A systematic review of the effect of habitual breakfast for adolescents aged 11-19 years on academic performance

Background: Breakfast consumption plays an important role for growth, energy, BMI, and lifestyle. Studies show that it has positive influences on cognitive and academic outcomes. Despite this benefits of consuming breakfast on school grades, there has been no systematic review of literature focusing habitual breakfast consumption on scholastic achievement among adolescent students aged 11-19. Objective: The objective of this systematic review was to evaluate the existing evidence on habitual breakfast consumption and academic performance in adolescents aged 11-19 years. Methods: A systematic review of studies was conducted through three electronic databases which were searched for relevant articles published between 1990 and 2015 in the PubMed, PsycInfo, and ERIC databases. Results: The search identified 163 articles. Of these, 12 papers met the inclusion criteria. Eight studies showed a positive relationship between habitual breakfast consumption and school grades, while four papers had non-significant results even though two of those were of a superior design. According to NHLBI criteria in terms of research design, most of studies were fair while only one study was strong, and three studies were weak. Various breakfast definitions and classifications within three different timeframes were used in the studies. Three academic achievement measurements, including school grades, standardized achievement tests and self-report school grades were used. Conclusion: There is mixed evidence to draw firm conclusions of the effect of habitual breakfast on academic performance and this review address some methodological problems among studies which need to be taken into account. Good study design and specific definitions and classifications of breakfast within specific timeframes of 7days, and objective measurements for breakfast and academic performance are needed in further research

Catalytic behaviour of the Cu(i)/L/TEMPO system for aerobic oxidation of alcohols - a kinetic and predictive model

Here, we disclose a new copper(i)-Schiff base complex series for selective oxidation of primary alcohols to aldehydes under benign conditions. The catalytic protocol involves 2,2,6,6-tetramethylpiperidine-N-oxyl (TEMPO), N-methylimidazole (NMI), ambient air, acetonitrile, and room temperature. This system provides a straightforward and rapid pathway to a series of Schiff bases, particularly, the copper(i) complexes bearing the substituted (furan-2-yl)imine bases N-(4-fluorophenyl)-1-(furan-2-yl)methanimine (L2) and N-(2-fluoro-4-nitrophenyl)-1-(furan-2-yl)methanimine (L4) have shown excellent yields. Both benzylic and aliphatic alcohols were converted to aldehydes selectively with 99% yield (in 1-2 h) and 96% yield (in 16 h). The mechanistic studies via kinetic analysis of all components demonstrate that the ligand type plays a key role in reaction rate. The basicity of the ligand increases the electron density of the metal center, which leads to higher oxidation reactivity. The Hammett plot shows that the key step does not involve H-abstraction. Additionally, a generalized additive model (GAM, including random effect) showed that it was possible to correlate reaction composition with catalytic activity, ligand structure, and substrate behavior. This can be developed in the form of a predictive model bearing in mind numerous reactions to be performed or in order to produce a massive data-set of this type of oxidation reaction. The predictive model will act as a useful tool towards understanding the key steps in catalytic oxidation through dimensional optimization while reducing the screening of statistically poor active catalysis.Peer reviewe

Elemental Contamination in Indoor Floor Dust and Its Correlation with PAHs, Fungi, and Gram+/− Bacteria

In this study, we performed elemental analysis for floor dust samples collected in Jordanian microenvironments (dwellings and educational building). We performed intercorrelation and cluster analysis between the elemental, polyaromatic hydrocarbon (PAH), and microorganism concentrations. In general, the educational building workshops had the highest elemental contamination. The age of the dwelling and its occupancy played a role on the elemental contamination level: older and more occupied dwellingshad greater contamination. The elemental contamination at a dwelling entrance was observed to be higher than in the living room. We found exceptionally high concentrations for Fe and Mn in the educational workshop and additionally, Hg, Cr, and Pb concentrations exceeded the limits set by the Canadian Council of Ministers of the Environment. According to the cluster analysis, we found three major groups based on location and contamination. According to the enrichment factor (EF) assessment, Al, Co, Mn, Ti, and Ba had EF 40 (i.e., extremely enriched). In contrast, Ca and P were geogenically enriched. Furthermore, significant Spearman correlations indicated nine subgroups of elemental contamination combined with PAHs and microbes

Elemental Contamination in Indoor Floor Dust and Its Correlation with PAHs, Fungi, and Gram+/− Bacteria

In this study, we performed elemental analysis for floor dust samples collected in Jordanian microenvironments (dwellings and educational building). We performed intercorrelation and cluster analysis between the elemental, polyaromatic hydrocarbon (PAH), and microorganism concentrations. In general, the educational building workshops had the highest elemental contamination. The age of the dwelling and its occupancy played a role on the elemental contamination level: older and more occupied dwellingshad greater contamination. The elemental contamination at a dwelling entrance was observed to be higher than in the living room. We found exceptionally high concentrations for Fe and Mn in the educational workshop and additionally, Hg, Cr, and Pb concentrations exceeded the limits set by the Canadian Council of Ministers of the Environment. According to the cluster analysis, we found three major groups based on location and contamination. According to the enrichment factor (EF) assessment, Al, Co, Mn, Ti, and Ba had EF 40 (i.e., extremely enriched). In contrast, Ca and P were geogenically enriched. Furthermore, significant Spearman correlations indicated nine subgroups of elemental contamination combined with PAHs and microbes

Elemental Contamination in Indoor Floor Dust and Its Correlation with PAHs, Fungi, and Gram plus /-Bacteria

In this study, we performed elemental analysis for floor dust samples collected in Jordanian microenvironments (dwellings and educational building). We performed intercorrelation and cluster analysis between the elemental, polyaromatic hydrocarbon (PAH), and microorganism concentrations. In general, the educational building workshops had the highest elemental contamination. The age of the dwelling and its occupancy played a role on the elemental contamination level: older and more occupied dwellings had greater contamination. The elemental contamination at a dwelling entrance was observed to be higher than in the living room. We found exceptionally high concentrations for Fe and Mn in the educational workshop and additionally, Hg, Cr, and Pb concentrations exceeded the limits set by the Canadian Council of Ministers of the Environment. According to the cluster analysis, we found three major groups based on location and contamination. According to the enrichment factor (EF) assessment, Al, Co, Mn, Ti, and Ba had EF 40 (i.e., extremely enriched). In contrast, Ca and P were geogenically enriched. Furthermore, significant Spearman correlations indicated nine subgroups of elemental contamination combined with PAHs and microbes.Peer reviewe

Effects of ambient temperatures and extreme weather events on circulatory mortality in a high population density area : exploring mortality data from Malta

Temperature-related circulatory mortality has gained consistent public health importance worldwide due to changes in inter-annual average temperatures and the increased frequency of extreme events over time. This study investigates the association between temperature and circulatory deaths in one of the highest population densities in the world (Malta) with a Mediterranean climate. Daily deaths relating to circulatory mortality (32,847 deaths) were obtained from January 1992 to December 2017. A distributed lag non-linear model (DLNM) with a Poisson distribution was utilized to estimate effects of ambient temperatures and heatwaves or cold spells (2–4 consecutive days). Effects were also explored for the specific cause of death, different age groups, gender and time periods. The study observed a U-shaped cumulative exposure–response curve with a greater mortality risk due to cooler temperatures (8–15°C) after adjusting for harvesting effects (0–27 days). Colder temperatures (<8.9°C) were strongly related to both ischemic heart disease (IHD) (RR, 1.85, 95% CI, 1.24–2.77) and cerebrovascular disease (RR, 3.80,95% CI, 1.57–9.17). While heat effects were short-term (0–5 lag days), the cold effects were long-term (0–27 days) and consistent across different lag days. Cooler temperatures (8.99–12.6°C) were also related to IHD mortality in males (RR, 1.94, 95% CI, 1.05–3.59) and females (RR, 1.95, 95% CI, 1.2–3.59) and cerebrovascular mortality in females (RR, 8.32, 95% CI, 2.58–26.80). Elderly females (over 65 years) had a higher risk of death relating to IHD (RR, 1.33, 95% CI, 1.19–3.18) and cerebrovascular diseases (RR, 8.84, 95% CI, 2.64–29.61). Interestingly, colder temperatures (<8.9°C) were highly related to cerebrovascular deaths in the earliest time period (1992–2000) and IHD deaths in the most recent time period (2000–2017). While the effect of heatwaves was unclear across the time periods, there was some visible cold-spell effects for cerebrovascular mortality (RR, 1.03, 95% CI, 1.01–1.06). This study used a long time series of mortality data from a high population density area to explore the impact of ambient temperature and extreme events on circulatory deaths. The results of the study will help to improve preventive and adaptive strategies to mitigate climatic health impacts.peer-reviewe

COVID-19 Pandemic Development in Jordan-Short-Term and Long-Term Forecasting

In this study, we proposed three simple approaches to forecast COVID-19 reported cases in a Middle Eastern society (Jordan). The first approach was a short-term forecast (STF) model based on a linear forecast model using the previous days as a learning data-base for forecasting. The second approach was a long-term forecast (LTF) model based on a mathematical formula that best described the current pandemic situation in Jordan. Both approaches can be seen as complementary: the STF can cope with sudden daily changes in the pandemic whereas the LTF can be utilized to predict the upcoming waves’ occurrence and strength. As such, the third approach was a hybrid forecast (HF) model merging both the STF and the LTF models. The HF was shown to be an efficient forecast model with excellent accuracy. It is evident that the decision to enforce the curfew at an early stage followed by the planned lockdown has been effective in eliminating a serious wave in April 2020. Vaccination has been effective in combating COVID-19 by reducing infection rates. Based on the forecasting results, there is some possibility that Jordan may face a third wave of the pandemic during the Summer of 2021.In this study, we proposed three simple approaches to forecast COVID-19 reported cases in a Middle Eastern society (Jordan). The first approach was a short-term forecast (STF) model based on a linear forecast model using the previous days as a learning data-base for forecasting. The second approach was a long-term forecast (LTF) model based on a mathematical formula that best described the current pandemic situation in Jordan. Both approaches can be seen as complementary: the STF can cope with sudden daily changes in the pandemic whereas the LTF can be utilized to predict the upcoming waves' occurrence and strength. As such, the third approach was a hybrid forecast (HF) model merging both the STF and the LTF models. The HF was shown to be an efficient forecast model with excellent accuracy. It is evident that the decision to enforce the curfew at an early stage followed by the planned lockdown has been effective in eliminating a serious wave in April 2020. Vaccination has been effective in combating COVID-19 by reducing infection rates. Based on the forecasting results, there is some possibility that Jordan may face a third wave of the pandemic during the Summer of 2021.Peer reviewe

Short-Term and Long-Term COVID-19 Pandemic Forecasting Revisited with the Emergence of OMICRON Variant in Jordan

Three simple approaches to forecast the COVID-19 epidemic in Jordan were previously proposed by Hussein, et al.: a short-term forecast (STF) based on a linear forecast model with a learning database on the reported cases in the previous 5–40 days, a long-term forecast (LTF) based on a mathematical formula that describes the COVID-19 pandemic situation, and a hybrid forecast (HF), which merges the STF and the LTF models. With the emergence of the OMICRON variant, the LTF failed to forecast the pandemic due to vital reasons related to the infection rate and the speed of the OMICRON variant, which is faster than the previous variants. However, the STF remained suitable for the sudden changes in epi curves because these simple models learn for the previous data of reported cases. In this study, we revisited these models by introducing a simple modification for the LTF and the HF model in order to better forecast the COVID-19 pandemic by considering the OMICRON variant. As another approach, we also tested a time-delay neural network (TDNN) to model the dataset. Interestingly, the new modification was to reuse the same function previously used in the LTF model after changing some parameters related to shift and time-lag. Surprisingly, the mathematical function type was still valid, suggesting this is the best one to be used for such pandemic situations of the same virus family. The TDNN was data-driven, and it was robust and successful in capturing the sudden change in +qPCR cases before and after of emergence of the OMICRON variant

Short-Term and Long-Term COVID-19 Pandemic Forecasting Revisited with the Emergence of OMICRON Variant in Jordan

Three simple approaches to forecast the COVID-19 epidemic in Jordan were previously proposed by Hussein, et al.: a short-term forecast (STF) based on a linear forecast model with a learning database on the reported cases in the previous 5–40 days, a long-term forecast (LTF) based on a mathematical formula that describes the COVID-19 pandemic situation, and a hybrid forecast (HF), which merges the STF and the LTF models. With the emergence of the OMICRON variant, the LTF failed to forecast the pandemic due to vital reasons related to the infection rate and the speed of the OMICRON variant, which is faster than the previous variants. However, the STF remained suitable for the sudden changes in epi curves because these simple models learn for the previous data of reported cases. In this study, we revisited these models by introducing a simple modification for the LTF and the HF model in order to better forecast the COVID-19 pandemic by considering the OMICRON variant. As another approach, we also tested a time-delay neural network (TDNN) to model the dataset. Interestingly, the new modification was to reuse the same function previously used in the LTF model after changing some parameters related to shift and time-lag. Surprisingly, the mathematical function type was still valid, suggesting this is the best one to be used for such pandemic situations of the same virus family. The TDNN was data-driven, and it was robust and successful in capturing the sudden change in +qPCR cases before and after of emergence of the OMICRON variant