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Objective To investigate the relationship between nonalcoholic fatty liver disease (NAFLD) and various obesity indicators, as well as to investigate their predictive value for NAFLD. Methods A total of 3 102 participants who underwent health examinations from April to August 2023 at the Xinshi Street Community Health Service Center in Baiyun District, Guangzhou, and the Junan Community Health Service Center in Shunde District, Foshan, were selected and divided into NAFLD and non-NAFLD groups. Logistic regression analysis was employed to examine the relationship between body mass index (BMI), weight-adjusted waist index (WWI), waist-height ratio (WHtR), waist circumference (WC), and NAFLD. Receiver operating characteristic (ROC) curves were used to evaluate the predictive ability of individual and combined obesity indicators for NAFLD. Results The prevalence of NAFLD in this study was 34.9%. All obesity indicators in the NAFLD group were significantly higher than those in the non-NAFLD group (all P<0.001). Multivariate logistic regression results indicated that all obesity indicators were associated with the risk of NAFLD (all P<0.05). ROC curve analysis showed that each obesity indicator could predict the risk of NAFLD (AUC>0.5 for all). Among females, BMI exhibited the best predictive power (P<0.05), while the AUC values for BMI (overall population) and WC (males) were slightly higher than those for the other three indicators, though without statistical significance (P>0.05). Compared to traditional obesity indicators, WWI did not demonstrate superior predictive power (P<0.05). In all populations, combined indicators showed better predictive efficacy than single obesity indicators (P<0.05), and the AUC value for the combined indicators of BMI and WC was slightly higher in all three populations but did not show significant statistical meaning (P>0.05). Conclusion BMI, WC, WHtR, and WWI are associated with the prevalence of NAFLD. The best predictive indicator for females is BMI. The new indicator WWI do not show better predictive ability compared to traditional obesity indicators across the three populations. Combined indicators demonstrate better predictive efficacy than single indicators. [ABSTRACT FROM AUTHOR]

Objective To investigate the association between different anthropometric parameters and the risk of type 2 diabetes mellitus (T2DM), aiming to provide scientific evidence for early prevention of T2DM. Methods 299 pairs of T2DM patients and healthy controls were recruited in this case-control study. Logistic regression models were used to analyze the association between BMI, waist circumference (WC), waist-hip ratio (WHR) and waist-to-height ratio (WHtR) and the risk of T2DM. Results After potential confounding factors were adjusted, compared with the healthy BMI group (BMI 18.5-23.9 kg/m²), the odds ratio (OR, 95%CI) in the overweight (BMI 24.0-27.9 kg/m²) and obesity groups (BMI≥28.0 kg/m² ) was 2.35 (1.56-3.57) and 6.47 (2.92-14.33), respectively. Compared with the normal WC（male < 85 cm, female < 80 cm), the OR (95%CI) of T2DM risk in the pre-central（male 85-89.9 cm, female 80-84.9 cm) and central obesity (male ≥ 90 cm, female ≥ 85 cm) groups was 2.99 (1.81, 4.95) and 3.88 (2.43, 6.22), respectively. The risk of T2DM was 4.35 times (95%CI： 2.48-7.64，P < 0.001) higher in the highest WHR group (Q4) and 3.45 times (95%CI： 1.94-6.14，P < 0.001) higher in the highest WHtR group (Q4) compared with those in the lowest WHR and WHtR groups (Q1) . Conclusion Overweight, general obesity, pre-central and central obesity may increase the risk of T2DM. [ABSTRACT FROM AUTHOR]

BACKGROUND: The detection rate of hypertension in children and adolescents has increased in recent years, which is a public health problem worthy of attention. At present, there is no research on the prevalence and influencing factors of hypertension among children and adolescents in Hainan Province. Early hypertension in children and adolescents has no obvious clinical symptoms and is not easy to be found. OBJECTIVE: To investigate the prevalence, distribution characteristics and influencing factors of hypertension among school students aged 6-18 years in Hainan Province, so as to provide a theoretical basis for early and precise prevention and intervention. METHODS: The health monitoring data of school students in 18 cities and counties in Hainan Province from 2013 to 2020 were collected. A total of 6 253 567 pieces of information were included, including 3 408 734 (54.51%) pieces of information for boys and 2 844 833 (45.49%) pieces of information for girls. The Blood Pressure Reference Standards for Sex, Age and Height of Chinese Children Aged 3-17 Years, the 2018 Revised Guidelines for Prevention and Treatment of Hypertension in China, Screening Cut-Off Values for Overweight and Obesity in School-Aged Children and Adolescents WS_ T586-2018, High Waist Circumference Screening Cut-Off Values for Children and Adolescents Aged 7 To 18 Years WS_T611-2018, and Comprehensive Evaluation of the Developmental Level of Children and Adolescents were used to detect blood pressure of children and adolescents aged 6-17 years, blood pressure, body mass index, waist circumference and spirometry index of adolescents aged 18 years. Whether to be abdominal obesity adopts the international recommended criteria, that is, the waist circumference and height ratio ≥ 0.5 is abdominal obesity. Spearman analysis and multinomial logistic regression analysis were used to analyze the correlation between body mass index, waist circumference, waist-to-height ratio, spirometry index and blood pressure and the risk factors. RESULTS AND CONCLUSION: The distribution of hypertension in school students aged 6-18 years in Hainan Province has the following characteristics: (1) The distribution of hypertension in children and adolescents has regional clustering, and the severity of blood pressure from high to low is in the south, east, west, center, and north. (2) There were significant differences in the degree of hypertension between boys and girls at different ages (P < 0.001). The detection rate of elevated blood pressure in boys after 13 years of age increased significantly than that in girls. The detection rate of stage 1 hypertension in boys increased significantly after 14 years of age. The severity of blood pressure in girls aged 6-13 years was higher than that in boys, and the severity of blood pressure in boys aged 14-17 years was higher than that in girls. (3) Multivariate logistic regression analysis results showed that female students [odds ratio (OR)=1.185, 95% confidence interval (CI): 1.180-1.189, P < 0.001], body mass index (overweight OR=1.144, 95% CI: 1.135-1.154, P < 0.001; obesity OR=1.120, 95% CI: 1.105-1.135, P < 0.001), waist circumference (high normal waist circumference OR=1.053, 95% CI: 1.046-1.061, P < 0.001; high waist circumference OR=1.025, 95% CI: 1.012-1.037, P < 0.001) and waist-to-height ratio (OR=1.286, 95% CI: 1.270-1.303, P < 0.001) were risk factors for hypertension in children and adolescents. Age, spiro-index (middle level: OR=0.956, 95% CI: 0.944-0.968, P < 0.001); middle and upper level: OR=0.869, 95% CI: 0.8588-0.880, P < 0.001; first-class level: OR=0.739, 95% CI: 0.726-0.753, P < 0.001) were protective factors for hypertension in children and adolescents. A higher spirometry index level indicated a lower risk of hypertension in children and adolescents. (4) The above data indicate that the detection rate of hypertension in school students aged 6-18 years is relatively high in Hainan province. Region, year, age, sex, body mass index, waist circumference, abdominal obesity, and spirometry index are all influencing factors for the detection rate of hypertension in children and adolescents. Body mass index, waist circumference and waist-to-height ratio should be controlled within the normal range in children and adolescents aged 6-18 years. Increasing spirometry index levels is an important tool for blood pressure control in children and adolescents. [ABSTRACT FROM AUTHOR]

Objective: To determine the percentile reference values and reference curves of total body fat percentage in children and adolescents by sex and age, and to evaluate the reliability of different anthropometric indicators in screening for obesity in children and adolescents in order to explore the validity and practicality of a large-scale screening tool for childhood obesity and its desirable thresholds., Methods: A total of 5983 children and adolescents aged 6-18 years from six primary and secondary schools were selected by stratified randomised cluster sampling in Hangzhou City in 2023, and their weight, height, waist and hip circumferences were measured, and the children&apos;s total body fat content was measured using the bioelectrical resistance-antibody composition analyser. A generalised additive model(GAMLSS) was used to construct a percentile reference curve for children&apos;s body fat percentage, and the performance of each anthropometric measure in correctly classifying children and adolescents as obese was assessed using receiver operating characteristic(ROC) curves., Results: Over the period 6-18 years, body fat percentage in girls tended to increase with age from year to year, whereas in boys it tended to increase and then decrease. Fat mass index was the main factor contributing to the difference in BMI at the same age and sex(the optimal cutoff values were 26.82 and 24.52, with AUC values of 0.988 and 0.992, respectively), and the contribution of fat mass index was greater in those with a higher BMI. BMI, which had the largest area under the curve for both boys and girls, was the best indicator for assessing obesity in children and adolescents; the waist-to-height ratio(WHtR), with small variability and equally large area under curve values(0.980 for boys and 0.970 for girls), could simultaneously meet the requirements of accuracy and practicality for obesity assessment in mass screening of children and adolescents., Conclusion: This study establish the percentile reference value and reference curve of body fat percentage of children and adolescents aged 6-18 years in Hangzhou based on bioelectrical impedance method, and found that WHtR is a simple, effective and practical screening tool for childhood obesity with low variability, which can provide a reference basis for evaluating growth and development and identifying obesity in children aged 6-18 years in this region.

Objective To explore the interaction between family history of diabetes and abnormal waist-to-height ratio (WHtR) on risk of type 2 diabetes mellitus (T2DM). Methods The Jinchang cohort (established in June, 2012) was used in this study, and the baseline data were collected in December 2013. For case-control study, 1 109 male patients and 834 female patients with T2DM were included in diabetic group, whereas 1 943 healthy subjects matched with gender were included in control group. The additive model was used to study the interaction; the adjusted OR values of risk factors and regression coefficient were analyzed by multivariate logistic regression analysis; and the interaction between the factors were analyzed by the EXCEL software developed by Andersson et al. Results After excluding 26 706 cases without data of waist circumeference, a total of 21 292 cases were included in our study. The prevalence of diabetes was 9.13% (1 943/21 292) in all subjects, but 9.11% (1 109/12 175) in male subjects and 9.15% (834/9 117) in female subjects. After adjusting for age, smoking, drinking and other confounding factors, there was positive additive interaction between family history of diabetes and abnormal WHtR on risk of T2DM. While the family history of diabetes and abnormal WHtR existing at the same time, the risk of diabetes was 9.09 (95%CI: 5.64-14.64) in male and 13.08 (95%CI: 6.99-24.47) in female compared with control. In male, the index of synergistic effect, the attribution of interaction effect, and the percentage of attribution of interaction effect was 1.58, 2.98 and 32.8%, respectively. In female, the index of synergistic effect, the attribution of interaction effect, and the percentage of attribution of interaction effect was 1.90, 5.72 and 43.7%, respectively. Conclusion Family history of diabetes and abnormal WHtR may have synergistic effect on risk of T2DM. [ABSTRACT FROM AUTHOR]

Objective To investigate and compare the optimal screening tool for impaired fasting glucose(IFG) subjects, impaired glucose tolerance(IGT) subjects and undiagnosed diabetes, using waist circumstance(WC) and waist-to-height ratio(WHtR) in Shanghai. Methods A total of 18 062 participants (aged ≥35 years) were enrolled from the Shanghai Chronic Disease and Risk Factor Surveillance in 2013. Correlational analyses of WC and WHtR with IFG and IGT were conducted using Pearson correlation method. The receiver operating characteristic (ROC) analysis was used to compare their predictive ability for IFG, IGT and undiagnosed diabetes. According to the recommended cut-off value, screening of the three abnormal glucose status was performed using WC, WHtR and/or body mass index (BMI). Results Both WC and WHtR were positively correlated with FPG (r=0.161, 0.153, P<0.05 all above) and 2 hPG (r=0.182, 0.225, P<0.05 all above). The AUCs of WC and WHtR in screening IGT, IFG and undiagnosed diabetes were 0.620(95%CI: 0.611-0.629),0.636 (95%CI: 0.628-0.645, Z=2.549, P<0.05), respectively. The same result was obtained among female patients in screening IGT (0.663 vs 0.636, Z=-2.386, P<0.05). The AUC of WC in screening IGT (0.617, 95%CI: 0.605-0.629) was significantly lower than that of WHtR(0.646, 95% CI: 0.635-0.658, Z=-3.418, P<0.01). However, no difference between WC and WHtR in screening IFG and undiagnosed diabetes was shown (P>0.05). The difference of the best cut-off value of WC and WHtR between male and female subjects was 3-5 cm and 0.01, respectively. Among 4 screening algorithms by combining BMI in parallel or in serial, the specificity of WC combing BMI in serial was the highest for the screening of IFG, IGT, undiagnosed diabetes, and abnormal glucose subject (67.61%, 69.17%, 68.94%, and 72.46%, respectively). The sensitivity of WHtR combing BMI in parallel was the highest (76.10%, 82.79%, 83.89%, and 81.63%). Conclusion WHtR is a better option than WC in screening IGT for females. There is almost no gender difference in the optimal cut off values of WHtR for screening of IGT, IFG and undiagnosed diabetes. [ABSTRACT FROM AUTHOR]

Objective: To investigate the association between serum leptin concentration with blood pressure and hypertension in different gender., Methods: A total of 343 non-hypertensive residents aged 30 to 65 were randomly selected from Zhejiang Province in 2014. Parameters including height, weight, waist, blood pressure, serum lipid and serum leptin concentration of participants were measured and determined by physical examination and laboratory detection in 2014 and 2017. The differences in serum leptin levels between the new hypertensive and non-hypertensive people were compared after three years. The relationship between serum leptin levels and hypertension was analyzed by Logistic regression., Results: In 2014 and 2017, concentration of serum leptin in females was significantly higher than that in males, and the blood pressure in males was higher than that in females. At the end of follow-up, 26 new cases of hypertension were found. Serum leptin levels were higher in the female hypertensive group than in the non-hypertensive group(P=0. 0289), whereas there was no statistical difference in males(P>0. 01). Regardless of gender, serum leptin was significantly positively correlated with body mass index(BMI) and waist-to-height ratio(WHtR)(P<0. 0001), and also had correlation with blood pressure. However, after adjusting for BMI or WHtR, the correlation between serum leptin and blood pressure disappeared(P>0. 01). Logistic regression also showed the similar result., Conclusion: Serum leptin is not directly related to blood pressure and hypertension, and the positive correlation between them may be explained largely by BMI and WHtR.

Objective: To explore the relationship between waist circumference( WC), waist hip ratio( WHR), waist-to-height( WHtR) and hypertriglyceridemia( HTG) in older adults in Lu'an City., Methods: In total, 1029 participants aged ≥ 60 years using cluster sampling method from two communities in Jin' an District and Yu' anDistrict of Lu'an City were invited to participate in this community-based study from June to September 2016. A questionnaire was used to collect the information of demographic characteristics, disease history, lifestyles, etc. Height, waist circumference, hip circumference, and blood triglyceride levels were measured. Binary logistic regression analysis was conducted to analysis the association between WC, WHR, WHtR and hypertriglyceridemia. The receiver operating characteristic( ROC) curve was used to evaluated the distinguishable effect of three indices on HTG., Results: Prevalence of HTG was 19. 7%( 14. 0% in male, 24. 5% in female, χ~2= 17. 71, P < 0. 001). After controlling the confounding factors, including area, gender, age, family history, educational level, sedentary time, physical exercise, smoking, alcohol consumption, diet habits, binary Logistics regression analysis showed that the risk of HTG was higher in the elderly with high WC, high WHR, high WHtR, the ORs were 5. 18( 95% CI 2. 81-9. 57), 3. 69( 95% CI 1. 95-6. 95) and 4. 93( 95% CI 2. 72-8. 91), respectively. The area under ROC curves of WC, WHR and WHtR were 0. 67, 0. 67 and 0. 69, respectively., Conclusion: WC, WHR and WHtR are closely related with the prevalence of HTG. WC and WHR were significant than others for male HTG and female HTG.

Objective: To assess the differences between anthropometric indices in predicting dyslipidemia in Chinese urban adult population and find optimal cut-off points., Methods: A total of 1615 subjects with information on key variables were enrolled by multistage stratified sampling process from March to July in 2016. Information on sociodemographic characteristics( age, gender, nationality, education and income), and health and disease history of subjects was collected. Height, weight, waist circumference( WC), hip circumference, body fat percentage( % Fat), and fasting lipid profiles were measured for each participant. The receiver operating characteristic( ROC) curve was used to compare the efficacy of the various anthropometric indices to discriminate those with and without dyslipidemia., Results: Waist-to-height ratio( WHtR) had the largest area under the ROC curve( AUC) for dyslipidemia in women( 0. 744). There weresignificant differences between AUC of WHtR and that of WC( P = 0. 008), body mass index( BMI, P = 0. 004), waist-to-hip ratio( WHR, P = 0. 005), and % Fat( P <0. 001) in pairwise comparisons. Cut-off point for WHtR was 0. 50 for dyslipidemia in urban adult women. Although the AUC for BMI was the highest for dyslipidemia in men, it did not differ significantly from other indices( P all > 0. 05). Cut-off point for BMI was24. 1 kg/m~2 for dyslipidemia in urban adult men., Conclusion: WHtR and BMI might be optimal indices for dyslipidemia for Chinese urban adult women and men, respectively. Regional and sexual differences should be considered when choosing proper indices.

Objective: Waist-to-height ratio (WHtR), a measurement of the distribution of body fat, correlated with abdominal obesity indicating that it might be a better predictor of cardiovascular risk and metabolic disease. We, therefore, evaluated optimal WHtR cutoff points according to the risk of framingham risk score (FRS) and metabolic syndrome (MS) in Chinese. Methods: The subjects were from China National Diabetes and Metabolic Disorders Survey during 2007-2008. Receiver operating characteristic analysis was used to examine the optimal cutoff values of WHtR according to the risk of FRS and MS. Results: A total of 27 820 women and 18 419 men were included in the evaluation. The average age was (45.0±13.7) years. The proportions of FRS ≥10% and MS increased with WHtR both in men and women. The cutoff points of WHtR for the risk of FRS ≥10% and MS were 0.51, 0.52 in men, and 0.52, 0.53 in women, respectively. When FRS ≥10% and MS were taken into consideration with a certain weights, the pooled cutoffs of WHtR were 0.51 in men, and 0.53 in women, respectively. By using the similar method, the optimized cutoff points were 0.52, 0.51, 0.50 for men and 0.51, 0.53, 0.54 for women in age group 20-39, 40-59 and ≥60 years, respectively. Conclusions: The optimal cutoffs of WHtR are 0.51 in men, and 0.53 in women for FRS≥10% in combination with MS indicating that this WHtR cutoff points might be used as indexes to evaluate obesity and risk of obesity-related diseases.