Table 3.

Estimated Effects with 95% Confidence Interval of Three Meals on Peak Continuous Glucose Monitoring, Area Under the Curve, and Time to Peak Using Linear Mixed Effects Model

Model parameters	Dependent variable
	Peak glucose (CGM), mg/dL	Area under the curve (5 h), mg/dL × min	Time to peak, min
β1	85.8	15465.9	116.5
	(38.6 to 133.4)	(7,264.5 to 23,703.4)	(77.3 to 155.7)
	P = 0.001	P < 0.001	P < 0.001
β2	−32.6	−6950.1	−24.5
	(−48.4 to −17.2)	(−10,324.7 to −3,698.6)	(−43.8 to −5.3)
	P < 0.001	P < 0.001	P = 0.02
β3	−43.2	−9813.3	−39.6
	(−58.7 to −27.7)	(−13,113.4 to −6,563.7)	(−59.1 to −20.2)
	P < 0.001	P < 0.001	P < 0.001

Using white rice as the reference (β₁), the estimated difference with higher protein pasta (β₂) and with regular pasta (β₃) are reported. The difference between regular pasta and higher protein pasta is estimated as β₃ − β₂.

The coefficient means (95% CI) and P-values were estimated using a linear mixed effects model (LMEM), including meal type, glucose at baseline, glucose rate of change at baseline (averaged for 15 min before the meal start), glucose at the end of the session, meal insulin bolus, total daily insulin per subject weight, hypoglycemic treatment, and period as fixed effects and subjects as random effects: . The differences between meal effects were computed: A − C: β₂, B − C: β₃, and B − A: β₃ − β₂; where meal A (M_A) is higher protein pasta, meal B (M_B) is regular pasta, and meal C is white rice (reference meal).

CGM, continuous glucose monitoring.