Empirical studies of factors associated with child malnutrition: highlighting the evidence about climate and conflict shocks

Birth weight mediates the association of maternal undernutrition with child undernutrition prevalence in West Africa

BACKGROUND

Maternal nutritional status before and during pregnancy is an important determinant of foetal health. In West Africa, maternal and child undernutrition remains a major public health problem and it is important to establish the mechanistic pathway linking the two disorders to help address the problem. We therefore assessed the mediating role of low birth weight (LBW) in the relationship of maternal undernutrition with child undernutrition in West Africa.

METHODS

We included recent (2010-2019) DHS data from thirteen West African countries. Poisson regression model with robust standard errors was used to assess the relationship between maternal undernutrition (body mass index and anaemia) and child undernutrition (stunting, wasting, underweight, and anaemia). Structural equation modelling was used to conduct the mediation analysis.

RESULTS

Prevalence of stunting, wasting, underweight, and anaemia among under-five children in West Africa was found to be 32.4%, 8.1%, 20.1%, and 71.5%, respectively. We found children of underweight mothers to be more likely to be undernourished (stunted, wasted, and underweight) and anaemic compared to children of normal-weight mothers. Also, children of anaemic mothers were more likely to be stunted and anaemic but not wasted compared with children of non-anaemic mothers. LBW mediated the observed relationships between maternal BMI and childhood stunting (22.6%), and maternal anaemia and childhood stunting (24.9%), wasting (11.7), and anaemia (6.6%).

CONCLUSION

We found maternal undernutrition to be associated with child undernutrition in West Africa with LBW noted to be a mediator of the observed relationship. We recommend that, to address the child undernutrition problem in West Africa, governments and policymakers must integrate measures to address the burden of LBW.

The Socio-Environmental Determinants of Childhood Malnutrition: A Spatial and Hierarchical Analysis

Despite a remarkable reduction in global poverty and famines, substantial childhood malnutrition continues to persist. In 2017, over 50 million and 150 million young children suffered from acute malnutrition (wasting) and chronic malnutrition (stunting), respectively. Yet, the measurable impact of determinants is obscure. We evaluate proposed socio-environmental related determinants of stunting and wasting across Kenya and Nigeria and quantify their effectiveness. We combine health and demographic data from Kenya and Nigeria Demographic Health Surveys (2003, 2008-2009, 2013, 2014) with spatially explicit precipitation, temperature, and vegetation data. Geospatial and disaggregated data help to understand better who is at risk and where to target mitigation efforts. We evaluate the responsiveness of malnutrition indicators using a four-level random intercept hierarchical generalized logit model. We find that spatial and hierarchical relationships explain 28% to 36% of malnutrition outcome variation. Temporal variation in precipitation, temperature, and vegetation corresponds with more than a 50% change in malnutrition rates. Wasting is most impacted by mother's education, family wealth, clinical delivery, and vaccinations. Stunting is most impacted by family wealth, mother's education, clinical delivery, vaccinations, and children asymptomatic of fever, cough, or diarrhea. Remotely monitored climatic variables are powerful determinants, however, their effects are inconsistent across different indicators and locations.

Climate change impacts on child and adolescent health and well-being: A narrative review

Background

Worldwide, the climate is changing and affecting the health and well-being of children in many ways. In this review, we provided an overview of how climate change-related events may affect child and adolescent health and well-being, including children's mental and physical health, nutrition, safety and security, learning opportunities, and family caregiving and connectedness.

Methods

In this narrative review, we highlighted and discussed peer-reviewed evidence from 2012-23, primarily from meta-analyses and systematic reviews. The search strategy used a large and varied number of search terms across three academic databases to identify relevant literature.

Results

There was consistent evidence across systematic reviews of impact on four themes. Climate-related events are associated with a) increases in posttraumatic stress and other mental health disorders in children and adolescents, b) increases in asthma, respiratory illnesses, diarrheal diseases and vector-borne diseases, c) increases in malnutrition and reduced growth and d) disruptions to responsive caregiving and family functioning, which can be linked to poor caregiver mental health, stress and loss of resources. Evidence of violence against children in climate-related disaster contexts is inconclusive. There is a lack of systematic review evidence on the associations between climate change and children's learning outcomes.

Conclusions

Systematic review evidence consistently points to negative associations between climate change and children's physical and mental health, well-being, and family functioning. Yet, much remains unknown about the causal pathways linking climate-change-related events and mental and physical health, responsive relationships and connectedness, nutrition, and learning in children and adolescents. This evidence is urgently needed so that adverse health and other impacts from climate change can be prevented or minimised through well-timed and appropriate action.

Climate variability, armed conflicts and child malnutrition in sub-saharan Africa: A spatial analysis in Ethiopia, Kenya and Nigeria

Background

Sub-Saharan Africa (SSA) has one of the highest prevalence of malnutrition among children under 5 in the world. It is also the region most vulnerable to the adverse effect of climate change, and the one that records the most armed conflicts. The chains of causality suggested in the literature on the relationship between climate change, armed conflict, and malnutrition have rarely been supported by empirical evidence for SSA countries.

Methods

This study proposes to highlight, under the hypothesis of spatial non-stationarity, the influence of climatic variations and armed conflicts on malnutrition in children under 5 in Ethiopia, Kenya, and Nigeria. To do this, we use spatial analysis on data from Demographic and Health Surveys (DHS), Uppsala Conflict Data Program Georeferenced Event Dataset (UCDP GED), Climate Hazards center InfraRed Precipitation with Station data (CHIRPS) and Moderate Resolution Imaging Spectroradiometer (MODIS).

Results

The results show that there is a spatial autocorrelation of malnutrition measured by the prevalence of underweight children in the three countries. Also, local geographically weighted analysis shows that armed conflict, temperature and rainfall are positively associated with the prevalence of underweight children in localities of Somali in Ethiopia, Mandera and Turkana of Wajir in Kenya, Borno and Yobe in Nigeria.

Conclusion

In conclusion, the results of our spatial analysis support the implementation of conflict-sensitive climate change adaptation strategies.

Undernutrition in children aged 0-59 months by region and over time: secondary analysis of the Burkina Faso 2012-2018 National Nutrition Surveys

The global burden of undernutrition remains high, responsible for significant under-five mortality in resource-limited settings. Numerous sustainable development goals (SDGs) are linked to nutrition, and nationally representative nutrition surveillance is a key activity to track progress towards SDGs and guide efficient programmes.

OBJECTIVES

The aim of this study is to look at spatial and temporal trends in undernutrition in children under 5 years age in Burkina Faso.

SETTING

We used data from annual National Nutrition Surveys using Standardised Monitoring and Assessment of Relief and Transitions methodology (anthropometry, morbidity) over 7 years (2012-2018) in Burkina Faso.

PARTICIPANTS

Children of under 5 years from households selected through systemic sampling at countrywide level.

MAIN OUTCOME MEASURES

Prevalence of stunting (height-for-age z-score, <-2), underweight (weight-for-age z-score, <-2) and wasting (weight-for-height z-score, <-2) at regional and national. We used general linear mixed models, adjusted by age, survey year, sex, presence of fever and/or diarrhoea, and poverty index to quantify the risk of undernutrition over time and by region of residence.

RESULTS

Between 2012 and 2018, decreases were observed overall in the prevalence of growth retardation (stunting) decreased from 33.0% (95% CI 32.3 to 33.8) in 2012 to 26.7% (95% CI 26.2 to 27.3) in 2018. Underweight reduced from 24.4% (95% CI 23.7 to 25.1) to 18.7% (95% CI 18.2 to 19.2) for the same period and wasting decreased from 10.8% (95% CI 10.3 to 11.3) in 2012 to 8.4% (95% CI 8.1 to 8.8) in 2018. However, there was substantial variation across the country, with increased risk of undernutrition in the regions of Sahel, East and Cascades primarily. High-risk regions were characterised by a lower poverty index and limited access to healthcare services.

CONCLUSIONS

Our findings could inform national policymakers in refining and optimising resource allocation based on the identification of high-risk areas.

Causes and consequences of child growth faltering in low-resource settings

Growth faltering in children (low length for age or low weight for length) during the first 1,000 days of life (from conception to 2 years of age) influences short-term and long-term health and survival1,2. Interventions such as nutritional supplementation during pregnancy and the postnatal period could help prevent growth faltering, but programmatic action has been insufficient to eliminate the high burden of stunting and wasting in low- and middle-income countries. Identification of age windows and population subgroups on which to focus will benefit future preventive efforts. Here we use a population intervention effects analysis of 33 longitudinal cohorts (83,671 children, 662,763 measurements) and 30 separate exposures to show that improving maternal anthropometry and child condition at birth accounted for population increases in length-for-age z-scores of up to 0.40 and weight-for-length z-scores of up to 0.15 by 24 months of age. Boys had consistently higher risk of all forms of growth faltering than girls. Early postnatal growth faltering predisposed children to subsequent and persistent growth faltering. Children with multiple growth deficits exhibited higher mortality rates from birth to 2 years of age than children without growth deficits (hazard ratios 1.9 to 8.7). The importance of prenatal causes and severe consequences for children who experienced early growth faltering support a focus on pre-conception and pregnancy as a key opportunity for new preventive interventions.

Investigating the relationship between growing season quality and childbearing goals

Agricultural production and household food security are hypothesized to play a critical role connecting climate change to downstream effects on women's health, especially in communities dependent on rainfed agriculture. Seasonal variability in agriculture strains food and income resources and makes it a challenging time for households to manage a pregnancy or afford a new child. Yet, there are few direct assessments of the role locally varying agricultural quality plays on women's health, especially reproductive health. In this paper we build on and integrate ideas from past studies focused on climate change and growing season quality in low-income countries with those on reproductive health to examine how variation in local seasonal agricultural quality relates to childbearing goals and family planning use in three countries in sub-Saharan Africa: Burkina Faso, Kenya, and Uganda. We use rich, spatially referenced data from the Performance Monitoring for Action (PMA) individual surveys with detailed information on childbearing preferences and family planning decisions. Building on recent advances in remote monitoring of seasonal agriculture, we construct multiple vegetation measures capturing different dimensions of growing season conditions across varying time frames. Results for the Kenya sample indicate that if the recent growing season is better a woman is more likely to want a child in the future. In Uganda, when the growing season conditions are better, women prefer to shorten the time until their next birth and are also more likely to discontinue using family planning. Additional analyses reveal the importance of education and birth spacing in moderating these findings. Overall, our findings suggest that, in some settings, women strategically respond to growing season conditions by adjusting fertility aspirations or family planning use. This study also highlights the importance of operationalizing agriculture in nuanced ways that align with women's lives to better understand how women are impacted by and respond to seasonal climate conditions.

Household behavior and vulnerability to acute malnutrition in Kenya

Anticipating those most at-risk of being acutely malnourished significantly shapes decisions that pertain to resource allocation and intervention in times of food crises. Yet, the assumption that household behavior in times of crisis is homogeneous-that households share the same capacity to adapt to external shocks-ostensibly prevails. This assumption fails to explain why, in a given geographical context, some households remain more vulnerable to acute malnutrition relative to others, and why a given risk factor may have a differential effect across households? In an effort to explore how variation in household behavior influences vulnerability to malnutrition, we use a unique household dataset that spans 23 Kenyan counties from 2016 to 2020 to seed, calibrate, and validate an evidence-driven computational model. We use the model to conduct a series of counterfactual experiments on the relationship between household adaptive capacity and vulnerability to acute malnutrition. Our findings suggest that households are differently impacted by given risk factors, with the most vulnerable households typically being the least adaptive. These findings further underscore the salience of household adaptive capacity, in particular, that adaption is less effective for economic vis-à-vis climate shocks. By making explicit the link between patterns of household behavior and vulnerability in the short- to medium-term, we underscore the need for famine early warning to better account for variation in household-level behavior.

Is stunting in children under five associated with the state of vegetation in the Democratic Republic of the Congo? Secondary analysis of Demographic Health Survey data and the satellite-derived leaf area index

Background

The prevalence of stunting in the Democratic Republic of the Congo (DRC) is one of the highest globally. However, only a few studies have attempted to measure the association between stunting and vegetation, which is an important food source. The leaf area index (LAI) is an excellent measure for the vegetation state.

Objective

This paper intended to measure the association between the LAI and stunting among children under five years of age in the DRC. Its aim was to better understand the boundary conditions of stunting and explore potential links to climate and environmental change.

Methods

This paper adopts a secondary data analysis approach. We used data on 5241 children from the DRC Demographic Health Survey (DHS) 2013-2014, which was collected from a nationally representative cross-sectional survey. We used the satellite-derived LAI as a measure for the state of vegetation and created a 10-km buffer to extract each DHS cluster centroid's corresponding mean leaf-area value. We used a generalised mixed-effect logistic regression to measure the association between LAI and stunting, adjusting the model for mother's education, occupation and birth interval, as well as child's age and national wealth quintile. A height-for-age Z-score (HAZ) was calculated and classified according to WHO guidelines.

Results

Children in communities surrounded by high LAI values have lower odds of being stunted (OR [odds ratio] = 0.63; 95% CI [confidence interval] = 0.47-0.86) than those exposed to low LAI values. The association still holds when the exposure is analysed as a continuous variable (OR = 0.84; 95% CI = 0.74-0.95).When stratified in rural and urban areas, a significant association was only observed in rural areas (OR = 0.6; 95% CI = 0.39-0.81), but not in urban areas (OR = 0.9; 95% CI = 0.5-0.5). Furthermore, the study showed that these associations were robust to LAI buffer variations under 25 km.

Conclusions

Good vegetation conditions have a protective effect against stunting in children under five years of age. Further advanced study designs are needed to confirm these findings.

Prevalence of pneumonia and malnutrition among children in Jigawa state, Nigeria: a community-based clinical screening study

OBJECTIVE

To estimate the point prevalence of pneumonia and malnutrition and explore associations with household socioeconomic factors.

DESIGN

Community-based cross-sectional study conducted in January-June 2021 among a random sample of households across all villages in the study area.

SETTING

Kiyawa Local Government Area, Jigawa state, Nigeria.

PARTICIPANTS

Children aged 0-59 months who were permanent residents in Kiyawa and present at home at the time of the survey.

MAIN OUTCOME MEASURES

Pneumonia (non-severe and severe) defined using WHO criteria (2014 revision) in children aged 0-59 months. Malnutrition (moderate and severe) defined using mid-upper arm circumference in children aged 6-59 months.

RESULTS

9171 children were assessed, with a mean age of 24.8 months (SD=15.8); 48.7% were girls. Overall pneumonia (severe or non-severe) point prevalence was 1.3% (n=121/9171); 0.6% (n=55/9171) had severe pneumonia. Using an alternate definition that did not rely on caregiver-reported cough/difficult breathing revealed higher pneumonia prevalence (n=258, 2.8%, 0.6% severe, 2.2% non-severe). Access to any toilet facility was associated with lower odds of pneumonia (aOR: 0.56; 95% CI: 0.31 to 1.01). The prevalence of malnutrition (moderate or severe) was 15.6% (n=1239/7954) with 4.1% (n=329/7954) were severely malnourished. Being older (aOR: 0.22; 95% CI: 0.17 to 0.27), male (aOR: 0.77; 95% CI: 0.66 to 0.91) and having head of compound a business owner or professional (vs subsistence farmer, aOR 0.71; 95% CI: 0.56 to 0.90) were associated with lower odds of malnutrition.

CONCLUSIONS

In this large, representative community-based survey, there was a considerable pneumonia and malnutrition morbidity burden. We noted challenges in the diagnosis of Integrated Management of Childhood Illness-defined pneumonia in this context.

Can we predict the burden of acute malnutrition in crisis-affected countries? Findings from Somalia and South Sudan

BACKGROUND

Sample surveys are the mainstay of surveillance for acute malnutrition in settings affected by crises but are burdensome and have limited geographical coverage due to insecurity and other access issues. As a possible complement to surveys, we explored a statistical approach to predict the prevalent burden of acute malnutrition for small population strata in two crisis-affected countries, Somalia (2014-2018) and South Sudan (2015-2018).

METHODS

For each country, we sourced datasets generated by humanitarian actors or other entities on insecurity, displacement, food insecurity, access to services, epidemic occurrence and other factors on the causal pathway to malnutrition. We merged these with datasets of sample household anthropometric surveys done at administrative level 3 (district, county) as part of nutritional surveillance, and, for each of several outcomes including binary and continuous indices based on either weight-for-height or middle-upper-arm circumference, fitted and evaluated the predictive performance of generalised linear models and, as an alternative, machine learning random forests.

RESULTS

We developed models based on 85 ground surveys in Somalia and 175 in South Sudan. Livelihood type, armed conflict intensity, measles incidence, vegetation index and water price were important predictors in Somalia, and livelihood, measles incidence, rainfall and terms of trade (purchasing power) in South Sudan. However, both generalised linear models and random forests had low performance for both binary and continuous anthropometric outcomes.

CONCLUSIONS

Predictive models had disappointing performance and are not usable for action. The range of data used and their quality probably limited our analysis. The predictive approach remains theoretically attractive and deserves further evaluation with larger datasets across multiple settings.

Conflict and Climate Factors and the Risk of Child Acute Malnutrition Among Children Aged 24-59 Months: A Comparative Analysis of Kenya, Nigeria, and Uganda

Acute malnutrition affects a sizeable number of young children around the world, with serious repercussions for mortality and morbidity. Among the top priorities in addressing this problem are to anticipate which children tend to be susceptible and where and when crises of high prevalence rates would be likely to arise. In this article, we highlight the potential role of conflict and climate conditions as risk factors for acute malnutrition, while also assessing other vulnerabilities at the individual- and household-levels. Existing research reflects these features selectively, whereas we incorporate all the features into the same study. The empirical analysis relies on integration of health, conflict, and environmental data at multiple scales of observation to focuses on how local conflict and climate factors relate to an individual child's health. The centerpiece of the analysis is data from the Demographic and Health Surveys conducted in several different cross-sectional waves covering 2003-2016 in Kenya, Nigeria, and Uganda. The results obtained from multi-level statistical models indicate that in Kenya and Nigeria, conflict is associated with lower weight-for-height scores among children, even after accounting for individual-level and climate factors. In Nigeria and Kenya, conflict lagged 1-3 months and occurring within the growing season tends to reduce WHZ scores. In Uganda, however, weight-for-height scores are primarily associated with individual-level and household-level conditions and demonstrate little association with conflict or climate factors. The findings are valuable to guide humanitarian policymakers and practitioners in effective and efficient targeting of attention, interventions, and resources that lessen burdens of acute malnutrition in countries prone to conflict and climate shocks.

Conflict and Child Malnutrition: a Systematic Review of the Emerging Quantitative Literature

PURPOSE OF REVIEW

Reduction of child malnutrition in conflict settings is on top of the international agenda on sustainable development. This association between child malnutrition and conflict has been hypothesised in the academic literature but not rigorously examined empirically till recently. This paper reviews the emerging quantitative literature, including conflict as an explanatory variable to understand the aspects of child malnutrition studied and how violent events are associated with child nutritional status. Limitations are also highlighted.

RECENT FINDINGS

Child malnutrition is investigated into its three main dimensions of stunting, wasting and undernourishment computed as z-score. Conflict is mostly studied in terms of duration, number of events, typology and intensity. The emerging literature generally establishes a significant and negative association between conflict and child malnutrition. However, limitations persist and are mainly due to the type of available data.

Sustainable food systems and nutrition in the 21st century: a report from the 22nd annual Harvard Nutrition Obesity Symposium

Food systems are at the center of a brewing storm consisting of a rapidly changing climate, rising hunger and malnutrition, and significant social inequities. At the same time, there are vast opportunities to ensure that food systems produce healthy and safe food in equitable ways that promote environmental sustainability, especially if the world can come together at the UN Food Systems Summit in late 2021 and make strong and binding commitments toward food system transformation. The NIH-funded Nutrition Obesity Research Center at Harvard and the Harvard Medical School Division of Nutrition held their 22nd annual Harvard Nutrition Obesity Symposium entitled "Global Food Systems and Sustainable Nutrition in the 21st Century" in June 2021. This article presents a synthesis of this symposium and highlights the importance of food systems to addressing the burden of malnutrition and noncommunicable diseases, climate change, and the related economic and social inequities. Transformation of food systems is possible, and the nutrition and health communities have a significant role to play in this transformative process.

One planet one health: What about the kids?

Humans in their increasing numbers and wealth are changing ecosystems through accelerated consumption of food, natural resources and energy which continue to cause significant damage to the planet. Using 'stunting in children' as a case study, we show how the traditional siloed (specialist) approaches have failed to reduce stunting world-wide. Despite significant effort, traditional approaches fail to appreciate the interconnectedness of the multiple factors that underpin stunting. We will not improve the lives of the millions of children living in poverty by doing the same things we have always done, rather we need to adopt approaches that recognise the interconnectedness of all the component parts and apply One Health methods designed to solve these intractable problems.

Forecasting transitions in the state of food security with machine learning using transferable features

Food insecurity is a growing concern due to man-made conflicts, climate change, and economic downturns. Forecasting the state of food insecurity is essential to be able to trigger early actions, for example, by humanitarian actors. To measure the actual state of food insecurity, expert and consensus-based approaches and surveys are currently used. Both require substantial manpower, time, and budget. This paper introduces an extreme gradient-boosting machine learning model to forecast monthly transitions in the state of food security in Ethiopia, at a spatial granularity of livelihood zones, and for lead times of one to 12 months, using open-source data. The transition in the state of food security, hereafter referred to as predictand, is represented by the Integrated Food Security Phase Classification Data. From 19 categories of datasets, 130 variables were derived and used as predictors of the transition in the state of food security. The predictors represent changes in climate and land, market, conflict, infrastructure, demographics and livelihood zone characteristics. The most relevant predictors are found to be food security history and surface soil moisture. Overall, the model performs best for forecasting Deteriorations and Improvements in the state of food security compared to the baselines. The proposed method performs (F1 macro score) at least twice as well as the best baseline (a dummy classifier) for a Deterioration. The model performs better when forecasting long-term (7 months; F1 macro average = 0.61) compared to short-term (3 months; F1 macro average = 0.51). Combining machine learning, Integrated Phase Classification (IPC) ratings from monitoring systems, and open data can add value to existing consensus-based forecasting approaches as this combination provides longer lead times and more regular updates. Our approach can also be transferred to other countries as most of the data on the predictors are openly available from global data repositories.

Considering climate and conflict conditions together to improve interventions that prevent child acute malnutrition

Despite early warning signs about threats to food security, humanitarian interventions often lag behind these warning signs. Climate and conflict conditions are among the most important factors preceding food system failures and malnutrition crises around the world. Research shows how conflict and climate conditions can upend functional food and economic systems, but this research does not address the severe health impacts of these conditions on infants and young children. Translating quantitative research findings into humanitarian interventions requires geographical detail, resulting in location-specific alerts of risks of food insecurity. We describe how the use of readily available, spatially referenced quantitative data can support targeted interventions for nutrition resiliency. Effective humanitarian programmes for targeted nutrition interventions require real-time datasets on food security drivers and models that can provide actionable guidance to mitigate negative impacts of conflict and climate conditions on the people most susceptible to food insecurity. Although treatment of acute malnutrition is important, treating existing malnutrition is not enough. Instead, action to prevent acute malnutrition should be taken to minimise suffering and to maximise wellbeing, particularly in contexts prone to worsening climate and conflict conditions.

Agricultural production diversity and child nutrition in Ethiopia

This study investigates how two aspects of agricultural production diversity – farm production diversity and composition of production – relate to child height-for-age and weight-for-height in Ethiopia. We use longitudinal data on child anthropometric measurements, household farm production diversity and farm production composition from the Ethiopia Socioeconomic Survey for 2011, 2013, and 2015 available through the World Bank. Using longitudinal fixed effects models, we show that an increase in farm production diversity reduces the risk of chronic food insecurity (child height-for-age) but has no impact on acute measures of food insecurity (child weight-for-height). Results also suggest that, in a context of poor rainfall, more diversity in farm production can adversely impact child height-for-age, although livestock sales might mitigate that detrimental effect. These findings highlight the importance of considering the relationship between farm-level food production and child nutrition in a context of climate change.

Viewpoint: Agri-nutrition research: Revisiting the contribution of maize and wheat to human nutrition and health

Research linking agriculture and nutrition has evolved since the mid-20th century. The current focus is on child-stunting, dietary diversity and 'nutrient-rich' foods in recognition of the growing burdens of malnutrition and non-communicable diseases. This article concerns the global dietary and health contribution of major cereals, specifically maize and wheat, which are often considered not to be 'nutrient-rich' foods. Nevertheless, these cereals are major sources of dietary energy, of essential proteins and micronutrients, and diverse non-nutrient bioactive food components. Research on bioactives, and dietary fibre in particular, is somewhat 'siloed', with little attention paid by the agri-nutrition research community to the role of cereal bioactives in healthy diets, and the adverse health effects often arising through processing and manufacturing of cereals-based food products. We argue that the research agenda should embrace the whole nutritional contribution of the multiple dietary components of cereals towards addressing the triple burden of undernutrition, micronutrient malnutrition, overweight/obesity and non-communicable diseases. Agri-nutrition and development communities need to adopt a multidisciplinary and food systems research approach from farm to metabolism. Agriculture researchers should collaborate with other food systems stakeholders on nutrition-related challenges in cereal production, processing and manufacturing, and food waste and losses. Cereal and food scientists should also collaborate with social scientists to better understand the impacts on diets of the political economy of the food industry, and the diverse factors which influence local and global dietary transitions, consumer behavioural choices, dietary change, and the assessment and acceptance of novel and nutritious cereal-based products.