ATP-binding cassette transporter A1 (ABCA1) has important roles in high-density lipoprotein (HDL) metabolism and reverse cholesterol transport, and is implicated in lipid-related disorders. Genetic variants are involved in the pathogenesis of gestational diabetes mellitus (GDM). The objective of this study was to investigate the association of rs2230806 (R219K), a single nucleotide polymorphism (SNP) in the lipid-related gene, with the risk of GDM and related traits.The SNP, rs2230806, was genotyped, and clinical and metabolic parameters were determined in 660 GDM patients and 1,097 control subjects. Genetic associations with related traits were also analyzed.The genotype distributions were similar in GDM patients and normal controls. However, significant differences in the variables examined in the study subjects were noted across the three genotypes. The genotype at the rs2230806 polymorphism was significantly associated with HDL-cholesterol (HDL-C) levels and atherogenic index (AI) values in GDM patients and total cholesterol (TC) and low-density lipoprotein-cholesterol (LDL-C) levels in control subjects. Subgroup analysis showed that the polymorphism was associated with diastolic blood pressure, in addition to HDL-C levels and AI, in overweight/obese GDM patients, while it was associated with TC levels, AI, pre-pregnancy body mass index (BMI), and BMI at delivery in non-obese GDM patients. In addition, this polymorphism was associated with TC, LDL-C, and apoB levels in overweight/obese control subjects.ABCA1 gene was associated with variations in atherometabolic traits in GDM patients, with characteristics of BMI dependency, but not with GDM. Our findings highlight a link between related phenotypes in women with GDM and genetic factors.The rs2230806 polymorphism in the  Gestational diabetes mellitus (GDM) is the most common metabolic disorder that occurs during pregnancy. It is defined as glucose intolerance beginning in the second or third trimester of pregnancy . The preABCA1 gene is located on the human chromosome 9q31 and it encodes an integral cell membrane protein that facilitates the efflux of cholesterol and phospholipids. ABCA1 is highly expressed in various human tissues, including the placenta, uterus, liver, adrenal glands, small intestine, lungs, and heart  is the rs2230806 SNP  in exon 7. This SNP results in the substitution of an arginine amino acid  with a lysine  amino acid at position 219 of the polypeptide. This amino acid substitution is functionally relevant to the role of ABCA1 in lipid metabolism. For example, the A allele of the SNP is associated with higher levels of HDL-cholesterol (HDL-C) in various populations, such as Turkish  or without  GDM from a well-characterized Chinese population. We also investigated whether this SNP was associated with the risk of GDM and related traits in our study subjects.We tested the hypothesis that ABCA1 rs2230806 SNP genotype is associated with the risk of GDM and/or atherometabolic traits in GDM patients. To date, there is little information on the possible relationship between Blood samples were taken from 1,757 Chinese women from 2013–2020, including 660 patients  with GDM and 1,097 control subjects . All study subjects were of Chinese Han ethnicity. This study was conducted in accordance with the principles of the Declaration of Helsinki. Written informed consent was obtained from all participants. The study was approved by the Institutional Review Board of West China Second University Hospital, Sichuan University (No. 2017–033).All patients with GDM were recruited from the Obstetrics Department of West China Second University Hospital at Sichuan University in Chengdu. Each patient with GDM met the diagnostic criteria recommended by the International Association of Diabetes and Pregnancy Study Groups  . Control2) was determined. Normal weight and overweight/obesity were defined as BMI < 25 and ≥ 25 kg/m2, respectively. Sitting blood pressure was measured on the right arm after a 10-min rest with a semi-automatic device (Omron HBP-1300). The infant’s length and weight were measured after birth. Blood samples of the study subjects were taken in a stage of late pregnancy after an overnight fast. Plasma aliquots were stored at -80°C.Body weight in light clothing and barefoot height were measured, and body mass index . The concentrations of TC, HDL-C, LDL-C, and TGs were measured in plasma samples using an enzyme assay , and serum apoA1 and apoB levels were determined by polyethylene glycol-enhanced immunoturbidimetric assay  using a Hitachi 7600-010 automatic analyzer . Plasma glucose levels were measured using the glucose oxidase technique . The intra- and inter-assay coefficients of variation for all measurements were less than 5% and 10%, respectively. The homeostatic model assessment of insulin resistance (HOMA-IR) was calculated as [fasting glucose concentration (mmol/L) × fasting insulin concentration (μU/mL)]/22.5. The atherogenic index (AI) was calculated using the following equation: AI = [(TC)-(HDL-C)]/[HDL-C] .ABCA1 polymorphisms were estimated by gene counting. Hardy-Weinberg equilibrium was tested in cases and controls using a chi-square test. Allele and genotype frequencies were compared between cases and controls using chi-square analysis. Differences in variables between the GDM and control subjects were evaluated using independent-sample Student t-tests. To assess the effects of ABCA1 gene polymorphism and changes in quantitative variables, we performed an analysis of variance. Adjustments for age and BMI were performed using analysis of covariance. The effects of other parameters, including the rs2230806 G/A genotypes of ABCA1, glycemic status , pre-pregnancy BMI, and BMI at delivery, on insulin, TG, TC, HDL-C, and LDL-C levels were evaluated by multivariate stepwise regression analyses. Statistical significance was set at p < 0.05. All statistical analyses were performed using the Statistical Program for Social Sciences (SPSS) 21.0 .Data are presented as the mean ± standard deviation. Allele frequencies of The comparison of clinical characteristics and biochemical parameters between the patients with GDM and controls is shown in p > 0.05).In addition, when GDM patients and control subjects were further divided into overweight/obese and non-obese subgroups, no significant differences in genotype or allele frequencies were observed between these subgroups Table 3.p < 0.05). These differences remained significant after adjusting for age and BMI. There were no significant changes in other parameters according to the genotype at the rs2230806 locus in GDM patients.Associations of the SNP rs2230806 and clinical characteristics and metabolic traits are shown in p < 0.05, In addition, in the control group, TC and LDL-C levels were lower in AA homozygotes than GG homozygotes  and non-obese (BMI < 25 kg/m2) subgroups. In the overweight/obese GDM group, we found that AA homozygotes at the rs2230806 polymorphic site had higher DBP and AI values than heterozygotes and GG homozygotes, lower TC levels than heterozygotes, and lower HDL-C levels than heterozygotes and GG homozygotes , we further analyzed the effects of the p < 0.05). Genotype-related effects at this locus were not observed in non-obese control subjects  with the risk of GDM and related traits. Our results showed, for the first time, that the polymorphism was significantly associated with HDL-C levels and AI values in GDM patients. Further subgroup analysis showed that the polymorphism was associated with DBP in addition to HDL-C levels and AI values in overweight/obese GDM patients, while it was associated with TC levels, AI values, prepregnancy BMI, and BMI at delivery in non-obese GDM patients. These results provide evidence that the polymorphism is associated with variations in atherometabolic traits in GDM patients, with characteristics of BMI dependency. These findings highlight a link between related phenotypes in women with GDM and the genetic component.The rs2230806 polymorphism controls the substitution of an arginine at residue 219 of the peptide with a lysine. This substitution may affect the function of ABCA1; that is, the first step in reverse cholesterol transport . Our resABCA1, are involved in the response to cholesterol depletion in the membranes . In contrast, non-obese GDM subjects with the AA genotype showed increased TC levels compared to those with GG or GA genotypes . This difference may be attributed to the different BMI statuses of GDM patients. Several studies have shown that the A allele of this polymorphism is significantly associated with lower TC levels (While we observed an association between the C levels –31. The p < 0.05). This is consistent with the results of previous studies  than those with the GA genotype (72.15 ± 8.59 mmHg). However, this difference was not observed in non-obese subjects with GDM. Clinical diabetes, including GDM, is considered an independent risk factor for cardiovascular complications. Women with GDM have a higher risk of developing hypertensive disorders or preeclampsia. One study using transcriptomics showed in the placenta a high level of pro-inflammatory factor expression with signs of major vascular dysfunction . AnotherABCA1 V825I were different between normotensive and hypertensive women, and DBP differed according to ABCA1 genotype  in mediating blood pressure variation, and modifying the additional interaction of components such as overweight/obese and smoking.Several studies have established an association between lipid-related gene polymorphisms and blood pressure variation or hypertension in different populations and ethnic groups. For example, one study reported that the genotype frequencies of genotype . Yin et genotype . In addiividuals , and ninividuals . These fABCA1 rs2230806 SNP and AI value in all GDM patients and in individual overweight/obese and non-obese subgroups. AI values were higher in AA homozygotes in the GDM group and its separate subgroups than in GG homozygotes (p < 0.05). These data strongly support the notion that patients with GDM have a higher risk of CAD and suggest that the genetic component is associated with atherogenic risk markers, including the AI values.In the present study, we also found an association between the ABCA1 rs2230806 SNP and prepregnancy BMI variation, which suggests that the maternal genetic component may have implications in determining the cardiometabolic health of the offspring by affecting maternal prepregnancy BMI.Several epidemiologic studies have shown positive associations between maternal gestational weight gain (GWG) and prepregnancy BMI and cardiometabolic risk factors in the offspring, such as fat mass , weight ABCA1 genetic variation was significantly associated with some lipid abnormalities in women with GDM and with metabolic adaption in normal pregnancies.Additionally, we have analyzed our data by regression analysis. The results demonstrated that prepregnancy BMI was an important predictor of TG, TC, HDL-C, and LDL-C levels, while the allelic variant, and both the allelic variant and glycemic status were also important predictors of HDL-C and LDL-C levels, respectively Table 7.ABCA1 expression levels according to different ABCA1 genotypes, which would have provided further insights into the mechanisms responsible for the genetic association. In addition, the sample size included in this study is relatively small. Moreover, our findings were limited to descriptive characteristics.Our study has some strengths and limitations that should be noted. The strengths of this study are as follows. First, the study included both maternal and fetal/neonatal data. Second, the study adds to the limited body of evidence regarding the genetics of hyperglycemia during pregnancy. Third, we provided insights into the genetic regulator of lipid metabolism and its effect on biomarkers of insulin resistance in human pregnancy. The study limitations include a lack of data on ABCA1 rs2230806 SNP is associated with GDM in Southwest Chinese women. However, it demonstrated that the rs2230806 polymorphism in the ABCA1 gene is associated with HDL-C levels and AI values in GDM patients, and with TC and LDL-C levels in control subjects. In addition, a subgroup analysis showed that this SNP was also associated with DBP levels in addition to HDL-C levels and AI values in overweight/obese GDM patients, while it was associated with TC levels, AI values, pre-pregnancy BMI, and BMI at delivery in non-obese GDM women. Moreover, this SNP was associated with TC, LDL-C, and apoB levels in overweight/obese control subjects. Our results suggest that the rs2230806 polymorphism may be associated with increased maternal cardiovascular risk in women with GDM, and thus potentially, with an increased future risk of type 2 diabetes and CHD in mothers and their offspring. Screening for this variant in GDM patients, especially those with different BMI levels, and weight loss through changes in diet and lifestyle in women with GDM, may be beneficial and have preventive effects against complications in these patients.In conclusion, our study found no evidence that the https://www.ncbi.nlm.nih.gov/snp/rs2230806.The datasets for this study can be found at the found here:ABCA1 (rs2230806): The studies involving human participants were reviewed and approved by The Institutional Review Board of West China Second University Hospital, Sichuan University. The patients/participants provided their written informed consent to participate in this study.HB conceived and designed the experiments, analyzed the data and revised the paper. FT performed experiments and wrote the paper. LG and XL was responsible for patient screening. MZ, YW, RL, YL, and SL helped with the experiments. PF and DL helped with the experiments and revised the paper. All authors have read and approved the final manuscript.This study was supported by grants from the National Natural Science Foundation of China 39870749, the National Key Research and Development Program of China 2016YFC1000400, Program for Changjiang Scholars and Innovative Research Team in University IRT0935, the Fundamental Research Funds for the Central Universities, and Research Seed Fund from West China Second University Hospital of Sichuan University (HB).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.


The use of inertial measurement unit (IMU) has become popular in sports assessment. In the case of velocity-based training (VBT), there is a need to measure barbell velocity in each repetition. The use of IMUs may make the monitoring process easier; however, its validity and reliability should be established. Thus, this systematic review aimed to (1) identify and summarize studies that have examined the validity of wearable wireless IMUs for measuring barbell velocity and (2) identify and summarize studies that have examined the reliability of IMUs for measuring barbell velocity. A systematic review of Cochrane Library, EBSCO, PubMed, Scielo, Scopus, SPORTDiscus, and Web of Science databases was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. From the 161 studies initially identified, 22 were fully reviewed, and their outcome measures were extracted and analyzed. Among the eight different IMU models, seven can be considered valid and reliable for measuring barbell velocity. The great majority of IMUs used for measuring barbell velocity in linear trajectories are valid and reliable, and thus can be used by coaches for external load monitoring. Velocity-based training (VBT) is a resistance training method consisting of monitoring the velocity of movement displacement to support the regulation of load imposed on athletes ,2,3,4,5.If an athlete is to benefit from VBT, certain instruments should be used to ensure that the velocity of movements is accurately and precisely measured ,22. For IMU solutions use fusion sensing to estimate velocity . Thus, dOn the basis of the importance of confirming the validity and reliability of IMU devices, different original studies have reported the results for different models in the sports sciences community ,47,48,49While several systematic reviews have been published about the use of IMUs ,51,52,53The systematic review strategy was conducted according to PRISMA  guidelines . The proThe inclusion and exclusion criteria can be found in The screening of the title, abstract, and reference list of each study to locate potentially relevant studies was independently performed by 2 of the authors (F.M.C. and M.R.G.). Additionally, they reviewed the full version of the included papers in detail to identify articles that met the selection criteria. An additional search within the reference lists of the included records was conducted to retrieve additional relevant studies. A discussion was made in the cases of discrepancies regarding the selection process with a third author (Z.A.). Possible errata for the included articles were considered.Electronic databases  were searched for relevant publications prior to 1 January 2021. Keywords and synonyms were entered in various combinations in the title, abstract, or keywords:  AND  AND  AND (barbell OR bar). Additionally, the reference lists of the studies retrieved were manually searched to identify potentially eligible studies not captured by the electronic searches. Finally, an external expert was contacted in order to verify the final list of references included in this scoping review in order to understand if there was any study that was not detected through our research. Possible errata were searched for each included study.A specific Excel spreadsheet was prepared for data extraction  following the guidelines of Cochrane Consumers and Communication Review Groups . The sprThe following information was extracted from the included original articles: (i) validity measure  and (ii) reliability measure  and/or typical error of measurement (TEM) (%) and/or coefficient of variation (CV) (%) and/or standard error of measurement (SEM)). Additionally, the following data items were extracted: (i) type of study design, number of participants (n), age-group , sex , training level ; (ii) characteristics of the wearable wireless IMU and comparator ; (iii) characteristics of the experimental approach to the problem, procedures, and settings of each study.The STROBE assessment was applied by 2 of the authors (J.P.O. and M.R.G.) to assess the methodological bias of eligible articles following the adaptation of O’Reilly et al. . Each ofThe searching of databases identified a total of 159 titles . These studies, together with another two included from external sources, were then exported to reference manager software . Duplicates (71 references) were subsequently removed either automatically or manually. The remaining 90 articles were screened for their relevance on the basis of titles and abstracts, resulting in the removal of a further 55 studies. Following the screening procedure, 35 articles were selected for in-depth reading and analysis. After reading full texts, a further 13 studies were excluded due to not meeting the eligibility criteria .The overall methodological quality of the cross-sectional studies can be found in Characteristics of the included studies can be found in Among the included studies, 10 tested the back squat ,63,65,68Overall, eight different IMU models were tested, in which two studies were conducted using the Sensei Bar ,46, one n = 4). Other studies were reported to be valid (n = 18). For the Barsensei model, the SEE values of validity were between 0.03 and 0.06 m•s−1 [r were 0.18 m•s−1 and r = 0.79, respectively [−1 and 0.05 m•s−1 and Pearson’s r values were between 0.76 and 0.98 [−1 and 26.6 m•s−1 and Pearson’s r values were between 0.38 and 0.92, and 2R values were between 0.59 and 0.97 [−1 and 0.091 m•s−1 and Pearson’s r values were between 0.97 and 0.90, and 2R value was 0.85 [−1 and Pearson’s r values were between 0.009 and 0.60, and 2R values were between 0.95 and 0.77 [r values were between 0.84 and 0.93 [Information of the validity levels obtained in the included studies can be found in 06 m•s−1 . For theectively . For theand 0.98 ,34. For and 0.97 ,67,69. Fwas 0.85 ,48,64,66and 0.77 ,60,68. Fand 0.93 ,70.Information of the reliability levels obtained in the included studies can be found in This systematic review aimed to identify and summarize studies that have examined the validity of wearable wireless IMUs for measuring barbell velocity and identify and summarize studies that have examined the reliability of IMUs for measuring barbell velocity. The IMUs in this study were compared with gold standards and previously tested devices as reference systems , or deadlift. The experience or type of competitive level of the participants had no effect on the tests.In light of the findings revealed in the systematic review, sports scientists and practitioners should question the validity of the IMUs they use during exercises. Even if they do not have appropriate conditions to validate UMIs, it is recommended that they use validated equipment as shown by the data discussed in this systematic review.Twenty-one of the studies in this systematic review investigated reliability see . Overall−1 [−1 [−1 [Reliability findings of IMUs, according to the brands and methods for the BarSensei model, the ICC values of validity were between 0.273 and 0.451, and the CV values ranged between 10% and 30% . For the−1 ,48,64,66−1 [−1 ,62,68. F [−1 [−1 .In brief, the Myotest did not reveal enough levels of precision (reliability) for measuring countermovement jump, while Barsensei was not precise for measuring velocity in squat and back squat exercises. The Myotest, Push Bando, Wimu, and Pasco revealed precision for measuring the main weight-room exercises such as bench press, bench throw, squat (front and back), or deadlift. This is extremely important since instruments must be as must precise as possible in order to provide useful and sensitive information about readiness monitoring in sports, particularly for VBT.The studies discussed in this systematic review investigated the reliability of the devices in certain movement patterns in field conditions. According to the authors, it is thought that studies on the long-term use of investigations of the reliability of IMUs should be designed to minimize the variables that might arise as a result of biological differences in longer use. However, it is also thought that malfunctions in the software data flow originating from the manufacturer may occur, and the disruptions in this data flow may affect the data reliability in IMUs. It is thought that research should be conducted to examine whether software and mobile phone applications that reflect instant data of IMU models transmit data reliably in real time. Among the studies discussed in this systematic review, none considered this situation. At the same time, to the best of the authors’ knowledge, there is no study in the literature that investigates the effects of software data flows on reliability.Most of the research in this systematic review examined the validity and reliability of IMUs during movements performed in a single plane. This systematic review only tested the validity and reliability of the Flores et al.  Olympic The studies discussed in this systematic review generally consist of short-term research designs. Since IMUs are used by people with biological differences, it should be considered that long-term biological changes may affect the validity and reliability of IMUs in the long term. To the best of the authors’ knowledge, there are no studies examining the validity and reliability of long-term IMUs. For this reason, future studies should examine the validity and reliability of data to uncover insights about the long-term use of IMUs.There may be some factors affecting the validity and reliability of IMUs beyond those that researchers have considered in their experimental designs. Some of these factors may be caused by the manufacturer. For example, it is believed that data transferred to software and mobile phone applications in real time result in errors in validity and reliability due to software malfunctions. In order for sports scientists, practitioners, and strength training coaches to use IMUs in a valid and reliable way, the effects of software factors on data quality should be investigated in future studies.This present systematic review summarized evidence about the validity and reliability of IMUs for measuring barbell velocity. A total of eight models were tested across the 22 included articles. The Barsensei was not valid and reliable in the studies reports. The Gyko sport, Beast Sensor, and PASCO were valid and reliable in all reports. The Myotest, PUSH band, and Wimu RealTrack were valid and reliable in the majority of the reports. The Rehagait was valid. Therefore, from the eight included models, seven can be used with some evidence of being accurate and precise. This evidence provides important information for coaches who need accurate information about barbell velocity to control the external load imposed on athletes and to be sensitive to human variations without any meaningful bias generated by measurement instruments.


IntroductionIt is difficult to diagnose the symptoms of acute appendicitis in pregnant women due to its similarities with pregnancy physiology. In this study, we examined the diagnostic value of laboratory parameters in the diagnosis of acute appendicitis in pregnant women.Material and methodsForty-two patients who underwent appendectomy during pregnancy were evaluated. The demographic characteristics, laboratory parameters and imaging methods of the patients were examined. According to the pathology results, the patients were evaluated in two groups as normal appendix and acute appendicitis. In addition, a non-pregnant control group was formed to compare the results between the pregnant and control groups.ResultsThe mean age of the 42 patients was 30±6 years, and the pathology results were evaluated as normal in 16 (38.1%) of the patients. As imaging methods, ultrasonography was undertaken in all patients, with MRI being additionally performed in two patients. When the normal appendix and acute appendicitis groups were compared, no significant difference was observed in terms of laboratory parameters . The group that had undergone appendectomy had a significantly higher rate of negative appendectomy compared to the control group (P=0.001).ConclusionLaboratory parameters alone cannot be sufficient for the diagnosis of acute appendicitis in pregnant patients. If clinical examination, laboratory parameters and USG are not sufficient for diagnosis, MRI is the imaging method that should be considered to reduce negative appendectomy rate. Acute appendicitis is the most common surgical pathology diagnosed in patients admitted to emergency departments with abdominal pain . ClinicaDiagnosis of acute appendicitis is often challenging and involves a synthesis of clinical, laboratory, and radiological findings . PregnanAlthough there is no specific laboratory marker for the diagnosis of appendicitis, various parameters, such as white blood cell (WBC) count, C-reactive protein (CRP), neutrophil-lymphocyte ratio (NLR), and platelet-lymphocyte ratio (PLR) are used to diagnose acute appendicitis . In our Patient dataThe approval for the study was obtained from the local ethics committee . Using the database of Ankara City Hospital, 3,132 women aged 18 and over, who underwent appendectomy between January 2015 and July 2020, were retrospectively analyzed. Forty-two patients who underwent appendectomy during pregnancy were included in the study. Open appendectomy was performed in all patients and. Diagnostic or therapeutic laparoscopy was not performed. Laboratory parameters were obtained from blood samples taken at the time of admission to the hospital. The pre-diagnosis of acute appendicitis was made by evaluating the physical examination, laboratory and radiological findings of the patients together. For all patients, the demographic characteristics, neutrophil count, lymphocyte count, white blood cell count, platelet count, NLR, PLR, mean platelet volume (MPV), red cell distribution width (RDW), week of gestation, fetal (abortus) and maternal complications (simultaneous cesarean section), and imaging methods used were evaluated. According to the pathology results, the patients were examined in two groups as normal appendix and acute appendicitis. In addition, the patients with acute appendicitis were evaluated in subgroups as simple and complicated appendicitis . The control group was randomly formed at one to two ratio with female patients in the same age range, who had undergone open appendectomy but not during pregnancy.Statistical analysisData analysis was carried out using SPPS v. 15 for Windows . The normality tests were performed using the Kolmogorov-Smirnov test. The descriptive statistics of normally distributed continuous variables were given as mean ± standard deviation (SD), and the descriptive statistics of non-normally distributed continuous variables were expressed as median (interquartile range) values. The inter-group differences of normally distributed variables were analyzed with Student’s t-test, while those of non-normally distributed variables were analyzed using the Mann-Whitney U test.The mean age of the 42 patients who had undergone appendectomy during pregnancy was 30±6 years. According to the pathology results, 16 (38.1%) patients had a normal appendix. There was no statistically significant difference between the two groups in terms of age, leukocyte count, neutrophil count, lymphocyte count, RDW, MPV, platelet count, NLR, and PLR . While abortus was seen in the first trimester, maternal complications were seen in the third trimester, and there was no significant difference between the groups in terms of complications (P>0.05). Of the 16 patients in the normal appendix group, seven (43.7%) were in the first, five (31.3%) were in the second and four (25%) were in the third trimester. In the acute appendicitis group, 13 (50%) of the 26 patients were in the first trimester, eight (30.8%) in the second trimester, and five (19.2%) in the third trimester. There was no significant difference between the groups in relation to trimesters (P>0.05) .When the 42 patients who had undergone appendectomy during pregnancy were compared with the 107 patients in the control group, it was observed that the rate of negative appendectomy during pregnancy was statistically significantly higher in the former (38.1%) than in the latter (13.%) (P=0.001). However, no statistical difference was detected in the rate of complicated appendicitis (P=0.723) (Table Pregnant women are less likely to have a classic presentation of appendicitis, but the most common symptom of appendicitis, such as pain in the lower right quadrant, occurs near McBurney's point in most pregnant women, irrespective of the stage of pregnancy . DiagnosIn our study, the laboratory parameters such as WBC, NLR, PLR, MPV, were not found significant for the diagnosis of acute appendicitis in pregnant patients. But Yazar et al.  determinIn this study, the imaging method used in all of our patients was ultrasonography, with MRI being additionally undertaken in two patients, and the rate of negative appendectomy was found to be 38.1%. It was observed that the rate of negative appendectomy in our study was high among pregnant patients. In the control group of our study, the rate of negative appendectomy was found to be 13.08%. In the literature, the rate of negative appendectomy differs, being reported as 30% by Arer et al. , 14.9% bAlthough negative appendectomy rate in our study is similar to some studies in the literature, it can be qualified as high. We consider that the negative appendectomy rate was high in our sample due to the limited use of MRI in pregnant patients. We think that if MRI had been performed on all patients, the high rate of negative appendectomy could have been reduced.The limitation of the present study is its retrospective design based on analysis of patient records and a relatively small sample size.In conclusion, diagnostic difficulties still continue in pregnant women who are considered to have appendicitis. Laboratory parameters alone are not sufficient for the diagnosis of acute appendicitis in pregnant patients. In cases that cannot be diagnosed with clinical examination, laboratory parameters and USG, if clinical suspicion of acute appendicitis still persists, MRI is the imaging modality that should be considered for diagnosis.


Korean elementary school students have the lowest life satisfaction levels among OECD countries. The use of smart devices has led to smartphone addiction, which seriously affects their quality of life. This study aims to establish and test variables that affect the quality of life (QOL) of elementary school students based on the Predisposing, Reinforcing and Enabling Constructs in Educational Diagnosis and Evaluation (PRECEDE) model, using smart device-related parental intervention, self-efficacy, social support, health promotion behaviors, family environment, smart device addiction, and QOL as measurement variables. Three elementary schools in the Republic of Korea completed self-report questionnaires. Descriptive statistical analysis and hypothetical model fit and test were used for data analysis. The model was found to be valid. Smart device addiction directly affected QOL. In contrast, health promotion behaviors, self-efficacy, social support, and smart device parental intervention indirectly affected QOL. Health-promoting behaviors also directly affected smart device addiction, self-efficacy, and family environment had a direct effect on health-promoting behavior. Therefore, to improve the QOL of elementary school students, the government should focus on developing programs that can help them actively perform health promotion activities and improve self-efficacy, social support, and parental intervention for smart devices that indirectly affect them. The life satisfaction level experienced by elementary school students in Korea was the lowest among 30 OECD countries in 2013 [Among elementary school students from the fourth to the sixth grade in Korea, the smartphone ownership rate is 74.2% [Smart devices are multimedia devices that emphasize portability with smartphones, tablet PCs, and other electronic devices that can be operated with fingers or touch pens . Smart pAccording to the National Survey on Internet and Smartphone Usage of 2018, smartphone dependency is increasing in the first to third grades of elementary school . In addiOne of the key variables involved in the use of smart devices by elementary school students is health promotion. Health promotion behavior refers to a multi-dimensional pattern in which self-realization, the individual’s level of well-being, and satisfaction are maintained and strengthened by habitual behavior regardless of the disease . Health Positive parenting of children at home is the best way to prevent smart device addiction . TherefoSelf-efficacy is the judgment and belief in one’s ability to overcome a situation on one’s own and to execute a task entrusted to them successfully . It has Green and Kreuter (2005) proposed the Predisposing, Reinforcing and Enabling Constructs in Educational Diagnosis and Evaluation (PRECEDE) model which evaluates several stages of diagnosis to understand health-related factors on QOL. The PRECEDE model has been used to plan and assess health promotion programs to address health issues . To dateThe current study established and verified a structural equation model (SEM) based on the PRECEDE model by selecting smart device addiction, health promotion activities, home environment, self-efficacy, social support, and smart device parent arbitration as factors affecting the QOL of elementary school students using smart devices. We further identified causality and influence through each step of the diagnosis.This study aimed to identify factors affecting the QOL of elementary school students in relation to their use of smart devices, by applying the PRECEDE model, and to establish a hypothesis model to verify the validity of the model.Specific research objectives were as follows.(1)Suggest a hypothetical model that explains the QOL of elementary school students using smart devices based on the theoretical background.(2)Test the suitability between the hypothetical model and the actual data and constructs and verify the structural model of the variable relationship.(3)Identify direct and indirect effects among variables affecting QOL and establish their mutual causal relationships.Based on the PRECEDE theory of Green and Kreuter (2005), this study identified factors affecting the QOL of elementary school students using smart devices through a literature review and established a theoretical framework . SpecifiHealth promotion behavior was selected as a behavioral factor, and environmental factors that affected smart device addiction, and attachment and communication between parents and children were included as family environmental factors. Prior studies have shown that the more the Internet game addiction is severe, the less likely people are to engage in health promotion activities ,27. For Self-efficacy was set as a predisposing factor, social support as a reinforcing factor, and smart device parent arbitration as an enabling factor. The lower the self-efficacy, the higher the degree of Internet addiction ,29. If sBased on the theoretical framework of this study and the results of prior studies, the paths between the variables were determined, and a hypothesis model was established, as shown in This structural model study built a hypothesis model based on the PRECEDE model to identify factors affecting the QOL of elementary school students on the use of smart devices and verified the suitability of the model and the hypotheses presented in the model through the collected data.The participants included fourth, fifth, and sixth graders from elementary schools in Daejeon and Sejong city, who gave their written consent to participate in the study. A sample size of 200 was recommended for the maximum likelihood estimation (MSE) most used in structural equations, with 10 to 20 times the observed variable allowance being recommended for the number of samples required . This stThe general characteristics of the respondents included gender, grade, daily time use of smart devices, and frequency of use. To ensure the validity of the instruments used in this study, confirmatory factory analysis (CFA) was conducted.Based on Bandura’s theory, the self-efficacy instrument developed by Sherher and Mddux  was tranThe social support instrument developed by Dubow and Ullman  was modiSmart device parental intervention was measured by an instrument that Park  modifiedThis study used a health promoting behavior tool that No  construcParent–child communication: This study used the parent–child communication instrument developed by the Korean Institute of Criminology  and modiParent–child attachment: This study used the parent–child attachment instrument developed by Riner  and tranThis study used the smart device addiction instrument that Jeong  modifiedThis study used a youth self-reported instrument for the PedsQLTM 4.0 Generic score scale developed by Varni  and valiData collection was conducted by one researcher and two research assistants from July to September 2018. Elementary schools located in Deajeon city and Sejong city received written consent from their guardians, explained the purpose of this study to the subjects, and conducted surveys to students who agreed to participate in the study. The survey took 30 min to complete, and participants could withdraw from the study at any time. Those who participated in the study received a small compensation.The collected data were analyzed at a significance level of 0.05 using SPSS version 23  and AMOS 21 . The verification of the general characteristics and normality of the subjects were analyzed using descriptive statistics. Correlation and multicollinearity between the variables were analyzed using Pearson’s correlation coefficient, and the verification of the normality of the samples was confirmed using skewness and kurtosis.2 verification, χ2/df, goodness of fit index (GFI ≥ 0.9), root mean square residual (RMR ≤ 0.05), and root mean square error of approximation (RMSEA = 0.05∼1). This study used the following incremental fit indices: normed fit index (NFI ≥ 0.9), incremental fit index (IFI), comparative fit index (CFI ≥ 0.9), and Tucker–Lewis index (TLI ≥ 0.9). Moreover, the parsimonious fit index was analyzed using the adjusted goodness of fit index (AGFI ≥ 0.9) and the parsimonious normalized fit index.Confirmatory factor analysis (CFA) was performed to verify the validity of the instrument by applying ML (perform bootstrap = 500). The fit indices were χp values, and the explanatory power of the endogenous variables was confirmed by the estimate of squared multiple correlation (SMC). Bootstrapping (=500) was used to test the statistical significance of the total, direct, and indirect effects of the hypothesis model.The significance test of the paths of the hypothesized model was confirmed by the standardized regression weight, critical ratio, p < 0.001; F = 5.554, p < 0.001). Specifically, the group that used smart devices for 10 to 30 min a day had a higher QOL than the other group.The mean scores for smart device parent intervention, social support, and self-efficacy were 2.57, 4.10, and 3.63, respectively. In addition, the mean scores of respondents’ health promotion, smart device addition, and QOL were 3.10, 2.30, and 4.36, respectively. In this study, the absolute values of skewness and kurtosis were less than 2 and 7, respectively, indicating that they were normally distributed. In addition, the correlation among the study variables were all less than 0.70, the tolerance limit was greater than or equal to 0.10, and the variance inflation factor (VIF) was less than 10; therefore, it was confirmed that no problem of collinearity was found among the study variables .This study identified convergent validity and discriminant validity to determine whether the construct concept was accurately measured by the variables. As a result of checking the average variance extracted (AVE) and reliability, AVE was found to have met the score of 0.5 or higher, and concept reliability was more than 0.7, making it more relevant. The mean variance extraction (AVE: 0.541–0.977) was found to be greater than the square of the correlation coefficient value (0.0002–0.456) among the latent variables, and the discriminant validity was satisfied.2/df was 2.48, fit below 3, and other indices  met the criteria. Incremental fit indices  were appropriate. The AGFI, which is distributed between 0 and 1, was 0.84 and PNFI was 0.68, indicating that PNFI was greater than 0.6. Overall, the goodness of fit index met the criteria and was determined as the final model because it was assessed to be parsimonious.As a result of the fitness test of the hypothetical model, χAs a result of analyzing the hypothetical model of this study, eight of the 13 paths were statistically significant. The coefficients and significance test results for each path are shown in p = 0.002) with 11.3% explanatory power. The variable that affects self-efficacy was social support, with 13.5% explanatory power . The variables that affect the family environment are social support  and smart device parent intervention , which have 72.3% explanatory ability power to describe the family environment. Variables affecting health-promoting behaviors were self-efficacy  and family environment , with a 54.9% explanatory power to describe health-promoting behaviors and 26.5% explained. The variables that significantly affected the QOL were smart device addiction , which had a 43.1% explanatory power for the QOL.The variable that affects social support is smart device parent intervention  had a significant direct effect on social support, and social support  had a significant direct effects on self-efficacy. Self-efficacy  and family environment  had direct effects on health-promoting behaviors. Social support  and smart device parent intervention  had indirect effects on health-promoting behaviors. Social support  and smart device parent intervention  had direct effects on family environment.The results of the analyses of the direct, indirect, and total effects of the hypothesis model were as follows: smart device parent intervention . Family environment , self-efficacy , and social support  had indirect effects on smart device addiction. Smart device addiction  had a direct effect on QOL, and health-promoting behaviors , self-efficacy , social support , and smart device parent intervention  had indirect effects on QOL.Health-promoting behaviors for smart device addiction had a direct effect , social support (reinforcing factors), parent intervention of smart devices (enabling factors), and family environment and health promotion behaviors  that affect the quality of life of elementary school students using smart devices.The variables that had the greatest influence on the quality of life of elementary school students in relation to the use of smart devices were smart device addiction and health-promoting behaviors. Self-efficacy, social support, and smart devices parent intervention indirectly affected their QOL. Health promotion behaviors affected smart device addiction, self-efficacy and family environment affected health-promoting behaviors, and social support and smart device parent intervention affected the family environment. Based on these variables, we actively encourage developing strategies to improve the quality of life of elementary school students who use smart devices.This study could be used as a basis for the practical usefulness of elementary school students’ QOL concepts, as it has identified the factors affecting elementary school students’ QOL using smart devices in a multi-dimensional manner, by applying the PRECEDE model. To improve the quality of life for elementary school students, schools and families are recommended to provide counseling by assessing the degree of addiction to smart devices and to apply education mediation programs at practical sites that increase health promotion activities. Furthermore, the PRECEDE model needs to be retested through repeated studies involving various variables related to the use of smart devices for elementary school students.


Preoperative distinction between transitional meningioma and atypical meningioma would aid the selection of appropriate surgical techniques, as well as the prognosis prediction. Here, we aimed to differentiate between these two tumors using radiomic signatures based on preoperative, contrast-enhanced T1-weighted and T2-weighted magnetic resonance imaging. A total of 141 transitional meningioma and 101 atypical meningioma cases between January 2014 and December 2018 with a histopathologically confirmed diagnosis were retrospectively reviewed. All patients underwent magnetic resonance imaging before surgery. For each patient, 1227 radiomic features were extracted from contrast-enhanced T1-weighted and T2-weighted images each. Least absolute shrinkage and selection operator regression analysis was performed to select the most informative features of different modalities. Subsequently, stepwise multivariate logistic regression was chosen to further select strongly correlated features and build classification models that can distinguish transitional from atypical meningioma. The diagnostic abilities were evaluated by receiver operating characteristic analysis. Furthermore, a nomogram was built by incorporating clinical characteristics, radiological features, and radiomic signatures, and decision curve analysis was used to validate the clinical usefulness of the nomogram. Sex, tumor shape, brain invasion, and four radiomic features differed significantly between transitional meningioma and atypical meningioma. The clinicoradiomic model derived by fusing the above features resulted in the best discrimination ability, with areas under the curves of 0.809  and 0.795  and sensitivity values of 74.0% and 71.4% in the training and validation cohorts, respectively. The clinicoradiomic model demonstrated good performance for the differentiation between transitional and atypical meningioma. It is a quantitative tool that can potentially aid the selection of surgical techniques and the prognosis prediction and can thus be applied in patients with these two meningioma subtypes. Meningiomas are the most common primary intracranial tumors in adults, accounting for 36.7% of all intracranial tumors . AccordiAccording to the European Association of Neuro-Oncology (EANO) guidelines, magnetic resonance imaging (MRI) is the main method used in the provisional diagnosis of meningiomas . At presGiven the above reasons, it is necessary to explore the imaging differences between AM and TM. Radiomic analysis is a reliable tool that can quantify high-dimensional tumor features that cannot be observed with the naked eye, such as intensity, texture, and shape features , 16. In To the best of our knowledge, this is the first study to differentiate TM from AM based on texture feature or radiomic analysis. Therefore, our study aimed first to identify MR and radiomic features that are associated with these two tumors from two MRI modalities [T2-weighted (T2) and T1-weighted post-contrast (T1C)]; second, to combine these two modalities generating a radiomic signature; and third, to build a nomogram fusing clinical factors, MR features, and radiomic signatures to differentiate TM from AM in MRIs of patients with suspected meningioma.For this retrospective analysis, ethical approval was obtained from the Institutional Review Board of Lanzhou University Second Hospital, and the requirement for informed consent was waived. In this study, all patients with TM and AM who underwent surgery in our institute between January 2015 and December 2019 were enrolled according to the following inclusion and exclusion criterias. The inclusion criteria were: (a) histological diagnosis of AM or TM, and (b) MRI, including T1C and T2 sequences, performed within 1 week before surgical tumor resection. The exclusion criteria were: (a) cases with motion artefacts that impacted the assessment; (b) incomplete MRI sequences; and (c) treatment such as radiotherapy, chemoradiotherapy, or surgery before surgical tumor resection.All tumors were resected with the aid of a microscope. Patients with TM and AM were diagnosed according to the pathological findings. Finally, a total of 242 patients  were enrolled. All patients were randomly divided into a training cohort and a validation cohort in a 7:3 ratio. The patient recruitment flowchart is shown in https://wiki.nci.nih.gov/display/CIP/VASARI) feature set. Brain invasion was diagnosed by pathology. Bone invasion assessments were performed by pathology and surgeon assessment intraoperatively. Sinus invasion was evaluated by an intraoperative neurosurgeon as a diagnostic standard.Two radiologists  independently analyzed the MRI characteristics . The image analysis was based on clinical experience. Both readers were blinded to all personal information and the histopathological results before analysis. For qualitative data, agreements were reached after discussion between the two in cases of difference of opinions. When the two readers were unsure, reader 3 (ZYZ) with 19 years of experience confirmed the results. For quantitative data, reader 1 measured the maximum diameter three times on the maximum level of the tumor, and calculated the average of three measurements. Reader 2 performed the data measurement in the same way. The final result was the average of the measurement values of two readers to minimize the deviation of the measurement results. Among MR features evaluation, peritumoral edema was evaluated on T2 images according to the standardized visually accessible Rembrandt Images . The MR sequences included T1C and T2 images, and the detailed parameters of each scanner are shown in www.itksnap.org). On both axial T1C and T2 images, the regions of interest (ROIs) of images were manually delineated on each slice of the entire tumor including hemorrhagic, necrotic lesions and without the surrounding brain tissue, and oedema. T2 images were segmented with reference to T1C images for visual guidance. The segmented tissues on each slice were fused together to generate the volume of interest, as shown in Two radiologists (TH and JZ) without prior knowledge of the pathological records manually segmented MR images using the open-source software ITK-SNAP  are described in Supplementary Material.The PyRadiomics platform was used to extract standardized radiomic features from the T1C and T2 imaging data . In thisP-value of less than 0.05 were selected. For clinical factors and MRI features, the correlation between these two factors and discrimination of AM and TM were tested via Student’s t-test and the chi-square test with the P-value set to 0.05. Then, stepwise multivariate logistic regression further selected the most informative features and deleted irrelevant features. Features with a P-value of less than 0.05 and preoperative factors were included in the model. Spearman correlation analysis was conducted to examine the correlation between the selected radiomic features and clinicoradiological features to determine whether these features are correlated with each other.For both T1C and T2 features, the least absolute shrinkage and selection operator (LASSO) regression with five-fold cross-validation was conducted to select the radiomic features highly correlated with discrimination of TM and AM , and the T2 model was built based on T2 features (two features), whereas the fusion model was built based on T1C and T2 fusion features . The clinical model was built based on a clinical factor (sex) and MRI features (tumor shape and brain invasion). Thus, the clinicoradiomic model was built by incorporating the clinical factor, MRI features, and the radiomic signature. In the training cohort, the maximum area under the receiver operating characteristic curve (AUC) with three-fold cross-validation determined the final regularization parameter.P-values indicated whether the improvement in reclassification was statistically significant after the inclusion of a new factor in the model. In addition, we used the DeLong test to compare the AUC estimates of the performance between different models.Integrated discrimination improvement (IDI)  was usedAfterward, a nomogram for clinical usefulness incorporating the radiomic signature and the correlated clinicoradiological features was constructed in the training cohort and validated in the validation cohort. The calibration curves assessed the discrimination ability of the nomogram for the training and test cohorts, and the Hosmer-Lemeshow test evaluated the agreement between the discrimination of TM from AM and the observed outcomes. Then, we used decision curve analysis (DCA) to quantify the net benefits at different threshold probabilities to evaluate the clinical efficacy of the nomogram .http://www.Rproject.org). R was also used to assess the prediction models. PyRadiomics was used to extract and select the radiomic features, as well as to build the prediction models. The Spearman correlation test was used to explore differences between clinicoradiological features and radiomic features. Student’s t-test and the chi-square test were used to compare continuous and categorical variables, respectively. Generally, two-sided P-values less than 0.05 were considered statistically significant. The intra-/inter-class correlation coefficients (ICCs) were used to assess the agreement of the two MR scanners and the extracted features by two radiologists.In this study, all statistical analyses were performed with R software  between the TM and AM groups, whereas age did not differ significantly (P > 0.05). For MR features, the parameters maximum diameter, tumor shape, peritumoral edema, enhanced features, bone invasion, and brain invasion were significantly different  in the univariate analysis. Among them, tumor shape and brain invasion were highly correlated with discrimination of TM from AM and can be used as independent predictive factors according to the multivariate logistic regression analysis. By contrast, tumor location, tumor border, dural tail sign, T2 signal, and sinus invasion were not significantly different  between the TM and AM groups.The clinical factors and MR features of the patients are shown in P < 0.05; The ICCs were calculated to evaluate the agreement of the two MR scanners and the features extracted by two radiologists, respectively. All values exceeded 0.75, reflecting good agreement. In total, 2454 radiomic features were extracted from each patient. Among them, two T1C features and two T2 features were selected, and all four radiomic features  were significantly different between the TM and AM groups . Thus, the radiomic signature, sex, tumor shape, and brain invasion were selected for the clinicoradiomic model building. The radiomics scores in the AM group were significantly higher than those in the TM group in the different models, as shown in the T1C and T2 radiomic features may correspond to different information. Though fusing the selected radiomic features, the radiomics signature can reflect the discrimination factors of TM and AM from different perspectives. Stepwise multivariate logistic regression analysis showed that sex, tumor shape, and brain invasion were significantly different between TM and AM groups , clinical, and the clinicoradiomic models are shown in P = 0.002) and 9.96% (P < 0.001) compared to the radiomic model in the training and validation cohorts, respectively. The comparisons between different models are shown in P value was 0.014 and 0.004 respectively, and there is no statistical significance in the validation cohort.The IDI index was calculated to assess the predictive usefulness of the different models. The clinicoradiomic model improved the integrated discrimination by 5.75%  model of radiomics showed good discrimination ability in both training  and validation  cohorts. Moreover, the nomogram incorporating clinicoradiological and radiomic features demonstrated the best performance in both training  and validation  cohorts.This is a preliminary study to develop a clinicoradiomic model that discriminates TM from AM based on MRI. The discrimination ability of this fusion model was validated Among clinical factors, sex was only the parameter that was significantly different between TM and AM. Females 86.5%) were prone to TM, whereas the male-to-female ratio was balanced in AM , which is consistent with the results of other studies , 25. Amo6.5% wereAt present, MR radiomics can reproducibly extract objective and quantitative data from different sequences  to diagnostically discriminate meningiomas from other tumor forms, such as craniopharyngioma from meningioma in the sellar/parasellar area  or maligWe also analyzed the correlation between clinicoradiological factors and radiomic features using Spearman’s correlation analysis. We found that some clinicoradiological factors were consistent with some radiomic features extracted from MR images in both training and validation cohorts. This revealed that clinicoradiological features also reflected some radiomic MRI features. For example, shape was correlated with T1C_WaveletGLSZMwavelet.HHL_GraylevelNonUniformity and T1C_SquareRootGLSZM_squareroot_zoneEntropy in both training and validation cohorts. This indicated that some radiomic features corresponded to tumor shape in MR images, such as entropy in GLSZM. The correlation between these features revealed that some specific feature combinations may be explained by some clinicoradiological features to some extent. Besides, the included four features were extracted from different sequences, and the combination of T1C and T2 models of radiomic features indicated a better discrimination ability than the T1C or T2 models alone. These results indicated that different sequences provided distinct information, and multiple sequences could show more information about tumors and increase the discrimination ability of the model. After Delong test, we found that the discrimination ability of clinicoradiomic model is better than that of Clinical and T2 models. However, there is no statistical significance in the validation cohort, which may be related to the small sample size of the validation cohort. This result indicated that we should include more data in future study to improve the performance and stability of the model. At present, the clinical application of radiomics is still in the exploratory research stage, and it needs time to accumulate. Radiomics-derived data, when combined with other pertinent data sources , can produce accurate robust evidence-based clinical-decision support systems .The nomogram incorporating clinicoradiological factors and radiomic features showed the best discrimination ability compared to radiomic models based on T1C, T2, T1C/T2 images, and clinicoradiological factors. The results indicated that fusing clinicoradiological factors and radiomic features significantly improved classification performance. Combining qualitative and quantitative imaging analyses provided an additive effect because the information contained in these features was complementary . PreoperOur study has several limitations. First, the analysis of MRI characteristics was independently performed by two radiologists, and imaging assessments are subjective. Second, we selected the T1C and T2 sequences for this study. On T2 images, the tumor had unclear boundaries in some cases. Although we referred to the T1C sequences for visual guidance to delineate tumor borders, there were still deviations. Third, our study was a single-center study, and a multi-center external validation is needed to test the generalizability and robustness of the model in the future. In addition, two neuroradiologists spent plenty of time to manually delineate two independent VOIs of tumors for each MRI sequence in this study, thus, efficient automatic segmentation and co-registration was available for meningiomas in the future research. In future, multimodal studies such as DWI and FLAIR sequences could be combined to improve accuracy.Preoperative identification of TM and AM would aid the clinical decision-making and prognosis prediction. In the radiomic analysis, four radiomic features were highly correlated with the discrimination between these two tumors. After the fusion of T1C and T2 features, the MRI-based radiomics signature effectively identified TM and AM on MR images. The clinicoradiomic model that combined the radiomic signatures and clinicoradiological factors showed the best discrimination ability and may be used in patients with TM and AM.The original contributions presented in the study are included in the article/The studies involving human participants were reviewed and approved by For this retrospective analysis, ethical approval was obtained from the Institutional Review Board of Lanzhou University Second Hospital, and the requirement for informed consent was waived. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.JZ, GZ, JLZ, KC, and YC contributed to conception and design of the study. TH organized the database. JR performed the statistical analysis. JZ wrote the first draft of the manuscript. ZZ, JR, YC, and GZ wrote sections of the manuscript. All authors contributed to manuscript revision, read, and approved the submitted version.This study was supported by grants of National Natural Science Foundation of China (82071872), Doctoral Research Startup Fund of Zunyi Medical University (BS2021-03), Technology Plan Project of Guizhou Province [Qiankehe Support (2020) No. 4Y179], and Science and Technology Fund Project of Guizhou Provincial Health Commission (gzwkj2021-375).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. 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To describe the factors associated to stunting in <5-year-old Yanomami Brazilian children, and to evaluate the association of short maternal stature to their offspring’s stunting. A cross-sectional study carried out in three villages in the Yanomami territory. We performed a census, in which all households with children < 5-years-old were included. The length/height-for-age z-score <−2 standard deviations was used to classify the children as stunted. Short maternal height was defined as <145 cm for adult women, and <−2 standard deviations of the height-for-age z-score for adolescent women. We used adjusted Poisson regression models to estimate prevalence ratios (PR) along the 90% confidence interval. We evaluated 298 children. 81.2% of children suffered from stunting and 71.9% of the mothers from short stature. In the bivariate analysis, a significant association of stunting with short maternal stature, gestational malaria and child’s place of birth were observed. Considering the variables of the children under five years of age, there were significant associations with age group, the child’s caregiver, history of malaria, pneumonia, and malnutrition treatment. In the adjusted hierarchical model, stunting was 1.22 times greater in the offspring of women with a short stature (90% CI: 1.07–1.38) compared to their counterparts. Brazilian Amazonian indigenous children living in a remote area displayed an alarming prevalence of stunting, and this was associated with short maternal height, reinforcing the hypothesis of intergenerational chronic malnutrition transmission in this population. In addition, children above 24 months of age, who were born in the village healthcare units and who had had previous treatment in the past for stunting presented higher rates of stunting in this study. Stunting, defined as the height-for-age deficit, not only raises the risk of mortality and incapacity in childhood , but is In general, the indigenous peoples of Latin America have been an ethnical group disproportionately less favored . IndigenThere is evidence that short maternal height negatively influences the growth of linear offspring , which pRecognizing the worrisome nutritional situation in indigenous children, the investigation of its determinants remains an important challenge not only for sanitary authorities, but also for healthcare workers and professionals . TherefoAuaris and Maturacá in the Brazilian Amazon. Two villages in the Maturacá region were included in the study, namely Ariabú and Maturacá  covers 9,664,975 hectares, bordering with Venezuela. This study was conducted with children under 5 years of age and their mothers, in the administrative regions Maturacá .Auaris region is located in the extreme north of the state of Roraima, one of the areas with the highest population density of the YIT  using data collection questionnaires. When key-informants did not speak Portuguese, a local translator mediated the interviews. The consent to participate was obtained through signature (or fingerprint) of the informed consent.A cross-sectional census study was conducted between 9 and 22 December 2018 in the ® stadiometer with an infantometer adaptor with a precision of 0.1 cm (length measure) and a Seca® portable digital scale (model 877) with maximum capacity of 150 kg and a precision of 0.1 kg.To measure the height and weight of participants we used the following equipment: vertical anthropometer or Alturexata® [® [We used the WHO-Anthro®  and WHO-® [®  programsWe classified children as stunted and adolescent women with a short stature if they presented a length/height-for-age z-score less than −2 standard deviations of the median population of reference, according to the WHO Growth Charts.Anthropometric information of six children was excluded from the analysis due to congenital malformations and implausible values of the length/height-for-age z-scores. No adolescent mother showed implausible z-score values ,18. For Auaris; Maturacá; Ariabú); (ii) parent knowledge (read or write) in Portuguese ; (iii) home source of income ; (iv) household water source for human consumption ; (v) waste management ; (vi) household wall-type ; (vii) household density .The following sociodemographic characteristics were considered: (i) region/village of residence .The maternal characteristics considered were: (i) age group ; (ii) short stature ; (iii) number of antenatal consultations ; (iv) gestational malaria history ; (v) children’s place of birth  sex ; (ii) age group ; (iii) child’s main caregiver ; (iv) weight at birth ; (v) previous pneumonia treatment ; (vi) previous malnutrition treatment ; (vii) previous malaria treatment .Differences between proportion were assessed using the Pearson chi-square test. The Crude-Poisson regression, adjusted to covariables with consistent covariance matrix estimator type HC2, was used to estimate the Prevalence Ratio (PR) for stunting .p value < 0.20 to further adjust the analysis, using an hierarchical framework based on previous studies [In the crude analysis, we selected variables with a  studies . The conp-values < 0.10 in each level to the final adjust model. Pre-selected variables in each level were retained in the subsequent models, independent of their p-value. Additionally, the interaction between household wall-type and place of birth was tested in the final adjusted model, considering a p-value < 0.10. After the first selection, we used the backward method to select variables associated at n = 298), we adopted p-values of 0.10 and 0.20 as statistically significant in order to guarantee that any effects from the studied variables could be tested. However, it is worth remembering that we carried out a census in the investigated villages, and all children under 5 years of age were included in the study. The villages included in the present study were based in hard-to-reach areas of the Brazilian Amazon. Due to the small sample size  and the lowest in Ariabú (76.2%). Considering only children older than 12 months of age, stunting prevalence was superior to 85%, and in the age-group ranging from 24 to 59 months of age stunting was superior to 90%, regardless of region/village. The prevalence of short maternal stature was 71.9%  (Auaris (87.7%) and the lowest in mothers in Ariabú (65.0%) regions/villages.The prevalence of stunting among indigenous children under 5 years of age was 81.2% , varyingn = 4.3) . SimilarAuaris did not know how to read and write in Portuguese (44.9%). Similarly, the stunting frequencies were higher among families that dispose household waste in the river or the forest (92.4%), households with no regular income (65.4%), and households with clay walls (74.4%) .When comparing the sociodemographic characteristics between the villages, we observed that most fathers in  (74.4%) . FurtherRegarding sociodemographic variables, only household wall-type was shown to be significantly associated with stunting . We founIn the hierarchical multiple regression analysis, which included the interactive term between household wall-type and child’s place of birth, the final model indicated a stunting risk of 22% (7–38%) higher in children whose mothers with a short stature, compared to those with normal stature .We described an alarming prevalence of stunting among Brazilian indigenous children living in the Amazon. Additionally, we found a significant association between short maternal stature and stunting in the offspring. Such findings reinforce the hypothesis of intergenerational transmission of stunting in Yanomami indigenous people, highlighting the precarity of health and nutrition conditions in these settings.Stunting prevalence varies markedly across regions of the world. Recent evidence suggests that stunting occurs in 39.0% and 55.0% of African and Asian children under five, respectively ,23. In BScientific research on the determinants of the nutritional status in indigenous children under five years of age can improve public policies and reduce social inequalities in health, fostering social protection mechanisms. At the same time, the association between short maternal stature and stunting in our study showed not only an intergenerational effect but reinforces previous findings of the high burden of stunting in Yanomami children, as well as the need for interventions aimed at breaking down the cycle of sickness and death that remain for decades ,28,29,30The critical scenario revealed in this study confirms that the high rates of stunting persist for a long time in the Yanomami Indigenous territory as a result of not only a permanent state of food insecurity but also due to structural racism historically imposed by the Government. In contrast with the goals of the 2030 Agenda for sustainable development , which aThroughout history, the indigenous people have been marginalized, discriminated against, and exploited by Western society. In turn, the Government has not implemented inclusive and sustainable public policies to reduce poverty and starvation and promote reparation for the violations suffered by these peoples. In addition, the Government continues to deny them access to essential public services, such as health, sanitation, education, employment, and income, as well as the rights to self-determination and the control over natural resources existing on their traditional territories. Moreover, in the last couple of years, several bills have been presented to the parliament in order to reduce rights assured in the Brazilian Federal Constitution. Therefore, we consider that the path to sovereignty should be built in another way, putting on the indigenous people at the center of the debate, valorizing their culture and their traditional knowledge, in order to attain a fairer and equitable society, where no child, no citizen and no nations will be left behind.A recent analysis regarding ethnic inequalities in the prevalence of stunting in children under 5 years of age in 13 Latin American countries showed a highly unfavorable situation for indigenous populations. The polled prevalence ratio of stunting for all countries was 1.34 (CI 95% 1.28 to 1.39) for indigenous children compared to non-indigenous children, even after adjustments were made to household wealth and place of residence . AlthougThe well-known intergenerational transmission of poverty and some critical prenatal determinants play a significant role in the high burden of stunting in many parts of the world. The more precarious the living conditions, the worse the malnutrition indicators in children, notably the stunting cases . This phFood insecurity leads to the reduction in quantity and quality of consumed foods, as well as changing eating habits, due to lack of money or the absence of other material resources. This combination of factors acting together negatively affects the nutritional status, health and welfare of families . There iIt is important to point out that, historically, indigenous people have been exposed to high loads of infectious and parasitic diseases, both in terms of frequency and seriousness of the reported clinical conditions ,38. In tOne of the long-term consequences of stunting in childhood is the short stature in adulthood . MothersIn turn, a study using data from birth cohorts carried out in five low- or middle-income countries  showed that mothers with a stature shorter than 150.1 cm presented a 3.2 times higher probability of having children with stunting at 2 years of age (CI 95%: 2.8–3.6) and 4.7 times higher in the adulthood (CI 95%: 4.1–5.4), when compared to mothers with a higher stature .Other potential threats help explain the precarious nutritional conditions of the Yanomami Brazilian children, such as the invasions of the traditional territories by illegal miners, loggers, grabbing, and other criminals searching of wealth in the Amazon Forest ,46. All Despite the illustrative findings of this investigation, consistent with the specialized literature, it is important to consider the limitations. It was not possible to evaluate children who were receiving healthcare treatments outside of the villages at the time of our visits. On the one hand, this could have contributed to underestimation of stunting prevalence in our study. On the other hand, the reduced number of villages included in this study does not represent the nutritional status of all the children who live in the YIT, thus requiring caution in the generalizations of the results. Although all of the house visits were conducted with a local translator, the information bias cannot be disregarded, as well as memory bias, especially in questions related to healthcare services access and former sickness in older children.n = 298) could be considered small, it was expressive since these children live in regions with difficult access and that, in certain circumstances, these children can pass months without regular visits by healthcare teams. Under the methodological point of view, the exposure and the outcome evaluated in this study were measured following quality recommendations standards by WHO. Despite the cross-sectional nature of our data, we can say that the reverse causality phenomenon did not affect our association estimates, since the short maternal stature exposure was already defined before pregnancy and childbirth, which eliminates the exposure-outcome temporality dilemma in our data. Finally, even without excluding the possibility of residual confusion, we adopted robust data analysis methods by a hierarchical approach, using a measure of appropriate association to sectional studies.Aside the aforementioned limitations, it is worth highlighting that although the number of Yanomami children evaluated (Auaris region, reveals an alarming and unprecedented situation of health neglect. Therefore, it is essential to remember that Article 21 of the United Nations Declaration on the Rights of Indigenous Peoples assures that: “Indigenous peoples have the right, without discrimination, to the improvement of their economic and social conditions, including, among other things, in the areas of education, employment, vocational training and retraining, housing, sanitation, health and social security” [The high prevalence of stunting recorded in children under 5 years of age in the Yanomami Indigenous territory, especially those living in the ecurity” .In conclusion, even if the birth of many generations is necessary to eliminate the effects of intergenerational short stature, it is vital to understand that specific, broad, and inclusive nutritional interventions and programs are essential to prevent stunting in an ethnic and culturally differentiated context, especially if they are addressed in the first 1000 days of a child’s life. This period is considered a unique window of opportunity, especially in indigenous children, seriously affected by stunting. Therefore, effective multisectoral measures must be implemented to eradicate stunting in the Yanomami Territory.Finally, we consider it equally essential to create sustainable projects by the Federal Government in close collaboration with non-governmental organizations and indigenous associations. These projects must propose strategies to assure regular income generation with the participation of local society in managing the resources, assuring self-identification patterns, cultural valorizing, respect to ancient knowledge, and traditional foods. The ultimate goal should be to reach food sovereignty and social inclusion, guaranteeing basic water supply services, sanitation in villages, and regular access to health services.


The prevalence of dyslipidemia among Korean women differs significantly according to menopausal status. This study aimed to identify major dietary patterns among Korean women and examine their associations with the prevalence of dyslipidemia and its components.This study recruited 6,166 women from the Cancer Screenee Cohort 2007–2019 from the National Cancer Center of Korea. Dietary patterns were identified using factor analysis. Multivariable logistic regression was performed to calculate odds ratios (ORs) and 95% confidence intervals (CIs) for the associations between dietary patterns and the prevalence of dyslipidemia and its components, including hypercholesterolemia, hypertriglyceridemia, hypo-high-density lipoprotein (HDL) cholesterol, and hyper-low-density lipoprotein (LDL) cholesterol. Stratification analyses were performed for the premenopausal and postmenopausal subgroups.The factor analysis identified three main dietary patterns, including traditional, western, and prudent dietary patterns. Compared with those with the lowest pattern scores, those with the highest pattern scores of the traditional  and western  diets had a higher prevalence of hyper-LDL cholesterol. When accounting for menopausal status in the analysis, traditional  and western  diets were still associated with hyper-LDL cholesterol in postmenopausal women. Additionally, consumption of a traditional diet was associated with a decreased prevalence of hypertriglyceridemia , and consumption of a western diet was associated with an increased prevalence of hypercholesterolemia  but a reduced prevalence of hypo-HDL cholesterol . However, the prudent dietary pattern was not significantly associated with dyslipidemia and its components in the group of all women or the subgroups according to menopausal status.There were significant associations between the traditional and western dietary patterns and hyper-LDL cholesterol in the entire group and postmenopausal subgroup of women. In the perspective of energy restriction, our findings recommend women not to eat either traditional or western diets excessively or too frequently. Menopause may induce the effect of both the traditional diet on triglyceride reduction and the western diet on increasing total cholesterol. Cardiovascular disease is the leading cause of non-communicable disease-related morbidity and mortality, accounting for an estimated 17.8 million deaths worldwide . It has Aging has histologically contributed to lipid abnormalities through changes in the liver sinusoidal endothelium, lipoprotein disposition, and endocytosis and hepatic blood flow reductions . In addiAccording to the Korean Society of Lipid and Atherosclerosis, the total daily energy intake in women has been constantly maintained over the past decade at 1,549 kcal in 2007 and 1,769 kcal in 2015 . Howevern = 10,324) and those who did not have blood lipid profile or anthropometric measurement data (n = 858), a total of 6,267 women subjects remained. We further excluded subjects with an implausible energy intake  or height . Finally, we analyzed the data of the remaining 2,409 premenopausal and 3,757 postmenopausal women.Data on 17,449 women who underwent health screening at the Center for Cancer Prevention and Detection, during 2007–2019 were obtained from the National Cancer Center, Korea . The stuAll participants were asked to complete a self-administered questionnaire with questions related to their demographic and lifestyle data including age, educational level, household income, marital status, smoking status, alcohol consumption, regular exercise, and menopausal status.Dietary intake was assessed by using the validated semi-quantitative FFQ for 106 food items . The aveHeight was measured to the nearest 0.1 cm, and weight was measured to the nearest 0.1 kg while the subjects wore light clothes, without shoes, using automatic height and weight measurements . Body mass index (BMI) was defined as the weight (kg) divided by the square of the height (m). Waist circumference was measured at the umbilical level using a measuring tape. Blood pressure was measured with the participants in the seated position after 15 min of rest, using an automatic blood pressure monitor .Venous blood samples for the biochemical analyses were collected from participants by venipuncture following 8 h of fasting. Triglycerides, HDL cholesterol, total cholesterol , and fasting glucose  were determined using a chemical analyzer . LDL cholesterol was estimated using Friedwald equation when TG was <400 mg/dL. Dyslipidemia was defined as the presence of at least one of the following criteria: triglycerides ≥200 mg/dL, total cholesterol ≥240 mg/dL, HDL cholesterol <40 mg/dL, LDL cholesterol ≥160 mg/dL, previous diagnosis of dyslipidemia, and use of lipid-lowering drugs.The dietary patterns were identified by factor analysis using the FACTOR procedure. An eigenvalue >1.5 was used to determine whether a factor should be considered as a major dietary pattern. Varimax rotation was applied to review the correlations between variables and factors. Food groups with either positive or negative loadings in each pattern indicated the direct or inverse relationships with that pattern. For each subject, the factor scores for each dietary pattern were calculated by summing the intake of each food group, weighted by the factor loading. The derived patterns were named based on the most positively loaded foods associated with the patterns. Participants had their own factor score for identified patterns, and they were categorized into tertiles for every emerged pattern by the subject's factor score.Differences in the distribution of covariates across tertiles of each dietary pattern score were examined using the chi-square test for categorical variables and a generalized linear model for continuous variables. Multivariable-adjusted logistic regression analysis was performed to compare the odds ratios (ORs) and 95% confidence intervals (CIs) for dyslipidemia among tertiles of each dietary pattern score. The logistic regression model was adjusted for age, education, household income, smoking status, alcohol consumption, regular exercise, BMI, and total energy intake. P for trend was calculated by assigning the median value of each tertile category as a continuous variable to examine the linear trend of dyslipidemia according to the tertiles of the three dietary patterns. Subgroup analysis considering menopausal status was also performed.P-value of 0.05 was considered to be statistically significant.Nationwide studies in Korea showed that the prevalence of dyslipidemia 2010–2012, hypercholesterolemia 2007–2016, elevated triglycerides 2008–2013, and reduced HDL cholesterol 2008–2013 were 14.9–52.9% , 9.3–20.p < 0.001). In contrast, a higher education level, household income, and alcohol consumption and more regular exercise were observed in women without dyslipidemia (p < 0.001).p < 0.001).Daily energy intake was not different between the premenopausal and postmenopausal women . CompareThe factor loading matrix of the factor analysis for the 24 food groups is presented in p < 0.001). Household income, tobacco smoking, alcohol consumption, and regular exercise were unequally distributed among the tertiles of all the dietary patterns. Additionally, the three dietary pattern scores were positively associated with total energy intake (p < 0.001). Regarding the lipid profile, while the average total cholesterol (p = 0.013) and LDL cholesterol (p = 0.012) concentrations were not equal among the tertiles of the traditional dietary pattern score, those of serum triglycerides (p < 0.001) and HDL cholesterol (p < 0.001) were significantly different between the tertiles of the western dietary pattern score. We observed unequal levels of all the components of the lipid profile between the tertiles of the prudent dietary pattern score (p ≤ 0.001).The association between dietary patterns and dyslipidemia and its components in Korean women is presented in In this cross-sectional study, factor analysis revealed three main dietary patterns in Korean women, namely, the traditional, western, and prudent dietary patterns. Overall, the prudent dietary pattern was not associated with dyslipidemia or its components. The high consumption of food groups associated with the traditional and western patterns was positively associated with the prevalence of hyper-LDL cholesterol. In postmenopausal women, there were additional significant associations of the high consumption of food groups in the traditional dietary pattern with the low prevalence of hypertriglyceridemia, as well as of the western dietary pattern with the high prevalence of hypercholesterolemia and the low prevalence of hypo-HDL cholesterol in Korean postmenopausal women.S-methlycysteinsulfoxide and S-allylcysteinsulfoxide in garlic, and capsaicin in red pepper, was reported  or elevated triglycerides (≥150 mg/dL)  in Korean women . Althougreported . These breported . Excessireported .N = 2,468), which showed high levels of LDL cholesterol among those with a high score in the western dietary pattern , with ORs (95% CIs) for the association between the western dietary pattern and elevated LDL cholesterol (≥140 mg/dL) of 1.75 (1.30–2.35)  . In the 30–2.35) . While o30–2.35) . In the 30–2.35) . Additio30–2.35) .The prudent dietary pattern was characterized by the high intake of fruits and milk and dairy products and the low intake of oils, sweets, and refined grains. The potentially protective effect of fruits or milk and dairy products on lipid profiles in the Korean population has been previously investigated in several studies, with similar findings –35. The The recent guidelines for the management of dyslipidemia in Korea recommend the consumption of a healthy dietary pattern with a focus on whole grains , fruits (1-2 servings/day), vegetables , fish (including fatty fish), lean meat, eggs, and beans . FurtherWhen we stratified the study population according to menopausal status, the traditional dietary pattern was positively associated with the prevalence of hyper-LDL cholesterol in only postmenopausal women. This result suggested that among women with hyper-LDL cholesterol, conventional Korean foods were preferred in the postmenopausal group compared with the premenopausal group. Regarding the western dietary pattern, we also observed a significant association with both the prevalence of hypo-HDL cholesterol and hyper-LDL cholesterol in only postmenopausal subjects. This result may be explained by the increase in LDL cholesterol and the decrease in HDL cholesterol in women after menopause due to estrogen concentration changes; accordingly, the HDL cholesterol and LDL cholesterol levels in premenopausal women tended to be within the normal range –43. In pThe main strength of the current study is the inclusion of a large number of participants in the final analysis, which enabled an assessment of the effects of dietary patterns on dyslipidemia and its components in the total population as well as in premenopausal and postmenopausal women. The findings provide basic evidence for the prevention of dyslipidemia, which is a risk factor for cardiovascular disease. Compared with the use of the 24-h recall FFQ in other nationwide surveys, we obtained dietary behavior data via the validated FFQ, which provided data on the average food group consumption rates over the previous year , 45. ComDespite its strengths, this study had several limitations. First, despite the large sample size, ~65% of the study population did not meet the eligibility criteria. Such a limited number of participants included in the final analysis may restrict the possibility of observing meaningful associations between dietary patterns and dyslipidemia. Second, the classification of the 24 food groupsmay be arbitrary. Additionally, the numbers of factors used for extraction and pattern labeling were subjective decisions . HoweverIn conclusion, the factor analysis identified three major dietary patterns in Korean women. There were significant associations between the traditional and western dietary patterns and hyper-LDL cholesterol in total and postmenopausal women, whereas non-significant associations were found for prudent dietary pattern. From the perspective of energy restriction, our findings recommend that women not to eat either traditional or western diet excessively or too frequently. Menopause may induce the effect of both the traditional diet on triglyceride reduction and the western diet on increasing total cholesterol.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.The studies involving human participants were reviewed and approved by National Cancer Center (number NCC2019-0204). The patients/participants provided their written informed consent to participate in this study.JK, JL, TH, and SL: conceptualization, methodology, and writing—review and editing. JK: validation, supervision, and project administration. JL and TH: formal analysis. JK and JL: data curation. TH and SL: writing—original draft preparation. All authors contributed to the article and approved the submitted version.This study was supported by grant from the National Cancer Center Korea (2210990).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.