Tracking Multimorbidity Changes in Diverse Racial/Ethnic Populations Over Time: Issues and Considerations

Capturing the care of complex community-based health center patients: A comparison of multimorbidity indices and clinical classification software

OBJECTIVE

To compare morbidity burden captured from multimorbidity indices and aggregated measures of clinically meaningful categories captured in primary care community-based health center (CBHC) patients.

DATA SOURCES AND STUDY SETTING

Electronic health records of patients seen in 2019 in OCHIN's national network of CBHCs serving patients in rural and underserved communities.

STUDY DESIGN

Age-stratified analyses comparing the most common conditions captured by the Charlson, Elixhauser, and Multimorbidity Weighted (MWI) indices, and Classification Software Refined (CCSR) and Chronic Condition Indicator (CCI) algorithms.

DATA COLLECTION/EXTRACTION METHODS

Active ICD-10 conditions on patients' problem list in 2019.

PRINCIPAL FINDINGS

Approximately 35%-56% of patients with at least one condition are not captured by the Charlson, Elixhauser, and MWI indices. When stratified by age, this range broadens to 9%-90% with higher percentages in younger patients. The CCSR and CCI reflect a broader range of acute and chronic conditions prevalent among CBHC patients.

CONCLUSION

Three commonly used indices to capture morbidity burden reflect conditions most prevalent among older adults, but do not capture those on problem lists for younger CBHC patients. An index with an expanded range of care conditions is needed to understand the complex care provided to primary care populations across the lifespan.

An Exploration of Methods to Resolve Inconsistent Self-Reporting of Chronic Conditions and Impact on Multimorbidity in the Canadian Longitudinal Study on Aging

OBJECTIVES

To quantify inconsistent self-reporting of chronic conditions between the baseline (2011-2015) and first follow-up surveys (2015-2018) in the Canadian Longitudinal Study on Aging (CLSA), and to explore methods to resolve inconsistent responses and impact on multimorbidity.

METHODS

Community-dwelling adults aged 45-85 years in the baseline and first follow-up surveys were included (n = 45,184). At each survey, participants self-reported whether they ever had a physician diagnosis of 35 chronic conditions. Identifiable inconsistent responses were enumerated.

RESULTS

32-40% of participants had at least one inconsistent response across all conditions. Illness-related information (e.g., taking medication) resolved most inconsistent responses (>93%) while computer-assisted software asking participants to confirm their inconsistent disease status resolved ≤53%. Using these adjudication methods, multimorbidity prevalence at follow-up increased by ≤1.6% compared to the prevalence without resolving inconsistent responses.

DISCUSSION

Inconsistent self-reporting of chronic conditions is common but may not substantially affect multimorbidity prevalence. Future research should validate methods to resolve inconsistencies.

Cohort Trends in the Burden of Multiple Chronic Conditions Among Aging U.S. Adults

OBJECTIVES

Multimorbidity, also referred to as multiple chronic conditions (MCCs), is the concurrent presence of 2 or more chronic health conditions. Increasing multimorbidity represents a substantial threat to the health of aging populations. Recent trends suggest greater risk of poor health and mortality among later-born cohorts, yet we are unaware of work examining cohort differences in multimorbidity among aging U.S. adults.

METHODS

We examine intercohort variation in MCC burden in adults aged 51 years and older using 20 years (n = 33,598; 1998-2018) of repeated assessment drawn from the Health and Retirement Study. The index of MCCs included 9 chronic conditions (heart disease, hypertension, stroke, diabetes, arthritis, lung disease, cancer excluding skin cancer, high depressive symptoms, and cognitive impairment). We used linear mixed models with various approaches to estimate age/period/cohort effects to model intercohort patterns in MCC burden. We also explored variation in the specific conditions driving cohort differences in multimorbidity.

RESULTS

More recent cohorts had greater MCC burden and developed multimorbidity at earlier ages than those born to prior generations. The burden of chronic conditions was patterned by life-course sociodemographic factors and childhood health for all cohorts. Among adults with multimorbidity, arthritis and hypertension were the most prevalent conditions for all cohorts, and there was evidence that high depressive symptoms and diabetes contributed to the observed cohort differences in multimorbidity risk.

DISCUSSION

Our results suggest increasing multimorbidity burden among more recently born cohorts of aging U.S. adults and should inform policy to address diminishing health in aging populations.

Physical Activity as a Mediator Between Race/Ethnicity and Changes in Multimorbidity

OBJECTIVES

Studies report racial/ethnic disparities in multimorbidity (≥2 chronic conditions) and their rate of accumulation over time as well as differences in physical activity. Our study aimed to investigate whether racial/ethnic differences in the accumulation of multimorbidity were mediated by physical activity among middle-aged and older adults.

METHOD

We assessed racial/ethnic differences in the accumulation of multimorbidity (of 9 conditions) over 12 years (2004-2016) in the Health and Retirement Study (N = 18,264, mean age = 64.4 years). Structural equation modeling was used to estimate latent growth curve models of changes in multimorbidity and investigate whether the relationship of race/ethnicity (non-Hispanic Black, Hispanic, non-Hispanic White participants) to changes in the number of chronic conditions was mediated by physical activity after controlling for age, sex, education, marital status, household wealth, insurance coverage, smoking, alcohol, and body weight.

RESULTS

There was a significant increase in multimorbidity over time. Initial levels and changes in multimorbidity over time varied significantly across individuals. Indirect effects of the relationship between race/ethnicity and changes in multimorbidity as mediated by physical activity were significant, consistent with the mediational hypothesis. Black respondents engaged in significantly lower levels of physical activity than White respondents after controlling for covariates, but there were no differences between Hispanic and White respondents once education was included. Discussion: These results provide important new information for understanding how modifiable lifestyle factors may help explain disparities in multimorbidity in mid-to-late life, suggesting greater need to intervene to reduce sedentary behavior and increase physical activity.

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.

Identifying multimorbidity clusters with the highest primary care use: 15 years of evidence from a multi-ethnic metropolitan population

Background

People with multimorbidity have complex healthcare needs. Some co-occurring diseases interact with each other to a larger extent than others and may have a different impact on primary care use.

Aim

To assess the association between multimorbidity clusters and primary care consultations over time.

Design and setting

A retrospective longitudinal (panel) study design was used. Data comprised electronic primary care health records of 826 166 patients registered at GP practices in an ethnically diverse, urban setting in London between 2005 and 2020.

Method

Primary care consultation rates were modelled using generalised estimating equations. Key controls included the total number of long-term conditions, five multimorbidity clusters, and their interaction effects, ethnic group, and polypharmacy (proxy for disease severity). Models were also calibrated by consultation type and ethnic group.

Results

Individuals with multimorbidity used two to three times more primary care services than those without multimorbidity (incidence rate ratio 2.30, 95% confidence interval = 2.29 to 2.32). Patients in the alcohol dependence, substance dependence, and HIV cluster (Dependence+) had the highest rate of increase in primary care consultations as additional long-term conditions accumulated, followed by the mental health cluster (anxiety and depression). Differences by ethnic group were observed, with the largest impact in the chronic liver disease and viral hepatitis cluster for individuals of Black or Asian ethnicity.

Conclusion

This study identified multimorbidity clusters with the highest primary care demand over time as additional long-term conditions developed, differentiating by consultation type and ethnicity. Targeting clinical practice to prevent multimorbidity progression for these groups may lessen future pressures on primary care demand by improving health outcomes.

Multimorbidity patterns and their related characteristics in European older adults: A longitudinal perspective

BACKGROUND

The concurrence of several chronic conditions is a rising concern that poses a serious burden on ageing populations. Analysing how these conditions appear together and how they change through time may provide useful information to design successful multimorbidity-management programs.

OBJECTIVE

To identify multimorbidity patterns and their related characteristics from a longitudinal perspective.

SUBJECTS

25,931 older adults aged 50+ drawn from the Survey of Health, Ageing and Retirement in Europe (SHARE), a population-based longitudinal European study.

METHODS

A sex-stratified Latent Transition Analysis was conducted to fit latent classes based on 15 self-reported chronic conditions across three time points. Health-related and socioeconomic variables were assessed as covariates of those patterns.

RESULTS

We identified 4 time-constant latent classes for each sex. A "severely impaired" class (with a weighted prevalence percentage of 7.24% for females and 3.30% for males at the first time point), a "metabolic" class (26.15% and 23.82%) and a "healthy" class (50.92% and 54.32%). The fourth class was named "osteoarticular" for females (15.70%) and "articular-COPD-ulcer" for males (18.56%). Age, smoke, material deprivation and a high body mass index were associated with worse health patterns, whereas education, being employed and physical activity were related to less multimorbid classes. Few class changes were detected when modelling transitions.

CONCLUSIONS

We reported information of multimorbidity classes and their characteristics that may help to develop targeted health strategies. Within a time window of four years, the identified latent classes were consistent between time points.

Racial and Ethnic Differences in Multimorbidity Changes Over Time

BACKGROUND

Our understanding of how multimorbidity progresses and changes is nascent.

OBJECTIVES

Assess multimorbidity changes among racially/ethnically diverse middle-aged and older adults.

DESIGN, SETTING, AND PARTICIPANTS

Prospective cohort study using latent class analysis to identify multimorbidity combinations over 16 years, and multinomial logistic models to assess change relative to baseline class membership. Health and Retirement Study respondents (age 51 y and above) in 1998 and followed through 2014 (N=17,297).

MEASURES

Multimorbidity latent classes of: hypertension, heart disease, lung disease, diabetes, cancer, arthritis, stroke, high depressive symptoms.

RESULTS

Three latent classes were identified in 1998: minimal disease (45.8% of participants), cardiovascular-musculoskeletal (34.6%), cardiovascular-musculoskeletal-mental (19.6%); and 3 in 2014: cardiovascular-musculoskeletal (13%), cardiovascular-musculoskeletal-metabolic (12%), multisystem multimorbidity (15%). Remaining participants were deceased (48%) or lost to follow-up (12%) by 2014. Compared with minimal disease, individuals in cardiovascular-musculoskeletal in 1998 were more likely to be in multisystem multimorbidity in 2014 [odds ratio (OR)=1.78, P<0.001], and individuals in cardiovascular-musculoskeletal-mental in 1998 were more likely to be deceased (OR=2.45, P<0.001) or lost to follow-up (OR=3.08, P<0.001). Hispanic and Black Americans were more likely than White Americans to be in multisystem multimorbidity in 2014 (OR=1.67, P=0.042; OR=2.60, P<0.001, respectively). Black compared with White Americans were more likely to be deceased (OR=1.62, P=0.01) or lost to follow-up (OR=2.11, P<0.001) by 2014.

CONCLUSIONS AND RELEVANCE

Racial/ethnic older adults are more likely to accumulate morbidity and die compared with White peers, and should be the focus of targeted and enhanced efforts to prevent and/or delay progression to more complex multimorbidity patterns.

Discrimination and Multimorbidity Among Black Americans: Findings from the National Survey of American Life

OBJECTIVES

There is a notable lack of research on the risk factors for multimorbidity, which has become more common over recent decades. Black Americans experience discrimination more often than their White counterparts, and also have significantly higher prevalence of multimorbidity. This paper examines the associations between discrimination and multimorbidity among Black Americans.

METHODS

We analyzed data from the National Survey of American Life to calculate the prevalence of two types of discrimination (everyday discrimination, major discriminatory events) and multimorbidity (physical, psychiatric, mixed, any). Using multivariable logistic regression, we examined the associations between discrimination and multimorbidity, adjusting for age, sex, years of education, income-to-poverty ratio, and ethnicity. The everyday discrimination scale was discretized into five categories (none, low, medium, high, very high), but was also treated as a continuous variable. The major discriminatory events were analyzed in separate adjusted models, and as a count of events.

RESULTS

When compared with those who did not experience any discrimination, people who experienced everyday discrimination were significantly more likely to report all types of multimorbidity in a dose-response fashion at a conventional level of statistical significance. Most major discriminatory events were associated with greater odds of reporting all types of multimorbidity, as were the counts of major discriminatory events, in a dose-response fashion.

CONCLUSIONS

We found strong evidence to suggest that discrimination was associated with greater odds of reporting multimorbidity. Future studies can expand on these findings using longitudinal data to capture the relations between discrimination and health over time, or by testing preventive interventions that allay the damaging health effects of discrimination.

A workshop report on the causes and consequences of sleep health disparities

Sleep deficiencies, which include insufficient or long sleep duration, poor sleep quality, and irregular timing of sleep, are disproportionately distributed among populations that experience health disparities in the United States. Sleep deficiencies are associated with a wide range of suboptimal health outcomes, high-risk health behaviors, and poorer overall functioning and well-being. This report focuses on sleep health disparities (SHDs), which is a term defined as differences in one or more dimensions of sleep health on a consistent basis that adversely affect designated disadvantaged populations. SHDs appear to share many of the same determinants and causal pathways observed for health outcomes with well-known disparities. There also appears to be common behavioral and biological mechanisms that connect sleep with poorer health outcomes, suggesting a link between SHDs and other health disparities observed within these designated populations. In 2018, the National Institute on Minority Health and Health Disparities, the National Heart, Lung, and Blood Institute, and the Office of Behavioral and Social Sciences Research convened a workshop with experts in sleep, circadian rhythms, and health disparities to identify research gaps, challenges, and opportunities to better understand and advance research to address SHDs. The major strategy to address SHDs is to promote integration between health disparity causal pathways and sleep and circadian-related mechanisms in research approaches and study designs. Additional strategies include developing a comprehensive, integrative conceptual model, building transdisciplinary training and research infrastructure, and designing as well as testing multilevel, multifactorial interventions to address SHDs.