The U.S. agri-food system is a driver of climate change and other impacts. In order to achieve environmental targets that limit global mean temperature rise ≤2 °C, a shift in American dietary patterns is critical. The purpose of this study was twofold: (1) to determine the environmental impact  related to consumption of five U.S. dietary patterns , and (2) to determine the specific impact of each food group in each dietary pattern on the three environmental indicators. This study utilized existing datasets to synthesize information related to the study’s environmental indicators and food production and connected these data to the current U.S. diet and the USDA-defined diets. Results indicate that the three omnivore diets contributed the greatest to GHG emissions, land use and water use. The Vegan diet scored the lowest across all indicators, although the water required for plant-based protein nearly offset other water gains. For the omnivore diets, red meat and dairy milk contributed the most to each environmental indicator. By considering sustainability as well as health outcomes in their recommendations in the Dietary Guidelines, the USDA can have a critical role in shifting diets necessary to alter climate change trends. When all people have access to “sufficient, safe and nutritious food that meets their dietary needs and food preferences for an active and healthy life,” our world will be considered food secure . UnfortuFood systems are the systems which include all the processes and infrastructure involved in feeding a population: production or growing of food, harvesting, processing, packaging, transporting, marketing, consumption, distribution and disposal of food and food-related items . It alsoAt a global level, it is estimated that about 34% of total greenhouse gas emissions are attributable to the global food system . The GHGUnited States (U.S.) agriculture has significant GHG emissions and use of water and land use. Agriculture and forestry together are estimated to account for 11.2 percent of GHG emissions, including methane emissions produced by raising livestock, and carbon dioxide emissions associated with agricultural energy consumption . In termThe decreasing availability and increasing cost of water and land for agricultural use, along with increasing temperatures and intense weather patterns threaten food security for future generations ,15,16. GAlthough sustainable diets can be defined in multiple ways, the Food and Agriculture Organization (FAO) has a comprehensive definition of sustainable diets that encompasses low environmental impact, nutritional adequacy, cultural acceptability, optimization of human resources, and economic affordability . It furtWhile the EAT-Lancet report is based on a robust literature base on the examination of sustainable diets, much of this literature has been conducted in European countries ,19,23. TAdditionally, several scholars have advocated taking a multi-level approach to assessing the role of the individual, household, and policy level when examining these issues . One wayTherefore, the overarching purpose of this study was to determine the environmental impact, defined as land use, water use, and GHG emissions of five different U.S. dietary patterns using U.S. environmental data. The five dietary patterns include the Current U.S., the Healthy U.S., Healthy Mediterranean, Healthy Vegetarian, and Vegan dietary pattern at the 2000-calorie level as defined by the United States Department of Agriculture (USDA). In addition, the specific impact of each food subgroup  within each dietary pattern on the three environmental indicators was also examined.A cross-sectional study design that utilized existing datasets for all variables was employed to achieve the following objectives of the study: (1) collect and synthesize data related to multiple environmental burdens and food production, (2) connect these data to the current U.S. diet and the USDA-defined diets, and (3) evaluate trade-offs across environmental burdens associated with these diets. All data were sourced from national datasets or peer-reviewed literature. The scope and functionality of each dataset utilized in this study is described below. This study was approved by the Institutional Review Board of the University of Texas Health Science Center (Study No. HSC-SPH-16-0766).Dietary patterns that were assessed in this study were developed by the USDA to assist individuals in adhering to dietary guideline recommendations ,33. SincThe five dietary patterns that were assessed in this study included the Current U.S. diet as well as four recommended dietary patterns as described in the 2020 versions of USDA Dietary Guidelines of Americans: Healthy U.S. (2020), Healthy Mediterranean (2020), Healthy Vegetarian (2020). Lastly, we also examined the Vegan recommended dietary pattern as described in the 2010 Dietary Guidelines as it was not included in the 2020 version ,33. TablRecommended amounts and limits in the USDA dietary patterns depend on 12 different calorie levels based on median length and body weight reference individuals, ranging from 1000 calories to 3200 calories per day . The 2002/kg), water use (L/kg), and GHG emissions  associated with each specific food item included in each of the five dietary patterns.For each of our three environmental indicators , we obtained national data sets which provided us with the environmental impact of a wide coverage of specific foods. Using the different data sets as described below, we developed a database with land use  are described below, followed by a discussion of how data for secondary  or processed  foods are derived from primary information.For the analysis of this study, we used a life-cycle assessment (LCA) approach. In order to deliver food to consumers, food systems go through specific cycles/stages which include the resources necessary to produce crops, feeding them to animals, processing foods, transporting them, and so forth. The data sets we used for the water and land use capture environmental inputs that occur on the farm but do not capture post-farm stages, such as processing, distributing, or use by consumers . However, for water use and land use, the on-farm stage (irrigation and cultivation in the field) is by far the dominant contributor to overall life cycle resource flows . In cont2/kg). As yield varies across the country as a function of climate, cropping practices, etc., production was used as a weight to calculate national values.Land use data were taken from the U.S. Census , which cWater use data was obtained from the Pfister and Bayer data set . AlthougAs harvested crops are used as food products , processed to make food products , or provided as rations to livestock, we adjusted the primary data described above using the following approaches. Conversion from wet matter to dry matter is from the FAO Global Livestock Environmental Assessment Model (GLEAM) . ChangesTo calculate GHG emissions we used dataFIELD, a database of GHG life cycle emissions for a variety of foods . This suThe USDA diet data are presented in terms of food groups and food subgroups. For example, the food group vegetables, is broken down into subgroups such as leafy green vegetables, dark green vegetables, starchy vegetables, etc. In order to connect these food groups and food subgroups to the specific commodities and foods for which environmental data are available, we used the following approach.First, subgroups were broken down to specific foods according to typical U.S. consumption patterns using the USDA’s Food Patterns and Percent Consumption (FPPC) database, which describes the consumption-based fraction that individual foods  contribute to overall food subgroups  . Data abThe Food Pattern Equivalents Database (FPED) was used to connect the food patterns to the crop data. The FPED relates masses of retail foods to the food patterns described in the diets . These mWe note that not all of the foods specified in the consumption patterns were reported in a given environmental inventory database. For example, the USDA Census may report data for broccoli and lettuce, but not other dark green vegetables. In priority, we looked for reasonable substitutes . When choosing a substitute was not feasible, we used a production-weighted average of the subgroup of foods that were reported. In this way, a diet pattern was decomposed into specific food items for which substitutes or subgroup averages were available. The environmental inventory data associated with these specific food items were then summed within groups and aggregated back to the diet level.The results present the land, water, and GHG impacts for each of the five different dietary patterns. The drivers for the intra- and inter-diet trends shown in each dietary pattern are also presented.2 and 5.12 m2, respectfully) with the Healthy Mediterranean dietary pattern using slightly less land (4.88 m2) (2). The amount of land used to produce red meat for each of the three omnivore diets is greater than the total amount (1.82 m2) of the lowest land-using dietary pattern (Vegan). Other significant food group contributors to land use in the omnivore diets examined are the dairy categories, specifically milk (0.26–0.55 m2) and cheese (0.26–0.55 m2); and grains, both refined (0.35–0.68 m2) and whole (0.13–0.45 m2). The U.S. Current diet is characterized by higher refined grained consumption therefore refined grains contribute more to land use in this dietary pattern. For the Vegan diet, refined (0.35 m2) and whole grains (0.45 m2) contribute the most to land use.Our results show that the omnivore dietary patterns  require more land use than those that include only plant-based foods . The Current U.S. and the Healthy U.S. dietary patterns are very closely associated with the most land use per day (5.17 m4.88 m2) . The majOur study found the Healthy U.S. dietary pattern requires the most water to produce (514 L/day), followed closely by the Healthy Mediterranean dietary pattern (487 L/day) . The maj2 eq/day) (2 eq/day) and Current U.S. (3.19 CO2 eq/day) dietary patterns. The lowest GHG-emitting diet patterns are the Vegan dietary pattern (0.72 CO2 eq/day) followed by the Healthy Vegetarian pattern (1.57 CO2 eq/day). GHG emissions related to the Mediterranean dietary pattern are 4.75 times greater than the Vegan dietary pattern’s emissions. Red meat is the highest contributing food group to all the omnivore dietary patterns related GHG emissions (1.83 CO2 eq/day–1.36 CO2 eq/day), contributing 2.5 times as much GHG emissions in the Current U.S. dietary pattern compared to total GHG emissions related to the Vegan diet. Low Omega-3 fish contributed 1/5th of total GHG emissions for the Mediterranean diet. For the Healthy Vegetarian dietary pattern, 40% of related GHG emissions can be attributed to dairy milk. We found the three omnivore dietary patterns studied are the greatest contributors to GHG emissions, with the Mediterranean dietary pattern contributing to the greatest number of GHG emissions , our results indicate that the three omnivore diets studied have the greatest environmental impact and are related to the highest GHG emissions, land use and water use. The two vegetarian diets have the lowest impact on the environmental indicators studied, with the Vegan dietary pattern scoring the lowest for all three indicators. These findings correspond with previous studies conducted in the U.S. and internationally regarding the impact of diets on the environment ,53. HoweWhen examining the different food groups that contribute the most to GHG emissions, land use and water use, we note some distinct patterns. In the case of the three omnivore diets, the food group that contributes the greatest percentage to each of the environmental indicators in our study is red meat. Dairy milk is also of concern for all three indicators, and Low Omega-3 fish is a high contributor to GHG emissions. For the two dietary patterns that do not include animal protein, the dairy food group and the nuts/seeds food group are the food groups that score the highest for GHG emissions. For water use, the nuts/seeds group are the largest contributors for the Vegan pattern, while dairy milk is the largest contributor in the Vegetarian diet. Lastly, for land use, for the Vegetarian diet, dairy milk, dairy cheese, and whole grains are the largest contributors while for the Vegan diet, whole grains and refined grains are the largest contributors. However, the food groups that are the largest contributors to the three environmental indicators in the Vegetarian and Vegan diets contribute much less to GHG emissions, land use and water use than the food groups that are the highest contributors to the omnivore dietary patterns.2 eq, it has a relatively high warming potential and is considered more detrimental to the environment than CO2 eq.Previous studies have found similar results with red meat/beef being the highest contributor to several critical environmental indicators . As ener2 eq per day per capita, to 2.45 kg CO2 eq per day per capita, and average beef consumption declined 40% per capita, which contributed to more than 50% of the observed GHG savings in the diet over the study period [Our findings suggest that the most impactful diet-related change that Americans can make towards a more sustainable diet is a shift towards a Vegetarian or Vegan diet and reducing the consumption of red meat and potentially dairy products . These ky period . Men agey period . HoweverInterestingly, the diet which is recommended by the U.S. Dietary Guidelines for all Americans to follow  does not recommend a substantial decrease in red meat. As a result, the Healthy U.S. dietary pattern has a greater impact on GHG emissions and land use than the Current dietary pattern. These results are congruent with several other studies examining the potential negative environmental impacts from switching from the current to a USDA recommended omnivore diet ,60,61. GAmericans and American politicians struggle to see the connection between individual-level behaviors and policies contributing to climate change . PerhapsAccording to the Socio-Ecological Model , potentiPast studies suggest that individual dietary behavior change can best be accomplished through policy change, however actions by governments must be paired by societal support to be effective . A recenAdditionally, future research opportunities exist to ask these questions we have asked in lower and middle-income countries, where persisting research gaps have been identified  and a neThere are certain limitations to the approaches utilized in the analyses for this study. The land and water use data in this study captures only water and land used in farm production and not post-farm transportation, manufacturing, etc. Water use for animal production, such as beef, does not include the water consumed by animals. However, the datasets we utilized were the most comprehensive data sets available. The lack of available data sets highlights the need for data sets that also include required land and water use for processing, manufacturing, and distribution of individual foods. A second limitation is that the agricultural data are based on national averages that consider regional variation but are not differentiated by agricultural practice , which may vary in water, land, and machinery usage. At this time, however, organic practices are not representative of the entire country, as certified organic cropland and pasture accounted for only around 1% of the U.S. total farmland in 2011 .We also did not take into account the variation between diets in different states, nor did we conduct a sensitivity analysis for the surrogates/proxies that we chose for the food items. Although these differentiated analyses would provide data for an interesting and useful future study, they require data that currently is not available.Lastly, another limitation is that GHG emissions, water use and land use related to the management of food waste were not considered in this analysis. Without taking waste into account, our analysis underestimates the true environmental impact for all foods.Many of our errors should be systematic across diets and, thus, are expected to have a minimal impact. Therefore, relative trends from our results, rather than absolute numbers or absolute differences, should be emphasized. An analysis that includes statistical precision and error has not been conducted and is an area for future research. Without having examined statistical uncertainty, all assertions about relative benefits or impacts of different diets are based on point estimates and should be considered interim conclusions.This study is a unique environmental assessment of U.S. dietary patterns, as it uses U.S. data and incorporates multiple environmental variables simultaneously. The results provide more environmental data, beyond GHGs, to facilitate a deeper reflection on the potential trade-offs of dietary patterns. The findings indicate that by switching to dietary patterns characterized by less red meat, such as the Vegan and Healthy Vegetarian-Style dietary patterns, less land use, water use, and GHG emissions will be the per-capita result for food production, as based on current practices. These implications call for an examination of agricultural practices and policy and policies in schools and communities as well as creative health promotion strategies to reduce barriers and increase consumption of foods that are more environmentally friendly .There are many environmental, economic, and social externalities that were not included in this analysis but would add to a more holistic snapshot of the sustainability of diets. To meet the FAO’s definition of sustainable diets, nutritional adequacy, cultural acceptability, optimization of human resources, and economic affordability also need to be considered . There iThis study has important policy and health promotion implications. Shifting towards more plant-based diets could result in reduced environmental impact. Reduced water, land use and GHG emissions could improve household food security in the U.S. and global food security for a growing population. Continued improvement in production methods for animal-sourced proteins, namely red meat, dairy milk and cheeses and Low omega-3 fish will be of interest. However, improving production methods for plant-based proteins, e.g., water use for almonds, could also have positive implications for creating more sustainable diets, thus greater food security for the planet. More work is needed in understanding how to encourage individuals to adopt sustainable dietary behaviors, such as more plant-based diets, to foster greater household food security in the U.S. and globally.


Metagenomics next-generation sequencing (mNGS) has been increasingly used in the clinic, which provides a powerful tool for the etiological diagnosis of infectious diseases. Precise treatment can be carried out according to the positive mNGS results. However, the role of negative results of mNGS remains poorly defined in clinical practice.The results of 1,021 samples from patients who received the mNGS test at Zhongshan Hospital, Fudan University, between January 2019 and December 2019 were analyzed.Mycobacterium, Aspergillus, and Mycoplasma ranked as the top 3 microorganisms on the undetected pathogen list.There were 308 samples (30.17%) of negative results included in the current study. The top 2 types of negative samples were blood (130/308) and tissue (63/308), which also accounted for the highest negative proportion in diseases. Sputum and bronchoalveolar lavage fluid (BALF) were more likely to have positive results. In false-negative results (defined as negative in mNGS test but reported positive in other sample types or assays), 118 samples were found when compared to regular microbiological assays. The negative predictive value (NPV) of mNGS was 95.79%  as compared to culture and smear. The present data indicate that when the mNGS test is negative, the negative prediction accuracy rate of the original specimen is significant. However, other laboratory assays results and clinical presentations should always be carefully considered prior to drawing a diagnosis. Infectious diseases are caused by a variety of pathogens, which lead to systemic or local inflammation  with sigWith the development of gene detection technology, metagenomics next-generation sequencing (mNGS) has been increasingly used in the clinic, which provides a powerful tool for the etiological diagnosis of infectious diseases . As it dWhen the mNGS test is positive, precise treatment could be carried out soundly according to the actual clinical situation. However, the role of negative results of mNGS remains poorly defined in clinical practice. As such, the present study is aimed to evaluate the clinical value of negative mNGS results and to provide evidence for its proper applications.A total of 1,021 samples from hospitalized patients who received mNGS test at Zhongshan Hospital, Fudan University, from January 2019 to December 2019 were collected and reviewed. Results of regular clinical assays of these samples were also collected at the same time. The study was approved by the institutional review board of Zhongshan Hospital, Fudan University (#B2021-694R). Written informed consent was obtained from each patient prior to the enrollment.Samples were collected at standard procedures according to their various types including blood, sputum, bronchoalveolar lavage fluid (BALF), and tissue. Nucleic acid was extracted and fragmented into DNA fragments, and then these fragments were end-repaired, barcoded, and amplified to be qualified libraries. Libraries were sequenced on the BGISEQ-50 platform. Sequencing data were compared to human references, then human sequence reads were removed, and nonhuman sequence reads were further filtered and compared to databases . Final data including stringent mapped reads number (SMRN), coverage rate (CovRate), relative abundance (Re_Abu), and sequencing depth were analyzed and reported.p-Values <0.05 were considered significant, and all tests were two-tailed.Continuous data are shown as mean values ± SE. Student’s t-test was used to measure the differences in variables, where appropriate. Data analysis was performed using SPSS 16.0 software. A total of 1,021 samples were included in the current study, with 713 samples (69.83%) of positive results and 308 samples (30.17%) of negative results Table 1.Blood and tissue accounted for the highest negative proportion in different common infectious diseases as listed in d-glucan test (G test), and galactomannan test (GM test). In addition, parasite detection was all negative in all samples suspected of parasite infection, so it was not listed. All the results of other conventional assays were collected and sampled at the same time as mNGS. However, the paired-culture test was the basic premise of the comparison. Therefore, 23 cases were excluded because they had no paired-culture results. The remaining 285 cases were further classified in In order to study the influence of sample type on mNGS results, true negative (TN) and false negative (FN) were defined. Laboratory results that were negative in all sample types and all assays were defined as TN, and laboratory results that were positive in some sample types or some assays were defined as FN. Conventional assays included in our study were culture, smear, TSPOT.TB (TSPOT), cryptococcal antigen (CrAg), immunoassay, 1-3-β-According to the definition and statistical results, TN was 58.6% (167/285) and FN was 41.4% (118/285). FN positively differed among culture and smear in the same specimen, culture, smear, and mNGS of other sample types and other assays as listed in Pseudomonas aeruginosa detected in sample 21 was in the colonized microorganism list, and Staphylococcus epidermidis detected in sample 203 was in the background list. Staphylococcus aureus in sample 38, P. aeruginosa in sample 118, Staphylococcus hominis in sample 153, and Actinomyces in sample 178 were not shown in the report but could be found in the database.Among FN cases, there were 12 paired-culture positive cases Figure 3As shown in Mycobacterium tuberculosis, CrAg for Cryptococcus, G test and GM test for fungus, and immunoassay for mycoplasma, Legionella, etc. There were 48 cases that were positive in the TSPOT test, but in the mNGS test, no Mycobacterium was detected in these cases, even in the database. G test and GM test were effectively used to detect Aspergillus , neutrophil (Neut), lymphocyte (Lymph), eosinophilia (EO), C-reactive protein (CRP), procalcitonin (PCT), interleukin-6 (IL-6), and erythrocyte sedimentation rate (ESR) of all the negative samples were collected. The disease groups with insufficient data for statistical analysis were removed. The comparison of WBC, Neut, Lymph, and EO between TN and FN is shown in In the present study, 1,021 mNGS reports were analyzed to evaluate the role of mNGS in clinical practice, in particular when the results were negative. The overall negative rate was 30.17%. Blood and tissue had the most frequent negative reports, accounting for 42.21% and 20.45%, respectively. According to the negative rate of all samples, blood (38.12%) and tissue (31.66%) also accounted for the third and fourth place of the negative rate. In addition, according to the distribution of diseases, the negative proportion of blood and tissue in various diseases was greater than that of other sample types.M. tuberculosis in mNGS vs. culture and smear  in the current study, which implies that when a negative mNGS result is reported, the negative prediction accuracy rate of the original specimen is high. The NPV of another study was 100%  for bacteria, 72.7%  for fungi, and 100%  for nd smear . Howeverrculosis , especiaSome pathogens with low SMRN or SMRNG were excluded in the report, and some pathogens were identified as colonized or background microorganisms. When the report is negative and there is a suspected specific pathogen infection in the clinic, it can be traced back to the original database for a query.The causes of FN both in the clinic and in the laboratory were analyzed. The first is the selection of sample types in the clinic. Clinicians should have a comprehensive consideration of the sample type for the mNGS test including the clinical symptoms, the location, and the type of the infection . HoweverSecond, the correlation between the status of infection and FN was explored. Complete blood count, CRP, PCT, IL-6, and ESR were collected on the day of examination of mNGS to determine the differences between FN and TN. There were no statistical differences between these two groups, which was consistent with another study . The datThird, the experimental data were compared to analyze the false-negative results in the experiment. There were differences between FN and TN groups in DNA concentration of sputum and library concentration of blood. When there is lower DNA concentration in sputum samples and lower library concentration in blood emerged, we should be vigilant. The experimental steps should first make sure that each step is double-checked. When it turned into a negative report, it should be returned to the clinic, and clinicians should be reminded to make a comprehensive diagnosis and judgment. There were no statistical differences between FN and TN groups in the sequencing step. Therefore, increasing the amount of data is meaningless for false-negative samples. Moreover, the host sequence ratio had no reference significance in the judgment of false negatives.Mycobacterium and Aspergillus were found to be the two most undetected pathogens. A possible explanation is that the cell walls of these pathogens were both thick and elaborate , Key Subject Construction Program of Shanghai Health Administrative Authority (ZK2019B30), the Shanghai Engineering Research Center of Tumor Multi-Target Gene Diagnosis (20DZ2254300), and Innovation Project funded by Science and Technology Commission of Jinshan District (2018-3-5). All authors obtained permission to acknowledge all those mentioned in the 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.


Water pipe smoking has become a global public health problem as its popularity increased over time, especially among youth. The objective of our study was to estimate water pipe tobacco smoking prevalence and to assess socioeconomic factors associated with ever water pipe smoking by public and private university students in Ankara, Turkey.n=2685) and private (n=2485) university students via an online questionnaire on demographics and water pipe consumption patterns. For every student in the sample, a socioeconomic status index was calculated using principal component analysis. Binary logistic regressions for the outcome variable of ever-using water pipe yielded estimates of adjusted odds ratios (aORs) for the associated factors such as the respondent’s age, gender, university type, and socioeconomic status.This descriptive study was based on a survey conducted among public (p=0.008). On average, private university students had higher socioeconomic status than public university students , financial support from family ), also demonstrated by a higher socioeconomic status index. Being a private university student , older , male , as well as having greater financial resources, such as having access to a car , or having income support from family , were associated with ever-using water pipe. A higher SES index was significantly associated with higher odds of ever using water pipe among both private  and public university  students.The prevalence of ever use of water pipe was 69.1% (95% CI: 67.2-70.9%) among private and 59.1% (95% CI: 57.2-60.9%) among public university students. A substantial share of ever users were current users (25.5% in private versus 21.6% in public, Water pipe smoking was common in both public and private universities; however, private university students had higher odds of ever using water pipe. There is an urgent need to implement evidence-based interventions, taking into account the socioeconomic status of young adults, to prevent them from water pipe smoking.The online version contains supplementary material available at 10.1186/s12889-022-13616-9. The consumption of tobacco in a water pipe (WP)  is a serious public health problem that is known to be associated with several adverse health outcomes such as respiratory diseases, bronchitis, oral cancer, lung cancer, low birth weight, metabolic syndrome, and cardiovascular diseases . WP use WP smoking in young people is worrying because of the economic burden it can generate in the long term by reducing productivity and imposing health costs. Therefore, it is important to understand the correlates of WP use among youth. Unfortunately, WP smoking has increased its popularity among adolescents and youth in the world. According to Global Youth Tobacco Survey, in 34 of the 100 sites surveyed, the use of tobacco products other than cigarettes increased, which was largely attributed to rising WP use .In Turkey, tobacco control is an important part of public health policy. The first law in 1996 aimed to protect people from tobacco smoke in governmental buildings, and health and educational institutions. The ban was broadened in 2008 to include school premises, all tourism and hospitality workplaces, and commercial taxis. Then, the hospitality sectors started to promote WP service especially to young people and tobacco smokers at cafés or “WP cafés”. The industry used the common belief in the community that WP smoking is less harmful than cigarette smoking because the harmful particles of WP smoke is filtered into the water. They also offered WP with flavored tobacco to enrich taste and smell. Young people began to enjoy smoking WP with their friends for hours and WP cafés became popular locations for socialization , 11.In Turkey, there were 129 public (state) universities and 72 private foundation universities in the 2018-19 academic year  , and to assess socioeconomic factors associated with ever WP smoking by public and private university students in Ankara, Turkey. The main contribution is to compare students in the two types of universities, namely private foundation universities and public universities.A cross-sectional (descriptive) online survey was conducted among university students in Ankara, the capital city of Turkey in the 2018-2019 academic year. In that year, there were 12 private and 7 public universities in Ankara. The number of university students in Ankara, the target population, was 26,781 male, 26,674 female in private universities, and 72,627 male, 80,607 female in public universities [To collect data, a questionnaire (prepared in SurveyMonkey) was used. The questionnaire had 46 questions on sociodemographic characteristics, tobacco smoking habits, and knowledge-attitudes on smoking.  and 5,245  undergraduate students in the two private foundation universities, and 35,331  undergraduate students in the public university.The student affairs or related administrative departments of the universities were requested to send the invitation email to all enrolled students through registered student email addresses. The participant inclusion criterion was being an undergraduate student in one of the three universities. The invitation email included general information about the study and the link to the online questionnaire. Reminder emails were sent every 3-4 weeks. The survey remained open for almost 3 months. The students answered the questionnaire of the study on a voluntary basis; they were not provided with any incentives. Informed consent was obtained from all participating students; no student was under 18. The convenience (non-probability) sample, consisting of students who participated in the survey, included 1,362 and 1,215 students in the private universities, and 2,731 students in the public university. Out of a total of 51,590 students who were invited to the study 5,308 responded, which yielded a response rate of 10.3%.Demographic characteristics data included gender and age. WP use status was determined based on ever using it, relying on the question “Have you ever smoked WP?”, since ever using WP is a major risk factor of using tobacco products in the future. If participants had ever smoked WP, their patterns of use  and the amount of spending on WP were surveyed.Family income or wealth were not asked in the survey, because of the difficulty of precisely measuring these variables in online surveys with voluntary participation. Instead, the survey included three other questions to help assess socioeconomic status (SES): Whether the student had access to a car (regardless of ownership); Living arrangement of the student , living at home with family, or sharing the residence with friends); and Source of income of the student . In the analyses, the binary (dummy) variable “Has a car” and the categorical variables “Living arrangement” and “Source of Income” were used as indicators of SES of students.In addition, to summarize the information in the three variables described above, a SES index was generated. The SES index  was deveStata/MP 15.1 was used to perform statistical analyses. Descriptive statistics were reported for never and ever smoking WP by students in private and public universities. Among ever users of water pipe, descriptive characteristics on the patterns of water pipe use were presented. To test whether students in private universities had the same prevalence rate or similar characteristics as those in public universities, p-values from chi-square tests were used. Binary logistic regressions, where the outcome variable was ever using WP, were used to estimate adjusted odds ratios (aOR) with 95% confidence intervals (CIs) for the associated factors . Binary logistic regression was estimated also for the associated factors of gender, age, and SES index. To compare aORs between public and private university students, tests of equality of the aORs were conducted. Regressions were estimated in samples of private and public university students separately, as well as in the pooled sample, where a binary (dummy) variable for being a private university student was added as another associated factor.A total of 2,485 private and 2,685 public university students answered the question on ever smoking WP. Students from different schools and departments of the universities participated in the survey. About 36% were from the School of Engineering, 27% from the School of Economic and Administrative Sciences, 15% from the School of Science and Letters, 6% from the School of Fine Arts, Design, and Architecture, 4% from the Law School, 3% were from the School of Nursery, 2.9% were from the School of Dentistry, and 2.6% were from the School of Pharmacy.p=0.045; females 61.4% versus 49%, p<0.001; in age groups the corresponding p-values were <0.001 in ages 18-19, 20-21, and 22-23). In most of the socioeconomic groups, the ever-smoking prevalence of WP was higher in private universities than in public university , among those who live alone (p=0.017), among those who receive family support (p=0.001).As shown in Table p<0.001). The prevalence of WP use within the last month was higher among private university students . Among ever-users of WP, the prevalence of current WP use was higher among private university students .Table p<0.001), facilitating socialization , can be shared with friends , makes conversation more fun , part of traditional culture , nice ambience and food in the venue  Table Students enjoyed WP for several reasons. The sensory charms of WP were important for youth. Compared to public university students, private university students found WP more enjoyable in many respects: Being pleasurable . Table In the calculation of the SES index, the first principal component  was used. It had positive factor scores on four variables (has a car (0.3281), lives with family (0.4979), lives alone (0.0231), and receives family support (0.4370)); therefore, these variables were thought to be associated with higher SES. The other four variables had negative factor scores: lives in dormitory (-0.4904), has roommate(s) (-0.0067), work as source of income (-0.0051), scholarship as source of income (-0.4609); therefore, they were thought to be associated with lower SES.n=752), average monthly spending on WP was statistically significantly higher among private university students (42 TL) than among public university students (29.6 TL) (not tabulated).It was found that private university students, on average, had higher SES than public university students. On average, the SES index was statistically significantly higher for private university students  than for public university students . A t-test for equality of means yielded a t-statistic of 4.62, leading to the rejection of equal means in private and public universities. The SES index took higher values for those who had a car, lived with family, lived alone, or received financial support from family. Consistent with this result, Table Table This study offers the first evidence that the prevalence of ever using WP was higher among private than public university students. In public universities 59.1% of students were ever users of WP; whereas among private university students 69.1% were ever users of WP. A substantial share of ever users of WP were current users of WP at the time of the survey, with a higher share reported among private than public university students.In this study, it was found that SES was an important factor associated with ever using WP. Moreover, SES was significantly higher for private university students than for public university students. Regression analyses showed that higher SES (as measured by the SES index) was statistically significantly associated with higher odds of ever using WP. It is also important that, even after controlling for the SES index, private university students still had higher odds of ever using WP.Several studies have reported that the prevalence of WP use among youth is quite high in the Middle Eastern countries and has been rising in the western part of the world as well , 20–22. Evidently, WP retail venues  were located in spots popular among youth and were in close proximity to students (around campuses), providing easy access. We found that such places were more abundant in locations close to private than public university students, because WP smoking at these venues can be quite costly. As explained before, private universities charge a substantial amount of tuition; therefore, it is not surprising that private university students come from more affluent families . It is eThis study found that the prevalence of ever using WP was higher among men than women, as in the earlier national studies on adolescents and youth , 11. TheThe findings of this research should be interpreted in light of several limitations: The sample included only university students; therefore, non-student young adults were not covered. The sample was a convenience sample with participants recruited from three universities in Ankara. Although the study benefitted from a large sample, it might not be representative of university students in the country. Moreover, since participation was voluntary and the topic of the survey might have been more interesting to ever-smokers of WP, a larger share of ever-smoker than never-smoker students might have responded to the survey, leading to an overestimation of the prevalence rates. Another point is that Ankara is the capital city with a higher than average per capita income and greater availability of outlets where the youth can access WP. In smaller cities, the consumption pattern might be different. Also, the survey did not cover tobacco consumption in the family or the city where the student attended high school, both of which might play a role in initiation.Both private university and public university students had substantial rates of WP smoking prevalence. WP smoking was associated with higher financial resources and higher SES. The results highlight the need for stricter regulations to curb WP use among university students.Additional file 1.


Self-rated health has been widely used as a useful screening tool to subjectively evaluate individuals' health status. Under the context of the rapid growth of aging, there was a dramatic rapid expansion in internal older migrants in China. Serious concerns on the issues of health status continue to attract quite a lot of attention over the past decades. Public health education is one of the most important health care services and methods to improve individuals' health status. However, most previous studies focus on the utilization of public health services such as visiting to doctors, physical examination, and hospitalization. There was limited evidence on the self-rated health and public health education of older migrants.The study aimed to evaluate self-rated health and the associated determinants in older migrants, as well as to gain a deeper insight into the current status of public health education received by older migrants.We derived the data from the National Migrants Population Health and Family Planning Dynamic Monitor Survey 2018, a cross-sectional study, for secondary analysis. Internal migrants aged 60 years old or over were included in the study. Self-rated health was the dependent variable, while sociodemographic characteristics were the independent variable. The univariate and multivariate analyses were performed by Stata 15.1.P < 0.5). However, the proportion of older migrants that received specific public health education was <50%. The most common approach to receiving public health education was through the leaflet, while <20% of older migrants received public health education through public consultation and one-to-one education.A total of 5,589 older migrants were included in the study. Eighty-two percentage of older migrants reported healthy self-rated health. There was a significant association between age, gender, minzu, education level, monthly income, public health education, and self-rated health (It was necessary to promote the publicity of public health education in older migrants through easy access and diverse approaches in order to effectively spread health-related knowledge to older migrants to satisfy their health needs and maintain their health. Self-rated health has been widely used as a screening tool in an abundance of studies . Self-raUnder the context of globalization and pluralistic development, migration becomes a worldwide phenomenon . China hA considerable body of literature has focused on the health-related issues in older migrants. Significantly, plenty of studies accentuated public health services utilization in internal migrants , 19–29. Public health education is one of the most important health care services and methods to improve individuals' health literacy and health status. Interestingly, research on public health education has been quite limited dated. In early 2014, the Chinese government pronounced a National Health Literacy Promotion Action Plan (2014–2020) . The NatThus, the aim of the current study was to better understand the self-rated health status and health education in internal migrants aged over 60 in the inland of China, also we aimed to explore some determinants related to self-rated health. Based on the results of the current study, we aimed to provide some insights for health policies makers into consideration in order to improve older migrants' access to receive public health education as well as to improve their health status.The main research questions in the current study were as follows: (1) Do Older migrants have a low level of self-rated health? (2) What were determinants of self-rated health in internal older migrants? (3) Was the access to public health education for older migrants inadequate?The current study was a secondary analysis. We derived the data from the National Migrants Population Health and Family Planning Dynamic Monitor Survey 2018 which was conducted by the National Health Commission of China in 2018. The survey is a cross-sectional study that used a probability proportionate to size (PPS) sampling method to do such a survey in 31 provinces and the Xinjiang Production and Construction Corps in the inland of China. The target population in the survey was nationally representative and was aged 15 years old and over. In addition, the target population had been living in the current city for at least 1 month or above, but did not get the household registration of the host city. In total, the sample of the National Migrants Population Health and Family Planning Dynamic Monitor Survey 2018 contained 152,000 persons.The aim of the current study was to estimate the self-rated health status and its' determinants in the older internal migrants. Internal migrants are defined as individuals who separate from the town or street of their household residence for more than half a year, excluding those living in a different town/district in the same city as their household residence. While the older internal migrants refer to internal migrants aged 60 years old or over .Self-rated health was selected to be the dependent variable. In the survey, participants were asked “How is your health state.” The answer would be “1 = healthy,” “2 = generally healthy,” “3 = unhealthy but with self-care ability,” “4 = unhealthy without self-care ability.” In our study, we classified self-rated health into a binary variable. In other words, the answer if the participants chose “healthy” or “generally healthy” would be classified as “healthy,” otherwise, it would be classified as “unhealthy.”In the current study, sociodemographic characteristics such as age, gender, minzu (ethnicity), education level, marital status, migrating region, monthly income, the establishment of the health record, signing family doctor service contracts, and medical insurance were the independent variables. Public health education was assessed by those questions “Have you ever received public health education related to chronic diseases, infectious diseases, occupational diseases, mental health, reproductive, maternal & child health care, public emergency or other health-related education?” The answer was “yes” or “no.” In the final analysis process, we classified it into “yes” if the participants chose any “yes,” while it would be classified into “no” if all of the answers were “no.”P < 0.05.We used Stata 15.1 to perform the data analysis. When describing the continuous data, the mean and standard deviation would be used. The categorical variables were demonstrated as frequency and percentages. The Chi-square test was used to assess the difference of distribution in sociodemographic variables between the healthy group and the unhealthy group. At the stage of multi-factor analysis, a generalized linear model, Poisson regression with robust variance estimate, was used to analyze the association between independent variables and self-rated health. The significance level was set at Totally, there were 5,589 older migrants included in this study. The median age was 64 years old. More than 57% of subjects were male, and the majority ethic of individuals was Han (nearly 92%). Most older migrants were less educated, and more than 75% of the older migrants graduated from middle school or below, and 16.5% from high school, while <8% from junior college or above. Most of the older migrants were married (84.52%). In terms of migrating regions, approximately 45% of older migrants floated cross-province. The median monthly income was 4,500 Yuan (RMB). Only 32.39% of subjects established health records, while more than 50% were without health records. Regarding making family doctor service contracts, <18% of older migrants signed such a primary health care program. Approximately 94% of older migrants had medical insurance. Although most older migrants believed themselves healthy, 18% of whom reported unhealthy.P < 0.05). However, we did not find a difference of distribution in making family doctor service contracts or having medical insurance between the healthy and unhealthy groups (P > 0.05). In order to determine the influencing factors of self-rated health in older migrants, we included all the independent variables in the generalized linear model. Shown in P < 0.001) in those of middle-old aged from 70 to 79 years old, while the IRR was 2.53  in those of oldest-old aged 80 years old and over. The IRR was 1.34  in female older migrants when compared with male ones. Regarding the education level, older migrants who graduated from primary school or below got a higher risk to be unhealthy  than that from junior college and above. As for monthly income, the IRR of those who had a monthly income of 4,501–7,800 Yuan, 2,501–4,500 Yuan, <2,500 Yuan was, namely, 1.26 (P = 0.029), 1.53 (P < 0.001), 2.46 (P < 0.001) when compared with those of more than 7,801 Yuan. Demonstrated from P < 0.001) than those who received public health education.In order to explore the distribution difference of self-rated health in older migrants, we performed a Chi-square test. Demonstrated in In total, 72.34% of older migrants received health-related education. However, as presented in In the current study, we estimated the self-rated health status of 5,589 older migrants. Interestingly, we found that 82% of the older migrants in the current study felt they were healthy, which was higher than we had expected. However, such a finding was similar to that in the study of Wei et al. . We alsoTo be specific, older migrants with older age got a higher relative risk to be unhealthy. Our results provided additional support to the conclusion that age predicted self-rated health of older migrants . With thUnsurprisingly, in the present study, monthly income was observed as one of the predictors of self-rated health in older migrants. In other words, a significant positive association between monthly income and self-rated health was detected. More specifically, older migrants with lower income had a higher likelihood to report poor self-rated health, which was in line with findings in previous research . One maiThere was an ongoing debate on the relationship between gender and self-rated health. Li et al.  pointed Additionally, minzu was detected as a determinant of self-rated health in internal older migrants. Compared with those of Han ethnicity, older migrants with ethnic minorities had a higher risk to report unhealthy. To our best knowledge, in China, there was a big gap of inequalities in the social economy, access to health care resources, employment status, and social connections between ethnic minorities and Han ethnicity . Such heNotably, as mentioned above, our findings revealed that there was a significant positive relationship between public health education and self-rated health. Compared to older migrants who received public health education, those without receiving any public health education got a higher likelihood of reporting unhealthy. Empirical studies suggest that the elderly have a higher demand for health-related services with the increase of age. Additionally, their demand for such services tends to be urgent and diverse to maintain their health . Public As for the approach of receiving public health education, leaflet was the most common way. 43.42% of older migrants in the survey received public health education through the leaflet, followed by public science gallery, health lecture. Surprisingly, the proportion of older migrants who received public health education through public consultation and one-to-one education was only 17.8 and 9.86%. On one hand, our results indicated that public health education did not get much publicity. On the other hand, public health education providers did not clearly take older migrants' preferences and abilities to receive health-related knowledge. In our study, over 80% of older migrants were with the education of middle school or below. Compared to younger migrants, older migrants had a lower education background. Therefore, it might be much easier to receive health knowledge through traditional educational methods such as health lectures, public consultation, or one-to-one education rather than through leaflets or public science galleries that required older migrants with higher self-learning abilities .Under the context of the rapid increase of the older internal migrants, it highly deserves to continue to attract attention to services and management capacity for such a huge group . StrategOne of the main limitations in our study was that we could only gain an insight into the health status at a precise moment, but could not get a deeper insight into that over time due to the nature of the cross-sectional design. Another limitation was that the current study derived data from a national survey for a secondary analysis, which prevented us from exploring the interlinkages between factors such as life events, life course trajectories, cross-cultural adjustment, social integration, social support and self-rated health in older migrants. We suggest that future research could do further explore with more variables in order to get better understand the determinants of self-rated health, which would help policymakers and primary health care providers to develop more precise and easier accepted health strategies to help older migrants realize healthy and positive aging.The current study estimated the self-rated health status and explored some possible influencing factors in older migrants. In conclusion, most older migrants reported good self-rated health. Factors such as age, gender, monthly income, minority, and public health education predicted self-rated health in older migrants. Despite the positive results on self-rated health, the proportion of public health education related to a specific kind of disease was rather small. Moreover, the approaches of receiving public health education seemed to be less easy and diverse. Based on the findings of our study, we suggest that it is necessary for policymakers and primary health care providers to develop and deliver more precise and easier accepted public health education programs to help older migrants realize healthy and positive aging.https://www.chinaldrk.org.cn/wjw/#/home.Publicly available datasets were analyzed in this study. This data can be found here: Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.WZ, SS, and YY conceived and designed the study. CW, HC, and DL collected, input and checked the data. BT, ZZ, and PL analyzed the data. WZ drafted the manuscript. All authors read and approved the final manuscript. All authors contributed to the article and approved the submitted version.This study was funded by the Ministry of Science and Technology of the People's Republic China (2020YFC2008801 and 2020YFC2008800), National Natural Science Foundation of China, Guizhou (81860245), and Science and Technology Platform and Talent Team Planning Project ([2019]5664), which offered support in the process of study design and financial support for publication.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.


Transient Elastography is a non-invasive, cost-efficient, non-ionizing, observer-independent and reliable method to detect liver fibrosis using Liver Stiffness Measurement (LSM) and the degree of fat accumulation in the liver using Controlled Attenuation Parameter (CAP). This study aims to derive reference values for both measures from healthy children and adolescents. Further, we aim to assess the potential influence of age, sex, puberty, and BMI-SDS on CAP and LSM.® device in a population-based cohort at 982 study visits of 482 healthy children aged between 10 and 18 years. Percentiles for LSM and CAP were estimated, and the effects of age, sex, puberty and weight status were assessed through hierarchical regression models.Within the LIFE Child study, amongst others, anthropometric data and pubertal status were assessed. Transient Elastography (TE) was performed using the FibroScanThere was a strong age dependency for LSM with higher values for older children, most pronounced in the upper percentiles in boys. Contrarily, CAP was relatively stable across the age span without considerable difference between boys and girls. We found a significant positive correlation between BMI-SDS and both CAP and LSM for BMI-SDS >1.28. For BMI-SDS < 1.28, the association was also positive but reached statistical significance only for CAP. Further, the association between BMI-SDS and CAP was significantly stronger in younger than in older children. There was no association between pubertal status and CAP. For LSM, we found that children with a high BMI-SDS but not children with normal weight had significantly higher LSM values in Tanner stage 4.Age, sex, pubertal status and weight status should be considered when interpreting LSM and CAP in pediatric patients to facilitate and improve early detection of abnormal liver function, which is associated with common pathologies, such as NAFLD. Non-alcoholic fatty liver disease (NAFLD) is the most common liver disease in children and adolescents. A recent systematic review and meta-analysis estimated a global NAFLD prevalence of 7.6% in children. Moreover, in studies focusing on children with obesity, the prevalence was as high as 34.2% . Due to NAFLD can lead to liver fibrosis and cirrhosis and increases the risk of developing hepatocellular carcinoma (HCC) , 5. MoreUntil today, the gold standard for diagnosing NAFLD is the histopathological examination of a liver biopsy. However, liver biopsy in children raises several ethical issues and is therefore reluctantly performed. Children often need general anesthesia, which entails a risk for the patient. Additionally, there is the risk of bleeding or mispuncture. Furthermore, since only a tiny part of the liver is examined, there is a risk of misdiagnosis due to sampling bias . Hence, Various serum parameters and imaging procedures have been evaluated in several studies over the last years, but mostly with rather disappointing results , 6, 8–10® ) has drawn a high amount of academic interest since it is a cost-efficient, observer-independent and non-ionizing method to detect fibrosis and steatosis reliably (® provides two different methods to examine the liver: liver stiffness measurement (LSM) and controlled attenuation parameter (CAP). While LSM is a parameter to estimate liver fibrosis, CAP quantifies the percentage of liver fat.Transient Elastography  Statement checklist for cohort studies .The LIFE Child study is a prospective longitudinal population-based cohort study with a life course approach to health and disease . As a pa® measurements  and their parents. Each study visit contained age-customized interviews, medical examinations, standardized tests, questionnaires and the collection of biological samples, as well as the implementation of FibroScanurements , 21.via advertisement at different institutions, by media or by word of mouth. The children were primarily healthy, without severe disorders like malignancies, syndromal diseases or diabetes. Accordingly, the acquired test results are qualified for generating reference values. Height was measured using a stadiometer . Participants were weighed with the “Seca701” scale . BMI was calculated and transformed into standard deviation scores (SDS) according to the guidelines of the German Obesity Association  were available. In N=249 cases, we performed double measurements.Our exclusion criteria were:Measurements from participants younger than 10 years and older than 18 years of age were excluded (N=71 visits and 41 children), due to the small number of measurements below and above that age.Participants with the intake of at least 1 of 92 potentially hepatotoxic drugs .rd and >97th percentile (BMI-SDS < -1.88 and BMI-SDS>1.88), resulting in data from 982 visits from 482 individuals.For the calculation of LSM and CAP percentiles, we excluded 165 participants (231 visits) with a BMI-SDS < 3Glucose and insulin measurements were available from 625 visits from 196 individuals.The examination was carried out after an overnight fast by specially trained and regularly re-certified examiners. The participants were asked to lie on the back, the right arm maximally abducted, and to stay immobile during the examination. Those participants who were designated for dual measurements were asked to stay in the same position after the first measurement, and the second measurement was performed by the same examiner immediately afterwards.® device with the M probe (25 - 65 mm measurement depth) or XL probe (35 - 75 mm measurement depth). The FibroScan® device includes the Automatic Probe Selection (APS) tool, which indicates which of the two probes should be used for measurement. LSM measures the propagation of produced shear waves, and the results are displayed in kilopascals (kPa). CAP measures the attenuation of the above-mentioned shear wave propagation, producing results in decibels per meter (dB/m). The measurement was successful when 10 valid data points could be measured.LSM and CAP values were measured using the FibroScanBlood samples were taken from the participants after an overnight fast. Serum glucose concentrations were measured by the photometric method . Serum insulin concentrations were measured using a quantitative electrochemiluminescence method (Roche) . HomeostDescriptive statistics are given as mean and standard deviations for continuous and counts and percentages for categorical variables.References for LSM and CAP were estimated as a continuous function of age, stratified by sex using the LMS method as implemented in the package gamlss . We corrrd degree). Otherwise, linear approximation yielded a sufficient fit. We tested for relevant interactions between predictors. Model terms were only kept if they were necessary. In addition, models were tested for variance inflation. Results were reported as (non-standardized) coefficients and the respective 95%-confidence interval.Associations between LSM and CAP as outcome and the assumed predictors  were assessed using hierarchical regression analysis. To assess the effect of puberty, raw measurements of LSM and CAP were used because of the strong dependency between age and puberty; in all other models, the age- and sex-adjusted SDS were used as outcome. All models were adjusted for multiple measurements per subject by adding the subject as random effect. The nature of associations was investigated using non-parametrical generalized additive models. The association between LSM and BMI-SDS required polynomial modeling  , 31. In via a structural equation model.The mediating effect of hepatic insulin resistance was assessed by mediation analyses using HOMA-IR implemented Analyses and visualization were performed using the packages gamlss , lme4 3 version.rd and 97th percentile, who were examined between December 2013 and June 2022 in the context of the Leipzig Research Centre for Civilization Diseases (LIFE). Since LIFE Child is a longitudinal study, some participants were measured more than once over the period of 8 years, resulting in a total of 982  visits for the calculation of the percentiles. Dual measurements for the evaluation of FibroScan® validity were performed in 249 individuals. The population characteristics for the entire study population (N=1358) are listed in We used the data of 482  healthy individuals, aged between 10 and 18 years with a BMI-SDS between 3For both LSM and CAP, we could show an “excellent” OACCU. OCCC and OPREC were “good” for LSM and “moderate” for CAP. The results are shown in rd, 10th, 50th, 90th and 97th percentile curves for LSM and CAP are shown for boys and girls in The 3rd, 10th and 50th percentile. The curves P50, P90 and P97 for boys, on the other hand, show continuous slopes until reaching their peaks, followed by a slight flattening. The age at which boys reach the highest values is comparable with that of girls (about 16.5 years) in P50, 90 and 97. In the lower percentiles, however, the highest values were measured at 18 years.LSM percentiles show increasing values for both sexes with, in general, higher values for boys, which becomes more pronounced in the upper percentiles . Also, the curve shapes differ from each other with regard to sex: The curves for girls ascend for the first 1.5 years, then slightly flatten for about 1.5 years, after which they ascend again until they reach their peak at about 16.5 years (P50 5.95kPa) which is followed by another slight drop in the 3CAP percentiles show similarly shaped curves for boys and girls. The reference values are comparable as well. Comparing the reference values at the age of ten and 18 years, the lower percentiles show a tendency to descend slightly while the higher percentiles tend to ascend slightly, reaching their peaks at about 14 years. P50 depicts rather stable values during the eight years .https://cran.r-project.org/package=childsds).The parameter tables are provided as part of the R package childs (version 0.8.0). The package also contains functions to transform measurement values into SDS and to create percentile curves. It is available from CRAN . The effects of weight status on LSM were not different, regardless of age and sex.After establishing percentiles, we assessed the association between weight status and both LSM and CAP values. In children with a BMI-SDS <1.28, there was a slightly positive association between LSM-SDS and BMI-SDS. However, it did not reach statistical significance . In children with overweight and obesity, the respective effect size was three times as high, and the association became significantly positive  . In addition, the effect varied significantly with age, having the strongest effect for younger children  and the weakest effect for older adolescents . The effect of weight status on CAP did not differ between sexes.In children with a BMI-SDS <1.28, we found a significant positive association between CAP-SDS and BMI-SDS . In children with a BMI-SDS >1.28, the effect size was six times as high   than in TS 5   3 , TS 4 , and TS 5  than in TS 1. In girls, there was no such distinct pattern. Considering weight status, there was a significant interaction between Tanner stage and BMI-SDS: While we found no effect of puberty in children with a BMI-SDS around or below 0, we found significantly higher LSM values for children with BMI-SDS of 1.88 or higher in TS 4 and 5. The effects were remarkably stronger in TS 4 (beta001) see Figure 4There was no significant association between CAP results and puberty. Moreover, the association between BMI-SDS and CAP did not differ between Tanner stages. Values were, on average, 10 kPa higher for males than for females (p=0.012). There was no interaction between sex and Tanner stage or BMI-SDS.Considering the rising prevalence of obesity and concomitant liver diseases, especially NAFLD, in children and adolescents, non-invasive diagnostic tools to accurately detect liver pathologies in pediatric patients are urgently needed. Transient Elastography has been used extensively to aid the diagnosis of fatty liver disease and fibrosis in the adult population for which TE reference values are available –36. SeveWith the aim to close this knowledge gap, this study provides pediatric reference values and presents the respective percentiles for the Transient Elastography measurements LSM and CAP, based on our investigation of a large and well-characterized cohort of healthy children and adolescents. We decided to include children with overweight when estimating percentiles because our analyses revealed that the influence of BMI-SDS was similar as in children with normal weight. In contrast, increasing BMI-SDS had considerably stronger effects on LSM and CAP for children with obesity Figure 3Furthermore, we analyzed the influence of age, sex, weight and pubertal status on LSM and CAP. Thereby, we enable examiners and practitioners to interpret LSM and CAP test results in children more accurately, having appropriate reference values at hand.5years median 3.2 kPa vs. Brunnert 2022: LSM10years median 3.9 kPa), we regard their study results, taken together with ours, as strongly supporting the validity of the assumption that pediatric LSM values increase with age. However, Mjelle et al.  for CAP of 0.82 for children with normal weight and 0.6 for children with obesity . RowlandThere are some limitations to our study. We only used data from a single study center with limited access to subjects with diverse ethnic background. Thus, our results are not necessarily representative of pediatric patients worldwide. Furthermore, families participating in the LIFE Child research project generally have a socio-economic status above average  which coNevertheless, our study has several strengths. To our knowledge, this paper is the first to provide reference values for both LSM and CAP based on a large pediatric cohort from 10 to 18 years. Additionally, we established that age, sex, BMI-SDS and pubertal status have an impact on TE test results and, thus, should be considered when evaluating LSM and CAP values. Accordingly, we suggest our sex- and age-adapted reference values to interpret TE results in pediatric practice. There are numerous studies evaluating the usefulness and feasibility of TE for pediatric subjects, but most of them only examine patients with NAFLD or obesity. However, in pediatric practice, we need reference values guiding us in our endeavor to identify potential risks or existing diseases in patients. Thus, the reference values and percentiles we present in this paper can help us to red-flag conspicuous test results.Given the already high and, most likely, further increasing prevalence of liver diseases such as NAFLD, it is paramount to detect potential diseases at an early stage. Our paper attempts to make a valuable contribution to this endeavor in terms of research as well as practice.dm@life.uni-leipzig.de). Requests to access the datasets should be directed to dm@life.uni-leipzig.de.The datasets presented in this article are not readily available because data cannot be shared publicly because there exist ethical restrictions. The LIFE Child study is a study collecting potentially sensitive information. Publishing data sets is not covered by the informed consent provided by the study participants. Furthermore, the data protection concept of LIFE requests that all  researchers interested in accessing data sign a project agreement. Researchers that are interested in accessing and analyzing data collected in the LIFE Child study may contact the data use and access committee , by the European Regional Development Fund , and by means of the Free State of Saxony. This publication was funded by the Open Access Publishing Fund of Leipzig University supported by the German Research Foundation within the program Open Access Publication Funding. Furthermore, we acknowledge support from the Roland-Ernst-Stiftung. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.This publication is supported by LIFE – Leipzig Research Center for Civilization Diseases, University of Leipzig. LIFE is funded by means of the European Union, by means of the European Social Fund (ESF, We are deeply grateful to all the families who have taken part in this study, and the whole LIFE Child team.TK received unrestricted research grants from Echosens SA, France, not related to this project. TK took part in a clinical advisory board meeting of Echosens SA.The remaining 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.


The Children Neuropsychological and Behavioral Scale-Revision 2016 (CNBS-R2016) is a widely used developmental assessment tool for children aged 0–6 years in China. The communication warning behavior subscale of CNBS-R2016 is used to assess the symptoms of autism spectrum disorder (ASD), and its value of >30 points indicates ASD based on CNBS-R2016. However, we observed that children with relatively lower values were also diagnosed with ASD later on in clinical practice. Thus, this study aimed to identify the suitable cutoff value for ASD screening recommended by the communication warning behavior of CNBS-R2016.A total of 90 typically developing (TD) children and 316 children with developmental disorders such as ASD, developmental language disorder (DLD), and global developmental delay  were enrolled in this study. All subjects were evaluated based on the CNBS-R2016. The newly recommended cutoff value of communication warning behavior for screening ASD was analyzed with receiver operating curves.Kappa values between the communication warning behavior and ABC, CARS, ADOS-2, and clinical diagnosis were 0.494, 0.476, 0.137, and 0.529, respectively, with an agreement rate of 76.90%, 76.26%, 52.03%, and 82.27%, respectively, when the cutoff point was 30. The corresponding Kappa values were 0.891, 0.816, 0.613, and 0.844, respectively, and the corresponding agreement rate was 94.62%, 90.82%, 90.54%, and 93.10%, respectively, when the cutoff point was 12.Children in the ASD group presented with lower developmental levels than TD, DLD, and GDD groups in overall developmental quotient assessed by CNBS-R2016. We compared the consistency between the scores of communication warning behavior subscale and Autism Behavior Checklist (ABC), Childhood Autism Rating Scale (CARS), Autism Diagnostic Observation Schedule, second edition (ADOS-2), and clinical diagnosis for the classification of ASD at a value of 30 based on the previously and newly recommended cutoff value of 12 by the CNBS-R2016. The The communication warning behavior subscale of CNBS-R2016 is important for screening ASD. When the communication warning behavior score is 12 points or greater, considerable attention and further comprehensive diagnostic evaluation for ASD are required to achieve the early detection and diagnosis of ASD in children. Autism spectrum disorder (ASD) is a life-long neurodevelopmental disorder characterized by persistent impairments of social communication and restricted and repetitive behavior , with inAutism spectrum disorder is a serious disease that affects children’s social adaptability. A national sample survey has shown that ASD is the leading cause of disability among disabled children aged 6 or younger in China . ASD notSome imported tools, such as the Checklist for Autism in Toddlers, Modified Checklist for Autism in Toddlers, Autism Behavior Checklist (ABC), and Clancy Autism Behavior Checklist, have been used for screening ASD , 25. AltThe Children Neuropsychological and Behavioral Scale is an indigenous development assessment tool with Chinese norms that was developed by the Capital Institute of Pediatrics of China  since thSome of developmental behavioral pediatricians or child healthcare physicians in China have screened and detected ASD based on the communication warning behavior. A point of the communication warning behavior over than 30 points indicates ASD as suggested by CNBS-R2016. However, we observed that children with lower values of communication warning behavior were also diagnosed with ASD later on in clinical practice. Therefore, we aimed to study the suitable cutoff value for screening ASD and provide suggestions about the application of CNBS-R2016 in the early detection of ASD in children.Children aged 2–5 years who visited the outpatient Division of Child Healthcare, Department of Pediatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology from March 2019 to December 2021 were enrolled in this study. Children with developmental disorders and typically developing (TD) children were recruited. Developmental disorders included ASD, developmental language disorder (DLD), and global developmental delay (GDD). All participants completed developmental assessment of the CNBS-R2016. ASD and GDD groups were diagnosed based on the ASD criteria of American Psychiatric Association Diagnostic and Statistical Manual of Mental Disorders 5th edition (DSM-V)  and furtAll children included in this study participated in the developmental assessment by the CNBS-R2016. The mean value of the general developmental quotient (DQ) and the five subscale quotients of the CNBS-R2016 is 100. A subscale quotient of less than 70 points (<2 standard deviations [SDs]) indicates a developmental delay; a quotient between 70 and 79 points is slightly below the threshold for developmental delay, and a quotient greater than or equal to 80 points showed no developmental delay . The comThe ABC is a behavior questionnaire that is completed by child’s parents or caregivers. The questionnaire covering five aspects of autism symptoms: sensory, relating, body concept and object use, language, social and self-care. Items are scored on a 4-point scale, ranging from 0 (no problem) to 3 (severe problem). The higher the score, the more serious the problem . The staThe Autism Diagnostic Observation Scale-2 (ADOS-2) is a standardized and partly structured tool that provides a standardized assessment of ASD symptoms. It is a play-based, semi-structured assessment tool used to assess communication, social interaction, and restricted and repetitive behavior in individuals with ASD, which forms the part of the recommended “gold standard” for the diagnosis of ASD . ADOS-2 We introduced this project to 685 parents and children, 434 of which agreed to participate in this project, including 341 children with developmental disorders and 90 typically developing children. Of the 341 children with developmental disorder, 25 were excluded because of incomplete medical records, and they did not meet the inclusion criteria.2 in size, and approximately 1 h was needed for each child. DLD and GDD were recruited simultaneously in accordance with the corresponding diagnostic criteria. All DLD and GDD children recruited in this study were assessed by CNBS-R2016, ABC, and CARS. Some diagnoses could not be distinguished from ASD, and ADOS-2 was scheduled as necessary. The later scale evaluators were blinded to the initial diagnosis of outpatient pediatrician to avoid bias. The hearing and vision of all children with developmental disorders were examined to exclude disabilities caused by serious hearing and vision loss. Brain MRI, EEG, molecular genetics, and metabolic test were scheduled optionally. TD children were recruited as the control group. They did not have any developmental problems, and they were assessed in accordance with the CNBS-R2016 as a part of the routine physical examination.These subjects were recruited in accordance with a standardized process. During the first visit to the hospital, children suspected of developmental delay received an initial inquiry approximately 20 min by an outpatient developmental behavioral pediatrician. This process collected information about children’s current health condition, developmental status, and family history. For children highly suspected of ASD, the outpatient pediatrician would schedule the evaluation, including ABC, CARS, CNBS-R2016, and ADOS-2. The parents completed the ABC by following the instruction of another developmental pediatrician; meanwhile, this pediatrician completed the CARS by observing children’s behavior and interviewing their parents or guardians. A trained and qualified developmental pediatrician would complete the CNBS-R2016 during children’s first visit. The ADOS-2 was scheduled within 1 week by a certified developmental pediatrician. It was completed in an assessment room approximately 20 mThe final diagnoses were established by integrating data from parent interviews, developmental status, medical records, information provided by other caregivers and teachers, and direct observation and interaction with children during at least two assessment visits. All diagnoses were confirmed by two developmental and behavioral pediatricians. Participants were excluded if they had any diseases of the nervous system, deafness, selective mutism, or other difficulties with known biomedical conditions such as metabolic or genetic diagnoses, and so on. The recruitment and diagnosis of participants are shown in post hoc test was performed for multiple comparison. In addition, the Kruskal–Wails H test was conducted to compare communication warning behavior scores of four groups. The chi-squared test (χ2) was used for categorical variables. Spearman’s correlations were conducted to examine the relationship between the communication warning behavior scores and established autism scales . P < 0.05 was considered statistically significant.Data analyses were performed using SPSS 22.0 and GraphPad Prism 6.0. The Kolmogorov–Smirnov test was used to determine the distribution of the analyzed variable before analysis. Continuous normal variables are described as means ± SDs. Non-normal distribution of variables is described as median (P25 and P75). Categorical variables are described as frequencies and percentages. One-way analysis of variance (ANOVA) was performed to compare age, subscale, and DQ scores among all groups , and the least significant difference (LSD) Kappa value and agreement rate . Kappa ≤ 0.2, Kappa ranging from 0.4–0.6, and Kappa ≥ 0.6 were interpreted as poor, moderate, and excellent consistency, respectively (The ability of the communication warning behavior to predict the diagnostic category for each of the cutoffs was examined by receiver operating characteristic (ROC) analysis. In evaluating the accuracy of the diagnostic instrument, the area under the curve (AUC) was used. Based on the criteria of Swets et al. , the AUCectively . With rep < 0.05).A total of four hundred and six cases aged 2–5 years were included in final analyses. Among them, 130 children fulfilled the diagnostic criteria of ASD, 100 children of DLD, 86 children of GDD, and 90 TD children. p < 0.05).The distribution of communication warning behavior scores of all four groups is shown in p < 0.05).The correlation between quotients of communication warning behavior and established autism scales in ASD children is presented in The communication warning behavior of CNBS-R2016 score of >30 points was selected for the prediction of ASD, and consistency with ABC, CARS, ADOS-2, and clinical diagnosis is shown in Youden’s index. The diagnostic validity  of CNBS-R2016 was analyzed by ROC analysis for ASD vs. TD, ASD vs. DLD, ASD vs. GDD, ASD vs. TD, and combination of DLD and GDD. The ROC curve plotted for the communication warning behavior scores  determinAs a native child developmental assessment tool in China, CNBS-R2016 has a unique role in cultural adaptability, and it has been widely used in child care department as a development assessment tool for routine well-child visit in Mainland China. Tang et al. had proven that the CNBS-R2016 and Griffiths Mental Development Scales (GMDS) showed good consistency in the developmental assessment of children with ASD . CompareThis study primarily explored whether a lower cutoff value for ASD screening is more recommended for referral in accordance with the Communication Warning Behavior of CNBS-R2016.We compared the developmental level of ASD, GDD, DLD, and TD groups assessed by CNBS-R2016. With regard to the overall developmental level, the ASD group had the lowest overall DQ, followed by GDD and DLD, and they were all significantly lower than the TD group. Children in the four above mentioned groups differed from one another in the subscale of CNBS-R2016. ASD showed the lowest score in language subscale probably because speech and language problems were the main reasons that encouraged caregivers to initially seek for treatment in preschool ASD population. In addition, children in the ASD group were generally normal in gross motor but delayed in fine motor, adaptive behavior, language, and personal-social domains. The DLD group was only delayed in language, whereas the GDD group showed developmental delays in all domains. This study showed that children with different developmental disorders varied in developmental profile of CNBS-R2016. The results of CNBS-R2016 were in line with the clinical presentation of children with ASD, DLD, and GDD.p < 0.05). Li et al.  and the total CARS  scores in children with ASD, respectively. ASD of preschoolers with low neurodevelopmental levels presented high scores of ABC, SRS, and CARS and a high communication warning behavior score (p < 0.05), and this result was consistent with conclusion of Li et al. , hearing loss, and metabolic or genetic diseases –49. A toThe sensitivity of 12 points was more excellent than 30, with no significant decrease in specificity. In clinical practice, the communication warning behavior is generally used to indicate children for further ASD diagnostic evaluation, thereby requiring high sensitivity. A cut off score of 12 points could serve this purpose well.We also analyzed the best cutoff values for distinguishing ASD vs. TD, ASD vs. DLD, and ASD vs. GDD using the same method, which were 3.5, 6.5, and 12.5, respectively, and corresponding AUC value was all above 0.85, which indicated high sensitivity and specificity. Children with DLD, GDD, and ASD have a communication disorder with varying degrees. This study could be used as a reference for clinical classification among ASD, DLD, GDD, and TD.The communication warning behavior subscale of CNBS-R2016 is important for the early detection and differential diagnosis of ASD. In this study, the communication warning behavior score of 12 points was the best cutoff for screening ASD children. Therefore, we suggest that when the communication warning behavior scores are 12 points or greater, considerable attention is needed, and further comprehensive diagnostic evaluation of ASD is required in institutions that are qualified to diagnose ASD. Moreover, in primary care hospital or institutions that are not qualified to diagnose ASD, children with a communication warning behavior score of 12 points or greater should be referred to qualified institutions for diagnosis.Our study sublimated the original explanation about communication warning behavior of CNBS-R2016 and provides specific and feasible recommendations for children with communication warning behavior scores over than 12 points. A recommended cutoff point of 12 for further comprehensive diagnostic evaluation for ASD can better assist the early detection and diagnosis of ASD in China.The limitations of this study must be noted to provide a comprehensive understanding of the results. First, the sample children were only recruited from Wuhan, China, and this study had a single-center design. Second, the size of the control group was smaller than that of the ASD group, and different groups were not matched in numbers. In addition, the control samples except for the TD group primarily recruited those with language disorders, and most ASD children had intellectual disabilities, which may limit the power of this study. Therefore, muti-centered and larger population with more different kinds of developmental disorders is necessary to verify the reliability of the results.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by Ethical Committee of Tongji Hospital Affiliated Tongji Medical College, Huazhong University of Science and Technology. Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.SC, XH, JZ, and YH designed the study. SC, JL, DW, TY, LT, LX, MC, SH, and YH recruited subjects and collected medical information. SC carried out the analysis and wrote the manuscript. JZ instructed the statistical method and writing idea. XH and LT revised the manuscript. YH guided and supervised all work. All authors contributed to the article and approved the submitted version.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.