Social risk factors are independently associated with cognitive and affective symptoms of depression, and more chronic diseases are independently associated with somatic symptoms, according to a study published in the Journal of Affective Disorders.

In this cross-sectional, population-based study, researchers analyzed individual-level data of participants of 6 US National Health and Nutrition Examination Surveys carried out between 2005 and 2016 (N=31,191). Depressive symptoms were assessed in all adult participants using the 9-item Patient Health Questionnaire. Investigators used the number of chronic diseases as a measure of overall physical health. The 3 social risk factors that were used included perceived lack of emotional support, divorce, and poverty status. A total of 36 tests were carried out, including 9 depressive symptoms and 4 risk factors (considering the number of chronic diseases as a continuous variable). The Benjamini-Hochberg test was used to examine the likelihood of finding false-positive associations.

Adjusting for sex, age, and race/ethnicity, there was a monotonic dose-dependent trend between the number of chronic diseases, feeling tired and having little energy, and moving/speaking slowly (or too fast). The depressive symptoms were more severe when more chronic diseases were reported.

Individuals who were divorced had higher levels of anhedonia, sad mood, worthlessness, suicidal ideation, and sleep problems. Poverty was related to higher levels of anhedonia, sad mood, suicidal thoughts, and slow movement/agitation. Perceived lack of emotional support was associated with anhedonia, sad mood, worthlessness, and poor appetite. All associations would have been statistically significant when allowing for a false discovery rate of 0.1, suggesting most associations were unlikely to be false discoveries.

Limitations of this study include its cross-sectional design and basis on a population-based sample as well as its assessment of depressive symptoms on a self-reported rating scale.

Symptom-level analysis of risk factor types may help to delineate more homogenous subsyndromes of depression and can be used to identify more specific structures and dynamics of depressive states.

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