Is Rural Residence an Independent Risk Factor for Spontaneous Preterm Birth at a Midwestern Tertiary Care Center? A Cross-Sectional Study

Statistical Analysis

Standard descriptive statistics were used to characterize the study population. Generalized linear mixed models (SAS Proc GLIMMIX) were used to determine whether the dichotomous outcome (<37 weeks [sPTB] vs. ≥37 weeks [full term]) was associated with potential RFs. As deliveries were nested with the mother, maternal-specific random intercepts were included to account for the association of multiple deliveries within the same mother. The potential RFs included were maternal age, race, ethnicity, rural vs. urban residence, type of medical insurance, sex of the baby, maternal smoking, primigravidity, and delivery at IHC after transfer from an outside hospital. Such factors were first tested individually, then factors with a P value below 0.15 were included in a full multivariable model, and the backward stepwise method was used to remove variables one at a time until all variables in the model had a P value below 0.05. Interaction terms, rurality with age, rurality with smoking status, and rurality with transferred were examined and tested in the multivariable model to evaluate for confounding variables. None of the interaction terms were significant at P value below 0.05 level, so the interaction terms were not controlled for in the final multivariable model. Collinearity diagnostics were conducted using the Variance Inflation Factor (VIF) for all predictor variables included in the model. The VIF values were all below 2, indicating that multicollinearity is unlikely to be a significant issue. Patients with missing values were categorized as unknown or other or missing categories to retain all observations, ensuring no loss of potentially valuable data. In the models, we present both unadjusted and adjusted odds ratios (aORs) for each RF with a 95% confidence interval (CI). P values <.05 were considered statistically significant. All statistical analyses were performed using SAS, version 9.4 (SAS Institute).

Rural Residence and sPTB

Rural residence was significantly and independently associated with increased risk of sPTB at IHC, whether transfers were included or excluded. When examined by individual RUCA codes, 3, 6, 5, and 4 were found to have the highest percentages of sPTB, at 27.3%, 20.0%, 19.9%, and 19.3%, respectively. These percentages of sPTB are difficult to interpret due to the small sample size in each of these RUCA codes. When women were dichotomized (rural vs. urban), sPTB was significantly increased among women from rural areas compared with women from urban areas. These results are consistent with other studies which found that rural communities had an increased the risk for PTB,^13,25,26 and expand the current base of literature, as our study is the first to draw the conclusion that maternal rural residence is associated with increased risk of sPTB in comparison to maternal urban residence. Other studies have shown that rural residence is associated with PTB, but have not discriminated between sPTB and iPTB.^13,25,26

This study is critically relevant to Iowans and potentially other Midwest residents living in rural areas with decreased access to prenatal and obstetrical care, as 43 out of 97 L&D units have closed across Iowa from 2000 to 2025, ²⁷ leaving 33 out of 99 counties without L&D services. ²⁸ As of 2025, 61% of 93 rural hospitals in Iowa do not provide L&D care. ²⁹ This is associated with decreased quality of patient care, with a recent study finding that rural L&D unit closures are associated with decreased number of prenatal care visits in Iowa. ³⁰ The greatly increased risk of sPTB among patients living in rural communities may be a result of this lack of access to prenatal care due closures of L&D units, as well as the stress that is associated with decreased access to prenatal care.^{31 -33} Furthermore, this limited healthcare access of rural communities will worsen with the Medicaid cuts that were recently passed by congress. ³⁴

In addition, although we were not able to measure pesticide concentrations, maternal exposure to pesticides may be affecting our rural population as counties with increased pesticide use have an increased risk of PTB. ³⁵ Increased incidence of pesticide drift, or accidental spray of pesticides on unintended areas, affect IHC’s more rural, adjacent counties at increased rates. ³⁶ Increased exposure to other contaminants associated with increased risk for sPTB may also be relevant to rural population, such as polyfluoroalkyl substances ³⁷ and nitrates. ⁹ The vast majority of the rural population in the U.S. uses groundwater sources for drinking water, ³⁸ and groundwater is susceptible to increased levels of pesticides, ³⁹ nitrates, ³⁹ and polyfluoroalkyl substances. ⁴⁰

Race and sPTB

We found no association with race and sPTB in this study. Current literature has found that mothers of minority race have increased incidence of PTB in the U.S. ¹⁰ More specifically to sPTB, a descriptive prospective study done in North Carolina, by Jesse et al, ⁴¹ among 260 women of low-income status and rural residence found that African American race was associated with increased risk of sPTB compared to White race, when controlling for other confounding variables. This study was able to exclude iPTB specifically and controlled for preeclampsia and chronic hypertension in their analysis.

Our contrasting results may be due to the robust exclusion criteria used in attempt to only include sPTB in our study. To include only sPTB, many deliveries among women who had chronic diseases were excluded because they were indications for iPTB. Racial minorities are disproportionately affected by these chronic diseases, including hypertension, ⁴² diabetes, ⁴³ and preeclampsia. ⁴⁴ This may have led to unintended exclusions of deliveries that were not induced, while disproportionately excluding mothers of minority race. Considering this, the racial findings of the current study suggest that the relationship between race and sPTB may not be direct but modulated by the relationship between race and other health conditions that impact pregnancy. This supports the understanding that race is a social construct and a social determinant of health. ⁴⁵ Race does not have a biological basis in increasing risk for poor health outcomes. Additionally, the categories of race in the model were Asian, Black, White, and other/unknown. The other/unknown category includes races of low prevalence in the sample and unknown race, which does not allow for inclusion of all races in the model.

When the deliveries transferred to IHC were excluded, the same variables entered the model with similar aORs, with the addition of maternal Asian race, which was found to be a protective factor for sPTB (aOR, 0.57; 95% CI, 0.35-0.91), with a P-value of 0.02. This finding was less significant than the other factors associated with sPTB and may be significant only due to the large sample size and not be a clinically meaningful finding. Despite this, the literature is consistent with this result, with Dongarwar et al ⁴⁶ finding that Chinese, Korean, Japanese, and Asian Indian mothers are at decreased risk of PTB when compared to White mothers. Our data did not have the granularity on specific Asian race categories noted by Dongarwar et al, and thus could not assess whether these subcategories were at decreased risk of sPTB.

Other RF and sPTB

The other significant RFs for sPTB found in our study, including extremes of maternal age and maternal smoking, were consistent with known risk factors for PTB, ⁶ although it was unclear in literature if these RFs were specific to sPTB as well. Additionally, female sex of the newborn was found to be a protective factor for sPTB and is a known protective factor of PTB. ²³ Lastly, our study finds that transfer to IHC from an outside hospital is highly associated with sPTB. This is expected, as transfers are typically due to the need for escalation of care for both the mother and the fetus, one of the indications being a PTB and the need for a higher-level nursery. We acknowledge that an aOR of 671.3 is unusually high and may raise concerns about model stability or potential multicollinearity. To address this, we conducted a collinearity diagnostic using the Variance Inflation Factor (VIF) for all predictor variables included in the model. The VIF values were all below 2, indicating that multicollinearity was unlikely to be a significant issue. The high aOR reflected a strong and genuine association between those transferred to IHC and sPTB in our sample. Specifically, 81.3% of transferred deliveries were sPTBs, compared to only 8.1% in the non-transferred group.

Additionally, a separate analysis was done with the transferred deliveries excluded due to concern that the rural population’s risk of sPTB was being inflated with the assumption that term deliveries from outside hospitals were less likely to be transferred to IHC. The resulting significant RFs were similar to the RFs found in the original analysis, the only difference being that Asian race was a significantly protective factor of sPTB. The analyses suggest that despite the high aOR for those transferred to IHC for sPTB, the other significant RFs included in the model are independently and statistically significant.

Strengths and Limitations

Strengths of our study include the large sample size spanning over 14 years, access to extensive EMR data including many PTB RFs, the use of a multivariable model, the Midwest region specific results, and the focus on sPTB. Many studies evaluating rurality as a RF for PTB in the past used birth record data along with patient surveys and had limited access to variables,^13,25,26 while the current study utilized all EMR data associated with pregnancies as well as the EMR data of the newborn. Second, the current study allowed for Midwest region specific conclusions, which is valuable, due to the wide variability in risk for PTB among U.S. states. ¹⁵ Many recent studies investigate rurality as a RF for PTB on a national level,^13,14 but this does not allow for region specific conclusions necessary for informing regional policy and clinical practice. Our study allows for conclusions specific to the Midwest, although this may be viewed as also a limitation, as the results may not be applicable outside of the Midwest. Additionally, our study focused on sPTB specifically to identify RFs for sPTB with unknown causation, as opposed to including iPTB, like other studies assessing rurality as a RF for PTB.^13,25,26 However, there could be misclassification bias, since it is possible that not all the preterm deliveries included in our study were sPTBs, as we did not have access to a variable stating if the PTB was induced or spontaneous. Instead, to include only sPTBs, pregnancies with diagnoses that were indications for iPTB ¹⁸ and induced abortion were excluded, ¹⁹ resulting in the possibility that some of the data set includes iPTB due to other indications that were not excluded, such as fetal intrauterine growth restriction. Furthermore, it is possible that not all the excluded high-risk pregnancies ended in induction, so sPTBs may have been excluded unintentionally.

Another limitation of this study was that our data was only as accurate as what was entered into the EMR. Additionally, not all known RFs for PTB were able to be tested in the study or were crudely measured due to data limitations. Maternal stress, ⁴⁷ illicit drug use, ⁴⁸ access to prenatal care, and environmental exposures were not included in the study, and maternal socioeconomic status ⁴⁷ was estimated by type of maternal health insurance. Illicit drug use is only measured when there is suspicion of such. The race categories were also crudely formed, as the unknown/other race category included many different races of low prevalence of those races in the data. These approximations and omissions may have caused potential for confounding variables in the study, although interactions for confounding variables were tested and not found to enter the models as noted in the statistical analyses above.

Lastly, it is known that nationally, rural mothers of higher risk pregnancies are more likely to seek care in an urban area than rural mothers of lower risk pregnancies. ¹¹ Because our data set did not include the denominator of all rural pregnancies in Iowa, it only included the deliveries occurring at IHC, it is possible that the rural pregnancies in our study are at higher risk of sPTB because the rural women traveling to our center may be inherently at higher risk. However, our study excluded many high-risk pregnancies in efforts to include only sPTB opposed to iPTB, and all of the adjacent counties to the county where IHC is located, except for 1 county, were either maternity care deserts, ²⁸ or have had a L&D unit closure during the time span the data set included. ⁴⁹