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Fig 1.

Adequate Ackerman model fits.

Estimated effective periods for the model fits by panel: A—1.9 hours, B—3.3 hours, C—4.9 hours, D—8.4 hours.

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Fig 1 Expand

Fig 2.

Inadequate Ackerman model fits.

Reasons for inadequate fit classification by panel: A— on boundary of parameter space, B— on boundary of parameter space, C— on boundary of parameter space, D— and on boundary of parameter space and small , E—large underestimation in max glucose concentration, F—small .

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Fig 2 Expand

Fig 3.

Predicted and observed maximum glucose concentrations.

Black line corresponds to perfect prediction. Grey lines correspond to a 10% relative difference. Blue triangles outside of the grey lines indicate fits for which the predicted maximum glucose concentration occurred later than the end of the OGTT.

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Fig 3 Expand

Fig 4.

Functional PCA plots.

Panel A—Proportion variance explained by principal component. Panels B-D—Eigenfunctions’ deviations about the mean curve. The dashed red line shows a predicted OGTT curve for a 1 standard deviation increase in the respective fPC score with all other scores held at 0. The dotted blue line shows the same but for a 1 standard deviation decrease in the respective fPC score.

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Fig 4 Expand

Fig 5.

Ackerman parameters and fPC scores scatterplot matrix.

Scatterplots and correlations between estimated Ackerman model parameters and fPC scores for OGTT curves which the Ackerman model adequately fit.

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Fig 5 Expand

Fig 6.

Predicted OGTT curves from Ackerman and fPCA fits against observed data.

Observed data are shown as black points, the Ackerman model fit as a solid red line, and the fPCA fit as a blue dashed line. Panel A—Adequate Ackerman model fit. Predicted Ackerman and fPCA fit largely agree. Panel B—Abnormal OGTT curve which neither the Ackerman nor fPCA fit model closely. Panel C—Boundary Ackerman model fit (). Ackerman and fPCA fit model the observed data closely. Panel D—Extrapolated max Ackerman model fit. The Ackerman fit models the observed data more closely, but the fPCA fit appears more reasonable.

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Fig 6 Expand

Table 1.

Logistic regression of ackerman model inadequate fit on demographic variables.

Reference group: female sex, Black race, never-smoker.

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Table 1 Expand

Table 2.

Linear regression of estimated effective period on demographic variables.

Adequate fits only. Effective period measured in hours. Reference group: female sex, Black race, never-smoker.

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Table 2 Expand

Table 3.

Linear regressions of standardized principal components on demographic variables.

Reference group: female sex, Black race, never-smoker.

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Table 3 Expand

Table 4.

Linear regression of usual gait speed (m/s) on standardized estimated ackerman model parameters, model 1.

Adjusted for age, BMI, sex, race, and smoking history.

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Table 4 Expand

Table 5.

Linear regression of usual gait speed on standardized estimated ackerman model parameters, models 2–4.

Usual gait speed measured in m/s. Adjusted for age, BMI, sex, race, and smoking history.

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Table 5 Expand

Table 6.

Linear regression of usual gait speed on standardized functional principal component scores.

Usual gait speed measured in m/s. Adjusted for age, BMI, sex, race, and smoking history.

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Table 6 Expand

Table 7.

Cox proportional hazards model of death, standardized estimated ackerman parameters.

Adjusted for age, BMI, sex, race, and smoking history.

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Table 7 Expand

Table 8.

Cox proportional hazards model of death, standardized functional principal components.

Adjusted for age, BMI, sex, race, and smoking history.

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Table 8 Expand