the european investigation into cancer and nutrition ( epic)-nl cohort consists of the two dutch contributions to the epic project : the prospect cohort and the monitoring project on risk factors for chronic diseases ( morgen ) cohorts . the study design of this combined cohort has previously been described in detail ( 13 ) . in brief , prospect is a prospective cohort study among 17,357 women aged 4970 years who participated in the breast cancer screening between 1993 and 1997 . the morgen cohort consists of 22,654 men and women aged 2059 years recruited from three dutch towns ( amsterdam , doetinchem , and maastricht ) . from 1993 to 1997 , each year a new random sample of ~5,000 individuals was examined for the morgen cohort . both studies complied with the declaration of helsinki . the prospect - epic study was approved by the institutional review board of the university medical center utrecht , and the morgen project was approved by the medical ethics committee of tno , the netherlands ( 13 ) . analyses were performed in two subsets composed of epic - nl participants , in whom all mets features were measured : the epic - nl case - cohort study ( 13 ) and a subset of epic - nl morgen participants ( 14 ) . the epic - nl case - cohort study consists of a subcohort , i.e. , 6.5% baseline random sample of the total epic - nl study ( n = 2,604 ) , all incident diabetes cases ( n = 924 ) , and all incident cvd cases ( n = 2,030 ) . by virtue of the random selection of a subcohort and use of the appropriated statistics for this type of research design , the results are expected to be generalizable to the entire cohort ( 15 ) . in the epic - nl case - cohort study , in addition to information on traditional mets features , information on nontraditional mets features , such as high - sensitivity c - reactive protein ( hscrp ) , was available . the epic - nl morgen subset was used as a replication sample for the analysis on model fit . this subset consists of 1,379 nondiabetic participants , who indicated that their last meal was on the day before blood sampling . in contrast to the epic - nl case - cohort study , plasma glucose was measured instead of hba1c , while information on nontraditional mets features was not available . participants with missing blood samples ( 157 participants in the random sample , 174 incident cvd case subjects , and 66 incident type 2 diabetes case subjects ) , participants who were taking glucose - lowering or blood pressure  lowering medication ( 282 participants in the random sample , 409 incident cvd case subjects , and 279 incident type 2 diabetes case subjects and 46 participants of the morgen subset ) or participants with missing values for one of the mets or mets - related features ( 237 participants in the random sample , 34 incident diabetes case subjects , and 135 incident cvd case subjects ) were excluded ( supplementary fig . subjects with missing blood samples were on average 2.4 years older and had a 1.1 kg / m higher bmi than those without missing blood samples . age and bmi were similar between subjects with and without missing values for one of the mets or mets - related features . finally , the epic - nl case - cohort study consisted of 545 incident diabetes case subjects , 1,312 incident cvd case subjects , and 1,928 participants in the random sample . of the random - sample participants , 53 were incident type 2 diabetes case subjects and 88 were incident cvd case subjects . an overlap between the case set and the random sample is a design feature of a case - cohort study . for the risk prediction analyses , prevalent type 2 diabetes and cvd case subjects were excluded from the random sample . the epic - nl morgen subset consisted of 1,333 participants , including 133 participants who were also included in the epic - nl case - cohort study . the ascertainment and verification of diabetes cases has previously been described in detail ( 16 ) . in short , diabetes was ascertained via self - report , a urinary glucose strip test , and linkage to registers of hospital discharge diagnoses . self - reported diabetes status was assessed in the baseline questionnaire and in two follow - up questionnaires , which were sent out at regular intervals of 35 years . for prospect participants only , a urinary glucose strip was sent out with the first follow - up questionnaire . follow - up by linkage to registers of hospital discharge diagnoses was completed on 1 january 2006 . potential cases were verified against participants ' general practitioner or pharmacist information . only verified type 2 diabetes cases were included . subsequently , primary and secondary causes of death were obtained through linkage with statistics netherlands . coronary heart disease ( chd ) was coded with icd-9 codes ( 410414 ) or with icd-10 codes ( i20i25 ) , and cerebrovascular accident ( cva ) was coded with icd-9 codes ( 430434 and 436 ) or with icd-10 codes cvd was defined as the presence of chd , cva , or both ( 17 ) . the study protocol of the epic - nl morgen study and the study protocol of the epic - nl prospect study were essentially similar . at baseline , a physical examination was performed and nonfasting blood samples were drawn . furthermore , a general questionnaire and a food frequency questionnaire ( ffq ) were filled out by each participant ( 13 ) . the protocol for the anthropometric measurements and the blood sampling protocol were identical for the epic - nl prospect and the epic - nl morgen studies . body weight was measured with light indoor clothing without shoes on to the nearest 100 g. during the physical examination , systolic and diastolic blood pressure measurements were performed twice in the supine position on the right arm using a boso oscillomat ( bosch & son , jungingen , germany ) ( prospect ) or twice on the left arm using a random zero sphygmomanometer ( morgen ) . triglycerides , alanine aminotransferase ( alt ) , aspartate aminotransferase ( ast ) ,  glutamyltransferase ( ggt ) , uric acid , and glucose were measured using enzymatic methods , whereas hscrp was measured with a turbidimetric method . these assays were all performed on an autoanalyzer ( lx20 ; beckman coulter , mijdrecht , the netherlands ) ( 13,14 ) . data on smoking habits , educational level , self - reported medication use , physical activity , and alcohol intake were obtained by general questionnaires and an ffq . triglycerides , hscrp , alt , ast , and ggt were log transformed to improve normality . using cfa , we designed several second - order one - factor mets models based on the mets model of shen et al . ( 9 ) consisting of three levels : a single mets factor ; several first - order factors ( e.g. , lipids ) , which defined the single mets factor ; and some second - order factors ( e.g. , triglycerides and hdl cholesterol ) , which defined the first - order factors . we designed the following one - factor mets models : model 1 , a standard mets model , based on the current definition of mets ( 1 ) , including the traditional mets features , i.e. , waist circumference , triglycerides , hdl cholesterol , systolic blood pressure , diastolic blood pressure , and as marker of glucose status , either hba1c or glucose ( fig . 1a and b ) ; model 2 , a standard mets model excluding the blood pressure factor ; and model 3 , a standard mets model extended with an hscrp factor ( fig . 1c ) , an albumin factor , a uric acid factor , or a liver enzymes factor . the liver enzymes factor was a first - order factor defined by the second - order factors alt , ast , and ggt . in all models , the factor variance of the mets factor , the factor loading of triglycerides , and the factor loading of systolic blood pressure were fixed to 1 . for model 3 , the mets model excluding blood pressure , not enough df were available to calculate model fit . therefore , the error variance of the factor with the highest factor loading ( waist circumference ) was fixed to 1 for the model fit calculations of this model . a : the standard second - order one - factor mets model in the random sample of epic - nl . b : the standard second - order one - factor mets model in the subset of the morgen study . c : the standard second - order one - factor mets model extended with hscrp in the random sample of epic - nl . the first - order factors are waist circumference ( wc ) , lipids , hba1c , fpg , and blood pressure . the second - order factors are triglyceride ( tg ) , hdl , systolic blood pressure ( sbp ) , and diastolic blood pressure ( dbp ) . model fit of mets models composed of traditional mets features was calculated in the random sample of epic - nl and in the epic - nl morgen subset . model fit of mets models including nontraditional features was calculated only in the random sample of epic - nl . we compared the model fit of all alternative mets models with the model fit of the standard one - factor mets model ( model 1 ) . the  test , the comparative fit index ( cfi ) , the standardized root means square residual ( srmr ) , and the root mean square error of approximation ( rmsea ) were used to assess model fit . models with rmsea > 0.10 , cfi < 0.95 , or srmr > 0.08 were rejected ( 19 ) . the  difference test was used to compare model fit across different models . for mets models with an acceptable model fit , we compared the predictive ability of the factor scores for incidence of type 2 diabetes , cvd , chd , and cva in the epic - nl case - cohort study . we calculated the factor scores using the factor score coefficients of the different mets features extracted by the regression method from the random sample . all factor score coefficients were standardized to the means and ses of the mets features in the random sample . for all factor scores , we calculated cox proportional hazard ratios ( hrs ) , c statistics , and integral discrimination indices ( idis ) for incidence of type 2 diabetes , cvd , chd , and cva . hrs were adjusted for the overrepresentation of cases in the case - cohort study with a pseudolikelihood method ( 20 ) , whereas idis and c statistics were adjusted for this overrepresentation by inverse probability weighing . hrs were calculated per sd of the factor score and adjusted for age , sex , cohort , smoking ( current , former , and never ) , educational level , cambridge physical activity index , and alcohol intake . the change in c statistics and the idis were used to compare predictive ability of the standard mets model , model 1 , with the alternative models . the c statistic is equivalent to the probability that the predicted risk is higher for a case than for a noncase subject ( 21 ) . the idi can be viewed as the difference in the proportion of variance explained by two models ( 22 ) . cfa analyses were performed in mplus , sixth edition ( muthn & muthn , los angeles , ca ) . hrs , c statistics , and idis were calculated in sas version 9.2 ( sas institute , cary , nc ) . the european investigation into cancer and nutrition ( epic)-nl cohort consists of the two dutch contributions to the epic project : the prospect cohort and the monitoring project on risk factors for chronic diseases ( morgen ) cohorts . the study design of this combined cohort has previously been described in detail ( 13 ) . in brief , prospect is a prospective cohort study among 17,357 women aged 4970 years who participated in the breast cancer screening between 1993 and 1997 . the morgen cohort consists of 22,654 men and women aged 2059 years recruited from three dutch towns ( amsterdam , doetinchem , and maastricht ) . from 1993 to 1997 , each year a new random sample of ~5,000 individuals was examined for the morgen cohort . both studies complied with the declaration of helsinki . the prospect - epic study was approved by the institutional review board of the university medical center utrecht , and the morgen project was approved by the medical ethics committee of tno , the netherlands ( 13 ) . analyses were performed in two subsets composed of epic - nl participants , in whom all mets features were measured : the epic - nl case - cohort study ( 13 ) and a subset of epic - nl morgen participants ( 14 ) . the epic - nl case - cohort study consists of a subcohort , i.e. , 6.5% baseline random sample of the total epic - nl study ( n = 2,604 ) , all incident diabetes cases ( n = 924 ) , and all incident cvd cases ( n = 2,030 ) . by virtue of the random selection of a subcohort and use of the appropriated statistics for this type of research design , the results are expected to be generalizable to the entire cohort ( 15 ) . in the epic - nl case - cohort study , in addition to information on traditional mets features , information on nontraditional mets features , such as high - sensitivity c - reactive protein ( hscrp ) , was available . the epic - nl morgen subset was used as a replication sample for the analysis on model fit . this subset consists of 1,379 nondiabetic participants , who indicated that their last meal was on the day before blood sampling . in contrast to the epic - nl case - cohort study , plasma glucose was measured instead of hba1c , while information on nontraditional mets features was not available . participants with missing blood samples ( 157 participants in the random sample , 174 incident cvd case subjects , and 66 incident type 2 diabetes case subjects ) , participants who were taking glucose - lowering or blood pressure  lowering medication ( 282 participants in the random sample , 409 incident cvd case subjects , and 279 incident type 2 diabetes case subjects and 46 participants of the morgen subset ) or participants with missing values for one of the mets or mets - related features ( 237 participants in the random sample , 34 incident diabetes case subjects , and 135 incident cvd case subjects ) were excluded ( supplementary fig . subjects with missing blood samples were on average 2.4 years older and had a 1.1 kg / m higher bmi than those without missing blood samples . age and bmi were similar between subjects with and without missing values for one of the mets or mets - related features . finally , the epic - nl case - cohort study consisted of 545 incident diabetes case subjects , 1,312 incident cvd case subjects , and 1,928 participants in the random sample . of the random - sample participants , 53 were incident type 2 diabetes case subjects and 88 were incident cvd case subjects . an overlap between the case set and the random sample is a design feature of a case - cohort study . for the risk prediction analyses , the epic - nl morgen subset consisted of 1,333 participants , including 133 participants who were also included in the epic - nl case - cohort study . the ascertainment and verification of diabetes cases has previously been described in detail ( 16 ) . in short , diabetes was ascertained via self - report , a urinary glucose strip test , and linkage to registers of hospital discharge diagnoses . self - reported diabetes status was assessed in the baseline questionnaire and in two follow - up questionnaires , which were sent out at regular intervals of 35 years . for prospect participants only , a urinary glucose strip was sent out with the first follow - up questionnaire . follow - up by linkage to registers of hospital discharge diagnoses was completed on 1 january 2006 . potential cases were verified against participants ' general practitioner or pharmacist information . only verified type 2 diabetes cases were included . coronary heart disease ( chd ) was coded with icd-9 codes ( 410414 ) or with icd-10 codes ( i20i25 ) , and cerebrovascular accident ( cva ) was coded with icd-9 codes ( 430434 and 436 ) or with icd-10 codes cvd was defined as the presence of chd , cva , or both ( 17 ) . the study protocol of the epic - nl morgen study and the study protocol of the epic - nl prospect study were essentially similar . at baseline , a physical examination was performed and nonfasting blood samples were drawn . furthermore , a general questionnaire and a food frequency questionnaire ( ffq ) were filled out by each participant ( 13 ) . the protocol for the anthropometric measurements and the blood sampling protocol were identical for the epic - nl prospect and the epic - nl morgen studies . body weight was measured with light indoor clothing without shoes on to the nearest 100 g. during the physical examination , systolic and diastolic blood pressure measurements were performed twice in the supine position on the right arm using a boso oscillomat ( bosch & son , jungingen , germany ) ( prospect ) or twice on the left arm using a random zero sphygmomanometer ( morgen ) . triglycerides , alanine aminotransferase ( alt ) , aspartate aminotransferase ( ast ) ,  glutamyltransferase ( ggt ) , uric acid , and glucose were measured using enzymatic methods , whereas hscrp was measured with a turbidimetric method . these assays were all performed on an autoanalyzer ( lx20 ; beckman coulter , mijdrecht , the netherlands ) ( 13,14 ) . data on smoking habits , educational level , self - reported medication use , physical activity , and alcohol intake were obtained by general questionnaires and an ffq . triglycerides , hscrp , alt , ast , and ggt were log transformed to improve normality . using cfa , we designed several second - order one - factor mets models based on the mets model of shen et al . ( 9 ) consisting of three levels : a single mets factor ; several first - order factors ( e.g. , lipids ) , which defined the single mets factor ; and some second - order factors ( e.g. , triglycerides and hdl cholesterol ) , which defined the first - order factors . we designed the following one - factor mets models : model 1 , a standard mets model , based on the current definition of mets ( 1 ) , including the traditional mets features , i.e. , waist circumference , triglycerides , hdl cholesterol , systolic blood pressure , diastolic blood pressure , and as marker of glucose status , either hba1c or glucose ( fig . 1a and b ) ; model 2 , a standard mets model excluding the blood pressure factor ; and model 3 , a standard mets model extended with an hscrp factor ( fig . 1c ) , an albumin factor , a uric acid factor , or a liver enzymes factor . the liver enzymes factor was a first - order factor defined by the second - order factors alt , ast , and ggt . in all models , the factor variance of the mets factor , the factor loading of triglycerides , and the factor loading of systolic blood pressure were fixed to 1 . for model 3 , the mets model excluding blood pressure , not enough df were available to calculate model fit . therefore , the error variance of the factor with the highest factor loading ( waist circumference ) was fixed to 1 for the model fit calculations of this model . a : the standard second - order one - factor mets model in the random sample of epic - nl . b : the standard second - order one - factor mets model in the subset of the morgen study . c : the standard second - order one - factor mets model extended with hscrp in the random sample of epic - nl . the first - order factors are waist circumference ( wc ) , lipids , hba1c , fpg , and blood pressure . the second - order factors are triglyceride ( tg ) , hdl , systolic blood pressure ( sbp ) , and diastolic blood pressure ( dbp ) . model fit of mets models composed of traditional mets features was calculated in the random sample of epic - nl and in the epic - nl morgen subset . model fit of mets models including nontraditional features was calculated only in the random sample of epic - nl . we compared the model fit of all alternative mets models with the model fit of the standard one - factor mets model ( model 1 ) . the  test , the comparative fit index ( cfi ) , the standardized root means square residual ( srmr ) , and the root mean square error of approximation ( rmsea ) were used to assess model fit . models with rmsea > 0.10 , cfi < 0.95 , or srmr > 0.08 were rejected ( 19 ) . the  difference test was used to compare model fit across different models . for mets models with an acceptable model fit , we compared the predictive ability of the factor scores for incidence of type 2 diabetes , cvd , chd , and cva in the epic - nl case - cohort study . we calculated the factor scores using the factor score coefficients of the different mets features extracted by the regression method from the random sample . all factor score coefficients were standardized to the means and ses of the mets features in the random sample . for all factor scores , we calculated cox proportional hazard ratios ( hrs ) , c statistics , and integral discrimination indices ( idis ) for incidence of type 2 diabetes , cvd , chd , and cva . hrs were adjusted for the overrepresentation of cases in the case - cohort study with a pseudolikelihood method ( 20 ) , whereas idis and c statistics were adjusted for this overrepresentation by inverse probability weighing . hrs were calculated per sd of the factor score and adjusted for age , sex , cohort , smoking ( current , former , and never ) , educational level , cambridge physical activity index , and alcohol intake . the change in c statistics and the idis were used to compare predictive ability of the standard mets model , model 1 , with the alternative models . the c statistic is equivalent to the probability that the predicted risk is higher for a case than for a noncase subject ( 21 ) . the idi can be viewed as the difference in the proportion of variance explained by two models ( 22 ) . cfa analyses were performed in mplus , sixth edition ( muthn & muthn , los angeles , ca ) . hrs , c statistics , and idis were calculated in sas version 9.2 ( sas institute , cary , nc ) . participants in the epic - nl case - cohort study were on average 51.8 years old , and 28.5% was male . mets prevalence was higher in incident diabetes case subjects ( 70.5% ) and incident cvd case subjects ( 38.6% ) than in the random sample ( 21.2% ) . in the morgen subset , participants were on average 39.1 years old , and 50.5% was male . mets prevalence was somewhat lower ( 14.9% ) than in the random sample of epic - nl ( 21.2% ) . baseline characteristics of the epic - nl study the standard one - factor mets model ( model 1 ) ( fig . 1a and b ) , which is based on the current definition of mets , had an acceptable model fit with a cfi of 0.95 ( table 2 ) . other one - factor mets models with a good model fit were the mets model excluding blood pressure ( model 2 ) and the mets model extended with hscrp ( model 3 ) ( fig . the cfis of one - factor mets models extended with uric acid , liver enzymes , or albumin were < 0.95 , indicating that their model fit was unacceptable . these extended mets models also did not fit well after the exclusion of the blood pressure factor ( data not shown ) . compared with the standard mets model ( model 1 ) , the standard mets model excluding blood pressure ( model 2 ) fitted better , whereas the model extended with hscrp ( model 3 ) fitted worse . model fit indices of several mets models in the random sample of the epic - nl study and in a subset with participants of the morgen study hrs for type 2 diabetes ( hr 2.71 [ 95% ci 2.303.18 ] ) and cvd ( 1.25 [ 1.131.39 ] ) were lowest in the mets model excluding blood pressure ( model 2 ) , whereas they were highest in the mets model extended with hscrp ( type 2 diabetes hr 3.94 [ 3.284.74 ] ; cvd 1.28 [ 1.161.42 ] ) ( table 3 ) . hrs were essentially similar after additional adjustment for fiber and energy intake ( data not shown ) . of all mets models , the model extended with hscrp ( model 3 ) predicted type 2 diabetes , chd , cva , and cvd the best ( type 2 diabetes c index 0.8013 ; cvd c index 0.6352 ) . for all models , the hosmer - lemeshow test was not significant , indicating a good calibration . we have examined the factor structure of mets using cfa in two population - based study samples . the good model fit of the standard one - factor mets model , representing the current definition , indicated that it is valid to compose one entity out of the traditional mets features . when the standard mets model was extended with hscrp , predictive ability for type 2 diabetes and cvd increased slightly , while model fit was still acceptable . in line with the results of previous cfa studies ( 79 ) , we found that it is valid to compose one entity , i.e. , one factor out of the five traditional mets features . the model fit of a one - factor mets model , composed of the traditional mets features , was even better after exclusion of the blood pressure factor . this is consistent with other studies indicating that blood pressure is distinct from the other traditional mets features , both from a physiological ( 23 ) and a statistical point of view . for example , blood pressure generally has the lowest factor loading in cfa mets models ( 711 ) . furthermore , blood pressure is identified as a separate factor in most efa studies ( 6 ) . although omitting the blood pressure factor improved model fit , it also considerably decreased the predictive ability for type 2 diabetes , cva , and chd . since this predictive ability is of clinical relevance , removal of blood pressure from the mets definition is questionable . of the one - factor mets models extended with nontraditional mets features , only the mets model extended with hscrp had an acceptable model fit . in 645 non - hispanic whites or african americans , an essentially similar mets model also had a good model fit ( 8) . in our data , the mets model extended with hscrp predicted type 2 diabetes , cva , and chd slightly better than the standard mets model . in contrast to type 2 diabetes and cva , the improvement in c index was not significant for chd . this suggests that in our data , the improvement in c index for cvds is mainly driven by the improvement for cva . in two large prospective cohort studies , though our findings are in line with these previous studies , the addition of hscrp to mets was clinically relevant in the earlier reports but not in our study . the reason for this discrepancy might be explained by a difference in study population ; e.g. , in our study compared with the previous studies , hscrp levels were lower . part of the added predictive power of hscrp may be explained by the association of hscrp with insulin resistance and fibrinolysis . both increase the risk of type 2 diabetes and cvd but are not included in the current definition of mets ( 26 ) . in our study , the model fit of other one - factor mets models extended with additional features , i.e. , albumin , liver enzymes , or uric acid , was not acceptable . to the best of our knowledge , models extended with albumin or liver enzymes have not previously been studied . our results are , however , in line with several efa studies ( 2427 ) . contrary to our results , among 410 spanish participants a one - factor mets model extended with uric acid had a very good model fit ( cfi 0.99 ) ( 4 ) . the relatively low factor loading of mets features strongly associated with uric acid , such as glucose ( 28 ) , may explain the bad model fit of the model extended with uric acid in our data . the strength of our study was the hypothesis - driven cfa approach , which we used to compare the model fit of a standard mets model with several modified mets models . furthermore , we tested the model fit of the mets models in two relatively large study samples , and results were very similar . we have adjusted the hrs for several lifestyle factors . as the hrs were similar before and after adjustment , the confounding effect of these lifestyle factors was probably small . the use of nonfasting triglycerides and hba1c instead of the conventional mets features , i.e. , fasting triglycerides and glucose , in the epic - nl case - cohort study may have affected model fit . as postprandial triglyceride levels are more strongly correlated with the other mets features than fasting triglyceride levels ( 29 ) , the use of postprandial triglycerides levels may have improved model fit and increased the factor loadings of the lipid factor in the epic - nl case - cohort . in contrast , for most mets features the correlations with hba1c and fasting plasma glucose were similar in 160 epic - nl participants with both measurements available . only the correlation of waist circumference and hba1c was weaker than the correlation of waist circumference and fasting plasma glucose . this weak correlation resulted in a relative low factor loading for the glucose factor ( based on hba1c ) and perhaps in somewhat lower model fit . however , although nonfasting triglycerides and hba1c were used in the epic - nl case - cohort study , conclusions regarding model fit in the epic - nl case - cohort study were similar to the morgen subset in which fasting plasma glucose and triglycerides were used . compared with fasting plasma glucose , therefore , inclusion of hba1c instead of fasting glucose in the epic - nl mets models has most likely increased predictive ability . however , as this applies to all mets models , the comparisons between the different mets models would probably have yielded similar conclusions if fasting plasma glucose had been included . moreover , as fasting plasma glucose levels were not available , we may have missed some undiagnosed type 2 diabetes cases . underestimation of diabetic cases may have weakened the associations with diabetes we found in epic - nl . the participants ( 7% ) we excluded from the epic - nl case - cohort owing to missing blood samples had on average a 1.1 kg / m higher bmi . as the correlations between waist circumference and other mets features were slightly higher in the group with missing blood samples , exclusion of these participants may have resulted in somewhat lower factor loadings for the waist circumference factor . additionally , the two datasets we used were not completely independent , as 133 subjects were present both in the epic - nl case - cohort study and in the morgen subset . however , when we excluded these 133 participants from the morgen subset , results were essentially similar . finally , in order to be able to estimate model fit of the mets model excluding blood pressure , we fixed the error variance of waist circumference in this model to one . this fixation has probably worsened the model fit . therefore , we may have underestimated the improvement in model fit obtained by deleting the blood pressure factor . in conclusion , it is valid to compose out of the traditional mets features one entity and consequently to view mets as a single disorder . a model additionally including hscrp still represented a single entity and predicted type 2 diabetes , cva , and chd somewhat better than a mets model with only the traditional features . cfa mets models , like ours , including the traditional mets features and possibly hscrp may be used as the basis to develop a new continuous mets definition with differential weights for the different mets features , using an approach described by hillier et al .
objectivemetabolic syndrome ( mets ) is a cluster of abdominal obesity , hyperglycemia , hypertension , and dyslipidemia , which increases the risk for type 2 diabetes and cardiovascular diseases ( cvds ) . 
 some argue that mets is not a single disorder because the traditional mets features do not represent one entity , and they would like to exclude features from mets . 
 others would like to add additional features in order to increase predictive ability of mets . 
 the aim of this study was to identify a mets model that optimally predicts type 2 diabetes and cvd while still representing a single entity.research design and methodsin a random sample ( n = 1,928 ) of the epic - nl cohort and a subset of the epic - nl morgen study ( n = 1,333 ) , we tested the model fit of several one - factor mets models using confirmatory factor analysis . 
 we compared predictive ability for type 2 diabetes and cvd of these models within the epic - nl case - cohort study of 545 incident type 2 diabetic subjects , 1,312 incident cvd case subjects , and the random sample , using survival analyses and reclassification.resultsthe standard model , representing the current mets definition ( epic - nl comparative fit index [ cfi ] = 0.95 ; morgen cfi = 0.98 ) ; the standard model excluding blood pressure ( epic - nl cfi = 0.95 ; morgen cfi = 1.00 ) ; and the standard model extended with hscrp ( epic - nl cfi = 0.95 ) had an acceptable model fit . 
 the model extended with hscrp predicted type 2 diabetes ( integral discrimination index [ idi ] : 0.34 ) and cvd ( idi : 0.07 ) slightly better than did the standard model.conclusionsit seems valid to represent the traditional mets features by a single entity . 
 extension of this entity with hscrp slightly improves predictive ability for type 2 diabetes and cvd .