The human electroencephalogram (EEG) of sleep undergoes profound changes with age. These changes can be conceptualized as "brain age", which can be compared to an age norm to reflect the deviation from normal aging process. Here, we develop an interpretable machine learning model to predict brain age based on two large sleep EEG datasets: the Massachusetts General Hospital sleep lab dataset (MGH, N = 2,621) covering age 18 to 80; and the Sleep Hearth Health Study (SHHS, N = 3,520) covering age 40 to 80. The model obtains a mean absolute deviation of 8.1 years between brain age and chronological age in the healthy participants in the MGH dataset. As validation, we analyze a subset of SHHS containing longitudinal EEGs 5 years apart, which shows a 5.5 years difference in brain age. Participants with neurological and psychiatric diseases, as well as diabetes and hypertension medications show an older brain age compared to chronological age. The findings raise the prospect of using sleep EEG as a biomarker for healthy brain aging.In total, we identify 2,621 EEGs where 189 of them have neurological or psychiatric diseases. Table 1 provides summary statistics for the dataset.

Health literacy, a more complex concept than knowledge, is a required capacity to obtain, understand, integrate and act on health information [1], in order to enhance individual and community health, which is defined by different levels, according to the autonomy and personal capacitation in decision making [2]. Medium levels of Health literacy in an adolescent population were found in a study conducted in 2013/2014, being higher in sexual and reproductive health and lower in substance use. It was also noticed that the higher levels of health literacy were in the area adolescents refer to have receipt more health information. The health literacy competence with higher scores was communication skills, and the lower scores were in the capacity to analyze factors that influence health. Higher levels were also found in younger teenagers, but in a higher school level, confirming the importance of health education in these age and development stage. Adolescents seek more information in health professionals and parents, being friends more valued as a source information in older adolescents, which enhance the importance of peer education mainly in older adolescents [3]. As a set of competences based on knowledge, health literacy should be developed through education interventions, encompassing the cultural and social context of individuals, since the society, culture and education system where the individual is inserted can define the way the development and enforcement of the health literacy competences [4]. The valued sources of information should be taken into account, as well as needs of information in some topics referred by adolescents in an efficient health education. Schizophrenia is a serious and chronic mental illness which has a profound effect on the health and well-being related with the well-known nature of psychotic symptoms. The exercise has the potential to improve the life of people with schizophrenia improving physical health and alleviating psychiatric symptoms. However, most people with schizophrenia remains sedentary and lack of access to exercise programs are barriers to achieve health benefits. The aim of this study is to evaluate the effect of exercise on I) the type of intervention in mental health, II) in salivary levels of alpha-amylase and cortisol and serum levels of S100B and BDNF, and on III) the quality of life and selfperception of the physical domain of people with schizophrenia. The sample consisted of 31 females in long-term institutions in the Casa de Saúde Rainha Santa Isabel, with age between 25 and 63, and with diagnosis of schizophrenia according to the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR). Physical fitness was assessed by the six-minute walk distance test (6MWD). Biological variables were determined by ELISA (Enzyme-Linked Immunosorbent Assay). Psychological variables were assessed using SF-36, PSPP-SCV, RSES and SWLS tests. Walking exercise has a positive impact on physical fitness (6MWD -p = 0.001) and physical components of the psychological test...

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