ABSTRACT
Background
Pregnancy induces profound cardiovascular adaptations that may have cumulative effects with repeated pregnancies. However, the relationship between parity and subclinical myocardial dysfunction in healthy women remains unclear.
Methods
This prospective cross‐sectional study enrolled 605 healthy pregnant women without cardiovascular disease or risk factors. All participants underwent comprehensive echocardiographic assessment including speckle‐tracking‐derived global longitudinal strain (GLS) analysis during the third trimester (28–32 weeks gestation). The relationship between parity and GLS was described using multivariable linear regression analysis, adjusting for age, body mass index and blood pressure. Participants were stratified into two groups (≥ 4 vs. < 4 pregnancies) for comparative analysis.
Results
Mean age was 30.9 ± 7.2 years with mean parity of 3.8 ± 2.4 pregnancies. Despite preserved ejection fraction across all women (63.2% ± 4.7%), each additional pregnancy was associated with a 0.21‐unit worsening in GLS independent of age (β = 0.21, 95% CI: 0.13–0.29, p < 0.001). Women with ≥ 4 pregnancies had significantly worse GLS compared to those with fewer pregnancies (−19.1% ± 2.5% vs. −20.5% ± 4.1%, p < 0.001). In multivariable linear regression, high parity remained independently associated with reduced GLS (β = 1.18, 95% CI: 0.52–1.84, p < 0.001) after adjusting for confounders. The effect was more pronounced in older women and those with shorter interpregnancy intervals (< 18 months).
Conclusion
Higher parity is independently associated with reduced myocardial strain detected by GLS despite preserved ejection fraction, demonstrating a continuous relationship with each additional pregnancy. While GLS values remain within physiological ranges for pregnancy, the shift toward lower values suggests cumulative haemodynamic effects that warrant further investigation.
Keywords: global longitudinal strain, parity, pregnancy, speckle‐tracking echocardiography, subclinical dysfunction
1. Introduction
Pregnancy induces profound cardiovascular adaptations to meet the metabolic demands of the developing fetus and prepare for delivery [1, 2]. These physiological changes include increases in blood volume, cardiac output, heart rate and left ventricular mass, accompanied by decreases in systemic vascular resistance [3]. While these adaptations are generally well‐tolerated in healthy women and typically reverse within months postpartum, emerging evidence suggests that repeated pregnancies may have cumulative effects on maternal cardiac structure and function [4, 5].
Higher parity is increasingly recognised as a potential risk factor for long‐term cardiovascular disease (CVD) in women [6, 7]. Epidemiological studies have demonstrated associations between higher parity and increased risks of hypertension, coronary artery disease, heart failure and cardiovascular mortality [8, 9]. However, the underlying mechanisms linking repeated pregnancies to adverse cardiovascular outcomes remain incompletely understood.
Conventional echocardiographic parameters, particularly left ventricular ejection fraction (LVEF), have limited sensitivity for detecting subtle myocardial dysfunction [10]. Speckle‐tracking echocardiography has emerged as a powerful tool for assessing myocardial mechanics through measurement of myocardial strain [11]. Global longitudinal strain (GLS), which quantifies the percentage change in myocardial fibre length during systole, provides superior sensitivity for detecting subclinical left ventricular dysfunction compared to LVEF [12, 13]. GLS has been validated in various cardiac conditions and is increasingly utilised in obstetric populations to evaluate pregnancy‐related cardiac adaptations [14].
Despite growing interest in the cardiovascular implications of higher parity, data examining the relationship between number of pregnancies and advanced echocardiographic markers of myocardial function remain sparse. Previous studies have primarily focused on traditional parameters or have been limited by small sample sizes and heterogeneous populations [15]. The dose–response relationship between parity and myocardial strain, and whether this relationship varies by maternal characteristics, remains poorly characterised.
The primary objective of this study was to describe the relationship between parity and myocardial function as assessed by speckle‐tracking‐derived GLS in healthy pregnant women without known CVD, using multivariable linear regression models to adjust for potential confounders. Secondary objectives included: (1) characterising the association between parity and traditional echocardiographic parameters; (2) examining whether the parity–GLS relationship is modified by maternal age; and (3) evaluating the effect of interpregnancy interval on myocardial strain. We hypothesised that higher parity would be independently associated with reduced GLS, even in the presence of preserved ejection fraction.
2. Methods
2.1. Study Design and Population
This study was conducted between September 2022 and October 2025 at a tertiary referral centre. The study protocol was approved by the institutional ethics committee (approval number: 2022/20‐05, dated 21 September 2022), and written informed consent was obtained from all participants prior to enrolment. The study was conducted in accordance with the principles of the Declaration of Helsinki.
The study employed a cross‐sectional design in which all participants were assessed at a single timepoint during pregnancy (28–32 weeks gestation). This design allows evaluation of associations between reproductive history and cardiac parameters at a standardised gestational age, though causal inference and temporal relationships cannot be definitively established.
Patients were not involved in the design, conduct, reporting or dissemination plans of this research. No core outcome set was identified for this topic; outcome selection was therefore based on clinical relevance and current echocardiographic standards.
This research received no specific grant from any funding agency in the public, commercial or not‐for‐profit sectors.
Pregnant women in their third trimester presenting for routine prenatal care were consecutively screened for eligibility. Inclusion criteria were: (1) singleton pregnancy, (2) gestational age between 28 and 32 weeks, (3) age ≥ 18 years and (4) willingness to participate. Exclusion criteria included: known CVD (congenital heart disease, valvular heart disease, cardiomyopathy, coronary artery disease, arrhythmias), pre‐existing or gestational hypertension, diabetes mellitus (pre‐gestational or gestational), chronic kidney disease, thyroid disorders, systemic autoimmune diseases, multiple pregnancy, preeclampsia or eclampsia, foetal anomalies or intrauterine growth restriction, cardiotoxic medications, active smoking and inadequate echocardiographic windows for strain analysis.
A total of 605 eligible pregnant women without known CVD or cardiovascular risk factors were prospectively enrolled and assessed during their third trimester. All participants underwent comprehensive clinical evaluation and echocardiographic assessment during a single study visit.
2.2. Clinical Data Collection
Detailed demographic and obstetric histories were obtained from all participants through structured interviews and medical record review. Demographic data included age, height, weight and body mass index (BMI). Comprehensive obstetric history was recorded, including total number of pregnancies (gravidity), number of deliveries (parity), number of live births, number of abortions (spontaneous and therapeutic) and gestational age at assessment. For multiparous women, interpregnancy intervals were calculated as the time elapsed between consecutive deliveries. Vital signs were measured after a 10‐min rest period. Blood pressure was measured in the right arm using an automated sphygmomanometer, with the average of three consecutive measurements recorded.
2.3. Laboratory Assessments
Venous blood samples were collected after an overnight fast. Complete blood count was performed using automated haematology analysers. The neutrophil‐to‐lymphocyte ratio was calculated by dividing the absolute neutrophil count by the absolute lymphocyte count. Serum biochemistry included creatinine, sodium and potassium levels.
2.4. Echocardiographic Examination
All echocardiographic examinations were performed during the third trimester between 28 and 32 weeks of gestation to ensure measurement homogeneity and minimise the confounding effects of gestational age‐related haemodynamic variations. Studies were conducted using a commercially available ultrasound system (GE Healthcare) equipped with a 2.5‐MHz phased‐array transducer. All examinations were performed by experienced sonographers blinded to clinical data, and images were analysed offline by a single investigator to minimise inter‐observer variability. Participants were examined in the left lateral decubitus position. Comprehensive two‐dimensional, M‐mode and Doppler echocardiography were performed according to the recommendations of the American Society of Echocardiography.
Left ventricular volumes (end‐diastolic volume and end‐systolic volume) were calculated using the biplane Simpson method from apical four‐chamber and two‐chamber views. LVEF was calculated as: [(end‐diastolic volume − end‐systolic volume)/end‐diastolic volume] × 100%. Diastolic function was assessed by pulsed‐wave Doppler and tissue Doppler imaging (TDI). Peak early (E) and late (A) diastolic mitral inflow velocities were measured, and TDI‐derived early diastolic (E') and late diastolic (A') myocardial velocities were obtained from the septal mitral annulus. The E/e' ratio was calculated as an estimate of left ventricular filling pressures.
For speckle‐tracking strain analysis, high‐quality two‐dimensional grayscale images were acquired from apical four‐chamber, two‐chamber and three‐chamber views at frame rates of 60–90 frames per second. Three consecutive cardiac cycles were recorded during end‐expiratory breath‐hold. Offline analysis was performed using dedicated software (EchoPAC version 202, GE Healthcare). The left ventricular endocardial border was manually traced at end‐systole, and the software automatically tracked speckle patterns throughout the cardiac cycle. Global longitudinal strain (GLS) was calculated as the average of peak systolic longitudinal strain values from all assessable segments across the three apical views. GLS values are expressed as negative percentages, with more negative values indicating better myocardial function. Based on established cut‐offs from non‐pregnant populations and previous pregnancy studies, impaired GLS was defined as values greater than −20% (less negative than −20%).
To assess reproducibility of GLS measurements, intra‐observer variability was evaluated by re‐analysing 30 randomly selected studies (approximately 5% of the cohort) at least 4 weeks after initial analysis, with blinding to initial measurements and clinical data. The intra‐observer ICC for GLS was 0.94 (95% CI: 0.88–0.97), mean difference −0.12% ± 0.54% and coefficient of variation 2.7%.
2.5. Statistical Analysis
Statistical analysis was performed using SPSS version 25.0 (IBM Corp., Armonk, New York). Continuous variables were tested for normality using the Kolmogorov–Smirnov test and visual inspection of histograms and Q‐Q plots. Normally distributed continuous variables are presented as mean ± standard deviation, and non‐normally distributed variables as median (interquartile range). Categorical variables are expressed as numbers and percentages.
Based on the distribution of parity in our cohort and clinical relevance, participants were stratified into Group 1 (≥ 4 pregnancies) and Group 2 (< 4 pregnancies) for comparative analysis. Comparisons between groups were performed using Student's t‐test for normally distributed continuous variables, Mann–Whitney U test for non‐normally distributed variables, and chi‐square or Fisher's exact test for categorical variables, as appropriate.
Multivariable linear regression analysis was performed to describe the relationship between parity and GLS while adjusting for potential confounders. Two models were constructed: (1) a continuous model with GLS as the dependent variable and number of pregnancies as the independent variable, adjusting for maternal age; and (2) a categorical model including parity group (≥ 4 vs. < 4 pregnancies), age, BMI, systolic blood pressure and diastolic blood pressure. Results are reported as β coefficients with 95% confidence intervals. Subgroup analyses were performed stratified by age categories (≤ 30, 31–40, > 40 years) and interpregnancy interval (< 18 vs. ≥ 18 months). Interaction terms were tested to assess whether the relationship between parity and GLS was modified by age. A two‐tailed p value < 0.05 was considered statistically significant for all analyses.
3. Results
A total of 605 pregnant women without known CVD were prospectively enrolled for cross‐sectional assessment during the third trimester. The mean gestational age at echocardiographic assessment was 29.8 ± 1.3 weeks. The study population had a mean age of 30.9 ± 7.2 years (range: 18–44 years), with a mean number of pregnancies of 3.8 ± 2.4 (range: 1–11). The mean number of live births was 3.1 ± 2.2, the mean number of deliveries was 3.4 ± 2.3, and the mean number of abortions was 0.5 ± 0.9. BMI averaged 27.3 ± 4.5 kg/m2. Vital signs revealed a mean heart rate of 89.9 ± 13.5 bpm, systolic blood pressure of 115.6 ± 12.1 mmHg, and diastolic blood pressure of 72.3 ± 9.6 mmHg. Baseline clinical and laboratory characteristics of the entire cohort are presented in Table 1.
TABLE 1.
Baseline characteristics of the entire study population.
| Variable | Value |
|---|---|
| Demographics | |
| Age (years) | 30.9 ± 7.2 |
| Body mass index (kg/m2) | 27.3 ± 4.5 |
| Gestational age at assessment (weeks) | 29.8 ± 1.3 |
| Obstetric history | |
| Number of pregnancies (gravidity) | 3.8 ± 2.4 |
| Number of deliveries (parity) | 3.4 ± 2.3 |
| Number of live births | 3.1 ± 2.2 |
| Number of abortions | 0.5 ± 0.9 |
| Vital signs | |
| Heart rate (bpm) | 89.9 ± 13.5 |
| Systolic blood pressure (mmHg) | 115.6 ± 12.1 |
| Diastolic blood pressure (mmHg) | 72.3 ± 9.6 |
| Laboratory parameters | |
| Haemoglobin (g/dL) | 11.8 ± 1.4 |
| White blood cell count (×103/mm3) | 7.8 ± 3.0 |
| Neutrophil‐to‐lymphocyte ratio | 5.0 ± 2.6 |
| Serum creatinine (mg/dL) | 0.65 ± 0.20 |
| Sodium (mEq/L) | 139.0 ± 3.2 |
| Potassium (mEq/L) | 4.2 ± 0.4 |
| Conventional echocardiographic parameters | |
| Ejection fraction (%) | 63.2 ± 4.7 |
| LVEDD (cm) | 4.52 ± 0.40 |
| LVESD (cm) | 2.80 ± 0.33 |
| End‐diastolic volume (mL) | 97.8 ± 15.5 |
| End‐systolic volume (mL) | 44.4 ± 9.1 |
| Fractional shortening (%) | 36.3 ± 4.2 |
| Interventricular septum diameter (cm) | 0.94 ± 0.46 |
| Posterior wall thickness (cm) | 0.89 ± 0.11 |
| Left atrial diameter (cm) | 3.3 ± 0.4 |
| Diastolic function parameters | |
| Mitral E wave velocity (cm/s) | 92.8 ± 16.7 |
| Mitral A wave velocity (cm/s) | 57.9 ± 11.6 |
| E/A ratio | 1.63 ± 0.39 |
| E' velocity (cm/s) | 12.0 ± 2.6 |
| A' velocity (cm/s) | 7.4 ± 1.6 |
| E/e' ratio | 8.0 ± 2.2 |
| Strain analysis | |
| Global longitudinal strain (%) | −19.9 ± 3.6 |
| Impaired GLS (> −20%), n (%) | 196 (32.4%) |
Note: Data are presented as mean ± standard deviation for continuous variables and n (%) for categorical variables. All echocardiographic measurements were performed at 28–32 weeks of gestation.
Abbreviations: GLS, global longitudinal strain; LVEDD, left ventricular end‐diastolic diameter; LVESD, left ventricular end‐systolic diameter.
Transthoracic echocardiographic evaluation revealed preserved left ventricular systolic function in all participants, with a mean ejection fraction of 63.2% ± 4.7%. Mean LVEDD was 4.52 ± 0.40 cm and LVESD was 2.80 ± 0.33 cm. Diastolic function parameters showed mitral E wave velocity of 92.8 ± 16.7 cm/s, A wave velocity of 57.9 ± 11.6 cm/s, E/A ratio of 1.63 ± 0.39, TDI‐derived E' velocity of 12.0 ± 2.6 cm/s, A' velocity of 7.4 ± 1.6 cm/s and E/e' ratio of 8.0 ± 2.2 (Table 1).
The mean GLS value for the study population was −19.9% ± 3.6%. Linear regression analysis demonstrated that each additional pregnancy was associated with a 0.21‐unit increase (less negative) in GLS (β = 0.21, 95% CI: 0.13–0.29, p < 0.001), independent of maternal age, indicating progressive myocardial impairment with increasing parity (Figure 1). In the study population, 196 women (32.4%) had GLS values > −20%, which is considered the lower limit of normal in non‐pregnant populations.
FIGURE 1.
Linear regression analysis: relationship between number of pregnancies and global longitudinal strain.
For comparative analysis, participants were stratified into Group 1 (high parity, ≥ 4 pregnancies, n = 274) and Group 2 (low parity, < 4 pregnancies, n = 331). Women in Group 1 were significantly older than those in Group 2 (34.1 ± 5.6 vs. 28.2 ± 7.1 years, p < 0.001). Gestational age at assessment was virtually identical between groups (29.9 ± 1.2 vs. 29.8 ± 1.3 weeks, p = 0.523). BMI was slightly but significantly higher in Group 1 (28.1 ± 4.4 vs. 26.7 ± 4.5 kg/m2, p < 0.001). Heart rate, blood pressure and laboratory parameters were comparable between groups.
No significant differences were observed in standard measures of left ventricular systolic function between the two groups. Ejection fraction was preserved and similar in both groups (63.3% ± 4.8% vs. 63.2% ± 4.6%, p = 0.821). LVEDD, LVESD, end‐diastolic and end‐systolic volumes, and fractional shortening were all comparable (Table 2). Mitral inflow velocities showed trends toward differences but did not reach statistical significance: E wave (91.3 ± 17.1 vs. 94.0 ± 16.3 cm/s, p = 0.065), E/A ratio (1.59 ± 0.38 vs. 1.66 ± 0.39, p = 0.054). However, TDI‐derived parameters revealed significant differences: E' velocity was significantly lower in Group 1 compared to Group 2 (11.5 ± 2.5 vs. 12.3 ± 2.7 cm/s, p = 0.001), indicating impaired early diastolic myocardial relaxation in women with higher parity. The E/e' ratio, although numerically higher in Group 1, did not reach statistical significance (8.2 ± 2.2 vs. 7.9 ± 2.1, p = 0.112).
TABLE 2.
Comparison of characteristics between groups based on parity stratification: unadjusted and adjusted analyses.
| Unadjusted comparisons | |||
|---|---|---|---|
| Parameter | Group 1 (≥ 4 pregnancies), n = 274 (mean ± SD) | Group 2 (< 4 pregnancies), n = 331 (mean ± SD) | Unadjusted p value |
| Demographic and obstetric variables | |||
| Age (years) | 34.1 ± 5.6 | 28.2 ± 7.1 | < 0.001 |
| Gestational age at assessment (weeks) a | 29.9 ± 1.2 | 29.8 ± 1.3 | 0.523 |
| BMI (kg/m2) | 28.1 ± 4.4 | 26.7 ± 4.5 | < 0.001 |
| Number of pregnancies | 5.9 ± 1.5 | 2.1 ± 0.8 | < 0.001 |
| Number of deliveries | 5.0 ± 1.7 | 1.8 ± 0.9 | < 0.001 |
| Number of live births | 4.8 ± 1.6 | 1.8 ± 0.9 | < 0.001 |
| Number of abortions | 0.9 ± 1.2 | 0.3 ± 0.6 | < 0.001 |
| Hemodynamic parameters | |||
| Heart rate (bpm) | 89.6 ± 13.2 | 90.2 ± 13.7 | 0.584 |
| Systolic BP (mmHg) | 116.2 ± 11.9 | 115.1 ± 12.3 | 0.289 |
| Diastolic BP (mmHg) | 72.9 ± 9.5 | 71.8 ± 9.7 | 0.197 |
| Laboratory parameters | |||
| Haemoglobin (g/dL) | 11.6 ± 1.5 | 11.9 ± 1.3 | 0.067 |
| WBC (103/mm3) | 8.0 ± 3.1 | 7.7 ± 2.9 | 0.268 |
| NLR | 5.0 ± 2.6 | 5.0 ± 2.7 | 0.946 |
| Creatinine (mg/dL) | 0.64 ± 0.19 | 0.66 ± 0.21 | 0.324 |
| Sodium (mEq/L) | 138.8 ± 3.3 | 139.2 ± 3.1 | 0.183 |
| Potassium (mEq/L) | 4.3 ± 0.4 | 4.2 ± 0.4 | 0.412 |
| Echocardiographic parameters | |||
| Ejection fraction (%) | 63.3 ± 4.8 | 63.2 ± 4.6 | 0.821 |
| EDV (mL) | 98.6 ± 15.9 | 97.2 ± 15.2 | 0.301 |
| ESV (mL) | 44.3 ± 9.3 | 44.5 ± 9.0 | 0.812 |
| LVEDD (cm) | 4.53 ± 0.39 | 4.51 ± 0.41 | 0.587 |
| LVESD (cm) | 2.81 ± 0.32 | 2.79 ± 0.34 | 0.514 |
| IVSD (cm) | 0.93 ± 0.14 | 0.94 ± 0.60 | 0.821 |
| PWT (cm) | 0.88 ± 0.12 | 0.89 ± 0.11 | 0.396 |
| LA diameter (cm) | 3.4 ± 0.4 | 3.3 ± 0.4 | 0.152 |
| Fractional shortening (%) | 36.5 ± 4.3 | 36.2 ± 4.2 | 0.462 |
| E wave velocity (cm/s) | 91.3 ± 17.1 | 94.0 ± 16.3 | 0.065 |
| A wave velocity (cm/s) | 58.6 ± 12.1 | 57.4 ± 11.2 | 0.246 |
| E/A ratio | 1.59 ± 0.38 | 1.66 ± 0.39 | 0.054 |
| E' velocity (cm/s) | 11.5 ± 2.5 | 12.3 ± 2.7 | 0.001 |
| A' velocity (cm/s) | 7.4 ± 1.7 | 7.3 ± 1.6 | 0.553 |
| E/e' ratio | 8.2 ± 2.2 | 7.9 ± 2.1 | 0.112 |
| Global longitudinal strain (%) | −19.1 ± 2.5 | −20.5 ± 4.1 | < 0.001 |
| Impaired GLS (> −20%), n (%) | 118 (43.1%) | 80 (24.2%) | < 0.001 |
| Multivariable‐adjusted analysis for global longitudinal strain | |||
|---|---|---|---|
| Continuous parity analysis | |||
| Variable | β coefficient | 95% CI | p |
| Number of pregnancies (per pregnancy) | 0.21 | 0.13 to 0.29 | < 0.001 |
| Age (per year) | 0.06 | 0.02 to 0.10 | 0.004 |
| Model statistics: R 2 = 0.076, adjusted R 2 = 0.073, F = 24.76, p < 0.001 | |||
| Categorical parity analysis (primary adjusted results) | |||
|---|---|---|---|
| Variable | β coefficient | 95% CI | p |
| High parity (≥ 4 vs < 4 pregnancies) | 1.18 | 0.52 to 1.84 | < 0.001 |
| Age (per year) | 0.06 | 0.02 to 0.10 | 0.004 |
| BMI (per kg/m2) | 0.08 | 0.02 to 0.14 | 0.012 |
| Systolic BP (per mmHg) | 0.02 | −0.01 to 0.04 | 0.189 |
| Diastolic BP (per mmHg) | 0.03 | −0.01 to 0.06 | 0.156 |
| Model statistics: R 2 = 0.104, adjusted R 2 = 0.089, F = 11.94, p < 0.001 | |||
Note: Interpretation: After adjusting for age, BMI and blood pressure, women with ≥ 4 pregnancies had GLS values 1.18 units higher (worse, less negative) compared to women with < 4 pregnancies (95% CI: 0.52–1.84, p < 0.001). This adjusted difference is comparable to the unadjusted difference of 1.4 units shown in Part A, indicating that confounding by age, BMI and blood pressure was minimal.
Abbreviations: BMI, body mass index; BP, blood pressure; CI, confidence interval; EDV, end‐diastolic volume; ESV, end‐systolic volume; GLS, global longitudinal strain; IVSD, interventricular septum diameter; LA, left atrium; LVEDD, left ventricular end‐diastolic diameter; LVESD, left ventricular end‐systolic diameter; NLR, neutrophil‐to‐lymphocyte ratio; PWT, posterior wall thickness; WBC, white blood cell.
All participants were assessed at a standardized gestational window of 28–32 weeks to minimize hemodynamic confounding.
The primary outcome, GLS, showed a highly significant difference between the groups. Women in Group 1 had significantly worse GLS compared to Group 2 (−19.1% ± 2.5% vs. −20.5% ± 4.1%, p < 0.001). This 1.4% absolute difference represents a clinically meaningful impairment in longitudinal myocardial deformation. When categorised by normal versus abnormal GLS (cut‐off −20%), 43.1% of women in Group 1 had impaired GLS (> −20%) compared to 24.2% in Group 2 (p < 0.001).
After adjusting for potential confounders in multivariable linear regression (age, BMI, systolic blood pressure and diastolic blood pressure), high parity (≥ 4 pregnancies) remained independently associated with worse GLS (β = 1.18, 95% CI: 0.52–1.84, p < 0.001). Age (β = 0.06/year, 95% CI: 0.02–0.10, p = 0.004) and BMI (β = 0.08 per kg/m2, 95% CI: 0.02–0.14, p = 0.012) also showed independent associations with GLS, while blood pressure parameters were not significant predictors. The model explained 8.9% of GLS variance (adjusted R 2 = 0.089, F = 11.94, p < 0.001). Full unadjusted and adjusted comparisons are presented in Table 2.
3.1. Subgroup Analysis
When stratified by age groups, the relationship between high parity and reduced GLS remained consistent: in women ≤ 30 years, GLS was −19.5% ± 2.8% in high parity versus −20.7% ± 4.2% in low parity (p = 0.012); in women 31–40 years, −18.9% ± 2.3% versus −20.2% ± 3.9% (p = 0.001); and in women > 40 years, −18.4% ± 2.1% versus −19.8% ± 3.7% (p = 0.047). The interaction between age and parity on GLS was statistically significant (p for interaction = 0.031), suggesting that the impact of higher parity on myocardial strain may be more pronounced in older age groups (Table S1).
In a subset analysis of 274 multiparous women with ≥ 4 pregnancies, women with shorter interpregnancy intervals (< 18 months, n = 94) had worse GLS compared to those with longer intervals (≥ 18 months, n = 180) (−18.6% ± 2.3% vs. −19.4% ± 2.5%, p = 0.012), suggesting that insufficient recovery time between pregnancies may contribute to the cumulative myocardial burden (Table S2).
4. Discussion
4.1. Main Findings
This prospective cross‐sectional study of 605 healthy pregnant women without CVD or risk factors demonstrates that parity is independently associated with subclinical left ventricular systolic dysfunction as assessed by GLS, despite preservation of conventional systolic function. The principal findings are: (1) each additional pregnancy was associated with a 0.21‐unit worsening in GLS independent of age (β = 0.21, 95% CI: 0.13–0.29, p < 0.001); (2) after adjusting for age, BMI and blood pressure, higher parity (≥ 4 pregnancies) remained independently associated with reduced GLS (β = 1.18, 95% CI: 0.52–1.84, p < 0.001), with the adjusted effect size comparable to the unadjusted difference, indicating minimal confounding; (3) women with ≥ 4 pregnancies had significantly worse GLS (mean difference 1.4%, −19.1% ± 2.5% vs. −20.5% ± 4.1%, p < 0.001), with 43.1% versus 24.2% exceeding the −20% threshold; (4) the parity–strain relationship is modified by maternal age (p for interaction = 0.031), with more pronounced effects in older women; and (5) among multiparous women, shorter interpregnancy intervals (< 18 months) are associated with worse GLS (p = 0.012).
A critical observation is that conventional echocardiographic parameters including LVEF showed no associations with parity despite significant parity‐related differences in GLS. This dissociation between preserved LVEF and impaired GLS is consistent with the well‐established principle that strain imaging detects myocardial dysfunction earlier than conventional parameters [16, 17]. LVEF has inherent limitations in sensitivity, as it relies on geometric assumptions and is influenced by loading conditions and compensatory mechanisms [18, 19]. GLS, by contrast, directly quantifies myocardial deformation with less dependence on geometric assumptions [20, 21]. In our cohort, 32.4% of women had GLS values > −20% despite universally preserved LVEF, highlighting the prevalence of subclinical dysfunction that would be missed by conventional assessment alone. Significant differences in E' velocity (11.5 vs. 12.3 cm/s, p = 0.001) further suggest concurrent effects on diastolic myocardial relaxation in higher parity women, consistent with the concept that diastolic dysfunction often precedes systolic impairment in early cardiac stress [22, 23].
4.2. Strengths and Limitations
This study has several strengths. The large sample size provides robust statistical power to detect associations and define thresholds. Strict inclusion and exclusion criteria, specifically excluding women with CVD or risk factors, allow isolation of the effects of parity on cardiac function independent of comorbidities. Standardisation of echocardiographic assessment timing (28–32 weeks gestation) minimises confounding from gestational age‐related haemodynamic variations. The excellent intra‐observer reproducibility (ICC = 0.94, coefficient of variation 2.7%) confirms that our GLS measurements were highly consistent, and the observed between‐group difference (1.4%) substantially exceeds measurement variability, ensuring that our findings reflect true biological differences rather than measurement error.
Several limitations should be acknowledged. The cross‐sectional design prevents definitive conclusions about causality or temporal relationships. We did not have pre‐pregnancy or postpartum echocardiographic data, limiting our ability to assess whether changes are persistent or reversible. The study was conducted at a single centre, which may limit generalisability.
Several technical and operator‐dependent factors influence the reproducibility of speckle‐tracking echocardiography. Inter‐vendor variability in strain algorithms, which can amount to up to 3.7 strain units across vendors [24], operator experience, image quality and frame‐rate settings with frame rates below 30 frames per cycle, shown to systematically underestimate longitudinal strain [24], can all affect strain measurements. In pregnant women specifically, additional extrinsic mechanical factors, particularly anterior chest wall deformity due to breast tissue and the gravid uterus, as illustrated by the attenuating effect of chest wall structural deformities such as pectus excavatum on STE‐derived strain indices [25], may further influence strain quantification. We attempted to minimise these sources of variability through standardised imaging protocols, a single ultrasound system (GE Healthcare), consistent frame rates (60–90 fps) and offline analysis by a single experienced investigator. However, the potential impact of these technical factors cannot be entirely eliminated, and this should be considered when interpreting our results.
We cannot exclude residual confounding by unmeasured factors such as nutrition, physical activity, socioeconomic status and genetic predisposition, which were not systematically assessed. The interpregnancy interval analysis was limited to women with ≥ 4 pregnancies and relied on self‐reported dates, which may introduce recall bias. We used a strain threshold (−20%) derived primarily from non‐pregnant populations; pregnancy‐specific normative values continue to evolve. Future studies with postpartum follow‐up are needed to determine whether these changes persist, normalise or predict adverse outcomes.
4.3. Interpretation
The cumulative haemodynamic burden of repeated pregnancies has been hypothesised to contribute to long‐term cardiovascular remodelling [26, 27]. Each pregnancy subjects the maternal cardiovascular system to substantial physiological stress, with cardiac output increasing by 30%–50% and blood volume expanding by approximately 40%–50% [28, 29]. While these adaptations are reversible in most women, incomplete recovery between pregnancies or cumulative volume loading may lead to persistent structural and functional alterations [30, 31]. Our findings provide direct evidence of measurable changes in myocardial mechanics with increasing parity, aligning with epidemiological data linking higher parity to increased cardiovascular morbidity in later life [32, 33].
The mean GLS in our study population (−19.9% ± 3.6%) and values in the high parity group (−19.1% ± 2.5%) remain within the physiological range expected for pregnant women in the third trimester, consistent with published British Society of Echocardiography guidance [34]. However, the consistent shift toward lower GLS values in multiparous women, the graded relationship per pregnancy (β = 0.21) and the finding that 43.1% of high parity women exceed the −20% threshold all warrant clinical attention and raise questions about whether further pregnancies or long‐term cardiovascular ageing may push these values into pathological ranges.
The significant interaction between age and parity on GLS (p = 0.031) suggests that the impact of higher parity may be amplified in older women, likely reflecting reduced cardiovascular reserve and cumulative ageing processes superimposed on repeated pregnancy‐related haemodynamic stress [35, 36]. Regarding interpregnancy interval, women with intervals < 18 months had significantly worse GLS, extending the concept of interpregnancy interval as a modifiable cardiovascular risk factor [37, 38] and suggesting that myocardial recovery may require substantial time. International guidelines generally recommend waiting at least 18–24 months between pregnancies; our data suggest cardiovascular considerations may support these recommendations [39, 40].
Higher parity should be recognised as one component of comprehensive cardiovascular risk assessment in pregnant women, alongside age, obesity and hypertension. While routine strain imaging in all multiparous women is not justified on current evidence alone, older women with high parity or closely‐spaced pregnancies may warrant closer cardiovascular monitoring during and after pregnancy.
5. Conclusion
This prospective cross‐sectional study demonstrates that parity is independently associated with myocardial strain in a dose–response manner, with each additional pregnancy contributing to progressive reduction in GLS despite preservation of conventional echocardiographic measures including ejection fraction. The relationship is modified by maternal age and interpregnancy interval, with more pronounced effects in older women and those with shorter intervals between pregnancies. Speckle‐tracking‐derived GLS emerges as a valuable tool for detecting parity‐related myocardial changes that would be missed by conventional assessment alone. Longitudinal studies with postpartum follow‐up are needed to determine whether these strain abnormalities persist, predict adverse outcomes in subsequent pregnancies or later life, and whether optimising cardiovascular health between pregnancies can attenuate the cumulative effects of multiparity.
Author Contributions
Ö.K., İ.U. and A.F.K. conceived and designed the study. Ö.K., İ.U., V.C., G.A. and E.Ö. performed data collection and extraction from electronic health records. F.P. conducted the statistical analyses and drafted the initial manuscript. F.P. V.C. and A.F.K. critically revised the manuscript for important intellectual content. Ö.K., İ.U., A.F.K., Ö.K. and V.C. supervised the study and provided senior oversight. All authors contributed to data interpretation, reviewed and approved the final manuscript, and agree to be accountable for all aspects of the work.
Funding
The authors have nothing to report.
Ethics Statement
The study was approved by the Van Training and Research Hospital Non‐Interventional Clinical Research Ethics Committee with the decision number 2022/20‐05 on 21 September 2022.
Consent
Written informed consent was obtained from all participants prior to enrolment after they received detailed verbal and written information about the study objectives, procedures, potential risks, and benefits. Participants were informed that their involvement was voluntary, that they could withdraw at any time without affecting their clinical care, and that anonymised study results may be published in scientific journals or presented at medical conferences. No individually identifiable patient information is disclosed in this publication. This prospective study was conducted in accordance with the principles of the Declaration of Helsinki, and the study protocol was approved by the institutional ethics committee. All data are aggregated or de‐identified and handled confidentially in accordance with institutional data protection policies.
Conflicts of Interest
The authors declare no conflicts of interest.
Supporting information
Table S1: Subgroup analysis of GLS by age and parity.
Table S2: Effect of interpregnancy interval on GLS in high parity women.
Acknowledgements
The authors used AI for language editing and minor grammatical corrections during the preparation of this manuscript. The AI tool was not used for study design, data collection, statistical analysis, interpretation of results or generation of core scientific content. After using this tool for language refinement, the authors reviewed and edited the content as needed and take full responsibility for the content of the publication. All scientific content, data analysis and conclusions represent the independent work and judgement of the authors. The research presented in this manuscript does not involve the development or utilisation of any custom software applications or specific code. As such, there is no code availability associated with this study. The analysis and findings rely on standard statistical methods and commercially available software tools (SPSS version 25.0).
Data Availability Statement
All relevant data supporting the findings of this study are available upon request and will be provided by the corresponding author. The research presented in this manuscript does not involve the development or utilisation of any custom software applications or specific code. As such, there is no code availability associated with this study. The analysis and findings rely on standard statistical methods and commercially available software tools. For any inquiries related to the methodology or data analysis, please contact the corresponding author.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Table S1: Subgroup analysis of GLS by age and parity.
Table S2: Effect of interpregnancy interval on GLS in high parity women.
Data Availability Statement
All relevant data supporting the findings of this study are available upon request and will be provided by the corresponding author. The research presented in this manuscript does not involve the development or utilisation of any custom software applications or specific code. As such, there is no code availability associated with this study. The analysis and findings rely on standard statistical methods and commercially available software tools. For any inquiries related to the methodology or data analysis, please contact the corresponding author.