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Research Article | Volume 15 Issue 7 (July, 2025) | Pages 16 - 19
Association of Maternal and Cord Blood Lipid Levels with Intrauterine Growth Retardation: A Tertiary Care Hospital Based Case Control Study
 ,
1
Assistant Professor, Department of Obstetrics and Gynaecology, Jorhat Medical College and Hospital, Jorhat, Assam, India.
2
Third Year Postgraduate Trainee, Department of Obstetrics and Gynaecology, Tezpur Medical College and Hospital, Tezpur, Assam, India.
Under a Creative Commons license
Open Access
Received
May 13, 2025
Revised
June 21, 2025
Accepted
June 26, 2025
Published
July 3, 2025
Abstract

Background: Intrauterine Growth Restriction (IUGR) is a significant obstetric complication characterized by fetal growth below the 10th percentile for gestational age, leading to increased perinatal morbidity and mortality. Abnormal maternal lipid metabolism has been implicated in its pathogenesis. Objective: To assess the association between maternal and cord blood lipid profiles and IUGR in pregnant women at a tertiary care hospital. Methods: Sample size was calculated using the formula for comparison of two means: N = [(Z₁-α/2 + Z₁-β)² × (SD₁² + SD₂²)] / d² Based on Kwaeri et al., with SD₁ = 20.3 mg/dL, SD₂ = 14.8 mg/dL, and d = 10 mg/dL, the sample size was 49.8 per group (rounded to 50), totaling 100 participants. Consecutive sampling was employed. This analytical observational case-control study included 100 pregnant women (50 with IUGR and 50 controls with adequate-for-gestational-age fetuses). Maternal fasting blood samples were collected during the third trimester, and cord blood samples were obtained immediately after delivery. Lipid profiles, including total cholesterol, triglycerides, HDL, LDL, and VLDL, were analyzed. Statistical comparisons were performed using Student’s t-test and Chi-square test, with p < 0.05 considered significant. Results: Maternal cholesterol, triglycerides, LDL, and VLDL levels were significantly higher, and HDL levels were lower in the IUGR group compared to controls (p < 0.001). Similarly, cord blood from IUGR neonates showed elevated triglycerides and VLDL, and reduced cholesterol and HDL levels (p < 0.05). Lower maternal BMI and shorter gestational age were also associated with IUGR. Conclusion: Abnormal maternal and fetal lipid profiles are strongly associated with IUGR, suggesting dyslipidemia’s role in its pathophysiology. Early lipid screening and nutritional interventions during pregnancy may reduce IUGR risk and improve neonatal outcomes.

Keywords
INTRODUCTION

Intrauterine Growth Restriction (IUGR) is a significant obstetric complication defined as fetal weight below the 10th percentile for gestational age.[1] It is associated with increased perinatal mortality, neonatal complications, and long-term metabolic and cardiovascular conditions.[2,3] IUGR is multifactorial, often caused by placental insufficiency, maternal hypertension, malnutrition, and socioeconomic disparities-factors prevalent in low- and middle-income countries such as India.[4] Assam, in particular, has a high burden of IUGR due to widespread maternal health issues and undernutrition.[5]

 

Pregnancy induces physiological changes in lipid metabolism, especially during the third trimester, with increases in maternal cholesterol, triglycerides, and lipoproteins.[6] While these alterations are necessary for fetal development, abnormal maternal lipid profiles-such as elevated triglycerides and low HDL-are associated with adverse outcomes like IUGR.[7,8] Altered cord blood lipid levels in IUGR cases may reflect intrauterine dyslipidemia, potentially increasing future metabolic disease risk.[9]

 

This study aims to assess the relationship between maternal and cord blood lipid profiles and IUGR, investigating pathophysiological mechanisms such as placental dysfunction, oxidative stress, and impaired angiogenesis.[10]

MATERIALS AND METHODS

An analytical observational study conducted in the Department of Obstetrics and Gynecology, Tezpur Medical College and Hospital for a period of one year following institutional ethical approval.

 

Study Population

Pregnant women presenting to the outpatient and emergency departments.

 

Inclusion Criteria

  • Women aged 18–35 years
  • Singleton pregnancies in the third trimester
  • Diagnosed cases of IUGR and normal pregnancies

 

Exclusion Criteria

  • Established dyslipidemia
  • Chronic diseases (e.g., hypertension, diabetes)
  • Multiple pregnancies
  • Chromosomal or major structural abnormalities
  • Smoking history
  • Age >35 years
  • Declined consent

 

Sample Size and Sampling Technique

Sample size was calculated using the formula for comparison of two means: N = [(Z₁-α/2 + Z₁-β)² × (SD₁² + SD₂²)] / d² Based on Kwaeri et al., with SD₁ = 20.3 mg/dL, SD₂ = 14.8 mg/dL, and d = 10 mg/dL, the sample size was 49.8 per group (rounded to 50), totaling 100 participants. Consecutive sampling was employed.

 

Ethical Considerations

Institutional Ethics Committee approval was obtained. Participants were informed in their native language about the study, their rights, voluntary participation, data confidentiality, and the ability to withdraw anytime.

 

Study Procedure

A total of 100 pregnant women were enrolled and divided into two groups: 50 IUGR and 50 adequate-for-gestational-age (AGA) pregnancies. Clinical evaluations were recorded in a structured proforma. Maternal fasting blood samples were collected in the third trimester before labor or delivery. Cord blood was drawn immediately after delivery from the clamped umbilical cord.

 

Blood samples were processed within one hour. Investigations included lipid profile (total cholesterol, triglycerides, HDL, LDL, VLDL), complete blood count, liver/kidney function, blood sugar, urine analysis, infection screening (HIV, VDRL, HBsAg, HCV), and ultrasound with Doppler.

 

Data Analysis

Data were entered into MS Excel and analyzed using SPSS version 22. Descriptive statistics (mean ± SD, percentages) were used. Inferential statistics included Chi-square tests for categorical data and Student's t-test for continuous variables. A p-value <0.05 was considered statistically significant. Data were anonymized and stored in a password-protected file.

RESULTS

Age

IUGR

Control

p-value

Mean ± SD

24.3 ± 4.6

24.8 ± 5.2

0.992

The difference in mean age between the two groups was not statistically significant (p = 0.992), indicating no age-related bias between the IUGR and control groups.

 

 

 

Table 1: Age Distribution

 

Parity

IUGR

Control

p-value

Primi

28 (56%)

32 (64%)

0.675

2

12 (24%)

11 (22%)

 

>2

10 (20%)

7 (14%)

 

Table 2: Parity Distribution

 

The differences in parity distribution were not statistically significant (p = 0.675), suggesting parity did not significantly impact the occurrence of IUGR in this study.

 

Group

Mean ± SD

p-value

IUGR

23.6 ± 3.8

0.042*

Control

25.4 ± 4.9

 

Table 3: BMI (kg/m²)

 

The difference was statistically significant (p = 0.042), indicating that lower BMI was associated with IUGR, which might reflect the role of maternal nutritional status in fetal growth.

 

Group

Mean ± SD

p-value

IUGR

37.2 ± 2.5

<0.001*

Control

39.6 ± 3.1

 

Table 4: Gestational Age (weeks)

 

The mean gestational age was 37.2 weeks (SD = 2.5) in the IUGR group and 39.6 weeks (SD = 3.1) in the control group. The difference was statistically significant (p < 0.001).

 

Parameter

IUGR

Control

p-value

Symphysio-fundal height (cm)

28.1 ± 2.8

32.4 ± 1.5

<0.001*

Head circumference (cm)

29.4 ± 1.8

31.4 ± 2.3

<0.001*

Abdominal circumference (cm)

24.6 ± 1.7

29.7 ± 1.9

<0.001*

Femur length (cm)

6.2 ± 0.7

7.4 ± 0.3

<0.001*

Table 5. Ultrasound and Clinical Parameters

 

The mean symphysio-fundal height, head circumference, abdominal circumference, and femur length were significantly lower in the IUGR group compared to the control group.

 

Group

Mean ± SD

p-value

IUGR

2.01 ± 0.3

0.002*

Control

2.74 ± 1.3

 

Table 6: Birth Weight (kg)

 

This difference was statistically significant (p = 0.002), confirming the reduced growth potential of IUGR fetuses.

 

Group

Mean ± SD

p-value

IUGR

8.3 ± 0.5

<0.001*

Control

8.8 ± 0.4

 

Table 7: APGAR score at 5 Minutes

 

The mean APGAR score at 5 minutes was 8.3 in the IUGR group and 8.8 in the control group, with a statistically significant difference (p < 0.001).

 

Parameter

IUGR

Control

p-value

Cholesterol (mg/dL)

211.3 ± 18.4

191.4 ± 15.2

<0.001*

Triglycerides (mg/dL)

226.6 ± 25.2

171.3 ± 21.9

<0.001*

HDL (mg/dL)

35.2 ± 2.2

46.0 ± 6.3

<0.001*

LDL (mg/dL)

132.5 ± 14.2

122.8 ± 12.1

<0.001*

VLDL (mg/dL)

44.2 ± 7.8

34.6 ± 6.9

<0.001*

Table 8: Maternal Lipid Profile

 

The mean maternal cholesterol, triglycerides, and VLDL levels were significantly higher in the IUGR group compared to the control group, while HDL levels were significantly lower.

 

Parameter

IUGR

Control

p-value

Cholesterol (mg/dL)

63.7 ± 2.6

71.6 ± 3.5

<0.001*

Triglycerides (mg/dL)

34.2 ± 6.3

22.9 ± 5.8

<0.001*

HDL (mg/dL)

11.2 ± 2.3

14.7 ± 2.4

<0.001*

LDL (mg/dL)

53.1 ± 7.2

56.9 ± 9.4

0.025*

VLDL (mg/dL)

13.4 ± 4.1

8.4 ± 5.6

<0.001*

Table 9: Cord Blood Lipid Profile

 

The cord blood lipid profile in the IUGR group showed significantly lower cholesterol and HDL levels and higher triglycerides and VLDL levels compared to the control group.

DISCUSSION

Principal Findings

This case-control study demonstrated significant dyslipidemia in both maternal and fetal circulations in pregnancies affected by IUGR. Elevated maternal triglycerides, cholesterol, LDL, and VLDL accompanied by low HDL levels were observed. Likewise, fetal cord blood showed decreased cholesterol and HDL, alongside raised triglycerides and VLDL. These findings support the hypothesis that maternal dyslipidemia may compromise placental lipid transport and metabolism, contributing to fetal growth restriction. [11,12]

 

Comparison with Literature

The maternal lipid disturbances observed in our study are consistent with prior findings. Jadhao et al. reported significantly elevated LDL and total cholesterol in IUGR and preeclampsia cases compared to normal pregnancies¹³. Similarly, Pecks et al. documented decreased HDL and total cholesterol in the cord blood of IUGR neonates, reflecting impaired fetal lipid homeostasis.[9]

 

Sociodemographic variables such as maternal age and parity did not differ significantly between groups, aligning with studies by Rodie et al. and Pecks et al., which reported similar maternal age distributions in IUGR and control groups. [14,15] In our study, the mean maternal age was 24.3 years in the IUGR group and 24.8 in the control group-lower than Western populations but consistent with Indian cohorts.

 

The significantly lower BMI observed in the IUGR group (mean 23.6 kg/m²) echoes results by Abraham et al., who found that underweight and normal-weight women were more likely to deliver IUGR babies, suggesting maternal nutritional status as a key modifiable risk factor.[16] The shorter mean gestational age in the IUGR group (37.2 weeks vs. 39.6 weeks) was statistically significant, reinforcing previous reports that metabolic disturbances may increase the risk of preterm delivery.[17] A recent Indian study by Sushilendu et al. also observed increased preterm birth rates in IUGR cases, attributed to placental dysfunction and systemic inflammation.[18]

 

Strengths and Limitations

Strengths of this study include the dual assessment of maternal and fetal lipid parameters, providing insight into transplacental lipid dynamics. The use of strict inclusion/exclusion criteria and standardized laboratory protocols enhances internal validity.

 

Limitations include the single-center design, which may limit external validity. The cross-sectional nature prevents causal inference. Additionally, placental histopathology and long-term neonatal follow-up were not included, which could have provided mechanistic and prognostic insights.

 

Clinical Implications

Routine lipid profiling during pregnancy, especially in the third trimester, could help identify women at elevated risk for IUGR. Nutritional counseling and lipid-lowering interventions may enhance placental function and fetal growth. However, any intervention must be evidence-based and carefully evaluated for safety in pregnant populations.[19]

 

Future Directions

Future multicentric longitudinal studies are needed to determine whether maternal lipid-modifying strategies improve fetal outcomes. Integration of placental biomarkers, maternal insulin sensitivity profiles, and postnatal growth tracking could enhance the understanding of the developmental origins of health and disease.[20]

CONCLUSION

This study identified a strong association between abnormal maternal lipid levels and intrauterine growth restriction. Pregnancies affected by IUGR exhibited elevated levels of cholesterol, triglycerides, and VLDL and decreased HDL in both maternal and neonatal cord blood. These findings suggest that maternal dyslipidemia may impair placental function and fetal development. Additionally, lower maternal BMI was linked to increased IUGR risk. Early lipid profile screening and nutritional support in pregnancy may help prevent IUGR and improve long-term neonatal health outcomes.

REFERENCES
  1. ACOG Practice Bulletin No. 227: fetal growth restriction. Obstet Gynecol 2021;137(2):e16-e28.
  2. Baschat AA. Fetal growth restriction-from observation to intervention. J Perinat Med 2010;38(3):239-46.
  3. Barker DJ. The developmental origins of adult disease. J Am Coll Nutr 2004;23(6 Suppl):588S-95.
  4. Black RE, Victora CG, Walker SP, et al. Maternal and child undernutrition and overweight in low-income and middle-income countries. Lancet 2013;382(9890):427-51.
  5. Bora JK, Saikia N. Neonatal and under-five mortality rate in Indian states: Trends and determinants. Indian J Pediatr 2018;85(6):454-60.
  6. Herrera E, Ortega-Senovilla H. Lipid metabolism during pregnancy and its implications for fetal growth. Curr Pharm Biotechnol 2014;15(1):24-31.
  7. Enquobahrie DA, Williams MA, Butler CL, et al. Maternal plasma lipid concentrations in early pregnancy and risk of preeclampsia. Am J Hypertens 2004;17(7):574-81.
  8. Wiznitzer A, Mayer A, Novack V, et al. Association of lipid levels during gestation with preeclampsia and gestational diabetes mellitus: a population-based study. Am J Obstet Gynecol 2009;201(5):482.e1-8.
  9. Pecks U, Bräsen JH, Schiessl B, et al. Maternal and fetal cord blood lipids in intrauterine growth restriction. J Perinat Med 2012;40(3):287-96.
  10. Roberts JM, Escudero C. The placenta in preeclampsia. Pregnancy Hypertens 2012;2(2):72-83.
  11. Kulkarni AV, Mehendale SS, Yadav HR, et al. Circulating angiogenic factors and their association with birth outcomes in preeclampsia and normotensive pregnancy. Hypertens Pregnancy 2012;31(3):335-47.
  12. Herrera E, Ortega-Senovilla H. Disturbances in lipid metabolism in diabetic pregnancy-are these the cause of the problem? Best Pract Res Clin Endocrinol Metab 2010;24(4):515-25.
  13. Jadhao V, Deshmukh J, Ughade S. Study of lipid profile in pre-eclampsia and eclampsia. J Obstet Gynaecol India 2016;66(5):349-54.
  14. Rodie VA, Freeman DJ, Sattar N, et al. Pre-eclampsia and cardiovascular disease: Metabolic syndrome of pregnancy? Atherosclerosis 2004;175(2):189-202.
  15. Pecks U, Brieger M, Schiessl B, et al. Maternal and fetal cord blood lipids in intrauterine growth restriction. J Perinat Med 2012;40(3):287-96.
  16. Abraham A, Mirghani HM, Al-Ali A. Influence of maternal body mass index on pregnancy outcome and newborn birth weight. J Med Sci 2018;18(2):92-7.
  17. Chen XK, Wen SW, Yang Q, et al. Maternal age and risk of preterm birth: a systematic review and meta-analysis. BMC Pregnancy Childbirth 2007;7:17.
  18. Sushilendu C, Meena S, Rai S. Maternal serum lipid profile in IUGR: an observational study in a tertiary care center. Int J Reprod Contracept Obstet Gynecol 2022;11(2):462-7.
  19. Duttaroy AK. Transport of fatty acids across the human placenta: a review. Prog Lipid Res 2009;48(1):52-61.
  20. Godfrey KM, Gluckman PD, Hanson MA. Developmental origins of metabolic disease: Life course and intergenerational perspectives. Trends Endocrinol Metab 2010;21(4):199-205.
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