How Do Income and Race Interact to Shape Trends in U.S. Preterm Birth Rates?

Cordova-Ramos et al. (2026) examine how U.S. preterm birth rates vary over time by household income and whether racial and ethnic disparities persist across income groups. They analyze nationally representative Pregnancy Risk Assessment Monitoring System (PRAMS) data covering 411,469 mother–infant dyads from 2011–2021. They find that preterm birth rates increased among households below 200% of the federal poverty level but remained stable among higher-income households. Overall rates were 10.4% among mothers below poverty compared with 7.5% among those at or above 200% of the federal poverty level. Black mothers experienced the highest risk across all income levels, with a 19% higher risk than White mothers in the lowest income group.

Why This Article Was Selected for The Policy Scientist

Cordova-Ramos et al. (2026) address a policy issue with broad public health and economic implications: the persistent disparities in preterm birth across socioeconomic and racial groups in the United States. Preterm birth remains a leading driver of infant mortality, long-term health complications, and substantial medical expenditures, making it a central concern for health policy and social policy. The topic is especially timely as recent national data show worsening maternal and infant health outcomes and widening socioeconomic inequality. The authors have contributed repeatedly to research on maternal health disparities, and this article extends that literature by documenting national income gradients in preterm birth using the large PRAMS dataset, which is widely regarded as a high-quality, nationally representative surveillance system. The findings likely generalize to other developed health systems where socioeconomic and racial disparities intersect with maternal health outcomes. The statistical analysis relies on multivariate regression models rather than causal inference techniques or randomized designs. While appropriate for descriptive analysis, the evidence base would be strengthened by future studies employing stronger causal identification strategies.

Full Citation and Link to Article

Cordova-Ramos, E. G., Ruiz, S. Y., Guyol, G. G., Kalluri, N. S., Elansary, M., McConnell, M., & Parker, M. G. (2026). Trends in US preterm birth rates by household income and race and ethnicity. JAMA Network Open, 9(1), e2550664. https://doi.org/10.1001/jamanetworkopen.2025.50664

Central Research Question

Cordova-Ramos et al. (2026) investigate how preterm birth rates in the United States vary across household income levels and whether those income gradients differ across racial and ethnic groups. Preterm birth, defined as delivery before 37 weeks of gestation, remains the leading cause of infant mortality and a major contributor to long-term health complications among children. Although racial disparities in preterm birth are well documented—particularly the persistent gap between Black and White mothers—the role of household income in shaping these patterns has received less systematic national attention. The authors therefore ask two closely related questions. First, how have preterm birth rates evolved from 2011 to 2021 across different income categories? Second, to what extent do racial and ethnic disparities persist within income groups? By examining trends over time and testing interactions between income and race, the study evaluates whether socioeconomic status mitigates or fails to mitigate existing disparities in maternal and infant health outcomes.

Previous Literature

A substantial body of research documents socioeconomic and racial disparities in maternal and infant health outcomes. Earlier epidemiological studies show that preterm birth is strongly associated with poverty, neighborhood disadvantage, chronic stress, and limited access to high-quality prenatal care. Systematic reviews and meta-analyses have also consistently found that Black mothers experience roughly twice the risk of preterm birth compared with White mothers in the United States. These disparities have remained remarkably stable over decades despite advances in medical technology and maternal care.

Recent scholarship has attempted to identify mechanisms linking socioeconomic status to birth outcomes. Researchers have pointed to pathways such as environmental exposures, food insecurity, differential access to medical services, and the cumulative effects of chronic stress. A related line of research examines how structural factors—including discrimination and residential segregation—may shape maternal health risks. However, many previous studies focus on either socioeconomic gradients or racial disparities in isolation rather than analyzing their interaction at the national level.

Cordova-Ramos and colleagues contribute to this literature by examining national trends in preterm birth across multiple income categories while explicitly modeling interactions between income and race and ethnicity. By using recent nationally representative survey data covering more than a decade, the study provides updated evidence on whether income gradients in preterm birth have widened, narrowed, or remained stable. In doing so, it extends earlier work that often relied on state-level data or shorter time horizons.

Data

The study uses data from the Pregnancy Risk Assessment Monitoring System (PRAMS), a large, nationally representative surveillance system administered by the Centers for Disease Control and Prevention in partnership with state health departments. PRAMS collects detailed survey information from mothers approximately two to four months after childbirth and links those responses to birth certificate records. This linkage allows researchers to combine self-reported maternal characteristics with clinical birth outcomes and demographic information.

The analytic sample includes 411,469 mother–infant dyads observed between 2011 and 2021. After applying survey weights, the dataset represents roughly 20 million births nationwide. The PRAMS sampling design intentionally oversamples historically underrepresented populations, allowing the dataset to produce population-level estimates for a wide range of demographic groups.

The key dependent variable is preterm birth, defined as birth occurring before 37 completed weeks of gestation. The primary independent variable is household income. Because the PRAMS survey records income in categorical ranges, the authors convert reported income into percentages of the federal poverty level (FPL), accounting for household size, state, and year. They then classify households into three groups: below 100 percent of the federal poverty level, between 100 and 199 percent, and at or above 200 percent of the poverty threshold.

Additional covariates include maternal age, educational attainment, language, insurance coverage before pregnancy, prenatal care utilization, diabetes, hypertension during pregnancy, smoking during pregnancy, and previous preterm birth. These variables capture a range of demographic and health-related factors known to influence birth outcomes.

Overall, PRAMS is widely considered a high-quality data source for maternal and infant health research. Its nationally representative design and large sample size allow researchers to examine relatively rare outcomes such as preterm birth with considerable statistical precision.

Methods

The authors employ a cross-sectional analytical framework using pooled PRAMS data across multiple years. To account for the survey’s complex sampling structure, the analysis incorporates survey weights, strata, and clustering variables provided by the CDC. This approach ensures that estimated trends accurately represent national population patterns.

The study begins by calculating annual preterm birth rates within each income category and testing for trends over time using the Cochran–Armitage trend test. This descriptive analysis provides an initial assessment of whether birth outcomes have improved or worsened across socioeconomic groups.

The authors then estimate a series of modified Poisson regression models with robust standard errors. This modeling strategy is commonly used in epidemiological research when the outcome variable is binary and when researchers wish to estimate relative risks rather than odds ratios. The first model estimates the unadjusted association between income category and preterm birth. Subsequent models introduce additional controls for maternal demographic characteristics, pregnancy-related risk factors, and health behaviors.

In the final model specification, the authors include interaction terms between household income and race and ethnicity. This allows them to evaluate whether the relationship between income and preterm birth differs across racial groups. In other words, the model tests whether income provides the same protective effect against preterm birth for all racial groups or whether disparities persist even among higher-income households.

To address potential bias arising from missing income data, the authors conduct two sensitivity analyses. The first introduces a separate category for observations with missing income. The second applies multiple imputation using demographic and socioeconomic variables to estimate missing values. Both approaches produce results that are substantively similar to the main analysis.

Findings/Size Effects

The study documents a clear income gradient in preterm birth outcomes. Across the entire study period, preterm birth rates are highest among mothers with household incomes below the federal poverty level. On average, preterm birth occurs in approximately 10.4 percent of births in the lowest income group, compared with 8.9 percent among households between 100 and 199 percent of the poverty line and 7.5 percent among households at or above 200 percent of the poverty line.

Trend analysis reveals that disparities widened during the study period. Between 2011 and 2021, preterm birth rates increased from 9.7 percent to 11.1 percent among households below the poverty line and from 7.8 percent to 10.0 percent among those between 100 and 199 percent of the federal poverty level. In contrast, rates remained essentially stable among higher-income households, fluctuating only slightly around eight percent.

The interaction analysis shows that racial disparities persist across all income categories. Black mothers experience the highest rates of preterm birth regardless of income level. In the lowest income category, Black mothers face a 19 percent higher risk of preterm birth than White mothers after adjusting for other factors. Even among the highest income households, Black mothers still experience a 13 percent higher risk than White mothers.

The analysis also reveals that income provides some protective effect for White mothers. Among White mothers, those in the highest income category have a roughly 9 percent lower risk of preterm birth than those living below the poverty line. However, the protective effect of income is weaker or absent for several other racial and ethnic groups.

Importantly, when race and ethnicity are introduced into the regression models, the independent effect of income on preterm birth becomes statistically insignificant. This pattern suggests that racial disparities account for a substantial portion of the observed relationship between income and birth outcomes.

Conclusion

Cordova-Ramos et al. conclude that disparities in preterm birth across income groups widened during the decade studied, with the highest rates consistently observed among families living below the federal poverty line. At the same time, racial disparities remain pronounced across all income categories. Black mothers experience elevated risks of preterm birth even when household income is relatively high.

The results indicate that socioeconomic status alone does not fully explain disparities in maternal and infant health outcomes. The persistence of racial gaps across income levels suggests that additional social and structural factors influence the risk of preterm birth.

More broadly, the study demonstrates the value of nationally representative surveillance systems such as PRAMS for tracking maternal and infant health outcomes over time. By combining a large dataset with rigorous statistical analysis, the authors provide updated evidence on how socioeconomic and demographic factors intersect to shape preterm birth risk in the United States.