Health, Lifestyle, and Psycho-Social Determinants of Poor Sleep Quality During the Early Phase of the COVID-19 Pandemic: A Focus on UK Older Adults Deemed Clinically Extremely Vulnerable

A case for the use of deep learning algorithms for individual and population level assessments of mental health disorders: Predicting depression among China's elderly

BACKGROUND

With the continuous advancement of age in China, attention should be paid to the mental well-being of the elderly population. The present study uses a novel machine learning (ML) method on a large representative elderly database in China as a sample to predict the risk factors of depression in the elderly population from both holistic and individual level.

METHODS

A total of participants met the inclusion criteria from the fourth waves of the China Health and Retirement Longitudinal Study (CHARLS) were analyzed with ML algorithms. The level of depression was assessed by the 10-item Center for Epidemiological Studies Depression Scale (CESD-10).

RESULTS

The current study found top 5 factors that were important for predicting depression in the elderly population in China, including average sleep time, gender, age, social activities and nap time during the day. The results also provide reliable diagnostic likelihood at the individual level to support clinicians identify the most impactful factors contributing to patient depression. Our findings also suggested that activities such as interacting with friends and play ma-Jong, chess or join community clubs may have a positive collaborative effect for elderly's mental health.

CONCLUSIONS

Holistic approaches are an effective method of deriving and interpreting sophisticated models of mental health in elderly populations. More detailed information about a patient's demographics, medical history, sleeping patterns and social/leisure activities can help to inform policy and treatment interventions on a population and individual level. Large scale surveys such as CHARLS are effective methods for testing the most accurate models, however, further research using professional clinical input could further advance the field.

Pandemic policies and sleeping problems in older adults

Sleep quality is fundamental to physical and mental health. Recent research shows that the COVID-19 pandemic has affected individuals' sleep quality. This study aims to investigate whether the containment and health policies (Oxford Coronavirus Government Response Tracker indexes) adopted by European countries and Israel during the pandemic are related to sleep problems in people aged 50 and over. A cross-sectional study was conducted using a logistic regression analysis based on data from the Survey of Health, Ageing and Retirement in Europe, collected in 27 European countries and Israel, in 2021. The results show that containment and health policies affect older adults' sleep, once we neutralise the influence of the sociodemographic, economic, and health characteristics of the individuals and close contact with COVID-19. In fact, the more containment and health policies, the fewer chances of sleep problems. A possible explanation for this is that these policies give people over 50 a sense of safety and security in relation to COVID-19, which may reduce sleep problems.

Global burden of sleep disturbances among older adults and the disparities by geographical regions and pandemic periods

Sleep disturbances are highly prevalent during the COVID-19 pandemic, especially among older adults. We aimed to evaluate sleep heath during COVID-19 pandemic and assess the differences among geographical regions and pandemic periods. We searched three databases (PubMed, Embase, Web of Science) to find articles up to March 12, 2023. We included observational studies that reported the prevalence of sleep disturbances among adults aged 60 years or older in any setting. Two researchers independently reviewed the literature and retrieved the data. We used Der Simonian-Laird random effects meta-analyses to pool the data, followed by subgroup analysis, sensitivity analysis, and meta-regression. A total of 64 studies with 181,224 older adults during the pandemic were included. The prevalence of poor sleep quality, short sleep duration, long sleep duration, and insomnia symptoms were 47.12% (95% CI: 25.97%, 68.27%), 40.81% (95% CI: 18.49%, 63.12%), 31.61% (95% CI: 24.83%, 38.38%), and 21.15% (95% CI: 15.30%, 27.00%), respectively. The prevalence of sleep problems reported by self-constructed items was 26.97% (95% CI: 20.73%, 33.22%). When compared to America (64.13%), Europe (20.23%) and the Western Pacific (21.31%) showed a lower prevalence of sleep problems (all P < 0.0001). The prevalence of worsened sleep problems was 27.88% (95% CI: 11.94%, 43.82%). Compared to 2020 (15.14%), it increased to 47.42% in 2021 (P < 0.05). Eight studies on sleep disturbances among 672 older COVID-19 patients were included. The prevalence of sleep problems and insomnia symptoms among older COVID-19 patients were 41.58% (95% CI: 21.97%, 61.20%) and 41.56% (95% CI: 28.11%, 58.02%), respectively. A significant burden related to poor sleep has been observed among older adults worldwide over the past three years, with variations across different regions and time periods. It is important to make more efforts in prevention and intervention to identify the risk factors, treatment, and rehabilitation of sleep disturbances for healthy aging.

Lifestyle and behavioural changes in older adults during the Covid-19 pandemic are associated with subjective cognitive complaints

Subjective cognitive complaints (SCC) is a self-reported experience of persistently impaired cognitive functions which could be the earliest red flag of neurocognitive disorders. The COVID-19 pandemic and related restriction measures changed the lifestyle and behaviour of older adults. The aim of this study was to assess the relation of these changes and SCC status in Hungary. This cross-sectional study analysed the data of 359 elderly Hungarians who filled out the WW-FINGERS-SARS-CoV2 survey. A quarter of the respondents (n:88) reported SCC in connection with the pandemic. We compared sociodemographic features, health status, lifestyle, and social life parameters between subjects with reported SCC and without. To eliminate the potential interrelation across group differences, stepwise logistic regression was applied. Participants with SCC showed the following characteristics, compared to individuals without: (1) they were older; (2) they were more likely to be women; (3) they had a higher number of chronic disorders; (4) showed more prominent impairment in physical mobility; (5) had worse sleep quality; (6) spent less time with family; and (7) used internet more frequently during the pandemic (all p's < 0.001). Logistic regression highlighted that only two parameters were related to SCC status independently, the physical mobility (ability to walk 500 m without difficulties; OR = 1.186; p < 0.001; 95%CI = 1.101, 1.270) and changes in time spent with grandchildren (OR = 1.04; p = 0.015; 95%CI = 1.008, 1.073). Our study draws attention to the importance of physical mobility and quality time with family as key factors in the cognitive well-being of elderly people.

Development and validation of prediction models for poor sleep quality among older adults in the post-COVID-19 pandemic era

BACKGROUND

Corona Virus Disease 2019 (COVID-19) has a significant impact on sleep quality. However, the effects on sleep quality in the post-COVID-19 pandemic era remain unclear, and there is a lack of a screening tool for Chinese older adults. This study aimed to understand the prevalence of poor sleep quality and determine sensitive variables to develop an effective prediction model for screening sleep problems during infectious diseases outbreaks.

MATERIALS AND METHODS

The Peking University Health Cohort included 10,156 participants enrolled from April to May 2023. The Pittsburgh Sleep Quality Index (PSQI) scale was used to assess sleep quality. The data were randomly divided into a training-testing cohort (n = 7109, 70%) and an independent validation cohort (n = 3027, 30%). Five prediction models with 10-fold cross validation including the Least Absolute Shrinkage and Selection Operator (LASSO), Stochastic Volatility Model (SVM), Random Forest (RF), Artificial Neural Network (ANN), and XGBoost model based on the area under curve (AUC) were used to develop and validate predictors.

RESULTS

The prevalence of poor sleep quality (PSQI >7) was 30.69% (3117/10,156). Among the generated models, the LASSO model outperformed SVM (AUC 0.579), RF (AUC 0.626), ANN (AUC 0.615) and XGBoost (AUC 0.606), with an AUC of 0.7. Finally, a total of 12 variables related to sleep quality were used as parameters in the prediction models. These variables included age, gender, ethnicity, educational level, residence, marital status, history of chronic diseases, SARS-CoV-2 infection, COVID-19 vaccination, social support, depressive symptoms, and cognitive impairment among older adults during the post-COVID-19 pandemic. The nomogram illustrated that depressive symptoms contributed the most to the prediction of poor sleep quality, followed by age and residence.

CONCLUSIONS

This nomogram, based on twelve-variable, could potentially serve as a practical and reliable tool for early identification of poor sleep quality among older adults during the post-pandemic period.

Sleep Disturbance and SARS-CoV-2 Vaccinations in Patients With Chronic Inflammatory Disease

OBJECTIVE

Immunocompromised patients with chronic inflammatory disease (CID) may have experienced additional psychosocial burden during the COVID-19 pandemic due to their immunocompromised status. This study was undertaken to determine if vaccination would result in improved patient-reported outcomes longitudinally among individuals with CID undergoing SARS-CoV-2 vaccination regardless of baseline anxiety.

METHODS

Data are from a cohort of individuals with CID from 2 sites who underwent SARS-CoV-2 vaccination. Participants completed 3 study visits before and after 2 messenger RNA vaccine doses in the initial vaccination series when clinical data were collected. Patient-reported outcomes were measured using the Patient-Reported Outcomes Measurement Information System 29-item Health Profile and expressed as T scores, with 2 groups stratified by high and low baseline anxiety. Mixed-effects models were used to examine longitudinal changes, adjusting for age, sex, and study site.

RESULTS

A total of 72% of the cohort was female with a mean ± SD age of 48.1 ± 15.5 years. Overall, sleep disturbance improved following both doses of SARS-CoV-2 vaccinations, and anxiety decreased after the second dose. Physical function scores worsened but did not meet the minimally important difference threshold. When stratifying by baseline anxiety, improvement in anxiety, fatigue, and social participation were greater in the high anxiety group. Physical function worsened slightly in both groups, and sleep disturbance improved significantly in the high anxiety group.

CONCLUSION

Sleep disturbance decreased in a significant and meaningful way in patients with CID upon vaccination. In patients with higher baseline anxiety, social participation increased, and anxiety, fatigue, and sleep disturbance decreased. Overall, results suggest that SARS-CoV-2 vaccination may improve mental health and well-being, particularly among those with greater anxiety.

Neurophenotypes of COVID-19: Risk factors and recovery outcomes

Coronavirus disease 2019 (COVID-19) infection is associated with risk of persistent neurocognitive and neuropsychiatric complications. It is unclear whether the neuropsychological manifestations of COVID-19 present as a uniform syndrome or as distinct neurophenotypes with differing risk factors and recovery outcomes. We examined post-acute neuropsychological profiles following SARS-CoV-2 infection in 205 patients recruited from inpatient and outpatient populations, using an unsupervised machine learning cluster analysis, with objective and subjective measures as input features. This resulted in three distinct post-COVID clusters. In the largest cluster (69%), cognitive functions were within normal limits, although mild subjective attention and memory complaints were reported. Vaccination was associated with membership in this "normal cognition" phenotype. Cognitive impairment was present in the remaining 31% of the sample but clustered into two differentially impaired groups. In 16% of participants, memory deficits, slowed processing speed, and fatigue were predominant. Risk factors for membership in the "memory-speed impaired" neurophenotype included anosmia and more severe COVID-19 infection. In the remaining 15% of participants, executive dysfunction was predominant. Risk factors for membership in this milder "dysexecutive" neurophenotype included disease-nonspecific factors such as neighborhood deprivation and obesity. Recovery outcomes at 6-month follow-up differed across neurophenotypes, with the normal cognition group showing improvement in verbal memory and psychomotor speed, the dysexecutive group showing improvement in cognitive flexibility, and the memory-speed impaired group showing no objective improvement and relatively worse functional outcomes compared to the other two clusters. These results indicate that there are multiple post-acute neurophenotypes of COVID-19, with different etiological pathways and recovery outcomes. This information may inform phenotype-specific approaches to treatment.

Risk Perception, Perceived Government Coping Validity, and Individual Sleep Problems in the Early Stage of the COVID-19 Pandemic in China: Mediation Analysis Based on Negative Emotions

This study aimed to investigate the relationship among risk perception, negative emotions, perceived government coping validity, and the sleep problem of the public, through regression analysis and mediation analysis of data from the early stages of the COVID-19 outbreak in China (three months after the outbreak). It found that people's perception of the risk of the pandemic, negative emotions, and perceived government coping validity significantly affected people's sleep quality and nightmares. Further analysis found that individuals' perception of risk not only affected their sleep but also intensified their negative emotions, ultimately impairing the quality of their sleep and leading to nightmares. However, having a high level of coping validity can mitigate negative emotions and consequently decrease the occurrence of nightmares, thereby enhancing the quality of sleep. Specifically, perceived government coping validity could not only directly reduce nightmares, but also indirectly reduce nightmares by lowering negative emotions. However, it could only indirectly improve sleep by reducing negative emotions. It implicated that improving and resolving sleep problems required not only medical intervention but also psychological intervention. Simultaneously, improving the government's response effectiveness could strengthen people's trust in the government, stabilize their mental states, and significantly improve their quality of life by reducing negative emotions and improving sleep.

Marital status, household size, and lifestyle changes during the first COVID-19 pandemic: NIPPON DATA2010

Stay-at-home strategies taken during the COVID-19 pandemic changed our lifestyle drastically. Although marital status and household size are important social determinants of health that affect lifestyle, their impacts on lifestyle during the pandemic are still unclear. We aimed to evaluate the association between marital status, household size, and lifestyle changes during the first pandemic in Japan. Questionnaire surveys on lifestyle changes from before to during the first COVID-19 pandemic were conducted on October 2020 in Japan. Classified into age groups, multivariable logistic regression analysis was performed to examine the combined association of marital status and household size on lifestyle, adjusted for potential confounders including socioeconomic factors. In our prospective cohort study, 1928 participants were included. Among older participants, the singles living alone were likely to perceive more unhealthy lifestyle changes (45.8%), compared with the married (33.2%), and significantly associated with at least one unhealthy change [adjusted odds ratio (OR): 1.81, 95% confidence interval (CI): 1,18-2.78], mainly due to decreased physical activity and increased alcohol consumption. Meanwhile, the younger participants showed no significant association between marital status, household size, and unhealthy changes, while those living alone had 2.87 times higher odds of weight gain (≥ 3 kg) than the married (adjusted OR: 2.87, 95% CI: 0.96-8.54) during the pandemic. Our findings suggest that older singles living alone are potentially vulnerable subgroups to drastic social changes which warrant special attention to prevent adverse health outcomes and additional burden on health systems in the following future.

ABO Blood System and COVID-19 Susceptibility: Anti-A and Anti-B Antibodies Are the Key Points

The implication of the ABO blood group in COVID-19 disease was formulated early, at the beginning of the COVID-19 pandemic more than 2 years ago. It has now been established that the A blood group is associated with more susceptibility and severe symptoms of COVID-19, while the O blood group shows protection against viral infection. In this review, we summarize the underlying pathophysiology of ABO blood groups and COVID-19 to explain the molecular aspects behind the protective mechanism in the O blood group. A or B antigens are not associated with a different risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection than that of other antigens. In this case, the cornerstone is natural anti-A and anti-B antibodies from the ABO system. They are capable of interfering with the S protein (SARS-CoV-2) and angiotensin-converting enzyme 2 (ACE2; host cell receptor), thereby conferring protection to patients with sufficient antibodies (O blood group). Indeed, the titers of natural antibodies and the IgG isotype (specific to the O blood group) may be determinants of susceptibility and severity. Moreover, older adults are associated with a higher risk of bad outcomes due to the lack of antibodies and the upregulation of ACE2 expression during senescence. A better understanding of the role of the molecular mechanism of ABO blood groups in COVID-19 facilitates better prognostic stratification of the disease. Furthermore, it could represent an opportunity for new therapeutic strategies.