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Asthma is a highly prevalent inflammatory condition, significantly affecting nearly six million U.S. children and impacting various facets of their developmental trajectories including neurodevelopment. Evidence supports a link between pediatric environmental exposures in two key areas: asthma and executive function (E.F.). E.F.s are a collective of higher-order cognitive processes facilitating goal-oriented behaviors. Studies also identify asthma-associated E.F. impairments in children. However, limited research has evaluated the inter-relationships among environmental exposures, asthma, and E.F. in children. This review explored relevant research to identify and connect the potential mechanisms and pathways underlying these dynamic associations. The review suggests that the role of the pediatric exposome may function through (1) several underlying biological pathways (i.e., the lung-brain axis, neuroendocrine system, and hypoxia), which could drive asthma and maladaptive E.F. in children and (2) the relationships between the exposome, asthma, and E.F. is a bidirectional linkage. The review reveals essential synergistic links between asthma and E.F. deficits, highlighting the potential role of the pediatric exposome.

This study is a qualitative research aimed to see the response of "pesantren" teachers in North Sumatra, Indonesia toward Islamist ideology. Specifically, this study attempted to find out the perception of "pesantren" teachers toward the ideas of Islamic country, Jihad, non-Muslim leaders and women as leaders. The teachers interviewed are those who teach Qur'an, "Hadith," and "Fiqh" classes. The data were analyzed by using the data analysis model proposed by Miles and Huberman. The results indicate that the majority of "pesantren" teachers consider that the establishment of an Islamic country and the implementation of Islamic law are important, but they oppose women and non-Muslims as leaders of Muslim communities or a country. According to Bassam Tibi's theory of Islamism, the response of these "pesantren" teachers can be categorized as moderate Islamism, not radical because they support the establishment of Islamic state and Islamic law, yet object to violence to achieve the goals.

BackgroundIn recent years, there has been growing concern about prejudice in crowdfunding; however, empirical research remains limited, particularly in the context of medical crowdfunding. This study addresses the pressing issue of racial disparities in medical crowdfunding, with a specific focus on cancer crowdfunding on the GoFundMe platform. ObjectiveThis study aims to investigate racial disparities in cancer crowdfunding using average donation amount, number of donations, and success of the fundraising campaign as outcomes. MethodsDrawing from a substantial data set of 104,809 campaigns in the United States, we used DeepFace facial recognition technology to determine racial identities and used regression models to examine racial factors in crowdfunding performance. We also examined the moderating effect of the proportion of White residents on crowdfunding bias and used 2-tailed t tests to measure the influence of racial anonymity on crowdfunding success. Owing to the large sample size, we set the cutoff for significance at P

Abstract Background Diabetes mellitus is one of the most common diseases worldwide with significant morbidity and mortality. HbA1c remains one of the most important methods for diagnosis and monitoring of the disease. Since HbA1c is a reflection of the glucose attached to red blood cells, factors affecting hemoglobin and red blood cells’ half-life can influence HbA1c measurements. Objective This study aims to evaluate the effect of different types of anemia including iron deficiency anemia, sickle cell anemia, β -thalassemia trait, and megaloblastic anemia on HbA1c levels in a tertiary hospital over the past 6 years (2016–2022). Method This is a retrospective chart review study of 324 patients including those with one of the four types of anemia mentioned above and a control group. The control group were healthy adults with normal HbA1c and hemoglobin, who were not known to have diabetes or anemia. Patients with diabetes or prediabetes based on self-reporting or elevated fasting, random blood sugar, or 2 hours post-prandial blood glucose were excluded. Results The mean HbA1c levels were significantly higher in sickle cell anemia at 5.83% (95% CI = 5.39–6.28) and in iron deficiency anemia at 5.75% (95% CI = 5.68–5.82) when compared to the control group at 5.32% (95% CI = 5.22–5.41). However, the mean HbA1c levels in megaloblastic anemia were 5.38% (95% CI = 5.26–5.5) and 5.45% (95% CI = 5.21–5.69) in beta thalassemia trait, which were not significantly different when compared to the control group. HbA1c significantly decreased from 5.75 to 5.44% after treatment in the iron-deficient group with a p-value of

Objective This study examines the associations of eating-related motivation, perceived norms, and their interaction with eating behaviors in emerging adults. Design Data are from the NEXT Generation Health Study, a nationally representative sample of US emerging adults. Binominal logistic regression analyses estimated associations of eating behaviors with self-determined motivation, non-self-determined motivation, and perceived social norms. Multiplicative interaction terms between each motivation construct and perceived social norms were tested in the models. Results Self-determined motivation was positively associated with intake frequency of whole grains, low-fat dairy, and fruit and vegetables. Soda intake frequency was inversely associated with greater non-self-determined motivation, but not self-determined motivation or perceived social norms. Perceived social norms were positively associated with the intake of whole grains, low-fat dairy, and fruit and vegetables. Perceived social norms did not moderate the association of motivation constructs with eating behaviors. Conclusion Self-determined motivation and perceived social norms may be considered in intervention targeting healthful eating behaviors in emerging adults.

This study aimed to assess the efficacy of the developmental assessment of young children second edition (DAYC-2) Scale in detecting Developmental Delay among Jordanian children aged birth to 71 months. Firstly, the scale was translated and reviewed for language and cultural appropriateness. Secondly, the Arabic Jordanian version of the scale was administrated to children diagnosed as developmental delay aged from birth to 48 months in the neurodevelopmental pediatric clinic in Jordan university hospital, and on children aged 48 to 71 months who were diagnosed as developmental delay in special education centers in Capital Amman. The scale was administrated also to normal development children aged 0 to 71 months who visited the Institute for family health--Noor al Hussein foundation and attended preschools in Capital Amman. Total of 310 children aged (0-71 months) were enrolled. Construct validity and discriminative validity were verified. Reliability was established through computing Kuder-Richardson Formula 20 (KR-20), test-retest, split half test methods.t-test showed that the scale discriminates between normally developed and developmentally delayed children. One-way ANOVA showed that age has significant effect on the performance of children favoring older age groups using Scheffé multiple comparisons test. Item efficacy was determined by calculating point-biserial correlation coefficients for all items in each domain. The results showed that the scale had good psychometric properties and was capable of detecting developmental delay in children aged from birth to 71 months in Jordan.

Abstract Background Rheumatoid arthritis (RA) is a systemic autoimmune disease that chronically affects patients with episodes of inflammation. New inflammatory hematological markers were investigated for follow‐up, such as the neutrophil–monocyte ratio (NMR), lymphocyte monocyte ratio (LMR), and neutrophil–lymphocyte ratio (NLR). This study was conducted to determine the most useful marker based on studies of association with RA disease activity and correlation with the classical markers C‐reactive protein (CRP), erythrocyte sedimentation rate (ESR), and rheumatoid factor (RF). Methods This case‐control study included 62 chronic RA patients who had previously been diagnosed and experienced episodes of symptoms while attending a variety of public and private rheumatology clinics in Ibb City, Republic of Yemen, for the period of September 1 to November 30, 2021. Twenty healthy volunteers were included in this study. Complete blood count, CRP, ESR, and RF levels were measured in all participants. Results The total leukocyte count, neutrophil count, platelet count, NMR, LMR, and NLR were positively correlated with CRP and ESR, but the monocyte count was reversed. The area under the curve (AUC = 0.861, 95% confidence interval [CI] = 0.769–0.948) for the NMR cutoff value of 4.7 was equal to that of CRP and close to that of ESR. This NMR cutoff value had 87% sensitivity and 80% specificity. LMR and NLR cutoff values of 4.35 and 1.35, respectively, resulted in AUCs of (AUC = 0.807, 95% CI, 0.708–0.905) and (AUC = 0.699, 95% CI, 0.571–0.819); their sensitivity and specificity were 62.3%, 90%, 57.4%, and 80%, respectively. Conclusions As a convenient and low‐cost inflammatory marker of RA activity, NMR outperformed LMR and NLR.

BackgroundTwitter has become a dominant source of public health data and a widely used method to investigate and understand public health–related issues internationally. By leveraging big data methodologies to mine Twitter for health-related data at the individual and community levels, scientists can use the data as a rapid and less expensive source for both epidemiological surveillance and studies on human behavior. However, limited reviews have focused on novel applications of language analyses that examine human health and behavior and the surveillance of several emerging diseases, chronic conditions, and risky behaviors. ObjectiveThe primary focus of this scoping review was to provide a comprehensive overview of relevant studies that have used Twitter as a data source in public health research to analyze users’ tweets to identify and understand physical and mental health conditions and remotely monitor the leading causes of mortality related to emerging disease epidemics, chronic diseases, and risk behaviors. MethodsA literature search strategy following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) extended guidelines for scoping reviews was used to search specific keywords on Twitter and public health on 5 databases: Web of Science, PubMed, CINAHL, PsycINFO, and Google Scholar. We reviewed the literature comprising peer-reviewed empirical research articles that included original research published in English-language journals between 2008 and 2021. Key information on Twitter data being leveraged for analyzing user language to study physical and mental health and public health surveillance was extracted. ResultsA total of 38 articles that focused primarily on Twitter as a data source met the inclusion criteria for review. In total, two themes emerged from the literature: (1) language analysis to identify health threats and physical and mental health understandings about people and societies and (2) public health surveillance related to leading causes of mortality, primarily representing 3 categories (ie, respiratory infections, cardiovascular disease, and COVID-19). The findings suggest that Twitter language data can be mined to detect mental health conditions, disease surveillance, and death rates; identify heart-related content; show how health-related information is shared and discussed; and provide access to users’ opinions and feelings. ConclusionsTwitter analysis shows promise in the field of public health communication and surveillance. It may be essential to use Twitter to supplement more conventional public health surveillance approaches. Twitter can potentially fortify researchers’ ability to collect data in a timely way and improve the early identification of potential health threats. Twitter can also help identify subtle signals in language for understanding physical and mental health conditions.

Flood is one of the most destructive natural disasters that causes loss of lives, properties, and significant resources, repeatedly occurring throughout Aceh, particularly in North Aceh. Given the more frequent floods and their damaging effects, it appears urgent and crucial to enhance the identification and mapping of flood susceptibility. One method that has been developed is the flood susceptibility mapping method. However, this method cannot address the challenges of flood susceptibility zone delineation due to the uncertainty of evaluation processes and the complex nonlinear relationships between indicators and risk levels, given that flood mapping is a multi-criteria spatial decision problem requiring hydrologic and geographic information. The objectives of this research are to assess flood susceptibility using the AHP-MCDM and to integrate using GIS to produce flood susceptibility map in Kr. Keureuto Watershed. Seven criteria from hydrologic and geographic information of the watershed were collected and analyzed using ArcGIS, and the weight of criteria using AHP from 25 expert responders. The results shows that there are four distinct levels of flood susceptibility: very high, high, medium, and low vulnerable. Significantly, the downstream Kr. Keureuto watershed emerges as highly susceptible to flooding, compared to the upstream zone.

Background. Methicillin-resistant Staphylococcus aureus (MRSA) is a prevalent pathogen associated with significant morbidity and mortality. In Lebanon, MRSA rates have recently started to rise. We aimed to determine risk factors for acquiring MRSA and Methicillin-sensitive Staphylococcus aureus (MSSA) infections and identify independent risk factors for in-hospital mortality among patients with S. aureus infection. Methods. We used a case-case-control study design that included patients with infections and compared them to uninfected controls. Two multivariable regression models were constructed to determine variables associated with acquiring MRSA and MSSA infections. We explored independent predictors of mortality in the overall population compared with the MRSA subgroup. Results. 356 patients with S. aureus infections were identified and compared to 208 uninfected controls. A recent history of surgery and underlying diabetes were independent risk factors for acquiring both infections. Having a urinary catheter for more than 6 days and steroid therapy were unique risk factors for MRSA infection (aOR 28.1, 95% CI 3.5-223.6 and 3.7, 95% CI 1.6-8.7, respectively). Risk factors exclusively associated with MRSA infection included ICU admission, acute renal failure, and malignancy. Conclusions. Risk factors associated with MRSA infection are distinct from those associated with MSSA infection. This can be used to risk stratify patients and will aid in choosing empirical antibiotic therapy.