Racial and Ethnic Differences in Multimorbidity Changes Over Time

Multimorbidity Patterns, Hospital Uses and Mortality by Race and Ethnicity Among Oldest-Old Patients

BACKGROUNDS

Adults aged 85 years and older ("oldest-old") are perceived as survivors resilient to age-related risk factors. Although considerable heterogeneity has been often observed in this population, less is known about the unmet needs in health and healthcare service utilization for diverse patients in healthcare systems. We examined racial-ethnic variation in patterns of multimorbidity associated with emergency department (ED), clinic visits, and mortality among the oldest-old patients with multimorbidity.

METHODS

Administrative and clinical data from an integrated healthcare system for five years included 25,801 oldest-old patients with two or more chronic conditions. Hierarchical cluster analysis identified patterns of multimorbidity by four racial-ethnic groups (White, Black, Hispanic, & Other). Clusters associated with ED and clinic visits, and mortality were analyzed using generalized estimation equations and proportional hazards survival model, respectively.

RESULTS

Hypothyroidism, Alzheimer's disease and related dementia, bone & joint conditions, metabolism syndrome, and pulmonary-vascular clusters were commonly observed across the groups. While most clusters were significantly associated with ED and clinic visits among White patients, bone & joint conditions cluster was the most significantly associated with ED and clinic visits among Black (RR = 1.32, p <.01 for ED; RR = 1.67, p <.0001 for clinic) and Hispanic patients (RR = 1.36, p <.0001 for ED; RR = 1.39, p <.0001 for clinic). Similar patterns were observed in the relationship between multimorbidity clusters and mortality.

CONCLUSIONS

Patterns of multimorbidity and its significant association with the uses of ambulatory and emergency care varied by race-ethnicity. More studies are needed to explore barriers when minoritized patients are faced with the use of hospital services.

Variation in multimorbidity by sociodemographics and social drivers of health among patients seen at community-based health centers

Purpose

Understanding variation in multimorbidity across sociodemographics and social drivers of health is critical to reducing health inequities.

Methods

From the multi-state OCHIN network of community-based health centers (CBHCs), we identified a cross-sectional cohort of adult (> 25 years old) patients who had a visit between 2019-2021. We used generalized linear models to examine the relationship between the Multimorbidity Weighted Index (MWI) and sociodemographics and social drivers of health (Area Deprivation Index [ADI] and social risks [e.g., food insecurity]). Each model included an interaction term between the primary predictor and age to examine if certain groups had a higher MWI at younger ages.

Results

Among 642,730 patients, 28.2% were Hispanic/Latino, 42.8% were male, and the median age was 48. The median MWI was 2.05 (IQR: 0.34, 4.87) and was higher for adults over the age of 40 and American Indians and Alaska Natives. The regression model revealed a higher MWI at younger ages for patients living in areas of higher deprivation. Additionally, patients with social risks had a higher MWI (3.16; IQR: 1.33, 6.65) than those without (2.13; IQR: 0.34, 4.89) and the interaction between age and social risk suggested a higher MWI at younger ages.

Conclusions

Greater multimorbidity at younger ages and among those with social risks and living in areas of deprivation shows possible mechanisms for the premature aging and disability often seen in community-based health centers and highlights the need for comprehensive approaches to improving the health of vulnerable populations.

Ethnic differences in physical and mental multimorbidity in working age adults with a history of depression and/or anxiety

BACKGROUND

The current study used data from an ethnically diverse population from South London to examine ethnic differences in physical and mental multimorbidity among working age (18-64 years) adults in the context of depression and anxiety.

METHOD

The study included 44 506 patients who had previously attended Improving Access to Psychological Therapies services in the London Borough of Lambeth. Multinomial logistic regression examined cross-sectional associations between ethnicity with physical and mental multimorbidity. Patterns of multimorbidity were identified using hierarchical cluster analysis.

RESULTS

Within 44 056 working age adults with a history of depression or anxiety from South London there were notable ethnic differences in physical multimorbidity. Adults of Black Caribbean ethnicity were more likely to have physical multimorbidity [adjusted relative risk ratio (aRRR) = 1.25, 95% confidence interval (CI) 1.15-1.36] compared to adults of White ethnicity. Relative to adults of White ethnicity, adults of Asian ethnicity were more likely to have physical multimorbidity at higher thresholds only (e.g. 4 + conditions; aRRR = 1.53, 95% CI 1.17-2.00). Three physical (atopic, cardiometabolic, mixed) and three mental (alcohol/substance use, common/severe mental illnesses, personality disorder) multimorbidity clusters emerged. Ethnic minority groups with multimorbidity had a higher probability of belonging to the cardiometabolic cluster.

CONCLUSION

In an ethnically diverse population with a history of common mental health disorders, we found substantial between- and within-ethnicity variation in rates of physical, but not mental, multimorbidity. The findings emphasised the value of more granular definitions of ethnicity when examining the burden of physical and mental multimorbidity.

Misuse of multinomial logistic regression in stroke related health research: A systematic review of methodology

Multinomial logistic regression (MLR) is often used to model the association between a nominal outcome variable and one or more covariates. The results of MLR are interpreted as relative risk ratios (RRR) and warrant a more coherent interpretation than ordinary logistic regression. Some authors compare the results of MLR to ordinal logistic regression (OLR), irrespective of the fact that these estimate different quantities. We aim to investigate the time trends in the use and misuse of MLR in studies including stroke patients, specifically the extent to which (1) the results are denoted as anything other than RRR, (2) comparisons are made of results with results of OLR and (3) results have been interpreted coherently. Secondarily, we examine the use of model validation techniques in studies with predictive aims. We searched EMBASE and PubMed for articles using MLR on populations of stroke patients. Identified studies were screened, and information pertaining to our aims was extracted. A total of 285 articles were identified through a systematic literature search, and 68 of these were included in the review. Of these, 60 articles (88%) did not denote exponentiated coefficients of MLR as relative risk ratios but rather some other measure. Additionally, 63 articles (93%) interpreted the results of MLR in a non-coherent manner. Two articles attempted to compare MLR results with those of OLR. Nine studies attempted to use MLR for predictive means, and three used relevant validation techniques. From these findings, it is clear that the interpretation of MLR is often suboptimal.

Self-regulatory coping among community dwelling older adults with multiple chronic conditions

Objectives

Many older adults with multiple chronic conditions (MCC) frequently experience hospitalizations, functional limitations, and poor quality of life. Outcomes may be improved by promoting self-regulation, which may individuals respond to health threats and manage their health conditions. The aim of this study was to describe self-regulatory coping among older adults with MCC.

Methods

A qualitative descriptive study using semi-structured interviews and content analysis and guided by the Common-Sense Self-Regulation Model. Seventeen community-dwelling older adults with two or more chronic conditions participated in our study.

Results

Three themes were developed from the analysis: (1) "I don't think about it unless something happens": coping in the absence of a health event, (2) "doing what I am supposed to do": coping during a health event, and (3) "How do I know if what I did works?": appraisal of coping success.

Discussion

Self-regulatory coping was influenced by individual beliefs and experiences (illness representations), context, self-efficacy and availability of support and resources to cope with MCC. These findings suggest implications for clinical practice and future self-regulation interventions for older adults with MCC.

Sleep health dimensions are associated with next-day symptoms in young adults with type 1 diabetes

OBJECTIVE

We investigated intra-individual reciprocal associations between sleep health dimensions (individual and composite) and symptoms among young adults with type 1 diabetes (T1D).

DESIGN AND MEASUREMENTS

Cross-lagged multilevel models were used to analyze electronic diary-reported sleep and symptom patterns over 7 days at waketime in 42 young adults with T1D. Sleep health dimensions included regularity, satisfaction, alertness, timing, efficiency (percentage of time spent asleep), and duration (total sleep time) and symptoms included mood, fatigue, and pain. Covariates included biological sex and age.

SETTING AND PARTICIPANTS

We recruited young adults (mean age 21.5 ± 2.1 years, HbA1c 6.8%, 85% female, 10% gender minority) with T1D for at least 6 months and no other major medical or psychiatric comorbidity from social media platforms, the College Diabetes Network, and ResearchMatch.

RESULTS

On days with a better sleep health composite, participants reported lower next-day symptoms (higher mood, lower fatigue, and lower pain) and on days when participants reported lower symptoms, participants reported better sleep health (as a composite). Several individual sleep health dimensions led to lower next-day symptoms (eg, higher satisfaction, alertness, and efficiency and higher mood); however, symptoms were no longer predictive of next-day sleep when controlling for prior day sleep.

CONCLUSIONS

Optimal sleep health is an antecedent of fewer next day symptoms. Sleep health dimensions likely have positive additive effects on lower symptoms as some of the individual sleep health dimensions were not significantly associated with some symptoms among young adults with T1D.

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.

Double, Triple, and Quadruple Jeopardy: Entering Pregnancy With Two or More Multimorbid Diagnoses and Increased Risk of Severe Maternal Morbidity and Postpartum Readmission

INTRODUCTION

Multimorbidity, the presence of two or more chronic disease diagnoses, is associated with an increased risk of mortality and high health care costs in the general population and older adults. However, little evidence is available about the prevalence and impact of multimorbidity in obstetric populations. The goal of this analysis was to estimate the association between multimorbidity and severe maternal morbidity (SMM) and 90-day postpartum readmission in an obstetric cohort in Atlanta, Georgia.

STUDY DESIGN

We conducted a retrospective cohort study of livebirths and stillbirths at Grady Memorial Hospital, from October 2015 to April 2021. To determine preexisting chronic conditions, we linked information on births to inpatient diagnoses within the prior year. Multimorbidity was defined as the presence of two or more chronic disease diagnoses at birth or within the prior year. We conducted multivariable log binomial regression to estimate risk ratios and 95% confidence intervals for the crude and adjusted (for age, race/ethnicity, parity, and insurance) association between multimorbidity (two or more chronic conditions vs. zero or one) and SMM (at or within 42 days after birth) or 90-day postpartum readmission for any reason.

RESULTS

Of 14,225 included births, 10.1% were to patients with multimorbidity. Overall, SMM complicated 7.5% of births, and the 90-day readmission rate was 2.4%. Both SMM and readmission were more common among women with multimorbidity (SMM, 18.6% among women with multimorbidity compared with 6.3% without; 90-day readmission, 5.4% compared with 2.1%). Adjusting for potential confounders, multimorbidity was associated with increased risk of SMM (adjusted risk ratio, 2.9; 95% confidence interval, 2.5-3.0) and readmission (adjusted risk ratio, 2.2; 95% confidence interval, 1.7-2.9).

CONCLUSIONS

Individuals entering pregnancy with two or more chronic diseases were at an increased risk of SMM and postpartum readmission compared with individuals with one or zero chronic disease diagnoses.

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.

Associations between multiple long-term conditions and mortality in diverse ethnic groups

Background

Multiple conditions are more prevalent in some minoritised ethnic groups and are associated with higher mortality rate but studies examining differential mortality once conditions are established is US-based. Our study tested whether the association between multiple conditions and mortality varies across ethnic groups in England.

Methods and findings

A random sample of primary care patients from Clinical Practice Research Datalink (CPRD) was followed from 1^st January 2015 until 31^st December 2019. Ethnicity, usually self-ascribed, was obtained from primary care records if present or from hospital records. Long-term conditions were counted from a list of 32 that have previously been associated with greater primary care, hospital admissions, or mortality risk. Cox regression models were used to estimate mortality by count of conditions, ethnicity and their interaction, with adjustment for age and sex for 532,059 patients with complete data. During five years of follow-up, 5.9% of patients died. Each additional condition at baseline was associated with increased mortality. The direction of the interaction of number of conditions with ethnicity showed a statistically higher mortality rate associated with long-term conditions in Pakistani, Black African, Black Caribbean and Other Black ethnic groups. In ethnicity-stratified models, the mortality rate per additional condition at age 50 was 1.33 (95% CI 1.31,1.35) for White ethnicity, 1.43 (95% CI 1.26,1.61) for Black Caribbean ethnicity and 1.78 (95% CI 1.41,2.24) for Other Black ethnicity.

Conclusions

The higher mortality rate associated with having multiple conditions is greater in minoritised compared with White ethnic groups. Research is now needed to identify factors that contribute to these inequalities. Within the health care setting, there may be opportunities to target clinical and self-management support for people with multiple conditions from minoritised ethnic groups.

Differences of body composition and physical strength among Japanese and Thai older adults living in Chiang Mai, Thailand: an inter-ethnic cross-sectional study

BACKGROUND

The number of adults aged over 65 years is rapidly increasing in several Southeast Asian countries. Muscle mass decreases with age, leading to sarcopenia. The primary objective of this study was to determine whether differences exist in the body composition and physical strength, according to ethnicity, among community-dwelling Japanese and Thai older adults living in Chiang Mai Province, Thailand.

METHODS

A survey was conducted in February and March 2019. Japanese and Thai adults aged ≥ 60 years living in Chiang Mai Province were recruited through community clubs. Participants completed a self-administered questionnaire that enabled collection of data on age, sex, educational background, marital status, annual income, current medical conditions, smoking and alcohol consumption, and exercise habits. Measurements were collected on height, weight, body composition, blood pressure, hand grip, and walking speed for 6 m. Body composition was measured using a standing-posture 8-electrode multifrequency bioimpedance analysis analyzer. Hand grip of each hand was measured with the patient in the standing position using a digital grip dynamometer. Multivariable logistic regression was used to determine factors associated with skeletal muscle mass index (SMI).

RESULTS

Of the total 119 participants, 47 were Japanese (26 men, 21 women) and 72 were Thai (16 men, 56 women). The prevalence of a low SMI was 3/26 (12%), 1/21 (5%), 6/16 (38%), and 5/56 (9%) among Japanese men, Japanese women, Thai men, and Thai women, respectively. The prevalence of low muscle strength was 2/26 (8%), 2/21 (10%), 3/16 (19%), and 13/56 (23%) among Japanese men, Japanese women, Thai men, and Thai women, respectively. There were significant differences between ethnic groups in body mass index for both sexes, percentage body fat in women, SMI in men, and average grip strength in men. Ethnic group, sex, age, and body mass index were independent predictors of SMI.

CONCLUSIONS

Ethnicity had a clinically important effect on body composition and physical strength among older Japanese and Thai adults living in a similar environment.