Food-insecurity-and-health-behaviors-in-a-disaster-affec_2025_Human-Nutritio.pdf
Food insecurity and health behaviors in a disaster-affected population: A
case study of Tacloban, Philippines
Gashaw Enbiyale Kasse a, Abdo Megra Geda b,*
, Aregash Wendimu Tumebo c,
Elvis Akem Tambe d, Abraham Belete Temesgen e, Mulusew Tesfaye Yitie a,
Tadesse Mihiret Yimam a, Samuel Atalay Shiferaw f
a Department of Veterinary Clinical Medicine, College of Veterinary Medicine and Animal Sciences, University of Gondar, Gondar, Ethiopia
b The Donkey Sanctuary, College of Veterinary Medicine and Agriculture, Addis Ababa University, Bishoftu, Ethiopia
c Department of Veterinary Medicine, School of Veterinary Medicine and Animal Sciences, Wachemo University, Hossana, Ethiopia
d Epidemiologist at M´edecins Sans Fronti`eres Belgium, One Health Researcher, Belgium
e Department of Veterinary Pathobiology, College of Veterinary Medicine and Animal Sciences, University of Gondar, Gondar, Ethiopia
f Biology Department, Bahire Giorgis Secondary School, Motta, Ethiopia
A R T I C L E I N F O
Keywords:
Food insecurity
Health behaviors
Tacloban
Typhoon haiyan
Philippines
A B S T R A C T
Background: Food insecurity is a widespread issue that poses a major global challenge with far-reaching impacts.
Objective: Investigate the relationship between food insecurity and health behaviors among the population of
Tacloban, Philippines, affected by Typhoon Haiyan in 2013.
Methods: This study employed a cross-sectional design, surveying 226 households between April 2022 and June
2023. Households were selected using a systematic random sampling technique to ensure representative
coverage. To evaluate food insecurity, we utilized the Food Insecurity Experience Scale-a robust tool that cap
tures the degree to which individuals or households face challenges in accessing sufficient and nutritious food
due to economic and social constraints. In addition, we explored a variety of health-related behaviors among
participants, including the use of traditional healing practices, engagement in physical activity, sleep patterns
and duration, dietary habits, medication adherence, as well as alcohol and tobacco use. The relationships be
tween food insecurity and these health behaviors were rigorously examined using multiple logistic regression
analysis, providing valuable insights into the interplay between access to food and lifestyle choices within the
community.
Results: The results showed that 94 % of households experienced food insecurity, with 27 % severely, 52 %
moderately, and 15 % mildly food insecure. The analysis revealed significant associations between food inse
curity and several health behaviors. Food insecurity was found to be significantly associated with lower medi
cation adherence, greater use of traditional healers, poorer dietary habits, and sleeping problems. However, no
significant associations were found between food insecurity and smoking behavior, physical activities, or alcohol
consumption.
Conclusion: Based on these findings, the study concluded that food insecurity negatively impacts health behav
iors. Therefore, the authors suggested that improving food security in households could potentially lead to im
provements in health behaviors.
1. Introduction
Access to adequate food is a fundamental human need, recognized as
a basic right at the 1996 World Food Summit in Rome [1,2]. The Food
and Agriculture Organization (FAO) has made a significant commitment
to eradicating hunger by 2030, as outlined in Sustainable Development
Goal Target 2.1 [3]. This goal aims to eliminate hunger and ensure that
all individuals, particularly those who are poor or in vulnerable situa
tions, including infants, have year-round access to safe, nutritious, and
sufficient food [4].
Food insecurity is a pervasive problem across low-, middle-, and
high-income countries. It remains an important and relevant issue due to
* Corresponding author.
E-mail address: obsadufera@gmail.com (A.M. Geda).
Contents lists available at ScienceDirect
Human Nutrition & Metabolism
journal homepage: www.sciencedirect.com/journal/human-nutrition-and-metabolism
https://doi.org/10.1016/j.hnm.2025.200327
Received 1 April 2025; Received in revised form 27 May 2025; Accepted 2 June 2025
Human Nutrition & Metabolism 41 (2025) 200327
Available online 3 June 2025
2666-1497/© 2025 Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ).
Received 1 April 2025; Received in revised form 27 will 2025; Accepted 2 June 2025
its prevalence and its association with adverse health and nutrition
outcomes [5]. It remains an important and relevant issue due to its
prevalence and its association with adverse health and nutrition out
comes, such as increased risk of chronic diseases, poor mental health,
and higher rates of hospitalizations [6]. For example, in 2023, an esti
mated 2.33 billion people globally-almost 29 % of the world’s
population-experienced moderate or severe food insecurity, high
lighting the widespread and persistent nature of this challenge [7].
According to FAO, in 2018, 9.2 % of the global population, which means
over 700 million people experienced severe food insecurity, while 17.2
% (around 1.3 billion people) faced moderate food insecurity [8].
Africa exhibits the highest levels of total food insecurity (moderate or
severe) compared to any other region, affecting over half of its popu
lation [9]. Latin America has a food insecurity prevalence exceeding 30
%, Asia stands at 23 %, while Northern America and Europe have rates
around 8 % [10]. FAO’s data from 2014 to 2016, collected using the food
insecurity experience scale (FIES), revealed that 14.3 million adults in
the Europe and Central Asia (ECA) region experienced severe food
insecurity [11].
Drought and conflict are the primary factors exacerbating issues
related to food production, distribution, and access [12]. According to
FAO FAO’s 2018 global food security eport, new or intensified conflict
and insecurity in regions such as Myanmar, north-east Nigeria, the
Democratic Republic of Congo, South Sudan, and Yemen, along with
prolonged drought conditions in eastern and southern Africa, have
significantly increased the number of people facing acute food insecurity
[13]. Additionally, high rates of population growth and poverty, within
fragile ecosystems, contribute to the challenge. For those facing poverty
or food insecurity, maintaining good health, adhering to a nutritious
diet, managing chronic diseases, or a combination of these tasks can be
particularly difficult due to limited financial resources, competing pri
orities, and stress [14]. Gregory and Coleman-Jensen’s study high
lighted that, in some cases, food insecurity is a stronger predictor of
chronic illness than income, with food insecurity status being signifi
cantly associated with a greater number and range of chronic diseases
compared to income alone [15]. Exposures to health risks like food
insecurity can have a profound impact on health outcomes, and the
onset and progression of diseases in later life [16,17].
The Philippines, located in Southeast Asia, has a population of about
108 million [18]. The Philippines is highly susceptible to natural di
sasters, including typhoons, earthquakes, and volcanic eruptions, mak
ing it one of the most disaster-prone countries globally [19]. In the first
half of 2018, the estimated poverty prevalence among Filipino in
dividuals was 21.0 %, affecting approximately 22 million people [20,
21]. The prevalence of household poverty during the same period was
recorded at 16.1 %. These figures represent a slight decrease from the
rates reported in 2015, which were 27.6 % for poverty prevalence
among individuals and 22.2 % for household poverty.
On November 8, 2013, the Visayas region of the Philippines—home
to some of the country’s most impoverished provinces—was struck by a
powerful typhoon called Yolanda (internationally known as Haiyan)
[22]. According to the National Risk Reduction and Management
Council, the aftermath of Typhoon Haiyan resulted in the loss of 6300
lives, with 1062 individuals reported as missing and 28,688 sustaining
injuries [23]. The report also revealed extensive destruction of agricul
tural land and infrastructure, amounting to an estimated total damage
cost of approximately US$1890 million. Additionally, around 1.1
million houses were partially or completely damaged, and the overall
impact on people’s livelihoods, environment, and food security affected
roughly 16 million individuals [24]. Similarly, Atienza et al. [25]
documented that the typhoon had a significant impact on the livelihoods
of those living both above and below the poverty threshold, affecting
86.7 % and 92.4 %, respectively.
High poverty and low-income levels, particularly among agricultural
households, contribute to difficulties in obtaining sufficient food [26].
This underscores/highlights the relevance of examining how food
insecurity affects health behaviours in vulnerable communities. The
resulting food insecurity poses long-term health risks, including nega
tive health behaviors. While previous studies have shown a link between
food insecurity and adverse health outcomes, further research is needed
to explore this association in northern Tacloban city specifically.
Therefore, the objective of this study was to examine the association
between food insecurity and health behaviors in a population that was
affected by Typhoon Haiyan.
2. Study design and methods
2.1. Study design and sample
This cross-sectional study was conducted in Tacloban City,
Philippines, between April 2022 and June 2023. Due to logistical and
resource constraints, data collection activities were carried out on
selected days within this timeframe rather than continuously. Upon our
arrival, the research team was welcomed by the Department of Health
(DOH) and we held meetings with their administration. During these
meetings, we provided an overview of our study, and they shared in
formation about the general food insecurity and health situation in the
city. Based on these discussions, we determined the specific study site to
be in the northern part of Tacloban. Throughout the research, DOH
assigned their staff members, such as nurses, village captains, and
ambulance drivers, who worked in the villages, to accompany us during
interviews. Their presence facilitated our interactions with community
members to gather relevant information.
The population affected by the 2013 Typhoon Haiyan, who were
displaced, resides in northern Tacloban City. This area encompasses
eight villages, of which six were included in our study: Village 97, 101,
105, 106, 107, and Village 108. According to the City Health Office in
Tacloban City, there were an estimated 7545 households in these six
villages as of 2018. However, many accommodations often remained
empty because households frequently returned to their previous
disaster-prone sites to sustain their livelihoods. We used a purposive
sampling method to select the study sites. These villages were purpo
sively selected because they hosted a significant number of displaced
Typhoon Haiyan victims. In total, we sampled 226 households, deter
mining the sample size based on the duration of data collection and
recommendations for interview research.
We employed a systematic sampling technique at the household
level, using specific house numbers assigned by the city administration.
Samples were proportionately collected from each of the six villages.
The total number of households in each village was divided by the total
number of households in all six villages and then multiplied by the
sample size (n = 226). The head of the household or any other member
with well-informed about the household’s day-to-day activities served
as the respondent for our semi-structured interviews. In cases where the
head of the household was unavailable or unable to respond, another
adult member—typically the primary caregiver or a person responsible
for managing food and health matters—was selected to ensure accurate
and reliable responses. Alongside interviews, we also conducted direct
observations and walked through the communities with local residents
(a method known as participatory transect walks) to better understand
conditions related to farming, livestock, water access, sanitation, edu
cation, healthcare services, and overall community well-being.
To guide the interviews, we utilized an interview guideline consist
ing of four sections: demographic characteristics, food security, liveli
hood conditions and strategies, and health behaviours [27]. We
collaborated with the assigned nurses, explaining the study and the
interview guidelines to them. They are nurses, proficient in English and
the local language (Tagalog or Waray), assisted in translating the in
terviews and explaining the responses to us. We ensured the accuracy
and relevance of the responses to the questions asked.
G.E. Kasse et al.
Human Nutrition & Metabolism 41 (2025) 200327
2
2.2. Socio-economic and demographic variables
This study analyzed various socio-economic and demographic fac
tors, including age, gender, marital status, occupation, and household
size, respondent’s education, and household income. The education
level of the household was determined based on the highest level
attained by the household head, categorized as elementary, secondary,
higher education or Technical and Vocational Education and Training
(TVET) level. Household income was assessed by considering the num
ber of individuals with income and calculating the average daily
household income. In households without regular or non-salaried jobs,
income tended to be unstable, leading to periods without any income.
The study also examined the occupation of household members, cate
gorising them into employed (civil service, private sector, self-
employed) or unemployed.
2.3. Livelihood condition of the households
The livelihood conditions of the households were assessed to deter
mine their abilities to cope with challenges and the strategies they
employed for survival. Various factors were considered, including the
number of household members with income, sources of household in
come, social networks, social protection instruments, access to land for
farming, infrastructural problems, and sources of food. The sources of
household income were classified as “earnings,” “relatives,” and “own
production.” Social networks were categorized as “relatives,” “none,”
and “neighbors.” Social protection instruments were divided into
“microfinance,” “MCCT (Modified Conditional Cash Transfer) and CCT
(Conditional Cash Transfer)" (government support provided to certain
households with conditions), and “saving".
The study also investigated infrastructural problems, such as trans
portation, water, and electricity issues. Sources of food were classified as
“purchasing,” “own production,” and “relatives.” The question of access
to land required a simple “yes” or “no” response. In terms of health, the
study assessed whether the household head had a health condition that
that affected their ability to earn income or perform daily activities. This
referred to long-term health problems that affect productivity, and re
spondents were asked to answer with either “yes” or “no.” Additionally,
the study inquired about the presence of any health insurance (private or
public) within the household.
2.4. Food insecurity assessment
The severity of food insecurity status was assessed using the Food
Insecurity Experience Scale (FIES). The FIES is a scale that was devel
oped by FAO Voices of the Hungry project [26]. Food insecurity as
measured by FIES refers to limited access to food, at the level of in
dividuals or households, due to a lack of money or other resources [5]. It
is an experience-based metric of the severity of food insecurity that relies
on people’s direct responses to a series of questions concerning their
access to adequate food. FIES, an experienced-based scale, puts people’s
experiences and behavioral responses at the core of the definition of
what food insecurity means [26].
According to FAO [5], FIES has been proven to be effective in
measuring the food insecurity status of respondents with diverse cul
tural, linguistic, and development contexts. With the ease of processing
FIES data, the results are timely, providing picture of the food insecurity
situation. Another important aspect of FIES is that it enables the mea
surement of food insecurity. This data can then be analyzed together
with indicators of its determinants such as livelihoods. It can also be
examined alongside indicators of its consequences like health outcomes,
to contribute to a more comprehensive understanding and inform more
effective policies and interventions [26].
FIES is composed of eight questions that explore individual or
household experiences with regard to food. This principle follows the
sequence of events associated with food insecurity [28]. The lived
experience of food insecurity was characterized initially by anxiety,
associated with worry about being able to get enough food. As condi
tions worsened, it resulted in a decreased amount of stored food in the
home, followed by worsening quality and diversity of the diet, a
decreased quantity of food eaten per meal, and, finally, being forced to
skip meals and feel hungry for an extended period [29]. In this study, the
households’ experience of food was explored in the past twelve months.
The questions given to the households are described in Table 1, adapted
from FAO [30]. The responses are either “yes” or “no”. We asked further
questions to know the reasons for the lack of money or other resources to
get food.
The results of the FIES scale according to Ballard et al. [26] can be
presented as mild, moderate, or severe food insecurity. Table 2 shows
the severity of food insecurity classification.
2.5. Health behaviors
In this study, various health behaviors were assessed, including the
use of traditional healers, physical activities, sleep behavior, dietary
habits, medication adherence, alcohol consumption, smoking, drug use,
and risky sexual behavior. The use of traditional healers was examined
as a measure of health-seeking behavior when individuals lacked the
financial means to seek conventional medical treatment. The partici
pants were asked if they visited traditional healers for healthcare, and if
the response was affirmative, the reasons behind their choice were
further explored. To investigate physical activities, participants were
asked about their engagement in exercises such as running, jogging,
basketball, gym workouts, or walking, excluding excluding physical
activity related to occupational duties. If they answered positively, de
tails such as the type of exercise, frequency per week, and average
duration per session were obtained. The responses were categorized as
either “yes” or “no” during analysis. Sleep behavior was assessed by
inquiring about the average duration of sleep per night.
Participants were also asked if inadequate access to food (due to lack
of resources or money) affected their sleep quality, causing them to
Table 1
Food insecurity experience scale.
“Now I would like to ask you some questions about food consumption in your
household in the last 12 months. During the last 12 months, was there a time when:
Question
number
Standard
label
Question
1
Worried
During the last 12 months, was there a time when
you or any other member of your household was
worried that s/he would not have enough food to
eat because of a lack of money or other resources?
2
Healthy
Still thinking about the last 12 months, was there a
time when you or any other member of your
household was unable to eat healthy and nutritious
food because of a lack of money or other resources?
3
Few foods
Was there a time when you or any other member of
your household ate only a few kinds of foods
because of a lack of money or other resources?
4
Skipped
Was there a time when you or any other member of
your household had to skip a meal because there
was not enough money or other resources to get
food?
5
Ateless
Still thinking about the last 12 months, was there a
time when you or any other member of your
household ate less than s/he thought s/he should
because of a lack of money or other resources?
6
Ranout
Was there a time when your household ran out of
food because of a lack of money or other resources?
7
Hungry
Was there a time when you or any other member of
your household was hungry but did not eat because
there was not enough money or other resources for
food?
8
Whole day
During the last 12 months, was there a time when
you or any other member of your household went
without eating for a whole day because of a lack of
money or other resources?
G.E. Kasse et al.
Human Nutrition & Metabolism 41 (2025) 200327
3
worry about acquiring food and impacting their ability to rest well. For
alcohol consumption, participants were asked if they consumed alcohol,
and if so, further details were gathered regarding the frequency of
consumption (frequent or occasional, defined as at least two times per
week or at most once weekly, respectively). Dietary behavior was
evaluated by asking participants about the average number of major
meals consumed per day (breakfast, lunch, and dinner) in their house
hold. The responses were categorized as one time per day, two times per
day, or three times per day. Medication adherence was assessed by
asking participants if they or any member of their household sometimes
skipped taking medication. If affirmative, the reasons for skipping
medication, such as lack of food or resources to acquire food, were
explored. Cigarette smoking and drug use were examined by directly
asking participants if they engaged in these behaviors.
2.6. Statistical analysis
Statistical data analyses were performed by using MS Excel and R
Studio software. The variables were both qualitative and quantitative.
Qualitative variables included gender, education, marital status, occu
pation, food security status, activities before disaster, source of income,
source of food, social network, social protection instrument, general
health problem, health care coverage, physical activities, medication
adherence, use of traditional healers, smoking, sleeping behavior,
alcohol consumption, and dietary habit. The quantitative variable in
cludes age, household size, household income per day, and the number
of households members (s) with income. After categorising qualitative
data, the description of the demographic, socio-economic characteris
tics, livelihood condition, and health behaviours was performed ac
cording to food security status. Descriptive analyses were used to
examine the distribution of key variables. A pairwise chi-square test was
used to examine the associations of household food insecurity with de
mographic and socio-economic characteristics. Multiple logistic re
gressions were performed to examine the association between food
insecurity and health behaviors. The factors that were significant at an
alpha level of 0.1 or less during univariate logistic regression were
included in the multivariate logistic regression model. The result of
multivariate logistic regression was presented as an odds ratio with a 95
% confidence interval. A p-value <0.05 was considered a level of sta
tistical significance.
3. Results
3.1. Socio-economics and demographic characteristics
The results of the study revealed that a total of 226 households were
successfully interviewed. Among the respondents, 144 (63.7 %) were
females, and 82 (36.3 %) were males. The median age of the respondents
was 39 years, ranging from 18 to 76 years. In terms of marital status, the
majority of households (54.4 %) were married, followed by those who
were cohabitating (29.2 %), separated (2.2 %), single parents (7.5 %),
and widowed (6.6 %). The mean household size was 5, with a range of
1–14 members.
Regarding income generation, 72.5 % of households relied on a
single member to generate income. The median daily household income
was 300 pesos (approximately 5.3 euros), ranging from 0 to 1450 pesos
(approximately 25 euros). The occupations of the households were
primarily self-employment (80.4 %), followed by civil servants (8.2 %)
and those in the private sector (6 %). A small percentage (4.9 %) of
households did not engage in income-generating activities and received
support from relatives.
The educational levels of the household heads varied, with 24.9 %
having completed primary education, 25.1 % having completed sec
ondary education, 24.6 % having completing TVET, and 24.7 % having
attained higher education. In addition, Table 3 provides a detailed
breakdown of the distribution of occupations according to educational
levels.
The study found significant variations in the occupation of house
holds before and after Typhoon Haiyan. Before the typhoon, the ma
jority of households were engaged in agricultural production, indicating
a high level of self-employment. These agricultural activities primarily
involved fishing, coconut cultivation, and rice production. This suggests
that agriculture played a vital role in the livelihoods of these households.
However, the devastating impact of Typhoon Haiyan led to the wide
spread destruction of agricultural infrastructure and crops. As a conse
quence, many households were forced to modify their occupations and
seek alternative income-generating activities. The aftermath of the
typhoon resulted in a significant shift in the types of jobs and livelihood
strategies pursued by these households.
Fig. 1 provides a visual representation of the comparison between
income-generating activities before and after Typhoon Haiyan. This
comparison highlights the changes that occurred in the livelihoods of
the affected households. The figure likely illustrates a decrease in agri
cultural activities and an increase in other forms of employment or in
come sources, as households sought to recover from the impact of the
typhoon. The transformation of livelihood strategies in response to the
typhoon underscores the resilience and adaptability of the affected
households. It also indicates the challenges they faced in rebuilding their
lives and finding alternative means of income generation after the loss of
their agricultural activities.
3.2. Livelihood condition
The study identified a range of major activities and sources of income
for the households in the studied population. These activities encom
passed various sectors and occupations. The most prevalent occupations
included driving, which involved operating different types of vehicles
such as bikes, multicabs, and jeepneys. Construction-related work, such
as laborers and carpentry, was also a significant source of income for
some households. Fishing and being a fish vendor were important oc
cupations, highlighting the significance of the local aquatic resources for
livelihoods in the community. Additionally, store ownership emerged as
another common occupation, indicating the presence of small businesses
within the community.
Fig. 2 provides a visual representation of the percentage distribution
of occupations within the studied population. It showcases the diversity
of occupations and the varying levels of involvement in each category. It
is important to note that while some occupations had a higher per
centage of households involved, others had lower representation.
Among the less common occupations were security guards, glass
Table 2
Severity of food insecurity classification.
FIES
Questions
Domains of the food insecurity
construct
Assumed severity of food
insecurity
1, 2, and 3
Uncertainty and Worry about food/
Inadequate food quality
Mild
4, 5, and 6
Insufficient food quantity
Moderate
7 and 8
Insufficient food quantity
Severe (Hunger)
Table 3
Distribution of occupation with the educational level of household heads, n =
226.
Educational
level
Civil
servant
(%)
Occupation
(%)
Private-sector
workers (%)
Self-
employment
(%)
Higher
education
4.4
1.8
2.6
15.9
TVET
0.8
0.8
1.8
21.2
Secondary
2.2
1.3
0.8
20.8
Elementary
0.8
0.8
0.8
22.5
G.E. Kasse et al.
Human Nutrition & Metabolism 41 (2025) 200327
4
installers, painters, laundry workers, rice mill workers, technicians,
peddlers, police officers, seamstresses, waste plastic sellers, woodcut
ters, wood sellers, cooks, waiters, hairdressers, cashiers, and coconut
vendors. These occupations represent a wide range of skills and services
provided by members of the community.
Among the households included in the study, a significant
Fig. 1. Comparison of some income-generating activities before and after Typhoon Haiyan.
Fig. 2. Illustrates the percentage distribution of occupations within the studied population of 226 households. The ‘‘others’’ category represents occupations in
which only one household is involved.
G.E. Kasse et al.
Human Nutrition & Metabolism 41 (2025) 200327
5
proportion, 54.2 % (123 households), relied on social protection in
struments such as MCCT or CCT. These instruments provide financial
support and assistance to vulnerable households. However, the number
of households with microfinance support was relatively low, accounting
for only 4.87 % (11 households). Similarly, only a negligible percentage,
1.33 % (3 households), reported having savings as a social protection
mechanism. The presence of pension funds within households was also
quite limited, with only 0.89 % (2 households) indicating such financial
support.
Regarding social networks, the majority of households, 186 (83.6 %)
reported having some form of social network. These networks were
primarily comprised of relatives, emphasising the importance of familial
connections in the community. Other sources of social networks
included workplaces and neighbors. Notably, none of the households
were affiliated with community groups or meetings, suggesting a po
tential area for community engagement and collaboration.
3.3. Food insecurity status
The analysis of food insecurity is described using the Food Insecurity
Experience Scale (FIES). According to this analysis, a significant ma
jority of the households in the study, 93.8 % (212 households), experi
enced food insecurity, while only a small proportion, 6.2 % (14
households), were classified as food secure. In addition, further exami
nation of the food insecurity status showed that 27 % (61 households)
were severely food insecure, 51.8 % (118 households) were moderately
food insecure, and 15 % (33 households) were mildly food insecure
(Fig. 3). This breakdown provides insights into the varying degrees of
food insecurity experienced by the households.
Among the reasons cited for the inability to acquire food, financial
constraints emerged as the primary factor, with almost all households,
92 % (208 households), attributing their food insecurity to this issue.
Additionally, all households identified water as a significant infra
structural problem they faced. Other infrastructural issues that were
mentioned to a lesser extent included electricity, transportation, and
accessibility to main markets. These findings highlight the multifaceted
nature of food insecurity, where financial limitations and inadequate
infrastructure play crucial roles in the households’ access to food.
3.4. Food insecurity, livelihoods, and health behaviors association
The associations between food security status and education, occu
pation, and sources of food were examined, and the results are presented
in Table 4. The statistical analysis revealed significant associations be
tween these variables and food security status. Education (p = 0.0053),
occupation (p = 0.0014), and sources of food (p < 0.001) all demon
strated significant relationships with food security status. Among the
respondents who had no occupation, 45.4 % of their households expe
rienced severe food insecurity. On the other hand, among self-employed
respondents, 47 (26 %) households experienced severe food insecurity,
102 (56 %) households experienced moderate food insecurity, and 22
(12.1 %) households experienced mild food insecurity.
In terms of food sources, 68.1 % of food-insecure households relied
solely on purchasing food. However, 29.6 % of food-insecure households
obtained their food through a combination of purchasing and own
production. A small percentage, 2.2 %, relied on purchasing and other
relatives’ gifts for their food. Additionally, it was found that 52.4 % of
food-insecure households had social protection instruments such as
MCCT, CCT, microfinance, social pension funds, or savings. This sug
gests that these households had some form of support system in place to
mitigate food insecurity. Furthermore, 73.4 % of food-insecure house
holds had health care coverage, primarily through the Philippine Health
Insurance Corporation.
Among the studied households, 26.5 % (60) of the respondents re
ported health problems that affected their productivity. Surprisingly,
despite the high percentage of households with health problems, there
was no significant association between health problems and food inse
curity status (p = 0.932). This suggests that while health issues may
impact productivity, they do not directly influence food security status
in this population. However, the analysis revealed a significant associ
ation between food security status and dietary habits of the households
(p < 0.001), as shown in Table 5. The dietary habits were categorized
into two groups: twice daily food intake and thrice daily food intake.
Among the food-insecure households, 42.0 % (89) reported a dietary
habit of consuming food twice daily, while the remaining 58.0 % (123)
reported a dietary habit of consuming food thrice daily. The odds ratios
(OR) of severe food insecurity and moderate food insecurity are pre
sented in Table 5. The odds ratio for severe food insecurity was 0.087
(95 % CL: 0.026–0.24), indicating a significantly lower likelihood of
severe food insecurity among households with a thrice daily food intake
compared to those with a twice daily food intake. Similarly, the odds
ratio for moderate food insecurity was 0.31 (95 % CL: 0.10–0.80),
indicating a lower likelihood of moderate food insecurity among
households with a thrice daily food intake. Regarding alcohol con
sumption, the majority of the respondents (81.4 %) consumed alcohol
occasionally, while a smaller percentage (16.4 %) did not consume
Fig. 3. Proportion of food insecurity status in the sampled households, n = 226.
G.E. Kasse et al.
Human Nutrition & Metabolism 41 (2025) 200327
6
Experience Scale (FIES). According to this analysis, a negligible ma-
alcohol, and only 2.2 % consumed alcohol frequently. However, the
analysis did not find a significant association between alcohol con
sumption and food insecurity. Sleeping problems were also significantly
associated with food insecurity (p = 0.002). The average duration of
sleep at night among the households was 7 h, with a standard deviation
of 1.4.
Among the 212 food-insecure households, 136 (64.1 %) respondents
reported non-adherence to medication, with a significant association (p
< 0.001). Regarding smoking, 131 (61.8 %) respondents were non-
smokers, and 81 (38.2 %) were smokers. However, there was no sig
nificant association between smoking and food security status (p =
0.132). In terms of physical activities, the majority of respondents (74.0
%) did not engage in physical activities beyond their normal jobs.
However, the analysis did not find a significant association between
physical activities and food insecurity status (p = 0.1032). A significant
association was observed between household food insecurity and the use
of traditional healers (p < 0.001).
The analysis revealed several associations between health-related
factors and food security status among the households. Medication
adherence was found to be significantly associated with food security
status (p < 0.001). The odds ratio for severe food insecurity households
(OR = 7.36, 95 % CL: 2.7–22.2) who had non-adherence to medication
was significantly higher compared to moderate food insecurity house
holds (OR = 1.33, 95 % CL: 0.52–3.74). As given details in Table 6, the
binomial logistic analysis showed a higher odds ratio for severe food
insecurity (OR = 10.44, 95 % CL: 3.98–30.6) and moderate food inse
curity (OR = 2.05, 95 % CL: 0.86–5.5) among households that used
traditional healers.
Table 4
Association of education, occupation, and food source with food security status.
Variables
Total (%)
Food security status
Food secure (%)
Food-insecure (%)
Mild
Moderate
Severe
p-value
Education
0.0053
Higher education
56 (24.8)
8 (14.3)
14 (25)
26 (46.4)
8 (14.3)
TVET
56 (24.8)
5 (8.9)
2 (3.6)
38 (67.8)
11 (19.6)
Elementary school
57 (25.2)
0 (0.0)
8 (14)
23 (40.4)
26 (45.6)
Secondary school
57 (25.2)
1 (1.7)
9 (15.6)
31 (54.4)
16 (28)
Occupation
0.0014
Civil servant
19 (8.4)
1 (5.3)
4 (21)
7 (36.8)
7 (36.8)
Private sector
14 (6.2)
1 (7)
2 (14.3)
6 (42.8)
5 (35.7)
Self-employment
182 (80.5)
10 (5.5)
22 (12.1)
102 (56)
47 (26.0)
No occupation
11 (4.9)
2 (18.2)
5 (45.4)
3 (27.7)
5 (45.4)
Food source
0.00017
Purchase and own production
67 (29.6)
7 (10.4)
11 (16.4)
28 (41.8)
21 (31.3)
Purchase
154 (68.1)
6 (3.9)
22 (14.3)
88 (57.1)
38 (24.7)
Purchase and relatives
5 (2.2)
1 (20)
0 (0.0)
2 (40)
2 (40)
Table 5
Association of food insecurity and health behaviours.
Health behavior
Total (%)
Food security status
Food secure (%)
Food insecure (%)
Mild
Moderate
Severe
p-value
Sleeping problem
0.002
No
208 (92.0)
14 (6.2)
29 (12.8)
115 (50.9)
50 (22.1)
Yes
18 (8.0)
0 (0.0)
4 (1.8)
3 (1.3)
11 (4.9)
Alcohol consumption
0.251
Frequently
5 (2.2)
0 (0.0)
1 (20.0)
1 (20.0)
3 (60.0)
No
37 (16.4)
1 (2.7)
9 (24.3)
17 (45.9)
10 (27.0)
Occasional
184 (81.4)
13 (7)
23 (12.5)
100 (54.3)
48 (26.1)
Dietary habit
<0.001
2/day
92 (40.7)
3 (3.3)
5 (5.4)
43 (46.7)
41 (44.6)
3/day
134 (59.3)
11 (8.2)
28 (20.9)
75 (56)
20 (14.9)
Medication adherence problem
<0.001
No
149 (66)
13 (8.7)
26 (17.4)
89 (59.7)
21 (14.9)
Yes
77 (34)
1 (1.3)
7 (9.1)
29 (37.6)
40 (51.9)
Smoking status
0.132
No
140 (62)
9 (6.4)
22 (15.7)
76 (54.3)
33 (23.6)
Yes
86 (38)
5 (5.8)
11 (12.8)
40 (46.5)
30 (34.9)
Physical activities
0.1032
No
167 (73.9)
7 (4.2)
27 (16.2)
85 (50.9)
48 (28.7)
Yes
59 (26.1)
7 (11.8)
6 (10.2)
33 (55.9)
13 (22.0)
Use of traditional healers
<0.001
No
126 (55.7)
8 (6.3)
26 (20.6)
76 (60.3)
16 (12.7)
Yes
100 (44.2)
6 (6.0)
7 (7.0)
42 (42.0)
45 (45.0)
*The Chi-square test was used to check the association between food insecurity and sleep problems, dietary habits, physical activities, alcohol consumption, and
smoking.
G.E. Kasse et al.
Human Nutrition & Metabolism 41 (2025) 200327
7
3.5. Results of transect walk and direct observation participatory
approaches
The transect walking and direct observation participatory ap
proaches utilized in this study involved direct observation and interac
tion with the people of the communities. Researchers, along with health
workers and village captains, walked through the villages to gain in
sights into the living conditions and way of life of the residents. Based on
these observations, it was noted that the shelters in the resettlement sites
had a similar structure and were constructed using solid rods and con
crete materials. Each household was allocated one room, which typically
measured around 20 square meters and included an internal bathroom.
Depending on the financial status of the household, they might partition
the room into different sections, such as a living area and a bedroom.
The interviews revealed that some respondents became emotional and
shed tears, likely due to the food insecurity issues they were facing.
The resettlement sites were located in confined areas with limited
access to markets. However, basic public services, such as schools and
health centers, were available in the camps. Schools were easily acces
sible, and new structures were being built in other camps, indicating
efforts to improve educational facilities. The health centers operated
daily throughout the week and sometimes provided services directly to
households. However, there were challenges with the water supply, and
people had to queue for hours to fetch water. In some areas, boreholes
were present, requiring physical effort to pump water. It was also
observed that there were limited or no farmlands available for agricul
ture in the villages.
On a positive note, common playgrounds were present in the com
munities, providing spaces for recreational activities. Among the youth,
basketball, and volleyball were the most popular games, fostering
community engagement and bringing them together. Overall, the tran
sect walking and direct observation participatory approaches provided
valuable firsthand information about the physical environment, living
conditions, access to services, and recreational activities in the com
munities. These observations help to paint a comprehensive picture of
the challenges and opportunities faced by the population under study.
4. Discussion
The purpose of this study was to examine how food insecurity is
related to health behaviors in a disaster-affected population. As indi
cated in the results, the proportion of food insecurity is higher than those
of previous studies. This can be explained by the fact that the study was
done in a relocation site in which all of the households lost their prop
erties during the 2013 Typhoon Haiyan. In 2011, an estimated 71 % of
households in Eastern Visayas (regional level) were classified as food
insecure according to a national survey based on Radimer-Cornell food
insecurity items; this was before the disaster [31].
As shown in the analysis of the present study, the type of occupation
of the household affected the food security status. Those with non-salary
jobs reported that they sometimes go for days without income. An
example of such a non-salary job was construction. If there are no
construction opportunities, these workers will have to stay without in
come. This will therefore affect the food security of the households. This
finding aligns with previous research in various settings. For example, a
study by Ref. [32] in rural Ethiopia demonstrated that households
relying on daily wage labor were more likely to experience food inse
curity compared to those with stable, salaried employment. In the
Philippines, a report by the Food and Nutrition Research Institute (FNRI,
2020) also highlighted that families dependent on seasonal or informal
work were at greater risk of food insecurity, especially during periods of
economic downturn or natural disasters [33]. The high level of
self-employment, 80.5 % showed that most of the households rely on
non-salary income. This was in line with the study of Atienza et al. [25],
which stated that livelihood schemes and entrepreneurial training are
extremely important for poor households to have a high level of
non-salary income.
Our findings highlighted the respondents’ insights into social pro
tection measures, social networks, and sources of food available to their
households. The reliance on social protection instruments such as the
Modified Conditional Cash Transfer (MCCT) or Conditional Cash
Transfer (CCT) programs underscores the critical role of external sup
port in addressing economic vulnerabilities and mitigating food inse
curity. This observation is consistent with studies from other contexts,
which have demonstrated the positive impact of social protection pro
grams on household food security. For example, in a multi-country
analysis, Study found that cash transfer programs significantly
improved food security and dietary diversity among beneficiary
households [34]. Similarly, in the Philippines, the Pantawid Pamilyang
Pilipino Program (4Ps), a national CCT initiative, has been shown to
reduce hunger and improve nutritional outcomes among children in
recipient families [35]. The reliance on purchasing food suggests po
tential challenges in achieving food self-sufficiency, although some
households engage in their own production through backyard gardens.
Limited access to agricultural land may further impede the expansion of
food production. Understanding the dynamics of social protection, so
cial networks, and food sources provides valuable insights for policy
makers, organizations, and community leaders in designing targeted
interventions and support systems to enhance the livelihoods and
well-being of the households in the studied population.
Our study showed that the major source of households’ income
before Typhoon Haiyan was self-employment. Households were
involved in fishing, coconut and rice farming, fish vending, and other
labor work. ACAPS [36] stated that an estimated 74 % of fishing com
munities reported that their main income sources were severely affected
by the typhoon. Agriculture, a primary source of livelihood declined by
23 %, followed by poultry and livestock, as well as fishing which fell by
18 % and 26 % respectively. Because there were fewer livelihood op
tions in the relocation sites, some households prefer to stay in their
original
coastal
habitats
where
they
can
easily
carry
out
income-generating activities like fishing. These findings corroborate
those of Atienza et al. [25], who found that although the original coastal
habitats have been designated by the government as “no-build zones”,
Table 6
Unadjusted and adjusted odd ratio of food security status in terms of negative
health behaviors.
Variables
Non-adjusted odd ratio (95 %
confidence interval)
Adjusted odd ratio (95 %
confidence interval)
Poor dietary habits
Mild food
insecure
Ref.
Ref.
Moderate food
insecure
0.29 (0.086–0.82)a
0.31 (0.10–0.80)a
Severe food
insecure
0.082 (0.022–0.24)a
0.087 (0.026–0.24)a
Food secure
0.65 (0.13–3.6)
0.67 (0.13–3.6)
Non-medication adherence
Mild food
insecure
Ref.
Ref.
Moderate food
insecure
1.21 (0.49–3.28)a
1.33 (0.52–3.74)a
Severe food
insecure
7.07 (2.75–20.23)a
7.36 (2.7–22.2)a
Food secure
0.28 (0.14–1.85)
0.39 (0.02–2.7)
Use of traditional healers
Mild food
insecure
Ref.
Ref.
Moderate food
insecure
1.88 (0.75–5.21)a
2.05 (0.86–5.5)a
Severe food
insecure
8.72 (3.21–26.3)a
10.44 (3.98–30.6)a
Food secure
3.2 (0.78–13.3)
2.78 (0.72–11.02)
a Significance difference from the reference (p < 0.05). Note: Adjusted for
household education, occupation, and household size.
G.E. Kasse et al.
Human Nutrition & Metabolism 41 (2025) 200327
8
some households had no choice but to remain in these areas to access
their livelihood activities.
The relocation sites also face the problem of water and trans
portation. Water remains a major infrastructural problem in these
resettlement areas as reported by all the households. Some households
also reported electricity to be another infrastructural issue in the
resettlement sites. The high prevalence of food insecurity underscores
the urgent need for interventions and support mechanisms to address the
financial constraints faced by these households. Efforts should also be
directed towards improving infrastructural facilities, particularly in
relation to water availability, electricity, transportation, and market
access, to alleviate the challenges faced by the households. By
addressing these underlying factors, it is possible to enhance the food
security and overall well-being of the households in the study
population.
Understanding the distribution of occupations within the studied
population offers insights into the local economy, employment oppor
tunities, and the diversity of skills present in the community. It also
sheds light on the potential sources of income and the occupations that
contribute significantly to the households’ livelihoods. Such information
can be valuable for policymakers, researchers, and organizations
seeking to support and improve the economic well-being of the com
munity. The study of Atienza et al. [25] in Eastern Vasayas showed that
the practice of helping one another is an important social interaction of
the people in the villages. This is not different from our findings, where
83.62 % of the households receive help mostly from relatives, and
sometimes neighbors and workplaces. This is a form of social cohesion.
The presence of social protection instruments and health care
coverage indicates potential avenues for addressing food insecurity and
improving the overall well-being of these households. Efforts to enhance
education opportunities, promote stable and diverse employment,
expand social protection programs, and improve access to affordable
and nutritious food are crucial in addressing the underlying factors
contributing to food insecurity in this population. Moreover, frequent
skipping of breakfast can result in nutritional imbalance, and people
who skip breakfast also have more unhealthy habits such as smoking,
drinking alcohol, and exercising less [37,38]. For these reasons, it would
be reasonable to select regular breakfast intake as an important
parameter of healthy habits. Other studies also had similar findings in
which the food security status of the household had an association with
health behaviors [39,40]. Household dietary habits, such as the fre
quency of meals, play a significant role in determining the level of food
insecurity experienced. However, health problems and alcohol con
sumption were not identified as direct factors influencing food insecu
rity in this study. Further research and analysis may be needed to
explore the complex relationship between health, alcohol consumption,
and food security in this population.
As shown in the results, food insecurity was associated with dietary
habits. Some households generally take two to three major meals per
day. However, the quality and the quantity of the meals were not taken
into consideration when assessing this dietary habit. Some households
went whole days without meals. The emotional stress triggered by food
insecurity may negatively affect individuals’ eating habits [41,42].
These findings highlight the interplay between socioeconomic factors,
access to resources, and food security status. Education, occupation, and
sources of food all play significant roles in determining the food security
status of households.
According to Willows et al. [39] rates of non-smoking, participation
in physical activities, and regular breakfast intake declined in
food-insecure individuals. The rate of non-smoking, in particular,
significantly declined in food-insecure respondents, and meal patterns,
perceptions of healthy eating, physical activity, and mental health, were
related to food insecurity [40,43]. However, the present study showed
that smoking has no significant association with food insecurity. Poorer
families, and especially women, are engaging in negative coping stra
tegies and limiting food intake. If these strategies continue for an
extended period, they may negatively affect the health and physical
well-being of the affected population [44].
Our study demonstrated the link between food insecurity and the use
of traditional healers. Households find a compromise between visiting a
medical center and use of traditional healers with scarce resources to get
food. According to Nonhlanhla et al. [45], the main reason for the use of
traditional healers was the perception of the effectiveness of treatment,
proximity, and low economic status (relating to food security status).
Other factors may influence this decision, such as education, rural or
urban. The study of Bishwajita and Yaya in Bangladesh also showed that
severe food insecurity was significantly associated with the under and
non-utilisation of maternal health services [46]. This supports our
findings on the use of traditional healers.
This study also demonstrated that there was no significant associa
tion between food insecurity and lack of physical exercise, alcohol
consumption, and smoking. However, other studies showed that alcohol
consumption and moderate-vigorous physical activities were related to
food insecurity [47]. Engaging in regular physical activity is indicative
of good self-care, as it is known to increase fitness, prevent obesity,
reduce prevalence rates of chronic diseases, and boost mental health
[48]. Furthermore, we assessed the association between household food
insecurity sleep duration, and sleep complaints. The data analysis
showed that food insecurity had an association with sleep complaints,
however, no significant relation was observed with sleep duration. Food
insecure respondents worried about food and they became stressed and
they did not sleep well. This result is supported by the findings of Ding
et al. [49] which reported that food insecurity participants were more
likely to report sleep complaints than food security participants and poor
sleep quantity and quality may predispose food insecure adults to
adverse health outcomes. Because of longer working hours, more shift
work, and the 24/7 availability of food and recreational activities, the
average number of hours of sleep has declined over the past century
[50]. Buysse et al. [51] suggested that complaints about sleep quality
had become common and that a considerable proportion of adult’s
experience sleep quality disturbances, such as difficulty initiating sleep.
Researchers found that more frequent sleep complaints and short sleep
duration were linked to low income [52]. Higher-income households or
individuals had better sleep quality, shorter sleep latency, and greater
sleep efficiency [53].
In this study, because of a lack of food in the households, members of
the households do not adhere to prescribed medications. In moderate
and severe food insecure households, they sometimes did not have food
to eat and may abandon their medications during that time. According
to the findings of Silverman et al. [54], food insecurity had an associa
tion with medication adherence and this study also explained that
low-income patients had lower medication adherence than high-income
patients. Food-insecure households are less likely to have correct
medication adherence and are more likely to forgo needed medical care
due to cost compared to food-secure households [55]. For example, se
vere food insecurity has been shown to dramatically increase the like
lihood of missed medication doses, with odds ratios indicating a strong
and consistent association across various populations and health con
ditions [56]. People with food insecurity have limited control over what
they eat; this sense of powerlessness leads to distress and affects their
medication adherence, for instance, HIV and diabetes patients [57].
Non-adherence to medication has been shown to be linked to poor
health outcomes in conditions such as HIV/AIDS, tuberculosis, and other
chronic diseases [58–60]. Poor health reduces productivity and this
further worsens food insecurity. Individuals with food insecurity report
taking medication less often than prescribed due to costs and deferring
paying for the medication in order to have money for food [61,62]. In
the face of limited resources, demands for food may compete with re
sources needed to procure medicines. Even when clinic consultations are
“free,” clinical care is not without costs as patients have to incur costs in
other ways such as travelling to distant clinics or waiting in long lines for
care, purchasing food.
G.E. Kasse et al.
Human Nutrition & Metabolism 41 (2025) 200327
9
Understanding changes in occupation and income sources is vital for
assessing the long-term impact of the typhoon on community stability
and well-being. This study highlights the link between food insecurity,
negative health behaviors, and financial constraints, underscoring the
need for targeted interventions. Expanding cash transfer programs like
MCCT and 4Ps, providing food assistance, and implementing
community-based nutrition education can help address these challenges.
Additionally, promoting backyard gardening and livelihood training can
improve self-sufficiency. These strategies are essential for enhancing
food security and resilience in disaster-affected communities.
5. Limitation
This study has several limitations that should be considered when
interpreting the findings. First, its cross-sectional design restricts the
ability to establish causal relationships between food insecurity, health
behaviors, and socio-economic factors. The purposive selection of six
villages in northern Tacloban City, which primarily included pop
ulations displaced by Typhoon Haiyan, may limit the generalizability of
the results to other regions or non-displaced populations. If a larger or
more diverse sample had been included, it is possible that the results
would have captured a broader range of experiences and potentially
revealed different patterns of food insecurity and health behaviors
across various socio-economic or geographic contexts. Additionally, the
use of systematic sampling based on house numbers could have intro
duced selection bias, particularly given the frequent movement of
households between villages and disaster-prone areas. Data collection
relied heavily on self-reported information through interviews, which
may be subject to recall bias and social desirability bias. The study
assessed experiences over the past twelve months, which may not cap
ture seasonal variations or longer-term trends in food insecurity and
health behaviors. In our analysis, a certain potential confounding vari
ables, such as mental health status and detailed socio-economic in
dicators, were not included in the regression model, which may have
introduced bias and affected the observed associations between the
main variables of interest and the outcomeLastly, while efforts were
made to adjust for potential confounders in the statistical analysis, un
measured variables such as mental health status or access to external
social support may have influenced the results.
6. Conclusion and recommendation
The study highlights the prevalence of household food insecurity in
the study area, primarily caused by financial constraints and worsened
by the impact of Typhoon Haiyan. The research reveals a negative
relationship between food insecurity and various health factors,
including dietary habits, medication adherence, sleeping problems, and
the use of traditional healers. It emphasizes the need to address food
insecurity as a determinant of overall health and well-being, not just
from a nutritional standpoint. The study suggests implementing a
monitoring and evaluation system to assess the effectiveness of existing
policies and interventions, with a focus on education to improve
knowledge and empower households to make healthier choices. Further
research is recommended to explore the links between food insecurity
and other risky behaviors. Overall, addressing food insecurity requires
comprehensive approaches to improve health behaviors and outcomes
in the study area. Future studies should consider employing larger and
more diverse samples across multiple locations to strengthen the
external validity and broader applicability of the results.
CRediT authorship contribution statement
Gashaw Enbiyale Kasse: Writing – review & editing, Visualization,
Validation, Investigation, Formal analysis, Data curation. Abdo Megra
Geda: Writing – review & editing, Visualization, Validation, Investiga
tion, Formal analysis, Data curation. Aregash Wendimu Tumebo:
Writing – review & editing, Visualization, Validation, Investigation,
Formal analysis, Data curation. Elvis Akem Tambe: Writing – original
draft, Methodology, Conceptualization. Abraham Belete Temesgen:
Writing – review & editing, Visualization, Validation, Investigation,
Formal analysis, Data curation. Mulusew Tesfaye Yitie: Writing – re
view & editing, Visualization, Validation, Investigation, Formal anal
ysis, Data curation. Tadesse Mihiret Yimam: Writing – original draft,
Visualization, Validation, Investigation, Formal analysis, Data curation.
Samuel Atalay Shiferaw: Writing – review & editing, Visualization,
Validation, Investigation, Formal analysis, Data curation.
Availability of the data and material
The data used to support the findings of this study have been
included in the body. Further inquiries can be directed to the corre
sponding author.
Consent for publication
Not applicable.
Ethical approval
This study has received approval from the Institutional Review Board
Committee of the University of Gondar (UoG), College of Veterinary
Medicine and Animal Sciences (CVMAS) (Ref. No CVMAS/05/2022),
following a review for ethical standards and confirmation of its moral
integrity.
Funding sources
This research did not receive any specific grant from funding
agencies in the public, commercial, or not-for-profit sectors.
Declaration of competing interest
The authors declare that they have no known competing financial
interests or personal relationships that could have appeared to influence
the work reported in this paper.
Acknowledgment
The author would like to acknowledge the University of Gondar,
College of Veterinary Medicine and Animal Sciences, for providing a
conducive working environment and free internet access to conduct this
research.
References
[1] Food and Agricultural Organization of the United Nations, Report of the world food
Summit, 13-17 November 1996, http://www.fao.org/3/w3548e/w3548e00.htm,
1996. (Accessed 17 December 2018).
[2] E.M. Berry, S. Dernini, B. Burlingame, A. Meybeck, P. Conforti, Food security and
sustainability: can one exist without the other? Public Health Nutr. 18 (13) (2015)
2293–2302.
[3] B. Herrmann, V. Rundshagen, Paradigm shift to implement SDG 2 (end hunger): a
humanistic management lens on the education of future leaders, Int. J. Manag.
Educ. 18 (1) (2020) 100368.
[4] Food and Agricultural Organization of the United Nations, The State of Food
Security and Nutrition in the World, FAO, 2018, 2018, http://www.fao.org/3/i9
553en/i9553en.pdf. (Accessed 19 December 2018).
[5] E. Carrillo-´Alvarez, B. Salinas-Roca, L. Costa-Tutusaus, R. Mil`a-Villarroel,
N. Shankar Krishnan, The measurement of food insecurity in high-income
countries: a scoping review, Int. J. Environ. Res. Publ. Health 18 (18) (2021) 9829.
[6] A. Odoms-Young, A.G. Brown, T. Agurs-Collins, K. Glanz, Food insecurity,
neighborhood food environment, and health disparities: state of the science,
research gaps and opportunities, Am. J. Clin. Nutr. 119 (3) (2024) 850–861.
[7] WHO, Hunger numbers stubbornly high for three consecutive years as global crises
deepen, UN report 24 (2024). Joint News Report.
[8] M.C. Boliko, FAO and the situation of food security and nutrition in the world,
J. Nutr. Sci. Vitaminol. 65 (Supplement) (2019) S4–S8.
G.E. Kasse et al.
Human Nutrition & Metabolism 41 (2025) 200327
10
The authors declare that they have some known competing financial
[9] E. Au, Africa Regional Overview of Food Security and Nutrition, 2020.
[10] Food and Agricultural Organization of the United Nations, The State of Food
Security and Nutrition in the World, FAO, 2019, 2019, http://www.fao.org/3/ca5
162en/ca5162en.pdf. (Accessed 16 August 2019).
[11] Food and Agricultural Organization of the United Nations, The State of Food
Security and Nutrition in Europe and Central Asia, FAO, 2017, 2017, http://www.
fao.org/3/a-i8194e.pdf. (Accessed 17 December 2018).
[12] M.M. Weigel, R.X. Armijos, Household food insecurity and psychosocial
dysfunction in Ecuadorian elementary schoolchildren, Hindawi I. J. Pediatrics
(2018) 6067283, https://doi.org/10.1155/2018/6067283, 7 pages.
[13] Patel NB: HIGHLIGHTS OF GLOBAL REPORT ON FOOD CRISES.
[14] C. Gundersen, J.P. Ziliak, Food insecurity research in the United States: where we
have been and where we need to go, Appl. Econ. Perspect. Pol. 40 (1) (2018)
119–135.
[15] C.A. Gregory, A. Coleman-Jensen, Food Insecurity, Chronic Disease, and Health
Among Working-Age Adults, ERR-235, U.S. Department of Agriculture, Economic
Research Service, 2017.
[16] B. Meg, I.V. Woerden, M. Todd, N. Melissa, Hungry to learn: the prevalence and
effects of food insecurity on health behaviors and outcomes over time among a
diverse sample of university freshmen, Int. J. Behav. Nutr. Phys. Activ. 15 (2018) 9,
https://doi.org/10.1186/s12966-018-0647-7.
[17] M.L. Djomaleu, A.B. Rogers, M.B. Barrie, G.W. Rutherford, S.D. Weiser, J.D. Kelly,
Long-term consequences of food insecurity among Ebola virus disease-affected
households after the 2013–2016 epidemic in rural communities of Kono District,
Sierra Leone: a qualitative study, PLOS Glob. Public Health 2 (10) (2022)
e0000770.
[18] E. Tolentino, Population Growth and the Catholic Church: Issues in Population
Control in the Philippines (Master’s thesis), 2019.
[19] S.I.M.M. Gabrielle, Disaster response in Southeast Asia: the ASEAN agreement on
disaster response and emergency management, Asian J. Int. Law 8 (1) (2018)
116–142.
[20] B. Roehlano, E. Antonio, C. Habito, E. Porio, D. Songco, Strategic review, food
security and nutrition in the Philippines. BRAIN TRUST, INC, 2017. https://docs.
wfp.org/api/documents/WFP0000015508/download/. (Accessed 15 June 2019).
[21] Philippines Statistics Authority, The proportion of Poor Filipinos registered at 21.0
percent in the First Semester of 2018. http://www.psa.gov.ph/sites/default/files/
press%20release_povertyf.pdf, 2019. (Accessed 15 July 2019).
[22] M.E. Atienza, People’s views about human security in five philippine
municipalities’, disaster prevention and management, Int. J. 24 (2015) 448–467,
https://doi.org/10.1108/DPM-12-2014-0277.
[23] National Risk Reduction and Management Council, Final report effects of typhoon
“Yolanda” haiyan. http://www.ndrrmc.gov.ph/attach
ments/article/1329/FINAL_REPORT_re_Effects_of_Typhoon_Yolanda_(Haiyan)
_06-09NOV2013.pdf, 2014.
[24] S. Lakeman, S. Lakeman, Typhoon haiyan: context, actors and response.
Environmental and Disaster Displacement Policy: Organisational Cooperation
between the UN High Commissioner for Refugees and the International
Organisation for Migration, 2022, pp. 129–158.
[25] M.E. Atienza, P. Eadie, M. Tan-Mullins, Human Security and Community Resilience
in the Wake of Typhoon Yolanda (Working Paper VI), ESRC/DFID, 2018. May
2018. Retrieved from, http://www.projectyolanda.org/documents/human-secu
rity-working-paper-may-2018.pdf.
[26] C. Cafiero, S. Viviani, M. Nord, Food security measurement in a global context: the
food insecurity experience scale, Measurement 116 (2018) 146–152.
[27] R.A. Ryan, B. Murphy, A.L. Deierlein, S. Lal, N. Parekh, J.D. Bihuniak, Food
insecurity, associated health behaviors, and academic performance among urban
university undergraduate students, J. Nutr. Educ. Behav. 54 (3) (2022) 269–275.
[28] A. Saint Ville, J.Y.T. Po, A. Sen, A. Bui, H. Melgar-Qui˜nonez, Food security and the
food insecurity experience scale (FIES): ensuring progress by 2030, Food Secur. 11
(2019) 483–491.
[29] C. Connors, L. Malan, S. Canavan, F. Sissoko, M. Carmo, C. Sheppard, F. Cook, The
Lived Experience of Food Insecurity under Covid-19. A Bright Harbour Collective
Report For the Food Standards Agency, Food Standard Agency, London, UK, 2020,
p. 41.
[30] Food and Agricultural Organization of the United Nations, The Food Insecurity
Experience Scale (FIES). Guidance for translation: intended meanings of the
questions and specific terms. http://www.fao.org/3/a-be898e.pdf, 2015.
(Accessed 7 August 2019). Consulted on.
[31] Food and Nutrition Research Institute (FNRI-DOST), Philippine nutrition facts and
figures 2011. DOST complex, FNRI bldg, Bicutan, Taguig City, And Metro Manila,
Philippines (2012), 122.53.86.125/facts_figures2011.pdf. (Accessed 28 July 2019).
[32] D.W. Benti, W.T. Biru, W.K. Tessema, The effects of commercial orientation on
(Agro) pastoralists’ household food security: evidence from (Agro) pastoral
communities of Afar, Northeastern Ethiopia, Sustainability (Basel) 14 (2) (2022)
731.
[33] I.M.R. Galang, Is food supply accessible, affordable, and stable? The state of food
security in the Philippines, in: PIDS Discussion Paper Series, 2022.
[34] R. Dwyer, The Impact of Cash Transfers across the Economic Spectrum, University
of British Columbia, 2022.
[35] E. Kandpal, H. Alderman, J. Friedman, D. Filmer, J. Onishi, J. Avalos, A conditional
cash transfer program in the Philippines reduces severe stunting, J. Nutr. 146 (9)
(2016) 1793–1800.
[36] ACAPS, Secondary Data Review: Philippines Typhoon Yolanda, Consulted, 2014.
www.humanitarianresponse.info/files/assessments/140111%20SDR%20Yolanda
%20Philippines%20final.pdf. (Accessed 28 December 2018).
[37] J.W. Lee, Effects of frequent eating-out and breakfast skipping on body mass index
and nutrients intake of male adults: analysis of 2001 Korea National Health and
Nutrition Survey data, Korean J. Commun. Nutr. 14 (2009) 789–797.
[38] L.E. Cahill, S.E. Chiuve, R.A. Mekary, Prospective study of breakfast eating and
incident coronary heart disease in a cohort of male US health professionals, J. Vasc.
Surg. 59 (2) (2014) 555.
[39] N. Willows, P. Veugelers, K. Raine, S. Kuhle, Associations between household food
insecurity and health outcomes in the Aboriginal population (excluding reserves),
Health Rep. 22 (2) (2011).
[40] B. Aur´elie, F. Vieux, S. Lioret, C. Dubuisson, F. Caillavet, N. Darmon, Socio-
economic characteristics, living conditions, and diet quality are associated with
food insecurity in France, Public Health Nutr. 18 (16) (2015) 2952–2961.
[41] J. Laitinen, E. Ek, U. Sovio, Stress-related eating and drinking behavior and body
mass index and predictors of this behavior, Prev. Med. 34 (2002) 29–39.
[42] E.A. Frongillo, Understanding obesity and program participation in the context of
poverty and food insecurity, J. Nutr. 133 (2003) 2225–2231.
[43] L. Iglesias-Rios, J.E. Bromberg, R.P. Moser, E.M. Augustson, Food insecurity,
cigarette smoking, and acculturation among Latinos: data from NHANES 1999-
2008. J Immigrant Minority Health, 2013, https://doi.org/10.1007/s10903-013-
9957-7.
[44] J.A. Mello, K.M. Gans, P.M. Risica, et al., How is food insecurity associated with
dietary behaviors? An analysis with low-income, ethnically diverse participants in
a nutrition intervention study, J. Am. Diet. Assoc. 110 (2010) 1906–1911.
[45] N. Nonhlanhla, O. Alaba, B. Harris, M. Chersich, J. Jane Goudge, Utilization of
traditional healers in South Africa and costs to patients: findings from a national
household survey June 2011, J. Publ. Health Pol. 32 (Suppl 1) (2011) S124–S136,
https://doi.org/10.1057/jphp.2011.26. Suppl 1.
[46] G. Bishwajita, S. Yaya, Household food insecurity is independently associated with
poor utilization of maternal healthcare services in Bangladesh, FACETS 2 (2017)
969–983, https://doi.org/10.1139/facets-2017-0018.
[47] M. Bruening, K. Argo, D. Payne-Sturges, M.N. Laska, The struggle is real: a
systematic review of food insecurity on post-secondary education campuses,
J. Acad. Nutr. Diet. (2017), https://doi.org/10.1016/j.jand.2017.05.022.
[48] K.S. Yim, Health-related behavioral factors associated with nutritional risks in
Koreans aged 50 years and over, Korean J. Commun. Nutr. 12 (2007) 592–605.
[49] M. Ding, M.K. Keiley, K.B. Garza, P.A. Duffy, C.A. Zizza, Food insecurity is
associated with poor sleep outcomes among US adults, J. Nutr. 145 (3) (2015)
615–621.
[50] T. Akersted, P.M. Nilsson, Sleep as restitution: an introduction, J. Intern. Med. 254
(2003) 6–12.
[51] D.J. Buysse, C.F. Reynolds, T.H. Monk, S.R. Berman, D.J. Kupfer, The Pittsburgh
Sleep Quality Index: a new instrument for psychiatric practice and research,
Psychiatry Res. 28 (1989) 193–213.
[52] M.A. Grandner, N.P. Patel, P.R. Gehrman, D. Xie Dsha, T. Weaver, N. Gooneratne,
Who gets the best sleep? Ethnic and socioeconomic factors related to sleep
complaints, Sleep Med. 11 (2010) 470–478.
[53] D.S. Lauderdale, K.L. Knutson, L.L. Yan, P.J. Rathouz, S.B. Hulley, S. Sidney, et al.,
Objectively measured sleep characteristics among early-middle-aged adults: the
CARDIA study, Am. J. Epidemiol. 164 (2006) 5–16.
[54] J. Silverman, J. Krieger, M. Kiefer, P. Hebert, J. Robinson, K. Nelson, The
relationship between food insecurity and depression, diabetes distress and
medication adherence among low-income patients with poorly-controlled diabetes,
J. Gen. Intern. Med. 30 (2015) 1476–1480.
[55] M.E. Martinez, B.W. Ward, Health Care Access and Utilization Among Adults Aged
18–64, by Poverty Level: United States, 2013–2015, vol. 262, NCHS Data Brief,
2016, pp. 1–8.
[56] J.A. Pellowski, S.C. Kalichman, S. Cherry, C. Conway-Washington, C. Cherry,
T. Grebler, L. Krug, The daily relationship between aspects of food insecurity and
medication adherence among people living with HIV with recent experiences of
hunger, Ann. Behav. Med. 50 (6) (2016) 844–853.
[57] J.S. Gonzalez, E. Shreck, C. Psaros, S.A. Safren, Distress and type 2 diabetes-
treatment adherence: a mediating role for perceived control, Health Psychol. 34 (5)
(2015) 505–513.
[58] S. Young, A.C. Wheeler, S.I. Mccoy, S.D. Weiser, A review of the role of food
insecurity in adherence to care and treatment among adult and pediatric
populations living with HIV and AIDS, AIDS Behav. 18 (2014) S505–S515.
[59] S. Weiser, K. Palar, A. Hatcher, S. Young, E. Frongillo, B. Laraia, Food Insecurity
and Health: A Conceptual Framework, 2015, https://doi.org/10.1201/b18451-3.
[60] M.R. Baldwin, P.P. Yori, C. Ford, et al., Tuberculosis and nutrition: disease
perceptions and health-seeking behavior of household contacts in the Peruvian
Amazon, Int. J. Tuberc Lung Dis. Dec. 8 (12) (2004) 1484–1491.
[61] A.F. Sullivan, S. Clark, D.J. Pallin, C.A. Camargo, Food security, health, and
medication expenditures of emergency department patients, J. Emerg. Med. 38 (4)
(2010) 524–528.
[62] J.R. Miner, B. Westgard, T.D. Olives, R. Patel, M. Biros, Hunger and food insecurity
among patients in an urban emergency department, West. J. Emerg. Med. 14 (3)
(2013) 253–262.83.
G.E. Kasse et al.
Human Nutrition & Metabolism 41 (2025) 200327
11