Adverse pregnancy outcomes among women in Norway with gestational diabetes using three diagnostic criteria

Anam Shakil Rai; Line Sletner; Anne Karen Jenum; Nina Cecilie Øverby; Signe Nilssen Stafne; Elisabeth Qvigstad; Are Hugo Pripp; Linda Reme Sagedal

doi:10.1371/journal.pone.0280750

. 2023 Jul 6;18(7):e0280750. doi: 10.1371/journal.pone.0280750

Adverse pregnancy outcomes among women in Norway with gestational diabetes using three diagnostic criteria

Anam Shakil Rai ^1,^*, Line Sletner ^2,³, Anne Karen Jenum ⁴, Nina Cecilie Øverby ⁵, Signe Nilssen Stafne ^6,⁷, Elisabeth Qvigstad ^3,⁸, Are Hugo Pripp ⁹, Linda Reme Sagedal ^1,¹⁰

Editor: Zhong-Cheng Luo¹¹

PMCID: PMC10325062 PMID: 37410781

Abstract

Introduction

The aim of this study was to examine the risk of adverse perinatal outcomes in women diagnosed with GDM by the World Health Organization (WHO) 1999 criteria, and in those retrospectively identified by the Norwegian-2017 and WHO-2013 criteria but not by WHO-1999 criteria. We also examine the effect of maternal overweight/obesity and ethnicity.

Material and methods

We used pooled data from four Norwegian cohorts (2002–2013), encompassing 2970 mother-child pairs. Results from universally offered 75-g oral glucose tolerance tests measuring fasting plasma glucose (FPG) and 2-hour glucose (2HG) were used to assign women into three diagnostic groups: Diagnosed and treated by WHO-1999 (FPG≥7.0 or (2HG ≥7.8 mmol/L), identified by WHO-2013 (FPG ≥5.1 or 2HG ≥8.5 mmol/L), and identified by Norwegian-2017 criteria (FPG ≥5.3 or 2HG ≥9.0 mmol/L). Perinatal outcomes included large-for-gestational-age (LGA) infants, cesarean section, operative vaginal delivery, preterm birth and preeclampsia.

Results

Compared to the non-GDM group, women diagnosed with GDM by either of the three criteria had an increased risk of large-for-gestational-age infants (adjusted odds ratios (OR) 1.7–2.2). Those identified by the WHO-2013 and Norwegian-2017 criteria but not diagnosed and treated by WHO-1999 criteria had an additional increased risk of cesarean section (OR 1.36, 95% CI 1.02,1.83 and 1.44, 95% CI 1.03,2.02, respectively) and operative vaginal delivery (OR 1.35, 95% CI 1.1,1.7 and 1.5, 95% CI 1.1,2.0, respectively). The proportions of LGA neonates and cesarean section were higher for women with GDM in both normal-weight and overweight/obese women. Asians had a lower risk of delivering large-for-gestational-age infants than Europeans applying national birthweight references, but maternal glucose values were similarly positively associated with birthweight in all ethnic groups.

Conclusions

Women who met the WHO-2013 and Norwegian-2017 criteria, but were not diagnosed by the WHO-1999 criteria and therefore not treated, had an increased risk of LGA, cesarean section and operative vaginal delivery compared to women without GDM.

Introduction

Gestational diabetes mellitus (GDM) is associated with increased risk of macrosomia, cesarean section, preeclampsia and preterm delivery [1], and with long term increased risk of obesity and type 2 diabetes in both mother and child [2].

Diagnostic thresholds of GDM applied in Norway were previously derived from criteria for glucose intolerance used for non-pregnant individuals [3]. In 2013, the World Health Organization (WHO) recommended glycaemic thresholds for the diagnosis of GDM based on findings from the multinational Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study, demonstrating a linear dose-response between maternal glycaemia and adverse neonatal outcomes [4]. These criteria identified women with an adjusted odds ratio (OR) of 1.75, relative to the mean, for pre-specified outcomes, such as large-for-gestational-age (LGA) neonates, primary cesarean section, and neonatal hypoglycaemia [5]. Glucose values set to identify women with a higher risk were also considered but rejected [4]. Nonetheless, several countries, including Canada, Finland, and Norway, adopted thresholds corresponding to a 2-fold risk for these outcomes.

Shifting from the former WHO-1999 criteria to the WHO-2013 criteria has been shown to increase the prevalence of GDM considerably due to a higher case identification of women with moderately increased fasting glucose levels only [6, 7]. However, it is unclear whether women classified as GDM by the new criteria but as non-GDM previously, have a clear risk of adverse pregnancy outcomes with a magnitude that warrants treatment, and whether ethnic background and overweight/obesity influence these relationships.

Accordingly, we aimed to explore the risk for LGA, cesarean delivery, operative vaginal delivery, preterm birth, and preeclampsia in women i) identified and treated for GDM by the WHO-1999 criteria or ii) identified by the Norwegian-2017 and the WHO-2013 criteria, but not by the WHO-1999 criteria (and therefore not treated), also taking maternal overweight/obesity and ethnicity into account.

Material and methods

Study design and population

We used data from The Norwegian Hyperglycaemia in Pregnancy consortium, a merged data set with two cohort studies [8, 9] and two randomized controlled trials (RCT) [10, 11] conducted in Norway between 2002 and 2013. The interventions in the two trials consisted of either an exercise program or a combination of a physical activity component and dietary counselling, but these interventions demonstrated no effect on GDM incidence or LGA and cesarean section. The four studies were merged to perform a pooled analysis. Detailed study methods for the pooled data set have been previously described [12] and participant characteristics for all studies are summarized in S1 Table in S1 File. In short, included studies comprised women with singleton live-born neonates recruited early in pregnancy (between week 15–20 with data on maternal age and pre-pregnancy BMI, glucose measurements obtained from at least one universally offered 75g 2-hour oral glucose tolerance test (OGTT) performed ≥ 20 weeks’ gestation, and at least one offspring measurement (birthweight). Only studies that had core data and were not based on specific selection criteria (e.g. obese women only) were considered for inclusion.

Obstetric and neonatal outcomes

Data on obstetric outcomes were obtained from hospital records, including mode of delivery (normal vaginal delivery, total cesarean section (planned or emergency), operative vaginal delivery (vacuum extraction or forceps)), gestational age at birth, preeclampsia or severe hypertensive disorder, and preterm delivery (<37 weeks of pregnancy). Routine anthropometric measurements (birthweight and length) of neonates were performed by study staff immediately following birth. Birthweight z-score and large-for-gestational-age (LGA) (birthweight >90th percentile) were calculated using Norwegian sex and gestational age-specific national references [13]. Birth weight z-scores express the weight as the number of standard deviations (SD) above or below the reference mean value for a specific gestational age and sex (not customized for ethnicity, maternal height etc.)

Main exposure and covariates

Our main exposure variable was GDM. During the data collection, the diagnosis of GDM was based exclusively on the WHO-1999 criteria. If diagnosed, women received standard GDM care according to national guidelines, which remained unchanged during the data collection period, with self- monitoring of blood glucose and dietary counselling. Oral antidiabetic therapy or insulin was commenced if blood glucose levels repeatedly exceeded treatment targets. Only 12 women received such pharmacological treatment.

We additionally applied the WHO-2013 diagnostic cut-offs (only fasting and 2-hour values as 1-hour glucose was not measured in these studies) and the Norwegian-2017 cut-offs to the same diagnostic OGTT. Based on their OGTT results, women were retrospectively assigned to the following (partly overlapping) diagnostic groups:

GDM diagnosed and treated according to WHO-1999 criteria (fasting glucose ≥7.0 mmol/l and/or 2-hour glucose (2HG) ≥7.8 mmol/l).
GDM retrospectively identified according to WHO-2013 criteria (fasting glucose ≥5.1 mmol/l and/or 2HG ≥8.5 mmol/l).
GDM retrospectively identified according to Norwegian-2017 criteria (fasting glucose ≥5.3 mmol/l and/or 2HG ≥9.0 mmol/l).

All participants provided questionnaire data, self-reported [9–11] or through interviews [8]. Height was measured directly at sites while weight prior to pregnancy was self-reported. Pre-pregnancy body mass index (BMI) was calculated and categorized according to the WHO International Classification of normal weight (≤24.9 kg/m²), overweight (25–29.9 kg/m²) and obesity (≥30 kg/m²).

Ethnic origin was defined by the pregnant woman’s mother’s country of birth and further merged into three groups in the current study: European (predominantly Scandinavian as well as East and West-European origin), Middle Eastern/African, and Asian (primarily South and East Asian ethnicity) [8].

The four birth cohorts provided data from 3315 pregnant women and 3293 live births (S1 Fig). After excluding women with multiple pregnancies, those lacking glucose values, infants with missing birthweight and fetal deaths the study sample consisted of 2970 mother-child pairs.

Statistical analyses

Assumptions for statistical analysis were tested and distributions of all potential covariates were checked for normality using Tests of Normality and inspection of probability plots, which confirmed that these variables followed a normal distribution. Data are reported as frequencies and percentages for categorical variables and mean and standard deviation for continuous variables, using X² test or Student’s t Test as appropriate.

To assign values for the missing data for pre-pregnancy weight (5%), height (0.4%), educational attainment (0.3%) and parity (0.3%) we used Stochastic regression imputation with predictive mean matching as the imputation model. Statistical analyses were carried out using statistical package IBM SPSS (version 23.0. Armonk, NY: IBM Corp).

Logistic regression models were used to estimate the OR and 95% confidence intervals (CI) for associations between maternal GDM status and clinical outcomes before and after adjustment for maternal age, pre-pregnancy BMI, ethnicity, parity, smoking and gestational age at birth. We also adjusted for study cohort to handle potential unmeasured confounders. We did not further adjust for maternal education, as it was not associated with our perinatal outcomes, and adding this variable to the models had no impact on the effect estimates of interest. During data collection, information about GDM and subsequent treatment was only offered to women diagnosed according to the WHO-1999 criteria. Hence, in the final models assessing the effect of GDM by Norwegian-2017 and WHO-2013 criteria, we additionally adjusted for whether they were diagnosed and offered treatment for GDM by the WHO-1999 criteria. Doing so allowed us to identify the group of women with an elevated fasting blood glucose only (fasting glucose 5.1–6.9 mmol/l and 2HG <7.8 mmol/l for WHO-2013, and fasting glucose 5.3–6.9 mmol/l and 2HG <7.8 mmol/l for Norwegian-2017 criteria) who were untreated. As a sensitivity analysis, and to verify the results achieved by the analyses where adjustment for treatment and a known diagnosis were made to the model, we repeated the same analysis after excluding participants who were diagnosed and treated based on the WHO-1999 criteria. Results are presented as unadjusted and multivariable-adjusted models.

As the definition used for LGA was derived from a predominantly ethnic Norwegian population, we explored in separate general linear models the effect of maternal glucose values on offspring birthweight z-score, stratified by ethnic groups in adjusted models. The conditions for a linear regression were checked, confirming a linear relationship between maternal glucose values and offspring birthweight. We did not mutually adjust for FPG and 2HG due to collinearity. All p values are two-tailed, and p values <0.05 were considered statistically significant.

Ethics

All studies were based on written informed consent. The Norwegian Regional Ethics committees (REC) approved that each constituent study could contribute to the consortium, and the current study was approved by the REC South East (2017/2533).

Results

Characteristics and pregnancy outcomes of the total cohort stratified by GDM status are presented in Table 1. In total 10.7% of women were diagnosed with GDM based on the WHO-1999 criteria, 16.9% with WHO-2013, and 10.3% with Norwegian-2017 criteria. As expected, women with GDM were older and had a higher pre-pregnancy BMI than those without GDM. All three groups of women diagnosed with GDM (according to WHO-1999, WHO-2013 and Norwegian-2017 criteria) had a higher rate of LGA neonates compared to their non-GDM counterparts, while higher rates of macrosomia (birthweight>4000g) were only found in those diagnosed by the Norwegian-2017 and WHO-2013 criteria. Similarly, women in all GDM groups had an increased risk of cesarean section, but only those who met the Norwegian-2017 and WHO-2013 criteria were more likely to have an operative vaginal delivery compared to their non-GDM counterparts. Only women diagnosed with GDM by the WHO-1999 criteria had a higher risk of preterm birth and preeclampsia.

Table 1. Characteristics and pregnancy outcomes in total study sample and according to their glucose tolerance status, using three diagnostic criteria for gestational diabetes.

For each column data are presented as mean ± SD or n (%).

	Total cohort	WHO-1999 criteria			WHO-2013 criteria			Norwegian-2017 criteria
Participant characteristic	2970	non-GDM, n = 2652 (89.3)	GDM, n = 318 (10.7)	Pª Value	non-GDM, n = 2469 (83.1)	GDM, n = 501 (16.9)	Pª Value	non-GDM, n = 2663 (89.7)	GDM, n = 307 (10.3)	Pª Value
Maternal age (years)	30.0 (4.4)	29.9 ± 4.4	31.6 ± 4.6	< .001	30.0 ± 4.3	30.8 ± 5.0	< .001	30.1 ± 4.3	30.8 ± 5.1	.007
Pre-pregnancy BMI (kg/m²)	23.7 ± 3.9	23.6 ± 3.9	24.8 ± 4.5	< .001	23.3 ± 3.5	25.7 ± 5.1	< .001	23.4 ± 3.6	26.0 ± 5.5	< .001
Pre-pregnancy BMI groups (kg/m²), n (%)				< .001			< .001			< .001
Normalweight ≤24.9	2127 (71.7)	1948 (73.5)	179 (56.3)		1864 (75.5)	263 (52.5)		1974 (74.1)	153 (49.8)
Overweight 25–29.9	610 (20.5)	516 (19.5)	94 (29.6)		462 (18.7)	148 (29.5)		524 (19.7)	86 (28.0)
Obesity ≥30	233 (7.8)	188 (7.1)	45 (14.2)		143 (5.8)	90 (18.0)		165 (6.2)	68 (22.1)
Ethnicity, n (%)				.055			< .001			< .001
European	253 (86.6)	2311 (87.1)	262 (82.4)		2221 (90.0)	352 (70.3)		2373 (89.1)	200 (65.1)
Middle-Eastern/African	174 (5.9)	151 (5.7)	23 (7.2)		113 (4.6)	61 (12.2)		133 (5.0)	41 (13.4)
Asian	223 (7.5)	190 (7.2)	33 (10.4)		135 (5.5)	88 (17.6)		157 (5.9)	66 (21.5)
Primipara, n (%)	1814 (61.1)	1621 (61.1)	193 (60.7)	.881	1150 (62.8)	264 (52.7)	< .001	1656 (62.2)	158 (51.5)	< .001
Education, n (%)				.009			< .001			< .001
Primary or less	146 (4.9)	120 (4.5)	26 (8.2)		89 (3.6)	57 (11.4)		105 (3.9)	41 (13.4)
High school education	640 (21.5)	566 (21.3)	74 (23.3)		493 (20.0)	147 (29.3)		544 (20.4)	96 (31.3)
Higher education	2184 (73.5)	1966 (74.1)	218 (68.6)		1887 (76.4)	297 (59.3)		2014 (75.6)	170 (55.4)
Current smoker, n (%)	80 (2.8)	72 (2.8)	8 (2.7)	.885	62 (2.6)	18 (3.9)	.116	68 (2.7)	12 (4.3)	.108
Fasting glucose at OGTT (mmol/L)	4.6 ± 0.5	4.5 ± 0.4	5.0 ± 0.6	< .001	4.4 ± 0.3	5.3 ± 0.5	< .001	4.5 ± 0.4	5.5 ± 0.6	< .001
2-hour glucose at OGTT (mmol/L)	6.1 ± 1.3	5.7 ± 1.0	8.6 ± 0.8	< .001	5.8 ± 1.1	7.4 ± 1.6	< .001	5.9 ± 1.2	7.6 ± 1.7	< .001
Gestational age at OGTT (weeks)	30.8 ± 2.5	30.8 ± 2.5	30.5 ± 2.3	.005	31.0 ± 2.5	29.8 ± 2.2	< .001	31.0 ± 1.7	31.0 ± 2.5	< .001
Gestational age at delivery (weeks)	39.8 (1.6)
Outcome
Birthweight, gram	3520 (522)	3517.9 (518.0)	3537.7 (555.2)	.523	3505 (515.7)	3594 (547)	< .001	3512 (517)	3588 (557)	.016
LGA, n (%)	230 (7.7)	184 (6.9)	46 (14.5)	< .001	165 (6.7)	65 (13.0)	< .001	183 (6.9)	47 (15.3)	< .001
Birthweight z-score	- 0.05 (0.9)	-0.748 (0.93)	0.085 (1.00)	.004	-0.097 (0.92)	0.138 (1.01)	< .001	-0.082 (0.92)	0.158 (1.15)	< .001
Macrosomia ≥4000g, n (%)	507 (17.1)	444 (16.7)	63 (19.8)	.168	392 (15.9)	115 (23.0)	< .001	433 (16.3)	74 (24.1)	.001
Preterm birth, n (%)	108 (3.9)	90 (3.4)	20 (6.3)	.010	87 (3.5)	23 (4.6)	.211	92 (3.5)	16 (5.2)	.120
Preeclampsia, n (%)	98 (3.6)	81 (3.3)	17 (5.7)	.036	82 (3.7)	16 (3.4)	.751	88 (3.6)	10 (3.4)	.872
Total cesarean section, n (%)	446 (15.0)	378 (14.3)	68 (21.4)	.004	339 (13.7)	107 (21.4)	< .001	375 (14.1)	71 (23.1)	< .001
emergency	298 (10.0)	258 (9.7)	40 (12.6)		230 (9.3)	68 (13.6)		250 (9.4)	48 (15.6)
planned	148 (5.0)	120 (4.5)	28 (8.8)		109 (4.4)	39 (7.8)		125 (4.7)	23 (7.5)
Operative vaginal delivery, n (%)	386 (13.0)	737 (27.8)	105 (33.0)	0.051	672 (27.2)	170 (33.9)	0.002	730 (27.4)	112 (36.5)	0.001
Received treatment/known diagnosis	318	2652 (0)	318 (100)		119 (4.8)	199 (39.7)		180 (6.8)	138 (45.0)

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ªIndependent sample T test for continuous variables and X² statistic for categorical variables.

WHO: World Health Organization, GDM: gestational diabetes mellitus, BMI: body mass index, OGTT: oral glucose tolerance test, LGA: large-for-gestational-age

Values are imputed for pre-pregnancy weight, parity and education.

Fig 1 shows relations between GDM and (a) LGA and (b) cesarean section in women with normal-weight or overweight/obesity. GDM by any criteria significantly increased the proportion of LGA infants in both normal-weight and overweight/obese subgroups, although the highest proportions were observed for overweight/obese women (S2 Table in S1 File). Similar results were found for cesarean section except when applying the WHO-1999 criteria.

The unadjusted and adjusted associations between GDM and LGA, cesarean section and operative vaginal delivery for each of the three GDM criteria are reported in Table 2. For those diagnosed with GDM according to the WHO-1999 criteria and treated accordingly, an increased risk was only found for delivering an LGA infant (adjusted OR 2.22, 95% CI 1.5,3.2). Women retrospectively classified as having GDM by the WHO-2013 criteria had a crude OR of 2.08 for LGA. After adjusting for confounders and for treatment by the WHO-1999 criteria (thereby expressing the risk related to having fasting glucose 5.1–6.9 mmol/l while 2HG <7.8 mmol/l) the OR for LGA for this group was 1.70 (95% CI 1.2,2.5,) compared to non-GDM women (both fasting glucose <5.1 mmol/l and 2HG <7.8 mmol/l). These women also had an increased risk of total cesarean section (OR 1.36, 95% CI 1.02,1.83). and for operative vaginal delivery (OR 1.35, 95% CI 1.1,1.7). Women identified with the Norwegian-2017 but not the WHO-1999 criteria (i.e. fasting glucose 5.3–6.9 mmol/l while 2HG ≤7.8) compared to women not identified by any of the two criteria, had an increased adjusted risk of LGA (OR 2.05, 95% CI 1.3,3.1), cesarean section (OR 1.44, 95% CI 1.03,2.02), operative vaginal delivery (OR 1.50, 95% CI 1.1,2.0) and emergency cesarean section (OR 1.57, 95% CI 1.1,2.3, P = 0.024).

Table 2. Crude and adjusted analyses of risk of large-for-gestational-age, total cesarean section and operative vaginal delivery, by GDM-criteria.

	Crude analysis			Adjusted analysis
				WHO-1999 criteria			WHO-2013 criteria			Norwegian-2017 criteria
	Crude OR	(95% CI)	p-value	aOR^*	(95% CI)	p-value	aOR^∞	(95% CI)	p-value	aOR^∞	(95% CI)	p-value
Large-for-gestational-age baby
GDM identified by Norwegian-2017 criteria	2.45	(1.7–3.5)	<0.001							2.05	(1.3–3.1)	0.001
identified by WHO-2013 criteria	2.08	(1.5–2.8)	<0.001				1.69	(1.2–2.5)	0.007
diagnosed and treated by WHO-1999 criteria	2.26	(1.6–3.2)	<0.001	2.22	(1.5–3.2)	<0.001	1.73	(1.1–2.6)	0.009	1.72	(1.1–2.6)	0.009
Prepregnancy BMI
Normalweight	1			1			1			1
Overweight	1.59	(1.2–2.2)	0.004	1.48	(1.1–2.1)	0.020	1.42	(1.0–2.0)	0.038	1.43	(1.0–2.0)	0.035
Obesity	2.11	(1.4–3.2)	<0.001	1.76	(1.1–2.8)	0.018	1.60	(1.0–2.6)	0.053	1.55	(1.0–2.5)	0.076
Ethnicity
European ethnicty	1			1			1			1
Middle Eastern/African ethnicty	1.05	(0.6–1.8)	0.860	0.69	(0.3–1.4)	0.326	0.66	(0.3–1.4)	0.276	0.65	(0.3–1.4)	0.251
Asian	0.15	(0–0.5)	0.001	0.11	(0.0–0.5)	0.003	0.10	(0.0–0.4)	0.002	0.09	(0.0–0.4)	0.001
Cesarean section (total; emergency and planned)
GDM identified by Norwegian-2017 criteria	1.83	(1.3–2.4)	<0.001							1.44	(1.0–2.0)	0.033
identified by WHO-2013 criteria	1.70	(1.3–2.1)	<0.001				1.36	(1.0–1.8)	0.037
diagnosed and treated by WHO-1999 criteria	1.63	(1.2–2.1)	0.001	1.19	(0.9–1.6)	0.262	1.02	(0.7–1.4)	0.903	1.04	(0.7–1.4)	0.807
Prepregnancy BMI
Normalweight	1			1			1			1
Overweight	1.49	(1.2–1.9)	0.001	1.47	(1.1–1.9)	0.002	1.43	(1.1–1.8)	0.005	1.44	(1.1–1.9)	0.004
Obesity	1.77	(1.2–2.5)	0.001	1.74	(1.2–2.5)	0.002	1.65	(1.2–2.4)	0.006	1.64	(1.1–2.3)	0.007
Ethnicity
European ethnicty	1			1			1			1
Middle Eastern/African ethnicty	1.00	(0.6–1.5)	1.000	0.84	(0.5–1.4)	0.508	0.82	(0.5–1.4)	0.443	0.81	(0.5–1.4)	0.428
Asian	1.13	(0.7–1.6)	0.509	0.95	(0.6–1.5)	0.841	0.91	(0.6–1.4)	0.683	0.90	(0.6–1.4)	0.643
Operative vaginal delivery
GDM identified by Norwegian-2017 criteria	1.52	(1.2–1.9)	0.001							1.50	(1.1–2.0)	0.006
identified by WHO-2013 criteria	1.37	(1.1–1.7)	0.002				1.35	(1.1–1.7)	0.017
diagnosed and treated by WHO-1999 criteria	1.28	(0.9–1.6)	0.051	1.07	(0.8–1.4)	0.604	0.93	(0.7–1.2)	0.614	0.93	(0.7–1.2)	0.620
Prepregnancy BMI
Normalweight	1			1			1			1
Overweight	1.27	(1–1.5)	0.018	1.29	(1.1–1.6)	0.013	1.26	(1.0–1.5)	0.024	1.27	(1.0–1.6)	0.021
Obesity	1.43	(1.1–1.9)	0.014	1.49	(1.1–2.0)	0.009	1.42	(1.0–1.9)	0.025	1.40	(1.0–1.9)	0.031
Ethnicity
European ethnicty	1			1			1			1
Middle Eastern/African ethnicty	0.95	(0.7–1.3)	0.790	1.22	(0.8–1.9)	0.348	1.19	(0.8–1.8)	0.420	1.18	(0.8–1.8)	0.443
Asian	0.92	(0.7–1.3)	0.607	1.18	(0.8–1.7)	0.408	1.12	(0.8–1.7)	0.564	1.10	(0.7–1.6)	0.639

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* Adjusted for BMI group and ethnicity, as shown. Additionally adjusted for age, gestational weeks at delivery, parity and study cohort.

^∞Adjusted for GDM diagnosed by WHO-1990 criteria, BMI group and ethnicity, as shown. Additionally adjusted for age, gestational weeks at delivery, parity and study cohort.

BMI categories: normalweight ≤24.9 kg/m², overweight 25–29.9 kg/m², obesity ≥30 kg/m²

WHO: World Health Organization, GDM: gestational diabetes mellitus, BMI: body mass index, OR: odds ratio, aOR: adjusted odds ratio

Sensitivity analyses (Table 3), applied on women with GDM by the WHO-2013 and Norwegian-2017 criteria after excluding those with GDM by the WHO-1999 criteria, showed almost identical effect estimates although statistical significance was reached for LGA only, presumably due to decreased population size. There was no significantly increased risk of preterm delivery or preeclampsia regardless of GDM criteria applied (S3 Table in S1 File).

Table 3. Adjusted analysis of risk of large-for-gestational-age, total cesarean section and operative vaginal delivery after excluding women with a GDM diagnosis based on WHO-1999 criteria.

n = 2652	Norwegian-2017 criteria onlyª (n = 119)			WHO-2013 criteria® (n = 180)
	aOR	(95% CI)	p-value	aOR	(95% CI)	p-value
Large-for-gestational-age*
GDM	2.02	(1.7–3.5)	0.012
Identified by Norwegian-2017 criteria	2.02	(1.7–3.5)	0.012
Identified by WHO-2013				1.75	1.1–2.7	0.014
Prepregnancy BMI
Normalweight
Overweight	1.314	0.9–1.9	0.154	1.303	0.8–1.8	0.168
Obesity	1.697	0.9–2.9	0.057	1.701	0.9–2.9	0.055
Ethnicity
European ethnicty
Middle Eastern/African ethnicty	0.711	0.3–1.6	0.414	0.717	0.3–1.6	0.425
Asian	0.066	0.0–0.5	0.008	0.067	0.0–0.5	0.008
Total cesarean deliveries (emergency and elective)^b
GDM	1.476	0.9–2.2	0.065
Identified by Norwegian-2017 criteria	1.476	0.9–2.2	0.065
Identified by WHO-2013 criteria				1.306	0.9–1.8	0.121
Prepregnancy BMI
Normalweight
Overweight	1.357	0.0–1.7	0.028	1.355	1.0–1.7	0.029
Obesity	1.490	0.9–2.2	0.055	1.5	0.9–2.2	0.051
Ethnicity
European ethnicty
Middle Eastern/African ethnicty	0.908	0.5–1.6	0.732	0.912	0.5–1.5	0.743
Asian	0.959	0.6–1.6	0.871	0.973	0.6–1.6	0.915
Operative vaginal delivery^b
GDM	1.411	0.9–2.0	0.058
Identified by Norwegian-2017 criteria	1.411	0.9–2.0	0.058
Identified by WHO-2013 criteria				1.251	0.9–1.6	0.119
Prepregnancy BMI
Normalweight
Overweight	1.231	0.9–1.5	0.064	1.23	0.9–1.5	0.066
Obesity	1.351	0.9–1.8	0.112	1.326	0.9–1.8	0.101
Ethnicity
European ethnicty
Middle Eastern/African ethnicty	1.381	0.8–2.1	0.157	1.388	0.8–2.1	0.153
Asian	1.136	0.7–1.7	0.562	1.152	0.7–1.7	0.519

Open in a new tab

ªThe analysis excludes treated women n = 318, and includes women with fasting glucose 5.3–6.9 and 2-h glucose ≤7.8

®The analysis excludes treated women n = 318, and includes women with fasting glucose 5.1–6.9 mmol/l and 2HG <7.8 mmol/l

*Adjusted for age, maternal smoking, parity and study cohort in addition.

^b Adjusted for age, gestational weeks at delivery, parity and study cohort in addition

aOR:adjusted odds ratio, GDM: gestational diabetes, WHO: Word Health Organization, BMI: body mass index, CI: confidence interval

Asians had substantially lower risk of delivering an LGA infant than Europeans (Table 2), however, as the definition of LGA in Norway was not ethnicity-specific, we further explored the linear association between maternal glucose and birthweight z-score separately for Europeans, South Asians, and Middle Eastern/Africans (Table 4). Fasting glucose was significantly associated with higher birthweight in all ethnic groups, implying that one mmol/l increase in fasting glucose was associated with an increase in birthweight z-score by 0.30 SD units after adjustments for relevant covariates, equivalent to approximately 130g in a full-term neonate. Similarly, 2HG was positively associated with birthweight z-score in all groups in both univariable simple and multivariable adjusted analyses.

Table 4. Linear regressions of maternal glucose on offspring’s birthweight z-score, stratified for ethnic group.

European, n = 2573 (86.6%)
			Fasting glucose		2-hour glucose
	Unadjusted		Adjusted^*		Adjusted*
	β	(95% CI)	β	(95% CI)	β	(95% CI)
Fasting glucose^ª	0.364	(0.3–0.4)	0.336	(0.2–0.4)
2-hour glucose^ª	0.084	(0.1–0.1)			0.081	(0.1–0.1)
Prepregnancy body mass index
Normalweight	1		1		1
Overweight	0.251	(0.2–0.3)	0.184	(0.1–0.3)	0.218	(0.1–0.3)
Obesity	0.326	(0.2–0.5)	0.215	(0.1–0.4)	0.277	(0.1–0.4)
Age	0.016	(0.0–0.0)	-0.010	(-0.0-(-0.0))	-0.009	(-0.02–0.0)
Middle Eastern/African ethnicity, n = 174 (5.9%)
			Fasting glucose		2-hour glucose
	Unadjusted		Adjusted*		Adjusted*
	β	(95% CI)	β	(95% CI)	β	(95% CI)
Fasting glucoseª	0.301	(0.1–0.5)	0.318	(0.0–0.6)
2-hour glucoseª	0.129	(0.0–0.2)			0.201	(0.0–0.4)
Prepregnancy body mass index
Normalweight	1		1		1
Overweight	0.063	(0.3–0.4)	-0.057	(-0.5–0.3)	0.018	(-0.4–0.4)
Obesity	0.609	(0.2–0.9)	0.496	(0.1–0.9)	0.592	(0.1–1.1)
Age	0.018	(-0.01–0.0)	0.000	(-0.04–0.0)	-0.005	(-0.04–0.3)
Asian, n = 223 (7%)
			Fasting glucose		2-hour glucose
	Unadjusted		Adjusted^*		Adjusted^*
	β	(95% CI)	β	(95% CI)	β	(95% CI)
Fasting glucose^ª	0.393	(0.2–0.5)	0.323	(0.1–0.5)
2-hour glucose^ª	0.149	(0.1–0.2)			0.177	(0.1–0.3)
Prepregnancy body mass index
Normalweight	1		1		1
Overweight	0.334	(0.1–0.6)	0.256	(-0.1–0.5)	0.275	(-0.03–0.6)
Obesity	0.409	(-0.1–0.8)	-0.047	(-0.5–0.4)	0.067	(-0.4–0.5)
Age	0.027	(0.0–0.1)	0.019	(-0.01–0.04)	0.016	(-0.01–0.1)

Open in a new tab

* Models are adjusted for cohort, smoking, parity and treatment by the WHO-1999 criteria in addition.

ªNot mutually adjusted. Significant values presented in bold.

Discussion

Among women universally tested for GDM by OGTT, we observed that the proportion of LGA infants was significantly higher in women with GDM identified by all three criteria compared to women without GDM. Those retrospectively identified by the Norwegian-2017 and WHO-2013 criteria, but who were not diagnosed and treated by the WHO-1999 criteria (i.e., women with moderately elevated fasting glucose only) also had an increased risk of cesarean section and operative vaginal delivery after adjustment for confounders. The proportion of LGA neonates and cesarean section was higher for women with GDM in both normal-weight and overweight/obese women. Although Asian women had a reduced risk of delivering a LGA infant compared with Europeans, a similar positive association between maternal glucose values and birthweight z-scores was found in all ethnic groups. Taken together, these findings indicate that moderately elevated fasting glucose, when unidentified and untreated, is associated with several adverse outcomes that were not observed in women where GDM was detected and treated according to WHO-1999 diagnostic criteria, which are primarily based on elevated 2HG values.

Conflicting evidence exists regarding the impact of introducing the WHO-2013 criteria on perinatal outcomes. Studies evaluating these criteria showed in general that women who would not have been identified with other criteria had higher adverse outcome rates compared to non-GDM women [7, 14, 15]. To our knowledge, only few studies, mainly from Canada, have examined adverse perinatal outcomes associated with implementing the 2.0 risk thresholds identified by the HAPO study, employed in Norwegian-2017 criteria [16–18]. One study found that when compared to women without GDM, those diagnosed with the equivalent of the Norwegian-2017 criteria had a significantly higher risk of preeclampsia, preterm birth, LGA and several other adverse outcomes, while the same was only found for LGA in the WHO-2013-only-group (fasting glucose 5.1–5.2 mmol/l and and/or 2HG 8.5–8.9 mmol/l) [17]. Although we didn’t create mutually exclusive GDM categories, our finding of larger risks for all the examined outcomes when applying the Norwegian-2017 compared to WHO-2013 criteria is in line with this. However, we did not find an increased risk for preterm delivery and preeclampsia, a finding that could be related to small numbers for these outcomes in our study, indicating low power to detect associations with GDM.

As the pathophysiology of GDM is intimately linked to maternal overweight/obesity and gestational weight gain, it is often difficult to sort out the differential contributions of maternal obesity and hyperglycaemia to pregnancy outcomes. The idea that maternal BMI level is a better predictor than glucose alone for outcomes frequently associated with GDM has been widely reported in the past [19–21]. Consistent with others [22, 23], our findings indicate that, in addition to glucose levels, maternal pre-pregnancy BMI has a strong independent association with most of the examined outcomes. However, the significant increase of LGA also in normal-weight women with GDM supports a role of hyperglycaemia not attributed to maternal BMI alone.

Although we found that Asians had a reduced risk of LGA, stratified analyses of birthweight z-score suggests that the association with elevated glucose levels was similar in all ethnic groups. We have previously shown that Asians have the highest GDM prevalence irrespective of criteria used, and in particular with the WHO-2013 criteria, when compared to Europeans [12]. However, as neonates with Asian origin generally have lower birthweight compared to Europeans, our finding of a low LGA risk is not surprising as LGA was, as in most countries, assessed using a national reference population, rather than ethnically customised centile charts. Previous studies, including one of the pooled cohort studies, have shown that offspring of Asian women have a birthweight distribution that is skewed compared with the distribution in the native Norwegian population, and demonstrated an influence of maternal glucose on fetal growth trajectories [24]. A study by Dias et al. also supports our findings, showing that WHO-2013 criteria is associated with greater birthweight in Sri Lankan pregnant women [25]. Furthermore, studies from the Born-in-Bradford cohort showed that infants with South Asian origin have greater fat mass at birth despite their lower birthweight, explained by higher maternal glucose levels [26, 27]. Clinicians should be mindful that although ethnic minority women from these countries have a lower risk of delivering LGA or macrosomic neonates, elevated blood glucose levels affect fetal growth, particularly in terms of greater adiposity in the children.

The finding of a lower rate of caesarean section and operative delivery in women diagnosed by the WHO-1999 criteria may be partially explained by a treatment effect, as the results of GDM testing were openly disclosed to caregivers and women at diagnosis. Clinical decisions such as timing of birth and induction of labour may be influenced by antenatally labelling pregnant women as having GDM. This could also be a possible explanation of lower rates of macrosomia observed in treated women in our study. Surprisingly, the expected beneficial effect of GDM treatment was not evident in the outcome of LGA, for which we found the highest risk among treated women. Mean gestational week at time of OGTT was 30 in our study, which may be too late for treatment to have a beneficial effect on fetal growth. Nevertheless, our results highlight the importance of identifying women with GDM to prevent complications and plan for a safer delivery in those with only moderately elevated fasting glucose as well, as these women demonstrate a higher risk of poor pregnancy outcomes, not observed in treated women with an established GDM diagnosis.

Our study has a number of strengths. We took advantage of previously collected maternal and offspring data, allowing more powerful and flexible analyses. Unlike many studies, participants were not selected based on high risk, as an OGTT was offered to all pregnant women. Our study also included women from some of the fastest-growing minority groups in Norway with a substantial risk of developing GDM. However, nearly all non-European women came from one study and the majority of Asians were of South Asian origin. As the overall race and ethnic composition in Europe differs and is constantly changing, the proportions included may not be fully representative for the present pregnant population.

Our study also has limitations. Glucose results were not blinded in the original studies and women with GDM were routinely treated when diagnosed by the WHO-1999 criteria. Information about adherence to any advice given and whether target glucose levels were achieved or not was unavailable. Therefore, any conclusions drawn about clinical outcomes should be interpreted with caution as treatment of GDM may be expected to lower the proportion of adverse outcomes and the natural effect of maternal hyperglycaemia. When comparing women with a GDM diagnosis by the WHO-2013 and Norwegian-2017 criteria, we have tried to control for this factor by adjusting for treatment. In addition, we performed sensitivity analysis excluding treated women which also showed similar associations of GDM and the studied outcomes. The rates of overweight and obesity in our cohort were somewhat lower than the general population, but closely approximated that of reproductive-aged women in Norway (8% vs 12% obesity nationally in 2018). Finally, we used a modified WHO-2013 criteria with only two timepoints, as 1-hour glucose concentrations were not collected in our study. The prevalence of GDM by the WHO-2013 criteria would presumably have been higher with the addition of the 1-hour timepoint.

Conclusion

After accounting for important confounders, women retrospectively identified as having GDM according to the Norwegian-2017- or WHO-2013 criteria, but not diagnosed and treated by the WHO-1999 criteria, implying that they had moderately elevated fasting glucose only, had an increased risk of LGA, cesarean section and operative vaginal delivery when compared to women without GDM by any criteria. Identification of these women may enable caregivers to better plan for a safer delivery for both women and their infants. Our data support the use of a fasting glucose threshold corresponding to a twofold risk of adverse pregnancy outcomes, as using the Norwegian-2017 criteria would identify women at substantial risk for adverse outcomes without increasing the prevalence of GDM. What remains unanswered and can be established by randomized trials is whether treating mild fasting hyperglycaemia benefits women and their offspring, leading to an improvement in perinatal outcomes.

Supporting information

S1 File

(XLSX)

Click here for additional data file.^{(22.9KB, xlsx)}

S1 Fig. Flowchart of included studies and excluded participants from each study.

Study names listed in the top boxes. TRIP: Training in pregnancy.

(SVG)

Click here for additional data file.^{(9.8KB, svg)}

Acknowledgments

The authors would like to thank the following members of the Norwegian Hyperglycaemia in Pregnancy consortium: Marie Cecilie Paasche-Roland (Oslo University Hospital-Rikshospitalet, Oslo, Norway) for her contribution in the STORK Rikshospitalet study, Siv Mørkved (Norwegian University of Science and Technology, Trondheim, Norway) for her contribution in the TRIP study, and Ingvild Vistad (University of Bergen, Bergen, Norway) for her contribution in the Fit for Delivery study.

Data Availability

The datasets generated and/or analyzed during the current study are not publicly available due to the dataset containing potentially sensitive data. The editors can access data (in de-identified form) used in the manuscript, code book, and analytical code upon request. The project manager will contribute to the access being provided under appropriate conditions. However, research data for this publication include identifying health information subject to confidentiality. It is therefore not possible to share raw data publicly. Name of ethics committee: Regional Committees for Medical and Health Research Ethics Non-author contact: The Norwegian Centre for Research Data and Anja Maria Lyche Brænd (a.m.l.brand@medisin.uio.no).

Funding Statement

This work was funded by South-Eastern Norway Regional Health Authority. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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PLoS One. doi: 10.1371/journal.pone.0280750.r001

Decision Letter 0

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15 Mar 2022

PONE-D-22-04306Adverse pregnancy outcomes among women in Norway with gestational diabetes using three diagnostic criteriaPLOS ONE

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Reviewer #1: Dear authors,

Thank you very much and congratulation for a very well conducted study.

Please find bellow some comments for your consideration.

Overall, the article by Anam Shakil Rai and colleague is very clear and described a very well conducted epidemiological study. The author have tested how the classification according to criteria based on cut-off values for FG and 2HG may associated with the risk of perinatal outcome. The data are original and informative, and ,the results are clinically relevant for Public Health.

I have very little comments to the study in general as the sections are concise and well described showing very good skills from the team overall.

I would recommend the authors to make two clarifications:

The authors pooled 4 studies: 2 cohorts and 2 RCTs and have chosen to make a pooled analysis.

One sentence in the method section:

“Studies that only included specific subgroups (e.g. obese women only) or without the core data were not considered for inclusion” suggests that the number of studies to start with was chosen according to selection criteria. This could be clarified.

Can the authors justify why they have chosen to make a pooled analysis (adjusted for study cohorts) instead of making a meta-analysis. Although this second approach has less statistical power it may help observing study specific effects. Please justify and may be discuss in the strength and limitation section.

Although it is well explained in the main text, the sentence in the abstract: Asians had a lower risk of delivering large-for-gestational-age infants than Europeans […] can be misleading to readers with limited knowledge in birth weight categorisation. Although you informed (’but maternal glucose values were similarly positively associated with birthweight in all ethnic groups’) I think that there is still a risk of miss-interpretation.

In theory, as Asian babies are clearly off-chart when it comes to LGA and SGA categorization (based on the Norwegian scales) the analyses cannot be performed as they are meaningless. I would suggest to remove Asian from the LGA analyses.

The discussion is very clear and concise. However, all the comma separators have been substituted by dots. This should be corrected of course.

Reviewer #2: 1. The study is relatively well conducted.

2. The formatting leaves much to be desired - for some part is not consistent and a lot of full stop '.' which should be comma ','.

3. In Figure 1 what are 'STORK Groruddalen', 'STORK Rikshospitalet', 'Fitfor Delivery', & 'TRIP' - all these acronyms must be explained in the figure.

4. The standard nomenclature for International Association of Diabetes and Pregnancy Study Groups (IADPSG) and World Health Organization 2013 (WHO 2013) recommendations is IADPSG or WHO 2013.

Using 2013(superscript)WHO criteria is not standard way of describing. Please show why are these criteria depicted this way - 2013WHO and not WHO 2013 criteria.

5. The study must make it clear they are not using the full 3 point WHO 2013 or IADPSG but instead using a modified 2 point IADPSG or modified WHO 2013 criteria without 1 hour. The 1 hour time point is an essential part of the IADPSG criteria and will independently adds another one third of cases. This must be stated clearly a limitation that only fasting and 2 hour timepoints are used and thus they are not reflecting the IADPSG full criteria but only comparing the 2 time points criteria within the WHO 2013 criteria.

6. It was shown that Asians had a lower risk of delivering large-for-gestational-age babies. This is not helpful as Asians are smaller size and their babies size norms may be lower. Are customised charts used for Asians, e.g. in relation to mother height and weight and ethnicity?

7. However can these findings be applied to Asia in terms of the timepoints? e.g. fasting and relation to baby birthweights etc. Please refer to an Asian paper - Sri Lanka paper with criteria similar to Norwegian for fasting time point, where a similar aspect of changes in the criteria affect the number of cases

- Dias T, Siraj SHM, Aris IM, Li LJ, Tan KH. Comparing Different Diagnostic Guidelines for Gestational Diabetes Mellitus in Relation to Birthweight in Sri Lankan Women. Front Endocrinol (Lausanne). 2018 Nov 15;9:682. doi: 10.3389/fendo.2018.00682. PMID: 30524375; PMCID: PMC6262349.

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Reviewer #1: No

Reviewer #2: No

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PLoS One. 2023 Jul 6;18(7):e0280750. doi: 10.1371/journal.pone.0280750.r002

Author response to Decision Letter 0

23 May 2022

Point-by-point response to reviewers

Reviewer 1:

Comment: I would recommend the authors to make two clarifications:

The authors pooled 4 studies: 2 cohorts and 2 RCTs and have chosen to make a pooled analysis.

One sentence in the method section:

Reply: Thank you for your overall positive review and your valuable comments. We agree that we can provide clarity to this part. We have now added to this paragraph the following sentence: “The four studies were merged to perform a pooled analysis.” (page 5)

We agree that this sentence may be misinterpreted. We have now changed the sentence to “Only studies that had core data and were not based on specific selection criteria (e.g. obese women only) were considered for inclusion.”(p.5)

Comment: Can the authors justify why they have chosen to make a pooled analysis (adjusted for study cohorts) instead of making a meta-analysis. Although this second approach has less statistical power it may help observing study specific effects. Please justify and may be discuss in the strength and limitation section.

Reply: Thank you for suggesting an alternative statistical analysis. In principal we have performed statistical analysis comparable with an IPD-meta analysis. However, the analysis was not performed in relation with a systematic review, as the studies included were chosen based on a consortium of studies with glucose data. As statistical power was limited also in the pooled analysis, we did not consider presenting results for these relatively rare outcomes from each individual study (as often done as a first step in a meta-analyses). We did however use the same principles as in a meta-analysis for harmonization of variables etc, and a simpler search did not identify other Norwegian studies, expect one study of obese pregnant women. Nevertheless, as we had not strictly followed all methodology recommended for an IPDMA we chose to call this a "pooled analysis".

Comment: Although it is well explained in the main text, the sentence in the abstract: Asians had a lower risk of delivering large-for-gestational-age infants than Europeans […] can be misleading to readers with limited knowledge in birth weight categorisation. Although you informed (’but maternal glucose values were similarly positively associated with birthweight in all ethnic groups’) I think that there is still a risk of miss-interpretation.

Reply: This sentence could arguably be clearer, and we have now adjusted it as follows below. We hope that it will be acceptable that the abstract now consists of 301 words.

“Asians had a lower risk of delivering large-for-gestational-age infants than Europeans, when applying national birthweight references, but maternal glucose values were similarly positively associated with birthweight in all ethnic groups".

Comment: In theory, as Asian babies are clearly off-chart when it comes to LGA and SGA categorization (based on the Norwegian scales) the analyses cannot be performed as they are meaningless. I would suggest to remove Asian from the LGA analyses.

Reply: Thank you for your suggestion. We agree that not having an ethnicity-specific definition for LGA is a limitation, and this is also discussed in the paper. Unfortunately, there are no customized charts for this group in Norway. In our considered opinion, it is better to employ the national references, which are regularly used in clinical practice for all pregnant women living in Norway, than to completely remove the Asian group from the analysis. As LGA based on a Norwegian reference population is not a very precise measure for Asian women, we have additionally performed linear regression using birthweight z-score (table 4) to explore the association with maternal glucose.

Comment: The discussion is very clear and concise. However, all the comma separators have been substituted by dots. This should be corrected of course.

Reply: I am sorry for this error that appeared at submission. This have now been corrected.

Reviewer 2:

Comment: In Figure 1 what are 'STORK Groruddalen', 'STORK Rikshospitalet', 'Fitfor Delivery', & 'TRIP' - all these acronyms must be explained in the figure.

Reply: Thank you for your valuable comments and suggestions. These are actually not acronyms but the original study titles (Groruddalen and Rikshospitalet are places/hospitals in Norway). TRIP is an acronym for Training in pregnancy. We have added an explanation to the figure text to make this clearer.

“Study names listed in the top boxes. TRIP: Training in pregnancy.” (p. 7)

Comment: The standard nomenclature for International Association of Diabetes and Pregnancy Study Groups (IADPSG) and World Health Organization 2013 (WHO 2013) recommendations is IADPSG or WHO 2013.

Using 2013(superscript)WHO criteria is not standard way of describing. Please show why are these criteria depicted this way - 2013WHO and not WHO 2013 criteria.

Reply: We chose superscript for the years (2013, 2017 and 1999) to increase readability and make it easier to follow for the reader, as these criteria are mentioned a large number of times and it can be confusing with all the numbers.

Comment: The study must make it clear they are not using the full 3 point WHO 2013 or IADPSG but instead using a modified 2 point IADPSG or modified WHO 2013 criteria without 1 hour. The 1 hour time point is an essential part of the IADPSG criteria and will independently adds another one third of cases. This must be stated clearly a limitation that only fasting and 2 hour timepoints are used and thus they are not reflecting the IADPSG full criteria but only comparing the 2 time points criteria within the WHO 2013 criteria.

Reply: We agree that this is an important point that should be emphasized. It has been mentioned as a limitation in the discussion, but to provide even more clarity, we have added the points suggested by you to this paragraph.

“Finally, we used a modified 2013WHO criteria with only two timepoints, as data for 1-hour glucose concentrations were not collected in our study. The prevalence of GDM by the 2013WHO criteria would presumably have been higher with the addition of the 1-hour timepoint.” (p. 22)

Comment: It was shown that Asians had a lower risk of delivering large-for-gestational-age babies. This is not helpful as Asians are smaller size and their babies size norms may be lower. Are customised charts used for Asians, e.g. in relation to mother height and weight and ethnicity?

Reply: See also response to reviewer 1. LGA was calculated using the same Norwegian reference population as used in clinical practice, for classification of LGA/SGA by sex and gestational age. Ethnically customized centile charts are not available in Norway (being a small country), and using customized charts from other countries could also potentially introduce bias, as mean birthweight in Norway is generally higher than for example UK (both for “White” and several immigrant groups). As we agree that LGA based on a Norwegian reference population is not a very precise measure for Asian women, we have instead performed linear regression using birthweight z-score (table 4) to explore the association with maternal glucose. We believe this analysis provides more useful knowledge for the non-European groups.

Comment: However can these findings be applied to Asia in terms of the timepoints? e.g. fasting and relation to baby birthweights etc. Please refer to an Asian paper - Sri Lanka paper with criteria similar to Norwegian for fasting time point, where a similar aspect of changes in the criteria affect the number of cases

Reply: thank for you suggesting this relevant paper. We have added this reference in the discussion, as it provides valuable insight into the subject discussed.

“A study by Dias et al. also supports our findings, showing that 2013WHO criteria is associated with greater birthweight in Sri Lankan pregnant women. (p.21)

Attachment

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PLoS One. doi: 10.1371/journal.pone.0280750.r003

Decision Letter 1

Andreas Beyerlein

28 Jun 2022

PONE-D-22-04306R1Adverse pregnancy outcomes among women in Norway with gestational diabetes using three diagnostic criteriaPLOS ONE

Dear Dr. Rai,

Please submit your revised manuscript by Aug 12 2022 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

We look forward to receiving your revised manuscript.

Kind regards,

Andreas Beyerlein

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Additional Editor Comments (if provided):

- Suggest to use the abbreviation LGA also in the abstract.

- Abstract / Results: In case of a lower or upper limit of 1.0 in a 95% CI, please add as many digits as necessary to indicate whether the 95% CI contains the 1 or not. Mentioning p-values in the main text will then become unnecessary.

- Is it correct that those mothers identified by the 2013WHO and 2017Norwegian criteria but not diagnosed and treated by 1999WHO criteria were mothers with an FPG between 5.1 and 6.9 mmol/L, irrespectively of 2HG? If so, the authors might consider to mention this definition throughout the manuscript to describe this group instead of the lengthy wording used in the manuscript (after justifying it based on the different GDM definitions).

- "Distributions of all potential covariates were tested for normality." Which test was used? Were all continuous covariates assumed to follow a normal distribution based on the test results? Please add this information to the main text.

- Table 1: Please clarify that % values refer to column %.

- Results: ORs are sometimes given with 2, sometimes with 3 digits. This should be handled in a uniform manner, apart from 1.0 in 95% CIs as mentioned above.

- It is unclear to me why the sensitivity analysis was done and what it adds. Please explain this in some detail.

- Table 4:

* Were the conditions for applying a linear regression between maternal glucose and offspring's birthweight checked? In particular, is it plausible to assume a linear relationship instead of a J-shaped or U-shaped one?

* Presumably, FPG and 2HG were not mutually adjusted due to collinearity. This should be explained in the text.

* Asian, unadjusted: "P" should read "95% CI"

* The sign "-" should not be used as a separator between the lower and upper limit of a 95% CI, as it is already needed to indicate negative values. Suggest to use "," or ";" instead (consistently throughout the manuscript)

- In the spirit of Open and Reproducible Science, the analysis code (or SPSS syntax) should be made available in an online repository together with a data dictionary, and the respective URL should be mentioned in the Methods section. Can the data also be made available, and if not, why not?

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #2: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #2: Yes

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #2: Yes

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6. Review Comments to the Author

Reviewer #2: Using a prefix, superscript year before the criteria is highly unconventional in medical literature for diabetes (usually reserved for atomic particles); and may also lead to formatting, spacing and search issues when published. Would still suggest in order of preference, for the 'year' , to be after the criteria and non superscript with space or dash or bracket if needed; or to be after the criteria as postfix.

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7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #2: Yes: Kok Hian TAN

**********

PLoS One. 2023 Jul 6;18(7):e0280750. doi: 10.1371/journal.pone.0280750.r004

Author response to Decision Letter 1

11 Aug 2022

Response to editor:

Comment: Suggest to use the abbreviation LGA also in the abstract.

Reply: I have now added the abbreviation LGA to the abstract and use this instead.

Comment: Abstract / Results: In case of a lower or upper limit of 1.0 in a 95% CI, please add as many digits as necessary to indicate whether the 95% CI contains the 1 or not. Mentioning p-values in the main text will then become unnecessary.

Reply: As suggested, I have now removed the p-values from the main text and added extra digits to the 95 CI% with a lower or upper limit of 1.0.

Comment: Is it correct that those mothers identified by the 2013WHO and 2017Norwegian criteria but not diagnosed and treated by 1999WHO criteria were mothers with an FPG between 5.1 and 6.9 mmol/L, irrespectively of 2HG? If so, the authors might consider to mention this definition throughout the manuscript to describe this group instead of the lengthy wording used in the manuscript (after justifying it based on the different GDM definitions).

Reply: This is not entirely correct. Mothers identified by the 2013-WHO and 2017-Norwegian criteria but not diagnosed and treated by 1999-WHO criteria were mothers with an FPG between 5.1 (or 5.3) and 6.9 mmol/L and with a 2H glucose < 7.8 mmol/L. To keep this as clear as possible to the readers we believe it’s necessary to refer to it in this way, although we agree it’s a bit lengthy.

Comment: "Distributions of all potential covariates were tested for normality." Which test was used? Were all continuous covariates assumed to follow a normal distribution based on the test results? Please add this information to the main text.

Reply: The information about the tests is now added to the main text. “Assumptions for statistical analysis were tested and distributions of all potential covariates were checked for normality using Tests of Normality and by inspection of probability plots, which confirmed that these variables followed a normal distribution.” (p.7-8)

Comment: Table 1: Please clarify that % values refer to column %.

Reply: To clarify this we have now changed the legend for Table 1 to:

Table 1. Characteristics and pregnancy outcomes in total study sample and according to their glucose tolerance status, using three diagnostic criteria for gestational diabetes. For each column data are presented as mean ± SD or n (%).

Comment: Results: ORs are sometimes given with 2, sometimes with 3 digits. This should be handled in a uniform manner, apart from 1.0 in 95% CIs as mentioned above.

Reply: Thank you for pointing this out. We have corrected this, and all OR’s are now given with 3 digits.

Comment: It is unclear to me why the sensitivity analysis was done and what it adds. Please explain this in some detail.

Reply: In the majority of studies similar to ours, researchers exclude participants that have received an intervention/treatment. As much as we would like to do the same, we were unable to due to limited number of participants in our studies. Excluding all participants diagnosed and treated based on the 1999-WHO criteria would leave us with reduced power to explore the outlined associations. The sensitivity analysis was therefore mainly performed to verify the results achieved by the regression analyses where adjustments for treatment and a known diagnosis were made to the model as an alternative to excluding women. To further clarify this point, the following part has been added to the manuscript:

“As a sensitivity analysis, and to verify the results achieved by the analyses where adjustment for treatment and a known diagnosis were made to the model, we repeated the same analysis after excluding participants who were diagnosed and treated based on the 1999WHO criteria as an alternative to excluding women.” (p.8-9).

Comment:

- Table 4:

Were the conditions for applying a linear regression between maternal glucose and offspring's birthweight checked? In particular, is it plausible to assume a linear relationship instead of a J-shaped or U-shaped one?

Reply: The conditions for a linear regression were checked, and the relationship between maternal glucose (fasting and 2HG) and birthweight z-score was linear. The sentence: “The conditions for a linear regression were checked, confirming a linear relationship between maternal glucose values and offspring birthweight” has been added to the methods section (p. 9).

* Presumably, FPG and 2HG were not mutually adjusted due to collinearity. This should be explained in the text.

Reply: It is correct that FPG and 2HG were not mutually adjusted and this is mentioned in the table text. However, it can be explained in the text as well. One sentence about this has now been added under Statistical Analyses: “We did not mutually adjust for FPG and 2HG due to collinearity.” (p.9)

* Asian, unadjusted: "P" should read "95% CI"

Thank you for this remark. It has now been corrected.

We have now changed this sign into to the suggested “,” throughout the manuscript.

Reply: The reason for not being able to share data has been explained thoroughly upon submission under “Data Availability”. This is copy of our statement previously sent:

Reviewer #2:

Comment: Using a prefix, superscript year before the criteria is highly unconventional in medical literature for diabetes (usually reserved for atomic particles); and may also lead to formatting, spacing and search issues when published. Would still suggest in order of preference, for the 'year' , to be after the criteria and non superscript with space or dash or bracket if needed; or to be after the criteria as postfix.

Reply: Thank you for your suggestion. We have changed this throughout the manuscript, and the criteria are now listed as: WHO-1999, WHO-2013 and Norwegian-2017.

Attachment

Submitted filename: Point-by-point response 08.8.22.docx

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PLoS One. doi: 10.1371/journal.pone.0280750.r005

Decision Letter 2

Zhong-Cheng Luo

4 Oct 2022

PONE-D-22-04306R2Adverse pregnancy outcomes among women in Norway with gestational diabetes using three diagnostic criteriaPLOS ONE

Dear Dr. Rai,

More specifically, please address all comments from the reviewer 3, and detail what/where changes are made. .

Please submit your revised manuscript by Nov 18 2022 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

We look forward to receiving your revised manuscript.

Kind regards,

Zhong-Cheng Luo

Academic Editor

PLOS ONE

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #2: All comments have been addressed

Reviewer #3: (No Response)

Reviewer #4: All comments have been addressed

Reviewer #5: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #2: Yes

Reviewer #3: Partly

Reviewer #4: Yes

Reviewer #5: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

Reviewer #3: Yes

Reviewer #4: I Don't Know

Reviewer #5: Yes

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4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #2: Yes

Reviewer #3: No

Reviewer #4: Yes

Reviewer #5: Yes

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #2: Yes

Reviewer #3: Yes

Reviewer #4: Yes

Reviewer #5: Yes

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6. Review Comments to the Author

Reviewer #2: The authors have make amendments to my suggestion of not using prefix for GDM criteria. No more comments.

Reviewer #3: See attached file

The authors present the results of a cohort study that aimed to compare perinatal outcomes between women diagnosed and treated for GDM by the more stringent WHO 1999 diagnostic criteria and women who during that period would have theoretically been diagnosed as having GDM by the lower threshold 2013 and 2017 criteria but were hence not labelled as GDM and thus untreated. This subject has been previously assessed in other studies in different countries and with varying combinations of GDM diagnostic thresholds. The cohort was somewhat unusually constructed by pooling data from 2 cohort studies and two RCTs which might insert an unmeasurable selection bias and influence generalizability. I am not sure whether this a revision of a previously submitted manuscript, but I have not had the opportunity to review it previously.

Overall, this a well thought out paper that is providing some additional information to the many papers that have been published attempting to retrospectively analyze the perinatal impact of changing GDM diagnostic criteria.

Below are my itemized individual comments and questions:

Reviewer #4: The main query is understanding the groups in the WHO 2013 and Norwegian 2017 cohorts that were offered treatment. In Table 1 e.g the WHO 2013 column for the non-GDM has 119 and for GDM 199. From the text it is stated that they were offered treatment if they met the WHO 1999 criteria . Presumably this meant that their 2-hr levels were between 7.8 and 8.5 mmol/l for those that were "non-GDM" and ≥8.5 for the "GDM" group? If this is a correct interpretation it would help to have this spelt out more clearly. The dilemma with labelling them as WHO 2013 GDMs is as you have noted that it misses the group who would have been diagnosed by the 1-hr value of ≥10.0.

My recommendation is that including this group does not add significantly to the paper and could be removed.

Table 1Normal weight should be ≤ 24.9 not ≥24.9

Minor correction the HAPO study being published in the USA is hyperglycemia, not hyperglycaemia.

Reviewer #5: (No Response)

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7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #2: Yes: Kok Hian TAN

Reviewer #3: No

Reviewer #4: Yes: Jeremy J N Oats

Reviewer #5: No

**********

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PLoS One. 2023 Jul 6;18(7):e0280750. doi: 10.1371/journal.pone.0280750.r006

Author response to Decision Letter 2

13 Dec 2022

The point-by-point response to reviewers is attached to this submission.

Reviewer 3

1. Abstract, results: The term “women diagnosed with GDM by all three criteria” might be confusing. Do you mean that women that would have been considered positive by either of the three diagnostic criteria i.e all women with either FPG>5.0 or 2hr >7.7 which would infer pooling of the GDM women in the cohorts or is the intent to say that women who were diagnosed in either of the groups (non-pooling) had increased rates of LGA. I assume the latter as this is more in line with what is stated in the results.

Respond: Thank you for your thorough review and overall positive comments.

We agree that the wording can be confusing, and as you suggest, we have edited the statement to:

“Compared to the non-GDM group, women diagnosed with GDM by either of the three criteria had an increased risk of large-for-gestational-age infants (adjusted odds ratios (OR) 1.7-2.2).” (p.2)

2. Introduction 1st paragraph: I would reconsider stating that “Gestational diabetes mellitus (GDM) is associated with … foetal and neonatal mortality”. While there is good data to support the association with other perinatal outcomes, this is not true for stillbirth and neonatal death. The reference provided (1) does not support this statement.

Respond: Foetal and neonatal mortality is now removed from the sentence, and the reference is updated to ensure that the content corresponds with the phrase. The new sentence is:

“Gestational diabetes mellitus (GDM) is associated with increased risk of macrosomia, caesarean section, preeclampsia and preterm delivery. (p.4)

3. Methods: Justify the grouping of south and east Asian ethnicity under “Asian”. Do these two distinct ethnic backgrounds have similar BMI/insulin resistance levels and rate of GDM related outcomes? Many studies have suggested that South Asians are a distinct group with regards to glucose handling.

Respond: This is a good point. However, out of the 223 Asian women included in this study, only 39 had East Asian origin. We did not have statistical power to study the relationship between glucose levels and the related outcomes in these two groups separately, but sensitivity analyses (not shown) did not suggest that they differed. We therefore made the decision to combine them. The mean BMI and mean birthweight were quite similar in the two groups, but, not surprisingly, South Asians had a somewhat higher prevalence of GDM (42% vs 24% in East Asians, using 2013-WHO criteria). This is already added as a limitation in the discussion.

“However, nearly all non-European women came from one study and the majority of Asians were of South Asian origin.” (p.25)

4. Methods: I would like to understand why fetal deaths that occurred after glucose testing were excluded and not reported as an adverse outcome? This potentially removes some of the most severe cases of poor glycemic control.

Respond: Fetal deaths in this study include abortion<22 weeks, stillbirth≥22 weeks and neonatal death. The majority of these occurred before the first OGTT, and we lack outcome data (birthweight, birth complications, sex etc.) from most of these. After excluding those lacking data on birthweight, we were left with only one fetal death (with normal glucose values) which was then excluded. We have changed the order of the words in the sentence to make it clearer that infants with missing birthweight were excluded first, and then fetal deaths (and figure 1 shows that only one fetal death was excluded).

“After excluding women with multiple pregnancies, those lacking glucose values, infants with missing birthweight and foetal deaths, the study sample consisted of 2970 mother-child pairs.”

5. I am trying to understand how many women diagnosed with GDM by WHO -99 criteria failed lifestyle modification. This is not reported in Table 1 but in the methods it is mentioned that only 12 needed “such pharmacological treatment” which I will assume means either insulin or oral hypoglycemics (correct me if I am wrong). If this is the case, then the rate of lifestyle modification failure was a bit less than 3.8%. This is much less than the reported rate in the literature (20- 40%) and is even more surprising in light of the fact that the FPG threshold for diagnosis and treatment was > 6.9 mmol/L which would have led to a high probability of treatment failure. When examining the mean FPG in the WHO-99 GDM group, the mean FPG was 5.0+/- 0.6 thus it seems that there were very few women with significantly elevated FPG raising questions regarding how representative this cohort is of the GDM population in general ( see comment my comment in the preamble). Perhaps add categorical data on the FPG and 2 hr values (i.e FPG 5.1-5.5; 5.6-6.0; 6.0-6.4; 65-6.9) for clarification of the population characteristics.

Respond: Your understanding is correct regarding how many women failed lifestyle modification - only 12 women needed insulin or metformin, based on available information in the hospital records. Several points may influence this rather low number. Some women may have started with lifestyle modification but later needed medication, in which case their medication may have been overlooked and their treatment registered incorrectly. Furthermore, universal screening was performed in our four cohorts as opposed to risk-factor based screening often carried out in many comparable studies. With that, we include women with a milder form of GDM, and our study may be more representative of real-life low risk populations. We have also touched upon in the discussion that our study included women with less overweight/obesity than the general population which may also have a certain impact.

6. Results: It is stated that “Women diagnosed with GDM by any criteria had a higher rate …”. I do not see a group defined as meeting ANY of the criteria thus this result is not visible in any of the tables and not indicated in the planned analysis (similar to comment 1 above). Please ensure that these group comparisons confirm to the planned analysis and to the groupings presented in the tables.

Respond: The term “diagnosed with GDM by any criteria..” means any of the three criteria. To clarify this further, we have changed the sentence to:

“All three groups of women diagnosed with GDM (according to WHO-1999, WHO-2013 and Norwegian-2017 criteria respectively) had a higher rate of LGA neonates compared to their non-GDM counterparts, while higher rates of macrosomia (birthweight>4000g) were only found in those diagnosed by Norwegian-2017 and WHO-2013 criteria.”(p.9)

7. Figures: pay attention to formatting issues. Figure 1 – not sure is needed in the main paper – could be in supplementary data. I would prefer that figure 1 be a diagram of the different cohorts by diagnostic criteria and the number that would have been identified and treated in each.

Respond: We accept your suggestion of moving Figure 1 to supplementary data. As we mainly look at these four cohorts as one pooled dataset, our main focus is not showing GDM rates in each cohort etc. However, the data on number of women identified and treated in each cohort was published in the first paper from this consortium, and a reference to this specific paper for those interested in more information is already added, and can be found under number 12:

“Detailed study methods for the pooled data set have been previously described (12)..” (p.5)

8. Table 2: Not clear what the first column represents. Add heading. I would also make it clear in the title (and text) that there is a global risk reported for each outcome followed by a stratified analysis by BMI and ethnicity. In the footer define what BMI define Normal, overweight and obesity. Also – in the footer it says that the variables adjusted for are age. gestational weeks at delivery, parity and study cohort while in the text it states that there was also adjustment for treatment by the WHO-1999 criteria. Please clarify and ensure uniformity in reporting.

Respond: Thank you for pointing out that this table was difficult to interpret; we appreciate the opportunity to clarify. The first column shows crude (unadjusted) analyses, while the next columns show adjusted analysis for each criteria (not a stratified analysis by BMI and ethnicity). This is now clearly presented in the table. The definition of BMI categories is now added to the footer.

Further, the analyses are also adjusted for treatment by WHO1999, as stated in the text and shown in the table, as well as pre-pregnancy BMI and ethnicity. The footnote stated that the analysis was “Additionally adjusted for age, maternal smoking, parity and study cohort” – these are the variables we adjusted for but which are not shown separately in the table. The actual number for the rest (treatment, BMI etc) are listed in the tables.

In order to avoid any confusion, we have amended the footer to explicitly define the adjusted analysis. The first applies to the column regarding WHO 1999 criteria, while the second applies to the WHO-2013 and Norwegian-2017 criteria.

* Adjusted for BMI group and ethnicity, as shown. Additionally adjusted for age, gestational weeks at delivery, parity and study cohort.

∞Adjusted for GDM diagnosed by WHO-1990 criteria, BMI group and ethnicity, as shown. Additionally adjusted for age, gestational weeks at delivery, parity and study cohort.

New title for table 2: Crude and adjusted analyses of risk of large-for-gestational-age, total cesarean section and operative vaginal delivery, by GDM-criteria. (p.13).

9. In both Table 2 and 3: I am not sure why under the outcome (LGA, CS etc) there is a subcategory of the diagnostic criteria. This is confusing and unnecessary as this is self-evident from the column identification. Also, Table 3 formatting is unusual with different Tables for each outcome and separate footnotes. Should align with format of Table 2.

Respond: Table 2: the subcategory of diagnostic criteria is listed mainly to show the crude analyses for each criteria, and the unadjusted risk would be impractical to present otherwise. In table 3 we agree that we could have just presented one row and typed “GDM” instead of GDM and the respective criteria. We have also merged the three tables into one and placed the footnotes in the end of the table to align with the format of table 2.

10. Also, in the title of Table 3 (and in text) it would be good to spell out for the reader that this analysis is for the subgroup of those that would have GDM by the newer criteria but were UNDIAGNOSED AS GDM AND THUS UNTREATED.

Respond: Thank you for this suggestion. In this sensitivity analysis, we repeat the same analysis as in table 2, but after excluding women who were diagnosed and treated according to the WHO-1999 criteria. One could of course turn it around and give it a title as suggested. However, what we wish to highlight here is that this is the exact same analysis as table 2 (in which we adjusted for the treatment effect) but it is performed after excluding diagnosed/treated women. The analysis presented in Table 3 was performed mainly for statistical reassurance, to support and verify our main analysis (Table 2).

11. As I was re-reading, another possibility is to add to Table 2 the untreated aOR with a footnote explaining the different cohort structure. This would allow the reader to compare visually the untreated vs the combination of treated and untreated cohorts. With appropriate Table design this could be not too complex.

Respond: Thank you for your suggestion. This could be possible, but, as this table is already complex with a lot of data and details, we would prefer to keep it as it is.

12. If needed – Table 4 could easily be a supplementary table.

Respond: We would like to include this table to demonstrate the important point that the use of LGA as an outcome representing excessive fetal growth is challenging, as the definition of LGA is not ethnicity-specific. Thus, very few ethnic Asian babies were born LGA. With the help of the analyses presented in this table, we show that the effect of elevated glucose on birthweight was similar across ethnic groups.

13. Discussion: Is the statement “Those retrospectively identified by the Norwegian-2017 and WHO-2013 criteria, but who were not diagnosed and treated by the WHO-1999 criteria (i.e., women with moderately elevated fasting glucose only) also had an increased risk of cesarean section and operative vaginal delivery after adjustment for confounders.” Accurate? In Table 3, that shows the results for “untreated GDM”, ONLY LGA was significant. Clarify and adjust discussion as needed.

Respond: Our main analyses are presented in table 2 and our goal was to include all women without having to exclude a large number of participants as this might lead to power limitations and less representativity. However, with advice from study statistician and suggestions from reviewers in the first revision round, we included a sensitivity analysis (table 3) to support and verify the results of our main analysis. This is explained under the heading “statistical analysis”:

This sensitivity analyses gave almost identical effect estimates as the main analyses (table 2), although, when women with GDM by WHO-1999 were excluded, statistical significance was only reached for LGA. This was probably due to the decreased population size in this analysis, which is why our conclusion is based on the analyses in table 2 to a greater extent.

14. At the end of the first paragraph in the discussion you state that “moderately elevated fasting glucose, when unidentified and untreated, is associated with several adverse outcomes” and that the increased risk was “…primarily based on elevated 2HG values.”. I do not see any separate analysis showing the effect of the individual abnormal 75 gram OGTT value except for the effect on z score birthweight which is definitely not an “adverse outcome” in itself. New results should not be entered into the discussion. Please clarify and if needed adjust manuscript accordingly.

Respond:

We regret that our wording has been unclear. Our intention was not to enter new results in this part of the paper, but rather to underline that the WHO-1999 criteria are primarily based on elevated 2HG values. To avoid misunderstandings, we have added to the sentence the words “which are”.

“Taken together, these findings indicate that moderately elevated fasting glucose, when unidentified and untreated, is associated with several adverse outcomes that were not observed in women where GDM was detected and treated according to WHO-1999 diagnostic criteria, which are primarily based on elevated 2HG values. (p.19)

15. When comparing the results to what is known in the literature you cite studies from Canada. For your interest one of the first studies from Canada is Am J Obstet Gynecol 2015;212:224.e1-9.

Respond: Thank you for making us aware of this relevant paper. We have now added this study along with the other studies from Canada in the reference list.

16. The last sentence in the conclusion states that “What remains unanswered and can be established by randomized trials is whether treating mild hyperglycaemia benefits women and their offspring, leading to an improvement in perinatal outcomes” is a bit bombastic and does not take into consideration ACHOIS (to a lesser degree) and the NICHD study (N Engl J Med 2009; 361:1339-1348).I would consider changing this.

Respond: You are correct that if read alone, this sentence doesn’t take into consideration the studies of Crowther and Landon. However, this sentence is connected to the previous sentences and must be read in light of them. Our data demonstrates that women with moderately elevated fasting glucose levels have an increased risk of adverse pregnancy outcomes, but we need more data, and especially RCT’s, demonstrating whether treating women falling into this particular group (moderately elevated fasting glucose but a low 2HG value) has clinical value. Although both studies (ACHOIS and NICHD) demonstrated a benefit of treatment of GDM, both of these studies employed criteria focused on elevated post-load glucose values (ACHOIS used criteria similar to WHO 1999, and NICHD included only women with fasting glucose <5,3 mmol/l combined with elevated 1-, 2- or 3- hour values) thereby demonstrating the need for more information on the effect of treating women with moderately elevated fasting glucose values only.

We have now modified this sentence to make it more nuanced:

“What remains unanswered and can be established by randomized trials is whether treating mild fasting hyperglycaemia benefits women and their offspring, leading to an improvement in perinatal outcomes.”

Reviewer 4:

My recommendation is that including this group does not add significantly to the paper and could be removed.

Table 1Normal weight should be ≤ 24.9 not ≥24.9

Minor correction the HAPO study being published in the USA is hyperglycemia, not hyperglycaemia.

Respond: Thank you for your comments and suggestions.

It is correct that women in the study were offered treatment if they met the WHO 1999 criteria – that is, fasting glucose ≥7.0 mmol/l and/or 2-hour glucose (2HG) ≥7.8 mmol/l. In the analyses we have adjusted for the treatment effect (or excluded treated women in the sensitivity analyses, table 3).

Women with GDM by WHO-2013 criteria, after controlling for or excluding treatment by WHO-1999 criteria, are those with fasting glucose 5.1-6.9 mmol/l and 2-hour glucose 2HG <7.8 mmol/l.

Women with GDM by Norwegian-2017 criteria, after controlling for or excluding treatment by WHO 1999-criteria, are those with fasting glucose 5.3-6.9 mmol/l and 2-hour glucose <7.8 mmol/l.

We have tried to explain this in the paper, both under statistical analyses and under results, see page 8 and 13:

“Doing so allowed us to identify the group of women with an elevated fasting blood glucose only (fasting glucose 5.1-6.9 mmol/l and 2HG <7.8 mmol/l for WHO-2013, and fasting glucose 5.3-6.9 mmol/l and 2HG <7.8 mmol/l for Norwegian-2017 criteria) who were untreated.”

“After adjusting for confounders and for treatment by the WHO-1999 criteria (thereby expressing the risk related to having fasting glucose 5.1-6.9 mmol/l while 2HG <7.8 mmol/l) the OR for LGA for this group was 1.70 (95% CI 1.2,2.5,) compared to non-GDM women (both fasting glucose <5.1 mmol/l and 2HG <7.8 mmol/l).(p.13)” etc

The reason we didn’t exclude treated women completely from our analyses is that it would affect representativity and result in low power to detect associations with GDM. Therefore, we have instead adjusted for the treatment effect when studying this group.

It is unclear if you suggest removing the women diagnosed by WHO 2013 criteria, as we do not have information on women with elevated 1-hour glucose values. We maintain that it is important to include this group, despite our acknowledged limitation, as it allows us to compare the outcomes associated with two different thresholds for fasting glucose: 5.1 mmol/l for WHO 2013 and 5.3 mmol/l for Norwegian 2017. Of these, the WHO 2013 criteria are most widely used, and therefore relevant for comparison.

The symbols have now been corrected as per your suggestion, so is the spelling of “hyperglycemia”.

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PLoS One. doi: 10.1371/journal.pone.0280750.r007

Decision Letter 3

Zhong-Cheng Luo

8 Jan 2023

Adverse pregnancy outcomes among women in Norway with gestational diabetes using three diagnostic criteria

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PLoS One. doi: 10.1371/journal.pone.0280750.r008

Acceptance letter

Zhong-Cheng Luo

12 Jan 2023

PONE-D-22-04306R3

Adverse pregnancy outcomes among women in Norway with gestational diabetes using three diagnostic criteria

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Supplementary Materials

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S1 Fig. Flowchart of included studies and excluded participants from each study.

Study names listed in the top boxes. TRIP: Training in pregnancy.

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Data Availability Statement

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PERMALINK

Adverse pregnancy outcomes among women in Norway with gestational diabetes using three diagnostic criteria

Anam Shakil Rai

Line Sletner

Anne Karen Jenum

Nina Cecilie Øverby

Signe Nilssen Stafne

Elisabeth Qvigstad

Are Hugo Pripp

Linda Reme Sagedal

Roles

Abstract

Introduction

Material and methods

Results

Conclusions

Introduction

Material and methods

Study design and population

Obstetric and neonatal outcomes

Main exposure and covariates

Statistical analyses

Ethics

Results

Table 1. Characteristics and pregnancy outcomes in total study sample and according to their glucose tolerance status, using three diagnostic criteria for gestational diabetes.

Fig 1.

Table 2. Crude and adjusted analyses of risk of large-for-gestational-age, total cesarean section and operative vaginal delivery, by GDM-criteria.

Table 3. Adjusted analysis of risk of large-for-gestational-age, total cesarean section and operative vaginal delivery after excluding women with a GDM diagnosis based on WHO-1999 criteria.

Table 4. Linear regressions of maternal glucose on offspring’s birthweight z-score, stratified for ethnic group.

Discussion

Conclusion

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Andreas Beyerlein

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Author response to Decision Letter 0

Decision Letter 1

Andreas Beyerlein

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Author response to Decision Letter 1

Decision Letter 2

Zhong-Cheng Luo

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Author response to Decision Letter 2

Decision Letter 3

Zhong-Cheng Luo

Roles

Acceptance letter

Zhong-Cheng Luo

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Associated Data

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Data Availability Statement

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