OBJECTIVE:To investigate the effect of body mass index (BMI) and body fat distribution as measured by waist-to-hip ratio (WHR) on the cardiovascular risk factor profile of the three major ethnic groups in Singapore (Chinese, Malay and Indian people) and to determine if WHO recommended cut-off values for BMI and WHR are appropriate for the different sub-populations in Singapore. DESIGN: Cross-sectional population study. SUBJECTS: A total of 4723 adult subjects (64% Chinese individuals, 21% Malay individuals and 15% Indian individuals) were selected through a multi-staged sampling technique to take part in the National Health Survey in 1998. MEASUREMENTS: Data on socio-economic status (education level, occupation, housing type) and lifestyle habits (smoking and physical activity), body weight, body height, waist and hip circumferences and blood pressure measured using standardised protocols. Fasting venous blood samples were obtained for determination of serum total cholesterol (TC), high density lipoprotein cholesterol (HDL), low density lipoprotein cholesterol (LDL), triglycerides (TG). Venous blood samples were taken for 2 h oral glucose tolerance test (2 h glu). RESULTS: Absolute and relative risks for at least one cardiovascular risk factor (elevated TC, elevated TC=HDL ratio, elevated TG, hypertension and diabetes mellitus) were determined for various categories of BMI and WHR. At low categories of BMI (BMI between 22 and 24 kg=m 2 ) and WHR (WHR between 0.80 and 0.85 for women, and between 0.90 and 0.95 for men), the absolute risks are high, ranging from 41 to 81%. At these same categories the relative risks are significantly higher compared to the reference category, ranging from odds ratio of 1.97 to 4.38. These categories of BMI and WHR are all below the cut-off values of BMI and WHR recommended by WHO. CONCLUSIONS:The results show that, at relatively low BMI and WHR, Singaporean adults experience elevated levels of risks (absolute and relative) for cardiovascular risk factors. These findings, in addition to earlier reported high percentage body fat among Singaporeans at low levels of BMI, confirm the need to revise the WHO cut-off values for the various indices of obesity and fat distribution, viz BMI and WHR, in Singapore.
During the COVID-19 pandemic, conflicting opinions on physical distancing swept across social media, affecting both human behavior and the spread of COVID-19. Inspired by such phenomena, we construct a two-layer multiplex network for the coupled spread of a disease and conflicting opinions. We model each process as a contagion. On one layer, we consider the concurrent evolution of two opinions — pro-physical-distancing and anti-physical-distancing — that compete with each other and have mutual immunity to each other. The disease evolves on the other layer, and individuals are less likely (respectively, more likely) to become infected when they adopt the pro-physical-distancing (respectively, anti-physical-distancing) opinion. We develop approximations of mean-field type by generalizing monolayer pair approximations to multilayer networks; these approximations agree well with Monte Carlo simulations for a broad range of parameters and several network structures. Through numerical simulations, we illustrate the influence of opinion dynamics on the spread of the disease from complex interactions both between the two conflicting opinions and between the opinions and the disease. We find that lengthening the duration that individuals hold an opinion may help suppress disease transmission, and we demonstrate that increasing the cross-layer correlations or intra-layer correlations of node degrees may lead to fewer individuals becoming infected with the disease.
Recurrent neural networks are widely used on time series data, yet such models often ignore the underlying physical structures in such sequences. A new class of physically-based methods related to Koopman theory has been introduced, offering an alternative for processing nonlinear dynamical systems. In this work, we propose a novel Consistent Koopman Autoencoder model which, unlike the majority of existing work, leverages the forward and backward dynamics. Key to our approach is a new analysis that unravels the interplay between consistent dynamics and their associated Koopman operators. Our network is interpretable from a physical viewpoint and its computational requirements are comparable to other baselines. We evaluate our method on a wide range of high-dimensional and short-term dependent problems. The datasets include nonlinear oscillators, sea surface temperature data, and fluid flows on a curved domain. The results show that our model yields accurate estimates for significant prediction horizons, while being robust to noise.
Background Youth with existing psychiatric illness are more apt to use the internet as a coping skill. Because many “in-person” coping skills were not easily accessible during the COVID-19 pandemic, youth in outpatient mental health treatment may have been particularly vulnerable to the development of problematic internet use (PIU). The identification of a pandemic-associated worsening of PIU in this population is critical in order to guide clinical care; if these youth have become dependent upon the internet to regulate their negative emotions, PIU must be addressed as part of mental health treatment. However, many existing studies of youth digital media use in the pandemic do not include youth in psychiatric treatment or are reliant upon cross-sectional methodology and self-report measures of digital media use. Objective This is a retrospective cohort study that used data collected from an app-based ecological momentary assessment protocol to examine potential pandemic-associated changes in digital media youth in outpatient mental health treatment. Secondary analyses assessed for differences in digital media use dependent upon personal and familial COVID-19 exposure and familial hospitalization, as well as factors associated with PIU in this population. Methods The participants were aged 12-23 years and were receiving mental health treatment in an outpatient community hospital setting. All participants completed a 6-week daily ecological momentary assessment protocol on their personal smartphones. Questions were asked about depression (PHQ-8 [8-item Patient Health Questionnaire]), anxiety (GAD-7 [7-item General Anxiety Disorder]), PIU (PIU-SF-6 [Problematic Internet Use Short Form 6]), digital media use based on Apple’s daily screen time reports, and personal and familial COVID-19 exposure. The analyses compared screen time, psychiatric symptoms, and PIU between cohorts, as well as between youth with personal or familial COVID-19 exposures and those without. The analyses also assessed for demographic and psychiatric factors associated with clinically significant PIU-SF-6 scores. Results A total of 69 participants completed the study. The participants recruited during the pandemic were significantly more likely to meet the criteria for PIU based on their average PIU-SF-6 score (P=.02) and to spend more time using social media each day (P=.049). The overall amount of daily screen time did not differ between cohorts. Secondary analyses revealed a significant increase in average daily screen time among subjects who were exposed to COVID-19 (P=.01). Youth with clinically significant PIU-SF-6 scores were younger and more likely to have higher PHQ-8 (P=.003) and GAD-7 (P=.003) scores. No differences in scale scores or media use were found between subjects based on familial COVID-19 exposure or hospitalization. Conclusions Our findings support our hypothesis that PIU may have worsened for youth in mental health treatment during the pandemic, particularly the problematic use of social media. Mental health clinicians should incorporate screening for PIU into routine clinical care in order to prevent potential familial conflict and subsequent psychiatric crises that might stem from unrecognized PIU.
We found few examples of comprehensive, patient-centered documents. Work is needed to achieve consensus as to the essential elements of TB treatment literacy and to create additional materials for children, patients with drug-resistant TB, and those with lower literacy levels.
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