Waking up on the wrong side of the bed: Depression severity moderates daily associations between sleep duration and morning affect

Mornings are salient times for disrupted affect that may be impacted by prior sleep. The current study extends work linking sleep disruptions with negative affect by examining how nightly changes in sleep duration, timing, and quality relative to a person's average impact morning affect. We further tested whether depression severity moderated the relationship between nightly variations in sleep and morning affect. This is a secondary analysis of participants ages 18-65 years with varying levels of depression (N = 91) who wore an Actiwatch for 3-17 days (n = 73) while reporting morning affect using a visual analogue scale. Multilevel models tested the previous night's sleep duration, timing, or quality as a predictor of morning affect. Sleep measures were group-mean centred to account for nightly variation in participants' sleep. A cross-level interaction between depression severity and nightly sleep was entered. Sleeping longer (b = 0.1; p < 0.001) and later (b = 1.8; p = 0.01) than usual were both associated with better morning mood. There was a significant interaction between nightly actigraphic sleep duration and depression severity on morning affect (b = 0.003; p = 0.003). Participants with higher depression severity reported worse affect upon waking after sleeping less than their usual. In comparison, sleeping less than usual did not affect morning affect ratings for participants with lower depression. A similar interaction was found for sleep quality (b = 0.02; p < 0.001). There was no interaction for midsleep timing. Sleeping less than usual impacted morning affect in individuals with greater depression, potentially suggesting a pathway by which sleep disturbances perpetuate depression.

0037 Melanopsin Driven Pupil Responses and Physical Activity: Stability of Activity from Day-to-Day in Winter in Seasonal Affective Disorder

Introduction

The post-illumination pupil response (PIPR) is a measure of the responsivity of intrinsically photosensitive retinal ganglion cells (ipRGCs), and reflects the cell biology of the photoentrainment pathway projecting from the retina to the circadian clock. Adequate signaling from the ipRGCs in the retina to the circadian clock is necessary to result in robust circadian output which we hypothesize would increase inter-daily stability (IS), a non-parametric modeling technique that examines stability of rest activity rhythms across successive days.

Methods

Participants were aged 18–66 years and recruited from the greater Pittsburgh area during the Winter with Seasonal Affective Disorder who completed both actigraphy and pupillometry (n = 16). PIPR measures were collected after a 1 second red or blue light pulse, and are calculated as the Net difference between red and blue at multiple time frames: at 6 seconds post stimulus (PIPR 6), from 10–30 seconds post-stimulus (PIPR 20), or from 10–40 seconds post-stimulus (PIPR 30). Using actigraphy, inter-daily stability (IS) was calculated as the amount of overall variability in the recording that is accounted for by the typical 24-hour profile, and reflects stability of the mean 24-h profile day-to-day.

Results

Inter-daily stability (IS) was associated with Net PIPR 20 (Β = 0.561; p = .031) and Net PIPR 30 (Β = 0.551; p = .034; all Β’s are standardized), but not Net PIPR 6 (Β = 0.298; p = .304). Retinal irradiance was calculated for each participant based on age and pupil diameter, to account for age-related differences in transmission of the stimulus to the retina. All raw Net PIPR values were adjusted for calculated retinal irradiance, and gender and time since wake were included as covariates.

Conclusion

Inter-daily stability (IS) values indicate greater stability of 24-hour activity profiles across days. If reduced responsivity to entraining pulses of light is associated with day-to-day instability in activity rhythms, as shown here, we might expect that amplifying entraining light through environmental changes or bright light therapy would normalize inter-daily stability in SAD, or the reverse, stabilizing activity profiles across days could improve depression and/or normalize retinal ipRGC responsivity.

Support

NIMH K.A.R. MH103303

1091 The Effects Of Sleep Duration, Timing, And Depressed Mood On Daily Eating Patterns

Introduction

Insufficient sleep, circadian misalignment, and altered eating patterns are linked to depression. Despite the temporal association between the sleep/wake and feed/fast cycles, it is unclear how depression severity influences this relationship.

Methods

Sixty-eight participants ages 18-65 years across the depression continuum wore an Actiwatch for 5-17 nights and reported daily meal times (730 nights total). Multilevel models tested previous night’s sleep timing and duration as predictors of the length of the next day’s eating window. Within-person sleep duration and timing were entered as Level 1 predictors to account for nightly variation in sleep. Between-person sleep duration and timing were entered as Level 2 predictors. A three-way interaction between depression severity and Level 2 sleep duration/timing was entered. Covariates included age, gender, and day (weeknight/weekend).

Results

Across participants, average later sleep timing predicted a longer eating window (&#914;= -.222; p =.005). Earlier sleep timing (&#914;= -.186; p &lt; .001) and shorter sleep duration(&#914;= -.103; p &lt; .001) relative to a person’s average each predicted a longer next-day eating window. A three-way interaction was found between sleep duration, timing, and depression (&#914;= -.159; p = .002). At shorter sleep durations, individuals with higher depression severity had a positive relationship between sleep timing and eating window length, and individuals with low depression had a negative relationship between sleep timing and eating window length.

Conclusion

At shorter sleep durations (&lt; 6.5 hr), individuals with high depression and later sleep timing or low depression and early sleep timing had the longest eating windows, which have been linked to adverse metabolic health. Future experiments should test short sleep duration, sleep timing, and depression as potential causes of lengthened eating windows to determine if targeting sleep duration and timing could improve adverse metabolic markers in depression.

Support

NIMH K.A.R. MH103303

1092 Attention-deficit/hyperactivity Disorder Symptoms And Sleep Characteristics Within A Seasonal Affective Disorder Spectrum

Introduction

Seasonal affective disorder (SAD) increases risk for attention-deficit/hyperactivity disorder (ADHD), although the mechanism linking SAD and ADHD is unknown. Prior research has identified insomnia and delayed sleep phase in both ADHD and SAD. We hypothesized that sleep duration and timing in SAD would be associated with the severity of ADHD symptoms.

Methods

Adults with SAD (n = 45) and subsyndromal SAD (S-SAD; n = 18) aged 19-66 years from Pittsburgh, PA., were assessed for ADHD symptoms, self-report sleep quality, depression severity, and daytime sleepiness in the Winter. Participants wore an Actiwatch for 4-14 days, from which we calculated sleep-onset latency, total sleep time, sleep midpoint, and sleep efficiency. We conducted a hierarchical multivariate linear regression to determine if sleep characteristics predict ADHD symptom severity in our sample while controlling for depressive symptoms. Age and gender were added in Step 1, seasonal depression severity in Step 2, actigraphy-based total sleep time, sleep onset latency, midpoint, and efficiency in Step 3, and self-reported sleep quality and daytime sleepiness in Step 4.

Results

Participants mostly scored in the “likely” or “highly likely” ADHD range (87.30%, n=55), higher than the national prevalence rate (4.4%). When controlling for age, gender, and depression severity, only shorter actigraphy-based total sleep time was associated with higher ADHD symptom severity (β=-0.30, p&lt;0.05). However, when self-reported sleep quality and daytime sleepiness were added as predictors, total sleep time was no longer a statistically-significant predictor of ADHD symptom severity and only daytime sleepiness predicted ADHD symptom severity (β=0.31, p&lt;0.05).

Conclusion

Our results suggest that individuals with SAD who experience daytime sleepiness and/or possibly shorter actigraphy-based sleep duration experience higher ADHD symptom severity. Treatments like Trans-C or CBT-I to improve daytime sleepiness and sleep duration may be indicated for SAD patients who present with comorbid ADHD symptoms.

Support

NIMH K.A.R. MH103303

0771 Explaining Self-reported Hypersomnolence In Seasonal Depression

Introduction

Hypersomnolence is commonly reported in Major Depressive Disorder with Seasonal Pattern (Seasonal Affective Disorder; SAD). However, self-reported hypersomnolence may conflate long sleep duration, daytime sleepiness, fatigue, increased time in bed, or maladaptive sleep cognitions, undermining treatment efforts.

Methods

Eighty-eight participants ages 18-65 years old were recruited during the winter (SAD = 43, Control = 45). Depression severity was assessed by a clinician rated interview, and self-reported hypersomnolence was determined by assessing self-reported sleep duration. Participants wore an Actiwatch for 4-14 days and completed self-report measures of daytime sleepiness and fatigue. We performed a hierarchical linear regression to determine which factors best explain self-reported winter hypersomnolence: actigraphic total sleep time (TST), time in bed (TIB), depression severity, sleepiness, or fatigue. Due to collinearity of TST and TIB, we separated those variables into two models predicting hypersomnolence.

Results

SAD participants endorsed greater hypersomnolence than controls during the winter (B = .714; p &lt; .001). In model 1, TST (OR(1,14) = .024, p &lt;.001) and daytime sleepiness (OR(1,14) = .208, p = .03) significantly predicted the presence of self-reported winter hypersomnolence above and beyond age, gender, depression, and fatigue. In model 2, only TIB (OR(1, 14) = .021, p = .001) was a significant predictor. Post-hoc analyses indicated that fatigue and depression severity significantly predicted self-reported hypersomnolence when entered separately into the model. Sleepiness accounted for the largest change in pseudo-R2 in bth models.

Conclusion

We found evidence for the multifaceted etiology of self-reported hypersomnolence. Daytime sleepiness, sleep duration, time in bed, and the shared variance between fatigue and depression severity all explained self-reported hypersomnolence. Treatment of hypersomnolence should include actigraphy, and should be individually tailored based on presentation.

Support

NIMH K.A.R. MH103303