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Significant health disparities exist among socioeconomically disadvantaged women, who experience elevated rates of depression and increased risk for poor depression treatment engagement and outcomes.
Injection of glucose plus GLP-1 in the diabetic rats showed that GLP-1 amplified the insulin response but induced a transient increase and then a poor depression of glucagon.
With an increasing number of these features, the likelihood of poor depression treatment outcome increased linearly.
The presence of pain and functional impairment may help identify those at risk for poor depression treatment outcome.
This result was surprising because in previous studies in adults sleep disturbances have been identified as risk factors for poor depression treatment outcome.
Logistic regression analysis was used to determine significant (P ≤ 0.05) predictors of poor depression treatment outcome (i.e., no improvement, nonresponse, nonpartial remission, and nonfull remission) in order to identify factors that might themselves be targets of intervention.
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A similar disconnect between aspirations and reality may help explain the association between employment and poorer depression outcomes for both genders.
Controlling for baseline depression, a linear regression model showed that the presence of pain at baseline was associated with poorer depression outcomes at 3 months mean difference=−1.16, (95% CI 0.12 to 2.2).
An ANCOVA model controlling for these covariates and baseline PHQ-9 revealed that the effect of pain group remained significant, with patients with baseline pain having poorer depression outcomes (mean difference=−1.16, 95% CI −2.2 to −0.12, p=0.028).
Psychosocial variables found to be associated with frailty included anxiety, poor wellbeing, depression and low sense of control (mastery).
A series of regression models (online supplement 1) identified three other significant predictors of poorer outcome of depression: poor EQ-5D mobility, loss of energy (BDI II item 15) and being male.
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