Global Food Security Assessment during 1961–2019

Abstract

Quantified components of the global food system are used to assess long-term global food security under a series of socio-economic, epidemic normalization and climate change scenarios. Here, we evaluate the global food security including the global farming system as well as the global food trade, reserve and loss systems from 1961 to 2019, and analyze their temporal and spatial characteristics by using the global food vulnerability (GFV) model. The spatio–temporal patterns of the vulnerability of the global food system were consistent with the GFSI. As food production and consumption vary greatly in different countries which have continued for a long time, food exports from many developed agricultural countries have compensated for food shortages in most countries (about 120 net grain-importing countries). As a result, many countries have relied heavily on food imports to maintain their domestic food supplies, ultimately causing the global food trade stability to have an increasing impact on the food security of most countries. The impact of global food trade on global food security increased from 9% to 17% during 1961–2019, which has increased the vulnerability of the global food system. The food damage in the United States, Russia, China, and India has varied significantly, and global cereal stocks have fluctuated even more since 2000. From 1961 to 2019, the food system security of some Nordic countries significantly improved, while the food system security of most African countries significantly deteriorated. Most countries with high food insecurity are located in Africa and South Asia. In order to cope with extreme events, these countries need to strengthen and improve their own food production and storage systems, which will help the World Food and Agriculture Organization to formulate relevant food policies and maintain sustainable development.

1. Introduction

Food security has been a pressing challenge for human society for a long time. The stability and security of the food system depend on the survival and sustainable development of human beings. Extreme events such as natural disasters, insect pests, diseases, and trade frictions have had serious impacts on the food system. Unfortunately, in 2020, the COVID-19 pandemic and unprecedented desert locust outbreaks in Eastern Africa obscured economic prospects in ways no one could have anticipated. This dire situation can worsen if we do not act urgently and take necessary actions [1,2,3].

The increase in extreme events has made the international market more complex, which threatens global food security. The whole world is committed to solving a common problem: how can the stability and sustainability of the global food system be ensured while extreme events happen frequently around the world? Global poverty has prevented rapid and sustainable development of the world for a long time. Since the beginning of the 21st century, societies have paid more attention to the security of their food systems. Specifically, in recent years, governments and global development communities have attempted to understand the impact of agricultural and food systems on their food security. Due to the impact of COVID-19 on food security and nutrition, the United Nations (UN) adjusted the UN sustainable development target in May 2020. Before the outbreak of COVID-19, the pace of global emission reduction was slowing down. It is estimated that the global goal of poverty eradication will not be achieved by 2030. The COVID-19 epidemic has caused tens of millions of people to fall back into extreme poverty that will last for many years. Despite the emphasis on the need to boost social protection, and emergency preparedness and response during the outbreak, the existing measures are not sufficient to protect poor and vulnerable groups. Since the establishment of the food tank, there have been remarkable efforts to reduce food waste, eliminate poverty, and increase farmers’ incomes. However, their influence on global people’s awareness of food security is still limited from a global perspective.

More cooperation is needed to eradicate global poverty and hunger, and improve the security of food systems. The food system security problem has existed for a long time [4,5,6,7,8]. Enhancing the efficiency and productivity of food systems and reducing food waste in different regions have been studied by many scholars during the past 50 years. They have also evaluated food supply patterns at the micro, meso and macro scales [8,9,10,11,12]. Fujimori et al. (2020) [13] proposed that food security includes four key components namely, food availability, stability, access, and utilization. Lu et al. (2020) [14] suggested a new self-adapting statistics allocation model (SASAM) to develop a global map of cropland distribution. Their analyses indicate that it is important to create more accurate global cropland maps for research and application in food security. Carney et al. (2020) [15] found that climate change and the continued neoliberalization of food systems have aggravated food insecurity and hunger, causing an ever-expanding population of displaced persons who are also nutritionally vulnerable. Anderson et al. (2019) [8] found that natural disasters such as El Niño Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD), Tropical Atlantic Variability (TAV), and North Atlantic Oscillation (NAO) can change the global corn, soybean, and wheat production by 18%, 7% and 6%, respectively. Bentham et al. (2020) [9] identified multi-dimensional food supply patterns by analyzing 18 food groups in 171 countries from 1961 to 2019. Kinnunen et al. (2020) [16] calculated the minimum distance between food production and consumption for six crops in the world. Their results show that most parts of the world rely on trade to feed themselves. It is evident that global food trade is essential to maintaining the stability of the global food system. However, increased extreme events may cause trade frictions, which can seriously damage the stability of the global food system. Global food insecurity has led to large-scale human displacements and migrations [17,18,19]. Using an adapted ecological model of health behavior, Naja et al. (2020) [20] presented a framework to maintain optimal nutrition at the individual, community, national and global levels in order to enhance the physical and mental health of individuals during COVID-19. Falkendal et al. (2021) [21] conducted a study on grain export restrictions during COVID-19 and found that many low- and middle-income countries have food insecurity risks, which indicates that the decline in local production has a moderate impact on global prices and supplies, and trade restrictions and preventive procurement may lead to global food price increases and severe local food shortages [21].

Proper assessment of food security is of great assistance to planners and administrators [22,23,24]. Many studies have constructed evaluation indexes for food security at various scales and from different perspectives [24,25,26,27,28]. At the global scale, the Global Food Security Index (GFSI) provides a common framework for understanding the root causes of food insecurity by looking at the dynamics of food systems around the world, which is produced by The Economist Intelligence Unit and supported by Corteva Agriscience [25]. Grebmer et al. [26] used the Global Hunger Index (GHI) to measure changes in the number of hungry people in different regions of the world. A limitation of GHI is the upward bias it induces due to the use of proxy indicators involving undernutrition and under-five mortality [27]. At the national scale, Lv et al. [28] built a food security index (FSI) based on the coupling of grain yield, population, and GDP to evaluate dynamic spatiotemporal changes in China’s food security. There are regional differences in food output, economic development, and population size, among other aspects in the world. Scale differences and spatial heterogeneity in food security and its influencing factors are existed. Hence, a comprehensive assessment of the changes in the global food system and the subsystems of food productivity, trade, savings, losses, and supply in different regions is still lacking. Additionally, the interaction mechanism among the various subsystems is unclear. To solve the abovementioned problems, we developed a set of multi-index models for a comprehensive analysis of the global food security system as well as the food production, trade, savings, and loss subsystems. In this study, the spatial and temporal patterns of the global food production, trade, savings, and vulnerability systems are obtained by developing the global food availability (GFA), global food access (GFE), global food stability (GFS), and global food vulnerability (GFV) models, respectively. GFV not only considered the food supply and food losses but also the supplementary role of economic purchasing power (Per capita cash savings). Finally, several suggestions have been made to assist the sustainable development of the global food system.

2. Materials and Methods

2.1. Global Food System Datasets

The arable land (AL) and cereal yield (CY) data used to calculate per capita food production for the period 1961–2019 were obtained from the World Bank. Prevalence of undernourishment (% of population) data from the Food and Agriculture Organization of the United Nations were used here (Discussion). We used the Food Balance Sheets Historic_E_All_Data to calculate the parameters of the FT, GS, and GL models. In addition, we used gross savings (% of GNI) and gross savings (current USD) data to investigate the implications of national stock variation for food systems for the period 1961–2019. All data used in this study are described in Table 1.

2.2. Global Food Vulnerability Model (GFV)

To simulate global food system dynamics, we built a GFV model that covers food availability, stability, access, and utilization. The framework comprises several submodels representing global food availability (GFA), stability (GFS), access (GFE), and utilization (GFU). Each model is described in brief below. In this study, the global food vulnerability composite index of each country in the world was constructed by several submodels: GFA, GFS, GFE, and GFU.

(1)${\mathrm{GFV}}_{\mathrm{ij}}=\left({1-\mathrm{GFA}}_{\mathrm{ij}}\right)+{\mathrm{GFE}}_{\mathrm{ij}}+\left(1-{\mathrm{GFS}}_{\mathrm{ij}}\right)+\frac{{\mathrm{S}}_{\mathrm{ij}}}{{\mathrm{GS}}_{\mathrm{ij}}}{\ast \mathrm{GFU}}_{\mathrm{ij}}$

where ${\mathrm{GFV}}_{\mathrm{ij}}$ represents the comprehensive index of food system vulnerability of country j in a certain time node i, and the greater the value is the greater the food system vulnerability.${\mathrm{GFA}}_{\mathrm{ij}}$ represents the comprehensive index of food availability of country j at a certain time node i. ${\mathrm{GFE}}_{\mathrm{ij}}$ represents the food access of country j at a certain time point i.${\mathrm{GFS}}_{\mathrm{ij}}$ represents the food stability of country j at a certain time point i.${\mathrm{GFU}}_{\mathrm{ij}}$ represents the food utilization of country j at a certain time point i.${\mathrm{S}}_{\mathrm{ij}}$ represents the total grain loss of country j at a certain time node i.${\mathrm{GS}}_{\mathrm{ij}}$ represents the total grain supply of country j at a certain time point i. Global food vulnerability was divided into five levels: high security (HS) (GFV ≤ 1.31), medium security (MS) (1.31< GFV ≤ 1.85), security (S) (1.85 < GFV ≤1.98), low security (LS) (1.98 < GFV ≤ 2.1), and extremely low security (ELS) (2.1 < GFV). GFV can quantitatively evaluate the food security of a nation relative to the global maximum.

GFA Model. To study the spatial and temporal pattern evolution characteristics of the global food productivity system, this study used the indexes of total arable land area (T), per capita arable land area (A) and arable land yield level (B) in the World Bank to construct FP. The formula of FP is as follows:

(2)${\mathrm{GFA}}_{\mathrm{ij}}=\frac{{\mathrm{A}}_{\mathrm{ij}}{\ast \mathrm{B}}_{\mathrm{ij}}}{{\mathrm{Max}(\mathrm{A}}_{\mathrm{ij}}{\ast \mathrm{B}}_{\mathrm{ij}})}$

where ${\mathrm{GFA}}_{\mathrm{ij}}$ represents the standardized index of grain productivity of country j at a certain time node i. ${\mathrm{A}}_{\mathrm{ij}}$ represents the per capita arable land area of country j at a certain time node i. ${\mathrm{B}}_{\mathrm{ij}}$ represents the unit yield level of arable land of country j at a certain time node i. The higher the value of ${\mathrm{GFA}}_{\mathrm{ij}}$ is in (0–1), the stronger the per capita grain productivity of the country is, and the safer the food production system is.

GFE Model. To study the impact of international trade on global food, this study uses food imports (ITs), food exports (ETs), domestic grain production (PT), the total population (H) and other indicators in the FAO food compilation balance table database to construct the GFE model.

(3)${\mathrm{GFE}}_{\mathrm{ij}}=\frac{{\mathrm{IT}}_{\mathrm{ij}}{/H}_{\mathrm{ij}}-{\mathrm{ET}}_{\mathrm{ij}}{/H}_{\mathrm{ij}}{}_{}}{\mathrm{Max}(\left|{\mathrm{IT}}_{\mathrm{ij}}{/H}_{\mathrm{ij}}-{\mathrm{ET}}_{\mathrm{ij}}{/H}_{\mathrm{ij}}{}_{}\right|)}$

where ${\mathrm{GFE}}_{\mathrm{ij}}$ represents the standardized index of a net import per capita of country j at a certain time node i, and its value is (−1,1). The smaller the value is, the larger the grain export volume is and the more sufficient the grain supply is. ${\mathrm{IT}}_{\mathrm{ij}}$ represents the grain import volume of country j at a certain time node i; ${\mathrm{ET}}_{\mathrm{ij}}$ represents the total grain export volume of country j at a certain time node i; $H_{\mathrm{ij}}$ represents the total population of country j at time node i.

GFS Model. Since it is impossible to fully adjust the per capita grain savings of different countries in the world, this study uses the global cash savings (TR) index in the World Bank database to construct the standardized index of grain savings per capita. The calculation formula is as follows:

(4)${\mathrm{GFS}}_{\mathrm{ij}}=\frac{{\mathrm{TR}}_{\mathrm{ij}}/H_{\mathrm{ij}}}{\mathrm{Max}\left({\mathrm{TR}}_{\mathrm{ij}}/H_{\mathrm{ij}}\right)}$

where ${\mathrm{GFS}}_{\mathrm{ij}}$ represents the standardized index of total savings per capita of country j at time node i. The higher the value of ${\mathrm{GFS}}_{\mathrm{ij}}$ in (0–1) is, the higher the cash value of the country’s total savings per capita. ${\mathrm{TR}}_{\mathrm{ij}}$ represents the total savings (cash value) of country j at time node i.

GFU Model. In this study, the food loss index of different countries in the world was constructed by using the food loss (S) index in the food balance table of the FAO.

(5)${\mathrm{GFU}}_{\mathrm{ij}}=\frac{{\mathrm{S}}_{\mathrm{ij}}/H_{\mathrm{ij}}}{\mathrm{Max}\left({\mathrm{S}}_{\mathrm{ij}}/H_{\mathrm{ij}}\right)}$

where ${\mathrm{GFU}}_{\mathrm{ij}}$ represents the per capita grain loss index of country j at a certain time node i. The higher the value of ${\mathrm{GFU}}_{\mathrm{ij}}$ is in (0–1), the greater the loss per capita, and the more serious the food loss. ${\mathrm{S}}_{\mathrm{ij}}$ represents the total grain loss of country j at a certain time node i.

3. Results

3.1. Analysis of the Changes in Global Grain Subsystems

3.1.1. Sustainably Increasing Global Grain Productivity in GFA

Grain productivity is an important factor affecting the regional grain self-sufficiency rate. Therefore, it is important to improve grain productivity in order to ensure regional food security. A comprehensive index of global grain production is calculated in GFA to analyze the spatial and temporal patterns of the per capita grain production in different regions of the world. Thereafter, the computed global per capita grain production index was divided into five levels by using the natural discontinuity method (Figure 1). The global arable land area increased from 9.8% to 11.1% from 1961 to 2019. However, the per capita arable land area in all regions of the world showed a linear declining trend, leading to a reduction (from 0.36 ha to 0.19 ha) in the global per capita arable land area (Supplementary Materials Figure S1). The global spatial distribution of arable land per capita is shown in the Supplementary Materials (Figure S2). With technological progress, the average global grain yield per unit area increased significantly from 1431 kg/ha in 1961 to 4074 kg/ha in 2019 (Supplementary Materials Figure S3). From 1961 to 2019, the per capita food production of Australia, the United States, and Canada was far ahead of that of other countries. From 1961 to 2019, the global per capita grain production showed an upward trend, the per capita grain production in North America, Oceania and Europe increased rapidly, and the production of grain per capita relatively accelerated in Eastern Europe after 2000 (Supplementary Materials Figure S6). However, the per capita grain production in South Africa showed a significant downward trend during 1961–2019.

3.1.2. Global Food Access Patterns and Changes over Time in GFE

The annual per capita grain import to Africa, South America, and Europe (Asia, North America and Oceania) was higher (lower) than the global average of 45 kg/per capita/year (Supplementary Materials Figure S7). On the other hand, the annual per capita grain export from North America, Europe, Oceania, and South America (Asia and Africa) was greater (smaller) than the global average of 46.49 kg/per capita/year (Supplementary Materials Figure S9).

Figure 2 shows that the net food import per capita in Oceania and North America are negative, while the net food imports per capita in Africa and Asia are positive. The per capita net import value of grain in Europe and South America has changed from positive to negative since 1990, indicating that their per capita food self-sufficiency has gradually improved and their per capita net food imports have gradually decreased. The per capita food access increased in North and West Europe from 1961 to 1990. In Southern Europe, the food access per capita from 1990 to 2019 was increasingly dependent on imports, which was mainly reflected in the increasing net food import. From 1961 to 2019, From 1961 to 2019, the overall change of per capita food access in Central Asia, South Asia, and Southeast Asia were relatively stable, mainly showing that the per capita net import remains stable and at a low level for a long time (Supplementary Materials Figure S11). However, the per capita food access in West Asia was mainly affected by the increase in food imports. the per capita grain import in Central Asia has been negative since 1990. In the Americas, the per capita food self-sufficiency of North America is sufficient, and the per capita net food import is negative, while the per capita net food import of Central America and the Caribbean is positive, and the per capita net food import of South America has been negative since 1990, indicating that the per capita food self-sufficiency of South America has gradually improved in the last 30 years. In Oceania, the per capita food self-sufficiency is sufficient, so the per capita net food import is negative, exporting a lot of food to other countries (Supplementary Materials Figure S11). The per capita food availability in Africa depended on food imports during 1961–2019. The net per capita food import in North Africa enhanced from 0.057 to 0.164, which put the food system in jeopardy. The net import per capita of South Africa has changed from negative to positive since 1990 and showed a significant increasing trend.

3.1.3. Implications of Global Total Reserves for Food Stability

Total reserves (e.g., gold and US dollars) allow purchasing of emergency food when an extreme food crisis occurs in a certain area (total reserves can be converted into food purchasing power to make up for the lack of local food production). Cash savings in all countries have shown an upward trend, which has accelerated significantly since 2000. The cash savings in each of the study regions showed an upward trend from 1961 to 2019 (Figure 3). After 2000, the cash savings in all the regions grew significantly due to the rapid economic development in the 21st century. As can be seen in Figure 3, the cash savings were higher in East Asia and the Pacific, followed by Europe and Central Asia, Latin America and the Caribbean, South Asia, North America, and Central Asia, Middle East, North Africa, and sub-Saharan Africa in the last 20 years. The imbalance of regional development is mainly because of their different cash savings. In fact, promoting the balanced development of global regions is of vital importance to maintaining the stability and security of the global food system.

From 1961 to 2001, the cash savings per capita of most countries were less than USD 1248 (Figure 4). After 2000, the cash savings per capita increased significantly and reached even more than USD 10,000 in some countries. In 1961, cash savings per capita of nine countries (namely, Switzerland, Kuwait, Malta, Belgium, Netherlands, New Zealand, Ireland, Canada, and the United States) exceeded USD 100, while in 2019, there were 16 countries (including Switzerland, Hong Kong Special Administrative Region (SAR) of China, Singapore, Macao SAR of China, Iceland, Saudi Arabia, Czech Republic, Qatar, San Marino, Israel, Norway, Libya, Denmark, United Arab Emirates, Japan, and Kuwait) with cash savings per capita of more than USD 10,000.

Except for sub-Saharan regions, global savings account for approximately 30% of total income (Supplementary Figure S16). The ratio of savings to income in South Asia showed a significant upward trend and increased from 10% to 33% during 1961–2019. In Europe and Central Asia, the percentage of total savings reduced from 31% in 1961 to 19% in 1992, while it showed a fluctuating rising trend during 1992–2019.

3.2. Sustainably Increasing Global Per Capita Food Supply

To build a global food security system, it is imperative to understand the characteristics of grain supply capacity in different regions of the world. Hence, we analyzed the temporal and spatial characteristics of the total and per capita food supplies of all countries.

The global grain and food supplies showed steady growth during 1961–2019 and reached 8.03 × 10⁸ in 1961 and 2.88 × 10⁹ tons in 2019, respectively. In these years, the patterns of grain supply and demand per capita were unbalanced. Asia has the largest grain supply (with a maximum of 1.55 × 10⁹ tons per year), accounting for more than half of the world’s grain supply. North America, Africa, and Europe were ranked second, third, and fourth having an annual grain supply of 4.23 × 10⁸, 2.72 × 10⁸, and 4.12 × 10⁸, respectively. The food supply in South America ranged from 3.20 × 10⁷ to 1.57 × 10⁸ tons during 1961–2019. Oceania had the lowest food supply with an annual value of fewer than 1.8 × 10⁷ tons. After 2012, the rate of the food supply in Asia increased. Approximately 50% of the global food supply was from Asia in 2019. The growth rate of the food supply in Europe was rapid during 1961–1990, reaching a peak of 4.90 × 10⁸ tons in 1900. Over 1990–2000, the food supply in Europe showed a sharp decline. From 2001 to 2019, the food supply in Europe fluctuated by approximately 350 × 10⁸ tons. We should ensure that the food supply will increase steadily in Asia, Africa, and America. In addition, we need to gradually restore the food supply capacity of Europe, continuously improve the grain supply capacity of Oceania, and maintain the stability and development of the global food system to the maximum extent.

As shown in Figure 5, the global food supply per capita shows some distinct variations in different periods. It showed a rapid increase over 1961–1980 and 2000–2019. From 1980 to 2000, the global food supply per capita showed a slow decline. After 2000, the food supply per capita in Oceania showed a fluctuating downward trend. Figure 5 shows that the annual per capita food supply in North America, Europe, and Oceania (Africa, South America, and Asia) was higher (lower) than the global mean. From 1978 to 2019, the total grain supply of the United States, China, India, and Brazil ranked first in the world. However, in 2019, North America had the highest food supply of 1177 kg/capita, followed by Europe and Oceania with a food supply of 559 kg and 517 kg/capita, respectively. Although the total grain supply in Asia ranked at the top of the grain supply quantity, its annual food supply was only 335 kg/capita, which is approximately one-third of that of developed countries in North America. In 2019, the per capita food supply in Africa was 245 kg, which was smaller than the global average of 398.9 kg (Figure 5). By increasing the per capita food supply in Asia, Africa, and other regions, the imbalance of global food supply will be mitigated, and global hunger will be diminished.

Figure 6 shows that the annual per capita grain supply of all countries has increased and the imbalance in the global food supply has become more prominent. From 1961 to 2019, the per capita food supply of the United States ranked first in the world, 3–5 times that of African countries. Dissolution of the Soviet Union had a certain impact on Russia’s per capita food supply. After 1991, Russia’s per capita food supply was lower than the previous level. After 2010, the regions with an annual per capita food supply of less than 260 kg are mainly concentrated in Africa and South Asia. The per capita food supply in the top 10 countries (namely, Denmark, the United States, Canada, Ireland, Netherlands, Cambodia, and Hungary, etc.) was more than 504 kg/per capita/year in 1961, but it increased to more than 713 kg/per capita/year in 2019. The bottom 25 countries in terms of the food supply (mainly including Jamaica, Maldives, Polynesia, Ecuador, Colombia, Liberia, Grenada, Angola, Mozambique, Dominica, Gabon, Solomon Islands, Congo, Fiji, Samoa Central African Republic, and Mozambique) had an annual per capita food supply of less than 100 kg/per capita/year in 1961 and 150 kg/per capita/year in 2019.

3.3. The Impact of Global Food Losses on Food Security

To improve global food security, it is necessary to reduce food losses in global food production, transportation, storage, and consumption. Two indicators are used to study the characteristics of global food loss. The first one is the total food loss, and the second one is the per capita food loss in different countries.

The total global food loss showed a gradually increasing trend from 1961 to 2019 (Supplementary Figure S17), while the global annual per capita food loss showed an increasing, a decreasing, and again an increasing trend over 1961–1990, 1991–2005, and 2006–2019, respectively. During 1961–2019, the total food loss in Africa showed a steady rising trend, while the annual per capita food loss showed a fluctuating downward and then an upward trend. The total grain loss per capita in North America has shown a significant increasing trend since 2014. In 2019, its value in North America was about 5.4 times more than that of Europe. The annual per capita food loss in South America initially enhanced but then reduced over 1961–2019. The annual per capita grain loss in South America showed an increasing trend and reached a maximum value of 32 kg/per capita/year in 2011. Thereafter, it exhibited a downward trend. In Asia, the annual per capita food loss grew during 1961–1995 and 2005–2019, while it reduced over 1995–2005. From 1961 to 1990, the annual per capita food loss in Europe indicated a fluctuating growing trend. After 1990, it showed a sharp descending trend. The total grain loss in Oceania displayed a fluctuating rising trend over 1961–2019. Figure 7 shows that the annual per capita food loss in Europe, South America, Africa, and Asia (Oceania and North America) was higher (lower) than the global mean.

During 1961–2019, the per capita food loss in South America and Europe was the highest in the world. After the dissolution of the former Soviet Union, the per capita food loss in Russia was lower than that in the former Soviet Union. The United States, Russia, China, and India were the countries with the largest food loss in the world (Supplementary Materials, Section 4). Before 1991, the per capita food loss of the former Soviet Union, Malawi, and Denmark were relatively high. After 2000, the per capita food loss in Argentina, Brazil, and Paraguay elevated. In 1961, 8 countries lost more than 30 kg/per capita/of food. In 2019, there were 28 countries whose per capita food loss exceeded 30 kg. Among them, the annual per capita food loss of Cambodia was as high as 101 kg (Figure 8).

3.4. Security Assessment and Vulnerability Map of the Global Food System

Generally, although agricultural production technology and output are improving, the population is also increasing. In particular, we are increasingly dependent on international trade, which makes us appear insufficient in terms of food security when encountering extreme events. According to the above analysis of factors affecting food security and equation (1), the comprehensive pattern map of the global food system vulnerability was generated. The results of this study are consistent with the results of the Economist Intelligence Unit’s (Global Food Security Index 2019) [25]. Shown as Figure 9, the vulnerability (food insecurity) index of the food system in Africa and South Asia gradually increased from 1961 to 2019, especially in Sudan, Botswana, Algeria, etc. Over the same period, the vulnerability of the global food security system in South America, northern Europe and East Asia is gradually decreasing, including Argentina, Finland, Sweden, China, etc. Additionally, the highest food security level was in the United States, Canada and Australia. From 1961 to 1991, the vulnerability of the food system in the former Soviet Union was decreasing until the dissolution of the former Soviet Union. After the dissolution of the former Soviet Union, the security level of Russian Federation’s food system has been gradually improving.

From 2000 to 2019, the incidence of the prevalence of undernourishment in North America was only 2.5% of the total population, while the incidence of the prevalence of undernourishment in Africa and South Asia was as high as 25% (Supplementary Materials Figures S19 and S20). In different time periods, although the most vulnerable countries are slightly different, their distribution regions have not changed much. In 1961, the food system was relatively fragile in the United Arab Emirates, Israel, French Polynesia, St. Kitts, and Nevis, Djibouti, Albania, New Caledonia, Antigua and Barbuda, Bahamas, and Barbados. In 2019, these countries are the top ranked countries in terms of food vulnerability, including Djibouti, the Netherlands, Cyprus, Belgium, Tunisia, Portugal, Ireland, Jordan, Algeria, Morocco, and Israel. In the harmonious development of the world, food security can be guaranteed, but extreme events indicate that hunger incidents may occur at any time in some regions, such as the food crisis in Venezuela in 2019. The multiple emergencies in 2020 necessitate more research on the impact of extreme events on food security. We must take some measures to ease our over-reliance on trade, such as “residents reserve short-term daily food for themselves”, and promote local production of food as far as possible to ensure self-sufficiency.

4. Discussion

Due to the occurrence of the COVID-19 pandemic, floods, desert locusts, conflicts, wars, and other disastrous events, the world must work together to ensure the smooth flow of global food trade (Falkendal et al., 2021; Dalin et al., 2019; Lam et al., 2020; Grafius et al., 2020; Friel et al., 2020) [21,22,23,24,25]. Different from previous studies on food security at the national scales, this study can better reveal spatial heterogeneity and identify fragility areas in food systems. The reason for this is that: (1) the 2019 GFSI introduces new metrics and additional indicators which are better than those of the GFSI in 2018 and before. (2) Our finding is consistent with the 2019 GFSI, in particular regarding food security in Ireland, Singapore, Switzerland, Finland, Canada, etc. Meanwhile, more attention and humanitarian assistance should be allocated to Africa, South Asia, and other areas with fragile food systems. Finally, we should advance agricultural technology, increase global food production capacity, improve consumption patterns in developed countries, reduce food losses, and formulate regional multi-level food reserve policies to ensure the safety and sustainable development of the global food system.

The security of the global food system is a complex issue, which includes the safety of food production, circulation, consumption, and storage. Any failure in each of these modules will cause severe damage to the global food system. The results of this study can be discussed as follows.

• In 2008, a large-scale freezing disaster occurred in southern China, causing some traffic to be blocked, and food shortages occurred in remote areas, especially some rural areas, which caught our attention. Therefore, we continued to conduct some investigations and analyses on China and other countries and found that, in recent years, the development of modern transportation and logistics has greatly changed everyone’s living habits. Most families have basically abandoned the habit of having surplus food at home. Not only do most urban residents not stock food, but also most rural residents no longer store grains. The gradual lack of awareness of emergency reserves has created a potential risk of a food security crisis.

• The mechanism of risk transmission and feedback in each module of the grain system is not very clear. The developed model investigates the vulnerability of each component of the global food system from 1961 to 2019. The results show that reducing food loss and waste and alleviating international food trade barriers are of vital importance to maintaining global food system security in extreme events. The risk transmission mechanism among the production, trade, saving, consumption, circulation, and loss of the global food system has not yet been understood. It is difficult to quantitatively assess the impact of different extreme events on the global food system as a whole and the feedback mechanism among the constituents of the global food system. A number of studies have shown that, in some cases, raising the price of agricultural products can increase farmers’ incomes. However, sub-Saharan African countries rely mainly on food imports for their daily rations, which undoubtedly increases the burden of people in Africa and the risk of hunger. This strategy transfers the risk of food insecurity to poorer areas, which undoubtedly expands the imbalance of global food system development.

• It is impossible to fully obtain the global food inventory. Hence, we analyzed the spatio–temporal variation characteristics of the global food inventory by using the changes in the global food inventory and the global total savings (cash value) through interpreting the food balance table compiled by the FAO of the United Nations. The indicators of global food inventory changes are the indicators in the food balance table of the United Nations. If a country is extremely short of food due to force majeure and global food trade is not interrupted, it is assumed that the country would use its total savings to purchase food in order to maintain national survival.

• Different food structures, consumption habits, and storage patterns highly impact food loss and waste. The spatial and temporal patterns of global food losses were analyzed. The findings indicated that (a) the annual per capita food loss of the developed countries was equal to the annual per capita food shortage in Africa, and (b) the regional development gap was widening. However, the cause of food loss and its impact on food security have not been analyzed yet. Previous studies on food security showed that advancing agriculture and reducing food waste can double agricultural production and reduce environmental impacts. On the other hand, the pressure on global food production can be mitigated by reducing bad eating habits. There are already more than 2 billion overweight people. By implementing health guidelines (e.g., taxing unnecessary food consumption, taxing food production that has a significant negative impact on the environment, etc.), Japan has generated a new source of income to support hunger eradication programs.

5. Conclusions

Due to the occurrence of COVID-19 pandemic, the global food system has been seriously impacted, and more than 820 million people have suffered from hunger. Given the diversity and complexity of food systems, countries need to implement a set of context-specific policies and strategies and increase public and private sector investments with significant policy coherence and improved planning and coordination across sectors and actors. We called for the increased use of technology and innovation and greater collaboration with governments, partners, and farmers to maintain global food security. The main conclusions of our study are as follows:

• Food system vulnerability should be reduced by increasing global food production and narrowing the gap of agricultural planting technologies in different regions. The unbalanced development of grain productivity systems in different regions has existed for a long time. Over 1961–2019, the global arable land area showed a significant upward trend, while the per capita arable land area had a remarkable downward trend. The global grain yield per unit area exhibited a significant growth, although there was a substantial gap in the grain yield of different regions. The per capita food production capacity of Australia, the United States, and Canada is far ahead of other countries.

• After 1990, per capita food access in North Africa was highly dependent on food imports, while it became widespread in Europe due to food production. The influence of global food trade on national food security is becoming more important. Some countries rely heavily on food imports to maintain their domestic food supply. The grain exports from a few developed agricultural countries provide the food supply of most countries. From 1961 to 2019, the impact of global food trade on global food security increased by almost 89%. Additionally, the amount of grain imports in Africa exceeds its domestic food production. The per capita grain exports from Australia, the United States, and Canada are much higher than their per capita grain imports.

• Global food stocks have become more volatile since 2000. Before 2000, the cash value of total savings per capita in all countries was relatively low. In most countries, it was less than US USD 1248. After 2000, the cash value of global total savings per capita increased significantly, and its annual figure reached even more than USD 10,000 in some countries.

• The United States, Russia, China, and India have experienced the largest grain losses in the world. Before 2000, the per capita grain losses of the former Soviet Union, Malawi, and Denmark were relatively high. After 2000, the grain losses in Argentina, Brazil, and Paraguay showed an increasing trend.

Overall, from 1961 to 2019, the fragility (insecurity) of the global food system gradually increased. Most countries with high food vulnerability are located in Africa and South Asia. In order to deal with extreme events, countries need to improve their food production and storage systems, which will help the World Food and Agriculture Organization to formulate relevant food policies and maintain sustainable development. We have made some suggestions: Firstly, in regions with sufficient per capita food supply, it is necessary to optimize eating habits and food supply methods to reduce food losses. Second, countries with high per capita food supply should actively provide humanitarian assistance to regions with insufficient per capita food supply. At the same time, these regions should utilize advanced agricultural technology and gain experience from countries with high per capita food yields. Third, in order to avoid monopoly and unilateral trade in the global food system, different organizations around the world should actively work together to achieve sustainable global food development. Fourth, the most important and practical recommendation is “residents reserve short-term daily food for themselves”. That is to say that every household in the world reserves at least 15–30 days of food per person, which is easy to operate and be adopted. In the event of a global extreme event, it can effectively stabilize food prices in the short term. This measure is equivalent to adding a stabilizer to global food security.

Author Contributions

Conceptualization, K.M. and Y.Z.; methodology, J.G.; software, Z.Y. and C.Y.; validation, Z.Q., T.X.; formal analysis, J.G.; investigation, C.Y.; resources, J.G.; data curation, Z.Y.; writing—original draft preparation, J.G.; writing—review and editing, J.G., S.M.B.; visualization, C.Y.; supervision, S.M.B.; project administration, K.M.; funding acquisition, K.M. All authors have read and agreed to the published version of the manuscript.

Funding

This work is supported by the National Key Research and Development Program of China (2019YFE0127600), National Natural Science Foundation of China (41771406). Fundamental Research Funds for Central Nonprofit Scientific Institution (Grant No. 1610132020014), and Open Fund of State Key Laboratory of Remote Sensing Science (Grant No. OFSLRSS201910).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

All data generated or analyzed during this study are included in this published article.

Acknowledgments

Thanks to the United Nations Food and Agriculture Organization and World for their support by providing the data.

Conflicts of Interest

The authors declare no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures and Table

Figure 1. Changes in global arable land productivity by the GFA in 1961–2019. The redder color shows the lower the per capita food production capacity. The greener color denotes the higher the per capita food production capacity (a safer food system).

Figure 2. Changes in global net import per capita by the GFE during 1961–2019. Net import per capita = import per capita − export per capita.

Figure 3. Cash savings (in US dollars) during 1961–2019.

Figure 4. Changes in the global cash savings per capita in 1961–2019.

Figure 5. Global food supply per capita in 1961–2019.

Figure 6. Global food supply per capita in 1961–2019.

Figure 7. Annual global food loss per capita, 1961–2019.

Figure 8. Annual per capita food loss of countries in the world from 1961 to 2019.

Figure 9. Comprehensive pattern of global food system vulnerability from 1961 to 2019.

Table 1

Data description for 1961–2019.

Data Indicators	1961–2016	2017	2018	2019
Arable land (hectares per person)	*	√	√	√
Arable land (% of land area)	*	√	√	√
Food_Aid_Shipments	*	√	√	√
Cereal yield (kg per hectare)	*	*	√	√
Prevalence of undernourishment (% of population)	*	*	*	*
FoodBalanceSheetsHistoric_E_All_Data	*	*	√	√
Gross savings (% of GNI)	*	*	*	√
Gross savings (current USD)	*	*	*	√

Note: * represents the original statistics from FAO and World Bank databases, √ represents the data supplemented by the triple moving average method.

Supplementary Materials

The following are available online at www.mdpi.com/article/10.3390/su132414005/s1, Figure S1:The per capita arable land changes of seven major regions and the world respectively from 1961–2019, Figure S2: Spatial distribution of arable land per capita in the world, Figure S3: The cereal yield changes of per unit area in seven major regions and the world from 1961–2019, Figure S4: Changes in per unit area yield of arable land in different regions from 1961 to 2019, Figure S5: Arable land area changes in seven major regions and the world from 1961–2019, Figure S6: The per capita grain production in different regions from 1961–2019, Figure S7: The per capita grain imports changes in different regions of the world from 1961–2019, Figure S8: The change of global per capita grain imports from 1961–2019,Figure S9: Changes in global per capita grain exports from 1961–2019, Figure S10: The change of international food exports per capita, 1961–2019, Figure S11: Changes in net food import per capita in different regions of the world from 1961–2019, Figure S12: The food stocks change in different regions of the world from 1961–2019, Figure S13: Changes in global grain stocks in 1961–2019, Figure S14: The savings cash dollar value in different regions of the world from 1961–2019, Figure S15: The cash value of total savings per capita in different regions of the world from 1961–2019, Figure S16: Cash savings as a percentage of total income by different regions, 1961–2019, Figure S17: The percentage of saving to total income in different regions from 1961–2019, Figure S18: Food losses of major regions in the world, 1961–2019, Figure S19: Spatial variation of the incidence of the prevalence of undernourishment in the world from 2000–2019, Figure S20: Spatial variation of the incidence of the prevalence of undernourishment in the world from 2000–2019.

References

1. Mullen, A. Stories of hope and success in the food system. Nat. Food; 2020; 1, pp. 250-251. [DOI: https://dx.doi.org/10.1038/s43016-020-0084-z]

2. Janssens, C.; Havlík, P.; Krisztin, T.; Baker, J.; Frank, S.; Hasegawa, T.; Leclère, D.; Ohrel, S.; Ragnauth, S.; Schmid, E. et al. Global hunger and climate change adaptation through international trade. Nat. Clim. Chang.; 2020; 10, pp. 829-835. [DOI: https://dx.doi.org/10.1038/s41558-020-0847-4]

3. FAOIFADUNICEFWFPWHO. The State of Food Security and Nutrition in the World 2020: Transforming Food Systems for Affordable Healthy Diets; FAO: Rome, Italy, 2020; [DOI: https://dx.doi.org/10.4060/ca9692en]

4. Ingram, J. A food systems approach to researching food security and its interactions with global environmental change. Food Secur.; 2011; 3, pp. 417-431. [DOI: https://dx.doi.org/10.1007/s12571-011-0149-9]

5. Ayanlade, A.; Radeny, M. COVID-19 and food security in Sub-Saharan Africa: Implications of lockdown during agricultural planting seasons. NPJ Sci. Food; 2020; 13, pp. 1-6. [DOI: https://dx.doi.org/10.1038/s41538-020-00073-0] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/34518540]

6. Wood, S.A.; Smith, M.R.; Fanzo, J.; Remans, R.; DeFries, R.S. Trade and the equitability of global food nutrient distribution. Nat. Sustain.; 2018; 1, pp. 34-37. [DOI: https://dx.doi.org/10.1038/s41893-017-0008-6]

7. Altink, H. Tackling child malnutrition in Jamaica, 1962–2020. Humanit. Soc. Sci. Commun.; 2020; 50, pp. 1-14. [DOI: https://dx.doi.org/10.1057/s41599-020-00536-5]

8. Anderson, W.B.; Seager, R.; Baethgen, W.; Cane, M.; You, L. Synchronous crop failures and climate-forced production variability. Sci. Adv.; 2019; 5, eaaw1976. [DOI: https://dx.doi.org/10.1126/sciadv.aaw1976]

9. Bentham, J.; Singh, G.M.; Danaei, G.; Green, R.; Lin, J.K.; Stevens, G.A.; Farzadfar, F.; Bennett, J.E.; Cesare, M.D.; Von Braun, J. Strategic body needed to beat food crises. Nature; 2010; 465, pp. 548-549.

10. Barrett, C.B. Actions now can curb food systems fallout from COVID-19. Nat. Food; 2020; 1, pp. 319-320. [DOI: https://dx.doi.org/10.1038/s43016-020-0085-y]

11. Basso, B.; Antle, J. Digital agriculture to design sustainable agricultural systems. Nat. Sustain.; 2020; 3, pp. 254-256. [DOI: https://dx.doi.org/10.1038/s41893-020-0510-0]

12. Fujimori, S.; Hasegawa, T.; Krey, V.; Riahi, K.; Bertram, C.; Bodirsky, B.L.; Bosetti, V.; Callen, J.; Després, J.; Doelman, J. et al. A multimodel assessment of food security implications of climate change mitigation. Nat. Sustain.; 2019; 2, pp. 386-396. [DOI: https://dx.doi.org/10.1038/s41893-019-0286-2]

13. Lu, M.; Wu, W.; You, L.; See, L.; Fritz, S.; Yu, Q.; Wei, Y.; Chen, D.; Yang, P.; Xue, B. A cultivated planet in 2010–Part 1: The global synergy cropland map. Earth Syst. Sci. Data; 2020; 12, pp. 1913-1928. [DOI: https://dx.doi.org/10.5194/essd-12-1913-2020]

14. Carney, M.A.; Krause, K.C. Immigration/migration and healthy publics: The threat of food insecurity. Palgrave Commun.; 2020; 6, 93. [DOI: https://dx.doi.org/10.1057/s41599-020-0461-0]

15. Kinnunen, P.; Guillaume, J.H.A.; Taka, M.; D’Odorico, P.; Siebert, S.; Puma, M.J.; Jalava, M.; Kummu, M. Local food crop production can fulfil demand for less than one-third of the population. Nat. Food; 2020; 1, pp. 229-237. [DOI: https://dx.doi.org/10.1038/s43016-020-0060-7]

16. FAO. Evidence on Internal and International Migration Patterns in Selected African Countries: Rome, Italy. 2017; Available online: www.fao.org/3/a-i7468e.pdf (accessed on 25 November 2019).

17. FAO. Forced Migration and Protracted Crisis. A Multilayered Approach: Rome, Italy. 2017; Available online: www.fao.org/3/a-i7880e.pdf (accessed on 25 November 2019).

18. FAO. Migration, Agriculture and Climate Change. Reducing Vulnerabilities and Enhancing Resilience: Rome, Italy. 2017; Available online: www.fao.org/3/I8297EN/i8297en.pdf (accessed on 25 November 2019).

19. Naja, F.; Hamadeh, R. Nutrition amid the COVID-19 pandemic: A multilevel framework for action. Eur. J. Clin. Nutr.; 2020; 74, pp. 1117-1121. [DOI: https://dx.doi.org/10.1038/s41430-020-0634-3]

20. Falkendal, T.; Otto, C.; Schewe, J.; Jägermeyr, J.; Konar, M.; Kummu, M.; Watkins, B.; Puma, M.J. Grain export restrictions during COVID-19 risk food insecurity in many low- and middle-income countries. Nat. Food; 2021; 2, pp. 11-14. [DOI: https://dx.doi.org/10.1038/s43016-020-00211-7]

21. Dalin, C.; Wada, Y.; Kastner, T.; Puma, M.J. Groundwater depletion embedded in international food trade. Nature; 2017; 543, pp. 700-704. [DOI: https://dx.doi.org/10.1038/nature21403]

22. Lam, V.W.Y.; Allison, E.H.; Bell, J.D.; Blythe, J.; Cheung, W.L.; Frölicher, T.L.; Gasalla, M.A.; Sumaila, U.R. Climate change, tropical fisheries and prospects for sustainable development. Nat. Rev. Earth Environ.; 2020; 1, pp. 440-454. [DOI: https://dx.doi.org/10.1038/s43017-020-0071-9]

23. Grafius, D.R.; Edmondson, J.L.; Norton, B.A.; Clark, R.; Mears, M.; Leake, J.R.; Corstanje, R.; Harris, J.A.; Warren, P.H. Estimating food production in an urban landscape. Sci. Rep.; 2020; 10, pp. 1-9. [DOI: https://dx.doi.org/10.1038/s41598-020-62126-4]

24. Friel, S.; Schram, A.; Townsend, B. The nexus between international trade, food systems, malnutrition and climate change. Nat. Food; 2020; 1, pp. 51-58. [DOI: https://dx.doi.org/10.1038/s43016-019-0014-0]

25. Odhiambo, V.O.; Hendriks, S.L.; Mutsvangwa-Sammie, E.P. The effect of an objective weighting of the global food security index’s natural resources and resilience component on country scores and ranking. Food Sec.; 2021; pp. 1-15. [DOI: https://dx.doi.org/10.1007/s12571-021-01176-6]

26. Grebmer, K.V.; Ringler, C.; Rosegrant, M.W.; Olofinbiyi, T.; Wiesmann, D.; Fritschel, H.; Badiane, O.; Torero, M.; Yohannes, Y.; Thompson, J.M. Global Hunger Index: The Challenge of Hunger: Ensuring Sustainable Food Security under Land, Water and Energy Stresses; International Food Policy Research Institute: Washington, DC, USA, 2012; 68.

27. Nigam, A.K. Improving Global Hunger Index. Agric. Res.; 2019; 8, pp. 132-139. [DOI: https://dx.doi.org/10.1007/s40003-018-0349-z]

28. Lv, F.; Deng, L.; Zhang, Z.; Wang, Z.; Wu, Q.; Qiao, J. Multiscale analysis of factors affecting food security in China, 1980–2017. Environ. Sci. Pollut. Res.; 2021; pp. 1-15. [DOI: https://dx.doi.org/10.1007/s11356-021-16125-1] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/34455560]