Prevalence and patterns of major depressive disorder and subthreshold depressive symptoms in south China

The Role of Depression and Anxiety in the Relationship Between Arthritis and Cognitive Impairment in Chinese Older Adults

BACKGROUND

Mental disorders and cognitive impairment are common in older patients with arthritis. While it is recognized that mental conditions may play a role in the connection between arthritis and cognitive impairment, the precise underlying relationship remains uncertain.

METHODS

The data was derived from the baseline survey of the Guangdong Mental Health Survey in South China, involving a sample of 3,764 citizens aged 65 and older. An array of aspects were explored, including socio-demographics, lifestyle behaviors, self-reported chronic conditions, depression, anxiety, and cognitive impairment. Logistic regression analyses examined the association between arthritis and cognitive impairment after adjustment for potential confounders. Serial mediation models were used to examine whether depression or anxiety played a mediating role in the arthritis-cognitive impairment linkage.

RESULTS

The prevalence rates of cognitive impairment and arthritis of the older adults were 28.9% and 12.1%, respectively. Compared to those without arthritis, participants with arthritis were at a higher risk of cognitive impairment (OR = 1.322, 95%CI: 1.022-1.709) after adjustment for socio-demographics, lifestyle behaviors, and mental health conditions. Serial mediation analyses indicated that depressive and anxiety symptoms co-played a serial mediating role in the association between arthritis and cognitive impairment (B1 = 0.025, 95%CI: 0.005-0.052; B2 = 0.050, 95%CI: 0.021-0.086).

CONCLUSIONS

Arthritis may heighten cognitive impairment risk in Chinese older adults, and the relationship was potentially mediated by depressive and anxiety symptoms. Future interventions should be considered, integrating mental health assessments into arthritis care frameworks and being alert to possible cognitive impairment.

Characterizing Major Depressive Disorder (MDD) using alpha-band activity in resting-state electroencephalogram (EEG) combined with MATRICS Consensus Cognitive Battery (MCCB)

BACKGROUND

The diagnosis of major depressive disorder (MDD) is commonly based on the subjective evaluation by experienced psychiatrists using clinical scales. Hence, it is particularly important to find more objective biomarkers to aid in diagnosis and further treatment. Alpha-band activity (7-13 Hz) is the most prominent component in resting electroencephalogram (EEG), which is also thought to be a potential biomarker. Recent studies have shown the existence of multiple sub-oscillations within the alpha band, with distinct neural underpinnings. However, the specific contribution of these alpha sub-oscillations to the diagnosis and treatment of MDD remains unclear.

METHODS

In this study, we recorded the resting-state EEG from MDD and HC populations in both open and closed-eye state conditions. We also assessed cognitive processing using the MATRICS Consensus Cognitive Battery (MCCB).

RESULTS

We found that the MDD group showed significantly higher power in the high alpha range (10.5-11.5 Hz) and lower power in the low alpha range (7-8.5 Hz) compared to the HC group. Notably, high alpha power in the MDD group is negatively correlated with working memory performance in MCCB, whereas no such correlation was found in the HC group. Furthermore, using five established classification algorithms, we discovered that combining alpha oscillations with MCCB scores as features yielded the highest classification accuracy compared to using EEG or MCCB scores alone.

CONCLUSIONS

Our results demonstrate the potential of sub-oscillations within the alpha frequency band as a potential distinct biomarker. When combined with psychological scales, they may provide guidance relevant for the diagnosis and treatment of MDD.

Patterns of unhealthy lifestyle and their associations with depressive and anxiety symptoms among Chinese young adults: A latent class analysis

BACKGROUND

There is little evidence on the association between patterns of unhealthy lifestyle and mental health among young adults.

METHOD

This study included a total of 28,978 young adults aged 18 to 44 years old in Guangdong province in south China, which was conducted from September to December in 2022. We used latent class analysis to classify the patterns of unhealthy lifestyle among young adults and used multiple logistic regression to explore their associations with depressive and anxiety symptoms.

RESULT

The weighted prevalence of depressive and anxiety symptoms were 28.0 % and 19.5 %, respectively. The cumulative effect of unhealthy lifestyles on depressive and anxiety symptoms was significant. Five patterns of unhealthy lifestyle were classified. Compared to the relatively healthy lifestyle class, the class with more unhealthy lifestyles (OR = 6.54, 95 % CI: 5.70-7.51) and insufficient sleep (OR = 6.16, 95 % CI: 4.92-7.70) had higher risk for depressive and anxiety symptoms. Meaningfully, having adequate mental health literacy could reduce the risk of depressive and anxiety symptoms from unhealthy lifestyle by half.

LIMITATIONS

The cross-section design study limited causal inferences, and the self-report information may lead to recall bias.

CONCLUSIONS

Unhealthy lifestyles have a negative impact on depressive and anxiety symptoms through independent, cumulative and combined effects, and they could be interrelated. Unhealthy lifestyle patterns differed in younger population by socio-demographic characteristics and mental health literacy. Health-care professionals and policymakers may provide programs to intervene multiple unhealthy lifestyles and improve mental health literacy by integrating healthy lifestyle education to promote youngers' mental health.

Effect of Regular Aerobic Exercise on Cognitive Function, Depression Level and Regulative Role of Neurotrophic Factor: A Prospective Cohort Study in the Young and the Middle-Aged Sample

Purpose

Mild cognitive impairment (MCI) and depressive disorder (DD), which are associated with unhealthy lifestyles, are prevalent worldwide. This study aimed to investigate the effects of regular aerobic exercise on cognitive function, depression, and the regulatory role of neurotrophic growth factors for providing scientific basis in preventing MCI and DD in healthy individuals.

Patients and Methods

Eighty members of the fitness center and 80 community residents were recruited, who were administered by the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) and the Patient Health Questionnaire (PHQ-9). Brain-derived neurotrophic factor (BDNF) and glial cell-line-derived neurotrophic factor (GDNF) in the peripheral blood were detected by enzyme-linked immunosorbent assay (ELISA).

Results

The RBANS and other factor scores, except for visuospatial abilities, were higher and PHQ-9 scores were lower in the study group than in the control group. The concentrations of BDNF and GDNF in the study group were higher than those in the control group. RBANS and its factor scores positively and PHQ-9 negatively correlated with BDNF and GDNF levels. Finally, multiple regression analysis showed that BDNF, as a predictor of RBANS, could explain 59.90% of its variance and that GDNF was a predictor of PHQ-9 could explain 12.30% of the variance.

Conclusion

Regular aerobic exercise can improve cognitive function and depressive symptoms by increasing the BDNF and GDNF levels.

Associations between breakfast skipping and outcomes in neuropsychiatric disorders, cognitive performance, and frailty: a Mendelian randomization study

BACKGROUND

Prior studies have identified a correlation between breakfast skipping and a heightened risk of mental health issues. This investigation aimed to employ a Two-Sample Mendelian Randomization (MR) approach to explore the potential causal links between breakfast skipping and various psychiatric, neurological disorders, cognitive performance, and frailty.

METHODS

Utilizing data from genome-wide association studies within European demographics, this research scrutinized the association between breakfast habits and several neuropsychiatric conditions and physical health outcomes, including Alzheimer's disease (AD), Attention Deficit Hyperactivity Disorder (ADHD), Bipolar Disorder (BD), Major Depressive Disorder (MDD), Narcolepsy, Insomnia, cognitive performance, and frailty. In this MR analysis, the Inverse Variance Weighted (IVW) method was primarily utilized for evaluation. Outcomes were reported as Odds Ratios (OR) and regression coefficients (β), and underwent validation through False Discovery Rate (FDR) corrections, thereby offering a rigorous evaluation of the effects of breakfast habits on both mental and physical health dimensions.

RESULTS

Findings demonstrate a significant causal link between skipping breakfast and an increased risk of ADHD (OR = 2.74, 95%CI: 1.54-4.88, PFDR = 0.003) and MDD (OR = 1.7, 95%CI: 1.22-2.37, PFDR = 0.005). Conversely, no substantial causal associations were identified between breakfast skipping and AD, BD, narcolepsy, or insomnia (PFDR > 0.05). Moreover, a notable causal relationship was established between skipping breakfast and a reduction in cognitive performance (β = -0.16, 95%CI: -0.29-0.04, PFDR = 0.024) and an increase in frailty (β = 0.29, 95%CI: 0.12-0.45, PFDR = 0.003).

CONCLUSION

The MR analysis reveals that skipping breakfast is associated with an increased risk of ADHD, MDD, decreased cognitive performance, and greater frailty, while showing no associations were found with AD, BD, narcolepsy, or insomnia. These findings warrant further investigation into the underlying mechanisms and emphasize the importance of regular breakfast consumption for mental and physical well-being.

Prevalence of depressive symptoms and correlates among individuals who self-reported SARS-CoV-2 infection after optimizing the COVID-19 response in China

Background

The burden of depression symptoms has increased among individuals infected with SARS-CoV-2 during COVID-19 pandemic. However, the prevalence and associated factors of depressive symptoms among individuals infected with SARS-CoV-2 remain uncertain after optimizing the COVID-19 response in China.

Methods

An online cross-sectional survey was conducted among the public from January 6 to 30, 2023, using a convenience sampling method. Sociodemographic and COVID-19 pandemic-related factors were collected. The depression symptoms were assessed using the Patient Health Questionnaire-9 (PHQ-9). Logistic regression analysis was performed to explore the associated factors with depressive symptoms.

Results

A total of 2,726 participants completed the survey. The prevalence of depression symptoms was 35.3%. About 58% of the participants reported experiencing insufficient drug supply. More than 40% of participants reported that they had missed healthcare appointments or delayed treatment. One-third of participants responded experiencing a shortage of healthcare staff and a long waiting time during medical treatment. Logistic regression analysis revealed several factors that were associated with depression symptoms, including sleep difficulties (OR, 2.84; 95% CI, 2.34-3.44), chronic diseases (OR, 2.15; 95% CI, 1.64-2.82), inpatient treatment for COVID-19 (OR, 3.24; 95% CI, 2.19-4.77), with COVID-19 symptoms more than 13 days (OR, 1.30, 95% CI 1.04-1.63), re-infection with SARS-CoV-2 (OR, 1.52; 95% CI, 1.07-2.15), and the increased in demand for healthcare services (OR, 1.32; 95% CI, 1.08-1.61).

Conclusion

This study reveals a moderate prevalence of depression symptoms among individuals infected with SARS-CoV-2. The findings underscore the importance of continued focus on depressive symptoms among vulnerable individuals, including those with sleeping difficulties, chronic diseases, and inpatient treatment for COVID-19. It is necessary to provide mental health services and psychological interventions for these vulnerable groups during the COVID-19 epidemic.