Objective: Pre-gestational diabetes increases the risks of adverse maternal and neonatal pregnancy outcomes such as preeclampsia, preterm delivery, neonatal macrosomia, and birth defects. These risks are further increased if the pregnancy was unplanned. This study aims to examine the prevalence, predictors, and consequences of unplanned pregnancy among women of reproductive age with pre-gestational diabetes in North Carolina.
Methods: Data will be obtained from the Carolina Data Warehouse for Health, a data repository of patient encounters obtained from the electronic medical records of the University of North Carolina Health Care System. Study sample will include female patients aged 15-44 years with ICD-10 codes for diabetes type 1 or type 2 (N=53,000) before the most recent ICD-10 code for pregnancy in the last 18 months. Using an electronic medical record search engine, eligible charts will be reviewed to identify the primary outcome (unplanned pregnancy), predictors (e.g. maternal age, race, education, income status, glycemic control, prior contraceptive use) and consequences (e.g. preterm delivery, neonatal macrosomia, birth defects). Data analyses will be conducted using Stata version 15. Multilevel logistic regression analyses will be used to examine the outcome, predictors, and consequences using appropriate statistical methods.
Results: Anticipated results include the estimated prevalence of unplanned pregnancy, predictors, and consequences of unplanned pregnancy, and the odd ratios estimating the effects of the predictors on the unplanned pregnancy.
Conclusion: Ensuring that women at risk of unplanned pregnancy receive appropriate preconception care, including contraceptives, will contribute towards improving maternal and neonatal health among women with pre-gestational diabetes in North Carolina.