Multimorbidity Groups Research Articles

The extent and burden of high multimorbidity on older adults in the US: a descriptive analysis of Medicare beneficiaries

BackgroundThe impact of multimorbidity (≥ 2 chronic diseases) on the well-being of older adults is substantial but variable. The burden of multimorbidity varies by the number and kinds of conditions, and timing of onset. The impact varies by age, race, ethnicity, socioeconomic status, and health indicators. Large scale longitudinal surveys linked to medical claims provide unique opportunities to characterize this variability.MethodsWe analyzed Medicare-linked Health and Retirement Study data for respondents 65 and older with 3 or more years of fee-for-service coverage (n = 17,199; 2000–2016). We applied standardized claims algorithms for operationalizing 21 chronic diseases. We compared multimorbidity levels, demographics, and outcomes at baseline and over time and escalation to high multimorbidity levels (≥ 5 conditions).ResultsAt baseline, 51.2% had no multimorbidity, 36.5% had multimorbidity, and 12.4% had high multimorbidity. Loss of function, cognitive decline, and higher healthcare utilization were up to ten times more prevalent in the high multimorbidity group. Greater rates of high multimorbidity were seen among non-Hispanic Black and Hispanic groups, those with lower wealth, younger birth cohorts, and adults with obesity. Rates of transition to high multimorbidity varied greatly and was highest among Hispanic and respondents with lower education.ConclusionsThe development and progression of multimorbidity in old age is influenced by many factors. Higher levels of multimorbidity are associated with sociodemographic characteristics, suggesting possible mitigation strategies.

A study on multimorbidity patterns, Inpatient care utilization, and associated factors in inpatients with Multimorbidity in township health centers of Guangxi

BackgroundThe epidemiology of multimorbidity, inpatient care utilization, and associated factors among inpatients in rural primary health care facilities in China remains unclear, hindering effective prevention and management of multimorbidity in rural populations. ObjectivesThis study aims to investigate the patterns of multimorbidity, inpatient care utilization, and related factors among hospitalized patients in township health centers (rural primary healthcare facilities) in Guangxi, China. MethodsA multistage stratified and cluster random sampling method was employed to select 10 township health centers (rural primary healthcare facilities) in Nanning, Wuzhou, Liuzhou, Yulin, and Guigang of Guangxi Autonomous Region of China. De-identified inpatient medical records from January 1, 2021, to June 30, 2023, were retrieved from inpatient and chronic disease management systems. Statistical analyses, including the Kruskal-Wallis H test, Mann-Whitney U test, and multinomial logistic regression, were used to explore the demographic characteristics, multimorbidity prevalence, comorbidity number, multimorbidity patterns, hospitalization frequency, and associated factors among inpatients with multimorbidity. ResultsA total of 9,330 patients with multimorbidity were included, with an average age of 68.1 ±11.8 years, and 52.6 % were female. The overall prevalence of multimorbidity was 31.24 %. The most prevalent comorbidity number was 2 (53.22 %), followed by 3 (28.76 %), 4 (12.92 %), and ≥5(5.1 %). Hypertension was the most prevalent co-existing chronic condition, and the most common multimorbidity patterns included combinations of hypertension, chronic cervical and lumbar spondylosis, chronic gastrointestinal diseases, stroke, diabetes mellitus, hyperlipidemia, and chronic pulmonary diseases. The median number of hospitalization frequency for the top 10 multimorbidity patterns ranged from 1 to 4.5, with significant differences in hospitalization frequency across multimorbidity groups. Age, BMI, gender, smoking, alcohol consumption, ethnicity, marital status, and medical insurance were significantly associated with number of co-existing chronic conditions, while age, gender, smoking, alcohol consumption, ethnicity, marital status, education level, medical insurance, and number of co-existing chronic conditions were significantly associated with hospitalization frequency. ConclusionsThe prevalence of multimorbidity among inpatients in township health centers(rural primary healthcare facilities) in Guangxi is high. Hypertension was the most prevalent co-existing condition, with frequent combinations involving chronic cervical and lumbar spondylosis, gastrointestinal diseases, stroke, diabetes, hyperlipidemia, and chronic pulmonary diseases. Multiple factors influence both number of co-exsiting chronic conditions and hospitalization frequency, emphasizing the need for comprehensive, multifaceted strategies to manage the challenges of multimorbidity in rural primary healthcare facilities.

Age, sex, and multi-morbidity stratified mortality risk estimates for adults with cerebral palsy to inform clinical decision making

BackgroundWhile research has provided key insights into mortality rates and risks for individuals with cerebral palsy (CP), clinically useable mortality risk estimates remain unreported for adults with CP, especially by key patient-level factors. ObjectiveThe objective of this study was to generate clinically useable mortality risk estimates among adults with CP to inform clinical decision making. MethodsThis retrospective cohort study, using a fee-for-service Medicare database, identified adults ≥18-years-old with CP from 01/01/2008-12/31/2010 and followed through 12/31/2019 for death. Mortality risk at 1-, 3-, 5-, and 9-year intervals were selected based on common clinical length of time to reasonably benefit from preventive care. Sex-stratified analyses assessed risk estimates by narrow age group (18-25/26-34/35-44/45-54/55-64/65-74/≥75 years old) and multi-morbidity group (Whitney Comorbidity Index score 0-2/3/4-6/≥7). ResultsOf 24,767 adults with CP, n=12,962 were men (mean [SD] age=48.3 [15.0] years) and n=11,805 were women (age=49.7 [15.8] years). Loss to follow-up was rare. 1-year risk was similar between men and women (3.4% vs. 3.3%), but increased slightly more for men than women through 9-years (30.1% vs. 28.0%). As expected, the mortality risk increased with older age and higher WCI scores. The probability of death (and survival) is presented per age and multi-morbidity group for men and women with CP. ConclusionsMortality risk estimates were reported at clinically relevant intervals by age, sex, and multi-morbidity status. This information can be used to weigh harm-to-benefit ratios of screening and treatment strategies based on mortality expectancy estimates.

Multimorbidity and associated informal care receiving characteristics for US older adults: a latent class analysis

BackgroundOlder adults with varying patterns of multimorbidity may require distinct types of care and rely on informal caregiving to meet their care needs. This study aims to identify groups of older adults with distinct, empirically-determined multimorbidity patterns and compare characteristics of informal care received among estimated classes.MethodsData are from the 2011 National Health and Aging Trends Study (NHATS). Ten chronic conditions were included to estimate multimorbidity patterns among 7532 individuals using latent class analysis. Multinomial logistic regression model was estimated to examine the association between sociodemographic characteristics, health status and lifestyle variables, care-receiving characteristics and latent class membership.ResultsA four-class solution identified the following multimorbidity groups: some somatic conditions with moderate cognitive impairment (30%), cardiometabolic (25%), musculoskeletal (24%), and multisystem (21%). Compared with those who reported receiving no help, care recipients who received help with household activities only (OR = 1.44, 95% CI 1.05–1.98), mobility but not self-care (OR = 1.63, 95% CI 1.05–2.53), or self-care but not mobility (OR = 2.07, 95% CI 1.29–3.31) had greater likelihood of being in the multisystem group versus the some-somatic group. Having more caregivers was associated with higher odds of being in the multisystem group compared with the some-somatic group (OR = 1.09, 95% CI 1.00-1.18), whereas receiving help from paid helpers was associated with lower odds of being in the multisystem group (OR = 0.36, 95% CI 0.19–0.77).ConclusionsResults highlighted different care needs among persons with distinct combinations of multimorbidity, in particular the wide range of informal needs among older adults with multisystem multimorbidity. Policies and interventions should recognize the differential care needs associated with multimorbidity patterns to better provide person-centered care.

Distinct Comorbidity Clusters in Patients With Acute Heart Failure: Data From RELAX-AHF-2

BackgroundMultimorbidity frequently occurs in patients with acute heart failure (AHF). The co-occurrence of comorbidities often follows specific patterns. ObjectivesThis study investigated multimorbidity subtypes and their associations with clinical outcomes. MethodsFrom the prospective RELAX-AHF-2 (Relaxin for the Treatment of Acute Heart Failure-2) trial, 6,545 patients (26% with HF with preserved ejection fraction, defined as LVEF ≥50%) were classified into multimorbidity groups using latent class analysis. The association between subgroups and clinical outcomes was examined. Validation of these findings was conducted in the RELAX-AHF trial, which comprised 1,161 patients. ResultsFive distinct multimorbidity groups emerged: 1) diabetes and chronic kidney disease (CKD) (often male, high prevalence of CKD and diabetes mellitus); 2) ischemic (ischemic HF); 3) elderly/atrial fibrillation (AF) (oldest, high prevalence of AF); 4) metabolic (obese, hypertensive, more often HF with preserved ejection fraction); and 5) young (fewest comorbidities). After adjusting for confounders, patients in the diabetes and CKD (HR: 1.80; 95% CI: 1.50-2.20), elderly/AF (HR: 1.42; 95% CI: 1.20-1.70), and metabolic (HR: 1.40; 95% CI: 1.20-1.80) groups had higher rates of the composite outcome than patients in the young group, primarily driven by differences in rehospitalization. Treatment allocation (placebo or serelaxin) modified these associations (Pinteraction <0.001). Serelaxin-treated patients in the young group were associated with a lower risk for all-cause mortality (HR: 0.59; 95% CI: 0.40-0.90). Similarly, patients from the RELAX-AHF trial clustered in 5 multimorbidity groups. The clinical characteristics and associations with outcomes could also be validated. ConclusionsComorbidities naturally clustered into 5 mutually exclusive groups in RELAX-AHF-2, showing variations in clinical outcomes. These data emphasize that the specific combination of comorbidities can influence adverse outcomes and treatment responses in patients with AHF.

#559 Validation of the Kidney Failure Risk Equation (KFRE) in individuals with chronic kidney disease and multimorbidity

Abstract Background and Aims Increasing numbers of individuals with chronic kidney disease (CKD) experience multiple long-term conditions (multimorbidity). Clinical guidance recommends the use of validated risk prediction equations, such as the kidney failure risk equation (KFRE), to guide referral to specialist kidney care services. However, multimorbidity may impact the accuracy of creatinine-based eGFR and bias the prognostic utility of KFRE. Equations with alternative filtration markers, such as Cystatin C eGFR (eGFRcys) or the combined creatinine and Cystatin C eGFR (eGFRcrcys), may improve KFRE's risk stratification and discrimination of future kidney failure risks. This study aimed to validate the four-variable KFRE in individuals with CKD, with and without multimorbidity in a research-based cohort (UK Biobank) and a population-based cohort (Stockholm Creatinine Measurements project (SCREAM)). The study also assessed the performance of KFRE when using eGFRcr, eGFRcys and eGFRcrcys. Method Individuals from both cohorts were included if they had CKD, defined as eGFR&amp;lt;60 mL/min/1.73 m2 by any of the three eGFR equations (eGFRcr, eGFRcys and eGFRcrcys), and had available proteinuria measurement at time of testing or within the previous 12 months. Multimorbidity was defined as the presence of two or more long-term conditions in addition to CKD and was grouped into multimorbidity clusters based on previous research. The outcome was kidney failure, defined as the need for long-term dialysis or kidney transplantation. KFRE performance at 2- and 5-years was assessed using the area under the receiver operating characteristic curve and c-index for discrimination and calibration curves for calibration. Results We included 24 489 individuals from UK Biobank and 42 902 individuals from SCREAM (mean age 62.8 (SD 5.6) and 70.1 (SD14.1), 54% and 66% female, respectively). In UK biobank, 14 998 individuals had multimorbidity, of which 5 375 had cardiometabolic multimorbidity. In SCREAM, 30 147 had multimorbidity and 17 854 cardiometabolic multimorbidity. Overall, there were 252 and 312 kidney failure events and 1 108 and 1 471 death events in UK Biobank and 918 and 1 098 kidney failure events and 8 785 and 10 152 death events in SCREAM within 2- and 5-years respectively. Model performance was consistent across both cohorts. Discrimination power of KFRE was good in individuals with and without multimorbidity and across the 2-year and 5-year models (Table 1). Calibration plots revealed over-estimation of risk at 2-years in both cohorts and under-estimation of risk at 5-years in patients with multimorbidity in UK Biobank. There was no improvement in model performance when using eGFRcys or eGFRcrcys compared to eGFRCr. There was a higher cumulative incidence of both kidney failure and death in the multimorbidity group, with a prominent increase in risk of death over time compared to the no multimorbidity group. This was most evident in the SCREAM cohort (Fig. 1). Conclusion KFRE adequately predicts kidney failure in individuals with multimorbidity and either creatinine or cystatin C can be used. Given the high rates of mortality amongst people with multimorbidity, exploration of models that account for the competing risk of death is warranted.

DIABETIC POLYNEUROPATHY AND COMORBIDITY ARE DIABETIC FOOT SYNDROME FORMATION FACTORS

Background. Data from the literature indicate about the development of diabetic polyneuropathy in 5 years after the onset of type 1 diabetes and in 10-15% of patients with newly diagnosed type 2 diabetes. The purpose of the study was to find out the clinical course of diabetic polyneuropathy and to determine the frequency of the occurrence of diabetic foot syndrome in conditions of the comorbidity. Methods. We examined 121 patients, aged from 19 to 69 years, diagnosed with diabetic polyneuropathy due to type 1 and type 2 diabetes. The examined patients were divided into three groups: with diabetic polyneuropathy and cardiovascular comorbidity (group A, n=52), multimorbidity (more than 3 nosologies) (group B, n=30), without comorbidity (group C, n=39). Conclusions. Clinical manifestations of the diabetic polyneuropathy were more significant in the individuals with the cardiovascular comorbidity. The presence of stenoses and occlusions in the arterial channel in groups A and B served as a basis for the formation of ulcerative defects of the limbs in the future.

Multistate survival modelling of multimorbidity and transitions across health needs states and death in an ageing population

BackgroundUnmet health needs have the potential to capture health inequality. Nevertheless, the course of healthcare needs fulfilment, and the role of multimorbidity in this process remains unclear. This study assessed...

Multimorbidity patterns and disability and healthcare use in Europe: do the associations change with the regional socioeconomic status?

Multimorbidity, the concurrence of several chronic conditions, is a rising concern that increases the years lived with disability and poses a burden on healthcare systems. Little is known on how it interacts with socioeconomic deprivation, previously associated with poor health-related outcomes. We aimed to characterize the association between multimorbidity and these outcomes and how this relationship may change with socioeconomic development of regions. 55,915 individuals interviewed in 2017 were drawn from the Survey of Health, Ageing and Retirement in Europe, a population-based study. A Latent Class Analysis was conducted to fit multimorbidity patterns based on 16 self-reported conditions. Physical limitation, quality-of-life and healthcare utilization outcomes were regressed on those patterns adjusting for additional covariates. Those analyses were then extended to assess whether such associations varied with the region socioeconomic status. We identified six different patterns, labelled according to their more predominant chronic conditions. After the “healthy” class, the “metabolic” and the “osteoarticular” classes had the best outcomes involving limitations and the lowest healthcare utilization. The “neuro-affective-ulcer” and the “several conditions” classes yielded the highest probabilities of physical limitation, whereas the “cardiovascular” group had the highest probability of hospitalization. The association of multimorbidity over physical limitations appeared to be stronger when living in a deprived region, especially for metabolic and osteoarticular conditions, whereas no major effect differences were found for healthcare use. Multimorbidity groups do differentiate in terms of limitation and healthcare utilization. Such differences are exacerbated with socioeconomic inequities between regions even within Europe.

Effect of multimorbidity on hypertension management

Multimorbidity, the coexistence of multiple health conditions, is associated with functional decline, disability, and mortality. We aimed to investigate the effects of multimorbidity on hypertension treatment and control rates by analyzing data from the Korean National Health and Nutrition Examination Survey database, which is a cross-sectional, nationally representative survey conducted by the Korean government. Multimorbidity, defined as having two or more chronic diseases, was evaluated by blood pressure measurements, blood chemistry examinations, and questionnaires. We classified the participants according to the number of multimorbidities from 0 to ≥ 6. Association analysis was performed to identify the patterns of multimorbidity related to hypertension control. From 2016 to 2020, 30,271 adults (≥ 20 years) were included in the analysis (age: 52.1 ± 16.8 years, male: 44.0%), and 14,278 (47.2%) had multimorbidity. The number of chronic conditions was significantly higher in older adults, women, and hypertensive patients. Multimorbidity was associated with hypertension treatment. The number of chronic conditions was significantly higher in controlled compared to uncontrolled patients (3.6 ± 1.7 vs 2.9 ± 1.6, p < 0.001). But the control rate of hypertension among treated patients was lower in patients with multimorbidity (75.6% in hypertension only group vs 71.8% in multimorbidity group, p = 0.009). Multimorbidity patterns showed distinct features in treated and controlled hypertensive patients. In conclusion, multimorbidity has a beneficial effect on the treatment of hypertension, but the control rate of systolic blood pressure was lower among the patients with multimorbidity. More attention should be paid to the hypertensive patients with multimorbidity to improve the control rate of hypertension.

The impact of dual VA-Medicare use on a data-driven clinical management tool for older Veterans with multimorbidity.

Healthcare systems are increasingly turning to data-driven approaches, such as clustering techniques, to inform interventions for medically complex older adults. However, patients seeking care in multiple healthcare systems may have missing diagnoses across systems, leading to misclassification of resulting groups. We evaluated the impact of multi-system use on the accuracy and composition of multimorbidity groups among older adults in the Veterans Health Administration (VA). Eligible patients were VA primary care users aged ≥65 years and in the top decile of predicted 1-year hospitalization risk in 2018 (n = 558,864). Diagnoses of 26 chronic conditions were coded using a 24-month lookback period and input into latent class analysis (LCA) models. In a random 10% sample (n = 56,008), we compared the resulting model fit, class profiles, and patient assignments from models using only VA system data versus VA with Medicare data. LCA identified six patient comorbidity groups using VA system data. We labeled groups based on diagnoses with higher within-group prevalence relative to the average: Substance Use Disorders (7% of patients), Mental Health (15%), Heart Disease (22%), Diabetes (16%), Tumor (14%), and High Complexity (10%). VA with Medicare data showed improved model fit and assigned more patients with high accuracy. Over 70% of patients assigned to the Substance, Mental Health, High Complexity, and Tumor groups using VA data were assigned to the same group in VA with Medicare data. However, 41.9% of the Heart Disease group and 14.7% of the Diabetes group were reassigned to a new group characterized by multiple cardiometabolic conditions. The addition of Medicare data to VA data for older high-risk adults improved clustering model accuracy and altered the clinical profiles of groups. Accessing or accounting for multi-system data is key to the success of interventions based on empiric grouping in populations with dual-system use.

Additive effect of frailty with distinct multimorbidity patterns on mortality amongst middle-aged and older adults in Taiwan: A 16-year population-based study.

This study aimed to explore the association between multimorbidity patterns with/without frailty and future mortality among Taiwanese middle-aged and older adults through a population-based cohort study design. Data were collected from the Taiwan Longitudinal Study on Aging. The data were obtained from Wave 3, with the multimorbidity patterns in the years of 1996 being analyzed through latent class analysis. Frailty was defined using the modified Fried criteria. The association between each disease group with/without frailty and mortality was examined using logistic regression, with the reference group as the Relatively healthy group without frailty. Survival analysis was performed using Cox regression, and the follow-up period of mortality was from 1 January 1996 to 31 December 2012. A total of 4748 middle-aged and older adults with an average age of 66.3 years (SD: 9.07 years) were included. Four disease patterns were identified in 1996, namely the Cardiometabolic (21.0%), Arthritis-cataract (11.9%), Relatively healthy (61.6%), and Multimorbidity (5.5%) groups. After adjusting for all covariates, the Relatively healthy group with frailty showed the highest risk for mortality (odds ratio: 3.66, 95% confidence interval [95% CI]: 2.24-5.95), followed by the Cardiometabolic group with frailty (odds ratio: 3.58, 95% CI: 1.96-6.54), Multimorbidity group with frailty (odds ratio: 2.28, 95% CI: 1.17-4.44), Multimorbidity group without frailty (odds ratio: 1.44, 95% CI: 1.01-2.04), and the Cardiometabolic group without frailty (odds ratio: 1.24, 95% CI: 1.04-1.49). Frailty plays an important role in mortality among middle-aged and older adults with distinct multimorbidity patterns. Middle-aged and older adults with a relatively healthy multimorbidity pattern or a cardiometabolic multimorbidity pattern with frailty encountered dismal outcomes. Geriatr Gerontol Int 2023; 23: 684-691.

Quality of life and associated factors among community-dwelling adults with multimorbidity in Shanghai, China: A cross-sectional study.

To compare the quality of life of patients with and without multimorbidity and investigate potential factors related to the quality of life in patients with multimorbidity. A descriptive cross-sectional study. This study included 1778 residents with chronic diseases, including single disease (1255 people, average age: 60.78 ± 9.42) and multimorbidity (523 people, average age: 64.03 ± 8.91) groups, who were recruited from urban residents of Shanghai through a multistage, stratified, probability proportional to size sampling method. The quality of life was measured using the World Health Organization Quality of Life Questionnaire. The socio-demographic data and psychological states were measured using a self-made structured questionnaire, Self-rating Anxiety Scale, and Self-rating Depression Scale. Differences in demographic characteristics were estimated using Pearson's chi-squared test, and independent t-test or one-way ANOVA followed by S-N-K test was used to compare the mean quality of life. Multiple linear regression analysis was conducted to identify risk factors for multimorbidity. There were differences in age, education, income, and BMI between single-disease and multimorbidity groups, but no differences in gender, marriage, and occupation. Multimorbidity had lower quality of life, reflected in all four domains. Multiple linear regression analyses showed that low level of education, low income, number of diseases, depression, and anxiety were negatively related to quality of life in all domains.

Association between multimorbidity patterns and incident depression among older adults in Taiwan: the role of social participation

BackgroundPrevious research has found different multimorbidity patterns that negatively affects health outcomes of older adults. However, there is scarce evidence, especially on the role of social participation in the association between multimorbidity patterns and depression. Our study aimed to explore the relationship between multimorbidity patterns and depression among older adults in Taiwan, including the social participation effect on the different multimorbidity patterns.MethodsData were retracted from the Taiwan longitudinal study on ageing (TLSA) for this population-based cohort study. 1,975 older adults (age > 50) were included and were followed up from 1996 to 2011. We used latent class analysis to determine participants’ multimorbidity patterns in 1996, whereas their incident depression was determined in 2011 by CES-D. Multivariable logistic regression was used to analyse the relationship between multimorbidity patterns and depression.ResultsThe participants’ average age was 62.1 years in 1996. Four multimorbidity patterns were discovered through latent class analysis, as follows: (1) Cardiometabolic group (n = 93), (2) Arthritis-cataract group (n = 105), (3) Multimorbidity group (n = 128) and (4) Relatively healthy group (n = 1649). Greater risk of incident depression was found among participants in the Multimorbidity group (OR: 1.62; 95% CI: 1.02–2.58) than the Relatively healthy group after the multivariable analysis. Compare to participants in the relatively healthy group with social participation, participants in the arthritis-cataract group without social participation (OR: 2.22, 95% CI: 1.03–4.78) and the multimorbidity group without social participation (OR: 2.21, 95% CI: 1.14–4.30) had significantly increased risk of having depression.ConclusionDistinct multimorbidity patterns among older adults in Taiwan are linked with the incident depression during later life, and social participation functioned as a protective factor.

Association between multimorbidity and memory-related diseases among middle-aged and older adults: Evidence from the China Health and Retirement Longitudinal Study.

This study aimed to examine the cross-sectional and longitudinal association between multimorbidity and memory-related diseases (MDs) among Chinese middle-aged and older adults. This study included 8,338 subjects who participated in the China Health and Retirement Longitudinal Study (CHARLS). Logistic regression and Cox proportional hazards regression models were used to explore the association and effect of multimorbidity on MDs. The overall prevalence of MDs was 2.52%, and the mean multimorbidity number was 1.87. In a cross-sectional analysis, compared with the no multimorbidity group, groups of multimorbidity with four or more non-communicable diseases (NCDs) were more likely to have MDs (OR: 6.49, 95%CI: 4.35-9.68). Within 2.7 years of follow-up, 82 cases of MDs (1.12%) were reported, and participants with multimorbidity were more likely to have new-onset MDs than participants without multimorbidity (HR: 2.93, 95%CI: 1.74-4.96). Multimorbidity is associated with MDs among Chinese middle-aged and older adults. This relationship gradually strengthens with the severity of multimorbidity, which indicates that early prevention for people with multimorbidity may reduce the risk of MDs.

Trends and all-cause mortality associated with multimorbidity of non-communicable diseases among adults in the United States, 1999-2018: a retrospective cohort study.

Multimorbidity of non-communicable diseases (NCDs) has brought enormous challenges to public health, becoming a major medical burden. However, the patterns, temporal trends, and all-cause mortality associated with NCD multimorbidity over time have not been well described in the United States. All adult participants were sourced from nationally representative data from the National Health and Nutrition Examination Survey. In total, 55,081 participants were included in trend analysis, and 38,977 participants were included in Cox regression. The 5 NCDs with the largest increases over the study period were diabetes, osteoporosis, obesity, liver conditions, and cancer. The estimated prevalence of multimorbidity increased with age, especially for middle-aged participants with 5 or more NCDs; in general, the prevalence of NCD multimorbidity was higher among females than males. Participants with 5 or more NCDs were at 4.49 times the risk of all-cause mortality of participants without any diseases. Significant interactions were found between multimorbidity and age group (p for interaction <0.001), race/ethnicity (p for interaction<0.001), and educational attainment (p for interaction=0.010). The prevalence of multiple NCDs significantly increased from 1999 to 2018. Those with 5 or more NCDs had the highest risk of all-cause mortality, especially among the young population. The data reported by this study could serve as a reference for additional NCD research.

1319 INTERACTION BETWEEN DISTINCT MULTIMORBIDITY PATTERNS AND DISABILITY AND ITS ASSOCIATION WITH FUTURE MORTALITY AMONG OLDER ADULTS

Abstract Background Multimorbidity patterns is associated with future mortality among older adults. However, the addictive effect of disability for distinct multimorbidity patters is unclear. Our aim was to identify the multimorbidity patterns of Taiwanese people aged over 50 years and to explore their association between multimorbidity patterns with/without disability and future mortality. Methods 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 analysed separately by latent class analysis (LCA). The association between each disease group with/without disability and mortality was examined using logistic regression. Results 5124 older adults with average age of 66.7 years old were included. Four disease patterns were identified in 1996, namely, the cardiometabolic (21.6%), arthritis-cataract (11.6%), relatively healthy (61.2%), and multimorbidity (5.6%) groups. After adjusting all the confounders, the cardiometabolic group with disability showed the highest risk for mortality (odds ratio: 2.83, 95% CI: 1.70-4.70), followed by Multimorbidity group with disability (odds ratio: 2.33, 95% CI: 1.17-4.64) and relatively health group with disability (odds ratio: 1.79, 95% CI: 1.22-2.62) and cardiometabolic group without disability (odds ratio: 1.21, 95% CI: 1.01-1.45). Conclusion This longitudinal study reveals disability plays an important role on mortality among older adults with distinct multimorbidity patterns. Older adults with a cardiometabolic multimorbidity pattern with disability had a dismal outcome. Thus, healthcare professionals should put more emphasis on the prevention and identification of cardiometabolic multimorbidity, with routine check-up of their functional limitation.

1266 ASSOCIATION OF MULTIMORBIDITY PATTERNS AND INCIDENT DEPRESSION AMONG OLDER ADULTS IN TAIWAN: ROLE OF SOCIAL PARTICIPATION

Abstract Background Multimorbidity has negative impacts on the health outcomes of older adults. Previous research has discovered different patterns of multimorbidity. However, evidence is scarce for associations between multimorbidity patterns and depression, especially the role of social participation in it. This study aimed to explore the relationship between multimorbidity patterns and depression among older adults in Taiwan and the effect of social participation in different multimorbidity patterns. Methods This population-based cohort study used data from the Taiwan Longitudinal Study on Aging. It included 1,975 older adults (age &amp;gt;50 years) who were followed from 1996 to 2011. The participants’ multimorbidity patterns in1996 were determined by latent class analysis; their incident depression was ascertained in 2011 by using the 10-item CES-D. Multivariate logistic regression was used to analyse the relationship between multimorbidity patterns and depression. Results In 1996, the participants’ average age was 62.1 years. Four multimorbidity patterns were discovered through latent class analysis, as follows: (1) Cardiometabolic group (n = 93), (2) Arthritis–cataract group (n = 105), (3) Multimorbidity group (n = 128), and (4) Relatively healthy group (n = 1649). After multivariate analysis, participants in the Multimorbidity group had a greater risk of incident depression (Odds ratio: 1.62; 95% Confidence interval: 1.02–2.58), compared with the Relatively healthy group. Subgroup analysis showed that participants without social participation in the Arthritis-Cataract and Multimorbidity groups had greater risks of developing depression. Conclusion This 16-year, population-based cohort study showed that distinct multimorbidity patterns among older adults in Taiwan were associated with incident depression during later life, while social participation played a role as protective factor.

The Association of Multimorbidity With Whole Health Activities Among Adults in the United States: Evidence From the NHIS and BRFSS.

Whole health is a holistic approach encompassing integrative medicine, emotional, and spiritual health and is critical to improving health outcomes among individuals with multimorbidity. To examine the prevalence of Whole Health activities and the association of multimorbidity and Whole Health activities using nationally representative datasets. As no single dataset has information on Whole Health self-care activities, data from the 2017 National Health Interview Survey (n = 25134) was used to measure participants' mind-body therapy usage, sleep, mental health, and physical activity. We used the 2017 Behavioral Risk Factor Surveillance System (n = 347029) to assess regular vegetable and/or fruit consumption. A significantly lower percentage of adults with multimorbidity had adequate sleep (58.2%vs.67.1%), no psychological distress (71.8%vs.82.1%), adequate physical activity (48.2%vs.62.1%), and regular vegetable and/or fruit consumption (54.2%vs.56.6%) compared to those without multimorbidity. Although lower percentages of adults with multimorbidity utilized mind-body therapies (22.9%vs.25.2%), the association was reversed when adjusted for socioeconomic factors. In the fully adjusted models, adults with multimorbidity were more likely to use mind-body therapies (AOR = 1.19, 95%CI = 1.09, 1.31). Furthermore, when adjusting for other independent variables, the associations of multimorbidity with sleep, psychological distress, and diet were exacerbated, and the association of multimorbidity with physical activity was attenuated. Adults with multimorbidity were less likely to engage in most of the Whole Health activities except mind-body therapies compared to the no multimorbidity group. Findings suggest that adjustment for other factors such as age and socioeconomic status changed the magnitude and direction of the association of multimorbidity with Whole Health activities.

MULTIMORBIDITY PROGRESSION AMONG MEDICARE BENEFICIARIES IN THE HEALTH AND RETIREMENT STUDY (1991–2015)

Abstract Older adults are at greater risk for developing and accumulating multimorbidity (2+ chronic conditions). This study describes the characteristics of older adults with multimorbidity using Medicare claims over a 24-year period. The HRS-Medicare data (1991-2015, N=17,199, age 67+ years) were used in descriptive analyses. We identified 8,800 (51%) beneficiaries who did not have multimorbidity at first observation (no multimorbidity), 6,270 (36%) with 2-4 conditions at the first observation (low multimorbidity), and 2,129 (12%) with 5+ conditions at the first observation (high multimorbidity). Older respondents (80+ years) had lower levels of multimorbidity at baseline compared with younger respondents (&amp;lt; 70 years); this appeared to be related to differences by birth cohort. Higher proportions of minoritized groups had high multimorbidity (15% non-Hispanic Black; 20% Hispanic; 11% non-Hispanic White). Despite only being 22% of the entire sample, persons with obese body mass index (&amp;gt;30) represented 41% of the high multimorbidity group. Higher incidence rates of disease accumulation were noted for Black (89/1,000 person years [py]) and Hispanic (94/1,000 py) compared with White respondents (82/1,000 py) in the high multimorbidity group. Hospitalization and ED rates increased linearly between the low and high multimorbidity groups. Functional loss was more prevalent in the high multimorbidity group compared with the no multimorbidity group; no difference was observed between no and low multimorbidity. Results highlight sociodemographic differences between Medicare fee-for-service beneficiaries with differing levels of multimorbidity, allowing new insights to guide interventions that address burdensome changes in late life.