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1. Introduction

Poverty and hunger are serious global issues. The United Nations Millennium Development Goals (UN MDGs) set up targets to “halve, between 1990 and 2015, the proportion of people whose income is less than $1.25 a day” (MDG-1A) and to “halve, between 1990 and 2015, the proportion of people who suffer from hunger” (MDG-1C). We have made progress on this: the proportion of people living on less than $1.25 a day in developing regions has dropped from 47% in 1990 to 22% in 2010; and the proportion of undernourished people in developing regions has decreased from 24% in 1990 – 1992 to 14% in 2011 – 2013 (UN, 2014). We need to make further efforts, however, in terms of the absolute numbers of people suffering from these issues, the

uneven distribution of the problems and slackening in the pace of improvement. For example, in 2010, one third of the world’s 1.2 billion extremely poor lived in India alone; and still, 842 million people were estimated to be suffering from chronic hunger in 2011– 2013 (UN, 2014). As a countermeasure, the United Nations Sustainable Development Goals (UN SDGs) that were adopted in September 2015 set up new targets to “eradicate extreme poverty for all people everywhere, currently measured as people living on less than $1.25 a day” (SDG-1.1) and to “end hunger and ensure access by all people, in particular the poor and people in vulnerable situations, including infants, to safe, nutritious and sufficient food all year round” (SDG-2.1) by 2030.

On the other hand, obesity and overweight are becoming an issue in both developed and developing

©2015 AIRIESGlobal Environmental Research19/2015: 165–172printed in Japan

How Can We Solve the Problems of Hunger and Obesity Simultaneously?

An Alternative Indicator for Sustainable Development

Seiji HASHIMOTO1*, Tomoki EHARA2, Kento TAMURA3 and Taro YAMAMOTO4

1*Department of Environmental Systems Engineering, College of Science and Engineering, Ritsumeikan University1-1-1 Noji-higashi, Kusatsu, Shiga 525-8577, Japan

2E-KONZAL3Advanced Architechtural Environmental and Civil Engineering Program,

Graduate School of Science and Engineering, Ritsumeikan University4Department of International Health, Institute of Tropical Medicine, Nagasaki University

and Leading Program, Graduate School of Biomedical Sciences, Nagasaki University*e-mail: shashimo@ fc.ritsumei.ac.jp

AbstractPoverty and hunger are serious global issues. On the other hand, obesity and overweight are becoming

an issue in both developed and developing countries. Recently, more attention has been directed towards addressing the double burden of malnourishment, which is the coexistence of both under-nutrition and over-nutrition in the same population. In this study, we estimated future per-capita energy intake and future prevalence of undernourishment (PoU) and overnourishment (PoO) for developing countries. Then we considered potential approaches to the reduction of hunger and obesity simultaneously through fair distribution of energy intake, i.e., reduction of the interquartile range (IQR) of the distribution. Our results show that, although economic growth may contribute to undernourishment reduction, it will not completely “end hunger” since some countries will not reach the economic growth level needed to make this feasible. Further, obesity could become a more important issue because the number of overnourished (NoO) would become comparable with the number of undernourished (NoU). We also found that, if a 50% IQR range reduction could be achieved, NoU and NoO could be decreased dramatically. Introducing this type of indicator for consideration would enable us to reduce hunger and obesity simultaneously. Further discussion, however, is needed regarding the levels of IQR reduction targets.

Key words: interquartile range (IQR), malnourishment, over-nutrition, per-capita energy intake, under-nutrition

166 S. HASHIMOTO et al.

countries. These constitute major risk factors for non-communicable diseases such as cardiovascular diseases, diabetes, musculoskeletal disorders and some cancers. According to the World Health Organization (WHO), most of the world's population live in countries where overweight kills more people than underweight (WHO, 2015). Moreover, the rate of increase of childhood obesity and overweight in developing countries has been more than 30% higher than in developed countries (WHO, 2015). Although obesity and overweight are not clearly mentioned in the SDGs, related targets are to “reduce by one third premature mortality from non-communicable diseases through prevention and treatment” (SDG-3.4) and to “end all forms of malnutrition” (SDG-2.2) by 2030.

Recently, more attention has been directed towards addressing the double burden of malnourishment, which is defined as the coexistence of both under-nutrition and over-nutrition in the same population (Shrimpton & Rokx, 2012). Chronic hunger is observed and monitored mainly in the least developed countries, where there is dire need for economic development. As development and growth occur, however, obesity and related health issues may also increase. What measures could be taken to address these issues simultaneously?

In this study, we estimated future per-capita energy intake based on GDP (gross domestic product) scenarios. Then we estimated the future prevalence of undernourishment (PoU) and over-nourishment (PoO) based on population and energy intake distribution scenarios. Finally, we considered potential approaches to the reduction of hunger and obesity simultaneously through fair distribution of energy intake, i.e., reduction of the interquartile range (IQR) of the distribution.

2. Methods

2.1 Target Foods and Scenarios UsedWe targeted 96 types of food reported in the Food

Balance Sheets of the Food and Agriculture Organization (FAO) (FAO, 2014). The Shared Socioeconomic Pathway (SSP) scenarios developed by the climate change research community were used for the future GDP and population scenarios from 2010 to 2050 (v9_130219) (IIASA, 2014). We selected SSP1 and SSP3 because SSP1 is the high economic growth scenario with low population growth, while SSP3 is the low economic growth scenario with high population growth. SSPs are reference pathways describing plausible alternative trends in the evolution of society and ecosystems in the absence of climate change or climate policies (O’Neil et al., 2014) and include many socioeconomic aspects other than GDP and population. We only used GDP and population scenarios among the SPPs, however. Therefore, we call SSP1 the “high economic and low population growth” (HELP) scenario and SSP3 the “low economic and high population growth” (LEHP) scenario. Estimations were made for five-year intervals.

2.2 Per-capita Energy IntakeFuture per-capita energy intakes in 187 countries and

regions were estimated, assuming that with the growth of per-capita GDP, those values would approach the average of developed countries or the average of Islamic countries with high per-capita GDP (including Brunei, Kuwait, Saudi Arabia and the United Arab Emirates because their per-capita GDPs are higher than the lowest per-capita GDP among the developed countries), considering differences in intake of foods such as pork and alcoholic beverages. More practically, the per-capita energy intake in country k at year t+1, pcCAL(k,t+1), was estimated using the following equation (Munesue & Masui 2008):

pcCAL(k, t +1)

= pcCAL(k, t) + α × pcGDP(k, t + 1) − pcGDP(k, t)pcGDP(k, t)

where pcCAL(k,t) is per-capita energy intake in country k at year t (kcal/capita/day), pcGDP(k,t) is the per-capita GDP of country k at year t (PPP-constant 2005 international $), and α is a parameter. α was calculated by executing a logarithmic regression analysis in per-capita GDP in 2010 as the x-axis and per-capita energy intake in 2010 as the y-axis:

pcCAL = α × ln(pcGDP) + β

Here, it is assumed that the change in per-capita energy intake under a unit change in per-capita GDP is constant under the same per-capita GDP, although the values of per-capita energy intake differ among countries in the base year (Munesue & Masui, 2008).

We fixed pcCAL(k,t) once per-capita GDP reached 20,000 (PPP-constant 2005 international $) or per-capita energy intake reached the average of developed countries or the average of Islamic countries with high per-capita GDP, because the energy intake pattern becomes stable under a per-capita GDP of 15,000 to 20,000 (PPP-constant 1990 international $) (Munesue & Masui, 2008).

The 57 members of the Organization of Islamic Cooperation are classified as Islamic countries and regions and others are classified as non-Islamic.

2.3 Prevalence of Undernourishment (PoU) and Overnourishment (PoO)

PoU (% of population) indicator has been monitored towards MDG target 1C of halving the proportion of people suffering from hunger. PoU is computed by comparing a probability distribution of habitual daily dietary energy consumption with a threshold level called the minimum dietary energy requirement (MDER). FAO (2014a, 2014b) provides the MDER threshold for each country. In the same way, PoO can be calculated. Overnourishment is defined for the purpose of this study as energy intake of more than 4,000 kcal/capita/day. The number of undernourished (NoU) and the number of

167How Can We Solve the Problems of Hunger and Obesity Simultaneously?

over-nourished (NoO) are estimated by multiplying PoU and PoO by the size of the reference population.

The skew-normal function is used for expressing the distribution of per-capita energy intake in each country as shown in Fig. 1 (FAO, 2014a, 2014b). With economic growth, this distribution shifts from the left to the right. For the purpose of this study, it is assumed that the distribution of energy intake among the population will shift with no changes in the shape (variation, skewness). The latest distribution curves were used with data on variation and skewness from FAO (2014b). These data are available only for major developing countries. Therefore we estimated PoU, NoU, PoO, and UoO for

the data-available countries.

2.4 Toward Fair Distribution of Energy IntakeThe pursuit of economic growth is an important

policy to “end hunger” because per-capita energy intake is expected to increase with economic development. However, as indicted in Fig. 1, economic development would not only decrease PoU and NoU, but could also increase PoO and NoO. We argue that a fair distribution of nutrition among people is required to address issues of both undernourishment and overnourishment.

In order to “end hunger” and “end obesity” simultaneously, the disparity of energy intake in the country should be reduced. We propose to reduce the interquartile range (IQR) of the energy intake distribution (Fig. 2). IQR is defined as the difference between the value which divides the lowest 25% and the highest 25% of a population. We ran a simulation of undernourishment and overnourishment in the case of a 50% reduction of the IQR by 2050, i.e., 50% reduction in variation of the skew-normal function, assuming linear reduction of IQR through 2050. This could increase the equitable distribution of food resources globally and among populations within countries.

3. Results and Discussion

3.1 Per-capita Energy IntakeThe average patterns of per-capita energy intake for

developed countries and Islamic countries with high per-capita GDP in 2010 are shown in Fig. 3. The energy intake in developed countries is a bit higher than that in the Islamic countries. Also energy intake from cereals is higher and those from vegetable oils, alcoholic beverages, meat, and milk are smaller in the Islamic countries. The significance levels of the regression analyses are < 0.01 for both non-Islamic and Islamic countries and regions.

pattern becomes stable under per-capita GDP of 15,000 to 20,000 (PPP-constant 1990 international $) (Munesue and Masui 2008). 2.3 Prevalence of undernourishment and overnourishment The prevalence of undernourishment (PoU) (% of population) indicator has been monitored towards MDG target 1C of halving the proportion of people suffering from hunger. PoU is computed by comparing a probability distribution of habitual daily dietary energy consumption with a threshold level called the minimum dietary energy requirement (MDER). FAO (2014a, 2014b) provides MDER threshold for each country. In the same way, the prevalence of overnourishment (PoO) can be calculated. Overnourishment is defined for the purpose of this study as energy intake of more than 4,000 kcal/capita/day. The number of undernourished (NoU) and the number of overnourished (NoO) are estimated by multiplying the PoU and PoO by the size of the reference population. The skew-normal function is used for expressing distribution of per-capita energy intake in each country as shown in Fig. 1 (FAO 2014a, 2014b). With economic growth, this distribution is shifted from the left to the right. For the purpose of this study, it is assumed that the distribution of energy intake among population will be shifted without any changes in the shape (variation, skewness). The latest distribution curves were used with data for variation and skewness from FAO (2013b).

Fig.1 Distribution of per-capita energy intake with prevalence of undernourishment (PoU), overnourishment (PoO), minimum dietary energy requirement (MDER), and threshold of overnourishment 2.4 Toward fair distribution of energy intake The pursuit of economic growth is an important policy to “end hunger” because

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Fig.1 Distribution of per-capita energy intake with prevalence of undernourishment (PoU), overnourishment (PoO), minimum dietary energy requirement (MDER), and threshold of overnourishment.

per-capita energy intake is expected to increase with economic development. However, as indicted in Fig.1, the economic development would not only decrease the PoU and NoU, but also could increase PoO and NoO. We argue that a fair distribution of nutrition among people is required to address issues of both undernourishment and overnourishment. In order to achieve “end hunger” and “end obesity” simultaneously, disparity of energy intake in a county should be reduced. We propose to reduce the interquartile range (IQR) of energy intake distribution (Fig. 2). IQR is defined as the difference between the value which divides the lowest 25% and the highest 25% of a population. We made simulation on undernourishment and overnourishment in the case of 50% reduction of the IQR by 2050, assuming liner reduction of IRQ through 2050. This could increase equitable distribution of food resources globally and among populations within countries.

Fig.2 Interquartile Range (IQR) of energy intake distribution and its 50% reduction scenario 3. Results and discussion 3.1 Per-capita energy intake Average pattern of per-capita energy intake for developed countries and Islamic countries with high per-capita GDP in 2010 are shown in Fig.3. The energy intake in developed countries is a bit higher than that in the Islamic countries. Also energy

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Fig.2 Interquartile Range (IQR) of energy intake distribution and its 50% reduction scenario.

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Fig.3 Average pattern of per-capita energy intake in developed countries and Islamic countries with high per-capita GDP in 2010.

168 S. HASHIMOTO et al.

Figure 4 shows the distribution of estimated per-capita energy intake for 187 countries under the HELP and LEHP scenarios. The current peak of 2800 – 3000 kcal/capita/day was estimated to move to 3200 – 3400 kcal/capita/day in 2050 under both scenarios: developing countries will increase their food energy consumption in accordance with their economic development. A higher peak was observed under the HELP scenario because of its higher economic growth.

3.2 Prevalence of Undernourishment (PoU) and Overnourishment (PoO)

The results of our scenario-based simulations show that the PoU (% ) in developing countries could drop from the current 12% to 7 – 9% by 2030 and 6 – 9% by 2050, while PoO would increase from the current 6% to 8 – 9% by 2030 and 8 – 10% by 2050 (Fig. 5a).

In terms of number, NoU could drop from the current 850 million to 550 – 750 million by 2030 (Fig. 5b), but it could increase instead under the LEHP scenario due to the high population growth. Population growth in Asia and Africa would have a particularly big effect on the increase of NoU in those countries under the LEHP scenario (Fig. 6b). China is expected to reduce its NoU significantly, with India’s keeping steady and other Asian countries’ and Africa’s increasing under the LEHP scenario (Fig. 6b). Although the HELP scenario would enable NoU reduction overall, Africa would still not manage to reduce it (Fig. 6a).

NoO could double, reaching 800 million by 2050 under both the HELP and LEHP scenarios (Fig. 5b), because of high economic growth under the HELP scenario and high population growth under the LEHP scenario. China’s share would continue to be large, and the NoO of Africa, India and other Asian countries is expected to increase under both HELP and LEHP scenarios (Fig.7).

Overall, the results indicate that, although economic growth could contribute to reduction of undernourishment, it would not completely “end hunger” since some countries would not reach the economic growth level needed to make this feasible. Further, obesity could become a more important issue because NoO would become comparable to NoU.

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Fig.5 Estimated prevalence of undernourishment (PoU) and overnourishment (PoO) and numbers of undernourished (NoU) and overnourished (NoO) under high economic and low population growth (HELP) and low economic and high population growth (LEHP) scenarios.

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169How Can We Solve the Problems of Hunger and Obesity Simultaneously?

3.3 Potential Scenarios for Reducing Hunger and Obesity Simultaneously

If a 50% IQR reduction can be achieved, the PoU could decrease dramatically to 3–5% by 2030 and 2–3% by 2050 and the NoU could drop to 300 – 400 million by 2030 and 100–300 million by 2050 (Fig. 8). The NoU in China and India was estimated to decrease significantly under both HELP and LEHP scenarios (Fig. 9), while

the NoU in Africa would remain steady through 2050 under the LEHP scenario (Fig. 9b).

In addition, PoO could decrease significantly to 2–3% by 2050 and NoO to 200–300 million by 2050 (Fig. 10). China’s share would be still large, but Africa, India, and other Asian countries would be able to avoid increased NoO under both HELP and LEHP scenarios (Fig.11).

As shown above, if we can start considering this type

Fig.6 Number of undernourished (NoU) under high economic and low population growth (HELP) and low economic and high population growth (LEHP) scenarios.

a) NoU under HELP, b) NoU under LEHP

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a) NoO under HELP scenario, b) NoO under LEHP scenario

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170 S. HASHIMOTO et al.

of indicator, we will be able to reduce hunger and obesity simultaneously. In order to address the double burden of malnutrition, we emphasize the need to integrate efforts to address both undernourishment and overnourishment, i.e., to increase equitable distribution of food resources globally and among populations within countries. We need further discussion, however, about levels of IQR reduction targets. For example, the

variations of the skew-normal function for China and India were 0.32 and 0.25, respectively, in 2013 (FAO, 2014b), so it maybe difficult to reduce it by 50% for those countries because the lowest value among the developing countries is currently 0.21 (FAO, 2014b). On the other hand, it would be meaningful for any African countries whose variations exceed 0.35.

Fig.8 Prevalence of undernourishment (PoU) and number of undernourished (NoU) with a 50% IQR range reduction under high economic and low population growth (HELP) and low economic and high population growth (LEHP) scenarios.

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171How Can We Solve the Problems of Hunger and Obesity Simultaneously?

4. Conclusions

In this study, we estimated future per-capita energy intake and future PoU and PoO for developing countries. Then we discussed potential approaches to the reduction of hunger and obesity simultaneously through fair distribution of energy intake, i.e., reduction of the IQR of the distribution. The following conclusions were drawn:1) Although economic growth may contribute to

undernourishment reductions, it will not completely “end hunger” since some countries will not reach the economic growth level needed to make this feasible.

Further, obesity could become a more important issue because NoO would become comparable to NoU.

2) If a 50% IQR range reduction could be achieved, NoU and NoO could be decreased dramatically. Introducing this type of indicator for consideration would enable us to reduce the hunger and obesity simultaneously. Further discussion, however, is needed regarding levels of IQR reduction targets.As mentioned in Section 1, the issues of obesity and

overweight are not explicitly described in the SDGs. We are about to start implementing the SDGs and developing national or local SDGs by reflecting on our own issues. Addressing the double burden of

Fig.10 Prevalence of overnourishment (PoO) and number of overnourished (NoO) with a 50% IQR range reduction under high economic and low population growth (HELP) and low economic and high population growth (LEHP) scenarios.

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malnourishment would be an important point of discussion in such activities.

Acknowledgements

This research was supported by the Environment Research and Technology Development Fund (S-11) of the Ministry of the Environment, Japan. We would like to thank the members of this project, including Dr. Tomohiro Tasaki and Dr. Masahiko Iguchi, for their kind discussion of this research.

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Seiji HASHIMOTO

Seiji HASHIMOTO is a professor in the Department of Environmental Systems Engineering, Ritsumeikan University, Japan. He studies assessment methodologies and system design for sustainable resource and waste management, looking at whole systems comprehensively from extraction of resources through disposal of

wastes. He is a member of the International Resource Panel (IRP) of the United Nations Environmental Programme (UNEP) and was a lead author of the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC).

Tomoki EHARA

Tomoki EHARA is a founder and representative executive of E-KONZAL, a Japanese consulting firm with expertise in energy and environmental policies. He has been a member of the Japanese Low-Carbon study since 2004. He is also an expert on renewable energy (mainly photovoltaic) and has been a member of the IEA PVPS Task8

team as well as several renewable energy committees in Japan.

Kento TAMURA

Kento TAMURA is a master’ s student in the Graduate School of Science and Engineering, Ritsumeikan University, Japan. His research examines the relationship between our biomass usage, i.e., consumption of food, biofuel and timber, and related planetary boundaries such as change in land use, biodiversity loss and

nitrogen and phosphorous flows. Now he is studying the consistency between planetary boundaries of change in land use and boundaries of biodiversity loss and measures to deal with both the boundaries.

Taro YAMAMOTO

Taro YAMAMOTO graduated from Nagasaki Medical School in 1990 and went on to post graduate school. He has earned two doctorate degrees, one in virology and the other in international health from Nagasaki University and the University of Tokyo, respectively. He has since then worked mainly in academia at

universities, including Nagasaki University, Kyoto University and Cornell University. He is now professor and chairman of the Department of International Health, Institute of Tropical Medicine, Nagasaki University. Before joining his current position he worked as a senior advisor on international health policy in the Ministry of Foreign Affairs for three years. His long-term overseas experience includes Zimbabwe (1999–2000), the U.S. (2003- 04) and Haiti (2004-05). He has participated in emergency relief in Haiti (2010), eastern Japan (2011) and Nepal (2015).

(Received 4 September 2015, Accepted 9 November 2015)