Dataset Information

Prevalence of Chronic Conditions and Multimorbidities in a Geographically Defined Geriatric Population With Diverse Races and Ethnicities.

ABSTRACT: OBJECTIVE:The objective of this study is to examine racial/ethnic differences in prevalence of chronic conditions and multimorbidities in the geriatric population of a state with diverse races/ethnicities. METHOD:Fifteen chronic conditions and their dyads and triads were investigated using Hawaii Medicare 2012 data. For each condition, a multivariable logistic regression model was used to investigate differences in race/ethnicity, adjusting for subject characteristics. RESULTS:Of the 84,212 beneficiaries, 27.8% were Whites, 54.6% Asians, and 5.2% Hispanics. Racial/ethnic disparities were prevalent for most conditions. Compared with Whites, Asians, Hispanics, and Others showed significantly higher prevalence rates in hypertension, hyperlipidemia, diabetes, and most dyads or triads of the chronic conditions. However, Whites had higher prevalence rates in arthritis and dementia. DISCUSSION:Race/ethnicity may need to be considered when making clinical decisions and developing health care programs to reduce health disparities and improve quality of life for older individuals with chronic conditions.

SUBMITTER: Lim E

PROVIDER: S-EPMC5634944 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

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Prevalence of Chronic Conditions and Multimorbidities in a Geographically Defined Geriatric Population With Diverse Races and Ethnicities.

Lim Eunjung E Gandhi Krupa K Davis James J Chen John J JJ

Journal of aging and health 20161202 3

<h4>Objective</h4>The objective of this study is to examine racial/ethnic differences in prevalence of chronic conditions and multimorbidities in the geriatric population of a state with diverse races/ethnicities.<h4>Method</h4>Fifteen chronic conditions and their dyads and triads were investigated using Hawaii Medicare 2012 data. For each condition, a multivariable logistic regression model was used to investigate differences in race/ethnicity, adjusting for subject characteristics.<h4>Results< ...[more]

PMID: 27913765

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Project description:BackgroundThe strategic framework on multiple chronic conditions released by the US Department of Health and Human Services calls for identifying homogeneous subgroups of older adults to effectively target interventions aimed at improving their health.ObjectiveWe aimed to identify combinations of chronic conditions, functional limitations, and geriatric syndromes that predict poor health outcomes. DESIGN, SETTING AND PARTICIPANTS Data from the 2010-2012 Health and Retirement Study provided a representative sample of U.S. adults 50 years of age or older (n?=?16,640).Main measuresOutcomes were: Self-reported fair/poor health, self-rated worse health at 2 years, and 2-year mortality. The main independent variables included self-reported chronic conditions, functional limitations, and geriatric syndromes. We conducted tree-based classification and regression analysis to identify the most salient combinations of variables to predict outcomes.Key resultsTwenty-nine percent and 23 % of respondents reported fair/poor health and self-rated worse health at 2 years, respectively, and 5 % died in 2 years. The top combinations of conditions identified through our tree analysis for the three different outcome measures (and percent respondents with the outcome) were: a) for fair/poor health status: difficulty walking several blocks, depressive symptoms, and severe pain (> 80 %); b) for self-rated worse health at 2 years: 68.5 years of age or older, difficulty walking several blocks and being in fair/poor health (60 %); and c) for 2-year mortality: 80.5 years of age or older, and presenting with limitations in both ADLs and IADLs (> 40 %).ConclusionsRather than chronic conditions, functional limitations and/or geriatric syndromes were the most prominent conditions in predicting health outcomes. These findings imply that accounting for chronic conditions alone may be less informative than also accounting for the co-occurrence of functional limitations and geriatric syndromes, as the latter conditions appear to drive health outcomes in older individuals.

Project description:Background & aimsThere are racial and ethnic differences in the incidence of gastric adenocarcinoma worldwide and in the US. Based on a decision analysis, screening for noncardia gastric adenocarcinoma might be cost-effective for non-White individuals 50 years or older. However, a lack of precise, contemporary information on gastric adenocarcinoma incidence in specific anatomic sites for this age group has impeded prevention and early detection programs in the US. We aimed to estimate the differences in gastric adenocarcinoma incidence in specific anatomic sites among races and ethnicities in individuals 50 years or older.MethodsWe analyzed California Cancer Registry data from 2011 through 2015 to estimate incidences of gastric adenocarcinoma in specific anatomic sites for non-Hispanic White (NHW), non-Hispanic Black, Hispanic, and the 7 largest Asian American populations. We calculated the differential incidence between non-White groups and NHW using incidence rate ratios and 95% confidence intervals (CIs).ResultsCompared with NHW subjects, all non-White groups had significantly higher incidences of noncardia gastric adenocarcinoma; the incidence was highest among Korean American men 50 years and older (70 cases per 100,000). Compared with NHW subjects 50 years and older, the risk of noncardia gastric adenocarcinoma was 1.8-fold (95% CI, 1.37-2.31) to 7.3-fold (95% CI, 5.73-9.19) higher in most non-White groups and 12.0-fold (95% CI, 9.96-14.6) to 14.5-fold (95% CI, 12.5-16.9) higher among Korean American men and women 50 years and older, respectively. Compared with NHW men 50 years and older, all non-White men, except Japanese and Korean American men, had a significantly lower risk of cardia gastric adenocarcinoma.ConclusionsWe identified several-fold differences in incidences of gastric adenocarcinoma in specific anatomic sites among racial and ethnic groups, with significant age and sex differences. These findings can be used to develop targeted risk reduction programs for gastric adenocarcinoma.

Dataset Information

Prevalence of Chronic Conditions and Multimorbidities in a Geographically Defined Geriatric Population With Diverse Races and Ethnicities.

Publications

Prevalence of Chronic Conditions and Multimorbidities in a Geographically Defined Geriatric Population With Diverse Races and Ethnicities.

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