METHODS: The study utilized data from the Global Burden of Disease, Injuries, and Risk Factors Study 2019, concentrating on adolescents aged 10 to 24 years with depression. We conducted an in-depth analysis of depression, including its age-standardized prevalence, incidence, and Disability-Adjusted Life Years (DALYs), across diverse demographics such as regions, ages, genders, and socio-demographic indexes, spanning from 1990 to 2019.
RESULTS: The analysis found decreasing trends in the prevalence, incidence, and DALYs of adolescent depression in the WPR between 1990-2019, although some countries like Australia and Malaysia showed increases. Specifically, the prevalence of adolescent depression in the region decreased from 9,347,861.6 cases in 1990 to 5,551,341.1 cases in 2019. The incidence rate declined from 2,508.6 per 100,000 adolescents in 1990 to 1,947.9 per 100,000 in 2019. DALYs decreased from 371.9 per 100,000 in 1990 to ASR 299.7 per 100,000 in 2019.
CONCLUSION: This study found an overall decreasing trend in adolescent depression burden in the Western Pacific Region between 1990 and 2019, with heterogeneity across countries. For 30 years, the 20-24 age group accounted for the majority of depression among adolescents Widening inequality in depression burden requires policy attention. Further analysis of risk factors contributing to epidemiological trends is warranted to inform prevention strategies targeting adolescent mental health in the region.
METHODS: This study utilized a comprehensive dataset encompassing confirmed COVID-19 cases, demographic statistics, and socioeconomic indicators. Several advanced deep learning models, including long short-term memory (LSTM), bidirectional LSTM, convolutional neural network (CNN), CNN-LSTM, multilayer perceptron, and recurrent neural network (RNN) models, were trained and evaluated. Bayesian optimization was also implemented to fine-tune these models.
RESULTS: The evaluation framework revealed that each model exhibited different levels of predictive accuracy and precision. Specifically, the RNN model outperformed the other architectures even without optimization. Comprehensive predictive and perspective analytics were conducted to scrutinize the COVID-19 dataset.
CONCLUSION: This study transcends academic boundaries by offering critical insights that enable public health authorities in the UAE to deploy targeted data-driven interventions. The RNN model, which was identified as the most reliable and accurate for this specific context, can significantly influence public health decisions. Moreover, the broader implications of this research validate the capability of deep learning techniques in handling complex datasets, thus offering the transformative potential for predictive accuracy in the public health and healthcare sectors.
METHOD: This study was designed based on PRISMA guidelines. PubMed, Scopus, and Google Scholar databases were searched with relevant keywords. After study selection according to inclusion criteria, data of knowledge and attitude were extracted for meta-analysis.
RESULT: Twenty-two studies included 8491 participants were included in this meta-analysis. The pooled analysis revealed a proportion of 0.44 (95%CI = [0.34, 0.54], P
METHODS: This cross-sectional study surveyed athletes without disabilities using online questionnaires (35 languages) from May to July 2020. Questions included aspects of alternative routines, training monitoring, recovery, sleep patterns, injury occurrence/prevention based on structured answers, and an open-ended question on lockdown training experiences.
RESULTS: Of the 11,762 athletes from 142 countries, 63% were male, including at World-Class, International, National, State and Recreational levels. During lockdown, 25% athletes used innovative or modern ways to maintain or improve fitness e.g., virtual reality and tracking devices (favoring World-Class level, 30%). Many athletes, regardless of gender (43%) watched video competitions to improve/maintain their mental skills and performance [World-Class (47%) and International (51%)]. Contact frequency between athletes and their coaches was mainly at least once a week (36%), more among higher-level (World-Class/International) than lower-level athletes (27 vs. 16%). Higher-level athletes (≥ 54%) monitored training load and were assisted by their coaches (21%). During lockdown, stretching (67%) was considered one of the primary means of recovery, especially for higher-level athletes (> 70%). Compared to pre-lockdown, about two-thirds of athletes reported "normal" or "improved" sleep quality and quantity, suggesting a low sleep quality pre-lockdown. On average, 40% utilized injury prevention exercises (at least) once a week [World-Class (51%) and International (39%)]. Most injury occurrences during lockdown involved the knee (18%), ankle (16%), and back (9%). Four key themes emerged regarding lockdown experiences: remote training adaptation (e.g., shifting training focus), training creativity (e.g., using household items), performance enhancement opportunities (e.g., refocusing neglected aspects), and mental and motivation challenges.
CONCLUSIONS: Both male and female athletes, particularly those of higher levels, displayed some adaptalibity during the COVID-19 lockdown, employing innovative approaches and technology for training. Many athletes implemented load monitoring, recovery, and attentive of injury prevention, while optimizing their sleep quality and quantity. Athletes demonstrated their abilities to navigate challenges, and utilized different coping strategies in response to the lockdown's constraints.
METHODS: Baseline and 1-year follow-up data from 5800 participants in the PREDIMED-Plus study were used. Each participant's food intake was estimated using validated semi-quantitative food frequency questionnaires, and the adherence to MD using the Dietary Score. The influence of diet on environmental impact was assessed through the EAT-Lancet Commission tables. The influence of diet on environmental impact was assessed through the EAT-Lancet Commission tables. The association between MD adherence and its environmental impact was calculated using adjusted multivariate linear regression models.
RESULTS: After one year of intervention, the kcal/day consumed was significantly reduced (-125,1 kcal/day), adherence to a MD pattern was improved (+0,9) and the environmental impact due to the diet was significantly reduced (GHG: -361 g/CO2-eq; Acidification:-11,5 g SO2-eq; Eutrophication:-4,7 g PO4-eq; Energy use:-842,7 kJ; and Land use:-2,2 m2). Higher adherence to MD (high vs. low) was significantly associated with lower environmental impact both at baseline and one year follow-up. Meat products had the greatest environmental impact in all the factors analysed, both at baseline and at one-year follow-up, in spite of the reduction observed in their consumption.
CONCLUSIONS: A program promoting a MD, after one year of intervention, significantly reduced the environmental impact in all the factors analysed. Meat products had the greatest environmental impact in all the dimensions analysed.
OBJECTIVES: To investigate the diaphragm function, respiratory muscle strength, and pulmonary function in patients with CNP. In addition, their associations were also examined.
DESIGN: A case-control study.
METHODS: A total of 54 participants were recruited including 25 patients with CNP (CNP group) and 29 healthy adults (CON group). Pulmonary function including forced vital capacity (FVC) and forced expiratory volume in 1 s (FEV1), and respiratory muscle strength represented by maximal inspiratory (MIP) and maximal expiratory pressure (MEP), as well as diaphragm function including ultrasonographic measures of mobility and thickness changes during maximal inspiration and expiration were assessed in all participants. Additionally, the intensity of pain and disability were evaluated using a Visual Analog Scale and Neck Disability Index only in patients with CNP.
RESULTS: Significant reductions of the FVC, FEV1, MIP, and MEP were found in the CNP group compared to the CON group (p
CASE PRESENTATION: A male patient, aged 27, presented with a complaint of unerupted two maxillary front teeth. This resulted in the displacement of adjacent teeth into the vacant region. An intraoral examination revealed a Class II molars on both sides, a deep curve of the space with a 2.3 mm overjet, and an edge-to-edge bite of 0.1 mm. The 3D cone beam computed tomography (CBCT) imaging unveiled a labial impacted and a rotation of approximately 90 degrees (horizontal impacted) on both central maxillary incisors.
DISCUSSION: The self-ligating bracket was installed and orthodontic traction aligned the affected tooth in the dental arch. To reach the labial surface of the impacted incisor, open surgical exposure by window excision of soft tissues with a laser was preferable due to the large bulge in the sulcus. Because self-ligating bracket systems employed modest pressures to position the maxillary right central incisor in the arch, the window surgical technique did not produce gingival scarring or increased clinical crown length.
CONCLUSION: The impacted upper central incisor was successfully treated using a collaborative interdisciplinary (surgical-orthodontic) approach, which resulted in a favorable aesthetic and functional outcome.