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Identifying research priorities for gestational weight gain in India: A national exercise
For correspondence: Dr Reema Mukherjee, Division of Reproductive Child Health and Nutrition, Indian Council of Medical Research, New Delhi 110 029, India e-mail: rima.mukerjee@gmail.com
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Received: ,
Accepted: ,
How to cite this article: Manna S, Roy SP, Lyngdoh T, Chowdhury R, Khandelwal S, Thiruvengadam R, et al. Identifying research priorities for gestational weight gain in India: A national exercise. Indian J Med Res. 2026;163:215-9. doi: 10.25259/IJMR_2976_2025.
Abstract
Background and objectives
Gestational weight gain is an important indicator of maternal and neonatal health, yet research on this topic in the Indian context remains limited. We conducted a research-setting exercise to identify priority research questions related to gestational weight gain in the Indian context, aiming to guide researchers and policymakers.
Methods
We used a hybrid approach combining Child Health and Nutrition research Initiative (CHNRI) and a modified James Lind Alliance- Priority Setting Partnership (JLA-PSP). The four CHNRI steps produced an interim priority list, which was refined through the modified JLA-PSP to finalise the priorities
Result
Sixty researchers participated in the online survey, yielding 54 questions (response rate:30%). These were consolidated into 12 questions across three domains- (a) development of standards and guidelines, (b) Epidemiology and determinants and (c) Evaluation of interventions and strategies for gestational weight gain. We calculated research priority scores, and average expert agreement. The expert group determined four priority questions, emphasising gestational weight gain cut-offs related to short- and long-term feto-maternal outcomes, determinants of gestational weight gain, and effective interventions.
Interpretation and conclusion
These priorities provide a roadmap for researchers and funders for targeted research in the area of gestational weight gain to improve maternal and child health outcomes in India.
Keywords
Child health and nutrition research initiative (CHNRI)
Expert consensus
Gestational weight gain
India
James Lind Alliance (JLA)
Research priorities
Women in India experience a dual burden of malnutrition, with a relatively high prevalence of both undernutrition and overweight. Approximately 42.2% of women enter pregnancy underweight,1 while 16.5% experience excessive gestational weight gain.1 About 30% of women attain optimal weight gain in gestation, as per recommendation.2 Both excessive and inadequate gestational weight gain is linked to adverse maternal and birth outcomes. However, evidence on optimal weight gain in Indian women including determinants, effective interventions, and links to maternal and neonatal outcomes remains limited. Existing recommendations are based on data in western populations and may not be applicable for Indian women.3 To address this evidence gap, we conducted a research priority-setting exercise to identify and prioritise relevant research questions related to optimal gestational weight gain in India. This effort aims to guide researchers and policymakers toward areas of research with the potential to improve maternal and child health.
Methods
We utilised two validated methods to identify and prioritise research questions related to optimal gestational weight gain. A modified version of the Child Health and Nutrition Research Initiative (CHNRI) framework4 followed by the adapted James Lind Alliance (JLA) Priority Setting Partnership (PSP) model5 was used. CHNRI framework was used (first four steps) to arrive at an interim prioritisation list. We used JLA-PSP model as a final step to arrive at the final prioritisation list.
Step 1: Define the scope and context of the research priority setting exercise
At the outset, we defined the scope and context of the exercise to provide a common frame of reference for all contributors. This included specifying the research area (gestational weight) and population of interest (pre conception/pregnant women), the geographical focus (India), and the time horizon (for the next five years) within which the research is expected to have an impact.
Step 2: Identifying key researchers
Researchers from India with prior publications in maternal health, nutrition, and related fields with prior publications in gestational weight gain were identified through a PubMed-based in last five-year search (2019–2024) for the purpose of identifying recent emerging research questions related to gestational weight gain.
Step 3: Identification of research questions or ideas
We then contacted researchers identified in step 1 and invited them to participate in an open-ended online survey. This survey asked them to list up to three priority research questions relevant to gestational weight gain in Indian context.
Step 4: Refining questions
Original research questions were retained. Where responses were provided as statements conveying a research idea, these were restructured into research questions. Duplicate and overlapping ideas were removed or merged. Since the aim was to capture the full range of expert views, questions were retained even if their phrasing was not entirely precise, as long as they represented a relevant research idea. This helped ensure that the original intent of the experts was reflected while grouping the questions under appropriate themes. Based on the emerging themes the questions were clustered into specific domains.
Step 5: Interim prioritisation (CHNRI-Based Scoring and Criteria)
Twenty experts were chosen purposively from ICMR’s database based on their expertise —maternal health (n=8), child health (n=2), basic research (n=3), and nutrition (n=7). The experts independently rated the final list of questions for novelty, answerability, and translational potential using the CHNRI scale (0= disagree,1=agree,0.5= neither agree nor disagree).6 Research priority scores (RPS)6 and average expert agreement (AEA)7 were calculated for each question. The AEA measures the degree of agreement among respondents by calculating the proportion of respondents selecting the most common score for each research question. The detailed methodology is described in the Supplementary Material.
Step 6: Final prioritization
The final prioritisation followed the James Lind Alliance Priority Setting Partnership (JLA-PSP) method. After completion of the CHNRI scoring, the same panel of experts from Step 4 participated in a full-day hybrid workshop held at ICMR, New Delhi, on May 26, 2025. The workshop was chaired by a designated chairperson and co-chairperson, who facilitated the process and ensured balanced participation. For each of the four domains, a lead discussant presented a summary of available evidence and key knowledge gaps. The expert panel then reviewed the refined list of research questions. During the discussions, participants were invited to: (i) propose additional questions and (ii) suggest modifications to better reflect outcomes or objectives. Through facilitated group discussion, a final set of priority questions was developed. All deliberations were transcribed to maintain transparency and create an auditable record. Consensus on the final list required ≥90 % affirmative votes (yes/no). Draft minutes and the revised priority list were circulated to all participants for verification.
Results
Sixty researchers were identified and invited to participate in an open-ended online survey, of which 18 responded (30% response rate; 11 males and 7 females; 9, 6 and 3 from South, North and West India, respectively) and collectively generated 54 research questions. Of 54 responses. 11 non-question statements were excluded. The remaining 43 were reviewed independently by three of the authors and, through consensus, were clustered into thematic domains. Overlapping or repetitive questions were merged. This process yielded a consolidated set of 12 representative research questions, which were further grouped under three domains based on the type of research required: (i) development of gestational weight gain standards and guidelines, (ii) epidemiology and determinants of gestational weight gain, and (iii) evaluation of interventions and strategies for gestational weight gain ( Table).
| Domain | Raw questions (n) | Retained questions (n) | Final retained research questions |
|---|---|---|---|
| Development of standards and guidelines for gestational weight gain in Indian context | 10 | 2 |
1. What are the optimal recommendations for Indian pregnant women based on pre-pregnancy BMI categories (underweight, normal weight, overweight, obese)? 2. How can India-specific standards be developed to predict optimal feto-maternal outcomes, considering regional variations in maternal anthropometry and dietary patterns? |
| Epidemiology and biological determinants of gestational weight gain | 4 | 3 |
3. What are the prevalence, associated risk factors, and mechanisms influencing gestational weight gain in the Indian setting? 4. What are the primary contributors to weight gain during pregnancy (e.g., water retention, fat deposition), and can studies help distinguish them to improve clinical management? 5. What is the level of knowledge among healthcare providers regarding appropriate gestational weight gain? |
| Evaluation of interventions and strategies to ensure optimal gestational weight gain | 27 | 7 |
6. What is the impact of maternal pre-pregnancy BMI and trimester-specific gestational weight gain on maternal outcomes (e.g., gestational hypertension), fetal outcomes (e.g., birth weight), and long-term offspring outcomes (e.g., obesity and metabolic syndrome)? 7. How does pre-pregnancy BMI influence gestational weight gain patterns and associated maternal and fetal outcomes? 8. In pregnant women with low BMI and inadequate gestational weight gain, does a targeted intervention of locally prepared, micronutrient-enriched balanced energy-protein (BEP) supplementation result in increased birth weight? 9. How effective is an integrated package of tailored nutrition intervention, counseling and exercise on ensuring appropriate weight gain in women who enter pregnancy with higher BMIs, and what is the impact on neonatal outcomes? 10. What is the optimal management strategy (e.g., dietary interventions, counseling) or clinical algorithm for addressing inadequate gestational weight gain across different trimesters to improve maternal and neonatal outcomes? 11. Implementation study to provide optimised Take Home Ration with supplementary nutrition and counseling to examine its impact on gestational weight gain. 12. What are the key windows of opportunity for interventions to optimise gestational weight gain, and what are the barriers to achieving optimal weight gain? |
The expert group scored12 research questions using CHNRI scoring criteria online. Supplementary Table shows the research priority scores (RPS) and average expert agreement (AEA) for the 12 retained research questions. The RPS ranged from 0.66 to 0.94. Average expert agreement (AEA) was generally high, ranging from 0.54 to 0.90, with the strongest consensus around Q1, Q2 and Q12.
The final prioritisation was done during the workshop. The experts were blinded to the actual scores (RPS and AEA) that the 12 questions had received, till the last step. After the facilitated discussions and the evidence reviews, the expert panel decided that the definition of context-specific gestational weight gain standards is the basic step to guide any subsequent strategies and interventions. These standards should be able to predict both short-term and long-term maternal and neonatal outcomes. Establishing such cut-offs was considered essential before the effectiveness of different interventions can be meaningfully evaluated. In addition, the panel emphasised the importance of understanding the epidemiology of gestational weight gain in India—specifically, the determinants of trimester-specific weight gain and their modifiability. This knowledge is required to inform policy and program design. Building on these two components, tailored intervention strategies can then be developed and tested.
Using the JLA-PSP method, the expert panel synthesised the final prioritisation list of four research questions from the interim list of research questions. The final prioritised questions were:
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(i).
What are the gestational weight gain cut-offs during the three trimesters of pregnancy, which can predict adverse outcomes (maternal outcomes such as-preeclampsia, gestational diabetes mellitus (GDM), mode of delivery; neonatal outcomes such as- preterm birth, small for gestational age, large for gestational age)?
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(ii).
What are the gestational weight gain cut-offs during the three trimesters of pregnancy, which are associated with long term maternal and child outcomes?
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(iii).
What are the determinants of trimester-specific gestational weight gain in the Indian setting? Which of these associations are modifiable?
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(iv).
Does a targeted, tailored intervention package customised according to early pregnancy BMI and gestational weight gain, compared to routine care, lead to improved maternal and birth outcomes?
The refinement process involved consolidating interrelated questions from the interim list. Q1, Q2, Q6, Q7, and Q10 were consolidated into the first two priority questions on trimester-specific GWG cut-offs and their ability to predict short- and long-term outcomes; Q3 and Q4 were merged into the third priority question, focusing on the prevalence, risk factors, and biological mechanisms underlying GWG in India, and which of these are amenable to modification; and the remaining questions (Q5, Q8, Q9, Q11, Q12) were integrated into the fourth priority question on tailored interventions, encompassing targeted supplementation, combined nutrition and lifestyle strategies, implementation approaches, and provider knowledge.
The RPS and AEA scores were then unblinded and it was observed that the scoring pattern was consistent with the priorities identified through discussion, thereby reinforcing the robustness of the final list (Supplementary Table). Although Q12 (windows and barriers for optimal GWG) received a high RPS and AEA, the panel had decided to incorporate it within the broader intervention priority rather than retain it as a stand-alone question, as it was considered to address implementation aspects of intervention design.
Discussion
This research prioritisation exercise identified critical research gaps on gestational weight gain in India to guide clinical practice, programme and policy. The highest-ranked priorities focused on defining India-specific, BMI-based gestational weight gain cut-offs that can predict optimal maternal and neonatal outcomes. The final four consolidated questions highlight a sequential research pathway: establishing context-specific gestational weight gain standards, characterising determinants and modifiable risks, and testing tailored intervention packages.
Multiple studies demonstrate that existing international references like IOM and Intergrowth-21st are inappropriate for Indian women.8,9 Therefore, establishing trimester-specific gestational weight gain cut-offs linked to maternal and child outcomes will provide clinicians with clearer standards for monitoring pregnancy and identifying women at risk of adverse outcomes. Brazil’s development of population-specific gestational weight gain curves illustrates how local anthropometry and outcome data can yield more relevant standards.10 World Health Organization has initiated the process to develop global standards suitable for public health monitoring across diverse settings.11
India is experiencing a major nutritional transition among pregnant women. Singh et al12 analysed data from the National Family Health Survey (2015–2016) and found that about 40% of women had a normal BMI (based on Asian cutoffs), while 22% were thin and 38% were overweight or obese. These findings highlight the need for targeted and tailored intervention packages, customised according to early pregnancy BMI and gestational weight gain. Evidence on their effectiveness will support policies and programme integrated within existing maternal health and nutrition platforms.
While the final priority list of four questions highlights the most critical evidence gaps the broader interim list of twelve questions offers a more detailed view of the research landscape and may guide researchers and policymakers. These lists represent the outcome of a systematic prioritisation process rather than author-driven recommendations. Readers are encouraged to interpret and utilise the interim and final lists based on their specific research interests, programmatic needs, and contextual relevance.
Despite our best efforts to identify all relevant research questions/topics, some may not have been captured. Additionally, research prioritisation exercises inherently carry some subjective bias. We duly acknowledge this and state that the priority list presented in this manuscript may not be a definitive priority list however it does provide an appropriate direction to the type of research that is needed to address the evidence gap related to optimal gestational weight gain in India.
Acknowledgment
Authors acknowledge Dr(s) Bani Aeri (Professor, Department of Food and Nutrition, Institute of Home Economics, University of Delhi); Vikas Yadav and Surabhi Chaturvedi [Bill & Melinda Gates Foundation (BMGF)]; Nitya Wadhwa (Senior Professor, Translational Health Science and Technology Institute); Sunita Taneja (Senior Scientist, Society for Applied Studies, New Delhi); Sadhana Joshi (Indian Research and Studies in Human Advancement, Pune); Sai Ram and Santosh Kumar (National Institute of Nutrition); and MsPreetu Mishra (UNICEF), for their valuable contributions and expert facilitation during the meeting.
Author contributions
RM: Conceptualized the study, involved in design, manuscript writing; SPR: Involved in design; SM: Involved in design, data analysis, manuscript writing. All authors have reviewed and approved the final printed version of the manuscript.
Financial support and sponsorship
None.
Conflicts of Interest
None.
Use of Artificial Intelligence (AI)-Assisted Technology for manuscript preparation
The authors confirm that there was no use of AI-assisted technology for assisting in the writing of the manuscript and no images were manipulated using AI.
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