| ObjectivesAnthropometric measurements(such as height,weight,waist circumference,etc.)were widely used to predict cardiovascular diseases and cardiometabolic risk factors.However,many epidemiological studies investigated the predictive value of BMI for cardiometabolic risk factors and cardiovascular events,and consistently showed that BMI had a lower discriminatory power than WC and waist-to-height ratio(WHtR)to distinguish individuals with high muscle mass from those with excess fat or abdominal obesity.Therefore,combining BMI and WC together to achieve more accurate predictions has become one of the research foci."A new body Shape index"(ABSI)is a new comprehensive adiposity index combining BMI and WC,which was developed by Krakauer in 2012 showing a better predictive value for mortality and CVDs than that of BMI or WC in Caucasians.The formula of ABSI is:ABSI=WC/BMI2/3height1/2.ABSI can predict mortality hazard independently of BMI,which made it had high predict value.Although the predictive power of ABSI has gradually been verified by some foreign epidemiology studies,but none of these previous studies examined the association with CVDs and there is lacking of knowledge of predictive value of ABSI for the cardiovascular risk factors among Chinese population.Also,there has been no research comparing the discriminatory power between ABSI and other anthropometric measurements for cardiometabolic risk factors and CVDs risk in a single large population.This study aimed to compare the predictive value of a newly developed ABSI in a large Chinese population with other 5 conventional obesity-related anthropometric indices(BMI,WC,Hip Circumference:HC,Waist-to-hip ratio:WHR,Waist-to-height ratio:WHtR)for predicting cardiometabolic risk factors and CVDs.The optimal thresholds of these anthropometric indices were also evaluated.And we also try to create a new anthropometric index for predicting cardiovascular disease and cardiometabolic risk factors based on the Chinese population for better early screening.Research ContentsFirstly,We measured and compared detailed information of different anthropometric measurements of both the traditional and new-built index in the same population,which presented a whole picture of the predictive values of all anthropometric parameters in single C hinese population,and this demonstrates the main merit of the current study as none of the previous study has been attempted to do so.Moreover,in terms of methodology,this study also tries to create a new anthropometric index for predicting cardiovascular disease and cardiometabolic risk factors based on the Chinese population for better early screening.Methods46285 participants in the study were derived from the baseline data of a prospective urban and rural epidemiological study in China(PURE-China).For the current analyses,we excluded participants without anuiropometric indices(n=715;1.5%)or blood sample data(n=1522;3.3%).Thus,44048 participants were included in this study.Generalized estimating equation and receiver operator characteristic curve analysis were used to evaluate the predictive values of obesity-related anthropometric indices to the cardiometabolic risk factors and CVDs.Participants of the study were divided into the development dataset(accounting for about 75%of the total population)and the validation dataset(accounting for about 25%of the total population)according to the baseline recruitment date.Establishment of the predict index was done in the development dataset.Validation of the predict index was accomplished through the Bootstrap simulation in the development dataset(internal validation),and through the directly application in the validation dataset(external validation).All analyses were performed in SAS version 9.4 and P value less than 0.05 was considered significant.ResultsThe study found that the prevalence of cardiometabolic risk factors and CVDs in Chinese adults aged 35-70 years were 52.11%for dyslipidemia,41.86%for hypertension,8.83%for diabetes,and 7.90%for CVDs.Standardized age prevalence is roughly half of the crude rate.The prevalence of each disease varies with age,gender,region,location,and different lifestyle.In general,aged,obesity,low physical activity and unhealthy eating habits were the main risk factors of CVDs.Considering cluster effect of community,this study explored the association between anthropometric measurements and cardiometabolic risk factors and CVDs by generalized estimating equations.A positive association was observed between each anthropometric index and cardiometabolic risk factors and CVDs in all models(P<0.001).Waist-to-height ratio and waist circumference had the highest odds ratio and the associations remained consistent in subgroups.However,ABSI didn't show a better association to either cardiometabolic risk factors or CVDs than that of any other traditional obesity-related indices.In addition,we also compared the predictive value of anthropometric indices for predicting cardiometabolic risk factors and CVDs.The optimal thresholds of these anthropometric indices were also evaluated.Waist circumference and waist height ratio were the best indicators for predicting cardiovascular diseases and its risk factors.The predictive power of waist circumference and waist-to-height ratio remained stable in different subgroups.This study also validated the predictive efficacy of ABSI in the Chinese population for the first time.We found that ABSI's predictive performance is much lower than traditional anthropometric measurements,and ABSI did not apply to the Chinese population.In this study,we created a new disease risk predictor called PURE Indexsub for the Chinese population.The formula of PURE_Indexsub is:PURE_Indexsub=waist/height-1/t×wight1/3×hip5/8 Compared to other anthropometric indicators,PURE_Indexsub has a stronger association with cardiovascular diseases and its risk factors and have higher predicted power.Moreover,the performance of PURE Indexsub in the internal simulation datasets and external verification datasets remained stable,which shows that this index had good internal consistency and extrapolation.ConclusionsABSI did not apply to Chinese population.Based on the newly created PURE Indexsub for Chinese population,the predictive power for cardiovascular diseases and its risk factors was superior to any other traditional anthropometric measurements.In addition,PURE Indexsub has good internal consistency and extrapolation,which can be used as the best predictor for cardiovascular diseases and cardiometabolic risk factors... |
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