In recent years, the role of inflammation in depression has received people's attention.Studies have suggested that immune disorder may play an important role in depression, and patients with depression exhibit characteristic immunophenotypes.Inflammation seems to interact with a variety of pathogenesis of depression.Therefore, immunoregulation is becoming an adjuvant therapy for depression.Clinically, not only antidepressants show anti-inflammatory effects, but also anti-inflammatory drugs show antidepressant effects, and they mainly including non-steroidal anti-inflammatory drugs, statins, and cytokine inhibitors.In addition, some non-drug treatment methods are also given immunomodulatory effects, such as electric shock therapy, vagus nerve stimulation, acupuncture and exercise therapy.However, there are still some problems in immunomodulation therapy, such as immunomodulation therapy may be only effective for some subgroups of patients, and its efficacy and safety need to be evaluated.In the future, looking for more effective biomarkers and identifying immune-inflammation-related subtype of depression, will serve to explore new diagnosis and treatment strategies.
Key words:
Major depression disorder; Immunomodulation; Inflammation; Anti-inflammatory; Therapy
The COVID-19 pandemic is expected to have long-term effects on mental health with implications at a population health level. While limiting the transmission of the virus, lockdown measures subject individuals to significant psychological distress and interpersonal isolation, which may increase risk for depression, a chronic and disabling disease associated with tremendous societal, individual, and economic costs (e.g., workplace productivity loss, unemployment, work absence, and long-term disability).1 In addition to the elevated risk of depression and loneliness attributable to frequent and prolonged social media (SM) use outside the context of epidemics, frequent exposure to fearful and exaggerated information through SM can exacerbate psychological and emotional distress.2, 3 We investigated the impact of SM use and psychological and emotional distress on depression in 3064 adults in Mainland China. A national convenience sample of 2574 health-care workers and 490 non-medical workers in China was surveyed cross-sectionally by telephone or WeChat between 29 January and 11 February 2020. Our study participants consisted of physicians (n = 783), nurses (n = 1587), and other medical staff (n = 204) employed in health-care settings providing direct care for patients in hospitals, as well as 490 adults not employed in a health-care setting (Table S1). The study was approved by the Institutional Review Board at Renmin Hospital of Wuhan University (No. WDRY2020-K004). Detailed methods and results are available in the Supplementary Information. We assessed the effect of SM use and psychological and emotional distress (according to the Hyperarousal, Intrusion, and Avoidance subscales of the 22-item Impact of Event Scale – Revised [IES-R]) on depressive symptom severity (according to the 9-item Patient Health Questionnaire [PHQ-9]). Greater IES-R and PHQ-9 scores indicate greater severity. Participants were asked about their use of SM to obtain information about COVID-19. We analyzed PHQ-9 score as a continuous outcome variable using generalized linear models with a negative binomial distribution and as a dichotomous outcome variable using binomial logistic regression models (reported in Supplementary Information). We evaluated the synergistic effect of prolonged SM use to obtain information about COVID-19 and psychological and emotional distress as a result of the epidemic on the risk for depression in Mainland China. We evaluated whether the odds of depressive symptoms with more prolonged SM use and greater psychological and emotional distress were significantly greater than the sum of the odds of depressive symptoms with more prolonged SM use alone and with greater distress alone. We calculated a synergy index and relative excess risk due to interaction to model interaction effects, with adjustments for age, sex, educational attainment, marital status, living arrangements, and health-care/non-health-care-worker status separately for each IES-R subscale.4, 5. The mean (standard error) PHQ-9 score among study participants was 5.2 (0.1), denoting the presence of clinically significant depressive symptoms. Approximately 18.1% (n = 554) of all participants reported spending less than 1 h per day on an SM platform in the past week, 41.6% (n = 1306) reported spending 1–2 h per day, 22.5% (n = 689) reported spending 3–4 h per day, and 16.8% (n = 515) reported spending more than 5 h per day on an SM platform. Greater time spent on SM predicted greater depressive symptom severity (Fig. S1). IES-R Intrusion and Hyperarousal subscale scores significantly predicted PHQ-9 scores, while the Avoidance subscale scores did not (Table S1). Individuals reporting both prolonged SM use (i.e. ≥3 h per day) and significant symptoms of distress, particularly hyperarousal, had significantly higher odds of having depressive symptoms or probable depression relative to individuals with either factor alone (Fig. 1). That is, the odds of depression with prolonged SM use and significant hyperarousal symptoms were significantly greater than the sum of the odds of depression with prolonged SM use (in the absence of significant hyperarousal) and hyperarousal (with reduced SM use), as instantiated by a positive synergistic effect (Table S2). SM networks can be used to provide reassurance, increase public awareness about effective ways to reduce risk of infection, and communicate practical information to curb public panic and reduce the mental health burden of public health crises.6 However, SM use is also associated with elevated risk for depression: greater symptoms of depression and loneliness are observed in young adults who use SM extensively.7, 8 Moreover, during public health crises, SM can aggravate public fear and panic: for example, SM networks have been implicated in the spread of false information and amplification of risk and harm during the 2014 Ebola outbreak.9 There is an urgent and unmet need to address the impact of COVID-19 on the mental health of affected individuals. Data are available on request from the authors. We would like to thank the participants from Wuhan and across Mainland China for their generosity with their time and completing the survey. We would like to thank the medical staff who work directly with patients infected with SARS-Cov-2 for their courage and commitment during this difficult period. This work was supported by the National Key R&D Program of China (2018YFC1314600 to Dr Z. Liu). R.S.M. has received research grant support from the Stanley Medical Research Institute, CIHR/GACD/Chinese National Natural Research Foundation; speaker/consultation fees from Lundbeck, Janssen, Shire, Purdue, Pfizer, Otsuka, Allergan, Takeda, Neurocrine, Sunovion, and Minerva. All other authors declare no competing interests. Appendix S1 Supplementary information. Figure S1 Mean 9-item Patient Health Questionnaire (PHQ-9) scores are significantly higher among individuals with more prolonged social media use. Marginal means reported after adjustment for age, sex, educational attainment, marital status, living arrangement, and health-care/non-health-care-worker status. Table S1 Demographics and summary of model effects on depressive symptom severity (according to the 9-item Patient Health Questionnaire [PHQ-9] total score as a continuous variable). Table S2 Predictors of depressive symptoms. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
Objective: The outbreak of the 2019 novel coronavirus disease (COVID-19) caused not only extraordinary public health concerns but also tremendous psychological distress, particularly among medical staff. We aimed to investigate the prevalence rate of insomnia and confirm the related social psychological factors among medical staff in hospitals during the COVID-19 outbreak. Method: Medical staff members in China were recruited, including frontline medical workers. The questionnaire, administered through the WeChat program, obtained demographic data and asked self-design questions related to the COVID-19 outbreak, insomnia/depressive/anxiety symptoms, and stress-related symptoms. We used logistic regression analysis to examine the associations between sociodemographic factors and insomnia symptoms. Result: There were 1,563 participants in our study. Five hundred and sixty-four (36.1%) participants had insomnia symptoms according to the Insomnia Severity Index (ISI) (total score ≥ 8). A multiple binary logistic regression model revealed that insomnia symptoms were associated with the education level of high school or below (OR = 2.69, p = 0.042, 95% CI = 1.0–7.0), occupation of doctor (OR = 0.44, p = 0.007, 95% CI = 0.2–0.8), currently working in an isolation unit (OR = 1.71, p = 0.038, 95% CI = 1.0–2.8), worry about being infected (OR = 2.30, p < 0.001, 95% CI = 1.6–3.4), perceived lack of helpfulness in terms of psychological support from news or social media with regard to COVID-19 (OR = 2.10, p = 0.001, 95% CI = 1.3–3.3), and having very strong uncertainty regarding effective disease control (OR = 3.30, p = 0.013, 95% CI = 1.3–8.5). Conclusion: Our study found that more than one-third of the medical staff suffered from insomnia symptoms during the COVID-19 outbreak. The related factors included education level, an isolation environment, psychological worries about the COVID-19 outbreak, and occupation of doctor. Interventions for insomnia among medical staff are needed considering the different sociopsychological factors.
The Beijing-Tianjin-Hebei region, characterized by frequent episodes of severe haze pollution during winter, is recognized as one of the key regions requiring air pollution control. To reduce the effects of severe pollution, early warning and emission reduction measures should be executed prior to these haze episodes. In this study, the efficacy of emission reduction procedures during severe pollution episodes was evaluated using the Weather Research and Forecasting model coupled with chemistry (WRF-Chem). To provide feedback and optimize emergency emission reduction plans, a pollution episode that occurred during the period of December 20–26, 2015, which was characterized by a high warning level, long warning period, and integrated pollution process, was selected as a case study to determine the influence of meteorological conditions and the effects of mitigation measures on heavy haze pollution episodes. Adverse meteorological conditions were found to increase PM2.5 concentrations by approximately 34% during the pollution episode. Moreover, the largest contributor to the episode was fossil fuel combustion, followed by dust emission and industrial processes; the first two factors play a significant role in most districts in Tianjin, whereas the third more strongly affects the adjoining districts and Binhai District. Emission reduction for industrial sources and domestic combustion more obviously decreases PM2.5 concentrations during the pollution dissipation stage than the pollution accumulation stage. Thus, different mitigation measures should be adopted in different districts and during different pollution stages. An approximate decrease of 18.9% in the PM2.5 concentration can be achieved when an emergency plan is implemented during the red alert period for heavy haze pollution episodes.
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