RESUMEN
【Objective】 To analyze the association between the composition of gut microbiota and blood pressure in children aged 6 - 9 years, in order to provide new ideas for childhood hypertension prevention and treatment. 【Methods】 A total of 411 children aged 6 - 9 years were recruited in Guangzhou from December 2015 to March 2017. The gut microbiota was characterized by 16S ribosomal RNA amplicon sequencing. The multivariate methods with unbiased variable selection in R (MUVR) were performed to identify the significant OTUs. Spearman correlation as well as multiple linear regression were used to explore the relationship between gut microbiota and blood pressure in children. 【Results】 Significant difference in β diversity index was observed between children with normal blood pressure and those with abnormal blood pressure (R2weighted=0.015,Pweighted=0.01; R2unweighted=0.027, Punweighted=0.001). After adjustment for covariates and controlling the false discovery rate (FDR), multiple linear regression analysis showed that blood pressure level in children decreased with the increasing abundance of OTU_3 (genus Blautia), OTU_131 (genus [Clostridium]_innocuum_group), OTU_1776 (genus Blautia), OTU_2159 (genus Prevotella) and OTU_91 (species Bifidobacterium_breve) (β:-0.18 --0.14; PFDR<0.05. In contrast, blood pressure in children increased with the increasing abundance of OTU_108(genus Sutterella), OTU_1(species Faecalibacterium_prausnitzii)、OTU_8(genus Roseburia), OTU_48 (genus Lachnoclostridium), OTU_81 (genus Coprococcus), OTU_401 (family Lachnospiraceae), OTU_1284 (family Lachnospiraceae) and OTU_2793 (family Lachnospiraceae)(β: 0.14 - 0.21; PFDR<0.05. The influence of gut microbiota on systolic pressure and diastolic pressure may be mediated by the increase of body mass index (BMI). 【Conclusions】 Pediatric blood pressure level is associated with the composition of gut microbiota, while BMI partially plays a mediating role in the relationship. It is recommended to modulate the abundance of microbiota as genus Blautia, Sutterella and so on to prevent hypertension in children.
RESUMEN
Objective To evaluate the accuracy of simple anthropometric parameters in diagnosing obesity in children in Guangzhou. Methods A cross-sectional study, including 465 children aged 6-9 years, was carried out in Guangzhou. Their body height and weight, waist circumference (WC) and hip circumference were measured according to standard procedure. Body mass index (BMI), waist to hip ratio (WHR) and waist-to-height ratio (WHtR) were calculated. Body fat percentage (BF%)was determined by dual-energy X-ray absorptiometry. Multiple regression analysis was applied to evaluate the correlations between age-adjusted physical indicators and BF%, after the adjustment for age. Obesity was defined by BF%. Receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic accuracy of the indicators for childhood obesity. Area under-ROC curves (AUCs) were calculated and the best cut-off point that maximizing'sensitivity+specificity-1'was determined. Results BMI showed the strongest association with BF% through multiple regression analysis. For'per-standard deviation increase' of BMI, BF%increased by 5.3%(t=23.1, P<0.01) in boys and 4.6%(t=17.5, P<0.01) in girls, respectively. The ROC curve analysis indicated that BMI exhibited the largest AUC in both boys (AUC=0.908) and girls (AUC=0.895). The sensitivity was 80.8% in boys and 81.8% in girls, and the specificity was 88.2%in boys and 87.1%in girls. Both the AUCs for WHtR and WC were less than 0.8 in boys and girls. WHR had the smallest AUCs (<0.8) in both boys and girls. Conclusion BMI appeared to be a good predicator for BF%in children aged 6-9 years in Guangzhou.
RESUMEN
Objective To evaluate the accuracy of simple anthropometric parameters in diagnosing obesity in children in Guangzhou. Methods A cross-sectional study, including 465 children aged 6-9 years, was carried out in Guangzhou. Their body height and weight, waist circumference (WC) and hip circumference were measured according to standard procedure. Body mass index (BMI), waist to hip ratio (WHR) and waist-to-height ratio (WHtR) were calculated. Body fat percentage (BF%)was determined by dual-energy X-ray absorptiometry. Multiple regression analysis was applied to evaluate the correlations between age-adjusted physical indicators and BF%, after the adjustment for age. Obesity was defined by BF%. Receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic accuracy of the indicators for childhood obesity. Area under-ROC curves (AUCs) were calculated and the best cut-off point that maximizing'sensitivity+specificity-1'was determined. Results BMI showed the strongest association with BF% through multiple regression analysis. For'per-standard deviation increase' of BMI, BF%increased by 5.3%(t=23.1, P<0.01) in boys and 4.6%(t=17.5, P<0.01) in girls, respectively. The ROC curve analysis indicated that BMI exhibited the largest AUC in both boys (AUC=0.908) and girls (AUC=0.895). The sensitivity was 80.8% in boys and 81.8% in girls, and the specificity was 88.2%in boys and 87.1%in girls. Both the AUCs for WHtR and WC were less than 0.8 in boys and girls. WHR had the smallest AUCs (<0.8) in both boys and girls. Conclusion BMI appeared to be a good predicator for BF%in children aged 6-9 years in Guangzhou.