obesity is emerging as an important health issue in venezuela , particularly in urban areas , paradoxically coexisting with undernutrition . the rising prevalence of overweight and obesity around the world shares a direct correlation with the increasing occurrence of obesity - related comorbidities such as high blood pressure ( hbp ) , metabolic syndrome ( ms ) , dyslipidemia , type 2 diabetes mellitus ( t2 dm ) , and cardiovascular disease ( cvd ) . several pathophysiological aspects have been proposed to explain the close relationship between these diseases , including the degree of adiposity and anatomic fat localization [ 13 ] . currently , it is accepted that the majority of individuals who have obesity progressively develop insulin resistance , beta cell failure , and lastly t2 dm , proving to be a biological continuum that is undeniably complicated and intricate [ 2 , 3 ] . however , approximately 1025% of obese individuals are metabolically healthy , most likely due to preserved insulin sensitivity probably due to genetic factors . on the other hand , visceral adipose tissue inflammation , ectopic fat deposition , and adipose tissue dysfunction have been proposed as an etiologic triumvirate that mediates insulin resistance in human obesity independently of total body fat mass . furthermore , it has been reported that around 1015% of lean subjects may exhibit insulin resistance and other metabolic disturbances like dyslipidemia , dysglycemia , and hbp . this landscape suggests four well - defined phenotypes existence in human beings according to body composition and metabolic status : ( a ) healthy normal weight ( hnw ) , ( b ) metabolically obese normal weight ( monw ) , ( c ) metabolically disturbed obese ( mdo ) , and ( d ) metabolically healthy obese ( mho ) [ 68 ] . it has been highlighted that the proposed waist circumference ( wc ) cut - off points for latin america , as well as other parts of the world , have relatively low areas under the curve ( auc ) and therefore relatively low sensitivities and specificities during cor curves construction [ 9 , 10 ] when using traditional criteria to classify subjects as healthy or sick , such as the presence of two or more components of the ms criteria as reported by hara et al . . recently , our group built roc curves for wc cutoff - point selection using 2 or more positive ms components to differentiate between healthy and sick individuals , rendering values of 90.25  cm ( 68.4% sensitivity , 65.8% specificity ) for women and 95.15  cm for men ( 71.1% sensitivity , 67.4% specificity ) . nevertheless , it has been suggested that unusual metabolic phenotypes such as monw and mho could influence the accuracy of obesity - centered studies due to difficulties in subject characterization [ 68 ] , and this setback includes sensitivity and specificity from wc cut - offs point selection for obesity diagnosis . the biological traits of these uncommon phenotypes [ 68 , 13 ] result in uncharacteristic grouping of metabolic components which could be difficult to predict . therefore , the proof - of - concept would be that the early detection of these phenotypes prior to wc selection could improve the accuracy of selected wc cutpoints , and their future application in epidemiological studies . the possibility of detecting monw and mho prior to any cut - off point selection method can not rely on common markers such as wc because they can be misleading , due to the uniqueness of such phenotypes [ 7 , 8 ] . in this context , the advantage of applying data mining techniques ( like cluster analysis ) is that it allows the spontaneous grouping of individuals according to the behavior of metabolic and anthropometric variables , superseding the discriminating capacity of internationally appointed wc cut - off points and other preestablished criteria for metabolic alterations . since these phenotypes do not behave in the same manner as the common ones , they could be considered as  noise  during the construction of roc curves and might affect the sensitivity of specificity of the selected cutpoints for wc . thus , the ability to identify and filter them from the roc construction process is not only optional , but actually necessary . taking all this information into consideration , the purpose of this investigation was to identify subjects with unusual metabolic phenotypes and , afterwards , evaluate their influence during the construction of roc curves for wc cut - off point selection . the maracaibo city metabolic syndrome prevalence study ( mmsps )   was a cross - sectional research study undertaken in the city of maracaibo - venezuela , whose purpose was the identification and analysis of ms and cardiovascular risk factors in the adult population of maracaibo , the second largest city in venezuela with 2.750.00 inhabitants . currently , there are 2,230 subjects enrolled , out of which 1,902 were selected , therefore excluding those individuals whose serum insulin levels were not determined and those diagnosis with diabetes mellitus ; the latter was excluded because pharmacological treatment of these patients would modify the variables used in this research . the study was approved by the bioethics committee of the endocrine and metabolic diseases research center , university of zulia , and all participants signed a written consent before being interrogated and physically examined by a trained team . the assessment of blood pressure was done applying the auscultatory technique , and hbp classification was made using the criteria proposed in the vii joint national committee on prevention , detection , evaluation , and treatment of high blood pressure . mean arterial pressure ( map )   was calculated using the equation ( diastolic pressure + ( systolic pressure  diastolic pressure/3 ) ) , expressed in mmhg . weight was assessed using a digital scale ( tanita , tbf-310 gs body composition analyzer , tokyo , japan ) , while height was obtained with a calibrated rod , with the patients shoeless and wearing light clothing . wc was measured using calibrated measuring tape in accordance to the anatomical landmarks proposed by the usa national institutes of health protocol . fasting levels of glucose , cholesterol , triglycerides ( tag ) , hdl - c , and hs - crp were determined using an automatized computer analyzer ( human gesellschaft fr biochemica und diagnostica mbh ) . when triacylglycerides were over 400  mg / dl measurement was done using lipoprotein electrophoresis and optical densitometry ( biorad gs-800 densitometer , usa ) . insulin was determined using an ultrasensitive elisa method ( drg instruments gmbh , germany , international drg division , inc ) . this was assessed by the homeostasis model assessment ( homa2-ir ) calculator , which is available at http://www.dtu.ox.ac.uk/homacalculator/index.php from the oxford centre for diabetes , endocrinology and metabolism . using roc curve construction technique , our research team determined that the optimal cutpoint for homa2-ir for our population is 2.00 . database construction and cluster analysis were done using the statistical package for the social sciences ( spss ) v19 for windows ( ibm inc . , chicago , il ) , while the roc curves were constructed using the r project for statistical computing , available at http://www.r - project.org/. normal distribution of continuous variables was assessed using geary 's test ; for normally distributed variables , the results were expressed as arithmetic mean  sd ( standard deviation ) . the differences between arithmetic means were assessed using student 's t - test ( when two groups were compared ) or one - way anova ( when three or more groups were compared ) . previously to the two - step cluster analysis , all individuals were classified according to bmi in normal weight , overweight , and obese . the obese groups were primarily evaluated as a group ( obese , bmi  30  kg / m ) and according to who classification ( class i , class ii , and class iii ) ; since the results showed similar behavior between them , we decided to use the classification of obesity because it allowed us to evaluate the subjects more clearly . each bmi category was submitted independently to the cluster analysis , categorizing the subjects as metabolically healthy or sick ; see figure 1 . the metabolic variables evaluated as possible metabolic predictors based on their physiological function and biological plausibility were map , tag , total cholesterol , hdl - c , homa2-ir , homa2-cell , homa2-s , fasting blood glucose , non - hdl - c cholesterol , tag / hdl - c index , and hs - crp ; wc was excluded because it was the assessed dependent variable . the predictive strength of these variables was analyzed in accordance to cluster ability and quality , ranging from 0.0 to 1.0 . the best metabolic predictive variables selected were ( a ) homa2-ir and homa2-cell for normal weight women ; ( b ) homa2-ir , homa2-cell and tag for normal weight men ; ( c ) homa2-ir and homa2-cell for overweight women ; ( d ) homa2-ir , homa2-cell , and tag for overweight men ; and ( e ) homa2-ir for male and female obese patients ( table 1 ) . the two - step cluster analysis for spss was conducted in two phases : during the first step ( called  precluster  ) , the subjects are divided into several small subclusters . then , the obtained subclusters are grouped into a preferred number of clusters ; if the desired number of clusters is unknown , the spss two - step cluster component will find the proper number of clusters automatically . once the program analyzed the subclusters and the characteristics of each bmi category ( as described previously ) , the subjects were categorized in 6 phenotypes : hnw , monw , healthy and metabolically disturbed overweight , mdo , and mho . to evaluate the quality of the resulting clusters , the cohesion , separation , and silhouette coefficient were calculated [ 2325 ] . the silhouette coefficient   encompasses the ideas of cohesion ( the closeness of related objects in a cluster ) and separation ( the distance between objects in a cluster ) , describing the average distances between variables within a cluster and between other clusters , the highest silhouette results being between 0.5 and 1 [ 23 , 26 ] . the clusters with high cohesion are preferred because it is a guarantee of good quality clustering , demonstrated by high silhouette values and truly clustered variables [ 2326 ] . cluster validation aims to evaluate the differences within a cluster in order to confirm clustering selection to estimate the accuracy of a prediction model . this method requires the division of the data into two groups : one to train ( training dataset ) and the other to validate ( testing dataset ) [ 27 , 28 ] . the process requires doing several rounds of partitioning and cross - validation , where all the analyses are performed on the training set and then validating such analyses in the testing set [ 27 , 28 ] , and agreement was assessed by cohen 's kappa coefficient . the receiving operating characteristic ( roc ) curves were used to analyze the predictive validity and to determine optimal cut - off values for wc following a series of exclusion steps ( figure 2 ) . several indexes were calculated to assess the optimal cut - off point on the curve , such as the youden index , the distance of the point closest to ( 0.1 ) on the roc curve and positive likelihood ratio were calculated . an overall 1,902 subjects were studied , out of which 52.15% were women and 47.84% were men . age arithmetic mean for all participants was 38.70  15.06 years ( ic 95% , 38.0239.08 ) , 37.17  14.54 years for men ( ic 95% , 36.8538.65 ) and 40.11  15.29 years for women ( ic 95% , 39.1541.06 ) . distribution of the population according to age groups , ethnic groups , bmi , and ms diagnosis is shown in table 2 . for anthropometric parameters , biochemical , and blood pressure results see table 3 . using all the information obtained from the clusters , six phenotypes were generated : hnw ( 28.29% ) , monw ( 3.36% ) , healthy overweight ( 28.08% ) , metabolically disturbed overweight ( 7.47% ) , mho ( 11.20% ) , and mdo ( 21.60% ) ( table 5 ) ; note that monw and mho subjects represent 14.56% of the total sample . cluster quality was assessed with the silhouette coefficient , which rendered > 0.5 for every cluster , meaning that all clusters were classified as good models . next , cross - validation was performed , dividing the subjects in two groups : s1 and s2 . the s1 group was used as the training set , where centroid - based clustering was calculated using the steps shown in figure 1 . the s2 group was used as the validating set ( s2 ) , where clusters were obtained using two methods : ( a ) normal clustering process ( s2-clusters ) and ( b ) clustering based on centroids and distances obtained from s1 ( s2 clusters according to s1 ) . all the resulting s2-derived clusters were compared using cohen 's kappa , resulting in 0.902 ; p < 0,00001 ( table 4 ) . we sought to find an appropriate cut - off point for this population sample , applying the 6 phenotypes previously described in a stepwise manner . in figure 3 , roc curves for men and women are shown . in figure 3(a ) , the selected cut - off point for women was 91.25  cm , with an auc 0.768 , sensitivity of 73.3% , and a specificity of 68.5% ( table 7 ) . in the next panel , figure 3(b ) , the chosen cut - off point for men was 98.15  cm , with an auc of 0.786 , 74.8% sensitivity , and 69.7% specificity . derived from the atypical phenotypes , monw and mho . in figure 4(a ) , the women 's roc curve is depicted , with a selected cut - off point of 91.50  cm , showing an auc of 0.890 , 80.1% sensitivity , and 79.3% specificity . in the following panel , figure 4(b ) , the selected cut - off point for men was 98.15  cm , with an auc of 0.919 , sensitivity of 83.8% , and a specificity of 82.3% ( table 7 ) . the final roc curves were built without the overweight groups , leaving only the hnw and the mdo . in figure 5(a ) , the women 's roc curve is shown , with a chosen cut - off point of 91.5  cm , characterized by an auc of 0.982 , sensitivity of 93.4% , and a specificity of 93.7% . in figure 5(b ) , the men 's cut - off point was 98.15  cm , with an auc of 0.998 , sensitivity of 96% , and a specificity of 99.5% ; see table 7 . finally , table 8 shows the metabolic variables of the subjects categorized with the obtained wc cut - off points from this investigation , resulting in significant differences between obese and nonobese subjects in every variable , except in homa-2cell in the women 's group . it is imperative to determine accurate wc cut - off values in order to diagnose abdominal obesity , given the progressive and fast rise in the worldwide prevalence of this disease . this growing epidemic has been a driving force for the development of improved diagnostic tests to aid physicians in their daily practice to diagnose abdominal obesity associated with metabolic disorders . the search for ethnic - specific values for anthropometric measures requires the application of several techniques , roc curves being one of the tools available in order to ascertain an appropriate cut - off point . roc curves approach to determine suitable cut - off points for wc has been extensively used [ 911 ] , especially in populations that are not properly classified in the latest ms criteria by the idf / nhlbi / aha-2009 due to lack of sufficient population - specific data for the wc variable . as opposed to more widespread methodology in these studies , the involvement of data mining techniques ( cluster analysis ) enhances the selection of healthy and sick subjects for the construction of roc curves because it does not use predetermined variables nor arbitrary cut - off points to decide ; instead it allows the program to group the individuals according to their biological characteristics and spontaneous tendencies . this improvement in subject classification guarantees cutoff points with superior sensitivity and specificity , which is the ultimate goal in surveys such as ours . several studies have suggested that the wc cut - off proposed by the idf / nhlbi / aha-2009 consensus seemed to be invalid for certain ethnicities , particularly the hispanic groups in latin america . aschner et al .   published their wc cut - off points based on roc curves using visceral fat area ( 100  cm ) as the independent variable , with resulting cut - off values of 94  cm for men ( 89.9% sensitivity and 80.2% specificity ) and 9092  cm for women ( 78.9%72.9% sensitivity and 67.6%74.5% specificity ) . however , aschner 's research conveys the use of visceral fat to find an optimal cut - off value of wc which detects subjects at risk of abdominal obesity . a cut - off point of 100  cm was calculated for japanese population , using metabolic criteria cutoffs that are now considered outdated ( e.g. , fasting glucose > 110  mg / dl ) . moreover , latin - americans are phenotypically and genetically different from asians , which hinders the possibility of properly extrapolating results from their group onto ours . despite these shortcomings , this currently , latin america also needs cut - off values concerning visceral fat , especially when ethnic minority groups are included , such as the amerindians and afro - descendants . two - step cluster analysis approach enhances sorting of the subjects , allowing for better grouping and evaluation according to biochemical and anthropometric coalescent variables , eliminating the bias observed in predetermined variables and cut - off points . on this reasoning , 6 phenotypes were constructed : healthy normal - weight , monw , healthy and metabolically disturbed overweight , mho , and metabolically disturbed obese . each group has diverse cardiometabolic profiles which have been widely described in the last decade [ 58 , 13 ] . evidently , the monw and mho are exceptions to rules that have been described traditionally , where first glance examination of an obese or lean patient would automatically classify them as sick or healthy , respectively . using the selected parameters according to bmi , a proper classification is possible , being demonstrated by the enhancement of sensitivity , specificity , and auc for abdominal circumference in these groups . roc curve programs allow the determination of true positive and negative cases , by providing cut - off points and their corresponding auc , sensitivity , and specificity ; nevertheless , this feature depends on an appropriate sorting of the sample and its accuracy is confirmed with the comparison of curves before and after selection . eliminating noise during the filtering of information is of paramount importance , since it behaves as phantom signals which derail the evaluation towards inaccurate values . exclusion of the monw and mho categories impedes the use of false data to determine a cut - off point , rendering enough sensitivity and specificity to identify subjects at risk . it is imperative that physicians embrace the advantages offered by both techniques in order to be able to determine valid cutoff points in ethnic - based studies concerning metabolic variables , which are categorized as biological and thus display a continuous behavior . the definition of overweight lies between normalcy and obesity , between 25.00 and 29.99  kg / m . this allocation confers this definition a  transition  quality which is based on the possibility of reducing weight and achieving normal weight or augmenting weight reaching obesity levels [ 35 , 36 ] . moreover , this also suggests that weight is a continuous biological factor , and the arbitrary classification of overweight is a transition phase in the natural history of obesity . therefore , since overweight subjects and considered  in transition  were removed them from the final wc roc curve construction . it is necessary to emphasize three facts : wc alone can not recognize monw or mho subjects , anthropometry is insufficient to determine healthiness , and relying on the information obtained in other variables is needed for the filtering process . these facts open a new window of opportunity to investigate the establishment of new strategies that can help identify peculiar phenotypes , such as the use of somatotypes constructed with local anthropometric and biochemical data , facilitating the identification of mown and mho subjects . the chosen cut - off point for the women 's group was 91.25  cm , very similar to that reported by herrera et al . , suggesting that the females in the sample tend to have higher wc values than the ones set previously both by atpiii   ( < 88  cm ) and idf / nhlbi / aha-2009 ( < 80  cm ) . this finding is probably explained by differences regarding height , fat distribution , and genetic background . it is noteworthy to point out that , even after the groups were filtered extracting mown , mho , and overweight individuals , the wc cut off point always remained the same , but sensitivity and specificity improved significantly , proving that this approach offers a better way to scrutinize metabolically heterogeneous groups . women appear to boast higher wc cut - offs , perhaps due to displaying a central fat distribution despite having femoral - gluteal fat distribution tendencies . regarding males , a similar trend was observed , this time with a selected cut - off of 98.15  cm which is between the cutoff points proposed in idf / nhlbi / aha-2009 ( < 90  cm ) and atpiii ( < 102  cm ) . we have previously published the prevalence of obesity in the city of maracaibo , reporting that the overall prevalence of abdominal obesity using idf / nhlbi / aha-2009 criteria   was 74.2% , while using the atpiii criteria   rendered a prevalence of 51.7% . using the cut - off points proposed in this research , the overall abdominal obesity prevalence using the complete sample of mmsps ( n = 2,230 ) is 35.6% ( n = 794 ) . thus , the new wc cut - off point reduces the alarming 74.2% obtained with the harmonizing criteria and offers better information to design strategies for primary and secondary prevention . first , the absence of imaging study confirmation such as visceral fat measurement ; this branch of the mmsps study is currently underway . second , we used bmi as a method of diagnosis and categorization instead of other obesity diagnostic tools like dexa for body composition   due to lack of resources for such endeavor . it has been reported that bmi has limitations in regard to adiposity diagnosis , especially in intermediate ranges of bmi . however , bmi cutoff point of 30  kg / m should be easily dismissed , since it has been associated with high specificity and positive predictive value for diagnosing obesity in both sexes   and strong association with other entities such as arterial hypertension , diabetes mellitus , stroke , premature death , and several types of cancer . in conclusion , we propose wc cut - off points of < 91.00  cm for women and < 98.00  cm for men , both providing an excellent sensitivity and specificity when concerning the diagnosis of abdominal obesity . the need for ethnic - specific wc cut - off points is paramount , especially when there is an association between wc and mortality prediction [ 46 , 47 ] . the application of statistical methods that allow the filtering and gathering of accurate information , like cluster analysis and roc curve constructs , will warrantee production of veracious cut - off points that can be applied in large prospective trials .
introduction . 
 the purpose of this study was to analyze the influence of metabolic phenotypes during the construction of roc curves for waist circumference ( wc ) cutpoint selection . 
 materials and methods . a total of 1,902 subjects of both genders were selected from the maracaibo city metabolic syndrome prevalence study database . two - step cluster analysis ( tsca ) 
 was applied to select metabolically healthy and sick men and women . 
 roc curves were constructed to determine wc cutoff points by gender . results . through tsca 
 , metabolic phenotype predictive variables were selected : homa2-ir and homa2-cell for women and homa2-ir , homa2-cell , and tag for men . 
 subjects were classified as healthy normal weight , metabolically obese normal weight , healthy and metabolically disturbed overweight , and healthy and metabolically disturbed obese . 
 final wc cutpoints were 91.50  cm for women ( 93.4% sensitivity , 93.7% specificity ) and 98.15  cm for men ( 96% sensitivity , 99.5% specificity ) . 
 conclusions . 
 tsca in the selection of the groups used in roc curves construction proved to be an important tool , aiding in the detection of mown and mho which can not be identified with wc alone . 
 the resulting wc cutpoints were < 91.00  cm for women and < 98.00  cm for men . 
 furthermore , anthropometry is insufficient to determine healthiness , and , biochemical analysis is needed to properly filter subjects during classification .