ATOA Journal

3.       Introduction 

Benin is a country in West Africa bordered by Burkino Faso, Niger, Nigeria, Togo as well as the Atlantic Ocean. Descibed as increasingly stable Benin still faces many challenges such as extreme corruption and a low adult literacy rate. Hunger is another major problem and this paper assesses the extent ofself-reported hungeramong 1,200 Benin respondents and then searches for the factors that predict hunger in that country.Even though Benin has been somewhat neglected the literature devoted to what is commonly called food insecurity will be reviewed. Some of the issues raised in the African food insecurities literature will be addressedand are questionscentral to this paper’s analysis. These include whether rural residents, especially agricultural workers, are hungrier than other Beninrespondents as well as whether there are gender differences in the degree of hunger. The discussion section will attempt to answer the question as to whether this paper has any implications or adds any knowledge about hidden hunger in Benin. 

4.       Hunger in the World and Africa 

According to theWHES (World Hunger Education Service) World Hunger and PovertyFacts and Statistics Report (2015) [1] hunger has three meanings. Two of those meanings deal with craving or desire for food. The third meaning refers to the want or scarcity of food in a country and it is in this sense that this paper addresses hunger. There are two classifications of hungry person that are of interest here. The broadest classification includes those who suffer from what is known as “Hidden hunger.” Since this paper utilizes a self report measure to assess hunger the results reported in this paper may be seen to more closely reflect hidden hunger. These are an estimated two billion persons that are affected by a chronic deficiency of essential vitamins and minerals.Among this population the signs of malnutrition and hunger are less visible but it has negative and long term consequences, often for long term health, productivity and cognitive development [2]. The second classification includes those who demonstrate clear cut hunger in the latest UN Food and Agriculture Organization Report (2015) the estimate was that 925 million people were hungry worldwide and that 239 million people in sub-Saharan Africa were hungry or undernourished. This made Africa the continent with the second largest number of hungry people following Asia and the Pacific with 578 million. Due to the difference in population sizes, Sub-Saharan Africa actually had the largest proportion of hungry/undernourished people, estimated at 30 percent of the population compared to 16 percent for Asia and the Pacific. 

5.       Food Insecurity in Sub-Saharan Africa 

As Clover (2003) [3] has suggested despite the fact that the right to food is one of the most consistently acclaimed assertions in international human rights law no other human right has been so frequently and spectacularly violated. Her discussion of food insecurity in Sub-Saharan Africa leads to the conclusion that hunger is a multi-faceted issue in Africa and that just growing more food will not eradicate the problem. Agriculture is important and Clover points out that Africa has gone from being a key agricultural commodity exporter into being a net importer the African continent now receives the most food aid. Perhaps the most important point Clover made was to suggest hunger will not be eradicated by just throwing money at the problem. Hunger is a political creation which must be ended by political means a theme which will bementioned below and revisited in the Discussion section. 

6.       Identified Hunger in Benin 

Malnutrition is the 8^th leading cause of death in Benin, and the 10^th leading cause of total deaths in the country; the country ranks 23^rd in the world in this category [4]. According to the World Food Program (2017) Benin relies on agriculture as the basis of its food security as well as economic development. Agricultural development is hindered by factors such as lack of modern farming technology poor soil, high food prices and inadequate storage preservation and food processing. The country is also highly vulnerable to natural disasters like flooding and drought which contribute further to nutritional instability. According to the World Food program in Benin 16 percent of children under 5 suffer from acute malnutrition and 45 percent of that same age group are described as chronically malnourished. 

7.       Hunger Related Factors 

According to Sanchez and Swaminathan. (2005) [5] roughly half 50 %, of the hungry worldwide are found in small holder farming households. and most likely three-quarters of the hungry in sub-saharanAfrica. This paper will look at farmers in order to determine if they are in fact hungrier than other Benin respondents. There are several issues that emerge from the rural hunger literature that will affect all farmers. The first is climate change Shisanya and Mafongoya (2016) [6] who suggested that smallholder subsistence farmerswill face severe negative impacts from climate change with their household food securitybeing seriously affected. This paper also addressethe waygender affects hunger in Benin especially female farmers. As Abebayo and Adekunie (2016) [7] have indicated the division of labor is becoming blurred. Many men have left the land to work in the towns or neighboring countries. Also HIV related diseases and deaths have had a major effect on the agricultural labor force As a result women sometimes comprise up to 80 % of the adult rural population and made to take on jobs that were traditionally done by men. 

8.       The Study: The Research Question

The picture of Benin presented above is grim. It is described an impoverished country with limited resources that cannot overcome its hunger problem in the near future. Against that backdrop, this study looks at the scope of hunger in Benin and attempts to identify the factors that are related to hunger in present day Benin. As the title of this paper suggests the search will be to determine whether there are any rays of hope for the hunger problem in Burundi or is hunger destined to be perpetual. Several known rays of hope are currently in the process of development and will be covered below in the Discussion section.

9.       Method

9.1.  The Data 

This study’s Data Source is the Afrobarometer project, As recently described by Fry (2017) [8] it is a collaborative research effort formed in 1999 when three independent research projects merged there were three core partners involved Michigan State University the Institute for Democracy in South Africa and the Center for Democratic Development. The Project's objectives are as follows: 1) to produce scientifically reliable data on public opinion in sub-Saharan Africa, 2) to strengthen institutional capacity for survey research in Africa, and 3) to broadly disseminate and apply survey results In 2000 Afrobarometer joined other regional barometers to form the Global Barometer Network the following year Afrobarometer completed the Round 1 survey. The project started with 12 countries in Round 1 and by 2016 when Round 6 was completed it included 36 African countries. The project uses a standardized questionnaire with new questions or country specific questions added by round. The individual country is the unit of analysis and sampling goal is to create national probability samples which represent cross sections of adult citizens, 18 years and older for each country. Sampling sizes are set at either 1, 200 or 2,400 respondents depending upon the country’s population size. The sampling procedures used in all of the Afrobarometer surveys are explained in detail in Bratton, Mattes and Gyimah-Boadi (2005) [9].

9.2.  The Dependent Variable: Hunger 

The study’s questionnaire included what is called The Lived Poverty Index used in the Afrobarometer studies which was adopted from Mattes (2003) [10]. One of the five questions in the Index asked “Over the past year how often if ever have you or anyone in your family gone without enough food to eat”.Fixed responses to this question were: never just once or twice several times many times always. These responses were coded as follows Never =1 just once or twice = 2 and many times and always =3.These categories provide the basis for the ordered logistical analysis presented in the Results section. 

9.3.  The Independent Variables 

The questionnaire did not ask respondents to report their income in the Afrobarometersurvey. As Bratton (2008) [11] indicated this is because manycitizens in poor countries operate in informalmarketswhere cash transactions including income areunrecorded and difficult to measure. Instead thisresearch used what is called an Asset-based WealthIndex a summed index created from fourquestions that ask abouthousehold assets. The survey asked respondents “Which of these things do youpersonally own: A radio?A television? A motor vehicle, car or motorcycle? a cell phone?” Responses to these questions were coded as binary. Either (0=don’t own; 1=own) and used to create a summed index for this study. Othercontrol variables are listed in Table 1 and were measured by a single item, like age and others were collapsed into fewer categories. Race was not included in Table 1 because over 99 percent of the respondents were classified as Black Africans. Education was reduced to five categories by combining no school informal only and completion some primary. Religion was reduced to three categories, Chrisiams, Muslims and others. Respondents were asked a series of work related questions like their employment status and to identify their occupationsRespondents were asked hypothetical questions like their first priority for additional investment if the country could increase spending. Fixed responses were provided which included education, infrastructure, security, healthcare, agriculture and development, energy supply or none of the above. The responses to these questions are also listed in Table 1. 

Table 1 shows that Afrobarometer met its sampling objective with equal numbers of males and females 600 each.This Beninsample was relatively young with 70 percent under the age of 50. Forty five percent of the respondents have some attendance or have completed primary school while 38 percent have not attended school or have received informal education only. Thirteen percent attended some or completed high school and 4 percent of the sample have post-secondary education. Only 10 percent of the sample was employed and 87 percent were unemployed. The sample was overwhelmingly rural 86percent and 70 percent listed their occupations as in agriculture, farming, forestry or fishing. In terms of the assets they owned 38 percent indicated they only owned a radio while 34 percent indicated they did not own any of the assets on the list. Eight percent of the sample owned a radio, TV and a vehicle. 

10.       Results 

The next task in the analysis was to identify the respondents self-reported level of hunger and perceptions of problems the government should address or where the government should direct funds if money was available. The responses to those items appear in Table 2.

Table 2 reveals that 77percent of this Benin sample reported some degree of hunger with 23 percent indicating they are always hungry. 82% indicated the government was doing badly ensuring that citizens had enough to eat. In terms of improving living standards for the poor 72 percent of the Benin respondents responded that the government was doing poorly. Education was the number one area where respondents would invest more funding, if it was available followed by infrastructure and health care. Agricultural development was fourth chosen by 15 percent of the respondents. 

The next task in the analysis was to cross-tabulate the study’s independent variables by hunger. These results appear in Table 3. 

Table 3 shows that almost all of the variables included in Table 3 were statistically significant, with gender being the only exception Most variables included in Table 3 were highly significant at .000.The final task in the analysis was to conduct an ordered logistical regression analysis variables in order to determine which variables predicted hunger in Benin. An ordered logistical model was appropriate because the study had a categorical dependent variable. The statistical program used for all of the analysis presented in this paper was Stata and Long and Freese (2006) [12] discuss the use of regression models for categorical dependent variables when using Stata. The results of this study’s ordered logistical analysis appear in Table 4. 

Table 4 shows that seven variables reached significance in the regression equation. In order of their strength these were whether respondents thought the government was ensuring that people had enough to eat respondent ‘Self reported meeting of their basic needs the extent of their personal assets the governments effort to improve the living standards of the poor, age, religion and being an agricultural worker Perhaps what is most interesting are those variables that were expected to be significant and were not. These include gender and the rural-urban dimension which the literature suggested were both significant predictors of hunger. Perhaps this can be explained by the significance of agriculture as an occupation. These issues will be included in the Discussion below. 

11.       Discussion 

At first glance the results of this study suggests it suffers from an abundance of significant results. This is not true in that these results should have been expected and can be interpreted. It must be remembered that the study’s dependent variable hunger, was measured by a single item included in the Afrobameter poverty index [10]. Whether respondents are able to meet their basic needs is central to the items included in  the Poverty Index so the fact that the basic needs item was so highly significant was also to be expected. The fact that the Assest-based Wealth indicator was highly significant as was age,was not surprising the elderly are m,more likely to be hungry in poor nations. These findings are consistent with the intrepretation that poverty is the primary cause of hunger in Benin. 

This is not to say that there were some surpring findingsn in this paper beginning  the importance of respondent perceptions about how well the government was handling whether people had enough to eat as well as raising the living standards of the poor. These results were contrary to earlier findings about respondent perceptions about the government and the HIV/AIDS epidemic [13,14] .  Simply respondents who resided in contries with the high HIV/AIDS prevalence rates, including some with rising rates, indicated they thought their government was doing a good job handling the HIV/AIDS epidemic. By way of contrast,these Benin respondents indicated they thought the government was doing a poor job handling food insecurity and raising the living standards of the poor. 

Another surprising finding was that gender did not predict the degree of hunger. When the female farmworker issue was examed more closely roughly one quarter (26 percent) of those who listed their occupation as agriculture were female and hunger was not found to be related to that breakdown (Data not shown). Why religion especially the food security status of Muslims was so significant was not readily apparent. Age was less surprising in that the elderly are more likely to be hungry in poor nations. 

The policy issue forthcoming from this study is that the government should develop and promote a public media campaign that stresses its recognition of hunger and discusses its current efforts to address hunger and the living standards of the poor. Regardless of the inability to have an impact the government must acknowledge  the problem and indicate it is doing all it can. It there is no funding available to address the hunger issue the government should acknowledge that and indicate it is seeking external help to address hunger in Benin. 

In conclusion the answer to the question which generated this paper is that hunger will be or remain a continuing problem in Benin into the foreseeable future. Hidden hunger is apparent, with 71Seventy-one percent of the respondents to this survey reporting some degree of hunger and with about one-fourth, 23 percent, reporting that they are hungry all the time. About 87 percent of the respondents in this study were unemployed and 27 percent listed some form of agriculture as their occupation. The surprising finding was that while significant at the bivariate level, gender and the rural urban distinction was not significant in the regression analysis suggesting that everyone is hungry in Benin, women and men and this study suggests there is no apparent improvement on the horizon. The policy implication of the study is that hunger in Benin will not have any short-term solutions. The findings suggest that there is a need for the government to engage in a media campaign, indicating it is aware of the problem and addressing hunger to the best of its ability. What follows must be a long term plan especially to generate the funding to implement an anti-food insecurity plan. Essentially the lack of substantive action oriented findings is griom in that no short-term fix was suggested in these results. Jobs, jobs appear to be the solution and how these jobs might be created appears unclear.

Table 1: Social and Demographic Characteristics of the Benin Sample (N=1,200).

Table 2: Self-Reported Hunger, lack of Access to basic necessities (Food) and perceptions of  overnmental priorities and possible investment (N=1,200).

­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­­Table 3: Cross-tabulation Hunger and Selected Independent Variables (N=1,200).

Table 4: Logistic regression with self-reported hunger as the dependent variable.

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3.       Clover J (2003) "Food security in sub-saharan Africa: feature." African security review 12: 5-15.

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Hunger is a worldwide problem, and Africa is the continent with the world’s highest percentage of hungry persons Benin is one of Africa’s poorest and hungriest countries and this paperaddresses those issues and then identifies the factors that predict hunger in that country. Benin has a substantial rural population slightly over half of the sample used in this study resides in rural areas and those respondents will receive some attention in this paper especially because the paper looks closely at literature’s suggestion thatAfrican farmers may be hungrier than the rest of the population and also that gender may be a factor.This study is based on a national probability sample of 1,200 Benin respondents included in Round 6 of the Afrobarometer survey conducted in 2014. The search is for policy related factors that might help alleviate Benin’s hunger problem. To preview the findings this study did not find any light at the end of the tunnel regarding hunger for Benin.The findings do provide information about the extent of hidden hungerin Benin.The result  highlight the role of poverty as the root cause of hunger in Benin. The study found support for the notion that farmers are hungrier than other respondents but gender and urban-rural differencesdisappeared in the analysis. The surpring findings were that respondent’s perceptions that the government was not ensuring that people have enough to eat and not handling improvement of the living standards of the poor were highly as well as age significant predictors of hunger in Benin.