
==== Front
Sci Rep
Sci Rep
Scientific Reports
2045-2322
Nature Publishing Group UK London

72223
10.1038/s41598-024-72223-3
Article
Maternal glucose homeostasis during pregnancy in women with overweight or obesity and offspring metabolic health
Mogensen Christina Sonne 1
Nygaard Malene nygaard@nexs.ku.dk

1
Kampmann Ulla 23
Mølgaard Christian 1
Magkos Faidon 1
Geiker Nina Rica Wium 145
1 https://ror.org/035b05819 grid.5254.6 0000 0001 0674 042X Department of Nutrition, Exercise and Sports, Faculty of Science, University of Copenhagen, Rolighedsvej 26, 1958 Frederiksberg C, Copenhagen, Denmark
2 grid.7048.b 0000 0001 1956 2722 Department of Clinical Medicine, Aarhus University Hospital, Aarhus University, Aarhus, Denmark
3 grid.154185.c 0000 0004 0512 597X Steno Diabetes Center Aarhus, Aarhus, Denmark
4 Centre for Childhood Health, Copenhagen, Denmark
5 https://ror.org/05bpbnx46 grid.4973.9 0000 0004 0646 7373 Dietetic and Clinical Nutrition Research Unit, Copenhagen University Hospital Herlev-Gentofte, Herlev, Denmark
13 9 2024
13 9 2024
2024
14 213982 5 2024
4 9 2024
© The Author(s) 2024
2024
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Gestational diabetes mellitus (GDM) adversely affects offspring glucose homeostasis and risk of developing obesity. Here, we examined the association between glycemia in pregnant women with overweight or obesity without GDM and offspring metabolic health. Maternal fasting glucose concentrations and glucose 2-h after an oral glucose tolerance test (OGTT) were measured in 208 women with a pre-pregnancy body mass index (BMI) of 28–45 kg/m2 without GDM. Offspring outcomes were collected at birth, 3, and 5 years of age. Linear mixed models with time as fixed factor and subject ID as random effects were used for analysis. No associations were found between maternal fasting or 2-h glucose concentrations with offspring glucose and insulin concentrations from birth to 5 years of age. However, maternal fasting glucose in GW 28 and 36, and 2-h OGTT glucose in GW 28 were positively associated with C-peptide concentration at birth. Maternal fasting glucose concentrations in GW 28 and 36 were positively associated with weight-for-length, and maternal fasting glucose in GW 36 was associated with BMI z-score at birth. In summary, blood glucose in pregnant women with overweight or obesity is positively associated with offspring C-peptide concentration, weight-for-length, and BMI z-score at birth, even in the absence of GDM.

Keywords

Prevention of childhood obesity
Fetal programming
Maternal overweight/obesity
Maternal glucose homeostasis
Childhood glucose homeostasis
Subject terms

Biomarkers
Endocrinology
Endocrine system and metabolic diseases
http://dx.doi.org/10.13039/501100009708 Novo Nordisk Fonden The Nordea FoundationDanish Pork Levy FoundationDanish Agriculture & Food CouncilDanish Dairy FoundationLEGO CharityPharmaNordPharmo Vitalissue-copyright-statement© Springer Nature Limited 2024
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pmcIntroduction

The prevalence of overweight and obesity among pregnant women is increasing1. In 2018, about 40% of women in the reproductive age in the United States (aged 20–39 years) had obesity (BMI ≥ 30 kg/m2)2 while in Denmark in 2021, about 40% of women aged 25–34 years had overweight (BMI ≥ 25 kg/m2) and 17% had obesity (BMI ≥ 30 kg/m2)3. Almost 6 out of 10 women with obesity prior to pregnancy exceed the recommendation for gestational weight gain (GWG)4. Maternal obesity and excessive GWG both increase the risk of pregnancy complications and offspring obesity during childhood and adulthood5–8.

Insulin sensitivity decreases as gestation proceeds favoring a channeling of nutrient supply to the developing fetus9. High pre-pregnancy BMI and excessive GWG, alone or combined, are associated with decreased maternal insulin sensitivity which, during pregnancy, may lead to gestational diabetes mellitus (GDM)10,11. Screening tools, as well as the threshold for GDM, differ across countries. World Health Organization (WHO) recommends a universal screening tool and defines GDM as a glucose concentration ≥ 10.0 or ≥ 8.5 mmol/L, 1-h and 2-h after an oral glucose tolerance test (OGTT) or a fasting glucose concentration of ≥ 5.1 mmol/L12. In Denmark, a selective screening program is performed in women with one or more risk factors (e.g. BMI ≥ 27 kg/m2) for developing GDM. In Denmark, GDM is diagnosed if 2-h glucose concentration after an OGTT is ≥ 9.0 mmol/L13.

Maternal glucose dysregulation during pregnancy is hypothesized to induce fetal hyperglycemia and hyperinsulinemia, stimulating fetal growth and leading to increased birthweight14. Offspring exposed to GDM in utero (as defined by WHO in 2013) have higher glucose concentrations after an OGTT and higher BMI at 7 years of age compared to offspring of women without GDM, but not different fasting glucose concentration15. This suggests that exposure to GDM in the intrauterine environment can have long-term consequences for offspring glucose regulation and growth. Moreover, across the range of maternal glucose values, fasting glucose concentrations are positively associated with risk of childhood obesity at age 5–7 and 10–14 years16,17.

As the diagnostic criteria for GDM differ across countries, it is important to better understand the relationship between glucose homeostasis during pregnancy in non-GDM women with overweight or obesity and longitudinal offspring health outcomes in early childhood. Therefore, in this study, we examined the association of maternal fasting glucose concentrations in gestational weeks (GW) 15, 28, 36, and 2-h glucose concentrations after an OGTT in GW 28 with markers of metabolic health in offspring born to women with overweight or obesity at birth, 3, and 5 years of age. This longitudinal observation of the offspring allowed us to evaluate not only the relationships at birth but also their possible persistence throughout early childhood.

Methods

Study design

This paper includes data from the APPROACH (An Optimized Programming of Healthy Children) study, which was a randomized controlled trial (RCT) conducted at Copenhagen University Hospital Herlev-Gentofte and the University of Copenhagen, Department of Nutrition, Exercise, and Sports (Copenhagen, Denmark). The RCT included a dietary intervention in women during pregnancy and was conducted from January 2014 to December 2017. This was followed by a longitudinal cohort study of the offspring born to participating women. Data on the offspring was collected at birth, 3 and 5 years of age, and collected from June 2014 to January 2023. A detailed description of the APPROACH study design and methodology can be found elsewhere18. The study was approved by the Ethical Committee of the Capital Region of Denmark (H-3–2013-119) and was registered at ClinicalTrials.gov (NCT01894139). All study procedures were conducted in accordance with the Helsinki II Declaration.

Participants

Pregnant women received information about the study during their trans-nuchal scan (from 11 weeks and 4 days to 13 weeks and 6 days of gestation). Women were eligible for inclusion if they had a singleton pregnancy, had a pre-pregnancy BMI between 28–45 kg/m2, and were older than 18 years. The women and their partner received both written and oral information about the study before signing an informed consent. Women were excluded if they developed GDM, defined in Denmark as a 2-h OGTT glucose concentration ≥ 9.0 mmol/L13, at any time point during the study.

Intervention

Included women were allocated in groups of 4–8 and subsequently randomized in a 1:1 ratio to one of two diets: i) the intervention diet characterized by high protein content (25% of total energy intake) and a low glycemic index of ~ 45, or ii) the control diet, with moderate protein content (18% of total energy intake) and a moderate glycemic index of ~ 54, aligning with the Nordic Nutritional Recommendations from 201219. Fat provided ~ 30% of calories in both diets. The women received nutrition guidance from a clinical dietician and were instructed to consume the diets ad libitum18.

Maternal anthropometry

At the baseline visit (GW 15), height was measured to the nearest 0.5 cm by a wall-mounted stadiometer (Seca, Germany), and body weight was measured to the nearest 0.1 kg by a medical scale (Tanita, Illinois, USA). Body weight was subsequently measured prior to every counseling session with the clinical dietitian (up to nine times during pregnancy). Accumulated GWG in GW 15, 28, and 36 was calculated as measured body weight at these time points minus pre-pregnancy body weight. Pre-pregnancy weight was self-reported or obtained by the general practitioner in GW 6–8. These values correlated with measured weight at GW 15 (R2 = 0.94). BMI was calculated as weight (kg) divided by height squared (m2). Parity was obtained by questionnaires and categorized as 0, 1, or ≥ 2.

Offspring anthropometry

At birth, midwives at the Copenhagen University Hospital Herlev-Gentofte obtained anthropometric measurements from the offspring. At 3 years (± 4 weeks) and 5 years (± 4 weeks) of age, anthropometric measurements were obtained by trained staff at the University of Copenhagen, Department of Nutrition, Exercise, and Sports, Copenhagen, Denmark.

At birth, the length was measured by using a non-elastic measuring tape to the nearest 0.5 cm. At 3 and 5 years of age, height was measured by using a wall-mounted stadiometer to the nearest 0.5 cm (Seca, Germany). Body weight at birth was measured by a medical beam scale (Tanita, USA) to the nearest 10 g and at 3, and 5 years of age, body weight was measured by a bioelectrical impedance scale (InBody570, USA) to the nearest 100 g.

Z-scores were calculated according to the WHO 2006 standards20 using the WHO Anthro software21 which includes children up to 60 months (5 years) of age. The WHO 2007 Reference for School-age Children and Adolescents (5 to 19 years) was used to calculate z-scores in children aged 61 months22.

Maternal blood markers

In GW 15, 28, and 36, venous blood samples from the women were drawn after an overnight fast (≥ 10 h) at the Copenhagen University Hospital Herlev-Gentofte. Samples were analyzed for fasting plasma glucose, glycated hemoglobin (HbA1c), C-peptide, total cholesterol, low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, very-low lipoprotein (VLDL) cholesterol, and triglycerides (TG). Moreover, the participants performed a 2-h 75-g OGTT in GW 28.

Offspring blood markers

Umbilical cord blood was collected at birth, and venous blood samples were collected at 3 years of age (after a 2-h fast) and at 5 years of age (after an overnight fast of ≥ 8 h). Samples were analyzed for fasting glucose, insulin, C-peptide, insulin growth factor-1 (IGF-1), insulin growth factor binding protein-3 (IGFBP-3), C-reactive protein (CRP), total cholesterol, LDL-cholesterol, HDL-cholesterol, and TG. All analyses were measured in plasma, except for glucose which was analyzed in whole blood.

Glucose at birth was measured using a colorimetric method, on a Pentra 400 analyzer (Horiba ABX). Fasting glucose at 3 and 5 years was analyzed on the same day as the blood sampling with Hemocue Glucose 201+ (HemoCue, Danmark).

Insulin, C-peptide, IGF-1, and IGFBP-3 were analyzed on Immulite 2000 (Siemens Healthcare, UK) and total cholesterol, LDL-cholesterol, HDL-cholesterol, TG, and CRP were analyzed on Pentra 400 (Horiba ABX SAS, France). For insulin concentration below 14.4 pmol/L (limit of detection), serum was used and analyzed with an ultrahigh sensitive insulin ELISA kit from Mercodia AB (cat no. 10–1132-01).

Statistical analysis

In this secondary analysis, the two diet arms of the primary RCT were pooled because there was no effect of the dietary intervention on maternal blood metabolic biomarkers18. To eliminate potential overlooked effects of the intervention, we adjusted for the allocated diet intervention group.

Histograms were used to visually evaluate data distributions. Characteristics of pregnant women and offspring are presented as mean ± standard deviation (SD) for normally distributed variables and as median with quartiles (Q1;Q3) for skewed variables. Categorical variables are presented as absolute and relative frequencies.

Available case analysis was carried out using a linear mixed model that included time as a fixed factor and subject ID as a random effect to examine the association of maternal fasting glucose concentrations in GW 15, GW 28, GW 36, and 2-h OGTT glucose concentration in GW 28 with offspring metabolic biomarkers and BMI z-score from birth to 5 years of age. A simple linear regression model was utilized to examine the association of maternal glycemia and weight-for-length at birth. We evaluated the models for normal distribution using qq-plots and residual plots to check for heteroscedasticity and linearity. If the model did not fulfill the model assumptions, outcomes were log-transformed, and β-estimates and 95% confidence intervals (CI) were back-transformed and are expressed as percentage changes. Otherwise, data is reported as β-estimates with 95% CI and corresponding p-values. The analyses were adjusted for potential confounders, with Model 1 being crude (unadjusted) and Model 2 being adjusted for pre-pregnancy BMI, allocated diet intervention group, accumulated gestational weight gain, gestational age, maternal age, parity, and offspring sex. A p-value < 0.05 was used to determine statistical significance. All statistical analyses were performed using R studio (version 4.2.2).

Results

A total of 209 offspring were born (one stillborn) (Fig. 1). Of the 208 mother–offspring dyads, maternal blood samples were collected from 203 women in GW 15, 200 women in GW 28, and 191 women in GW 36; out of the 208 offspring, 42 (~ 20%) dropped out before the 3-year follow-up and 25 more (~ 15%) dropped out before the 5-year follow-up. Thus, a total of 208, 166, and 141 mother–offspring dyads at birth, 3, and 5 years, respectively, were included in the analysis.Fig. 1 Flow chart.

Maternal characteristics

The pregnant women were 30.7 (± 4.79) years old and had a pre-pregnancy BMI of 32.8 (31.1;35.9) kg/m2. Maternal fasting plasma glucose concentrations in GW 15, 28, and 36 were 5.04 (± 0.38), 4.93 (± 0.36), and 4.89 (± 0.39) mmol/L, respectively. Glucose concentration 2-h after the OGTT in GW 28 was 6.28 (± 0.97) mmol/L (Table 1).Table 1 Maternal characteristics.

	Pre-pregnancy	Gestational week 15	Gestational week 28	Gestational week 36	
	N		N		N		N		
Age, years	208	30.69 ± 4.79		–		–		–	
Body height, m	208	1.68 ± 0.06		–		–		–	
Body weight, kg	208	96.07 ± 12.71	204	96.26 ± 12.49	204	99.31 ± 12.21	190	102.70 ± 12.82	
Gestational weight gain, kg	208	–	204	0.37 ± 3.07	204	3.20 ± 4.45	190	6.55 ± 5.31	
BMI, kg/m2	208	32.84 (31.12;35.91)	204	34.10 ± 3.83	204	35.1 ± 3.73	190	36.3 ± 3.99	
Parity, no. (%)	207			–		–		–	
 0		115 (55.55%)							
 1		71 (34.30%)							
 ≥ 2		21 (10.15%)							
Fasting glucose, mmol/L		–	203	5.04 ± 0.38	200	4.93 ± 0.36	191	4.89 ± 0.39	
HbA1C, mmol/mol		–	203	31.99 ± 3.05	201	30.94 ± 3.27	192	33.59 ± 3.94	
2-h glucose*, mmol/L		–			186	6.28 ± 0.97		–	
C-peptide, pmol/L		–	190	518.0 (415.5;682.5)	185	669 (549;857)	179	854 (654;1045)	
Cholesterol, mmol/L		–	203	5.07 ± 0.91	201	6.10 ± 1.17	193	6.48 ± 1.32	
TG, mmol/L		–	203	1.48 ± 0.53	201	2.14 ± 0.71	193	2.74 ± 1.05	
HDL, mmol/L		–	203	1.54 ± 0.32	201	1.71 ± 0.40	193	1.65 ± 0.40	
LDL, mmol/L		–	203	2.87 ± 0.84	201	3.44 ± 1.11	189	3.65 ± 1.26	
VLDL, mmol/L		–	203	0.67 ± 0.24	201	0.96 ± 0.32	193	1.23 ± 0.47	
Pre-pregnancy outcomes are obtained at screening visit (gestational week 8–14). Data are presented as mean ± standard deviation for normally distributed variables, and as median (Q1;Q3) for skewed variables, or as absolute numbers and percentages (%) for categorical variables.

BMI Body mass index, HbA1c Hemoglobin A1c, HDL High-density lipoprotein, LDL Low-density lipoprotein, OGTT Oral glucose tolerance test, TG Triglycerides, VLDL Very-low-density lipoprotein.

*Measured after an OGTT.

Offspring characteristics

At birth, 3, and 5 years of age, offspring glucose concentrations were 5.48 (± 0.37), 5.04 (± 0.57), and 5.08 (± 0.50) mmol/L, respectively; and insulin concentrations were 30.9 (19.1;64.1), 47.0 (19.3;90.5), and 16.2 (12.3;22.8) pmol/L, respectively. Offspring BMI z-scores were -0.11 (-0.76;0.47), 0.61 (± 0.95), and 0.17 (± 0.98) at birth, 3, and 5 years, respectively (Table 2).Table 2 Offspring characteristics at birth, 3, and 5 years of age.

	Birth (n = 208)	3 years (n = 156)	5 years (n = 141)	
N		N		N		
Gender, girls (%)		94 (45)		62 (40)		55 (39)	
Age, days	208	0	156	1100 ± 13.3	141	1830 ± 14.0	
Gestational age, days	208	282.5 (276.0;288.0)					
Weight-for-length z-score	204	− 0.68 ± 1.24					
Length/Height, cm	207	52.0 (51.00;53.00)	156	96.4 ± 3.57	140	113 ± 3.99	
Body weight, kg	207	3.60 (3.32;3.90)	156	15.3 ± 1.57	141	19.9 ± 2.61	
Length/height z-score	207	1.12 (0.59;2.07)	156	0.18 ± 0.94	141	0.62 ± 0.85	
Weight z-score	207	0.59 (0.03;1.21)	156	0.54 ± 0.81	140	0.50 ± 0.89	
BMI z-score	207	− 0.11 (-0.76;0.47)	156	0.61 ± 0.95	140	0.17 ± 0.98	
Glucose, mmol/L	127	5.48 ± 0.37	119	5.04 ± 0.57	94	5.08 ± 0.50	
Insulin, pmol/L	123	30.90 (19.05;64.05)	114	47.00 (19.32;90.50)	83	16.2 (12.30;22.75)	
C-peptide, pmol/L	126	318.0 (212.5;454.5)	116	408 (229.2;605.0)	85	216 ± 81.9	
IGF-1, ng/mL	125	55.85 ± 22.33	38	74.76 ± 29.18	85	94.1 ± 28.6	
IGFBP-3, ug/mL	126	1.70 ± 0.39	38	3.24 ± 0.68	85	3.85 ± 0.68	
CRP, mg/mL	128	0.14 (0.13;0.16)	114	0.28 (0.14;0.72)	86	0.22 (0.12;0.62)	
Cholesterol, mmol/L	128	1.65 ± 0.41	116	3.76 ± 0.62	86	3.59 ± 0.56	
TG, mmol/L	128	0.51 (0.39;0.62)	116	0.78 (0.56;1.03)	86	0.52 (0.42;0.66)	
HDL, mmol/L	128	0.65 ± 0.17	116	1.23 ± 0.25	86	1.38 ± 0.24	
LDL, mmol/L	128	0.66 ± 0.23	116	2.16 ± 0.55	86	2.17 ± 0.52	
Data are presented as mean ± standard deviation for normally distributed variables, and as median (Q1;Q3) for skewed variables, or as absolute numbers and percentages (%) for categorical variables.

CRP C-reactive protein, HDL High density lipoprotein, IGF-1 Insulin-like Growth factor-1, IGFBP-3 Insulin-like growth factor binding protein 3, LDL Low density lipoprotein, TG Triglycerides.

Maternal fasting glucose in GW 15 and offspring outcomes

No association was found between maternal fasting glucose concentration in GW 15 and offspring metabolic biomarkers. There was a positive association with offspring BMI z-score at birth, nonetheless, the significant association disappeared when adjusting for confounders (Table 3).Table 3 Associations between maternal fasting glucose in GW 15 and offspring outcomes.

	Model 1	Model 2	
N1	β-estimate (95%CI)	P-value	N1	β-estimate (95%CI)	P-value	
Glucose, mmol/L	331			322			
Birth		0.08 (− 0.36;0.52)	0.716		0.10 (− 0.34;0.54)	0.651	
3y		0.08 (− 0.36;0.52)	0.720		0.13 (− 0.31;0.57)	0.565	
5y		0.07 (− 0.46;0.60)	0.797		0.10 (− 0.43;0.62)	0.728	
Insulin, pmol/L*	316			306			
Birth		1.19 (0.79;1.80)	0.407		1.23 (0.81;1.87)	0.344	
3y		1.15 (0.76;1.73)	0.507		1.16 (0.77;1.77)	0.485	
5y		1.03 (0.62;1.72)	0.902		1.04 (0.62;1.74)	0.888	
C-peptide, pmol/L*	323			313			
Birth		1.20 (0.93;1.56)	0.166		1.22 (0.94;1.58)	0.139	
3y		1.16 (0.89;1.50)	0.271		1.18 (0.91;1.53)	0.224	
5y		1.12 (0.81;1.54)	0.492		1.13 (0.82;1.55)	0.477	
IGF-1, ng/mL	245			237			
Birth		− 1.45 (− 13.09;10.17)	0.809		− 0.82 (− 12.18;10.67)	0.890	
3y		− 11.83 (− 35.17;11.52)	0.324		− 11.78 (− 35.09;11.02)	0.327	
5y		0.91 (− 13.31;15.10)	0.901		0.60 (− 13.34;14.80)	0.935	
IGFBP-3, ug/mL	246			238			
Birth		0.01 (− 0.24;0.26)	0.932		0.04 (− 0.21;0.29)	0.773	
3y		− 0.19 (− 0.68;0.30)	0.457		− 0.16 (− 0.66;0.33)	0.528	
5y		0.19 (− 0.12;0.49)	0.232		0.19 (− 0.11;0.50)	0.228	
CRP, mg/mL*	324			314			
Birth		1.04 (0.67;1.62)	0.855		1.04 (0.67;1.63)	0.855	
3y		0.78 (0.50;1.21)	0.272		0.77 (0.48;1.21)	0.263	
5y		0.67 (0.39;1.14)	0.140		0.65 (0.38;1.13)	0.136	
BMI z-score	492			482			
Birth		0.43 (0.03;0.83)	0.038		0.11 (− 0.34;0.57)	0.630	
3 years		− 0.30 (− 0.75;0.15)	0.191		− 0.34 (− 0.81;0.12)	0.159	
5 years		− 0.07 (− 0.55;0.41)	0.767		− 0.16 (− 0.62;0.29)	0.492	
Weight-for-length2	195			190			
Birth		0.46 (− 0.00;0.93)	0.052		0.42 (− 0.06;0.90)	0.083	
Data were reported as estimates with 95% confidence intervals (CIs) and p-values using a linear mixed model with random effects of ID.

Model 1: Crude (unadjusted),

Model 2: Adjusted for pre-pregnancy BMI, allocated intervention group, accumulated gestational weight gain in gestational week 15, gestational age, maternal age, parity, and offspring sex.

CRP C-reactive protein, IGF-1 Insulin-like Growth factor-1, IGFBP-3 Insulin-like growth factor binding protein 3.

1Includes all observations at any time point.

2A simple linear regression model was used.

*Unfitted models were log-transformed and estimates and 95% CIs were back-transformed and expressed as %.

Significant values are in bold.

Maternal fasting glucose in GW 28 and offspring outcomes

Maternal fasting glucose concentration in GW 28 was associated with increased offspring C-peptide at birth, and decreased CRP at 3 and 5 years of age. Moreover, BMI z-score and weight-for-length increased at birth for every 1 mmol/L increase of maternal fasting glucose, however, statistical significance for BMI z-score was lost after adjusting for confounders (Table 4).Table 4 Associations between maternal fasting glucose in GW 28 and offspring outcomes.

	Model 1	Model 2	
N1	β-estimate (95%CI)	P-value	N1	β-estimate (95%CI)	P-value	
Glucose, mmol/L	326			321			
Birth		− 0.10 (− 0.56;0.37)	0.688		− 0.06 (− 0.52;0.41)	0.815	
3y		− 0.13 (− 0.60;0.34)	0.584		− 0.10 (− 0.57;0.38)	0.696	
5y		0.20 (− 0.37;0.77)	0.495		0.28 (− 0.30;0.86)	0.350	
Insulin, pmol/L*	310			304			
Birth		1.50 (0.96;2.33)	0.076		1.50 (0.96;2.34)	0.081	
3y		1.02 (0.65;1.60)	0.935		1.01 (0.64;1.61)	0.958	
5y		0.90 (0.51;1.60)	0.716		0.88 (0.49;1.60)	0.682	
C-peptide, pmol/L*	317			311			
Birth		1.62 (1.23;2.13)	 < 0.001		1.62 (1.23;2.13)	 < 0.001	
3y		1.04 (0.79;1.38)	0.780		1.05 (0.77;1.39)	0.765	
5y		1.11 (0.78;1.60)	0.548		1.10 (0.77;1.60)	0.608	
IGF-1, ng/mL	242			238			
Birth		4.23 (− 7.97;16.45)	0.501		1.38 (− 10.69; 13.48)	0.827	
3y		− 22.79 (− 50.28;4.67)	0.105		− 22.80 (− 50.16;3.81)	0.105	
5y		7.66 (− 8.14;23.46)	0.347		4.74 (− 11.18;20.74)	0.570	
IGFBP-3, ug/mL	243			239			
Birth		0.09 (− 0.17;0.35)	0.509		0.05 (− 0.21;0.32)	0.698	
3y		− 0.31 (− 0.88;0.26)	0.296		− 0.30 (− 0.87;0.27)	0.319	
5y		0.20 (− 0.13;0.54)	0.240		0.17 (− 0.17;0.51)	0.345	
CRP, mg/mL*	318			312			
Birth		1.13 (0.71;1.80)	0.600		1.10 (0.69;1.76)	0.690	
3y		0.55 (0.34; 0.89)	0.016		0.51 (0.32;0.84)	0.010	
5y		0.40 (0.22;0.73)	0.003		0.38 (0.20;0.70)	0.002	
BMI z-score	483			477			
Birth		0.57 (0.192; 0.95)	0.003		0.30 (− 0.15;0.74)	0.198	
3 years		− 0.24 (− 0.66; 0.18)	0.270		− 0.32 (− 0.78;0.15)	0.189	
5 years		− 0.26 (− 0.70; 0.19)	0.260		− 0.38 (− 0.83;0.06)	0.101	
Weight-for-length2	193			191			
Birth		0.59 (0.18;1.01)	0.005		0.57 (0.14;1.00)	0.010	
Data were reported as estimates with 95% confidence intervals (CIs) and p-values using a linear mixed model with random effects of ID.

Model 1: Crude (unadjusted),

Model 2: Adjusted for pre-pregnancy BMI, allocated intervention group, accumulated gestational weight gain in gestational week 28, gestational age, maternal age, parity, and offspring sex.

CRP C-reactive protein, IGF-1, Insulin-like Growth factor-1, IGFBP-3 Insulin-like growth factor binding protein 3.

Significant values are in bold.

1Includes all observations at any time point.

2A simple linear regression model was used.

*Unfitted models were log-transformed and estimates and 95% CIs were back-transformed and expressed as %.

Maternal fasting glucose in GW 36 and offspring outcomes

Maternal fasting glucose concentration in GW 36 was associated with an increase in offspring BMI z-score, weight-for-length, C-peptide, and IGF-1 at birth. In the unadjusted model, each 1.0 mmol/L increase in maternal fasting glucose concentration in GW 36 was associated with a decrease in offspring CRP at 5 years of age, however, when adjusting for confounders, the association was attenuated (Table 5).Table 5 Associations between maternal fasting glucose in GW 36 and offspring outcomes.

	Model 1	Model 2	
N1	β-estimate (95%CI)	P-value	N1	β-estimate (95%CI)	P-value	
Glucose, mmol/L	321			313			
Birth		− 0.26 (− 0.69;0.17)	0.236		− 0.35 (− 0.77;0.08)	0.119	
3y		− 0.00 (− 0.46;0.45)	0.992		− 0.02 (− 0.47;0.44)	0.939	
5y		0.09 (− 0.43;0.61)	0.730		0.14 (− 0.38;0.67)	0.603	
Insulin, pmol/L*	305			296			
Birth		1.41 (0.95;2.09)	0.089		1.34 (0.90;2.01)	0.161	
3y		1.02 (0.67;1.55)	0.934		1.06 (0.69;1.64)	0.800	
5y		0.83 (0.51;1.37)	0.469		0.84 (0.50;1.41)	0.510	
C-peptide, pmol/L*	312			303			
Birth		1.41 (1.10;1.82)	0.008		1.37 (1.06;1.77)	0.020	
3y		0.96 (0.73;1.26)	0.773		0.98 (0.74;1.30)	0.870	
5y		0.89 (0.64;1.23)	0.478		0.88 (0.64;1.25)	0.469	
IGF-1, ng/mL	239			232			
Birth		14.45 (3.18;25.74)	0.013		13.98 (2.55;25.43)	0.021	
3y		− 10.44 (− 37.76; 16.77)	0.445		− 5.78 (− 33.59;20.40)	0.675	
5y		0.07 (− 14.06;14.17)	0.993		0.41 (− 13.93;14.96)	0.957	
IGFBP-3, ug/mL	240			233			
Birth		0.24 (− 0.00;0.48)	0.058		0.25 (0.00;0.50)	0.054	
3y		0.06 (− 0.51;0.62)	0.832		0.14 (− 0.43;0.70)	0.624	
5y		− 0.00 (− 0.30;0.30)	0.983		0.01 (− 0.30;0.31)	0.956	
CRP, mg/mL*	313			304			
Birth		1.14 (0.74;1.76)	0.556		1.14 (0.73;1.78)	0.571	
3y		0.72 (0.45;1.16)	0.177		0.74 (0.45;1.21)	0.234	
5y		0.58 (0.34;0.99)	0.049		0.59 (0.34;1.04)	0.072	
BMI z-score	462			448			
Birth		0.64 (0.29;0.98)	 < 0.001		0.54 (0.10;0.97)	0.019	
3 years		− 0.13 (− 0.52;0.27)	0.527		− 0.15 (− 0.61;0.31)	0.535	
5 years		− 0.21 (− 0.62;0.21)	0.337		− 0.28 (− 0.72;0.16)	0.218	
Weight-for-length2	186			181			
Birth		0.56 (0.18;0.94)	0.004		0.55 (0.16;0.94)	0.006	
Data were reported as estimates with 95% confidence intervals (CIs) and p-values using a linear mixed model with random effects of ID.

Model 1: Crude (unadjusted),

Model 2: Adjusted for pre-pregnancy BMI, allocated intervention group, accumulated gestational weight gain in gestational week 36, gestational age, maternal age, parity, and offspring sex.

CRP C-reactive protein, IGF-1 Insulin-like Growth factor-1, IGFBP-3 Insulin-like growth factor binding protein 3.

1Includes all observations at any time point.

2A simple linear regression model was used.

*Unfitted models were log-transformed and estimates and 95% CIs were back-transformed and expressed as %.

Significant values are in bold.

Maternal 2-h glucose concentration after an OGTT in GW 28 and offspring outcomes

Maternal 2-h glucose after an OGTT was associated with an increase in offspring C-peptide and IGFBP-3 at birth, and a decrease in CRP at 5 years of age. No associations were found between 2-h glucose concentration after an OGTT and BMI z-score or weight-for-length (Table 6).Table 6 Associations between maternal 2-h glucose after an OGTT in GW28 and offspring outcomes.

	Model 1	Model 2	
N1	β-estimate (95%CI)	P-value	N1	β-estimate (95%CI)	P-value	
Glucose, mmol/L	317			311			
Birth		− 0.05 (− 0.22;0.13)	0.588		− 0.01 (− 0.19;0.16)	0.889	
3y		− 0.04 (− 0.21;0.13)	0.647		0.01 (− 0.16;0.18)	0.914	
5y		− 0.07 (− 0.27;0.13)	0.488		− 0.05 (− 0.24;0.15)	0.643	
Insulin, pmol/L*	302			295			
Birth		1.17 (0.99;1.38)	0.071		1.18 (1.00;1.40)	0.052	
3y		0.99 (0.841;1.17)	0.910		0.97 (0.82;1.15)	0.739	
5y		0.97 (0.79;1.19)	0.774		0.97 (0.80;1.20)	0.804	
C-peptide, pmol/L*	308			301			
Birth		1.17 (1.06;1.30)	0.003		1.19 (1.08;1.32)	0.001	
3y		1.01 (0.91;1.11)	0.904		1.00 (0.90;1.10)	0.945	
5y		0.95 (0.84;1.19)	0.400		0.95 (0.84;1.08)	0.415	
IGF-1, ng/mL	233			229			
Birth		2.97 (− 1.57;7.52)	0.205		2.66 (− 1.96;7.16)	0.257	
3y		2.23 (− 5.62;10.07)	0.582		2.21 (− 5.81;9.70)	0.582	
5y		− 4.41 (− 9.93;1.13)	0.122		− 4.82 (− 10.50;0.48)	0.089	
IGFBP-3, ug/mL	234			230			
Birth		0.11 (0.02;0.20)	0.025		0.11 (0.01;0.20)	0.031	
3y		0.10 (− 0.06;0.27)	0.213		0.10 (− 0.06;0.26)	0.214	
5y		− 0.07 (− 0.11;0.04)	0.209		− 0.08 (− 0.19;0.03)	0.182	
CRP, mg/mL*	309			302			
Birth		0.95 (0.80;1.13)	0.568		0.96 (0.80;1.14)	0.640	
3y		0.84 (0.71;1.01)	0.060		0.85 (0.71;1.02)	0.085	
5y		0.72 (0.58;0.89)	0.003		0.71 (0.57;0.88)	0.003	
BMI z-score	455			446			
Birth		0.05 (− 0.11;0.20)	0.550		0.09 (− 0.08;0.26)	0.289	
3 years		− 0.05 (− 0.22;0.12)	0.551		0.03 (− 0.14;0.21)	0.707	
5 years		− 0.08 (− 0.27;0.10)	0.370		− 0.02 (− 0.19;0.15)	0.849	
Weight-for-length2	180			168			
Birth		0.07 (− 0.11;0.24)	0.472		0.02 (− 0.15;0.19)	0.831	
Data were reported as estimates with 95% confidence intervals (CIs) and p-values using a linear mixed model with random effects of ID.

Model 1: Crude (unadjusted),

Model 2: Adjusted for pre-pregnancy BMI, allocated intervention group, accumulated gestational weight gain in gestational week 28, gestational age, maternal age, parity, and offspring sex.

CRP C-reactive protein, IGF-1 Insulin-like Growth factor-1, IGFBP-3 Insulin-like growth factor binding protein 3.

1Includes all observations at any time point.

2A simple linear regression model was used.

*Unfitted models were log-transformed and estimates and 95% CIs were back-transformed and expressed as %.

Significant values are in bold.

Discussion

In the current study, we investigated markers of metabolic health in offspring born to women with overweight or obesity but without GDM. We found a positive association between maternal fasting glucose in GW 28 and 36 with offspring weight-for-length at birth, and between maternal fasting glucose in GW 15, 28, and 36 with offspring BMI z-score at birth. However, the association with BMI z-score at birth attenuated after adjusting for confounders in GW 15 and 28. We did not find any significant associations between maternal fasting glucose concentrations in GW 15, 28, 36, and 2-h glucose concentration after an OGTT with offspring glucose and insulin concentrations from birth to 5 years of age. Nevertheless, maternal fasting glucose concentrations in GW 28, 36, and 2-h glucose concentrations after an OGTT were positively associated with offspring C-peptide concentrations at birth. Moreover, we found a negative association between maternal fasting glucose concentrations in GW 28 and offspring CRP concentrations at 3 and 5 years of age, as well as a negative association between 2-h glucose concentrations after an OGTT and CRP concentrations at 5 years of age.

Contrary to C-peptide, offspring insulin concentration was not associated with maternal glucose concentrations during pregnancy. C-peptide is co-secreted in equimolar amounts with insulin from the pancreatic β-cells23, therefore, cord blood C-peptide concentration is considered an indicator of fetal β-cells function. The concentration of insulin is affected by many other physiological pathways—besides its rate of secretion—that affect the overall clearance of insulin from the circulation, which may have precluded a significant relationship from being observed. Technical errors during cord blood collection may also be involved: hemolysis in cord blood has been shown to affect insulin concentration as it causes degradation of insulin, whereas C-peptide is unaffected24. Nonetheless, exclusion of samples that were hemolysed (n = 18) did not change the results. The positive association between maternal glycemia and offspring cord C-peptide might indicate that maternal glucose concentrations are related to β-cell function in the newborn. This is in line with the hypothesis that maternal hyperglycemia during pregnancy induces hyperglycemia in the offspring, as maternal glucose freely passes the placenta and stimulates the fetal pancreas to secrete more insulin, potentially leading to hyperinsulinemia14. Here, we demonstrate the association between maternal fasting glucose and offspring C-peptide among women with overweight or obesity without GDM, which might reflect a compensatory mechanism in the offspring being exposed to higher maternal glycemia during pregnancy.

The Hyperglycemia and Adverse Pregnancy Outcome (HAPO) trial was designed to examine the association between maternal glycemia at ~ 28 weeks of gestation with the risk of adverse pregnancy outcomes25. The HAPO follow-up study of the offspring found that increasing concentrations of maternal glucose below the diagnostic threshold for diabetes—defined as fasting glucose ≥ 5.8 mmol/L or 2 h OGTT of ≥ 11.1 mmol/L—were positively associated with offspring cord C-peptide among ~ 23,000 multi-ethnic mother–offspring dyads26. Furthermore, maternal fasting glucose concentration, and glucose concentrations 1-h and 2-h after an OGTT, were positively associated with an increased odds ratio for offspring cord blood C-peptide above the 90th percentile26. Our findings are in line with these observations. Also, we did not observe any associations between maternal glucose homeostasis and offspring glucose concentrations from birth to 5 years of age. Interestingly, the HAPO follow-up study of the offspring at 10–14 years of age found a positive association of maternal fasting glucose in GW 28 and 2-h glucose concentration after an OGTT with elevated fasting glucose in the offspring. These associations persisted after adjusting for both maternal BMI in pregnancy and child BMI z-scores at follow-up27. Another HAPO follow-up study found higher 30 min, 1-h, and 2-h glucose concentrations among offspring exposed to GDM defined by the WHO criteria, compared with non-exposed offspring at 10–14 years of age28. Offspring in this age group might be challenged as puberty is a dynamic transitional phase that challenges the glucose homeostatic system, typically involving an increase in insulin resistance and a compensatory increase in insulin secretion29. This raises the possibility that programming occurring during the intrauterine life manifests in late childhood, around the time of puberty, when glucose homeostasis is challenged.

The impact of GDM on offspring glucose metabolism remains unclear due to variations in study populations, statistical power, definitions of GDM, and the timing of offspring follow-up (pre- or post-pubertal)30. However, a study involving 597 mother–offspring dyads found that offspring exposed to GDM had higher BMI, waist/height ratio, visceral adipose tissue, and subcutaneous adipose tissue at 10–16 years of age compared to those not exposed31. These factors contribute to an increased risk of developing chronic diseases later in life30.

The present study also identified positive associations between maternal fasting glucose in GW 28, and 36 with offspring weight-for-length and maternal fasting glucose in GW 36 with offspring BMI z-score at birth. This is consistent with the previous observation that maternal fasting, 1-h, and 2-h glucose concentrations are associated with the occurrence of birthweights above the 90th percentile26. In our study, we further demonstrate these relationships do not persist by 3 and 5 years of age. This is in line with a HAPO sub-study, which conducted a follow-up of 1165 offspring and found no association between maternal glycemia in GW 28 and offspring BMI z-score at the age of 2 years32. In an expanded follow-up cohort of 1320 offspring, the same study reported that maternal fasting glucose concentrations were positively associated with BMI z-score and sum of skinfolds at 5–7 years of age33. However, the associations weakened after adjusting for maternal BMI, highlighting the importance of maternal pre-pregnancy BMI as an important confounder, which might, to some extent, explain the association between maternal glycemia during pregnancy and obesity risk in the offspring33. Interestingly, the HAPO follow-up study examined offspring BMI z-score in 4832 offspring aged 10–14 years of age and found a positive association with maternal fasting and post-OGTT glucose concentrations across the glucose range. These associations persisted even after adjusting for maternal BMI16. Despite adjusting for maternal pre-pregnancy BMI in our analyses, the associations of maternal glucose concentrations with offspring BMI z-score at birth remained unaffected.

In a prospective multicenter cohort study, offspring exposed to preexisting diabetes or GDM in utero had an increased risk of being overweight or obese by the age of 5.5 years. Furthermore, as offspring grew older, the risk of developing overweight or obesity increased notably among those whose mothers had diabetes compared to those whose mothers did not have diabetes34. This finding is supported by a meta-analysis demonstrating a greater risk of overweight or obesity in offspring born to women with GDM or type 1 diabetes, and this was particularly evident during late childhood and adolescence35.

Our study found a negative association between maternal fasting glucose concentrations in GW 28 and offspring CRP concentrations at 3 and 5 years of age. A follow-up study in adult offspring, however, found no difference in CRP concentrations between those born to mothers with GDM and those without36, suggesting that the association diminishes with age. Instead, that study found higher CRP concentrations in adult offspring born by mothers with pre-pregnancy overweight compared to those with normal weight36. In our study we did not obtain data on environmental exposures (e.g. diet, physical activity) which might affect the association between maternal glucose levels and offspring CRP concentration. Therefore, further research is needed to fully understand the mechanisms behind this association.

An important strength of the present study is the longitudinal design consisting of blood sampling and anthropometric measurements of the mother–offspring dyads through pregnancy and early childhood until the age of 5 years. Furthermore, this study includes women with overweight or obesity without GDM in a Danish setting, which allowed us to investigate a wider spectrum of maternal glucose concentrations as the diagnostic threshold for GDM is higher in Denmark compared to other countries. This adds valuable information to the current literature in a high-risk population for developing GDM and the association with long-term offspring health. However, the findings presented in this paper rely on secondary analyses and should therefore be considered exploratory whereby causality cannot be established. Further, results from observational longitudinal studies are subject to confounding by co-existing behavioral and environmental factors challenging interpretation. Also, generalization of our findings to other populations is limited because of different diagnostic thresholds for GDM, and differences in methodology and sample size between studies.

In conclusion, maternal glucose concentrations during pregnancy in women with overweight or obesity who do not have GDM are positively associated with cord blood C-peptide concentration, weight-for-length, and BMI z-score in the offspring at birth, but not with glucose and insulin concentrations in the offspring during the first 5 years of life. Thus, adequate monitoring and optimal control of maternal glycemia during pregnancy may be important even when GDM is not present in women with overweight and obesity.

Acknowledgements

We thank all women participating in the study and the agreement for their children to participate in the currently ongoing cohort study. We thank the midwives and doctors at the Department of Pregnancy and Childbirth, Herlev and Gentofte Hospital, clinical dietician Annette Vedelspang, laboratory technician Søren Andresen, and ICH-GCP specialist Lene Stevner from the Department of Nutrition, Exercise and Sports, University of Copenhagen for their contributions to the APPROACH study.

Author contributions

The author contributions were as follow—N.R.W.G. conceptualized the study and acquired the funding. C.S.M. and M.N. performed the data analysis and drafted the manuscript; F.M., N.R.W.G., C.M., and U.K. reviewed and edited the manuscript; C.S.M. and M.N. had full access to the data in the study and had the responsibility for the integrity of the data analysis. The corresponding author had complete access to all study data and final responsibility for submission. All authors read and approved the final manuscript.

Funding

The Novo Nordisk Foundation funded this follow-up study of the offspring, while the APPROACH intervention study received support from The Nordea Foundation, Danish Pork Levy Foundation, Danish Agriculture & Food Council, Danish Dairy Foundation, LEGO Charity, PharmaNord, and Pharmo Vital. The funders played no role in study design, data collection, analysis, interpretation, or manuscript writing.

Data availability

The datasets generated and/or analyzed during the current study are not publicly available due to privacy protection of the participants but are available from the corresponding author on reasonable request.

Competing interests

The authors declare no competing interests.

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

These authors contributed equally: Christina Sonne Mogensen, Malene Nygaard.
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