TABLE 1.
Baseline characteristics among ACT1ON study participants included or excluded from the analytic sample (total n = 68)1
| Included (n = 45) | Excluded (n = 23) | P value | |
|---|---|---|---|
| Age, mean ± SD, y | 25.4 ± 3.3 | 25.6 ± 2.8 | 0.73 |
| Female gender, n (%) | 31 (68.9) | 18 (78.3) | 0.42 |
| Non-Hispanic White race and ethnicity,2n (%) | 34 (75.6) | 11 (47.8) | 0.02 |
| UNC site, n (%) | 27 (62.8) | 12 (48.0) | 0.23 |
| Diabetes duration, mean ± SD, y | 15.1 ± 6.4 | 11.8 ± 5.7 | 0.03 |
| Insulin pump use, n (%) | 25 (58.1) | 15 (60.0) | 0.88 |
| BMI, median (Q1, Q3) | 30.8 (28.2, 34.0) | 29.7 (27.1, 33.2) | 0.33 |
| HbA1c, mean ± SD, % | 7.8 ± 1.4 | 8.0 ± 1.3 | 0.52 |
| Body fat percentage, median (Q1, Q3) | 41.6 (34.7, 45.1) | 39.2 (32.6, 43.8) | 0.46 |
| Percentage lean mass, median (Q1, Q3) | 55.2 (52.3, 62.1) | 57.6 (54.0, 64.2) | 0.40 |
| Included (n = 39) 3 | Excluded (n = 19) 3 | ||
| Total fiber intake, grams | 12.9 (9.3, 22.1) | 14.2 (10.5, 19.3) | 0.76 |
| Included (n = 38) 3 | Excluded (n = 19) 3 | ||
| Time in range (70–180 mg/dL), mean ± SD, % | 52.6 ± 22.0 | 44.1 ± 20.5 | 0.16 |
| Time above range (>180 mg/dL), mean ± SD, % | 40.2 ± 25.2 | 50.4 ± 22.8 | 0.14 |
| Time below range (54–70 mg/dL), median (Q1, Q3), % | 3.7 (1.7, 7.4) | 3.3 (1.0, 5.5) | 0.39 |
Group differences in continuous variables were tested using independent t-tests for normally distributed variables or Mann–Whitney U (Wilcoxon rank sum test) for nonnormally distributed continuous variables. Group differences in categorical variables were tested using the χ2 test for independence or the Fisher exact test if any cell sizes were less than n = 5. Note: Body composition measures were only available pre-COVID-19 due to discontinuation of DXA after the transition to a virtual protocol during COVID-19. ACT1ON, Advancing Care for Type 1 Diabetes and Obesity Network; HbA1c, glycated hemoglobin; Q1, quartile 1; Q3, quartile 3; UNC, University of North Carolina at Chapel Hill.
Race and ethnicity were collapsed into non-Hispanic white and Other due to sample size limitations. To avoid the possibility of participant identification, we express frequencies with <3 individuals as “n <3” rather than disclosing the absolute number: of those included in the analytic sample, n = 4 (8.9%) identified as African American, n < 3 identified as Asian, n < 3 identified with >1 race; n = 36 (80.0%) identified as White; n = 6 (13.3%) identified as Hispanic or Latino. Of those excluded from the analytic sample, n <3 identified as African American, n <3 identified as Native Hawaiian/Other Pacific Islander, n <3 identified as Asian, n <3 identified as Other race, n = 4 (17.4%) identified with >1 race; n = 13 (56.5%) identified as White; n = 5 (21.7%) identified as Hispanic or Latino.
Six and 7 participants included in the analysis were missing data for diet and continuous glucose monitoring, respectively, at the baseline visit.