Multimorbidity Trends in United States Adults, 1988-2014

Personalized (N-of-1) Trials for Patient-Centered Treatments of Multimorbidity

Treatment of patients who suffer from concurrent health conditions is not well served by (1) evidence-based clinical guidelines that mainly specify treatment of single conditions and (2) conventional randomized controlled trials (RCTs) that identify treatments as safe and effective on average. Clinical decision-making based on the average patient effect may be inappropriate for treatment of those with multimorbidity who experience burdens and obstacles that may be unique to their personal situation. We describe how the personalized (N-of-1) trials can be integrated with an automatic platform and virtual/remote technologies to improve patient-centered care for those living with multimorbidity. To illustrate, we present a hypothetical clinical scenario-survivors of both coronavirus disease 2019 (COVID-19) and cancer who chronically suffer from sleeplessness and fatigue. Then, we will describe how the four standard phases of conventional RCT development can be modified for personalized trials and applied to the multimorbidity clinical scenario, outline how personalized trials can be adapted and extended to compare the benefits of personalized trials versus between-subject trial design, and explain how personalized trials can address special problems associated with multimorbidity for which conventional trials are poorly suited.

What is the impact of multimorbidity on out-of-pocket healthcare expenditure among community-dwelling older adults in Ireland? A cross-sectional study

OBJECTIVES

Individuals with multimorbidity use more health services and take more medicines. This can lead to high out-of-pocket (OOP) healthcare expenditure. This study, therefore, aimed to assess the association between multimorbidity (two or more chronic conditions) and OOP healthcare expenditure in a nationally representative sample of adults aged 50 years or over.

DESIGN

Cross-sectional analysis of data collected in 2016 from wave 4 of The Irish Longitudinal Study on Ageing.SettingIreland.ParticipantsCommunity-dwelling adults aged 50 years and over.MethodA generalised linear model with log-link and gamma distributed errors was fitted to assess the association between multimorbidity and OOP healthcare expenditure (including general practitioner, emergency department, outpatients, specialist consultations, hospital admissions, home care and prescription drugs).

RESULTS

Overall, 3453 (58.5%) participants had multimorbidity. Among those with any OOP healthcare expenditure, individuals with multimorbidity spent more on average per annum (€806.8 for two conditions, €885.8 for three or more conditions), than individuals with no conditions (€580.3). Pharmacy-dispensed medicine expenditure was the largest component of expenditure. People with multimorbidity on average spent more of their equivalised household income on healthcare (7.1% for two conditions, 9.7% for three or more conditions), than people with no conditions (5.0%). A strong positive association was found between number of conditions and OOP healthcare expenditure (p<0.001) and between having private health insurance and OOP healthcare expenditure (p<0.001). A strong negative association was found between eligibility for free primary/hospital care and heavily subsidised medicines and OOP healthcare expenditure (p<0.001).

CONCLUSIONS

This study suggests that having multimorbidity in Ireland increases OOP healthcare expenditure, which is problematic for those with more conditions who have lower incomes. This highlights the need for this financial burden to be considered when designing healthcare/funding systems to address multimorbidity, so that access to essential healthcare can be maximised for those with greatest need.

Temporal Trends in Racial and Ethnic Disparities in Multimorbidity Prevalence in the United States, 1999-2018

BACKGROUND

Disparities in multimorbidity prevalence indicate health inequalities, as the risk of morbidity does not intrinsically differ by race/ethnicity. This study aimed to determine if multimorbidity differences by race/ethnicity are decreasing over time.

METHODS

Serial cross-sectional analysis of the National Health Interview Survey, 1999-2018. Included individuals were ≥18 years old and categorized by self-reported race, ethnicity, age, and income. The main outcomes were temporal trends in multimorbidity prevalence based on the self-reported presence of ≥2 of 9 common chronic conditions.

FINDINGS

The study sample included 596,355 individuals (4.7% Asian, 11.8% Black, 13.8% Latino/Hispanic, and 69.7% White). In 1999, the estimated prevalence of multimorbidity was 5.9% among Asian, 17.4% among Black, 10.7% among Latino/Hispanic, and 13.5% among White individuals. Prevalence increased for all racial/ethnic groups during the study period (P ≤ .001 for each), with no significant change in the differences between them. In 2018, compared with White individuals, multimorbidity was more prevalent among Black individuals (+2.5 percentage points) and less prevalent among Asian and Latino/Hispanic individuals (-6.6 and -2.1 percentage points, respectively). Among those aged ≥30 years, Black individuals had multimorbidity prevalence equivalent to that of Latino/Hispanic and White individuals aged 5 years older, and Asian individuals aged 10 years older.

CONCLUSIONS

From 1999 to 2018, a period of increasing multimorbidity prevalence for all the groups studied, there was no significant progress in eliminating disparities between Black individuals and White individuals. Public health interventions that prevent the onset of chronic conditions in early life may be needed to eliminate these disparities.

Team-Based Care for Cancer Survivors With Comorbidities: A Systematic Review

Coordination of quality care for the growing population of cancer survivors with comorbidities remains poorly understood, especially among health disparity populations who are more likely to have comorbidities at the time of cancer diagnosis. This systematic review synthesized the literature from 2000 to 2022 on team-based care for cancer survivors with comorbidities and assessed team-based care conceptualization, teamwork processes, and outcomes. Six databases were searched for original articles on adults with cancer and comorbidity, which defined care team composition and comparison group, and assessed clinical or teamwork processes or outcomes. We identified 1,821 articles of which 13 met the inclusion criteria. Most studies occurred during active cancer treatment and nine focused on depression management. Four studies focused on Hispanic or Black cancer survivors and one recruited rural residents. The conceptualization of team-based care varied across articles. Teamwork processes were not explicitly measured, but teamwork concepts such as communication and mental models were mentioned. Despite team-based care being a cornerstone of quality cancer care, studies that simultaneously assessed care delivery and outcomes for cancer and comorbidities were largely absent. Improving care coordination will be key to addressing disparities and promoting health equity for cancer survivors with comorbidities.

Emerging approaches to multiple chronic condition assessment

Older adults experience a higher prevalence of multiple chronic conditions (MCCs). Establishing the presence and pattern of MCCs in individuals or populations is important for healthcare delivery, research, and policy. This report describes four emerging approaches and discusses their potential applications for enhancing assessment, treatment, and policy for the aging population. The National Institutes of Health convened a 2-day panel workshop of experts in 2018. Four emerging models were identified by the panel, including classification and regression tree (CART), qualifying comorbidity sets (QCS), the multimorbidity index (MMI), and the application of omics to network medicine. Future research into models of multiple chronic condition assessment may improve understanding of the epidemiology, diagnosis, and treatment of older persons.

Associations between PFAS occurrence and multimorbidity as observed in an electronic health record cohort

Per and polyfluoroalkyl substances (PFAS) are associated with health outcomes ranging from cancer to high cholesterol. However, there has been little examination of how PFAS exposure might impact the development of multiple chronic diseases, known as multimorbidity. Here, we associated the presence of one or more PFAS in water systems serving the zip code of residence with chronic disease and multimorbidity.

Can diverse population characteristics be leveraged in a machine learning pipeline to predict resource intensive healthcare utilization among hospital service areas?

Background

Super-utilizers represent approximately 5% of the population in the United States (U.S.) and yet they are responsible for over 50% of healthcare expenditures. Using characteristics of hospital service areas (HSAs) to predict utilization of resource intensive healthcare (RIHC) may offer a novel and actionable tool for identifying super-utilizer segments in the population. Consumer expenditures may offer additional value in predicting RIHC beyond typical population characteristics alone.

Methods

Cross-sectional data from 2017 was extracted from 5 unique sources. The outcome was RIHC and included emergency room (ER) visits, inpatient days, and hospital expenditures, all expressed as log per capita. Candidate predictors from 4 broad groups were used, including demographics, adults and child health characteristics, community characteristics, and consumer expenditures. Candidate predictors were expressed as per capita or per capita percent and were aggregated from zip-codes to HSAs using weighed means. Machine learning approaches (Random Forrest, LASSO) selected important features from nearly 1,000 available candidate predictors and used them to generate 4 distinct models, including non-regularized and LASSO regression, random forest, and gradient boosting. Candidate predictors from the best performing models, for each outcome, were used as independent variables in multiple linear regression models. Relative contribution of variables from each candidate predictor group to regression model fit were calculated.

Results

The median ER visits per capita was 0.482 [IQR:0.351–0.646], the median inpatient days per capita was 0.395 [IQR:0.214–0.806], and the median hospital expenditures per capita was $2,302 [1$,544.70-$3,469.80]. Using 1,106 variables, the test-set coefficient of determination (R²) from the best performing models ranged between 0.184–0.782. The adjusted R² values from multiple linear regression models ranged from 0.311–0.8293. Relative contribution of consumer expenditures to model fit ranged from 23.4–33.6%.

Discussion

Machine learning models predicted RIHC among HSAs using diverse population data, including novel consumer expenditures and provides an innovative tool to predict population-based healthcare utilization and expenditures. Geographic variation in utilization and spending were identified.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-022-08154-4.

Application of a TEG-Platelet Mapping Algorithm to Guide Reversal of Antiplatelet Agents in Adults with Mild-to-Moderate Traumatic Brain Injury: An Observational Pilot Study

BACKGROUND

Traumatic intracranial hemorrhages expand in one third of cases, and antiplatelet medications may exacerbate hematoma expansion. However, the reversal of an antiplatelet effect with platelet transfusion has been associated with harm. We sought to determine whether a thromboelastography platelet mapping (TEG-PM)-guided algorithm could limit platelet transfusion in patients with hemorrhagic traumatic brain injury (TBI) prescribed antiplatelet medications without a resultant clinically significant increase in hemorrhage volume, late hemostatic treatments, or delayed operative intervention.

METHODS

A total of 175 consecutive patients with TBI were admitted to our university-affiliated, level I trauma center between March 2016 and December 2019: 54 preintervention patients (control) and 121 patients with TEG-PM (study). After exclusion for anticoagulant administration, availability of neuroimaging and emergent neurosurgery, 62 study patients and 37 control patients remained. Intervention consisted of administration of desmopressin (DDAVP) for nonsurgical patients with significant inhibition at the arachidonic acid or adenosine diphosphate receptor sites. For surgical patients with significant inhibition, dual therapy with DDAVP and platelet transfusion was employed. Study patients were compared with a group of historical controls, which were identified from a prospectively maintained registry and typically treated with empiric platelet transfusion.

RESULTS

Median age was 75 years (interquartile range 85-67) and 77 years (interquartile range 81-65) in the TEG-PM and control patient groups, respectively. Admission hemorrhage volumes were similar (10.7 cm³ [20.1] in patients with TEG-PM vs. 14.1 cm³ [19.7] in controls; p = 0.41). There were no significant differences in admission Glasgow Coma Scale, mechanism of trauma, or baseline comorbidities. A total of 57% of controls versus 10% of patients with TEG-PM (p < 0.001) were transfused platelets; 52% of intervention patients and 0% controls were treated with DDAVP. Expansion hemorrhage volumes were not significantly different (14.0 cm³ [20.2] patients with TEG-PM versus 13.6 cm³ [23.7] controls; p = 0.93). There was no significant difference in rates of clinical deterioration, delayed neurosurgical intervention, or late platelet transfusion between groups.

CONCLUSIONS

Among patients with hemorrhagic TBI prescribed preinjury antiplatelet therapy, our study suggests that the use of a TEG-PM algorithm may reduce platelet transfusions without a concurrent increase in clinically significant hematoma expansion. Further study is required to prove a causative relationship.

Multimorbidity patterns across race/ethnicity as stratified by age and obesity

The objective of our study is to assess differences in prevalence of multimorbidity by race/ethnicity. We applied the FP-growth algorithm on middle-aged and elderly cohorts stratified by race/ethnicity, age, and obesity level. We used 2016–2017 data from the Cerner HealthFacts electronic health record data warehouse. We identified disease combinations that are shared by all races/ethnicities, those shared by some, and those that are unique to one group for each age/obesity level. Our findings demonstrate that even after stratifying by age and obesity, there are differences in multimorbidity prevalence across races/ethnicities. There are multimorbidity combinations distinct to some racial groups—many of which are understudied. Some multimorbidities are shared by some but not all races/ethnicities. African Americans presented with the most distinct multimorbidities at an earlier age. The identification of prevalent multimorbidity combinations amongst subpopulations provides information specific to their unique clinical needs.

The effect of disease co-occurrence measurement on multimorbidity networks: a population-based study

Background

Network analysis, a technique for describing relationships, can provide insights into patterns of co-occurring chronic health conditions. The effect that co-occurrence measurement has on disease network structure and resulting inferences has not been well studied. The purpose of the study was to compare structural differences among multimorbidity networks constructed using different co-occurrence measures.

Methods

A retrospective cohort study was conducted using four fiscal years of administrative health data (2015/16 – 2018/19) from the province of Manitoba, Canada (population 1.5 million). Chronic conditions were identified using diagnosis codes from electronic records of physician visits, surgeries, and inpatient hospitalizations, and grouped into categories using the Johns Hopkins Adjusted Clinical Group (ACG) System. Pairwise disease networks were separately constructed using each of seven co-occurrence measures: lift, relative risk, phi, Jaccard, cosine, Kulczynski, and joint prevalence. Centrality analysis was limited to the top 20 central nodes, with degree centrality used to identify potentially influential chronic conditions. Community detection was used to identify disease clusters. Similarities in community structure between networks was measured using the adjusted Rand index (ARI). Network edges were described using disease prevalence categorized as low (< 1%), moderate (1 to < 7%), and high (≥7%). Network complexity was measured using network density and frequencies of nodes and edges.

Results

Relative risk and lift highlighted co-occurrences between pairs of low prevalence health conditions. Kulczynski emphasized relationships between high and low prevalence conditions. Joint prevalence focused on highly-prevalent conditions. Phi, Jaccard, and cosine emphasized associations involving moderately prevalent conditions. Co-occurrence measurement differences significantly affected the number and structure of identified disease clusters. When limiting the number of edges to produce visually interpretable graphs, networks had significant dissimilarity in the percentage of co-occurrence relationships in common, and in their selection of the highest-degree nodes.

Conclusions

Multimorbidity network analyses are sensitive to disease co-occurrence measurement. Co-occurrence measures should be selected considering their intrinsic properties, research objectives, and the health condition prevalence relationships of greatest interest. Researchers should consider conducting sensitivity analyses using different co-occurrence measures.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-022-01607-8.

Developing a Medication Self-management Program to Enhance Medication Adherence among Older Adults with Multimorbidity Using Intervention Mapping

BACKGROUND AND OBJECTIVES

Suboptimal medication adherence is prevalent in older adults with multimorbidity. However, intervention programs for enhancing adherence in this population are limited. This study describes the development process of a medication self-management program for older adults with multimorbidity.

RESEARCH DESIGN AND METHODS

We adopted the first four steps of the Intervention Mapping to develop the program: (1) needs assessment, including a literature review, a systematic review, and a cross-sectional study, (2) development of program outcomes and objectives, (3) selection of theory-based intervention methods and practical applications, and (4) development of the program.

RESULTS

We conducted a needs assessment to identify factors affecting medication adherence among older adults with multimorbidity and created a logic model of the adherence problem in Step 1. In Step 2, we developed the specific program outcomes and objectives and then selected adherence information, personal motivation, social motivation, behavioral skills, and treatment experiences as modifiable and important targets that needed to change in this program. In Step 3, we chose several theory-based methods and strategies for practical applications. We finally created a nurse-led medication self-management program in Step 4. Feedback from relevant stakeholders refined the intervention protocol and materials.

DISCUSSION AND IMPLICATIONS

The newly developed medication self-management program incorporated theory and evidence from literature and empirical studies with the engagement of multiple stakeholders, making it a contextually and culturally appropriate intervention. This study provides insights into strategies for geriatrics healthcare professionals to support medication self-management among older adults with multimorbidity.

Trend in Blood Pressure Control Post Antihypertensive Drug Initiation in the U.S

INTRODUCTION

The aim of this study is to evaluate the temporal trends in systolic blood pressure control over 18 months after blood pressure‒lowering drug initiation in the U.S.

METHODS

From U.S. nationally representative electronic health records, 1,036,775 adults initiating and continuing blood pressure‒lowering drugs for ≥18 months during 2006-2018 were identified (January 2021). Prevalence trends of cardiovascular disease, diabetes, and depression at blood pressure‒lowering drug initiation, blood pressure‒lowering drug therapy intensification over 18 months, and the adjusted probability of achieving systolic blood pressure control 6 months after baseline and sustaining the control for over 18 months were evaluated.

RESULTS

At blood pressure‒lowering drug initiation, the prevalence of diabetes and depression consistently increased during the study period across all age groups, particularly in those aged 18-49 years, whereas the prevalence of cardiovascular disease was stable. Adjusted probabilities of achieving sustainable systolic blood pressure control by age group were 0.62 (95% CI=0.61, 0.63) for ages 18-39 years, 0.55 (95% CI=0.55, 0.56) for ages 40-49 years, 0.50 (95% CI=0.49, 0.50) for ages 50-59 years, 0.43 (95% CI=0.42, 0.43) for ages 60-69 years, and 0.37 (95% CI=0.37, 0.38) for ages 70-80 years. Those with cardiovascular disease or cardiovascular disease and diabetes had approximately 20% lower adjusted probability of achieving systolic blood pressure control (31%/29%) than those without these conditions (52%, p<0.01). Those with depression had a 4% higher probability of systolic blood pressure control than those without the condition (49% vs 45%, p<0.01).

CONCLUSIONS

In the U.S., only 30%-50% of the population are achieving sustainable blood pressure control over 18 months after blood pressure‒lowering drug initiation, with no indication of improvement in control over the last decade.

The importance of chronic conditions for potentially avoidable hospitalizations among non-Hispanic Black and non-Hispanic White older adults in the US: a cross-sectional observational study

Background

Non-Hispanic (NH) Black older adults experience substantially higher rates of potentially avoidable hospitalization compared to NH White older adults. This study explores the top three chronic conditions preceding hospitalization and potentially avoidable hospitalization among NH White and NH Black Medicare beneficiaries in the United States.

Methods

Data on 4993 individuals (4,420 NH White and 573 NH Black individuals) aged ≥ 65 years from 2014 Medicare claims were linked with sociodemographic data from previous rounds of the Health and Retirement Study. Conditional inference random forests were used to rank the importance of chronic conditions in predicting hospitalization and potentially avoidable hospitalization separately for NH White and NH Black beneficiaries. Multivariable logistic regression with the top three chronic diseases for each outcome adjusted for sociodemographic characteristics were conducted to quantify the associations.

Results

In total, 22.1% of NH White and 24.9% of NH Black beneficiaries had at least one hospitalization during 2014. Among those with hospitalization, 21.3% of NH White and 29.6% of NH Black beneficiaries experienced at least one potentially avoidable hospitalization. For hospitalizations, chronic kidney disease, heart failure, and atrial fibrillation were the top three contributors among NH White beneficiaries and acute myocardial infarction, chronic obstructive pulmonary disease (COPD), and chronic kidney disease were the top three contributors among NH Black beneficiaries. These chronic conditions were associated with increased odds of hospitalization for both groups. For potentially avoidable hospitalizations, asthma, COPD, and heart failure were the top three contributors among NH White beneficiaries and fibromyalgia/chronic pain/fatigue, COPD, and asthma were the top three contributors among NH Black beneficiaries. COPD and heart failure were associated with increased odds of potentially avoidable hospitalization among NH White beneficiaries, whereas only COPD was associated with increased odds of potentially avoidable hospitalizations among NH Black beneficiaries.

Conclusion

Having at least one hospitalization and at least one potentially avoidable hospitalization was more prevalent among NH Black than NH White Medicare beneficiaries. This suggests greater opportunity for increasing prevention efforts among NH Black beneficiaries. The importance of COPD for potentially avoidable hospitalizations further highlights the need to focus on prevention of exacerbations for patients with COPD, possibly through greater access to primary care and continuity of care.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-022-07849-y.

Trends of Multimorbidity Patterns over 16 Years in Older Taiwanese People and Their Relationship to Mortality

Understanding multimorbidity patterns is important in finding a common etiology and developing prevention strategies. Our aim was to identify the multimorbidity patterns of Taiwanese people aged over 50 years and to explore their relationship with health outcomes. This longitudinal cohort study used data from the Taiwan Longitudinal Study on Aging. The data were obtained from wave 3, and the multimorbidity patterns in 1996, 1999, 2003, 2007, and 2011 were analyzed separately by latent class analysis (LCA). The association between each disease group and mortality was examined using logistic regression. Four disease patterns were identified in 1996, namely, the cardiometabolic (18.57%), arthritis–cataract (15.61%), relatively healthy (58.92%), and multimorbidity (6.9%) groups. These disease groups remained similar in the following years. After adjusting all the confounders, the cardiometabolic group showed the highest risk for mortality (odds ratio: 1.237, 95% confidence interval: 1.040–1.472). This longitudinal study reveals the trend of multimorbidity among older adults in Taiwan for 16 years. Older adults with a cardiometabolic multimorbidity pattern had a dismal outcome. Thus, healthcare professionals should put more emphasis on the prevention and identification of cardiometabolic multimorbidity.

Impact of prenatal and childhood adversity effects around World War II on multimorbidity: results from the KORA-Age study

Background

While risk factors for age-related diseases may increase multimorbidity (MM), early life deprivation may also accelerate the development of chronic diseases and MM.

Methods

This study explores the prevalence and pattern of MM in 65–71 year-old individuals born before, during, and after World War II in Southern Germany based on two large cross-sectional KORA (Cooperative Health Research in the Region of Augsburg) -Age studies in 2008/9 and 2016. MM was defined as having at least two chronic diseases, and birth periods were classified into five phases: pre-war, early war, late war, famine, and after the famine period. Logistic regression models were used to analyze the effect of the birth phases on MM with adjustment for sociodemographic and lifestyle risk factors. Furthermore, we used agglomerative hierarchical clustering to investigate the co-occurrence of diseases.

Results

Participants born during the late war phase had the highest prevalence of MM (62.2%) and single chronic diseases compared to participants born during the other phases. Being born in the late war phase was significantly associated with a higher odds of MM (OR = 1.83, 95% CI: 1.15–2.91) after adjustment for sociodemographic and lifestyle factors. In women, the prevalence of joint, gastrointestinal, eye diseases, and anxiety was higher, while heart disease, stroke, and diabetes were more common in men. Moreover, three main chronic disease clusters responsible for the observed associations were identified as: joint and psychosomatic, cardiometabolic and, other internal organ diseases.

Conclusions

Our findings imply that adverse early-life exposure may increase the risk of MM in adults aged 65–71 years. Moreover, identified disease clusters are not coincidental and require more investigation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-022-02793-2.

Multimorbidity Accumulation Among Middle-Aged Americans: Differences by Race/Ethnicity and Body Mass Index

BACKGROUND

Obesity and multimorbidity are more prevalent among U.S. racial/ethnic minority groups. Evaluating racial/ethnic disparities in disease accumulation according to body mass index (BMI) may guide interventions to reduce multimorbidity burden in vulnerable racial/ethnic groups.

METHOD

We used data from the 1998-2016 Health and Retirement Study on 8 106 participants aged 51-55 at baseline. Disease burden and multimorbidity (≥2 co-occurring diseases) were assessed using 7 chronic diseases: arthritis, cancer, heart disease, diabetes, hypertension, lung disease, and stroke. Four BMI categories were defined per convention: normal, overweight, obese class 1, and obese class 2/3. Generalized estimating equations models with inverse probability weights estimated the accumulation of chronic diseases.

RESULTS

Overweight and obesity were more prevalent in non-Hispanic Black (82.3%) and Hispanic (78.9%) than non-Hispanic White (70.9 %) participants at baseline. The baseline burden of disease was similar across BMI categories, but disease accumulation was faster in the obese class 2/3 and marginally in the obese class 1 categories compared with normal BMI. Black participants across BMI categories had a higher initial burden and faster accumulation of disease over time, while Hispanics had a lower initial burden and similar rate of accumulation, compared with Whites. Black participants, including those with normal BMI, reach the multimorbidity threshold 5-6 years earlier compared with White participants.

CONCLUSIONS

Controlling weight and reducing obesity early in the lifecourse may slow the progression of multimorbidity in later life. Further investigations are needed to identify the factors responsible for the early and progressing nature of multimorbidity in Blacks of nonobese weight.

The relationship between multimorbidity, obesity and functional impairment in older adults

BACKGROUND

Declining mortality rates and an aging population have contributed to increasing rates of multimorbidity (MM) in the United States. MM is strongly associated with a decline in physical function. Obesity is an important risk factor for the development of MM, and its prevalence continues to rise. Our study aimed to evaluate the associations between obesity, MM, and rates of functional limitations in older adults.

METHODS

We analyzed body mass index (BMI) and self-reported comorbidity data from 7261 individuals aged ≥60 years from the National Health and Nutrition Examination Surveys 2005-2014. Weight status was defined based on standard BMI categories. MM was defined as 2 or more comorbidities, while functional limitations were self-reported. Adjusted logistic regression quantified the association between standard BMI categories and MM. We also examined the difference in the prevalence of limitations between those with and without MM.

RESULTS

The overall proportion of individuals with concomitant MM and obesity was 27.0%. Compared to a normal BMI, older adults with obesity had higher odds of MM (Prevalence odds ratio 1.79, 95% CI 1.49, 2.12). Overall, 67.5% of patients with MM also reported a functional limitation, with rates of functional limitation increasing with increasing BMI. When evaluating functional limitations in those with MM by BMI class, 90% of patients classified as severely obese (BMI ≥40 kg/m² ) with MM also had a concomitant functional limitation.

CONCLUSIONS

Compared to normal weight status, obesity is associated with an increased burden of MM and functional limitation among older adults. Our results underscore the importance of identifying and addressing obesity, MM, and functional limitation patterns and the need for evidence-based interventions that address all three conditions in this population.

The 5Ms of Geriatrics in Gastroenterology: The Path to Creating Age-Friendly Care for Older Adults With Inflammatory Bowel Diseases and Cirrhosis

The number of Americans 65 years or older in 2060 will be more than double what it was in 2014. Approximately 40% of patients seen in gastroenterology (GI) and hepatology practices in the United States are 60 years or older. Adapting care delivery models, curating data on shifting risk-benefit decisions with geriatric syndromes, understanding appropriate assessments, and focusing on tailored implementation strategies are challenges that are actively confronting us as we provide care for a burgeoning population of older adults. Limited availability of geriatric specialists results in an onus of specialists caring for older adults, such as gastroenterologists, to innovate and develop tailored, comprehensive, and evidence-based care for adults in later life stages. In this article, we present the 5M framework from geriatrics to achieve age-friendly healthcare. The 5Ms are medications, mind, mobility, multicomplexity, and what matters most. We apply the 5M framework to 2 chronic conditions commonly encountered in clinical GI practice: inflammatory bowel diseases and cirrhosis. We highlight knowledge gaps and outline future directions to expand evidence-based care and advance the creation of age-friendly GI care.

Cultivating informatics capacity for multimorbidity: A learning health systems use case

Background

The aim of this study was to characterize patterns of multimorbidity across patients and identify opportunities to strengthen the informatics capacity of learning health systems that are used to characterize multimorbidity across patients.

Methods

Electronic health record (EHR) data on 225,710 multimorbidity patients were extracted from the Arkansas Clinical Data Repository as a use case. Hierarchical cluster analysis identified the most frequently occurring combinations of chronic conditions within the learning health system’s captured data.

Results

Results revealed multimorbidity was highest among patients ages 60 to 74, Caucasians, females, and Medicare payors. The largest numbers of chronic conditions occurred in the smallest numbers of patients (i.e., 70,262 (31%) patients with two conditions, two (<1%) patients with 22 chronic conditions). The results revealed urgent needs to improve EHR systems and processes that collect and manage multimorbidity data (e.g., creating new, multimorbidity-centric data elements in EHR systems, detailed longitudinal tracking of compounding disease diagnoses).

Conclusions

Without additional capacity to collect and aggregate large-scale data, multimorbidity patients cannot benefit from the recent advancements in informatics (i.e., clinical data registries, emerging data standards) that are abundantly working to improve the outcomes of patients with single chronic conditions. Additionally, robust socio-technical system studies of clinical workflows are needed to assess the feasibility of integrating the collection of risk factor data elements (i.e., psycho-social, cultural, ethnic, and socioeconomic attributes of populations) into primary care encounters. These approaches to advancing learning health systems for multimorbidity could substantially reduce the constraints of current technologies, data, and data-capturing processes.

COVID-19 pandemic and weight gain in American adults: A nationwide population-based study

BACKGROUND

The COVID-19 pandemic has affected the lives of people in many ways. However, little is known about weight gain in American adults during the pandemic.

AIMS AND METHODS

The purpose of this study was to conduct a national assessment of weight gain in adult Americans after the first year of the pandemic. An online questionnaire was employed to explore perceptions of adults regarding pandemic weight gain and the relationship between weight gain and sociodemographic characteristics, pre-pandemic weight status, and psychological distress. Multiple methods were used to assess the psychometric properties of the questionnaire (i.e., face validity, content validity, and internal consistency reliability testing). Chi-Square tests and logistic regression analysis were used to assess group differences and predictors of weight gain in the study participants.

RESULTS

A total of 3,473 individuals participated in the study with weight changes distributed as: gained weight (48%), remained the same weight (34%), or lost weight (18%). Those who reported being very overweight before the pandemic were most likely to gain weight (65%) versus those who reported being slightly overweight (58%) or normal weight (40%) before the pandemic. Weight gain was statistically significantly higher in those with anxiety (53%), depression (52%), or symptoms of both (52%). The final multiple regression model found that the statistically significant predictors of pandemic weight gain were psychological distress, pre-pandemic weight status, having children at home; and time since last bodyweight check.

CONCLUSIONS

Population health promotion strategies in the pandemic should emphasize stress reduction to help individuals manage body weight and avoid chronic diseases in the future.

Using Geriatric Assessment to Guide Conversations Regarding Comorbidities Among Older Patients With Advanced Cancer

PURPOSE

Older patients with advanced cancer often have comorbidities that can worsen their cancer and treatment outcomes. We assessed how a geriatric assessment (GA)-guided intervention can guide conversations about comorbidities among patients, oncologists, and caregivers.

METHODS

This secondary analysis arose from a nationwide, multisite cluster-randomized trial (ClinicalTrials.gov identifier: NCT02107443). Eligible patients were ≥ 70 years, had advanced cancer (solid tumors or lymphoma), and had impairment in at least one GA domain (not including polypharmacy). Oncology practices (n = 30) were randomly assigned to usual care or intervention. All patients completed a GA; in the intervention arm, a GA summary with recommendations was provided to their oncologist. Patients completed an Older Americans Resources and Services Comorbidity questionnaire at screening. The clinical encounter following GA was audio-recorded, transcribed, and coded for topics related to comorbidities. Linear mixed models examined the effect of the intervention on the outcomes adjusting for practice site as a random effect.

RESULTS

Patients (N = 541) were 76.6 ± 5.2 years old; 94.6% of patients had at least one comorbidity with an average of 3.2 ± 1.9. The intervention increased the average number of conversations regarding comorbidities per patient from 0.52 to 0.99 (P < .01). Moreover, there were a greater number of concerns acknowledged (0.52 v 0.32; P = .03) and there was a 2.4-times higher odds of having comorbidity concerns addressed via referral, handout, or other modes (95% CI, 1.3 to 4.3; P = .004). Most oncologists in the intervention arm (76%) discussed comorbidities in light of the treatment plan, and 41% tailored treatment plans.

CONCLUSION

Providing oncologists with a GA-guided intervention enhanced communication regarding comorbidities.

Multimorbidity and healthcare utilization among Black Americans: A cross-sectional study

Aim

Racial disparities between multimorbidity presence and healthcare utilization are present within the United States, but less is known about the relationship between multimorbidity presence and healthcare utilization among Black Americans. This study was conducted to examine the relationship between multimorbidity and healthcare utilization among Black Americans.

Design

Cross‐sectional study.

Methods

This study (n = 425, 57% female) used adult level data from the 2012–2013 Connecticut Health Care Survey.

Results

Multivariate logistic regressions indicated that multimorbidity presence predicted a doctor and a specialist visit, but not a dentist visit.

Conclusion

This study identified multimorbidity presence as a predictor for healthcare utilization, but further research is necessary to understand healthcare utilization experiences among Black Americans with multimorbidity to assess the quality of care. Appropriate measures should also be considered to increase access to dental care for Black Americans with multimorbidity.

Developing the Total Health Profile, a Generalizable Unified Set of Multimorbidity Risk Scores Derived From Machine Learning for Broad Patient Populations: Retrospective Cohort Study

BACKGROUND

Multimorbidity clinical risk scores allow clinicians to quickly assess their patients' health for decision making, often for recommendation to care management programs. However, these scores are limited by several issues: existing multimorbidity scores (1) are generally limited to one data group (eg, diagnoses, labs) and may be missing vital information, (2) are usually limited to specific demographic groups (eg, age), and (3) do not formally provide any granularity in the form of more nuanced multimorbidity risk scores to direct clinician attention.

OBJECTIVE

Using diagnosis, lab, prescription, procedure, and demographic data from electronic health records (EHRs), we developed a physiologically diverse and generalizable set of multimorbidity risk scores.

METHODS

Using EHR data from a nationwide cohort of patients, we developed the total health profile, a set of six integrated risk scores reflecting five distinct organ systems and overall health. We selected the occurrence of an inpatient hospital visitation over a 2-year follow-up window, attributable to specific organ systems, as our risk endpoint. Using a physician-curated set of features, we trained six machine learning models on 794,294 patients to predict the calibrated probability of the aforementioned endpoint, producing risk scores for heart, lung, neuro, kidney, and digestive functions and a sixth score for combined risk. We evaluated the scores using a held-out test cohort of 198,574 patients.

RESULTS

Study patients closely matched national census averages, with a median age of 41 years, a median income of $66,829, and racial averages by zip code of 73.8% White, 5.9% Asian, and 11.9% African American. All models were well calibrated and demonstrated strong performance with areas under the receiver operating curve (AUROCs) of 0.83 for the total health score (THS), 0.89 for heart, 0.86 for lung, 0.84 for neuro, 0.90 for kidney, and 0.83 for digestive functions. There was consistent performance of this scoring system across sexes, diverse patient ages, and zip code income levels. Each model learned to generate predictions by focusing on appropriate clinically relevant patient features, such as heart-related hospitalizations and chronic hypertension diagnosis for the heart model. The THS outperformed the other commonly used multimorbidity scoring systems, specifically the Charlson Comorbidity Index (CCI) and the Elixhauser Comorbidity Index (ECI) overall (AUROCs: THS=0.823, CCI=0.735, ECI=0.649) as well as for every age, sex, and income bracket. Performance improvements were most pronounced for middle-aged and lower-income subgroups. Ablation tests using only diagnosis, prescription, social determinants of health, and lab feature groups, while retaining procedure-related features, showed that the combination of feature groups has the best predictive performance, though only marginally better than the diagnosis-only model on at-risk groups.

CONCLUSIONS

Massive retrospective EHR data sets have made it possible to use machine learning to build practical multimorbidity risk scores that are highly predictive, personalizable, intuitive to explain, and generalizable across diverse patient populations.

Microbiome First Approaches to Rescue Public Health and Reduce Human Suffering

The is a sequential article to an initial review suggesting that Microbiome First medical approaches to human health and wellness could both aid the fight against noncommunicable diseases and conditions (NCDs) and help to usher in sustainable healthcare. This current review article specifically focuses on public health programs and initiatives and what has been termed by medical journals as a catastrophic record of recent failures. Included in the review is a discussion of the four priority behavioral modifications (food choices, cessation of two drugs of abuse, and exercise) advocated by the World Health Organization as the way to stop the ongoing NCD epidemic. The lack of public health focus on the majority of cells and genes in the human superorganism, the microbiome, is highlighted as is the "regulatory gap" failure to protect humans, particularly the young, from a series of mass population toxic exposures (e.g., asbestos, trichloroethylene, dioxin, polychlorinated biphenyls, triclosan, bisphenol A and other plasticizers, polyfluorinated compounds, herbicides, food emulsifiers, high fructose corn syrup, certain nanoparticles, endocrine disruptors, and obesogens). The combination of early life toxicity for the microbiome and connected human physiological systems (e.g., immune, neurological), plus a lack of attention to the importance of microbial rebiosis has facilitated rather than suppressed, the NCD epidemic. This review article concludes with a call to place the microbiome first and foremost in public health initiatives as a way to both rescue public health effectiveness and reduce the human suffering connected to comorbid NCDs.

Health-Related Quality of Life: A Comparative Analysis of Caregivers of People With Dementia, Cancer, COPD/Emphysema, and Diabetes and Noncaregivers, 2015-2018 BRFSS

BACKGROUND

Many informal caregivers experience significant caregiving burden and report worsening health-related quality of life (HRQoL). Caregiver HRQoL may vary by disease context, but this has rarely been studied.

PURPOSE

Informed by the Model of Carer Stress and Burden, we compared HRQoL outcomes of prevalent groups of caregivers of people with chronic illness (i.e., dementia, cancer, chronic obstructive pulmonary disease [COPD]/emphysema, and diabetes) and noncaregivers and examined whether caregiving intensity (e.g., duration and hours) was associated with caregiver HRQoL.

METHODS

Using 2015-2018 Behavioral Risk Factor Surveillance System data, we identified caregivers of people with dementia (n = 4,513), cancer (n = 3,701), COPD/emphysema (n = 1,718), and diabetes (n = 2,504) and noncaregivers (n = 176,749). Regression analyses were used to compare groups.

RESULTS

Caregiver groups showed small, nonsignificant differences in HRQoL outcomes. Consistent with theory, all caregiver groups reported more mentally unhealthy days than noncaregivers (RRs = 1.29-1.61, ps < .001). Caregivers of people with cancer and COPD/emphysema reported more physically unhealthy days than noncaregivers (RRs = 1.17-1.24, ps < .01), and caregivers of people with diabetes reported a similar pattern (RR = 1.24, p = .01). However, general health and days of interference of poor health did not differ between caregivers and noncaregivers. Across caregiver groups, most caregiving intensity variables were unrelated to HRQoL outcomes; only greater caregiving hours were associated with more mentally unhealthy days (RR = 1.13, p < .001).

CONCLUSIONS

Results suggest that HRQoL decrements associated with caregiving do not vary substantially across chronic illness contexts and are largely unrelated to the perceived intensity of the caregiving. Findings support the development and implementation of strategies to optimize caregiver health across illness contexts.

Associations of multiple (≥5) chronic conditions among a nationally representative sample of older United States adults with self-reported pain

OBJECTIVES

The association between an individuals' demographic and health characteristics and the presence of multiple chronic conditions is not well known among older United States (US) adults. This study aimed to identify the prevalence and associations of having multiple chronic conditions among older US adults with self-reported pain.

METHODS

This retrospective, cross-sectional study used data from the 2017 Medical Expenditure Panel Survey. Study subjects were aged ≥50 years and had self-reported pain in the past four weeks. The outcome variable was multiple (≥5) chronic conditions (vs. <5 chronic conditions). Hierarchical logistic regression models were used to identify significant associations between demographic and health characteristics and multiple chronic conditions with significance indicated at an a priori alpha level of 0.05. The complex survey design was accounted for when obtaining nationally-representative estimates.

RESULTS

The weighted population was 57,074,842 US older adults with pain, of which, 66.1% had ≥5 chronic conditions. In fully-adjusted analyses, significant associations of ≥5 comorbid chronic conditions included: age 50-64 vs. ≥65 years (adjusted odds ratio [AOR]=0.478, 95% confidence interval [CI]=0.391, 0.584); male vs. female gender (AOR=1.271, 95% CI=1.063, 1.519); white vs. other race (AOR=1.220, 95% CI=1.016, 1.465); Hispanic vs. non-Hispanic ethnicity (AOR=0.614, 95% CI=0.475, 0.793); employed vs. unemployed (AOR=0.591, 95% CI=0.476, 0.733); functional limitations vs. no functional limitations (AOR=1.862, 95% CI=1.510, 2.298); work limitations vs. no work limitations (AOR=1.588, 95% CI=1.275, 1.976); little/moderate vs. quite a bit/extreme pain (AOR=0.732, 95% CI=0.599, 0.893); and excellent/very good (AOR=0.375, 95% CI=0.294, 0.480) or good (AOR=0.661, 95% CI=0.540, 0.810) vs. fair/poor physical health.

CONCLUSIONS

Approximately 38 million of the 57 million US older adults with pain in this study had ≥5 chronic conditions in 2017. Several characteristics were associated with multiple chronic conditions, which may be important for health care professionals to consider when working with patients to manage their pain. This study was approved by The University of Arizona Institutional Review Board (2006721124, June 12, 2020).

Minority Women

Perceptions of illness, pain, and death are not static. They vary among populations according to their cultural and biological characteristics. Older black and Hispanic/Latinx women are unique in their approach to health care with respect to mentation, mobility, medication adherence, and what matters to them. It is the complexity of these components, which affect the ability of these women to age gracefully.

The Associations between Asymmetric Handgrip Strength and Chronic Disease Status in American Adults: Results from the National Health and Nutrition Examination Survey

This study examined the associations between asymmetric handgrip strength (HGS) and multimorbidity in American adults. Secondary analyses of data from persons aged at least 40 years from the 2011-2012 and 2013-2014 waves of the National Health and Nutrition Examination Survey were conducted. A handheld dynamometer collected HGS on each hand and persons with a strength imbalance >10% between hands were classified as having asymmetric HGS. Adults with the presence of ≥2 of the following conditions had multimorbidity: cardiovascular disease, chronic obstructive pulmonary disease, chronic kidney disease, asthma, arthritis, cancer, obesity, stroke, hypertension, high cholesterol, and diabetes. Of the n = 3483 participants included, n = 2700 (77.5%) had multimorbidity. A greater proportion of adults with multimorbidity had HGS asymmetry (n = 1234 (45.7%)), compared to persons living without multimorbidity (n = 314 (40.1%); p < 0.05). Relative to individuals without asymmetry, adults with asymmetric HGS had 1.31 (95% confidence interval (CI): 1.03-1.67) greater odds for multimorbidity. Moreover, persons with HGS asymmetry had 1.22 (CI: 1.04-1.44) greater odds for accumulating morbidities. Asymmetric strength, as another indicator of diminished muscle function, is linked to chronic morbidity status. Healthcare providers should recommend healthy behaviors for reducing asymmetries to improve muscle function and mitigate morbidity risk after completing asymmetry screenings.

Applying resolved and remission codes reduced prevalence of multimorbidity in an urban multi-ethnic population

OBJECTIVE

To estimate the prevalence and determinants of multimorbidity in an urban, multi-ethnic area over 15-years and investigate the effect of applying resolved/remission codes on prevalence estimates.

STUDY DESIGN AND SETTING

This is a population-based retrospective cross-sectional study using electronic health records of adults registered between 2005 -2020 in general practices in one inner London borough (n = 826,936). Classification of resolved/remission was based on clinical coding defined by the patient's general practitioner.

RESULTS

The crude and age-adjusted prevalence of multimorbidity over the study period were 21.2% (95% CI: 21.1 -21.3) and 30.8% (30.6 -31.0), respectively. Applying resolved/remission codes decreased the crude and age-adjusted prevalence estimates to 18.0% (95% CI: 17.9 -18.1) and 27.5% (27.4 -27.7). Asthma (53.2%) and depression (20.2%) were responsible for most resolved and remission codes. Substance use (Adjusted Odds Ratio 10.62 [95% CI: 10.30 -10.95]), high cholesterol (2.48 [2.44 -2.53]), and moderate obesity (2.19 [2.15 -2.23]) were the strongest risk factor determinants of multimorbidity outside of advanced age.

CONCLUSION

Our study highlights the importance of applying resolved/remission codes to obtain an accurate prevalence and the increased burden of multimorbidity in a young, urban, and multi-ethnic population. Understanding modifiable risk factors for multimorbidity can assist policymakers in designing effective interventions to reduce progression to multimorbidity.

Relationship between chronic diseases and depression: the mediating effect of pain

BACKGROUND

Chronic diseases have a high incidence in China and may cause pain and depression. However, the association of chronic diseases with pain and the incidence of depression has not been comprehensively investigated.

METHODS

The study population was obtained from the 2015 China Health and Retirement Longitudinal Study (CHARLS). The cross-sectional data from15,213 persons were included. CHARLS provides nationally representative data from21,097 individuals aged 45 years and older in approximately 150 districts and 450 villages. The main outcome was the incidence of depression. The main independent variable was chronic disease (no chronic disease, one chronic disease, and two or more chronic diseases). The mediators were the degree of pain (no pain, mild pain, and moderate to severe pain) and whether measures were taken to relieve pain (measures taken and no measures taken). We performed chi-square and binary logistic regression analyses of the associations of chronic disease with pain and the incidence of depression. The mediation model was examined using the Sobel test.

RESULTS

Patients with more chronic diseases had more severe pain (OR = 3.697, P < 0.001, CI = 2.919-4.681) and were more likely to develop depression (OR = 2.777, P < 0.001, CI = 2.497-3.090). The degree of pain partially mediated the interaction between chronic disease and depression in this study (t = 7.989, P < 0.001). The incidence of depression was high in people who were female, less educated, unmarried, living in rural areas, and working.

CONCLUSIONS

The degree of pain had a partial mediating effect on chronic disease and depression. Pain relief measures should be considered when treating patients with depression.

Trends in U.S. Population Health: The Central Role of Policies, Politics, and Profits

Recent trends in U.S. health have been mixed, with improvements among some groups and geographic areas alongside declines among others. Medical sociologists have contributed to the understanding of those disparate trends, although important questions remain. In this article, we review trends since the 1980s in key indicators of U.S. health and weigh evidence from the last decade on their causes. To better understand contemporary trends in health, we propose that commonly used conceptual frameworks, such as social determinants of health, should be strengthened by prominently incorporating commercial, political-economic, and legal determinants. We illustrate how these structural determinants can provide new insights into health trends, using disparate health trajectories across U.S. states as an example. We conclude with suggestions for future research: focusing on structural causes of health trends and inequalities, expanding interdisciplinary perspectives, and integrating methods better equipped to handle the complexity of causal processes driving health trends and inequalities.

A cross-sectional study of financial distress in persons with multimorbidity

BACKGROUND

Financial distress among persons with multimorbidity is an important topic which has been inadequately addressed to date.

OBJECTIVE

We examined the extent of financial distress among persons with multimorbidity, using data from the 2017 Behavioral Risk Factor Surveillance System (BRFSS).

DESIGN

Cross-sectional, population-based study.

PARTICIPANTS

Adults ages ≥ 18 years with multimorbidity.

MAIN MEASURES

Low income and selected social determinants of health that are indicators of financial distress.

KEY RESULTS

Multimorbidity was more common among those with a household income of less than $15,000 per year (P < 0.001) and among those who were 65 years of age or older (P < 0.001). There was an approximately linear increase in the percentage of individuals who had a household income of less than $15,000 or $25,000 per year with increasing number of morbidities. About one-quarter of individuals who had five or more morbidities had a household income of less than $15,000 per year as compared with 4.49% of individuals with no morbidities (P < 0.001). For all of the social determinants of health examined (Couldn't pay bills, didn't have money for food, didn't have money for balanced meals, didn't have enough money to make ends meet, and felt this kind of stress), there was an approximately linear increase in the percentage of individuals with an indicator of financial distress with increasing number of morbidities. Further research is needed examining the prevalence and correlates of financial distress in this population as well effective strategies for ameliorating its impact on the health and wellbeing of these persons.

Microbiome First Medicine in Health and Safety

Microbiome First Medicine is a suggested 21st century healthcare paradigm that prioritizes the entire human, the human superorganism, beginning with the microbiome. To date, much of medicine has protected and treated patients as if they were a single species. This has resulted in unintended damage to the microbiome and an epidemic of chronic disorders [e.g., noncommunicable diseases and conditions (NCDs)]. Along with NCDs came loss of colonization resistance, increased susceptibility to infectious diseases, and increasing multimorbidity and polypharmacy over the life course. To move toward sustainable healthcare, the human microbiome needs to be front and center. This paper presents microbiome-human physiology from the view of systems biology regulation. It also details the ongoing NCD epidemic including the role of existing drugs and other factors that damage the human microbiome. Examples are provided for two entryway NCDs, asthma and obesity, regarding their extensive network of comorbid NCDs. Finally, the challenges of ensuring safety for the microbiome are detailed. Under Microbiome-First Medicine and considering the importance of keystone bacteria and critical windows of development, changes in even a few microbiota-prioritized medical decisions could make a significant difference in health across the life course.

How do multimorbidity and lifestyle factors impact the perceived health of adults with intellectual disabilities?

BACKGROUND

Adults with intellectual disability (ID) have poorer physical and perceived health than the general population. Knowledge of perceived health predictors is both limited and important for guiding the development of preventive actions. The aims of this study were to investigate (1) the associations between perceived health and demographics, degree of ID, physical health conditions, and weight and physical activity level and (2) lifestyle factors and multimorbidity as predictors for perceived health adjusted for age, gender, and level of ID.

METHOD

The North Health in Intellectual Disability study is a community based cross-sectional survey. The POMONA-15 health indicators were used. Univariate and multivariate logistic regression analyses with poor versus good health as the dependent variable were applied.

RESULTS

The sample included 214 adults with a mean age 36.1 (SD 13.8) years; 56% were men, and 27% reported perceiving their health as poor. In univariate analyses, there were significant associations between poor health ratings and female gender, lower motor function, number of physical health conditions and several indicators of levels of physical activity. In the final adjusted model, female gender [odds ratio (OR) 2.4, P < 0.05], level of ID (OR 0.65, P < 0.05), numbers of physical health conditions (OR 1.6, P < 0.001) and lower motor function (OR 1.5 P < 0.05) were significant explanatory variables for poor perceived health, with a tendency to independently impact failure to achieve 30 min of physical activity daily (OR 2.0, P = 0.07).

CONCLUSION

Adults with ID with female gender, reduced motor function and more physical health conditions are at increased risk of lower perceived health and should be given attention in health promoting interventions. A lack of physical activity tends to negatively influence perceived health.

Measuring Multimorbidity: Selecting the Right Instrument for the Purpose and the Data Source

BACKGROUND

Adults have a higher prevalence of multimorbidity-or having multiple chronic health conditions-than having a single condition in isolation. Researchers, health care providers, and health policymakers find it challenging to decide upon the most appropriate assessment tool from the many available multimorbidity measures.

OBJECTIVE

The objective of this study was to describe a broad range of instruments and data sources available to assess multimorbidity and offer guidance about selecting appropriate measures.

DESIGN

Instruments were reviewed and guidance developed during a special expert workshop sponsored by the National Institutes of Health on September 25-26, 2018.

RESULTS

Workshop participants identified 4 common purposes for multimorbidity measurement as well as the advantages and disadvantages of 5 major data sources: medical records/clinical assessments, administrative claims, public health surveys, patient reports, and electronic health records. Participants surveyed 15 instruments and 2 public health data systems and described characteristics of the measures, validity, and other features that inform tool selection. Guidance on instrument selection includes recommendations to match the purpose of multimorbidity measurement to the measurement approach and instrument, review available data sources, and consider contextual and other related constructs to enhance the overall measurement of multimorbidity.

CONCLUSIONS

The accuracy of multimorbidity measurement can be enhanced with appropriate measurement selection, combining data sources and special considerations for fully capturing multimorbidity burden in underrepresented racial/ethnic populations, children, individuals with multiple Adverse Childhood Events and older adults experiencing functional limitations, and other geriatric syndromes. The increased availability of comprehensive electronic health record systems offers new opportunities not available through other data sources.

The Psychosocial Impact of Spouse-Caregiver Chronic Health Conditions and Personal History of Cancer on Well-being in Patients With Advanced Cancer and Their Caregivers

CONTEXT

Caregiving during advanced cancer presents many physical and psychological challenges, especially for caregivers who are coping with their own history of cancer or their own chronic health conditions. There is growing recognition that caregiver health and patient health are interdependent.

OBJECTIVES

The objective of this study was to use quantitative and interview data to examine and explore the impact of a caregiver's personal cancer history and chronic health conditions on the psychosocial well-being of both the caregiver and patient.

METHODS

This was a secondary analysis of data from 88 patients with advanced lung/gastrointestinal cancer and their spouse-caregivers. Participants self-reported subjective health, chronic health conditions (including cancer), anxiety and depression symptoms, and social support and social stress. Caregivers self-reported caregiving burden and preparedness for caregiving. Caregivers also completed semistructured interviews.

RESULTS

Participants were mostly white, non-Hispanic, and in their mid-60s. Caregivers reported 1.40 (SD = 1.14) chronic conditions on average; 11 reported a personal history of cancer ("survivor-caregivers"). The number of caregiver chronic health conditions was positively associated with patient depression symptoms. Patients of survivor-caregivers also reported more depression symptoms than patients of caregivers without cancer (t(85) = -2.35, P = 0.021). Survivor-caregivers reported higher preparedness for caregiving than caregivers without cancer (t(85) = -2.48, P = 0.015). Interview data enriched quantitative findings and identified factors that may drive patient depression, including emotions such as resentment or guilt. Experiencing cancer personally may provide caregivers unique insight into the patient experience.

CONCLUSION

Providers should be aware of caregiver chronic conditions and cancer history, given the potential negative effects on patient psychosocial well-being.

Effects of Living Alone and Sedentary Behavior on Quality of Life in Patients With Multimorbidities: A Secondary Analysis of Cross-Sectional Survey Data Obtained From the National Community Database

BACKGROUND

Having multimorbidities may increase health problems. Moreover, health-related quality of life correlates negatively with the number of chronic conditions a patient has. Living alone has been identified as a predictor of poorer quality of life, and a sedentary lifestyle is widely known to increase health problems and mortality.

PURPOSE

This study was designed to identify the effects of living alone and of sedentary behavior on health-related quality of life in patients with multimorbidities using nationally representative community data.

METHODS

A secondary data analysis of the Korea National Health and Nutrition Examination Survey was conducted. In this study, 1,725 adult patients aged 19 years and above with two or more chronic diseases were selected for the analysis. Health-related quality of life was measured using the European Quality of Life-5 Dimensions. Multiple logistic regression was performed to identify the effects of living alone and of sedentary behavior on health-related quality of life. The statistical analyses took into account the components of the complex sampling design such as the strata, clusters, weights, and adjustment procedures, and missing data were treated in a valid manner.

RESULTS

After adjusting for gender, age, employment status, and number of chronic diseases, it was found that the odds of having a high health-related quality of life were lower in single households than in multiperson households (odds ratio = 0.62, 95% confidence interval [0.46, 0.84]). In addition, after adjusting for gender, age, employment status, number of chronic diseases, and living arrangement, the odds of having a high health-related quality of life decreased as sedentary time increased (odds ratio = 0.93, 95% confidence interval [0.89, 0.96]).

CONCLUSIONS/IMPLICATIONS FOR PRACTICE

To improve quality of life in patients with multimorbidities, nursing interventions that support patients who live alone and have complicated disease-related issues and that reduce sedentary behavior should be developed.

Effectiveness of a nurse-led hospital-to-home transitional care intervention for older adults with multimorbidity and depressive symptoms: A pragmatic randomized controlled trial

OBJECTIVE

To evaluate the effectiveness of a nurse-led hospital-to-home transitional care intervention versus usual care on mental functioning (primary outcome), physical functioning, depressive symptoms, anxiety, perceived social support, patient experience, and health service use costs in older adults with multimorbidity (≥ 2 comorbidities) and depressive symptoms.

DESIGN AND SETTING

Pragmatic multi-site randomized controlled trial conducted in three communities in Ontario, Canada. Participants were allocated into two groups of intervention and usual care (control).

PARTICIPANTS

127 older adults (≥ 65 years) discharged from hospital to the community with multimorbidity and depressive symptoms.

INTERVENTION

This evidence-based, patient-centred intervention consisted of individually tailored care delivery by a Registered Nurse comprising in-home visits, telephone follow-up and system navigation support over 6-months.

OUTCOME MEASURES

The primary outcome was the change in mental functioning, from baseline to 6-months. Secondary outcomes were the change in physical functioning, depressive symptoms, anxiety, perceived social support, patient experience, and health service use cost, from baseline to 6-months. Intention-to-treat analysis was performed using ANCOVA modeling.

RESULTS

Of 127 enrolled participants (63-intervention, 64-control), 85% had six or more chronic conditions. 28 participants were lost to follow-up, leaving 99 (47 -intervention, 52-control) participants for the complete case analysis. No significant group differences were seen for the baseline to six-month change in mental functioning or other secondary outcomes. Older adults in the intervention group reported receiving more information about health and social services (p = 0.03) compared with the usual care group.

CONCLUSIONS

Although no significant group differences were seen for the primary or secondary outcomes, the intervention resulted in improvements in one aspect of patient experience (information about health and social services). The study sample fell below the target sample (enrolled 127, targeted 216), which can account for the non-significant findings. Further research on the impact of the intervention and factors that contribute to the results is recommended.

TRIAL REGISTRATION

clinicaltrials.gov Identifier: NCT03157999.

Relationship of Multimorbidity, Obesity Status, and Grip Strength among Older Adults in Taiwan

Background: The combination of multiple disease statuses, muscle weakness, and sarcopenia among older adults is an important public health concern, and a health burden worldwide. This study evaluates the association between chronic disease statuses, obesity, and grip strength (GS) among older adults in Taiwan. Methods: A community-based survey was conducted every 3 years among older adults over age 65, living in Chiayi County, Taiwan. Demographic data and several diseases statuses, such as diabetes mellitus, hypertension, cerebrovascular disease, cardiovascular disease, and certain cancers, were collected using a questionnaire. Anthropometric characteristics were measured using standard methods. Grip strength was measured using a digital dynamometer (TKK5101) method. Results: A total of 3739 older individuals were recruited (1600 males and 2139 females) with the mean age of 72.9 years. The mean GS was 32.8 ± 7.1 kg for males and 21.6 ± 4.8 kg for females. GS significantly decreased most in males with cerebrovascular disease (from 33.0—29.5 kg, p < 0.001) and in females with diabetes mellitus (from 21.8—21.0 kg, p < 0.01). GS was highest in older adults with obesity (body mass index ≥ 27 kg/m²); however, there was no significant change of GS as the disease number increased. Conclusion: Older adults who have two, rather than one or greater than three chronic diseases, have significantly lower GSs than those who are healthy. Stroke and CKD for males, and hypertension and diabetes for females, are important chronic diseases that are significantly associated with GS. Furthermore, being overweight may be a protective factor for GS in older adults of both sexes.

A Web-Based Social Network Tool (GENIE) for Supporting Self-management Among High Users of the Health Care System: Feasibility and Usability Study

Background

Primary care providers are well positioned to foster self-management through linking patients to community-based health and social services (HSSs). This study evaluated a web-based tool—GENIE (Generating Engagement in Network Involvement)—to support the self-management of adults. GENIE empowers patients to leverage their personal social networks and increase their access to HSSs. GENIE maps patients’ personal social networks, elicits preferences, and filters local HSSs from a community service directory based on patient’s interests. Trained volunteers (an extension of the primary care team) conducted home visits and conducted surveys related to life and health goals in the context of the Health TAPESTRY (Teams Advancing Patient Experience: Strengthening Quality) program, in which the GENIE tool was implemented. GENIE reports were uploaded to an electronic medical record for care planning by the team.

Objective

This study aims to explore patients’, volunteers’, and clinicians’ perceptions of the feasibility, usability, and perceived outcomes of GENIE—a tool for community-dwelling adults who are high users of the health care system.

Methods

This study involved 2 primary care clinician focus groups and 1 clinician interview (n=15), 1 volunteer focus group (n=3), patient telephone interviews (n=8), field observations that captured goal-action sequences to complete GENIE, and GENIE utilization statistics. The patients were enrolled in a primary care program—Health TAPESTRY—and Ontario’s Health Links Program, which coordinates care for the highest users of the health care system. NVivo 11 (QSR International) was used to support qualitative data analyses related to feasibility and perceived outcomes, and descriptive statistics were used for quantitative data.

Results

Most participants reported positive overall perceptions of GENIE. However, feasibility testing showed that participants had a partial understanding of the tool; volunteer facilitation was critical to support the implementation of GENIE; clinicians perceived their navigation ability as superior to that of GENIE supported by volunteers; and tool completion took 39 minutes, which made the home visit too long for some. Usability challenges included difficulties completing some sections of the tool related to medical terminology and unclear instructions, limitations in the quality and quantity of HSSs results, and minor technological challenges. Almost all patients identified a community program or activity of interest. Half of the patients (4/8, 50%) followed up on HSSs and added new members to their network, whereas 1 participant lost a member. Clinicians’ strengthened their understanding of patients’ personal social networks and needs, and patients felt less social isolation.

Conclusions

This study demonstrated the potential of GENIE, when supported by volunteers, to expand patients’ social networks and link them to relevant HSSs. Volunteers require training to implement GENIE for self-management support, which may help overcome the time limitations faced by primary care clinicians. Refining the filtering capability of GENIE to address adults’ needs may improve primary care providers’ confidence in using such tools.

Assessing polypharmacy in the older population: Comparison of a self-reported and prescription based method

PURPOSE

To explore differences in the prevalence and determinants of polypharmacy in the older general population in Belgium between self-reported and prescription based estimates and assess the relative merits of each data source.

METHODS

Data were used from participants aged ≥65 years of the Belgian national health survey 2013 (n = 1950). Detailed information was asked on the use of medicines in the past 24 h and linked with prescription data from the Belgian compulsory health insurance (BCHI). Agreement between polypharmacy (use or prescription ≥5 medicines) and excessive polypharmacy (≥10 medicines) between both sources was assessed with kappa statistics. Multinomial logistic regression was used to study determinants of moderate (5-9 medicines) and excessive polypharmacy (≥10 medicines) and over- and underestimation of prescription based compared to self-reported polypharmacy.

RESULTS

Self-reported and prescription based polypharmacy prevalence estimates were respectively 27% and 32%. Overall agreement was moderate, but better in men (kappa 0.60) than in women (0.45). Determinants of moderate polypharmacy did not vary substantially by source of outcome indicator, but restrictions in activities of daily living (ADL), living in an institution and a history of a hospital admission was associated with self-reported based excessive polypharmacy only.

CONCLUSIONS

Surveys and prescription data measure polypharmacy from a different perspective, but overall conclusions in terms of prevalence and determinants of polypharmacy do not differ substantially by data source. Linking survey data with prescription data can combine the strengths of both data sources resulting in a better tool to explore polypharmacy at population level.

Primary Care Variation in Rates of Unplanned Hospitalizations, Functional Ability, and Quality of Life of Older People

PURPOSE

To investigate variability in older people's outcomes according to general practitioner (GP) and practice characteristics in New Zealand and the Netherlands.

METHODS

We used data from 2 primary care-based, cluster-randomized, controlled trials to separately fit mixed models of unplanned admission rates, functional ability, and quality of life (QOL) and examine variation according to GP- and practice-level characteristics after adjusting for participant-level characteristics. For the New Zealand sample (n = 3,755 aged 75+ years in 60 practices), we modeled 36-month unplanned admission rates, Nottingham Extended Activities of Daily Living (NEADL) scale, and QOL domain ratings from the brief version of the World Health Organization Quality of Life assessment tool. For the Netherlands sample (n = 3,141 aged 75+ years in 59 practices), we modeled 12-month unplanned admission rates, Groningen Activity Restriction Scale scores, and EuroQOL 5 dimensions (EQ-5D) summary index.

RESULTS

None of the GP or practice characteristics were significantly associated with rates of unplanned admissions in the New Zealand sample, but we found greater rates of admission in larger practices (incidence rate ratio [IRR], 1.45; 95% CI, 1.15-1.81) and practices staffed with a practice nurse (IRR, 1.74; 95% CI, 1.20-2.52) in the Netherlands sample. In both samples, differences were consistently small where there were significant associations with function (range, -0.26 to 0.19 NEADL points in the New Zealand sample; no associations in the Netherlands sample) and QOL (range, -1.64 to 0.97 QOL points in New Zealand; -0.01 EQ-5D points in the Netherlands).

CONCLUSIONS

In the absence of substantial differences in older people's function and QOL, it remains unclear whether intriguing GP- or practice-related variations in admission rates represent low- or high-quality practice.

National Institutes of Health Advancing Multimorbidity Research

BACKGROUND

Multimorbidity, the co-occurrence of 2 or more chronic diseases, is more common than having a single chronic disease, especially among persons age 65 years and older. The routine measurement of multimorbidity can facilitate a better understanding of potential causes and interactions and promote more effective treatment and improved outcomes.

OBJECTIVES

To present a multimorbidity research framework and identify gaps in the research literature related to multimorbidity.

DESIGN

In preparation for an expert panel workshop convened in September 2018, planning committee members reviewed the literature and developed a guiding framework that informed the selection of topics and speakers.

RESULTS

The framework, grounded in a patient-centered approach, incorporates the concept of concordant and discordant comorbidity, and includes potential causes, interactions, and outcomes. This work informed workshop presentations and discussion related to identifying and selecting the best available multimorbidity instruments and determining future research needs.

CONCLUSIONS

Multimorbidity research can be advanced by addressing gaps in study design and target populations, and by increasing attention to universal outcome measurement.

Examine the association between key determinants identified by the chronic disease indicator framework and multimorbidity by rural and urban settings

Background

Multimorbidity, often defined as having two or more chronic conditions is a global phenomenon. This study examined the association between key determinants identified by the chronic disease indicator framework and multimorbidity by rural and urban settings. The prevalence of individual diseases was also investigated by age and sex.

Methods

The Canada Community Health Survey and linked health administrative databases were used to examine the association between multimorbidity, sociodemographic, behavioral, and other risk factors in the province of Ontario. A multivariable logistic regression model was used to conduct the main analysis.

Results

Analyses were stratified by age (20-64 and 65-95) and area of residence (rural and urban). A total sample of n = 174,938 residents between the ages of 20-95 were examined in the Ontario province, of which 18.2% (n = 31,896) were multimorbid with 2 chronic conditions, and 23.4% (n = 40,883) with 3+ chronic conditions. Females had a higher prevalence of 2 conditions (17.9% versus 14.6%) and 3+ conditions (19.7% vs. 15.6%) relative to males. Out of all examined variables, poor self-perception of health, age, Body Mass Index, and income were most significantly associated with multimorbidity. Smoking was a significant risk factor in urban settings but not rural, while drinking was significant in rural and not urban settings. Income inequality was associated with multimorbidity with greater magnitude in rural areas. Prevalence of multimorbidity and having three or more chronic conditions were highest among low-income populations.

Conclusion

Interventions targeting population weight, age/sex specific disease burdens, and additional focus on stable income are encouraged.

Differences in Multimorbidity among Cisgender Sexual Minority and Heterosexual Adults: Investigating Differences across Age-Groups

Objectives: Despite increased risk for chronic disease, there is limited research that has examined disparities in multimorbidity among sexual minority adults and whether these disparities differ by age. Methods: Data were from the 2014-2018 Behavioral Risk Factor Surveillance System. We used sex-stratified multinomial logistic regression to examine differences in multimorbidity between sexual minority and heterosexual cisgender adults and whether hypothesized differences varied across age-groups. Results: The sample included 687,151 adults. Gay, lesbian, and bisexual adults had higher odds of meeting criteria for multimorbidity than same-sex heterosexual adults. These disparities were greater among sexual minority adults under the age of 50 years. Only other non-heterosexual men over the age of 50 years and lesbian women over the age of 80 years were less likely to have multimorbidity than their same-sex heterosexual counterparts. Discussion: Health promotion interventions to reduce adverse health outcomes among sexual minorities across the life span are needed.

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.

A Longitudinal Observational Study of Multimorbidity and Partner Support for Physical Activity Among People with Osteoarthritis

BACKGROUND

Physical activity can improve osteoarthritis-related symptoms; however, many people with osteoarthritis (PWOA) are insufficiently active. Social support for physical activity from an intimate partner can help PWOA increase activity, but managing multiple, chronic physical or mental health conditions (i.e., multimorbidity) may influence provision and receipt of that support.

METHOD

Data from a 1-year longitudinal observational study was used to examine associations between multimorbidity and three dimensions of partner support for physical activity-companionship partner support (doing activity together), enacted partner support, and social support effectiveness-in 169 insufficiently active PWOA and their partners.

RESULTS

Multivariable-adjusted multi-level models indicated baseline differences in support by multimorbidity status: when partners had multimorbidity, PWOA reported receiving less companionship support and less effective support from partners; when PWOA had multimorbidity, partners reported providing less enacted support and both partners and PWOA reported less effective partner support. Broad trends (p < .05) indicate initial increases and subsequent decreases in companionship and enacted partner support when PWOA had multimorbidity, and among partners with and without multimorbidity. When PWOA had multimorbidity, an initial increase in support effectiveness was followed by no significant change; a similar trend was seen among partners with and without multimorbidity.

CONCLUSION

Multimorbidity may generally contribute to less partner support for physical activity or less effective support, although influences on support over time are less clear. Physical activity interventions for couples experiencing multimorbidity would likely benefit from attention to the impact of multiple chronic health conditions on physical activity and physical activity-related partner support.

Engagement of older adults with multimorbidity as patient research partners: Lessons from a patient-oriented research program

Background

Patient "engagement" in health research broadly refers to including people with lived experience in the research process. Although previous reviews have systematically summarized approaches to engaging older adults and their caregivers in health research, there is currently little guidance on how to meaningfully engage older adults with multimorbidity as research partners.

Objectives

This paper describes the lessons learned from a patient-oriented research program, the Aging, Community and Health Research Unit (ACHRU), on how to engage older adults with multimorbidity as research partners. Over the past 7-years, over 40 older adults from across Canada have been involved in 17 ACHRU projects as patient research partners.

Methods

We developed this list of lessons learned through iterative consensus building with ACHRU researchers and patient partners. We then met to collectively identify and summarize the reported successes, challenges and lessons learned from the experience of engaging older adults with multimorbidity as research partners.

Results

ACHRU researchers reported engaging older adult partners across many phases of the research process. Five challenges and lessons learned were identified: 1) actively finding patient partners who reflect the diversity of older adults with multimorbidity, 2) developing strong working relationships with patient partners, 3) providing education and support for both patient partners and researchers, 4) using flexible approaches for engaging patients, and 5) securing adequate resources to enable meaningful engagement.

Conclusion

The lessons learned through this work may provide guidance to researchers on how to facilitate meaningful engagement of this vulnerable and understudied subgroup in the patient engagement literature.