chronic conditions were assessed using self-reported measures.

CONCLUSIONS

The growing burden of multimorbidity, especially multimorbidities of digestive and arthritic diseases, was associated with a significantly increased risk of healthcare utilization and health expenditures. The findings may help in planning future healthcare and managing multimorbidity more effectively.

Life-course fertility and multimorbidity among middle-aged and elderly women in China: Evidence from China health and retirement longitudinal study

Background

Multimorbidity has become an important public health problem in China, especially among middle-aged and elderly women. Few studies have been reported on the association between multimorbidity and female fertility, which is an important stage in the life course. This study aimed to explore the association between multimorbidity and fertility history among middle-aged and elderly women in China.

Methods

Data from 10,182 middle-aged and elderly female participants in the China Health and Retirement Longitudinal Study (CHARLS) in 2018 were used in this study. Multimorbidity was defined as the presence of at least two or more chronic conditions. Logistic regression analysis, negative binomial regression analysis, and restrictive cubic splines (RCSs) were used to analyze the relationship between female fertility history and multimorbidity or the number of chronic conditions. Multivariable linear regression was used to analyze the relationship between female fertility history and multimorbidity pattern factor scores.

Results

The results of this study showed that high parity and early childbearing were significantly associated with an increased risk of multimorbidity and an increased number of chronic conditions among middle-aged and elderly women in China. Late childbearing was significantly associated with reduced risk of multimorbidity and lessened diseases. Parity and age of first childbirth were significantly correlated with the odds of multimorbidity. The association between fertility history and multimorbidity was found to be influenced by age and urban-rural dual structure. Women with high parity tend to have higher factor scores of cardiac-metabolic, visceral-arthritic, and respiratory-psychiatric patterns. Women with early childbearing tended to have higher factor scores of the visceral-arthritic pattern and those with late childbearing tended to have lower factor scores of the cardiac-metabolic pattern.

Conclusion

Fertility history has a significant effect on multimorbidity in the middle and later lives of Chinese women. This study is of great importance for reducing the prevalence of multimorbidity among Chinese women through their life course and promoting health during their middle and later lives.

How to define today a medical disorder? Biological and psychosocial disadvantages as the paramount criteria

BACKGROUND

The 20th century has seen great developments in the concept of disease. Marked by the biopsychosocial paradigm, several strategies for disease definition were added to previous descriptive organic views, but a final concept is still out of reach.

METHOD

A critical review was carried out on thorough analysis of articles and textbooks to describe the main concepts and definitions of disease.

RESULTS

The concept 'disease' is a pragmatic construct, not a natural kind. Three main ways to define disease were identified, and characterized: Biological (disease as a lesion, disadvantage/deviation from normal and dysfunction), Psychosocial (distress and disability, existential potentials, descriptive prototype, and prototype typification), and values-based definition.

CONCLUSION

All the paradigms have advantages and flaws, but progressive use of all criteria in disease definition adds validity and reliability to diagnostic constructs. Such constructs must be, above all, useful for practice and research. Biological paradigm is relevant, but fails to cover all the complexity that involves human illness and the treatment process. An emphasis on distress, dysfunction, and carefully selected value-laden characteristics might be the right direction for useful diagnostic construct conceptions.

Data-driven patient stratification of UK Biobank cohort suggests five endotypes of multimorbidity

Multimorbidity generally refers to concurrent occurrence of multiple chronic conditions. These patients are inherently at high risk and often lead a poor quality of life due to delayed treatments. With the emergence of personalized medicine and stratified healthcare, there is a need to stratify patients right at the primary care setting. Here we developed multimorbidity analysis pipeline (MulMorPip), which can stratify patients into multimorbid subgroups or endotypes based on their lifetime disease diagnosis and characterize them based on demographic features and underlying disease-disease interaction networks. By implementing MulMorPip on UK Biobank cohort, we report five distinct molecular subclasses or endotypes of multimorbidity. For each patient, we calculated the existence of broad disease classes defined by Charlson's comorbidity classification using the International Classification of Diseases-10 encoding. We then applied multiple correspondence analysis in 77 524 patients from UK Biobank, who had multimorbidity of more than one disease, which resulted in five multimorbid clusters. We further validated these clusters using machine learning and were able to classify 20% model-blind test set patients with an accuracy of 97% and an average Jaccard similarity of 84%. This was followed by demographic characterization and development of interlinking disease network for each cluster to understand disease-disease interactions. Our identified five endotypes of multimorbidity draw attention to dementia, stroke and paralysis as important drivers of multimorbidity stratification. Inclusion of such patient stratification at the primary care setting can help general practitioners to better observe patients' multiple chronic conditions, their risk stratification and personalization of treatment strategies.

Raising the Alarm: Environmental Factors in the Onset and Maintenance of Chronic (Low-Grade) Inflammation in the Gastrointestinal Tract

Chronic inflammatory disease of the gastrointestinal (GI) tract is defined by several pathophysiological characteristics, such as dysbiosis of the microbiota, epithelial barrier hyperpermeability, systemic dissemination of endotoxins and chronic inflammation. In addition to well-reported environmental factors in non-communicable disease, such as smoking, diet, and exercise, humans are frequently exposed to myriads more environmental factors, from pesticides to food additives. Such factors are ubiquitous across both our diet and indoor/outdoor environments. A major route of human exposure to these factors is ingestion, which frequently occurs due to their intentional addition (intentional food additives) and/or unintentional contamination (unintentional food contaminants) of food products-often linked to environmental pollution. Understanding how this persistent, diverse exposure impacts GI health is of paramount importance, as deterioration of the GI barrier is proposed to be the first step towards systemic inflammation and chronic disease. Therefore, we aim to evaluate the impact of ingestion of environmental factors on inflammatory processes in the GI tract. In this review, we highlight human exposure to intentional food additives (e.g. emulsifiers, bulking agents) and unintentional food contaminants (e.g. persistent organic pollutants, pesticides, microplastics), then present evidence for their association with chronic disease, modification of the GI microbiota, increased permeability of the GI barrier, systemic dissemination of endotoxins, local (and distal) pro-inflammatory signalling, and induction of oxidative stress and/or endoplasmic reticulum stress. We also propose a link to NLRP3-inflammasome activation. These findings highlight the contribution of common environmental factors towards deterioration of GI health and the induction of pathophysiology associated with onset and maintenance of chronic inflammation in the GI tract.

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.

Neuroendocrine-Immune Regulatory Network of Eucommia ulmoides Oliver

Eucommia ulmoides Oliver (E. ulmoides) is a popular medicinal herb and health supplement in China, Japan, and Korea, and has a variety of pharmaceutical properties. The neuroendocrine-immune (NEI) network is crucial in maintaining homeostasis and physical or psychological functions at a holistic level, consistent with the regulatory theory of natural medicine. This review aims to systematically summarize the chemical compositions, biological roles, and pharmacological properties of E. ulmoides to build a bridge between it and NEI-associated diseases and to provide a perspective for the development of its new clinical applications. After a review of the literature, we found that E. ulmoides has effects on NEI-related diseases including cancer, neurodegenerative disease, hyperlipidemia, osteoporosis, insomnia, hypertension, diabetes mellitus, and obesity. However, clinical studies on E. ulmoides were scarce. In addition, E. ulmoides derivatives are diverse in China, and they are mainly used to enhance immunity, improve hepatic damage, strengthen bones, and lower blood pressure. Through network pharmacological analysis, we uncovered the possibility that E. ulmoides is involved in functional interactions with cancer development, insulin resistance, NAFLD, and various inflammatory pathways associated with NEI diseases. Overall, this review suggests that E. ulmoides has a wide range of applications for NEI-related diseases and provides a direction for its future research and development.

Association of a housing based individual socioeconomic status measure with diabetic control in primary care practices

AIMS

Socioeconomic status (SES) is an important variable that impacts healthcare outcomes. However, grouped SES data is not always representative of all members and it is difficult to obtain individual level data. A validated individual housing-based measure termed HOUSES is available, but has not been studied in diabetes. We hypothesize that patients in the lowest HOUSES quartile are associated with worse diabetic control as measured by the D5.

METHODS

A retrospective cohort study of 5463 patients with diabetes in 5 patient centered medical home practices in southeast Minnesota was conducted. HOUSES is a validated, standardized housing-based SES measure constructed from publicly available county assessor's office data. Diabetic control was assessed by the D5 (HgbA1c < 8, BP < 140/90, statin use, nonsmoking status, and antiplatelet therapy).

RESULTS

In the lowest HOUSES quartile, more patients had an uncontrolled D5 (56.4%) than any of the other quartiles (49.2%, 49.8%, 49.6% respectively, p < 0.001). A multivariate analysis shows the adjusted odds of D5 control for patients in the 2nd, 3rd or 4th HOUSES quartiles as opposed to the 1st quartile are 1.28, 1.21, and 1.20, respectively.

CONCLUSION

Lower SES as represented by the first quartile of HOUSES index, is associated with lower odds of D5 control and thus worse diabetic outcomes. Using the HOUSES index to identify these individuals in a patient centered medical home might prove useful in deciding where to focus diabetic control efforts.

Childhood ADHD, Going Beyond the Brain: A Meta-Analysis on Peripheral Physiological Markers of the Heart and the Gut

Attention-Deficit/Hyperactivity Disorder (ADHD) is the most common neurodevelopmental disorder diagnosed in children. Questions regarding its increased diagnostic rates and pharmacological treatments in developing children have led to a more holistic review of the multi-system pathophysiology observed in ADHD. The dopaminergic neurotransmitter system, known for its influence on reward-motivated behaviors and motor control, and the frontostriatal systems, that mediate motor, cognition, and behavior, are associated with ADHD's development. However, studies have shown that these neural systems do not wholly account for ADHD's multilayered and heterogeneous symptom presentation. For instance, the literature suggests that emotional dysregulation, the inability to regulate one's emotional responses to provoking stimuli, is associated with increased risk for social impairment in ADHD. A broader examination of physiological systems in children with ADHD has found potential markers in the heart-brain and gut-brain axes that correspond with certain behaviors associated with emotional dysregulation in recent studies. Hence, the purpose of this meta-analysis is to aggregate ten applicable published case studies and analyze task-related heart rate reactivity (HRR; n = 5 studies) and gut microbiota (n = 5 studies) data in children with and without ADHD. Data from a total of 531 youth with ADHD and 603 youth without ADHD revealed significant small and medium effect sizes for higher Chao1 levels and Actinobacteria levels in the ADHD group, respectively, but no evidence of altered task-related HRR. Thus, further research into multi-system psychophysiological measures of emotional dysregulation and ADHD is warranted. The clinical, empirical, and educational implications of these findings are discussed.

SYSTEMATIC REVIEW REGISTRATION

https://www.crd.york.ac.uk/prospero/, identifier PROSPERO (CRD42021236819).

Does Low Grade Systemic Inflammation Have a Role in Chronic Pain?

One of the major clinical manifestations of peripheral neuropathy, either resulting from trauma or diseases, is chronic pain. While it significantly impacts patients’ quality of life, the underlying mechanisms remain elusive, and treatment is not satisfactory. Systemic chronic inflammation (SCI) that we are referring to in this perspective is a state of low-grade, persistent, non-infective inflammation, being found in many physiological and pathological conditions. Distinct from acute inflammation, which is a protective process fighting against intruders, SCI might have harmful effects. It has been associated with many chronic non-communicable diseases. We hypothesize that SCI could be a predisposing and/or precipitating factor in the development of chronic pain, as well as associated comorbidities. We reviewed evidence from human clinical studies indicating the coexistence of SCI with various types of chronic pain. We also collated existing data about the sources of SCI and who could have it, showing that those individuals or patients having SCI usually have higher prevalence of chronic pain and psychological comorbidities. We thus elaborate on the need for further research in the connection between SCI and chronic pain. Several hypotheses have been proposed to explain these complex interactions.

Sulfur mustard and biological ageing: A multisystem biological health score approach as an extension of the allostatic load in Sardasht chemical veterans

BACKGROUND

Mustard gas as a chemical weapon has been used in wars and its long-term side effects are substantial in the human body. This study was aimed to apply an extension of allostatic load, known as synthetic biological health score (BHS), including the wear-and-tear of four physiological systems (endocrine, inflammatory, cardiovascular and metabolic systems) and two organs (liver and kidney) to estimate biological aging caused by sulfur mustard (SM) gas poisoning.

METHODS

The plasma samples were prepared from two following groups of people; 1) 446 individuals exposed to SM gas in 1987. 2) 115 healthy members, at the same range of age and residence, as the non-exposed group. These people were chosen from the same patients' families and have not had any exposure to SM or pulmonary dysfunction. To estimate BHS, 18 blood-derived biomarkers of the mentioned systems and organs were measured and the relative contribution of many social and body parameters across the age groups was explored.

RESULTS

It was revealed, in BHS calculation, the cardiovascular system had the most effect. Also, in the SM group, BHS was significantly higher than in the control group. This feature has a positive correlation with physical parameter (BMI) and a negative correlation with social parameters (salary and educational levels).

CONCLUSION

The multisystem BHS could be useful in the evaluation of biological aging due to SM exposure. Social (education, good-paying job) and physical (BMI) parameters could influence BHS and the higher BHS indicates the progress of biological aging due to mustard gas.

Universal health care - A matter of design and agency?

Universal health care (UHC) is primarily a financing concern, whereas primary health care (PHC) is primarily concerned with providing the right care at the right time to achieve the best possible health outcomes for individuals and communities. A recent call for contributions by the WHO emphasized that UHC can only be achieved through PHC, and that to achieve this goal will require the strengthening of the three pillars of PHC - (a) enabling primary care and public health to integrate health services, (b) empowering people and communities to create healthy living conditions, and (c) integrating multisectoral policy decisions to ensure UHC that achieves the goal of "health for all." "Pillars" - as a static metaphor - sends the wrong signal to the research and policy-making community. It, in fact, contradicts the WHO's own view, namely that there is "the need to strengthen comprehensive primary health care systems based on local priorities, needs and contexts … [that are] co-developed by people who are engaged in their own health." What we really need to develop PHC as the basis to achieve the goal of UHC is a dynamic agency to drive a "system-as-a-whole framework" that simultaneously takes into account finance, individual, and local needs. Health systems are socially constructed organizational systems that are "functionally layered" in a hierarchical fashion - governments and/or funders at the top-level not only promote the goals of the system (policies) but also constrain the system (rules, regulations, resources) in its ability to deliver. Hence, there is a need to focus on two key system features - political leadership and dynamic bottom-up agency that maintains everyone's focus on the goal to be achieved, and a limitation of system constraints so that communities can shape best adapted primary care services that truly meet the needs of their individuals, families, and community.

Beyond multimorbidity: What can we learn from complexity science?

Multimorbidity - the occurrence of two or more long-term conditions in an individual - is a major global concern, placing a huge burden on healthcare systems, physicians, and patients. It challenges the current biomedical paradigm, in particular conventional evidence-based medicine's dominant focus on single-conditions. Patients' heterogeneous range of clinical presentations tend to escape characterization by traditional means of classification, and optimal management cannot be deduced from clinical practice guidelines. In this article, we argue that person-focused care based in complexity science may be a transformational lens through which to view multimorbidity, to complement the specialism focus on each particular disease. The approach offers an integrated and coherent perspective on the person's living environment, relationships, somatic, emotional and cognitive experiences and physiological function. The underlying principles include non-linearity, tipping points, emergence, importance of initial conditions, contextual factors and co-evolution, and the presence of patterned outcomes. From a clinical perspective, complexity science has important implications at the theoretical, practice and policy levels. Three essential questions emerge: (1) What matters to patients? (2) How can we integrate, personalize and prioritize care for whole people, given the constraints of their socio-ecological circumstances? (3) What needs to change at the practice and policy levels to deliver what matters to patients? These questions have no simple answers, but complexity science principles suggest a way to integrate understanding of biological, biographical and contextual factors, to guide an integrated approach to the care of people with multimorbidity.

Multimorbidity of chronic non-communicable diseases: burden, care provision and outcomes over time among patients attending chronic outpatient medical care in Bahir Dar, Ethiopia-a mixed methods study protocol

INTRODUCTION

Multimorbidity refers to the presence of two or more chronic non-communicable diseases (NCDs) in a given individual. It is associated with premature mortality, lower quality of life (QoL) and greater use of healthcare resources. The burden of multimorbidity could be huge in the low and middle-income countries (LMICs), including Ethiopia. However, there is limited evidence on the magnitude of multimorbidity, associated risk factors and its effect on QoL and functionality. In addition, the evidence base on the way health systems are organised to manage patients with multimorbidity is sparse. The knowledge gleaned from this study could have a timely and significant impact on the prevention, management and survival of patients with NCD multimorbidity in Ethiopia and in LMICs at large.

METHODS AND ANALYSIS

This study has three phases: (1) a cross-sectional quantitative study to determine the magnitude of NCD multimorbidity and its effect on QoL and functionality, (2) a qualitative study to explore organisation of care for patients with multimorbidity, and (3) a longitudinal quantitative study to investigate disease progression and patient outcomes over time. A total of 1440 patients (≥40 years) on chronic care follow-up will be enrolled from different facilities for the quantitative studies. The quantitative data will be collected from multiple sources using the KoBo Toolbox software and analysed by STATA V.16. Multiple case study designs will be employed to collect the qualitative data. The qualitative data will be coded and analysed by Open Code software thematically.

ETHICS AND DISSEMINATION

Ethical clearance has been obtained from the College of Medicine and Health Sciences, Bahir Dar University (protocol number 003/2021). Subjects who provide written consent will be recruited in the study. Confidentiality of data will be strictly maintained. Findings will be disseminated through publications in peer-reviewed journals and conference presentations.

Impacts of multimorbidity on medication treatment, primary healthcare and hospitalization among middle-aged and older adults in China: evidence from a nationwide longitudinal study

Background

Multimorbidity is a significant contributor to inequalities in healthcare and has become a major unaddressed challenge for the health system in China. The aim of this study is to assess the socio-demographic distribution of multimorbidity and the relationships between multimorbidity, primary healthcare, hospitalization and healthcare spending.

Methods

We conducted this nationwide population-based panel data study in China. Study participants included 12,306 residents aged ≥45 years from the China Health and Retirement Longitudinal Study in 2011, 2013 and 2015. Random-effects logistic regression models were applied to estimate the association between multimorbidity and primary healthcare as well as admission to the hospital. We used log-linear regression models to investigate the association between multimorbidity and health spending.

Results

Overall, 46.2% of total interviewees reported multimorbidity. Random-effects logistic regression analyses showed that multimorbidity was associated with a higher likelihood of medication use (Adjusted odds ratio (AOR) =19.19, 95% CI = 17.60, 20.93), health check (AOR = 1.51, 95% CI = 1.43, 1.59), outpatient care (AOR = 2.39, 95% CI = 2.23, 2.56) and admission to hospital (AOR = 2.94, 95% CI = 2.68, 3.21). Log-linear regression models showed that multimorbidity was also positively associated with spending for outpatient care (coefficient = 0.64, 95% CI = 0.59, 0.68) and hospitalization (coefficient = 0.65, 95% CI = 0.60, 0.71).

Conclusions

Multimorbidity is associated with higher levels of primary care, hospitalization and greater financial burden to individuals in China. Health systems need to shift from single-disease models to new financing and service delivery models to more effectively manage multimorbidity.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-11456-7.

Allostatic Load in Cancer: A Systematic Review and Mini Meta-Analysis

BACKGROUND

Individuals with cancer experience stress throughout the cancer trajectory. Allostatic load (AL), a cumulative multi-system measure, may have a greater value in stress assessment and the associated biological burden than individual biomarkers. A better understanding of the use of AL and its operationalization in cancer could aid in early detection and prevention or alleviation of AL in this population.

PURPOSE

To consolidate findings on the operationalization, antecedents, and outcomes of AL in cancer.

METHODS

Seven databases (CINAHL, Ovid MEDLINE, Web of Science, APA PsycInfo, Scopus, Embase, and Cochrane CENTRAL) were searched for articles published through April 2020. The NIH tools were used to assess study quality.

RESULTS

Twelve studies met inclusion criteria for this review. Although variability existed in the estimation of AL, biomarkers of cardiovascular, metabolic, and immune systems were mostly used. Associations of AL with cancer-specific variables were examined mostly utilizing population-databases. Significant associations of AL with variables such as cancer-related stress, positive cancer history, post traumatic growth, resilience, tumor pathology, and cancer-specific mortality were found. Mini meta-analysis found that a one-unit increase in AL was associated with a 9% increased risk of cancer-specific mortality.

CONCLUSION

This review reveals heterogeneity in operationalization of AL in cancer research and lack of clarity regarding causal direction between AL and cancer. Nevertheless, AL holds a significant promise in cancer research and practice. AL could be included as a screening tool for high-risk individuals or a health outcome in cancer. Optimal standardized approaches to measure AL would improve its clinical utility.

Medical costs and out-of-pocket expenditures associated with multimorbidity in China: quantile regression analysis

Objective

Multimorbidity is a growing challenge in low-income and middle-income countries. This study investigates the effects of multimorbidity on annual medical costs and the out-of-pocket expenditures (OOPEs) along the cost distribution.

Methods

Data from the nationally representative China Health and Retirement Longitudinal Study (CHARLS 2015), including 10 592 participants aged ≥45 years and 15 physical and mental chronic diseases, were used for this nationally representative cross-sectional study. Quantile multivariable regressions were employed to understand variations in the association of chronic disease multimorbidity with medical cost and OOPE.

Results

Overall, 69.5% of middle-aged and elderly Chinese had multimorbidity in 2015. Increased number of chronic diseases was significantly associated with greater health expenditures across every cost quantile groups. The effect of chronic diseases on total medical cost was found to be larger among the upper tail than those in the lower tail of the cost distributions (coefficients 12, 95% CI 6 to 17 for 10th percentile; coefficients 296, 95% CI 71 to 522 for 90th percentile). Annual OOPE also increased with chronic diseases from the 10th percentile to the 90th percentile. Multimorbidity had larger effects on OOPE and was more pronounced at the upper tail of the health expenditure distribution (regression coefficients of 8 and 84 at the 10th percentile and 75th percentile, respectively).

Conclusion

Multimorbidity is associated with escalating healthcare costs in China. Further research is required to understand the impact of multimorbidity across different population groups.

Professional judgement in clinical practice (part 3): A better alternative to strong evidence-based medicine

Parts 1 and 2 in this series of three articles have shown that and how strong evidence-based medicine has neither a coherent theoretical foundation nor creditable application to clinical practice. Because of its core commitment to the discredited positivist tradition it holds both a false concept of scientific knowledge and misunderstandings concerning clinical decision-making. Strong EBM continues attempts to use flawed adjustments to recover from the unsalvageable base view. Paper three argues that a promising solution is at hand if we can manage several modes of inclusion. A modified original, moderate version of EBM continues though usually overshadowed. As definitively laid out by Sackett in the 1990s, clinical decision making is intended to be person-centered, recognizing and integrating multiple modes of evidence and knowledge that have been marginalized: professional experience, illness narratives, and individual patients' values and preferences. Complementary resources are at hand: interpretative understanding and practice, such as philosophical anthropology, hermeneutical phenomenology, complexity theory, and phronetic practices respond to the major problems and open new possibilities. Phronesis is especially important in regard to public decision making. Within part 3 an additional tone necessarily occurs. While most of papers 1, 2, and 3 are written in the classical mode of contrasting the theoretical-logical and empirical evidence offered by contending positions bearing on the decision making and judgement in clinical practice, a shift occurs when considerations move beyond what is possible for clinical practitioners to accomplish. A different, discontinuous level of power operates in the trans-personal realm of instrumental policy, insurance, and hospital management practices. In this social-economic-political-ethical realm what happens in clinical practice today increasingly becomes a matter of what is "done unto" clinical practitioners, of what hampers their professional action and thus care of individual patients and clients.

Increases in multimorbidity with weight class in the United States

Little is known regarding how multimorbidity combinations associated with obesity change with increase in body weight. This study employed data from the national Cerner HealthFacts Data Warehouse to identify changes in multimorbidity patterns by weight class using network analysis. Networks were generated for 154 528 middle-aged patients in the following categories: normal weight, overweight, and classes 1, 2, and 3 obesity. The results show significant differences (P-value<0.05) in prevalence by weight class for all but three of 82 diseases considered. The percentage of patients with multimorbidity (excluding obesity) increases from in 55.1% in patients with normal weight, to 57.88% with overweight, 70.39% with Class 1 obesity, 73.99% with Class 2 obesity, and 71.68% in Class 3 obesity, increasing most substantially with the progression from overweight to class 1 obesity. Most prevalent disease clusters expand from only hypertension and dorsalgia in normal weight, to add joint disorders in overweight, lipidemias in class 1 obesity, diabetes in class 2 obesity, and sleep disorders and chronic kidney disease in class 3 obesity. Recognition of multimorbidity patterns associated with weight increase is essential for true precision care of obesity-associated chronic conditions and can help clinicians identify and address preclinical disease before additional complications arise.

Does social support mediate the effect of multimorbidity on mental wellbeing in the German working population? A longitudinal mediation analysis using structural equation modelling

This study provides insights into the longitudinal relation between multimorbidity, mental wellbeing, and social support. The analysis used the German Sociomedical Panel of Employees, a study of the German working population aged 40 to 54. In the context of multimorbidity, this population has been little studied. Multimorbidity is significantly associated with reduced mental wellbeing and social support, whereas social support increases mental wellbeing. We argue that, especially among the working population, multimorbidity reduces perceived social support and decreases mental wellbeing. We elaborate on the mediation process empirically by comparing two distinct structural equation models: a cross-lagged panel mediation model that models a potential reverse-causality between social support and mental wellbeing; and a synchronous mediation model that allows for more immediate mediation. Both models estimated significant mediation. The relative size of the mediation effect, however, varied widely based on the added mediational paths (8.57% vs. 28%). Fit statistics for both models were good, and the comparison did not favour either model. We conclude that theoretical reasoning must prevail over empirical testing. The cross-lagged model implies a more longitudinal (lagged) mediation process for social support. However, we suggest an immediate, flexible mediation as more plausible. Nevertheless, we suggest that cross-lagged models, when given a data structure and time gaps, reflect the social processes adequately.

Multimorbidity and its associated factors among adults aged 50 and over: A cross-sectional study in 17 European countries

AIMS

To estimate the prevalence of multimorbidity among European community-dwelling adults, as well as to analyse the association with gender, age, education, self-rated health, loneliness, quality of life, size of social network, Body Mass Index (BMI) and disability.

METHODS

A cross-sectional study based on wave 6 (2015) of the Survey of Health, Ageing and Retirement in Europe (SHARE) was conducted, and community-dwelling participants aged 50+ (n = 63,844) from 17 European countries were selected. Multimorbidity was defined as presenting two or more health conditions. The independent variables were gender, age group, educational level, self-rated health, loneliness, size of network, quality of life, BMI and disability (1+ limitations of basic activities of daily living). Poisson regression models with robust variance were fit for bivariate and multivariate analysis.

RESULTS

The prevalence of multimorbidity was 28.2% (confidence interval-CI 95%: 27.5.8-29.0) among men and 34.5% (CI95%: 34.1-35.4) among women. The most common health conditions were cardiometabolic and osteoarticular diseases in both genders, and emotional disorders in younger women. A large variability in the prevalence of multimorbidity in European countries was verified, even between countries of the same region.

CONCLUSIONS

Multimorbidity was associated with sociodemographic and physical characteristics, self-rated health, quality of life and loneliness.

Associating modifiable lifestyle factors with multimorbidity in community dwelling individuals from mainland China

AIMS 

Lifestyle factors have been well-established as essential targets for fighting individual chronic diseases, but little research has concentrated on multimorbidity from the perspective of multiple lifestyle factors in the Chinese population. Thus, this study aimed to explore the associations of lifestyle factors with the occurrence of multimorbidity.

METHODS AND RESULTS 

Cross-sectional data retrieved from the China Health and Retirement Longitudinal Study were used for analysis. Multimorbidity was calculated on a simple count of self-reported chronic conditions. Lifestyle factors included sleep duration, physical activity, alcohol intake, smoking status, and body mass index. Logistic regression analysis was used to examine the independent and accumulating effects of lifestyle factors on multimorbidity. Latent class analysis was performed to explore the lifestyle patterns. Six thousand, five hundred, and ninety-one valid subjects were included for analysis. Overall, the community dweller's median number of chronic conditions was 1 (range 1-11) and median number of high-risk lifestyle factors was 2 (range 0-5). All lifestyle factors were associated with the occurrence of multimorbidity but varied between genders. We also identified that participants who accumulated more unhealthy lifestyle factors having a higher likelihood of multimorbidity. 'Physical activity and weight', 'smoke and drink', and 'sleep and weight' dominated high-risk lifestyles were the most common lifestyle patterns.

CONCLUSION 

This study revealed the associations of unhealthy lifestyle factors and their accumulating effect with multimorbidity in Chinese community dwellers. Three common lifestyle patterns indicated that a holistic approach focused on engaging and changing multiple modifiable lifestyle behaviours within an individual might be more effective in managing multimorbidity.

The effect of multimorbidity on functional limitations and depression amongst middle-aged and older population in China: a nationwide longitudinal study

BACKGROUND

multimorbidity contributes to a large portion of the disease burden in low- and middle-income countries. However, limited research has been undertaken in China. This study has investigated the prevalence of multimorbidity and the associations of multimorbidity with activities of daily living (ADL), instrumental activities of daily living (IADL) and depression in China.

METHODS

the study participants included 10,055 adults aged 45 years and older from three rounds of the China Health and Retirement Longitudinal Study 2011-2015. Random-effects logistic regression models were used to examine the association of multimorbidity with ADL limitation, IADL limitation and mental disease.

RESULTS

the prevalence of multimorbidity amongst adults in China aged 45 years and older was 62.1% in 2015. The prevalence of multimorbidity was increased with older age, among women, in a higher socio-economic group and in the most deprived regions. Multimorbidity is associated with an increased likelihood of experiencing ADL limitation (adjusted odds ratio [AOR] = 5.738, 95% confidence intervals (CI) = 5.733, 5.744) and IADL limitation (AOR = 2.590, 95% CI = 2.588, 2.592) and depression (AOR = 3.352, 95% CI = 3.350, 3.354). Rural-urban disparities in functional difficulties and depression were also found amongst patients with multimorbidity.

CONCLUSIONS

the burden of multimorbidity is high in China, particularly amongst the older population. Multimorbidity is associated with higher levels of functional limitations and depression. China healthcare reforms should introduce integrated care models and patient-centred healthcare delivery. The increasing need for reorientation of healthcare resources considering the distribution of multimorbidity and its adverse effect requires more attention from health policymakers in China and other developing countries.

Urban-rural differences in the impacts of multiple chronic disease on functional limitations and work productivity among Chinese adults

BACKGROUND

Chronic disease multimorbidity has become a major challenge for health systems. While a lot of research has evaluated the direct economic burden of multimorbidity on health care utilization and cost, little attention has been given to the impacts on work productivity and functional limitations, as indirect indicators of disease burden.

OBJECTIVES

This study aims to examine the prevalence of multimorbidity among Chinese adults and its impact on functional disability and work productivity. It also investigates urban-rural differences in these relationships.

METHOD

This study utilized the data from the China Health and Retirement Longitudinal Study (CHARLS) in 2015, including 11,176 participants aged 45 years and older. Multivariable logistic regression models were used to estimate the effect of multimorbidity on functional disability (i.e. ADL: activities of daily life; IADL: instrumental activities of daily life), and work productivity loss due to health problems. Negative binomial regression models were used to assess the association of multimorbidity with sickness absences from agricultural work and employed non-agricultural work.

RESULTS

68.8% of total participants in CHARLS had multimorbidity in China in 2015. Rural residents with multimorbidity reported higher proportions of physical functions and days of sick leave than urban residents. Multimorbidity was positively associated with ADL limitation (odds ratio 1.924, 95% CI 1.656-2.236), IADL limitation (1.522, 1.326-1.748), limited work due to health problems (1.868, 1.601-2.178) and days of sick leave (for agricultural work, incidence rate ratio 1.676, 95% CI 1.390-2.020; for employed non-agricultural work, 2.418, 1.245-4.696). For the rural group, the impact of multimorbidity on functional limitations and work productivity loss (except for early retirement), was less than the urban group.

CONCLUSIONS

Multimorbidity poses significant challenges for functional health and work productivity These have significant negative economic consequences for individuals, the Chinese health system and the society.

Weathering in Detroit: Place, Race, Ethnicity, and Poverty as Conceptually Fluctuating Social Constructs Shaping Variation in Allostatic Load

Policy Points Despite 30 years of attention to eliminating population health inequity, it remains entrenched, calling for new approaches. Targeted universalism, wellness-based local development, and Jedi Public Health approaches that are community informed, evidence based, and focused on improving everyday settings and diverse lived experiences are important policy directions. State and federal revenue transfers are necessary to mitigate the harms of austerity and assure greater equity in fiscal and population health in places like Detroit, Michigan.

CONTEXT

US population health inequity remains entrenched, despite mandates to eliminate it. To promote a public health approach of consequence in this domain, stakeholders call for moving from risk-factor epidemiology toward consideration of dynamic local variations in the physiological impacts of structured lived experience.

METHODS

Using a community-based, participatory research approach, we collected and analyzed a unique data set of 239 black, white, and Mexican adults from a stratified, multistage probability sample of three Detroit, Michigan, neighborhoods. We drew venous blood, collected saliva, took anthropometric measurements, and assayed specimens to measure allostatic load (AL), an indicator of stress-mediated biological dysregulation, linking participants' AL scores and survey responses. In a series of nested Poisson models, we regressed AL on socioeconomic, psychosocial, neighborhood, and behavioral stressors to test the hypothesis that race/ethnicity and poverty-to-income ratio (PIR) are conceptually fluctuating variables whose impacts on AL are sensitive to structured lived experience.

FINDINGS

White and Mexican Detroit participants with PIR < 1 have higher AL than counterparts nationally; black participants in Detroit and nationwide had comparable AL. Within Detroit, disparities by PIR were higher in whites than blacks, with no significant difference by PIR in Mexicans. The size of estimated effects of having PIR < 1 for whites is 58 percentage points greater than that of Mexicans and twice that of blacks.

CONCLUSIONS

Structurally rooted unobserved heterogeneity bias threatens the validity of independent main effects interpretations of associations between race/ethnicity, socioeconomic characteristics, or place and health. One-size-fits-all analytic or policy models developed from the perspective of the dominant social group insufficiently address the experiences of diverse populations in specific settings and historical moments; nor do they recognize culturally mediated protective resources residents may have developed against material and psychosocial hardship.

Planning and optimising CHAT&PLAN: A conversation-based intervention to promote person-centred care for older people living with multimorbidity

BACKGROUND

Older people are more likely to be living with cancer and multiple long-term conditions, but their needs, preferences for treatments, health priorities and lifestyle are often not identified or well-understood. There is a need to move towards a more comprehensive person-centred approach to care that focuses on the cumulative impact of a number of conditions on daily activities and quality of life. This paper describes the intervention planning process for CHAT& PLANTM, a structured conversation intervention to promote personalised care and support self-management in older adults with complex conditions.

METHODS

A theory-, evidence- and person-based approach to intervention development was undertaken. The intervention planning and development process included reviewing relevant literature and existing guidelines, developing guiding principles, conducting a behavioural analysis and constructing a logic model. Optimisation of the intervention and its implementation involved qualitative interviews with older adults with multimorbidity (n = 8), family caregivers (n = 2) and healthcare professionals (HCPs) (n = 20). Data were analysed thematically and informed changes to the intervention prototype.

RESULTS

Review findings reflected the importance of HCPs taking a person-centred (rather than disease-centred) approach to their work with older people living with multimorbidity. This approach involves HCPs giving health service users the opportunity to voice their priorities, then using these to underpin the treatment and care plan that follow. Findings from the planning stage indicated that taking a structured approach to interactions between HCPs and health service users would enable elicitation of individual concerns, development of a plan tailored to that individual, negotiation of roles and review of goals as individual priorities change. In the optimisation stage, older adults and HCPs commented on the idea of a structured conversation to promote person-centred care and on its feasibility in practice. The idea of a shared, person-centred approach to care was viewed positively. Concerns were raised about possible extra work for those receiving or delivering care, time and staffing, and risk of creating another "tick-box" exercise for staff. Participants concluded that anyone with the appropriate skills could potentially deliver the intervention, but training was likely to be required to ensure correct utilisation and self-efficacy to deliver to the intervention.

CONCLUSIONS

CHAT&PLAN, a structured person-centred conversation guide appears acceptable and appealing to HCPs and older adults with multimorbidity. Further development of the CHAT&PLAN intervention should focus on ensuring that staff are adequately trained and supported to implement the intervention.

Mental health is the health of the whole body: How psychoneuroimmunology & health psychology can inform & improve treatment

BACKGROUND

Converging and accumulating evidence for the cross-communication among the nervous, immune, and endocrine systems, a field of study known as psychoneuroimmunology, implicates immunological dysfunction as a shared and common mechanism of both mental and physical illness. For example, psychiatric disorders like schizophrenia, bipolar disorder, major depression, and anxiety disorders have higher prevalence rates across a spectrum of autoimmune conditions compared to the general population. Additionally, subclinical immunological abnormalities are observed in a variety of psychiatric conditions, with chronic inflammation most extensively studied in the pathophysiology of depression. These observations blur the historical distinctions between mental and physical illness, yet clinical practice remains fragmented and primarily focused on differentially treating individual symptoms.

PROPOSED THESIS

Therapeutically targeting inflammation offers translational opportunities for integrating mental and physical healthcare, a key niche of the interdisciplinary field of health psychology.

CONCLUSION

Utilizing a psychoneuroimmunological lens, health psychologists and clinicians can reconceptualize healthcare through integrative treatment approaches and advocacy for comprehensive policy-level reform at both the individual-level of care as well as community-wide prevention approaches.

Designing health care: A community health science solution for reducing health disparities by integrating social determinants and the effects of place

BACKGROUND

In the United States chronic illnesses have become a way of life for multiple generations - they are the number one cause of death and disability (accounting for more than 70% of deaths), 60% of American adults have at least one chronic disease, and 40% have multiple chronic conditions. Although multiple factors contribute to the growth in chronic disease prevalence, a major factor has been overreliance on health care systems for promoting health and preventing disease. Large health care systems are ill equipped for this role since they are designed to detect, treat, and manage disease, not to promote health or address the underlying causes of disease.

METHODS

Improving health outcomes in the U.S. will require implementing broad-based prevention strategies combining biological, behavioral, and societal variables that move beyond clinical care. According to community medicine, clinical care alone cannot create, support, or maintain health. Rather, health can only ensue from combining clinical care with epidemiology and community organization, because health is a social outcome resulting from a combination of clinical science, collective responsibility, and informed social action.

RESULTS

During the past 20 years, our team has developed an operational community medicine approach known as community health science. Our model provides a simple framework for integrating clinical care, population health, and community organization, using community-based participatory research (CBPR) practices for developing place-based initiatives. In the present paper, we present a brief overview of the model and describe its evolution, applications, and outcomes in two major urban environments.

CONCLUSION

The paper demonstrates means for integrating the social determinants of health into collaborative place-based approaches, for aligning community assets and reducing health disparities. It concludes by discussing how asset-based community development can promote social connectivity and improve health, and how our approach reflects the emerging national consensus on the importance of place-based population system change.

Physical multimorbidity, health service use, and catastrophic health expenditure by socioeconomic groups in China: an analysis of population-based panel data

Background

Multimorbidity, the presence of two or more mental or physical chronic non-communicable diseases, is a major challenge for the health system in China, which faces unprecedented ageing of its population. Here we examined the distribution of physical multimorbidity in relation to socioeconomic status; the association between physical multimorbidity, health-care service use, and catastrophic health expenditures; and whether these associations varied by socioeconomic group and social health insurance schemes.

Methods

In this population-based, panel data analysis, we used data from three waves of the nationally representative China Health and Retirement Longitudinal Study (CHARLS) for 2011, 2013, and 2015. We included participants aged 50 years and older in 2015, who had complete follow-up for the three waves. We used 11 physical non-communicable diseases to measure physical multimorbidity and annual per-capita household consumption spending as a proxy for socioeconomic status.

Findings

Of 17 708 participants in CHARLS, 11 817 were eligible for inclusion in our analysis. The median age of participants was 62 years (IQR 56–69) in 2015, and 5766 (48·8%) participants were male. 7320 (61·9%) eligible participants had physical multimorbidity in China in 2015. The prevalence of physical multimorbidity was increased with older age (odds ratio 2·93, 95% CI 2·71–3·15), among women (2·70, 2·04–3·57), within a higher socioeconomic group (for quartile 4 [highest group] 1·50, 1·24–1·82), and higher educational level (5·17, 3·02–8·83); however, physical multimorbidity was more common in poorer regions than in the more affluent regions. An additional chronic non-communicable disease was associated with an increase in the number of outpatient visits (incidence rate ratio 1·29, 95% CI 1·27–1·31), and number of days spent in hospital as an inpatient (1·38, 1·35–1·41). We saw similar effects in health service use of an additional chronic non-communicable disease in different socioeconomic groups and among those covered by different social health insurance programmes. Overall, physical multimorbidity was associated with a significantly increased likelihood of catastrophic health expenditure (for the overall population: odds ratio 1·29, 95% CI 1·26–1·32, adjusted for sociodemographic variables). The effect of physical multimorbidity on catastrophic health expenditures persisted even among the higher socioeconomic groups and across all health insurance programmes.

Interpretation

Concerted efforts are needed to reduce health inequalities that are due to physical multimorbidity, and its adverse economic effect in population groups in China. Social health insurance reforms must place emphasis on reducing out-of-pocket spending for patients with multimorbidity to provide greater financial risk protection.

Funding

None.

An integrated model of multimorbidity and symptom science

BACKGROUND

Prevalence and complexity of persons with multiple chronic conditions (MCC), also known as multimorbidity, are shifting clinical practice from a single disease focus to one considering MCC and symptoms. Although symptoms are intricately bound to concepts inherent in MCC science, symptoms are largely ignored in multimorbidity research and literature.

PURPOSE

Introduce an Integrated Model of Multimorbidity and Symptom Science.

METHODS

Critical integrative review and synthesis process.

FINDINGS

The model comprises three primary domains: 1. Contributing/ Risk Factors; 2. Symptom/Disease/Treatment Interactions; and 3. Patient Outcomes.

DISCUSSION

The model highlights the multilevel nature of contributing factors and the recursive interactions among multiple etiologies, conditions, symptoms, therapies, and outcomes.

Stress and Feline Health

In the health sciences, stress often is defined in terms of stressors; events that are perceived as threats to one's perception of control. From this perspective, a stressor is anything that activates the central threat response system (CTRS). Recent research shows that the CTRS can be sensitized to environmental events through epigenetic modulation of gene expression. When CTRS activation is chronic, health and welfare may be harmed. Environmental modification can mitigate the harmful effects of chronic CTRS activation by reducing the individual's perception of threat and increasing its perception of control, which improves health and welfare.

Burden of migraine in Finland: multimorbidity and phenotypic disease networks in occupational healthcare

BACKGROUND

Migraine is a complex neurological disorder with high co-existing morbidity burden. The aim of our study was to examine the overall morbidity and phenotypic diseasome for migraine among people of working age using real world data collected as a part of routine clinical practice.

METHODS

Electronic medical records (EMR) of patients with migraine (n = 17,623) and age- and gender matched controls (n = 17,623) were included in this retrospective analysis. EMRs were assessed for the prevalence of ICD-10 codes, those with at least two significant phi correlations, and a prevalence >2.5% in migraine patients were included to phenotypic disease networks (PDN) for further analysis. An automatic subnetwork detection algorithm was applied in order to cluster the diagnoses within the PDNs. The diagnosis-wise connectivity based on the PDNs was compared between migraine patients and controls to assess differences in morbidity patterns.

RESULTS

The mean number of diagnoses per patient was increased 1.7-fold in migraine compared to controls. Altogether 1337 different ICD-10 codes were detected in EMRs of migraine patients. Monodiagnosis was present in 1% and 13%, and the median number of diagnoses was 12 and 6 in migraine patients and controls. The number of significant phi-correlations was 2.3-fold increased, and cluster analysis showed more clusters in those with migraine vs. controls (9 vs. 6). For migraine, the PDN was larger and denser and exhibited one large cluster containing fatigue, respiratory, sympathetic nervous system, gastrointestinal, infection, mental and mood disorder diagnoses. Migraine patients were more likely affected by multiple conditions compared to controls, even if no notable differences in morbidity patterns were identified through connectivity measures. Frequencies of ICD-10 codes on a three character and block level were increased across the whole diagnostic spectrum in migraine.

CONCLUSIONS

Migraine was associated with an increased multimorbidity, evidenced by multiple different approaches in the study. A systematic increase in the morbidity across the whole spectrum of ICD-10 coded diagnoses, and when interpreting PDNs, were detected in migraine patients. However, no specific diagnoses explained the morbidity. The results reflect clinical praxis, but also undoubtedly, the pathophysiological phenotypes related to migraine, and emphasize the importance of better understanding migraine-related morbidity.

Association Between Speed of Multimorbidity Accumulation in Old Age and Life Experiences: A Cohort Study

Rapidly accumulating multiple chronic conditions (multimorbidity) during aging are associated with many adverse outcomes. We explored the association between 4 experiences throughout life-childhood socioeconomic circumstances, early-adulthood education, midlife occupational stress, and late-life social network-and the speed of chronic disease accumulation. We followed 2,589 individuals aged ≥60 years from the Swedish National Study on Aging and Care in Kungsholmen for 9 years (2001-2013). Information on life experiences was collected from detailed life-history interviews. Speed of disease accumulation was operationalized as the change in the count of chronic conditions obtained from clinical examinations, medical histories, laboratory data, drug use, and register linkages over 9 years. Linear mixed models were used to analyze the data. Speed of disease accumulation was lower in individuals with more than elementary education (for secondary, β × time = -0.065, 95% CI: -0.126, -0.004; for university, β × time = -0.118, 95% CI: -0.185, -0.050); for active occupations compared with high-strain jobs (β × time = -0.078, 95% CI: -0.138, -0.017); and for richer social networks (for moderate tertile, β × time = -0.102, 95% CI: -0.149, -0.055; for highest tertile, β × time = -0.135, 95% CI: -0.182, -0.088). The association between childhood circumstances and speed of disease accumulation was attenuated by later-life experiences. Diverse experiences throughout life might decelerate chronic disease accumulation during aging.

Multimorbidity: Implications and directions for health psychology and behavioral medicine

The increasing prevalence of multimorbidity in the United States and the rest of the world poses problems for patients and for health care providers, care systems, and policy. After clarifying the difference between comorbidity and multimorbidity, this article describes the challenges that the prevalence of multimorbidity presents for well-being, prevention, and medical treatment. We submit that health psychology and behavioral medicine have an important role to play in meeting these challenges because of the holistic vision of health afforded by the foundational biopsychosocial model. Furthermore, opportunities abound for health psychology/behavioral medicine to study how biological, social and psychological factors influence multimorbidity. This article describes three major areas in which health psychologists can contribute to understanding and treatment of multimorbidity: (a) etiology; (b) prevention and self-management; and (c) clinical care. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Geo-clustered chronic affinity: pathways from socio-economic disadvantages to health disparities

Objective

Our objective was to develop and test a new concept (affinity) analogous to multimorbidity of chronic conditions for individuals at census tract level in Memphis, TN. The use of affinity will improve the surveillance of multiple chronic conditions and facilitate the design of effective interventions.

Methods

We used publicly available chronic condition data (Center for Disease Control and Prevention 500 Cities project), socio-demographic data (US Census Bureau), and demographics data (Environmental Systems Research Institute). We examined the geographic pattern of the affinity of chronic conditions using global Moran’s I and Getis-Ord Gi* statistics and its association with socio-economic disadvantage (poverty, unemployment, and crime) using robust regression models. We also used the most common behavioral factor, smoking, and other demographic factors (percent of the male population, percent of the population 67 years, and over and total population size) as control variables in the model.

Results

A geo-distinctive pattern of clustered chronic affinity associated with socio-economic deprivation was observed. Statistical results confirmed that neighborhoods with higher rates of crime, poverty, and unemployment were associated with an increased likelihood of having a higher affinity among major chronic conditions. With the inclusion of smoking in the model, however, only the crime prevalence was statistically significantly associated with the chronic affinity.

Conclusion

Chronic affinity disadvantages were disproportionately accumulated in socially disadvantaged areas. We showed links between commonly co-observed chronic diseases at the population level and systematically explored the complexity of affinity and socio-economic disparities. Our affinity score, based on publicly available datasets, served as a surrogate for multimorbidity at the population level, which may assist policymakers and public health planners to identify urgent hot spots for chronic disease and allocate clinical, medical and healthcare resources efficiently.

Early-life inequalities and biological ageing: a multisystem Biological Health Score approach in UnderstandingSociety

Social position is known to play a role in the quality of ageing, notably through the stimulation/dysregulation of key physiological systems in response to external stresses. Using data from one wave of Understanding Society including 9088 participants, we defined, as an extension of the allostatic load, a synthetic Biological Health Score (BHS) capturing the wear-and-tear of four physiological systems (endocrine, inflammatory, cardiovascular and metabolic systems) and two organs (liver and kidney). We used 16 established blood-derived biomarkers of these systems to calculate the BHS and explored the relative contribution of socioeconomic position to the BHS and its main components across age groups. We identified a systematic decreasing education-related gradient of the BHS (p<0.001) leading to lower biological risk in participants with longer education. Education-related differences in the BHS were detected early in life, and were not attributable to lifestyle and behavioural factors. We found a consistent contribution of the inflammatory and metabolic systems to the overall score throughout from early adulthood onwards, while the contribution of the other four systems seems to vary across age groups and gender. Our findings highlight the social-to-biological processes ultimately leading to health inequalities, and suggest that such disparities can already be detected in the 20-40 years old age group and cannot be fully explained by lifestyle and behavioural factors. This may define early adulthood social condition as a precursor to accelerated biological ageing and as an important target for public health policies.

Cortisol and Racial Health Disparities Affecting Black Men in Later Life: Evidence From MIDUS II

In the United States, Black men have poorer overall health and shorter life spans than most other racial/ethnic groups of men, largely attributable to chronic health conditions. Dysregulated patterns of daily cortisol, an indicator of hypothalamic-pituitary-adrenal (HPA) axis stress-response functioning, are linked to poor health outcomes. Questions remain regarding whether and how cortisol contributes to Black-White differences in men's health. This exploratory study compared early day changes in cortisol levels (diurnal cortisol slopes from peak to pre-lunch levels) and their associations with medical morbidity (number of chronic medical conditions) and psychological distress (Negative Affect Scale) among 695 Black and White male participants in the National Survey of Midlife in the United States (MIDUS II, 2004-2009). Black men exhibited blunted cortisol slopes relative to White men (-.15 vs. -.21, t = -2.97, p = .004). Cortisol slopes were associated with medical morbidity among Black men (b = .050, t = 3.85, p < .001), but not White men, and were unrelated to psychological distress in both groups. Findings indicate cortisol may contribute to racial health disparities among men through two pathways, including the novel finding that Black men may be more vulnerable to some negative health outcomes linked to cortisol. Further, results suggest that while cortisol may be a mechanism of physical health outcomes and disparities among older men, it may be less important for their emotional health. This study increases understanding of how race and male sex intersect to affect not only men's lived experiences but also their biological processes to contribute to racial health disparities among men in later life.

Health and Disease-Emergent States Resulting From Adaptive Social and Biological Network Interactions

Health is an adaptive state unique to each person. This subjective state must be distinguished from the objective state of disease. The experience of health and illness (or poor health) can occur both in the absence and presence of objective disease. Given that the subjective experience of health, as well as the finding of objective disease in the community, follow a Pareto distribution, the following questions arise: What are the processes that allow the emergence of four observable states-(1) subjective health in the absence of objective disease, (2) subjective health in the presence of objective disease, (3) illness in the absence of objective disease, and (4) illness in the presence of objective disease? If we consider each individual as a unique biological system, these four health states must emerge from physiological network structures and personal behaviors. The underlying physiological mechanisms primarily arise from the dynamics of external environmental and internal patho/physiological stimuli, which activate regulatory systems including the hypothalamic-pituitary-adrenal axis and autonomic nervous system. Together with other systems, they enable feedback interactions between all of the person's system domains and impact on his system's entropy. These interactions affect individual behaviors, emotional, and cognitive responses, as well as molecular, cellular, and organ system level functions. This paper explores the hypothesis that health is an emergent state that arises from hierarchical network interactions between a person's external environment and internal physiology. As a result, the concept of health synthesizes available qualitative and quantitative evidence of interdependencies and constraints that indicate its top-down and bottom-up causative mechanisms. Thus, to provide effective care, we must use strategies that combine person-centeredness with the scientific approaches that address the molecular network physiology, which together underpin health and disease. Moreover, we propose that good health can also be promoted by strengthening resilience and self-efficacy at the personal and social level, and via cohesion at the population level. Understanding health as a state that is both individualized and that emerges from multi-scale interdependencies between microlevel physiological mechanisms of health and disease and macrolevel societal domains may provide the basis for a new public discourse for health service and health system redesign.

Functional disorders can also be explained through a non-reductionist application of network theory

A network structure explains why reductionism is not possible for mental illness, but the same argument applies for the somatic symptoms of functional disorders. Because the covariation of symptoms of functional disorders cannot be explained in terms of symptom-to-symptom causality, explanation requires a network of biological mechanisms having emergent properties that cannot be reduced to biology.

Multimorbidity and functional impairment-bidirectional interplay, synergistic effects and common pathways

This review discusses the interplay between multimorbidity (i.e. co-occurrence of more than one chronic health condition in an individual) and functional impairment (i.e. limitations in mobility, strength or cognition that may eventually hamper a person's ability to perform everyday tasks). On the one hand, diseases belonging to common patterns of multimorbidity may interact, curtailing compensatory mechanisms and resulting in physical and cognitive decline. On the other hand, physical and cognitive impairment impact the severity and burden of multimorbidity, contributing to the establishment of a vicious circle. The circle may be further exacerbated by people's reduced ability to cope with treatment and care burden and physicians' fragmented view of health problems, which cause suboptimal use of health services and reduced quality of life and survival. Thus, the synergistic effects of medical diagnoses and functional status in adults, particularly older adults, emerge as central to assessing their health and care needs. Furthermore, common pathways seem to underlie multimorbidity, functional impairment and their interplay. For example, older age, obesity, involuntary weight loss and sedentarism can accelerate damage accumulation in organs and physiological systems by fostering inflammatory status. Inappropriate use or overuse of specific medications and drug-drug and drug-disease interactions also contribute to the bidirectional association between multimorbidity and functional impairment. Additionally, psychosocial factors such as low socioeconomic status and the direct or indirect effects of negative life events, weak social networks and an external locus of control may underlie the complex interactions between multimorbidity, functional decline and negative outcomes. Identifying modifiable risk factors and pathways common to multimorbidity and functional impairment could aid in the design of interventions to delay, prevent or alleviate age-related health deterioration; this review provides an overview of knowledge gaps and future directions.

Are big data analytics helpful in caring for multimorbid patients in general practice? - A scoping review

BACKGROUND

The treatment of multimorbid patients is one crucial task in general practice as multimorbidity is highly prevalent in this setting. However, there is little evidence how to treat these patients and consequently there are but a few guidelines that focus primarily on multimorbidity. Big data analytics are defined as a method that obtains results for high volume data with high variety generated at high velocity. Yet, the explanatory power of these results is not completely understood. Nevertheless, addressing multimorbidity as a complex condition might be a promising field for big data analytics. The aim of this scoping review was to evaluate whether applying big data analytics on patient data does already contribute to the treatment of multimorbid patients in general practice.

METHODS

In January 2018, a review searching the databases PubMed, The Cochrane Library, and Web of Science, using defined search terms for "big data analytics" and "multimorbidity", supplemented by a search of grey literature with Google Scholar, was conducted. Studies were not filtered by type of study, publication year or language. Validity of studies was evaluated independently by two researchers.

RESULTS

In total, 2392 records were identified for screening. After title and abstract screening, six articles were included in the full-text analysis. Of those articles, one reported on a model generated with big data techniques to help caring for one group of multimorbid patients. The other five articles dealt with the analysis of multimorbidity clusters. No article defined big data analytics explicitly.

CONCLUSIONS

Although the usage of the phrase "Big Data" is growing rapidly, there is nearly no practical use case for big data analysis techniques in the treatment of multimorbidity in general practice yet. Furthermore, in publications addressing big data analytics, the term is rarely defined. However, possible models and algorithms to address multimorbidity in the future are already published.

What matters in "multimorbidity"? Arguably resilience and personal health experience are central to quality of life and optimizing survival

RATIONALE

Much is written about "multimorbidity" as it is a difficult problem for health systems, as it reflects a complex phenomenon unique to each individual health journey and health service context. This paper proposes the adoption of 2 constructs or knowledge streams into mainstream "multimorbidity" care which are arguably most important to person-centered care-personal health perceptions and resilience.

ANALYSIS

"Multimorbidity" is the manifestation of multiple nonlinear physical, psychosocial, and environmental phenomena in an individual health journey. Multimorbidity encompasses very stable states for the most part together with highly unstable phases that are difficult to manage. Averting or controlling the underlying loss of resilience in instability can be challenging without early warning signals pointing towards tipping points. Monitoring resilience and early warning signals for tipping points is new to health care. Yet what should we monitor in the complexity of multimorbidity? There are multiple and competing health service features and biometrics that can be measured. However, an expanding of literature endorses importance of simply asking a person about their self-rated health in order to provide predictions of their resilience and survival. Interoception, exemplified as self-rated health, arises from internal neurocognitive self-monitoring functions of different internal and external phenomena. Interoception is being to be recognized as predictors and barometers of resilience and survival.

CONCLUSIONS

Two phenomena of human systems-interoception and resilience-can guide care in the complex nature of multimorbidity in unstable health journeys and should be incorporated into clinical practice.

Advanced serious illness, multimorbidity, and multibeneficence: The role of communication

Sturmberg et al write about multimorbidity as "several diagnosable diseases within the same individual." They posit that this syndrome is the result of multiple interconnected disturbances reflecting scale-free, fractal signs of pathology ranging from biochemical/hormonal alterations at one end of a spectrum to community and societal ills at the other. In this commentary, I will be focusing on 3 perspectives: 1) a preterminal phase of multimorbidity that is indicative of that loss of reparative or even homeokinetic properties, known by some as "advanced serious illness"; 2) the manifestations of advanced serious illness multimorbidity that, using the same networks that connect into the patient, are signs of this syndrome at the levels of the immediate family/friend social network, the broader community, and society at large; and 3) the potential for these same networks that transmit pathological forces to convey the positive effects of therapeutic interventions in a scale-free manner, with a focus on how conversation can lead to what I'm calling "multibeneficence."