Perception and Impact of Food and Beverage Marketing on Children's Eating Behaviors and Associated Health Issues.

BACKGROUND AND OBJECTIVE: Children are more susceptible to food and beverage marketing than adults, but little is known about the specific effects of marketing through the media most used by children. This study aims to discover variables that can help inform childhood obesity prevention strategies. Our findings indicate an association between food advertisements and children's consumption, evidencing a need for the concerned authorities to create strict guidelines that consider the nutritional value of advertised foods. This study aims to study the attitudes and practices of children related to their preference for unhealthy meals due to food marketing and their association with childhood obesity. METHODOLOGY: A cross-sectional study of randomly selected guardians of children who were screened for obesity. A structured questionnaire was given to the children's parents. RESULTS: The study found that most of the participants' children prefer fast food (291, 78.0%), eat healthy meals (287, 76.9%), and eat fruits and vegetables every day (198, 53.1%). Furthermore, most participants (340, 91.2%) indicated that they were aware of unhealthy diets, and 105 (28.2%) said their children were overweight. Most participants (326, 87.4%) also indicated that watching television (TV) was associated with eating high-calorie foods. CONCLUSIONS: There is strong evidence that children exposed to food marketing develop attitudes about and choose unlimited healthy food and unhealthy foods, which negatively impacts their health. It is recommended that future research employs a wide range of methodologies to study contemporaneous marketing strategies.

Prehospital Fibrinolysis Therapy in Acute Myocardial Infarction: A Narrative Review.

Acute myocardial infarction is a fatal condition. Acute myocardial infarction requires appropriate timely reperfusion therapy to improve the outcomes. Fibrinolysis and percutaneous coronary intervention are the cornerstone strategies for managing such cases. In this review, our objective is to summarize the available evidence concerning the administration of prehospital fibrinolysis and its impact on patient outcomes in patients with acute myocardial infarction. We conducted a comprehensive literature search across PubMed, Cochrane Library, Scopus, and Web of Science databases. Our search strategy included the following terms: "Prehospital," "EMS," "Emergency Medical Services," "ambulance," "Fibrinolytic Therapy," "alteplase," "streptokinase," "reteplase," "tenecteplase," "Acute Myocardial Infarction," and "patient outcomes." We found prehospital administration of fibrinolysis may improve the outcomes and decrease the mortality rate. We found that some recommendations were to use prehospital fibrinolysis only if the percutaneous coronary intervention was not accessible within two hours. Additionally, we discussed recommendations to use newer prehospital fibrinolysis as they have better efficacy and safety outcomes. In conclusion, prehospital fibrinolysis decreases the total ischemic time and improves outcomes in acute myocardial infarction patients when timely percutaneous coronary intervention is not available. The guidelines strongly recommend it when the anticipated time for percutaneous coronary intervention exceeds two hours. Ongoing research optimizes patient selection, treatment tools, and prehospital systems of care.

Sleep Hygiene Practices and Its Impact on Mental Health and Functional Performance Among Adults in Tabuk City: A Cross-Sectional Study.

Background Poor or imperfect sleep hygiene practices include all factors that promote arousal or disrupt the normal balance of the sleep-wake cycle. It is necessary to clarify the relationship between sleep hygiene behaviors and a person's mental health. This may allow a better understanding of this problem and might help design effective awareness programs about good sleep hygiene practices for reducing the serious outcomes of this problem. Therefore, the current study was conducted to evaluate sleep hygiene practices and assess the impact of sleep hygiene on sleep quality and the mental health of the adult population of Tabuk city, Saudi Arabia. Methodology This cross-sectional, survey-based study was conducted in Tabuk city, Saudi Arabia in 2022. All adult residents of Tabuk city, Saudi Arabia were invited to participate. Participants with incomplete data were excluded from the study. A self-administered questionnaire was developed by the researchers to assess sleep hygiene practices and their impact on the sleep quality and mental health of the study participants. Results The study included 384 adults. There was a significant association between the frequency of sleep problems and poor sleep hygiene practices (p < 0.001). The percentage of subjects who had problems sleeping during the past three months was significantly higher among those having poor sleep hygiene practices (76.5%) than their counterparts (56.1%). The rates of excessive or severe daytime sleepiness were significantly higher among individuals with poor hygiene practices (22.5% versus 11.7% and 5.2% versus 1.2%, p = 0.001). Participants with depression were found to be significantly higher among the poor hygiene group (75.8%) in comparison to those having good hygiene practices (59.6%) (p = 0.001). Conclusions The findings of the present study indicate significant associations between poor sleep hygiene practices and sleep problems, daytime sleepiness, and depression among adult residents of Tabuk city, Saudi Arabia.

Prevalence of Nocturnal Enuresis Among Children and Its Association With the Mental Health of Mothers in Northern Saudi Arabia.

Background Nocturnal enuresis (NE) is troubling for children and their families. This study aims to investigate the prevalence of NE, its associated health problems, and the outcome of the provided management among children aged 6-18 years and to assess the impact of NE on the mental health of mothers in Northern Saudi Arabia. Methodology A retrospective cross-sectional study was conducted in Arar, Northern Saudi Arabia, among children aged 6-18 years old. Data were collected using a structured questionnaire including a Perceived Stress Scale (PSS). Means ± standard deviations (SDs) were used to represent quantitative data, and frequencies and percentages were used to represent qualitative data. Ordinal logistic regression was used to assess the association of NE with perceived stress. Results A total of 420 participants were included in this study. Nocturnal enuresis was reported in 24% of the respondents' children. Around 51% of the mothers know about the causes of NE. Nocturnal enuresis caused embarrassment and social shame to 71% of the mothers. Two-thirds (66%) of the mothers wake up the child at night for urination. Three-quarters (76%) of the participants reported improvement on decreasing fluid intake before sleeping. Of the mothers, 19% perceived low stress, 78% perceived medium stress, and 3% perceived high stress. NE was associated with a higher risk of stress (adjusted odds ratio (OR): 2.14; 95% confidence interval (CI): 1.05-4.37). Conclusion About a quarter of the children suffer from NE, of which a large proportion of mothers face embarrassment and shame. There was a significant association between NE and a higher level of stress. Mothers of children with NE should be provided with counseling and social support to ensure good mental health.

Predicting Risk of Stroke From Lab Tests Using Machine Learning Algorithms: Development and Evaluation of Prediction Models.

BACKGROUND: Stroke, a cerebrovascular disease, is one of the major causes of death. It causes significant health and financial burdens for both patients and health care systems. One of the important risk factors for stroke is health-related behavior, which is becoming an increasingly important focus of prevention. Many machine learning models have been built to predict the risk of stroke or to automatically diagnose stroke, using predictors such as lifestyle factors or radiological imaging. However, there have been no models built using data from lab tests. OBJECTIVE: The aim of this study was to apply computational methods using machine learning techniques to predict stroke from lab test data. METHODS: We used the National Health and Nutrition Examination Survey data sets with three different data selection methods (ie, without data resampling, with data imputation, and with data resampling) to develop predictive models. We used four machine learning classifiers and six performance measures to evaluate the performance of the models. RESULTS: We found that accurate and sensitive machine learning models can be created to predict stroke from lab test data. Our results show that the data resampling approach performed the best compared to the other two data selection techniques. Prediction with the random forest algorithm, which was the best algorithm tested, achieved an accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and area under the curve of 0.96, 0.97, 0.96, 0.75, 0.99, and 0.97, respectively, when all of the attributes were used. CONCLUSIONS: The predictive model, built using data from lab tests, was easy to use and had high accuracy. In future studies, we aim to use data that reflect different types of stroke and to explore the data to build a prediction model for each type.

Does a Mobile Phone Depression-Screening App Motivate Mobile Phone Users With High Depressive Symptoms to Seek a Health Care Professional's Help?

BACKGROUND: The objective of disease screening is to encourage high-risk subjects to seek health care diagnosis and treatment. Mobile phone apps can effectively screen mental health conditions, including depression. However, it is not known how effective such screening methods are in motivating users to discuss the obtained results of such apps with health care professionals. Does a mobile phone depression-screening app motivate users with high depressive symptoms to seek health care professional advice? This study aimed to address this question. METHOD: This was a single-cohort, prospective, observational study of a free mobile phone depression app developed in English and released on Apple's App Store. Apple App Store users (aged 18 or above) in 5 countries, that is, Australia, Canada, New Zealand (NZ), the United Kingdom (UK), and the United States (US), were recruited directly via the app's download page. The participants then completed the Patient Health Questionnaire (PHQ-9), and their depression screening score was displayed to them. If their score was 11 or above and they had never been diagnosed with depression before, they were advised to take their results to their health care professional. They were to follow up after 1 month. RESULTS: A group of 2538 participants from the 5 countries completed PHQ-9 depression screening with the app. Of them, 322 participants were found to have high depressive symptoms and had never been diagnosed with depression, and received advice to discuss their results with health care professionals. About 74% of those completed the follow-up; approximately 38% of these self-reported consulting their health care professionals about their depression score. Only positive attitude toward depression as a real disease was associated with increased follow-up response rate (odds ratio (OR) 3.2, CI 1.38-8.29). CONCLUSIONS: A mobile phone depression-screening app motivated some users to seek a depression diagnosis. However, further study should investigate how other app users use the screening results provided by such apps.