In December 2019, multiple cases of novel coronavirus disease (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), were reported in Wuhan, China.¹ On March 11, 2020, the World Health Organization (WHO) declared that COVID-19 can be characterized as a pandemic. To date, the transmission of COVID-19 is still difficult to contain, as confirmed and death cases are still increasing. Up to March 16, 2022, 460 280 168 confirmed cases and 6 050 018 confirmed deaths have been reported to the WHO.² Rapid spread of COVID-19 has had enormous social, economic, and health care system effects around the world. Effective treatment to block the spread of COVID-19 is not developed yet, so countries have implemented a series of nontreatment interventions such as social distancing, isolation, face mask mandates, and quarantining to reduce its rapid transmission.³ Existing evidence has shown that most of COVID-19 cases are missed by screening because infected persons are unaware they were exposed and have not developed symptoms yet.^4-6

Aims: To assess the association of sleep factors (sleep duration, trouble sleeping, sleep disorder) and combined sleep behaviours with the risk of clinically relevant depression (CRD). Methods: A total of 17 859 participants (8806 males and 9053 females) aged 20–79 years from the National Health and Nutrition Examination Survey (NHANES) 2007–2014 waves were included. Sleep duration, trouble sleeping and sleep disorder were asked in the home by trained interviewers using the Computer-Assisted Personal Interviewing (CAPI) system. The combined sleep behaviours were referred to as ‘sleep patterns (healthy, intermediate and poor)’, with a ‘healthy sleep pattern’ defined as sleeping 7–9 h per night with no self-reported trouble sleeping or sleep disorders. And intermediate and poor sleep patterns indicated 1 and 2–3 sleep problems, respectively. Weighted logistic regression was performed to evaluate the association of sleep factors and sleep patterns with the risk of depressive symptoms. Results: The total prevalence of CRD was 9.5% among the 17 859 participants analysed, with females having almost twice as frequency than males. Compared to normal sleep duration (7–9 h), both short and long sleep duration were linked with a higher risk of CRD (short sleep: OR: 1.66, 95% CI: 1.39–1.98; long sleep: OR: 2.75, 95% CI: 1.93–3.92). The self-reported sleep complaints, whether trouble sleeping or sleep disorder, were significantly related with CRD (trouble sleeping: OR: 3.04, 95% CI: 2.59–3.56; sleep disorder: OR: 1.83, 95% CI: 1.44–2.34). Furthermore, the correlations appeared to be higher for individuals with poor sleep pattern (OR: 5.98, 95% CI: 4.91–7.29). Conclusions: In this national representative survey, it was shown that there was a dose-response relationship between sleep patterns and CRD.

Cardiovascular disease (CVD) is the leading cause of death worldwide. Population aging is becoming the most important driver of the CVD epidemic. With the rapid increase in an aging population, the burden of CVD will continuously increase. Most old people also suffer multimorbidity, which is strongly associated with impaired quality of life, disability, dependence, and mortality. However, few reviews evaluated the CVD burden accompanied by population aging and the challenges of CVD care in elderly individuals with multimorbidity. This review identified and summarized the current status of the CVD epidemic associated with aging and highlighted the challenges and needs of CVD care for the elderly.

Inflammation is known as an important mechanism of cognitive dysfunction. Systemic immune inflammation index (SII) and system inflammation response index (SIRI) are two blood inflammatory markers, which are related to many chronic diseases including cognitive impairment. It is recognized that dietary inflammatory index (DII), which is used to estimate the overall inflammatory potential of diet, may be related to mild cognitive impairment (MCI) as well. This study aimed to explore the relationship between SII, SIRI and DII, as well as the role of these inflammatory indexes on MCI in elderly people. A total of 1050 participants from Beijing were included. Neuropsychological tests were used for cognitive evaluation. Energy-adjusted DII scores were calculated based on semi-quantitative food frequency questionnaire. Blood samples were tested for calculating SII and SIRI. Log-binomial regression models were used to estimate the correlation of indexes. After adjusting demographic characteristics, SII and SIRI in MCI individuals were higher than controls (p ≤ 0.001). DII, SII and SIRI had positive relationship with MoCA scores (p < 0.005). DII also correlated with SIRI in MCI (β = 0.11, p = 0.031). Higher DII and SIRI could definitely increase the risk of MCI, as well as DII and SII (p < 0.005). In conclusion, DII was positively correlated with blood inflammation. The elderly with higher level of DII and SIRI, or DII and SII could be considered as people with higher risk of developing MCI.