The analysis of acute malnutrition in 2018 for the Integrated Phase Classification of Food Security in Yemen shows that high malnutrition rates are present in Abyan governorate (23%) and Lahj governorate (21%). This analysis was community based addressed all children and mostly due to problems related to food intake. The role of diseases was not yet addressed in Yemen. The aim of this study is to assess acute and chronic malnutrition among hospitalized children at 12–59 months of age in Lahj and Abyan governorates in Yemen.A cross-sectional, multi-center study is designed. The assessment of the nutritional status was measured by standardized anthropometry of 951 sick children at 12–59 months of age.The prevalence of Global acute malnutrition (GAM) among the sick children seeking care in health facilities in Lahj and Abyan is 21%. More specifically; the prevalence of moderate acute malnutrition (MAM) is 15.1% while the prevalence of severe acute malnutrition (SAM) is 6.2%. The prevalence of acute malnutrition (wasting) among the studied sick children in lahj is 23.4% while in Abyan is 19.3%. The prevalence of MAM in Lahj is 17.7% and the prevalence of SAM is 5.7%. The prevalence of acute malnutrition (wasting) in Abyan is 12.6% while the prevalence of SAM in Abyan is 6.7%. The prevalence of acute malnutrition among male children (25.2%) is significantly higher than among female children (17.5%). The prevalence of the chronic malnutrition (Stunting) in the studied sick children is 41.3%; the prevalence of stunting in Lahj is 41% while in Abyan is 41.7%.High acute and chronic malnutrition rates were identified among sick children seeking care in health facilities in lahj and Abyan, and higher than the SPHERE indicators of malnutrition. Boys are more exposed than girls to acute and chronic malnutrition. Malnutrition in children is of high concern in developing countries like Yemen. However, malnutrition is multifactorial. Malnutrition in low-income countries is often, but not solely, be attributable to limited access to food and/or medical care, it is often triggered by disease . In one Most of the local and international reports described the situation in Yemen is the worst humanitarian crises in the world. Malnutrition among Yemeni children is one of the painful crises. In 2015, UNICEF's report concludes that a striking ten of Yemen's 22 governorates are on the edge of famine, as defined by the five-point Integrated Food Security Phase Classification (IPC) scale . In 2017The rate of child malnutrition in Yemen is one of the highest in the world and the nutrition situation continues to deteriorate. World food program (WFP) reported that about one third of families have gaps in their diets, and hardly ever consume foods like pulses, vegetables, fruit, dairy products or meat. Malnutrition rates among children in Yemen remain among the highest in the world, with 2.3 million children under five years requiring treatment for acute malnutrition .Another study among children under five years of age identified that the high malnutrition level  , and < 125 mm] were considered a moderately malnourished. While the green color [MUAC ≥ 125 mm] were categorized as normal according to WHO classification.Wasting: Weight‐for‐height (wasting) provides the clearest picture of acute malnutrition.Moderate Acute Malnutrition (MAM) is identified by moderate wasting WFH ≤ -2 z score and ≥ -3 z‐score for children 0‐59 months . Table Severe Acute Malnutrition (SAM) is identified by severe wasting < -3 z‐score for children 12‐59 months  or the presence of bilateral pitting edema.Global Acute Malnutrition (GAM) is the presence of both MAM and SAM in a population. A GAM value of more than 10 percent indicates an emergency. If GAM is exceeding 15% it is considered critical while at 11–14% is severe GAM and if GAM at level of > 5% and less than 10% is considered poor indicator.Chronic malnutrition (Stunting) (Height-for-age Z score (HAZ)) The HAZ measure indicates if a child of a given age is chronically malnourished (stunted). The height-for-age index of a child from the studied population is expressed in Z-score (HAZ).proportion of wasting  among the hospitalized children in Lahj and Abyan = Number of hospitalized children have MAM/ all hospitalized children under study. = Number of hospitalized children have SAM/ all hospitalized children under study.Proportion of stunting  among the hospitalized children in Lahj and Abyan = Number of hospitalized children have stunting/ all hospitalized children under study.Data were transforming from the KOBO application data set to excel file, then to the statistical package for social sciences (SPSS) version 24. Descriptive statistics uses are mean, standard deviations, to describe the quantitative variables while frequency and percentages to describe the qualitative variables. Chi square test is used as a tool of inferential statistics to assess the significance of association between malnutrition and the independent variables of gender, residency, family income, availability of drinking water in the house. A cut of point of 0.05 was used for significant level. Fischer exact test is used alternatively to chi square test if the expected dells are less than 5.For purpose of bivariate and logistic regression; the dependent variables were ree-classified into two categories: the acute malnutrition is reclassified into acute malnutrition and normal, where acute malnutrition included MAM and SAM children. The chronic malnutrition (Stunting) variable is a dependent variable is re-classified int o two categories: Chronic malnutrition (Stunting) and normal, where chronic malnutrition included moderate stunting and sever stunting. the socioeconomic variables of more than two categories are reclassified. The independent variables are re-classified in to two categories: For example, residency is re-classified to be  and 95% confidence interval (95%CI) are used to assess the strength of the association.The total number of sick children seeking care in the selected 10 health facilities in Lahj and Abyan during the study period  are 951 children at the age of 12–59 months. The mean age is 29.5 years old (± 14 years). The range from 12 to 59 months. A total of 491 female children (51.6%) while male children are 460 children (48.4%). There are 474 children form Lahj governorate (49.8%) and 477 children from Abyan governorate (50.2%). Most of the children's mothers are either illiterate (37.4%) or has primary /essential education (36/1%) while most of the fathers had primary or essential education (39.2%). About 64% of children's fathers are employed, but about 35% is unemployed; most of the mothers reported that their family monthly income is not enough (88.1%). About 75% of the children are of resident families and 23.7% of internal displaced people (IDPs). Most of the households of the children (62%) has irregular drinking water supply  Table The prevalence of Global acute malnutrition (GAM) among the sick children seeking care in health facilities in Lahj and Abyan is 21% 203/951) Fig. /951 Fig.P-value 0.113).The prevalence of global acute malnutrition (wasting) among the studied sick children in lahj is 23.4% while in Abyan is 19.3%. The prevalence of MAM in Lahj is 17.7% and the prevalence of SAM is 5.7%. The prevalence of MAM among the studied sick children in Abyan is 12.6% while the prevalence of SAM in Abyan is 6.7% but these differences are not significant . Table The prevalence of the chronic malnutrition (Stunting) in the studied sick children is 41.3%; the prevalence of stunting in Lahj is 41% while in Abyan is 41.7%. The prevalence of moderate stunting in all the studied sick children is 24.3% and the prevalence of severe stunting is 17.2%. Prevalence of moderate stunting is higher in Abyan 26.4% while the prevalence of severe stunting is higher in Lahj (19.2%) but these differences are not significant . Table The prevalence of acute malnutrition among male children (25.2%) is significantly higher than prevalence of acute malnutrition among female children (17.5%). Moreover, Prevalence of MAM and SAM among males (17.6% & 7.6% respectively) are significantly higher than females (12.8% & 4.9% respectively) . The prevalence of stunting in males (45.3%) is significantly higher than females (37.7%). Moreover, Prevalence of moderate stunting and severe stunting among males (25.5% & 19.8% respectively) are significantly higher than females (22.6% & 15.1% respectively) . In Table p = 0.003) when other variables are held constant. Also, the odds of a child admitted into hospital having acute malnutrition is 0.45 lower than the child from the PHC facility child , p = 0.001) when other variables are held constant. Regarding chronic malnutrition (Stunting); gender, type of health facility  and residency are significantly associated with chronic malnutrition (stunting). The odds of a male child have chronic malnutrition is 40% higher than that of the female child  when other variables are held constant, P-value 0.010. The odds of a child admitted into hospital having chronic malnutrition is 80% more than the child from the PHC facility , P-value 0.000 when other variables are held constant. The odds of child of non-resident family having acute malnutrition are 39% more than the child from resident family  when other variables are held constant. Table In logistic regression, gender  and type of health facility  are significantly associated with acute malnutrition (wasting). The odds of a male child have acute malnutrition is 60% higher than that of the female child , 97, p = 0This health facility-based study was conducted in two southern governorates in Yemen (Lahj and Abyan) where facing armed conflicts since 2015 affecting negatively upon the provision of the health services and exacerbate the existing malnutrition problem among children under five years. Out of the scope of the routine measurements of malnutrition in the community; this study focused on sick children seeking care in the health facilities for other health problems rather than malnutrition.In this study; results revealed high prevalence of acute and chronic malnutrition (21.3% & 41.3% respectively) among studied sick children at 12–59 months of age in Lahj and Abyan governorates. This study focused on sick children observed in the outpatient clinics in both primary health care centers and hospitals. The reported rates of malnutrition in this study are higher than what, were reported in other developed or developing countries. Studies in developed countries reported significant proportion of malnutrition among hospitalized patients, Groleau V 2014) in their study in Canada reported that the prevalence of acute and chronic malnutrition among hospitalized children was 13.3% . In anot14 in theSevere acute malnutrition (SAM) has a significant contribution to child death if untreated, and may be exceeded the minimum Sphere standard (< 10%) especially in developing countries like Yemen and Ethiopia , 26.In this study; the prevalence of SAM and MAM in sick children were 6.2% and 12.8% respectively, these figures are higher than the same indicators from community-based survey in Yemen   and EthiMale children are more exposed to both acute and chronic malnutrition than females , 30. In Concurrent wasting and stunting are an important problem among children under five years and it is considered risk factor to child mortality . in thisPoverty is a critical determinant of malnutrition –36. YemeThe implication of this study is to give more attention for screening malnutrition among sick children as a routine examination. Studies reported that this routine screening is ignored in the routine medical care of sick children in many developing countries. In one study in Burundi (2019) it was found that only 3% of health workers screened children (6–59 months) for malnutrition .There are certain limitations of this study. The study was limited to a selected health facilities in two governorates in southern Yemen due to logistics and accessibility issues. The study limited to patients attending health facilities in outpatient clinics, so critically ill-children were not included in the study.High acute and chronic malnutrition rates were identified among sick children seeking care in health facilities in lahj and Abyan governorates in Yemen. These higher malnutrion rates exceeded the SPHERE indicators of malnutrition. Boys are more exposed than girls to acute and chronic malnutrition. Gender  and type of health facility  are predictors to acute malnutrition (wasting) while gender, type of health facility  and residency (Non-resident) are predictors to chronic malnutrition (stunting). Authors advised that early detection of malnutrition in children at outpatient clinics should not be neglected. To avoid this ignorance to treat appropriately and to reduce mortality, authors recommended every sick child observed in outpatient or in-patents pediatric departments should be screening for malnutrition.


The historical signal in nucleotide sequences becomes eroded over time by substitutions occurring repeatedly at the same sites. This phenomenon, known as substitution saturation, is recognized as one of the primary obstacles to deep-time phylogenetic inference using genome-scale data sets. We present a new test of substitution saturation and demonstrate its performance in simulated and empirical data. For some of the 36 empirical phylogenomic data sets that we examined, we detect substitution saturation in around 50% of loci. We found that saturation tends to be flagged as problematic in loci with highly discordant phylogenetic signals across sites. Within each data set, the loci with smaller numbers of informative sites are more likely to be flagged as containing problematic levels of saturation. The entropy saturation test proposed here is sensitive to high evolutionary rates relative to the evolutionary timeframe, while also being sensitive to several factors known to mislead phylogenetic inference, including short internal branches relative to external branches, short nucleotide sequences, and tree imbalance. Our study demonstrates that excluding loci with substitution saturation can be an effective means of mitigating the negative impact of multiple substitutions on phylogenetic inferences.  One of the key steps in phylogenomics is to identify a suitable set of loci for reconstructing the evolutionary history of a group of organisms. The inference of phylogenetic trees from nucleotide sequences can be misled by a number of factors. For example, the sequences might contain too little information if they have evolved too slowly . On the One popular approach for exploring phylogenetic informativeness is to identify the loci that have experienced substitution saturation . A widelIn an extensive simulation study, Data sets in phylogenomics are typically composed of many alignments of non-recombining regions of the genome (loci). The phylogenetic information signal in each locus is often summarized using its “gene tree.” Tests of substitution saturation can be used to select loci for phylogenetic analysis e.g., . This foIn this study, we describe the performance of a common test of saturation, and evaluate the impact of saturation in a broad range of empirical phylogenomic data sets. We also describe a novel approach to examining substitution saturation that focuses exclusively on phylogenetically informative sites. This approach greatly ameliorates the negative influence of slowly evolving sites on the measurement of overall base composition, which is central to the performance of the entropy-based tests of saturation. Using two simulation studies, we first aim to identify the characteristics of sequence alignments to which the tests are sensitive, including a high rate of substitution. In our second simulation study, we explore a broad continuum of evolutionary scenarios to examine the power of the tests to identify loci with amounts of substitution saturation that are likely to mislead estimates of phylogeny and branch lengths. We then evaluate the degree of substitution saturation in 36 phylogenomic data sets, and investigate the link between saturated loci and amount of discordance in phylogenetic signal across sites. Our results suggest that saturation can affect large portions of phylogenomic data sets, and that testing for saturation is an effective approach to identify loci with poor historical signal in phylogenomic studies.The degree of substitution saturation in a nucleotide sequence alignment can be described using a measure of entropy . The entTherefore, the expected entropy of a sequence alignment under full saturation can be calculated using the number of taxa  and their flanking regions. Therefore, we assessed the performance of the test based exclusively on phylogenetically informative sites . This avoids the worst effects of constant sites on the test in data matrices with small numbers of taxa, small numbers of sites, or both. The focus of the test on phylogenetically informative sites will have a diminishing effect on the test as the size of the data matrix increases, and is expected to have a null effect under infinite sites.The guidelines require revision so that the test can be implemented more effectively for empirical data. Very small sequence alignments can pose challenges for the reliability of the test, due to the disproportionate effect of small numbers of outlier sites. Similarly, alignments with large numbers of slow-evolving sites and an overrepresentation of a particular nucleotide type will be highly sensitive to single outlier sites. Therefore, a test of saturation using the entropy We used a simulation study to examine the circumstances under which substitution saturation is a significant problem that can be addressed in empirical data, relative to other causes of misleading inferences. We simulated the evolution of nucleotide sequences along trees with variable numbers of taxa  to generate data sets with three different sequence lengths . Starting with trees that were fully symmetric and in which all branches had equal length, we varied several conditions that can affect the performance of phylogenetic methods, including: the number of substitutions along each branch of the tree ; tree imbalance ; ratio of the sum of internal to the sum of external branch lengths, or stemminess . We only explore loci with a minimum of 30 phylogenetically informative sites, and in which none of the nucleotide frequencies is greater than 0.5. These bounds ameliorate the severe impact that outlier sites can have on the estimates of the Our proposed test of substitution saturation was performed separately for each locus in each data set, where “locus” is defined as in the studies from which we obtained the data. Our analyses focused on the test on informative sites only, given that a test on complete alignments has inferior performance under most conditions , that between phylogenetic imbalance and stemminess of the true tree . In contrast, the statistic on phylogenetically informative sites was reasonably well explained by the interaction between the true tree length and the substitution model used for simulation . Specifically, according to multiple regression, the values of  of taxa .Supplementary Fig. S1 available on Zenodo), while the test on all sites had poor performance throughout scenarios. The test on informative sites was also virtually unaffected by model underparameterization when including small numbers of taxa. These results are consistent with our simulations showing that the primary drivers of misleading branch-length estimates are large tree lengths, high stemminess, and excessive tree imbalance, rather than the accuracy of the substitution model among those examined.The test on informative sites also had a reasonable ability to identify inaccurate inferences of branch lengths .Our implementation of the entropy tests of saturation on empirical data sets took an average of 0.141 s per locus. Saturation was flagged as being highly prevalent in more than a quarter of the data sets examined (10 of 36), affecting turation a. Unsatuturation b. This mOur analyses revealed that the impact of saturation on discordance across sites in gene trees can be substantial. Loci flagged for saturation yielded gene trees that had mean aLRT branch supports that were 4.8% lower on average than the trees inferred from unsaturated loci, being 25% poorer in one data set . NonetheData sets that targeted exons and introns had higher proportions of saturated loci than those that targeted UCEs and anchored-enriched regions a. Data sSupplementary Fig. S3 available on Zenodo). Interestingly, loci with relatively few informative sites in each data set were frequently flagged as being saturated, such that they should be scrutinized in empirical data. One solution is to use the entropy Our study has shown that substitution saturation can be highly misleading in phylogenetics, even when compared with a range of other factors that can also mislead inference. Saturation was flagged as occurring in large numbers of loci in nearly one-third of a broad range of empirical data sets examined, and tended to be flagged in loci with highly discordant signals across sites . This might be due to a more careful choice of markers and data filtering before analyses of UCEs, which is also reflected in the small portions of loci rejected.Our analyses of empirical data sets suggest that different data types have comparable portions of saturated loci. Rather than depending on data type, saturation is typically flagged as a problem for loci that have small numbers of fast-evolving sites. This finding lends support to the hypothesis that variable sites in highly conserved genomic regions have more saturation than those in highly variable genome regions . DespiteStrikingly, our test identified large proportions of loci as being saturated in multiple data sets, in some cases identifying saturation in more than half of the data. This suggests that assessing substitution saturation can have a dramatic effect in reducing noise in phylogenomic data sets. Assessing saturation in alignments as a whole can be particularly useful after filtering by taxa e.g.,  and by sOur findings on the performance of the entropy saturation test also point to the importance of assessing substitution model adequacy in phylogenetic studies e.g., . Our resThe entropy test of substitution saturation on phylogenetically informative sites shows good performance across a broad range of scenarios and is likely to be robust to other factors that were not explored in this study. For example, the test is likely to perform well in the presence of rate variation across sites, provided that this form of variation is modeled appropriately . HoweverAn important matter when developing tests of phylogenetic signal or model adequacy is to identify appropriate critical values that balance the rates of true and false positives. Identifying such critical values can be a difficult task, for many reasons. In particular, phylogenetic information is not straightforward to capture in test statistics that summarize the features of sequence alignments . We findAlternative methods of assessing substitution saturation might prove to have better performance. For example, a common practice for model assessment in evolutionary biology is to use null distributions based on simulations , which aSubstitution saturation is detrimental to phylogenetic inference and is common in phylogenomic data sets, but it can be effectively identified using appropriate tests. Phylogenomic data sets are now widespread and researchers need to identify the data, models, and methods that are most suitable for answering the biological questions being posed e.g., . The ent


Frequency of alcohol drinking is a potential predictor of binge drinking of alcohol, a serious social problem for university students. Although previous studies have identified skipping breakfast as a predictor of various health-compromising behaviors and cardiometabolic diseases, few studies have assessed the association between skipping breakfast and the incidence of frequent alcohol drinking. This retrospective cohort study included 17,380 male and 8799 female university students aged 18–22 years admitted to Osaka universities between 2004 and 2015. The association between breakfast frequency  and the incidence of frequent alcohol drinking, defined as drinking ≥4 days/week, was assessed using multivariable-adjusted Cox proportional hazards models. During the median observational period of 3.0 years, 878 (5.1%) men and 190 (2.2%) women engaged in frequent alcohol drinking. Skipping breakfast was significantly associated with the incidence of frequent alcohol drinking . University students who skipped breakfast were at a higher risk of frequent alcohol drinking than those who ate breakfast every day. Excessive alcohol consumption is a global health and social burden because it is associated with suicide , death bBreakfast is the most important meal of the day. Japanese people mainly eat rice or bread at breakfast . MultiplThe present 5-year retrospective cohort study aimed to clarify the association between skipping breakfast and the incidence of frequent alcohol drinking in 26,179 university students at a single national university in Japan, where drinking alcohol under the age of 20 is prohibited by law. The findings of the present study clarify the clinical impact of skipping breakfast on the frequency of alcohol drinking in young adults.The eligible participants of the present study were 38,111 university students admitted to Osaka University, one of the largest national universities in Japan, between 2004 and 2015. The participants underwent baseline health checkups on admission in April or October between 2004 and 2015. We excluded 229 (0.6%) students aged <18 and >22 years, 36 (0.1%) who drank ≥4 days/week at baseline, 8918 (23.4%) with missing baseline data, and 2749 (7.2%) who had no measurement of drinking status after their baseline checkups during the 5-year observation period. Finally, we included 26,179 (68.7%) students to assess the association between skipping breakfast and the incidence of frequent alcohol drinking .The study protocol was approved by the ethics committee of the Health and Counseling Center of Osaka University  and Osaka University Hospital (No. 18352–3). The present study used an opt-out approach to provide informed consent according to the Japanese Ethical Guidelines for Medical and Health Research Involving Human Subjects. All procedures in this study involving human participants were performed in accordance with the ethical standards of the institutional and national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.2 (m2)), and general questionnaires regarding breakfast frequency, frequency of drinking alcohol, and potential confounders, including smoking status  and 8790 [99.9%], respectively), smoking status was categorized into two categories: non-smokers with the answer of “I do not smoke”, and smokers with other answers. Weekday sleep duration was ascertained by the question “How long do you sleep on weekdays?” with five possible responses of <5, 5–6, 6–7, 7–8, and ≥8 h. Living arrangement was asked using the question “Which is your living arrangement?” with four possible answers: living with family, living alone, living in a dormitory, and other living arrangements. Stress frequency was determined by the question “Do you feel stressed?” with four possible answers: “I rarely feel stressed”, “I sometimes feel stressed”, “I often felt stressed”, and “I always feel stressed.”All data were retrieved from the electronic database of the Health and Counseling Center of Osaka University. The baseline variables at the health checkup on admission included age, body mass index (BMI = body weight (kg)/heightg status ,41, streg status ,43, weekg status ,45, and g status ,46. BreaThe outcome measure of the present study was the incidence of frequent alcohol drinking, which was defined as ≥4 days/week of alcohol drinking based on the questionnaire at the annual health checkups during the 5-year observational period. We set the outcome at ≥4 days/week of alcohol drinking because the previous Canadian cohort study showed that adults with ≥3 day/week of alcohol drinking were vulnerable to binge drinking . The obsn = 201 [1.2%] and 76 [0.9%], respectively), we combined those usually skipping breakfast and those skipping often into a single category. Thus, breakfast frequency was recategorized into three groups: eating every day, skipping occasionally, and skipping often/usually.Owing to the small number of students usually skipping breakfast , smoking status , living arrangements , weekday sleep duration , and stress frequency  as covariates. For female students, smoking status was not included in the multivariable-adjusted model because of the small number of smokers (n = 9). The proportional hazard assumption was tested using the Schoenfeld residuals.All analyses were performed separately for male and female students. Baseline characteristics of the three groups of breakfast frequency were compared using analysis of variance or the chi-square test, as appropriate. The cumulative probabilities of frequent alcohol drinking in the three breakfast frequency groups were calculated using the Kaplan–Meier method and compared using the log-rank test. To assess the association between breakfast frequency and the incidence of frequent alcohol drinking, unadjusted and adjusted hazard ratios (HRs) were calculated using unadjusted and multivariable-adjusted Cox proportional hazard models. Multivariable-adjusted Cox proportional hazards models included age , BMI .Continuous variables are expressed as mean ± standard deviation or median (25–75%), as appropriate, and categorical variables are expressed as numbers with proportions. Statistical significance was set at p < 0.05). Similar tendencies were observed in 8799 female students  years, 686 (4.9%), 116 (5.2%), and 76 (7.4%) male students who ate breakfast every day, skipped it occasionally, and skipped it often/usually, respectively, engaged in frequent alcohol drinking a. An unaOf the 8799 female students, the incidence of frequent alcohol drinking was observed in 150 (1.9%), 23 (3.0%), and 17 (6.1%) students eating breakfast every day, skipping it occasionally, and skipping it often/usually, respectively, during the median observational period of 3.04 years (3.01–3.06) . Comparen = 26,179), which enabled statistically meaningful analyses to assess the clinical impact of skipping breakfast on the incidence of frequent alcohol drinking in both male and female students.The present retrospective cohort study identified skipping breakfast as a significant predictor of frequent alcohol drinking in university students. Some advantages of the present study were the cohort study design with the 5-year observational period and the large sample size (Several large cross-sectional studies have reported the association between skipping breakfast and the prevalence of alcohol consumption. A Chinese cross-sectional study including 19,542 school-aged adolescents reported that female adolescents who skipped breakfast were more likely to drink during the past 7 days than those who did not skip breakfast, whereas no association between skipping breakfast and the prevalence of drinking was observed in male adolescents . AnotherOne plausible mechanism for the association between skipping breakfast and frequency of alcohol drinking may be depression. Skipping breakfast is a clinical predictor of depression. A 1-year prospective Chinese cohort study, including 757 university students, reported that skipping breakfast, defined as breakfast consumption of ≤1, 2–5, vs. ≥6 times/week, was associated with the incidence of self-reported depressive symptoms based on the Zung Self-Rating Depression Scale in a dose-dependent manner . A similThe present study had several limitations. First, because alcohol consumption at each drinking occasion was not available in the present study, the clinical impact of skipping breakfast on the frequency of binge drinking was not assessed in the present study. An international cross-sectional study including 21,972 university students in 28 countries showed that skipping breakfast was associated with the prevalence of binge drinking . HoweverThe present retrospective cohort study, which included 26,179 university students at a single university, identified skipping breakfast as a significant predictor of the incidence of frequent alcohol drinking. These findings provide clinically useful information to identify university students potentially vulnerable to excessive alcohol consumption. A well-designed study is essential to verify the clinical impact of skipping breakfast on alcohol use disorders in young adults.


Social media platforms are increasingly being used to disseminate mental health information online. User-generated content about attention-deficit/hyperactivity disorder (ADHD) is one of the most popular health topics on the video-sharing social media platform TikTok. We sought to investigate the quality of TikTok videos about ADHD.Journal of American Medical Association (JAMA) benchmark criteria were used to assess the overall quality, understandability, and actionability of the videos.The top 100 most popular videos about ADHD uploaded by TikTok video creators were classified as misleading, useful, or personal experience. Descriptive and quantitative characteristics of the videos were obtained. The Patient Education Materials Assessment Tool for Audiovisual Materials (PEMAT-A/V) and n = 52) were classified as misleading, 27% (n = 27) as personal experience, and 21% (n = 21) as useful. Classification agreement between clinician ratings was 86% (kappa statistic of 0.7766). Videos on the platform were highly understandable by viewers but had low actionability. Non-healthcare providers uploaded the majority of misleading videos. Healthcare providers uploaded higher quality and more useful videos, compared to non-healthcare providers.Of the 100 videos meeting inclusion criteria, 52% (Approximately half of the analyzed TikTok videos about ADHD were misleading. Clinicians should be aware of the widespread dissemination of health misinformation on social media platforms and its potential impact on clinical care. Although social media can reduce mental health stigma and improve health literacy, there is also concern about misinformation and the potential for illness/health anxiety (“cyberchondria”) due to the volume of unmoderated, user-generated content online.6 For example, TikTok videos have been implicated in a recent rise of tic-like behaviours in adolescents, and it is thought that exposure to tic-related videos is responsible for this phenomenon.79Social media platforms are a popular means of sharing medical information online. TikTok in particular is a relatively new social media platform that has seen rapid adoption by adolescents and young adults, becoming the most downloaded social media application in 2020 with more than 1 billion monthly active users. With TikTok being a relatively new social media platform, there is little research on the quality and accuracy of its content. As a result, there have been increasing calls for more research to understand the potential implications of TikTok on health information dissemination. Recent studies examining TikTok videos have found that misinformation was common for a variety of medical topics including those about acne, diabetes, and cosmetic surgery.1012 To our knowledge, no study has examined the quality of mental health information disseminated on TikTok. Thus, our objective was to assess the quality of medical information in the most popular TikTok videos related to ADHD.Additionally, social media platforms use proprietary algorithms that focus on increasing user engagement and may promote videos that do not necessarily reflect accurate health information. A recent systematic review found that the prevalence of health misinformation was high across almost all social media platforms.1315 Videos meeting the inclusion criteria were then included for extraction of video characteristics and further analysis.The TikTok mobile phone application was queried with a search for the hashtag “#adhd” on July 18, 2021 . The pro17 Videos were viewed, analyzed, and classified as: (1) useful; (2) personal experience; or (3) misleading. Videos were classified as useful if the video contained scientifically correct information about any aspect of ADHD: prevention, symptoms, diagnosis, treatments, or other information . Videos were classified as personal experiences if it described a user's own personal or anecdotal experience of ADHD symptoms or treatment. Videos were classified as misleading if it contained information lacking scientific evidence . If a personal experience video additionally contained any generalized misleading statements, it was classified as misleading rather than personal experience.One psychiatrist and one psychiatry resident  with clinical experience in the diagnosis and management of ADHD independently assessed the videos using a categorical classification often used to assess the content quality of social media videos.19 In cases where there was disagreement between the first two raters, a third psychiatrist rater (EAJ) independently rated the video to decide on the final rating.Where applicable, raters referenced the Canadian ADHD Resource Alliance (CADDRA) Canadian ADHD Practice Guidelines, Fourth Edition, and American Academy of Pediatrics ADHD Clinical Practice Guidelines. Finally, videos were also rated on the Journal of American Medical Association (JAMA) benchmark criteria, a four-point scale which assesses medical information quality based on: (1) authorship , (2) attribution , (3) disclosure , and (4) currency (dates that content was posted and updated are indicated).All videos were also assessed using the Patient Education Materials Assessment Tool for Audiovisual Materials (PEMAT-A/V), a validated instrument to assess the understandability and actionability of audiovisual patient education videos.t test was used to compare video characteristics, PEMAT scores, and JAMA scores between HCPs and non-HCPs video uploaders. Pearson's chi-square test was used to compare frequencies of the video classifications between HCPs and non-HCPs. One-way analysis of variance was used to compare video characteristics, PEMAT scores, and JAMA scores between the three video classifications. A P-value of less than 0.05 was considered significant for all analyses. All statistical analyses were performed using Stata 17.0.Video metadata was extracted automatically using an open-source web scraper using TypeScript programming language (TikTok-scraper). Descriptive characteristics for each video included: user type , number of views, number of likes, and number of shares. The kappa statistic was calculated to assess inter-rater reliability for the initial video classification between the two raters. Student's Prior to applying the exclusion criteria, there were a total of 4.3 billion views on videos tagged with “#adhd” at the time of the query. The 100 videos meeting inclusion criteria had a total of 283,459,400 views; 89 videos were uploaded by non-HCPs, while 11 were uploaded by individuals identifying as HCPs . None of the videos in this sample were uploaded by corporations, health organizations, for-profit entities, or non-profit entities. There was an average of 2.8 million views  and 31,175 shares  per video. The average video length was 36.7 s (range: 8.0–74). Across all videos, the average PEMAT-A/V understandability score was 94.3% (range: 66.7–100%), and the average PEMAT-A/V actionability score was 14.3% (range: 0–100%). The average JAMA benchmark score was 1.3 (range: 1–3).P < 0.001). Personal experience videos had the highest PEMAT-A/V understandability score, with an average score of 98.3% (P < 0.001), and were the most popular .The full video characteristics by the classification are described in Of the 21 useful videos, 17 videos (81%) described signs and symptoms of ADHD specific to the disorder, or informed viewers that transdiagnostic symptoms may be due to other medical conditions or comorbid psychiatric disorders. Three videos (14%) provided information on treatments or strategies for coping with ADHD that have been validated. One video (5%) accurately described the prognosis and risk factors for ADHD. Of the 27 personal experience videos, all videos described individual experiences of living with ADHD symptoms and/or its impact on day-to-day life.P < 0.001) and personal experience videos  than HCPs. HCPs had significantly more useful videos than non-HCPs . Non-HCP videos were more popular, though this was not statistically significant.The full descriptive characteristics of the videos by creator type (HCP vs. non-HCP) are described in In this analysis of popular TikTok videos about ADHD, there were over 2.8 million views per video and each video was shared on average 31,000 times. Approximately half of the videos analyzed (52%) were misleading, with non-HCPs uploading most of these videos (49 out of 52 videos). There was substantial agreement among raters on the classification of the videos as useful, misleading, or personal experience. Our study is the first to show that misleading videos about ADHD are being widely disseminated and viewed on TikTok.11 Our results are also similar to a study by Thapa et al. that analyzed YouTube videos about ADHD and found that 38% of analyzed videos were misleading and only 5% were useful. The study also found that first-person or personal experience videos received the highest engagement , while misleading videos were the most common. Our study replicated these findings on TikTok: personal experience videos received the highest engagement , while misleading videos were the most common. These consistent findings across different social media platforms suggest that viewers are most drawn to videos made by individuals with lived experience, and less so towards institutional or HCP-created videos. Increasingly, social media influencers and independent video creators have been found to have an outsized influence on the dissemination of health information online.2325 Indeed, in our study, none of the top 100 videos were uploaded by corporations, health organizations, for-profit entities, or non-profit entities, and only 11% of videos were uploaded by HCPs. This limited presence of HCPs on TikTok has been observed in other studies as well. Overall, HCPs did score significantly higher on the JAMA benchmark criteria and made significantly more useful videos and less misleading videos. Although this suggests that healthcare providers do upload higher quality content on the platform, 27% of HCP videos (3 out of 11) were still rated as misleading.These findings are in line with previous studies of TikTok videos that have found high rates of misinformation for medical conditions, including acne and diabetes.We additionally found that all videos about ADHD were highly understandable, scoring over 90% on the PEMAT-A/V understandability score. The understandability score does not reflect accuracy, but merely that the information is presented in an understandable manner. Thus, individuals may be seeing videos about ADHD on the platform that are highly understandable and yet misleading. This was seen in our qualitative review of misleading videos, which often had an oversimplified or reductionist explanation of ADHD. The proprietary TikTok algorithm has been found to have a propensity to show users similar videos over time, which may further propagate misleading videos.28 Additionally, viral trends on TikTok, “echo chambers” in social media, and romanticization of mental health symptoms31 may perpetuate the dissemination of misleading information on TikTok. Increased healthcare use may occur for individuals who seek clinical attention after viewing TikTok videos about ADHD, a phenomenon that has been widely documented by major news organizations.4 Since self-report of ADHD symptoms may be over-endorsed, there may be an increased risk for overdiagnosis or misdiagnosis in these individuals as well. In general, there has also been renewed interest over rising rates of ADHD diagnoses,3335 and debate about the overdiagnosis of ADHD.The findings from our study provide several important insights into the dissemination of medical information about ADHD on TikTok. Approximately half of all videos analyzed were misleading, and the misinformation they contain has the potential to contribute to health anxiety or lead to increased healthcare utilization.37 One related example is the rapid increase in tic-like behaviours that have been observed over the course of the COVID-19 pandemic.9 Tic disorder specialists have seen a dramatic increase in referrals for tic-like behaviours in primarily adolescent females that are inconsistent with usual presentations of primary tic disorders. These presentations are thought to be most consistent with a diagnosis of functional neurological disorder, related to stressors over the course of the pandemic. The sociogenic propagation of tic-like behaviours across TikTok is a reflection of the impact of social media platforms on health behaviours.9TikTok has become particularly popular over the course of the COVID-19 pandemic. The pandemic context raises the question of whether individuals may be misattributing difficulties from pandemic public health measures  to ADHD symptoms. However, there are currently no other widely used or accepted methods of assessing medical information videos online.Limitations of our study include TikTok's proprietary search algorithm results, which exclude video ads and do not allow for systematic searching of all videos or deleted videos. Not all videos contained detailed information to identify whether an uploader was a health professional or not. Additionally, the current study only screened for the top 100 most popular videos. Less popular videos may have different content quality and characteristics not captured in this study. Also, the conceptualization of what is considered as a misleading, useful, or personal experience video was done from the perspective of raters who are HCPs. This perspective may not necessarily be in line with healthcare consumers or patients. For instance, while some videos may not be useful from the perspective of an HCP, others may find it useful for other reasons. Additionally, although our inter-rater agreement was high, videos classified as useful could potentially be classified as personal experience videos. Videos on the platform may also be recorded to be humorous or spontaneous, and not necessarily recorded with the intent to disseminate medical information. However, even videos made without intent to disseminate medical information may describe non-specific symptoms, overgeneralizations, and characterizations about ADHD that could be misleading to viewers. Finally, there have also been criticisms of the use of tools such as the JAMA benchmark criteria as a method to evaluate online videos. It is thus important for clinicians to be aware of the dissemination of misleading videos on TikTok and the potential impact on clinical care. Future areas of research include a better understanding of the prevalence and nature of misinformation on TikTok for other mental health topics such as depression, anxiety, suicide, and self-harm. Our finding that HCPs generally upload higher quality and more useful videos deserves replication and further study to see whether HCP engagement on the platform could help correct misinformation regarding ADHD and other mental health disorders.In summary, this study is the first to show that misleading videos about ADHD are being widely disseminated on TikTok. Although the platform is the most popular social media application of 2020 and 2021, it is currently the least studied of the major social media platforms.Click here for additional data file.Supplemental material, sj-xls-1-cpa-10.1177_07067437221082854 for TikTok and Attention-Deficit/Hyperactivity Disorder: A Cross-Sectional Study of Social Media Content Quality by Anthony Yeung, Enoch Ng and Elia Abi-Jaoude in The Canadian Journal of Psychiatry


Out-of-hours discharge from ICU to the ward is associated with increased in-hospital mortality and ICU readmission. Little is known about why this occurs. We map the discharge process and describe the consequences of out-of-hours discharge to inform practice changes to reduce the impact of discharge at night.This study was part of the REcovery FoLlowing intensive CarE Treatment mixed methods study. We defined out-of-hours discharge as 16:00 to 07:59 hours. We undertook 20 in-depth case record reviews where in-hospital death after ICU discharge had been judged “probably avoidable” in previous retrospective structured judgment reviews, and 20 where patients survived. We conducted semistructured interviews with 55 patients, family members, and staff with experience of ICU discharge processes. These, along with a stakeholder focus group, informed ICU discharge process mapping using the human factors–based functional analysis resonance method.Three U.K. National Health Service hospitals, chosen to represent different hospital settings.Patients discharged from ICU, their families, and staff involved in their care.None.Out-of-hours discharge was common. Patients and staff described out-of-hours discharge as unsafe due to a reduction in staffing and skill mix at night. Patients discharged out-of-hours were commonly discharged prematurely, had inadequate handover, were physiologically unstable, and did not have deterioration recognized or escalated appropriately. We identified five interdependent function keys to facilitating timely ICU discharge: multidisciplinary team decision for discharge, patient prepared for discharge, bed meeting, bed manager allocation of beds, and ward bed made available.We identified significant limitations in out-of-hours care provision following overnight discharge from ICU. Transfer to the ward before 16:00 should be facilitated where possible. Our work highlights changes to help make day time discharge more likely. Where discharge after 16:00 is unavoidable, support systems should be implemented to ensure the safety of patients discharged from ICU at night. The link between out-of-hours discharge to the ward from ICU  and subsequent in-hospital mortality has long been recognized , 2. Our The work reported here formed part of the REcovery FoLlowing intensive CarE Treatment (REFLECT) project, a U.K.-based mixed methods study examining the care of patients discharged from ICU to hospital wards . The oveThere is no consensus on the definition of out-of-hours discharge from ICU. In international literature, start times range from 16:00 to 22:00 and end times from 05:59 to 09:00 , 11. In Premature discharge was defined as occurring for those patients experiencing ongoing clinical problems at ICU discharge which did not respond to ward-based therapy within the first 48 hours of transfer, in line with published definitions .Probably avoidable death was defined as those having a greater than 50% chance of preventability if changes had been made to the care delivered .The REFLECT study was granted ethical approval by Wales REC 4 (reference 17/WA/0139) and registered (ISRCTN14658054). Data were collected at three NHS trusts.A retrospective case record review (RCRR) of 300 patients discharged from ICU who did not survive to hospital discharge using the structured judgment review method  has prevSupplemental file 1, Fig. 1, http://links.lww.com/CCM/H83). A summary of the methodology can be found in the protocol .In the RCRR, we judged 20 post-ICU deaths as “probably avoidable” . We undehttp://links.lww.com/CCM/H83). Further details of the approach taken are published elsewhere (http://links.lww.com/CCM/H83).We conducted thematic analysis  of semisFindings from these in-depth analyses and interviews relating to out-of-hours discharge are presented here, including a vignette drawn from the RCRR, to offer context.The FRAM method is widely used in safety reviews in industry and increasingly in healthcare –20. The This FRAM, focusing on ICU to ward discharge, was informed by the primary data from the REFLECT study and input from stakeholders. An HF scientist with experience facilitating FRAMs (L.M.) led the meeting. Key staff members  from the three REFLECT study sites, including an ICU consultant, an ICU follow-up practitioner with a nursing background, and a senior ICU nurse, took part. Two research team members with in-depth knowledge of the primary data and ICU- and ward-based nursing and physiotherapy clinical experience also attended. At the start of the session, an information package was presented to the group, including relevant prior research and data from the REFLECT study.The HF scientist commenced the FRAM by reiterating the focus on the “ideal world” situation—that is, discharging a patient from ICU “in-hours” (before 16:00). Group members suggested a function in the ICU discharge process. A facilitated discussion of this function took place to identify each condition . From this, further functions and their conditions were identified, and links between the functions developed.https://functionalresonance.com/FMV/index.html).The HF scientist documented the developing framework on whiteboards using sticky notes color-coded to match the framework. This was refined through discussion, with changes made to functions, lines redrawn, and further functions added. The process ended when the group was happy that all functions and associated conditions directly related to the process had been captured. The final FRAM model was transcribed from the white boards into FRAM visualizer software . Only two of these high EWS were escalated, with between 3 and 9 hours to the next documented EWS (see vignette). In comparison, only two of 12 in-hours discharges had a high EWS on arrival, and both were escalated according to local protocol.For 12 of 28 patients discharged overnight, their initial ward Early Warning Score (EWS) was high , suggesting failure to optimize prior to discharge Table  , with staff voicing concern about the subsequent impact on patient safety and experience (quotes 1 to 8).Overall, care provision at night was perceived as challenging due to reduced staffing and skill mix, and high workload. Staff described this as impacting their ability to manage patients who were identified as potentially being discharged before they were ready, due to high bed occupancy. These challenges augmented the perception of vulnerability experienced by patients being transferred from ICU to the ward.Supplemental file 4, Table 1 (http://links.lww.com/CCM/H83).Five functions were identified as essential to facilitating discharge from ICU before 16:00. Figure Confirming a patient was ready for ICU discharge was identified as a multidisciplinary team (MDT) decision. Patient-based preconditions included not requiring organ support or drugs only administered in ICU and assessed by physiotherapist as ready for discharge. This decision was usually made during morning ward rounds, which may not occur until late morning depending on the unit workload.The timing of this decision was perceived to have consequences for ward bed identification. Where the discharge decision was made the evening before, this facilitated earlier communication with the bed manager.Function 2 was also identified as an MDT process. The key precondition identified was handover documentation prepared by nurses, doctors, and physiotherapists. Drug charts, fluid balance, and vital signs charts must also be transposed into ward-friendly formats and drugs reviewed by the ICU pharmacist. This preparation requires knowledge of the ward environment and what is deliverable on the ward.Key resources include nursing time to complete and collate documentation, remove invasive catheters and monitoring, and liaise with the ward.A hospital-wide mandated morning bed meeting is held at all three organizations, to discuss discharges and bed availability. This relies on discharge information which is dependent on ICU and ward round decision-making (function 1).Based on bed meeting information, staffing levels, and ICU bed needs , a ward bed may be allocated for the ICU patient ready for discharge.Once a bed has been allocated, ICU and ward staff negotiate a discharge time and ICU inform the ward of any special requirements such as a side room (for infection control) or equipment .This function is time dependent on discharge of the patient occupying the ward bed, in turn reliant on the ward round, discharge medication preparation, and availability and appropriateness of the discharge lounge .The final outcome relies on the timely output of all the key functions, which rely on all preconditions, resources, and inputs being in place. Although the functions are not entirely linear, delay of any activity or precondition will impact the time of discharge.Using data from three NHS hospitals, we outlined the consequences of discharge from ICU to the ward after 16:00. Out-of-hours discharge was common at all hospitals and linked to poorer handover and a delay to first medical review. Patients discharged at night were more likely to have a high EWS on ward arrival, indicating higher acuity, which was rarely escalated overnight. Almost all premature discharges occurred out-of-hours, and consequences for these patients were profound. Both staff and patients voiced concerns about discharge at night, identified as a time of high workload and low skill mix. The combination of higher acuity of illness, a reduction in staffing and skill mix, and poorer handover of information compounds the challenges of receiving patients from ICU overnight. To examine how ICU discharge during the day may be facilitated, the process for discharging a patient from ICU to the ward was mapped in consultation with stakeholders. Examining this process identified five key functions essential to facilitating discharge from ICU before 16:00.This study had several strengths. Data were collected from three NHS trusts, as part of a larger project, which was registered and the protocol was published . The thrAs the focus of the REFLECT study incorporated the whole post-ICU ward stay, data on out-of-hours discharge were somewhat limited. Future work including contextual data on bed occupancy, patient flow, organizational stress, staffing levels, and delays to hospital discharge may offer further insight into reasons for out-of-hours discharge . In thisLimitations of RCRR include reliance on documentation (risking loss of data and context) and hindsight bias , 26. By Although this work was conducted solely in the United Kingdom, our meta-analysis found no difference in the association between out-of-hours discharge and poor outcome between countries, indicating this is an international problem . This woThe FRAM approach differed from our planned prioritization exercise in the protocol as we identified fewer distinct problems in care than anticipated. This allowed stakeholder involvement to focus on developing our understanding of each problem. The FRAM stakeholder group was relatively small but was informed by primary data from interviews with 55 patients, family members, and staff, 300 structured judgment reviews, and 40 in-depth reviews.Our work provides context to the association identified by our meta-analysis between out-of-hours discharge and poor outcome , includiThe high frequency of “problems in care” occurring out-of-hours identified by in-depth reviews suggests significant failure of care provision overnight. Combining this with interview data offered contextual information underlying these problems. Patients discharged out-of-hours rarely received a medical review on arrival. When they did, this was usually by the most junior doctors. This suggests lack of experience may have contributed to poor outcome out-of-hours. A before-and-after study of a “Hospital At Night” multidisciplinary deterioration response initiative  found anInterviewed staff perceived out-of-hours discharge as inevitable due to the need to create beds for incoming patients. This was supported by the high proportion of discharges occurring after 16:00 and the complexity identified in the FRAM. In-depth reviews identified several overnight premature discharges experiencing significant ongoing medical problems. Both out-of-hours and premature discharge from ICU have been identified as indicators of ICU capacity strain , with neThe FRAM illuminated structural issues in processes of care, amenable to changes. We identified five functions where delay would increase the risk of failure to reach the end goal of discharge before 16:00. Timing of the ICU discharge decision (function 1) relies on the timing of the morning ward round, which often occurs after the bed meeting (function 3). Making the discharge decision (function 1) the evening before ICU discharge facilitates timely information flow to the bed meeting (function 3) and therefore earlier ward bed allocation (function 4). It also gives more time to prepare the ICU patient for discharge (function 2). Finally, it allows longer for the ward to prepare a bed for the incoming patient (function 5), including facilitating discharge of ward patients to create capacity and sourcing specialist equipment. The only function where timing is immovable is the bed meeting (function 3), as it is embedded in organizational practice. Process changes need to accommodate these established practices to succeed, and the impact of delays should be acknowledged and planned for.Although the FRAM identified strategies to support discharge before 16:00, both this work and previous literature have shown it is likely some out-of-hours discharges will be unavoidable due to limited bed capacity , 39. In This study identified significant limitations in out-of-hours care provision for patients discharged from ICU overnight. Transfer to the ward before 16:00 should be facilitated where possible. Our work highlights four alterable functions where changes will help make day-time discharge more likely. Where discharge after 16:00 is unavoidable, clear acknowledgment of ongoing clinical problems in discharge documentation, a medical review on ward arrival and careful monitoring of EWS should be implemented to ensure the safety of patients discharged from ICU at night.We gratefully acknowledge the patients, family members, and staff who participated in the REcovery FoLlowing intensive CarE Treatment study and the sites who supported us in the conduct of this research.


There were few studies to report whether drinking water sources and habits affected health outcomes. Therefore, this study aimed to examine how boiled water and lifespan water sources affected the risks of cardiovascular disease (CVD) and all-cause mortality in the elderly.This study was a 20-year cohort study. All participants aged ≥60 years were eligible. Exposures of interest included lifespan drinking water sources and habits, which were collected using a validated questionnaire. Drinking water sources included wells, surface water, spring, and tap water in childhood, around the age of 60 years, and at present. Drinking habits included boiled and un-boiled water. The main end events included CVD and all-cause mortality.HR: 1.092, 95% CI: 1.051–1.134, P < 0.001; and HR: 1.136, 95% CI: 1.081–1.194, P < 0.001, respectively). However, only drinking spring around aged 60 years and drinking well at present were associated with a lower CVD mortality . Boiled water was not associated with mortality.There were 33,467 participants in this study. Compared to tap water, drinking well and surface water around the age of 60 years were associated with a higher risk of all-cause mortality (Drinking water from well and surface water around the age of 60 years were associated with increased all-cause mortality. Drinking water from spring around the age of 60 years and well at present was associated with a decreased CVD mortality. However, boiled water was not associated with mortality. As drinking water is an essential issue for human beings, access to safe drinking water is the most fundamental requirement for public health. It is reported that about 2.2 billion people have no access to improved drinking water worldwide . It is eThe associations of water, sanitation, and hygiene with health outcomes are critical for the prevention of diseases and improvement of life expectancy. Until now, there were many studies to report the associations of drinking water with health outcomes, including mortality and cardiovascular disease (CVD) –7. HowevIn this study, the Chinese Longitudinal Healthy Longevity Survey (CLHLS) was used to examine how boiled water and lifespan water sources affect CVD and all-cause mortality. As a result, this study would contribute to the improvement of health in the elderly.The CLHLS was first conducted in 1998, and followed by waves in 2000, 2002, 2005, 2008–2009, 2011–2012, 2014, and 2017–2018. Twenty-three provinces/ municipalities were randomly selected from 31 provinces/ municipalities in China. Then, about half of the counties and city districts were randomly sampled within 23 provinces/ municipalities. In a healthy longevity survey, there were 19.5 thousand centenarians, 26.8 thousand nonagenarians, and 29.7 thousand octogenarians. The older people aged 80 years or older accounted for 67.4% of the total sample. A validated questionnaire was used to collect information on family structure, physical performance, health status, history of chronic diseases, and so on.This study included all participants aged 60 years or older. If subjects had incomplete data on drinking water sources, drinking habits, and other covariates, they would be excluded. Meanwhile, subjects with abnormal data on covariates, such as weight and blood pressure, were also excluded. The detailed screening procedure is shown in via a similar question: Water you drink is mainly from? Participants were required to select an answer from the following options: 1. well, 2. rivers or lakes, 3. spring, 4. pond or pool, and 5. tap water. In the final analysis, drinking water sources were classified as follows: tap water, well, surface water, and spring. Similarly, a question “What kind of water you usually drink?” was used to identify drinking habits, including boiled and un-boiled water.Exposures of interest included drinking water sources and drinking habits. Drinking water sources in childhood, around the age of 60 years, and at present were identified End-events of interest included CVD mortality and all-cause mortality. In each wave, survival status was checked for each participant in a face-to-face interview. If someone died before a certain survey, the ascertainable date of death was identified by interviewing a close family member or local doctors. Furthermore, cause-specific mortality was further interviewed. Deceased participants caused by CVD were considered to have an end-event of CVD mortality.via the following questions: How often do you eat fresh fruit at present? How often do you eat vegetables at present? How often do you eat meat at present? How often do you eat fish at present? Information on alcohol consumption, current smoking habits, physical activity, self-rated health, and history of hypertension, diabetes, and CVD were collected using a validated questionnaire, which was described in detail elsewhere  and were compared with the differences between-group using the chi-square test. Hazard ratios (HRs) and 95% CIs of drinking water sources and habits on the risks of CVD and all-cause mortality were estimated using Cox regressions with adjustments for age, sex, weight, ethnicity, education levels, marital status, living areas, current smoker, current alcohol consumer, physical activity, dietary intakes including fruits, vegetables, meat, and fish, history of hypertension, history of diabetes, self-reported health, and waves. Based on the adjusted factors mentioned above, drinking water source was additionally adjusted when drinking habits as the main exposure. Meanwhile, drinking habits were further adjusted based on the common- adjusted factors mentioned above when drinking water source as the main exposure. The Fine-Gray competing risk model was used to correct the competitive risk of death caused by other causes when CVD mortality is the end event. Cox regressions were further stratified by sex and living areas. In this study, the proportional hazards assumption was confirmed to hold in all Cox regressions. To prevent the possibility that deaths were caused by other fatal illnesses, sensitivity analysis was conducted with participants who died within the first 2 years after baseline being excluded from the analysis. All analyses were conducted using SAS 9.4 . A two-tailed P ≤ 0.05 indicated a statistical significance.A P = 0.480). Meanwhile, significant differences between censoring and end-event caused by CVD were observed in all baseline characteristics, except weight (P = 0.141), marital status (P = 0.224), education (P = 0.065), ethnicity (P = 0.425), current smoking habits (P = 0.194), current alcohol consumption (P = 0.613), self-reported health (P = 0.238), history of diabetes (P = 0.905), and drinking habits (P = 0.185) as shown in Finally, there were 33,467 participants included in this study. The median time of follow-up was 5 years. The averages of age and weight were 86.38 ± 11.53 years and 49.60 ± 11.18 kg, respectively. The proportions of males and females were 43.33 and 56.67%, respectively. There were 31,904 and 1,563 participants drinking boiled and un-boiled water, respectively. There were 20,295 and 1,210 deceased participants caused by all-cause mortality and CVD, accounting for 60.64 and 3.80%, respectively. There were significant differences between censoring and end-event caused by all-cause mortality in all baseline characteristics, except a history of hypertension . Compared to tap water, drinking well, surface water, and spring in childhood was not associated with all-cause mortality . However, drinking well  and surface water  around the age of 60 years, but not drinking spring , was associated with all-cause mortality. Furthermore, drinking surface water at present was associated with a lower all-cause mortality   .HR: 1.055, 95% CI: 1.007–1.106, P = 0.026; HR: 1.112, 95% CI: 1.024–1.207, P= 012, respectively). The results stratified by living areas were compared with those in the total sample.HR: 1.280, 95% CI: 0.948–1.729, P < 0.107). Furthermore, drinking spring around the age of 60 years and drinking well at present were associated with a lower CVD mortality .HR: 0.461, 95% CI: 0.251–0.846, P = 0.013). In females, subjects drinking well at present had a lower CVD mortality   .HR: 0.828, 95% CI: 0.702–0.978, P = 0.026; HR: 0.688, 95% CI: 0.550–0.861, P = 0.001, respectively)  .HR: 1.132, 95% CI: 1.076–1.191, P < 0.001; HR: 1.202, 95% CI: 1.130–1.278, P < 0.001; and HR: 1.043, 95% CI: 1.006–1.082, P = 0.022, respectively), which was consistent with the main results. Meanwhile, subjects drinking spring around the age of 60 years and drinking well at present had a lower CVD mortality , which was comparable with the main results  can be found below: The studies involving human participants were reviewed and approved by the Institutional Review Board, Duke University (Pro00062871) and the Biomedical Ethics Committee, Peking University (IRB00001052–13074). The patients/participants provided their written informed consent to participate in this study.XL contributed to writing the original draft. ZP contributed to reviewing and editing the draft. ZZ contributed to data curation and formal analysis. YZ contributed to data and results interpretation. YC contributed to the study design and conceptualization. All authors read and approved the final manuscript.This study was supported by the National Natural Science Foundation of China (81903416).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


This current study explores the influence of learners’ working memory capacity (WMC) on the facilitation effect of an instructor’s presence during video lectures. Sixty-four undergraduates were classified into high and low WMC groups based on their performance in an operation span task. They watched three types of video lectures on unfamiliar topics in a random order: video lectures with an instructor’s voiceover but without presence (VN), video lectures with the instructor’s face picture (VP), and video lectures with the same instructor talking (VV). We collected their eye movement data during the video lectures and their learning performance in the comprehension tests following each video. Two-way ANOVA and post-hoc analyses showed that the instructor’s presence significantly improved comprehension performance in only the low WMC group. They allocated more attention to the instructor’s face picture and talking head than the high WMC group. Our results highlight the value of the instructor’s presence as a social cue in video lectures, which is particularly beneficial for learners with a low WMC. As lecture videos become popular, research on the effectiveness of video design is expanding. An instructor’s presence in a video, as one of the most significant features of effective video design, has received increasing attention in recent years. Some studies demonstrated that the instructor’s presence promotes learning and induces positive affective arousal e.g., . As MayeHowever, a few studies showed that the instructor’s presence might distract and overburden the learners e.g., . LearnerSo far, most research on the instructor presence effect has focused on the effectiveness of the video lecture design  e.g., , 2022. OInstructional video design should guide learners’ cognitive processes to integrate new information with their existing knowledge without overloading their limited WMC e.g., . LearnerOnline video learning lacks direct student-instructor interactions, compared with traditional face-to-face classroom instruction. Is the instructor’s presence in video lectures a distraction or an aid for learners with limited WMC? The social agency theory  postulatAlthough the instructor’s presence may foster generative processing, it could also increase extraneous processing and leave less cognitive capacity for essential processing. Further, the instructor’s onscreen presence might distract learners, causing their attention to be constantly shifted from the content to the instructor and then back again. Frequent attention-switching will overload learners  and may Similarly to the conflicting theoretical propositions, the empirical evidence for the instructor presence effect is also mixed. As mentioned earlier, many studies have shown that the instructor’s presence in video lectures improves students’ learning performance e.g.,  and affeVariations in video lectures may cause contradictory results in existing research on the instructor presence effect: duration, learning domain, human embodiment, and study settings . While nThe limited WMC has been postulated as a key tenet of the cognitive load theory  and the The use of eye-tracking technology in learning research , particuAn increasing number of researchers have utilized eye-tracking to investigate the instructor presence effect e.g., . Using eDespite the growing number of studies using the eye-tracking technique to explore the learning process of multimedia learning, little is known about the modulation of learners’ WMC in terms of their eye movements during the learning process . The current eye-tracking study explores the influence of an instructor’s presence on learners’ visual attention allocation in video lectures.The current study examined the modulation of learners’ WMC on their learning process and learning performance when watching instructor-present/instructor-absent video lectures. For the vast majority of video-conferencing platforms, such as Zoom meetings, online instructors can easily switch on their cameras to be continuously present throughout lectures. In the current study, we presented all participants with three types of video formats: video lectures with an instructor’s narration but without their presence (VN), video lectures with the instructor’s neutral face image (a static headshot) (VP), and video lectures with the same instructor’s talking head (VV) embedded to explain the content in a synchronized manner. Each participant watched three videos in each of the three conditions , and their eye movements were recorded simultaneously. A comprehension test followed each video to assess participants’ learning performance. Since WM is typically measured by complex memory span tasks , we usedWe hypothesized that the instructor presence effect would interact with individual differences in WMC to affect participants’ learning outcomes and attention allocation. Specifically, we expected learners with a high WMC would perform better in instructor-present videos than those with a low WMC. The low-WMC learners might allocate more attention to the presented instructor than their high-WMC counterparts. This study adopted a three-by-two factorial mixed design, with video type  as a within-subjects variable and WMC (high WMC and low WMC) as a between-subjects variable. Unlike previous studies that usually set the video type as a between-subjects variable, this study adopted a within-subject design to eliminate the subject variance among video formats. All participants were requested to watch nine videos, with three in each of the three conditions. We randomized the presentation sequence of the nine videos across the participants to minimize fatigue and practice effects. Eye movement data were collected via an Eyelink 1000 eye tracker  in the desktop-mounted mode. Participants sat approximately 60 cm from the screen and listened to the video via headphones connected to the computer. Sixty-four Chinese undergraduateshttps://zh.wikipedia.org/wiki/Wikipedia (accessed on 2 May 2021)). Each text comprised approximately 400 words. Twenty Chinese college students, who were not involved in the eye-tracking experiment, evaluated the familiarity of each topic on a five-point Likert scale from 1  to 5 (very familiar). They also rated the difficulty of its content using a five-point Likert scale from 1  to 5 (very difficult). Based on their self-reports, the topics were unfamiliar (mean rating scores = 2.03 ± 1.22) and not difficult (mean rating scores = 2.23 ± 0.93). In the current study, all videos were developed by the authors of this study  recorded all of the videos in three different formats. In the VN condition, only the content  and the instructor’s narration were presented (as a voiceover in the background). In the VP condition, a picture of the instructor’s neutral face was presented in the upper-right corner—as the default talking head in Zoom meetings—along with the written text and a topic-related picture. In the VV condition, a video window of the instructor’s talking head was placed in the same location as the instructor’s picture in the VP condition see b. The viThe comprehension test included eight true/false judgment questions following each video. The test assessed the participant’s retention of the content covered in the video. The comprehension questions would appear successively in the same window as the lecture video as soon as the video ended c. ParticFollowing the comprehension test of each video, participants rated their familiarity with the video topic and the difficulty level of its content  to investigate the learners’ visual attention distribution: the text, the topic-related picture, and the instructor. The size  and the location of each of the AOIs were the same across all video formats. In each AOI, we examined the participants’ fixation count percentage  and dwell time percentage . Additionally, as in previous research , we examWe adopted the automated operation span test  to measut-test showed that the high WMC group and the low WMC group differed significantly in their Ospan scores .We adopted the mean-split approach for grouping based on the Ospan scores. Thirty-two participants who scored higher than the mean score were included in the high WMC group, and 32 participants who scored lower than the mean were admitted to the low WMC group. An independent sample After signing the informed consent form, participants were tested individually in an eye-tracking room. A nine-point calibration procedure was applied prior to watching each video. Immediately after watching each video, participants were instructed to answer eight comprehension questions (by pressing the yes/no buttons on the keyboard). They then rated the familiarity and difficulty of each video . Participants watched the nine videos in a randomized order. p < 0.001, η2 = 0.13) but not WMC  = 1.87, p = 0.176, η2 = 0.029). However, the interaction between the video type and WMC was significant  = 4.45, p = 0.014, η2 = 0.06). Multiple comparison tests (with the Bonferroni adjustment) showed that for the low WMC group, the instructor’s presence (either in the format of a face picture (VP) or a talking head (VV)) led to a better learning performance (ps < 0.05), while for those with a high WMC, the videos with or without the instructor’s presence resulted in the same comprehension performance (ps > 0.05). Moreover, the high WMC group achieved significantly higher comprehension scores than the low WMC group in the instructor-absent video lectures (VN) (p < 0.01). In the instructor-present conditions (VP and VV), the two groups showed a similar comprehension performance. We conducted a series of independent samples t-tests to examine whether learners with different WMCs might differ in their attention distribution in each video type condition .ps > 0.05). Regardless of their WMC, all participants distributed their attention similarly when there was no instructor in the video lecture: more than 86% of their time was allocated to the text while watching the instructor-absent videos  (p = 0.058)   and marg= 0.058) . Finallyp < 0.05) (p < 0.05)   and dwel < 0.05) . In addiLearners have a limited WMC, which assists in generative, extraneous, and essential multimedia learning processing. The instructor’s presence as a social cue in video lectures may facilitate the generative processing. It may also induce extraneous processing that overloads the learner’s WMC and impairs their learning. The present eye-tracking study explored the modulation of the learners’ WMC on the instructor presence effect in video lectures. We found that learners with a low WMC, compared to those with a high WMC, spent more time fixating on the onscreen instructor and benefited more from the instructor’s presence. The two groups were significantly different in their learning performance of the instructor-absent videos. However, with an instructor’s face picture (the VP condition) or talking head (the VV condition), the low-WMC participants caught up with their high-WMC peers. Our findings provide empirical evidence for the instructor presence effect and suggest that the instructor’s presence in video lectures is vital for low WMC learners.In the present study, learners watched video lectures on unfamiliar topics, which were not difficult based on their self-reports. The learning outcome indicated by the comprehension scores revealed that adding an instructor to the video lectures was advantageous. As hypothesized, the individual differences in WMC modulate the instructor presence effect. However, contrary to our prediction, the onscreen instructor (in the VP and VV conditions) reinforced the comprehension performance of the low WMC group but not the high WMPC group. Eye-tracking data analyses revealed that the low WMC group focused significantly more on the instructor when viewing instructor-present videos than the high WMC group.According to the social agency theory , the onsFor learners with a low WMC, the onscreen instructor seemed to be a conducive tool for understanding video lectures. Low WMC learners performed significantly worse than the high WMC group in the instructor-absent videos. Such group differences, however, disappeared in the instructor-present videos. In other words, even though the instructor is only displayed as a static face image on the screen , people with a low WMC were more sensitive to their instructor’s presence and profited more from it. Despite having a low WMC, they were not overburdened by the instructor’s presence. Thus, contrary to what we had predicted, the low WMC group was facilitated, but not hindered, by the presence of the instructor in video lectures. Interestingly, we found that the instructor’s neutral face image as a low-embodied social cue facilitated learning in our low WMC group, which is consistent with a recent study by In sum, our findings support the facilitative function of an instructor’s presence on learning performance  and haveAs we hypothesized, the presented instructor attracted more attention from the low WMC group, as evidenced by more fixations and a longer dwell time on the instructor AOI compared to the high WMC group . ResearcOur results also demonstrated that students paid greater attention to the instructor’s talking head (in the VV condition) than to the instructor’s face image (in the VP condition), regardless of their WMCs. The high and low WMC groups gave the instructor’s face image 2.5% and 3.71% of their attention in video lectures. When the instructor was presented in the form of a talking head (VV), these percentages rocketed to 9.08% and 14.66% see . CompareIn the current study, the low WMC group was the only one to experience the instructor presence effect. For them, the additional onscreen instructor  was not distracting but retained its positive value as a social cue. That is to say, the supposedly disadvantaged group (learners with a low WMC) managed to reap the instructor-presence benefits in video lectures. Our results align with earlier studies on learners’ prior knowledge. The poor WMC group’s comprehension performance was unaffected by the attention paid to the instructor on the screen. The videos in the current study might not be challenging even for low-WMC learners. They might not have an overburdened cognitive load in this low-load learning context. They subconsciously took advantage of the instructor’s onscreen presence as a valuable social cue to compensate for their inadequate learning ability in video learning. Our findings support this proposal by demonstrating that appealing details promote learning in low-load situations .Finally, our findings provide insights for future research into the underlying mechanisms of instructor-present video learning. For instance, the instructor’s presence provides social cues  and linguistic cues . Thus, which of these cues is more helpful for learning, particularly for those with low cognitive abilities? Is the social presence offered by the social cues  or the more direct assistance from the linguistic cues  more beneficial? The cognitive process behind the instructor presence effect in low WMC learners may be clarified further in subsequent studies using more advanced instructional designs or techniques.To our knowledge, this is the first study to investigate how learning from instructor-presented video lectures is related to learner variations in WMC. Our results showed that learners’ WMC moderated the instructor presence effect. In this study, learners with a low WMC benefited more from the addition of an instructor to the video lecture than did learners with high cognitive capacities. The results offer evidence against the claim that learners are distracted by the onscreen instructor. Even those students who were thought to be prone to distractions in this study did not experience any detrimental effects from paying attention to the presented instructor. The teacher should, therefore, be visible on the video screen to promote social presence, which is advantageous for all learners in general and those with a low WMC in particular. This is the direct practical implication for video lecture designers. The results of the current study further highlight the importance of evaluating the differential effects of learners’ cognitively based individual characteristics on their learning outcomes and attention allocation in online video lectures. Further research is still needed to determine which learner types will gain the most from watching the onscreen instructor.Although the study added new evidence for the benefits of a teacher’s presence in video lectures, it is crucial to note that our findings need to be interpreted with some caution. First, in the current study, we adopted a within-subjects design. As pointed out by an anonymous reviewer, though the order of video presentation was randomized, it was unlikely to completely eliminate the potential carry-over effects. Future research can address this problem by adopting a different approach, such as a between-subjects design with matched participants to further investigate the issue. Second, we assessed participants’ prior knowledge of each video topic using a five-point Likert scale rather than a more objective prior knowledge test. Third, participants self-reported that each video was easy and moderate to comprehend. Each video’s low-load context may make it less likely to tax students’ meager attentional resources. Future research could investigate whether an instructor’s presence in a high-load situation causes varying magnitudes of the instruction presence effect in learners with various WMCs. The difficulty of the topics could be included as a moderating variable. Finally, the study’s comprehension check exam was a straightforward retention test. As The current study explored the influence of learners’ WMC on their learning performance in video lectures with an instructor either present or absent. We found that the presence of an instructor, particularly the talking head of the instructor, was beneficial for video lecture learning, particularly for learners with a low WMC. Future research should examine learners with various WMCs in high-load video lectures and examine diverse learning outcomes with neurological techniques.