Is Hunger Destined to be Perpetual in Burundi?

Abstract

p> Hunger is a worldwide problem, and Africa is the continent with the world’s highest percentage of hungry persons; Burundi is Africa’s hungriest country. This paper addresses hunger in Burundi and then identifies the factors that predict hunger in that country. Burundi is a rural country and its rural population will receive a great deal of attention in this paper, especially because the study looks closely at literature’s suggestion that farmers may be hungrier than the rest of the population, and gender may be a factor. This study is based on a national probability sample of 1,200 Burundi respondents included in Round 6 of the Afrobarometer survey conducted in 2014. The search is for policy related factors that would help alleviate Burundi’s hunger problem. To preview the findings, this study did not find any light at the end of the tunnel. The factors that predicted hunger were primarily immutable indicators, education, agriculture as an occupation, and wealth, as measured by assets owned. Over 80 percent of the respondents felt the government was not ensuring that people had enough to eat. Eighty-seven percent were unemployed, 86 percent were rural residents and 71 percent of the respondents reported some degree of hunger, about one-fourth reported being hungry all of the time. The gender and hunger relationship was significant at the bivariate level, but that relationship disappeared in the ordered logistical analysis. </p

Full text

Food Science and Nutrition Studies
ISSN 2573-1661 (Print) ISSN 2573-167X (Online)
Vol. 1, No. 1, 2017
www.scholink.org/ojs/index.php/fsns
11
Is Hunger Destined to be Perpetual in Burundi?
Lincoln J. Fry1*
1 Academic Member, Sociology Research Unit, Athens Institute for Education and Research (ATINER),
Athens, Greece
* Lincoln J. Fry, E-mail: lincolnfry@bellsouth.net
Received: February 21, 2017 Accepted: March 5, 2017 Online Published: March 15, 2017
doi:10.22158/fsns.v1n1p11 URL: http://dx.doi.org/10.22158/fsns.v1n1p11
Abstract
Hunger is a worldwide problem, and Africa is the continent with the world’s highest percentage of
hungry persons; Burundi is Africa’s hungriest country. This paper addresses hunger in Burundi and
then identifies the factors that predict hunger in that country. Burundi is a rural country and its rural
population will receive a great deal of attention in this paper, especially because the study looks closely
at literature’s suggestion that farmers may be hungrier than the rest of the population, and gender may
be a factor. This study is based on a national probability sample of 1,200 Burundi respondents included
in Round 6 of the Afrobarometer survey conducted in 2014. The search is for policy related factors that
would help alleviate Burundi’s hunger problem. To preview the findings, this study did not find any
light at the end of the tunnel. The factors that predicted hunger were primarily immutable indicators,
education, agriculture as an occupation, and wealth, as measured by assets owned. Over 80 percent of
the respondents felt the government was not ensuring that people had enough to eat. Eighty-seven
percent were unemployed, 86 percent were rural residents and 71 percent of the respondents reported
some degree of hunger, about one-fourth reported being hungry all of the time. The gender and hunger
relationship was significant at the bivariate level, but that relationship disappeared in the ordered
logistical analysis.
Keywords
Burundi, hunger, rural, agriculture, farmers
1. Introduction
In 2014, Burundi topped the Global Hunger Index for the third year in a row. The country has been
described as one of the least developed countries (Jenicek & Grofova, 2015) and the hungriest, not only
in Africa, but in the world (Africaranking.com, 2015). A landlocked country in the African Great Lakes
region, it is bordered by Rwanda, Tanzania and the Democratic Republic of the Congo. Two civil wars
and genocides during the 1970s and again in the 1990s have left this predominantly rural country not
only undeveloped and its population of roughly 10.5 million, one of the poorest in the world.

www.scholink.org/ojs/index.php/fsns Food Science and Nutrition Studies Vol. 1, No. 1, 2017
12
Published by SCHOLINK INC.
Against that backdrop, this paper assesses the extent of self-reported hunger among 1,200 Burundi
respondents and then searches for the factors that predict hunger in that country. Even though Burundi
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 addressed and are
questions central to this paper’s analysis. These include whether rural residents, especially agricultural
workers, are hungrier than other Burundi respondents. Other topics include whether gender differences
in hunger are apparent, and are there any implications in this research that add any knowledge about
hidden hunger? As the title of the paper suggests, the big question will be is there any light at the end of
the tunnel regarding hunger in Burundi?
1.1 Hunger in the World and Africa
According to the WHES (World Hunger Education Service) World Hunger and Poverty Facts and
Statistics Report (2015), 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 persons that are of interest here.
The broadest classification includes those who suffer from what is known as “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 (Muthayya et al., 2013). 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.
1.2 Food Insecurity in Sub-Saharan Africa
As Clover (2003) has suggested, despite the fact that the right to food is one of the most consistently
acclaimed rights in international human rights law, no other human right has been so frequently and
spectacularly violated. Clover’s 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 be mentioned below and revisited in the Discussion section.
1.3 Hunger in Burundi
Malnutrition is the 4th leading cause of death in Burundi, and the 3rd leading cause of total deaths in the

www.scholink.org/ojs/index.php/fsns Food Science and Nutrition Studies Vol. 1, No. 1, 2017
13
Published by SCHOLINK INC.
country. The country ranks 6th in the world in this category (worldlifeexpectancy.com, 2016), with over
60% of the country’s population deemed undernourished. According to Jenicek and Grofova (2015)
they classify Burundi as the world’s third poorest country, a country that is highly vulnerable to natural
disasters which contribute further to nutritional instability. Burundi has been afflicted by a wide range
of challenges such as land shortage, land degradation, corruption, increased political instability and
ethnic civil unrest (especially since 1990), and, HIV/AIDS. According to Fauk et al. (2017), there are
610,000 children in Burundi who are orphans. Most because of AIDS, but many have been abandoned
by their parents because of their dire economic situation. To make matters worse, even those with intact
families are faced with poor access to education, which means that the country’s youth is challenged in
the task of bringing about significant development in the near future.
Burundi is a rural country and its economy is based on agriculture. As Jenicek and Grofova (2015)
noted, as of 2007, 90 percent of Burundi’s population lived in rural areas. Food crops occupy 85
percent of agricultural land and most crops are produced for the owner’s consumption. There is a
shortage of agricultural land and there has been a fourfold increase in population and land holdings
have been divided to accommodate the claims of sons for family land. The return of nearly 500.000
refugees has increased the pressure on land ownership. The UN started intervening in 1993—first
through efforts at peace-keeping, and then through reconstruction projects. Today, 42% of Burundi’s
national income is from foreign aid.
1.4 Hunger and Farmers, Climate Change, and Gender
As Sanchez and Swaminathan (2005) indicated, roughly half, 50%, of the hungry are found in small
holder farming households. Another 20% are the landless rural and 10% are pastoralists, fishers and
forest dwellers; the remaining 20 percent are urban residents. This paper will look at farmers, in order
to determine if they are in fact hungrier than other Burundi respondents. There are several issues that
emerge from the rural hunger literature. The first is climate change Shisanya and Mafongoya (2016)
who suggested that smallholder subsistence farmers will face severe negative impacts from climate
change, with their household food security being seriously affected. This paper examines the extent to
which farmers see climate change as an issue the government should address. The final issue addressed
here is the way gender affects hunger in Burundi, especially female farmers. As Abebayo and Adekunie
(2016) 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 are made to take on jobs that were traditionally done by men; farming is one focus in
this paper.
1.5 The Study: The Research Question
The picture of Burundi painted by Jenicek and Grofova (2015) is grim. They described an
impoverished, over-populated country with limited resources that cannot overcome its hunger problem
in the near future. They noted that in 2005, the real per capita GNP dropped to $105, which meant that

www.scholink.org/ojs/index.php/fsns Food Science and Nutrition Studies Vol. 1, No. 1, 2017
14
Published by SCHOLINK INC.
if that trend persisted, Burundi would need 225 years to reduce its poverty by half. Against that
backdrop, this study looks at hunger in Burundi and attempts to identify the factors that are related to
hunger in present day Burundi. 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.
2. Method
The Data: This study’s Data Source is the Afrobarometer project. As recently described by Fry (2017),
it is a collaborative research effort formed in 1999 when three independent research projects merged;
there were 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 Round 6
was completed, in 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).
2.1 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). 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.
2.2 The Independent Variables
The Afrobarometer questionnaire does not ask respondents to report their income. As Bratton (2008)
indicated, this is because many citizens in poor countries operate in informal markets where cash
transactions, including income, are unrecorded and difficult to measure. Instead, this research used
what is called an Asset-based Wealth Index, a summed index created from four questions that ask about
household assets. The survey asked respondents: “Which of these things do you personally own: A
radio? A television? A motor vehicle, car or motorcycle? a cell phone?” Responses to these questions

www.scholink.org/ojs/index.php/fsns Food Science and Nutrition Studies Vol. 1, No. 1, 2017
15
Published by SCHOLINK INC.
were coded as binary. Either (0 = don’t own; 1 = own), and these responses were used to create a
summed index for this study.
Other control variables are listed in Table 1 and were measured by a single item, like age, and others
were collapsed into fewer categories. Race and religion are not included in Table 1 because over 99
percent of the respondents were classified as Black Africans and over 95 percent of the respondents
reported that they were Christians. Education was reduced to four categories from nine by combining
no school, informal only and then creating primary, high school. And post secondary categories.
Respondents were asked a series of work related questions, like their employment status. Respondents
were also asked to identify the most important problems faced by the country that the government
should address. Respondents were provided with two hypothetical questions which asked what would
be their top and second priorities 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. Note that race and religion are not included in Table 1 because over 99 percent of
the respondents were classified as Black Africans and over 95 percent of the respondents reported that
they were Christians.
Table 1. Social and Demographic Characteristics of the Burundi Sample (N = 1,200)
Variable
N (%)
Gender
Male
600 (50)
Female
600 (50)
Education
No formal/informal schooling
456 (38)
Some/Primary school completed
540 (45)
Some/completed high school
156 (13)
postsecondary/college/graduation
46 (4)
Employment
Unemployed
1,038 (87)
Employed part time
38 (3)
Employed full time
124 (10)
Residence
Urban
168 (14)
Rural
1,032 (86)
Age
18 through 29
402 (34)

www.scholink.org/ojs/index.php/fsns Food Science and Nutrition Studies Vol. 1, No. 1, 2017
16
Published by SCHOLINK INC.
30 through 49
434 (36)
50 and over
364 (30)
Agricultural worker/occupation
Yes
818 (70)
No
356 (30)
Asset-based Wealth
None of these
407 (34)
Radio
458 (38)
Radio and TV
241 (20)
Radio, TV and motor vehicle (car or motorcycle)
93 (8)
Table 1, shows this Burundi sample 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, 86 percent 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.
3. Results
The next task in the analysis was to identify the respondents self-reported level of hunger, how often
they go with out basic necerssities (food) 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. Self-Reported Hunger, Lack of Access to Basic Necessities (Food), and Perceptions of
Governmental Priorities and Possible Investment (N = 1,200)
Variable
N (%)
Hunger
Never
348 (29)
Sometimes
581 (48)
Always
271 (23)
Basic necessities (food)
About once every two to three months
42 (4)

www.scholink.org/ojs/index.php/fsns Food Science and Nutrition Studies Vol. 1, No. 1, 2017
17
Published by SCHOLINK INC.
Once a month
105 (9)
Two or three times a month
165 (14)
Once a week
185 (16)
Several times a week
455 (38)
Everyday
158 (13)
Government ensuring everyone has enough to eat
Badly
971 (82)
Well
216 (18)
Respondent selections of the priorities government should
address
Poverty/Food Shortage/famine
294 (9)
Farming and Agriculture
266 (8)
Corruption
233 (7)
Health
220 (7)
Crime
215 (7)
Water supply
207 (6)
Unemployment
42 (4)
Management of the economy
88 (3)
AIDS
7 (> 1)
Votes for Top Priority for additional government investment
(count)
Agricultural development
649
Healthcare
600
Education
440
Infrastructure
244
Security
242
Energy supply
182
None of the above
20
Table 2 reveals that 71 percent of this Burundi sample report some degree of hunger, with 23 percent
indicating they are always hungry. Thirty-eight percent reported being hungry several times a week.
And 13 percent reported being hungry every day. Poverty and destitution was the top choice as the
priority the government should address, 15 percent, followed by food shortage, 9 percent, and farming
and agriculture, 8 percent. Agricultural development received the most votes regarding where the
government should invest funds if money was available. Healthcare was second, followed by education
and infrastructure.
The next task in the analysis was to cross-tabulate some of the study’s independent variables by hunger.
These results appear in Table 3.

www.scholink.org/ojs/index.php/fsns Food Science and Nutrition Studies Vol. 1, No. 1, 2017
18
Published by SCHOLINK INC.
Table 3. Cross-Tabulation Hunger and Selected Independent Variables (N = 1,200)
Hunger level
None
Some
a lot
Total
P
Variable
N (%)
N (%)
N (%)
Gender
Male
180 (30)
306 (51)
114 (19)
600
.01
Female
168 (28)
275 (46)
157 (26)
600
Education
No formal/informal only
90 (20)
219 (48)
147 (32)
456
.000
Some/Primary school completed
150 (28)
283 (52)
107 (20)
540
Some/completed high school
72 (46)
71 (45)
15 (9)
158
Postsecondary/college/graduation
36 (78)
8 (17)
2 (4)
46
Employment
Unemployed
288 (28)
504 (49)
246 (24)
1,038
.04
Employed part time
17 (45)
15 (39)
6 (16)
38
Employed full time
43 (35)
62 (50)
19 (15)
124
Residence
Urban
83 (49)
61 (36)
24 (14)
168
.000
Rural
265 (26)
520 (50)
247 (24)
1,032
Agricultural worker/occupation
Yes
191 (23)
397 (49)
230 (28)
518
.000
No
145 (41)
175 (49)
36 (10)
356
Asset-based Wealth
None of these
87 (21)
190 (47)
130 (32)
407
.000
Radio
124 (27)
229 (50)
105 (23)
458
Radio and TV
71 (29)
141 (59)
29 (12)
241
Radio, TV and motor vehicle
66 (71)
20 (22)
7 (9)
93
Age
18 through 29
118 (29)
196 (49)
88 (22)
402
.71
30 thru 49
134 (31)
203 (47)
97 (22)
434
50 and over
96 (26)
182 (50)
86 (24)
364
Government ensuring everyone has enough to eat
Badly
282 (29)
475 (49)
214 (22)
971
.65
Good
64 (30)
99 (46)
53 (24)
216
Table 3 shows that most of the variables included in Table 3 were statistically significant. The two

www.scholink.org/ojs/index.php/fsns Food Science and Nutrition Studies Vol. 1, No. 1, 2017
19
Published by SCHOLINK INC.
exceptions were age and respondent perceptions regarding whether the government was ensuring that
people had enough to eat. Some other variables included in Table 3 were highly significant. These
included education, residence, agricultural work as an occupation and the asset based wealth index. All
at p = .000. Gender at p = .01 and employment status, p = .04, were also significant, but to a lesser
degree.
The final task in the analysis was to conduct an ordered logistical regression analysis to determine
which variables predicted hunger in Burundi. 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) 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. Logistic Regression with Self-Reported Hunger as the Dependent Variable
Variable
Coefficient
Standard Error
Z
P
urban-rural
-.13
.21
.61
.54
Gender
.12
1.31
.19
Employment status
.06
.19
.59
.55
Total assets
-.29
.11
-2.63
.01
Education
-.42
.10
4.27
.00
Agriculture worker
.48
.15
3.11
.00
Age
-.10
.08
-1.28
.20
Government doing enough
.64
.28
2.27
.02
Invest agriculture
.04
.03
1.50
.13
Number of observations = 1,097
LR chi2(12) = 164.29
Prob > chi2 = 0.0000
Pseudo R2 = 0.07
Table 4 shows that 4 variables reached significance in the regression equation. In order of their strength,
these were education, agricultural worker as the respondent’s occupation, the asset based wealth
indicator, and whether respondents thought the government was ensuring that people had enough to eat.
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 significant
predictors of hunger. Perhaps this can be explained by the significance of agriculture as an occupation.
Another significant variable identified above and not included in the regression analysis was the basic
necessity indicator, and that was because the items multicollinearity with hunger.

www.scholink.org/ojs/index.php/fsns Food Science and Nutrition Studies Vol. 1, No. 1, 2017
20
Published by SCHOLINK INC.
4. Discussion
Another issue which disappeared in the regression analysis was the need to invest in agriculture, which
appears to be a major solution to the world food and hunger crisis found in the recent literature (Fan &
Rosegrant, 2016). The thinking is that increased agricultural growth will play a major role in addressing
the world food crisis and the major stumbling block will be the cost.
There are grass roots approaches to the hunger problem in Burundi noted in the literature and one will be
mentioned here. This may be defined as taking advantage of what already exists in the environment.
The example is provided by Akinnifesi et al. (2006), who noted that among the consequences of most
countries in Southern Africa experiencing acute malnutrition, food insecurity, and poverty among both
rural and urban populations is deforestation and loss of biodiversity. It has been recognized what are
known as the Miombo woodlands are in danger, an area which includes Southern Burundi. This forest
area is known to have over 75 Indigenous Fruit Trees (IFTs), which bear edible fruits. These fruits are
rich in minerals and vitamins, can be sold for cash income and are an important food source during
emergencies. Akinnifesi et al. provide an overview of some efforts to domesticate the IFTs identified by
farmers and users as priority species, which is as an important step to providing opportunities for
resource-poor farmers to cultivate and generate income from the sale of fresh and processed products.
The approach used involves four basic steps: 1) identification of priority species by communities and
other users, 2) participatory selection of superior trees and naming them in situ, 3) propogation and
cultivation of trees as fruit orchards, and 4) dissemination and adoption. To this point, over 5000
farmers in four countries are involved in on-farm testing of IFTs in the field and homesteads.
This example points to the need to create an enabling environment, and demonstrates that policy
reforms and market development will be necessary to achieve socioeconomic empowerment of the
resource poor farmers in the region through domestication, utilization and commercialization of fruits
and other agricultural commodities, which in turn stresses the need for product development research,
private sector involvement and strong policy support, in order for other similar projects to have tangible
impact.
As far as can be determined, this is the only published study that has assessed hunger in Burundi
through individual level survey methods, yet, the results presented here are consistent with other
assessments of hunger in Burundi. For example, the Borgenproject (2014) reported that the rates of
malnutrition have increased and Burundi is only one of four nations that has seen an increase in GHI
(Global Hunger Index) from 1990 to 2016, indicating a worsening of the food situation in the country.
The picture presented here and elsewhere suggest that the prospects for the future of hunger looks
dismal for Burundi. At first glance, the fact that education was the first predictor to emerge from the
regression analysis might seem favorable. In fact, Burundi has been identified as the African Country
least able to retain its top talent (Mail Guardian, 2015). This comes about because the pursuit of
opportunities outside the country is called a feature of working life, and Burundi was ranked number
one in terms of the country where the best and brightest leave for opportunities in other countries and at

www.scholink.org/ojs/index.php/fsns Food Science and Nutrition Studies Vol. 1, No. 1, 2017
21
Published by SCHOLINK INC.
the bottom of the list of African Countries able to attract top talent. The country cannot create more
farm land, and the remaining forest land must be and will be protected; the example provided by the
Miombo woodlands makes that case.
In conclusion, the answer to the question which generated this paper is that hunger will be or remain
perpetual in Burundi into the foreseeable future. Seventy-one percent of the respondents to this survey
reported some degree of hunger, 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 86 percent listed
some form of agriculture as their occupation. The surprising finding was that, while significant at the
bivariate level, gender was not significant in the regression analysis, suggesting that everyone is hungry
in Burundi, women and men, and this study suggests there is no apparent improvement on the horizon.
References
Adebayo, S. A., & Adekunle, O. A. (2016). Socio-economic status of women in group membership in
selected areas of Kwara State, Nigeria. Agrosearch, 16(1), 57-64.
https://doi.org/10.4314/agrosh.v16i1.5
Akinnifesi, F., Kwesiga, J., Mhango, T., Chilanga, A., Mkonda, C., & Kadzere, K. I. (2006). Towards
the development of miombo fruit trees as commercial tree crops in southern Africa. Forests, Trees
and Livelihoods, 16(1), 103-121. https://doi.org/10.1080/14728028.2006.9752548
Borgenproject. (2014). Malnutrition in Burundi. Retrieved from https://www.borgenproject.org
Bratton, M., Robert, B. M., & Emmanuel, G.-B. (2005). Public opinion, democracy, and market reform
in Africa. Cambridge University Press.
Clover, J. (2003). Food security in sub-Saharan Africa: Feature. African security review, 12(1), 5-15.
https://doi.org/10.1080/10246029.2003.9627566
Fan, S., & Rosegrant, M. (2016). Investing in agriculture to overcome the world food crisis and reduce
poverty and hunger. Washington, DC: IFPRI (International Food Policy Research Institute).
Retrieved from https://www.vtechworks.lib.vt.edu
Fauk, N., Mwakinyali, S., Sukma, P., & Mwanri, L. (2017). Understanding the strategies employed to
cope with increased numbers of AIDS-orphaned children in families in rural settings: A case of
Mbeya Rural District, Tanzania. Infectious Diseases of Poverty, 6(1).
https://doi.org/10.1186/s40249-016-0233-7
Fry, L. (2017). The Value of Publicly Available Data Sets for Social Science Research and Evaluation.
International Journal of Current Advanced Research, 6(1), 1777-1783.
Jeníček, V., & Grofová, S. (2015). Least developed countries-the case of Burundi. Agric. Econ.-Czech,
61, 234-247. https://doi.org/10.17221/48/2014-AGRICECON
Long, J., & Freese, J. (2006). Regression models for categorical dependent variables using Stata. Stata
press.
Mail guardian. (2015). Brain drain in Africa: Burundi least able to retain its top talent, Rwanda, Kenya

www.scholink.org/ojs/index.php/fsns Food Science and Nutrition Studies Vol. 1, No. 1, 2017
22
Published by SCHOLINK INC.
top Jammeh’s Gambia surprises. Retrieved from http:://www.mgafrica.com/article.2015-08-28
Mattes, R., & Gyimah-Boadi, E. (2005). Public Opinion, Democracy, and Market Reform in Africa.
Cambridge: Cambridge University Press.
Mattes, R., Bratton, M. & Davids, Y. (2003). Poverty, Survival, and Democracy in Southern Africa.
Afrobarometer Working Paper.
Muthayya, S., Jee, H., Sugimoto, J. Roos, F., Kraemer, H., & Black, R. (2013). The global hidden
hunger indices and maps: An advocacy tool for action. PLoS One, 8(6), e67860.
https://doi.org/10.1371/journal.pone.0067860
Notes, Hunger. (2011). World hunger and poverty facts and statistics. Washington, DC: World Hunger
Education Service.
Poor People and Democratic Citizenship in Africa. (2008). In A. Krishna (Ed.), Poverty, Participation
and Democracy. New York: Cambridge University.
Sanchez, P. A., & Swaminathan, M. S. (2005). Hunger in Africa: The link between unhealthy people
and unhealthy soils. The Lancet, 365(9457), 442. https://doi.org/10.1016/S0140-6736(05)70241-5
Shisanya, S., & Mafongoya, P. (2016). Adaptation to climate change and the impacts on household
food security among rural farmers in uMzinyathi District of Kwazulu-Natal, South Africa. Food
Security, 8(3), 597-608. https://doi.org/10.1007/s12571-016-0569-7
The material and political bases of lived poverty in Africa: Insights from the Afrobarometer. (2008). In
Barometers of Quality of Life Around the Globe (pp. 161-185). Springer Netherlands.
Tilman, D., & Clark. (2015). Food, Agriculture & the environment: Can we feed the world & save the
Earth? Daedalus, 144(4), 8-23. https://doi.org/10.1162/DAED_a_00350
World Health Rankings: Burundi. (2013). Retrieved from http://www.worldlife
expectancy.com/Burundi
Worldlifeexpectancy, Burundi. (n.d.). Retrieved from
http://www.worldlifeexpectancy.com/burundi-life-expectancy