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<p>Prenatal detection of congenital heart disease (CHD) reduces neonatal morbidity and mortality. Disparities in access to fetal echocardiography persist across socioeconomic status, rurality, insurance, race, and ethnicity.&#xa0;To assess whether neighborhood-level socioeconomic and environmental factors influence the likelihood of receiving a prenatal echocardiogram among infants with CHD in Western Pennsylvania.&#xa0;Retrospective, single-center cohort study (2010–2024) of mother-infant dyads where infants had CHD requiring surgical or catheter intervention within 6 months after birth. Exclusions included only minor anomalies, inability to link dyads, intervention after 6 months, or missing neighborhood data. Maternal variables included demographics, diabetes status, insurance type, and neighborhood-level characteristics (Area Deprivation Index, Rural-Urban Commuting Area codes, Walk Score). The primary outcome was receipt of a prenatal echocardiogram within 6 months before delivery.&#xa0;Among 1,092 dyads, 545 (49.9%) received a prenatal echocardiogram. In unadjusted analysis, those who received a prenatal echocardiogram were more likely to live in highly-deprived neighborhoods (38.7% vs. 28.7%), have Black mothers (15.8% vs. 8.2%), and have mothers with diabetes (9.7% vs. 3.9%). After adjusting for maternal diabetes, neighborhood deprivation was no longer significantly associated with receiving a prenatal echocardiogram. Maternal diabetes remained a strong independent predictor (OR = 2.60, 95% CI: 1.29–5.20). Rurality, Walk Score, and insurance type were not associated with odds of receiving a prenatal echocardiogram.&#xa0;Maternal diabetes, rather than neighborhood factors, predicted prenatal echocardiogram receipt. Only half of significant CHD cases had a prenatal echocardiogram, highlighting room for improvement. Integrating clinical and neighborhood data can help distinguish true disparities from differences driven by clinical risk.</p>

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Neighborhood Socioeconomic & Geographic Determinants of Prenatal Congenital Heart Disease Diagnosis

  • 期刊论文

  • 发表日期：

    2026年1月29日

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  • Matthew M. Tran,
  • Mary D. Schiff,
  • Floyd W. Thoma,
  • Frederick W. Roberts,
  • Sharon Mazzocco,
  • Craig P. Dobson

摘要

Prenatal detection of congenital heart disease (CHD) reduces neonatal morbidity and mortality. Disparities in access to fetal echocardiography persist across socioeconomic status, rurality, insurance, race, and ethnicity. To assess whether neighborhood-level socioeconomic and environmental factors influence the likelihood of receiving a prenatal echocardiogram among infants with CHD in Western Pennsylvania. Retrospective, single-center cohort study (2010–2024) of mother-infant dyads where infants had CHD requiring surgical or catheter intervention within 6 months after birth. Exclusions included only minor anomalies, inability to link dyads, intervention after 6 months, or missing neighborhood data. Maternal variables included demographics, diabetes status, insurance type, and neighborhood-level characteristics (Area Deprivation Index, Rural-Urban Commuting Area codes, Walk Score). The primary outcome was receipt of a prenatal echocardiogram within 6 months before delivery. Among 1,092 dyads, 545 (49.9%) received a prenatal echocardiogram. In unadjusted analysis, those who received a prenatal echocardiogram were more likely to live in highly-deprived neighborhoods (38.7% vs. 28.7%), have Black mothers (15.8% vs. 8.2%), and have mothers with diabetes (9.7% vs. 3.9%). After adjusting for maternal diabetes, neighborhood deprivation was no longer significantly associated with receiving a prenatal echocardiogram. Maternal diabetes remained a strong independent predictor (OR = 2.60, 95% CI: 1.29–5.20). Rurality, Walk Score, and insurance type were not associated with odds of receiving a prenatal echocardiogram. Maternal diabetes, rather than neighborhood factors, predicted prenatal echocardiogram receipt. Only half of significant CHD cases had a prenatal echocardiogram, highlighting room for improvement. Integrating clinical and neighborhood data can help distinguish true disparities from differences driven by clinical risk.