| In 2010,the American Heart Association(AHA)proposed seven simple cardiovascular health(CVH)metrics(including smoking,body mass index,diet,physical activity,blood pressure,total cholesterol,and fasting blood glucose),aiming to improve cardiovascular health and reduce the risk of cardiovascular events.However,since many cardiovascular risk factors could also increase the risk of diabetes mellitus,the association between CVH metrics and incident diabetes mellitus is also worth exploring.Type 2 diabetes mellitus(T2DM),as the main type of diabetes mellitus,has become a serious threat to human health of chronic non-communicable diseases,and early identification of T2DM risk factors and the appropriate prevention and control measures are of great significance to reduce the incidence of T2DM and the disease burden caused by T2DM.At present,there are still few studies on the association between CVH metrics and incident T2DM.Although there were two prospective cohort studies in China which exploring the association between CVH metrics and incident T2DM,there are still the following problems in this research field:1)The participants of the existing studies in China are all from the occupational population,and there is still lack of study evidence based on the general population;2)When exploring the association between CVH metrics and incident T2DM,there is still lack of relevant studies on the possible interaction of CVH metrics and other factors with incident T2DM;3)Whether there is a mediating variable that plays a mediating role in the association of CVH metrics with incident T2DM has not been reported yet.Therefore,this study will further explore the association of CVH metrics and its dynamic change with incident T2DM in Chinese general adult population through the number of ideal CVH metrics and CVH score,so as to provide epidemiological evidence for the development of prevention and control strategies for T2DM in the future.Objectives1.To explore the association between CVH metrics and incident T2DM,and to compare predictive ability of the number of ideal CVH metrics and CVH score for T2DM.2.To explore the association between the dynamic change of CVH metrics and incident T2DM.3.To explore the association of incident T2DM with the interaction between CVH metrics and its dynamic change and other influence factors.4.To explore the mediating effect of insulin resistance in the association of CVH metrics and its dynamic change with incident T2DM.MethodsA prospective cohort study design was used in this study.A total of 20194 rural adults aged 18 years and older were included in the baseline survey in 2007-2008 by using a cluster random sampling method.Through questionnaire interview,physical examination,and blood sample collection,we collected information of demographic,behavioral risk factors,family disease history,disease history,anthropometric and laboratory measurements.A follow-up survey of 17265 participants was completed from 2013 to 2014,with a follow-up rate of 85.5%.After excluding participants with baseline age 18 to 20 years old,with baseline T2DM and type 1 diabetes mellitus,with baseline and follow-up gestational diabetes mellitus,with incomplete baseline CVH metrics information,death during the follow-up examination,and with missing information of T2DM event during follow-up survey,a total of 12150 participants were enrolled to explore the association of CVH metrics with incident T2DM.According to the definition of CVH metrics,the number of CVH metrics achieving ideal status was calculated and defined as the number of ideal CVH metrics,meanwhile each CVH indicator was respective given 0,1 and 2 points according to the poor,intermediate and ideal status,and the sum of the scores of each CVH indicator was calculated and defined as CVH score:1)Cox proportional hazard regression model was used to evaluate association of the number of ideal CVH metrics and CVH score with incident T2DM,estimating hazard ratios(HRs)and the 95%confidence intervals(CIs),and the sensitivity analysis and subgroup analysis were also conducted.2)Populational Attributable Risk Percentage(PAR%)and its 95%CI were calculated for preventing the proportion of incident T2DM when the number of ideal CVH metrics and CVH score reached the specified level.3)To assess whether there is a multiplicative or additive interaction of the number of ideal CVH metrics and CVH score with other factors(gender,age,education level,marital status and alcohol consumption)on incident T2DM.4)To explore the mediating effect of triglyceride glucose(TyG)index(a surrogate of insulin resistance)on the association of the number of ideal CVH metrics and CVH score with incident T2DM.5)Receiver Operating Characteristic(ROC)curve was used to compare the predictive ability of the ideal number of CVH metrics and CVH score on incident T2DM.Based on the enrolled 12150 participants,a total of 11450 participants were enrolled after excluding participants with incomplete information of each CVH metric during the follow-up survey.The difference of the number of ideal CVH metrics and CVH score between follow-up and baseline examination were calculated to explore the association between dynamic change of CVH metrics and incident T2DM:1)Logistic regression model was used to evaluate association of dynamic change of the number of ideal CVH metrics and CVH score with incident T2DM,estimating odds ratios(ORs)and 95%CIs,and the sensitivity analysis and subgroup analysis were also conducted.2)To assess whether there is a multiplicative or additive interaction of dynamic change of the number of ideal CVH metrics and CVH score with other factors on incident T2DM.3)To explore the mediating effect of TyG index on the association of dynamic change of the number of ideal CVH metrics and CVH score with incident T2DM.Results1.In this study,a total of 840 newly onset T2DM patients were observed over a median follow-up period of 6.01 years,with incidence of 11.68/1000 person-years.Each increase in the number of ideal CVH metrics was associated with a 24%decrease in the risk of incident T2DM(HR=0.76,95%CI:0.70-0.82).The higher the number of ideal CVH metrics,the higher the PAR%of incident T2DM.When the number of ideal CVH metrics was≥ 5,the incident T2DM was reduced about 49%(PAR%=49.0,95%CI:29.7-64.5).The number of ideal CVH metrics has a multiplicative interaction with age on incident T2DM,and there was not only a multiplicative interaction with gender,but also an additive interaction.The results were consistent with the total population analysis except for≥ 65 years,unmarried,divorced or widowed,and alcohol consumption.TyG index played a partial mediating role in the protective effect of the increment of the number of ideal CVH metrics on incident T2DM.2.Each increase in CVH score was associated with a 15%decrease in the risk of incident T2DM.(HR=0.85,95%CI:0.81-0.88).The higher the CVH score,the higher the PAR%of incident T2DM.When the CVH score was≥ 11,the incident T2DM was reduced about 52%(PAR%=52.0,95%CI:24.7-71.6).CVH score has a multiplicative interaction with age on incident T2DM,and there is not only a multiplicative interaction with gender,but also an additive interaction.The results were consistent with the total population analysis except for≥ 65 years,unmarried,divorced or widowed,and alcohol consumption.TyG index played a partial mediating role in the protective effect of CVH score on incident T2DM.In addition,there was no significant difference in the area under the ROC curve between the number of ideal CVH metrics and CVH score on the prediction ability of T2DM(P=0.334).3.With the dynamic increase of the number of ideal CVH metrics by 1-unit,the negative correlation strength of incident T2DM change by 33%(OR=0.67,95%CI:0.60-0.74).No interaction effect was found between the dynamic change of the number of ideal CVH metrics and other factors for incident T2DM.In different baseline demographic characteristics of the subgroup analysis showed that except for≥ 65 years and unmarried,divorced or widowed people,the results were consistent with the total population analysis.TyG index played a complete mediating role in the protective effect of the dynamic increase of the number of ideal CVH metrics on incident T2DM.In addition,compared with the study participants with low CVH status in both baseline and follow-up examination,the negative correlation strength of incident T2DM changed by 58%(OR=0.42,95%CI:0.24-0.74)in participants with the status of the number of ideal CVH metrics changed from low to high,and the negative correlation strength of incident T2DM changed by 73%(OR=0.27,95%CI:0.20-0.36)in participants with those who kept CVH status at high status both in baseline and follow-up examination.4.With the dynamic increase of CVH score by 1-point,the negative correlation strength of incident T2DM change by 23%(OR=0.77,95%CI:0.72-0.82).No interaction effect was found between the dynamic change of CVH score and other factors for incident T2DM.In different baseline demographic characteristics of the subgroup analysis showed that except for≥ 65 years,the results were consistent with the total population analysis.TyG index played a complete mediating role in the protective effect of the dynamic increase of CVH score on incident T2DM.In addition,compared with the study participants with low CVH status in both baseline and follow-up examination,the negative correlation strength of incident T2DM changed by 68%(OR=0.32,95%CI:0.15-0.72)in participants with the status of CVH score changed from low to high,and the negative correlation strength of incident T2DM changed by 75%(OR=0.25,95%CI:0.18-0.35)in participants with those kept CVH status at high status both in baseline and follow-up examination.Conclusions1.The higher the number of ideal CVH metrics and CVH score have a certain protective effect on incident T2DM,and the higher the number of ideal CVH metrics and CVH score,the higher proportion of T2DM incidence could be reduced in the population.Therefore,attention should be paid to improving cardiovascular health in the future to reduce the risk of T2DM.In addition,no difference was found between the number of ideal CVH metrics and CVH score in predicting incident T2DM in the current study.2.Increasing dynamic increment of the number of ideal CVH metrics and CVH score,improving the status of the number of ideal CVH metrics and CVH score and maintain them in a higher status are likely to play protective role for incident T2DM,which suggests it is of great public health significance to actively improve or maintain good CVH status to prevent the occurrence of T2DM.3.There is a multiplicative interaction between the number of ideal CVH metrics and CVH score and age,and both a multiplicative interaction and an additive interaction between the number of ideal CVH metrics and CVH score and gender were observed,which suggesting that the association between CVH metrics and incident T2DM may exist differences due to gender and age,especially the risk of T2DM in women with low the number of ideal CVH metrics and low CVH score.4.The protective effect of elevating the number of ideal CVH metrics and CVH score on incident T2DM may be realized by reducing the level of insulin resistance to a certain extent,and the protective effect of the dynamic increment of the number of ideal CVH metrics and CVH score on incident T2DM may be realized entirely by reducing the level of insulin resistance. |
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