Classifying Veterans' pre-pregnancy health risks using latent class analysis.

Abstract

Background: Veterans using Department of Veterans Affairs (VA) healthcare have a high burden of pre-pregnancy chronic disease that likely contributes to the observed high rate of pregnancy-related morbidity. Many common diseases frequently co-occur; understanding patterns of multimorbidity may inform the design and delivery of pre-pregnancy interventions to lower pregnancy morbidity risk.

Objective: The current study sought to identify patterns of co-occurrence of pre-pregnancy chronic disease among Veterans.

Design: We conducted a retrospective cohort study using VA administrative data.

Methods: Our population included Veterans ages 18-45 with ⩾1 pregnancy outcome (ectopic, spontaneous abortion, stillbirth, and/or live birth) during fiscal years 2010-2019. Presence of common chronic diseases with implications for pregnancy was detected using encounter International Classification of Diseases, 9th and 10th Revision (ICD-9 and ICD-10) codes in the 2 years prior to pregnancy. Patients were grouped based on latent class models of diagnosis patterns; two to seven latent groups were examined for model fit and clinical interpretability.

Results: We identified 56,853 pregnancies from 41,034 Veterans. More than half of pregnancies were complicated by an array of pre-pregnancy medical and mental health conditions that may negatively impact pregnancy health and contribute to adverse pregnancy outcomes. The most frequently occurring conditions included chronic pain (51.2% of pregnancies), depression (31.4%), anxiety (25.9%), and post-traumatic stress disorder (22.8%). A five-group model demonstrated the best balance between model fit and clinical interpretability. Groups included: "Pain and Mental Health" (28%), with high prevalence of chronic pain, depression, and anxiety; "Pain and Metabolic" (17%), high prevalence of chronic pain, obesity, and migraines; "Substance Use and Mental Health" (7%), high prevalence of alcohol use disorder, depression, and post-traumatic stress disorder; "Low Diagnosis" (43%), lower than average prevalence of diagnoses; and "High Complexity" (5%), high prevalence of conditions across multiple physiologic systems.

Conclusions: We identified five distinct, clinically meaningful groups of Veterans based on co-occurring pre-pregnancy diseases. Tailoring interventions to these groups may address Veterans' complex pre-pregnancy health risks effectively and efficiently.