Understanding the Impact of Sleep Disorders on Cognitive Function in Major Depressive Disorder

Background

Major Depressive Disorder (MDD) is a chronic condition characterized by profound effects on an individual’s emotional and cognitive well-being. Symptoms include loss of interest, persistent feelings of sadness, disrupted sleep patterns, and recurrent thoughts of death. For a diagnosis of MDD, a patient must score over 24 on the Hamilton Depression Scale (HAMD-17). As one of the leading mental health disorders, MDD is known for its high prevalence, propensity for recurrence, low remission rates, and considerable impact on daily functioning.

Methods and Materials

Study Participants

The study included participants who met the DSM-5 diagnostic criteria for MDD, scored more than 24 on the HAMD-17, and had their first MDD episode within a year. Patients aged 18 to 55, with at least primary education, and no history of using psychotropic substances, benzodiazepines, or prolonged hypnotic medications were eligible. Exclusion criteria included patients with severe physical health issues, substance abuse, or unwillingness to participate in combined antipsychotic drug therapy.

Investigation Tools

General Information Questionnaire

This self-made questionnaire captured demographic information such as name, age, sex, education, and medical history.

The Hamilton Depression Scale

This 17-item scale gauges the severity of depressive symptoms.

The Hamilton Anxiety Scale

The Hamilton Anxiety Scale (HAMA) evaluates anxiety levels, using 14 items rated by trained evaluators. An HAMA score above 29 indicates major anxiety, while any score above 14 signifies the presence of anxiety.

Pittsburgh Sleep Quality Index

The Pittsburgh Sleep Quality Index (PSQI) assesses sleep quality over the past month, with a score of 0-21, where higher scores indicate poorer sleep.

Repeatable Battery for the Assessment of Neuropsychological Status

The Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) is a comprehensive tool that includes various tasks to evaluate memory, language, attention, and executive functions.

Quality Control

All researchers underwent standardized training to ensure consistent administration of the assessments. The study took place in a tertiary-level hospital by a team of experienced clinicians.

Statistical Analysis

The researchers used a Latent Growth Curve Model (LGCM) to analyze the longitudinal changes in depressive symptoms, HAMA scores, sleep quality, and cognitive performance over eight weeks. They also performed a t-test to explore inter-group differences based on demographics and depression severity.

Results

Patient Characteristics

Changes in Sleep and Cognition

Table 2 Scores on the Scales at Different Stages of the Evaluation in Patients With Major Depressive Disorder

At the initial assessment, all patients had severe symptoms of depression, anxiety, and sleep disorders. By the eighth week, symptoms improved significantly, although some sleep disorders and cognitive impairments persisted.

Correlation Between Depressive Symptoms and Neurological Impairment

Table 3 Change in Value From Different Scales in MDD Patients at Baseline and the 8th Week

The study found that sex, education level, and occupation influenced the RBANS scores at baseline and improvements over eight weeks. Depression and anxiety levels decreased significantly, but the correlation with cognitive function improvements was not statistically significant.

Trajectory of Symptoms and Cognitive Function

The linear unconditional latent variable growth models, presented in Figure 1, showed a significant decline in depression, anxiety, and sleep disorder scores. Conversely, there was a linear increase in cognitive function scores.

Figure 1 Development trajectory of depressive symptoms, anxiety, sleep disturbance, and cognitive function in MDD patients.

Table 5 Fit indicators of the Latent Variable Growth Model

Table 6 Specific parameter estimates of the Latent Variable Growth Model

Impact of Changes in Depression/Anxiety/Sleep on Cognitive Function

To understand relationships among these variables, the study applied LGCM. Depression and anxiety scores at baseline did not predict cognitive function scores, but changes over time did. Faster improvements in depression and anxiety correlated with enhancements in cognitive function.

Figure 2 Latent Growth Curve Model of Depressive Symptoms and Cognitive Function

Similarly, anxiety and sleep disorder improvements significantly predicted cognitive function gains.

Figure 3 Latent Growth Curve Model of Sleep Disturbance and Cognitive Function

Factors Influencing the Impact of Sleep Disorders on Cognitive Function

The study concluded that gender, age, education duration, and occupational type did not significantly influence the relationship between sleep disorders and cognitive function improvements.

Table 7 Variations on the Model Expressing the Variation Relationship Between the Sleep Situation and the Cognitive Function of Both Sexes in MDD Patients

Table 8 Variations on the Model Expressing the Variation Relationship Between the Sleep Problem and the Cognitive Function of MDD Patients Above or Below 35 Years Old

Table 9 Variations on the Model Expressing the Variation Relationship Between the Sleep Problem and the Cognitive Function in the Patients With the Education of 12 Years or Below

Table 10 Variations on the Model Expressing the Variation Relationship Between the Sleep Problem and the Cognitive Function in the Patients Engaged in Mental and Physical Work

Table 11 Variations on the Model Expressing the Variation Relationship Between the Sleep Problem and the Cognitive Function in the Patients With 8-Week Decremental Rate of HAMD

Discussion

Pre and Post Treatment Evolution

Improvements in cognitive function were notable, but further research is needed to explore long-term outcomes.

Influencing Factors on Cognitive Function Improvement

Age and education were critical predictors of cognitive function recovery. Patients with more severe depression and anxiety showed greater memory and executive function declines.

Dynamic Influence of Sleep Disturbance

Rapid improvements in sleep disorders accelerated cognitive recovery.

Factors Affecting Cognitive Function Enhancement

Sex, age, education, and occupational type did not significantly affect the dynamic impact of sleep on cognitive function in this study.

Conclusion

In conclusion, MDD patients often experience severe anxiety, sleep disturbances, and cognitive impairments. Treatment leads to significant reductions in depression and anxiety levels, with sleep quality improvements preceding cognitive gains. The study highlights the importance of addressing sleep issues during MDD treatment to enhance overall cognitive recovery.

Abbreviations

• MDD, Major Depressive Disorder
• HAMD, Hamilton Depression Scale
• HAMA, Hamilton Anxiety Scale
• PSQI, Pittsburgh Sleep Quality Index
• RBANS, Repeatable Battery for the Assessment of Neuropsychological Status
• LGCM, Latent Growth Curve Model

Data Sharing Statement

The datasets used and/or analyzed during this study are available from the corresponding author upon reasonable request.

Ethics Approval and Informed Consent

This study was approved by the Ethics Committee of Tianjin Anding Hospital. All participants provided written informed consent for clinical research.

Weakness of This Study

The study has several limitations:

• It was a single-center study lacking comprehensive generalizability. Future research should involve larger samples and longer follow-ups.
• Only one sleep quality assessment method (PSQI) was used. PSG monitoring should be considered for more objective evaluations.
• Confounding factors such as substance abuse were not controlled, limiting the interpretation of results.

Call to Action

This comprehensive study sheds light on the interplay between sleep disorders, depression, and cognitive function in patients with MDD. Understanding these dynamics can inform better treatment strategies. Share your thoughts, insights, or additional research findings below. Your comments can contribute to the ongoing dialogue in the field of mental health. Don’t forget to subscribe for updates on future articles!