Stunting affects 160 million pre-school children around the world, and imposes significant costs on a child’s health, cognitive development, schooling and economic performance. Stunting in early childhood has been linked to poor dietary diversity, notably low intake of animal-sourced foods (ASFs) rich in high quality protein and other growth-stimulating nutrients. Surprisingly, however, very little economic research has focused on ASFs and child growth. In this paper we redress this omission through an analysis of 112,553 children aged 6-23 months from 46 countries. We first document distinctive patterns of ASF consumption among children in different regions, particularly highly variable patterns of dairy consumption, low consumption of eggs and meat, and surprisingly frequent consumption of fish in several poor regions of Africa and Asia. We then examine how ASF consumption is associated with child stunting in multivariate models saturated with control variables.

Reducing undernutrition requires improving access to goods and services from a wide range of economic and social sectors, including agriculture, education and health. Yet despite broad agreement on the multisectoral nature of the global burden of undernutrition, relatively little research has analyzed how different dimensions of accessibility, such as urbanization and travel times to urban centers, affect child nutrition and dietary outcomes. In this paper we study these relationships in sub-Saharan Africa, a highly rural continent still severely hindered by remoteness problems. We link spatial data on travel times to 20,000 person cities to survey data from 10,900 communities in 23 countries. We document strong negative associations between nutrition indicators and rural livelihoods, but only moderately strong associations with remoteness to cities. Moreover, the harmful effects of remoteness and rural living largely disappear once education, wealth, and social/infrastructural services indicators are added to the model. This implies that the key nutritional disadvantage of rural populations stems chiefly from social and economic poverty. Combating these problems requires either an acceleration of urbanization processes, or finding innovative cost-effective mechanisms for extending basic services to isolated rural communities.

Since the Sustainable Development Goals (SDGs) were adopted by the United Nations General Assembly in 2015, heads of state and ministers at global convenings have repeatedly expressed commitments in support of achieving SDG2 — Zero Hunger — by 2030. Yet progress toward SDG2 has stalled, owing to economic slowdowns, unforeseen crises, geopolitical conflict, and lackluster investment in agricultural productivity and open trade. Where have commitments to SDG2 fallen short? While SDG2 calls for ending global hunger, food insecurity, and malnutrition by 2030, this brief predominantly focuses on progress and commitments related to hunger and food insecurity. Drawing on the results of two recent studies, the policy brief (1) discusses trends and setbacks toward reducing hunger and food insecurity, (2) analyzes progress on the “means of implementation,” or mix of finances, technology, and policy choices, to address SDG2, (3) assesses 107 commitment statements in support of SDG2 made at 68 global meetings since 2015, and (4) explores how to improve accountability in the commitment-making process to accelerate progress toward Zero Hunger.

This brief examines estimates produced by several recent model simulations and frameworks that focus on the cost of ending hunger as well as progress toward other development goals—estimates that range from US$7 billion to US$265 billion per year. The differences among these estimates are largely attributable to the different targeted objectives and policy questions of each modeling exercise, different investment strategies considered, and varying assumptions about the role of different sectors in reducing hunger.

Cost and affordability of healthy diet (CoAHD) metrics developed in a handful of academic studies have quickly become mainstream food security indicators among major development institutions. The World Bank and FAO now report CoAHD statistics in their widely used databanks, and the UN’s State of Food Insecurity and Nutrition in the World (SOFI) reports CoAHD metrics on an annual basis, with the headline conclusion being that over 3 billion people worldwide cannot afford a healthy diet. While quantifying affordability constraints is indeed a vital addition to the suite of global food security indicators, there is a dearth of scientific analysis on the accuracy and sensitivity of CoAHD methods. Published global CoAHD estimates rely on three implicit assumptions: that demographic differences across countries have little effect on average diet costs; that non-food expenditure requirements have little systematic variation across countries; and that international food price data is representative in a population sense and product coverage sense. Testing these assumptions on the cost of the EAT-Lancet reference diet, we find sizable sensitivity of baseline methods to adjusting diet affordability estimates for systematic cross-country differences in demographic profiles and non-food expenditure requirements, smaller effects of adjusting for inadequate food product coverage in international price data, and inconclusive evidence on issues of urban bias in price surveys. Our proposed methodological improvements significantly change country, regional and global estimates of healthy diet affordability, though not the headline conclusion that several billion people cannot afford a healthy diet. Even so, the accuracy, rigor, and reliability of CoAHD statistics warrant closer investigation given their widespread adoption and utilization.

International food prices have become increasingly volatile in recent decades, with “global food crises” in 2008, 2011 and most recently in 2022. The 2008 crisis prompted international agencies to ambitiously extend their monitoring of domestic food prices in developing countries to strengthen early warning systems and food and nutrition surveillance. However, food inflation by itself is not sufficient for measuring disposable income or food affordability; for that, one must measure either changes in income or changes in an income proxy. Here we propose the use of a low-cost income proxy that can be monitored at the same high frequency and spatial granularity as food prices: the wages of poor unskilled workers. While not all poor people are unskilled wage earners, changes in the real “reservation wages” of low skilled activities are likely to be highly predictive of changes in disposable income for poorer segments of society (Deaton and Dreze 2002). We demonstrate this by estimating changes in “food wages” – wages deflated food price indices – during well-documented food price crises in Ethiopia (2008, 2011 and 2022), Sri Lanka (2022) and Myanmar (2022). In all these instances, food wages declined by 20-30%, often in the space of a few months. Moreover, in Myanmar we use a household panel survey data to show that the decline in food wages over the course of 2022 closely matches estimate declines in household disposable income and proportional increases in income-based poverty. We argue that the affordability of nutritious food for “all people, at all times” is a critically important dimension of food security, and we advocate for monitoring the wages of the poor as a cheap and accurate means of capturing that dimension.

In developing countries macroeconomic volatility is common, and severe negative economic shocks can substantially increase poverty and food insecurity. Less well understood are the implications of these contractions for child acute malnutrition (wasting), a major risk factor for under-5 mortality. This study explores the nutritional impacts of growth shocks over 1990-2018 by linking wasting outcomes collected for 1.256 million children from 52 countries to lagged annual changes in national income. Difference-in-difference estimates suggest that a 10% annual decline in national income increases moderate/severe (WHZ<-2) and severe wasting (WHZ<-3) by 14 and 22 percent. An exploration of possible mechanisms suggests negative economic shocks increase risks of diarrhea, fever, and maternal underweight prevalence, and reduce child dietary diversity. Applying these results to the predicted economic impacts of COVID-19 suggests that millions of pre-school children are at increased risk of wasting and wasting-related morbidity and mortality unless urgent preventative action is taken.

Although the diversification of national food supplies (DFS) is a necessary (but not sufficient) condition for the diversification of diets and for reductions in undernutrition in poor countries, little previous research has analyzed how DFS varies across countries and regions, how rapidly it has changed over time, and what economic, social, and agroecological factors may be driving these observed patterns and trends in DFS. The study addresses those questions through a cross-country analysis. We first review economic theory and evidence on the diversification of production and diets in developing countries, particularly the importance of economic growth and other structural transformation processes, as well as the scope for agroecological factors to shape consumption outcomes in the presence of market imperfections, such as high transport costs. We then construct and analyze a rich cross-country dataset linking a simple DFS indicator—the share of calories supplied by nonstaple foods—with a wide range of economic, social, infrastructural, and agroecological indicators. Descriptive evidence and regression analyses show that several indicators of structural transformation (economic growth, urbanization, and demographic change) are strong predictors of DFS within countries. However, the results also suggest that time-invariant agroecological factors are significantly associated with DFS, such that some countries have exceptionally low or high DFS relative to their level of economic development. We discuss the implications of these findings for food and nutrition strategies, particularly the challenge of accelerating dietary diversification in the absence of sustained and very rapid economic growth and structural transformation, especially in countries where agroecological conditions additionally hinder access to a more diverse food basket.

In most countries and globally, malnutrition rates exceed poverty rates. The World Bank estimates that about 9 percent (689 million) of the global population is poor, yet an estimated 25 percent (2 billion people) suffer from micronutrient deficiencies. Such a discrepancy begs the question: Do standard poverty metrics poorly reflect nutritional needs? The most prevalent methodology for measuring poverty in low- and middle-income countries – the cost of basic needs approach – estimates food baskets that satisfy a dietary energy standard while reflecting consumption patterns of poor households. However, poor households typically consume monotonous diets characterized by large quantities of calorically cheap staple foods that are poor sources of nutrients. This reality creates a circular logic whereby the cost of basic nutritional needs is estimated from populations who are consuming nutritionally inadequate diets. We argue that a healthy diet is a basic need and that the standard used to calculate cost of basic needs food poverty lines should be expanded to satisfy nutritional dietary recommendations, while continuing to reflect context-specific dietary patterns. We develop an approach to estimate food poverty lines that satisfies the food group proportionality associated with healthy diet recommendations while also adhering to observed within-food group consumption patterns of poor households. Furthermore, we address the limitation of estimating a single national food basket – which fails to capture variation in local consumption patterns driven by preferences, availability, and relative prices – by estimating utility-consistent regional poverty lines. We demonstrate the approach using data from Myanmar. Energy-based poverty lines significantly underestimate the cost of acquiring a healthy diet, are severely deficient in multiple micronutrients, and therefore result in a drastic underestimate of the rate of poverty based on a healthy diet standard. The resulting higher cost of basic needs also has important implications for inclusive economic growth strategies and nutrition-sensitive food policies and social protection.

Robust food insecurity indicators are needed for monitoring development targets, humanitarian advocacy efforts, and rationally allocating foreign aid. Longstanding dissatisfaction with the FAO’s undernourishment indicator prompted the development of new metrics in recent decades, including the FAO’s Food Insecurity Experience Scale (FIES) and the unaffordability of healthy diets. However, no previous research has assessed whether food insecurity and poverty indicators are in broad agreement on which countries are insecure/poor, and whether global food insecurity is rising or falling. Unfortunately, this new mix of methods produces mixed messages. At the country level, FIES severe food insecurity is often higher in Latin America and the Caribbean than in Niger and other extremely poor African countries. On global trends, the FAO reports increasing undernourishment and FIES food insecurity over 2014-2022, whereas the World Bank reports monetary poverty declining and healthy diets becoming more affordable. Moreover, trends in FAO food security indicators are not statistically explained by hypothesized factors cited in FAO reports, such as conflict or climate change, and increases in the FAO’s calorie consumption inequality metric are inconsistent with declining income inequality reported by the World Bank. We provide four concrete suggestions to improve food security measurement and monitoring: (1) the FAO should cease modelling undernourishment; (2) new independent studies should re-evaluate the FIES and test new metrics; (3) international agencies should implement coordinated, high-frequency, multi-purpose, open-access surveys; and (4) researchers should further improve the “nowcasting” of poverty and food insecurity for data-scarce crisis contexts.