anthropometric measures are widely used as simple markers to identify subjects at risk of cardiovascular disease and diabetes . a high bmi reflects generalized overweight and obesity and is associated with cardiovascular morbidity and mortality . abdominal fat distribution is commonly measured as waist girth or waist / hip ratio , measures that have been shown to predict cardiovascular disease independent of bmi [ 2 , 3 ] . in fact , a recent large meta - analysis suggests that bmi is not a significant predictor of cardiovascular mortality except in patients with severe obesity . more recently ,  abdominal height  or sagittal abdominal diameter ( sad ) has shown to be strongly associated with glucose intolerance , cardiovascular risk [ 59 ] , and mortality [ 1013 ] , independently of other anthropometric measures . sad is also an excellent estimate of visceral fat [ 1416 ] implying that sad might be a particularly good marker of insulin resistance , which also has been demonstrated in men   and women . despite these promising data , the role of sad has been overlooked whereas waist girth has received more attention [ 5 , 1921 ] . we have previously reported that sad was a better predictor of cardiometabolic risk compared to waist girth and other conventional measures . now we thus need cutoffs for sad , data that needs to be derived from a large population - based sample comparing sad with other measures of abdominal obesity . it is necessary to identify cutoffs in order to use sad either in research as a screening tool or in the clinic to identify individuals with elevated cardiometabolic risk . hence , the aim of this study was to identify optimal cutoffs for sad to be used in future prospective studies and research . in a population - based sample of swedish subjects aged 60 we compared sad with other more conventional anthropometric measures . in 1997 to 1999 , every third man and woman ( n = 5460 in total , 2681 men and 2779 women ) living in stockholm county , sweden , born between 1937 and 1938 , was invited to participate in a health screening survey . of all invited , 4228 individuals agreed to participate ( 2036 men and 2192 women , 78% response rate ) , representing the general population of subjects aged 60 . in the current study we excluded subjects without complete data on all anthropometric , metabolic and cardiovascular variables , resulting in 4032 subjects ( 1936 men , and 2096 women ) that comprise the current study population . all subjects underwent a physical examination including anthropometry and blood biochemistry after an overnight fast . body weight was measured using an electronic scale to the nearest 0.1  kg , with the subjects wearing light clothing and no shoes . bmi was calculated as weight ( kg ) divided by height ( m ) squared . sad ( anteroposterior ) or  abdominal height  was measured after a normal expiration to nearest 0.1  cm in supine position with straight legs on a firm examination table , without clothes in the measurement area . at the level of iliac crest ( l4 - 5 ) intraobserver variation ( coefficient of variation ) for sad was 1.6% , and intrasubject variation was 2.7% . waist girth was measured according to the who in underwear in standing position after normal expiration , midway between the lower rib margin and the iliac crest and hip girth was measured at symphysis trochanter level . systolic and diastolic blood pressures were measured twice after 5 minutes rest in supine position , using a digital blood pressure monitor ( hem 711 , omrom health care ) and the mean of the two values was calculated . cholesterol and triglycerides in serum were analyzed by enzymatic methods ( bayer diagnostics , tarrytown , usa ) [ 25 , 26 ] . hdl - cholesterol in serum was measured enzymatically after isolation of ldl and vldl ( boehringer mannheim gmbh , germany ) and ldl - cholesterol was estimated using friedewald 's method . serum glucose was measured with an enzymatic colorimetric test ( bayer diagnostics , tarrytown , usa ) . serum insulin levels were determined using the elisa technique ( boeringer mannheim gmbh , diagnostica , germany ) . plasma fibrinogen was measured with a functional spectrophotometric test ( boehringer mannheim , germany ) . -glutamyltransferase in serum was determined using an enzymatic colorimetric test ( bayer diagnostics , tarrytown , usa ) . pearson 's correlation coefficients were used to investigate the associations between anthropometric and metabolic variables . an established cardiometabolic risk score ( reflecting metabolic aberrations related to the metabolic syndrome ) was calculated , and comprised serum triglycerides , hdl - cholesterol , fasting glucose , fasting insulin , and supine systolic and diastolic blood pressures . for all items except hdl - cholesterol the 20% lowest values were given the quintile value 1 and so on . hdl - cholesterol was given quintile numbers in the reverse order , so that the 20% with the lowest values were given the quintile value 5 , and so forth . the sum may span from 6 to 30 and a value above the 80th percentile within each sex was defined as an elevated cardiometabolic risk score . in addition to the cardiometabolic risk score , we also identified cutoffs by using the framingham risk score ( http://www.nhlbi.nih.gov/guidelines/cholesterol/risk_tbl.htm ) . we defined an elevated framingham risk score as the highest quintile per gender , thus we used a similar definition as for the cardiometabolic risk score to facilitate comparison . from the framingham point scores , total framingham risk was estimated as a 10-year risk ( % ) of having cardiovascular disease . for each anthropometric measure , a receiver operating characteristic ( roc ) curve was calculated for prediction of an elevated cardiometabolic risk score , within each sex . the c - statistic ( area under the roc curve ) and an optimal cutoff , calculated from the youden index   ( the maximal sum of sensitivity and specificity ) , the sensitivity and specificity ( with confidence intervals ) based on the optimal cutoff are also presented . confidence intervals for the c - statistic and significance tests for comparison of c - statistics from different anthropometric measures were calculated according to the method described by delong et al . . jmp and sas version 9 software packages were used for statistical analyses ( sas institute inc . , cary , nc , usa ) . the mean ( sd ) cardiometabolic risk score was 14 ( 5 ) for men and 10 ( 5 ) for women . baseline characteristics of subjects with data on all variables are presented as quintiles for men and women , respectively ( tables 1 and 2 ) . all anthropometric measures were significantly correlated with all individual risk factors except to ldl cholesterol for waist girth , whr , and bmi in men ( table 3 ) . sad was the only significant predictor of ldl cholesterol , although the correlation was weak ( table 3 ) .   among the men , 20.4% were at elevated cardiometabolic risk score , and among the women 22.4% these figures are in accordance with those reported for this population concerning prevalence of the metabolic syndrome . sad was more strongly correlated to most risk factors as compared with other anthropometric measures in men whereas in women sad was not consistently better than other anthropometric measures ( table 3 ) . sad showed the strongest correlation with the cardiometabolic risk score among men ; whereas it was not a better correlate than other anthropometric measures in women . the stronger correlation between sad and the cardiometabolic risk score was statistically significantly different compared with all other anthropometric measures in men ( all p < .5 ) , but was only significantly different from bmi in women ( table 3 ) . in men , sad showed the highest area under the roc curve which was statistically significant compared with the other measures except bmi ( p = .003 , p < .0001 ,   and p = .09 for comparison with waist girth , whr , and bmi , resp . ) , and in women sad showed together with waist girth the highest area under the roc curve ( p = .9 , p = .3 ,   and p < .001 for comparison between sad and waist girth , whr , and bmi , resp . ) the optimal ( 95% ci ) sad cutoff for an elevated calculated cardiometabolic risk score for men was 22.2 ( 21.6 to 22.8 ) and for women 20.1 ( 19.4 to 20.8 ) ( table 5 ) . the optimal cutoffs for waist girth , whr , and bmi are shown in table 5 . to further validate these results , we also assessed optimal cutoffs for sad using the more established framingham risk score . the present sad cutoff of 22  cm for men was unchanged if replacing the cardiometabolic risk score with framingham risk score . in women the cutoff was 21  cm if using the framingham risk score instead of the cardiometabolic risk score . the highest quintile of framingham risk score started at 14 risk points for men , and at 17 risk points for women which corresponded to a 2% and 5% 10-year risk of cardiovascular disease , respectively . in this population , a sad of 22  cm corresponded to 20% risk in men , and a sad of 21  cm corresponded to a 14% risk in women . the optimal cutoffs for identifying subjects with an elevated cardiometabolic risk score were ~22  cm in men and ~20  cm in women . this is the first study using roc curves to identify cutoffs for sad in a large population - based sample . based on a canadian population in 81 men and 70 women , a sad > 25  cm was suggested to be associated with multiple metabolic disorders . since the sample size of that study was small it may be unwise to compare that study with ours where the cutoffs where lower . notably , the present sad cutoff of 22  cm for men was unchanged if replacing the cardiometabolic risk score with the framingham risk score , a finding that strengthen the validity of this cutoff . in women the cutoff was however 1  cm higher if using the framingham risk score instead of the cardiometabolic risk score .   in men , sad was significantly more closely correlated with the cardiometabolic risk score versus all other anthropometric measures and also showed slightly stronger correlations with most individual risk factors . in women , sad was an equally good predictor for an elevated cardiometabolic risk score as waist girth . if one should use only one anthropometric measure , sad thus may be a good choice to capture elevated cardiometabolic risk . the stronger capacity of sad to predict cardiometabolic risk in men may be explained by the higher visceral fat content in men versus women at a given bmi . this is relevant since visceral adiposity may confer a higher cardiometabolic risk than other fat depots , although this has been debated . indeed , sad seems particularly good in capturing visceral fat ( which during the supine measurement does not  float out  sideways , as would more be the case for subcutaneous fat ) [ 15 , 35 ] . also , the cardiometabolic risk score was lower in women ( 10 versus   14 ) providing a higher number of men at risk , which could contribute to gender differences observed in this study .   in line with previous data on men , but also to some extent in women , sad was more closely related to hyperlipidemia   and cardiovascular risk [ 79 , 36 , 37 ] than bmi , waist girth , and whr . recent   data also showed that sad was the best correlate to hypertension [ 7 , 36 ] and plasminogen activating inhibitor-1 . furthermore , in the swedish obese subjects study the change in sad was most closely related to the change of metabolic disorders . we have also shown that sad was a significantly better predictor of insulin resistance than waist girth in men , even independently of bmi and waist girth . similarly , sad was the strongest predictor of insulin resistance and crp levels in healthy women . a recent study in elderly 389 men and 437 women ( aged 5683 years ) did however not find that sad was superior to waist with regard associations with components of the metabolic syndrome . the latter inconsistency might be due to older age groups studied , ethnic , sex , phenotype , or methodological differences . one possible explanation for a somewhat better predictive capacity of sad is the higher measurement reliability of sad compared with waist girth [ 23 , 40 ] . sad may also be the only measure with high reliability in both lean and obese subjects . again , sad may more closely reflect visceral adiposity [ 1416 , 41 ] and thereby better capture cardiometabolic risk . however , it should be noted that sad also is a valid measure of total abdominal fat .   it has been shown that a large waist is a useful tool to detect metabolic disorders [ 5 , 19 , 20 , 42 ] . these studies did however not compare the predictive capacity with sad . in one study sad and waist girth were equally good markers of various metabolic disorders . the present results in a large population do suggest that in men sad is more strongly associated with individual cardiometabolic risk factors . with regard to mortality , available studies indicate that sad is a strong predictor of mortality independently of bmi [ 1013 ] , especially in younger adults [ 11 , 13 ] . however , these studies did not include waist girth or the waist - hip ratio , and only one study included women which showed that sad was a stronger predictor of mortality than bmi also in women . it has sometimes been argued that waist girth is more practical to measure than sad . our results support the use of sad as a valuable screening tool in research since it is a simple , reliable , and cheap marker to identify men at elevated cardiometabolic risk . this is a cross - sectional study and further prospective analyses will be needed to verify sad as a predictor of mortality . in addition , the cardiometabolic risk score used have not been established as a determinant of cardiovascular events and mortality . it should however be noted that cutoffs for waist circumference used in current clinical guidelines worldwide are based on cross - sectional data as well . another relevant limitation is the arbitrary definition of an elevated cardiometabolic risk score , but similar results were obtained if the framingham risk score was used thus supporting the data . strengths of the study include the population - based , representative sample of men and women of the same age ( age 60 ) . for the latter reason confounding influences of age are avoided . on the other hand , caucasians comprised the majority of the population but several ethnicities were represented in this study ; that is ,   19% was of non - swedish origin   . notably , sad seems to be useful in various ethnic groups [ 13 , 44 ] and in a us population , sad ( measured in standing ) predicted coronary heart disease across racial groups   . the optimal cutoffs for sad were > 22  cm in men and > 20  cm in women . in line with the previous studies , sad was the best marker of an elevated cardiometabolic risk score in men , and at least as good as other anthropometric measures in women . thus , sad may be a good alternative to waist girth as a simple screening tool in research aiming at recruiting subjects at elevated cardiometabolic risk , especially men .
background . waist girth and bmi are commonly used as markers of cardiometabolic risk . accumulating data however suggest that sagittal abdominal diameter ( sad ) or  abdominal height  may be a better marker of intra - abdominal adiposity and cardiometabolic risk . 
 we aimed to identify cutoffs for sad using a cardiometabolic risk score . 
 design . a population - based cross - sectional study . methods . in 4032 subjects ( 1936 men and 2096 women ) at age 60 , 
 different anthropometric variables ( sad , bmi , waist girth , and waist - to - hip ratio ) were measured and cardiometabolic risk score calculated . 
 roc curves were used to assess cutoffs . results . among men sad showed the strongest correlations to the majority of the individual risk factors ; whereas in women sad was equal to that of waist girth . in the whole sample , 
 the area under the roc curve was highest for sad . 
 the optimal sad cutoff for an elevated cardiometabolic risk score in men was 22  cm ( 95%ci ; 21.6 to 22.8 ) and in women 
 20  cm ( 95%ci ; 19.4 to 20.8 ) . 
 these cutoffs were similar if the framingham risk score was used . 
 conclusions . these cutoffs may be used in research and screening to identify  metabolically obese  men who would benefit from lifestyle and pharmacological interventions . 
 these results need to be verified in younger age groups .