Sociodemographic Factors Associated with Antenatal Steroid Exposure among Late Preterm Births
Abstract As the risk of preterm birth is known to vary widely, we aimed to determine if antenatal steroid exposure among LPBs varied based on sociodemographic characteristics. We hypothesized that sociodemographic factors may influence a provider ‘s clinical judgment of a patient ‘s likelihood of preterm birth and, therefore, also be associated with antenatal steroid use. This cross-sectional analysis used the 2021 US natality data and included non-anomalous, liveborn, hospital-based singleton births at ≥34 weeks of gestation to mothers without diabetes, a cohort similar to those in the ALPS Trial. The following sociodemographic factors were compared among those who received vs. did not receive steroids using chi-square tests: age, race (as designated and categorized on the birth certificate), ethnicity, primary pay for the delivery, marital status, and education. In 2021, 237,025 late preterm births met eligibility criteria, of which 17.3% were exposed to antenatal steroids. Among the following sociodemographic factors, the odds of antenatal steroid receipt were lower compared to the reference majority population: 1) Black (adjusted odds ratio (aOR) 0.88 (95% CI 0.81, 0.96)) and Native Hawaiian or Other Pacific Islander (NHOPI) (aOR 0.58 (95% CI 0.43, 0.79) compared to White race; 2) less than high school education (aOR 0.76 (95% CI 0.72, 0.81)) or high school education (Aor 0.87 (95% CI 0.83, 0.91)) compared to post-secondary education; and 3) public (aOR 0.83 (95% CI 0.78, 0.87)) or no insurance (aOR 0.68 (95% CI 0.61, 0.77)) compared to private insurance. Age and marital status were not associated with steroid receipt. Despite no known differential treatment effects of antenatal steroids by sociodemographic factors, steroid exposure among LBPs varied significantly among races, ethnicities, payers, and education levels in the US..
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Preprint| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
bioRxiv.org - (2024) vom: 29. Jan. Zur Gesamtaufnahme - year:2024 |
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| Sprache: |
Englisch |
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| Beteiligte Personen: |
Clapp, Mark A. [VerfasserIn] |
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| Links: |
Volltext [kostenfrei] |
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| doi: |
10.1101/2024.01.22.24301562 |
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| PPN (Katalog-ID): |
XBI042286956 |
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| 520 | |a Abstract As the risk of preterm birth is known to vary widely, we aimed to determine if antenatal steroid exposure among LPBs varied based on sociodemographic characteristics. We hypothesized that sociodemographic factors may influence a provider ‘s clinical judgment of a patient ‘s likelihood of preterm birth and, therefore, also be associated with antenatal steroid use. This cross-sectional analysis used the 2021 US natality data and included non-anomalous, liveborn, hospital-based singleton births at ≥34 weeks of gestation to mothers without diabetes, a cohort similar to those in the ALPS Trial. The following sociodemographic factors were compared among those who received vs. did not receive steroids using chi-square tests: age, race (as designated and categorized on the birth certificate), ethnicity, primary pay for the delivery, marital status, and education. In 2021, 237,025 late preterm births met eligibility criteria, of which 17.3% were exposed to antenatal steroids. Among the following sociodemographic factors, the odds of antenatal steroid receipt were lower compared to the reference majority population: 1) Black (adjusted odds ratio (aOR) 0.88 (95% CI 0.81, 0.96)) and Native Hawaiian or Other Pacific Islander (NHOPI) (aOR 0.58 (95% CI 0.43, 0.79) compared to White race; 2) less than high school education (aOR 0.76 (95% CI 0.72, 0.81)) or high school education (Aor 0.87 (95% CI 0.83, 0.91)) compared to post-secondary education; and 3) public (aOR 0.83 (95% CI 0.78, 0.87)) or no insurance (aOR 0.68 (95% CI 0.61, 0.77)) compared to private insurance. Age and marital status were not associated with steroid receipt. Despite no known differential treatment effects of antenatal steroids by sociodemographic factors, steroid exposure among LBPs varied significantly among races, ethnicities, payers, and education levels in the US. | ||
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