Maternal and child gluten intake and association with type 1 diabetes: The Norwegian Mother and Child Cohort Study.

BACKGROUND: The relationship between maternal gluten intake in pregnancy, offspring intake in childhood, and offspring risk of type 1 diabetes has not been examined jointly in any studies. Our aim was to study the relationship between maternal and child intake of gluten and risk of type 1 diabetes in children. METHODS AND
FINDINGS: We included 86,306 children in an observational nationwide cohort study, the Norwegian Mother and Child Cohort Study (MoBa), with recruitment from 1999 to 2008 and with follow-up time to April 15, 2018. We used registration of type 1 diabetes in the Norwegian childhood diabetes registry as the outcome. We used Cox proportional hazard regression to estimate hazard ratios (HRs) for the mother's intake of gluten up to week 22 of pregnancy and offspring gluten intake when the child was 18 months old. The average time followed was 12.3 years (0.70-16.0). A total of 346 children (0.4%) children were diagnosed with type 1 diabetes, resulting in an incidence rate of 32.6/100,000 person-years. Mean gluten intake per day was 13.6 g for mothers and 8.8 g for children. There was no association between the mother's intake of gluten in pregnancy and offspring type 1 diabetes, with an adjusted HR (aHR) of 1.02 (95% confidence interval [CI] 0.73-1.43, p = 0.91) for each 10-g-per-day increment. There was an association between offspring intake of gluten and a higher risk of type 1 diabetes, with an aHR of 1.46 (95% CI 1.06-2.01, p = 0.02) for each 10-g-per-day increment. Among the limitations are the likely imprecision in estimation of gluten intake and that we only had information regarding gluten intake at 2 time points in early life.
CONCLUSIONS: Our results show that, while the mother's intake of gluten in pregnancy was not associated with type 1 diabetes, a higher intake of gluten by the child at an early age may give a higher risk of type 1 diabetes.

Introduction

Type 1 diabetes is an increasingly common disease often presenting in childhood, with some of the highest incidence rates in the Nordic countries [1]. Type 1 diabetes occurs after an immune-mediated destruction of pancreatic beta cells, which in the end leads to lifelong dependence on insulin treatment [2]. While genetic factors are important in the aetiology of the disease, increased incidence rates over recent decades suggest a role for nongenetic factors [1].

Gluten has been hypothesised to be one of the environmental factors involved in the development of type 1 diabetes [3]. It has been found in animal models and in vitro studies that gluten may have an effect on the immune system by increasing proinflammatory cytokine production or may lead to dysbiosis of the gut microbiota [3].

Most of the prospective studies in humans that have examined aspects of gluten intake as a risk factor for type 1 diabetes have focused on age at introduction of cereals or gluten-containing foods in infancy in high-risk cohorts, with inconsistent results [4-11]. Two small studies reported no association between maternal intake of gluten-containing foods in pregnancy and development of islet autoimmunity [12, 13], but a recent, large cohort study found that the mother’s intake of gluten while pregnant may increase the probability of the offspring having type 1 diabetes [14]. The relationship between maternal gluten intake in pregnancy, the child’s intake at 18 months, and the child’s risk of type 1 diabetes have not been examined together in any studies.

The aim was to study the relationship between maternal and child intake of gluten and risk of type 1 diabetes in children.

Methods

Participants and study design

We included participants in the Norwegian Mother and Child Cohort Study (MoBa) [15]. MoBa is a prospective nationwide, population-based pregnancy cohort in Norway during 1999–2009. The women consented to participation in 41% of the pregnancies. A total of 86,306 children, of whom 346 developed type 1 diabetes, were included in the analysis (Fig 1).

Fig 1

Flowchart of the study cohort.

*The food frequency questionnaire was introduced in 2002 (response rate 92%). †In the analysis including both pregnancy and childhood gluten intake, there were 62,900 participants with valid data (255 of these were type 1 diabetes cases). ‡Nine cases were excluded from the analyses due to having the outcome of type 1 diabetes prior to the exposure measurement at 18 months. MoBa, Norwegian Mother and Child Cohort Study.

The current study is based on version VIII of the quality-assured data files. We used a prospective analysis plan in designing the study (S1 Text). We used exposure information from questionnaires (for English versions, see https://www.fhi.no/en/studies/moba/for-forskere-artikler/questionnaires-from-moba) at pregnancy week 22 and offspring age 18 months. Data were linked to the Medical Birth Registry of Norway and the Norwegian Patient Register using personal identity numbers assigned to all Norwegian residents.

Exposures: Gluten intake during pregnancy and in the child at age 18 months

Intake of gluten was assessed from a semiquantitative food frequency questionnaire completed around pregnancy week 22 and from a questionnaire at child’s age 18 months (S1 Fig). For the food frequency questionnaire completed around pregnancy week 22, we derived the average protein intake (grams per day) from gluten-containing flour or grains from the MoBa food database. The food frequency questionnaire covered the period up to week 22 of pregnancy and has been validated for food and nutrient intake [16]. To estimate the child’s gluten intake, we used a questionnaire completed at 18 months covering the frequency of wheat-, rye-, and barley-containing food intake. Portion sizes were obtained from a published report [17] and product labels. We estimated the average protein intake (grams per day) from gluten-containing flour or grains by using recipes and nutritional contents of food items from the Norwegian Food Composition Table [18] in addition to traditional recipes and ingredient lists from product labels. The average gluten intake (grams per day) was estimated by using a conversion factor of 0.75 in accordance with most studies [19-21]. The conversion factor of 0.75 is based on conversion factors of 0.80 for wheat, 0.65 for rye, and 0.50 for barley [21-23], wheat being the most widely used grain in the different food products assessed.

We excluded from the analyses children with a gluten intake above 35 g/day at 18 months of age (n = 39, Fig 1). We categorised intake of gluten into percentiles (<10, 10–20, 20–50, 50–80, 80–90, and ≥90) for comparison with the recently published study from Denmark [14]. Characteristics of participants are shown in Table 1. (Characteristics for participants with valid information on intake of gluten in childhood are shown in S1 Table) Characteristics of participants excluded due to missing exposure data are shown in S2 Table.

Table 1

Characteristics of the study participants included in the analysis of maternal gluten intake during pregnancy and risk of type 1 diabetes in the child.

Gluten intake by percentile	All participants	<10%	10%–20%	20%–50%	50%–80%	80%–90%	>90%
Median (range) in g/day	13.0 (0–62.5)	5.9 (0–7.6)	8.7 (7.6–9.5)	11.4 (9.5–13.0)	14.8 (13.0–17.3)	18.4 (17.3–20.1)	23.0 (20.1–62.5)
Maternal characteristics	n = 86,306	n = 8,518	n = 8,616	n = 25,962	n = 25,928	n = 8,653	n = 8,629
Age in years, mean (SD)	30.2 (4.6)	29.7 (4.9)	30.2 (4.6)	30.4 (4.5)	30.5 (4.4)	30.2 (4.5)	29.6 (4.9)
<25	9,165 (10.6)	1,293 (15.2)	965 (11.2)	2,422 (9.3)	2,267 (8.7)	924 (10.7)	1,294 (15.0)
25–34	61,812 (71.6)	5,818 (68.3)	6,091 (70.7)	18 797 (72.4)	18,844 (72.7)	6,254 (72.3)	6,008 (69.6)
≥35	15,329 (17.8)	1,407 (16.5)	1,560 (18.1)	4,743 (18.3)	4,817 (18.6)	1,475 (17.0)	1,327 (15.4)
Prepregnancy BMI, mean (SD)	24.1 (4.3)	24.3 (4.5)	24.3 (4.4)	24.2 (4.3)	24.0 (4.2)	23.7 (4.1)	23.9 (4.4)
<20	10,522 (12.2)	1,068 (12.5)	945 (11.0)	2,954 (11.4)	3,133 (12.1)	1,208 (14.0)	1,214 (14.1)
20–25	47,032 (54.5)	4,307 (50.6)	4,672 (54.2)	14 182 (54.6)	14,388 (55.5)	4,838 (55.9)	4,645 (53.8)
25–29.9	18,475 (21.4)	1,936 (22.7)	1905 (22.1)	5,671 (21.8)	5,496 (21.2)	1,757 (20.3)	1,710 (19.8)
≥30	8,055 (9.3)	916 (10.8)	896 (10.4)	2,500 (9.6)	2,289 (8.8)	646 (7.5)	808 (9.4)
Missing data	2,222 (2.6)	291 (3.4)	198 (2.3)	655 (2.5)	622 (2.4)	204 (2.4)	252 (2.9)
Prematurity	5,391 (6.2)	567 (6.7)	551 (6.4)	1,587 (6.1)	1,540 (5.9)	550 (6.4)	596 (6.9)
Missing data	61 (0.1)	6 (0.1)	7 (0.1)	22 (0.1)	16 (0.1)	3 (0.0)	7 (0.1)
Parity
0	39,548 (45.8)	4,561 (53.5)	4,196 (48.7)	11,744 (45.2)	11,201 (43.2)	3,858 (44.6)	3,988 (46.2)
1	30,447 (35.3)	2,667 (31.3)	2,885 (33.5)	9,339 (36.0)	9,561 (36.9)	3,085 (35.7)	2,910 (33.7)
≥2	16,311 (18.9)	1,290 (15.1)	1,535 (17.8)	4,879 (18.8)	5,166 (19.9)	1,710 (19.8)	1,731 (20.1)
Smoking during pregnancy
No	78,332 (90.8)	7,570 (88.9)	7,780 (90.3)	23,814 (91.7)	23,769 (91.7)	7,858 (90.8)	7,541 (87.4)
Occasionally	1,465 (1.7)	154 (1.8)	163 (1.9)	427 (1.6)	404 (1.6)	159 (1.8)	158 (1.8)
Yes	6,044 (7.0)	745 (8.7)	619 (7.2)	1,586 (6.1)	1,615 (6.2)	602 (7.0)	877 (10.2)
Missing data	465 (0.5)	49 (0.6)	54 (0.6)	135 (0.5)	140 (0.5)	34 (0.4)	53 (0.6)
Maternal education
<12 years	31,116 (36.1)	3,864 (45.4)	3,331 (38.7)	8,858 (34.1)	8,247 (31.8)	3,006 (34.7)	3,810 (44.2)
12–15 years	34,982 (40.5)	2,909 (34.2)	3,408 (39.6)	10 854 (41.8)	11,128 (42.9)	3,537 (40.9)	3,146 (36.5)
≥16 years	19,789 (22.9)	1,672 (19.6)	1,846 (21.4)	6,141 (23.7)	6,442 (24.8)	2,069 (23.9)	1,619 (18.8)
Missing data	419 (0.5)	73 (0.9)	31 (0.4)	109 (0.4)	111 (0.4)	41 (0.5)	54 (0.6)
Breastfeeding duration, mean (SD)	9.9 (4.5)	9.4 (4.6)	9.6 (4.6)	9.9 (4.5)	10.1 (4.5)	10.2 (4.5)	9.6 (4.6)
<6.0 months	12,701 (14.7)	1,424 (16.7)	1,395 (16.2)	3,825 (14.7)	3,525 (13.6)	1,139 (13.2)	1,393 (16.1)
6.0–11.9 months	26,226 (30.4)	2,453 (28.8)	2,596 (30.1)	8,136 (31.3)	7,969 (30.7)	2,630 (30.4)	2,442 (28.3)
≥12 months	24,304 (28.2)	1981 (23.3)	2,270 (26.3)	7,433 (28.6)	7,802 (30.1)	2,580 (29.8)	2,238 (25.9)
Missing data	23,075 (26.7)	2,660 (31.2)	2,355 (27.3)	6,568 (25.3)	6,632 (25.6)	2,304 (26.6)	2,556 (29.6)
Fibre intake (g), mean (SD)	31.2 (11.9)	19.4 (8.1)	23.6 (7.7)	27.6 (7.1)	33.1 (7.9)	38.7 (9.0)	48.4 (16.7)
<20th centile	15,776 (18.3)	6,003 (70.5)	4,016 (46.6)	4,842 (18.7)	845 (3.3)	56 (0.6)	14 (0.2)
20–40th centile	16,719 (19.4)	1,318 (15.5)	2,431 (28.2)	8,432 (32.5)	4,098 (15.8)	360 (4.2)	80 (0.9)
40–60th centile	17,418 (20.2)	624 (7.3)	1,209 (14.0)	6,709 (25.8)	7,358 (28.4)	1,235 (14.3)	283 (3.3)
60–80th centile	17,931 (20.8)	325 (3.8)	633 (7.3)	4,201 (16.2)	8,328 (32.1)	3,099 (35.8)	1,345 (15.6)
80–100th centile	18,461 (21.4)	248 (2.9)	327 (3.8)	1,778 (6.8)	5,299 (20.4)	3,903 (45.1)	6,906 (80.0)
Missing data	1 (0.0)	-	-	-	-	-	1 (0.0)
Energy intake (MJ), mean (SD)	9.8 (3.2)	6.9 (2.0)	7.9 (1.8)	8.9 (1.9)	10.3 (2.2)	11.6 (2.5)	14.1 (5.4)
<20th centile	15,744 (18.2)	5,699 (66.9)	3,701 (43.0)	5,060 (19.5)	1,205 (4.6)	70 (0.8)	9 (0.1)
20–40th centile	16,886 (19.6)	1,527 (17.9)	2,632 (30.5)	7,694 (29.6)	4,408 (17.0)	517 (6.0)	108 (1.3)
40–60th centile	17,420 (20.2)	703 (8.3)	1,309 (15.2)	6,636 (25.6)	6,833 (26.4)	1,468 (17.0)	471 (5.5)
60–80th centile	17,883 (20.7)	369 (4.3)	699 (8.1)	4,541 (17.5)	7,804 (30.1)	2,828 (32.7)	1,642 (19.0)
80–100th centile	18,372 (21.3)	220 (2.6)	275 (3.2)	2,031 (7.8)	5,678 (21.9)	3,770 (43.6)	6,398 (74.1)
Missing data	1 (0.0)	-	-	-	-	-	1 (0.0)
Offspring characteristics
Cesarean section	13,001 (15.1)	1,450 (17.0)	1,401 (16.3)	3,863 (14.9)	3,730 (14.4)	1,225 (14.2)	1,332 (15.4)
Type 1 diabetes	346 (0.4)	23 (0.3)	45 (0.5)	102 (0.4)	99 (0.4)	42 (0.5)	35 (0.4)
Female	42,179 (48.9)	4,189 (49.2)	4,201 (48.8)	12,749 (49.1)	12,715 (49.0)	4,211 (48.7)	4,114 (47.7)
Birth weight (g), mean (SD)	3,561 (587)	3,514 (593)	3,539 (587)	3,561 (585)	3,580 (583)	3,571 (585)	3,557 (598)
<2,500	3,585 (4.2)	403 (4.7)	378 (4.4)	1,108 (4.3)	965 (3.7)	341 (3.9)	390 (4.5)
2,500–3,499	33,185 (38.5)	3,538 (41.5)	3,401 (39.5)	9,934 (38.3)	9,731 (37.5)	3,267 (37.8)	3,314 (38.4)
3,500–4,499	45,932 (53.2)	4,261 (50.0)	4,529 (52.6)	13,860 (53.4)	14,067 (54.3)	4,690 (54.2)	4,525 (52.4)
≥4,500	3,598 (4.2)	315 (3.7)	308 (3.6)	1,058 (4.1)	1,162 (4.5)	355 (4.1)	400 (4.6)
Missing data	6 (0.0)	1 (0.0)	-	2 (0.0)	3 (0.0)	-	-
Age at gluten introduction
<4.0 months	515 (0.6)	70 (0.8)	52 (0.6)	135 (0.5)	129 (0.5)	46 (0.5)	83 (1.0)
4.0–5.9 months	16,603 (19.2)	1,575 (18.5)	1,657 (19.2)	4,950 (19.1)	4,974 (19.2)	1,710 (19.8)	1,737 (20.1)
≥6 months	59,347 (68.8)	5,614 (65.9)	5,883 (68.3)	18,193 (70.1)	18,061 (69.7)	5,935 (68.6)	5,661 (65.6)
Missing data	9,841 (11.4)	1,259 (14.8)	1,024 (11.9)	2,684 (10.3)	2,764 (10.7)	962 (11.1)	1,148 (13.3)
Coeliac disease diagnosis	828 (1.0)	70 (0.8)	84 (1.0)	253 (1.0)	269 (1.0)	83 (1.0)	69 (0.8)
Missing data	153 (0.2)	16 (0.2)	22 (0.3)	55 (0.2)	33 (0.1)	12 (0.1)	15 (0.2)
Weight gain (kg) 0–12 months, mean (SD)	6.4 (1.05)	6.4 (1.07)	6.4 (1.07)	6.4 (1.04)	6.4 (1.05)	6.3 (1.06)	6.4 (1.06)
Missing data	28,829 (33.4)	3,231 (37.9)	2,923 (33.9)	8,238 (31.7)	8,298 (32.0)	2,911 (33.6)	3,228 (37.4)

Abbreviation: BMI, body mass index

Outcome: Type 1 diabetes

Time to clinical type 1 diabetes diagnosis in the child was used as the outcome. Data on offspring type 1 diabetes were obtained from the Norwegian Patient Registry and Norwegian Childhood Diabetes Registry [24]. Nine cases of monogenic or type 2 diabetes were excluded from the study. Identified during follow-up were a total of 346 children with type 1 diabetes with valid information on maternal gluten intake at week 22 of pregnancy and 271 children with valid information on child gluten intake at 18 months of age (Fig 1). Participants excluded due to missing exposure information did not differ in their incidence of type 1 diabetes compared to those included in the current analysis (S2 Fig).

Other variables

We obtained maternal age, parity, and mode of delivery and child sex, birth weight, and gestational age—categorised as shown in Table 1—from the Medical Birth Registry of Norway. The MoBa recruitment questionnaire completed at week 18 of pregnancy provided data on maternal education, smoking, prepregnant body mass index (BMI), maternal coeliac disease diagnosis, and maternal type 1 diabetes diagnosis. From MoBa questionnaires completed at child age 6 and 18 months, we obtained information on breastfeeding duration and child age at the time of gluten introduction [25]. MoBa age-7 or -8 questionnaires and register linkage to the Norwegian Patient Register (to the end of 2016) provided information on the child’s coeliac disease diagnosis [26]. The Norwegian Patient Register also provided data on parents’ medical codes indicative of coeliac disease and type 1 diabetes. We excluded children of mothers with type 1 diabetes or coeliac disease due to the influence on the mother’s intake of gluten, and potentially the child’s intake (n = 1,682; Fig 1).

Statistical analysis

Based on the previous Danish study [14] showing a relative risk of 2 comparing the upper and lower categories of maternal gluten intake, we calculated that our sample size would provide us with a statistical power of 94% for the analyses of maternal gluten intake and 88% for child’s gluten intake.

We used Cox regression analysis to estimate hazard ratios (HRs) with 95% confidence intervals (CIs). Follow-up time was counted from birth (when analysing mother’s gluten intake) or from child’s age of 18 months (when analysing child’s gluten intake) to type 1 diabetes diagnosis or end of follow-up (April 15, 2018). In analyses mutually adjusting for maternal and child gluten intake, we started the follow-up at 18 months. We found no evidence for violation of the proportional hazards assumption by visually assessing log-minus log plots or formally testing Schoenfeld residuals. We used robust cluster variance estimation to account for potential correlation among siblings in the cohort. We predefined statistical significance as p-values of 0.05 or 95% CIs for the HR not including 1.00. The primary analysis was further predefined to be the test for linear trend (per 10-g increase in gluten intake per day), with covariates defined in model 2 (see subsequently), and to be based on a data set in which we imputed missing covariates using multiple imputation with chained equations [27]. To test nonlinearity, we analysed gluten as a categorical variable using the same cut-offs as the Danish national prospective cohort study (Table 1 and S1 Table) [14].

In addition to unadjusted analyses, we decided a priori to adjust for variables that may be associated with gluten intake and type 1 diabetes. Model 1 adjusted for covariates similar to the Danish national prospective cohort study [14]: prepregnancy maternal BMI, age, parity, smoking status, education, breastfeeding duration, cesarean section, energy intake, and child’s sex. Model 2, our primary model, additionally adjusted for age at gluten introduction, birth weight, prematurity, weight gain 0–12 months, and maternal fibre intake during pregnancy and mutually adjusted maternal and child’s gluten intake. (In the mutually adjusted analyses, maternal gluten intake is a potential confounder for the child’s gluten intake–type 1 diabetes association, whereas child’s gluten intake is a potential mediator in the maternal gluten intake–type 1 diabetes association.)

In sensitivity analyses to assess the impact of imputing missing covariates, we repeated the main analyses in those with complete covariate data. In response to a peer review comment, we made a Kaplan Meier survival plot of the main analyses stratified by child’s sex and birth weight, and we made a density plot showing the distribution of maternal gluten intake in pregnancy and child’s gluten intake at age 18 months. We also assessed the association of maternal fibre intake and gluten intake from refined grains during pregnancy and risk of type 1 diabetes in the child. Also, we assessed the impact of further adjusting our analyses for the child’s coeliac disease, and we performed analyses after excluding children who were diagnosed with coeliac disease during follow-up, as suggested in a peer review comment. In response to other peer review comments, we did additional analyses including children who have a mother with type 1 diabetes or celiac disease in the primary model, and we additionally adjusted for other types of diabetes in the mother (type 2 diabetes or gestational diabetes obtained from the medical birth registry of Norway) in the primary model. All analyses were done in Stata version 15 (College Station, TX).

Patient and public involvement

We conducted the study on previously collected data with no patient involvement in development of the research question or outcome measures, nor in the development of design, the recruitment, or the conduct of the study. Patients were not asked to advise on interpretation or writing up of results. Results from MoBa are disseminated to study participants through press releases, a yearly newsletter sent to all participating families, and the study’s and the Norwegian Institute of Public Health’s websites.

Ethical approval

The establishment and data collection in MoBa was previously based on a licence from the Norwegian Data Inspectorate and approval from the Regional Committee for Medical and Health Research Ethics South East, and it is now based on regulations related to the Norwegian Health Registry Act. All participants provided written informed consent. The present study was approved by the Regional Committee for Medical and Health Research Ethics South East.

Results

Of all participating children, 0.4% were diagnosed with type 1 diabetes (n = 346) after a mean of 12.3 years (range 0.7–16.0) of follow-up (Fig 1). The mean age at diagnosis was 7.5 years (range 0.7–15.0). We had information on islet autoantibodies (towards insulin, glutamic acid decarboxylase, and IA2) at diagnosis from 76% the children who developed type 1 diabetes, and 92% were positive for at least one islet autoantibody. The overall incidence rate of type 1 diabetes per 100,000 person-years was 32.6. Mean maternal gluten intake during pregnancy was 13.6 g/day (standard deviation 5.2, median 13.0 g/day), and the child’s mean gluten intake at age 18 months was 8.8 g/day (standard deviation 3.6, median 8.2 g/day). The distribution of the mother’s intake of gluten and offspring intake of gluten in childhood is shown in S3 Fig.

Gluten intake was lower (p < 0.001) in mothers who had a lower fibre and energy intake (Table 1). Gluten intake was also lower (p < 0.001) in children of mothers who were younger and less educated and who breastfed their child for a shorter duration (S1 Table). Children of mothers with a low gluten intake during pregnancy tended to have a lower gluten intake at 18 months, but the correlation was weak (Spearman’s rho = 0.11, p < 0.001, S4 Fig).

Maternal gluten intake during pregnancy and risk of type 1 diabetes in the child

Maternal gluten intake during pregnancy was not associated with risk of type 1 diabetes in the child (Table 2). For each 10-g/day-increase of gluten intake, the adjusted hazard ratio (aHR) was 1.02 (95% CI 0.73–1.43, p = 0.91). For each standard deviation (5.2 g/day) increase of gluten intake, the aHR was 1.01 (95% CI 0.85–1.20, p = 0.91). While there was a tendency towards a nonlinear association—with higher risk of type 1 diabetes in those with the next lowest and in those with the next highest category of maternal gluten intake—the global likelihood ratio test did not support a significant nonlinear association (p = 0.11).

Table 2

Association between maternal gluten intake during pregnancy (n = 86,306) or the child’s intake at 18 months (n = 66,725) and the risk of type 1 diabetes in the child.

Gluten intake	Cases	Incidence rate (per 100,000)	HR (95% CI) of type 1 diabetes
			Unadjusted	p-Value	Adjusted model 1*	p-Value	Adjusted model 2† (primary model)	p-Value	Adjusted model 3‡	p-Value
Maternal/pregnancy
Continuous, per 10-g/day increase	346	36.6	1.04 (0.86–1.27)	0.68	1.02 (0.81–1.30)	0.84	1.02 (0.73–1.43)	0.91	1.01 (0.71–1.42)	0.97
By category
<7.6 g/day	23	22.3	Ref.		Ref.		Ref.		Ref.
7.6–9.5 g/day	45	42.6	1.90 (1.13–3.18)	0.01	1.90 (1.13–3.20)	0.01	1.71 (0.94–3.09)	0.08	1.65 (0.91–3.00)	0.10
9.5–13.0 g/day	102	32.0	1.42 (0.89–2.27)	0.14	1.44 (0.90–2.31)	0.13	1.37 (0.79–2.37)	0.26	1.32 (0.76–2.30)	0.32
13.0–17.3 g/day	99	31.1	1.39 (0.87–2.22)	0.17	1.39 (0.84–2.29)	0.18	1.23 (0.67–2.26)	0.51	1.20 (0.65–2.20)	0.56
17.3–20.1 g/day	42	39.5	1.76 (1.04–2.96)	0.03	1.81 (1.04–3.16)	0.04	1.50 (0.75–2.98)	0.25	1.41 (0.71–2.82)	0.33
>20.1 g/day	55	32.7	1.45 (0.85–2.49)	0.18	1.44 (0.78–2.63)	0.23	1.60 (0.75–3.39)	0.22	1.56 (0.73–3.33)	0.24
ptrend			0.43		0.45		0.53			0.55
Child/18 months of life
Continuous, per 10-g/day increase	262	35.9	1.44 (1.05–1.98)	0.03	1.44 (1.05–1.98)	0.02	1.46 (1.06–2.01)	0.02	1.41 (1.01–1.96)	0.04
By category
<4.8 g/day	19	26.3	Ref.		Ref.		Ref.		Ref.
4.8–5.8 g/day	25	34.3	1.32 (0.72–2.44)	0.37	1.32 (0.72–2.43)	0.37	1.30 (0.71–2.40)	0.39	1.37 (0.73–2.56)	0.32
5.8–8.2 g/day	77	34.9	1.35 (0.81–2.26)	0.25	1.34 (0.80–2.25)	0.26	1.33 (0.80–2.23)	0.27	1.40 (0.82–2.37)	0.22
8.2–11.4 g/day	76	34.7	1.25 (0.74–2.10)	0.40	1.24 (0.74–2.10)	0.41	1.24 (0.74–2.09)	0.42	1.24 (0.73–2.11)	0.43
11.4–13.5 g/day	30	41.2	1.61 (0.89–2.90)	0.11	1.60 (0.89–2.89)	0.12	1.61 (0.89–2.91)	0.11	1.58 (0.87–2.89)	0.14
>13.5 g/day	35	48.2	1.84 (1.04–3.27)	0.04	1.85 (1.04–3.28)	0.04	1.86 (1.05–3.30)	0.03	1.86 (1.04–3.34)	0.04
ptrend			0.05		0.05		0.04			0.07

*Model 1 (as in Antvorskov and colleagues [14]): adjusted for maternal age, prepregnant maternal BMI, parity, smoking during pregnancy, education, cesarean section, breastfeeding, sex, and energy intake.

†Model 2 (primary model): as model 1 with additional adjustment for birth weight, age at gluten introduction, prematurity, fibre intake, weight gain 0–12 months, and child’s or mother’s gluten intake (mutually adjusted exposures).

‡Model 3: as model 2 with additional adjustment for child coeliac disease.

Abbreviations: BMI, body mass index; CI, confidence interval; HR, hazard ratio; Ref., Reference category

Gluten intake by the child at age 18 months and subsequent risk of type 1 diabetes

The child’s intake of gluten was significantly associated with higher risk of type 1 diabetes with a dose-response relationship (Table 2). For each 10-g/day increase of gluten intake, the aHR was 1.46 (95% CI 1.06–2.01, p = 0.02). For each standard deviation (3.6 g/day) increase of gluten intake, the aHR was 1.15 (95% CI 1.02–1.29, p = 0.02).

While the child’s gluten intake remained significantly associated with risk of type 1 diabetes after adjustment for maternal gluten intake during pregnancy, the suggestive association with maternal gluten intake in category 2 and 5 were blunted after adjustment for child’s gluten intake (Table 2).

Additional analyses

Analyses of those with complete covariate data showed similar results as in the main analyses (S3 Table). The overall pattern across subgroups for birth weight and child’s sex was consistent with the main findings (S5 Fig). We found no association between maternal dietary fibre intake or gluten intake from refined grains during pregnancy and risk of type 1 diabetes in the child (S4 Table and S5 Table). In analyses with further adjustment for child coeliac disease, our results were essentially unchanged (Table 2). However, since the HR for child’s gluten intake was slightly attenuated, we performed another sensitivity analysis after excluding children who were diagnosed with coeliac disease during follow-up. The HR remained similar (aHR = 1.37, 95% CI 0.98–1.93, p = 0.07 per 10-g increase for childhood intake), adjusted as in model 2, but it was no longer significant due to the reduction of type 1 diabetes cases. Including children who have a mother with type 1 diabetes or celiac disease in the primary model gave essentially unchanged results (S6 Table). Finally, we additionally adjusted for other types of diabetes in the mother (type 2 diabetes or gestational diabetes obtained from the medical birth registry of Norway) in the primary model, and the results were essentially unchanged (HR 1.48, 95% CI 1.09–1.99, p = 0.01, per 10-g/day increase in the child’s gluten intake, and HR 0.98, 95% CI 0.71–1.36, p = 0.91, per 10-g/day increase in the maternal gluten intake).

Discussion

In this study, with both maternal and child gluten intake as exposures, we found that the child’s gluten intake at 18 months of age was associated with the risk of type 1 diabetes while maternal gluten intake during pregnancy was not.

Comparison with previous studies

Our results on the mother’s intake of gluten during pregnancy are not in line with those from the only previous study to assess this [14], despite remarkable similarities in characteristics, maternal gluten intake, and methodology. A possible explanation for the discrepancy could be that we were able to exclude participants based on maternal coeliac disease, while the other study neither excluded nor adjusted for this in their analyses. Two studies of high-risk children that investigated maternal intake of gluten-containing foods in pregnancy and development of islet autoimmunity reported no significant association [12, 13]. Of note, both the exposure (intake of gluten-containing cereals rather than amount of gluten) and outcome was different from our study, and the number of children with outcome was small in these high-risk cohorts. A recent study of high-risk children found that an increased gluten intake in childhood was associated with islet autoimmunity but not with type 1 diabetes [28], while another study of high-risk children found no significant association between the child’s gluten intake and islet autoimmunity or progression from islet autoimmunity to type 1 diabetes [29]. Again, the apparent inconsistency may have been due to studies investigating different outcomes (clinical type 1 diabetes versus progression) in different populations or due to lack of power. Our results are probably generalizable to other industrialised countries but may not be applicable to populations of non-European origin. In a recently published study from The Environmental Determinants of Diabetes in the Young (TEDDY), a higher gluten intake during the first 5 years of life was associated with increased risk of coeliac disease autoimmunity and coeliac disease among genetically predisposed children [30]. In another cohort of at-risk children, gluten intake between the ages of 1 and 2 years—and, to a lesser extent, the cumulative intake throughout childhood—were associated with the appearance of coeliac disease autoimmunity and coeliac disease [31]. We have previously reported that an increased gluten intake at 18 months was associated with a modestly increased risk of coeliac disease in children from MoBa [32].

Strengths and weaknesses

The prospective design with recruitment in pregnancy, large sample size, and linkage to national registries with high levels of ascertainment are the strongest advantages of the study. Missing data on child’s gluten intake at 18 months of age was mainly due to loss of follow-up, which occurs in all cohorts that are based on voluntary participation. Having no significant difference in risk of type 1 diabetes in those without complete data suggests that missing-data bias was not a serious weakness. Furthermore, multiple imputation analyses have further contributed to minimising any influence of bias due to missing data [27].

The recently published Danish national prospective cohort study has been criticised for not including other dietary components related to gluten intake [33]. We included data on maternal dietary fibre intake and gluten intake from refined grains during pregnancy. We also adjusted for age at gluten introduction and infant weight gain [34]. We are not able to explore all aspects of food intake; however, no dietary factors are established as a risk factor for type 1 diabetes [35]. We accounted for coeliac disease, both by excluding children of mothers with coeliac disease from the analyses and adjusting for child coeliac disease.

Observational studies cannot exclude the possibility of unmeasured, unknown confounders that could have influenced the results. Yet no environmental aetiological factors are clear, plausible confounders.

We assessed gluten intake prospectively, but imprecisions in the estimations are likely, and we only had information regarding gluten intake for the mother in the first half of pregnancy and for the child at 18 months of age and no other time points in early life. We used questionnaires, which are suitable for estimating regular diet consumed over time but are not as precise as other dietary assessment methods such as a dietary recall or records covering shorter time periods—which, again, do not detect foods consumed outside the time of data registration. The estimated intake of gluten was comparable to what has been reported in studies using the same or other dietary assessment methods, both for adults [14] and children [36-39]. It is unlikely that imprecisions in gluten intake assessment from questionnaires is influenced by future type 1 diabetes. Any bias is nondifferential when we have accounted for coeliac disease in the child and in the mother. The large majority of type 1 diabetes cases were diagnosed long after 18 months, with the potential for reverse causation likely small. We did not have prediagnostic data on islet autoantibodies and are therefore not able to provide information on whether the associations with gluten intake are related to risk of islet autoimmunity or progression from islet autoimmunity to type 1 diabetes. Another limitation is the lack of genetic susceptibility variants. However, while these genetic variants obviously predict type 1 diabetes in the child, it is not obvious that they will confound the associations between maternal or child’s gluten intake and type 1 diabetes by influencing also gluten intake, independently of coeliac disease. We did not have detailed information on different ethnicities, but MoBa primarily consists of ethnic Norwegians.

Self-selection in recruitment and losses to follow-up could lead to a nonrepresentative sample in the analyses. Those consenting to participate, and those continuing to participate in MoBa, differ from the average population of women giving birth in Norway, in that the participants have high maternal age and education and there is a low proportion of daily smokers among them [40]. Selection has been shown to play a minor role in association studies in MoBa [40]. Adjusting for maternal education, age, and smoking during pregnancy did not change our results substantially, suggesting that selection bias is unlikely to have had a major influence on our findings.

Implications for research, clinical practice, and public policy

Our results show that, while the mother’s intake of gluten in pregnancy was not associated with type 1 diabetes, a higher intake of gluten by the child at an early age may give a higher risk. The results from a similar Danish national prospective cohort study [14] was not replicated in our cohort, suggesting that there may not be causality. This may also be the case for our finding of childhood intake of gluten as a possible risk factor for type 1 diabetes later in life, which needs to be replicated in other large cohorts or intervention studies.

The child’s gluten intake at 18 months of age may possibly increase the risk of type 1 diabetes through several mechanisms related to the immune system [3]. It has been shown that increased gut permeability, which facilitates abnormal absorption of macromolecules, is associated with type 1 diabetes and is detectable before clinical onset [41]. In a recently published study from TEDDY, small changes in abundance of bacterial genera were found in cases with type 1 diabetes compared to controls, such that controls had a higher abundance of bacterial genera that might be indicative of enhanced gut integrity [42]. The child’s diet in early life is more important for microbiota development in the child than maternal diet during pregnancy, and our assessment of childhood intake of gluten was during the transitional phase of the developing microbiome, before the stable phase that is observed after 30 months of age [42]. The median age at seroconversion to islet autoimmunity preceding type 1 diabetes is around 24 months of age [43].

If replicated in prospective studies, these findings may motivate further interventional studies of gluten amount in childhood and type 1 diabetes. The results from our study should not lead to changing of recommendations or lead to unnecessary dietary changes among individuals to avoid type 1 diabetes. Ours and other published data to date should be interpreted cautiously, as there are currently few prospective studies in this field, with conflicting results, and no randomised intervention studies.

Conclusion

In conclusion, a higher intake of gluten in the child’s diet at 18 months, but not in maternal diet during pregnancy, was associated with an increased risk of type 1 diabetes in the child.

(DOC)

Click here for additional data file.

Characteristics of the study participants included in the analysis of the child’s gluten intake at age 18 months and risk of type 1 diabetes.

(DOCX)

Click here for additional data file.

Characteristics of excluded participants due to missing exposure data.

(DOCX)

Click here for additional data file.

Association between maternal gluten intake during pregnancy (n = 54,332) or child’s intake at 18 months (n = 56,257) and the risk of type 1 diabetes in the child.

Complete case analyses*.

(DOCX)

Click here for additional data file.

Association between maternal intake of fibre during pregnancy and the risk of type 1 diabetes in the child.

(DOCX)

Click here for additional data file.

Association between maternal intake of gluten from refined grains during pregnancy and the risk of type 1 diabetes in the child*.

(DOCX)

Click here for additional data file.

Analyses of model 2 (primary model) including children who have a mother with type 1 diabetes or coeliac disease (n = 1,033)*.

(DOCX)

Click here for additional data file.

Excerpts of questionnaires at week 22 of pregnancy and child’s age 18 months.

(DOCX)

Click here for additional data file.

Cumulative incidence of type 1 diabetes in participants included in the analyses and in those excluded due to missing gluten data.

(DOCX)

Click here for additional data file.

Distribution of maternal gluten intake during pregnancy and child’s gluten intake at age 18 months.

(DOCX)

Click here for additional data file.

Correlation between maternal gluten intake during pregnancy and child’s gluten intake at age 18 months.

(DOCX)

Click here for additional data file.

Association between maternal gluten intake during pregnancy and child’s gluten intake at age 18 months and risk of type 1 diabetes, stratified by child’s sex and birth weight.

(DOCX)

Click here for additional data file.

Analysis plan.

(DOCX)

Click here for additional data file.

31 Oct 2019

Dear Dr. Lund-Blix,

Thank you very much for submitting your manuscript "Maternal and child gluten intake and risk of type 1 diabetes: The Norwegian Mother and Child Cohort Study" (PMEDICINE-D-19-03046) for consideration at PLOS Medicine.

Your paper was evaluated by a senior editor and discussed among all the editors here. It was also discussed with an academic editor with relevant expertise, and sent to independent reviewers, including a statistical reviewer. The reviews are appended at the bottom of this email and any accompanying reviewer attachments can be seen via the link below:

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In light of these reviews, I am afraid that we will not be able to accept the manuscript for publication in the journal in its current form, but we would like to consider a revised version that addresses the reviewers' and editors' comments. Obviously we cannot make any decision about publication until we have seen the revised manuscript and your response, and we plan to seek re-review by one or more of the reviewers.

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Requests from the editors:

Abstract – please use both 95%Cis and p values for all quantifiable data (also throughout main text and tables, as needed)

Please add a sentence on the study’s limitations as the final sentence of the ‘Methods and Findings’ section of the abstract.

As this is an observational study and not a trial, please avoid overheated language, such as “could increase” (conclusions in abstract)…”may” would be better (again, line 296)

At this stage, we ask that you include a short, non-technical Author Summary of your research to make findings accessible to a wide audience that includes both scientists and non-scientists. The Author Summary should immediately follow the Abstract in your revised manuscript. This text is subject to editorial change and should be distinct from the scientific abstract. Please see our author guidelines for more information: https://journals.plos.org/plosmedicine/s/revising-your-manuscript#loc-author-summary

(please remove the 2 sections what we know / what this study adds)

Please use square brackets in the main text for references and site the refs before the full stop, instead of after.

Line 235 – “to the best of our knowledge”

Line 344 – please remove the section on copyright (this will be an open access publication). Please also remove funding and competing interests statements etc as these are automatically pulled in from the submission system.

Strobe – please use sections and paragraph numbers instead of pages as these can alter during revisions / formatting, etc.

I just wanted to check that all questionnaire material is provided – I see one URL, but there are a couple of mentions of questionnaires. Any additional ones can be provided as Supp files. Apols if they are all provided already.

Comments from the reviewers:

Reviewer #1: Thank you for the opportunity to review this paper. The authors report findings on a large Norwegian birth cohort on the association between maternal pregnancy gluten intake up to 22 weeks and childhood gluten intake at 18 months and Type 1 diabetes in two separate mutually adjusted Cox regression models. They found that increasing gluten intake in children at 18 months was associated future increased risk of Type 1 diabetes in children but no association between maternal pregnancy gluten intake and risk of Type 1 diabetes in children. This study is well-presented and provides some convincing observational evidence that childhood gluten may have some role to play in increasing risk of type 1 diabetes.

The adjusted Cox regression models are appropriate for the analyses. The authors have adjusted for confounders/covariates, considered the impact of missing values (completing a complete-case analysis for comparison to the imputed), and excluded patients who may have key confounding factors which may alter the exposure patterns (i.e. mothers with Type 1 diabetes or monogenic diabetes). They have used a cluster variance method to also account for correlation between siblings. I only have a few comments that could be considered.

1) Just a matter of presentation: I would suggest the exposures paragraph (starting lines 116) are presented before the outcome section in the methods as authors mention the exposures comparisons in the outcome section prior to the exposure being described (for instance, lines 111-112 about exclusion due to missing exposure information).

2) Other variables (Lines 142): Prior history of type 2 diabetes of mothers factored considered and gestational diabetes - as both of these would potentially affect dietary factors, including gluten intake. If possible and information is available, please adjust for both these factors in the regression models (though I would think you could obtain the medical codes from the Norwegian Patient Register). If not, then the discussion limitations need to reflect this.

3) Statistical analysis (lines 157): There are two primary models presented (1) looking at maternal gluten intake (2) looking at childhood gluten intake. The authors have mutually adjusted each of the gluten intake in both of these models as covariates. Whilst the childhood model makes sense to conduct a baseline adjustment for the maternal gluten intake (as the maternal gluten intake occurs PRIOR to the childhood intake), the maternal model using a baseline adjustment for the childhood gluten intake (which occurs AFTER the exposure period), may not entirely be appropriate. It would be better to incorporate the effects of the childhood intake as a time-dependent covariate in the model instead if you want to stick with a time 0 = birth model.

The issue with the baseline adjustment of covariates is the effect on survival time. In your maternal model, starting point of follow-up occurs at time 0 = birth. That means that anything occurring afterwards such as childhood gluten could be directly caused/associated with your exposure maternal gluten intake. In fact, I would imagine these two factors in linked due to dietary similarities within families. Another possibility, instead of a time-varying covariate, is to simply start your maternal model follow-up time concordant to the child's follow-up period from 18 months. Hence, your mutual adjustment here would then discount the period of time where temporality was violated for baseline covariate adjustment. At the least, this analysis should be presented as a sensitivity analyses to stress test the results.

4) Related to point 3) it would then be useful to quantify the relationship between maternal gluten intake and childhood gluten intake - if there is any association between these factors - as family dietary patterns should be inevitably correlated which would again suggest the two exposures are linked.

5) Lines 163 - The authors adjusted for potential correlation between siblings in this cohort - which is good practice but is possible to identify within this cohort siblings? If this is possible, this presents a very unique opportunity to conduct a stratified analyses, comparing low and high gluten intake between siblings to account for the influence of genetics. Potential consideration for the discussion or future analyses.

6) Any potential sub-group differences between child's gender and birthweight would be useful to see (perhaps in a KM survival plot)

Reviewer #2: The manuscript presents findings on type 1 diabetes outcome in children in relation to gluten intake by mothers during pregnancy and by children at age 18 months. The findings are from the Norwegian Mother and Child Cohort study (MoBa). Previous findings from a Danish study indicated that increased gluten intake during pregnancy was associated with increased risk in the offspring. The Moba study was unable to confirm the Danish findings. The authors show that gluten intake in mid-pregnancy was not associated with the development of type 1 diabetes in the child (adjusted HR, 1.02; 95%CI, 0.73-1.43). They also find that the child's gluten intake at age 18 months was associated with the development of type 1 diabetes (HR, 1.46 per 10 g/day increase).

The study is important. It is generally sound and well performed. The question whether gluten intake influences type 1 diabetes risk remains unclear.

Comments to address:

1. An aspect of the analysis that requires some justification is the use of 10 g/day increase for the HRs. This is particularly so for the children where the average intake was 8.8 g/day (SD, 3.6) and the median 8.2 g/day. A 10 g/day increase is nearly 3 SD. What is the rationale for relating the data to such a large increase other than consistency with the Danish study (where it is also a concern)? One can see from table 2 that the increased risk is only seen at the upper centiles of gluten intake at 18 months. The authors should report the HRs in relation to a smaller increment, at least in the children intake analysis.

2. A distribution of the gluten intake in pregnancy and at age 18 months should be shown.

3. The data in Sup Table 6 shows information from Table 2 plus model 3 that includes adjustment for celiac disease in the child. Model 3 is an important one, especially given the recent publication by the TEDDY study that reports increased transglutaminase autoantibody risk in relation to gluten intake and the known association between type 1 diabetes and celiac disease. The authors should, therefore, add model 3 to table 2 and remove sup table 6.

4. The authors should discuss the findings of the above-mentioned TEDDY study (transglutaminase autoantibody risk and gluten intake; JAMA 2019).

5. There is a slight attenuation of risk associated with child gluten intake in model 3. A sensitivity analysis with and without the cases of celiac disease should be performed.

6. Children who have a mother with type 1 diabetes or celiac disease were excluded. These are likely to include a relevant number of cases of type 1 diabetes. The authors should add as supplementary information an analysis in which these children are included.

7. It would be of interest to show the findings in relation to celiac disease. One appreciates that this may be the subject of a separate manuscript, but it is likely to be relevant to the current analysis and the authors should seriously consider this.

8. Many of the cases of type 1 diabetes in the current study will have developed islet autoantibodies prior to age 18 months. The authors should discuss this aspect since their findings do not provide knowledge as to whether the association is related to risk of islet autoimmunity or development/progression to diabetes.

9. A statement on the power of the study in the pregnancy dataset and in the children dataset should be given.

10. Some statistics (eg p values) should be given in the text in the second paragraph of the results when stating lower than.

11. Although the food questionnaire is validated, it has its limitations and it is unlikely to be as robust as a 3-day record. Some comment on its limitation should be included.

Reviewer: Ezio Bonifacio

Reviewer #3: This interesting manuscript evaluates the relationship between gluten intake during pregnancy or early childhood and risk of developing TIDM during the first 10-20 years of life. The authors find a relationship between reported gluten intake at age 18 months and risk of subsequent TIDM development. Strengths of the study include the nationally representative sample, good sample size, robust identification of exposures and outcomes and limited missing data. Limitations include the lack of genetic information (given that genetic risk factors for TIDM are recognised), the lack of information on other dietary intake and whether or not this is also associated with TIDM risk, the lack of information on other autoimmune outcomes or TIDM-associated antibody levels to establish whether these are associated with gluten intake, and the lack of information on gluten intake at other timepoints during early childhood. It is hard to understand whether this association is specific to gluten when oat intake was not explored, or other foods which don't contain gluten.

Any attachments provided with reviews can be seen via the following link:

[LINK]

19 Dec 2019

Dear Dr. Lund-Blix,

Thank you very much for re-submitting your manuscript "Maternal and child gluten intake and risk of type 1 diabetes: The Norwegian Mother and Child Cohort Study" (PMEDICINE-D-19-03046R1) for review by PLOS Medicine.

I have discussed the paper with my colleagues and the academic editor and it was also seen again by xxx reviewers. I am pleased to say that provided the remaining editorial and production issues are dealt with we are planning to accept the paper for publication in the journal.

The remaining issues that need to be addressed are listed at the end of this email. Any accompanying reviewer attachments can be seen via the link below. Please take these into account before resubmitting your manuscript:

[LINK]

Our publications team (plosmedicine@plos.org) will be in touch shortly about the production requirements for your paper, and the link and deadline for resubmission. DO NOT RESUBMIT BEFORE YOU'VE RECEIVED THE PRODUCTION REQUIREMENTS.

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We ask every co-author listed on the manuscript to fill in a contributing author statement. If any of the co-authors have not filled in the statement, we will remind them to do so when the paper is revised. If all statements are not completed in a timely fashion this could hold up the re-review process. Should there be a problem getting one of your co-authors to fill in a statement we will be in contact. YOU MUST NOT ADD OR REMOVE AUTHORS UNLESS YOU HAVE ALERTED THE EDITOR HANDLING THE MANUSCRIPT TO THE CHANGE AND THEY SPECIFICALLY HAVE AGREED TO IT.

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If you have any questions in the meantime, please contact me or the journal staff on plosmedicine@plos.org.

We look forward to receiving the revised manuscript by 23 December 2019.

Sincerely,

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Senior Editor

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Requests from Editors:

Title – please remove ‘risk’ in favour of 'association' as this is an observational study

Data – the link provided appears to be a broken page https://www.fhi.no/en/op/dataaccess-from-health-registries-health-studies-and-biobanks/data-from-moba/mobaresearch-data-files/

Author summary – Please remove CIs as this is supposed to be a lay summary?

Please add a space between text and reference brackets throughout

Abstract-please clarify what is meant by mid-pregnancy?

Author summary- please change “may increase risk…” to “associated with increased risk..” as this is an observational study

Discussion- please avoid assertions of primacy

Please present and organize the Discussion as follows: a short, clear summary of the article's findings; what the study adds to existing research and where and why the results may differ from previous research; strengths and limitations of the study; implications and next steps for research, clinical practice, and/or public policy; one-paragraph conclusion.

Please clarify why the KM plots requested by reviewers have not been included in the main manuscript or the supplementary information. Please include this as SI files and provide a reference within the manuscript

Did your study have a prospective protocol or analysis plan? Please state this (either way) early in the Methods section.

a) If a prospective analysis plan (from your funding proposal, IRB or other ethics committee submission, study protocol, or other planning document written before analyzing the data) was used in designing the study, please include the relevant prospectively written document with your revised manuscript as a Supporting Information file to be published alongside your study, and cite it in the Methods section. A legend for this file should be included at the end of your manuscript.

b) If no such document exists, please make sure that the Methods section transparently describes when analyses were planned, and when/why any data-driven changes to analyses took place.

c) In either case, changes in the analysis-- including those made in response to peer review comments-- should be identified as such in the Methods section of the paper, with rationale.

Comments from Reviewers:

Reviewer #1: The authors did an excellent job revising and amending their manuscript. They have thoroughly addressed my queries and provided additional analyses. With the additional analyses, their primary findings stand, hence this paper can be recommended for publication. As with all observational studies, there are limitations but the authors have done their best to control for these factors.

The only final point two points I would suggest are in the discussion:

1) Limitations - no description of ethnicity but assume this is predominantly White Caucasian as gluten, both exposures with dietary influences and rates of T2DM can vary by ethnic group

2) Conclusions - authors suggest (Lines 388 onwards) that future interventional studies may be warranted to explore this in children but I think this may be difficult to actually test in practice - given that the long duration of follow-up, the ethics around restricting gluten in otherwise healthy children. I would think that more causal observational designs would be more likely and practical (i.e. Mendelian randomisation) with identifying genetics risk markers that are instrumental variables for gluten metabolism and then testing the relationship between the instrument which is not confounded by environmental influences on the outcome of T2DM.

Reviewer #2: Thank you. No further comments.

Any attachments provided with reviews can be seen via the following link:

[LINK]

27 Jan 2020

Dear Dr. Lund-Blix,

On behalf of my colleagues and the academic editor, Dr. Ronald Ma, I am delighted to inform you that your manuscript entitled "Maternal and child gluten intake and association with type 1 diabetes: The Norwegian Mother and Child Cohort Study" (PMEDICINE-D-19-03046R2) has been accepted for publication in PLOS Medicine.

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PLOS Medicine

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