Table 3 Within-day level: model estimates of the multilevel models with Level-1 predictors mean SG and glucose variability (CV) and dependent variable working memory.

Effect	Estimate	SE	95% CI
			LL	UL
Model 1 − mean SG
Fixed effects
Intercept	1.76	0.12	1.53	1.98
Mean SG^a	0.00	0.00	−0.00	0.00
Trial Number	0.03	0.01	0.01	0.04
Concentration^b	0.01	0.00	0.01	0.02
HOMA-IR^c	−0.20	0.10	−0.40	−0.00
Age	−0.02	0.01	−0.03	−0.01
Sex	0.15	0.15	−0.14	0.45
Education	0.04	0.03	−0.01	0.10
Random effects
SD (Intercept)	0.72	0.07	0.60	0.86
SD (Mean SG^a)	0.00	0.00	0.00	0.01
SD (Trial Number)	0.02	0.01	0.00	0.05
SD (Concentration^b)	0.01	0.00	0.00	0.01
Model 2 − Glucose variability (CV)
Fixed effects
Intercept	1.73	0.13	1.48	1.98
Glucose variability^d	−0.00	0.00	−0.01	0.01
Trial Number	0.03	0.01	0.01	0.04
Concentration^b	0.01	0.00	0.01	0.02
HOMA-IR^c	−0.19	0.10	−0.39	0.02
Age	−0.02	0.01	−0.03	−0.01
Sex	0.17	0.15	−0.13	0.47
Education	0.05	0.03	− 0.01	0.10
Random effects
SD (Intercept)	0.75	0.08	0.62	0.92
SD (Glucose variability^d)	0.01	0.01	0.00	0.03
SD (Trial Number)	0.02	0.01	0.00	0.04
SD (Concentration^b)	0.01	0.00	0.00	0.01

Estimates of the two multilevel models are presented as log-odds. The inverse logit function (e.g., R function plogis) was used to convert the log-odds to proportion of correct responses (WM performance) for data interpretation.
CV coefficient of variation, CI confidence interval, HOMA-IR homeostasis model assessment of insulin resistance, LL lower limit, SE standard error, SG sensor glucose, UL upper limit. Sex (0 = male, 1 = female).
N = 103.
^aMean SG was log-transformed to correct right-skewed data.
^bSelf-reported item.
^cHOMA-IR was log transformed to correct right-skewed data.
^dGlucose variability is measured by the coefficient of variation (CV) which was log-transformed to correct right-skewed data.

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