Abstract
Abstract
Objectives
To compare birth weight-to-placental weight (BW:PW) ratios between pregnancies complicated by gestational diabetes mellitus (GDM) and normoglycaemic pregnancies, and to evaluate the associations between BW:PW ratio, perinatal outcomes, and placental histopathologic features within the GDM group.
Design
A prospective cohort study.
Setting
A university hospital in Bangkok, Thailand.
Participants
A total of 200 women with GDM and 100 normoglycaemic controls.
Outcome measures
BW:PW ratios were calculated and compared between the two groups. Participants with GDM were stratified into three categories based on the BW:PW ratio percentiles: <10th, 10th–90th and >90th. Perinatal outcomes and placental histological abnormalities were analysed across these categories.
Results
Median BW:PW ratios were not significantly different between the GDM and normoglycaemic groups: 6.3 (IQR 5.6 to 6.9) versus 6.2 (IQR 5.6 to 6.8); p=0.399. Within the GDM cohort, the BW:PW ratio cut-offs corresponding to the 10th and 90th percentiles were 5.2 and 7.6, respectively. The prevalence of small-for-gestational-age (SGA) neonates differed significantly among the three BW:PW ratio groups: 14.3% (<10th), 1.3% (10th–90th) and 4.5% (>90th); p=0.004. Similarly, the prevalence of chorangiosis varied significantly across these groups (66.7%, 52.9% and 22.7%, respectively; p=0.009). A BW:PW ratio <10th percentile was associated with an increased risk of SGA neonates (adjusted OR (aOR) 9.94; 95% CI 1.14 to 86.80), while a ratio >90th percentile was associated with reduced odds of chorangiosis (aOR 0.35; 95% CI 0.11 to 0.85).
Conclusions
BW:PW ratios did not differ significantly between the GDM and normoglycaemic groups. However, in GDM pregnancies, extremes in the BW:PW ratio were associated with distinct perinatal and placental outcomes, indicating altered placental efficiency and potential clinical relevance.
Trial registration number
TCTR20211122001.
Keywords: Diabetes in pregnancy, OBSTETRICS, Pregnancy
STRENGTHS AND LIMITATIONS OF THIS STUDY.
This study’s prospective design allowed for consistent and high-quality data collection, thereby strengthening the reliability of the findings.
Including both gestational diabetes mellitus (GDM) and normoglycaemic pregnancies enabled direct comparisons, helping to clarify the specific impact of GDM on placental efficiency.
The integrated analysis of placental histology and perinatal outcomes revealed novel associations between the birth weight-to-placental weight (BW:PW) ratio, chorangiosis and the risk of small-for-gestational-age births.
Small subgroup sizes in the <10th and >90th percentile BW:PW categories may have limited the statistical power to detect less common outcomes.
Overrepresentation of mild (A1) GDM cases in this study may limit the generalisability of findings to more severe forms of GDM.
Introduction
The placenta is a vital organ that facilitates the transport of nutrients and oxygen essential for foetal development. Serving as the critical interface between maternal and foetal systems, it regulates immune tolerance and maintains an optimal environment for foetal growth.1 Given its central role in supporting the pregnancy, any dysfunction or abnormality in placental development can have a profound effect on pregnancy outcomes.
In light of its essential functions, assessing how well the placenta supports foetal growth becomes crucial. Placental efficiency refers to this capability and is typically measured by the amount of foetal mass produced per unit of placental mass.2 This metric serves as an important indicator of key placental functions, particularly the delivery of nutrients to the fetus. One widely used marker of placental efficiency is the birth weight-to-placental weight (BW:PW) ratio.3 A higher BW:PW ratio suggests that more foetal growth is achieved per gram of placental tissue, indicating better placental performance. Conversely, a lower ratio may reflect impaired placental function, which has been associated with adverse outcomes such as foetal growth restriction (FGR) and small-for-gestational-age (SGA) infants.3
One condition that may significantly impact placental efficiency is gestational diabetes mellitus (GDM), a common medical complication of pregnancy characterised by glucose intolerance first recognised during gestation.4 The resulting hyperglycaemic intrauterine environment can adversely affect both placental structure and function,5 6 potentially contributing to foetal growth abnormalities and other adverse perinatal outcomes. In pregnancies complicated by GDM, both the foetal and placenta are often enlarged; however, the placenta tends to grow disproportionately more than the fetus, resulting in a lower BW:PW ratio.7,9
While low BW:PW ratios have been linked to adverse outcomes such as FGR, low Apgar scores and neonatal intensive care unit (NICU) admission,10,12 their association with perinatal outcomes in GDM pregnancies remains underexplored. Given the distinct metabolic and placental environment in GDM, evaluating the BW:PW ratio in this context may provide valuable insights into associated perinatal risks.
The primary objective of this study was to compare the BW:PW ratio between pregnancies complicated by GDM and those with normoglycaemic pregnancies, and to evaluate its association with perinatal outcomes in women with GDM. Additionally, we examined whether specific placental histological features were linked to variations in the BW:PW ratio.
Methods
Study design and population
This prospective observational cohort study was conducted as part of the Placenta in Gestational Diabetes Mellitus (PL-GDM) project. Participants were recruited between December 2021 and May 2024 at the Faculty of Medicine Vajira Hospital, Navamindradhiraj University in Bangkok, Thailand. The cohort included pregnant women diagnosed with GDM—managed with either diet or insulin—according to the Carpenter and Coustan criteria,13 as well as women without GDM. The study was approved by the Institutional Review Board of our institution (approval no. 215/2564) and conducted in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology guidelines. Written informed consent was obtained from all participants before enrolment.
Participants with and without GDM were recruited consecutively and concurrently during routine antenatal visits. To be eligible, women had to be aged 18 years or older with a singleton pregnancy. For the analysis, only those who delivered at ≥37 weeks of gestation were included. Women were excluded if they had pre-existing type 1 or type 2 diabetes mellitus, chronic hypertension, HIV or syphilis infection, foetal congenital anomalies or missing placental pathology reports.
Sample size
As no previous studies had directly examined the association between the BW:PW ratio and perinatal outcomes in pregnancies complicated by GDM, the sample size was estimated using statistical data from the Department, based on 90 women with GDM who delivered at our institution in 2018. The review found a 22.2% prevalence of SGA infants among those with a BW:PW ratio below the 10th percentile. Using a two-sided alpha of 0.05 and allowing for a 20% margin of error, a minimum of 170 participants was required. This subproject used the same cohort of 300 women from the main PL-GDM study. Since the main study focused on GDM, the cohort comprised twice as many women with GDM as normoglycaemic controls.
GDM diagnosis and management
Screening for GDM at our institution has been described previously.14 Briefly, a glucose challenge test is performed at 24–28 weeks of gestation in women without risk factors, and at the initial visit with rescreening at 28–32 weeks in those with risk factors. A glucose challenge test result ≥140 mg/dL prompted a diagnostic 100-g oral glucose tolerance test.
Women with one or no abnormal values were classified as not having GDM, whereas GDM was diagnosed if ≥2 values met the Carpenter and Coustan criteria.13 Management of women with GDM, as well as those with only one abnormal value, included education on diet and lifestyle modification. In women with GDM, glycaemic control was assessed through daily self-monitoring of blood glucose and at hospital visits every 2–4 weeks, using fasting plasma glucose (FPG) and 2-hour postprandial measurements. Insulin therapy, prescribed by an endocrinologist, was initiated when FPG ≥95 mg/dL and/or postprandial glucose ≥120 mg/dL, considering adherence, gestational age (GA) at diagnosis, and the severity and frequency of abnormal values. Optimal glycaemic control was defined as more than 80% of testing results within target ranges; otherwise, it was classified as suboptimal.
Data collection and outcome assessment
Maternal demographic and clinical data, including maternal age, ethnicity, prepregnancy body mass index (BMI), parity and GDM class, were collected at enrolment. At delivery, GA, mode of delivery, infant sex and birth weight were recorded, with birth weight measured using a calibrated digital scale (Seca model 374; IDS Medical Systems, Samut Prakan, Thailand).
Placentas were collected immediately after delivery along with their attached umbilical cords. After fixation in 10% buffered formalin, placentas were trimmed to remove membranes and the umbilical cord, then weighed using a calibrated digital scale (PULISITE model PTX-5102; Provision Scientific, Bangkok, Thailand). The BW:PW ratio was calculated by dividing the infant’s birth weight (in g) by the trimmed placental weight (in g).
Histological examination was conducted according to the Amsterdam Placental Workshop Group Consensus Statement.15 Placental lesions of interest included both Amsterdam-classified abnormalities—maternal vascular malperfusion (MVM), foetal vascular malperfusion (FVM), histologic chorioamnionitis and villitis of unknown aetiology (VUE)—as well as two additional, non-classified lesions: chorangiosis and delayed villous maturation (DVM). MVM, FVM, histologic chorioamnionitis and VUE were diagnosed per the Amsterdam guidelines.15 16 Chorangiosis was defined as the presence of 10 or more capillaries in at least 10 terminal chorionic villi, observed in 10 or more non-infarcted areas across a minimum of three low-power microscopic fields of the placenta.17 DVM was characterised by a uniform population of 10 or more villi exhibiting centrally located capillaries and a marked reduction in vasculosyncytial membranes.15 This diagnosis was confirmed when such features were present in at least 30% of a full-thickness parenchymal slide.15 Each histological sample was independently assessed twice by a pathologist (CC) who was blinded to the patients’ diabetic status and perinatal outcomes. In cases of discrepancies, the slides were reviewed collaboratively with a second pathologist (ST) to reach consensus.
Perinatal outcomes included foetal heart rate (FHR) decelerations,18 SGA and large-for-gestational-age neonates (LGA) (defined as birth weight below the 10th percentile and above the 90th percentile, respectively, for GA based on Thai birth weight nomograms),19 low Apgar scores (<7 at 1 min), neonatal hypoglycaemia (per American Academy of Paediatrics criteria),20 respiratory distress syndrome (RDS), NICU admissions, and a composite adverse perinatal outcome, defined as the presence of any of the aforementioned seven outcomes.
Statistical analysis
All statistical analyses were conducted using SPSS V.28.0 (IBM, Armonk, New York, USA). Continuous variables for GDM and normoglycaemic pregnancies were presented as mean±SD or median (IQR), depending on distribution, and compared using the Student’s t-test or Mann-Whitney U test. Categorical variables were reported as frequencies and percentages and analysed using the χ2 test or Fisher’s exact test, as appropriate.
The BW:PW ratio was stratified into three groups based on its distribution: below the 10th percentile, between the 10th and 90th percentiles (reference group), and above the 90th percentile. Comparisons of continuous variables among these groups were performed using one-way analysis of variance, followed by posthoc testing with the least significant difference method. Categorical variables were compared using the χ2 or Fisher’s exact test, depending on data distribution.
Logistic regression analysis was used to evaluate the association between BW:PW ratio categories and both perinatal outcomes and placental abnormalities, adjusting for potential confounders including maternal age, prepregnancy BMI, parity, GA at delivery and infant sex. A p value of <0.05 was considered statistically significant.
Patient and public involvement
Patients and/or the public were not involved in the design, conduct, reporting or dissemination plans of this research.
Results
Study population characteristics
The study included 300 pregnant women of Thai or Southeast Asian ethnicity: 200 with GDM and 100 normoglycaemic controls. Participants with GDM were significantly older and had higher prepregnancy BMI than normoglycaemic women (table 1). GA at delivery was significantly lower in the GDM group, while no significant differences were seen in parity, mode of delivery, birth weight, infant sex distribution, placental weight or BW:PW ratio.
Table 1. Demographic and clinical characteristics of women with gestational diabetes mellitus and normoglycaemia.
| GDM | Normoglycaemia | P value | |
|---|---|---|---|
| (n=200) | (n=100) | ||
| Age (years) | 33.0±5.7 | 29.3±5.6 | <0.001 |
| Ethnicity | 0.619 | ||
| Thai | 174 (87.0) | 89 (89.0) | |
| Other Southeast Asians | 26 (13.0) | 11 (11.0) | |
| Prepregnancy BMI (kg/m2) | 26.2 (23.0–29.6) | 22.2 (19.7–25.2) | <0.001 |
| Multiparous | 117 (58.5) | 50 (50.0) | 0.162 |
| GA at delivery (weeks) | 38.1±0.8 | 38.6±0.9 | <0.001 |
| Mode of delivery | 0.870 | ||
| Vaginal delivery | 100 (50.0) | 51 (51.0) | |
| Caesarean delivery | 100 (50.0) | 49 (49.0) | |
| Birth weight (g) | 3153.6±410.7 | 3185.9±358.6 | 0.503 |
| Infant sex | 0.191 | ||
| Male | 94 (47.0) | 55 (55.0) | |
| Female | 106 (53.0) | 45 (45.0) | |
| Placental weight (g) | 508.2±96.5 | 518.9±91.6 | 0.352 |
| BW:PW ratio | 6.3 (5.6–6.9) | 6.2 (5.6–6.8) | 0.399 |
Data are presented as mean±SD, number (%), or median (IQR).
BMI, body mass index; BW:PW, birth weight-to-placental weight ratio; GA, gestational age; GDM, gestational diabetes mellitus.
Clinical and histopathologic characteristics stratified by BW:PW ratio
In the GDM group, participants were stratified into three categories based on the distribution of BW:PW ratios: <10th percentile (n=21), 10th–90th percentile (n=157) and >90th percentile (n=22). The BW:PW ratio cut-offs corresponding to the 10th and 90th percentiles were 5.2 and 7.6, respectively. The clinical characteristics and histological placental abnormalities across these BW:PW ratio categories are summarised in table 2. Placental weight decreased significantly with increasing BW:PW ratio (p<0.001), while birth weight did not significantly differ across the groups (p=0.301). There were no statistically significant differences in maternal age, prepregnancy BMI, parity, GDM class, GA at delivery, mode of delivery or infant sex among the BW:PW categories.
Table 2. Clinical characteristics and histological abnormalities of placentas in the gestational diabetes mellitus group stratified by birth weight-to-placental weight ratio distribution.
| Variable | BW:PW ratio category | P value | ||
|---|---|---|---|---|
| <10th percentile | 10th–90th percentile | >90th percentile | ||
| (n=21) | (n=157) | (n=22) | ||
| Clinical characteristics | ||||
| Age (years) | 33.5±4.8 | 32.8±5.8 | 32.1±5.4 | 0.346 |
| Prepregnancy BMI (kg/m2) | 26.1±4.1 | 26.9±5.1 | 26.3±5.0 | 0.751 |
| Multiparous | 12 (57.1) | 96 (61.1) | 9 (40.9) | 0.195 |
| GDM class | 0.850 | |||
| A1 | 16 (76.2) | 120 (76.4) | 18 (81.8) | |
| A2 | 5 (23.8) | 37 (23.6) | 4 (18.2) | |
| GA at delivery (weeks) | 37.8±0.7 | 38.1±0.9 | 38.4±0.7 | 0.064 |
| Mode of delivery | 0.660 | |||
| Vaginal delivery | 11 (52.4) | 80 (51.0) | 9 (40.9) | |
| Caesarean delivery | 10 (47.6) | 77 (49.0) | 13 (59.1) | |
| Birth weight (g) | 3029.3±581.0 | 3162.2±390.5 | 3210.2±352.5 | 0.301 |
| Infant sex | 0.386 | |||
| Male | 11 (52.4) | 70 (44.6) | 13 (59.1) | |
| Female | 10 (47.6) | 87 (55.4) | 9 (40.9) | |
| Placental weight (g) | 634.9±117.5*† | 506.1±77.8 | 402.5±48.2* | <0.001 |
| Histologic abnormalities | ||||
| MVM | 14 (66.7) | 107 (68.2) | 14 (63.6) | 0.911 |
| FVM | 12 (57.1) | 72 (45.9) | 14 (63.6) | 0.216 |
| Acute chorioamnionitis | 3 (14.3) | 36 (22.9) | 8 (36.4) | 0.218 |
| VUE | 1 (4.8) | 11 (7.0) | 2 (9.1) | 0.857 |
| Chorangiosis | 14 (66.7)† | 83 (52.9) | 5 (22.7)* | 0.009 |
| DVM | 2 (9.5) | 29 (18.5) | 3 (13.6) | 0.535 |
Data are presented as mean±SD or number (%).
p<0.01, compared with the 10th–90th percentile BW:PW ratio group.
p<0.01, compared with the >90th percentile BW:PW ratio group.
BMI, body mass index; BW:PW, birth weight-to-placental weight ratio; DVM, delayed villous maturation; FVM, foetal vascular malperfusion; GA, gestational age; GDM, gestational diabetes mellitus; MVM, maternal vascular malperfusion; VUE, villitis of unknown aetiology.
In the histopathologic analysis, MVM and FVM were frequent across all BW:PW ratio categories, with no significant differences in prevalence (table 2). By contrast, chorangiosis differed significantly, being most common in the <10th percentile group (66.7%) and least common in the >90th percentile group (22.7%) (p=0.009). No significant differences were observed for chorioamnionitis, VUE or DVM. Subgroup analysis revealed that the difference in chorangiosis was limited to the GDM A2 subgroup (table 3).
Table 3. Placental histologic abnormalities in gestational diabetes mellitus classes A1 and A2 by birth weight-to-placental weight ratio.
| Histologic abnormality | BW:PW ratio category | P value | ||
|---|---|---|---|---|
| <10th percentile | 10th–90th percentile | >90th percentile | ||
| GDM class A1 | n=16 | n=120 | n=18 | |
| MVM | 10 (62.5) | 82 (68.3) | 13 (72.2) | 0.829 |
| FVM | 9 (56.3) | 59 (49.2) | 12 (66.7) | 0.358 |
| Histologic chorioamnionitis | 3 (18.8) | 23 (19.2) | 7 (38.9) | 0.158 |
| VUE | 1 (6.3) | 8 (6.7) | 2 (11.1) | 0.784 |
| Chorangiosis | 9 (56.3) | 59 (49.2) | 5 (27.8) | 0.180 |
| DVM | 1 (6.3) | 23 (19.2) | 3 (16.7) | 0.441 |
| GDM class A2 | n=5 | n=37 | n=4 | |
| MVM | 4 (80.0) | 25 (67.6) | 1 (25.0) | 0.181 |
| FVM | 3 (60.0) | 13 (35.1) | 2 (50.0) | 0.506 |
| Histologic chorioamnionitis | 0 (0) | 13 (35.1) | 1 (25.0) | 0.269 |
| VUE | 0 (0) | 3 (8.1) | 0 (0) | 0.677 |
| Chorangiosis | 5 (100)* | 24 (64.9)† | 0 (0) | 0.007 |
| DVM | 1 (20.0) | 6 (16.2) | 0 (0) | 0.659 |
Data are presented as number (%).
p<0.01, compared with the >90th percentile BW:PW ratio group.
p<0.05, compared with the >90th percentile BW:PW ratio group.
BW:PW, birth weight-to-placental weight ratio; DVM, delayed villous maturation; FVM, foetal vascular malperfusion; GDM, gestational diabetes mellitus; MVM, maternal vascular malperfusion; VUE, villitis of unknown aetiology.
Univariable logistic regression showed an association between the BW:PW ratio and chorangiosis, but not with MVM, FVM, histologic chorioamnionitis or VUE. After adjustment for maternal age, prepregnancy BMI, parity, GA at delivery and infant sex, and using the 10th–90th percentile as the reference, a BW:PW ratio >90th percentile was inversely associated with chorangiosis (adjusted OR (aOR) 0.35; 95% CI 0.11 to 0.85; p=0.042). In contrast, a ratio <10th percentile was not independently associated (aOR 2.35, 95% CI 0.78 to 7.09; p=0.128).
Perinatal outcomes stratified by BW:PW ratio
The prevalence of SGA neonates was significantly higher in the <10th percentile group (14.3%) compared with the 10th–90th percentile (1.3%) and >90th percentile (4.5%) groups (p=0.004) (table 4). Notably, this association was largely driven by the significant relationship observed in the GDM A2 subgroup (table 5). No significant differences were observed among the groups in the incidence of FHR decelerations, LGA neonates, low Apgar scores, neonatal hypoglycaemia, RDS, NICU admissions or composite adverse outcomes.
Table 4. Perinatal outcomes in the gestational diabetes mellitus group stratified by birth weight-to-placental weight ratio distribution.
| Outcome | BW:PW ratio category | P value | ||
|---|---|---|---|---|
| <10th percentile | 10th–90th percentile | >90th percentile | ||
| (n=21) | (n=157) | (n=22) | ||
| FHR decelerations | 0 (0) | 5 (3.2) | 0 (0) | 0.495 |
| SGA | 3 (14.3)* | 2 (1.3) | 1 (4.5) | 0.004 |
| LGA | 6 (28.6) | 37 (23.6) | 3 (13.6) | 0.476 |
| Low Apgar scores | 0 (0) | 9 (5.7) | 0 (0) | 0.275 |
| Neonatal hypoglycaemia | 0 (0) | 8 (5.1) | 1 (4.5) | 0.571 |
| RDS | 0 (0) | 1 (0.6) | 0 (0) | 0.871 |
| NICU admission | 2 (9.5) | 26 (16.6) | 3 (13.6) | 0.682 |
| Composite adverse outcomes† | 10 (47.6) | 63 (40.1) | 5 (22.7) | 0.203 |
Data are presented as number (%).
p<0.01, compared with the 10th–90th percentile BW:PW ratio group.
Defined as the presence of any of the following seven outcomes: FHR decelerations, SGA, LGA, low Apgar scores, neonatal hypoglycaemia, RDS or NICU admission.
BW:PW, birth weight-to-placental weight ratio; FHR, foetal heart rate; LGA, large for gestational age; NICU, neonatal intensive care unit; RDS, respiratory distress syndrome; SGA, small for gestational age.
Table 5. Perinatal outcomes in gestational diabetes mellitus classes A1 and A2 by birth weight-to-placental weight ratio.
| Perinatal outcome | BW:PW ratio category | P value | ||
|---|---|---|---|---|
| <10th percentile | 10th–90th percentile | >90th percentile | ||
| GDM class A1 | n=16 | n=120 | n=18 | |
| FHR decelerations | 0 (0) | 4 (3.3) | 0 (0) | 0.559 |
| SGA | 1 (6.3) | 2 (1.7) | 1 (5.6) | 0.391 |
| LGA | 6 (37.5) | 23 (19.2) | 2 (11.1) | 0.137 |
| Low Apgar scores | 0 (0) | 7 (5.8) | 0 (0) | 0.354 |
| Neonatal hypoglycaemia | 0 (0) | 5 (4.2) | 1 (5.6) | 0.669 |
| RDS | 0 (0) | 1 (0.8) | 0 (0) | 0.867 |
| NICU admission | 0 (0) | 17 (14.2) | 3 (16.7) | 0.253 |
| Composite adverse outcomes* | 7 (43.8) | 43 (35.8) | 4 (22.2) | 0.394 |
| GDM class A2 | n=5 | n=37 | n=4 | |
| FHR decelerations | 0 (0) | 1 (2.7) | 0 (0) | 0.883 |
| SGA | 2 (40.0)† | 0 (0) | 0 (0) | <0.001 |
| LGA | 0 (0) | 14 (37.8) | 1 (25.0) | 0.225 |
| Low Apgar scores | 0 (0) | 2 (5.4) | 0 (0) | 0.775 |
| Neonatal hypoglycaemia | 0 (0) | 3 (8.1) | 0 (0) | 0.677 |
| RDS | 0 (0) | 0 (0) | 0 (0) | – |
| NICU admission | 2 (40.0) | 9 (24.3) | 0 (0) | 0.373 |
| Composite adverse outcomes* | 3 (60.0) | 20 (50.1) | 1 (25.0) | 0.507 |
Data are presented as number (%).
Defined as the presence of any of the following seven outcomes: FHR decelerations, SGA, LGA, low Apgar scores, neonatal hypoglycaemia, RDS or NICU admission.
p<0.01, compared with the 10th–90th percentile BW:PW ratio group.
BW:PW, birth weight-to-placental weight ratio; FHR, foetal heart rate; LGA, large for gestational age; NICU, neonatal intensive care unit; RDS, respiratory distress syndrome; SGA, small for gestational age.
In univariable analyses, the BW:PW ratio was associated with SGA but not with other adverse perinatal outcomes, including FHR decelerations, LGA, low Apgar scores, neonatal hypoglycaemia, RDS, NICU admission or the composite outcome. In multivariable analysis adjusted for maternal age, prepregnancy BMI, parity, GA at delivery and infant sex, a BW:PW ratio <10th percentile remained significantly associated with SGA neonates (aOR 9.94; 95% CI 1.14 to 86.80; p=0.038). This association persisted after further adjustment for chorangiosis (aOR 11.75; 95% CI 1.01 to 137.47; p=0.049), although chorangiosis itself was not independently associated with SGA (aOR 0.88; 95% CI 0.10 to 7.87; p=0.910). By contrast, a BW:PW ratio >90th percentile showed no independent association with SGA neonates (aOR 5.42; 95% CI 0.43 to 68.27; p=0.191).
Discussion
Main findings
In this prospective cohort study, BW:PW ratios did not differ significantly between pregnancies complicated by GDM and those with normoglycaemia. However, within the GDM cohort, extremes in the BW:PW ratio (<10th and >90th percentiles) were associated with distinct placental and perinatal outcomes. A ratio below the 10th percentile was linked to an increased risk of SGA neonates, particularly in the GDM A2 subgroup, and this association persisted after adjusting for chorangiosis. By contrast, a ratio above the 90th percentile was not associated with SGA but was independently linked to lower odds of chorangiosis. Other placental lesions (MVM, FVM, chorioamnionitis, VUE or DVM) and adverse neonatal outcomes (FHR decelerations, LGA, low Apgar scores, neonatal hypoglycaemia, RDS, NICU admission or composite outcomes) showed no significant variation across ratio categories.
Comparison with existing literature
Previous studies have reported lower BW:PW ratios in pregnancies complicated by GDM compared with normoglycaemic pregnancies, suggesting reduced placental efficiency.7,9 In contrast, our study found no significant difference between the groups. This discrepancy may be attributable to differences in GDM severity.21 Notably, 77% of GDM cases in our cohort were classified as A1, indicating milder hyperglycaemia that may exert less impact on placental development and function.
Within the GDM cohort, however, a more nuanced pattern emerged. Pregnancies with a BW:PW ratio below the 10th percentile had the highest placental weights, followed by the 10th–90th percentile and >90th percentile groups, whereas infant birth weights showed only a non-significant upward trend across these categories. These findings suggest that variations in BW:PW ratios were primarily driven by placental weight rather than foetal weight, aligning with previous research.7,9 Notably, the observed placental overgrowth did not correspond with improved foetal growth, highlighting the complex and potentially maladaptive nature of placental adaptation in the context of maternal metabolic stress.
Low BW:PW ratios have also been linked to adverse perinatal outcomes, including FGR and SGA neonates, in general obstetric populations.3 22 Our findings extend this association to GDM pregnancies, showing that a low ratio similarly conferred an elevated risk of SGA. In this context, placental hypertrophy without a proportional increase in foetal mass may reflect impaired placental efficiency, likely driven by chronic maternal metabolic disturbances.
Building on these outcome-based associations, we examined whether extremes in the BW:PW ratio were accompanied by specific placental lesions. In the group with a ratio below the 10th percentile, chorangiosis—a marker of chronic hypoxia and abnormal vascular proliferation17 23—was more prevalent and coincided with the highest frequency of SGA neonates. These findings suggest that a low ratio reflects not only disproportionate placental growth but also underlying pathology associated with increased fetal risk.
Because both chorangiosis and DVM have been implicated in GDM pathophysiology, we analysed these lesions in greater detail. Chorangiosis, associated with chronic hypoxia and impaired perfusion,17 23 showed a strong link with low BW:PW ratios, particularly in GDM class A2. However, chorangiosis did not independently predict SGA status. This may reflect the limited number of cases or the possibility that it represents a compensatory rather than causal process. It is also plausible that multiple overlapping placental lesions, rather than any single abnormality, underlie the increased risk of SGA.
In contrast, DVM, although frequently reported in diabetic pregnancies,24 showed no variation across BW:PW strata in our cohort. This lack of association suggests that, unlike chorangiosis, DVM may not contribute directly to BW:PW extremes, but rather represents an alternative pathway of impaired placental maturation.
Inflammatory lesions, including histologic chorioamnionitis and VUE, were likewise not associated with BW:PW extremes, underscoring a more prominent role for vascular and hypoxia-related changes. Nevertheless, prior studies have shown that maternal obesity and GDM are linked to placental inflammation and oxidative stress,25 26 which may act in concert with vascular maladaptation. This interplay could help explain the higher prevalence of chorangiosis observed in GDM class A2 pregnancies.
Clinical implications
Incorporating the BW:PW ratio analysis into routine placental evaluation may enhance collaboration among obstetricians, neonatologists and pathologists, particularly in cases of suspected growth restriction. As a simple, readily obtainable measurement at delivery, it offers a valuable adjunct to standard perinatal assessments and may serve as a retrospective marker of placental inefficiency—especially when FGR or SGA is present despite a normal or enlarged placenta.
In pregnancies complicated by GDM, placental overgrowth may appear clinically unremarkable. However, our findings suggest that when placental enlargement is not proportionally accompanied by foetal growth, it may reflect underlying placental insufficiency. Early recognition of this imbalance could guide neonatal monitoring and inform long-term follow-up, given the growing evidence linking abnormal placental development to future metabolic and neurodevelopmental disorders.27 28
Research implications
Longitudinal studies tracking placental growth and glycaemic control throughout gestation may provide valuable insights into how GDM affects placental efficiency and foetal development. Placental weight can be estimated with reasonable accuracy using two-dimensional ultrasound with volumetric calculations,29 a practical and non-invasive method for routine prenatal care. To support clinical application, further research is needed to evaluate the reproducibility and utility of the antenatal foetal BW:PW ratio derived from this approach.
The observed association between low BW:PW ratios and chorangiosis raises questions about the role of chronic hypoxia and angiogenic imbalance in diabetic placental pathology. Future studies incorporating biomarkers of oxidative stress, vascular function and placental oxygenation could help clarify these mechanisms and offer avenues for early detection and targeted intervention in high-risk GDM pregnancies.
Strengths and limitations
A major strength of this study is its prospective design, ensuring systematic data collection and enhancing reliability. The inclusion of both GDM and normoglycaemic pregnancies allowed for direct comparisons, offering a clearer understanding of GDM’s impact on placental efficiency. Additionally, the combined assessment of placental histopathology and perinatal outcomes revealed novel associations between the BW:PW ratio, lesions such as chorangiosis, and adverse outcomes like SGA. Together, these insights deepen our understanding of placental dysfunction in GDM and support the BW:PW ratio as a potential marker for identifying high-risk pregnancies.
Despite its strengths, this study has limitations. First, the small number of cases in the <10th and >90th percentile BW:PW groups may have reduced power to detect less frequent outcomes. Second, although both GDM and normoglycaemic pregnancies were recruited sequentially and concurrently during the study period, the process was not matched, which could introduce bias, as GDM pregnancies are more common in older, multiparous and obese women. Third, being a single-centre study in a Southeast Asian population using Carpenter and Coustan criteria, the findings may not generalise to other ethnic groups or diagnostic standards. Fourth, the predominance of A1 GDM—reflecting milder disease—limits applicability to more severe cases, highlighting the need for studies in higher-risk cohorts. Finally, long-term outcomes were not assessed; the impact of abnormal BW:PW ratios on offspring’s metabolic and neurodevelopmental health warrants further research.
Conclusions
This study underscores the potential of the BW:PW ratio as a marker of placental efficiency and foetal well-being in GDM pregnancies. Although overall ratios did not differ from those in normoglycaemic pregnancies, low ratios in the GDM group were associated with heavier placentas, increased chorangiosis and a higher risk of SGA neonates, suggesting maladaptive placental responses to maternal metabolic stress. Further studies involving more diverse populations and GDM phenotypes are needed to validate these associations and explore long-term child outcomes. As a simple clinical tool, the BW:PW ratio may help identify GDM pregnancies at increased risk for adverse perinatal outcomes.
Acknowledgements
We gratefully acknowledge the pathology technicians at the Faculty of Medicine Vajira Hospital, Navamindradhiraj University (Bangkok, Thailand), for their assistance during the PL-GDM study period.
Footnotes
Funding: This study was supported by the Navamindradhiraj University Research Fund (grant number 005/2565). The funders had no role in the design, conduct, data collection, management, analysis, interpretation, manuscript preparation, review, approval or decision to submit the manuscript for publication.
Prepublication history for this paper is available online. To view these files, please visit the journal online (https://doi.org/10.1136/bmjopen-2025-104482).
Data availability free text: Data are available upon reasonable request. The data used to support the findings of this study are available from the corresponding author upon request.
Patient consent for publication: Not applicable.
Ethics approval: This study involves human participants and was approved by the Institutional Review Board of the Faculty of Medicine, Vajira Hospital. Approval number 215/2564. Participants gave informed consent to participate in the study before taking part.
Provenance and peer review: Not commissioned; externally peer reviewed.
Patient and public involvement: Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Data availability statement
Data are available upon reasonable request.
References
- 1.Burton GJ, Fowden AL. The placenta: a multifaceted, transient organ. Philos Trans R Soc Lond B Biol Sci. 2015;370:20140066. doi: 10.1098/rstb.2014.0066. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Fowden AL, Sferruzzi-Perri AN, Coan PM, et al. Placental efficiency and adaptation: endocrine regulation. J Physiol. 2009;587:3459–72. doi: 10.1113/jphysiol.2009.173013. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Hayward CE, Lean S, Sibley CP, et al. Placental Adaptation: What Can We Learn from Birthweight:Placental Weight Ratio? Front Physiol. 2016;7:28. doi: 10.3389/fphys.2016.00028. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Szmuilowicz ED, Josefson JL, Metzger BE. Gestational Diabetes Mellitus. Endocrinol Metab Clin North Am. 2019;48:479–93. doi: 10.1016/j.ecl.2019.05.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Ehlers E, Talton OO, Schust DJ, et al. Placental structural abnormalities in gestational diabetes and when they develop: A scoping review. Placenta. 2021;116:58–66. doi: 10.1016/j.placenta.2021.04.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Calvo MJ, Parra H, Santeliz R, et al. The Placental Role in Gestational Diabetes Mellitus: A Molecular Perspective. touchREV Endocrinol. 2024;20:10–8. doi: 10.17925/EE.2024.20.1.5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Strøm-Roum EM, Haavaldsen C, Tanbo TG, et al. Placental weight relative to birthweight in pregnancies with maternal diabetes mellitus. Acta Obstet Gynecol Scand. 2013;92:783–9. doi: 10.1111/aogs.12104. [DOI] [PubMed] [Google Scholar]
- 8.Ramos A, Caimari F, Pujol IM, et al. In women with gestational diabetes mellitus factors influencing growth have a larger effect on placental weight than on birth weight. Eur J Obstet Gynecol Reprod Biol. 2016;202:60–5. doi: 10.1016/j.ejogrb.2016.04.022. [DOI] [PubMed] [Google Scholar]
- 9.Choo S, de Vrijer B, Regnault TRH, et al. The impact of maternal diabetes on birth to placental weight ratio and umbilical cord oxygen values with implications for fetal-placental development. Placenta. 2023;136:18–24. doi: 10.1016/j.placenta.2023.02.008. [DOI] [PubMed] [Google Scholar]
- 10.Eskild A, Haavaldsen C, Vatten LJ. Placental weight and placental weight to birthweight ratio in relation to Apgar score at birth: a population study of 522 360 singleton pregnancies. Acta Obstet Gynecol Scand. 2014;93:1302–8. doi: 10.1111/aogs.12509. [DOI] [PubMed] [Google Scholar]
- 11.Shehata F, Levin I, Shrim A, et al. Placenta/birthweight ratio and perinatal outcome: a retrospective cohort analysis. BJOG. 2011;118:741–7. doi: 10.1111/j.1471-0528.2011.02892.x. [DOI] [PubMed] [Google Scholar]
- 12.Bortolus R, Chatenoud L, Di Cintio E, et al. Placental ratio in pregnancies at different risk for intrauterine growth. Eur J Obstet Gynecol Reprod Biol. 1998;80:157–8. doi: 10.1016/s0301-2115(98)00124-9. [DOI] [PubMed] [Google Scholar]
- 13.ACOG Practice Bulletin No. 190: Gestational Diabetes Mellitus. Obstet Gynecol. 2018;131:e49–64. doi: 10.1097/AOG.0000000000002501. [DOI] [PubMed] [Google Scholar]
- 14.Phaloprakarn C, Tangjitgamol S. Glucose levels during gestational diabetes pregnancy and the risk of developing postpartum diabetes or prediabetes. BMC Pregnancy Childbirth. 2022;22:22. doi: 10.1186/s12884-021-04352-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Khong TY, Mooney EE, Ariel I, et al. Sampling and Definitions of Placental Lesions: Amsterdam Placental Workshop Group Consensus Statement. Arch Pathol Lab Med. 2016;140:698–713. doi: 10.5858/arpa.2015-0225-CC. [DOI] [PubMed] [Google Scholar]
- 16.Redline RW, Ravishankar S, Bagby CM, et al. Four major patterns of placental injury: a stepwise guide for understanding and implementing the 2016 Amsterdam consensus. Mod Pathol. 2021;34:1074–92. doi: 10.1038/s41379-021-00747-4. [DOI] [PubMed] [Google Scholar]
- 17.Vafaei H, Karimi Z, Akbarzadeh-Jahromi M, et al. Association of placental chorangiosis with pregnancy complication and prenatal outcome: a case-control study. BMC Pregnancy Childbirth. 2021;21:99. doi: 10.1186/s12884-021-03576-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.American College of Obstetricians and Gynecologists Practice Bulletin No. 116: Management of Intrapartum Fetal Heart Rate Tracings. Obstet Gynecol. 2010;116:1232–40. doi: 10.1097/AOG.0b013e3182004fa9. [DOI] [PubMed] [Google Scholar]
- 19.Borisut P, Kovavisarach E. Standard intrauterine growth curve of Thai neonates delivered at Rajavithi hospital. J Med Assoc Thai. 2014;97:798–803. [PubMed] [Google Scholar]
- 20.Adamkin DH, Committee on Fetus and Newborn Postnatal Glucose Homeostasis in Late-Preterm and Term Infants. Pediatrics. 2011;127:575–9. doi: 10.1542/peds.2010-3851. [DOI] [PubMed] [Google Scholar]
- 21.Lao TT, Lee CP, Wong WM. Placental weight to birthweight ratio is increased in mild gestational glucose intolerance. Placenta. 1997;18:227–30. doi: 10.1016/s0143-4004(97)90097-7. [DOI] [PubMed] [Google Scholar]
- 22.Macdonald EM, Koval JJ, Natale R, et al. Population-based placental weight ratio distributions. Int J Pediatr. 2014;2014:291846. doi: 10.1155/2014/291846. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Stanek J. Chorangiosis of Chorionic Villi: What Does It Really Mean? Arch Pathol Lab Med. 2016;140:588–93. doi: 10.5858/arpa.2015-0160-OA. [DOI] [PubMed] [Google Scholar]
- 24.Dasgupta S, Banerjee U, Mukhopadhyay P, et al. Clinicopathological study and immunohistochemical analysis of expression of annexin A5 and apelin in human placentae of gestational diabetes mellitus. Diabetes Metab Syndr. 2022;16:102435. doi: 10.1016/j.dsx.2022.102435. [DOI] [PubMed] [Google Scholar]
- 25.Doshani A, Konje JC. Placental dysfunction in obese women and antenatal surveillance. Best Pract Res Clin Obstet Gynaecol. 2023;91:102407. doi: 10.1016/j.bpobgyn.2023.102407. [DOI] [PubMed] [Google Scholar]
- 26.Jantape T, Kongwattanakul K, Arribas SM, et al. Maternal Obesity Alters Placental and Umbilical Cord Plasma Oxidative Stress, a Cross-Sectional Study. Int J Mol Sci. 2024;25:10866. doi: 10.3390/ijms251910866. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Lodefalk M, Chelslín F, Patriksson Karlsson J, et al. Placental Changes and Neuropsychological Development in Children-A Systematic Review. Cells. 2023;12:435. doi: 10.3390/cells12030435. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Gardella B, Dominoni M, Scatigno AL, et al. What is known about neuroplacentology in fetal growth restriction and in preterm infants: A narrative review of literature. Front Endocrinol. 2022;13:936171. doi: 10.3389/fendo.2022.936171. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Azpurua H, Funai EF, Coraluzzi LM, et al. Determination of placental weight using two-dimensional sonography and volumetric mathematic modeling. Am J Perinatol. 2010;27:151–5. doi: 10.1055/s-0029-1234034. [DOI] [PubMed] [Google Scholar]