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BACKGROUND: Obesity and type 2 diabetes mellitus (T2DM) are risk factors for hyperuricemia. However, which anthropometric indices can better predict incident hyperuricemia in patients with T2DM remains inconsistent. This study aimed to examine the associations between hyperuricemia and different anthropometric indices in middle-aged and older male patients with T2DM. METHODS: In this retrospective study, a total of 1447 middle-aged (45-65 years, n = 791) and older (≥ 65 years, n = 656) male patients with T2DM were collected from December 2015 to January 2020 at Shanghai Xinhua Hospital. Hyperuricemia was defined as a serum uric acid level above 7.0 mg/dL. Weight, height, waist circumference (WC) and hip circumference (HC) were measured by trained nurses at visit. RESULTS: The median uric acid level of subjects was 5.6 (interquartile ranges: 4.7-6.7) mg/dl, and 279 (19.3%) were hyperuricemia, with 146 (18.5%) in the middle-aged group, and 133 (20.3%) in the older group. After adjusting for age, duration of T2DM, fasting plasma glucose and insulin, homeostasis model assessment-ß, aspartate aminotransferase, triglycerides, high-density lipoprotein cholesterol and estimated glomerular filtration rate, body mass index (BMI), WC, HC, and waist-to-height ratio (WHtR) were associated with a higher risk of hyperuricemia in both middle-aged and older group (P < 0.05). After further adjusting for BMI and WC, HC still showed a positive relationship with the risk of hyperuricemia (Odds Ratio = 1.51, 95% confidence intervals: 1.06-2.14) in the middle-aged group, but such relationship was not found in the older group. Moreover, according to receiver operating characteristic analysis, the optimal cutoff value was 101.3 cm of HC for hyperuricemia screening in the middle-aged male patients with T2DM. CONCLUSION: In middle-aged male patients with T2DM, more attention should be paid to HC with the cutoff value of 101.3 cm in clinical practice for early recognition of individuals with a high risk of hyperuricemia for targeted guidance on disease prevention, such as community screening.
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Diabetes Mellitus Tipo 2 , Hiperuricemia , Pessoa de Meia-Idade , Humanos , Masculino , Idoso , Diabetes Mellitus Tipo 2/complicações , Diabetes Mellitus Tipo 2/epidemiologia , Ácido Úrico , Hiperuricemia/epidemiologia , Estudos Retrospectivos , China/epidemiologiaRESUMO
BACKGROUND: In a cohort of hospitalized children with congenital heart disease (CHD), a new digital pediatric malnutrition screening tool as a mobile application was validated, and its effectiveness and clinical value were determined as a prospective study. METHODS AND RESULTS: Children with CHD (n = 1125) were screened for malnutrition risk. The incidence of risk and the differences among various age groups and types of CHD were characterized. The optimal threshold for the tool to determine if there is a risk of malnutrition is score 2, while the Youden index was 79.1%, and the sensitivity and specificity were 91.2% and 87.9%, respectively. Based on such criterion, 351 children were at risk of malnutrition accounting for 31.20% of the total. Compared with the non-malnutritional risk group, the median age for the group at risk for malnutrition was younger (8.641 months [4.8, 23.1] vs. 31.589 months [12.4, 54.3], P < 0.01), and the length of stay was longer (12.000 [8.0, 17.0] vs. (8.420 [5.0, 12.0], P < 0.01]. There were significant differences in malnutrition risk among different age groups (χ2 = 144.933, P < 0.01), and children under one year of age exhibited the highest risk for malnutrition and more extended hospital stay (H = 78.085, P < 0.01). The risk of malnutrition among children with cyanotic CHD was higher than in those with non-cyanotic CHD (χ2 = 104.384, P < 0.01). CONCLUSIONS: The new digital pediatric malnutrition screening tool showed high sensitivity and specificity in children with CHD. The tool indicated that the malnutrition risk for young children and children with cyanotic or Bethesda moderate and complex CHD was higher, and the hospitalization time was longer than in the non-risk group. The tool provides a rational approach to targeted nutrition intervention and support and may improve clinical outcomes.
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Cardiopatias Congênitas , Desnutrição , Criança , Humanos , Lactente , Pré-Escolar , Criança Hospitalizada , Estudos Prospectivos , Desnutrição/diagnóstico , Desnutrição/epidemiologia , Desnutrição/etiologia , Hospitalização , Cardiopatias Congênitas/complicações , Cardiopatias Congênitas/diagnóstico , Estado NutricionalRESUMO
CONTEXT: Insulin resistance (IR) has been common in obese children, but the effect of different adiposity factors on IR is still unclear. OBJECTIVE: To evaluate the associations between IR with body mass index (BMI), waist circumference (WC), body fat mass (BFM), and body fat percentage (BFP) in obese children and adolescents. METHODS: A total of 224 simple obese children were included in this study, including 150 boys and 74 girls, aged 3-18 who were seen in the clinical nutrition outpatient of Xinhua Hospital from September 2012 to December 2019. Basic information, body composition and laboratory tests were collected. RESULTS: Compared with girls, boys had higher height, weight, BMI, WC, and BFM (P < 0.05), but on the contrary, boys' FINS and HOMA- IR were lower than girls' (P > 0.05). With the age increasing, height, weight, BMI, BFM, WC, HC, WHtR, FINS and HOMA-IR increased accordingly (P < 0.05). The results from univariate analysis and multiple linear regression analysis showed that the impact of BMI on IR was slightly lower than BFM, WC and HC, but higher than BFP, with adjusting for the effects of age, sex and lipid metabolism (P < 0.01). CONCLUSION: Overall adipose tissue, especially abdominal adipose tissue, is a powerful marker in inducing IR in obese children and adolescents. In addition, more attention should be paid to WC and BFM than BMI in obese people with IR.
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Resistência à Insulina , Obesidade Infantil , Adiposidade , Adolescente , Índice de Massa Corporal , Criança , Feminino , Humanos , Masculino , Circunferência da CinturaRESUMO
Background: Despite extensive research on hyperuricemia (HUA) in adults, there remains a dearth of studies examining this condition in youth. Consequently, our objective was to investigate the prevalence of HUA among youth in the United States, as well as identify the corresponding risk factors. Methods: This study employed a nationally representative subsample of 1,051 youth aged 13-20 from the US National Health and Nutrition Examination Survey (NHANES) conducted between January 2017 and March 2020. Univariate and multivariate techniques were utilized to examine the association between HUA and obesity, dietary nutrients, liver and kidney function, glucose and lipid metabolism, inflammation, and other indicators in the adolescent population. Results: The study encompassed a cohort of 1,051 youth aged 13-20 years, comprising 538 boys and 513 girls. The overall prevalence of HUA was found to be 7% (74 out of 1,051). Univariate analysis revealed that the HUA group exhibited greater age, body mass index (BMI), waist circumference (WC), hip circumference (HC), and waist-to-hip ratio (WHR). Additionally, the prevalence of obesity was significantly higher in the HUA group compared to the non- HUA group (all p < 0.05). Regarding biochemical indicators, the levels of urea nitrogen, creatinine (Cr), alanine aminotransferase (ALT), glutamic oxalic aminotransferase (AST), gamma-glutamyl transferase (GGT), total cholesterol (TC), triglyceride (TG), and HS C reactive protein (Hs CRP) were found to be significantly higher in the HUA group compared to the non-HUA group (all p < 0.05). Further analysis using binary logistics regression showed that BMI (p = 0.024, OR1.158, 95%CI1.019-1.316), ALT (p = 0.020, OR1.032, 95%CI1.005-1.059), and Cr (p = 0.016, OR1.028, 95%CI1.005-1.051) were identified as risk factors for HUA, after controlling for age, gender, BMI, WC, HC, WHR, ALT, AST, GGT, TG, TC, Cr, Hs CRP, and other indicators. Interestingly, neither univariate nor multivariate analysis found any association between dietary nutrients and the risk of HUA (all p > 0.05). Conclusion: High BMI remains a major risk factor for HUA in US youth aged 13-20 years, and ALT and Cr levels should be closely monitored along with serum uric acid.
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Objective: This study aimed to evaluate the efficiency of tri-ponderal mass index (TMI) in determining obesity in Chinese children aged 6-9 years, using the criteria of percentage of body fat (PBF) and body mass index z-scores (BMI-Z). Methods: The cross-sectional study included 5365 children, aged 6-9 years, who participated in the project survey "Group prevention and treatment of obesity among students and school health promotion in Shanghai" from September 2007 to September 2009. Height, weight, waist circumference, body mass index (BMI), TMI, waist-to-height ratio (WHtR), and PBF were recorded. Statistical analyses including Kolmogorov-Smirnov test, chi-square test, receiver operating characteristics curve, and kappa chi-square test were performed. Results: TMI for both sexes was relatively constant with increasing age, and statistically significant differences were not observed at some ages (P > 0.05 at 6, 7, 8, and 9 years). WHtR showed subtle changes, while BMI and PBF increased significantly with age in boys and girls (P < 0.01). Using BMI-Z criteria as the measure of general obesity, the results indicated that TMI cutoff values for 6-9 years were 14.60 kg/m3 for boys and 14.84 kg/m3 for girls (P < 0.001). Analysis of the agreement between TMI and BMI-Z showed that the kappa statistic was 0.826 in boys and 0.709 in girls (P < 0.001). Conclusion: TMI, as a constant tool, holds great potential as an alternative screening method for identifying children aged 6-9 years who may be at risk of obesity at an early stage.
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Obesidade Infantil , Masculino , Feminino , Humanos , Criança , Obesidade Infantil/diagnóstico , Obesidade Infantil/epidemiologia , Estudos Transversais , China , Índice de Massa Corporal , Curva ROCRESUMO
Objective: This study aimed to evaluate whether serum uric acid (SUA) plays a mediating role in the development of insulin resistance (IR) in obese children and adolescents. Methods: A total of 369 participants aged 4-17 years with obesity who attended the Nutrition Outpatient Clinic for Obesity at Xinhua Hospital from January 2012 to January 2019 were recruited for this retrospective study. We classified participants into two groups on the basis of HOMA-IR values: the low HOMA-IR group (< 3.16) (n = 222) and the high HOMA-IR group (≥ 3.16) (n = 147). Results: The univariate analysis found that the high HOMA-IR group had higher BMI, SUA, and fasting insulin (FINS) (P < 0.05). Multiple linear regression analysis and mediating effect analysis indicated that body mass index (BMI) could directly regulate FINS and HOMA-IR (both P < 0.05). The results from the mediating effect analysis found that UA partially played an indirect role in the link between BMI, FINS and HOMA-IR (both P < 0.05) but had no effect on fasting blood glucose (P > 0.05). Conclusions: SUA should be investigated in obesity and plays a partial mediating role in insulin resistance induced by obesity in obese children and adolescents.
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Resistência à Insulina/fisiologia , Obesidade Infantil/sangue , Ácido Úrico/sangue , Adolescente , Índice de Massa Corporal , Criança , Pré-Escolar , Feminino , Humanos , Insulina/sangue , Masculino , Estudos RetrospectivosRESUMO
BACKGROUND AND OBJECTIVES: There is no evidence on the most effective nutritional screening tool for hospitalized children. The objective of this study was to develop and validate a pediatric nutritional screening tool to assess undernutrition risk upon hospital admission. METHODS AND STUDY DESIGN: The study had a two-phase prospective observational design. A novel pediatric nutritional screening score (PNSS) was developed and sensitivity, specificity, and reliability were evaluated by comparing with a complete dietetic assessment. Length of hospital stay, weight loss, disease complications, and nutritional support were recorded. RESULTS: PNSS consisted of three elements: disease with malnutrition risks, changes in food intake, and anthropometric measurements, with a score of 0-2 for each element. The optimal cut-off score to identify patients (n=96) at risk of undernutrition was two. The agreement between PNSS and the complete dietetic assessment was moderate (κ=0.435, 95% CI=0.373-0.498). Sensitivity and specificity values of PNSS were 82% (95% CI=76%-87%) and 71% (95% CI=67%-74%), respectively. Inter-rater agreement had a κ value of 0.596 (95% CI=0.529-0.664, p<0.001). The percentage of children with undernutrition risk was 44.9%. Children with oncologic, gastrointestinal, and cardiac diseases were most likely to be at risk of undernutrition. The at-risk group was associated significantly with longer length of hospital stay and higher percentage of weight loss compared with the not-at-risk group. CONCLUSION: PNSS is the first nutritional screening tool developed for hospitalized children and validated in a large population of patients in China.