Association Between Obesity With Ischemic Stroke:A Prospective Cohort Study

Background and objective:Stroke is one of the common chronic diseases with high incidence,which has become an important risk factor threatening human health and life.China is one of the countries with the highest incidence of stroke.Stroke is divided into ischemic stroke and hemorrhagic stroke.Ischemic stroke（IS）is the main type of stroke in China,accounting for 74%of all stroke.Overweight and obesity are important risk factors of ischemic stroke.Traditional obesity-related indicators including body mass index（BMI）,waist circumference（WC）,waist-to-height ratio（WHt R）and waist-to-hip ratio（WHR）.They are the main tools for diagnosis and screening of obese individuals.They are widely used in clinical practice and have the advantages of non-invasive,effective and easy to implement.However,there are some limitations in the practical application of traditional obesity-related indicators.BMI can not accurately reflect the actual obesity status and body fat distribution.WC,WHt R,WHR as a measure of central obesity,only consider the accumulation of body fat in the abdomen and buttocks,do not consider muscle mass and other factors.Therefore,some new obesity-related indicators have been proposed to better evaluate obesity.Conicity index（CI）is a comprehensive obesity-related indicators based on weight,height and WC,which can better determine the degree of central obesity and the accumulation of abdominal fat.CI has been widely used to assess the risk of different diseases.New obesity-related indicators:body shape index（ABSI）,body roundness index（BRI）and abdominal volume index（AVI）can also be used to estimate the degree of abdominal obesity and visceral fat.At present,the correlation between CI,ABSI,BRI,AVI and the risk of IS needs to be further discussed.Lack of prospective cohort to explore the impact of new and traditional obesity-related indicators on the risk of IS and its predictive ability in the Chinese population.Therefore,this study used the Qingdao project site of the China Kadoorie Biobank（CKB）to explore the relationship between obesity-related indicators and the risk of IS and its predictive ability.It is of great significance to predict and prevent the occurrence and development of IS for early and accurate identification of high-risk groups of IS.Methods:The participates came from the Qingdao project site of the CKB.A total of 35,508 Participants were included in the baseline survey.Excluding self-reported diagnosis of coronary heart disease（n₁=1,827）,stroke（n₂=238）and cancer（n₃=162）,a total of33,355 subjects were included in this study.The baseline survey mainly includes three parts:physical examination,random blood glucose and questionnaire.The detailed information of the incidence of IS in the cohort was obtained through the National Surveillance Point system（DSP）of the Chinese Center for Disease Control and Prevention,combined with the public security population information system and medical insurance participation information.Obesity-related indicators include body mass index（BMI）,waist circumference（WC）,waist-height ratio（WHt R）,waist-to-hip ratio（WHR）,conicity index（CI）,a body shape index（ABSI）,body roundness index（BRI）and abdominal volume index（AVI）.Multivariate Cox regression model was used to analyze the association between obesity and the risk of IS,restricted cubic spline was used to analyze the dose-response relationship between obesity and the risk of IS.The subgroup analysis was conducted according to the baseline characteristics of the participants to examine the association between obesity and IS with different characteristics.The participants with IS in the two years before follow-up were excluded for sensitivity analysis.The prediction effect of obesity-related indicators on the risk of IS by using the receiver operating characteristic（ROC）curve,and the differences of area under the curves（AUC）were compared.The maximum Youden index was used to determine suitable cut-point value of prediction.Results:1.In the baseline survey,women accounted for 55.31%,the average age was（50.09±9.88）years.The physical activity,SBP,WC,WHR and CI of males were higher than those of females,while random blood glucose,BMI,WHt R and BRI of males were lower than those of females（P<0.05）.The intake of meat in males was higher than that in females,while the intake of vegetables,fruits and dairy products was lower than that in females（P<0.05）.2.In this study,a total of 302,008.88 person-years were followed up for an average of9.05.1,093 of incidence cases of IS（530 males and 563 females）.The incidence density of 361.91 per 100,000 person-years.3.The relationship between obesity-related indicators and the risk of IS:After adjusting gender,age,occupation,marital status,education level,annual family income,smoking,drinking,physical activity and family history of stroke（Model 2）,the Cox regression analysis results showed that with the increase of BMI,WC,WHt R,WHR,CI,ABSI,BRI and AVI,the risk of IS increased,the same trend in both males and females.There was a positive nonlinear dose-response relationship between WC,WHt R,WHR,CI,ABSI,BRI and the risk of IS(P _Nonlinear<0.05),but there was not find nonlinear dose-response relationship between BMI and IS(P _Nonlinear>0.05).4.The AUC of obesity-related indicators:BMI（AUC:0.60,95%CI:0.59-0.62）;WC（AUC:0.67,95%CI:0.66-0.69）;WHt R（AUC:0.69,95%CI:0.68-0.71）;WHR（AUC:0.68,95%CI:0.67-0.70）;CI（AUC:0.71,95%CI:0.69-0.72）;ABSI（AUC:0.64,95%CI:0.62-0.65）;BRI（AUC:0.70,95%CI:0.68-0.71）;AVI（AUC:0.67,95%CI:0.66-0.69）.The suitable cut-point of obesity-related indicators:BMI was 25.75（kg/m²）,WC was88.85（cm）,WHt R was 0.54,WHR was 0.88,CI was 1.24(m^3/2/kg^1/2),ABSI was 0.08(m^7/6/kg^2/3),BRI was 4.17,AVI was 15.92（cm²）。5.The AUC of obesity-related indicators in male:BMI（AUC:0.56,95%CI:0.54-0.58）;WC（AUC:0.62,95%CI:0.60-0.64）;WHt R（AUC:0.65,95%CI:0.63-0.67）;WHR（AUC:0.64,95%CI:0.61-0.66）;CI（AUC:0.67,95%CI:0.64-0.69）;ABSI（AUC:0.59,95%CI:0.57-0.62）;BRI（AUC:0.65,95%CI:0.63-0.68）;AVI（AUC:0.62,95%CI:0.59-0.64）.The suitable cut-point of obesity-related indicators in male:BMI was 24.05（kg/m²）,WC was 89.45（cm）,WHt R was 0.52,WHR was 0.91,CI was 1.25(m^3/2/kg^1/2),ABS was0.08(m^7/6/kg^2/3),BRI was 3.67,AVIwas16.17（cm²）。6.The AUC of obesity-related indicators in female:BMI（AUC:0.64,95%CI:0.62-0.66）;WC（AUC:0.72,95%CI:0.70-0.74）;WHt R（AUC:0.74,95%CI:0.72-0.76）;WHR（AUC:0.72,95%CI:0.70-0.74）;CI（AUC:0.74,95%CI:0.72-0.76）;ABSI（AUC:0.67,95%CI:0.65-0.69）;BRI（AUC:0.74,95%CI:0.72-0.76）;AVI（AUC:0.71,95%CI:0.69-0.73）.The suitable cut-point of obesity-related indicators in female:BMI was 26.55（kg/m²）,WC was 87.15（cm）,WHt R was 0.56,WHR was 0.88,CI was 1.23(m^3/2/kg^1/2),ABSI was 0.08(m^7/6/kg^2/3),BRI was 4.42,AVI was 15.92（cm²）。7.According to the baseline characteristics of the participants,subgroup analysis showed that there were significant differences in age,smoking,drinking,random blood glucose and blood pressure between obesity-related indicators and the risk of IS.8.The sensitivity analysis is consistent with the overall population analysis results.Conclusions:1.The increase of obesity-related indicators（BMI,WC,WHt R,WHR,CI,ABSI,BRI,AVI）was associated with the risk of IS.2.There was a positive non-linear dose-response relationship between obesity-related indicators（WC,WHt R,WHR,CI,ABSI,BRI,AVI）and the risk of IS.3.Among the eight obesity-related indicators,the new obesity-related indicators CI has the best predictive effect on the risk of IS in Chinese population.The index calculation includes height,weight and WC.It has good internal consistency and crowd extrapolation.