Postnatal trends of surrogate anthropometric indices in infants of diabetic mothers: A prospective cohort study from South India

Abstract

Background

Infants of diabetic mothers (IDMs) are shown to have predisposition for obesity and metabolic complications in childhood and adolescence. While several studies found growth differences in IDMs during childhood, data on growth in early infancy are scarce. This study aimed to assess the surrogate anthropometric parameters which evaluate physical growth in more detail during first 6 weeks of life in IDMs.

Methods

A prospective cohort study was conducted among late preterm and term IDMs with infants of non-diabetic mothers taken as controls. Basic demographics, delivery characteristics, maternal anthropometry and birth anthropometry including auxologic parameters were recorded postnatally. Follow-up measurements were taken till 6 weeks. Statistical analysis was performed using STATA.

Results

IDMs showed higher weight for length at 6 weeks and higher BMI at birth and at 6 weeks of age. MUAC was significant at birth but not at 6 weeks age. Birth weight and large-for-gestational age were significantly higher in diabetic group. At 6 weeks, 14% of infants of diabetic mothers were overweight, though not statistically significant.

Conclusion

The IDMs seemed to have significant difference in their auxologic parameters and had greater prevalence of overweight in early postnatal period as early as at 6 weeks postnatal age in this study albeit small sample size. Close monitoring of growth and metabolic parameters in infants of diabetic mothers in larger sample sizes are necessary for better monitoring for complications and better long-term outcomes as their body composition possibly seems to differ from those of IDMs in early infancy.

Keywords

diabetes mellitus infant of diabetic mother infants neonate pregnancy

Introduction

Diabetes mellitus is a growing global health concern, affecting 10.5% of adults worldwide (536.6 million people) and 8.9% in India.¹ Hyperglycemia during pregnancy, due to pre-existing type 1 (T1DM) or type 2 diabetes (T2DM) or gestational diabetes mellitus (GDM), is common, with GDM affecting about 14% of pregnancies globally.² Prevalence of GDM shows significant regional variation in India with about 11.5% prevalence in Andhra Pradesh.^3,4 In the health center where this study was conducted, diabetic pregnancies accounted for 20.3% of all deliveries from December 2021 to November 2023 [unpublished data from the department of obstetrics and gynecology at the institute where the study was conducted].

Diabetes during pregnancy is linked to various complications to the infant like macrosomia, risk of preterm delivery, perinatal mortality, congenital anomalies, and metabolic and hematological disorders.^5,6 Intrauterine growth restriction (IUGR) and small-for-gestational age (SGA) infants are also seen with long-term uncontrolled diabetes.⁶ During childhood, infants of diabetic mothers (IDM) tend to have higher body mass indices (BMI) and risk of early obesity, metabolic syndrome, pre-diabetes, and T2DM.⁵ This risk persists into adulthood, with increased and early occurrence of T2DM and obesity.^7,8

Despite existing research on growth trajectories and obesity risks in offspring of diabetic mothers during childhood, adolescence, and adulthood, there is a notable gap in data regarding early postnatal growth and nutritional disorders, particularly in Indian contexts where maternal diabetes rates are rising. Also, the age at which the growth and body composition of infants of diabetic and non-diabetic mothers starts to differ is not studied extensively. This study was undertaken to assess and compare various surrogate markers of obesity among infants of diabetic and non-diabetic mothers and to evaluate if there was any predisposition for early changes in body composition among IDM.

Material and methods

This prospective cohort study was conducted in the department of neonatology of a tertiary health center in Southern India. Approval from the institutional ethics committee was obtained before commencement of the study. All live singleton late preterm (>34 weeks of gestation) and term babies without any gross congenital anomalies born in this institute during the period of December 2023 to January 2024 were included in this study after obtaining consent from the parent. Babies with gross congenital anomalies, gestational age <34 weeks (early preterms), multifetal pregnancy and absence of antenatal diabetes screening records were excluded. With the expected change in weight [mean (SD)] between birth and 3 months of age being 3.6 (0.46) in infants of mothers without diabetes and 3.3 (0.63) in infants of mothers with diabetes⁹ and attrition rate being 5%, confidence interval 95% and power 80%, the sample size was calculated to be 28 in each group using nMaster 2.0. Maternal diabetes was diagnosed using ADA 2020 guidelines.¹⁰ Infants of mothers satisfying this were grouped under infant of diabetic mother (IDM) which included GDM, T1DM, and T2DM while infants born to mothers who do not satisfy any of the criteria were grouped under infants of non-diabetic mother (INDM).

The details regarding demographics of the mother, antenatal period, delivery, maternal diabetes, and natal and postnatal history of the infant were collected from the patient records in the postnatal ward. The height and weight of the mother were measured within 24 hours of delivery and postpartum BMI was calculated. Infant birth anthropometry was taken in the postnatal ward or NICU at 6–24 hours of life. The second measurements were taken during follow-up at 7 days and third measurement in the 6th week during routine vaccination. The infant anthropometric parameters included conventional markers like weight, length, weight for length (W/L), and additional anthropometric parameters like BMI and mid upper arm circumference (MUAC). The infant was weighed naked using an electronic digital weighing scale of 1 g accuracy (KRUPS NOBLE, DOCTOR BELI RAM & SONS). Length was measured using infantometer with an accuracy of 0.1 cm (SECA 417, Seca GmbH & Co. KG) and MUAC using a flexible non-stretchable measuring tape on the extended left arm with 1 mm accuracy. W/L z-score was calculated using online W/L calculator application¹¹ and BMI was derived from weight and length.

Percentiles and z-scores of the obtained anthropometric values were calculated from standard WHO growth charts.¹² Based on anthropometry at 6 weeks, the infants were grouped into different categories of under and over nutrition (W/L, weight for age [W/A], length for age [L/A], BMI <−2SD and >2SD, and MUAC<11 cm).^13,14 We compared the MUAC, BMI, and weight for length between IDMs and INDMs as surrogate anthropometric markers of body composition in infants.^15,16

Statistical analysis

The data was analyzed using STATA statistical software version 14. Categorical variables were summarized as proportions and continuous variables were summarized as mean (SD) and median (IQR). Appropriate statistical analysis was performed using Student “t” test and chi square test. p value <0.05 was considered significant.

Results

Out of 54 INDM and 43 IDM enrolled at birth, all required information was available for 56 infants, 28 in each group. In IDM, two mothers had T2DM, 19 had GDM controlled by medical nutrition therapy (GDMA1) and seven had GDM which required medical management (GDMA2). 2 T2DM and 4 GDMA2 were using insulin and 3 GDMA2 were using metformin for controlling diabetes. Mean weeks of gestation at diagnosis of GDM was 29 (4.64). Basic characteristics of the infants are given in Table 1.

Table 1.

Characteristics of the infants.

Variable	Category	INDM, n = 28Frequency (%)	IDM, n = 28Frequency (%)	Total, n = 56Frequency (%)	p-value
Sex	Male	14 (50.00%)	17 (60.71%)	31 (55.36%)	0.420
Sex	Female	14 (50.00%)	11 (39.29%)	25 (44.64%)
Size at birth	AGA	19 (67.854%)	22 ((78.57%)	41 (73.21%)	0.001*
	SGA	8 (28.57%)	0	8 (14.29%)
	LGA	1 ((3.57%)	6 (21.42%)	7 (12.50%)
Gestational age at birth	Term	25 (89.29%)	25 (89.29%)	50 (89.29%)	1.000
Gestational age at birth	Preterm	3 (10.71%)	3 (10.71%)	6 (10.71%)
NICU admission	Present	5 (17.85%)	9 (32.14%)	14 (25%)	0.218
Duration of NICU stay (hours)^d	Median (IQR)	72 (24–96)	24 (8–72)	24 (8–72)	0.351
Initiation of first breastfeeding	Early (<1 hour)	10 (35.71%)	14 (50%)	24 (42.86%)	0.281
Attainment of full breastfeeding (days)	Median (IQR)	2 (1.25–3.5)	2 (2–3.5)	2 (2–4)	0.714

Bold values indicate statistically significant results.

Maternal weight, BMI, number of obese mothers, and prevalence of hypothyroidism were significantly higher for IDM, but characteristics like age, socioeconomic status,¹⁷ consanguinity of marriage, and obstetric history were similar. Other antenatal complications encountered were oligohydramnios, pre-eclampsia, hypertension, and anemia. Lower segment caesarean section (LSCS) was the most common mode of delivery, the most common indication in INDM being history of previous LSCS and IDM being fetal distress.

Sex of infants, number of preterms, NICU admission, and duration of NICU stay were similar for both groups. The prevalence of large-for-gestational age (LGA) was significantly higher in the IDM while that of SGA was higher in INDM. Neonates attained full breastfeeding at median age of 2 days and 100% of the infants were on exclusive breastfeeding at 1 week.

Multivariate regression analysis for confounding factors with GDM which could affect outcomes was performed. Factors which were significantly different among the maternal characteristics of the two groups like maternal obesity and maternal hypothyroidism did not have any significant effect on the anthropometric parameters. However, presence or absence of diabetes had significant effect on the anthropometric parameters (p values 0.0002, <0.001, and 0.001 for weight, BMI, and weight for length z-score, respectively). Change in infant length and weight from birth to 6 weeks was not affected by any of these factors including maternal diabetes.

The trajectories of anthropometry of the infants are shown in Figure 1. Figures 1(a) and (b) describe the weight and length for age parameters of these infants from birth to 6 weeks. W/L and BMI were significantly higher in IDM at 6 weeks, with BMI also higher at birth (Figures 1(c) and (d)). MUAC was initially higher in IDM but difference became insignificant by 6 weeks (Figure 1(e)).

Figure 1.

Change in anthropometric indices of infants from birth to 6 weeks.

The number of infants with nutritional disorders is given in Table 2. At 6 weeks, prevalence of under-nutrition according to criteria W/L <−2SD was 11% in INDM and 7% in IDM. Over nutrition with W/L >2SD had a prevalence of 14% in IDM while none of the infants were overweight in INDM. Even though overweight was more common in IDM and under-nutrition in INDM, there was no statistically significant difference. Trends of weight for length z-scores, BMI, and MUAC trends in infants are tabulated in Table 3.

Table 2.

Number of infants with malnutrition according to different criteria at 6 weeks.

Variable	Category	INDM, n = 28Frequency (%)	IDM, n = 28Frequency (%)	Total, n = 56Frequency (%)	p-value
W/A	<−2SD	0	0	0	0.315
	−2SD to 2SD	28 (100%)	27 (96.43%)	55 (98.21%)
	>2SD	0	1 (3.5%)	1 (1.8%)
W/L	<−2SD	3 (10.7%)	2 (7.1%)	5 (8.9%)	0.111
	−2SD to 2SD	25 (89.23%)	22 (78.57%)	47 (83.93%)
	>2SD	0	4 (14.3%)	4 (7.1%)
BMI	<−2SD	4 (14.3%)	1 (3.5%)	5 (8.9%)	0.148
	−2SD to 2SD	24 (85.71%)	25 (89.23%)	49 (87.5%)
	>2SD	0	2 (7.1%)	2 (3.5%)
MUAC	<11 cm	15 (53.5%)	12 (42.9%)	27 (48.2%)	0.422
MUAC	≥11 cm	13 (46.43%)	16 (57.14%)	29 (51.78%)	0.422

Note. The total number of infants who were overweight (wt/length >2SD) and those with BMI >2SD were more in the IDM group but this was not statistically significant. W/A: weight for age, W/L: weight for length, BMI- body mass index, MUAC: mid upper arm circumference.

Table 3.

Trends of weight for length z-scores, BMI, and MUAC trends in infants.

Age	Non-exposed group INDM, n = 28	Exposed group IDM, n = 28	Total, n = 56	p value
Trends of wt for length z-scores
Birth	−1.12 (−2.29 to −0.28)	−0.64 (−1.9–0.42)	−0.79 (−2.05 to −0.03)	0.282
1 week	−1.52 (−2.88 to −0.85)	−1.32 (−2.66 to −0.03)	−1.46 (−2.86 to −0.51)	0.425
6 weeks	−0.58 (−1.06 to −0.07)	0.35 (−089 to 1.42)	−0.41 (−0.96 to 0.85)	0.017*
BMI trends of infants
Birth	11.77 (1.38)	12.60 (1.46)	12.19 (1.47)	0.033*
1 week	11.23 (1.31)	12.00 (1.54)	11.62 (1.47)	0.050
6 weeks	14.13 (1.26)	15.35 (1.77)	14.74 (1.64)	0.005*
MUAC trends of infants
Birth	9.68 (0.88)	10.47 (0.64)	10.08 (0.86)	<0.001*
1 week	9.83 (0.97)	10.41 (0.62)	10.12 (0.85)	0.011*
6 weeks	11.5 (1.08)	11.60 (0.96)	11.55 (1.02)	0.697

Note. The BMI was significantly higher at birth and at 6 weeks in the IDM group, but the mean MUAC though higher at birth and at 1 week was not significantly higher at 6 weeks of life in the IDM group. Bold values indicate statistically significant results.

Discussion

IDM showed higher W/L at 6 weeks and higher BMI at birth and 6 weeks, while the MUAC and length difference became insignificant at 6 weeks, though significant at birth. At 6 weeks, 14.3% of IDM were overweight based on W/L criteria, compared to none in INDM. This was not statistically significant.

While previous studies had described a higher incidence of preterm delivery, LSCS, and NICU admission in IDM, this study did not observe such significant differences probably due to good antenatal glycemic control and limited sample size.^5,18 The higher weight and BMI and higher prevalence of obesity in diabetic mothers substantiated the association between GDM and obesity.¹⁹ Diabetic mothers were not significantly older, suggesting early diabetes onset. Higher postpartum obesity observed in this study than other Indian studies may have contributed to this early onset.²⁰ This higher prevalence of obesity could also be a result of classifying using immediate postpartum anthropometry. Consistent with the literature, IDM had higher birth weight and a higher incidence of LGA, while SGA though a recognized complication of diabetic pregnancies was not observed, likely due to the smaller number of pre-gestational diabetic mothers and the limited sample size.

BMI was significantly higher for IDM at birth and 6 weeks. Same has been observed by an Iranian study in which BMI of IDM exceeded WHO reference standards up to 2 years²¹ Anderson-hall et al also observed higher BMI in IDM, though not statistically significant.²² These studies supported the association between intrauterine diabetes exposure and higher adiposity in the infant. BMI changes during infancy have been linked to various metabolic disorders in later life, highlighting the need for long-term follow-up of IDM to identify and address these concerns early.²³

W/L z-scores were higher for IDM throughout, with significant difference only at 6 weeks. Alaaraj et al also reported higher W/L in IDM throughout infancy.²⁴ Some other studies had reported a different pattern in which IDM had higher W/L at birth which became similar to or less than INDM in infancy.^9,25,26 While these studies observed that W/L of both groups equalized during infancy, the current study showed a more pronounced difference at 6 weeks, suggesting truncal adipose tissue accumulation disproportionate to skeletal growth in IDM.

MUAC was significantly higher for IDM at birth but equalized by 6 weeks and similar findings were reported by Krishnaveni et al where the higher MUAC for IDM was observed at birth but not at 1 year.²⁷ Few studies have explored changes in MUAC of IDM during infancy, highlighting the need for further research on body circumference patterns, including MUAC, and their role in detecting adiposity and nutritional abnormalities in IDM.

The weight of IDM remained higher throughout the follow-up, consistent with previous studies of Andersson-Hall et al and Alaaraj et al.^22,24 Uebel et al observed this pattern when comparing IDM to infants of lean non-diabetic mothers.²⁸ But, infants of obese non-diabetic mothers in that study had higher birth weight, which became lower than IDM by 6 weeks and remained so throughout infancy. This difference could be due to higher maternal BMI in the obese non-diabetic group and lower breastfeeding rates in IDM. Dode et al and Liu et al observed higher birth weight in IDM which became lower than INDM by 3 months.^9,25 Differences in population characteristics and variation in diagnostic criteria may explain these differences, as Dode et al used self-reporting by the mothers while Liu et al employed sequential testing with two tests. Dode et al found no significant difference in breastfeeding between the groups, but exact data was not reported. While in the study by Liu et al, 70% of participants were on mixed feeding with only 12% of IDM being exclusively breastfed.

Length trajectories similar to this study was observed in several other studies also, in which length difference was either insignificant from birth or became equal during infancy.^{9,22,24,25,27,28} Another study also has noticed shorter lengths for IDM in early childhood.²⁹ All these studies suggest that even if the length of IDM is higher at birth, these infants exhibit catch-down growth and the difference is eliminated at some point in infancy. The same is substantiated by decrease in L/A percentiles of IDM in this study.

The changes in weight for age and length for age percentile values of this cohort of infants from birth till 6 weeks have been published recently elsewhere,³⁰ and the changes in other auxologic parameters of this cohort were hence studied in greater detail in this study.

Exposure to hyperglycemia during pregnancy is an established risk factor for obesity in infancy and childhood,⁵ as seen at 6 weeks in this study, where overweight and obesity were more prevalent among IDM. A Taiwanese study found 25% of INDM overweight by 6 months, with IDM prevalence ranging from 10% to 55% and breastfeeding was found to reduce childhood overweight among IDM.³¹ The higher prevalence can be because of the use of Taiwanese growth curves and not WHO standards. While the protective effects of breastfeeding against overweight and adiposity in INDM are well established, its role is still unclear in IDM.³² Hence, focused research on the effects of breastfeeding and other interventions on obesity development in IDM are also necessary.

Overall, the study suggested that while limb lengths and circumferences of IDM and INDM became similar, IDM tended to remain heavier, which could possibly indicate a tendency for more adiposity in the truncal area and more concerningly starting in early infancy despite adequate breastfeeding. This aligns with several other studies which observed higher adiposity and risk of obesity in IDM from early age.²⁸ The study also highlights the possible inadequacy of MUAC as a screening tool for detecting nutritional abnormalities in infants and underscores the need for better nutritional indices in early infancy, particularly given the rising prevalence of metabolic disorders.

This study is one of the few cohort studies in India to simultaneously evaluate the various auxologic parameters and body composition markers in IDM and INDM during early infancy. Despite the limited sample size and short study duration, statistically significant differences were observed in several anthropometric parameters. However, the study’s findings have limited generalizability due to its hospital-based design and small sample size. Using immediate postpartum maternal BMI for classifying maternal obesity instead of pre-pregnancy anthropometry is another limitation which could affect the outcomes of the infants.

This study underscores the importance of pre-conceptional and antenatal interventions targeting diabetic and high-risk women to control glucose levels and minimize effects of hyperglycemia on fetal development. Close monitoring of IDM’s physical growth and metabolic changes throughout infancy, along with early nutritional and lifestyle interventions may be required to ensure healthy development and better long-term health outcomes. This study also highlights the need for further research focusing on genetic factors of the infants and variations in breast milk composition that may contribute toward early onset obesity and metabolic disorders in these infants.

Conclusion

The IDMs exhibited higher W/L and BMI at 6 weeks of age but MUAC although higher at birth in IDMs was equal by 6 weeks of age. There was also a higher prevalence of overweight at 6 weeks among IDMs although not statistically significant. This pattern of anthropometric parameters suggests a significant difference in auxologic parameters of IDMs as early as 6 weeks of postnatal life and could possibly indicate an early onset risk of deviant growth patterns in IDMs but must be evaluated with larger sample sizes.

Hence close monitoring of growth and metabolic parameters in early postnatal life along with long-term follow-up is essential to promptly identify and effectively prevent metabolic disorders in future. Further investigation is necessary to explore additional factors contributing to these differences, especially in populations like that of India, which are potentially at a high risk for diabetes and other metabolic disorders.

Footnotes

ORCID iD

Thirunavukkarasu Arun Babu

Funding

ICMR Funded Project - STS 2023 (Reference ID: 2023-03749).

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

References

Sun

Saeedi

Karuranga

, et al. IDF Diabetes Atlas: global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045. Diabetes Res Clin Pract 2022; 183: 109119.

Wang

Chivese

, et al. IDF diabetes atlas: estimation of global and regional gestational diabetes mellitus prevalence for 2021 by international association of diabetes in pregnancy study group’s criteria. Diabetes Res Clin Pract 2022; 183: 109050.

Mantri

Goel

Patel

, et al. National and regional prevalence of gestational diabetes mellitus in India: a systematic review and Meta-analysis. BMC Public Health 2024; 24(1): 527.

Paka

Jampana

Rajesh

. Clinical study of prevalence of gestational diabetes mellitus and associated risk factors: a teaching hospital based study. Int J AcadMedPharm 2022; 4(5): 674–678.

Szmuilowicz

Josefson

Metzger

. Gestational diabetes mellitus. Endocrinol Metab Clin North Am 2019; 48(3): 479–493.

Daniela

. Fetal and neonatal complications of diabetic pregnancy. The Moldovan Medical Journal 2017; 60(4): 50–56.

Pettitt

Aleck

Baird

, et al. Congenital susceptibility to NIDDM. Role of intrauterine environment. Diabetes 1988; 37(5): 622–628.

Bowers

Ehrlich

Dolan

, et al. Elevated anthropometric and metabolic indicators among young adult offspring of mothers with pregestational diabetes: early results from the transgenerational effect on adult morbidity study (the TEAM study). J Diabetes Res 2021; 2021: 1–10.

Liu

Sun

, et al. Maternal OGTT glucose levels at 26–30 gestational weeks with offspring growth and development in early infancy. BioMed Res Int 2014; 2014: e516980.

10.

American Diabetes Association . 2. Classification and diagnosis of diabetes: standards of medical care in diabetes-2021. Diabetes Care 2021; 44(Suppl 1): S15–S33.

11.

MSD Manual Professional Edition . Calculators: WHO infant weight for length percentiles (<24 Months). Available from. https://www.msdmanuals.com/professional/multimedia/clinical-calculator/who-infant-weight-for-length-percentiles-24-months (Accessed on 2024 Mar 3).

12.

The WHO child growth standards. Available from: https://www.who.int/tools/child-growth-standards/standards (Accessed on 2024 Mar 3).

13.

Chand

Shah

Kumar

, et al. Mid-upper arm circumference for detection of severe acute malnutrition in infants aged between one and six months. Indian Pediatr 2015; 52(6): 528–532.

14.

World Health Organization . Guideline: assessing and managing children at primary health-care facilities to prevent overweight and obesity in the context of the double burden of malnutrition. Geneva: World Health Organization, 2017. Available from: https://iris.who.int/handle/10665/259133

15.

Bindu Nair

Elizabeth

Geetha

, et al. Mid arm circumference (MAC) and body mass index (BMI) – the two important auxologic parameters in neonates. J Trop Pediatr 2006; 52(5): 341–345. DOI: 10.1093/tropej/fml023.

16.

Daly-Wolfe

Jordan

Slater

, et al. Mid-arm circumference is a reliable method to estimate adiposity in preterm and term infants. Pediatr Res 2015; 78: 336–341. DOI: 10.1038/pr.2015.103.

17.

Radhakrishnan

Nagaraja

. Modified Kuppuswamy socioeconomic scale 2023: stratification and updates. Int J Community Med Public Health 2023; 10: 4415–4418.

18.

Chehab

Ferrara

Greenberg

, et al. Glycemic control trajectories and risk of perinatal complications among individuals with gestational diabetes. JAMA Netw Open 2022; 5(9): e2233955.

19.

Kutchi

Chellammal

Akila

. Maternal obesity and pregnancy outcome: in perspective of new asian Indian guidelines. J Obstet Gynecol India 2020; 70(2): 138–144.

20.

Chopra

Kaur

Singh

, et al. Population estimates, consequences, and risk factors of obesity among pregnant and postpartum women in India: results from a national survey and policy recommendations. Int J Gynecol Obstet 2020; 151(S1): 57–67.

21.

Nouhjah

Shahbazian

Latifi

, et al. Body mass index growth trajectories from birth through 24 months in Iranian infants of mothers with gestational diabetes mellitus. Diabetes Metab Syndr 2019; 13(1): 408–412.

22.

Andersson-Hall

Järvinen

EAJ

Bosaeus

, et al. Maternal obesity and gestational diabetes mellitus affect body composition through infancy: the PONCH study. Pediatr Res 2019; 85(3): 369–377.

23.

Kelsey

Zaepfel

Bjornstad

, et al. Age-related consequences of childhood obesity. Gerontology (Basel) 2014; 60(3): 222–228.

24.

Alaaraj

Soliman

Alyafei

, et al. Postnatal growth and weight gain in term and near-term infants with severe neonatal hypoglycemia: a comparison between offspring of diabetic and non-diabetic mothers. InEndocrine Abstracts 2024; 99: 2024072.

25.

Dode

MASO

Santos

González

. Anthropometry from birth to 24 months among offspring of women with gestational diabetes: 2004 Pelotas Birth Cohort. J Dev Orig Health Dis 2011; 2(03): 144–151.

26.

Liu

Wei

, et al. Association of gestational diabetes mellitus with offspring weight status across infancy: a prospective birth cohort study in China. BMC Pregnancy Childbirth 2021; 21(1): 21.

27.

Krishnaveni

Hill

Leary

, et al. Anthropometry, glucose tolerance, and insulin concentrations in Indian children: relationships to maternal glucose and insulin concentrations during pregnancy. Diabetes Care 2005; 28(12): 2919–2925.

28.

Uebel

Pusch

Gedrich

, et al. Effect of maternal obesity with and without gestational diabetes on offspring subcutaneous and preperitoneal adipose tissue development from birth up to year-1. BMC Pregnancy Childbirth 2014; 14: 138.

29.

Touger

Looker

Krakoff

, et al. Early growth in offspring of diabetic mothers. Diabetes Care 2005; 28(3): 585–589.

30.

Praful

Somanath

Sharmila

, et al. Early postnatal growth trajectories of infants of diabetic mothers. Indian J Pediatr 2025; 92: 105. DOI: 10.1007/s12098-024-05322-8.

31.

Huang

Luo

Lee

, et al. Factors affecting the growth of children till the age of three years with overweight whose mothers have diabetes mellitus: a population-based cohort study. BMC Pediatr 2021; 21(1): 298.

32.

Dugas

Perron

Kearney

, et al. Postnatal prevention of childhood obesity in offspring prenatally exposed to gestational diabetes mellitus: where are we now. Obes Facts 2017; 10(4): 396–406.