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Review article, global trends and future prospects of child nutrition: a bibliometric analysis of highly cited papers.

• 1 School of Management, Lanzhou University, Lanzhou, China
• 2 Gansu Provincial Hospital, Lanzhou, China
• 3 Department of Social Medicine and Health Management, School of Public Health, Lanzhou University, Lanzhou, China
• 4 Evidence Based Social Science Research Center, School of Public Health, Lanzhou University, Lanzhou, China

Child nutrition has always been a global concern. This study performed visual analysis of 1,398 child nutrition highly cited papers (HCPs) from 2009 to 2019. The purpose of the study was to evaluate and present the performances of authors, journals, countries, institutions, top cited papers; to explore the hot topics, prospects, and to propose the future research directions on child nutrition. We used bibliometric methods to conduct in-depth statistical analysis of HCPs on child nutrition, showing research progress, trends and hot spots. We included HCPs on child nutrition from the Science Citation Index-Expanded (SCI-E) database February 7, 2020. Two tools, CiteSpace and VOSviewer, were used to conduct the bibliometric analyses. The results showed that, since 2011, the number of HCPs on child nutrition has increased rapidly. The top three contributors in this field were the USA, the UK and Canada. However, the contribution of developing countries was very limited. Intestinal microflora, food allergy, overweight and obesity were the three major research hotspots in this field. Results of this study provide valuable references for ongoing child nutrition related research, which may be interesting and noteworthy to the researchers involved.

Introduction

Child nutrition has always been a global concern. The United Nations International Children's Emergency Fund (UNICEF) released a report in 2019 about children, food and nutrition, entitled “The State of the World's Children in 2019” ( 1 ). The report mentioned that one-third of the world's children under the age of five still cannot get the nutrition they need to grow up currently. At the same time, the burden of malnutrition has become increasingly prominent ( 2 – 4 ). Among the global children under five, there are still 149 million stunted, and nearly 50 million children are in a state of wasting. Three hundred and forty million children face vitamin and mineral deficiencies, which is also known as “hidden hunger” ( 5 ). The problem of overweight is developing rapidly ( 6 ). Lack of necessary nutrients which may weaken the immune system, cause visual and hearing impairments and may also cause obesity. Studies have shown that the average lifetime income loss per child with growth retardation was $ 1,400, and in developed countries, it was as high as $ 30,000 ( 7 ). Overweight and obesity-related diseases, including heart disease, cancer, diabetes, and chronic respiratory diseases, was projected to cost more than $7 trillion in low and middle-income countries between 2011 and 2025 ( 7 – 12 ).

Carrying out scientific research on child nutrition can guide children to take in nutrition reasonably and promote children's healthy growth and development. Black's et al. paper “Global, regional, and national causes of child mortality in 2008: a systematic analysis” conducted a systematic analysis of global causes of child mortality in 2008, and found that nutrition was crucial to guide global efforts to improve child survival ( 13 ). Pries's et al. paper “Snack food and beverage consumption and young child nutrition in low–and middle–income countries: A systematic review” believed that although snacks could provide important nutrients for young children during the complementary feeding period, consumption of energy-dense, nutrient-poor snack foods and sugar-sweetened beverages (SSB) influences undernutrition and overnutrition among young children ( 14 ). Robertson's et al. paper “The Human Microbiome and Child Growth–First 1,000 Days and Beyond” found that an “undernourished” microbiome is intergenerational, thereby perpetuating growth impairments into successive generations, which may contribute to lifelong and intergenerational deficits in growth and development ( 15 ). The results of the above papers have greatly promoted the research on children's health, and have been cited by relevant scholars for many times. Highly cited papers (HCPs) in the Essential Science Indicators database refer to papers with citations in the top 1% of all papers in a research field, and they are considered to be symbols of scientific excellence and top performance of the past 10 years ( 16 ). The identification of HCPs on child nutrition could reflect the research progress and hot topics in this field accurately, which has an important reference to relevant scholars ( 16 , 17 ). Bibliometric analysis is description of the external characteristics of the literature through mathematical and statistical methods, mainly based on the content of published journal papers as the main research object, and descriptive statistics on the academic status, such as journal distribution and main research institutions. Bibliometric analysis is one of the more effective research methods for evaluating the development stage of the discipline and predicting the future development trend ( 18 , 19 ).

Methodology

Data source and search strategy.

We searched the Science Citation Index-Expanded (SCI-E) database on February 7, 2020. The specific retrieval strategy can be found in the Supplementary Material . The initial search yielded a total of 214,264 papers in the period from 1980 to the present. Among them, we chose the selection of “highly cited” in the field. Finally, 1,398 researches were included. There are no limitations on language, publication year, data category, and document type.

Analysis Method

In this research, CiteSpace and VOSviewer tools were used to analyze the publication characteristics, including paper type, language and quantity, active authors, countries and institutions, journals, co-cited journals and co-cited references, co-occurrence keywords and burst keywords, and form social network maps (SNMs) based on the characteristics of the papers published ( 20 – 23 ). Due to the particularity of data format requirements of CiteSpace software, the selected literature was exported in the format of “RefWorks,” the data was saved in the format of “Download_XXX,” and imported into CiteSpace. Set the “Years Per Slice” length to “1,” the “Terms Types” to “Burst Terms,” and the “Pruning” to “Pathfinder.” Meanwhile, the selected literature was downloaded in the format of “TXT” and imported into VOSviewer software. The data type was set to “Create a map based on bibiographic data” and the data source was set to “Read data from bibliographic database files.” Different nodes represent different elements such as authors, countries, institutions, and keywords in a cluster map. The size of nodes indicates the number of publications or co-occurrence times of keywords. The lines between nodes reflects the relations of cooperation, co-occurrence, or co-citations. Nodes and lines of the same color represent the same cluster ( 24 , 25 ). Microsoft Excel 2016 was used to conduct data aggregation and analysis.

Paper Type, Language and Quantity

A total of 1,398 HCPs were retrieved from SCI-E, which includes 944 (67.525%) full-length research articles and 454 (32.475%) reviews. Most of the papers 1,394 (99.714%) were published in English, followed by 2 (0.143%) were published in German and 2 (0.143%) were published in Spanish.

The HCPs on child nutrition were published in 2009 (92 papers) and exceeded 100 papers in 2010 ( Figure 1 ). In 2011, the number of publications decreased (103 papers). Since 2012, the number of publications increased by more than 30 (135 papers) and the growth rate continues slowly and steadily to 2017 (155 papers). The number of publications dropped significantly in 2018 and <100 papers in 2019 (Incomplete statistics). In this study, the relationship between the publication year and the number of publications is described using a polynomial model. There is a significant correlation between the number of studies and the year with a high coefficient of determination ( R 2 = 0.9109).

Figure 1 . Publication years for HCPs on child nutrition.

Active Authors, Countries, and Institutions

The HCPs on child nutrition included 7,868 authors. The top 10 authors and co-cited authors were shown in Table 1 . Tremblay has published the most, 17 (1.22%) papers, following Victora with 14 (1.00%) publications. The third were Lawlor and Bhutta both 12 publications (0.86%), following Black 11 publications (0.79%) and Smith 10 publications (0.72%). The other 4 authors all published fewer than 10 publications. The highest co-cited author was World Health Organization (621 co-citations), the remaining co-cited authors were Ogden (183 co-citations), Victora (135 co-citations), Deonis (132 co-citations), Cole (127 co-citations), Sallis (119 co-citations), Flegal (112 co-citations), and Kramer (107 co-citations). Other co-cited authors both 100 co-citations.

Table 1 . The top 10 authors and co-cited authors [ n (%)].

In total, 113 countries published papers in this study. The top 10 countries and institutions were shown in Table 2 , with the USA ranked first, accounting for 59.87% and the UK ranked second (362 publications, 25.89%), followed by Canada (200 publications, 14.31%), Australia (161 publications, 11.52%), Switzerland (133 publications, 9.51%), Netherlands (127 publications, 9.08%), Germany (113 publications, 8.08%), France (101 publications, 7.22%). The other countries Italy and Spain both published <100 publications. As shown in Figure 2 , the 59 countries with more than 4 papers were divided into 4 categories, with close cooperation among them.

Table 2 . The top 10 countries and institutions [ n (%)].

Figure 2 . The network map of countries.

Countries and institutions with greater influence and the status of cooperation could be displayed through the network maps. Two thousand four hundred eighty-two institutions contributed to the publications of this research. Table 3 showed the top 10 institutions. Harvard University ranked first (85 publications, 6.08%), followed by University of North Carolina (56 publications, 4.01%), University of Washington (48 publications, 3.43%), Center for Disease Control and Prevention (43 publications, 3.07%), University of Toronto (41 publications, 2.93%). The University of California, San Francisco and the World Health Organization published the same amount of papers (40 publications, 2.86%). Duke University and Emory University published the same amount of papers (39 publications, 2.79%). The 10th University of Pennsylvania published 38 (2.72%).

Table 3 . The top 10 journals and co-cited journals [ n (%)].

The cooperation of institutions with more than 10 papers was shown in Figure 3 . Major research institutions were divided into 5 clusters, and close collaboration between the groups.

Figure 3 . The network map of institutions.

Journals, Co-cited Journals and Co-cited References

The study was published in 423 journals. The top 10 journals and co-cited journals, as well as the journal citation frequency, publishing countries and impact factor (IF) in 2019 could be seen in Table 3 . The most published journal was Lancet (95 publications, 6.8%), following New England Journal of Medicine (67 publications, 4.79%), Pediatrics (43 publications, 3.08%), Journal of American Medical Association (37 publications, 2.65%), Cochrane Database of Systematic Reviews (29 publications, 2.07%). Six of the top 10 journals were from the UK and others from the USA. “Citation/N” represents the average citations per paper. The Lancet ranked the highest because the average citation frequency of papers published in the journal was 648.33 times.

Lancet was the most co-citation (2,994 co-citations), followed by The American Journal of Clinical Nutrition (2,620 co-citations) and Pediatrics (2,581 co-citations). Among the top 10 co-cited journals, 7 are from the USA. Table 4 shows the top 10 co-cited references related to this research. The co-citation can reflect the researchers' attention. One paper was co-cited more than 60 times ( 26 ). Two papers were co-cited between 35 and 60 times ( 27 , 28 ). Others were co-cited between 30 and 35 times ( 29 – 35 ). The top 20 HCPs are shown in Figure 4 . Papers with a high frequency of citations are represented by red bars, and with a low frequency of citations are represented by green bars. The first reference with citation bursts appeared in 2009, 85.00% were first discovered between 2009 and 2011. After 2009, 3 HCPs were detected with citation burst.

Table 4 . Top 10 co-cited references.

Figure 4 . Top 20 references with the strongest citation burst.

Co-occurrence Keywords and Burst Keywords

We summarized and counted the keywords from the 1,398 HCPs. Figure 5 showed the visualization of color spectral density based on keywords and hotspot intensity, where warm red represents the hot areas and cold blue represents the cold areas. Children, obesity, health, prevalence, risk, risk-factors, metabolic syndrome, united-states, physical-activity, and adolescents were the keywords with the highest density.

Figure 5 . The density map of keywords.

The cluster map of the main keywords was shown in Figure 6 . Four clusters were formed by these keywords. Cluster 1 was the largest of the four clusters, including 19 keywords, mainly focused on intestinal flora and physical health in children. Cluster 2 included 15 keywords, primarily focused on children's food intake and the prevention of food allergies. Cluster 3 included 14 keywords, mainly focused on the adverse outcomes of children who are overweight or obese. Cluster 4 included 6 keywords, mainly focused on the prevalence of overweight children in the USA.

Figure 6 . The network map of keywords.

The map of burst keywords was shown in Figure 7 to identify hot topics. The time period that represents the strongest citation bursts was indicated in red bar. Among them, 8 keywords were detected in 2009. In this period, Vitamin D supplements, obesity-related complications such as diabetes, coronary heart disease, and the National Health and Nutrition Examination Survey (NHANES) findings were hot research topics. From 2010 to 2014, metabolic syndrome, steatohepatitis, insulin resistance, low birth weight and the establishment of models and environments to promote children's health, were major concerns. After 2014, no prominent keywords were detected.

Figure 7 . Top 20 keywords with the strongest citation burst.

Analysis of Paper Types and Publication Year

There were two types of HCPs included in this study, with reviews accounted for 32.475%. This phenomenon means that a lot of summaries and conclusions has been completed by researchers on the basis of existing research. This was undoubtedly great progress. Thus, we were confident that the number of studies on child nutrition will continue to increase, with greater content in the future. This trend will create more awareness and draw attention to children's nutrition and health globally.

The included HCPs were published from 2009 to 2019. Before 2012, the number of published HCPs was in a state of slow growth, and <130, which suggested that the development of child nutrition research was slow during the period, and researchers did not realize the importance of children's nutrition and health. After 2012, HCPs began to growth slowly and reached peak of 159 in 2016. This may be due to the fact that the WHO Child Growth Standards demonstrate that, by the time children reach the age of five, differences are more affected by nutrition, feeding methods, environment, and health care than by genetic or racial characteristics, and the Ninth Global Conference on health promotion focused on global childhood obesity ( 36 , 37 ). After 2016, the number of HCPs has shown a decreasing trend. In general, the number of publications ranged from 90 to 160 annually.

The Geographical Distribution of Research Group

Among 1,398 HCPs included, 7,868 authors involved. But only 6 (0.08%) authors have published more than 10 papers. Sixty-one (0.78%) authors have published more than 5 papers. Statistical results showed that 6,865 (87.25%) authors published only 1 paper. This reflects that few researchers have been committed to child nutrition and health.

Among the top 10 authors, 3 from Canada, Tremblay, Bhutta, and Chaput. They have published 38 HCPs in total. The reason might be that Tremblay, as a leader, has published many papers on the prevalence and long-term changes in overweight and obesity about Canadian children and adolescents. Tremblay and Chaput have been working closely together and have published several papers on children's physical activity to control overweight and obesity. Among them, Systematic review of sedentary behavior and health indicators in school-aged children and youth , published by Tremblay et al. was cited the most ( 38 ), more than 800 times. Among the top 10 co-cited authors, 5 from the USA, and the total number of citations was 614. Prevalence of Childhood and Adult Obesity in the United States, 2011–2012 , published by Ogden et al. ( 32 ); Prevalence and Trends in Obesity Among US Adults, 1999–2008 , published by Flegal et al. ( 39 ); Maternal and child undernutrition and overweight in low-income and middle-income countries , published by Black et al. ( 27 ); Evaluation, Treatment, and Prevention of Vitamin D Deficiency: an Endocrine Society Clinical Practice Guideline , published by Holick et al. ( 40 ) has been cited more than 1,000 times. This shows that the active and influential scholars are from Canada and the USA. Interestingly, neither the top 10 authors nor the co-cited authors have any scholars from China. Probably because: ( 1 ) Chinese scholars pay little attention to child nutrition; ( 2 ) The number and quality of papers published by Chinese scholars on child nutrition were small; ( 3 ) Chinese scholars had low English proficiency and obvious language barriers. Therefore, in the future, it is important for Chinese scholars to strengthen exchanges and cooperation with outstanding foreign scholars to learn advanced research methods, broaden their horizons and ideas.

Although child nutrition deserves global attention, 24.11% of countries have only 1 highly cited paper. Among the top 10 countries with HCP on child nutrition, all included developed countries and no developing countries, which indicates that developing countries are lagging in this field. Among the top 10 institutions, 8 from the USA and 1 from Canada. This phenomenon showed that the USA was in a dominant position and there was a large gap between developing and developed countries in child nutrition research. In short, the global impact of developing countries on child nutrition is limited. There was need for collaborative efforts between high income countries and Low and Middle income countries (LMIC) to improve and carry out more high impact research in the areas of child nutrition especially among children in LMIC.

In terms of cooperation between countries, both the USA and the UK maintain close cooperation with 55 countries, Canada and Switzerland with 54 countries, respectively, followed by Australia and Belgium with 53 and 50 countries, respectively, while Slovakia did not cooperate with any country. It was noteworthy that, China has partnerships with 48 countries, so we are confident that China will be at the forefront on child nutrition in the future.

Analysis of Published Sources

The included 1,398 HCPs were published in 423 journals, each journal should publish an average of 3.30 papers, but in fact, 6.38% of journals published more than 10 papers and 58.16% of journals only published 1 paper. Four major journals published 242 papers, accounting for 17.32%. These journals were as follows: Lancet (6.80%), New England Journal of Medicine (4.79%), Pediatrics (3.08%), Journal of American Medical Association (2.65%). The Lancet was the journal with the most productive and cited researches of HCPs on child nutrition. Among the authors, Black et al. ( 27 ) and Ng et al. ( 30 ) from the USA published many papers, and have been cited 2,568 times and 5,253 times, respectively. The unprecedented World Summit for Children, held at the United Nations headquarters in New York City in 1990, set out 10-year goals for children's health, nutrition and education ( 41 ); the special session on children held in 2002 reviewed the progress made in children's affairs since the 1990 World Summit for Children and reinvigorated the global commitment to children's rights ( 42 ). Through holding these international conferences, scholars have developed great interest on child nutrition, which has also aroused scholars' attention.

Among the top 10 journals, six were from the UK and none from China, which once again confirms the huge gap in scientific research between developing and developed countries. Citation/N is an important index to measure the scientific importance or quality of a paper. It also shows that the quality of the journal is high and the content is attractive. The American Journal of Allergy and Clinical Immunology performed well. This journal were recognized and welcomed by scholars, because although the journal published only 21 HCPs, the citation /N was high, which also shows the high academic influence of the journal.

Analysis of the Main Keywords

Intestinal flora and physical health.

In this study, one of the important research hotspots and directions was the composition and roles of intestinal microbiota in children ( Figure 6 , cluster 1). There are a large number of bacteria in the human gut, which together make up the intestinal flora. In the human body, cells and bacterial cells are symbiotic, and there are 10 times as many bacterial cells as there are human cells ( 43 , 44 ). The effects of intestinal flora on the human body are mainly manifested as nutrient absorption, substance metabolism, and immune defense ( 45 ). Some minerals, such as calcium, iron, and magnesium, are absorbed by the body through the intestinal flora ( 46 ). The intestinal flora is also involved in the metabolism of certain substances by fermenting food, synthesizing exercise fatty acids and vitamin K, which are then absorbed by the body ( 47 ). For children, intestinal bacteria can not only regulate the activity of cytotoxic T cells and natural killer cells, reduce the replication of viruses in cells, but also play an important role in innate immunity, activation of the immune system and the formation of an adaptive immune response ( 48 , 49 ). Probiotics can significantly increase the expression of CD3 + CD4 + in children with severe HFMD caused by EV71, enhance the immune function of T cells and improve the cellular immune response of children. Therefore, intestinal flora plays an important role in children's growth. Gao et al. considered that the diversity of intestinal microflora in obese children was lower than that in normal children, and the relative abundance of intestinal flora at different classification levels was significantly different ( 50 ). Some studies have shown that the mode of delivery affects the bacterial community in the newborn gut. Guarino et al. noted in cesarean delivery, direct contact of the mouth of the newborn with vaginal and intestinal microbiota is replaced by exogenous non-maternally derived bacteria colonizing the infants' intestine producing a less diverse flora ( 51 ). Biasucci et al. believed that intestinal bacterial colonization of infants born by cesarean section is more likely to change ( 52 ). However, Rutayisire et al. considered that the diversity and colonization pattern of intestinal flora were significantly correlated with the mode of delivery 3 months before birth, but the difference disappeared after 6 months ( 53 ). Therefore, the diversity and colonization level of intestinal microflora and the mode of delivery as well as its extensive impact on the health of infants at all stages of life should be further studied.

Prevention of Food Allergies

Food allergies are common and affect about 8% of children in the United States. It brings a huge physiological, economic and social burden to children and families. There is no cure for food allergies ( 54 ). Therefore, the prevention and treatment of food allergy in children is also a key topic in recent years ( Figure 6 , cluster 2). Food allergies can be a variety of symptoms in children, with skin and gastrointestinal symptoms being the most common ( 55 ). Children under the age of 6 are often allergic to high-protein foods such as eggs, milk, peanut, and soy, as children's immune systems are not yet mature and the protective function of the gastrointestinal mucosa in infants is not perfect ( 56 ). Food allergies have a significant impact on the morbidity, living quality of infants and young children, which has become a concern for many parents ( 57 ). Peanut is one of the most common food allergies in children, which is becoming more and more common over time. So far, there is no effective treatment for peanut allergy, only through the use of epinephrine to avoid and alleviate this symptom. The double allergen exposure hypothesis suggested that the dermal sensitization of peanut may be the pathophysiological mechanism of peanut allergy development. In the future, oral and epicutaneous immunotherapy may be used as exciting tools to achieve peanut desensitization in children. In the past, people focused on the treatment of food allergy, but seldom considered the mental health consequences of living with the condition ( 58 , 59 ). Feng et al. found that patients with food allergy may have depression, anxiety, post-traumatic stress, being bullied, and poor overall quality of life. At the same time, the patient's family life will also be disturbed ( 60 ). Parents of children with food allergies, especially mothers, report anxiety, depression, and decreased quality of life ( 61 ). Fong et al. stressed that children and adolescents with food allergies in the Australian population are vulnerable to bullying. It's a significant social problem that requires addressing to positively assist these children ( 62 ).

At present, in the treatment and prevention of food allergies, bacterial therapy has attracted more and more attention from scholars. They believe that one of the effective ways to prevent allergic diseases is fecal flora transplantation ( 63 , 64 ).

Overweight or Obesity in Children

At present, childhood obesity is also widely concerned ( Figure 6 , cluster 3 and cluster 4). In 2017, the WHO announced that the number of obese children and adolescents aged 5 to 19 worldwide has increased ten-fold in the past 40 years. If the current trend continues, the number of obese children and adolescents will exceed the number of moderately or severely underweight by 2022 ( 64 ). American children's obesity rate ranks first in the world. Children with obesity may develop many serious comorbidities. These diseases include musculoskeletal diseases, cardiovascular diseases such as hypertension, insulin resistance and hyperlipidemia, respiratory diseases such as sleep apnea or asthma, and digestive system diseases such as non-alcoholic fatty liver disease ( 65 , 66 ). Childhood obesity has a greater risk of persistence in adulthood. Low socioeconomic status, immigration background, and clinical susceptibility to obesity are the serious risk factors for obesity. However, the individual causes of obesity are quite complex, so it is necessary to make a systematic analysis of individual differences, and to formulate differentiated and realistic treatment plans. In addition to the rare monogenic or syndromic obesity, the treatment of childhood obesity should rely on professional lifestyle intervention programs. In general, a key component of a treatment strategy should include improving nutrition, physical exercise and self-esteem, while reducing stress. Besides, the inclusion of parents in treatment strategies has proved beneficial and necessary. Studies have shown that male children are 1.6 times more likely to be overweight/obesity than female children; children of overweight mothers are 3.34 times more likely to be overweight/obesity than children of normal weight mothers; preschool children's overweight/obesity is related to physical activity, screen time, eating snacks when watching TV, using computers, tablets and mobile phones ( 64 ).

Considering the individual differences between obese children and the complexity of obesity, there is no effective treatment for all groups. The most appropriate intervention method is determined by the age of children and the degree of overweight. The current methods of weight loss include lifestyle change interventions, bariatric surgery and drug use. Lifestyle change is the most widely used way to treat childhood obesity ( 67 ). This approach is designed to improve the quality of diet, increase physical activity and reduce sedentary behavior, usually using behavior change techniques to help maintain positive change and prevent recurrence. Many interventions focus on families, and parents are defined as “agents of change,” especially among children under 12 ( 68 ). Bariatric surgery generally includes gastric shunt, sleeve gastrectomy and gastric banding ( 69 ). Currently, the drugs used to treat obesity include: ( 1 ) Sibutramine, an appetite inhibitor, which is still allowed in Brazil, was suspended by the European drug agency in 2010 due to its adverse cardiovascular effects, and was withdrawn by the US Food and Drug Administration (FDA) in 2010; ( 2 ) Orlistat, a fat absorption inhibitor, has been approved by the FDA, but only for children under the age of 12. Other drugs often used to treat childhood obesity include the antidiabetic drug metformin and the antidepressant fluoxetine ( 67 ). New drugs for appetite regulation are currently under development or evaluation.

Conclusions

At present, more and more researches on child nutrition have been published. The bibliometric method could be used to systematically analyze the characteristics of the papers and show the research status, hot spots, and future development trends. The results showed that 6,865 authors (87.65%) only published 1 paper. Scholars from the UK, the USA, and Canada had a greater academic influence. Scientific research institutions from the USA contributed the most. Strengthening academic exchanges and cooperation is the top priority for future development. Although great progress has been made, further research is needed to understand most of the unknown problems. Combining the above research results, the future development direction of children's nutrition research is put forward:

It has been concluded that the mode of delivery will affect the bacterial community in the intestinal tract of newborns. However, it is still controversial whether the adverse effects will last into childhood or even adulthood. Further research should be carried out in the future, because the results may affect pregnant women's choice of delivery mode.

Food allergies have a significant impact on the morbidity, living quality of children, but there is no effective treatment. The future research should focus on the induction of food allergy in children, the causes of sensitization, clinical manifestations, prognosis, precautions and so on, to solve this scientific problem.

Strengthen the research on the causes, types, prevention and targeted intervention measures of overweight or obesity in children. A large number of studies predict that the number of overweight or obese children will continue to increase in the future. Therefore, we should better understand the source of obesity and control the number and type of obesity children from the source.

Strengths and Limitations

According to our knowledge, this study is the first bibliometric analysis of highly cited articles on child nutrition. Therefore, the study is original. This study not only provide a historical perspective for future research, but also highlight research areas requiring further investigation and development. In addition, before literature search, we read a large number of high-level papers and extracted search terms related to child nutrition. After integration, we formulated the search strategy for this study. Therefore, the search strategy is complete and scientific. Of course, this study also has some shortcomings, the WOS database is considered the most critical data source in bibliometric analysis, so we only searched it ( 70 ), some studies may have been overlooked. Besides, there are many authors in this study, some authors may have the possibility of renaming or having the same author from different institutions. Although we have carefully proofread the process, some mistakes are inevitable.

Author Contributions

JW designed this study. YW, QL, and YC performed search and collected data and wrote the manuscript. YQ rechecked data. BP and QW performed analysis. LG rechecked. JW and GD reviewed the manuscript. All authors contributed to the article and approved the submitted version.

This work was supported by the National Research Project Development Plan of Gansu Provincial Hospital (19SYPYB-18); Lanzhou Chengguan District Science and Technology Plan Project (2019RCCX0011).

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fped.2021.633525/full#supplementary-material

Abbreviations

HCPs, highly cited papers.

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Keywords: child nutrition, bibliometric analysis, highly cited papers, intestinal microflora, obesity

Citation: Wang Y, Liu Q, Chen Y, Qian Y, Pan B, Ge L, Wang Q, Ding G and Wang J (2021) Global Trends and Future Prospects of Child Nutrition: A Bibliometric Analysis of Highly Cited Papers. Front. Pediatr. 9:633525. doi: 10.3389/fped.2021.633525

Received: 25 November 2020; Accepted: 16 August 2021; Published: 09 September 2021.

Reviewed by:

Copyright © 2021 Wang, Liu, Chen, Qian, Pan, Ge, Wang, Ding and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Jiancheng Wang, wangyh2415@126.com

† These authors have contributed equally to this work and share first authorship

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Article Contents

Introduction, school-age health and nutrition terminology and knowledge gaps, specificities of growth and development in school age, role of nutrition in school age, global status of nutrition in school age, recovery from nutrient deficiencies, growth faltering, and cognition in school-age children, revisiting priorities, acknowledgments.

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Nutrition in school-age children: a rationale for revisiting priorities

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Jose M Saavedra, Andrew M Prentice, Nutrition in school-age children: a rationale for revisiting priorities, Nutrition Reviews , Volume 81, Issue 7, July 2023, Pages 823–843, https://doi.org/10.1093/nutrit/nuac089

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Middle childhood and early adolescence have received disproportionately low levels of scientific attention relative to other life stages, especially as related to nutrition and health. This is partly due to the justified emphasis on the first 1000 days of life, and the idea that early deficits and consequences may not be fully reversible. In addition, these stages of life may superficially appear less “eventful” than infancy or late adolescence. Finally, there has been historical ambiguity and inconsistency in terminology, depending on whether viewing “childhood” through physiologic, social, legal, or other lenses. Nevertheless, this age bracket, which encompasses most of the primary education and basic schooling years for most individuals, is marked by significant changes, inflection points, and sexually driven divergence in somatic and brain growth and development trajectories. These constitute transformative changes, and thus middle childhood and early adolescence represents a major and last opportunity to influence long-term health and productivity. This review highlights the specificities of growth and development in school age, with a focus on middle childhood and early adolescence (5 years–15 years of age, for the purposes of this review), the role of nutrition, the short- and long-term consequences of inadequate nutrition, and the current global status of nutrition in this age group. Adequate attention and emphasis on nutrition in the school-age years is critical: (a) for maintaining an adequate course of somatic and cognitive development, (b) for taking advantage of this last major opportunity to correct deficits of undernutrition and “catch-up” to normal life course development, and (c) for addressing the nutritional inadequacies and mitigating the longer-term consequences of overnutrition. This review summarizes and provides a rationale for prioritizing nutrition in school-age children, and for the need to revisit priorities and focus on this part of the life cycle to maximize individuals’ potential and their contribution to society.

The last three decades of academic and public health efforts have enthusiastically embraced the importance of early life nutrition as a foundational component of lifelong health. The gestational period through the first 2 years of age (the first 1000 d) and early childhood through 5 years of age have received justified attention over the last few decades. However, the ultimate realization of an individual’s potential requires a successful bridging from early childhood to adulthood. The subsequent periods in the life cycle—5 years to 9 years of age, referred to as “middle childhood,” and 10 years–15 years, “early adolescence”—are commonly encompassed in the “school years.”

Middle childhood and early adolescence bridge the period between the relatively steady growth occurring from 2 years to 5 years of age and the final maturation period of late adolescence to adulthood. This period is characterized by multiple dramatic inflection points in the course of growth and development, as well as behavioral and psychosocial events occurring around the arrival of puberty. These inflections represent transformational changes in the brain and cognitive processing, linear bone growth and bone mineralization, body composition, and other organ systems. It is also during this period that major sex-driven inflections and divergences occur in growth and development. The nutrition of children during this period is critical for supporting these changes. In addition, can help overcome early deficits, and may help correct dietary excesses that have been occurring since infancy. Thus, school age constitutes a final major window of opportunity to influence growth and development, and the associated health consequences in mature life.

Unfortunately, relative to other life stages, school-age nutrition has received a disproportionately low level of scientific attention, in part due to a misleading but widespread perception that early deficits in growth and development cannot be rectified. In the last few years, scientific, public health, and other academic voices have been calling attention to this life stage as a critical and potentially last major window of opportunity for intervention in maximizing the potential of individuals as productive members of society. 1–5

This aim of this review was to highlight the critical growth, developmental, and nutritional aspects of these transformative school-age years, and the challenges and gaps in knowledge around these, and to provide arguments for why nutrition during school age deserves greater and more focused attention to maximize individuals’ growth, development, and ultimate productivity.

To achieve this aim, a comprehensive review of the literature was conducted, using PubMed to identify eligible and relevant publications through 2021. Papers were identified by combining the following Medical Subject Heading keywords: children, school age, middle childhood, adolescence, nutrition, nutrients, growth, development (multiple aspects/organ systems), malnutrition, stunting, overweight, and obesity. Literature was selected and prioritized that included information and data for the 5–15-year age group, primarily based on population, cohort, or epidemiologic studies and reviews, as well as literature addressing biologic aspects of specific areas of growth and development for this age group, with a focus on somatic growth, body composition, and neurologic development. Nutrition- and diet-related behavioral, psychologic, or social aspects were not included in the scope of this review.

Compared with the nutrition and health research literature for other life stages, there is a historical neglect of middle childhood and adolescence. Estimates of the published literature describing child health (PubMed sources 2005–2016) show 95.3% of this literature is dedicated to early childhood (<5 y), 3.5% to 5 years–9 years, 0.55% to 10 years–14 years, and 0.61% to 15 years–19 years. 6 The health and nutritional status of school-age children, particularly that during middle childhood, remains the least studied of all life stages.

Public databases of most agencies track rates of malnutrition, stunting, and other health markers for children, but usually do so only until 5 years of age, and only pick up again during adolescence or adulthood. 7 Regional or international databases of nutritional data for middle childhood (5 y–10 y of age) are extremely scarce. Many reviews for this age group rely on extrapolations, eg, using Demographic and Health Surveys (DHS) data for children 4 years–5 years of age 8 or including data of 10-year-olds to 14-year-olds within child surveys. 9 On the other end of school age, most research and data for children 10 years–15 years (early adolescence) is sometimes conflated with the data of adults, eg, Multiple Indicator Cluster Surveys (MICS) and DHS data for females 15 years–19 years. As discussed below, research, particularly concerning child growth and cognition, led to the notion that the consequences of nutritional and environmental insults in the first 2 years of age were irreversible. This may have resulted in reduced interest and research bias, due to underestimating the significant potential for growth and developmental catch-up possible during middle childhood and adolescence.

In part, inadequate research in this age group is also due to ambiguity, inconsistency, and overlapping terminology, resulting from viewing this age group through different lenses: physiologic, reproductive, social, legal, or school system, etc. Terms such as “early childhood,” “middle childhood,” “late childhood,” “school age”, “adolescence,” and “young adulthood” often overlap. From the general physiologic point of view, “middle childhood” (ages 5 y–9 y) is a period of growth and consolidation, followed by an adolescent growth spurt (ages 10 y–14 y), each associated with specific behavioral changes, before a final growth consolidation (ages 15 y to early 20s), and subsequent maturation into adulthood. 1 More broadly speaking, the developmental stages in the life cycle have been classified into 3 main categories: physical growth, cognitive development, and socioemotional/psychosocial development. 10 And while interdependent, the rate of progress for each of these life-stage categories can vary individually, making it hard to propose a purely chronological or age-based approach.

Many organizations and legal systems define “child” as an individual 0 years–18 years. 8 , 11 WHO defines an “adolescent” as aged 10 years to 19 years, “youth” in general as 15 years–24 years, and “young people” covers 10 years–24 years. 2 , 12 More recently, a broader definition for “adolescence” has been advocated as including the entire 10-year-old to 24-year-old group within the term. As explained by the 2016 Lancet Commission on Adolescent Health and elsewhere, 9 , 12 this would support consideration of appropriate social and economic policies, service systems, and legal frameworks for this broad age group. While useful for certain objectives, this approach fails to distinguish the significant differences between the transitional aspects of development (and therefore the distinct difference in needs) of early adolescence versus late adolescence. Others support the use of “young people” (not “adolescents”) as a term for all 10–24-year-olds, distinguishing “adolescents” (10 y–19 y) from “young adults” or “emerging adults” (20 y–24 y). And some suggest that considering people in their early 20s as adolescents could lead to underestimating their competencies and capabilities. 13 Clearly, no definition should be rigid. Approaches to defining “school age” and “adolescence” can vary by setting and should consider the cultural and societal context.

Schools are a significant platform, not always adequately utilized, for delivering nutrition as well as education in nutrition. “Schooling” plays a role as a defining factor in a person’s development, includes what is generally called “primary” and “secondary” schooling, and is quite variable from country to country. Globally, most children in primary school are between 5 years and 14 years of age, and there tends to be late entry into school in low- and middle-income countries. Many consider that “high school” and “preparatory school” fall into this category; others do not. Schooling provides opportunities for promoting nutrition and health. Research and interventions can leverage society’s investment in education and take advantage of the potential synergy between health and education investments. 1 , Figure 1 summarizes the terminology most commonly used for childhood growth and developmental stages. Acknowledging there is no perfect life-stage categorization, given the physiologic and growth changes, most agree that data should be disaggregated for 5 years–9 years (middle childhood), 10 years–14 years (early adolescence), 15 years–20 years (late adolescence), and 20 years–24 years (older adolescents or young adults). 1 , 9 ”School age” defined as comprising “middle childhood” (5 y–9 y) and “early adolescence” (10 y–15 y) will be the age group of focus and the terminology used in this paper.

Major developmental life stages (in gray) and commonly used terminology for specific developmental stages as related to age . Modified and adapted from Bundy et al 2017 1 and Sawyer et al 2018 9

What makes school age of particular significance nutritionally is that it encompasses numerous changes in trajectory from the relatively steady growth of the preschool child, through sex differentiation, and into the final consolidation period of late adolescence. These changes are driven by pubertal onset and course, with population variations primarily dependent on genetic, environmental, and nutritional factors. Pubertal sex hormone secretion will also determine changes in growth rate and growth termination. However, much work still remains to be done in understanding the underlying genetics, the timing of puberty (including early-life determining factors), growth variability during puberty, and adiposity and weight gain. 14

Two specific processes contribute to the sex-differentiating physical developmental changes during this period: adrenarche and gonadarche. Adrenarche occurs between 6 years and 8 years of age, earlier in girls and later in boys, and refers to the maturation of the adrenal cortex and increased secretion of adrenal androgens, namely dehydroepiandrosterone. It is involved in the development of pubic hair (pubarche), body odor, skin oiliness, and axillary hair. Gonadarche is initiated by specialized neurons of the hypothalamus that secrete gonadotropin-releasing hormone (GnRH) in a cyclical pattern that regulates the release of follicle-stimulating hormone (FSH) and luteinizing hormone (LH) by the anterior pituitary, leading to gonadarche, starting at around 9 years–10 years of age in girls, and around 10 years–12 years in boys. In girls, FSH stimulates estrogen production, follicle formation, and eventually ovulation and menarche. In boys, LH stimulates testosterone production and eventually maturation of spermatozoa.

Finally, these changes during middle childhood and early adolescence are directly related to a differentiated phase of social learning and experimentation, heralding shifts in cognition, motivation, and social behavior, with significant implications for the ultimate development of each child’s personality. These shifts encompass major domains such as the development of independence and decision-making, acquisition of cultural norms, increase in complex moral reasoning, increase in understanding of social hierarchies, increase in sense of gender identity, gender segregation, and romantic attraction, as well as changes in food preferences and dietary habits, the expansion of which are beyond the scope of this paper. 15

These growth and change phenomena and influential factors are interrelated, and nutrition plays a fundamental role. Protein-energy malnutrition is associated with delayed puberty, and subsequently poor growth and development. Secular trends have changed the timing of these processes in different populations, likely reflecting nutrition and health changes in the last century. In Europe and North America, from the early 19th century to the mid 20th century, age at menarche decreased from approximately 17 years to about 12 years–13 years. 16 In China, in just the past 25 years, the mean age of menarche has decreased by 4.5 months per decade. 17 As discussed below, changes in growth patterns, particularly in height and body–mass index (BMI), are interrelated with the onset of puberty. Increases in height and BMI are associated with an earlier onset of puberty, and earlier puberty is associated with an increased rate of later obesity. 14 Obesity, which has risen dramatically in children, is associated with a shift towards earlier onset of puberty, particularly in girls; the situation is less clear in boys. 16

The course of sex hormone secretion will determine the termination of growth during late adolescence into adulthood. The pubertal process is usually complete 2 years to 4 years after physical changes begin to occur. However, physical maturation will continue into the third decade of life. For instance, bone and brain development continues into the 20 s. Hormonal differences during puberty will also affect the size and function of organ systems related to aerobic and anaerobic physical fitness. Heart size and cardiac function, lung size, bone development, muscle volume and strength, erythropoiesis, and substrate utilization will diverge and determine different ultimate fitness and strength levels. 18

Puberty happens in the middle of the school-age years and marks and determines the changes in trajectory and the switch in somatic and brain growth and development rates, which characterize this part of the life cycle. Two significant phenomena arise in this period:

Several inflection points and trajectory changes occur in somatic and brain growth and development, at different time points, for various measures of development (eg, height, adiposity, lean mass accretion, bone mineralization, brain growth and reorganization, with subsequent cognitive development, and secondary sexual characteristics) and social and behavioral changes

Sex divergences appear or become significantly more pronounced in these measures.

The dynamic somatic, cognitive, and behavioral changes that occur during school age underscore the importance of preparing children during middle childhood and facilitating their transition into adolescence during this period. Figure 2 shows the changes in trajectory for key anthropometric changes during the school years.

Growth trajectories in school-age years (gray-shaded area) . Fat and fat mass: estimates. All others are medians . Compiled and adapted from Tanner and Davies 1985 24 (height velocity), Weaver et al 2016 33 (BMC gain), Veldhuis et al 2005 21 (fat and fat mass), US CDC 19 (BMI). BMC: bone mineral content; BMI: body–mass index

Body composition

Although height velocity decreases during the preschool years, height gain remains relatively steady, and the amount of body fat remains relatively constant; therefore, most children in middle school will appear slimmer than when they were toddlers. In fact, median BMI will be at its lowest in life at about 5.2 years in girls and at about 5.75 years in boys, ie, just as they enter school age. 19 During this period, a child’s adiposity (corresponding to an increase in number of adipocytes) will rise, giving way to what is called the “adiposity rebound” or second rise in BMI during life. BMI, a reflection of adiposity, is the first anthropometric inflection point to appear in the school-age years. 20

The age at which this inflection happens is inversely proportional to their BMI percentile (children with higher BMI will rebound earlier). Furthermore, an earlier adiposity rebound is associated with a higher risk of later obesity. As mentioned above, secular trends show an interplay between nutritional status and puberty. In addition, overweight and obesity in girls will lead to earlier puberty. Boys, however, show a less clear pattern: overweight boys seem to mature earlier, but obese boys mature later. The mechanisms are not yet clear, and there appears to be a bidirectional influence between puberty and weight gain. 16

Body compositional changes during the school years also mark significant changes in trajectory and sex divergence. Large-scale normative data for body compositional changes for middle childhood and early adolescence are lacking, although some estimations and extrapolations have been done. Fat mass, fat-free mass, and percentage body fat have been estimated by aggregating data from several cross-sectional analyses from European and American populations. 21 During the preschool years, actual fat mass in kilograms is similar in both sexes. Between 5 years and 10 years, girls will accumulate fat mass faster than boys, gaining approximately 6% (2 kg) more than boys. After this, with the onset of puberty, girls will gain about 1.14 kg of fat, while boys will maintain a relatively fixed fat mass. Throughout the school years, until 15 years, girls will have increased their fat mass almost 5-fold, while boys will have increased theirs by around 3-fold. Ultimately, fat mass will increase from 10%–12% of body weight at birth to approximately 15% in young men and approximately 25% in young women. In boys, after a prepubertal increase in percentage body fat, this percentage actually declines with puberty and stabilizes with maturation. 21 The rate of accumulation of fat-free mass (including muscle mass) remains comparable by sex until the onset of puberty. With the onset of puberty, boys will accumulate lean mass significantly faster and for a longer period than girls. Gains in adipose tissue are primarily driven by an increase in the number and size of fat cells, while muscle development happens mainly by an increase in muscle cell mass (hypertrophy). The increase in body weight gain during puberty is mainly attained through an increase in lean tissue in boys.

Skeletal muscle mass, which represents about 25% of body weight at birth, will increase to 40%–45% body weight in late adolescence. 18 , 20 Girls will reach adult stabilization by 15 years–16 years, while boys will do so by 18 years–20 years. 21 Skeletal muscle mass has been estimated for children of school age using appendicular lean tissue mass extracted from dual photon absorptiometry measurements 22 and bioelectrical impedance. 23 Both approaches show that muscle mass and rates of gain are similar in both sexes until middle childhood. At around 5 years of age, boys maintain a slightly higher muscle mass, and girls a higher fat mass, after which trajectories increasingly diverge. This results in an approximately 3.5–5-fold increase in muscle mass in boys and a 3–4-fold increase in muscle mass in girls between 5 years and 15 years, in part depending on the methodology used. Conversely, fat mass will increase more in girls than in boys during this period.

Height and linear bone growth

The increase in height gain is the most noticeable change in trajectory in anthropometric measures of the school years. About 40% of an individual’s linear growth will occur during this time. Based on the United States CDC growth curve medians, by 5 years of age, boys and girls will, on average, be at 61% and 65%, respectively, of their ultimate height. By 15 years, they will be at 96% and 99%, respectively of ultimate height. 19 There are major differences between the first 5 and second 5 years of school age.

During middle childhood, height velocity actually decreases, to the lowest levels of the entire life cycle, only to quickly increase in the middle of the school years to the highest rate of linear gain of all post-infancy years. In North America, CDC growth velocity charts 19 show median height velocity will be at its lowest since birth just before 9 years of age in girls and at approximately 10.5 years in boys. At that point, before the puberty-related acceleration, both girls and boys will have reached ∼80% of their final height. Thus, height at that point will be a strong predictor of ultimate height in most individuals. This speaks to the importance of adequate nutrition and sustained growth between 5 years and 10 years of age.

With the onset of puberty, height velocity rapidly increases. In early adolescence, median peak height velocity in girls reaches its peak at around 11.5 years of age, with growth rates similar to those at 2 years of age (∼8.3 cm/y). In boys, a peak growth rate of about 9.5 cm/year happens at around 13.5 years of age, surpassing the 2 years of age rate of height attainment. 24 In girls, this growth spurt starts earlier (∼9 y in girls vs ∼10.5 y in boys) and ends earlier (∼11.5 y vs ∼13.5 y), lasting at least 0.5 years less than in boys. The ultimate median height in males will be greater due to greater height at the onset of puberty (boys ∼9 cm–10 cm taller than girls), a more prolonged growth spurt period, and a greater increase following pubertal onset (boys gaining ∼3 cm more than girls between the onset and end of the growth spurt). The pubertal growth rate declines rapidly after their gender-specific peak in both sexes, to 1 cm/year or less after 14.5 years in girls and 17 years in boys. 21 , 24

Height gains are dependent on longitudinal bone growth determined by epiphyseal growth plate function. Growth plate chondrocytes proliferate by mitosis, mature, become hypertrophic, lengthen the bone, and ultimately replace osteoblasts to form new calcified bone tissue. Growth hormone and insulin-like growth factor are the key hormonal drivers of this process. Adequate nutrition is critical for providing substrates for epiphysial growth, particularly energy, protein, and zinc. Calcium and vitamin D may play lesser roles in longitudinal bone growth. Very importantly, independent of nutrient provision, bone growth regulation can be blocked by corticosteroids and inflammatory cytokines. Chronic inflammation from infection, environmental factors, autoimmune disease, and the use of corticosteroids can all curtail linear bone growth. In addition, inflammation can lead to insulin and growth hormone resistance, which can further inhibit linear bone growth, thus compounding the effect of undernutrition, as often occurs in underserved populations. 25–27 As discussed below, poor linear growth and stunting (two standard deviations beyond the normal curve median) remain the most prevalent clinical manifestation of undernutrition globally. 28

Bone mineralization

Linear bone growth is followed by increases in bone mass and bone mineralization. Bone matrix becomes mineralized with the deposition of calcium phosphate nanocrystals (carbonated hydroxyapatite). The degree of deposition will determine bone mineral content (BMC), measured in grams, for a specific skeletal location or for the total body. This sequence of events will be similar, with variations by sex.

Total BMC will rapidly increase in early adolescence. Data derived from North American individuals show that by the end of middle childhood, prior to the onset of the growth spurt (2.5 y to 3 y before peak height), children will have achieved 37%–40% of ultimate total body BMC. In the short period between the 2 years before and 2 years after peak height is attained, another 39% of ultimate BMC is accrued. By the end of school age, more than 80% of total body BMC will have been attained, and final total body BMC appears to plateau at around 18 years of age in girls and 20 years in boys. 29 , 30

Similar to height gain, the BMC accretion will increase rapidly with the onset of puberty, and the median peak rate of BMC accretion will occur at around 12.5 years in girls and 14 years in boys. Thus, the peak BMC accretion rate will lag compared with the peak height velocity, which occurs at around 11.5 years and around 13.5 years in girls and boys, respectively. Therefore, there is a transient decrease in bone density relative to height and bone elongation, and consequently an increase in bone fragility lasting about 12 months in girls and 6 months in boys (see Figure 2 ). This may partially explain the higher rate of forearm fractures reported in girls between 8 years and 10 years, and in boys between 10 years and 12 years. 30 , 31

Ultimate bone mass, measured as bone mineral density (BMD) or mineral content divided by bone area, will depend on genetic and environmental factors. Studies in twins suggest that genetics can explain 50%–85% of the variance in peak bone mass, with multiple genes being involved, some of which may interact with environmental factors, including diet. 32 Thus diet and “lifestyle” factors, including exercise, can still significantly influence BMC and BMD. As stated above, middle childhood and early adolescence are the periods of fastest mineral accrual, and more than 90% bone mass is achieved by 18 years–20 years. By the late 20s, bone mass will begin a gradual process of decline, leading to varying degrees of osteoporosis, which can only partially be modified by diet and other environmental factors. It follows that school age becomes a critical age of intervention and “investment” in bone health by maximizing peak bone mass and decreasing the risk of fractures in later life. This includes optimizing nutrition, particularly provision of protein, calcium, and vitamin D, as well as activity and exercise during this life stage. 31 , 33

Brain and cognition

Brain size increases by 4-fold during the preschool years, reaching approximately 90% of adult volume by age 6. 34 However, brain development will be a continuous process with age-specific phases until adulthood. The growth rate of cortical gray matter peaks during school age, by 10 years–12 years of age. Cerebral white matter volume increases through school age until mid-to-late adolescence, peaking by 18 years–20 years. 35 , 36 Total brain size is about 9% greater in males than females, and the difference persists, even if controlling for height and weight. These differences should not be understood as conferring advantage or disadvantage, as they do not represent neuronal or synaptic connectivity or other components of brain architecture and function (see Figure 3 ). 37 , 38

Neuromaturational and cognitive development trajectories in school-age years (gray-shaded area) . Compiled and adapted from Peterson et al 2021 38 (brain and gray matter growth), Tapert and Schweinsburg 2005 114 (neuromaturation process rate), Lee et al 2014 115 (brain region development), and Anderson 2002 46 (cognitive development executive domains)

During the school years, though at a slower rate than during the preschool years, total brain size increases, as does the sex-driven divergence, with boys being faster and peaking by 14.5 years, and girls peaking earlier by 11.5 years. 37 During this period, brain development is also marked by a significant increase in 2 major neuro-maturational processes: continued myelination and an increase in synaptic refinement and pruning, both of which are important for the efficiency of neuronal networks. Dendritic synaptic pruning eliminates unused or weak connections, and a reduction in myelination rates improves connectivity. This fine-tuning within and between brain regions strengthens a number of particular pathways, which increases brain efficiency, critical to the development of cognitive abilities. 39 , 40

School age will be marked by the highest rate of development of specific areas of the brain, particularly the posterior sensorimotor cortex, temporal association complex, and prefrontal cortex, and this development peaks at between 5 years and 15 years of age, in the middle of school age. All these areas are “associative cortices,” which process input from the sensory cortices and ultimately generate behaviors (see Figure 3 ). These structures are the key determinants of higher-order functions, particularly cognitive development (including language, mathematics, and executive function [EF]) and socio-emotional regulation, which among other things, allows for organization of information to serve goal-directed behaviors, decision-making, peer affiliation, and social behaviors. 41 , 42 The parietal and temporal association cortex, responsible for language skills, also develops at a fast rate and this development peaks during school age. For example, language acquisition and proficiency, especially the ability to master a second language as a native speaker, decreases at the end of school age, by 15 years of age. 43

The development of the prefrontal cortex peaks in the middle of the school years and continues to mature into the third decade. The gray matter volume in the frontal cortex peaks at 11 years of age in girls and at just after 12 years in boys. 44 This part of the brain supports higher-level integration and processing, allowing for abstract thinking, problem-solving, understanding others’ thoughts and intentions, and the relating of thoughts temporally, allowing for goal setting. Thus, the prefrontal cortex is generally regarded as the “seat” of EF. EF is a broad term that incorporates a collection of mental processes that (a) enable individuals to hold and recall relevant information (working memory), (b) focus their attention, inhibiting automatic responses to stimuli (inhibitory control), and (c) shift the focus of attention to the managing of problems or multiple-aspect tasks successfully (cognitive flexibility), to yield purposeful, goal-directed behaviors. Ultimately, these processes influence behavior, emotional control, and social interaction. EF is associated with academic performance as well as intelligence quotient (IQ). 42 , 45 , 46

One well-recognized model of EF conceptualizes and maps chronologically 4 distinct and interrelated developmental domains, each of which gathers and processes stimuli from multiple sources: attention control, information processing, cognitive flexibility, and goal setting. Attentional control matures relatively early, by the end of preschool age; information processing and cognitive flexibility are mostly developed by the end of middle childhood; and goal setting is well developed before the end of early adolescence (see Figure 3 ). 46

In addition, the increased synaptic pruning and myelination that occurs during this period significantly reshapes and modifies circuitry and allows malleability and adaptation to environmental experiences, or brain plasticity. There is evidence, eg, that both synaptic pruning and myelination are driven or modified by an individual’s experiences. 47 Thus, behaviors toward the environment are shaped by biologic changes in the brain, which in turn may be shaped by environmental, social, and cultural learning experiences. School age marks a major development of the associative brain regions and the resulting cognitive development and EFs, as well as the maturation of reward and emotional sensitivity areas, which interact with higher function control areas to develop emotional regulation, identity development, and longer-term planning and purpose. Adequate provision of nutrition, healthy social interactions, and cultural experiences, as well as adequate sleep, are all key to physical and psychosocial well-being. 41

The onset of early adolescence will be marked by an increase in social and cultural interactions, and changes in the home, community, and school relationships, which influence behavior. The interaction between behavior resulting from brain functions and external influences appears to be bidirectional. At the onset of puberty, the prefrontal associative brain areas continue to develop, but at a slower pace than some subcortical brain areas. These limbic emotion- and reward-related regions, such as the amygdala, appear to mature earlier than the prefrontal areas, which are responsible for inhibitory control of impulses and regulation of gratification and other emotions. This “mismatch” may in part explain the increase in risk-taking, emotion-driven behaviors seen in adolescence. 48

In summary, between the age of 5 years and 15 years, children go through major accelerations and inflections in their somatic growth, from a prepubertal state in the first 5 years to early adolescence changes in the next 5 years. By the end of school age, and before entering the final stages of “late adolescence,” healthy boys and girls, respectively, will have attained approximately 96% and 95% of their adult height, 19 92% and 77% of their total BMC, 49 89% and 85% of their fat mass, 21 and 84% and 95% of their muscle mass. 22 During this period, neuro-maturational processes will have also undergone significant changes. These include peaks in the development of specific areas of the brain and particularly the prefrontal cortex (implicated in complex cognitive behavior, planning, personality expression, decision-making, and moderation of social behavior) in the middle of the school years. Processes like synaptic pruning, which increase brain efficiency, will also peak by the end of this period, allowing for plasticity and increased brain efficiency. Delaying, altering, or blunting these accelerations and inflection points can significantly affect the ultimate attainment of physical growth, and cognitive, and socioemotional/psychosocial development. The necessity of preparing the child for these changes and supporting them through these accelerations and inflections, leading to the final maturational phase of late adolescence and ultimately adulthood, cannot be overstated.

The number of changes and dynamics of development mentioned above make the school years a particularly sensitive time, especially since most of the final growth and development is attained, which if not achieved will limit physical, cognitive, and social potential. These changes happen against a genetic backdrop expressed in, and dependent upon, multiple environmental and social scenarios that modulate physical and psychosocial development.

All these changes are underpinned by adequate nutrition in this period, as is true for all life cycle phases. Inadequate nutrition will slow or blunt physical and neurocognitive development trajectories during this last period of growth and development, with long-term consequences, inhibiting an individual’s ultimate potential. If environmental conditions, particularly nutrition, are favorable, the growth course and final height and overall body shape will be determined by an individual’s genes. 27 The acceleration and change in growth trajectories discussed above increase the chances for curtailing growth and development if increased nutritional demands are not met. Because of the growth dynamics in this period, the school years become critical for the necessary nutrition (a) to maintain adequate growth trajectories until maturity, or (b) to correct inadequacies and imbalances (deficits and excesses) for a healthy transition to a productive adulthood.

WHO, the US Institute of Medicine, the European Food Safety Authority (EFSA), and other regional authoritative groups all distinguish and define specific energy, macro-, and micro-nutrient requirements for the school-age years (early childhood and early adolescence) distinct from those of other life stages.

Energy and protein

As the child grows, changes in metabolism are directly related to total energy requirements and indirectly to growth, and consist of basal metabolic rate, energy cost of growth, and activity energy expenditure. 50 As a fraction of the total energy requirements, the energy cost of growth is highest in the newborn period, decreases to about 3% at 1 year of age, and goes up again between middle childhood and early adolescence to about 4%. 51 Imbalances between energy intake and expenditure can result in deficits (leading to a decrease in body fat and a deceleration of growth) or excesses (in the form of fat accumulation, increased body weight, and its related consequences).

The factors that affect child energy requirements are growth and body composition (which are sex-dependent), as well as physical activity. Daily energy requirements diverge by sex at the start of school age, and will remain different throughout the life cycle. Sex differences in metabolic rate and energy expenditure are in part driven by differences in body fat and fat-free mass that emerge during school age.

Between 5 years and 15 years of age, physical activity is a particularly important factor in energy balance. In adults, the estimated difference in energy requirements between a sedentary individual and an active individual is below 20%, while in 5-year-olds to 15-year-olds it is around 35%, indicating the need for adequate energy provision—in proportion to the recommended “active” level of physical activity during this period of the life cycle. 51 Energy provision throughout the day is also critical for brain activity, where increased neuronal activity drives increased energy consumption. In addition to all the neurodevelopmental changes occurring during school age mentioned above, the cerebral metabolic rate of glucose utilization is at its highest in middle childhood and early adolescence (apart from during the newborn period), then drops towards the end of adolescence. The mature brain is only approximately 2% of the body weight in adulthood, but is responsible for around 20% of energy consumption. Estimations for 12-year-old children suggest that brain energy consumption is as high as 30%. 52–54 Lastly, this increase in energy requirement and utilization is also dependent on the presence of adequate quantities of several micronutrients. These include riboflavin (vitamin B2), niacin (nicotinamide; vitamin B3), pyridoxine (vitamin B6), cobalamin (vitamin B12), vitamin C, vitamin D, calcium, iron, and phosphorus. They all act as co-factors for key enzymes in the metabolic pathways that generate and use energy.

Protein is the major functional and structural component of every cell in the body. The quality of a source of dietary protein depends on its ability to provide the nitrogen and amino acid requirements necessary for the body’s growth, maintenance, and repair. Through to the end of the growth years, enough protein is required to maintain the nitrogen equilibrium plus protein deposition in tissues. Low consumption of protein, often associated with low protein quality, is strongly associated with stunting, and if marked, other signs of undernutrition. As opposed to requirements for energy and some micronutrients, protein requirements do not change significantly by age or sex during the school years. The United States recommended dietary allowance is 0.95 g/kg/day, representing 10%–30% of total calories, from 4 years to 13 years of age. The recommended dietary allowance decreases slightly after adolescence. In general, proteins from animal sources such as meat, poultry, fish, eggs, milk, cheese, and yogurt provide all indispensable amino acids and are referred to as “complete proteins.” Proteins from plants, legumes, grains, nuts, seeds, and vegetables tend to be deficient in one or more of the indispensable amino acids.Thus, attention needs to be paid to children whose diets are low in animal protein sources to avoid essential amino acid deficiencies. 51

Micronutrients

In the United States, the Estimated Adequate Requirements, and Dietary Reference Intakes for micronutrients are the same for all children up to age 8 years. For the first time, they diverge for boys and girls during the school years: there are small differences (eg, for iron) for 9 years–13 years, and larger differences in requirements for late adolescence, at 14 years–18 years. 51 EFSA has slightly different and more specific age cut-offs for Population Reference Intakes (PRIs) for most vitamins and minerals. 55 Recommendations are made for 4 years–6 years, 7 years–10 years, 11 years–14 years of age, and separately define PRIs for 4 years–10 years and 11 years–17 years for calcium, 1 year–6 years, 7 years–11 years, and 12 years–17 years for iron, and 3 years–9 years and 10 years–17 years for copper, with some differences for sex in these nutrients. EFSA also differentiates requirements in energy and protein for boys and girls starting at 4 years. While specific benefits have been well established in relation to deficiencies for many micronutrients, consensus on optimal doses and combinations of these nutrients for promotion of specific health benefits in otherwise healthy school-age children is not universal and would benefit from further clinical research and substantiation.

Linear growth appears particularly sensitive to restrictions in energy, protein (particularly essential amino acids), zinc, iodine, and phosphorus, as well as some electrolytes. Protein quantity and quality remain fundamental components of adequate growth and function at all ages. Yet, the minimum protein necessary for adequate linear growth remains to be ascertained. Animal proteins, including dairy protein sources, have a selective effect in promoting height gain in undernourished and well-nourished children. In populations with low consumption of foods from animal sources, protein and zinc deficiencies will be more common. While iron and vitamin A are essential for multiple other reasons, intervention studies suggest that their deficiency does not affect linear growth. As discussed further below, calcium is critical for bone mineralization but appears to be of less consequence regarding linear growth. 27

Independent of nutrient provision, as mentioned above, bone growth regulation can be blocked by inflammation, such as recurrent childhood infections, which, if bi-directionally compounded by undernutrition, result in poor growth led to stunting. The term “environmental enteric dysfunction” has been used to refer to chronic and recurrent infections and infestations in areas with poor sanitation, where infection, inflammation, and malabsorption coalesce and perpetuate undernutrition. These conditions may explain why nutrition or dietary interventions alone may not be sufficient to address stunting in children. Current interventions to reduce stunting need to target sanitation and environmental factors as well as nutrition in low- and middle-income country settings. 25 , 27

Calcium is essential for adequate mineralization of bones, and 99% of all calcium in humans is found in bones and teeth. Dietary calcium can be absorbed passively, but the active transport of calcium in the gut is mediated by vitamin D. Both nutrients are inextricably linked in determining BMC. Low calcium intake in young children is associated with low BMC, and sustained low intakes (below 200 mg daily) with radiographic signs of rickets. 56

There is clear evidence suggesting that peak bone mass and risk of fractures in later life are influenced by bone mineral accretion throughout childhood, including school age. As discussed above, peak rates of bone mineralization are reached 6 months–12 months after the peak rate of bone elongation is reached. By the end of school age, median peak height has been achieved in girls (achieved a year later in boys), and more than 80% BMC has been accrued. The exact cessation of mineral accrual varies depending on the skeletal site, but appears to be complete by 18 years in the spine and femoral neck. After peak BMC is reached, the rate of bone mass and mineral content accretion gradually and continually decreases for the rest of an individual’s life. 33 , 57 Therefore, the rate and amount of BMC attained in the school years will greatly determine peak bone mass and be a major contributor to the relative risk of low bone mass and eventual osteoporosis and bone fractures for the rest of an individual’s life. Recent estimates from the United States in adults older than 50 years show a prevalence of low bone mass of 51.5% in women and 33.5% in men, and frank osteoporosis of 19.6% in women and 4.4% in men. 58 Estimates from the International Osteoporosis Foundation indicate that, worldwide, after 50 years of age, 30% of women and 20% of men will have hip, vertebral, or wrist fractures from osteoporosis in the remainder of their lives. 59 Thus, meeting dietary protein and calcium requirements, maintaining adequate vitamin D through diet and sunlight exposure, and physical activity during school-age years constitute critical investments in achieving long-term bone health. 31 , 60

Iron, zinc, polyunsaturated fatty acids (especially docosahexaenoic acid), vitamin B12, and folate have all been specifically identified as critical nutrients for adequate brain growth, cognition, and EF development. However, as for other aspects of life-stage nutrition, most data have been accumulated for these nutrients and their longer-term effects in relation to consumption in the first 5 years of life. They have often not been the primary focus of studies and are poorly investigated in healthy school-age populations. 61

Deficiency in iron deserves highlighting in relation to nutritional consequences for later life, due to its prevalence in and coexistence with all forms of malnutrition. Iron deficiency is the most common nutritional deficit in people worldwide and the most common deficiency in children, whether suffering or not from acute or chronic malnutrition. Anemia, half of which is due to iron deficiency, affects around 33% of the global population. Globally in 2019, iron deficiency was the leading cause of years lived with disability in children and young adults (aged 10 y–24 y), with the highest prevalence in most African and many Asian countries. 62 While its prevalence is higher in low- and middle-income countries, it persists in varying degrees in all socio-economic levels. Iron is a crucial nutrient in maintaining levels of neurotransmitters, including dopamine and serotonin. And its deficiency can decrease brain myelination, alter synaptogenesis, and decrease the functioning of basal ganglia. The consequences in childhood include deficits in motor function and impaired cognitive development, leading to lower cognitive skills, lower school achievement, impaired psychomotor and behavioral development, and ultimately lower work capacity and productivity in adulthood. 63 , 64

The consequences of iron deficiency in childhood, some of which may be irreversible, have been recognized for a long time and have led to global efforts in improving iron status through supplementation in infancy and childhood. 64 , 65 Given the significant changes in brain structure and function that happen during the school years, and the potential long-term consequences of deficiency, iron remains a major nutrient of interest, highlighting the need for adequate preventive interventions as well as treatment of deficiencies during this life stage. There is increasing and robust evidence that improving iron status, particularly in the presence of anemia, significantly affects cognitive performance in school-age children older than 5 years. Interestingly, the evidence for this effect of iron on older children appears stronger than for interventions in children under 2 years of age. 66

Consequences of inadequate nutrition in school age on growth and development

Inadequate nutrition in school age ultimately results from inadequate diets, which in turn are a consequence of multiple factors. On the one hand, food security, availability, and provision are essential. On the other, a healthy diet requires appropriate food choices, which depend on many environmental influences—from home, the community, the school, and broader society. These influences will not only determine the delivery of adequate foods but shape the behavior of children and thus their food choices for the long term. Influences at this age are critical, when cognitive, socioemotional, and psychosocial development are associated with increasing independence, decision-making, and self-image and awareness. Addressing all these factors remains critical for increasing an individual’s chances for long-term health. Discussion of these is beyond the scope of this review.

The immediate and most visible consequences of not meeting nutritional requirements are loss of body weight and adipose tissue (thinness/wasting/low BMI). Prolonged marginal provision of macronutrients, most often accompanied by micronutrient deficits, leads to slowing of linear growth (low height for age). In both cases, infection, or other inflammatory states, coupled with enteropathies related to poor sanitation, can further increase requirement for an effective immune response, lead to a negative nitrogen balance, mobilization of protein from muscle tissues, as well as inhibition of linear bone growth. 25 , 28 Wasting and stunting are often linked and can occur together in the same population, often in the same child. 67 Longitudinal analyses show that wasting is a precursor to stunting. 68 In addition, low BMI and wasting are related to delayed pubertal onset, which in school-age children affects growth trajectories. Globally, stunting (height-for-age greater than 2 standard deviations below the WHO reference) remains by far the most prevalent clinical manifestation of undernutrition, including micronutrient deficiencies. 28

Stunting in early life is associated with poor cognitive development, lower development of EF, lower rates of schooling and school achievement, and ultimately decreased productivity and earning power. These associations, however, do not necessarily infer causality. Stunting is often accompanied by multiple nutrient deficiencies and their consequences, beyond iron deficiency anemia. And the occurrence of stunting due to poor nutrition, and its cognitive and other consequences, cannot be delinked from the effects of the physical and social environments where stunting occurs 69–71 ; nonetheless, it is likely they are causally related. Beyond cognitive impact, not achieving an individual’s height potential can also be associated with higher psychologic dysfunction all the way to late adolescence, with increased chances of developing low self-esteem, anxiety, depressive symptoms, and anti-social behaviors. 72 , 73

Stunting can occur at any age before adulthood, but for most school-age children, it is a continuation of poor growth in early infancy. WHO and World Bank global estimates show that globally, stunting in children under 5 years of age has decreased from 33% (203.6 million children) to 22% (149.2 million children) from 2000 to 2020, 7 with the highest prevalence in Africa and parts of Asia and Latin America. Thus, a great number of children are stunted when entering school age. Stunting prevalence in school age will result from stunting occurring under 5 years, with some “new” cases being added or a decrease in cases from “catch-up” growth. 74 Although most stunting may start in infancy, it can continue or worsen in the school years. As discussed below, given school age is the last and second fastest period of height attainment after infancy, this life stage may offer the last “window of opportunity” for correcting deficits and potentially achieving catch-up growth and catch-up cognitive development, ameliorating its negative consequences for individuals and society.

Lastly, children who remain stunted through school years may be at increased risk for obesity. There is growing evidence that stunted infants and children who gain weight rapidly in later childhood have an increased risk of overweight, obesity, and noncommunicable diseases as adults. 75 , 76 However, stunting at 1 year alone does not seem to raise obesity risk consistently. 77 This is becoming increasingly important, as the secular transition from undernutrition to obesity is accelerating in many populations, as discussed below. The peak incidence of obesity by age has been occurring earlier and earlier in life in many populations (see below). Its consequences (related to metabolic disease, diabetes, cardiovascular disease, and other noncommunicable conditions) constitute the greatest health challenges of this century.

Specific nutrient deficiencies, individually or in combination, and their syndromes are both present and prevalent in school age. The consequences of these in addition to those mentioned above are beyond this review. Suffice it to say that persistent deficiencies such as of iron (and its effects on long-term cognitive function) as well as calcium and vitamin D (and their potential in preventing osteoporosis and fractures well into adult and mature life) are prime examples of the need for maintaining adequacy or correcting deficiencies during school age.

Compared with infant data, apart from some recent increase in data on the adolescent years, there is a serious lack of information on nutritional status and its consequences for middle childhood through adolescence. One analysis showed that, a literature search for 2004–2017 including the terms “health,” “mortality,” or “cause of death in the first 20 years of life” found that about 99% of the publications in Google Scholar and 95% of the publications in PubMed focused on children under age 5 years. 8 Global School-based Student Surveys, a collaboration of WHO, CDC, UNICEF, UNESCO, and UNAIDS, have primarily included only 13-year-olds to 17-year-olds. 78 In addition, data for this age group is often embedded and difficult to disaggregate from “childhood studies” that may include preschool and school-age children, or from studies on “adolescents” that include children of 10 years or 12 years and above. Overall, the ages 5 years–9 years and 10 years–14 years have the least number of research data sources for estimating morbidity and mortality risk factors compared with 0 years–5 years and 15 years–19 years. Another recent large population-based study showed that, within the relatively small amount of available data for height, weight, and BMI in school-age children, 78.9% of studies had data for 15 years–19 years, but only 50.3% had data for 10 years–14 years, and 39.9% for 5 years–9 years of age. 79 In another larger analysis, less than half of the studies included data for middle childhood (5 y–9 y), compared with nearly 90% with data for adolescents (10 y–19 y). Overall, the quantity and quality of data vary significantly by country and region. Still, the relative lack of data for middle childhood is notable across the board, limiting the capacity to compare growth or nutrition outcomes of this age group with earlier or later life stages. 80

A systematic review, one of the few studies focusing on school age (6 y–12 y) in low- and middle-income countries (LMICs), showed underweight and thinness were most prevalent (21%–36%) in South-East Asian and African countries, with lower prevalence in Latin America (8%–6%). The prevalence of overweight and obesity was highest in Latin America (∼26%), compared with 13% in Southeast Asia and 7% in Africa. The mean prevalence of iron deficiency ranged from 29% in Africa to 20% in Southeast Asia, and 14% in Latin America. Iodine, vitamin A, and zinc deficiencies are the most common. The prevalence of vitamin A deficiency was 9% in Latin America (on the lower end), to 54% zinc deficiency prevalence in Africa (on the highest end). 81

Very recently, data from population-based studies supported by the Non-Communicable Disease Risk Factor Collaboration 79 , 80 and the B&M Gates Foundation 82 are shedding light on this global picture. These are the most comprehensive reviews on growth and temporal trends available to date for this age group, and the only available review addressing this age group at a global level. One analysis, NCD RisC 2017, 79 included 31.5 million children from 200 countries aged 5 years–19 years, and estimated trends from 1975 to 2016. The other, NCD RisC 2020, 80 pooled data from 2181 population-based studies, with height and weight measurements for 65 million participants in 200 countries, and estimated trends from 1985 to 2019 in height and BMI for children 5 years–19 years. In this study, data were reported without specific cut-off points for over- or under-nutrition. Data and trends from these studies are summarized immediately below.

Thinness and wasting

From 1975 to 2016, the overall global prevalence of moderate and severe underweight (thinness and wasting) in children 5 years–19 years decreased from 9.2% to 8.4% in girls and from 14.8% to 12.4% in boys, with the expected large variations regionally. The prevalence of moderate and severe underweight remained highest in south Asia, with 22.7% among girls and 30.7% among boys in India. Although the populations increased in most regions, the number of moderately and severely underweight school-age children actually decreased. And while prevalence declined, the relatively small change at the global level was partly due to greater population growth in countries where the prevalence of underweight is higher. 79

Mean BMI trends showed increases in almost every country over the last 30 years, with the greatest increases seen in Sub-Saharan Africa. Low BMI (compared with the WHO reference median in 5-year-old children) persisted primarily in Southeast Asia and Sub-Saharan Africa. In most countries, it decreased as they entered adolescence, and in some countries it disappeared by age 19 years. 80 The trends showed that, globally, the absolute number of underweight children peaked around the year 2000 and has since been decreasing, reaching levels in 2016 close to those in 1975. 79

Data from surveys in 57 LMICs between 2003 and 2013, comprising children 12 years–15 years, showed a global prevalence of stunting of 10%. 75 However, the limited data available on stunting in this age group shows very wide variations. Stunting in adolescent girls (15 y–19 y) in LMICs range from 52% in Guatemala and 44% in Bangladesh to 6% in Brazil. 83

The 2 most extensive global studies including children 5 years–19 years of age 79 , 80 did not report height based on a particular cut-off for stunting. Nevertheless, in age-related trends, most countries showed that height was at or above the WHO median for children at 5 years of age, with girls doing better than boys. Still, in approximately 20% of countries for girls and 30% of countries for boys, the mean height during the school years was significantly below the WHO median. Today, the estimated difference in height of 19-year-olds between countries with the tallest populations (eg, the Netherlands, Denmark) and the shortest populations (eg, Timor-Leste, Laos, Guatemala, Bangladesh) was 20 cm. More concerning is that, in some countries, height adequacy in middle childhood may decrease as children grow older. Children who have optimal height at 5 years of age fall under the WHO median at 19 years by 2 cm or more, particularly in some middle-income countries.

In terms of temporal trends, with rare exceptions, the last 3 decades show significant gains in height in most countries and all regions for boys and girls, except for Sub-Saharan Africa (for both sexes) and Oceania (for boys). The greatest gains have been made in countries with emerging economies, including China and South Korea, and parts of Southeast Asia, the Middle East, and in some countries in North Africa, Latin America, and the Caribbean. 80

Overnutrition

Over the last 40 years, obesity has increased in every country in the world. The NCD-RisC 2017 study 79 showed that, from 1975 to 2016, the global prevalence of obesity in 5-year-olds to 29-year-olds increased from 0.7% to 5.6% in girls, and from 0.9% in 1975 to 7.8% in boys. The number of girls with obesity increased from about 5 million to 50 million in 2016, and the number of boys from about 6 million to 74 million. Trends in mean BMI have continued accelerating, particularly in east and south Asia. Southern African countries had the greatest rise in obesity (∼400% per decade), given the obesity prevalence was minimal 40 years ago.

On the other hand, since about 2000, the increase in prevalence has begun to plateau, and it recently flattened in northwestern Europe, in “high-income English-speaking” and Asia-Pacific regions for both sexes, in southwestern Europe for boys, and in central and Andean Latin America for girls. While not exactly comparable, these findings are consistent with another earlier large study 82 that analyzed 1769 population-based surveys and studies in 19 244 children aged 2 years–19 years (not reporting disaggregated data for school age). These investigators found that, from 1980 to 2013, in developed countries, the prevalence of overweight and obesity for 2-year-old to 19-year-old children (as a group) increased from 16.9% to 23.8% in boys and 16.2% to 22.6% in girls. In the same period, in developing countries, the prevalence of overweight and obesity increased from 8.1% to 12.9% in boys and 8.4% to 13.4% in girls. All studies show that globally, the peak prevalence of obesity is shifting to younger ages. While the prevalence remains higher in developed countries, the great majority of overweight and obese girls and boys (in absolute numbers) are from LIMCs, 79 thus representing a double burden of poor nutrition for the most populous countries in the world.

The NCD RisC 2020 study 80 showed that the difference between the highest mean BMI (eg, Pacific Island countries, the United States, Chile, South Africa) and lowest mean BMI (eg, India, Bangladesh, Ethiopia, and Chad) was 9 kg/m 2 –10 kg/m 2 in girls. Thus, the mean BMI difference, between these countries, was greater than 2 standard deviations in BMI for a 15-year-old girl. Trends by age varied significantly, and they worsened with age in many countries. In some countries (eg, Mexico, South Africa, New Zealand), 5-year-old children with healthy BMI progressively gained more in BMI than in height through the school-age years. Over time, some countries showed too little height gain, and/or too much weight gain for height (eg, Sub-Saharan Africa, New Zealand, the United States, Malaysia, some Pacific Island nations, and Mexico), with some differences by sex.

In summary, though the landscape has changed significantly in the last few decades, undernutrition (wasting/thinness/low BMI) and poor linear growth (low height for age/stunting), as well as overnutrition (elevated BMI with or without low height), remain major nutritional challenges globally. Today, still, despite the increase in overweight and obesity, more school-age children worldwide are moderately or severely underweight than overweight or obese. That said, in most countries, the prevalence increases in overweight and obesity are greater than the declines in prevalence of underweight. So, if current trends continue globally, the prevalence of obesity in school age will be higher than that of moderate and severe underweight before 2025. 80

The considerable global differences in these markers of nutritional adequacy reflect the geographic and socio-economic gaps that also persist globally. While genetics and other factors play a role, a difference of 20 cm in height and 9 kg/m 2 –10 kg/m 2 in BMI between extremes in populations is a partial reflection of the persistence of undernutrition and the large global nutritional and environmental gaps. Lastly, a rapid closing of those gaps may signal a “too rapid” transition from a mostly underweight population to a mostly overweight and obese population, as has occurred in parts of Asia and Latin America, accelerating and increasing the burden of nutrition-related conditions, particularly for LMIC populations.

While trajectories vary regionally, in many countries, based on height and BMI, nutritional status appears to be adequate at 5 years (which may reflect efforts over the last decades in improving early childhood health and nutrition) but deteriorates as children move through the school years. This heightens the relative neglect in attention to school-age nutritional focus, particularly for the 5–10 year-old population.

The global rise in obesity related to socio-economic and other environmental changes, including changes in nutrition, contributes to increases and exacerbations of type 2 diabetes, cardiovascular disease, and other noncommunicable diseases, exacerbating the double burden of disease and of cost to society. Prevention, starting prenatally, remains the most cost-effective and realistic approach. 84 So far, however, no clear or strong regional or national success stories have been demonstrated in the last decades. 82

Micronutrient deficiencies

Micronutrient deficiencies continue to be considered a major contributor to the global burden of disease. Despite this, a recent global report confirms a persistent and wide gap in data and information around micronutrient intake and nutrient status for all ages. 85 Individual deficiencies rarely occur in isolation. As for other indicators of nutrition and health, some school-age micronutrient data is available for some nutrients, and some are available from studies in adolescents and young adults. Still, data in 5-year-old to 15-year-old children is the least available across the board.

Based on the high prevalence of their deficiencies, WHO considers iron, vitamin A, vitamin D, zinc, iodine, and folate the most critical micronutrients globally. It is estimated that 25% of school-age children (around 305 million children) have anemia and that 50% of it is primarily associated with iron deficiency. 86 A 2004 report estimated the prevalence of vitamin A deficiency in school-age children in South Asia to be 23.4% or 83 million children, 9 million of whom had xerophthalmia. 87 In low-income countries, vitamin A deficiency prevalence has been estimated at 20% among early adolescent (10–14-year-old) girls and 18% among late adolescent (15–19-year-old) girls. 83 Worldwide, inadequate zinc intake is estimated at around 17%, with little data disaggregated for school children, 88 90% of which is in Africa and Asia. 89 The prevalence of inadequate iodine intake in 6-year-old to 12-year-old school-age children has been estimated at around 30% (241 million children), ranging from 13% in the Americas to 39% in Africa. 90 Limited data on folate deficiency in females 12 years–49 years (reproductive age) indicate a prevalence of more than 20% in lower-income and less than 5% in higher-income countries. There are no good global estimates of folate deficiency for school-age children. 88 , 91

In one report, vitamin D deficiency in 6-year-old to 12-year-old children ranged from 16% in North America, to 28% in Mexico, to 88% in China. 92 For calcium, as opposed to most other nutrients where adequacy can be measured using biomarkers, there is no universally accepted definition for deficiency. So dietary intake is used as the best proxy for adequacy. In addition, recommended intakes vary significantly by regional or expert groups. For school-age children, EFSA has stated a PRI of 800 mg/day for 4-year-olds to 10-year-olds and 1150 mg/day for 11-year-olds to 17 year-olds. The Institute of Medicine in the United States has stated a recommended dietary allowance of 1000 mg/day for 4-year-olds to 8-year-olds and 1300 mg for 9-year-olds to 13-year-olds. 55 While good estimates are lacking, average calcium intake in the United States for children 1 year to 14 years has been estimated at between 856 mg/day and 993 mg/day, depending on methodology, suggesting that many children fall below recommendations. There are no good global estimations, but from the little data available, it is evident that the great majority of children in developing countries fall far below any current recommendations. 93 Micronutrient deficiencies further compound the total burden of poor nutrition, as they coexist with wasting and obesity.

Studies and systematic reviews of micronutrient supplementation and fortification that include school-age children clearly show that micronutrient status can be improved. The demonstration of clinical effects, including growth and morbidity, varies significantly. The best documented is iron supplementation and fortification, which has been shown to improve iron status and reduce anemia in school-age children 5 years–12 years old. 94 A positive effect of iron supplementation on cognitive development has been shown, and interestingly, effectiveness appears greater for children older than 7 years than for younger ages. 95 Other effects of micronutrient supplementation, including growth and morbidity, are less clear. 81 , 96

Early attention to the significant effect of nutrition until 2 years of age and the assertions, even until recently, that stunting and cognitive delays were irreversible 97 , 98 may have contributed to the lower attention to middle childhood and adolescence as opportunities for recovery, particularly as related to stunting and cognitive deficits. Evidence today suggests this is not the case.

Catch-up growth through the school-age years is possible with the right interventions. Historical reports and observational studies of immigrant populations and adopted children document that in situations where environmental and nutritional conditions change positively, meaningful linear catch-up is possible. 99 Longitudinal observational data from the COHORT multicounty study and longitudinal data from rural Gambia have shown that significant catch-up in height can be achieved between 2 years of age and the end of middle childhood (10 y of age), and between middle childhood and adulthood, even in the absence of any nutrition or health interventions. 2 Catch-up growth is also possible in chronic conditions, including celiac disease and inflammatory bowel disease, with the right medical and nutritional interventions. 100 , 101

Although results are not always consistent, some longitudinal studies that include school-age populations (6 y–11 y old) show linear catch-up is possible with multiple micronutrient supplementation. 102 , 103 A recent systematic review and meta-analysis of the effectiveness of several nutrition-based interventions after 2 years of age (where more than half of the studies included children older than 5 years of age) showed including supplementation of protein, vitamin A, and/or multiple micronutrients, and particularly zinc supplementation, can improve linear growth, especially in children that have experienced early stunting. However, supplementation of other micronutrients, including iodine, iron, calcium, or food-based interventions, did not significantly affect growth, even if resolving anemia or other deficiencies. 96

Although populations and methodologies vary, some studies have not found a correlation between linear growth recovery and cognitive measures in short-term studies over 6 months, 104 while others have. Data from a longitudinal observational cohort in several LMICs found that children who had stunting by 1 year of age with linear growth catch-up by age 8 years had significantly better cognitive outcomes than those who remained stunted. 105 Height catch-up in these children was positively associated with improvements in mathematics achievement, reading comprehension, and receptive vocabulary. Children who remained stunted performed less well, and children who were never stunted remained ahead of the other groups. A subsequent study of the same cohort 74 analyzed catch-up growth between the ages of 8 years and 15 years and showed that more than one third of those stunted at age 8 years caught up to their peers by age 15 years, and also improved their cognitive scores compared with those who did not catch up in height. Notably, linear growth faltering was also accompanied by a decrease in cognitive outcomes in those children who became stunted between 8 years and 15 years. Thus, associations between linear growth and cognitive development vary from country to country and do not always persist from middle childhood through adolescence. 74 , 106 The extent of linear catch-up effect in various studies will vary obviously due to the timing of the initial insult, the timing of the intervention, the duration of the intervention, and other environmental conditions beyond nutrition. Given the obvious genetic, epigenetic, and environmental carryover between young mothers and their offspring, it seems likely also that reversing the cycle of undernutrition will probably require cross-generational catch-up. 107

Inadequate bone mass and mineral accretion in school-age children can have long-term consequences. While no good markers (except assessment of calcium intake and vitamin D) are available, adequate intakes remain important for reducing long-term risks. During the school-age years, a higher milk intake is associated with higher BMC, BMD, and reduced fracture risk in adulthood. Consuming less than one serving of milk a day in childhood was associated with a 2-fold increase in fracture risk as adults. 108 Establishing healthy dietary behaviors with a well-balanced diet that includes adequate calcium and vitamin D, particularly with inclusion of dairy products and regular physical activity, can bring about long-term bone health.

Despite the limited knowledge we have, the nutritional objectives for school-age children appear quite clear: providing energy and protein adequacy (including avoiding excesses), decreasing deficiencies of iron, iodine, vitamin A, vitamin D, calcium, zinc, and folate, and avoiding excesses of simple sugars and sodium. Long-term studies are still lacking, and there appears to be no “magic bullet” for improving dietary intakes and avoiding excesses. However, there is increasing evidence to support school dietary and physical activity–based interventions in schoolchildren to prevent deficiencies and address overweight and obesity. 109–111 The school setting has excellent potential for providing a significant part of daily intake to improve diet quality tailored to the local environment and educate children in nutrition and diet. The potential remains to be tapped.

This can only be accomplished with adequate individual, community, and population education, as well as policies that support these endeavours at multiple levels and by multiple stakeholders—a discussion that is beyond the scope of this review.

Very recently, the last 4 years to 5 years have brought about an increasing level of attention and calls for action to address the health and nutrition of middle childhood and adolescence. In 2017, Bundy et al published a comprehensive volume as part of the World Bank’s Disease Control Priorities series, with support from the Bill and Melinda Gates Foundation, highlighting child and adolescent health, with a focus on ages 5 years–19 years, as “neglected potential” that needs to be realized. 1 They noted an “asymmetry between the public investment in formal education versus health during the age range of 5 years–19 years, and a lack of recognition that the developmental returns from education are themselves dependent on concurrent good health and diet.” This “historical neglect of investments… [beyond the first 1000 d], including the next 7000 days of middle childhood and adolescence… is also reflected in investment in research into the older age-groups.” 1

Around this time, collaborative efforts in population-based studies are finally presenting a more comprehensive and clearer global picture of the nutritional status of children above 5 years of age. 79 , 80 Several research groups have reported on the significant potential that nutrition and health interventions have on improving outcomes during school age, thus constituting a true (and possibly last) major window of opportunity for supporting adequate nutrition, overcoming deficits from earlier life, shaping future dietary behaviors, and improving long-term health and well-being. 2–5

Even more recently, UNICEF’s Nutrition Strategy for 2020–2030 Framework called for “strategic shifts” in upholding children’s right to nutrition and ending child malnutrition in all its forms (as part of the global Sustainable Development Goals). The Strategy includes a comprehensive life cycle approach to nutrition programming, and maternal and child nutrition during the first 1000 days as core to UNICEF programs, and also explicitly states that “nutrition during middle childhood and adolescence is both a right and a window of opportunity for growth, development and learning, particularly for girls, and for breaking the intergenerational cycle of malnutrition.” The 2 first measurable Results areas for the Strategy are 1. Early Childhood Nutrition and 2. Nutrition in Middle Childhood and Adolescence. 112 UNICEF’s Programmatic Guidance for Nutrition in Middle Childhood and Adolescence includes specific priorities of nutritious foods, healthy food environments in schools and beyond, micronutrient supplementation and deworming, nutrition education in school curricula, and healthy dietary practices for school-age children and adolescents. 113

While not neglecting early-life nutrition, a life-cycle approach to nutrition requires increased attention and a re-prioritization of middle childhood and early adolescence. The school-age years provide unique opportunities that will need to be embraced, even more so now, given the added challenges placed on the world by the recent COVID pandemic and climate change.

Nutrition during the formative years remains the foundation for long-term health and productivity of the individuals who make up society. Of these formative years, the first 5, with good reason, have received great attention over the last few decades. Decreasing infant mortality, including the vicious cycle of undernutrition and disease, and a better understanding of health and disease’s developmental origins, have improved our focus and understanding of the critical first few years of life. This, however, was coupled with the poorly documented notion that somatic and cognitive harm or delay in the first 2 years of life were irreversible, and hindered in part the attention given to the rest of childhood, particularly middle childhood and early adolescence. Middle childhood and early adolescence remain the most underrepresented of all life stages in health and nutrition research and clinical, nutritional, and epidemiologic data.

After the first 1000 days, the school-age years represent the most dynamic period of change in somatic and cognitive development before an individual reaches maturity, with multiple changes and inflection points in growth and development trajectories. Figure 4 summarizes key milestones in somatic and brain growth and development and shows how “eventful” this life-cycle period truly is. Deficits in growth, bone health, cognitive development, and alterations in body composition during this period have a life-long impact. It is possible and critical that we intervene during school age (a) to maintain an adequate course of somatic and cognitive development and a bridge to adult life, (b) to correct deficits of undernutrition and “catch-up” to the normal course of growth and development, and (c) to modulate or mitigate inadequacies of overnutrition and avoid longer-term consequences. Middle childhood and adolescence are thus a last major opportunity for investment, to affect growth, nutrition, and ultimate health and cognitive outcomes.

The figure depicts key events in somatic and brain growth and development trajectories occurring in middle childhood and early adolescence. The timing is meant to show sequence, and the ages are best approximations. Divergence relates to differences between sexes. See text for related references. BMC: bone mineral content.

Childhood education, the basis for societal development, is not possible without adequate nutrition. In addition, child education and school systems themselves provide significant tangible opportunities for influencing dietary intake as well as for educating future generations on diet and nutrition. Therefore, it is imperative to improve our understanding of the opportunities presenting themselves during this period of life, and to develop policies and strategies to improve the current level of response to those opportunities. Only very recently has this understanding led to a revisiting of priorities in combating poor nutrition and its long-term consequences. The emphasis on intervention during the school-age years needs to be nurtured and reinforced.

The authors would like to thank Dr Francois-Pierre Martin, Dr Laurence Donato-Capel, and Dr Marie-Claire Fichot for reviewing and providing valuable suggestions regarding the manuscript.

Author contributions . All authors participated in the planning, review, and final approval of the manuscript. The content is solely and entirely the work of the authors.

Funding . The collection of material for this manuscript was partially supported by the Société des Produits Nestlé.

Declaration of interest . J.M.S. is a consultant for Société des Produits Nestlé, and Scaled Microbiomics. A.P. is a board member of the Nestlé Nutrition Institute.

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• science of nutrition
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• school-age child
• growth and development

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Nutrition for kids: Guidelines for a healthy diet

You want your child to eat healthy foods, but do you know which nutrients are needed and in what amounts? Here's a quick overview.

Introduction

Nutrition for kids is based on the same ideas as nutrition for adults. Everyone needs the same types of things, such as vitamins, minerals, carbohydrates, protein and fat. These are called nutrients. Children need different amounts of specific nutrients at different ages.

The best eating pattern for a child's growth and development considers the child's age, activity level and other characteristics. Check out these nutrition basics for kids, based on the latest Dietary Guidelines for Americans.

Food packed with nutrients — with no or limited sugar, saturated fat, or salt added to it — is considered nutrient dense. Focusing on nutrient-dense foods helps kids get the nutrients they need while limiting overall calories.

Consider these nutrient-dense foods:

• Protein. Choose seafood, lean meat and poultry, eggs, beans, peas, soy products, and unsalted nuts and seeds.
• Fruits. Encourage your child to eat a variety of fresh, canned, frozen or dried fruits. Look for canned fruit that says it's light or packed in its own juice. This means it's low in added sugar. Keep in mind that 1/4 cup of dried fruit counts as one serving of fruit.
• Vegetables. Serve a variety of fresh, canned, frozen or dried vegetables. Choose peas or beans, along with colorful vegetables each week. When selecting canned or frozen vegetables, look for ones that are lower in sodium.
• Grains. Choose whole grains, such as whole-wheat bread or pasta, oatmeal, popcorn, quinoa, or brown or wild rice.
• Dairy. Encourage your child to eat and drink fat-free or low-fat dairy products, such as milk, yogurt and cheese. Fortified soy beverages also count as dairy.

Aim to limit your child's calories from:

• Added sugar. Naturally occurring sugars, such as those in fruit and milk, aren't added sugars. Examples of added sugars include brown sugar, corn sweetener, corn syrup and honey. To avoid added sugar, check nutrition labels. Choose cereals with minimal added sugars. Avoid sodas and other drinks with added sugars. Limit juice servings. If your child drinks juice, make sure it's 100% juice without added sugars.
• Saturated fats. Saturated fats mainly come from animal sources of food, such as red meat, hot dogs, poultry, butter and other full-fat dairy products. Pizza, sandwiches, burgers and burritos are a common source of saturated fat. Desserts such as cakes and ice cream are another common source of saturated fat. When cooking, look for ways to replace saturated fats with vegetable and nut oils, which provide essential fatty acids and vitamin E.
• Salt. Most children in the United States have too much salt in their daily diets. Another name for salt is sodium. Salt can hide in sandwiches, where the sodium in bread, meat, condiments and toppings adds up. Processed foods, such as pizza, pasta dishes and soup, often have high amounts of salt. Encourage snacking on fruits and vegetables instead of chips and cookies. Check nutrition labels and look for products low in sodium.

If you have questions about nutrition for kids or specific concerns about your child's diet, talk to your child's health care provider or a registered dietitian.

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• 2020-2025 Dietary Guidelines for Americans. U.S. Department of Health and Human Services and U.S. Department of Agriculture. https://www.dietaryguidelines.gov. Accessed July 27, 2022.

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Childhood Nutrition

​ Nearly 1 in 3 children in America is overweight or obese . Despite all the focus on kids being overweight and obese, many parents are still confused, especially when it comes to what kids eat.  How much does your child need? Is he getting enough calcium? Enough iron? Too much fat?

Whether you have a toddler or a teen, nutrition is important to his or her physical and mental development. Here's what children need — no matter what the age.

During this stage of life, it's almost all about the milk — whether it's breast milk , formula , or a combination of the two. Breast milk or formula will provide practically every nutrient a baby needs for the first year of life.

At about six months most babies are ready to start solid foods like iron-fortified infant cereal and strained fruits, vegetables, and pureed meats. Because breast milk may not provide enough iron and zinc when babies are around six to nine months, fortified cereals and meats can help breastfed babies in particular.

Once you do start adding foods, don't go low-fat crazy . Although the AAP guidelines state fat restriction in some babies is appropriate, in general, you don't want to restrict fats under age two because a healthy amount of fat is important for babies' brain and nerve development.

Toddlers & Preschoolers

Toddlers and preschoolers grow in spurts and their appetites come and go in spurts, so they may eat a whole lot one day and then hardly anything the next. It's normal, and as long as you offer them a healthy selection, they will get what they need.

Calcium, the body's building block, is needed to develop strong, healthy bones and teeth. Children may not believe or care that milk "does a body good," but it is the best source of much-needed calcium. Still, there's hope for the milk-allergic , lactose-intolerant, or those who just don't like milk. Lactose-free milk, soy milk, tofu, sardines, and calcium-fortified orange juices, cereals, waffles, and oatmeal are some calcium-filled options. In some cases, pediatricians may recommend calcium supplements.

Fiber is another important focus. Toddlers start to say "no" more and preschoolers can be especially opinionated about what they eat. The kids may want to stick to the bland, beige, starchy diet (think chicken nuggets, fries, macaroni), but this is really the time to encourage fruits, vegetables , whole grains, and beans, which all provide fiber. Not only does fiber prevent heart disease and other conditions, but it also helps aid digestion and prevents constipation , something you and your child will be thankful for.

Gradeschoolers 

It isn't uncommon for a 6- or 7-year-old to suddenly decide to be a vegetarian once they understand animals and where food comes from. This doesn't mean your child won't get enough protein ; animal tissue isn't the only place we get protein. Rice, beans, eggs, milk, and peanut butter all have protein. So whether your child goes "no-meat" for a week or for life, he or she will likely still get sufficient amounts of protein.

Areas that might be a little too sufficient are sugars, fats, and sodium.

This is a time when kids first go to school and have a little bit more choices in what they eat, especially if they're getting it in the cafeteria themselves. Cakes, candy, chips, and other snacks might become lunchtime staples.

The body needs carbs (sugars), fats, and sodium, but should be eaten in moderation, as too much can lead to unneeded weight gain and other health problems.

Packing your child's lunch or going over the lunch menu and encouraging him or her to select healthier choices can help keep things on track.

Preteens & Teens

As puberty kicks in, young people need more calories to support the many changes they will experience. Unfortunately, for some, those extra calories come from fast food or "junk" foods with little nutritional value.

Some adolescents go the opposite way and restrict calories, fats, or carbs. Adolescence is the time kids start to become conscious of their weight and body image, which, for some, can lead to eating disorders or other unhealthy behaviors. Parents should be aware of changes in their child's eating patterns and make family dinners a priority at least once or twice a week.

Like calories, calcium requirements are higher. Calcium is more important than ever during the tween and teen years because the majority of bone mass is built during this time. Encouraging kids to have milk, milk products, or calcium-rich alternatives, should help them get more calcium.

Your child's gender may play a role in whether he or she needs more of a particular nutrient. For instance, teen girls need more iron than their male counterparts to replace what's lost during menstruation , and males need slightly more protein than girls.

Although getting your child to eat healthy — regardless of his or her age — can be a constant battle, its one well worth fighting. A healthy child becomes a healthy adult, and only with your support and guidance will your child be both.

Water: Drink Up!

Water makes up more than half of kids' body weight and is needed to keep all parts of the body functioning properly.

There's no specific amount of water recommended for children, but it's a good idea to give them water throughout the day — not just when they're thirsty.

Babies generally don't need water during the first year of life.

If your child doesn't like the taste of water, add a bit of lemon or lime for flavor.

Fruits and veggies are also good sources of water.

Kids should drink more water when ill, when it's hot out , or when engaged in physical activity.

Recommended Amount of Calories

Here's what the United States Department of Agriculture (USDA) recommends kids get calorie-wise and from each food group for a healthy, balanced diet:

Additional Information from HealthyChildren.org:

• Kids Need Fiber: Here's Why and How
• How to Get Your Child to Eat More Fruits and Veggies
• Making Healthy Food Choices
• Healthy and Unhealthy Choices at Fast Food Restaurants

Home — Essay Samples — Nursing & Health — Eating Habits — The Causes, Effects, And Solution Of Poor Nutrition In Children

The Causes and Effects of Poor Nutrition in Children

• Categories: Eating Habits

About this sample

Words: 1240 |

Published: Nov 22, 2018

Words: 1240 | Pages: 3 | 7 min read

Table of contents

Causes of poor nutrition, what are the effects of bad nutrition (essay), works cited.

• Roblin, J. (2007). The influence of advertising on children’s food choices. Pediatrics & Child Health, 12(2), 105–108.
• Pollert, G. A., Kauffman, M., & Veilleux, J. (2016). The effects of poor nutrition on children. In V. R. Preedy (Ed.), Handbook of Children’s Health: Global and Local Perspectives (pp. 149-159). Springer International Publishing. https://doi.org/10.1007/978-3-319-14526-8_13
• Brown, K. A., & Ogden, J. (2004). Children's eating attitudes and behaviour: A study of the modelling and control theories of parental influence. Health Education Research, 19(3), 261-271.
• Cimino, A., Cerniglia, L., Paciello, M., & Alicart, H. (2019). An exploratory study on eating habits and their relation with psychological well-being in a sample of Italian primary school children. Eating and Weight Disorders, 24(4), 723–733. https://doi.org/10.1007/s40519-019-00680-3
• Contento, I. R. (2008). Nutrition education: Linking research, theory, and practice. Jones and Bartlett Publishers.
• Nwokocha, L. M., & Williams, D. E. (2021). Understanding the global burden of childhood malnutrition: An overview of the causes, consequences, and solutions. Journal of Global Health Reports, 5, e2021035. https://doi.org/10.29392/joghr.5.e2021035
• Lopes, L., Pinto, A., Rodrigues, L. P., & Moreira, P. (2020). Impact of parents’ eating habits and behavior on children’s food intake and preferences. Appetite, 146, 104512.
• Serra-Majem, L., Ribas-Barba, L., & Salvador Castell, G. (2006). What and how much do we need to know about food and nutrition in children and young people? British Journal of Nutrition, 96(S1), S3-S9.
• Skouteris, H., McCabe, M., Swinburn, B., Hill, B., & Busija, L. (2006). A parent-focused intervention to reduce infant obesity risk behaviors: A randomized trial. Pediatrics, 117(5), 1629-1638.
• Veugelers, P. J., & Fitzgerald, A. L. (2005). Effectiveness of school programs in preventing childhood obesity: A multilevel comparison. American Journal of Public Health, 95(3), 432-435.

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Importance of Nutrition During the Infancy and Toddler-Hood Period Essay

As Woody (2007, pp.6-7) argues, occurrences in a child’s early stages of life are primary determinants of developments in a child’s later stages of life. That is, because of the developments and refinement of abilities associated with childhood, occurrences in a child’s early stages of life are primary determinants of later life bodily developments hence, the need for a good growth environment and a balanced nutritional intake.

During infancy and toddler-hood, most children are undergoing a period of rapid development and refinement of bodily systems, a factor that makes it necessary for parents to ensure young children receive the necessary dietary provisions to boost such developments.

Failure to provide kids with required dietary foods can greatly impair development, because of the role played by micronutrients not only in physical development, but also motor, language, brain and neurodevelopment. It is important to note that, before birth, children depend entirely on their mothers for nutritional nourishment, factor that changes immediately after birth (Wooldridge, Isaacs, & Brown, 2007, pp. 219-246).

Immediately after birth, infants depend on their mother’s breast milk for nourishment hence, an important period in a child’s development, because it helps in promoting the child-mother relationship. In addition to development of a healthy relationship, breast milk plays a crucial role of protecting children from diseases hence, reducing chances of postnatal deaths. Introduction of solid foods during weaning marks another period of children’s nutritional life, as caretakers struggle to ensure children receive the required nutrients for appropriate growth.

Nourishing a toddler with nutritive foods is necessary in ensuring children develop required cognitive abilities. As research studies show, failure to provide young children with nutritive foods at this stage may lead to brain maladjustments, which may greatly impair development of other abilities, for example, crawling, walking, and laughing. Good examples of nutrients necessary for brain development include vitamin c and iron (Brotherson, 2005, p.1).

During the toddler-hood and infancy stages, other body systems for example, the hearing and vision systems are also in a process of development, as a child’s interactions with the external environment increases. This makes is necessary for parents to feed their children with required nutrient provisions, necessary for ensuring that the auditory and vision systems develop to their full potential. On the other hand, nutrition also plays a central role when it comes to language development.

Because of the connection between brain development and the role played by nutrition in brain development, nutritional deficiencies can greatly impair language development more so in vocabulary acquisition, for such deficiencies will delay development of brain areas responsible for language processing and articulation (Woody, 2007, pp. 7-12).

In addition to development of the brain, hearing systems, and language acquisition, feeding children with nourishing foods is of great significance when it comes to physical growth and motor development.

During infancy and toddler-hood, children are in a process of developing their physical abilities hence, the rapid increases in weight and height. Biologically, because of the surface area to volume ratio concept, toddlers requires more nutrients supplements as compared to mature people hence, the need to provide toddlers with required foods to avoid development problems and illnesses.

In addition, to meet the toddler’s Basal Metabolic Rate (BMR) needs, there is need for parents to feed children with foods with required nutrients and energy content, which in turn will promote health growth. For example, during infancy and toddler-hood, children are in a process of developing more and strong teeth and bones; processes that their bodies cannot accomplish without the presence of calcium, vitamin D, Zinc, and Iron.

On the other hand, it is important ton note that, human growth and development goes hand in hand with an individual’s health status hence, nutritional deficiencies can greatly impair the overall growth of toddlers’ body functionalities (Specker, 2004, p.1)

A proper nutrition is also of significance when it comes to prevention against health hazards, resulting from the body’s inability to fight diseases and infections. Because of change in the mode of acquiring nutrients immediately after birth, infants and toddlers depend on external foods to nourish their nutrient needs.

Hence, failure to provide such nutrients may greatly impair the working of the immune system, leading to many health risks, for example, anemia; which results iron deficiency in the body (Olney, Kariger, Stoltzfus et Al, 2009, pp. 763-772).

In conclusion, nutrition plays a very important role in determining a toddler’s future life, because lack of required nutrients in the body can greatly impair the development of an individual’s functional abilities not only in childhood, but also in later life stages.

Reference List

Brotherson, S. (2005). Understanding brain development in young children. North Dakota State University. Web.

Olney, D. K., Kariger, P. K., Stoltzfus, R. J., et al. (2009). Development of nutritionally at Risk young children is predicted by malaria, anemia, and stunting in Pemba, Zanzibar. Journal of Nutrition, 139, 4, 763-772. Web.

Specker, B. (2004). Nutrition influences bone development from infancy through toddler Years. The American Society of Nutritional Science, 134, 691s-695s. Web.

Wooldridge, N. H., Isaacs, J., Brown, J. (2007). Nutrition through the lifecycle . Belmont: Thomson Higher Education. Web.

Woody, D. J. (2007). Infant and toddlerhood . Web.

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1. IvyPanda . "Importance of Nutrition During the Infancy and Toddler-Hood Period." March 18, 2024. https://ivypanda.com/essays/importance-of-nutrition-during-the-infancy-and-toddler-hood-period/.

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Changes in Child Nutrition in India: A Decomposition Approach

1 School of Economics and Finance, Xi’an Jiaotong University, Xi’an 710061, China

Anu Rammohan

2 Department of Economics, University of Western Australia, Perth, WA 6009, Australia; [email protected]

Wencke Gwozdz

3 Institute of Household Sciences, Justus-Liebig-University, 35390 Giessen, Germany; [email protected]

4 Department of Intercultural Communication and Management, Centre for Corporate Social Responsibility, Copenhagen Business School, 2000 Frederiksberg, Denmark

Alfonso Sousa-Poza

5 Institute for Health Care & Public Management, University of Hohenheim, 70599 Stuttgart, Germany; [email protected]

Background: Improvements in child health are a key indicator of progress towards the third goal of the United Nations’ Sustainable Development Goals. Poor nutritional outcomes of Indian children are occurring in the context of high economic growth rates. The aim of this paper is to conduct a comprehensive analysis of the demographic and socio-economic factors contributing to changes in the nutritional status of children aged 0–5 years in India using data from the 2004–2005 and 2011–2012 Indian Human Development Survey. Methods: To identify how much the different socio-economic conditions of households contribute to the changes observed in stunting, underweight and the Composite Index of Anthropometric Failure (CIAF), we employ both linear and non-linear decompositions, as well as the unconditional quantile technique. Results: We find the incidence of stunting and underweight dropping by 7 and 6 percentage points, respectively. Much of this remarkable improvement is encountered in the Central and Western regions. A household’s economic situation, as well as maternal body mass index and education, account for much of the change in child nutrition. The same holds for CIAF in the non-linear decomposition. Although higher maternal autonomy is associated with a decrease in stunting and underweight, the contribution of maternal autonomy to improvements is relatively small. Conclusions: Household wealth consistently makes the largest contribution to improvements in undernutrition. Nevertheless, maternal autonomy and education also play a relatively important role.

1. Introduction

Improvements in child health are a key indicator of progress towards the third goal of the United Nations’ Sustainable Development Goals: A universal guarantee of a healthy life and well-being at all ages. Undernutrition puts children at a greater risk of disease vulnerability, also adversely affects their physical, cognitive, and mental development [ 1 , 2 ], may adversely impact productivity in later life [ 3 ] and increase economic inequality [ 4 ].

Globally, India performs poorly across standard child nutritional measures [ 5 ]. For child malnutrition, India ranked 114 out of 132 countries, just ahead of Afghanistan and Pakistan [ 6 ]. Data from India’s nationally representative National Family Health Survey (NFHS), from 1992–1993 to 2015–2016, paint a bleak picture of child nutrition. Although the prevalence of stunting among under-five children decreased from 52% to 38% and underweight declined from 53% to 36% between 1992 and 2016, prevalence is still alarmingly high [ 7 ]. In 2016, India had 62 million stunted children, accounting for 40% of the global share of stunting [ 7 ]. Large regional differences also exist with stunting over 46% and 48% in the states of Uttar Pradesh (India’s most populated state) and Bihar [ 8 ].

These poor nutritional outcomes of Indian children are occurring in the context of high economic growth rates, but with low levels of maternal autonomy. Furthermore, a large body of empirical research has linked greater maternal autonomy to better nutrition of children, particularly girls [ 9 , 10 ]. An improvement in maternal autonomy is expected to improve a mother’s ability to make decisions regarding her children’s health and nutrition; and a more autonomous mother is also likely to have greater access to resources, may lead to the adoption of healthy and diversified diets, improve the nutritional content of diets, contribute to better food hygiene and sanitation, and thereby reduce the risk of infection and disease. Since undernutrition is the outcome of insufficient food intake and repeated infectious diseases [ 11 ], it is imperative to understand the links between household-level socio-economic factors (and in particular the role of maternal autonomy) and the extent to which it manifests into poor nutritional outcomes for children.

The aim of this paper, therefore, is to use the 2004–2005 and 2011–2012 data from the Indian Human Development Survey (IHDS) to conduct a comprehensive analysis of the demographic and socio-economic factors contributing to changes in the nutritional status (HAZ, WAZ and the Composite Index of Anthropometric Failure (CIAF)) of children aged 0–5 years in India. A special focus of our analysis is on the role that maternal autonomy plays in improving child undernutrition. Specifically, we address three key questions: (i) Have there been any changes in the nutritional status of children over the period 2004/2015–2011/2012? (ii) Do the changes differ across regions? (iii) What factors are associated with the changing nutritional outcomes of children, and, in particular, what role does maternal autonomy play?

2. Prior studies

2.1. socio-economic factors associated with child undernutrition in india.

A large body of research has used nationally representative secondary data to investigate the socio-economic factors associated with poor child nutrition in India. These studies find an increase in inequalities for vulnerable groups such as girls and lower socio-economic individuals [ 12 , 13 , 14 , 15 , 16 ]. Pathak and Singh [ 17 ] show that, over the period 1992–2006, the burden of undernutrition was disproportionately concentrated among poor children, with relatively better child nutrition in areas where households can access the Government funded Integrated Child Development Services (ICDS). Launched in 1975, the ICDS Program is a Government of India funded program aimed at improving the nutrition and health status of pre-school age children. In addition, Coffey [ 18 ] finds that state-level variation in neonatal mortality is associated with child heights. These findings are consistent with Subramanyam et al.’s [ 19 ] conclusion that over these 14 observation years, social disparities in undernutrition have either widened or stayed the same.

There is also empirical support for the role of maternal autonomy in influencing child nutrition [ 20 , 21 ]. In the Indian context, Shroff et al. [ 22 ] show that higher maternal autonomy (indicated by access to money and freedom to go to the market) is associated with a decreased risk of stunting among children aged below three years in the state of Andhra Pradesh. Similarly, Shroff et al. [ 23 ] find that maternal household decision-making autonomy is positively associated with weight-for-height (WHZ) and WAZ; while mobility autonomy is positively linked with HAZ when adjusting for birth weight among infants aged 3–5 months. Similarly, Imai et al. [ 24 ] show that maternal autonomy (measured by whether she is allowed to go to market without her husband’s permission) is positively associated with HAZ and WAZ; and Arulampalam et al. [ 25 ] demonstrate that maternal autonomy (a composite measure of decision-making, mobility and financial autonomy) has a significant positive impact on HAZ, but is not associated with WHZ. Interestingly, Imai et al. [ 24 ] further indicate that maternal autonomy is only associated with HAZ at the low end of the conditional distribution. Nevertheless, one recent study [ 25 ] shows that maternal decision-making autonomy is not associated with any of undernutrition outcomes when adjusting for maternal and household socio-economic factors. Thus, empirical evidence is mixed although the majority of studies support an association between child nutrition and maternal autonomy.

Another strand of literature focuses on the role of poor health infrastructure. For example, Paul et al. [ 26 ] attribute the poor nutritional outcomes among Indian children to weak health systems and a policy focus on children aged 3–6 years at the expense of those aged 0–2 years, although much of a child’s growth occurs in the early years. Spears [ 27 ] and Hammer and Spears [ 28 ] further explain poor child nutrition among Indian children in terms of sanitation, arguing that environmental threats from open defecation and exposure to fecal germs reduce nutrient absorption, while exposure to early life disease leads to undernutrition, stunting, and diarrhea. Using data from the NFHS, Spears [ 29 ] shows that open defecation remains exceptionally widespread in India and sanitation has not improved substantially despite rapid economic growth. Although these studies provide useful benchmarks for assessing the links between socio-economic characteristics and child nutrition, they are based on National Family and Health Survey (NFHS) and National Sample Survey (NSS) data sets that are over a decade old.

2.2. Applying Decomposition Analyses to Explain the Socio-Economic Factors Underlying Child Undernutrition in India

The three major decomposition techniques, including Blinder-Oaxaca (BO) linear decomposition, nonlinear decomposition, and quantile-based decomposition, have been used in previous studies in India to analyze the gap in child undernutrition/health between certain groups (such as poor/non-poor, Muslims/Hindu, rural/urban). BO decomposition is used to decompose differences in a continuous variable (e.g., child undernutrition outcome) into a part attributable to differences in characteristics (explained part or endowments part) and a part attributable to coefficients (unexplained part or effects part). Nonlinear decomposition, in essence, employs an extension of the BO decomposition for binary variables (e.g., underweight or stunting). BO decomposition is a mean-based approach, yet covariate and coefficient contributions may differ at different parts of the distribution of undernutrition. Quantile-based decomposition is thus used to explore the contributions of covariates at different quantiles of the outcome distribution. For example, Bhalotra et al. [ 30 ] apply a non-linear decomposition technique [ 31 ] to three waves of the NFHS (1992/1993, 1998/1999, and 2005/2006) to measure the Hindu-Muslim gap in under-five child undernutrition. They show that the 29% difference in stunting between these two groups is mainly attributable to maternal education, maternal age at parturition, and child’s birth year, while the 20% gap in wasting is primarily explainable by maternal education and state of residence. Similarly, Kumar and Singh [ 32 ] apply the BO decomposition method to 2005–2006 NFHS data to measure the gap in under-five child undernutrition between poor and non-poor households in urban India. They identify the main contributing factors as underutilization of health care services, poor maternal body mass index (BMI), and low levels of parental education among impoverished urbanists.

In a regression-based decomposition of the same datasets to assess (concentration index-based) inequalities in under-five child mortality and undernutrition outcomes, Chalasani [ 33 ] identifies wealth and mother’s education as the two largest contributors to severe stunting and severe underweight inequality over the 1992/1993–2005/2006 period. These results are supported by Kumar and Kumari [ 34 ], who use BO decomposition to show that household economic status (wealth score) and parental education are the most significant contributors to the rural-urban gap in childhood undernutrition in India (measured using z-scores of weight-for-age). Similarly, using the 2005–2006 NFHS data, Mazumdar [ 35 ] identifies household wealth and mother’s education as the two largest contributors to inequality in child undernutrition in explaining the child undernutrition inequalities. Van de Poel and Speybroeck [ 36 ], in their earlier BO decomposition of 1998–1999 IDHS data, attribute the observed child undernutrition gap among scheduled castes and scheduled tribes primarily to their lower wealth, education level, and use of health care services. Cavatorta et al. [ 37 ] use Machado and Mata’s conditional quantile decomposition approach [ 38 ] to show that the surprisingly modest height-for-age disparities across six Indian states can be explained by covariate differences in endowment effects.

Summing up, previous analyses of undernutrition changes in pre-school age Indian children point to household economic status (particularly wealth) and maternal education as the two most important contributors. With few exceptions, however, this research predominantly uses BO decomposition, which can provide misleading estimates when the outcome variable is binary and explanatory variables differ substantially across groups [ 39 ]. To the best of our knowledge, only two studies analyze child undernutrition using non-linear decomposition: Bhalotra et al. [ 30 ], who use the Fairlie method to identify Hindu-Muslim disparities in under-five child mortality and undernutrition, and Cavatorta et al. [ 37 ], who employ Machado and Mata’s conditional quantile decomposition technique [ 38 ] to explore the relative contributions of covariates and coefficients over the entire height-for-age distribution. Moreover, we are not aware of previous studies using the Fairlie non-linear decomposition to examine anthropometric failure differences between groups or over time, and the Machado and Mata’s method is not extendable to a detailed decomposition for each determinant. We address both these research gaps and conduct a comprehensive analysis of the demographic and socio-economic factors contributing to changes in the nutritional status (HAZ, WAZ and CIAF) of children aged 0–5 years in India using the IHDS data for 2004–2005 and 2011–2012.

3. Materials and Methods

The data for this analysis are taken from the IHDS 2004–2005 and 2011–2012, a collaborative research program between researchers from the National Council of Applied Economic Research, New Delhi, and the University of Maryland. This nationally representative multi-topic survey was administered to households in 1503 villages and 971 urban neighborhoods across India and the sample includes 384 districts out of a total of 593 identified in 2001 census. Villages and urban blocks (comprising of 150–200 households) form the primary sampling unit (PSU) from which the households are selected [ 40 ]. Urban and rural PSUs are selected using a different design. Specifically, to draw a random sample of urban households, all urban areas in a state are listed in the order of their size with the number of blocks drawn from each urban area allocated based on probability proportional to size [ 40 ]. When the numbers of blocks for each urban area are fixed, the enumeration blocks are then selected randomly with the assistance from Registrar General of India. Drawing on these Census Enumeration Blocks of about 150–200 households, a complete household listing is conducted and a household sample of 15 households is selected within each block. For sampling purposes, some smaller states are merged with nearby larger states. Nevertheless, the rural sample encompasses about half the households that are interviewed initially by NCAER in 1993–1994 in a survey titled Human Development Profile of India (HDPI) and the other half of the samples are drawn from both districts surveyed in HDPI as well as from the districts located in the states and union territories not covered in HDPI [ 40 ]. The first phase, IHDS-I (2004–2005), comprised two one-hour interviews with each household on topics such as health status, education, employment, economic status, marriage, fertility, gender relations, and social capital. The second phase, IHDS-II, was conducted between 2011–2012. A detailed description of sampling design and data quality is available in Reference [ 40 ]. All individual- and household-level data are available for public use [ 41 ].

Our sample is restricted to those households with children born in the five years prior to the survey, where information was available on all our variables of interest. Because data on certain outcome variables of interest are limited, our final pooled sample contains 6445 observations for stunting, 7634 observations for underweight, and 5693 observations for the CIAF.

3.2. Study Variables

3.2.1. dependent variables.

In keeping with the World Health Organization’s reference standards [ 42 ], we measure children’s nutritional outcomes conventionally using z-scores of height-for-age (HAZ) and weight for age (WAZ). According to Waterlow et al. [ 43 ], the height-for-age z-score, expressed in standard deviations from the reference population mean, is a good indicator of nutritional status. Whereas HAZ measures long-term nutrition by showing the cumulative effects of growth deficiency (often associated with chronic insufficient food intake, frequent infections, sustained incorrect feeding practices, and/or low socio-economic family status), WAZ reflects both acute and chronic undernutrition, making it a better single indicator of childhood undernutrition [ 44 ].

Children with z-score values below −2 (below −3) of the reference population are considered undernourished (severely undernourished) [ 42 ]. However, because these conventional undernutrition measures reflect different aspects of anthropometric failure, they cannot individually determine the overall prevalence of child undernutrition in a population, and may underestimate the true extent of undernutrition, primarily due to the overlapping of children into multiple categories of anthropometric failure [ 45 , 46 , 47 , 48 ]. For instance, underweight cannot identify children who are suffering from underweight combined with stunting and/or wasting [ 46 , 47 ]. We address this shortcoming using Svedberg’s [ 48 ] CIAF, an aggregated single anthropometric proxy for the overall estimation of malnourished children. In our analysis, we combine Nandy et al.’s [ 45 ] Group Y, underweight only, with six of Svedberg’s groups [ 48 ]: Group A, no failure; Group B, wasting only; Group C, wasting and underweight; Group D, wasting, stunting, and underweight; Group E, stunting and underweight; and Group F, stunting only (see Table A1 for a detailed classification). CIAF is thus a binary variable for which 0 indicates no failure, and 1 signals one or more anthropometric failures.

3.2.2. Explanatory Variables

Maternal characteristics. We control for mother’s education using four categories: No education, primary, secondary, tertiary and above. As a proxy for mother’s health, we include her BMI measured in kg/m 2 (categorizing into three groups: Underweight for BMI < 18.5, normal for 18.5 ≤ BMI ≤ 24.9 and overweight/obesity for BMI ≥ 25).

Economic characteristics. A household’s economic status is measured using the household wealth index, which is a categorical variable divided into five population quintiles from the poorest 20% to the wealthiest 20% of households [ 49 ]. This index is calculated with Principle Component Analyses (PCA) using 33 dichotomous items measuring household ownership of assets and housing quality. Relative to income and consumption, this measure of wealth is less volatile and thus arguably a better long-run measure of household economic status.

Maternal autonomy. A key advantage of our dataset is the rich array of attitudinal questions that are available on married women’s decision-making authority in the household. Autonomy is regarded as a multidimensional construct, encompassing dimensions such as the ability to make purchases, control over resources, decision-making autonomy both relating to own health care or child’s medical needs [ 50 ]. We therefore categorize maternal autonomy into:

• Decision-making autonomy: A female respondent (child’s mother) is assumed to have decision-making autonomy if she was involved in decision-making either on her own or in conjunction with another household member on: (i) What is to be cooked, (ii) making expensive purchases, (iii) the number of children to have, and (iv) children’s medical needs (decide what to do when a child falls sick).
• Mobility autonomy: The child’s mother is assumed to have mobility autonomy if she can go on her own: (i) To visit relatives/friends, (ii) to the local health center, and (iii) to the local grocery store.

These individual responses are coded as binary indicators which we use to construct two factors: Maternal autonomy in decision-making and mobility using PCA.

Hygiene characteristics. We include three binary variables that capture the level of sanitation and hygiene practiced in the household: Drinking water source (1 if the household’s drinking water is piped or supplied by tube well or hand pump, 0 otherwise), access to a flushing toilet (1 = yes, 0 = no), and hand-washing behavior (1 = yes, 0 = no).

Regional characteristics. The 24 Indian states are classified into six regions as per the regional definitions used in the IHDS data (see Table A2 ). These are: North (comprising of the states of Jammu and Kashmir, Himachal Pradesh, Punjab, Chandigarh, Uttaranchal, Uttar Pradesh, Haryana and Delhi); Central (Chhattisgarh and Madhya Pradesh); East (Bihar, West Bengal, Jharkhand, Odisha); South (Andhra Pradesh, Karnataka, Kerala, Tamil Nadu and Pondicherry); North East (Sikkim, Arunachal Pradesh, Nagaland, Manipur, Mizoram, Tripura, Meghalaya and Assam); and West (Rajasthan, Goa, Maharashtra, Daman and Diu, Dadar and Nagar Haveli and Gujarat). The descriptive analysis of regional changes in child nutrition are based on these six regions.

Other characteristics. Our specifications also include controls for child’s age (in years) and gender (1 = male and 0 = female), father’s education levels (a categorical variable, 1 = no education, 2 = primary, 3 = secondary and 4 = tertiary and above), religion (a categorical variable, 1 = Hindu, 2 = Muslim and 3 = others), caste (a categorical variables, 1 = other, 2 = other backward and 3 = scheduled caste/tribe) and a binary variable for rural residence (1 = rural and 0 = urban).

3.3. Estimation Procedure

Blinder-Oaxaca (BO) decomposition . We use BO decomposition to explain changes in the nutritional measures HAZ and WAZ as a function of selected explanatory factors. The BO decomposition quantifies the distribution differences of factors that explain the average gap, and also identifies differences in these factors’ effects [ 51 ]. The total difference in mean z-scores of our three measures of child undernutrition can be decomposed as follows:

where X ¯ i is a vector of the averaged values of the independent variables and β ^ i is a vector of the coefficient estimates for wave i (here, i = 2004/2005, 2011/2012).

Re-centred influence function regression (RIFR) decomposition . Because covariate and coefficient contributions may differ between the median and tails of the childhood undernutrition distribution, we use RIFR decomposition [ 52 ] to investigate the contributions of demographic and socio-economic characteristics at different quantiles of the unconditional marginal distribution. The RIFR method involves a two-step procedure: First, we calculate an influence function (IF) at each quantile τ of the distribution of the outcome variable (z-score of child undernutrition), as follows:

where q τ   represents the unconditional τ t h quantile of the z -score, f z s c o r e ( q τ ) is the unconditional density of the z -score at the τ t h quantile, and 1 [ z s c o r e ≤ q τ ] is an indicator function for whether the outcome variable is smaller or equal to the τ t h quantile. For each quantile, the coefficient on X for waves 2004/2005 and 2011/2012 are then estimated by regressing the RIF on X :

where q w a v e ,   τ is the unconditional τ t h quantile of the z -score for wave 2004/05 and 2011/12, respectively. θ ^ w a v e , τ is the coefficient of the unconditional quantile regression, which captures the marginal effect of a change in the distribution of X on the unconditional quantile of the z -score.

In the second step, we employ the BO decomposition strategy at different quantiles (25%, 50%, and 75%) calculated by the RIFR:

Both the explained and unexplained parts are then decomposed into the contributions of each covariate at the τ t h quantile in Equation (5), which is in effect analogous to the BO decomposition in Equation (1).

Fairlie’s (1999) non-linear decomposition. Applying standard BO decomposition to a linear probability model provides misleading estimates for binary dependent variables, particularly if the group differences for an influential independent variable are relatively large [ 39 ]. It is therefore preferable to apply a relatively straightforward simulation technique for non-linear decomposition. Accordingly, we estimate the contributions of socio-economic and demographic factors to identified differences in our key undernutrition indicators by employing a non-linear decomposition approach for binary dependent variables. Stunting, underweight, and CIAF are the dependent variables, so the decomposition for the non-linear equation, Y = F ( X β ^ ) , can be expressed as:

where N j denotes the sample size of each wave ( j = 2004/2005, 2011/2012). The function F ( . ) represents a probit model. Two aspects are worth noting: First, the BO decomposition in Equation (1) is a special case of Equation (6) where F ( X i β ) = X i β . Second, in Equations (1) and (6), the first (explained) term on the right indicates the contribution resulting from a difference in the distribution of the determinant of X , and the second (unexplained) term refers to the part attributable to a difference in the effect of the determinants. Equally noteworthy, the second term captures all the potential effects of differences in unobservables [ 39 ]. In keeping with previous research using decomposition, we focus on the explained terms and their disaggregated contribution for individual covariates, which result primarily from the difficulty of interpreting the unexplained part [ 53 ]. The contribution of a variable is given by the average change in the function if that variable is changed while all other variables remain the same. For severe childhood undernutrition in terms of HAZ and WAZ , we use the same specification as in Equation (6).

One potential concern related to Fairlie’s sequential decomposition is path dependence, the possibility that changing the order of variables in the decomposition may produce different results [ 39 , 54 ]. We therefore test the sensitivity of decomposition estimates to variable re-ordering by randomizing their order in the decomposition [ 39 ] using 1000 replications, the minimum number recommended for most applications [ 39 ]. As a robustness check, we also perform an analysis using 5000 replications. These results are not reported here but are available on request.

When reporting the decomposition results for these three decomposition methods, we categorize the disaggregated contributions of the determinants in the explained part into five main dimensions depicted above, namely: Maternal autonomy, maternal characteristics, household economic status, hygiene, and other.

4.1. Descriptive Statistics

As Table 1 shows, stunting, underweight, and anthropometric failure improved significantly over the 2004–2012 period (a 43% to 36% decline in stunting, a 33% to 28% decline in underweight, and a 58% to 50% decline in CIAF). Severe stunting declined from 25% to 18% and severe underweight from 14% to 10%. In keeping with previous research, the CIAF indicates a much higher prevalence of undernutrition than the individual measures [ 45 , 46 , 47 ]. Nevertheless, the improvements within the 7-year timeframe of our analysis are remarkable. These significant improvements in malnutrition are also depicted in the kernel densities of the z-scores stratified by year in Figure 1 . Together with this significant improvement in malnutrition we also observe a large improvement in the economic status of households (household wealth): 6 percentage points increase for the rich and 9 percentage points for the richest households. We also note that the majority of items depicting maternal autonomy have improved.

Kernel density estimates for HAZ and WAZ by year. Notes: Kolmogrov–Smirnov test p -value: HAZ : Combined K–S 0.098; p -value = 0.000; WAZ : Combined K–S 0.062; p -value = 0.000.

Descriptive statistics of nutritional outcomes and covariates, IHDS 2004/2005–2011/2012.

Notes: Mean values are reported for variables in the IHDS 2004/2005 and 2011/2012. Observations for HAZ (stunting/severe stunting) are 3272 in 2004/2005 and 3173 in 2011/2012, respectively. Observations for WAZ (underweight/severe underweight) are 3967 in 2004/2005 and 3667 in 2011/2012, respectively. Observations for CIAF are 2807 in 2004/2005 and 2886 in 2010/2011, respectively. The observations for other independent variables are the same as those of WAZ. The significance of the changes is based on independent t-tests. * p ≤ 0.05, ** p ≤ 0.01, *** p ≤ 0.001.

Regional differences in child nutrition outcomes are presented in Table 2 . The main results in Table 2 are: (i) Large and statistically significant improvements in all nutrition measures in Central; (ii) Although not as large as in Central, all measures improved in the West; (iii) No improvements at all in East and South; (iv) Stunting, underweight and severe underweight improved slightly in the North, although severe stunting has actually gotten worse. Our composite measure has also gotten worse in this region; and finally, (v) in the Northwest, there are no significant changes in our conventional measures, yet a dramatic improvement in our composite measure.

Descriptive statistics (z-score indicators and nutritional status changes between IHDS 2004/2005 and 2011/2012).

Notes: Mean/percentage values are reported for key variables in the IHDS 2004/2005 and 2011/2012. The significance of the changes is based on independent t-tests. * p ≤ 0.05, ** p ≤ 0.01, *** p ≤ 0.001.

4.2. Explaining the Differences in Nutritional Outcomes

4.2.1. bo decomposition estimates.

The results of the conventional BO decomposition for the HAZ and WAZ z-scores are reported in Table 3 . For HAZ and WAZ, we observe that the contributions of the explained part are 9% and 38%, respectively. As regards the separate contributions to the explained part, household wealth is the most important contributor to the improvement in the average values of HAZ (21%) and WAZ (25%). Maternal mobility autonomy accounts for approximately 4% of the improvements in the average values of HAZ and WAZ. Interestingly, we do not find any associations of maternal decision-making autonomy with nutritional outcomes. In order to assess whether the influence of maternal autonomy is associated with a mother’s age, we also split our full sample into two groups (mothers aged ≤25 and mothers aged >25) and rerun the estimates. Results (presented in Table A3 ) indicate that, especially for younger mothers aged ≤25, mobility autonomy is an important contributor explaining 12% (6%) of the difference in HAZ (WAZ). Maternal autonomy matters less for older mothers. We also find that regions (taking East as the reference group as there are no significant improvements of all child undernutrition indicators in this region), in particular, North (−13%) and South (8%), play a relatively important role in explaining changes in HAZ. Note that the negative contribution of North actually implies that this region should actually decrease the national difference in HAZ. We observe no significant contributions in the case of WAZ.

Blinder-Oaxaca (BO) decomposition of socio-economic differences in undernutrition among Indian children under five: IHDS 2004/2005–2011/2012.

Note: The dependent variables are the z-scores of height-for-age (HAZ) and weight-for-age (WAZ). Groups in the explained part are mother’s characteristics (mother’s BMI; mother’s education), household economic situation (household wealth); hygiene (water source; flushing toilet; and hand washing); and others (child age; child gender; father's education; caste; religion; rural resident) and 5 regional binary variables. Standard errors are in parentheses. * p ≤ 0.05, ** p ≤ 0.01, *** p ≤ 0.001.

4.2.2. RIFR Decomposition Estimates

The results of the RIFR decomposition are presented in Table 4 . We observe large differences in malnutrition between the two surveys, particularly at the bottom end of the distributions, and insignificant at the upper end (75th quantile). The decomposition analysis produces three noteworthy findings: First, household wealth makes the largest contribution to the overall explained part for both HAZ and WAZ (panels A and B, respectively), especially at the lower parts of the distribution (for HAZ, 25th quantile: 25%, 50th quantile: 37%; for WAZ, 25th quantile: 22%, 50th quantile: 61%). Second, in the lowest part of the distribution (25th quantile) of HAZ (Panel A), about 4% of the improvements can be explained with maternal characteristics of BMI and education and about 5% and 6% in the median quantile respectively. With regards to WAZ (Panel B), the contribution of maternal characteristics to the explained component becomes even larger, ranging from 6% at 25th quantile to 16% at the median. Third, mobility autonomy’s contribution to the improvement in HAZ ranges from 4% to 5% at the 25th and 50th quantiles, respectively (panel A). Additionally, we also find that regions (North and South) also make a relatively large contribution to the overall explained part for HAZ, though the relative contributions of North and South are much larger at the median level than these at the 25th quantile (North: 14% versus -6%; South: 15% versus 5%). However, we only observe a larger contribution of Southern region (10%) to the overall explained part for WAZ at the median level.

RIFR decomposition of socio-economic differences in HAZ and WAZ among Indian children under five: IHDS 2004/2005–2011/2012.

Note: The dependent variables are the z-scores of height-for-age (HAZ) and weight-for-age (WAZ). Groups in the explained part are mother’s characteristics (mother’s BMI; mother’s education), household economic situation (household wealth); hygiene (water source; flushing toilet; and hand washing); and others (child age; child gender; father's education; caste; religion; rural resident) and 5 regional binary variables. Standard errors are in parentheses. Standard errors are in parentheses. * p ≤ 0.05, ** p ≤ 0.01, *** p ≤ 0.001.

4.2.3. Fairlie Nonlinear Decomposition Estimates

The results of Fairlie non-linear decomposition are presented in Table 5 . As can be seen, the contributions of the explained part vary substantially for the different measures of child undernutrition: 12% for stunting, 8% for underweight, and 40% for the CIAF. For the individual contribution of each dimension in the explained part, household economic status (household wealth) uniformly explains the largest proportion of improvements in stunting, underweight, and anthropometric failure, with contributions of 20%, 24%, and 19%, respectively. Likewise, maternal characteristics (including maternal BMI and education) explain 3% of stunting, 5% of underweight, 7% of anthropometric failure. Maternal mobility autonomy accounts for about 3% of the improvement in all measures. We also find that regions (especially South) play an important role in accounting for the improvements in stunting and CIAF (stunting: 7%; CIAF: 11%). In addition, the Southern region also contributes to around 3% of the improvement of underweight.

Non-linear decomposition of socio-economic differences in stunting, underweight and CIAF among Indian children under five: IHDS 2004/2005–2011/2012.

Note: The dependent variable is a dummy for whether the respondent is suffering or has suffered from stunting, underweight, and/or anthropometric failure. Groups in the explained part are mother’s characteristics (mother’s BMI; mother’s education), household economic situation (household wealth); hygiene (water source; flushing toilet; and hand washing); and others (child age; child gender; father's education; caste; religion; rural resident) and 5 regional binary variables. Bootstrapped-adjusted errors are in parentheses. * p ≤ 0.05, ** p ≤ 0.01, *** p ≤ 0.001.

We also examine severe forms of stunting and underweight (z-score < −3). In Table 6 we note that, once again, household wealth is the most important contributor to improvements in severe childhood undernutrition, accounting for 22% and 20% of the improvement in stunting and underweight, respectively. Maternal mobility autonomy explains around 3% of the variation in both severe underweight and stunting. In addition, the Northern region makes a moderate contribution (9%) to the improvements in severe underweight. The Southern region contributes approximately 4% of the change in severe stunting.

Non-linear decomposition of socio-economic differences in severe stunting and severe underweight among Indian children under five: IHDS 2004/2005–2011/2012.

Note: The dependent variable is a dummy for the respondent is suffering or has suffered from severe stunting and underweight. Groups in the explained part are mother’s characteristics (mother’s BMI; mother’s education), household economic situation (household wealth); hygiene (water source; flushing toilet; and hand washing); and others (child age; child gender; father's education; caste; religion; rural resident) and 5 regional binary variables. Standard errors are in parentheses. * p ≤ 0.05, ** p ≤ 0.01, *** p ≤ 0.001.

Taken together, the results for the BO, non-linear, and RIFR decompositions suggest that household economic status consistently makes the largest contribution to the improvements in child undernutrition, especially at the lower ends of the distributions. The same holds for CIAF in the non-linear decomposition. Maternal characteristics of BMI and education also make a relatively important contribution. Furthermore, regions, in particular, North and South, account for improvements in child undernutrition. The RIFR quantile-based decomposition further indicates that North and South make relatively larger contributions to the total explained part in HAZ, especially at the median level.

5. Discussion

The poor nutritional outcomes for children in India, coupled with the high economic growth rates in recent decades, have been the subject of much research. We contribute to this research by analyzing data from phases I (2004–2005) and II (2011–2012) of the nationally representative Indian Human Development Study in order to provide a comprehensive econometric analysis of the key demographic and socio-economic factors associated with the changes in undernutrition of Indian children under five years. Our study makes a number of important contributions to the literature. First, our analysis provides a comprehensive empirical analysis of the nutritional status of India’s children aged 0–5 years, focusing on changes over the period 2004–2012, using data from the nationally representative Indian Human Development Survey (IHDS). Second, we examine regional differences in child nutrition, with a focus on the regional changes in malnutrition between 2004–2012. Third, we analyze the role of different dimensions of maternal autonomy on child nutrition. Fourth, we identify how much the different dimensions of maternal autonomy as well as the general socio-economic conditions of households contribute to the changes observed in child undernutrition. To identify each dimension’s contribution, we employ both linear Blinder-Oaxaca (BO) and non-linear decompositions [ 55 ], as well as the unconditional quantile technique developed by Firpo et al. [ 52 ].

5.1. Key Findings

Our analysis finds a pronounced improvement in stunting, underweight, and overall anthropometric failure, as well as in severe undernutrition, especially severe stunting. Considering the relative short time period under analysis, these improvements are impressive, with the incidence of stunting and underweight dropping by 7 and 6 percentage points, respectively. However, the CIAF scores reveal a much higher prevalence of child undernutrition, suggesting that conventional undernutrition indicators like stunting, and underweight may underestimate its actual extent. There are, however, large regional differences in child nutritional outcomes. The marked improvements in outcomes are particularly evident in the Central region and in the West, with smaller declines observed in the North. Very little improvement can be observed in the South and East. The positive development in the Central region may be attributable to having a nutrition mission and state-level interventions in maternal nutrition in the Central states of Chhattisgarh and Madhya Pradesh. For example, in the state of the central state of Chhattisgarh, 83% of the beneficiaries with children aged 6–35 months received supplementary feeding under ICDS, with the figure being 60% for those with children under 36–71 months [ 56 ]. In terms of growth monitoring, 88% of the Anganwadi Centers (AWCs) under the ICDS program had access to functional weighing scale, 86% of the Anganwadi workers (AWWs) had correct knowledge of intake of food by pregnant women and in terms of health service delivery personnel, 100% of the ASHAs selected were in post. In contrast in Uttar Pradesh in the North, only 23% (23) of the beneficiaries with children in the 6–35 month (36–71 months) age-group received supplementary feeding under ICDS; only 50% of the AWCs had functioning baby weighing scales and only 85% of the ASHAs had been appointed.

All three decomposition techniques (BO, non-linear, and RIFR) indicate that household economic status (indicated by household wealth) consistently makes the largest contribution to improvements in undernutrition. These results are in line with the descriptive statistics where we observe a large decline in the proportion of children in the poorest household wealth, and echo previous findings by Chalasani [ 33 ], Van de Poel and Speybroeck [ 36 ], and Mazumdar [ 35 ]. Nevertheless, maternal education and BMI also play a relatively important role. Our unconditional-quantile decomposition also confirms that household economic status and maternal characteristics primarily affect the lower ends of the distribution (25% and 50% quantiles) of HAZ and WAZ. This may imply stronger impacts of household wealth, maternal BMI and education on under-five children with lower HAZ and WAZ.

In addition, BO decomposition indicates that regions, especially North and South, also play a relatively important role in accounting for the overall explained part in HAZ. Results from unconditional quantile decomposition further reveal that both regions make a significant contribution to the overall explained part for HAZ, especially at the median level of the distribution. Nonlinear decomposition results demonstrate that both regions also make relatively larger contributions to the improvements in stunting. One possible explanation is the economic growth observed over this period, which could have led to large declines in stunting particularly in the Northern states.

Maternal mobility autonomy makes a relatively small contribution to the improvements in both HAZ and WAZ, ranging from 3%–5%. This finding might be attributable to the possibility that those mothers with higher mobility autonomy are more likely to attend postnatal check-ups, monitor adequate child growth and obtain professional advice on health care [ 23 ]. Interestingly, the contribution of maternal decision-making autonomy is negligible, which is also echoed by Rajaram et al. [ 57 ] using the 2005/2006 NFHS. One possible explanation for this finding is that, even though greater maternal autonomy will improve child nutritional status, this is based on the assumption that women are well-educated, aware of best child-care practices and care about their children [ 25 ]. Thus, without supporting infrastructure and policies, maternal autonomy may come at the expense of less time for child care, particularly for those in the labor market [ 25 ]. Our results also provide evidence that maternal autonomy is particularly important for younger mothers. The United National Children’s Fund’s (UNICEF) conceptual framework for undernutrition defines basic, underlying, and immediate causes of child undernutrition (including individual, household, and environmental factors) [ 58 ]. Generally, our results find that household wealth, maternal BMI, education and autonomy play a key role in the improvements of Indian child undernutrition, which are well in line with the basic causes of child undernutrition in the UNICEF conceptual framework of nutrition; in particular, household access to adequate financial, human, physical and social capital [ 58 ].

5.2. Limitations

Some limitations should be taken into account: First, omitted variables may potentially bias the estimates. For instance, better indicators of maternal health, campaigns/programs/other structural changes, the availability of public health services and environmental factors that may have influenced children’s nutritional status were not included in the model due to data availability. Second, all three decomposition approaches (mean-based BO, Fairlie’s nonlinear and unconditional quantile-base) decompose a difference without assessing causality. Finally, as we have observed in this study, child undernutrition shows a large variation across geographical areas of India. Due to data limitations (most notably small sample sizes), we are unable to explore what drives these spatial heterogeneities of undernutrition at a state or district level [ 7 ].

5.3. Future Research Directions

The limitations of this study point to several future research directions. First, more focused analyses that have detailed information on maternal health, campaigns/programs/other structural changes, the availability of public health services and environmental factors could provide additional insights into the causes of undernutrition. Second, there is a dearth of research on the causal relationship between maternal autonomy and child undernutrition in India. Having appropriate data and a convincing identification strategy is a challenging endeavor for future research. Third, as we have observed, given the huge geographical/regional differences in child undernutrition in India, it is important to assess spatial-temporal heterogeneities across states or even districts. Finally, future research is needed to track the variations in child undernutrition and explore the underlying drivers over a longer time period.

6. Conclusions

As highlighted by the 2013 Lancet Maternal and Child Nutrition Series (MCNS) [ 59 ], the new sustainable development agenda should prioritize all forms of undernutrition, with a special emphasis on nutrition-specific interventions and programs (e.g., addressing the immediate determinants of child undernutrition), nutrition-sensitive programs and approaches (e.g., addressing the underlying determinants of child undernutrition), and building an enabling environment (e.g., addressing the basic determinants of child undernutrition). Our research has highlighted some important factors (household wealth, maternal BMI, autonomy, and education) associated with changes in undernutrition among Indian children. Our analysis also shows, however, that the impressive improvements in undernutrition among children under five in India go well beyond the improvements one would expect based on the developments of these determinants. This observation may well point to the effectiveness of public programs such as the ICDS [ 60 ], which has experienced a funding increase from US$35 million in 1990 to US$170 million in 2000, and a 2005 Indian government decision to give high priority to its expansion. Several other national and regional nutrition and education programs, including the National Midday Meal Scheme, the National Rural Health Mission, the Comprehensive Rural Health Project, the Integrated Nutrition and Health Program, and the Public Distribution System may have contributed to this improvement in undernutrition.

Acknowledgments

This research uses data from the Indian Human Development Studies (IHDS) which was collected by the University of Maryland and the National Council of Applied Economic Research (NCAER), New Delhi. We would like to thank the academic editor and four anonymous referees for valuable comments on an earlier version of this paper. The usual disclaimer applies.

Anthropometric failure groups among children under five.

Source: Based on Nandy et al. [ 45 ]. Note: The theoretical combination of wasting and stunting is not physically possible because a child cannot simultaneously experience wasting and stunting and not be underweight.

Regional definitions: IHDS 2004/2005–2011/2012.

Blinder-Oaxaca decomposition of socioeconomic differences in malnutrition among Indian children under 5: IHDS 2004/2005–2011/2012(mothers aged ≤ 25 vs. mothers aged > 25).

Note: The groups are the same as in Table 3 . The dependent variables are the z -scores of height-for-age ( HAZ ) and weight-for-age ( WAZ ). Groups in the explained part are mother’s characteristics (mother’s BMI; mother’s education), household economic situation (household wealth); hygiene (water source; flushing toilet; and hand washing); and others (child age; child gender; father’s education; caste; religion; rural resident) and 5 regional binary variables. Standard errors are in parentheses. * p ≤ 0.05, ** p ≤ 0.01, *** p ≤ 0.001.

Author Contributions

Conceptualization, P.N., A.R., W.G. and A.S.-P.; Data curation, P.N.; Formal analysis, P.N.; Methodology, P.N.; Software, P.N.; Supervision, P.N., A.R., W.G. and A.S.-P.; Validation, P.N.; Visualization, P.N.; Writing–original draft, P.N., A.R., W.G. and A.S.-P.; Writing–review & editing, P.N., A.R., W.G. and A.S.-P. All authors approved the final manuscript.

This research received no external funding.

Conflicts of Interest

The authors declare no conflict of interest.

Poor Nutrition and its Effects on Learning

How it works

Nutrition is essential to human welfare, however, numerous number of people are badly affected by poor nutrition especially children. Malnutrition is a major concern which ranges from undernutrition to problems of overweight and obesity. It’s usually caused by deficiency in essential vitamins and nutrients needed for intellectual development and learning. The most critical stage for brain development is mainly from conception to the first 2 years of life. It’s highly important that pregnant mothers are given the necessary vitamins and nutrients required to enable the baby develop to its full potential.

Poverty plays a major role in lack of good nutrition and it’s a fundamental cause of malnutrition. Poverty-stricken families don’t have enough funds to spend on food. In most cases, their kids are sent to school without nutritional meal and are unable to concentrate in school.

According to Carlos Lee in his thesis,“Poverty, regardless of level, is robustly linked to reduced academic achievement. Students who live in poverty come to school every day without the proper tools for success. As a result, they are commonly behind their classmates physically, socially, emotionally or cognitively.” Some of the kids tend to become withdrawn or become aggressive towards their peers in school. For instance, a child going to school without have breakfast would make the child absent minded which would lead to lagging behind in class. Several measures has been put in place to eradicate poverty on the long run. However, some of the short term solutions include; Government should provide aids for parents in low-income families, it would enable them gain appropriate education, training, and working skills which would help them get better paid jobs. Also, social workers in schools should identify children from low income households and give them nutritious meals for free. It would help them develop mentally and physically. Another major problem of poor nutrition is caused by change in climate. It affects the society in several ways which includes human health, influences yield from crops, and in most cases alters rainfall that results in drought. For instance, When drought occurs, it leads to severe poverty, food insecurity, and malnutrition. Alice Moyo, project manager for CRS’ vulnerable children programs stated, “Drought is very connected to education in many ways. To start with, there’s no food if there’s drought. Children concentrate less when they’re hungry, and also there’s a lot of running that takes place at school,” To solve this problem, the government should enforce policies on recycling waste water and desert landscaping to enable areas with drought get good clean water. Also, the government can use advanced transportation means to move water from areas where it rains to areas with drought. Lastly, Food insecurity can delay a child’s learning abilities if not attended to.

Research has shown that in the US, a considerable number of kids under the age of 5 live in households that lack adequate quality of food that is needed to improve healthy and energetic living. Anna Johnson, an assistant professor at Georgetown University declared, ‘In our study, food insecurity in infancy and toddlerhood predicted lower cognitive and social-emotional skills in kindergarten, skills that can predict later success in academics and life.’ To this end, it is imperative for the government to provide food pantry in each communities whereby low income families can fed at least twice a day. In conclusion, it is obvious that malnutrition has a major effect on the learning , most especially in third world countries whereby people are affected by poverty, climate change, and food insecurity. The government can do its bit in eradicating poverty but the onus still lies with the entire community who live among the poor to ensure that all the policies are implemented.

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