Association between three-timepoint maternal blood pressure trajectories during pregnancy and low birth weight: a longitudinal study based on NHANES 2005-2006

Abstract

Background: Dynamic changes in maternal blood pressure influence neonatal birth weight however, studies investigating the association between blood pressure trajectories during pregnancy and low birth weight (LBW) remain limited. This study aims to identify maternal blood pressure trajectories based on three time points using group-based trajectory modeling (GBTM) and explore their association with LBW.

Methods: This study was based on the NHANES 2005-2006 database and included 330 pregnant women meeting the eligibility criteria (41 cases in the LBW group and 289 in the control group). GBTM was applied to model three blood pressure measurements [systolic blood pressure (SBP), diastolic blood pressure (DBP), pulse pressure (PP)] taken during pregnancy. Multilevel logistic regression was used to assess the relationship between blood pressure trajectories and LBW. Additionally, stratified analyses were conducted to evaluate the modifying effects of age, body mass index (BMI), and education level, and directed acyclic graph (DAG) were employed for covariate selection.

Results: Three distinct blood pressure trajectory patterns were identified. Logistic regression revealed that, compared with the low blood pressure trajectory, mothers with a high-medium SBP trajectory had a significantly increased risk of delivering an LBW infant [odds ratio [OR] = 4.479, 95% confidence interval [CI]: 2.541-7.895, P < 0.001]. Stratified analyses indicated that this association was more pronounced in mothers who were older than 40 years, had a BMI >28, had lower income, did not consume alcohol, and had abnormal cholesterol levels. The DAG analysis further supported the independent effect of blood pressure trajectories on LBW.

Conclusions: Maternal blood pressure trajectories based on three prenatal measurements are closely associated with LBW, particularly among mothers with a high-medium SBP trajectory. This study underscores the importance of monitoring blood pressure fluctuations during pregnancy and suggests that early intervention may help reduce the risk of LBW.

Keywords: directed acyclic graph (DAG); group-based trajectory modeling (GBTM); low birth weight (LBW); maternal risk factors; pregnancy blood pressure trajectories; systolic blood pressure (SBP).

Figure 1

Flowchart of sample data selection.

Figure 2

Box plot analysis of three blood pressure measurements during pregnancy.

Figure 3

Maternal blood pressure trajectory model (GBTM) analysis results. This figure displays three distinct trajectory groups for (A) systolic blood pressure, (B) diastolic blood pressure, and (C) pulse pressure across gestational weeks 10, 20, and 30. The identified trajectories are labeled as high–low, high–medium, and medium–low, reflecting different trends in blood pressure changes over time. Pulse pressure was calculated as the difference between systolic and diastolic blood pressure.

Figure 4

DAG analysis for covariate selection. The green node represents the exposure variable (blood pressure trajectory), the blue node represents the outcome variable (LBW), and the pink nodes represent potential confounders, including age, BMI, race, education level, income, marital status, alcohol consumption, smoking, and cholesterol levels.