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. 2026 Jul 28;27:624. doi: 10.1186/s13063-026-09468-y

A randomized controlled double-blinded trial to assess the risk of gestational diabetes mellitus in non-anemic pregnant women who receive oral iron supplementation

Joe Varghese 1,✉, Molly Jacob 1, Padmanaban Venkatesan 1, Manisha Madhai Beck 2, Swati Rathore 2, Monica Peter 1, Anuja Abraham 2, Kavitha Abraham 2, Aaron Chapla 3, Prasanna Samuel 4
PMCID: PMC13693179  PMID: 42919408

Abstract

Background

Pregnant women in India are routinely prescribed oral iron supplements as part of the national Anemia Mukt Bharat (AMB) program for anemia control. In women with iron-deficiency anemia, the benefits of iron supplementation during pregnancy, both for the mother and child, are very clear. In non-anemic pregnant women, however, the benefits of iron supplementation vis-à-vis associated risks that have been reported have not been studied adequately. Studies have suggested that iron may impair insulin secretion, thus increasing the risk of gestational diabetes mellitus (GDM).

Primary objective: To determine the incidence of GDM among non-anemic pregnant women receiving 60 mg/day of elemental iron as oral supplementation, compared with those receiving 30 mg/day.

Secondary objectives: To assess beta-cell functional capacity and quantify unmethylated insulin promoter DNA (a sensitive and specific marker of beta-cell damage) in blood samples from the two study groups.

Methods

This study is a randomized, parallel-group, double-blinded clinical trial, with 800 non-anemic primigravidae in each arm. One arm will receive oral supplementation at a dose of 60 mg per day (as per current national guidelines), while the other arm will receive 30 mg per day, for a duration of 12 weeks in the second trimester. The incidence of GDM in the two arms will be compared. Insulin secretion kinetics will be assessed using an oral glucose tolerance test (OGTT) done at the end of the intervention. Additionally, the unmethylated insulin promoter DNA in circulating free DNA (a marker of beta-cell damage) will be quantified in both arms.

Discussion

The study’s findings will provide important evidence relevant to the current national guidelines in India on universal oral iron supplementation during pregnancy. The results are expected to inform future policy decisions on whether universal supplementation for all pregnant women is appropriate or whether it should be targeted to those with low iron status.

Trial registration

CTRI/2024/04/065301 [registered on 05/04/2024]—trial registered prospectively.

Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1186/s13063-026-09468-y.

Keywords: Gestational diabetes mellitus, Iron deficiency, Iron-replete status, Insulin secretion, Non-transferrin-bound iron, Oral iron supplementation, Pregnancy

Administrative information

Note: the numbers in curly brackets in this protocol refer to SPIRIT checklist item numbers. The order of the items has been modified to group similar items (see http://www.equator-network.org/reporting-guidelines/spirit-2013-statement-defining-standard-protocol-items-for-clinical-trials/).

Title {1} A randomized controlled double-blinded trial to assess the risk of gestational diabetes mellitus in iron-replete pregnant women who receive oral iron supplementation
Trial registration {2a and 2b} CTRI/2024/04/065301 [registered on 05/04/2024]—trial registered prospectively
Protocol version {3} Version 1.0.0
Funding {4} The study is funded by the Indian Council of Medical Research (ICMR) under Investigator-Initiated Projects—Intermediate Grant with the ID: ICMR ref no. IIRPIG-2023-0000204
Author details {5a}

1. Joe Varghese, Department of Biochemistry, Christian Medical College, Vellore, Tamil Nadu, India

2. Molly Jacob, Department of Biochemistry, Christian Medical College, Vellore, Tamil Nadu, India

3. Padmanaban Venkatesan, Department of Biochemistry

4. Manisha Madhai Beck, Department of Obstetrics and Gynecology, Christian Medical College, Vellore, Tamil Nadu, India

5. Swati Rathore, Department of Obstetrics and Gynecology, Christian Medical College, Vellore, Tamil Nadu, India

6. Monica Peter, Department of Biochemistry, Christian Medical College, Vellore, Tamil Nadu, India

7. Anuja Abraham, Department of Obstetrics and Gynecology, Christian Medical College, Vellore, Tamil Nadu, India

8. Kavitha Abraham, Department of Obstetrics and Gynecology, Christian Medical College, Vellore, Tamil Nadu, India

9. Aaron Chapla, Department of Endocrinology, Diabetes and Metabolism, Christian Medical College, Vellore, Tamil Nadu, India

10. Prasanna Samuel, Department of Biostatistics, Christian Medical College, Vellore, Tamil Nadu, India

Name and contact information for the trial sponsor {5b}

This investigator-initiated study is funded by a grant award to Dr. Joe Varghese by the Indian Council of Medical Research (ICMR), V. Ramalingaswami Bhawan, P.O. Box No. 4911, Ansari Nagar, New Delhi, 110029, India

Ph: 91-11-26588895/91-11-26588980, 91-11-26589794/91-11-26589336, 91-11-26588707

Fax: 91-11-26588662

Email: icmrhqds@sansad.nic.in

Role of sponsor {5c} The ICMR, which is the funding agency for the study, has no role in study design, collection, management, analysis, and interpretation of data, and writing and submission of the report for publication. The funding agency will periodically monitor the progress and implementation of the study

Introduction

Background and rationale {6a}

Gestational diabetes mellitus (GDM) is defined as glucose intolerance that is first recognized during pregnancy [1]. It is a common complication during pregnancy, affecting approximately 1 in 6 births worldwide [2] and is associated with significant adverse health consequences for both the mother and the child [3]. The pathogenesis of GDM is not clearly understood, but has been linked to increased insulin resistance and functional impairment of beta cells in the pancreas [4].

There are several observational studies, systematic reviews, and meta-analyses that have shown an association between elevated serum ferritin levels (a marker of body iron stores) and GDM [5–11]. Several lines of evidence show that iron overload impairs beta-cell function and decreases insulin sensitivity in the body [12–15]. For example, patients with hereditary hemochromatosis (HH), a group of genetic conditions characterized by iron overload, are at increased risk of developing diabetes due to a decrease in beta cell function [16–18]. Similarly, beta cell failure and increased insulin resistance have been reported in patients with beta-thalassemia, another condition characterized by iron overload [19–22]. Overall, there is considerable evidence indicating a strong association between increased body iron stores and impaired pancreatic beta-cell function.

In several developing countries, including India, pregnant women receive universal iron supplementation, especially during the second and third trimesters, to meet increased requirements for the mother, the placenta, and the growing fetus [23]. Iron supplementation is clearly beneficial in decreasing the burden of iron-deficiency anemia during pregnancy [24]. However, it has also been reported to be associated with increased risk of GDM, oxidative stress, and pregnancy-induced hypertension, apart from gastrointestinal side effects [24–31]. The benefits of iron supplementation in non-anemic pregnant women, vis-à-vis the associated risks, are not clear [24].

Elevated body iron stores have been associated with both insulin resistance and impaired insulin secretion [32], both of which can contribute to the development of GDM. Ferrous sulfate and other highly bioavailable forms of iron that are used as oral supplements are rapidly absorbed into the blood, transiently giving rise to a highly redox-active form of iron, which is termed non-transferrin-bound iron (NTBI) [33, 34]. NTBI is taken up by pancreatic beta cells, potentially subjecting them to oxidative damage [35, 36]. It is in this context that the possible role of iron supplementation in inducing beta-cell damage becomes relevant in GDM.

Several studies have investigated the link between iron supplementation and GDM [extensively reviewed in [37, 38]]. While some support a positive association [8, 27, 29, 39–42], others do not [43–51]. Such variability in findings may be due to numerous heterogeneous factors operational in different studies. These include differences in the baseline iron status of participants, the types of iron formulation and doses used, and the duration of iron supplementation. These differences make it difficult to accurately interpret the results of these studies and to make comparisons between them. Evidence from well-designed randomized control trials (RCTs) is conspicuously lacking. Another glaring lacuna is a lack of data from India.

To summarize, the currently available evidence from published literature suggests that iron supplementation in non-anemic pregnant women may increase the risk of GDM; however, conclusive evidence is lacking.

Rationale for the current study

In pregnant women with iron-deficiency anemia, the benefits of iron supplementation far outweigh any associated risks. Since the prevalence of anemia is as high as 52.2% among pregnant women in India (as per NFHS-5 data), iron supplementation to all pregnant women (irrespective of iron status) is recommended as part of the Anemia Mukt Bharat (AMB) program. Currently, under the AMB program, 60 mg of elemental iron per day is given as an oral supplement to all pregnant women who are not anemic, from the start of the second trimester till delivery. Those who are anemic are recommended a dose of 120 mg of oral iron per day [52]. The Centers for Disease Control (USA) recommends 30 mg/day of elemental iron for primary prevention of iron deficiency during pregnancy [53], as this dose has been reported to be adequate to meet the requirements during pregnancy [54, 55]. The World Health Organization (WHO) recommends a dose of 30–60 mg/day, with the higher dose (60 mg) preferred for regions where the prevalence of anemia among pregnant women exceeds 40% [56]. Since the prevalence of anemia in pregnant women in India is high (52.2% according to NFHS-5 data), the AMB program’s recommendation of 60 mg/day aligns with the WHO recommendation.

As described in detail above, there are contradictory reports that associate oral iron supplementation with increased incidence of GDM. Given the lack of evidence from well-designed RCTs, the present study aims to determine whether oral iron supplementation, at the currently recommended dose of 60 mg/day, increases the risk of GDM compared to a lower dose of 30 mg/day, without increasing the risk of anemia.

Research question

Does oral iron supplementation at a dose of 60 mg of elemental iron per day in non-anemic pregnant women increase their risk of developing GDM, compared to those who receive 30 mg/day?

Objectives {7}

Hypothesis

Oral iron supplementation at currently recommended doses in pregnant women can potentially damage pancreatic beta cells and impair insulin secretion, putting them at increased risk of developing GDM.

Primary objective

To determine the incidence of GDM among non-anemic pregnant women receiving 60 mg/day of elemental iron as oral supplementation, compared with those receiving 30 mg/day.

Secondary objectives

To assess beta-cell functional capacity and quantify unmethylated insulin promoter DNA (a sensitive and specific marker of beta-cell damage) in blood samples from the two study groups.

Trial design {8}

Randomized, parallel-group, double-blinded, 1:1 allocation ratio, superiority clinical trial.

Methods: participants, interventions, and outcomes

Study setting {9}

This is a collaborative study between the Departments of Biochemistry and Obstetrics and Gynecology, at Christian Medical College (CMC), Vellore. The study will be conducted in the Department of Obstetrics and Gynecology, at Christian Medical College (CMC), Vellore, Tamil Nadu, India, which is a tertiary care perinatal center and teaching hospital.

Eligibility criteria {10}

Inclusion criteria

  • Primigravidae, age 18 to 35 years

  • Singleton pregnancy, as a result of natural conception

  • Gestational age: 12–16 weeks

  • Hemoglobin level ≥ 11 g/dL

  • Willing to come to CMC, Vellore, for regular antenatal check-up till OGTT is done (at 24–28 weeks of gestation)

Exclusion criteria

  • Previously diagnosed to have diabetes mellitus or found to have a fasting glucose ≥ 92 mg/dL at first antenatal visit

  • Any major medical illness requiring regular medication (e.g., thyroid disorders, autoimmune conditions), which may affect systemic iron homeostasis

  • High-risk pregnancy (as determined by the treating obstetrician) or those with complications of pregnancy

Who will take informed consent? {26a}

Written informed consent will be obtained from each participant before recruitment by research personnel in the study. They will be trained by the investigators on the study to perform this task.

Additional consent provisions for collection and use of participant data and biological specimens {26b}

From the women who will be recruited, a subset will undergo assessments to evaluate beta cell function and estimate the fraction of unmethylated insulin promoter DNA in cell-free circulating DNA in blood samples. This subset (100 from each arm) will be randomly selected from the recruited participants. Additional written informed consent will be obtained from this subgroup.

Interventions

Explanation for the choice of comparators {6b}

The comparator agent is iron and folic acid (IFA) tablet containing 60 mg elemental iron (as ferrous sulfate) and folic acid (500 µg) to be taken orally every day for 12 weeks starting between 12 and 16 weeks of gestation. This is the standard of care recommended by the Anemia Mukt Bharat program of the Government of India for pregnant women who are not anemic.

Intervention description {11a}

IFA tablet containing 30 mg elemental iron (as ferrous sulfate) and folic acid (500 µg), to be taken orally every day for 12 weeks, starting between 12 and 16 weeks of gestation.

Criteria for discontinuing or modifying allocated interventions {11b}

  • If hemoglobin is found to be ≤10.5 g/dL at 20–24 weeks of gestation

  • Withdrawal of consent by the subject at any time during the trial

  • Development or diagnosis of any complication of pregnancy that requires termination of pregnancy (e.g., congenital malformation or intrauterine death)

All subjects who withdraw from the study will receive antenatal care in accordance with hospital protocols.

Strategies to improve adherence to interventions {11c}

At the time of the first antenatal visit (12–16 weeks of gestation), each participant will receive the trial medication for 4 weeks and be provided with the investigator’s contact information. Each participant will receive daily reminders (via SMS text messages) and weekly phone calls to remind them to take their medication and to record any adverse events. Four weeks later, at antenatal visit 2 (16–20 weeks of gestation), a pill count will be performed on the previous batch of tablets. Following this, trial medication will be provided for the next 4 weeks. The same process will be repeated at antenatal visit 3 (20–24 weeks of gestation). A final assessment of adherence to the interventions and adverse effects will be conducted at antenatal visit 4 (24–28 weeks of gestation). Daily reminders to take the medication, as described above, will continue till the end of the study.

Relevant concomitant care permitted or prohibited during the trial {11d}

Routine antenatal care (as per standard of care) will be provided concomitantly. However, this will not include any oral iron supplements, which will be provided only as part of the trial medication.

Provisions for post-trial care {30}

Post-trial care and benefits are not applicable to this study. Following the completion of the intervention, which will last 12 weeks, all participants will continue to receive standard antenatal care in accordance with hospital protocols.

Outcomes {12}

Primary outcome: Incidence of GDM in the 2 groups at the end of intervention, as determined by results of the oral glucose tolerance test (OGTT).

The one-step 75-g OGTT will be done (as per standard procedure) for the diagnosis of GDM, using the criteria of the International Association of Diabetes and Pregnancy Study Groups (IADPSG) [57].

The proportion of participants who develop GDM in the 2 groups in the study will be compared using a two-sample proportion test. The primary analysis will be performed using the intent-to-treat approach, which will include all study participants randomized into one of the two arms, irrespective of the extent of adherence to the interventions. Missing outcome data will be imputed using multiple imputations if more than 5% of participants are lost to follow-up or have missing data in the outcome variable. Unadjusted relative risks and risk differences for GDM will be calculated with 95% confidence intervals. In addition, a per-protocol analysis will be conducted as a sensitivity analysis, including only participants who complied adequately with the intervention (>75% of supplement intake) and for whom outcomes are available.

Secondary outcomes:

  1. Incidence of anemia (Hb ≤ 10.5 g/dL) in the 2 groups at the end of the interventions, at 24–28 weeks of gestation

  2. Changes in hematological parameters (hemoglobin, MCV, MCH, and MCHC) and iron-related parameters (serum iron, ferritin, transferrin saturation, non-transferrin bound iron [NTBI], and soluble transferrin receptor [sTfR]) at the end of the interventions, compared to baseline

Data on continuous variables for secondary outcomes (serum iron, ferritin, transferrin saturation, NTBI, etc.) in the 2 groups will be compared using the independent two-sample t-tests for normally distributed variables and the Mann-Whitney test for variables with a skewed distribution.

Mean (or median) differences between the two arms, along with 95% confidence intervals, will be calculated. For categorical variables related to secondary outcomes (incidence of anemia in the two arms), percentage differences will be tested using the two-sample proportion test. Regression analysis will be performed to explore relationships between the iron doses used (exposure) and primary and secondary outcomes.

Participant timeline {13}

Illustrated in Fig. 1.

Fig. 1.

Fig. 1

Study timeline. *Iron-related and other parameters: serum iron, ferritin, transferrin saturation, total iron-binding capacity (TIBC), soluble transferrin receptor (sTfR), NTBI, and inflammatory marker hsCRP. &Baseline anthropometric measurements: height, weight, mid-arm circumference, and body mass index (BMI). $Follow-up assessment: assessment of the extent of adherence to the interventions (by pill counting) and documentation of adverse effects

Sample size {14}

Sample size for primary objective

Published data from Tamil Nadu shows an overall prevalence of GDM of 15.7% [53]. After consulting with clinical collaborators and epidemiologists, an effect size of 5% was deemed clinically meaningful. Based on this, the expected incidence of GDM in the standard-of-care group (60 mg/day of oral elemental iron) was taken to be 15.7% and the expected incidence in the other group (30 mg/day) would be 10.7%. Keeping alpha error at 5%, with 80% power (two-side test), we calculated a sample size of 718 subjects in each arm.

Since we plan to have 2 interim analyses (with alpha and beta errors at 5% and 20% respectively), based on the O’Brien and Fleming method, the sample size is increased by a factor of 1.017. This gives 730 subjects per arm. Allowing for 9–10% dropout, we plan to recruit 800 subjects in each arm.

Sample size for secondary objectives

As per Miyakoshi et al. [58], the mean and standard deviation for the oral disposition index in pregnant women without GDM is 2.59 ± 0.96. To detect a difference of 0.4 units (representing ~15% improvement) at 0.05 alpha error and 80% power, using t-test to compare between two independent groups (two-tailed), the sample size required is 100 in each group.

Recruitment {15}

Primigravidae, aged 18 to 35 years, who attend the antenatal clinics of the Department of Obstetrics and Gynecology, at CMC, Vellore, will be the participants in the trial. Those who make their first antenatal visit between 12 and 16 weeks of gestation will be invited to participate. Based on the patient load in these antenatal clinics, it is expected that it will be feasible to recruit 1600 eligible participants over 3.5 years.

Assignment of interventions: allocation

Sequence generation {16a}

Method of randomization: Eligible participants who meet the inclusion and exclusion criteria for the trial will be randomly allocated to one of the two arms (1:1 ratio). Randomization sequences will be generated by an independent statistician using a computer-generated algorithm based on a randomly permuted block design, with variable sizes of four and six.

Concealment mechanism {16b}

Method of allocation concealment

The randomization sequence will be generated by the trial statistician and communicated only to an independent pharmacist who is not otherwise involved in participant recruitment, assessment, or outcome evaluation. The pharmacist will prepare the study medications according to the randomization sequence and label them with unique study identification numbers.

Implementation {16c}

Participants will be enrolled and assigned study identification numbers sequentially, and allocation will occur in the order of enrollment. Investigators, study staff, and participants will remain blinded to treatment allocation throughout the study.

Assignment of interventions: blinding

Who will be blinded {17a}

Both the participants and the investigators (research personnel who will be responsible for patient recruitment, data entry, and data management, co-investigators, and PI) will be blinded to treatment allocation (double-blinded).

Procedure for unblinding if needed {17b}

Unblinding is not necessary. If any participant is found to be anemic during antenatal visits or develops any complications, they will discontinue participation in the study and receive antenatal care according to hospital protocols.

Data collection and management

Plans for assessment and collection of outcomes {18a}

Plans for assessment and collection of outcomes for the primary objective

The primary outcome measure (GDM or non-GDM) will be based on the results of the oral glucose tolerance test (OGTT), as interpreted by the criteria of the IADPSG.

Assessment of co-variates

Participants’ relevant clinical data will be collected using digital forms hosted on a local RedCap server. The form to be used is shown in the supplementary material.

Dietary iron intake will be assessed using a food frequency questionnaire and 24-h dietary recall [59, 60]. For this, the research personnel will be trained in the Department of Dietetics, CMC, Vellore. They will use a standardized food frequency questionnaire and a 24-h dietary recall form. These will be available as digital forms hosted on a local RedCap server. Dietary iron intake will be calculated using previously published nutrition data on Indian foods [61].

Anthropometry: The research personnel will measure the weight, height, and mid-arm circumference of each participant. Body weight will be measured using a calibrated electronic weighing scale, and height will be measured using a tape measure attached to a wall, with participants standing in the Frankfurt position. Mid-arm circumference (of preferably the right arm) will be measured using a non-stretchable measuring tape, at the midpoint between the acromion process of the scapula and the olecranon process of the elbow.

Biochemical parameters will be estimated in blood samples as described in Table 1. Serum/plasma samples will be stored at −70 °C until analyses.

Table 1.

Laboratory tests

Sample Method Laboratory
Complete blood count, including hemoglobin Whole blood—collected in an EDTA tube Automated analyzer (Sysmex XN 9000 automated hematology analyzer)

Department of Transfusion Medicine and Immunohematology, Christian Medical College, Vellore

Routine test offered by this diagnostic laboratory

Serum iron and unsaturated iron-binding capacity (UIBC) Serum sample from blood collected in clot activator tube Automated chemistry analyzer (Roche Diagnostics GmbH), using a colorimetric method

Department of Clinical Biochemistry, Christian Medical College, Vellore

Routine test offered by this diagnostic laboratory

Total iron-binding capacity (TIBC) Calculated from values for serum iron and UIBC
Transferrin saturation Calculated from values for serum iron and TIBC
Serum ferritin Serum sample from blood collected in clot activator tube Atellica IM 1600 automated immunoassay analyzer (Siemens Healthcare Diagnostics Inc.), using a chemiluminescence assay

Department of Clinical Biochemistry, Christian Medical College, Vellore

Routine test offered by this diagnostic laboratory

Soluble transferrin receptor (sTfR) Serum sample from blood collected in clot activator tube Atellica IM 1600 automated immunoassay analyzer (Siemens Healthcare Diagnostics Inc), using a chemiluminescence assay

Department of Clinical Biochemistry, Christian Medical College, Vellore

Routine test offered by this diagnostic laboratory

Non-transferrin-bound iron (NTBI) Serum sample from blood collected in clot activator tube

NTBI will be estimated using a modified version of a published method [62]

The NTBI fraction will be separated using 30-kDa filters, after reaction with a weak iron chelator (nitrilotriacetic acid). The separated NTBI will be estimated using inductively coupled plasma mass spectrometry

Departments of Biochemistry and Clinical Biochemistry, Christian Medical College, Vellore. The assay is standardized for accuracy and precision
hsCRP Serum sample from blood collected in clot activator tube Automated analyzer (BN Prospec Siemens analyzer (Siemens, GmbH, Marburg, Germany))

Department of Microbiology, Christian Medical College, Vellore

Routine test offered by this diagnostic laboratory

Glucose Plasma samples from blood collected in tubes containing sodium fluoride, at baseline (fasting) and 30, 60, 90, and 120 min after ingestion of 75 g of glucose Automated analyzer (Roche Cobas c702 autoanalyzer), using a colorimetric method

Department of Clinical Biochemistry, Christian Medical College, Vellore

Routine test offered by this diagnostic laboratory

C-peptide and insulin Serum from blood samples collected in clot activator tubes, at baseline (fasting) and 30, 60, 90, and 120 min of the OGTT Immulite 2000XPi automated immunoassay analyzer (Siemens Healthcare Diagnostics Inc), using a chemiluminescence assay

Department of Clinical Biochemistry, Christian Medical College, Vellore

Routine test offered by this diagnostic laboratory

Plans for assessment and collection of data on outcomes for secondary objective

  • Insulin secretion kinetics:

    This will be done using serum samples from 100 subjects from each arm of the trial, selected by simple random sampling, after all participants have completed the study. Insulin secretion kinetics will be determined by deconvolution of C-peptide levels in blood samples obtained at 0, 30, 60, and 120 min during the OGTT [63]. Glucose and insulin levels will also be estimated in each of these samples. Insulin and C-peptide will be measured as described in Table 1. The data will be used to estimate the oral disposition index, which is a widely used integrated index of beta cell function [64]. In addition, we will estimate insulin sensitivity (Matsuda index) [65] and insulin clearance rate [66], using standard methods.

  • Beta cell-derived unmethylated INS promoter DNA in circulating cell-free DNA (cfDNA):

    This will be estimated using a next-generation sequencing (NGS)-based assay, as described previously, with appropriate quality control measures [67]. Paired serum samples, obtained at baseline (before the intervention) and the fasting sample at the time of the OGTT, will be stored at −70 °C until analysis.

Plans to promote participant retention and complete follow-up {18b}

The participants will be contacted by daily SMS messages to take their medication and weekly phone calls to encourage them to adhere to the intervention protocol and record any adverse effects. The extent of adherence to the interventions and incidence of adverse effects will be assessed during antenatal visits by pill counting.

Data management {19}

All study-related data will be collected and stored using forms hosted on a local RedCap server of Christian Medical College, Vellore. The data collection forms will be built with quality checks and will have restricted access to edit data entered, as well as records of editing history.

Confidentiality {27}

Access to data on and data download from the RedCap server will be restricted to the principal investigator and a limited number of co-investigators. Access to the RedCap server is password-protected. The management of data collection forms, data quality control, and security will be ensured with the assistance of the Department of Biostatistics at Christian Medical College, Vellore. Participants’ data will be shared with others, if necessary, only after all identifying features have been removed.

Plans for collection, laboratory evaluation, and storage of biological specimens for genetic or molecular analysis in this trial/future use {33}

Samples will be collected to quantify beta cell-derived unmethylated INS DNA in circulating cell-free DNA (cfDNA) using an NGS-based protocol (as described above) after obtaining consent. Serum samples will be stored at −70 °C until the time of laboratory analysis.

Statistical methods

Statistical methods for primary and secondary outcomes {20a}

The characteristics of the participants at the time of recruitment (baseline) will be described using summary statistical methods. Categorical variables will be presented as frequencies (and percentages) and continuous variables will be presented as mean (SD) or median (IQR), as appropriate for the distribution of the data.

The primary analysis will compare the incidence of GDM among participants in the two arms of the trial (those who receive 30 mg/day or 60 mg/day) using the two-sample proportion test. Unadjusted relative risks and risk differences for GDM will be calculated, with 95% confidence intervals. Both intention-to-treat and per-protocol analyses will be carried out. The latter will be conducted as a sensitivity analysis, using data from participants who adhered to the intervention protocol, ingested more than 75% of the supplement, and for whom data on outcomes are available.

Analyses of continuous variables to determine differences in secondary outcomes (serum iron, ferritin, transferrin saturation, NTBI, etc.) in the 2 arms will be performed using the independent two-sample t-test for normally distributed data and the Mann-Whitney test for data with a skewed distribution. Differences in the means (or medians) and 95% CIs in the 2 arms will be calculated. For categorical variables to determine secondary outcomes (incidence of anemia in the 2 arms), differences in percentages will be compared using the two-sample proportion test. Regression analyses will be carried out to explore relationships between iron doses (exposure) and primary and secondary outcomes.

Analyses of continuous variables to determine differences in secondary outcomes (beta cell functional capacity and unmethylated INS DNA levels) in the 2 treatment arms will be done, using the independent two-sample t-test for normally distributed data and the Mann-Whitney test for data with a skewed distribution.

Differences in the means (or medians) and 95% CIs will be calculated. To determine secondary outcomes for categorical variables, differences in percentages between the two treatment arms will be compared using the two-sample proportion test. Regression analysis will be conducted to investigate the relationships between iron doses (exposure) and beta cell functional capacity, as well as unmethylated INS DNA levels in blood (outcomes).

Interim analyses {21b}

Two interim analyses will be performed during the trial. The first will be done when data is available for 530 participants (one-third of the sample size target). The second will be completed when data is available for 1060 participants (two-thirds of the target sample size). Using the O’Brien Fleming approach, we have set the following Z/P values at each interim analysis to decide on continuing or stopping the trial:

  • Interim analysis 1: Z = 3.438, P = 0.0006

  • Interim analysis 2: Z = 2.431, P = 0.0151

  • Final analysis: Z = 1.95, P = 0.047

Methods for additional analyses (e.g., subgroup analyses) {20b}

An exploratory subgroup analysis will be performed to determine the effect of the intervention on the development of GDM, by using BMI, measured prior to randomization (first antenatal visit at 12–16 weeks of gestation) and age.

Methods in analysis to handle protocol non-adherence and any statistical methods to handle missing data {20c}

The primary analysis will be performed using the intent-to-treat approach, by including all study participants who are randomized to one of the arms, irrespective of extent of extent of adherence to the interventions. Missing outcome data will be imputed using multiple imputations if more than 5% of participants are lost to follow-up or have data on the outcome variable missing.

Plans to give access to the full protocol, participant-level data, and statistical code {31c}

Public access to the full protocol is available via the Clinical Trial Registry of India (CTRI). Access to participant-level datasets, statistical code, etc. will be provided in accordance with the rules of the ICMR.

Oversight and monitoring

Composition of the coordinating center and trial steering committee {5d}

This is a single-site trial. It will be coordinated, and its day-to-day activities managed, by the principal investigator and the team of co-investigators, which includes a statistician. The investigators will meet periodically, at intervals of 3 months, to review the trial’s progress.

Composition of the data monitoring committee, its role and reporting structure {21a}

Christian Medical College, Vellore, has a Data Safety Monitoring Board (DSMB) composed of the Vice-Principal of Research, subject experts, and statisticians within the institution. It monitors all clinical trials conducted within the institution; this trial will be monitored in a similar manner. An independent subject expert is nominated as a neutral referee to the DSMB for this trial. Data from the trial, including any adverse events, will be submitted and presented to the DSMB at periodic intervals. The DSMB will review the trial’s progress and make appropriate recommendations.

Adverse event reporting and harms {22}

Information on adverse events will be collected during the weekly phone calls and monthly visits to the antenatal clinic during the intervention period. The participants will also be provided with the contact information of the investigators and encouraged to inform them of any adverse events they experience.

All information related to safety, adverse events, and other relevant matters will be reported to the DSMB. All severe adverse events (SAEs) will be reported to the research office of the institution within 24 h, using the institution’s established mechanisms.

Frequency and plans for auditing trial conduct {23}

The trial is subject to audit by the Research Office, Christian Medical College, Vellore, to which the investigators will submit details of the number of patients recruited on a monthly basis. The funding agency, the Indian Council of Medical Research, India, will audit the trial on an annual basis based on annual progress reports submitted by the investigators.

Plans for communicating important protocol amendments to relevant parties (e.g., trial participants, ethical committees) {25}

Protocol amendments, if any, that have been approved by all investigators will be submitted to the Institutional Review Board for scientific and ethical review. Upon approval, the amendment will be submitted to the clinical trial registry, and the funding agency will be informed. The participant information sheet (if applicable) will be updated to reflect the protocol amendments and reissued to participants.

Dissemination plans {31a}

The study results will be presented at national and international conferences and published in open-access research journals to disseminate the results to the scientific community and healthcare professionals. Efforts will be made to leverage social media and the lay press to disseminate the key findings of the study.

Discussion

Current evidence is inconclusive on the role of iron supplementation in the development of GDM and its effect on beta-cell function. In this study, we plan to answer the question of whether a lower dose (30 mg/day of elemental iron) of oral supplementation can reduce the risk of GDM compared to the dose (60 mg/day of elemental iron) currently recommended for all pregnant women in India, without increasing the risk of anemia, through a well-designed, randomized, adequately controlled, double-blinded trial. In addition to this, we hope to uncover potential mechanisms of iron-mediated adverse effects on beta cells through the study of insulin secretion kinetics and the detection of circulating unmethylated insulin promoter DNA, a marker of beta-cell damage.

Trial status

Protocol version: 1.0.0.

Registered at Clinical Trials Registry of India with the no. CTRI/2024/04/065301 [registered on 05/04/2024].

Date of start of recruitment: 07/08/2025.

Total number of participants recruited so far: 109 (as on 31 Dec 2025).

Total number of participants who completed the study so far: 17 (as on 31 Dec 2025).

Date of expected completion of recruitment: 31 July 2028.

Supplementary Information

Supplementary Material 1. (133.9KB, pdf)
Supplementary Material 2. (151.9KB, pdf)

Acknowledgements

None.

Authors’ contributions {31b}

JV is the principal investigator of the study and was involved in the conception of the study, development of the proposal and study design, and obtaining funding for the study. MJ was involved in conception of the study and development of the proposal and study design. PV contributed to the study design, plan for statistical analysis, and calculation of sample size. MMB and SR contributed to the study design and development of the study protocol, particularly with regard to the plan for patient recruitment and trial logistics. AA, KA, and MP contributed to the development of the study protocol. AC contributed to the study protocol related to one of the secondary objectives. PS contributed to the development of the statistical plan for analysis and sample size calculation.

Funding {4}

The study is funded by a grant awarded to Dr. Joe Varghese (principal investigator) by the Indian Council of Medical Research under the Intermediate Research Grant for Extramural Investigators scheme, with the number: ICMR Ref No. IIRPIG-2023-0000204. The funding agency had no role in study design. It will not have any role in the collection, analysis and interpretation of data, or in writing the manuscript.

Data availability {29}

The final data will be available to the PI and co-investigators of the study for analysis and interpretation. It will also be submitted to the funding agency, the Indian Council of Medical Research, as required.

Declarations

Ethics approval and consent to participate {24}

The trial is approved by the Institutional Review Board (IRB) of Christian Medical College with the number: IRB min no. 16034 dated 24.01.2024. Informed written consent will be obtained from all participants of the study.

Consent for publication {32}

Not applicable.

Competing interests {28}

The authors declare that they have no competing interests.

Footnotes

Iron (Fe) supplementation and Diabetes in Pregnancy (FeDiP).

Publisher's Note

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

References

  • 1.Buchanan TA, Xiang A, Kjos SL, Watanabe R. What is gestational diabetes? Diabetes Care. 2007;30(Suppl 2):S105-111. [DOI] [PubMed] [Google Scholar]
  • 2.International Diabetes Federation. Gestational diabetes. Available from: https://idf.org/about-diabetes/gestational-diabetes/. Cited 2023 Jul 11.
  • 3.McIntyre HD, Catalano P, Zhang C, Desoye G, Mathiesen ER, Damm P. Gestational diabetes mellitus. Nat Rev Dis Primer. 2019;5(1):47. [DOI] [PubMed] [Google Scholar]
  • 4.Plows JF, Stanley JL, Baker PN, Reynolds CM, Vickers MH. The pathophysiology of gestational diabetes mellitus. Int J Mol Sci. 2018;19(11):3342. [DOI] [PMC free article] [PubMed]
  • 5.Chen X, Scholl TO, Stein TP. Association of elevated serum ferritin levels and the risk of gestational diabetes mellitus in pregnant women: the Camden study. Diabetes Care. 2006;29(5):1077–82. [DOI] [PubMed] [Google Scholar]
  • 6.Cheng Y, Li T, He M, Liu J, Wu K, Liu S, et al. The association of elevated serum ferritin concentration in early pregnancy with gestational diabetes mellitus: a prospective observational study. Eur J Clin Nutr. 2020;74(5):741–8. [DOI] [PubMed] [Google Scholar]
  • 7.Durrani L, Ejaz S, Tavares LB, Mohyeldin M, Abureesh D, Boorenie M, et al. Correlation between high serum ferritin level and gestational diabetes: a systematic review. Cureus. 2021;13(10):e18990. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Zhang X, Wu M, Zhong C, Huang L, Zhang Y, Chen R, et al. Association between maternal plasma ferritin concentration, iron supplement use, and the risk of gestational diabetes: a prospective cohort study. Am J Clin Nutr. 2021;114(3):1100–6. [DOI] [PubMed] [Google Scholar]
  • 9.Afkhami-Ardekani M, Rashidi M. Iron status in women with and without gestational diabetes mellitus. J Diabetes Complications. 2009;23(3):194–8. [DOI] [PubMed] [Google Scholar]
  • 10.Lin Y, Wu C, An R, Liu H, Chen M, Tan H, et al. The association of iron status, supplement iron in the first-trimester pregnancy with gestational diabetes mellitus: a nested case-control study. J Obstet Gynaecol Res. 2023;49(2):597–605. [DOI] [PubMed] [Google Scholar]
  • 11.Zhang C, Rawal S. Dietary iron intake, iron status, and gestational diabetes. Am J Clin Nutr. 2017;106(Suppl 6):1672S-1680S. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Backe MB, Moen IW, Ellervik C, Hansen JB, Mandrup-Poulsen T. Iron regulation of pancreatic beta-cell functions and oxidative stress. Annu Rev Nutr. 2016;17(36):241–73. [DOI] [PubMed] [Google Scholar]
  • 13.Blesia V, Patel V, Al‐Obaidi H, Zariwala M. Excessive iron accumulation induces beta cell cellular oxidative stress and insulin secretory dysfunction in MIN6 cells. In: Diabetic medicine. Liverpool: Wiley; 2019. p. 26–46. Available from: 10.1111/dme.2_13883. Cited 2020 Jul 31. [DOI]
  • 14.Jung IR, Choi SE, Jung JG, Lee SA, Han SJ, Kim HJ, et al. Involvement of iron depletion in palmitate-induced lipotoxicity of beta cells. Mol Cell Endocrinol. 2015;15(407):74–84. [DOI] [PubMed] [Google Scholar]
  • 15.Venkatesan P, Ramasamy J, Vanitha S, Jacob M, Varghese J. Impaired pancreatic beta-cell function after a single dose of oral iron: A before-and-after (pre-post) study. J Hum Nutr Diet. 2023;36(3):1111–1120. [DOI] [PubMed]
  • 16.Cooksey RC, Jouihan HA, Ajioka RS, Hazel MW, Jones DL, Kushner JP, et al. Oxidative stress, beta-cell apoptosis, and decreased insulin secretory capacity in mouse models of hemochromatosis. Endocrinology. 2004;145(11):5305–12. [DOI] [PubMed] [Google Scholar]
  • 17.McClain DA, Abraham D, Rogers J, Brady R, Gault P, Ajioka R, et al. High prevalence of abnormal glucose homeostasis secondary to decreased insulin secretion in individuals with hereditary haemochromatosis. Diabetologia. 2006;49(7):1661–9. [DOI] [PubMed] [Google Scholar]
  • 18.Abraham D, Rogers J, Gault P, Kushner JP, McClain DA. Increased insulin secretory capacity but decreased insulin sensitivity after correction of iron overload by phlebotomy in hereditary haemochromatosis. Diabetologia. 2006;49(11):2546–51. [DOI] [PubMed] [Google Scholar]
  • 19.Noetzli LJ, Mittelman SD, Watanabe RM, Coates TD, Wood JC. Pancreatic iron and glucose dysregulation in thalassemia major. Am J Hematol. 2012;87(2):155–60. [DOI] [PubMed] [Google Scholar]
  • 20.De Sanctis V, Soliman AT, Elsedfy H, Pepe A, Kattamis C, El Kholy M, et al. Diabetes and glucose metabolism in thalassemia major: an update. Expert Rev Hematol. 2016;9(4):401–8. [DOI] [PubMed] [Google Scholar]
  • 21.Farmaki K, Angelopoulos N, Anagnostopoulos G, Gotsis E, Rombopoulos G, Tolis G. Effect of enhanced iron chelation therapy on glucose metabolism in patients with beta-thalassaemia major. Br J Haematol. 2006;134(4):438–44. [DOI] [PubMed] [Google Scholar]
  • 22.Gamberini MR, De Sanctis V, Gilli G. Hypogonadism, diabetes mellitus, hypothyroidism, hypoparathyroidism: incidence and prevalence related to iron overload and chelation therapy in patients with thalassaemia major followed from 1980 to 2007 in the Ferrara Centre. Pediatr Endocrinol Rev PER. 2008;6(Suppl 1):158–69. [PubMed] [Google Scholar]
  • 23.Cao C, O’Brien KO. Pregnancy and iron homeostasis: an update. Nutr Rev. 2013;71(1):35–51. [DOI] [PubMed] [Google Scholar]
  • 24.Georgieff MK, Krebs NF, Cusick SE. The benefits and risks of iron supplementation in pregnancy and childhood. Annu Rev Nutr. 2019;39(21):121–46. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Asadi N, Vafaei H, Kasraeian M, Yoosefi S, Faraji A, Abbasi L. Effects of prophylactic iron supplementation on outcome of nonanemic pregnant women: a non-randomized clinical trial. J Chin Med Assoc. 2019;82(11):840–4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Bhatla N, Kaul N, Lal N, Kriplani A, Agarwal N, Saxena R, et al. Comparison of effect of daily versus weekly iron supplementation during pregnancy on lipid peroxidation. J Obstet Gynaecol Res. 2009;35(3):438–45. [DOI] [PubMed] [Google Scholar]
  • 27.Bo S, Menato G, Villois P, Gambino R, Cassader M, Cotrino I, et al. Iron supplementation and gestational diabetes in midpregnancy. Am J Obstet Gynecol. 2009;201(2):158.e1-6. [DOI] [PubMed] [Google Scholar]
  • 28.Dewey KG, Oaks BM. U-shaped curve for risk associated with maternal hemoglobin, iron status, or iron supplementation. Am J Clin Nutr. 2017;106(Suppl 6):1694S-1702S. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Jirakittidul P, Sirichotiyakul S, Ruengorn C, Techatraisak K, Wiriyasirivaj B. Effect of iron supplementation during early pregnancy on the development of gestational hypertension and pre-eclampsia. Arch Gynecol Obstet. 2018;298(3):545–50. [DOI] [PubMed] [Google Scholar]
  • 30.Zhang Y, Xu S, Zhong C, Li Q, Wu M, Zhang G, et al. Periconceptional iron supplementation and risk of gestational diabetes mellitus: a prospective cohort study. Diabetes Res Clin Pract. 2021;176:108853. [DOI] [PubMed] [Google Scholar]
  • 31.Zhuang T, Han H, Yang Z. Iron, oxidative stress and gestational diabetes. Nutrients. 2014;6(9):3968–80. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Simcox JA, McClain DA. Iron and diabetes risk. Cell Metab. 2013;17(3):329–41. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Dresow B, Petersen D, Fischer R, Nielsen P. Non-transferrin-bound iron in plasma following administration of oral iron drugs. Biometals. 2008;21(3):273–6. [DOI] [PubMed] [Google Scholar]
  • 34.Brittenham GM, Andersson M, Egli I, Foman JT, Zeder C, Westerman ME, et al. Circulating non-transferrin-bound iron after oral administration of supplemental and fortification doses of iron to healthy women: a randomized study. Am J Clin Nutr. 2014;100(3):813–20. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Coffey R, Knutson MD. The plasma membrane metal-ion transporter ZIP14 contributes to nontransferrin-bound iron uptake by human β-cells. Am J Physiol Cell Physiol. 2017;312(2):C169–75. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Hansen JB, Tonnesen MF, Madsen AN, Hagedorn PH, Friberg J, Grunnet LG, et al. Divalent metal transporter 1 regulates iron-mediated ROS and pancreatic β cell fate in response to cytokines. Cell Metab. 2012;16(4):449–61. [DOI] [PubMed] [Google Scholar]
  • 37.Liu L, Yan F, Yan H, Wang Z. Impact of iron supplementation on gestational diabetes mellitus: a literature review. Diabetes Obes Metab. 2023;25(2):342–53. [DOI] [PubMed] [Google Scholar]
  • 38.Petry CJ. Iron supplementation in pregnancy and risk of gestational diabetes: a narrative review. Nutrients. 2022;14(22):4791. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Hao L, Zhang Y, Lan X, Zhang J, Wu C, Dong H, et al. Effects of iron supplement intake on gestational diabetes mellitus in early and middle pregnancy in Chengdu City in 2017. Wei Sheng Yan Jiu. 2020;49(2):227–32. [DOI] [PubMed] [Google Scholar]
  • 40.Si S, Shen Y, Xin X, Mo M, Shao B, Wang S, et al. Hemoglobin concentration and iron supplement during pregnancy were associated with an increased risk of gestational diabetes mellitus. J Diabetes. 2021;13(3):211–21. [DOI] [PubMed] [Google Scholar]
  • 41.Zhang Y, Xu S, Zhong C, Li Q, Wu M, Zhang G, et al. Periconceptional iron supplementation and risk of gestational diabetes mellitus: a prospective cohort study. Diabetes Res Clin Pract. 2021;176:108853. [DOI] [PubMed] [Google Scholar]
  • 42.Petry CJ, Ong KK, Hughes IA, Dunger DB. Associations between maternal iron supplementation in pregnancy and changes in offspring size at birth reflect those of multiple micronutrient supplementation. Nutrients. 2021;13(7):2480. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Chan KKL, Chan BCP, Lam KF, Tam S, Lao TT. Iron supplement in pregnancy and development of gestational diabetes--a randomised placebo-controlled trial. BJOG Int J Obstet Gynaecol. 2009;116(6):789–97; discussion 797–798. [DOI] [PubMed]
  • 44.Kinnunen TI, Luoto R, Helin A, Hemminki E. Supplemental iron intake and the risk of glucose intolerance in pregnancy: re-analysis of a randomised controlled trial in Finland. Matern Child Nutr. 2016;12(1):74–84. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Palma S, Perez-Iglesias R, Prieto D, Pardo R, Llorca J, Delgado-Rodriguez M. Iron but not folic acid supplementation reduces the risk of low birthweight in pregnant women without anaemia: a case-control study. J Epidemiol Community Health. 2008;62(2):120–4. [DOI] [PubMed] [Google Scholar]
  • 46.Liu XN, Pang J. A retrospective study of supplemental iron intake in singleton pregnancy women with risk of developing gestational diabetes mellitus. Medicine. 2018;97(26):e10819. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.Bowers K, Yeung E, Williams MA, Qi L, Tobias DK, Hu FB, et al. A prospective study of prepregnancy dietary iron intake and risk for gestational diabetes mellitus. Diabetes Care. 2011;34(7):1557–63. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Zhu B, Liang C, Xia X, Huang K, Yan S, Hao J, et al. Iron-related factors in early pregnancy and subsequent risk of gestational diabetes mellitus: the Ma’anshan Birth Cohort (MABC) Study. Biol Trace Elem Res. 2019;191(1):45–53. [DOI] [PubMed] [Google Scholar]
  • 49.Khambalia AZ, Aimone A, Nagubandi P, Roberts CL, McElduff A, Morris JM, et al. High maternal iron status, dietary iron intake and iron supplement use in pregnancy and risk of gestational diabetes mellitus: a prospective study and systematic review. Diabet Med J Br Diabet Assoc. 2016;33(9):1211–21. [DOI] [PubMed] [Google Scholar]
  • 50.Zhao L, Lian J, Tian J, Shen Y, Ping Z, Fang X, et al. Dietary intake of heme iron and body iron status are associated with the risk of gestational diabetes mellitus: a systematic review and meta-analysis. Asia Pac J Clin Nutr. 2017;26(6):1092–106. [DOI] [PubMed] [Google Scholar]
  • 51.Kataria Y, Wu Y, Horskjær P de H, Mandrup-Poulsen T, Ellervik C. Iron status and gestational diabetes-a meta-analysis. Nutrients. 2018;10(5):621. [DOI] [PMC free article] [PubMed]
  • 52.Anemia Mukt Bharat | Anemia Mukt Bharat. Available from: https://anemiamuktbharat.info/. Cited 2023 Jul 7.
  • 53.Recommendations to prevent and control iron deficiency in the United States. Centers for Disease Control and Prevention. MMWR Recomm Rep Morb Mortal Wkly Rep Recomm Rep. 1998;47(RR-3):1–29. [PubMed]
  • 54.Chanarin I, Rothman D. Further observations on the relation between iron and folate status in pregnancy. Br Med J. 1971;2(5753):81–4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 55.Scott DE, Pritchard JA. Anemia in pregnancy. Clin Perinatol. 1974;1(2):491–506. [PubMed] [Google Scholar]
  • 56.Antenatal iron supplementation. Available from: https://www.who.int/data/nutrition/nlis/info/antenatal-iron-supplementation. Cited 2023 Jul 7.
  • 57.American Diabetes Association. 2. Classification and diagnosis of diabetes: standards of medical care in diabetes-2020. Diabetes Care. 2020;43(Suppl 1):S14–31. [DOI] [PubMed]
  • 58.Miyakoshi K, Saisho Y, Tanaka M, Shimada A, Itoh H, Yoshimura Y. Pancreatic β-cell function in women with gestational diabetes mellitus defined by new consensus criteria. Diabetes Care. 2011;34(1):e8. [DOI] [PubMed] [Google Scholar]
  • 59.Iqbal R, Ajayan K, Bharathi AV, Zhang X, Islam S, Soman CR, et al. Refinement and validation of an FFQ developed to estimate macro- and micronutrient intakes in a south Indian population. Public Health Nutr. 2009;12(1):12–8. [DOI] [PubMed] [Google Scholar]
  • 60.Tyagi S, Toteja GS, Bhatia N. Maternal dietary intake during pregnancy and its association with size of offspring at birth and one year of age (P11–031–19). Curr Dev Nutr. 2019;3(Suppl 1). Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6574318/. Cited 2021 May 29.
  • 61. Longvah T, An̲antan̲ I, Bhaskarachary K, Venkaiah K. Indian food composition tables. National Institute of Nutrition, Indian Council of Medical Research. 2017:536.
  • 62.Sasaki K, Ikuta K, Tanaka H, Ohtake T, Torimoto Y, Fujiya M, et al. Improved quantification for non-transferrin-bound iron measurement using high-performance liquid chromatography by reducing iron contamination. Mol Med Rep. 2011;4(5):913–8. [DOI] [PubMed] [Google Scholar]
  • 63.Van Cauter E, Mestrez F, Sturis J, Polonsky KS. Estimation of insulin secretion rates from C-peptide levels. Comparison of individual and standard kinetic parameters for C-peptide clearance. Diabetes. 1992;41(3):368–77. [DOI] [PubMed] [Google Scholar]
  • 64.Utzschneider KM, Prigeon RL, Faulenbach MV, Tong J, Carr DB, Boyko EJ, et al. Oral disposition index predicts the development of future diabetes above and beyond fasting and 2-h glucose levels. Diabetes Care. 2009;32(2):335–41. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 65.Matsuda M, DeFronzo RA. Insulin sensitivity indices obtained from oral glucose tolerance testing: comparison with the euglycemic insulin clamp. Diabetes Care. 1999;22(9):1462–70. [DOI] [PubMed] [Google Scholar]
  • 66.Castillo MJ, Scheen AJ, Letiexhe MR, Lefèbvre PJ. How to measure insulin clearance. Diabetes Metab Rev. 1994;10(2):119–50. [DOI] [PubMed] [Google Scholar]
  • 67.Lehmann-Werman R, Neiman D, Zemmour H, Moss J, Magenheim J, Vaknin-Dembinsky A, et al. Identification of tissue-specific cell death using methylation patterns of circulating DNA. Proc Natl Acad Sci U S A. 2016;113(13):E1826-1834. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Material 1. (133.9KB, pdf)
Supplementary Material 2. (151.9KB, pdf)

Data Availability Statement

The final data will be available to the PI and co-investigators of the study for analysis and interpretation. It will also be submitted to the funding agency, the Indian Council of Medical Research, as required.


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