Individual and County-Level Factors Associated with Severe Maternal Morbidity at Delivery: An Investigation of a Privately Insured Population in the United States, 2008 to 2018

Abstract

Objective

Few studies have explored the impact of county-level variables on severe maternal morbidity (SMM) subtypes. To address this gap, this study used a large commercial database to examine the associations between individual- and county-level factors and SMM.

Study Design

This retrospective cohort study used data from the Optum's deidentified Clinformatics Data Mart Database from 2008 to 2018. The primary outcomes of this study were any SMM, nontransfusion SMM, and nine specific SMM subtypes. Temporal trends in the prevalence of SMM and SMM subtypes were assessed using Joinpoint Regression. Multilevel logistic regression models were used to investigate the association of individual- and county-level factors with SMM.

Results

Between 2008 and 2018, there was not a significant change in the prevalence of any SMM (annual percent change [APC]: −0.9, 95% confidence interval [CI]: −2.2, 0.5). Significant increases in prevalence were identified for three SMM subtypes: other obstetric (OB) SMM (APC: 10.3, 95% CI: 0.1, 21.5) from 2013 to 2018, renal SMM (APC: 8.5, 95% CI: 5.5, 11.6) from 2008 to 2018, and sepsis (APC: 23.0, 95% CI: 6.5, 42.1) from 2014 to 2018. Multilevel logistic regression models revealed variability in individual and county risk factors across different SMM subtypes. Adolescent mothers (odds ratio [OR]: 2.10, 95% CI: 1.29, 3.40) and women in the 40 to 55 (OR: 1.67, 95% CI: 1.12, 2.51) age group were found to be at significant risk of other OB SMM and renal SMM, respectively. For every increase in rank within a county's socioeconomic social vulnerability index (SVI), the risk of respiratory SMM increased 2.8-fold, whereas an increase in rank in the racial/ethnic minority SVI was associated with a 1.6-fold elevated risk of blood transfusion.

Conclusion

This study underscores the complex association between individual and county factors associated with SMM, emphasizing the need for multifaced approaches to improve maternal care.

Key Points

• No increase in composite SMM rates from 2008 to 2018.

• Increases in obstetric SMM subtypes and sepsis.

• Risk factor profiles may differ across SMM subtypes.

• Key risk factors: age, comorbidities, prenatal care.

• County socioeconomic status associated with respiratory SMM risk.

Keywords

severe maternal morbidity - maternal comorbidities - obstetric comorbidity index - maternal health - social vulnerability index

• References

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