TY - JOUR
T1 - Symptom profiles of women at risk of mood disorders
T2 - A latent class analysis
AU - Weiss, Sandra J.
AU - Flynn, Heather
AU - Christian, Lisa
AU - Hantsoo, Liisa
AU - di Scalea, Teresa Lanza
AU - Kornfield, Sara L.
AU - Muzik, Maria
AU - Simeonova, Diana I.
AU - Cooper, Bruce A.
AU - Strahm, Anna
AU - Deligiannidis, Kristina M.
N1 - Publisher Copyright:
© 2021
PY - 2021/12/1
Y1 - 2021/12/1
N2 - Background: Depression is the leading cause of disease burden among women worldwide. However, an understanding of symptom profiles among women at risk of mood disorders is limited. We determined distinct profiles of affective symptoms among high risk women, along with their distinguishing characteristics. Methods: Women were recruited from 17 clinical sites affiliated with the National Network of Depression Centers. They completed measures of depression (Patient Health Questionnaire – 9) and anxiety (Generalized Anxiety Disorder – 7) as well as questions regarding demographics, reproductive status, behavioral/mental health history, and life stress/adversity. Latent class analysis and multinomial logistic regression were used to identify and characterize symptom profiles. Results: 5792 women participated, ages 18 to 90 (M = 38). Three latent classes were identified: generally asymptomatic (48%), elevated symptoms of comorbid anxiety and depression (16%), and somatic symptoms (36%). Financial security and greater social support were protective factors that distinguished asymptomatic women. The profile of the class with elevated anxiety/depressive symptoms constituted a complex mix of adverse social determinants and potentially heritable clinical features, including a diagnosis of Bipolar Disorder. Women in the 3rd latent class were characterized by menstrual irregularity and a stronger expression of neurovegetative symptoms, especially sleep disturbance and fatigue. Limitations: Limitations included less than optimal racial diversity of our sample and reliance on self-report. Conclusions: Different symptom profiles may reflect distinct subtypes of women at risk of mood disorders. Understanding the etiology and mechanisms underlying clinical and psychosocial features of these profiles can inform more precisely targeted interventions to address women's diverse needs.
AB - Background: Depression is the leading cause of disease burden among women worldwide. However, an understanding of symptom profiles among women at risk of mood disorders is limited. We determined distinct profiles of affective symptoms among high risk women, along with their distinguishing characteristics. Methods: Women were recruited from 17 clinical sites affiliated with the National Network of Depression Centers. They completed measures of depression (Patient Health Questionnaire – 9) and anxiety (Generalized Anxiety Disorder – 7) as well as questions regarding demographics, reproductive status, behavioral/mental health history, and life stress/adversity. Latent class analysis and multinomial logistic regression were used to identify and characterize symptom profiles. Results: 5792 women participated, ages 18 to 90 (M = 38). Three latent classes were identified: generally asymptomatic (48%), elevated symptoms of comorbid anxiety and depression (16%), and somatic symptoms (36%). Financial security and greater social support were protective factors that distinguished asymptomatic women. The profile of the class with elevated anxiety/depressive symptoms constituted a complex mix of adverse social determinants and potentially heritable clinical features, including a diagnosis of Bipolar Disorder. Women in the 3rd latent class were characterized by menstrual irregularity and a stronger expression of neurovegetative symptoms, especially sleep disturbance and fatigue. Limitations: Limitations included less than optimal racial diversity of our sample and reliance on self-report. Conclusions: Different symptom profiles may reflect distinct subtypes of women at risk of mood disorders. Understanding the etiology and mechanisms underlying clinical and psychosocial features of these profiles can inform more precisely targeted interventions to address women's diverse needs.
KW - Anxiety
KW - Depression
KW - Latent class analysis
KW - Mood
KW - Symptom clusters
KW - Women
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U2 - 10.1016/j.jad.2021.08.013
DO - 10.1016/j.jad.2021.08.013
M3 - Article
C2 - 34450523
AN - SCOPUS:85113306241
SN - 0165-0327
VL - 295
SP - 139
EP - 147
JO - Journal of Affective Disorders
JF - Journal of Affective Disorders
ER -