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BackgroundLifestyle of children and adolescents have changed extensively during the COVID-19 pandemic due to school suspension and social distancing measures, which can affect their sleep health. Existing studies in the area used convenient samples and focused on the initial months of the pandemic. MethodAs part of a territory-wide epidemiological study in Hong Kong, this cross-sectional study recruited primary and secondary school students by stratified random sampling. We investigated the pandemics effects on sleep parameters using multivariate regression, adjusting for age, sex, household income, seasonality and presence of mental disorders, and the effects moderators and mediators. FindingsBetween September 1, 2019 and June 2, 2021, 791 primary and 442 school students were recruited and analysed. After correcting for multiple testing, being assessed during COVID predicted a longer sleep latency in primary and secondary school students in school days (95% CI = 1.0-5.2 minutes, adjusted p-value = 0.010; and 95% CI= 3.9-13.0 minutes, adjusted p-value =0.004, respectively) and non-school days (95% CI = 1.7-7.2 minutes, adjusted p-value = 0.005; 95% CI = 3.4-13.7 minutes, adjusted p-value = 0.014, respectively). Low household income was a moderator for later bedtime (adjusted p-value = 0.032) and later sleep onset (adjusted p-value = 0.043) during non-school days among secondary school students. Sex and digital leisure time were not moderator and mediator of the pandemics effect on sleep parameters, respectively. InterpretationChanges associated with the COVID-19 pandemic have a widespread and enduring effect on sleep health of school-aged students in Hong Kong. Household income play a role in adolescents sleep healths resilience against these changes, and anti-epidemic measures effects on the health gap of the youth should be considered. FundingGovernment of the Hong Kong Special Administrative Region, Food and Health Bureau, Health and Medical Research Fund (Ref. No.: MHS-P1(Part 1)-CUHK).
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Alzheimer's disease (AD) is the most prevalent form of dementia. Biomarkers such as levels of amyloid beta (Abeta) in cerebrospinal fluid and ApoE genotyping were suggested for the diagnosis of AD, however, the result is either non-conclusive or with invasive procedure. Genome-wide association studies (GWASs) for AD suggested single nucleotide polymorphisms (SNPs) in many genes are associated with the risk of AD, but each only contributed with small effect to the disease. By incorporating a panel of established genetic susceptibility factors, the risk of an individual in getting AD could be better estimated. Further research will be required to reveal if adding to the current well-developed clinical diagnosis protocol, the accuracy and specificity of diagnosis of AD would be greatly improved and if this might also be beneficial in identifying pre-symptomatic AD patients for early diagnosis and intervention of the disease.