Key result
Latent class analysis identifies cardiovascular risk phenotypes in ~38% of senior women Veterans.
Why the study?
Senior-aged women Veterans experience multiple morbidities that require characterization to better prepare healthcare systems to meet their needs.
Observational (n=38,597)
Yes
Senior-aged women Veterans exhibit six major multimorbidity clusters, with the largest group being at risk for cardiovascular disease, highlighting the need for tailored clinical practice guidelines.
Reveals cardiovascular risk as dominant multimorbidity cluster in older women Veterans; hypothesis-generating for targeted strategies pending validation.
BACKGROUND AND OBJECTIVES: This study characterizes the multiple morbidities experienced by senior-aged women Veterans so that the Veterans Health Administration (VHA) and other healthcare systems may be better prepared to meet the healthcare needs of this growing cohort. RESEARCH DESIGN AND METHODS: Using the VHA's Corporate Data Warehouse (CDW), we conducted a retrospective observational study of the 38,597 female veteran patients who were at least sixty-five years old and received care in the VHA during 2013 and 2014. We use a latent class analysis model to cluster diagnoses associated with inpatient and outpatient events over the years. RESULTS: The senior-aged women Veterans are characterized by six major classes of disease clusters. We defined these classes as: Healthy (16.24% of the cohort); Ophthalmological Disorders (13.84%); Musculoskeletal Disorders (14.22%); At Risk for Cardiovascular Disease (37.53%); Diabetic with Comorbidities (9.05%); and Multimorbid (9.12%). The patterns and prevalence of these condition classes vary by race, age and marital status. DISCUSSION AND IMPLICATIONS: Each of the six clusters can be used to develop clinical practice guidelines that are appropriate for senior-aged women Veterans. Consistent with past literature, the most common conditions in this cohort are hypertension and hyperlipidemia; together they form the most common class, "At Risk of Cardiovascular Disease (CVD)". Results also show evidence of race-related disparities, with Blacks being more likely to be in the highest risk classes. Also, members of the cohort who are currently married having improved chances of being in the healthy class. And finally, we see a "healthy survivor" effect with the oldest women in our cohort having low overall rates of disease.
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Gonsoulin et al. (2017) conducted an observational in Multiple morbidities (n=38,597). Multiple morbidities was evaluated on Major classes of disease clusters. Latent class analysis identified six major disease clusters among senior-aged women Veterans, most commonly 'At Risk for Cardiovascular Disease' (37.53%) and 'Healthy' (16.24%).
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