Additional file 1 of Random capillary glucose levels throughout pregnancy, obstetric and neonatal outcomes, and long-term neurodevelopmental conditions in children: a group-based trajectory analysis
Creators: name: Chen, Shuyun
name: Persson, Margareta
name: Wang, Rui
name: Dalman, Christina
name: Lee, Brian K.
name: Karlsson, Håkan
name: Gardner, Renee M.
Publisher: name: figshare
Year: 2023
Subjects: subject: Medicine
subject: Cell Biology
subject: Chemical Sciences not elsewhere classified
subject: Sociology
subject: FOS: Sociology
subject: Immunology
subject: FOS: Clinical medicine
subject: Mathematical Sciences not elsewhere classified

description: Additional file 1: Supplementary Methods &amp; Table S1-S14 &amp; Figure S1-S7. Supplementary Methods-group-based trajectory modeling. The procedure involved in group-based trajectory modeling. Table S1. A description of random capillary glucose measurements. A description of random capillary glucose measurements during the entire pregnancy. Table S2. RCG values. Testing hour-standardized RCG z-scores and original RCG valuesmeasured at different times throughout the day. Table S3. Diagnostic codes. Diagnostic codes and register databases used to ascertain diagnoses within the Stockholm Youth Cohort. Table S4. Details of the selected group-based trajectory models. The details of the three best modelsfor each group-based trajectory model with different numbers of groups. Table S5. Model adequacy for selected models. The model adequacy of the 5-group and the 6-group model. Table S6. Characteristics of offspring born to mothers with or without missing RCG level data. Characteristics of offspring whose mothers had no missing values in random capillary glucose level, with 1missing value, or with more than 1 missing values in different time intervalsduring pregnancy. Table S7. Characteristics of offspring whose mothers have or do not have missing RCG level values within each time frame. Characteristics of offspring whose mothers had missing values in random capillary glucose levels during ≤20, &gt;20-28, &gt;28-34, and &gt;34 wkGA throughout pregnancy. Table S8. Characteristics of the study sample. The Characteristics of the final study sample. Table S9. The parameter estimation. The parameter estimation of the final trajectory model. Table S10. The variance and covariance matrix. The variance and covariance matrix of the final trajectory model. Table S11. The misclassification error matrix. The misclassification error matrix of the final trajectory model. Table S12. Statistics for model adequacy. Statistics for the adequacy of the final trajectory model, considering scenarios where missing values were replaced with either the smallest or largest RCG levels within each time frame, or where instances with missing values were excluded altogether. Table S13. Sensitivity analysis by excluding women with overweight/obesity. The sensitivity analysis of the association between trajectory groups and obstetric/neonatal outcomes and offspring NDCs outcomes by excluding women with overweight/obesity. Table S14. Sensitivity analysis by excluding gestational hypertensive diseases. Sensitivity analysis for the association between glucose trajectories and offspring NDCs by excluding gestational hypertensive diseases. Fig S1. Sample derivation. A description of sample derivation. Fig S2. A depiction of RCG levels measured at different times over a day. Median, 25th and 75th percentile of random capillary glucose levelsmeasured at different times from 07:00 to &lt;19:00 throughout pregnancy. Fig S3. The distribution of average RCG z-scores throughout pregnancy. Histograms illustrating the distribution of RCG z-scores in general, as well as during each time frame throughout pregnancy. Fig S4. Overlapping and mutually exclusive NDC outcomes. A description of NDC outcomes, accounting for both instances of overlap and non-overlap in the final study sample. Fig S5. The BIC values for each model. A depiction of BIC values for each trajectory model consisting of 1-6 groups and featuring polynomials ranging from 1 to 3. Fig S6. The best-fitting 5-group and the best-fitting 6-group models. A depiction of the best-fitting 5-groupand the best-fitting 6-group models. Fig S7. RCG z-score trajectory groups in the sensitivity analyses. RCG z-score trajectory groups after excluding those with RCG missing in any time intervals, replacing missing values with the smallest, and largest values during each time interval in pregnancy.