ArticleInnovation in aging2017
A Health Profile of Senior-Aged Women Veterans: A Latent Class Analysis of Condition Clusters.
Article in Innovation in aging, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 3 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed, 3 syntheses or guidelines pooled it, 13 citations in OpenAlex.
- A systematic review of latent class analysis in psychology: Examining the gap between guidelines and research practice.Behavior research methods · 2025Pooled it
- An Evidence Map of the Women Veterans' Health Literature, 2016 to 2023: A Systematic Review.JAMA network open · 2025Pooled it
- Do replicable profiles of multimorbidity exist? Systematic review and synthesis.European journal of epidemiology · 2019Pooled it
- When the golden years are not so golden: Aging women Veterans, MST, PTSD, and homelessness.Journal of military, veteran and family health · 2026Article
- Middle-age healthcare spending and utilization at the intersection of comorbidities, functional limitation, and race/ethnicity.Innovation in aging · 2026Article
- Multimorbidity patterns and mortality in older adults: a two-cohort pooled analysis.Aging clinical and experimental research · 2025Article
- Multimorbidity classes indicate differential patterns of health care engagement among people who inject drugs.Journal of substance abuse treatment · 2022Article
- Article
- Patterns of Multimorbidity and Differences in Healthcare Utilization and Complexity Among Acutely Hospitalized Medical Patients (≥65 Years) - A Latent Class Approach.Clinical epidemiology · 2020Article
- A mobile telehealth program for behavioral treatment of urinary incontinence in women Veterans: Qualitative evaluation of MyHealthJournal of women & agingArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 5 institutions in 1 country.
Funding
Abstract
BACKGROUND AND
objectivesThis 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
methodsUsing 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.
resultsThe 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.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.