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Background: The accelerated growth of elderly population is creating a heavy burden to the healthcare system in many developed countries and regions. Electrocardiogram (ECG) analysis has been recognized as effective approach to cardiovascular disease diagnosis and widely utilized for monitoring personalized health conditions.Method: In this study, we present a novel approach to forecasting one-day-forward wellness conditions for community-dwelling elderly by analyzing single lead short ECG signals acquired from a station-based monitoring device. More specifically, exponentially weighted moving-average (EWMA) method is employed to eliminate the high-frequency noise from original signals at first. Then, Fisher-Yates normalization approach is used to adjust the self-evaluated wellness score distribution since the scores among different individuals are skewed. Finally, both deep learning-based and traditional machine learning-based methods are utilized for building wellness forecasting models.Results: The experiment results show that the deep learning-based methods achieve the best fitted forecasting performance, where the forecasting accuracy and F value are 93.21% and 91.98% respectively. The deep learning-based methods, with the merit of non-hand-crafted engineering, have superior wellness forecasting performance towards the competitive traditional machine learning-based methods.Conclusion: The developed approach in this paper is effective in wellness forecasting for community-dwelling elderly, which can provide insights in terms of implementing a cost-effective approach to informing healthcare provider about health conditions of elderly in advance and taking timely interventions to reduce the risk of malignant events. [ABSTRACT FROM AUTHOR]

In the last 50 years Thailand has achieved advanced demographic and health transitions. Many infectious diseases are controlled and infant and maternal mortality rates are among the lowest in the region. Within such a low mortality setting, however, substantial variations in health persist, with education being a major driver. This paper assesses the ongoing mortality transition in Thailand, examining relationships between risk factors and mortality outcomes among a large nationwide cohort of distance-learning Open University students, as well as examining the differential mortality benefit enjoyed by this educated group when compared with the general Thai population. The cohort comprised 87,151 participants, who in 2005 completed a questionnaire collecting detailed information on socio-demographics, health behaviours and health outcomes. Participants were aged 15-87 at baseline and lived in all regions of the country. Cohort members' citizen identification numbers were matched with official death registration records to identify mortality among participants. A total of 1401 deaths were identified up to November 2016. Results show cohort study participants experiencing mortality at approximately one-third of the rate of the general population in the same age and sex groups. The gap between the mortality rates in the two groups widened with increased age. Differential risk factor prevalence among the two populations, particularly lower overweight and obesity prevalence and lower cigarette smoking rates in the cohort, can explain some of this variation. The largely unmeasurable effect of aspiration for life improvement through distance education while embedded in their communities is shown by this study to have a powerful effect on mortality risk. With overall education levels, including higher education, rising in Thailand this growing group of educated aspirational Thais may represent future trends in Thai mortality. Identifying the drivers and characteristics of this mortality variation can help inform policies to provide health services and to help reduce mortality in the whole population. [ABSTRACT FROM AUTHOR]

Patients' experience of stereotype threat in clinical settings and encounters may be one contributor to health care disparities. Stereotype threat occurs when cues in the environment make negative stereotypes associated with an individual's group status salient, triggering physiological and psychological processes that have detrimental consequences for behavior. By recognizing and understanding the factors that can trigger stereotype threat and understanding its consequences in medical settings, providers can prevent it from occurring or ameliorate its consequences for patient behavior and outcomes. In this paper, we discuss the implications of stereotype threat for medical education and trainee performance and offer practical suggestions for how future providers might reduce stereotype threat in their exam rooms and clinics. [ABSTRACT FROM AUTHOR]

Aging is associated with a number of physiologic and functional declines that can contribute to increased disability, frailty, and falls. Contributing factors are the loss of muscle mass and strength as age increases, a phenomenon called sarcopenia. Sarcopenia can result or be exacerbated by certain chronic conditions, and can also increase the burden of chronic disease. Current research has demonstrated that strength-training exercises have the ability to combat weakness and frailty and their debilitating consequences. Done regularly (e.g., 2 to 3 days per week), these exercises build muscle strength and muscle mass and preserve bone density, independence, and vitality with age. In addition, strength training also has the ability to reduce the risk of osteoporosis and the signs and symptoms of numerous chronic diseases such as heart disease, arthritis, and type 2 diabetes, while also improving sleep and reducing depression. This paper reviews the current research on strength training and older adults, evaluating exercise protocols in a variety of populations. It is clear that a variety of strength-training prescriptions from highly controlled laboratory-based to minimally supervised home-based programs have the ability to elicit meaningful health benefits in older adults. The key challenges as this field of exercise science moves forward are to best identify the most appropriate strength-training recommendations for older adults and to greatly increase the access to safe and effective programs in a variety of settings. [ABSTRACT FROM AUTHOR]