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Depressive Symptom Subgroups and Their Association with Prevalent and Incident Cardiovascular Risk Factors in the Coronary Artery Risk Development in Young Adults (CARDIA) Study

Diana A Chirinos, Kiarri N Kershaw, Norrina B Allen, Allison J Carroll, Tené T Lewis, Pamela J Schreiner, Cora E Lewis, Catarina I Kiefe, Briana Mezuk, Mercedes R Carnethon

International Journal of Behavioral Medicine

Background: We sought to identify depressive symptom subgroups in a community sample of young adults, investigate their stability over time, and determine their association with prevalent and incident cardiovascular disease (CVD) risk factors.

Method: Participants were 3377 adults from the Coronary Artery Risk Development in Young Adults study. Using latent class and latent transition analysis, we derived subgroups based on items of the 20-item version of the Center for Epidemiologic Studies Depression Scale in 1990, and examined patterns of change over a 10-year period (1990-2000). Cox regression models were used to examine associations between subgroup membership and prevalent (2000) and incident (2000 to 2016) obesity, hypertension, and diabetes.

Results: Three baseline subgroups were identified and labeled: "No Symptoms" (63.5%), "Lack of Positive Affect" (PA, 25.6%), and "Depressed Mood" (10.9%). At 10-year follow-up, individuals in "No Symptoms" subgroup had the highest probability (0.84) of being classified within the same subgroup. Participants classified as "Lack of PA" were likely (0.46) to remain in the same subgroup or be classified as "No Symptoms." Participants in the "Depressed Mood" were most likely to transition to the "Lack of PA" subgroup (0.38). Overall, 30.5% of participants transitioned between subgroups, with 11.4% classified as "Worsening" and 19.1% as "Improving." Relative to the "No Symptoms Stable," other subgroups ("Depressed Stable," "Worsening," and "Improving") were associated with prevalent obesity and hypertension.

Conclusion: We identified distinct depressive symptom subgroups that are variably stable over time, and their change patterns were differentially associated with CVD risk factor prevalence.