briefly , the study was conducted at four clinical centers . centers in oakland and los angeles ,
california , recruited non - hispanic whites and african americans from kaiser permanente , a nonprofit hmo .
two other centers in san antonio , texas , and san luis valley , colorado , recruited non - hispanic whites and hispanics from two ongoing population  based studies , the san antonio heart study and the san luis valley diabetes study .
a total of 1,625 individuals were enrolled ( 56% women ) between october 1992 and april 1994 .
a follow - up examination was performed 5 years after the baseline examination ( range 4.56.6 years ) .
the present report includes information on 826 ( 79.2% ) participants ( 332 non - hispanic whites , 206 african americans , and 288 hispanics ) after excluding 153 individuals who failed to return to the follow - up visit and 64 individuals with missing information on relevant variables .
baseline characteristics were similar in the participants included in this analysis and those who were excluded ( e.g. , age , ethnicity , sex , glucose tolerance status , bmi , waist circumference , and si [ all comparisons , p  0.2 ] ) except for air ( higher in eligible participants , p = 0.005 ) .
each examination required two visits , one week apart , of 4 h each . during the first visit
, a 75-g oral glucose tolerance test was administered to assess glucose tolerance status . during the second visit , insulin sensitivity and first - phase insulin secretion
first , an injection of regular insulin was used to ensure adequate plasma insulin levels for the accurate computation of insulin sensitivity across a broad range of glucose tolerance ( 20 ) .
second , the reduced sampling protocol ( 12 samples ) was used because of the large number of subjects .
si and sg were calculated using mathematical modeling methods ( minmod , version 3.0 , los angeles , california , courtesy of richard bergman , phd ) ( 21 ) .
air was calculated as the mean of 2- and 4-min insulin concentrations after glucose administration and di as the product of si and air .
plasma glucose and insulin concentrations were determined by the glucose oxidase and dextran - charcoal radioimmunoassay methods , respectively .
the 1999 world health organization criteria were used to define diabetes ( fasting glucose concentration 7.0 mmol / l , 2-h plasma glucose concentration 11.1
mmol / l , or treatment with hypoglycemic medications ) and igt ( 2-h plasma glucose level between 7.8 and < 11.1 mmol / l ) .
the analysis was carried out using the sas statistical software ( version 9.1 , sas institute , cary , nc ) .
one - way ancova or logistic regression analysis was used to compare the differences for continuous or dichotomous variables between groups , respectively .
linear regression analyses were used to examine the relation of sg to si , air , and di . in separate models
risk of future diabetes associated with si , air , di , and sg was assessed by logistic regression analysis .
odds ratios ( ors ) were expressed for binary traits or per sd increase for continuous traits .
demographic variables , family history of diabetes , measures of obesity , and plasma glucose concentrations were also included as covariates .
we assessed the impact of these covariates on the relation of di and sg to conversion to diabetes by including appropriate interaction terms in separate logistic regression models . in both linear and logistic regression models , log - transformed values of si , air , and di were used to improve discrimination and calibration of the models and to minimize the influence of extreme observations .
given that some individuals had si and di equal to zero , we used the natural logarithms of si + 1 and di + 1 as the transformation for si and di , respectively .
accuracy for the prediction of diabetes was determined by the area under the receiver operating characteristic curve ( auc ) .
the analysis was carried out using the sas statistical software ( version 9.1 , sas institute , cary , nc ) .
one - way ancova or logistic regression analysis was used to compare the differences for continuous or dichotomous variables between groups , respectively .
linear regression analyses were used to examine the relation of sg to si , air , and di . in separate models
risk of future diabetes associated with si , air , di , and sg was assessed by logistic regression analysis .
odds ratios ( ors ) were expressed for binary traits or per sd increase for continuous traits .
demographic variables , family history of diabetes , measures of obesity , and plasma glucose concentrations were also included as covariates .
we assessed the impact of these covariates on the relation of di and sg to conversion to diabetes by including appropriate interaction terms in separate logistic regression models . in both linear and logistic regression models , log - transformed values of si , air , and di were used to improve discrimination and calibration of the models and to minimize the influence of extreme observations .
given that some individuals had si and di equal to zero , we used the natural logarithms of si + 1 and di + 1 as the transformation for si and di , respectively .
accuracy for the prediction of diabetes was determined by the area under the receiver operating characteristic curve ( auc ) .
during the 5-year follow - up period , 128 ( 15.5% ) of 826 iras participants developed type 2 diabetes : 44 ( 7.9% ) of 557 participants with normal glucose tolerance at baseline , and 84 ( 31.2% ) of 269 participants with igt at baseline .
those participants converting to type 2 diabetes did not differ from nonconverters in terms of sex or ethnicity ( table 1 ) .
converters also had higher bmi and waist circumference , higher glucose and insulin levels , and lower si , air , di , and sg .
baseline characteristics by diabetes status at follow - up data are n ( % ) with 95% ci or means  sd .
results are adjusted for age , sex , race / ethnicity , and research center .
these variables were then back - transformed to their units for presentation in the table . in linear regression models ,
sg was directly related to si ( parameter estimate  1 sd , 0.11  0.02 , p < 0.001 ) , air ( parameter estimate  1 sd , 0.22  0.03 , p < 0.001 ) , and di ( parameter estimate  1 sd , 0.29  0.05 , p <
0.001 ) after accounting for the effects of age , sex , race / ethnicity , and research center .
there was no interaction effect of family history of diabetes on the relation of sg to si ( p = 0.534 ) , air ( p = 0.139 ) , and di ( p = 0.990 ) .
we used the auc to quantify the ability of di to predict conversion to diabetes relative to that of a model with both si and air ( found in the supplemental figure , available in an online appendix at http://care.diabetesjournals.org/cgi/content/full/dc10-0165/dc1 ) .
the auc of the model with si and air was similar to that of di ( 0.767 vs. 0.774 , p = 0.543 ) .
the 5-year incidence of diabetes by baseline tertiles of sg and each one of the other measures ( si , air , or di ) are presented in fig . 1 . five - year incidence of diabetes by tertiles of si , air , di , and sg .
results were adjusted for age , sex , race / ethnicity , research center , igt , family history of diabetes , and bmi . cut points for tertiles of si (  10 min  u  ml ) were 1.16 ( lower ) , 1.172.38 ( middle ) , and 2.39 ( upper ) .
corresponding cut points for tertiles of air ( u / ml ) were 37.5 , 38.075.0 , and 75.5 ; di (  10 min  u ml per u  ml ) 55.8 , 55.9120.0 , and 120.1 ; sg (  10 ml ) , 1.58 , 1.592.22 , and 2.23 .
sg predicted future development of diabetes after adjusting for age , sex , race / ethnicity , and research center ( or  1 sd , 0.50 [ 0.400.64 ] ) , as did di ( or  1 sd , 0.47 [ 0.400.56 ] ) . in a multivariate logistic regression model that included sg and di as independent variables
, the odds remained statistically significant for both sg ( or  1 sd , 0.61 [ 0.470.80 ] ) and di ( or  1 sd , 0.68 [ 0.540.85 ] ) ( table 2 ) .
age , sex , race / ethnicity , research center , family history of diabetes , fasting glucose , 2-h glucose , bmi , and waist circumference were also included as covariates . in a different model that included si , air , and sg , these three measures were all independent predictors of diabetes .
predictors of conversion to type 2 diabetes by multiple logistic regression analysis ors expressed for binary traits or per 1 sd unit change for continuous traits .
* results in model 1 adjusted also for race / ethnicity ( p = 0.494 ) and research center ( p = 0.006 ) ; log - transformed variables ; results in model 2 also adjusted for race / ethnicity ( p = 0.446 ) and research center ( p = 0.006 ) . in separate logistic regression models , we examined the impact of age , sex , race / ethnicity , research center , bmi , glucose tolerance status , family history of diabetes on the relationship between sg ( or di ) , and incident diabetes . none of these variables had a significant impact on the relation of sg and di to conversion to diabetes ( p  0.16 for all potential interactions ) except for age on the relationship between di and conversion to diabetes ( p = 0.038 ) .
the strength of the relation of di and sg to conversion to diabetes differed little between categories of age , sex , race / ethnicity , glucose tolerance status , bmi , and family history of diabetes ( fig .
f ) . additionally , the interaction term di  sg was not statistically significant ( p  0.71 ) .
di and sg were independent risk factors across different degrees of insulin sensitivity and insulin secretion ( fig .
risk of developing diabetes associated with di and sg by ethnicity , sex , glucose tolerance status , bmi and age categories , family history of diabetes , and tertiles of si and air .
age , sex , race / ethnicity , research center , bmi , igt , family history of diabetes , di , and sg were all included as independent variables in all eight models .
log - transformed values of di were used to improve discrimination and calibration of the models and to minimize the influence of extreme observations .
in cross - sectional analyses , sg is directly related to insulin sensitivity and first - phase insulin secretion . further in prospective analyses , sg and di were found to be independent predictors of conversion to diabetes similarly across race / ethnic groups , varying states of glucose tolerance , family history of diabetes , and obesity .
the predictive power of di is comparable to that of the combination of si and air . expanding a previous analysis by martin et al .
( 4 ) , goldfine et al . ( 5 ) examined the risk of conversion to diabetes associated with directly measured di in 155 offspring of parents who both had type 2 diabetes and 181 subjects with normal glucose tolerance and without family history of diabetes .
concluded that di and particularly insulin resistance was not sufficient for the development of diabetes in individuals without family history of the disease .
these individuals , however , had a very low incidence of diabetes ( 6 cases during a mean follow - up period of 25 years ) . in another study of pima indians , incident diabetes
was predicted by di independent of the effect of demographic variables and percentage of body fat ( 7 ) .
our results validate previous studies and extend the findings to men and women , all three race / ethnic groups , and varying states of glucose tolerance , family history of diabetes , and adiposity .
ferrannini and mari ( 10 ) have questioned the hyperbolic paradigm of the relationship between insulin sensitivity and first - phase insulin secretion . in a recent cross - sectional study
( 22 ) , however , these authors confirmed the paradigm while arguing against the compensation for insulin resistance as the sole mechanism responsible for hyperglycemia .
they also indicated that an intrinsic -cell function defect is the most important mechanism for hyperglycemia . in agreement with the hyperbolic paradigm ,
our results suggest that the predictive power of di is comparable with that of its components .
di , however , is not the only independent risk factor for the development of diabetes .
since fasting and 2-h plasma glucose values remain strong predictors of diabetes , we can not disregard other determinants of glucose homeostasis , such as additional aspects of secretory response to glucose stimulation ( e.g. , -cell glucose sensitivity and potentiation ) , from the disease process .
lopez et al . ( 23 ) recently reported that sg is related to si in individuals with family history of diabetes but not in those without such a history .
our results , however , indicate that family history of diabetes has little influence on the relationship between sg and si .
sg is independent of the dynamic insulin response but is influenced by the basal insulin level ( 13 ) .
in other words , sg is influenced by the effect of insulin on glucose uptake by insulin - dependent tissues ( basal insulin 
similarly , in longitudinal studies by martin et al . ( 4 ) and goldfine et al . ( 5 ) , sg predicted conversion to diabetes independent of di but only among offspring of type 2 diabetic parents .
individuals without family history of diabetes had a very low risk of future diabetes and neither sg nor di predicted diabetes .
( 18 ) examined the risk of progression to igt or diabetes associated with sg in 81 first - degree relatives of african americans with type 2 diabetes .
sg as well as directly measured insulin resistance and secretion were independent predictors of worsening glucose tolerance status .
nevertheless , none of these studies adjusted their results for glucose tolerance status and adiposity . in the iras
, sg is an independent risk factor for future diabetes in individuals with family history of diabetes and similar results are demonstrated in all other categories regardless of age , sex , race / ethnicity , glucose tolerance , and adiposity .
experiments in canines have suggested that this relationship is an artifact of the minimal model method ( 24 ) . in mice
, however , the effect of first - phase insulin secretion ( in physiological conditions ) on sg is minimal ( 20 ) .
furthermore , fsigtt with the minimal model analysis may overestimate sg . in human subjects ,
the difference between minimal model- and clamp - derived sg appears to be related to the assumption of mono - compartmental distribution of glucose by the minimal model analysis ; however , both measures are highly correlated ( 25 ) .
therefore , minimal model - derived sg is considered an adequate measure of nonsteady - state glucose kinetics and a dependable index . in conclusion ,
the predictive discrimination of di for future diabetes is comparable with that of the combination of si and air ; therefore , our results support the validity of the hyperbolic paradigm .
di and sg are important , independent determinants of diabetes in different ethnic groups and varying states of glucose tolerance , family history of diabetes , and obesity .
prospective studies are needed to examine the natural course of sg relative to that of insulin resistance and -cell function .
 objectivedisposition index ( di ) and glucose effectiveness ( sg ) are risk factors for diabetes . 
 however , the effect of di and sg on future diabetes has not been examined in large epidemiological studies using direct measures.research design and methodsinsulin sensitivity index ( si ) , acute insulin response ( air ) , and sg were measured in 826 participants ( aged 4069 years ) in the insulin resistance atherosclerosis study ( iras ) by the frequently sampled intravenous glucose tolerance test . 
 di was expressed as si  air . at the 5-year follow - up examination , 128 individuals ( 15.5% ) 
 had developed diabetes.resultsthe area under the receiver operating characteristic curve of a model with si and air was similar to that of di ( 0.767 vs. 0.774 , p = 0.543 ) . in a multivariate logistic regression model that included both di and sg , conversion to diabetes was predicted by both sg ( odds ratio  1 sd , 0.61 [ 0.470.80 ] ) and di ( 0.68 [ 0.540.85 ] ) after adjusting for demographic variables , fasting and 2-h glucose concentrations , family history of diabetes , and measures of obesity . 
 age , sex , race / ethnicity , glucose tolerance status , obesity , and family history of diabetes did not have a significant modifying impact on the relation of sg and di to incident diabetes.conclusionsthe predictive power of di is comparable to that of its components , si and air . 
 sg and di independently predict conversion to diabetes similarly across race / ethnic groups , varying states of glucose tolerance , family history of diabetes , and obesity . 
RESEARCH DESIGN AND METHODS
Statistical analyses
RESULTS
CONCLUSIONS
Supplementary Material