319 Maternal age-specific drivers of severe maternal morbidity

Abstract

Compare the contribution of risk factors to risk of severe maternal morbidity (SMM) between maternal age groups and estimate their population attributable risks. Retrospective population-based cohort study of all US live births using birth certificate records, 2012-2016. Demographic, medical, and pregnancy factors were compared between 5 strata of maternal age (<16, 16-17, 18-34, 35-39 and ≥40 years). The primary outcome was composite SMM, defined as maternal ICU admission, blood transfusion, unplanned hysterectomy, or ruptured uterus. Multivariate logistic regression estimated the relative influence of risk factors associated with SMM among maternal age categories. Population-attributable fraction (PAF) calculations assessed the contribution of individual risk factors to overall SMM. Of 19,473,910 births in the U.S. from 2012-2016, 76,919 (39 cases per 10,000 delivery hospitalizations) experienced SMM. The highest rates of SMM were observed at the extremes of maternal age, 52 per 10,000 at <16 years (RR 1.40, 95%CI [1.25-1.57]) and 69 per 10,000 (RR 1.80, CI [1.75-1.86]) for ≥40 years. In all age groups, no prenatal care and Cesarean delivery were associated with increased adjusted relative risk of SMM. In adolescents, preeclampsia was the factor associated with highest SMM risk, while preterm birth had the strongest influence among older mothers. Risk factors with greatest PAF were Medicaid insurance (6.8%), preeclampsia (8.9%), preterm delivery (18.1%), and Cesarean delivery (36.8%). Based on these estimates if births only occurred in mothers between the ages of 18-34, the SMM rate could be reduced to 35 per 10,000 live births. A larger reduction would occur with elimination of preterm birth and cesarean delivery, to reductions of SMM in the US to 32 and 24 cases per 10,000 live births, respectively. Both adolescent and advanced-age pregnancies have increased risk of SMM. However, there are age-specific differences in drivers of SMM. This information may allow for better identification of those at a higher risk of SMM and ultimately aid preventive efforts.View Large Image Figure ViewerDownload Hi-res image Download (PPT)