The cost of inaction: a global tool to inform nutrition policy and investment decisions on global nutrition targets

Abstract

At present, the world is off-track to meet the World Health Assembly global nutrition targets for 2025. Reducing the prevalence of stunting and low birthweight (LBW) in children, and anaemia in women, and increasing breastfeeding rates are among the prioritized global nutrition targets for all countries. Governments and development partners need evidence-based data to understand the true costs and consequences of policy decisions and investments. Yet there is an evidence gap on the health, human capital, and economic costs of inaction on preventing undernutrition for most countries. The Cost of Inaction tool and expanded Cost of Not Breastfeeding tool provide country-specific data to help address the gaps. Every year undernutrition leads to 1.3 million cases of preventable child and maternal deaths globally. In children, stunting results in the largest economic burden yearly at US$548 billion (0.7% of global gross national income [GNI]), followed by US$507 billion for suboptimal breastfeeding (0.6% of GNI), US$344 billion (0.3% of GNI) for LBW and US$161 billion (0.2% of GNI) for anaemia in children. Anaemia in women of reproductive age (WRA) costs US$113 billion (0.1% of GNI) globally in current income losses. Accounting for overlap in stunting, suboptimal breastfeeding and LBW, the analysis estimates that preventable undernutrition cumulatively costs the world at least US$761 billion per year, or US$2.1 billion per day. The variation in the regional and country-level estimates reflects the contextual drivers of undernutrition. In the lead-up to the renewed World Health Assembly targets and Sustainable Development Goals for 2030, the data generated from these tools are powerful information for advocates, governments and development partners to inform policy decisions and investments into high-impact low-cost nutrition interventions. The costs of inaction on undernutrition continue to be substantial, and serious coordinated action on the global nutrition targets is needed to yield the significant positive human capital and economic benefits from investing in nutrition.

Nutrition, economics, cost, financing, maternal and child health

Key Messages

• New nutrition economic modelling tools were developed to generate estimates of the health, human capital and economic cost of inaction (or not investing) in nutrition, specifically with regards to the World Health Assembly global nutrition targets for stunting, breastfeeding, anaemia and low birthweight (LBW).

• The global annual economic cost of inaction on nutrition is estimated to be US$548 billion for stunting, US$507 billion for breastfeeding, US$274 billion for anaemia (in women and children) and US$344 billion for LBW. Accounting for overlap the analysis estimates that preventable undernutrition cumulatively costs the world at least US$761 billion per year, or US$2.1 billion per day.

• These new tools provide country-level data to inform advocacy, policy decisions and investments by decision-makers.

Introduction

Undernutrition can present itself in many forms, including stunting, wasting, being underweight and deficiencies in vitamins and minerals. Certain populations, such as young children under 5 years, adolescent girls and pregnant women, are more vulnerable to undernutrition, thereby predisposing them to increased risk of morbidity and mortality. Young children who are severely undernourished are up to nine times more likely to die than the children that are well-nourished (UNICEF, 2009), and anaemia is one of the leading causes of maternal mortality (Rahman et al., 2016).

Malnutrition, in all its forms, is responsible for more ill health than any other issue, and the treatment costs are borne by individuals, families as well as public sector health and insurance systems (Katherine et al., 2020). Expensive treatment costs can push poor families further into poverty. Suboptimal physical growth causes life-long susceptibility to illnesses, which leads to lower labour productivity and absenteeism from work, and results in lower lifetime earnings. Poor nutrition during early childhood and adolescence impairs cognitive development, hinders school attendance and reduces attainment, resulting in lost employment opportunities (UNICEF, 2009).

Recognizing the need to address the burden of malnutrition, in 2012 the World Health Assembly (WHA) specified a set of six global nutrition targets by 2025 to achieve:

• A 40% reduction in the number of children under 5 years who are stunted,

• a 50% reduction in the rate of anaemia in women of reproductive age,

• a 30% reduction in rate of low birthweight (LBW),

• no increase in childhood overweight,

• an increase in the rate of exclusive breastfeeding in the first 6 months to 50%,

• a reduction and maintenance of childhood wasting to <5%

This paper presents global, regional, and country level economic costs related to four of the six nutrition targets focused on preventative undernutrition: stunting, anaemia, LBW and exclusive breastfeeding. Since the endorsement of the WHA targets in 2012, there has been an increasing demand for the inclusion of a target on childhood anaemia. This paper includes analysis on the scope of the economic burden of childhood anaemia to support the discussion on the potential inclusion of childhood anaemia in the global nutrition targets.

At present, the world is off course to meet all four of these targets; in fact, the prevalence of anaemia in girls and women has actually increased since 2012 (Cesare et al., 2021). A large number of studies have concluded that progress towards ending these forms of undernutrition needs to be accelerated, and several have estimated the investment required to achieve significant reduction in the burden of stunting, LBW, anaemia and inadequate breastfeeding (Shekar et al., 2017; Scott et al., 2020). Previous studies have quantified the economic costs of malnutrition at the global and regional levels, and for some priority countries, national level estimates exist. However, evidence gaps still exist regarding the human capital and economic consequences of not addressing malnutrition, and existing data are likely out of date. For advocates, policy makers and investors, data on the costs of malnutrition and other social issues are valuable, if not critical, for making a strong case to governments for improved prioritization and resource allocation for nutrition interventions. The cost of inaction is defined as the losses resulting from doing nothing or from not doing more than is already being done in addressing a challenge. In nutrition, these costs might be losses such as illness, lower educational achievement and productivity losses.

To address this gap in economic research, the Cost of Inaction analytical tool was envisioned to generate evidence-based estimates of the health, human capital and economic consequences of current levels of stunting, anaemia and LBW at the country and regional levels. The analytical tool was created in 2023 by Nutrition International. Similarly, to generate national-level estimates on the health, human capital and economic costs of not breastfeeding according to World Health Organization (WHO) recommendations, the Cost of Not Breastfeeding tool, first published in 2019 (Walters et al., 2019), was updated by Nutrition International in 2022 in partnership with Alive & Thrive and Limestone Analytics, with funding from the Government of Canada. Both tools provide a user-friendly online platform for policymakers and advocates to understand the national-level economic costs related to undernutrition for more than 140 countries.

The objective of this paper is to present the economic costs related to inaction on stunting, anaemia in women and children, LBW and exclusive breastfeeding at global, regional and national levels. The Methods section provides an overview of the nutritional deficiencies, the underlying methodology of the tools and the data sources. The Results section presents key findings at the global and regional levels, and provides a spotlight on a few countries, while the data for all 140 countries are available on the online Cost of Inaction (Nutrition International, 2023) and Cost of Not Breastfeeding (Nutrition International and Alive & Thrive, 2022) tools. The Discussion section reflects on the results from the analysis and discusses the potential application and knowledge translation strategies of the tools for advocates, policy makers and investors.

Methods

In this paper, the nutritional conditions of interest are—stunting in children, anaemia in women and children, and LBW and suboptimal breastfeeding in infants.

Stunting

Stunting, or low height-for-age, is defined as being <2 SD below WHO child growth standards median. It is the result of chronic or recurrent undernutrition, usually associated with poor socio-economic conditions, frequent illness, or inappropriate infant and young child feeding and care in the first 1000 days of a child’s life (WHO, 2015a). Stunting is irreversible and leads to decreased cognitive and physical development, productive capacity and poor health and an increased risk of degenerative diseases such as diabetes (UNICEF, 2013). At present, stunting affects 22% of children under 5 years (148 million children) globally (UNICEF, WHO, The World Bank, 2023).

Anaemia

Anaemia is a condition in which the number and size of red blood cells or haemoglobin concentration is lower than normal, diminishing the capacity for blood to transport oxygen around the body. The causes of anaemia are numerous and variable by context.¹ While cause-specific anaemia data by country are not widely available, it is estimated that between 30% and 70% of the cases of anaemia in children, adolescent girls and women are due to iron deficiency, depending on the burden of infection in the population.

Iron deficiency anaemia is associated with lower productivity in adulthood (Marcus et al., 2021), and maternal iron deficiency can lead to increased mortality and adverse pregnancy and newborn outcomes (Black et al., 2013). Many studies have shown an association between iron deficiency anaemia and poor cognitive and motor development outcomes in children (McCann and Ames, 2007), which impacts physical performance (WHO, 2017). In low- and middle-income countries (LMICs), children and women of reproductive age are at the greatest risk of suffering from iron deficiency (Shekar et al., 2017). Currently, almost 30% of girls and women aged 15–49 years (586 million) suffer from anaemia, globally. WHO estimates that globally 41% of all children under 5 years (∼245 million) are anaemic (WHO, 2021a).

Low birthweight

LBW is defined by the WHO as weight at birth <2500 g, and it is a major predictor of neonatal mortality and morbidity (WHO, 2015b). LBW also increases the risk of non-communicable diseases, such as diabetes and cardiovascular diseases later in life (Risnes et al., 2011). At present, LBW impacts ∼14.7% of all live births, ∼19.8 million newborns every year (UNICEF, 2023).

Breastfeeding

Breastfeeding reduces risk of childhood infections, provides optimal nutrition, supports ideal growth, improves cognitive development (Horta et al., 2015; Victora et al., 2016) and is associated with reducing the prevalence of overweight and diabetes later in life. For breastfeeding mothers, it reduces the risk of post-partum haemorrhage and depression as well as premature mortality from breast and ovarian cancer, and type II diabetes in mothers (Chowdhury et al., 2015; Victora et al., 2016). More than 50% of children are not breastfed according to the WHO recommendations (WHO, 2021b). The global rates of early initiation (within the first hour of life), exclusive breastfeeding (for the first 6 months of life) and continued breastfeeding (6–23 months) were 47, 48 and 65%, respectively (UNICEF, 2022). Approximately, 68 million infants (0–5 months of age) are not exclusively breastfed according to WHO recommendations (WHO, 2021b) each year.

The Cost of Inaction tool

The user-friendly Cost of Inaction tool (Figure 1) was developed in Microsoft Excel and is now available as an interactive online analytical tool. It summarizes the national health, human capital and economic costs for malnutrition in over 140 countries and presents aggregate estimates at regional and global levels as well. The tool allows the users to choose a country or region of interest and then generates estimates for the cost of inaction at the country, based on current (as of August 2023) levels of stunting, anaemia and LBW.

Figure 1.

The Nutrition International Cost of Inaction tool

The analytical methods used in the Cost of Inaction tool were drawn from previously published studies on the economic consequences of stunting (Olofin et al., 2013; McGovern et al., 2017), LBW (Black et al., 2008) and anaemia (Horton and Ross, 2003). Some modifications to the methods were necessary to be compatible with the variables contained in open-access data sets.

For each nutritional deficiency or condition, the Cost of Inaction tool calculates health, human capital and economic impact at current prevalence rates. Then, the future economic costs due to mortality and cognitive losses for the cohort of live births (for LBW) and children under 5 years of age (for stunting and anaemia) are projected into the long-term future over their productive years, assuming a 3% discount rate on potential future economic losses as recommended in the Bill and Melinda Gates Foundation Reference Case for Economic Evaluations (Claxton et al., 2014) and the Investment Framework for Nutrition (Shekar et al., 2017). The calculations assumed a long-term mean annual gross domestic product (GDP) per capita growth rate of 3% in each country (International Monetary Fund, 2024). All monetary figures presented are in 2021 US Dollars.

Additional ‘What If scenario’ analysis in this paper was conducted to demonstrate the potential impact of achieving an improvement in the prevalence of malnutrition through action. This analysis is especially beneficial for policymakers hoping to understand the significance of achieving a national-level prevalence target or multilateral agencies setting global targets.

Cost of stunting

Total cases of stunting in a country are calculated by multiplying the stunting prevalence of a given country by the total population of children under 5 years for the latest available year. Then, the total number of under 5-year mortality cases attributable to stunting is calculated by factoring in the relative risk of mortality associated with stunting (Olofin et al., 2013) to the total cases of under 5-year stunting. For non-fatal cases of stunting, these cases are multiplied by the productivity deficit associated with stunting in men and women, respectively (McGovern et al., 2017). While stunting-related mortality is an annual estimate, the non-fatal cases of stunting are divided by five to estimate the incremental number of cases each year in the cohort of children under the age of 5 years. Then, the present value of the lost share of labour income for children is calculated. For all non-fatal cases of stunting, cognitive losses are estimated as 10.86 IQ points lost per case of stunting (Galasso and Wagstaff, 2019) and 1.74 years of education lost per case of stunting (Galasso and Wagstaff, 2019).

Cost of anaemia

For both anaemia in children (6–59 months) and in adolescent girls and women (15–49 years of age), total cases are calculated as the product of the prevalence of anaemia for each group and their respective population. For children, a 2.5% productivity deficit associated with each case of anaemia as calculated by Horton and Ross (2003) is applied. Then, the present value of the future lost share of labour income is calculated. This present value of the future productivity loss due to anaemia is estimated from the point that the children would turn 15 years of age until their health-adjusted life expectancy. The cohort of children with anaemia is defined as children aged 6–59 months; thus, total cases are divided by five to estimate the incremental number of cases each year in the cohort of children under the age of 5 years.

For adolescent girls and women, as they are already within the labour force age range, only current (1 year) losses in wages are estimated as described by Horton and Ross (2003). First, a 4% productivity deficit is applied to those employed in all wage sectors. Then, a further 1% productivity deficit is applied to those employed in the manual labour sector [assumed to be 60% of total active labour force (ILOSTAT, 2021)]. Lastly, for the subset of the population that is employed in the heavy manual labour sector,² a further 12% productivity deficit is applied to their annual wage earnings. Total productivity loss was calculated as the sum of present annual wage earnings lost by the economically active subset of the cohort.

Cost of LBW

Total cases of LBW in a given country for 1 year are calculated by taking the product of the prevalence of LBW and the annual live births estimate. Where country-level LBW prevalence was not available, a regional estimate is applied. The total cases of neonatal mortality resulting from low birth are calculated by applying the relative risk of neonatal mortality associated with LBW (Black et al., 2008) to the total number of cases of LBW. Then, for all non-fatal cases of LBW, cognitive losses are estimated as 10 IQ points lost per case of LBW from Gu et al. (2017). Per Hanushek and Woessmann (2008), loss of 1 IQ point is associated with a 1.07% loss in earnings. Loss in future earnings as a result of mortality and cognitive losses are thus calculated while factoring in the labour force participation rate and labour share of GDP. The present value of the future loss to labour income due to LBW is presented.

The Cost of Not Breastfeeding tool

The Cost of Not Breastfeeding tool was first created and released for 30 countries in 2019 by Alive & Thrive. In 2022, a second version of the tool was developed by Nutrition International and Alive & Thrive. The Cost of Breastfeeding tool is available as a user-friendly interactive online analytical tool that summarizes the results of the global, regional and national analysis of the health, human capital and economic costs of the current prevalence of breastfeeding for more than 140 countries.

Cost of Not Breastfeeding

A description of the underlying methods for Cost of Not Breastfeeding tool can be found in the previously published Walters et al. (2019) article. Suboptimal breastfeeding impacts child health through diarrhoea and pneumonia. The cases and deaths resulting from diarrhoea and pneumonia for each country included in the analysis are available through the Global Burden of Disease database (Institute for Health Metrics and Evaluation, 2020). To estimate the cases and child deaths resulting from suboptimal breastfeeding, the cases are multiplied by the relative risks for each infection pathway (Black et al., 2008) and the current percentage of households in each breastfeeding behaviour category. Additionally, cognitive losses resulting from suboptimal breastfeeding are calculated as 2.62 IQ points lost per case of non-exclusive breastfeeding (Horta et al., 2015; Victora et al., 2016). The potential future income lost due to cognitive losses is calculated in the same fashion as the LBW indicator in the Cost of Inaction tool.

The total potential future income lost due to child mortality is equal to the present value of the product of child deaths and projected GNI per capita, from the year a child turns 15 years of age until the earliest point between the expected retirement at age 65 or the country’s healthy life expectancy.

Suboptimal breastfeeding also impacts maternal health through incidence of breast and ovarian cancers and type II diabetes. To estimate the cases and deaths resulting from breast and ovarian cancers and type II diabetes, the incidence in women is multiplied by the odds ratio (1 − odds ratio) of each condition (Victora et al., 2016) and the current level of breastfeeding in each country. The calculation for maternal mortality only counted for the foregone productive years between the age of mortality until the retirement age or healthy life expectancy.

The total combined economic loss of not breastfeeding is the present value of sum of the health system cost,³ future economic cost of mortality and future economic cost of cognitive losses for each country or region.

Data sources and assumptions

For both tools, data sources used across the indicators for each country include: (1) World Population Prospects data for population data on children under the age of 5 years, total number of adolescent girls and women 15–49 years, total number of adults aged 15–65 years, total number of live births and crude birth rate; (2) United Nations Children’s Fund (UNICEF)/WHO/World Bank Joint Child Malnutrition Estimates (JME) 2023 for stunting prevalence data; (3) WHO, Global Health Observatory repository data on prevalence on anaemia in children aged 6–59 months (from 2021) and adolescent girls and women 15–49 years (from 2022); (4) UNICEF/WHO incidence of LBW estimates (from 2023); (5) neonatal, infant, and child mortality data from the UN Inter-agency Group for Child Mortality Estimation; (6) labour force participation information and labour share of GNI from International Labour Organization modelled estimates (from 2020); and (7) WHO, Global Health Observatory Data Repository (from 2019) data for healthy life expectancy data; (8) Gross National Income estimates and from World Development Indicators (from 2021). Additional sources from 2021 used in the Cost of Not Breastfeeding tool include (1) Global Burden of Disease, (2) UNICEF Infant and Young Child Feeding estimates, (3) UNICEF Diarrhoea and Pneumonia estimates, (4) WHO CHOICE healthcare cost data and (5) International Diabetes Foundation diabetes prevalence and cost data. For both tools, all economic costs are adjusted by a social discount rate of 3% and a GNI growth rate of 3%.

Results

Global and regional results

Health and human capital impact

Stunting, suboptimal breastfeeding, and LBW are significant contributors to child mortality. Globally, annual deaths related to these issues are estimated to be 1.3 million, 424 000 and 478 000 deaths, respectively. The mortality estimates from stunting, LBW and suboptimal breastfeeding cannot be added up due to significant overlaps in the population they affect. Suboptimal breastfeeding leads to 135 million cases of diarrhoea and 2 million cases of pneumonia each year. Stunting, LBW and suboptimal breastfeeding also contribute to cognitive losses in children. Globally, it is estimated that 304 million IQ points are lost to stunting, 168 million IQ points to LBW and 195 million IQ points to suboptimal breastfeeding each year. Additionally, stunting and suboptimal breastfeeding contribute to ∼49 million and 68 million school years lost in children per year, respectively.

Regionally, each year, sub-Saharan Africa experiences the highest number of cases of stunting and anaemia in children under the age of 5 years, and the highest stunting and suboptimal breastfeeding-related child mortality. The region experiences an estimated 811 000 preventable stunting-related deaths, 246 000 suboptimal breastfeeding-related child deaths and 9900 maternal deaths each year. South Asia experiences the highest burden of LBW with 212 000 neonatal deaths per year and 7 million cases each year. South Asia also accounts for 40% of the global cases for anaemia in women and girls, which amounts to 247 million anaemic girls and women.

North America experiences the lowest prevalence of breastfeeding, resulting in 2.65 million cases of diarrhoea, and 89 000 cases of pneumonia each year.

Economic cost

The global annual economic costs related to stunting and suboptimal breastfeeding are similar: US$548 billion and US$507 billion, respectively. LBW-related deaths and cognitive losses have an economic cost of US$344 billion in the world. Anaemia in women and children leads to loss of productivity, and the lost economic potential is approximately US$161 billion per year for children, and US$113 billion per year for adolescent girls and women. Similar to mortality, the economic costs from stunting, suboptimal breastfeeding, and LBW cannot be summed up, as there are significant overlaps in the populations they affect. If an aggregate on cost of undernutrition is to be estimated from the tools, the authors suggest a conservative approach of adding the maximum estimate among the costs of stunting, LBW, and not breastfeeding to the cost of anaemia in adolescent girls and women, and the cost of anaemia in children aged 6–59 months who are anaemic but not stunted (Tran et al., 2019; Christian et al., 2023). Using this method, it is clear, that at the current prevalence levels, undernutrition costs the world at least US$761 billion per year, or US$2 billion per day. The annual economic cost per individual is US$96.5.

Figure 2 reflects annual absolute economic costs by region for each condition. For regional classification, the World Bank regional aggregates are used. There are three key parameters that impact the economic cost results—prevalence rate, population size and GNI of the countries included in the region. Even though Sub-Saharan Africa has the highest prevalence of stunting, East Asia and the Pacific has the highest absolute economic cost related to stunting since the aggregate GNI of the countries in East Asia and the Pacific is more than 10 times higher than the aggregate GNI of Sub-Saharan Africa. Thus, the economic estimates should be interpreted with this contextual understanding. East Asia and the Pacific region have the highest absolute cost of stunting, anaemia in children and anaemia in women, among all regions, due to high GNI per economically active adult. North America has the lowest prevalence of optimal breastfeeding of all the regions, and one of the highest GNI per economically active adult. Therefore, North America’s economic burden of LBW and suboptimal breastfeeding is the highest.

Figure 2.

The absolute cost of current levels of undernutrition by region (US$ billion)

When economic costs are interpreted in the context of the GNI, the true burden of undernutrition becomes evident—Sub-Saharan Africa has the highest economic cost related to each condition as a % of GNI. For stunting, anaemia and LBW, South Asia has the second highest economic costs. For suboptimal breastfeeding, the second highest economic costs are in North America. Figure 3 presents the economic costs associated with each condition as a percentage of GNI for different regions.

Figure 3.

The cost of current levels of undernutrition by region as a percentage of GNI

Case studies: country-level results

The tables below present the number of annual cases, deaths and economic costs of inaction for six selected countries for comparison purposes (Ecuador, Ethiopia, India, Indonesia, Mexico, Nigeria) at their current rates of stunting, anaemia in children, anaemia in adolescent girls and women of reproductive age, LBW and suboptimal breastfeeding. These countries together contain 33% of the population of all LMICs. These economies bear disproportionate repercussions from the growing burden of malnutrition from the global viewpoint. To show the variation in the burden of malnutrition, the focus countries include three upper-middle income countries, two lower-middle income countries and one low-income country. The online Cost of Inaction tool provides detailed data for nearly 140 countries. It is important to note that each country’s case should be studied with context since each country’s social, political and economic determinants of malnutrition are unique.

Health impact

Table 1 presents the health impacts of current levels of malnutrition in the focus countries. While India has the largest burden on stunting, anaemia and LBW cases, Nigeria has the largest number of cases of diarrhoea due to suboptimal breastfeeding. Among deaths, while India suffers from the largest number of deaths due to LBW of the focus countries, Nigeria accounts for the largest number of deaths due to stunting, as well as suboptimal breastfeeding.

Table 1.

The annual health impact of stunting, anaemia, LBW and exclusive breastfeeding at current levels in six countries

	Stunting			Anaemia (women)		Anaemia (children)		LBW			Suboptimal breastfeeding
Country	Rate (%)	Cases	Child deaths	Rate (%)	Cases	Rate (%)	Cases	Rate (%)	Cases	Child deaths	Rate (%)	Diarrhoea cases	Child and maternal deaths
Ecuador	22.7	67 725	765	17.2	823 469	23.5	63 137	10.6	32 089	323	39.6	445 287	622
Ethiopia	34.4	1 238 226	52 018	23.9	7 231 593	52.1	1 678 326	13.2	527 394	20 088	58.8	3 301 163	13 916
India	31.7	7 265 228	186 676	53	196 161 823	53.4	11 031 953	18.2	4 234 879	109 774	58.0	9 406 596	78 979
Indonesia	31.0	1 383 546	25 859	31.2	22 174 388	38.4	1 544 013	9.9	447 986	7752	50.7	4 256 330	12 321
Mexico	12.6	246 241	3102	15.3	5 252 617	21.7	383 653	10.2	193 222	2382	27.1	2 185 472	5504
Nigeria	34.2	2 401 735	248 961	55.1	27 541 126	68.9	4 322 252	7.3	592 146	32 899	28.7	12 317 480	97 318

Economic cost

Table 2 presents the total annual economic cost of current levels (as of August 2023) of stunting, anaemia, LBW and suboptimal breastfeeding. India experiences the highest absolute economic costs for all undernutrition burdens. Of all the conditions, stunting has the highest economic cost overall. The single highest economic cost as a percentage of GNI is due to stunting in Nigeria (10.7%), and the second highest is in Ethiopia (5.9%).

Table 2.

The annual economic cost of stunting, anaemia, LBW and exclusive breastfeeding at current levels in six countries

	Stunting			Anaemia (women)			Anaemia (children)			LBW			Breastfeeding
Country	Total costs (US$)	Total costs (% GNI)	Per individual (US$)	Total costs (US$)	Total costs (% GNI)	Per individual (US$)	Total costs (US$)	Total costs (% GNI)	Per individual (US$)	Total costs (US$)	Total costs (% GNI)	Per individual (US$)	Total costs (US$)	Total costs (% GNI)	Per individual (US$)
Ecuador	2.9B	2.6	163	185M	0.2	10	338M	0.3	19	724M	0.6	40	910.7M	0.9	53
Ethiopia	7.5B	5.9	61	353M	0.3	3	1.1B	0.9	9	1.8B	1.4	15	961.7M	0.9	8
India	86B	2.6	61	8.5B	0.3	6	17B	0.5	12	30B	0.9	22	15.8B	0.5	11
Indonesia	29B	2.2	104	2.4B	0.2	9	3.9B	0.3	14	5.0B	0.4	18	5.0B	0.4	18
Mexico	12B	0.8	91	989M	0.1	8	2.3B	0.2	18	4.9B	0.4	38	7.4B	0.6	56
Nigeria	48B	10.5	221	3.2B	0.7	14	7.8B	1.7	36	6.2B	1.4	29	12.5B	2.8	56

Note: M, million; B, billion.

The estimated total annual aggregate economic costs are highest for India and Nigeria, at US$102 billion and US$56 billion, respectively. It is evident that total economic cost of undernutrition varies hugely by regions and socioeconomic factors, ranging from 12.2% of the GNI in Nigeria to 1.0% in Mexico. Ecuador, which reports some of the lowest cases and deaths among the five economies, still estimates US$3 billion in combined economic losses from stunting and anaemia in women and children. The economic cost of anaemia in children is estimated to be consistently higher than the economic cost in women in this model, as anaemia in children is assumed to impact their lifetime earnings, while only women’s current earnings are included. The model also does not include intergenerational effects of anaemia in pregnant women who pass on negative health and developmental effects to newborns and may not capture the full costs of anaemia in women due to health care costs, caregiving or mental health. The results of all the other small-, medium-, large-sized countries are available on the Cost of Inaction tool. In the other countries, the estimated combined cost of stunting and anaemia ranges from 0.1 to 14.2% of GNI (median = 1.2%). Each country in this analysis—no matter the size of the population or economy—has a lot to gain from investing in corrective nutrition policies, actions and investments.

Benefits of reaching a target (‘What if scenario’)

A further ‘What if scenario’ analysis was conducted to estimate the potential benefits of making progress on the current prevalence of nutritional deficiencies. Table 3 presents the cases, deaths averted and economic losses averted if the focus countries were to achieve the targets set out in the WHA global nutrition targets for 2025. As there is not currently a global nutrition target for anaemia in children, a hypothetical scenario of 50% reduction in prevalence from 2012 levels (similar to the Global Nutrition target for anaemia in women) is assumed.

Table 3.

The annual economic benefits of achieving the WHA targets on stunting, anaemia, LBW and exclusive breastfeeding in six countries

	Stunting			Anaemia (women)			Anaemia (u5)			LBW			Breastfeeding
Country	WHA target (%)	Total Losses Averted (US$)	Total Losses Averted (% GNI)	WHA target (%)	Total Losses Averted (US$)	Total Losses Averted (% GNI)	Target (%)	Total Losses Averted (US$)	Total Losses Averted (% GNI)	WHA target (%)	Total Losses Averted (US$)	Total Losses Averted (% GNI)	WHA target (%)	Total Losses Averted (US$)	Total Losses Averted (% GNI)
Ecuador	13.8	1.1B	1.0	8.6	92M	0.1	12.5	158M	0.1	7.9	184M	0.2	50	151M	0.1
Ethiopia	21.1	2.9B	2.3	11.2	187M	0.1	25.3	565M	0.4	9.2	547M	0.4	70	228M	0.2
India	27.0	13.0B	0.4	26.6	4.2B	0.1	29.0	7.6B	0.2	15.1	5.2B	0.2	70	4.0B	0.1
Indonesia	21.0	9.2B	0.7	13.5	1.4B	0.1	18.5	2.0B	0.2	7.1	1.4B	0.1	70	1.8B	0.2
Mexico	8	4.3B	0.3	7.9	478M	0.1	12	1.0B	0.1	5.6	2.2B	0.2	50	2.2B	0.2
Nigeria	18	23B	5.0	27.4	1.6B	0.3	36	3.7B	0.8	5.1	1.9B	0.4	50	3.1B	0.7

Notes: The economic costs from stunting, suboptimal breastfeeding and LBW cannot be summed up, as there are significant overlaps in the populations they affect. If an aggregate on cost of undernutrition is to be estimated from the tools, the authors suggest a conservative approach of adding the maximum estimate among the costs of stunting, LBW, and not breastfeeding to the cost of anaemia in adolescent girls and women, and the cost of anaemia in children aged 6–59 months who are anaemic but not stunted (Tran et al., 2019; Christian et al., 2023). M, million; B, billion.

The findings from the Table 3 highlight that significant health and human capital gains can be achieved through evidence-based action. It is evident that significant potential economic gains can be made if the countries were to achieve the WHA global nutrition targets. When accounting for economic costs as a percentage of GNI, it is evident that Nigeria is estimated to benefit the most from achieving these improvements (up to an additional 6% of the GNI). Nigeria also has the highest present value of economic losses averted, approximately US$27 billion. India is expected to have the second highest present value of economic losses averted at US$22 billion. Additional ‘What If scenario’ analysis could be conducted by countries to inform and influence advocacy, policy decisions and investments at the national level or for the 2030 WHA global nutrition targets.

Discussion

Governments and development partners need evidence-based data to understand the true price of inaction on malnutrition and the benefits of investing in reducing malnutrition now and in the future. As the analysis demonstrates, the price of stalled progress towards the global nutrition targets is both substantial and enduring. The total global economic cost of undernutrition is estimated to be at least US$761 billion each year, representing 1.0% of global aggregate GNI, and ranges up to 3.2% and 6.8% of GNI in high-burden regions such as South Asia and Sub-Saharan Africa, respectively. These numbers reflect the millions of infants, children and women permanently affected by the lack of nutrition progress, and whose physical and cognitive deficits will adversely impact labour productivity and their contributions to national economies both now and into the future. The health, human capital and economic cost of inaction on nutrition—which are largely preventable with existing low-cost, high-impact interventions—create barriers to meaningful progress on social development, reinforce existing inequities, and keep countries locked in intergenerational cycles of poverty. This should serve as a ‘wake-up call’ to the stakeholders within the nutrition space to demonstrate more commitments to increased investments on high-impact nutrition interventions to accelerate progress towards the renewed WHA global nutrition targets and the Sustainable Development Goals towards 2030.

Unmade progress on malnutrition also generates new and significant costs that both health systems and their users will bear moving forward. When a population is undernourished, they are more vulnerable to preventable infections and diseases, leading to increased spending on healthcare and treatment. Persistent malnutrition in at-risk populations, including infants, young children and pregnant women, can also be life-threatening. Malnutrition impacts school performance and educational attainment, in turn affecting workforce capabilities and performance. Nutrition is foundational for human capital and economic development.

Previous studies have provided either a methodology for determining the cost of malnutrition of selected countries or global estimates have shown to be powerful for advocacy with governments, industry and the public for informing nutrition policy decisions, actions and investments. However, the Nutrition International Cost of Inaction and Cost of Not Breastfeeding tools provide evidence-based data that is updated regularly for indicators related to the health, human capital and economic costs of malnutrition for over 140 countries, mostly LMICS, for the first time. These publicly available nutrition economic modelling tools are a useful resource for LMICs by providing instant, evidence-based estimates for the health economic burden of malnutrition, as an alternative to costly and time-consuming in-depth studies to attain similar estimates.

The next few years will usher in important opportunities to accelerate progress towards the WHA targets. With the upcoming 2025 Nutrition for Growth Summit and plans to refresh and extend the WHA targets to 2030, these tools could play an important complementary role as governments consider their own priorities and commitments between now and the end of the SDG period.

Limitations

These economic modelling tools for nutrition advocacy have certain limitations, including data gaps and an efficiency-quality trade-off. For example, data on the prevalence of LBW are not consistently available across all countries. In such cases, regional prevalence is used as a proxy. Similarly, not all countries conduct surveys each year, thus modelled estimates from the JME, and WHO are used in order to utilize data for all countries. The source data comes from open-source data sets such as Demographic and Health Surveys, Multiple Indicator Cluster Surveys, etc., and thus may differ from the latest available survey from a given country, or their national nutrition surveys. The tools at present do not have the capacity to provide subnational cost of inaction on malnutrition, as there is very limited standardized subnational data. Future analyses could include the costs of other forms of malnutrition, such as childhood obesity, wasting, neural tube defects and nutrition preventable non-communicable diseases.

Policy, advocacy and investor implications

Past experience with the first version of the Cost of Not Breastfeeding tool by Alive & Thrive and Nutrition International, the similar Nutrition International Multiple Micronutrient Supplementation (MMS) Cost-Benefit tool (Verney et al., 2023) and testing of the Nutrition International Cost of Inaction tool have shown that evidence-based nutrition modelling tools with user-friendly web-based interfaces respond to identified needs for better data for decision-making, and help advance the agenda for ending malnutrition by facilitating the rapid creation and dissemination of critical insights for advocates, policymakers and investors at the subnational, national and global levels.

The Cost of Not Breastfeeding tool has contributed to policy impact cited in Indonesia, Timor-Leste, Malaysia, Vietnam, Philippines and West Africa, and furthermore used in country-level World Breastfeeding Week advocacy events worldwide and in regional advocacy forums including the Association of Southeast Asian Nations and Inter-Parliamentary Union. As well, the tool has been used at the global level for the Global Breastfeeding Collective Investment Case and has been cited in WHO, Food and Agriculture Organization and UNICEF guidelines. Since 2019, the MMS Cost-Benefit tool has been utilized for advocacy and policymaking purposes in South Africa, Niger, Kenya, Tanzania, Senegal, Ethiopia, Mexico, Indonesia and others, as well as in Pakistan and Nigeria as part of implementation research projects to inform government decision-making on scaling maternal health interventions. At the global levels, the NI MMS Cost-Benefit tool was used for analysis that informed the WHO antenatal care guidelines update on MMS (WHO, 2020). The Cost of Inaction tool aims to build on these experiences on the issues of stunting, anaemia and LBW nationally and globally. All of these tools excel in the simplification of complex economic analysis, which is critically important for making essential data understandable for advocates, policy decision-makers and potential investors to inspire the allocation of domestic and global resources towards nutrition.

For advocates, the data generated from the Cost of Inaction tool can play a significant role in framing the anticipated costs and benefits of investing to achieve 3 of the 6 WHA targets with global, regional and national audiences. The tool also increases the capacity of advocates to communicate across sectors, including with stakeholders involved in the design of national budgets. Target users include members of the Scaling Up Nutrition movement, its donors and partners. Target use cases include supporting nutrition commitment making, such as the Nutrition for Growth Summit, annual national budget planning, in conjunction with the Global Financing Facility’s Investment Cases for Nutrition at the global and country-level, amongst others. The user-friendly nature of the tools is conducive to sharing results with non-technical audiences via social media and with journalists to write articles with the country-level cost of inaction. For policymakers at the regional, national and subnational levels, the data can be included to justify further detailed analyses or included in budget briefs, multisectoral nutrition action plans, or investment cases to justify allocations towards nutrition interventions. At the global level, the Cost of Inaction tool would be useful in the updating of the WHA global nutrition targets for 2030. For philanthropic investors, the analysis of the Cost of Inaction tool can support the assessment of priorities for potential investments at the country level or selection of thematic areas for investment.

The case for revising the WHA target for anaemia to include children (6–59 months)

In addition to the above use cases for action on four existing WHA targets, the tool provides data for potential use by the WHA to consider the economic argument for the revision of the WHA Global Nutrition target on anaemia to include children (6–59 months) in addition to women of reproductive age. The analysis contained in the Cost of Inaction tool suggests that the economic costs of anaemia in children are substantial. With the existence of scalable, evidenced-based interventions including large-scale food fortification, iron supplementation and micronutrient powders, a potential target on anaemia in children seems to be valuable and potentially more feasible to achieve in the foreseeable future. This economic argument uncovered by the Cost of Inaction tool supports the proposal made during the 2021 Nutrition for Growth (N4G) summit discussions on the potential to modify the existing WHA Global Nutrition Target of ‘achieve a 50% reduction of anaemia in women of reproductive age’ to add ‘and children’ to the target phrasing.

Conclusion

While the price of unmade progress towards the global nutrition targets on undernutrition remains unacceptably high, there are many proven interventions, policies and programmes that have multisectoral benefits for the health and human capital of economies. Greater nutrition investments, which are smart, cost-effectiveness and scalable, are critically needed from governments and donors to prevent additional health, human capital and economic costs from undernutrition, and to meet WHA nutrition targets. As the global debt burden continues to grow in the wake of COVID-19, the fiscal space for social spending is shrinking, and political will for preventive actions is declining. Policymakers need credible, relevant data to understand the trade-offs for their investments both now and into the future. The data made available through the Nutrition International Cost of Inaction tool present a strong case for focused, intentional investments to reach the WHA targets, to avert future GDP losses, reduce unwanted additional costs, and ensure their populations make enduring progress towards the end of poverty.

Data Availability

The data underlying this article were derived from sources in the public domain and are listed in the Data sources and assumptions section. It can be shared on reasonable request to the corresponding author.

Funding

This research was funded by Nutrition International with a grant from Global Affairs Canada.

Acknowledgements

Nutrition International would like to thank Dr Michelle Gaffey and Prof. Sue Horton for their work that contributed to the initial underlying economic model of the Cost of Inaction tool. The authors are grateful to the Nutrition International Global Technical Services unit, especially Dr Mandana Arabi, Alison Greig and Dr Daniel Lopez De Romana, and the Communications and Advocacy units for their critical contribution to the methodology and design of the model. Nutrition International would also like to thank Alive & Thrive for their collaboration on the Cost of Not Breastfeeding Tool.

Author contributions

The manuscript was conceived by D.W., S.J. and S.A. Also, S.J., S.A., Z.R. and B.C. conducted the analyses. D.W., S.J. and S.A. drafted the manuscript. All authors provided a critical review of the analyses and manuscript, and approved the final submitted manuscript.

Reflexivity statement

The authors include one female, the primary author and creator of the Cost of Inaction tool, and four males. The first and second authors are citizens of LMICs, and three are from HICs. The authors together bring a variety of backgrounds in education, including health economics, global development, policy studies, disability rights, engineering and health and nutrition. This concept for this analysis originated in direct response to demands from LMIC governments, advocacy groups and funding agencies for information and data on the economic consequences of malnutrition in all countries. The conceptualization, analysis and writing for this study involved a balanced representation based on multinational, varied age and gender-balanced research project team. Consultations were conducted with numerous LMIC-based colleagues on the design of the cost of inaction analysis and tool. Overall, there was a strong commitment to work collaboratively in the analysis, writing, framing and review of the manuscript, though individual contributions varied at different stages of the work.

Ethical approval.

No ethical approval was required for this study.

Conflict of interest:

None declared.

Footnotes

1.

Not all anaemia is preventable through nutrition interventions and not all nutritional anaemia is preventable through interventions that aim to address iron deficiency.

2.

Population working in the heavy manual labour sector is assumed to comprise 50% of the total population working in the agriculture and construction sectors. Share of population in agriculture is available through ILO. It is assumed that share of population in construction is 15% of the share of population in agriculture (Horton and Ross, 2003).

3.

To understand more on health system costs calculations, see the ‘Cost of Not Breastfeeding methodology paper’ and Walters et al. (2019).