<b>Objectives</b><br/>The objective of this review was to analyze quantitative data on autism spectrum disorder (ASD) and to increase the accuracy of estimates of the prevalence of ASD.
<br/><b>Methods</b><br/>This review, which was reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement, included studies conducted from January 2008 to June 2024 on children aged 3 to 18 years that used standardized measurement tools and reported cut-off scores for ASD. The prevalence of ASD was the primary outcome analyzed in this review. The PubMed, Clinical Key, Scopus, Embase, CINAHL, and Web of Science databases were reviewed for relevant studies. The review protocol was registered with PROSPERO and followed the Cochrane collaboration guidelines.
<br/><b>Results</b><br/>A total of 66 studies reported on the prevalence of ASD, screening 21,313,061 children worldwide. Among these, 25 studies were conducted in Europe, 22 in Asia, and 13 in America. Additionally, 3 studies each were reported from Africa and Australia. According to a meta-analysis, 0.77% of children globally are diagnosed with ASD, with boys comprising 1.14% of this group. Notably, Australia showed the highest prevalence rate, with an effect size of 2.18, highlighting it as a critical area for public health focus.
<br/><b>Conclusion</b><br/>ASD represents a significant global health burden. Early detection, increased awareness among parents, and prompt intervention are crucial for mitigating developmental problems in children later in life. It is essential for health policymakers to acknowledge the prevalence and growing trends of ASD in order to implement effective interventions.
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<b>Objectives</b><br/>The objectives of this review and meta-analysis were twofold: first, to determine the prevalence of substance use among school-going children in Arab and African countries; and second, to highlight the considerable influence of variables such as the nation’s region and the timeframe of the study on the prevalence of substance use.
<br/><b>Methods</b><br/>Research was sourced from Science Direct, Scopus, Web of Science, Google Scholar, and PubMed. Thirty-seven articles were incorporated in accordance with the PRISMA guidelines. This review included studies published from 2013 to 2023. The statistical meta-analysis was performed using Comprehensive Meta-Analysis ver. 3 software. Across 37 studies, the total number of study participants was 73,508.
<br/><b>Results</b><br/>The meta-analysis revealed that tobacco was the most commonly used substance, with a prevalence of 16% (95% confidence interval [CI], 12.7%–20.02%). This was closely followed by alcohol, which had a prevalence of 15% (95% CI, 10.5%–22.8%), stimulants at 11.4% (95% CI, 7.4%–17%), khat at 10% (95% CI, 5.7%–15%), and cannabis at 8% (95% CI, 3.3%–18.4%). Notably, alcohol was the only substance that showed an increasing trend in prevalence from before to after 2019, rising from 13.3% (95% CI, 6.2%–26.1%) to 17% (95% CI, 10.2%–27%) (p<0.001). Additionally, the prevalence of substance use varied significantly between Arab and African countries (p<0.001).
<br/><b>Conclusion</b><br/>Although the prevalence of substance use among school-going populations has significantly decreased over time, with the exception of alcohol, it is imperative that both African and Arab countries implement comprehensive measures and stringent laws to address the production and marketing of substances.
<b>Objectives</b><br/>Patients with coronavirus disease 2019 (COVID-19) present with a variety of oral manifestations. Therefore, we conducted a systematic review to estimate the prevalence of oral lesions among COVID-19 patients. Methods: An extensive literature search of several electronic bibliographic databases (PubMed, Scopus, Science Direct, Litcovid) was conducted to retrieve all articles published in the English language from January 1, 2020 to March 31, 2023 that reported the prevalence of oral manifestations among COVID-19 patients. A meta-analysis of pooled prevalence was performed using Jamovi ver. 2.3 (2022). The I2 and Q statistics were used to assess heterogeneity between studies, and p-values <0.01 were considered statistically significant. Results: In total, 79 studies with data from 13,252 patients were included. The articles were predominantly published in 2020 (n=33), and Italy was the most common country (n=14). Most of the affected patients more than 50 years old and women (56.6%). The most common sites of involvement were the tongue (n=65), followed by the oral mucosa (n=37) and lips (n=19). High heterogeneity was found between studies. The most common oral manifestation was taste alteration, followed by xerostomia and ulceration, showing pooled prevalence rates of 48%, 35%, and 21%, respectively. Conclusion: COVID-19 patients show various oral manifestations that may help clinicians identify the disease promptly. Recognition of the signs and symptoms of COVID-19 is critical for an early diagnosis and better prognosis.
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The extensive history of pandemics has spanned many centuries, profoundly impacting societies, economies, and public health, and thereby shaping the course of history in various ways. Advances in medicine, science, and public health practices have played a pivotal role in mitigating the effects of pandemics over time. This review explores the scientific landscape of contemporary pandemics, examining their diverse and complex nature. It goes beyond the biological aspects of pandemics to consider socioeconomic, environmental, and technological factors. Through a scientific lens, this study aims to understand the complexities of pandemics and contribute to the expanding knowledge base that helps humanity strengthen its defenses against global health threats. By elucidating the enigmas of pandemics, the study hopes to foster a more resilient and prepared global health environment. Highlighting the importance of a multidisciplinary, cross-disciplinary, and transdisciplinary approach, this exploration emphasizes the critical need to integrate biological, socioeconomic, environmental, and technological domains to develop more robust defenses against these global health challenges.
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<b>Objectives</b><br/>This review and meta-analysis examined the effectiveness of non-pharmacological therapies delivered through school-based interventions for smoking cessation among adolescents in South and Southeast Asian countries.
<br/><b>Methods</b><br/>A systematic search was conducted across PubMed, Scopus, Science Direct, BioMed Central, the Cochrane Library, and ProQuest Dissertations & Theses Global from inception to October 2024. Eligible studies comprised randomized controlled trials and quasi-experimental studies that compared non-pharmacological smoking cessation interventions delivered in schools or other educational institutions. Data on smoking abstinence outcomes were extracted from published studies, and odds ratios (ORs) with 95% confidence intervals (CIs) were pooled using a random-effects model via the Mantel-Haenszel estimator.
<br/><b>Results</b><br/>Seven studies involving 1,260 participants were included. The meta-analysis demonstrated that non-pharmacological school-based therapies significantly increased smoking abstinence compared to controls (OR, 2.83; 95% CI, 1.83–4.40; p<0.001. Subgroup analyzes revealed benefits across both randomized controlled trials and quasi-experimental studies with varying abstinence rates. Studies utilizing biochemical verification showed significant positive effects despite substantial heterogeneity, and short-term (<3 months) abstinence was significantly higher in intervention groups compared to controls. Overall, no differences were found between subgroups regarding intervention effectiveness.
<br/><b>Conclusion</b><br/>This meta-analysis indicates that non-pharmacological school-based interventions positively impact smoking abstinence rates, although effectiveness may vary based on study design, follow-up duration, and use of biochemical verification. The findings underscore the need for further research with larger sample sizes, extended follow-up periods, and improved methodological rigor in these regions.
Global health security threats in the post-coronavirus disease 2019 era include dense urban populations, increased human–animal proximity, migration driven by political or economic instability, climate change, humanitarian crises, antimicrobial resistance (AMR), and the misuse of biological research—including the accidental or intentional release of high-risk pathogens. The foundational preparation for these threats is to establish a robust, resilient public health system based on universal health coverage. The World Health Organization’s International Health Regulations must continue to promote global solidarity by maintaining core capacities such as surveillance, national laboratories, and epidemiological investigations of emerging infectious diseases, with timely reporting and information sharing within the global health security community. A One Health approach is essential for addressing AMR. Infection prevention and control must be enhanced to reduce healthcare-associated infections in medical facilities. Additionally, regulations concerning biosafety and biosecurity should address dual-use research of concern as well as the accidental or intentional release of highrisk pathogens from laboratories. Global health security is a collective responsibility because these threats know no borders and require coordinated action.
<b>Objectives</b><br/>Despite effective vaccination strategies, measles remains a global public health challenge. The study explored individual and contextual factors associated with measles infection in Malaysia from 2018 to 2022, informing the development of targeted public health interventions. Methods: This cross-sectional study utilised data from the Ministry of Health, the Department of Statistics, and the Department of Environment Malaysia. Multilevel logistic regression analysis was employed to examine individual-level factors, including age, sex, ethnicity, nationality, contact history, travel history, and vaccination status. Concurrently, contextual factors were assessed, encompassing district-level determinants such as population density, median household income, urbanisation, the number of health and rural clinics, vaccination rates, fine particulate matter less than 2.5 μm (PM2.5) levels, relative humidity, and temperature, to determine their impact on measles infection risk. Results: Measles infection was significantly associated with various individual factors. These included age (adjusted odds ratio [aOR], 1.02; 95% confidence interval [CI], 1.02–1.03), ethnicity, non-Malaysian nationality (aOR, 34.53; 95% CI, 8.42– 141.51), prior contact with a measles case (aOR, 2.36; 95% CI, 2.07–2.69), travel history (aOR, 2.30; 95% CI, 1.13–4.70), and vaccination status (aOR, 0.76; 95% CI, 0.72–0.79). Among contextual factors, urbanisation (aOR, 1.56; 95% CI, 1.16– 2.10) and the number of clinics (aOR, 0.98; 95% CI, 0.97–0.99) were significant determinants. Conclusion: This multilevel logistic regression analysis illuminates the complexities of measles transmission, advocating public health interventions tailored to individual and contextual vulnerabilities. The findings highlight the need for a synergistic approach that combines vaccination campaigns, healthcare accessibility improvements, and socioeconomic interventions to effectively combat measles.
<b>Objectives</b><br/>Mild cognitive impairment (MCI) is prevalent among older adults and may progress to dementia. This study evaluated the effectiveness of a game-based brain exercise program in reducing MCI among older adults.
<br/><b>Methods</b><br/>A quasi-experimental study was conducted with 2 groups of older participants in Pathum Thani Province, Thailand. A total of 96 individuals with Thai mental state examination (TMSE) scores between 12 to 23, indicating MCI but no dementia diagnosis, were recruited. Using multi-stage sampling, participants were divided into an intervention group (n=48) and a control group (n=48). The intervention group participated in a 6-week game-based brain exercise program, while the control group received a self-administered brain exercise manual. Face-to-face interviews assessed outcomes at baseline, post-intervention, and 3-month follow-up. Data were analyzed using descriptive statistics and repeated-measures analysis of variance.
<br/><b>Results</b><br/>Significant differences were observed in mean TMSE scores and MCI knowledge between the intervention and control groups at the 3-month follow-up (p<0.001). The intervention group showed significant increases in TMSE scores and MCI knowledge post-intervention and at 3-month follow-up (p<0.001).
<br/><b>Conclusion</b><br/>The findings suggest that a game-based brain exercise program can improve cognitive function in older adults. Healthcare professionals can implement such programs to reduce MCI by addressing planning, management, and related issues in the future.
<b>Objectives</b><br/>Several previous studies have stated that consuming certain foods and beverages might increase the risk of chronic kidney disease (CKD). This study aimed to examine the relationships of food and beverage consumption with other risk factors for CKD. Methods: Data sources included the 2018 Basic Health Research (Riskesdas) and the National Socio-Economic Survey (Susenas), which were analyzed using a cross-sectional design. The study samples were households from 34 provinces in Indonesia, and the analysis was performed with provincial aggregates. Data were analyzed using risk factor analysis followed by linear regression to identify relationships with CKD. Results: The prevalence of CKD in Indonesia was 0.38%. The province with the highest prevalence was North Kalimantan (0.64%), while the lowest was found in West Sulawesi (0.18%). Five major groups were formed from 15 identified risk factors using factor analysis. A linear regression model presented 1 significant selected factor (p=0.006, R2 =31%). The final model of risk factors included water quality, consumption of fatty foods, and a history of diabetes. Conclusion: Drinking water quality, fatty food consumption, and diabetes are associated with CKD. There is a need to monitor drinking water, as well as to promote health education and provide comprehensive services for people with diabetes, to prevent CKD.
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<b>Objectives</b><br/>This study systematically reviewed and analyzed epidemiological evidence regarding the association between dietary total antioxidant capacity (DTAC) and both the risk of developing diabetes and glycemic biomarker levels.
<br/><b>Methods</b><br/>We searched the PubMed, Scopus, ScienceDirect, and Google Scholar databases through July 2024 without imposing any date restrictions. Original studies that examined the relationship between DTAC and either the risk of developing diabetes or glycemic biomarker levels—specifically fasting blood glucose (FBG), hemoglobin A1C (HbA1C), insulin, and the homeostatic model assessment for insulin resistance (HOMA-IR)—were eligible for inclusion. After eliminating duplicates and irrelevant records, relevant studies were selected, and data were extracted through rigorous critical analysis.
<br/><b>Results</b><br/>A total of 32 articles were included in the review. Of the 19 studies that evaluated diabetes risk, 15 reported a lower risk among subjects with higher DTAC values. All 4 studies examining prediabetes risk found lower risk in participants with high DTAC scores. Additionally, significant inverse relationships were observed between DTAC values and FBG (9/15 studies), HbA1C (1/6 studies), insulin (5/6 studies), and HOMA-IR (8/9 studies).
<br/><b>Conclusion</b><br/>The majority of evidence indicates that high adherence to an antioxidant-rich diet may reduce diabetes risk and improve glycemic biomarkers, including FBG, insulin, and HOMA-IR.
<b>Objectives</b><br/>The coronavirus disease 2019 (COVID-19) pandemic continues to pose significant challenges to the public health sector, including that of the United Arab Emirates (UAE). The objective of this study was to assess the efficiency and accuracy of various deep-learning models in forecasting COVID-19 cases within the UAE, thereby aiding the nation’s public health authorities in informed decision-making. 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.
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