{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T05:12:37Z","timestamp":1772169157167,"version":"3.50.1"},"update-to":[{"DOI":"10.12688\/wellcomeopenres.15934.1","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2022,2,22]],"date-time":"2022-02-22T00:00:00Z","timestamp":1645488000000}},{"DOI":"10.12688\/wellcomeopenres.15934.2","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2022,2,22]],"date-time":"2022-02-22T00:00:00Z","timestamp":1645488000000}},{"DOI":"10.12688\/wellcomeopenres.15934.3","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2022,2,22]],"date-time":"2022-02-22T00:00:00Z","timestamp":1645488000000}}],"reference-count":98,"publisher":"F1000 Research Ltd","license":[{"start":{"date-parts":[[2022,2,22]],"date-time":"2022-02-22T00:00:00Z","timestamp":1645488000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100009053","name":"The Wellcome Trust DBT India Alliance","doi-asserted-by":"publisher","award":["IA\/CPHI\/16\/1\/502648"],"award-info":[{"award-number":["IA\/CPHI\/16\/1\/502648"]}],"id":[{"id":"10.13039\/501100009053","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["wellcomeopenresearch.org"],"crossmark-restriction":false},"short-container-title":["Wellcome Open Res"],"abstract":"<ns3:p>\n                    <ns3:bold>Background:\u00a0<\/ns3:bold>\n                    High prevalence of maternal malnutrition, low birth-weight and child malnutrition in India contribute substantially to the global malnutrition burden. Rural India has disproportionately higher levels of child malnutrition. Stunting and wasting are the primary determinants of child malnutrition and their district-level distribution shows clustering in different geographies and regions. Cereals, particularly millets, constitute the bulk of protein intake among the poor, especially in rural areas in India where high prevalence of wasting persists.\n                  <\/ns3:p>\n                  <ns3:p>\n                    <ns3:bold>Methods:\u00a0<\/ns3:bold>\n                    The previous round of National Family Health Survey (NFHS4) has disaggregated data by district, enabling a more fine-scale characterisation of the prevalence of markers of malnutrition. We used data from NFHS4 and agricultural statistics datasets to analyse relationship of prevalence of malnutrition at the district level and area under cereal cultivation. We analysed malnutrition through data on under-5 stunting and wasting by district.\u00a0\n                  <\/ns3:p>\n                  <ns3:p>\n                    <ns3:bold>Results:\u00a0<\/ns3:bold>\n                    Stunting and wasting patterns across districts show a distinct geographical and age distribution; districts with higher wasting showed relatively higher prevalence at six months of age. Wasting prevalence at district level was associated with higher cultivation of millets, with a stronger association seen for jowar and other millets (Kodo millet, little millet, proso millet, barnyard millet and foxtail millet). District level stunting was associated with higher district level cultivation of wheat. In multivariable analysis, wasting was positively associated with women\u2019s body mass index and stunting with women\u2019s short stature.\n                  <\/ns3:p>\n                  <ns3:p>\n                    <ns3:bold>Conclusions:\u00a0<\/ns3:bold>\n                    Well-designed intervention studies will be required to confirm causal pathways contributing to ecogeographic patterns of child malnutrition. The cultivation of other millets has a strong association with prevalence of wasting. State-of-the-art studies that improve our understanding of bio-availability of amino acids and other nutrients from the prevalent dietary matrices of rural poor communities will be needed to confirm causal pathways contributing to potential eco-geographic patterns.\n                  <\/ns3:p>","DOI":"10.12688\/wellcomeopenres.15934.4","type":"journal-article","created":{"date-parts":[[2022,2,22]],"date-time":"2022-02-22T10:30:07Z","timestamp":1645525807000},"page":"118","update-policy":"https:\/\/doi.org\/10.12688\/wellcomeopenres.crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Eco-geographic patterns of child malnutrition in India and its association with cereal cultivation: An analysis using demographic health survey and agriculture datasets"],"prefix":"10.12688","volume":"5","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4288-883X","authenticated-orcid":false,"given":"Rama 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Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/wellcomeopenresearch.org\/articles\/5-118\/v4\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/wellcomeopenresearch.org\/articles\/5-118\/v4\/pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/wellcomeopenresearch.org\/articles\/5-118\/v4\/iparadigms","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,3]],"date-time":"2024-12-03T02:25:16Z","timestamp":1733192716000},"score":1,"resource":{"primary":{"URL":"https:\/\/wellcomeopenresearch.org\/articles\/5-118\/v4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,2,22]]},"references-count":98,"URL":"https:\/\/doi.org\/10.12688\/wellcomeopenres.15934.4","relation":{"has-version":[{"id-type":"doi","id":"10.12688\/wellcomeopenres.15934.3","asserted-by":"subject"},{"id-type":"doi","id":"10.12688\/wellcomeopenres.15934.2","asserted-by":"subject"},{"id-type":"doi","id":"10.12688\/wellcomeopenres.15934.1","asserted-by":"subject"}],"has-review":[{"id-type":"doi","id":"10.21956\/wellcomeopenres.19560.r48847","asserted-by":"subject"},{"id-type":"doi","id":"10.21956\/wellcomeopenres.19560.r50740","asserted-by":"subject"},{"id-type":"doi","id":"10.21956\/wellcomeopenres.19560.r50740","asserted-by":"object"},{"id-type":"doi","id":"10.21956\/wellcomeopenres.19560.r48847","asserted-by":"object"}]},"ISSN":["2398-502X"],"issn-type":[{"value":"2398-502X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,2,22]]},"assertion":[{"value":"Indexed","URL":"https:\/\/wellcomeopenresearch.org\/articles\/5-118\/v4#article-reports","order":0,"name":"referee-status","label":"Referee status","group":{"name":"current-referee-status","label":"Current Referee Status"}},{"value":"10.21956\/wellcomeopenres.19560.r48847, Edward J.M. Joy, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, 04 Apr 2022, version 4, indexed","URL":"https:\/\/wellcomeopenresearch.org\/articles\/5-118\/v4#referee-response-48847","order":0,"name":"referee-response-48847","label":"Referee Report","group":{"name":"article-reports","label":"Article Reports"}},{"value":"10.21956\/wellcomeopenres.18006.r41339, Suparna Ghosh-Jerath, Indian Institute of Public Health-Delhi, Public Health Foundation of India, Gurgaon, Haryana, 09 Jun 2021, version 2, 1 approved with reservations, 1 not approved","URL":"https:\/\/wellcomeopenresearch.org\/articles\/5-118\/v2#referee-response-41339","order":1,"name":"referee-response-41339","label":"Referee Report","group":{"name":"article-reports","label":"Article Reports"}},{"value":"<b>Prashanth N Srinivas<\/b>; \n<i>Posted: 25 Jun 2021<\/i>; In the paper we analyse data in order to explore the possible link between type of cereal consumed and the occurrence of child malnutrition, given that cereals constitute upwards of 70% of diet in the rural areas where malnutrition is the highest. We maintain that this is a novel \n<u>exploratory study<\/u>, as we have not come across a study that has \n<u>explored<\/u>&nbsp;this relationship.  In the interest of advancing critical inquiry at the heart of the scientific process, we believe that overwhelming existing evidence should NOT be a reason for non-acceptance of new kinds of evidence demonstrating&nbsp;\n<u>plausibility<\/u>&nbsp;if not causation.&nbsp;A reasonable approach in our opinion for anyone with differences from the line of thought that we pursue here would be to demonstrate mistakes in our analysis and\/or over-reach of conclusions (which in fact was pointed out by RI and has been significantly revised in our version 2).&nbsp;  The reviewer repeatedly brings out the argument that millets are nutritious and in the same breath says that malnutrition is more common in communities consuming millets (see for eg. R2 assertion in response to v1 &quot;\u201cIt's not surprising that households with high coarse cereals consumption have high wasting and malnutrition\u201d) This is in fact the relationship that we attempt to explain (we do not attempt to causally link the two). Such an explanation requires reaching across disciplines ranging from cellular pathways, agriculture and nutrition which we attempt in this paper.  It is the dietary matrix and how it impacts on the absorption of various nutrients that is important as opposed to making millet a singular causal candidate. Our approach is that since there is substantial variability in the dietary availability of various key nutrients in different cereals there are likely to be differences in their effects in different populations. The low glycaemic index of some millets which may be advantageous to the obese diabetic may be a disadvantage to the unborn of a pregnant adolescent with poor dietary diversity. We have indicated in our version2 that most millets indeed have greater micronutrient levels in comparison to rice &amp; wheat which could be contributory to stunting in areas where they are predominantly consumed. Our contention is that the lower amino acid availability could be similarly causing wasting in areas where millets are consumed. To emphasize this aspect, we have brought out the Digestible ingested amino acid scores(DIAAS), as acceptable by WHO, of different cereals from published literature. The correct approach mitigate this lack of nutritional availability by pre-processing like nixtamalization or fermentation or to supplement above by appropriate changes in the matrix or with added nutritional supplements in the way Iron and Folate is supplemented in pregnancies in most developing countries.  So what we are asking is for a closer scientific scrutiny into the nutritional availability of key components in commonly consumed diets by rural Indians. To reject the question itself, as the reviewer has done in conclusion, demonstrates the lack of engagement with our analysis and results presented possibly due to an overwhelming reliance on the existing assertions about nutritious value of millets rather than an openness to engage with evidence critical of a given hypothesis.&nbsp;  We believe that our assertions are reasonably demonstrated by the evidence we present and were hoping to be proved wrong by demonstrating errors in our analysis or conclusions. In the lack of that, we shall continue working harder on communicating our findings better to the scientific community.","URL":"https:\/\/wellcomeopenresearch.org\/articles\/5-118\/v4#referee-comment-4675","order":2,"name":"referee-comment-4675","label":"Referee Comment","group":{"name":"article-reports","label":"Article Reports"}},{"value":"10.21956\/wellcomeopenres.18904.r46243, Nicholas J. Kassebaum, Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, 26 Oct 2021, version 3, 2 approved with reservations, 1 not approved","URL":"https:\/\/wellcomeopenresearch.org\/articles\/5-118\/v3#referee-response-46243","order":3,"name":"referee-response-46243","label":"Referee Report","group":{"name":"article-reports","label":"Article Reports"}},{"value":"<b>Prashanth N Srinivas<\/b>; \n<i>Posted: 22 Feb 2022<\/i>; Thank you for your detailed review.&nbsp; On the minor points you have highlighted:  We have made suitable edits to improve readability. Regarding teh&nbsp; Error related to year of NFHS4&nbsp;regretted and corrected\n<b>.<\/b>  Response to major\/substantive comments below; extensive changes made in v4 to address these:&nbsp;  Figure 1 has been&nbsp;re-done the figures to improve visual contrast of the pattern\n<b>.&nbsp;<\/b> References to birth weight data from NFHS have now been removed as we do not use it in our analysis. On the assertion regarding arbitrariness of \u201chigh\u201d vs. \u201clow\u201d stunting\/wasting districts:&nbsp;In the paper by Junaid and Mohanty, the districts were classified as low stunting (less than 26%), medium stunting (prevalence 26.1-46%) and high stunting (prevalence higher than 46%) based on mean and standard deviation, as per their results. Highest wasting prevalence districts&nbsp; were categorised as more than 28%. We utilised this&nbsp; classification for illustrating the districts with high prevalence of stunting, wasting as well as both high stunting and wasting in the maps. However, Z scores of less than -2 SD have been used for stunting &amp; wasting cut off to assess prevalence in NFHS4. Their &nbsp;prevalence in districts (without distinction into high and low) have been used for the scatter plots and multivariable regression. A table (table 1) indicating different variables used in the maps and other results is shown for clarity in this version. We accept that our choosing of these cut-offs will affect the wider applicability of these findings. However, in the lack of a globally comparable standard, we have chosen this. Furthermore, this categorisation is only applicable to our map-based visualisations. The multivariable analysis indeed uses district-level percentages of stunting and wasting. &nbsp; On the points raised in Discussion that are not in the results:&nbsp;We have re-written the Discussion section to focus better on the results reported. WE have now removed any tables and figures from our discussion and have modified earlier figure 9, a pie chart into a bar and moved it up to the results. The figure showing pathways to nutrition and information about mechanisms through MTORC1 has been only referred to and all narrative\/figures on the pathway have now been shifted out of the paper. On the reviewers points about findings presented in Table 2 and Table 3:&nbsp;Thank you for the opportunity to clarify this further and thank you for your comments on the potential applications of our findings. In our revision, we have attempted to address these important comments to the extent possible. However, some of these comments being policy and practice implications of the underlying hypotheses we are examining, we have been unable to comprehensively address them even in our revised discussion. Moreover, many of these important observations by the reviewer are in age-groups outside of our analysis (nonetheless having important implications). We hope that our paper shall contribute to expanding the literature on the points raised by the reviewer. However, given the importance of these points, we attempt to provide some response hereunder to those aspects that are yet not addressed in our revised discussion. We hope to develop these further once this analysis achieves peer acceptability. The literature and evidence on food security potentially connects socio-demographic factors mechanistically to food supply. One definition of food security is \u201cAccess by all people at all times to sufficient food and nutrition for a healthy and productive life\u201d\n<sup>1<\/sup> . The opposite term, food insecurity has been defined by one source as \u201cA person is&nbsp;food insecure when they lack regular access to enough safe and nutritious food for normal growth and development and an active and healthy life&nbsp;\u201d\n<sup>2<\/sup>.&nbsp;&nbsp; Moderate food insecurity, like seen among the poor in high-income countries, is also associated with obesity\n<sup>3<\/sup> . Severe food insecurity is associated with hunger. A study based on data suitable for measuring food security from Maharashtra, India&nbsp; indicated that food insecurity is no longer associated&nbsp; with statistically significant stunting, wasting or underweight, when controlled for dietary diversity and all other child, maternal or household characteristics implying&nbsp; the importance of dietary diversity as a determinant of malnutrition\n<sup>4<\/sup>. The Lancet 2013 series clearly brought that the Nutrition specific interventions , when brought up to scale of over 90% could help tackle about 20% of global burden of malnutrition\n<sup>8<\/sup>. Noticeably, the emphasis in the Lancet series of both 2008 &amp; 2013 was on the first 1000 days as far as Nutrition specific interventions are concerned\n<sup>8,9<\/sup>. However, longitudinal studies point to the fact that children both become stunted and recover in growth, from infancy through adolescence, thereby extending the period of intervention for healthy growth from the first 1000 days till adolescence\n<sup>10,11<\/sup>. Greater persistent stunting after 5 years till 15 years, in one study in India and Ethiopia vis-&agrave;-vis Peru and Vietnam, points to an environmental context in the former countries\n<sup>11<\/sup>. India also has the largest number of low birth weight&nbsp; among countries in the world, a reflection on the health and nutrition of women through their lives\n<sup>12<\/sup>. A study analysing secular trends in improvement of child malnutrition indices in Vietnam and Bangladesh, attributed rapid improvements in HAZ scores to changes in underlying determinants like socioeconomic status, maternal education, hygiene and food security\n<sup>13<\/sup>. Changes in&nbsp; maternal nutritional knowledge and child dietary diversity were associated with only 20% of the total change\n<sup>12<\/sup>. A cross country study about drivers of nutritional change suggested four factors which predict reduction in undernutrition as, women\u2019s secondary education, reduction in fertility, increased access to health services and increase in household assets\n<sup>14<\/sup>. Clearly, a combination of nutrition sensitive and specific measures as per context would be the way forward\n<sup>15<\/sup>. The Integrated Child Development Services (ICDS) of India covers a wide range of services involving teenage nutrition, pre-school feeding, health and education as well as nutrition of pregnant &amp; breast feeding mothers, conducted through 1.3 million Anganwadi centres all over India \n<sup>16,17<\/sup>. In 2006, the ICDS was scaled up substantially following a Supreme Court directive\n<sup>18<\/sup>. There was a significant improvement in ICDS coverage as seen through comparison of NFHS 3 &amp; 4 after this scaling up. A threefold increase in percentage of women and children receiving food supplementation during pregnancy, lactation and early childhood was noted during the period\n<sup>17,18<\/sup>.There were also significant improvements recorded in breast feeding practices, antenatal coverage, immunization, age of marriage, women\u2019s education and several other health related practices \n<sup>18<\/sup>.&nbsp; Concomitantly, a 10 percentage reduction in stunting in children aged 0-5 years&nbsp; was recorded in 2016 vis-&agrave;-vis 2006 ,as per NFHS data\n<sup>17,18<\/sup>. The improvement is heterogenous across states of India, with intra-state disparities seen particularly among the poor and lower castes. However, in IYCF practices, complementary feeding and minimal meal frequency showed decline in 2016 over 2006. Clearly, the ICDS is a work in progress and there is much room for improvement with respect to coverage and efficacy\n<sup>17,18<\/sup>. A&nbsp; meta-analysis on school feedings showed significant improvements in height and weight over 12 months , compared to controls\n<sup>19<\/sup>. A recent study has clearly indicated substantial benefits of India\u2019s mid-day meal (MDM)&nbsp; scheme,&nbsp; in estimated improvement in stunting up to 0.4 SD among children born to mothers with greater exposure to MDM\n<sup>20<\/sup>. This points to the intergenerational benefits of&nbsp; school feeding apart from its multisectoral economic benefits which extend from health, social protection, education, fertility reduction to local agriculture\n<sup>20,21<\/sup>.A closer look at countries which have shown impressive declines in stunting and other mother and child nutrition related parameters, such as China and Peru , show presence of robust school feeding programs including provision of milk , over the last few decades\n<sup>22,23<\/sup>. Improving the quality of&nbsp; school feeding (coupled with deworming , nutrition education etc)&nbsp;&nbsp; and extending it to include adolescents could arguably bring about&nbsp; undernutrition reduction substantially by synergising the nutrition specific and sensitive nature of interventions involved. A practice like eating down in pregnancy, wherein mothers eat less for fear of labour related complications due to a large baby is not unheard of in many parts of rural India\n<sup>24<\/sup>. Health care systems should be made more accessible and effective, particularly in terms of priority areas like vaccination services, as well as obstetric and child care. This will also help deal with hidden issues like maternal depression as well as&nbsp; common infectious causes of child wasting such as tuberculosis, Malaria, diarrhoeas and respiratory infections\n<sup>25,26<\/sup>. Replacement of iron folate&nbsp; to multiple micronutrient supplements, targeted balanced energy micronutrient supplements to pregnant mothers with low BMI have been recommended\n<sup>8 <\/sup>.This could be extended to breast feeding mothers given the high rates of malnutrition in early infancy in India.\n<sup>&nbsp; <\/sup>The MDM should be expanded to include older children with provision of a breakfast with milk to start the day. Greater emphasis on play at ICDS and school&nbsp; should address both child stunting and rising prevalence of obesity(twin burdens of malnutrition) well. Conditional cash transfers for poorer households like the Oportunidades in Mexico\n<sup>27<\/sup>, could be used to improve dietary diversity among women and children of the poorer states through encouraging use of Nutrition, education and health services. Optimum resource allocation for multisectoral improvements&nbsp; in both nutrition specific and sensitive areas with close monitoring of benefits to the targeted population nation-wide, could bring about transformational benefits. Dietary matrix data like studies by Kurpad et al on commonly consumed food preparations by the poor with a focus on means to enhance nutrient availability through simple measures can be utilised for better quality nutritional advice or education\n<sup>28<\/sup>. The effect of cereal type on the variability in nutrient(s) availability will have to be factored while designing\/ recommending appropriate diets. Well-designed biofortification on a large scale could be explored to improve micronutrient levels in a population. Quality of breast milk , nutrient availability in the breast milk and maternal depression among mothers consuming different dietary matrices( like, say, by using different cereal types) would be immensely beneficial&nbsp; to focus on type of diets needed by&nbsp; lactating mothers in different ecogeographic areas . Given that most of the countries with high rates of malnutrition in early infancy have high cultivation of coarse cereals (our observation), it would be relevant and important to explore the relationship between type of cereal consumed and foetal growth restriction in communities with low dietary diversity and a cereal based diet. Considering that one third of Indian women in NFHS report never consuming eggs and 11% never consuming dairy products, research in optimal diet to support this group for the first 1000 days is urgently needed\n<sup>29<\/sup>. Use of mobile services for personalised dietary advise to the general population is another unexplored avenue. Research into quality of India\u2019s preschool services should be extended to states with poorer indicators of performance with an aim to translate best practices consistently across the states\n<sup>30,31<\/sup>.   References: 1. Gibson M. Food Security-A Commentary: What Is It and Why Is It So Complicated? Foods. 2012 Dec 3;1(1):18-27. doi: 10.3390\/foods1010018. PMID: 28239088; PMCID: PMC5302220.  2. FAO, IFAD, UNICEF, WFP and WHO. 2021.&nbsp;\n<i>The State of Food Security and Nutrition in the World 2021.&nbsp;Transforming food systems for food security, improved nutrition and affordable healthy diets for all<\/i>. Rome, FAO.  3. Dhurandhar EJ. The food-insecurity obesity paradox: A resource scarcity hypothesis. Physiol Behav. 2016 Aug 1;162:88-92. doi: 10.1016\/j.physbeh.2016.04.025. Epub 2016 Apr 26. PMID: 27126969; PMCID: PMC5394740.  4. Chandrasekhar S, Aguayo VM, Krishna V, Nair R. Household food insecurity and children's dietary diversity and nutrition in India. 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Swaminathan Research Foundation.  31. Rao N. Preschool Quality and the Development of Children from Economically Disadvantaged Families in India.&nbsp;\n<i>Early Educ. Dev.&nbsp;<\/i>2010;21:167\u2013185. doi:&nbsp;10.1080\/10409281003635770.[CrossRef]&nbsp;[Google Scholar]","URL":"https:\/\/wellcomeopenresearch.org\/articles\/5-118\/v4#referee-comment-4913","order":4,"name":"referee-comment-4913","label":"Referee Comment","group":{"name":"article-reports","label":"Article Reports"}},{"value":"10.21956\/wellcomeopenres.19560.r50740, Ilana Cliffer, Tufts University, Boston, MA, 13 Jun 2022, version 4, indexed","URL":"https:\/\/wellcomeopenresearch.org\/articles\/5-118\/v4#referee-response-50740","order":5,"name":"referee-response-50740","label":"Referee Report","group":{"name":"article-reports","label":"Article Reports"}},{"value":"This work was supported by the Wellcome Trust through a DBT\/Wellcome Trust India Alliance Fellowship to PNS [IA\/CPHI\/16\/1\/502648]. This award also supports YCB and SKU. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.","order":6,"name":"grant-information","label":"Grant Information"},{"value":"This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.","order":0,"name":"copyright-info","label":"Copyright"}]}}