Asthma is a prevalent respiratory condition that poses a substantial burden on public health in the United States. Understanding its prevalence and associated risk factors is vital for informed policymaking and public health interventions. This study aims to examine asthma prevalence and identify major risk factors in the U.S. population. Our study utilized NHANES data between 1999 and 2020 to investigate asthma prevalence and associated risk factors within the U.S. population. We analyzed a dataset of 64,222 participants, excluding those under 20 years old. We performed binary regression analysis to examine the relationship of demographic and health related covariates with the prevalence of asthma. The study found that asthma affected 8.7% of the U.S. population. Gender emerged as a significant factor, with 36.0% of asthma patients being male and 64.0% female (p < 0.001). Individuals aged 60 and older having the highest asthma prevalence at 34.0%. Non-Hispanic whites had the highest prevalence at 46.4%, followed by non-hispanic blacks at 26.0%. In contrast, Mexican Americans and other hispanic individuals had lower rates, at 9.6% and 9.0%, respectively. Females were 1.76 times more likely to have asthma than males (p < 0.001). Obese individuals had a 1.74 times higher likelihood of current asthma compared to underweight individuals (p < 0.001). Notably, both Non-Hispanic Whites and Non-Hispanic Blacks showed higher odds of current asthma compared to Mexican Americans (with adjusted odds ratios of 2.084 and 2.096, respectively, p < 0.001). The research findings indicate that asthma is prevalent in 8.7% of the U.S. population. Our study highlights that individuals who are female, have low income, are obese, and smoke have the highest likelihood of being affected by asthma. Therefore, public health policies should prioritize addressing these risk factors in their preventive strategies.

Effective communication of scientific knowledge plays a crucial role in the advancement of medical research and health care. Technological advancements have introduced large language models such as Chat Generative Pre-Trained Transformer (ChatGPT), powered by artificial intelligence (AI), which has already shown promise in revolutionizing medical writing. This study aimed to conduct a detailed evaluation of ChatGPT-3.5’s role in enhancing various aspects of medical writing. From May 10 to 12, 2023, the authors engaged in a series of interactions with ChatGPT-3.5 to evaluate its effectiveness in various tasks, particularly its application to medical writing, including vocabulary enhancement, text rewriting for plagiarism prevention, hypothesis generation, keyword generation, title generation, article summarization, simplification of medical jargon, transforming text from informal to scientific and data interpretation. The exploration of ChatGPT’s functionalities in medical writing revealed its potential in enhancing various aspects of the writing process, demonstrating its efficiency in improving vocabulary usage, suggesting alternative phrasing, and providing grammar enhancements. While the results indicate the effectiveness of ChatGPT (version 3.5), the presence of certain imperfections highlights the current indispensability of human intervention to refine and validate outputs, ensuring accuracy and relevance in medical settings. The integration of AI into medical writing shows significant potential for improving clarity, efficiency, and reliability. This evaluation highlights both the benefits and limitations of using ChatGPT-3.5, emphasizing its ability to enhance vocabulary, prevent plagiarism, generate hypotheses, suggest keywords, summarize articles, simplify medical jargon, and transform informal text into an academic format. However, AI tools should not replace human expertise. It is crucial for medical professionals to ensure thorough human review and validation to maintain the accuracy and relevance of the content in case they eventually use AI as a supplementary resource in medical writing. Accepting this mutually symbiotic partnership holds the promise of improving medical research and patient outcomes, and it sets the stage for the fusion of AI and human knowledge to produce a novel approach to medical assessment. Thus, while AI can streamline certain tasks, experienced medical writers and researchers must perform final reviews to uphold high standards in medical communications.

Self-medication is the use of drugs to treat self-diagnosed ailments without the use of a formal prescription. Self-medication is defined by the World Health Organization as the use of medications to address self-diagnosed diseases or symptoms. Over-the-counter (OTC) pharmaceuticals are medications that can be sold without a prescription directly to the client in accordance with the laws of each nation. During the COVID-19 pandemic, an increasing tendency in the use of OTC and self-medication was seen, with the situation in India particularly deteriorating due to lax regulatory restrictions. This has resulted in a slew of problems, ranging from a lack of drugs to severe responses due to overdosage and drug-drug combinations. There is an urgent need for more tangible regulatory control over self-medication and OTC medications to safeguard the uninformed populace from harm.

The monkeypox virus (MPXV), an Orthopoxvirus family member, is the zoonotic agent that causes mpox (formerly known as monkeypox). The ongoing mpox pandemic has caused cases across continents involving 110 countries. This study aimed to assess mpox knowledge and its determinants among healthcare personnel. This cross-sectional study was conducted from June 6 to June 25, 2022, among 17 Arab countries. The self-administered questionnaire consists of 53 questions assessing the knowledge about the monkeypox virus. In total, 5874 medical students and clinical doctors from 17 Arab countries participated in this study. Only 13.8% (n = 812) of respondents have ever received information about mpox during their studies in medicine. The mean knowledge score was 13.84, and the median score was 15 (range 1–34). More than half (51.3%, n = 3012) have heard about mpox before. A low proportion of the participants had a good level of knowledge on mpox. Only 11.7% of respondents had correctly identified the natural host and the incubation period of mpox. More than half (58.9%) were aware of the signs and symptoms of mpox. Few respondents (28%) believed that mpox and smallpox have similar signs and symptoms. Specialist doctors had higher knowledge of mpox (AOR = 2.96, 95% CI = 2.24–3.92, p < 0.001) than other cadres. Mpox awareness among Arabic medical students and practitioners is low; hence immediate action in creating awareness among arab healthcare professionals is the need of the hour. This is crucial in the mpox early detection and prevention of its spread.

Background: University students’ knowledge, attitude, and practice (KAP) toward COVID-19 are vital to prevent the spread of the virus, especially in the context of developing countries. Consequently, the present study aimed to determine the KAP levels of university students and associated anxiety during the earlier stage of the pandemic in Bangladesh.Methods: A cross-sectional, online study with 544 university students was conducted during April 17–May 1, 2020. The questionnaire incorporated several KAP-related test items aligned with the World Health Organization (WHO) guidelines. Anxiety was measured with the 2-item Generalized Anxiety Disorder scale (GAD-2). Multivariable logistic regression analysis was performed to determine the association between KAP levels and anxiety adjusting for sociodemographic variables. Subgroup analyses included rerunning models stratified by gender and quarantine status.Results: Approximately 50% of students showed high levels of knowledge about COVID-19 guidelines, 59% reported behavioral practices that aligned with COVID-19 guidelines, and 39% had negative attitudes toward COVID-19 guidelines. Attitudes differed by anxiety (χ² = 23.55, p < 0.001); specifically, negative attitudes were associated with higher anxiety (OR: 2.40, 95% CI = 1.66–3.46, p < 0.001). Associations were significant for male (OR = 2.36; 95% CI = 1.45–3.84, p < 0.001) and female (OR = 2.45; 95% CI = 1.3–4.34; p < 0.001) students. Stratified analyses found non-quarantined students with negative attitudes had three times the chance of experiencing anxiety (OR = 3.14, 95% CI: 1.98–4.98, p < 0.001). Non-quarantined students with low levels of knowledge had half the chance of developing anxiety (OR = 0.49, 95% CI: 0.31–0.78, p < 0.01).Conclusion: Based on these findings, it is recommended that university authorities continue to prioritize proactive and effective measures to develop higher levels of knowledge, more positive attitudes and better behavioral practices regarding COVID-19 for the mental health of their students.

Background: Cardiovascular disease (CVD) is a leading cause of global mortality. Early intervention and prevention of CVD depend on accurately predicting the risk of CVD. This study aimed to investigate the association between the TyG index and the risk of coronary heart disease (CHD), congestive heart failure (CHF), heart attack (HA), stroke, and hypertension (HTN) among patients without diabetes in the United States. Methods: In this retrospective, cross-sectional study, we used data from the National Health and Nutrition Examination Survey (NHANES) from 2001 to 2020. We conducted several regression analysis models and calculated the sensitivity and specificity of (TyG) index for predicting the onset of CHD, CHF, HA, stroke, and HTN. Results: A total of 10,937 individuals without diabetes participated in our study. Individuals with a TyG index greater than 8.96 displayed significant increasing in various parameters, including BMI, systolic/diastolic blood pressure, total cholesterol, LDL, and Apo-B levels (p < 0.001). Almost all regression models ensured that a higher TyGI value was associated with higher odds of having CHD, CHF, HA, stroke, and HTN, which patients with a TyGI value higher than 8.96 have odds ratios of 2.24–5.58 for CHD, 1.68–4.42 for stroke, 2.45–3.77 for HA and 1.75–3.93 for HTN comparing than patients with a TyGI value lower than 8.11 (p-value < 0.05).We evaluated the predictive value of the TyG index for each endpoint, obtaining the following area under the curve (AUC) values: 54.75% for CHF (95% CI: 0.542–0.614), 52.32% for stroke (95% CI: 0.529–0.584), 55.67% for HA (95% CI: 0.595–0.646), 55.59% for HTN (95% CI: 0.574–0.597), and 50.31% for CHD (95% CI: 0.592–0.646). Conclusion: The TyG index showed a strong correlation with cardiovascular risk factors in individuals without diabetes, however it was a poor predictor of almost studied cardiovascular diseases.