Background: Worldwide, oral contraceptive (OC) use is a very common form of birth control, although it has been associated with symptoms of depression and insomnia. Insomnia is a risk factor for... Show moreBackground: Worldwide, oral contraceptive (OC) use is a very common form of birth control, although it has been associated with symptoms of depression and insomnia. Insomnia is a risk factor for major depressive disorder (MDD) but may also be a symptom of the disorder. Despite the large number of women who use OC, it is yet unknown whether women with previous or current diagnosis of depression are more likely to experience more severe depressive and insomnia symptoms during concurrent OC use than women without diagnosis of depression. Aim: This study examined associations between OC use and concurrent symptoms of depression (including atypical depression) and insomnia as well as between OC and prevalences of concurrent dysthymia and MDD. Participants were adult women with and without a history of MDD or dysthymia. We hypothesized that OC use is associated with concurrent increased severity of depressive symptoms and insomnia symptoms, as well as with an increased prevalence of concurrent diagnoses of dysthymia and MDD. We also hypothesized that a history of MDD or dysthymia moderates the relationship between OC use and depressive and insomnia symptoms. Methods: Measurements from premenopausal adult women from the Netherlands Study of Depression and Anxiety (NESDA) were grouped, based on whether participants were using OC or naturally cycling (NC). OC use, timing and regularity of the menstrual cycle were assessed with a structured interview, self-reported symptoms of depression (including atypical depression), insomnia with validated questionnaires, and MDD and dysthymia with structured diagnostic interviews. Results: We included a total of 1301 measurements in women who reported OC use and 1913 measurements in NC women (mean age 35.6, 49.8% and 28.9% of measurements in women with a previous depression or current depression, respectively). Linear mixed models showed that overall, OC use was neither associated with more severe depressive symptoms (including atypical depressive symptoms), nor with higher prevalence of diagnoses of MDD or dysthymia. However, by disentangling the amalgamated overall effect, within-person estimates indicated increased depressive symptoms and depressive disorder prevalence during OC use, whereas between-person estimated indicated lower depressive symptoms and prevalence of depressive disorders. OC use was consistently associated with more severe concurrent insomnia symptoms, in the overall estimates as well as in the within-person and between-person estimates. Presence of current or previous MDD or dysthymia did not mod-erate the associations between OC use and depressive or insomnia symptoms. Discussion: The study findings showed consistent associations between OC use and more severe insomnia symptoms, but no consistent associations between OC and depressive symptoms or diagnoses. Instead, post-hoc analyses showed that associations between OC and depression differed between within-and between person -estimates. This indicates that, although OC shows no associations on the overall level, some individuals might experience OC-associated mood symptoms. Our findings underscore the importance of accounting for individual differences in experiences during OC use. Furthermore, it raises new questions about mechanisms underlying associations between OC, depression and insomnia. Show less
Background: Predicting the onset and course of mood and anxiety disorders is of clinical importance but remains difficult. We compared the predictive performances of traditional logistic regression... Show moreBackground: Predicting the onset and course of mood and anxiety disorders is of clinical importance but remains difficult. We compared the predictive performances of traditional logistic regression, basic probabilistic machine learning (ML) methods, and automated ML (Auto-sklearn).Methods: Data were derived from the Netherlands Study of Depression and Anxiety. We compared how well multinomial logistic regression, a naïve Bayes classifier, and Auto-sklearn predicted depression and anxiety diagnoses at a 2-, 4-, 6-, and 9-year follow up, operationalized as binary or categorical variables. Predictor sets included demographic and self-report data, which can be easily collected in clinical practice at two initial time points (baseline and 1-year follow up).Results: At baseline, participants were 42.2 years old, 66.5% were women, and 53.6% had a current mood or anxiety disorder. The three methods were similarly successful in predicting (mental) health status, with correct predictions for up to 79% (95% CI 75?81%). However, Auto-sklearn was superior when assessing a more complex dataset with individual item scores.Conclusions: Automated ML methods added only limited value, compared to traditional data modelling when predicting the onset and course of depression and anxiety. However, they hold potential for automatization and may be better suited for complex datasets. Show less
Background and objectives: Comorbidity among anxiety and depression disorders and their symptoms is high. Rumination and worry have been found to mediate prospective cross-disorder relations... Show moreBackground and objectives: Comorbidity among anxiety and depression disorders and their symptoms is high. Rumination and worry have been found to mediate prospective cross-disorder relations between anxiety and depression disorders and their symptoms in adolescents and adults. We examined whether generic repetitive negative thinking (RNT), that is content- and disorder-independent, also mediates prospective cross-disorder associations between anxiety and depressions disorders and their symptoms.Methods: This was studied using a 5-year prospective cohort study. In a mixed sample of 1859 adults (persons with a prior history of or a current affective disorder and healthy individuals), we assessed DSM-IV affective disorders (Composite Interview Diagnostic Instrument), anxiety (Beck Anxiety Inventory) and depression symptoms (Inventory of Depressive Symptomatology) and RNT (Perseverative Thinking Questionnaire).Results: We found that baseline depression disorders and symptom severity have predictive value for anxiety disorders and symptom severity five years later (and vice versa) and that these associations were significantly mediated by level of RNT as assessed two years after baseline. The significant and rather large mediation effects seemed mainly due to the mental capacity captured by RNT, especially in the prospective relation of anxiety with future depression.Limitations: The mediation effects were greatly attenuated or even nullified after rigorously controlling for concomitant psychopathology at two years after baseline.Conclusions: From these results it can be concluded that repetitive negative thinking could be an important transdiagnostic factor, that may constitute a suitable target for treatment. Show less
Abramovitch, A.; Anholt, G.E.; Cooperman, A.; Balkom, A.J.L.M. van; Giltay, E.J.; Penninx, B.W.; Oppen, P. van 2019
Background: : Psychiatric disorders are associated with overweight/obesity. Obsessive-compulsive disorder(OCD) may be an exception, as anecdotal evidence suggests lower BMI in OCD. Additionally,... Show moreBackground: : Psychiatric disorders are associated with overweight/obesity. Obsessive-compulsive disorder(OCD) may be an exception, as anecdotal evidence suggests lower BMI in OCD. Additionally, depression isassociated with elevated BMI, but effects of comorbid secondary depression are unknown. The aim of the presentstudy was to assess BMI and risk for overweight/obesity in OCD and to assess the effect of comorbid depressionon BMI.Methods: : BMI, demographics, and clinical status were assessed in large samples of individuals with OCD,anxiety disorders, depressive disorders, comorbid anxiety/depressive disorders, and non-clinical controls (NCC).Results: : Although no initial differences were found between the samples on BMI, the non-depressed OCDsubsample had significantly lower BMI and risk for overweight/obesity compared to all other clinical samples.NCC were nearly twice as likely to be overweight compared to non-depressed OCD.Limitations: : Eating disorders were excluded in the OCD sample, but BMI < 17 was used as an exclusion cri-terion in the clinical control groups in lieu of screening for Anorexia. Group differences on demographics werecontrolled for. Recruitment methodology differed between samples.Conclusions: : OCD is associated with significantly lower rates of obesity and overweight, but this relationshipwas not found when comorbid depression was present. This suggests that the purer the phenotype of OCD, themore substantial protective factor against overweight/obesity emerges compared to other clinical samples andNCC. An OCD-specific reward/anhedonia model, previously offered to elucidate lower smoking rates in OCD,may account for lower BMI in OCD. These results warrant careful clinical attention to the negative impact ofcomorbid depression on OCD that spans from increasing risk for obesity and cigarette smoking, to hinderingtreatment response. Show less
