COVID-19 might have long-term mental health impacts. We aim to investigate the longitudinal changes in mental problems from initial COVID-19 peak to its aftermath among general public in China. Depression, anxiety and insomnia were assessed among a large-sample nationwide cohort of 10,492 adults during the initial COVID-19 peak (28 February 2020 to 11 March 2020) and its aftermath (8 July 2020 to 8 August 2020) using the Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, and Insomnia Severity Index. We used generalized estimating equations and linear mixed models to explore factors associated with long-term mental health symptoms during COVID-19. During the five months, mental health symptoms remained consistently elevated (baseline 46.4%; follow-up 45.1%). Long-term depression, anxiety and insomnia were associated with several personal and work-related factors including quarantine (adjusted OR for any mental health symptoms 1.31, 95%CI 1.22–1.41, p < 0.001), increases in work burden after resuming work (1.77, 1.65–1.90, p < 0.001), occupational exposure risk to COVID-19 (1.26, 1.14–1.40, p < 0.001) and living in places severely affected by initial COVID-19 peak (1.21, 1.04–1.41, p = 0.01) or by a COVID-19 resurgence (1.38, 1.26–1.50, p < 0.001). Compliance with self-protection measures, such as wearing face masks (0.74, 0.61–0.90, p = 0.003), was associated with lower long-term risk of mental problems. The findings reveal a pronounced and prolonged mental health burden from the initial COVID-19 peak through to its aftermath in China. We should regularly monitor the mental health status of vulnerable populations throughout COVID-19.

Background: Although traumatic experiences in childhood have been recognized as contributors to disordered eating behaviors, critical gaps remain in our understanding. There is limited evidence on the individual, cumulative, and distinct patterns of childhood trauma associated with risky restrictive eating and binge/purging behaviors. Methods: Individuals aged 12–25 years from Xiamen, Fujian Province, China, completed online questionnaires assessing childhood trauma, risky restrictive eating and binge/purging behaviors. Childhood trauma was examined through three analytical approaches: individual types, cumulative trauma scores, and latent class analysis. Logistic regression models were used to investigate the associations between childhood trauma and disordered eating behaviors. Results: Among the 3424 participants, 7.3% (n = 251) reported disordered eating behaviors occurring two or more times per month over the past year. After adjusting for covariates, our analyses showed that emotional abuse independently associated with increased odds of both risky restrictive eating (OR: 2.11, 95% CI 1.28–3.47) and binge/purging behaviors (OR: 2.20, 95% CI 1.34–3.62). Physical abuse was associated only with increased odds of binge/purging behavior (OR: 2.09, 95% CI 1.20–3.64). Traumatic experiences showed a cumulative effect on disordered eating, significant at two or more incidents. Three trauma patterns were identified: ‘low trauma,’ ‘low neglect,’ and ‘high trauma.’ Youth with the ‘high trauma’ pattern exhibited the highest odds of both risky restrictive eating (OR: 2.88, 95% CI 1.65–5.02) and binge/purging behaviors (OR: 3.21, 95% CI 1.85–5.54), whereas those in the ‘high neglect’ pattern showed increased odds only for binge/purging behavior (OR: 1.52, 95% CI 1.01–2.29). Conclusions: Our findings highlight the need to consider the types, numbers, and patterns of childhood trauma when developing prevention and treatment strategies for disordered eating behaviors.

Digital mental health services (DMHSs) have great potential for mitigating the mental health burden related to COVID-19, but public accessibility (ease of acquiring services when needed) to DMHSs during the pandemic is largely unknown. Accessibility to DMHSs was tracked longitudinally among a nationwide sample of 18,804 adults in China from before to one year after COVID-19 outbreak. Unconditional and conditional latent growth curve models and latent growth mixture models were fitted to explore the overall growth trend, influencing factors, and latent trajectory classes of accessibility to DMHSs throughout COVID-19. Generalized estimating equation models and generalized linear mixed models were employed to explore the association between accessibility to DMHSs and long-term mental health symptoms. We found that people generally reported increased difficulty in accessing DMHSs from before to one year after COVID-19 outbreak. Males, youngsters, individuals with low socioeconomic status, and individuals greatly affected by COVID-19 reported greater difficulty in accessing DMHSs. Four DMHS accessibility trajectory classes were identified: “lowest–great increase” (6.3%), “moderate low–slight increase” (44.4%), “moderate high–slight decrease” (18.1%) and “highest–great decrease” (31.2%). Trajectory classes reporting greater difficulty in accessing DMHSs were at higher risk for long-term mental symptoms. In conclusion, an overall increase in difficulty in accessing DMHSs is observed throughout COVID-19, and heterogeneity exists in DMHS accessibility trajectories. Our results suggest that easy access to DMHSs should be consistently facilitated. Moreover, access gaps should be reduced across demographic groups, and target populations for service allocation should alter as the pandemic evolves.

During the pandemic era, quarantines might potentially have negative effects and disproportionately exacerbate health condition problems. We conducted this cross-sectional, national study to ascertain the prevalence of constant pain symptoms and how quarantines impacted the pain symptoms and identify the factors associated with constant pain to further guide reducing the prevalence of chronic pain for vulnerable people under the pandemic. The sociodemographic data, quarantine conditions, mental health situations and pain symptoms of the general population were collected. After adjusting for potential confounders, long-term quarantine (≥15 days) exposures were associated with an increased risk of constant pain complaints compared to those not under a quarantine (Odds Ratio (OR): 1.26; 95% Confidence Interval (CI): 1.03, 1.54; p = 0.026). Risk factors including unemployment (OR: 1.55), chronic disease history (OR: 2.38) and infection with COVID-19 (OR: 2.15), and any of mental health symptoms including depression, anxiety, insomnia and PTSD (OR: 5.44) were identified by a multivariable logistic regression. Additionally, mediation analysis revealed that the effects of the quarantine duration on pain symptoms were mediated by mental health symptoms (indirect effects: 0.075, p < 0.001). These results advocated that long-term quarantine measures were associated with an increased risk of experiencing pain, especially for vulnerable groups with COVID-19 infection and with mental health symptoms. The findings also suggest that reducing mental distress during the pandemic might contribute to reducing the burden of pain symptoms and prioritizing interventions for those experiencing a long-term quarantine.

Background: Low muscle mass (LMM), poor sleep quality, and reduced quality of life (QOL) are common concerns in older adults. This study examined their cross-sectional associations and explored the statistical indirect association involving sleep quality, with particular attention to sensitivity to body-size adjustment and alternative model specifications. Methods: We analyzed data from 9366 adults aged 65 years or older in the 2018 Chinese Longitudinal Healthy Longevity Survey. LMM was classified using anthropometrically predicted appendicular skeletal muscle mass, while sleep quality and overall QOL were assessed using single-item self-reports. Regression-based indirect associations were estimated with 5000 bootstrap resamples. Sensitivity analyses examined alternative measurements, body-size adjustment, depressive symptoms, model ordering, missing-data assumptions, and sampling weights. Results: Anthropometrically estimated LMM was associated with poorer sleep quality (B = −0.066, 95% CI: −0.110 to −0.022) and lower QOL (total association: B = −0.073, 95% CI: −0.108 to −0.039). Better sleep quality was associated with higher QOL (B = 0.163, 95% CI: 0.147 to 0.178). The indirect association was small (B = −0.011, 95% bootstrap CI: −0.018 to −0.003) and attenuated after continuous body mass index adjustment (B = −0.001, 95% bootstrap CI: −0.010 to 0.008). Adjustment for depressive symptoms further attenuated the estimated indirect association, while a reverse-order model also yielded a non-zero indirect association (B = −0.020). Residual-confounding sensitivity analyses indicated dependence on assumptions about unmeasured common causes. Conclusions: Anthropometrically estimated LMM was associated with poorer perceived sleep quality and overall QOL, but the estimated indirect association involving sleep quality was small and sensitive to body-size adjustment, psychological covariates, and model specification. These cross-sectional findings do not establish a muscle-specific association independent of overall body size or a causal sleep-mediated pathway. Longitudinal studies incorporating directly measured body composition and validated multidimensional sleep and QOL assessments are needed to clarify these relationships.