The temporal order of changes in physical activity and subjective sleep in depressed versus nondepressed individuals:Findings From the MOOVD Study

Epidemiological studies have shown an association between physical activity and sleep, but it is unclear what the temporal order of this association is and whether it differs for depressed patients and healthy controls. Using a multiple repeated observations design, 27 depressed and 27 pair-matched nondepressed participants completed daily measurements of subjective sleep quality and duration during 30 consecutive days while an accelerometer continuously registered their physical activity. Changes in sleep duration, not quality, predicted next-day changes in physical activity (B = -0.21, p <.001), but not the other way around. Significant heterogeneity between individuals was observed, but the effect was not different for depressed and nondepressed participants. The findings underline the strength of a multiple repeated observations design in observational sleep research

Cortisol and alpha-Amylase Secretion Patterns between and within Depressed and Non-Depressed Individuals

ObjectivesAssociations between biological stress markers and depression are inconsistent across studies. We assessed whether inter- and intra-individual variability explain these inconsistencies.MethodsPair-matched depressed and non-depressed participants (N = 30) collected saliva thrice a day for 30 days, resulting in 90 measurements per individual. The relationships between measures of stress-system function and depression were examined at the group level by means of mixed model analyses, and at the individual level by means of pair-matched comparisons. The analyses were repeated after adjusting for time-varying lifestyle factors by means of time-series regression analyses.ResultsCortisol and α-amylase levels were higher, the α-amylase/cortisol ratio larger, and the daily cortisol slope steeper in the depressed compared to the non-depressed group. Adjusting for lifestyle factors and antidepressant use reduced the associations under study. In 40%-60% of the matched comparisons, depressed individuals had higher cortisol and α-amylase levels, a larger α-amylase/cortisol ratio, and a steeper daily slope than their non-depressed match, regardless of adjustment.ConclusionsOur group-level findings were mostly in line with the literature but generalization to individuals appeared troublesome. Findings of studies on this topic should be interpreted with care, because in clinical practice the focus is on individuals instead of groups

Bidirectionality between sleep symptoms and core depressive symptoms and their long-term course in major depression

OBJECTIVES: To investigate the bidirectional dynamic relationship between sleep symptoms and core depressive symptoms and to identify subgroups differing with respect to their course. METHODS: The weekly state of depressive symptoms in depressed primary care patients (N = 267) was assessed retrospectively every 3 months for 3 consecutive years. The bidirectional relationship between sleep and core symptoms was estimated by means of manifest Markov modeling. Data-driven subgroups were estimated with parallel processes-latent class growth analyses to identify differences in courses of sleep and core symptoms. RESULTS: In total, core symptoms were associated with next-week development (odds = 1.42; 95% confidence interval [CI] = 1.20-1.67; p < .001) and remission of sleep symptoms (odds = 0.86; 95% CI 0.75 to 0.99, p = .033).Evidence was also found for a reverse pathway such that sleep symptoms were associated with the development (odds = 1.26; 95% CI = 1.05-1.50; p = .012) and remission of core symptoms (odds = 0.87; 95% CI = 0.76-0.99; p = .038). Three classes with different 3-year courses were derived. In class 1, the likelihood that core symptoms remitted was reduced if sleep symptoms were present, and symptoms remained present over 3 years. In class 2, symptoms were bidirectionally related and remitted over 3 years. In class 3, symptoms were not associated, and sleep symptoms declined less steeply than core depressive symptoms. CONCLUSIONS: The results suggest that sleep symptoms should be treated alongside core depressive symptoms in patients with an asynchronic decrease of sleep and core symptoms and in patients that do not respond to treatment to increase the chance of complete remission

Sleep quality predicts positive and negative affect but not vice versa. An electronic diary study in depressed and healthy individuals

Background: The exact nature of the complex relationship between sleep and affect has remained unclear. This study investigated the temporal order of change in sleep and affect in participants with and without depression. Methods: 27 depressed patients and 27 pair-matched healthy controls assessed their sleep in the morning am their affect 3 times a day for 30 consecutive days in their natural environment. Daily sleep quality and average, positive affect (PA) and negative affect (NA) were used to examine whether changes in sleep quality preceded or followed changes in PA and NA, and whether this was different for patients and healthy controls. Second. presumptive mediating factors were investigated. We hypothesized that fatigue mediated the effect of changes in sleep quality on subsequent PA/NA, and that rumination mediated the effect of changes in PA/NA on subsequent sleep quality. Results: Multilevel models showed that changes in sleep quality predicted changes in PA (B=0.08, p <0.001: and NA (B=-0.06, p <0.001), but not the other way around (PA: B=0.03, p=0.70, NA: B=-0.05, p=0.60). Fatigue was found to be a significant mediator of the relationship between sleep quality and PA (Indirect Effect=0.03, p <0.001), and between sleep quality and NA (Indirect Effect=-0.02, p=0.01). Rumination was no investigated because of non-significant associations between PA/NA and sleep quality. The associations were not different for patients and controls. Limitations: The analyses were restricted to self-reported sleep quality, and conclusions about causality could not be drawn. Conclusions: Improvements in sleep quality predicted improvements in affect the following day, partly mediated by fatigue. Treatment of sleep symptoms would benefit affect in clinical care and beyond

An investigation of emotion dynamics in major depressive disorder patients and healthy persons using sparse longitudinal networks

BACKGROUND: Differences in within-person emotion dynamics may be an important source of heterogeneity in depression. To investigate these dynamics, researchers have previously combined multilevel regression analyses with network representations. However, sparse network methods, specifically developed for longitudinal network analyses, have not been applied. Therefore, this study used this approach to investigate population-level and individual-level emotion dynamics in healthy and depressed persons and compared this method with the multilevel approach. METHODS: Time-series data were collected in pair-matched healthy persons and major depressive disorder (MDD) patients (n = 54). Seven positive affect (PA) and seven negative affect (NA) items were administered electronically at 90 times (30 days; thrice per day). The population-level (healthy vs. MDD) and individual-level time series were analyzed using a sparse longitudinal network model based on vector autoregression. The population-level model was also estimated with a multilevel approach. Effects of different preprocessing steps were evaluated as well. The characteristics of the longitudinal networks were investigated to gain insight into the emotion dynamics. RESULTS: In the population-level networks, longitudinal network connectivity was strongest in the healthy group, with nodes showing more and stronger longitudinal associations with each other. Individually estimated networks varied strongly across individuals. Individual variations in network connectivity were unrelated to baseline characteristics (depression status, neuroticism, severity). A multilevel approach applied to the same data showed higher connectivity in the MDD group, which seemed partly related to the preprocessing approach. CONCLUSIONS: The sparse network approach can be useful for the estimation of networks with multiple nodes, where overparameterization is an issue, and for individual-level networks. However, its current inability to model random effects makes it less useful as a population-level approach in case of large heterogeneity. Different preprocessing strategies appeared to strongly influence the results, complicating inferences about network density

The person-specific interplay of melatonin, affect, and fatigue in the context of sleep and depression

The aim of the present study was to reveal how positive affect (PA), negative affect (NA), fatigue, and melatonin are inter-related in individuals with and without MDD. We used a unique dataset with up to 90 measurements of 14 depressed and 15 pair-matched non-depressed participants and the novel network analysis approach Group Iterative Multiple Model Estimation (GIMME) to reveal how affect, fatigue, and melatonin were related across time at the group- and the person-specific level. Thereafter, we investigated how individual differences in the role of melatonin were related to sleep and depression severity. PA and NA (beta = -0.47), and PA and fatigue (beta = -0.44) were related contemporaneously in the full sample. Substantial between-person differences were found. In 83% of the study participants, melatonin was related to either affect or fatigue. Those who did not have associations with melatonin in their networks had relatively greater depression severity, worse sleep quality, and lower energy expenditure. This study revealed the possibilities of network mapping for dynamic person-specific psychological and biological data. The results underline not only the presence of large heterogeneity, but also show that despite this heterogeneity, meaningful generalizations can be made regarding the interplay of melatonin with affect and fatigue in depression