Objective: To analyze the consumption frequency of major foods among Chinese children aged 6-17 years old, and to provide a basis for optimizing the dietary structure of children in China. Methods: Using data from the China Nutrition and Health System Survey and Application Program for Children 0-18 years old, 56 734 children aged 6-17 years old from North, Norththeast East, Central, South, Southwest and Northwest seven regions in China were selected for the study using stratified cluster random sampling from 2019 to 2021. A food frequency questionnaire was used to investigate the intake frequency of eight food groups in a month, including fresh vegetables, fresh fruits, livestock and poultry meats, aquatic products, eggs, dairy products, legumes, and cereals and potatoes. The foods were grouped according to whether they met the recommended intake criteria outlined in the Dietary Guidelines for Chinese Residents 2022. The〖KG*2〗χ2 test was used to compare the differences in the proportion of childrens intake frequency of each food group meeting the standard in different regions and age groups. Results: The proportions of Chinese children aged 6-17 years who consumed fresh vegetables and cereals and potatoes ≥3 times/d were 12.1% and 67.2%, respectively. The proportions of children who consumed fresh fruits, livestock and poultry meats, eggs and dairy products ≥1 time/d were 50.8%, 58.8%, 36.0% and 54.3%, respectively. The proportion of legumes consumed ≥4 times/week was 37.4%, and the proportion of aquatic products consumed ≥2 times/week was 39.7%. Fresh vegetables (5.5%), fresh fruits (33.1%), and dairy products (36.4%) had the lowest frequency of meeting the recommended standards in South China, and aquatic products (27.4%) and eggs (21.1%) had the lowest frequency of meeting the recommended standards in Northwest (P<0.008 3). Conclusion The overall intake frequency of fresh vegetables, fresh fruits, legumes, and dairy products are insufficient among Chinese children, with significant regional variations.

Objective: To explore the associations between caregivers nutrition literacy and pediatric nonalcoholic fatty liver disease (NAFLD), so as to provide scientific evidence for the key contents of family intervention measures. Methods: In September 2022, a study involving 1 609 thirdgrade students and their caregivers from six schools in Yinzhou, Haishu, and Zhenhai Districts of Ningbo City, Zhejiang Province, was conducted. Venous blood samples were collected to measure lipid profiles and investigate the prevalence of nonalcoholic fatty liver disease (NAFLD) among the children. Family Food Environment Questionnaire was used to assess the nutrition literacy levels of the caregivers. Generalized linear regression analysis was employed to explore the correlation between caregivers nutrition literacy levels and the prevalence of NAFLD in children. Results: Among the surveyed students, 191 were in the NAFLD group, whereas 1 418 were in the nonNAFLD group. The median nutrition literacy score of caregivers in the NAFLD group and nonNAFLD group all were 11.00 (9.00,12.00), which was not significantly different (Z=-0.40, P=0.71). The generalized linear regression results revealed that the level of nutrition literacy of caregivers had no significant effect on childrens Triglyceride-glucose (TyG) index and Triglyceride-glucose-Waisttoheight ratio (TyG-WHtR) [β(95%CI) were 0.001(-0.005-0.006) and 0.000(-0.014-0.014), P>0.05]. Conclusions The nutrition literacy level of caregivers has no significant correlation with the direct incidence of NAFLD in children. As for family intervention measures, it is necessary not only to improve the nutrition literacy level of caregivers but also to effectively apply nutritional knowledge in practice to optimize health management.

To investigate the correlation between vitamin D nutritional status and insulin resistance in pubertal adolescents.

Objective: To analyze the association of eating dining locations and their association with nutritional status among Chinese children aged 6-17 years,so as to provide reference for guiding children s reasonable diet. Methods: Stratified random cluster sampling was used to select children aged 6 to 17 years from 28 cities and rural areas of 14 provinces in East, North, Central, South, Southwest, Northwest, Northeast of China, and a total of 52 535 children were included in the study from 2019 to 2021. Information including dining locations, demographic characteristics, dietary intakes and physical activity were collected through a questionnaire survey. Fasting body height and weight were measured in the morning. Unordered multiclass Logistic regression analysis was conducted to assess the relationship between dining locations and nutritional status in children. Results: Regarding children s dining locations, 66.3% ate breakfast at home,25.8% ate breakfast at school,7.9% ate breakfast outside (small dining tables, restaurants, stalls, etc.); 67.7% ate dinner at home,29.0% ate dinner at school,3.3% ate dinner outside; and 63.6% ate lunch at school,30.8% ate lunch at home,5.7% ate lunch outside. The prevalence rates of overweight/obesity and undernutrition were 28.6% and 9.3%, respectively. The adjusted multiclass Logistic regression analysis (controlling for age, region, parental education, household income, total energy intake, and moderate-to-vigorous physical activity) demonstrated that, compared to eating at home, school based breakfast and dinner consumption was associated with significantly lower overweight/obesity risks for both genders (boys: breakfast OR =0.70, 95% CI =0.65-0.75; dinner OR =0.80, 95% CI = 0.74- 0.86; girls: breakfast OR = 0.89 , 95% CI = 0.82-0.96; dinner OR =0.88, 95% CI =0.81-0.95), whereas eating lunch away from home significantly increased overweight/obesity risks (boys: OR =1.32, 95% CI =1.17-1.48; girls: OR =1.43, 95% CI =1.26- 1.62 ), with all associations being statistically significant ( P <0.05). After adjusting for confounding factors, boys who ate breakfast away from home showed a significantly reduced risk of undernutrition ( OR =0.80,95% CI =0.66-0.97), while those consuming lunch away from home had an increased risk ( OR =1.26, 95% CI =1.01-1.57) ( P <0.05). Conclusions The choice of dining locations for children is becoming more diverse, and a relatively high proportion of children eat meals outside the home and at school. Eating out have a higher risk of malnutrition for children. School feeding may be beneficial to children s physical health.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

Purpose: The aim of this study was to investigate the feasibility of an intelligent handheld ultrasound (US) device for assisting non-expert general practitioners (GPs) in detecting carotid plaques (CPs) in community populations. Methods: This prospective parallel controlled trial recruited 111 consecutive community residents. All of them underwent examinations by non-expert GPs and specialist doctors using handheld US devices (setting A, setting B, and setting C). The results of setting C with specialist doctors were considered the gold standard. Carotid intima-media thickness (CIMT) and the features of CPs were measured and recorded. The diagnostic performance of GPs in distinguishing CPs was evaluated using a receiver operating characteristic curve. Inter-observer agreement was compared using the intragroup correlation coefficient (ICC). Questionnaires were completed to evaluate clinical benefits. Results: Among the 111 community residents, 80, 96, and 112 CPs were detected in settings A, B, and C, respectively. Setting B exhibited better diagnostic performance than setting A for detecting CPs (area under the curve, 0.856 vs. 0.749; P<0.01). Setting B had better consistency with setting C than setting A in CIMT measurement and the assessment of CPs (ICC, 0.731 to 0.923). Moreover, measurements in setting B required less time than the other two settings (44.59 seconds vs. 108.87 seconds vs. 126.13 seconds, both P<0.01). Conclusion Using an intelligent handheld US device, GPs can perform CP screening and achieve a diagnostic capability comparable to that of specialist doctors.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.