Background: Although maternal deaths are among the most tragic events related to pregnancy, they are uncommon in the US and, therefore, inadequate indicators of a woman's pregnancy-related health. Maternal morbidity has become a more useful measure for surveillance and research. Traditional attempts to monitor maternal morbidity have used hospital discharge data, which include data only on complications that resulted in hospitalisation, underestimating the frequency and scope of complications.
Methods: To obtain a more accurate assessment of morbidity, we applied a validated computerised algorithm to identify pregnancies and pregnancy-related complications in a defined population enrolled in a health maintenance organisation in the south-eastern US. We examined the most common morbidities by pregnancy outcome and maternal characteristics.
Results: We identified 37 741 pregnancies; in half (50.7%), at least one complication occurred. The five most common were urinary tract infections, anaemia, mental health conditions, pelvic and perineal complications, and obstetrical infections. Complications were more likely in women with low socio-economic status (SES), and among non-Hispanic Black women compared with non-Hispanic White women. Multivariable models stratified by race/ethnicity indicated that in pregnancies among non-Hispanic White women, low SES had a modest effect on the odds of having preexisting medical conditions [adjusted odd ratio (AOR) 1.3 [95% confidence interval (CI) 1.2, 1.5]] or having any morbidity (AOR 1.3 [95% CI 1.2, 1.4]). Low SES had little effect on complications among non-Hispanic Black women.
Conclusion: Our findings suggest that comprehensive health insurance coverage may lessen the unfavourable impact of socio-economic disadvantage on the risk of maternal morbidity.