Empirical Analysis of Household Food Insecurity and Hunger Among Rural Communities in Southern Somalia

Empirical Analysis of Household Food Insecurity and Hunger Among Rural Communities in Southern Somalia | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Empirical Analysis of Household Food Insecurity and Hunger Among Rural Communities in Southern Somalia Mohamud Yasin Artan, Nurul Nadia Ramli, Mad Nasir Shamsudin, Mark Buda, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9172675/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract In Southern Somalia, food insecurity remains an ongoing concern as climate variability and economic instability, coupled with limited livelihood options, continue to compromise household access to adequate and nutritious food. Using experience-based indicators, this study assesses the prevalence and severity of household food insecurity and hunger among rural households. The study specifically adopts the Household Food Insecurity Access Scale (HFIAS) and the Household Hunger Scale (HHS) to measure food insecurity and hunger in different socioeconomic and demographic groups. The analysis used for this study is a cross-sectional analysis, where primary data were collected through household survey across three states in Southern Somalia. Using a multistage sampling approach, 420 rural households were selected to be representative of all livelihood zones. Descriptive statistics was used to determine the factors related to food insecurity. Households were categorized by food access and consumption patterns as measured by HFIAS and HHS. The proportion of households with food insecurity was 96.4%, among which mild, moderate, and severe food insecurity accounted for 6.0%, 35.0%, and 55.4%, respectively. According to HHS results, 26.43% of households had moderate to severe hunger and 73.57% had little or no hunger, indicating continued challenges to food access in rural Somalia. Female-headed households witnessed a disproportionate impact from their struggle for livelihoods, confirming the deep-seated inequality in access to economic resources and opportunities. These results expose the abiding structural dimensions of food insecurity in rural Southern Somalia and point to a clear need for policy responses that address integrated livelihoods resilience, agricultural productivity improvement and gender implicating food security interventions. Food insecurity HFIAS HHS Rural Households Southern Somalia Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Background Food security is a compound phenomenon that involves the physical, social, and economic access to enough, safe, and nutritious food to lead an active and healthy life (Coates et al. 2007 ; Piperata et al. 2023 ). According to (Coates et al. 2007 ; Maxwell et al. 2014; Moroda et al. 2018 ; Pandey and Bardsley 2019 ), food security definition is “when all people at all times have physical or economic access to sufficient, safe and nutritious food to meet their dietary needs and food preferences for an active and healthy life”. Food insecurity persists despite decades of international efforts to end hunger, and it is made worse by poverty, climate change, economic inequality, and conflicts (Maxwell et al. 2014; Mota et al. 2019 ). Food insecurity continues to be one of the most pressing global problems of our era, impacting millions of people around the world. Nowadays, the current chronic hunger affects the lives of over 800 million people’s worldwide with a big impact of this issue on Sub-Saharan Africa (Mota et al. 2019 ). With hunger on the rise in low- to middle-income countries and across pockets of developed countries, the path to global food security is sounding pretty complex. Moreover, the promise of ending hunger by 2030 is becoming increasingly unattainable without immediate, extensive interventions that fortify food systems and bolster resilience across all echelons amidst enduring post-pandemic disparities, supply chain interruptions, and climate shocks (Demie and Gessese 2023 ; Addai et al. 2024 ). Among the main drivers of global food insecurity is population expansion. The global population was at 7.7 billion in 2019 and is projected to reach 8.5 billion in 2030 and further to 10.9 billion in 2100 (Ugal and Imam 2023 ). Sub-Saharan Africa (SSA) bears a disproportionate burden of this demographic shift, as the region is projected to account for more than half of global population growth by 2050 (UN 2019 ). Rapid population increase exerts immense pressure on food systems already constrained by limited resources, fragile economies, and volatile political environments. As a result, food security is particularly challenged in SSA due to persistent low agricultural productivity, deteriorating environmental conditions, and inadequate investments in agriculture. Unlike other regions of the world where undernutrition has declined, malnutrition in SSA remains stubbornly high, with the prevalence of undernourishment increasing in many fragile and conflict-affected states (FAO et al. 2022 ). Somalia faces food insecurity due to cyclical droughts that further increase the level of famine risk and negatively impact food insecurity. For example, the Bay region continues to report very high rates of acute malnutrition and death, suggesting ongoing reduced food consumption and sustained nutritional deficits (IPC Global Partners 2022 ). Climatic shocks are exacerbated by long-term conflict and political fragility which prevents governance and institutions from robustly regulating food systems. As Maxwell and Fitzpatrick ( 2012 ) highlight, in fragile states conflict frequently intensifies resource scarcity, through amongst other things, undermining markets, disrupting access to food, and constraining humanitarian access. Weak administration, recurring conflict and extreme climate events reinforce each other in creating conditions in Somalia that drive chronic dependency on external food assistance for millions of people. Determining food insecurity is an important variable that supports efforts to understand and, therefore, addressing challenges to food access, as well as informing appropriate policy interventions and the progress made towards the goal of eradicating hunger (Knueppel et al. 2010 ; Kabalo et al. 2019 ). The Household Food Insecurity Access Scale (HFIAS) and the Household Hunger Scale (HHS) are the two widely used tools that have proven to be effective in providing insights into household food insecurity (Regassa and Stoecker 2012 ). Nine standardized questions which included anxiety about the food supply, qualitative insufficiency in food consumption and insufficient quantity of food consumed were used to measure food insecurity using HFIAS developed by the USAID-funded Food and Nutrition Technical Assistance (FANTA) Project (Coates et al. 2007 ; Regassa and Stoecker 2012 ; Pandey and Bardsley 2019 ; Berra 2020 ). The HHS assesses only the most severe hunger-related behaviours (Butaumocho and Chitiyo 2017 ). These tools allow policymakers, researchers, and humanitarian organizations to analyze trends in food insecurity across cultural contexts and identify changes over time (Regassa and Stoecker 2012 ). While HFIAS and HHS provide significant efficiency and practicality, concerns around biases from response and seasonal variability underscore the necessity for further validation. Accurate assessment of food insecurity is crucial to mitigate targeted interventions and to enhance protective factors in the food access and resilience of vulnerable communities (Berra 2020 ). This study aims to empirically assess the prevalence and severity of household food insecurity and hunger among rural households in Southern Somalia. With the high level of prevalence and recurrent nature of food insecurity in the region, identifying its multidimensional consequence is an important topic for intervention design and targeting. While there is increasing reliance on standardized food security measurement tools by global stakeholders, there are few empirical studies utilizing the Household Food Insecurity Access Scale (HFIAS) and Household Hunger Scale (HHS), particularly from Southern Somalia. It is in response to this evidence gap that the present study aims to produce household-level food security data, and test whether and how relevant standard tools – in particular HFIAS and HHS – are capturing food insecurity experiences in Somalia. Previous studies have examined food security in different regions, such as Ukonu et al. ( 2024 ) on food accessibility and dietary diversity in Nigeria, Moroda et al. ( 2018 ) on food insecurity determinants in Ethiopia, and Nour and Abdalla ( 2021 ) on food security in Sudan using HFIAS. This study provides to the current body of work on food insecurity measurement and will enable operationalizing targeted policies and programs to increase food accessibility in vulnerable populations. Methods Description of the study area The study was conducted in Southern Somalia, specifically in Southwest State, Jubaland State, and Hirshabelle State as shown in Fig. 1 , which are highly vulnerable to food insecurity due to recurring droughts, conflict, and economic instability. Southern Somalia covers various agro-ecological zones between approximately 1°N–6°N latitude and 41°E–46°E longitude. It is bordered by Ethiopia to the west and Kenya to the southwest, while the Indian Ocean lies to the east. The area is a typical arid and semiarid climate with an average annual temperature ranging from 25 to 35°C. Rainfall is bimodal: the Gu season (April–June) is the main rainy season, while the Deyr season (October–December) provides secondary and relatively unreliable rainfall. The region has a mixed livelihood system that comprises pastoralism, agro-pastoralism, and riverine farming, with major agricultural density along the Juba and Shabelle rivers. Population density is dispersed, with urban centers like Baidoa, Kismayo, and Jowhar serving as economic epicenters. Recurrent climate shocks, combined with displacement from conflict and inadequate infrastructure, amplify food insecurity in the region, presenting an urgent need for study. Research design and Sampling procedure A quantitative research design was adopted in the study and data was gathered based on face-to-face structured questionnaire with household respondents. The researcher incorporated various perspectives on food security among rural households using structured questionnaire data by including a broad analysis. Fieldwork was undertaken by six well-trained enumerators. The questionnaire comprised of questions regarding the household heads demographic and economic status: age, gender, marital status, education level, employment and income; the questionnaire also included the nine questions explained above that determine food insecurity for each month, thus allowing the calculation of the HFIAS. Stratified random sampling at the village level was used to select the sample as shown in Fig. 2 (Regassa 2011 ; Maxwell et al. 2014; Grobler and Dunga 2017 ; Mota et al. 2019 ). The selected households were then asked to participate in the survey, and all respondents were allowed to respond in their native language. Sample households were selected at random from different livelihood zones. To ensure a representative sample size, the study employed the defined population proportion formula as determined by (Taro Yamane 1967 ; Dessalegn 2018 ; Mota et al. 2019 ): $$\:n=\:\frac{N}{1+N\:{\left(e\right)}^{2}}$$ Where n is the sample size, N is the population size, e is the Margin of error and 1 = probability of the event occurring. Applying this formula, the sample size was calculated as follows: $$\:n=\:\frac{N}{1+N\:{\left(e\right)}^{2}}=\:\frac{\text{1,091,524}}{1+\text{1,091,524}\:{\left(0.05\right)}^{2}}=\frac{\text{1,091,524}}{\text{2,729.81}}\:=400$$ After adjusting for the non-response and incomplete responses, the final sample size was adjusted to 420 households. This study used a multistage sampling method to select respondents. As illustrated in Fig. 2 , the first phase of this study employed a deductive approach to purposively select the context of Southern Somalia, which has been identified as the most vulnerable geographic region to food insecurity as a consequence of climate change, environmental degradation, and widespread poverty. In the second phase, Stratified Random Sampling was used, the study area was divided into three strata based on their respective states (Hirshabelle, Southwest, and Jubaland), which had different livelihood zones. The purposively selected districts from each of the states were Jowhar (Hirshabelle), Baidoa (Southwest), and Kismayo (Jubaland) during the third phase, based on their livelihood strategies and a high variety of their vulnerability to food insecurity and poverty. The fourth phase involved randomly selecting four villages within each district to capture variability in food security conditions. Lastly, in the fifth phase, Simple Random Sampling was utilized to choose households from each village which resulted in the total sample size of 420 farming households (Mayanja et al. 2015 ; Dessalegn 2018 ; Wassie et al. 2023 ). The structured sampling process provided a representative and minimized the opportunity for selection bias ensuring a statistically significant evaluation of household food insecurity and resilience. Source: (Mota et al. 2019 ; Wassie et al. 2023 ) Household Food Insecurity Measurements Household Food Insecurity Access Scale (HFIAS) The Household Food Insecurity Access Scale (HFIAS), developed by the Food and Nutrition Technical Assistance II (FANTA) project in collaboration with other organizations, was used to assess household food insecurity (McDonald et al. 2015 ; Musemwa et al. 2015 ; Bahta 2022 ). The HFIAS has nine primary questions that have been validated in many countries to accurately capture food security status in households across diverse cultural contexts as shown in Table 1 . These items are derived from respondents’ memory of how often they have not had enough food and the experiences associated with this shortfall over the prior 30 days. The HFIAS data provides important information about the prevalence of food insecurity in households (access) and can be used to monitor changes in food security status for a population across time frames. The questionnaire was then translated into Somali for greater clarity and relevance to participants. Subsequently, pilot testing of the translated items for comprehensibility and accuracy was performed with five households in each district ensuring items were not misunderstood. It excluded these households from the core analysis. During the pilot study, all nine HFIAS questions were asked and the replies accurately recorded. Respondents had the opportunity to discuss whether they had understood properly each item, that its wording was acceptable for their culture, and that it was unambiguous with respect to local situations. This approach enabled the researcher to test aspects of accuracy, clarity and cultural appropriateness of the HFIAS tool in a Somali context, which supports that the final household survey was reliable. The data was further analyzed and required changes were worked on before crystallizing the questionnaire into an improved and revised module. Table 1 HFIAS questions No. HFIAS Question 1 Did you worry that your household would not have enough food? 2 Were you or any household member not able to eat the kinds of foods you preferred because of a lack of resources? 3 Did you or any household member eat just a few kinds of food day after day because of a lack of resources? 4 Did you or any household member eat food that you did not want to eat because of a lack of resources to obtain other types of food? 5 Did you or any household member eat a smaller meal than you felt you needed because there was not enough food? 6 Did you or any household member eat fewer meals in a day because there was not enough food? 7 Was there ever no food at all in your household because there were no resources to get more? 8 Did you or any household member go to sleep at night hungry because there was not enough food? 9 Did you or any household member go a whole day without eating anything because there was not enough food? Source: (Kabalo et al. 2019 ) The nine standardized items of the Household Food Insecurity Access Scale (HFIAS) focus on a broad range of experience-based measures of food insecurity, from anxiety to actual reduction in amount consumed. These questions are designed to mirror three main sub-dimensions including uncertainty about and concerns for food supply (Q1), poor-quality/low dietary diversity (Q2–Q4) and not eating sufficient amounts of food (Q5–9). By measuring these continuities and gradations, the approach allows to gauge not just prevalence but also severity of food insecurity within households (Coates et al. 2007 ; Deitchler et al. 2010 ). The questions on anxiety, preference and dietary monotony as part of the food security module indicate that lack of access to enough food is not simply an issue of physical shortage but also encompasses psychological and social deprivation (Maxwell et al. 2014). Meanwhile, the escalation in the question sequence to any reduction of meals, experienced hunger and complete food absence signals increased severity of the situation and thus can be used as a proxy index to categorize household as either food-secure; mildly, moderately or severe food-insecure (Swindale and Bilinsky 2006 ). As such, the HFIAS scale conceptualizes food insecurity in a manner that is generalizable across cultures and context-sensitive, rendering it very well-suited to study rural Somali households where shocks, poverty and conflict frequently impede access to food. To calculate the HFIAS score per household, the frequency-of-occurrence responses were summed, and each response was pre-coded with the following values [0 = no, 1 = rarely, 2 = sometimes, 3 = often]. This allowed a maximum score of 27. A higher score reflects a greater level of food insecurity with respect to access, while a lower score indicates to a lesser degree of food insecurity or better access to food for the household. Responses to nine questions (Q1-Q9) on the occurrence of food insecurity (FI) and the corresponding frequency-of-occurrence responses were used to assess household food insecurity (Musemwa et al. 2015 ; Demie and Gessese 2023 ; Addai et al. 2024 ). Using these responses, households were categorized into four levels of food security. A household was considered food-secure if the score on the first FI frequency-of-occurrence question (Q1) was ‘0’ or ‘1’, and on Q2 to Q9 was ‘0’. The data was regarded as mildly food-insecure when the first FI frequency item scored ‘2’ or ‘3’, or if Q2 to Q4 scored ‘1’, while Q5 to Q9 remained as ‘0’. A household was considered moderately food-insecure if Q3 or Q4 scored ‘2’ or ‘3’, or if Q5 or Q6 scored ‘1’ or ‘2’ but Q7 to Q9 scored ‘0’. If Q5 or Q6 scored ‘3’, or if Q7 to Q9 scored ‘1’, ‘2’, or ‘3’, then a household was considered as severely food-insecure household (Kabalo et al. 2019 ; Demie and Gessese 2023 ). The study used a validated indicator of food security—Household Food Insecurity Access Scale (HFIAS)—to classify households into distinct categories based on specific threshold values, as demonstrated in Table 2 . The HFIAS identifies populations in four categories: food secure (with scores between 0–1), mildly food insecure (with scores between 2–8), moderately food insecure (with scores between 9–16), and severely food insecure (with scores between 17–27) households. This classification serves as an effective property to characterize households' observations and experiences related to food access, quality, consumption, and uncertainty or worry about food availability. Table 2 Classification and Thresholds for Household Food Insecurity Access Scale (HFIAS) Indicator Category number Category description Range HFIAS 1 Food secure 0–1 2 Mildly food insecure 2–8 3 Moderately food insecure 9–16 4 Severely food insecure 17–27 Source : (Kabalo et al. 2019 ; Demie and Gessese 2023 ) Household Hunger Scale (HHS) In this study, food insecurity was assessed by the Household Hunger Scale (HHS), which reflects the lack of food in a household and concerns about having enough and sufficiently diverse food. The HHS consists of three main occurrence questions and three additional frequency-of-occurrence questions corresponding to those occurrence questions. According to (Butaumocho and Chitiyo 2017 ; Berra 2020 ), HHS is based on the following three questions: During the last [4 weeks/30 days], was there ever no food to eat of any kind in your house because of lack of resources to get food? During the last [4 weeks/30 days], did you or any household member go to sleep at night hungry because there was not enough food? During the last [4 weeks/30 days], did you or any household member go a whole day and night without eating anything at all because there was not enough food? This method provides a direct measure of severe food deprivation, which can offer important information on the depth and severity of hunger faced by households (Butaumocho and Chitiyo 2017 ). Respondents who answered "yes" to any of the Household Hunger Scale (HHS) occurrence questions were asked follow-up question to determine the frequency-of-occurrence of the reported condition in the past four weeks. Responses, thus, ranged from rarely (one or two times), sometimes (three to ten times), or often (more than ten times (Xu et al. 2023 ). This method gave a better sense of the severity and duration of food insecurity in the household. Household data on hunger were scored using the Household Hunger Scale (HHS), and numerical values were assigned to each response. For every “no” response to the three core questions, a score of 0 was assigned. A score of 1 was given for a “yes” if the reported frequency of occurrence derived from the questionnaire was considered rarely (code 1) or sometimes (code 2). A "yes" at the level of often (code 3) was given a score of 2 (Demie and Gessese 2023 ; Xu et al. 2023 ). Total HHS score was calculated as the sum of the three individual questions, and ranged from 0 to 6, with higher scores indicating higher levels of food insecurity and more severe limitations in household food access. Table 3 displays household classification based on Household Hunger Scale (HHS), which is an experience-based scale that is commonly used in assessing food security. The HHS assigns households into three categories: little to no hunger (0–1), moderate hunger (2–3), and severe hunger (4–6). This continuum describes the frequency and severity of experiences related to hunger, which can fluctuate from occasional worries about access to food to chronic or extreme deprivation (Ballard et al. 2011 ; Maxwell et al. 2013). The tool is particularly important in fragile and food insecure contexts, including Somalia where repeated shocks continuously erode household access to food and its coping mechanisms. Through distinction of moderate and severe hunger, HHS allows policy makers and humanitarian actors to better target those most at risk and most in need for specific interventions over-and-above caloric provision necessary for sustained life by addressing long-term vulnerability and resilience gaps (Deitchler et al. 2010 ). Furthermore, its cross-cultural validation makes it a powerful tool for analysis comparison between areas and also increases the applicability for local planning and trends in global food security monitoring. Table 3 Classification and Thresholds for Household Hunger Scale (HHS) Indicator Category number Category description Range HHS 1 Little to no hunger 0–1 2 Moderate hunger 2–3 3 Severe hunger 4–6 Source: (Saaka 2016 ; Kolog et al. 2023 ) Data analysis Analysis of the data was performed by using IBM SPSS Statistics (Version 31.0.1.0.). Frequencies and percentages were employed using descriptive statistics to present household demographic, socio-economic characteristics and food insecurity indicators. The severity and prevalence of household food insecurity in Southern Somalia were measured using the Household Food Insecurity Access Scale (HFIAS) and the Household Hunger Scale (HHS) for rural areas. These instruments provided a way to classify the level of food insecurity and discover trends among different household characteristics. Interpretations of the results were used to guide policy and intervention development. Results Socio-demographic characteristics The socio-demographic characteristics of the surveyed households were described in Table 4 , which offers essential context for understanding food security outcomes and resilience trends. The characteristics of head of household such as gender, age, marital status, the highest education level achieved by the household head and the employment status were examined alongside income levels of the household. These variables are key to understanding the ways in which social and economic characteristics influence household vulnerability, capacity for coping and access to food. The data shows that age-wise distribution of household heads shows that 38.6% household head belong to the age group of 30–39 years, and 24.5% household head belong to the age group of 40–49 years. Food insecurity is compounded as older heads of households experience low functional capacity, restricting their participation in income-generating activities and disrupting economic productivity. When it comes to gender, data shows that 76.9% of households were male-headed while 23.1% were female-headed households. Female-headed households were especially vulnerable to food insecurity because of their limited access to land, credit, and agricultural resources. With regards to marital status, 76.9% of heads of household are married, and 11.9% are divorced. Households with married partners, which have a larger labor force, were potentially able to increase food security, but also have greater dependency burdens. Food security is primarily influenced by education, with 40.7% of household heads having no formal schooling while 31.4% receiving informal education. Given that low education levels limit access to employment and income diversification, this negatively impacts the ability to access food, leading to a high risk of food insecurity. The results from the employment status analysis show that 67.6% of household heads are engaged in on-farm activities only, and only 30.2% are engaged in both on-farm and off-farm work. This dependence on farming makes it susceptible to climate shocks. The household income findings show that 45.6% earned between US $ 100–199 per month, while 28.8% earned less than US $ 99, indicating widespread poverty and economic constraints. Lower-income households which struggle to be able to buy enough food are more food-insecure. The socio-demographic factors examined in this study are important for understanding household vulnerability and resilience to food insecurity in southern Somalia. The study specifically addresses its aim of identifying the socioeconomic determinants that affect household food access and coping capacity in terms of gender, age, marital status, level of education, employment status and income. The importance of female-headed households as more vulnerable also corresponds to the prior literature highlighting that there is a gender disparate access to land, credit, and resources throughout Sub-Saharan Africa (Peterman et al. 2014 ; Doss et al. 2018 ). Likewise, the association between low education level and food insecurity is in line with evidence proving that limited human capital impedes diversification of livelihoods as well as adaptive capacity (Smith and Haddad 2014 ). The heavy reliance on on-farm activities highlights how fragile are the rural livelihoods in fragile states, where climate-induced shocks instantly lead to food insecurity (Mekonnen et al. 2021 ). Furthermore, high prevalence of low incomes also underscores the connection between structural poverty and food insecurity as reported by Feleke et al. ( 2003 ) who suggest that poor households must cope with limited purchasing power, resulting in low food quality and diversity. On the whole, these findings validate previous research and contribute to that body of work while situating it within Somalia, where conflict, climate uncertainty, and fragile institutions amplify vulnerabilities. The findings further buttress the need to prioritize and synergize across education, gender equity, livelihood diversification, and income generation for both resilience and food insecurity reduction. Table 4 Socio-demographic characteristics of the study population Variable Category Frequency % Age 18–29 yrs 55 13.1 30–39 yrs 162 38.6 40–49 yrs 103 24.5 50–59 yrs 65 15.5 ≥ 60 yrs 35 8.30 Gender Male 323 76.9 Female 97 23.1 Marital Status Divorced 50 11.9 Married 319 76.0 Separated 19 4.5 Single 6 1.4 Widowed 26 6.2 Education Informal education 132 31.4 No Schooling 171 40.7 Primary 73 17.4 Middle 29 6.9 Secondary 12 2.9 Tertiary education 3 0.7 Employment Off-farm 5 1.2 On-farm 284 67.6 Both 127 30.2 Unemployed 4 1.0 Income 0–99 USD 121 28.8 100–199 USD 193 46.0 200–299 USD 55 13.1 ≥ 300 USD 51 12.1 Household Food Insecurity Access Scale (HFIAS) The Household Food Insecurity Access Scale (HFIAS) is commonly employed to measure food insecurity, based on the notion that a household experiences food insecurity during certain periods if a member of the household cannot limit the quantity or quality of food consumed or that a member has to depend on other strategies to cope with food shortages (Coates et al. 2007 ; Ukonu et al. 2024 ). Table 5 shows the response distribution to the nine HFIAS questions which measure varying dimensions of household food insecurity among the 420 households sampled for South Somalia. Responses to that question of severity further indicate a progressive increase in food insecurity as experiences become more extreme and aligned with hunger, compared with experiences that are more associated with access to food. The first few questions in the table show a relatively high percentage of households that frequently worry that food will not be available to them and are unable to buy foods they like and need because they cannot afford them. A few respondents confirmed this lack of diversity in food groups and said they were obliged to eat less appealing foods due to a deficit of resources. The total number of households reporting food insecurity, however, varied based on how severe the food insecurity was among those households, with a slight increase in the number of households that reported they had to eat fewer meals a day or go to sleep hungry and the number of households that reported they had to reduce the size of their meals in the last 30 days. The various respondents in Table 5 cover the last set of HFIAS questions, which represent the most severe cases of food insecurity, where households simply go to bed without eating or, in the worst-case scenario, for an entire day and night. The extremely high proportion of “yes” responses to these extreme indicators indicates that many of the households in Southern Somalia are experiencing chronic food insecurity and turning to coping strategies typically associated with crisis levels of food insecurity. The results reported in Table 5 offer important information on the complexity of food insecurity within rural households in Southern Somalia. The patterns suggest a continuum from worry about having enough food to severe deprivation, which is consistent with the theoretical model of food insecurity addressed as a progressive process (Coates et al. 2007 ; Maxwell et al. 2014). The higher proportion of extreme responses (e.g., decreasing meal size, skipping meal, or fasting for a whole day) demonstrates that households are chronically exposed and already stretching their limited ability to adjust; this is also in line with research by Mekonnen et al. ( 2021 ); Woleba et al. ( 2023 ). These results show that food-insecurity in Somalia is not a short-term issue, but is more fundamentally structural, with underlying causes related to poverty, climatic stress and market dependency. The results highlight the importance of including resilience in responses to repeated cycles of hunger, through maximizing access opportunities and options, promoting livelihood diversity amongst households, and ensuring food systems at household level are strong. Table 5 Questions of the Household Food Insecurity Access Scale and affirmatively answered questions by the study population in Southern Somalia (n = 420). In the past four weeks… No Household Food Insecurity Access Scale Questions n % 1 Did you worry that your household would not have enough food? 412 98.10 2 Were you or any household member not able to eat the kinds of foods you preferred because of a lack of resources? 404 96.19 3 Did you or any household member have to eat a limited variety of foods due to a lack of resources? 393 93.57 4 Did you or any household member have to eat some foods that you really did not want to eat because of a lack of resources to obtain other types of food? 386 91.90 5 Did you or any household member have to eat a smaller meal than you felt you needed because there was not enough food? 374 89.05 6 Did you or any household member have to eat fewer meals in a day because there was not enough food? 368 87.62 7 Was there ever no food to eat of any kind in your household because of lack of resources to get food? 363 86.43 8 Did you or any household member go to sleep at night hungry because there was not enough food? 309 73.57 9 Did you or any household member go a whole day and night without eating anything because there was not enough food? 188 44.76 Figure 3 shows the percentage of households responding 'Yes' to each of the nine HFIAS questions (Q1–Q9), alongside the proportion of households that reported 'No' responses and illustrates a clear trajectory of food insecurity among the surveyed households in Southern Somalia. The results follow a similarly stark trajectory from anxiety about access to food, to hunger, to severe rationing and deprivation. Q1 and Q2 at first show that a strong proportion of households worry that food is available at the cost they need, and they can’t afford the food they need. This hearkens to perpetual financial volatility, restricting access to varied and nutritious diets. Q3 and Q4 show a decline in food quality, characterized by many households eating a small number of foods widely and relying more often on less preferred foods as household resources tighten. As food insecurity increases, Q5 and Q6 indicate that many households reduce meal size and the number of meals eaten a day as coping strategies. The prevalence of “sometimes” and “often” responses in those categories is a signal of deepening food shortages and growing vulnerability. The findings are alarming, in particular the most severe indicators, Q7, Q8 and Q9, which point to cases of extreme food deprivation, whereby a significant proportion of households go to bed hungry, or those that do not have anything to eat for a whole day and night. The predominance of “often” and “sometimes” among such responses is testament to chronic hunger and malnourishment as well as a growing food crisis. Results from the HFIAS provide important information about the multi-dimensional aspects of food insecurity in rural households in Southern Somalia. The transition from food-related anxiety to extreme deprivation indicates the chronic and cyclical nature of hunger in insecure livelihoods. These findings directly contribute to the objective of the present study, which is to determine the prevalence and severity of food insecurity based on experience-based indicators. The response trajectory from low diet diversity to skipping meals is symptomatic of structural poverty and precarious food access and confirms patterns found in similar contexts elsewhere in Sub-Saharan Africa (Coates et al. 2007 ; Maxwell et al. 2014). The high proportion of extreme coping measures, such as going to bed without food and fasting a whole day, is consistent with another study from Mekonnen et al. ( 2021 ) who found that experiencing drought and market shocks repeatedly increases the depth of food insecurity. Yet, the current study builds on previous work by affirming HFIAS validity in a Somali context and its cultural appropriateness and empirical robustness to measure local experiences of food insecurity. These results show that food insecurity is more than resources scarcity but is also rooted in systemic vulnerability. Figure 4 shows the levels of food insecurity among Households in Southern Somalia are categorized into four levels of food in/secure groups, namely food secure, mildly food insecure, moderately food insecure, and severely food insecure groups. The HFIAS addresses the access dimension and reflects information on severity and prevalence of food insecurity in a given population (Addai et al. 2024 ). The findings shed light on the grim reality of households, where only a small percentage have stable access to food, while the rest face moderate to severe levels of food insecurity. Food secure households (3.57%) were households that, at all times, had access to enough food for an active, healthy life and had no or very limited anxiety about availability of food; and little or no risk of hunger. But mildly food insecure households (5.95%) face some challenges, such as necessary reduction in the food variety or quality, but are still able to maintain food availability. These households are not in immediate crisis, but they are clearly at risk of crisis due to external shocks. A large share (35.00%) represents households that are moderately food insecure and often experience reduced food intake, eating fewer meals, or other dietary changes. This group is under pressure economically and environmentally, so they are especially vulnerable to additional deterioration in food security. The most concerning category is severely food insecure households (55.48%) that have chronic hunger, severely reduced meal frequency, and people who go whole days without food. Such a high prevalence in this category is indicative of a serious food crisis in the region. Results from the analysis of HFIAS depict a chilling reality on household level food insecurity in Southern Somalia, its prevalence as well the extent and degree across the different categories. The fact that the vast majority of moderate and severe food-insecure households were diagnosed underlines a structural and chronic food crisis, which mirrors the severe economic development and climatic vulnerabilities found in this region (Mekonnen et al. 2021 ; Woleba et al. 2023 ). These findings directly indicates that for many households, there has been no improvement in food access due mainly to poverty, environmental shocks, as well as limited livelihood diversification. The results align with a previous study conducted by Alam et al. ( 2016 ) and Asesefa Kisi et al. ( 2018 ), which also highlighted a high prevalence of moderate to severe food insecurity among agrarian households residing in fragile and vulnerable contexts. Yet, the present study broadens this perception by demonstrating that even somewhat food-insecure households are highly vulnerable to crises in the face of shocks. Household Hunger Scale (HHS) The Household Hunger Scale (HHS) is a tool commonly used to measure the severity of hunger, specifically by indicating to what extent households are deprived of food (Tambo et al. 2021 ). Responses were scored numerically in order to classify each household type across experiences of hunger. Figure 5 classifies households into two levels of household hunger: little to no and moderate household hunger and vividly illustrates the amount of food deprivation in Southern Somalia. The results show that 73.57% of households fall into the moderate household hunger category, which defines households reporting frequent reductions in meal size, going to bed hungry or not eating for an entire day. This implies that a large percentage of the population suffers from chronic food shortages reflecting high vulnerability to economic instability, seasonal variations, and climate-related shocks. At the same time, only 26.43% of households reported no or very little household hunger — a sign of some level of food security. However, considering the broader trends of food insecurity observed throughout the region, this group would still be at risk of falling into food insecurity in the event of worsened external conditions. The results of the study based on HHS demonstrate an important insight for understanding nature and conditions that drive household food insecurity in Southern Somalia to go beyond simple classification to ascertain structural features. This reflects the aim of this study to comprehend not just food insecurity status, but rather the context in which it occurs, and demonstrates that hunger is no temporary problem, but a manifestation of long-term risk exposure combined with an insufficient capacity to cope. The implications of these results indicate that resilience promotion approaches need to be comprehensive integrated interventions, which reinforce increased access to productive assets, social safety nets and climate-smart agriculture practices in order to achieve a sustainable positive cycle from vulnerability. Results from the HHS shed important light on the severity, and longevity of hunger among households in Southern Somalia, which verifies that food insecurity has a long-term character. The over representation of households classified into the moderate hunger category is indicative of structural poverty, narrowness in livelihood diversification and repeated exposure to climate-induced shocks mainly drought that depletes food access (Maxwell et al. 2014; Mekonnen et al. 2021 ). These findings are particularly relevant to the aim of this study looking that hunger in Somalia is not just an occasional event, but instead a chronic consequence of structural vulnerability. The findings are in line to studies of Deitchler et al. ( 2010 ); Maxwell et al. ( 2020 ); Woleba et al. ( 2023 ), for example, who show that high HHS scores are directly associated with dependence on rain-fed agriculture and poor market functioning. Nonetheless, this research adds new empirical evidence in the rural Southern Somalia context where chronic food insecurity remains despite of humanitarian support. These results reinforce the urgency for resilience-based interventions to break the cycle of chronic hunger and vulnerability. Relationship Between Household Head Gender and Food Insecurity Measures Table 6 shows the HFIAS and HHS scores by household head gender, highlighting that gender is a major predictor of food insecurity and hunger in the household. Findings show that female-headed household has higher levels of food insecurity and hunger than male-headed households, reflecting wider gender inequalities in accessing food, financial stability, and resilience to shocks. When comparing male- to female-headed households, female-headed households show a higher average HFIAS score and a higher proportion of households with severe food insecurity. This indicates increased incidence of food insecurity, with women-led households potentially experiencing limited food access, poor food quality and not enough to eat. Poorer female-headed households often have limited access to land tenure, financial resources and agricultural inputs that contribute to food insecurity. Likewise, HHS findings show that households headed by females are more likely to report experiencing moderate to severe hunger than their male-headed counterparts. This suggests women-headed households are more likely to cut down on meals, going hungry, and employing coping strategies like meal skipping or eat smaller meals. The economic and food security vulnerability of female-headed households is further exacerbated by the structural barriers they face around credit access, employment, and social networks. These findings demonstrate a critical need for gender-targeted action in Southern Somalia, including targeted livelihood support for women, enhanced access to financial services, and agricultural empowerment programs. Reducing food insecurity and hunger among vulnerable groups, such as female-headed households, requires addressing gender-based inequalities within food security policies and development programs. Table 6 Household Head Gender and Its Impact on Food Insecurity and Hunger Levels in Southern Somalia Food insecurity status Male Female Total Household Food Insecurity Access Scale (HFIAS) Food Secure 15 0 15 Mildly Food Insecure Access 25 0 25 Moderately Food Insecure Access 104 43 147 Severely Food Insecure Access 179 54 233 Total 323 97 420 Household Hunger Scale (HHS) Little to no household hunger 106 5 111 Moderate household hunger 217 92 309 Severe household hunger 0 0 0 Total 323 97 420 Discussion This research explored the causes and prevalence of food insecurity in rural areas of Southern Somalia, using the Household Food Insecurity Access Scale (HFIAS) and the Household Hunger Scale (HHS) as major instruments of analysis. The HFIAS, a validated proxy for measuring food insecurity at the household level, gave a full view of how households in the study area perceive various experiences of food insecurity including uncertainty and anxiety over food availability to inadequacy of dietary quality and quantity. The progression of the HFIAS questions indicated an incremental deterioration of household food access, starting with pervasive worry about whether food was available and affordable, followed by compromises on the quality of food consumed, and then engaging in severe coping strategies such as skipping meals, going to bed hungry, or enduring entire days without food. These results highlight the complex multi-faceted food insecurity situation, and especially in areas susceptible to climate variability, economic vulnerability, and poor market infrastructure. The sum of the responses to the HFIAS items not only served as an indicator of the severity of food insecurity but also as a basis for classification of households by tier of food security. The categories ranged from food-secure households, who had no major problems in obtaining food, to those classified as mildly insecure, moderately insecure, and, most disturbingly, severely food insecure. Households classified as severely food insecure revealed patterns of hunger, meal skipping, and entire lack of food consistent with systemic failure of food access. These classifications mirror wider structural impediments in the Somali context, with livelihood options being relatively narrow, value chain development being limited, and continued susceptibility to climate shocks. In this respect, the HFIAS is an important diagnostic instrument, not just saying that people are food insecure, but how and to what extent they are affected, and one which allows a more nuanced policy and programmatic response. The HHS results supplemented the results of the HFIAS by providing an explicit focus on the severity of hunger within households. The HHS, which measures behavioral and experiential manifestations of hunger, found that a significant number of households are experiencing moderate forms of hunger, where cutting a meal, sleeping without eating, and spending the entire day without eating are frequent experiences. While a lower share of HHs reported no or low hunger, the context in which hunger is low indicates that many households are probably at risk of food insecurity if there is a worsening of shocks. The reinforcing relationship between HFIAS and HHS measures emphasizes about a chronic emergency of limited access to food that is limited not only in terms of the quality of types of foods consumed and their variety, but the actual sufficiency of caloric consumption. These findings indicate that food deprivation in southern Somalia is not occasional or seasonal but persists as a chronic systemic inadequacy. The results indicate that there are noticeable differences between males and females in the levels of food insecurity and hunger among rural households. Male head households have presence in all four food insecurity categories (including those who are food secure and mild insecure), thus showing relatively wider access to food. All female-headed households are found in the moderate and severe food insecurity, none are food-secure or mildly food insecure. This pattern underscores a particularly vulnerable group of female-headed households that may be at increased risk for both limited access to food and more severe food insecurity. The same tendency is observed in the HHS outcome. Most male-headed households are in the little or no hunger category, which contrasts with nearly all female headed households that fall in the moderate hunger classification. The results indicated that gender is an important determinant for household’s food security status and that female headed households suffer from structural constraints, such as limited productive asset access, less income opportunities and socio-cultural restrictions, which increase their vulnerability to food insecurity and hunger. To be able to design inclusive and effective food security interventions in Southern Somalia, there is a need to address these gendered differences. Conclusions The results of this study indicate an alarming degree of household food insecurity and hunger among rural groups in Southern Somalia. Examination of the HFIAS and HHS show that a significant proportion of households are moderately or severely food insecure. The high prevalence of extreme responses, such as decrease in meal size, skipping meals, going to bed without food or fasting for a day are indicative of chronic and structural dimensions to food deprivation in the region. These trends are closely linked with restricted access to livelihood opportunities, low dietary diversity, poverty and recurring exposure of climate-induced shocks. Households headed by females in particular are disproportionately affected, with both a greater level of food insecurity and prevalence of hunger, highlighting the gender differentiated nature of food access and vulnerability within Somalia. Going forward, an over-arching approach to increase long-term resilience and decrease chronic hunger is required. Developing and implementing gender-sensitive policies into national food security frameworks, community-based early warning and response systems, strengthening institutional capacity for monitoring food security using standardized tools such as HFIAS and HHS. Policymakers and development actors need to move from short-term relief to long-term solutions addressing the underlying causes of food insecurity including poverty, inequality, environmental degradation and fragile rural economies. These results reinforce the importance of using evidence to design and implement more effective strategies for improving food security and reducing hunger in Southern Somalia. Abbreviations UPM Universiti Putra Malaysia HFIAS Household Food Insecurity Access Scale HHS Household Hunger Scale USAID United States Agency for International Development FANTA Funded Food and Nutrition Technical Assistance Declarations Ethics approval This study was conducted in compliance with all applicable ethical guidelines emphasizing safety, respect, and the rights of the participants. The methodology of this study has been approved by the Ethics Committee for Research Involving Human Subjects, Universiti Putra Malaysia (UPM) in compliance with ethical research practice according to international standards. All participants included in the study provided written informed consent. Clinical trial number Not applicable. Competing interests The authors declare that they have no competing interests. Consent to publish Not applicable. Funding This research was not supported by any specific grant from funding agencies in the public, commercial or not-for-profit sectors. Author Contribution The work proposal concept and design, data collection and analysis as well as drafting of the manuscript was done by MYA and NNR. Revising the manuscript for important intellectual content and final approval was performed by MNS, MB and AFA. The manuscript was critically reviewed by all authors, who also read and approved the final version. Acknowledgements Not applicable Data Availability The data supporting the findings of this study are available upon reasonable request from the corresponding author. References Addai KN, Ng’ombe JN, Temoso O. (2024) Can farmer organization membership improve household food security and nutrition? Evidence from Northern Ghana. World Food Policy. https://doi.org/10.1002/wfp2.12076 Alam MM, Siwar C, Wahid ANM, Talib BA. Food security and low-income households in the Malaysian east coast economic region: An empirical analysis. Rev Urban Reg Dev Stud. 2016;28:2–15. https://doi.org/10.1111/rurd.12042 . 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9172675","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":626197263,"identity":"e5fda12f-00fb-47c4-8f96-b497610c744e","order_by":0,"name":"Mohamud Yasin Artan","email":"","orcid":"","institution":"Universiti Putra Malaysia","correspondingAuthor":false,"prefix":"","firstName":"Mohamud","middleName":"Yasin","lastName":"Artan","suffix":""},{"id":626197264,"identity":"127f45d7-2bef-4171-93e9-420895a731f6","order_by":1,"name":"Nurul Nadia Ramli","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEUlEQVRIie3RMUvDQBTA8RcOUoeTbPIk5jsEArFS0a+SI3BZEukoKBgQnpN2rZNfoVNxLATbJR/gxrh0U9rRQWnTWl2OpqPI/ae3/HjHPQCT6a9WAVi0HtvcWQ9sO4l+CfLDfFeSfxPwRw3kGLMpiucz76E1smcfKR4FKnsZwGVH5AelryMn/SREUcYB8Yg93g+Rh+pCKigTkbuplvhK2iiICYKIwf6KpKGyqGgiN4KcilmfSxL0a/LVSApBGDFWb/GxJvkWUk5ZW9AkIHy9Zd6SYPkuVTROAnJlV0sm0lJzuvKeenFhvQ1Pz527bKxm1x2v58YD/Tf/tDkN8NWlwIY97cN08c3QqnYlJpPJ9K9bAAGEXGU5TExnAAAAAElFTkSuQmCC","orcid":"","institution":"Universiti Putra Malaysia","correspondingAuthor":true,"prefix":"","firstName":"Nurul","middleName":"Nadia","lastName":"Ramli","suffix":""},{"id":626197265,"identity":"c90c3db2-6413-4509-ba77-66fcd1a49754","order_by":2,"name":"Mad Nasir Shamsudin","email":"","orcid":"","institution":"Universiti Putra Malaysia","correspondingAuthor":false,"prefix":"","firstName":"Mad","middleName":"Nasir","lastName":"Shamsudin","suffix":""},{"id":626197266,"identity":"2a1a7bac-8ef5-4320-8de8-d1c9fd8a52ed","order_by":3,"name":"Mark Buda","email":"","orcid":"","institution":"Universiti Putra Malaysia","correspondingAuthor":false,"prefix":"","firstName":"Mark","middleName":"","lastName":"Buda","suffix":""},{"id":626197267,"identity":"8b4bccd6-26f7-4932-9e87-17017759bf34","order_by":4,"name":"Abdullahi Farah Ahmed","email":"","orcid":"","institution":"Somali National University","correspondingAuthor":false,"prefix":"","firstName":"Abdullahi","middleName":"Farah","lastName":"Ahmed","suffix":""}],"badges":[],"createdAt":"2026-03-19 19:54:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9172675/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9172675/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107576370,"identity":"f26b54b4-f71c-4f8a-be84-b569c648cea3","added_by":"auto","created_at":"2026-04-22 20:27:57","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1562287,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMap of Somalia and its boundaries\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-9172675/v1/532e2218c698b9a7c5d75d4f.png"},{"id":107706143,"identity":"64420244-dc82-42b4-a713-f6def3f2510d","added_by":"auto","created_at":"2026-04-24 09:17:30","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":236454,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSchematic presentation of sampling procedure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSource: \u0026nbsp;(Mota et al. 2019; Wassie et al. 2023)\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-9172675/v1/deca5c78001fdb077a161421.png"},{"id":107705673,"identity":"015de499-8a46-47df-bb63-0a08508b0272","added_by":"auto","created_at":"2026-04-24 09:14:20","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":338702,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHFIAS Responses in Southern Somalia\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-9172675/v1/3f05eeab6cbb4b9a2a6e466b.png"},{"id":107576373,"identity":"a588486e-241e-451d-9b18-c2b9de48a7c2","added_by":"auto","created_at":"2026-04-22 20:27:57","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":91362,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHousehold Food Insecurity Access Prevalence\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-9172675/v1/6788174487764d3b8c34b763.png"},{"id":107705743,"identity":"ffaa502d-1297-43fe-906e-9da9576894a6","added_by":"auto","created_at":"2026-04-24 09:14:57","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":84864,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCategories of Household Hunger Scale (HHS)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-9172675/v1/0a9594b75a5375a9e81681d4.png"},{"id":108803486,"identity":"f10b2aa7-affb-453c-8353-4225b3b2bf2f","added_by":"auto","created_at":"2026-05-08 14:56:19","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2752250,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9172675/v1/154d56fd-77bc-43c0-868d-1283a35041e3.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Empirical Analysis of Household Food Insecurity and Hunger Among Rural Communities in Southern Somalia","fulltext":[{"header":"Background","content":"\u003cp\u003eFood security is a compound phenomenon that involves the physical, social, and economic access to enough, safe, and nutritious food to lead an active\u0026ensp;and healthy life (Coates et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Piperata et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). According to (Coates et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Maxwell et al. 2014; Moroda et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Pandey and Bardsley \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), food security definition is \u0026ldquo;when all people at all times have physical or economic access to sufficient, safe and nutritious food to meet their dietary needs and food preferences for an active and healthy life\u0026rdquo;. Food insecurity persists despite decades of international efforts to end hunger, and it is made worse by poverty, climate change, economic inequality, and conflicts (Maxwell et al. 2014; Mota et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Food insecurity continues to be one of the most pressing global problems of our era, impacting millions of people around the world. Nowadays, the current chronic hunger affects the lives of over 800\u0026nbsp;million people\u0026rsquo;s worldwide with a big impact of this\u0026ensp;issue on Sub-Saharan Africa (Mota et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). With hunger on the rise in low- to middle-income countries and\u0026ensp;across pockets of developed countries, the path to global food security is sounding pretty complex. Moreover, the\u0026ensp;promise of ending hunger by 2030 is becoming increasingly unattainable without immediate, extensive interventions that fortify food systems and bolster resilience across all echelons amidst enduring post-pandemic disparities, supply chain interruptions, and climate shocks (Demie and Gessese \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Addai et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAmong the main drivers of global food insecurity is population expansion. The global population was at 7.7\u0026nbsp;billion in 2019 and is projected to reach 8.5\u0026nbsp;billion in 2030 and further to 10.9\u0026nbsp;billion in 2100 (Ugal and Imam \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Sub-Saharan Africa (SSA) bears a disproportionate burden of this demographic shift, as the region is projected to account for more than half of global population growth by 2050 (UN \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Rapid population increase exerts immense pressure on food systems already constrained by limited resources, fragile economies, and volatile political environments. As a result, food security is particularly challenged in SSA due to persistent low agricultural productivity, deteriorating environmental conditions, and inadequate investments in agriculture. Unlike other regions of the world where undernutrition has declined, malnutrition in SSA remains stubbornly high, with the prevalence of undernourishment increasing in many fragile and conflict-affected states (FAO et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSomalia faces food insecurity due to cyclical droughts that further increase the level of famine risk and negatively impact food insecurity. For example, the Bay region continues to report very high rates of acute malnutrition and death, suggesting ongoing reduced food consumption and sustained nutritional deficits (IPC Global Partners \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Climatic shocks are exacerbated by long-term conflict and political fragility which prevents governance and institutions from robustly regulating food systems. As Maxwell and Fitzpatrick (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) highlight, in fragile states conflict frequently intensifies resource scarcity, through amongst other things, undermining markets, disrupting access to food, and constraining humanitarian access. Weak administration, recurring conflict and extreme climate events reinforce each other in creating conditions in Somalia that drive chronic dependency on external food assistance for millions of people.\u003c/p\u003e \u003cp\u003eDetermining food insecurity is an important variable that supports efforts to understand and, therefore, addressing challenges to food access, as well as informing appropriate policy interventions and the progress made towards the goal of eradicating hunger (Knueppel et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Kabalo et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The Household Food Insecurity Access Scale (HFIAS) and the Household Hunger Scale (HHS) are the two widely used tools that have proven to be effective in providing insights into household food\u0026ensp;insecurity (Regassa and Stoecker \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Nine standardized questions which included anxiety about the food supply, qualitative insufficiency in food consumption and insufficient quantity of food consumed were used to measure food insecurity using HFIAS developed by the USAID-funded Food and Nutrition Technical Assistance (FANTA) Project (Coates et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Regassa and Stoecker \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Pandey and Bardsley \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Berra \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The HHS assesses only the most severe hunger-related behaviours (Butaumocho and Chitiyo \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). These tools allow policymakers, researchers, and\u0026ensp;humanitarian organizations to analyze trends in food insecurity across cultural contexts and identify changes over time (Regassa and Stoecker \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). While HFIAS and HHS provide significant efficiency and\u0026ensp;practicality, concerns around biases from response and seasonal variability underscore the necessity for further validation. Accurate assessment of food insecurity is crucial to mitigate targeted interventions and to enhance protective factors in the food access and resilience of\u0026ensp;vulnerable communities (Berra \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis study aims to empirically assess the prevalence and severity of household food insecurity and hunger among rural households in Southern Somalia. With the high level of prevalence and recurrent nature of food insecurity in the region, identifying its multidimensional consequence is an\u0026ensp;important topic for intervention design and targeting. While there is increasing reliance on standardized food security measurement tools by global stakeholders, there are few empirical studies utilizing the Household Food Insecurity Access Scale (HFIAS) and Household Hunger Scale (HHS), particularly from Southern Somalia. It is in response to this evidence gap that the present study aims\u0026ensp;to produce household-level food security data, and test whether and how relevant standard tools \u0026ndash; in particular HFIAS and HHS \u0026ndash; are capturing food insecurity experiences in Somalia. Previous studies have examined food security in different regions, such as Ukonu et al. (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) on food accessibility and dietary diversity in Nigeria, Moroda et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) on food insecurity determinants in Ethiopia, and Nour and Abdalla (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) on food security in Sudan using HFIAS. This study provides to the current body of work on food insecurity measurement and will enable operationalizing targeted policies and programs to increase food accessibility in vulnerable\u0026ensp;populations.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eDescription of the study area\u003c/h2\u003e \u003cp\u003eThe study was conducted in Southern Somalia, specifically in Southwest State, Jubaland State, and Hirshabelle State as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, which are highly vulnerable to food insecurity due to recurring droughts, conflict, and economic instability. Southern Somalia covers various agro-ecological zones between approximately\u0026ensp;1\u0026deg;N\u0026ndash;6\u0026deg;N latitude and 41\u0026deg;E\u0026ndash;46\u0026deg;E longitude. It is bordered by Ethiopia to the west and Kenya to the southwest, while the Indian Ocean lies to the east. The area is a typical arid and semiarid climate with an average annual temperature ranging from 25 to 35\u0026deg;C. Rainfall is bimodal: the Gu season (April\u0026ndash;June) is the main rainy season,\u0026ensp;while the Deyr season (October\u0026ndash;December) provides secondary and relatively unreliable rainfall. The region has a mixed livelihood\u0026ensp;system that comprises pastoralism, agro-pastoralism, and riverine farming, with major agricultural density along the Juba and Shabelle rivers. Population density is dispersed, with urban centers like Baidoa, Kismayo, and Jowhar serving as\u0026ensp;economic epicenters. Recurrent climate shocks, combined with displacement from conflict\u0026ensp;and inadequate infrastructure, amplify food insecurity in the region, presenting an urgent need for study.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eResearch design and Sampling procedure\u003c/h3\u003e\n\u003cp\u003eA quantitative research design was adopted in the study and data was gathered based on face-to-face structured questionnaire\u0026ensp;with household respondents. The researcher incorporated various perspectives on food security among rural households using\u0026ensp;structured questionnaire data by including a broad analysis. Fieldwork was undertaken by six well-trained enumerators. The questionnaire comprised of questions regarding the household heads demographic and economic status: age, gender, marital status, education level, employment and income; the questionnaire also included the nine questions explained above that determine food insecurity for each month, thus allowing the calculation\u0026ensp;of the HFIAS.\u003c/p\u003e \u003cp\u003eStratified random sampling at the village level was used\u0026ensp;to select the sample as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e (Regassa \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Maxwell et al. 2014; Grobler and Dunga \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Mota et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The selected households were then asked to participate in the survey, and all respondents\u0026ensp;were allowed to respond in their native language. Sample households were\u0026ensp;selected at random from different livelihood zones. To ensure a representative sample size, the study employed the defined population proportion formula as determined by (Taro Yamane \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e1967\u003c/span\u003e; Dessalegn \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Mota et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2019\u003c/span\u003e):\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:n=\\:\\frac{N}{1+N\\:{\\left(e\\right)}^{2}}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere n is the sample size, N is the population size, e is the Margin of error and 1\u0026thinsp;=\u0026thinsp;probability of the event occurring.\u003c/p\u003e \u003cp\u003eApplying this formula, the sample size was calculated as follows:\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\:n=\\:\\frac{N}{1+N\\:{\\left(e\\right)}^{2}}=\\:\\frac{\\text{1,091,524}}{1+\\text{1,091,524}\\:{\\left(0.05\\right)}^{2}}=\\frac{\\text{1,091,524}}{\\text{2,729.81}}\\:=400$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eAfter adjusting for the non-response and incomplete responses, the final sample size was adjusted to 420 households.\u003c/p\u003e \u003cp\u003eThis study used a multistage sampling\u0026ensp;method to select respondents. As illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, the first phase of this study employed a deductive approach to\u0026ensp;purposively select the context of Southern Somalia, which has been identified as the most vulnerable geographic region to food insecurity as a consequence of climate change, environmental degradation, and widespread poverty. In the second phase, Stratified Random Sampling was used, the study area was divided into three strata based on their respective states (Hirshabelle,\u0026ensp;Southwest, and Jubaland), which had different livelihood zones. The purposively selected districts from each of the states\u0026ensp;were Jowhar (Hirshabelle), Baidoa (Southwest), and Kismayo (Jubaland) during the third phase, based on their livelihood strategies and a high variety of their vulnerability to food insecurity and poverty. The fourth phase involved randomly selecting four villages\u0026ensp;within each district to capture variability in food security conditions. Lastly, in the fifth phase, Simple Random Sampling was utilized to choose households from each village which resulted in the total sample size of 420\u0026ensp;farming households (Mayanja et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Dessalegn \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Wassie et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The structured sampling process provided a\u0026ensp;representative and minimized the opportunity for selection bias ensuring a statistically significant evaluation of household food insecurity and resilience.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSource: (Mota et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Wassie et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u003c/p\u003e\n\u003ch3\u003eHousehold Food Insecurity Measurements\u003c/h3\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eHousehold Food Insecurity Access Scale (HFIAS)\u003c/h2\u003e \u003cp\u003eThe Household Food Insecurity Access Scale (HFIAS), developed by the Food and Nutrition Technical Assistance II (FANTA) project in collaboration with other organizations, was used to assess household food insecurity (McDonald et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Musemwa et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Bahta \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The HFIAS has nine primary questions that have been validated in many countries to\u0026ensp;accurately capture food security status in households across diverse cultural contexts as shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. These items are derived from respondents\u0026rsquo; memory of how often they have not had enough food and the experiences associated with this shortfall over the\u0026ensp;prior 30 days. The HFIAS data provides important\u0026ensp;information about the prevalence of food insecurity in households (access) and can be used to monitor changes in food security status for a population across time frames.\u003c/p\u003e \u003cp\u003eThe questionnaire was then translated\u0026ensp;into Somali for greater clarity and relevance to participants. Subsequently, pilot testing of the translated items for comprehensibility and accuracy was\u0026ensp;performed with five households in each district ensuring items were not misunderstood. It excluded these households from\u0026ensp;the core analysis. During the pilot study, all nine HFIAS questions were asked and the replies accurately recorded. Respondents had the opportunity to discuss whether they had understood properly each item, that its wording was acceptable for their culture, and that it was unambiguous with respect to local situations. This approach enabled the researcher to test aspects of accuracy, clarity and cultural appropriateness of the HFIAS tool in a Somali context, which supports that the final household survey was reliable. The data was further analyzed and required changes were worked\u0026ensp;on before crystallizing the questionnaire into an improved\u0026ensp;and revised module.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHFIAS questions\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHFIAS Question\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDid you worry that your household would not have enough food?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWere you or any household member not able to eat the kinds of foods you preferred because of a lack of resources?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDid you or any household member eat just a few kinds of food day after day because of a lack of resources?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDid you or any household member eat food that you did not want to eat because of a lack of resources to obtain other types of food?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDid you or any household member eat a smaller meal than you felt you needed because there was not enough food?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDid you or any household member eat fewer meals in a day because there was not enough food?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWas there ever no food at all in your household because there were no resources to get more?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDid you or any household member go to sleep at night hungry because there was not enough food?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDid you or any household member go a whole day without eating anything because there was not enough food?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eSource: (Kabalo et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe nine standardized items of the Household Food Insecurity Access Scale (HFIAS) focus on a broad range of experience-based measures of food insecurity, from anxiety to actual reduction in amount consumed. These questions are designed to mirror three main sub-dimensions including uncertainty about and concerns for food supply (Q1), poor-quality/low dietary diversity (Q2\u0026ndash;Q4) and not eating sufficient amounts of food (Q5\u0026ndash;9). By measuring these continuities and gradations, the approach allows to gauge not just prevalence but also severity of food insecurity within households (Coates et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Deitchler et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). The questions on anxiety, preference and dietary monotony as part of the food security module indicate that lack of access to enough food is not simply an issue of physical shortage but also encompasses psychological and social deprivation (Maxwell et al. 2014). Meanwhile, the escalation in the question sequence to any reduction of meals, experienced hunger and complete food absence signals increased severity of the situation and thus can be used as a proxy index to categorize household as either food-secure; mildly, moderately or severe food-insecure (Swindale and Bilinsky \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). As such, the HFIAS scale conceptualizes food insecurity in a manner that is generalizable across cultures and context-sensitive, rendering it very well-suited to study rural Somali households where shocks, poverty and conflict frequently impede access to food.\u003c/p\u003e \u003cp\u003eTo calculate the HFIAS score per household,\u0026ensp;the frequency-of-occurrence responses were summed, and each response was pre-coded with the following values [0\u0026thinsp;=\u0026thinsp;no, 1\u0026thinsp;=\u0026thinsp;rarely, 2\u0026thinsp;=\u0026thinsp;sometimes, 3\u0026thinsp;=\u0026thinsp;often]. This\u0026ensp;allowed a maximum score of 27. A higher score reflects a greater level of food insecurity with respect to access, while a lower score indicates to a lesser degree of food insecurity or better access to food for the\u0026ensp;household.\u003c/p\u003e \u003cp\u003eResponses to nine questions (Q1-Q9) on the occurrence of food insecurity (FI) and the corresponding frequency-of-occurrence responses\u0026ensp;were used to assess household food insecurity (Musemwa et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Demie and Gessese \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Addai et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Using these responses, households were categorized into\u0026ensp;four levels of food security. A household was considered food-secure if the score\u0026ensp;on the first FI frequency-of-occurrence question (Q1) was \u0026lsquo;0\u0026rsquo; or \u0026lsquo;1\u0026rsquo;, and on Q2 to Q9 was \u0026lsquo;0\u0026rsquo;. The data was regarded as mildly food-insecure when the first FI frequency item scored\u0026ensp;\u0026lsquo;2\u0026rsquo; or \u0026lsquo;3\u0026rsquo;, or if Q2 to Q4 scored \u0026lsquo;1\u0026rsquo;, while Q5 to Q9 remained as \u0026lsquo;0\u0026rsquo;. A household was\u0026ensp;considered moderately food-insecure if Q3 or Q4 scored \u0026lsquo;2\u0026rsquo; or \u0026lsquo;3\u0026rsquo;, or if Q5 or Q6 scored \u0026lsquo;1\u0026rsquo; or \u0026lsquo;2\u0026rsquo; but Q7 to Q9 scored \u0026lsquo;0\u0026rsquo;. If Q5 or Q6 scored \u0026lsquo;3\u0026rsquo;, or if Q7 to Q9 scored \u0026lsquo;1\u0026rsquo;, \u0026lsquo;2\u0026rsquo;, or \u0026lsquo;3\u0026rsquo;, then a household was considered as severely food-insecure household (Kabalo et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Demie and Gessese \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe study used a validated indicator of food security\u0026mdash;Household Food Insecurity Access Scale (HFIAS)\u0026mdash;to classify households into distinct categories based on specific threshold values, as demonstrated in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The HFIAS identifies populations in four categories: food secure (with scores between 0\u0026ndash;1), mildly food insecure (with scores between 2\u0026ndash;8), moderately food insecure\u0026ensp;(with scores between 9\u0026ndash;16), and severely food insecure (with scores between 17\u0026ndash;27) households. This classification serves as an effective property to characterize households' observations and experiences related to food access, quality, consumption, and uncertainty or worry\u0026ensp;about food availability.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eClassification and Thresholds for Household Food Insecurity Access Scale (HFIAS)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndicator\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory number\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCategory description\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRange\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003eHFIAS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFood secure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u0026ndash;1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMildly food insecure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u0026ndash;8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModerately food insecure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9\u0026ndash;16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSeverely food insecure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17\u0026ndash;27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cb\u003eSource\u003c/b\u003e: (Kabalo et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Demie and Gessese \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eHousehold Hunger Scale (HHS)\u003c/h3\u003e\n\u003cp\u003eIn this study, food insecurity was assessed\u0026ensp;by the Household Hunger Scale (HHS), which reflects the lack of food in a household and concerns about having enough and sufficiently diverse food. The HHS consists of three main\u0026ensp;occurrence questions and three additional frequency-of-occurrence questions corresponding to those occurrence questions. According to (Butaumocho and Chitiyo \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Berra \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), HHS is based on the following three questions:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eDuring the last [4 weeks/30 days], was there ever no food to eat of any kind in your house because of lack of resources to get food?\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eDuring the last [4 weeks/30 days], did you or any household member go to sleep at night hungry because there was not enough food?\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eDuring the last [4 weeks/30 days], did you or any household member go a whole day and night without eating anything at all because there was not enough food?\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eThis method provides a direct measure of severe food deprivation, which can offer important information on the depth and severity\u0026ensp;of hunger faced by households (Butaumocho and Chitiyo \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Respondents who answered \"yes\" to any of the Household Hunger Scale (HHS) occurrence questions were asked follow-up question to\u0026ensp;determine the frequency-of-occurrence of the reported condition in the past four weeks. Responses, thus, ranged from rarely (one or two times), sometimes\u0026ensp;(three to ten times), or often (more than ten times (Xu et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This method gave\u0026ensp;a better sense of the severity and duration of food insecurity in the household.\u003c/p\u003e \u003cp\u003eHousehold data on hunger were scored using the Household Hunger Scale (HHS), and numerical\u0026ensp;values were assigned to each response. For every \u0026ldquo;no\u0026rdquo; response to the\u0026ensp;three core questions, a score of 0 was assigned. A score of 1 was given for a \u0026ldquo;yes\u0026rdquo; if the reported\u0026ensp;frequency of occurrence derived from the questionnaire was considered rarely (code 1) or sometimes (code 2). A \"yes\" at the level of often (code 3)\u0026ensp;was given a score of 2 (Demie and Gessese \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Xu et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Total HHS score was calculated as the sum of the three individual questions, and ranged from 0 to 6, with higher scores indicating higher levels of food insecurity and\u0026ensp;more severe limitations in household food access.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e displays household classification based on Household Hunger Scale (HHS), which is an experience-based scale that is commonly used in assessing food security. The HHS assigns households into three categories: little to no hunger (0\u0026ndash;1), moderate hunger (2\u0026ndash;3), and severe hunger (4\u0026ndash;6). This continuum describes the frequency and severity of experiences related to hunger, which can fluctuate from occasional worries about access to food to chronic or extreme deprivation (Ballard et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Maxwell et al. 2013). The tool is particularly important in fragile and food insecure contexts, including Somalia where repeated shocks continuously erode household access to food and its coping mechanisms. Through distinction of moderate and severe hunger, HHS allows policy makers and humanitarian actors to better target those most at risk and most in need for specific interventions over-and-above caloric provision necessary for sustained life by addressing long-term vulnerability and resilience gaps (Deitchler et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Furthermore, its cross-cultural validation makes it a powerful tool for analysis comparison between areas and also increases the applicability for local planning and trends in global food security monitoring.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eClassification and Thresholds for Household Hunger Scale (HHS)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndicator\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory number\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCategory description\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRange\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eHHS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLittle to no hunger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u0026ndash;1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModerate hunger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u0026ndash;3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSevere hunger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u0026ndash;6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eSource: (Saaka \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Kolog et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eAnalysis of the data was performed by\u0026ensp;using IBM SPSS Statistics (Version 31.0.1.0.). Frequencies and percentages were employed\u0026ensp;using descriptive statistics to present household demographic, socio-economic characteristics and food insecurity indicators. The severity and prevalence of\u0026ensp;household food insecurity in Southern Somalia were measured using the Household Food Insecurity Access Scale (HFIAS) and the Household Hunger Scale (HHS) for rural areas. These instruments provided a way to classify the level of food insecurity and\u0026ensp;discover trends among different household characteristics. Interpretations of the results\u0026ensp;were used to guide policy and intervention development.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eSocio-demographic characteristics\u003c/h2\u003e \u003cp\u003eThe socio-demographic characteristics of the surveyed households were described in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, which offers essential context for understanding food security outcomes and resilience trends. The characteristics of head of household such as gender, age, marital status, the highest education level achieved by\u0026ensp;the household head and the employment status were examined alongside income levels of the household. These variables are key to understanding the ways in which social and economic characteristics influence household vulnerability, capacity for coping and access to food.\u003c/p\u003e \u003cp\u003eThe data shows that age-wise distribution of household heads shows that 38.6% household head belong to the age group of\u0026ensp;30\u0026ndash;39 years, and 24.5% household head belong to the age group of 40\u0026ndash;49 years. Food\u0026ensp;insecurity is compounded as older heads of households experience low functional capacity, restricting their participation in income-generating activities and disrupting economic productivity. When it\u0026ensp;comes to gender, data shows that 76.9% of households were male-headed while 23.1% were female-headed households. Female-headed households were\u0026ensp;especially vulnerable to food insecurity because of their limited access to land, credit, and agricultural resources.\u003c/p\u003e \u003cp\u003eWith regards to marital status, 76.9% of heads of household\u0026ensp;are married, and 11.9% are divorced. Households with married partners,\u0026ensp;which have a larger labor force, were potentially able to increase food security, but also have greater dependency burdens. Food\u0026ensp;security is primarily influenced by education, with 40.7% of household heads having no formal schooling while 31.4% receiving informal education. Given that low education levels limit access to employment and income diversification, this negatively impacts the ability to access food, leading to a\u0026ensp;high risk of food insecurity.\u003c/p\u003e \u003cp\u003eThe results from the employment status analysis show that 67.6% of household heads are engaged in on-farm activities only, and only 30.2% are engaged\u0026ensp;in both on-farm and off-farm work. This dependence on\u0026ensp;farming makes it susceptible to climate shocks. The household income findings show that 45.6% earned between US\u003cspan\u003e$\u003c/span\u003e100\u0026ndash;199\u0026ensp;per month, while 28.8% earned less than US\u003cspan\u003e$\u003c/span\u003e99, indicating widespread poverty and economic constraints. Lower-income households which struggle to be able\u0026ensp;to buy enough food are more food-insecure.\u003c/p\u003e \u003cp\u003eThe socio-demographic factors examined in this study are important for understanding household vulnerability and resilience to food insecurity in southern Somalia. The study specifically addresses its aim of identifying the socioeconomic determinants that affect household food access and coping capacity in terms of gender, age, marital status, level of education, employment status and income. The importance of female-headed households as more vulnerable also corresponds to the prior literature highlighting that there is a gender disparate access to land, credit, and resources throughout Sub-Saharan Africa (Peterman et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Doss et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Likewise, the association between low education level and food insecurity is in line with evidence proving that limited human capital impedes diversification of livelihoods as well as adaptive capacity (Smith and Haddad \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). The heavy reliance on on-farm activities highlights how fragile are the rural livelihoods in fragile states, where climate-induced shocks instantly lead to food insecurity (Mekonnen et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Furthermore, high prevalence of low incomes also underscores the connection between structural poverty and food insecurity as reported by Feleke et al. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) who suggest that poor households must cope with limited purchasing power, resulting in low food quality and diversity. On the whole, these findings validate previous research and contribute to that body of work while situating it within Somalia, where conflict, climate uncertainty, and fragile institutions amplify vulnerabilities. The findings further buttress the need to prioritize and synergize across education, gender equity, livelihood diversification, and income generation for both resilience and food insecurity reduction.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSocio-demographic characteristics of the study population\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18\u0026ndash;29 yrs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u0026ndash;39 yrs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40\u0026ndash;49 yrs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50\u0026ndash;59 yrs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge; 60 yrs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e323\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e76.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eMarital Status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDivorced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e319\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e76.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSeparated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWidowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInformal education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo Schooling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e40.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e17.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTertiary education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eEmployment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOff-farm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOn-farm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e284\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e67.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnemployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eIncome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u0026ndash;99 USD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100\u0026ndash;199 USD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e200\u0026ndash;299 USD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge; 300 USD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eHousehold Food Insecurity Access Scale (HFIAS)\u003c/h2\u003e \u003cp\u003eThe Household Food Insecurity Access Scale (HFIAS) is commonly employed to measure food insecurity, based on the notion that a household experiences food insecurity\u0026ensp;during certain periods if a member of the household cannot limit the quantity or quality of food consumed or that a member has to depend on other strategies to cope with food shortages (Coates et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Ukonu et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows the response distribution to the nine HFIAS questions which measure varying dimensions of household food insecurity among the 420 households sampled for South Somalia. Responses to that question of severity further indicate a progressive increase in food insecurity as experiences become more extreme and aligned with hunger, compared with experiences that are\u0026ensp;more associated with access to food. The first few questions in the table show a relatively high\u0026ensp;percentage of households that frequently worry that food will not be available to them and are unable to buy foods they like and need because they cannot afford them. A few respondents confirmed this lack of diversity in food groups and said they were obliged to eat less appealing foods due to a deficit of\u0026ensp;resources. The total number of households reporting food insecurity, however, varied based on how severe the food insecurity was among those households, with a slight increase in the number of households that reported they had to eat fewer meals a day or go to sleep hungry and the number of households that reported they had to reduce the size of their\u0026ensp;meals in the last 30 days. The various respondents in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e cover the\u0026ensp;last set of HFIAS questions, which represent the most severe cases of food insecurity, where households simply go to bed without eating or, in the worst-case scenario, for an entire day and night. The extremely high proportion of \u0026ldquo;yes\u0026rdquo; responses to these extreme indicators indicates that many of the households in Southern Somalia are experiencing chronic food insecurity and turning to coping strategies typically associated with\u0026ensp;crisis levels of food insecurity.\u003c/p\u003e \u003cp\u003eThe results reported in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e offer important information on the complexity of food insecurity within rural households in Southern Somalia. The patterns suggest a continuum from worry about having enough food to severe deprivation, which is consistent with the theoretical model of food insecurity addressed as a progressive process (Coates et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Maxwell et al. 2014). The higher proportion of extreme responses (e.g., decreasing meal size, skipping meal, or fasting for a whole day) demonstrates that households are chronically exposed and already stretching their limited ability to adjust; this is also in line with research by Mekonnen et al. (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e); Woleba et al. (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). These results show that food-insecurity in Somalia is not a short-term issue, but is more fundamentally structural, with underlying causes related to poverty, climatic stress and market dependency. The results highlight the importance of including resilience in responses to repeated cycles of hunger, through maximizing access opportunities and options, promoting livelihood diversity amongst households, and ensuring food systems at household level are strong.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eQuestions of the Household Food Insecurity Access Scale and affirmatively answered questions by the study population in Southern Somalia (n\u0026thinsp;=\u0026thinsp;420). In the past four weeks\u0026hellip;\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHousehold Food Insecurity Access Scale\u0026nbsp;Questions\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDid you worry that your household would not have enough food?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e412\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e98.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWere you or any household member not able to eat the kinds of foods you preferred because of a lack of resources?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e96.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDid you or any household member have to eat a limited variety of foods due to a lack of resources?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e393\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e93.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDid you or any household member have to eat some foods that you really did not want to eat because of a lack of resources to obtain other types of food?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e386\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e91.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDid you or any household member have to eat a smaller meal than you felt you needed because there was not enough food?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e374\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e89.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDid you or any household member have to eat fewer meals in a day because there was not enough food?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e368\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e87.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWas there ever no food to eat of any kind in your household because of lack of resources to get food?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e363\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e86.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDid you or any household member go to sleep at night hungry because there was not enough food?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e309\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e73.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDid you or any household member go a whole day and night without eating anything because there was not enough food?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e44.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the percentage of households responding 'Yes' to each of the nine HFIAS questions (Q1\u0026ndash;Q9), alongside the proportion of households that reported 'No' responses and illustrates a clear trajectory of food insecurity among the surveyed households in Southern Somalia. The results follow a similarly stark trajectory from anxiety about access to food,\u0026ensp;to hunger, to severe rationing and deprivation. Q1 and Q2\u0026ensp;at first show that a strong proportion of households worry that food is available at the cost they need, and they can\u0026rsquo;t afford the food they need. This hearkens to perpetual financial volatility,\u0026ensp;restricting access to varied and nutritious diets. Q3 and Q4 show a decline in food quality, characterized by many households eating a small number of foods\u0026ensp;widely and relying more often on less preferred foods as household resources tighten. As food insecurity increases, Q5 and Q6 indicate that many households reduce meal\u0026ensp;size and the number of meals eaten a day as coping strategies. The prevalence of \u0026ldquo;sometimes\u0026rdquo; and \u0026ldquo;often\u0026rdquo; responses in\u0026ensp;those categories is a signal of deepening food shortages and growing vulnerability. The findings are alarming, in particular the most severe indicators, Q7, Q8 and Q9, which point to cases of extreme food deprivation, whereby a significant proportion of households go to\u0026ensp;bed hungry, or those that do not have anything to eat for a whole day and night. The predominance of \u0026ldquo;often\u0026rdquo; and \u0026ldquo;sometimes\u0026rdquo; among such responses is testament to\u0026ensp;chronic hunger and malnourishment as well as a growing food crisis.\u003c/p\u003e \u003cp\u003eResults from the HFIAS provide important information about the multi-dimensional aspects of food insecurity in rural households in Southern Somalia. The transition from food-related anxiety to extreme deprivation indicates the chronic and cyclical nature of hunger in insecure livelihoods. These findings directly contribute to the objective of the present study, which is to determine the prevalence and severity of food insecurity based on experience-based indicators. The response trajectory from low diet diversity to skipping meals is symptomatic of structural poverty and precarious food access and confirms patterns found in similar contexts elsewhere in Sub-Saharan Africa (Coates et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Maxwell et al. 2014). The high proportion of extreme coping measures, such as going to bed without food and fasting a whole day, is consistent with another study from Mekonnen et al. (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) who found that experiencing drought and market shocks repeatedly increases the depth of food insecurity. Yet, the current study builds on previous work by affirming HFIAS validity in a Somali context and its cultural appropriateness and empirical robustness to measure local experiences of food insecurity. These results show that food insecurity is more than resources scarcity but is also rooted in systemic vulnerability.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows the levels of food insecurity among Households in Southern Somalia are categorized into four levels of food in/secure groups, namely food secure, mildly food insecure, moderately food insecure, and severely food insecure groups. The HFIAS addresses the access dimension and reflects information on\u0026ensp;severity and prevalence of food insecurity in a given population (Addai et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The findings shed light on the grim reality of households, where only a small percentage have stable access to food, while the rest face moderate to severe levels of food insecurity. Food secure households (3.57%) were households that, at all times, had access to enough food for an active, healthy life and had no or very limited\u0026ensp;anxiety about availability of food; and little or no risk of hunger. But mildly food insecure households (5.95%) face some challenges, such as necessary reduction in the food variety or quality, but are\u0026ensp;still able to maintain food availability. These households are not in immediate crisis, but they are clearly at risk of crisis due to external\u0026ensp;shocks. A large share (35.00%) represents households that are moderately food insecure and often experience reduced\u0026ensp;food intake, eating fewer meals, or other dietary changes. This group is under pressure economically and environmentally, so they are especially\u0026ensp;vulnerable to additional deterioration in food security. The most concerning category is severely food\u0026ensp;insecure households (55.48%) that have chronic hunger, severely reduced meal frequency, and people who go whole days without food. Such a high prevalence in this\u0026ensp;category is indicative of a serious food crisis in the region.\u003c/p\u003e \u003cp\u003eResults from the analysis of HFIAS depict a chilling reality on household level food insecurity in Southern Somalia, its prevalence as well the extent and degree across the different categories. The fact that the vast majority of moderate and severe food-insecure households were diagnosed underlines a structural and chronic food crisis, which mirrors the severe economic development and climatic vulnerabilities found in this region (Mekonnen et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Woleba et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). These findings directly indicates that for many households, there has been no improvement in food access due mainly to poverty, environmental shocks, as well as limited livelihood diversification. The results align with a previous study conducted by Alam et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) and Asesefa Kisi et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), which also highlighted a high prevalence of moderate to severe food insecurity among agrarian households residing in fragile and vulnerable contexts. Yet, the present study broadens this perception by demonstrating that even somewhat food-insecure households are highly vulnerable to crises in the face of shocks.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eHousehold Hunger Scale (HHS)\u003c/h2\u003e \u003cp\u003eThe Household Hunger Scale (HHS) is a tool commonly used to\u0026ensp;measure the severity of hunger, specifically by indicating to what extent households are deprived of food (Tambo et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Responses\u0026ensp;were scored numerically in order to classify each household type across experiences of hunger. Figure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e classifies households into two levels of\u0026ensp;household hunger: little to no and moderate household hunger and vividly illustrates the amount of food deprivation in Southern Somalia. The results show that 73.57% of households fall into the moderate household hunger category, which defines households reporting frequent reductions\u0026ensp;in meal size, going to bed hungry or not eating for an entire day. This implies that a large percentage of the population suffers from\u0026ensp;chronic food shortages reflecting high vulnerability to economic instability, seasonal variations, and climate-related shocks. At the same time, only 26.43% of households reported no or very little household hunger \u0026mdash; a sign\u0026ensp;of some level of food security. However, considering the broader trends of food insecurity observed throughout the region,\u0026ensp;this group would still be at risk of falling into food insecurity in the event of worsened external conditions.\u003c/p\u003e \u003cp\u003eThe results of the study based on HHS demonstrate an important insight for understanding nature and conditions that drive household food insecurity in Southern Somalia to go beyond simple classification to ascertain structural features. This reflects the aim of this study to comprehend not just food insecurity status, but rather the context in which it occurs, and demonstrates that hunger is no temporary problem, but a manifestation of long-term risk exposure combined with an insufficient capacity to cope. The implications of these results indicate that resilience promotion approaches need to be comprehensive integrated interventions, which reinforce increased access to productive assets, social safety nets and climate-smart agriculture practices in order to achieve a sustainable positive cycle from vulnerability.\u003c/p\u003e \u003cp\u003eResults from the HHS shed important light on the severity, and longevity of hunger among households in Southern Somalia, which verifies that food insecurity has a long-term character. The over representation of households classified into the moderate hunger category is indicative of structural poverty, narrowness in livelihood diversification and repeated exposure to climate-induced shocks mainly drought that depletes food access (Maxwell et al. 2014; Mekonnen et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). These findings are particularly relevant to the aim of this study looking that hunger in Somalia is not just an occasional event, but instead a chronic consequence of structural vulnerability. The findings are in line to studies of Deitchler et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2010\u003c/span\u003e); Maxwell et al. (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2020\u003c/span\u003e); Woleba et al. (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), for example, who show that high HHS scores are directly associated with dependence on rain-fed agriculture and poor market functioning. Nonetheless, this research adds new empirical evidence in the rural Southern Somalia context where chronic food insecurity remains despite of humanitarian support. These results reinforce the urgency for resilience-based interventions to break the cycle of chronic hunger and vulnerability.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eRelationship Between Household Head Gender and Food Insecurity Measures\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e shows the HFIAS and HHS scores by household head\u0026ensp;gender, highlighting that gender is a major predictor of food insecurity and hunger in the household. Findings show that female-headed household has higher levels of food insecurity and hunger\u0026ensp;than male-headed households, reflecting wider gender inequalities in accessing food, financial stability, and resilience to shocks. When comparing male- to female-headed households, female-headed households show a higher average HFIAS score and a higher\u0026ensp;proportion of households with severe food insecurity. This indicates increased incidence of food insecurity, with women-led households\u0026ensp;potentially experiencing limited food access, poor food quality and not enough to eat. Poorer female-headed households often have limited access to land tenure, financial resources and\u0026ensp;agricultural inputs that contribute to food insecurity.\u003c/p\u003e \u003cp\u003eLikewise, HHS findings show that\u0026ensp;households headed by females are more likely to report experiencing moderate to severe hunger than their male-headed counterparts. This suggests women-headed households are more likely to cut\u0026ensp;down on meals, going hungry, and employing coping strategies like meal skipping or eat smaller meals. The economic and food security vulnerability of female-headed households\u0026ensp;is further exacerbated by the structural barriers they face around credit access, employment, and social networks. These findings demonstrate a critical need for gender-targeted action in Southern Somalia, including\u0026ensp;targeted livelihood support for women, enhanced access to financial services, and agricultural empowerment programs. Reducing\u0026ensp;food insecurity and hunger among vulnerable groups, such as female-headed households, requires addressing gender-based inequalities within food security policies and development programs.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHousehold Head Gender and Its Impact on Food Insecurity and Hunger Levels in Southern Somalia\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFood insecurity status\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHousehold Food Insecurity Access Scale (HFIAS)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFood Secure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMildly Food Insecure Access\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerately Food Insecure Access\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e147\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeverely Food Insecure Access\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e179\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e233\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e323\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e420\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHousehold Hunger Scale (HHS)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLittle to no household hunger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e111\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate household hunger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e309\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSevere household hunger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e323\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e420\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis research explored the causes and prevalence of food insecurity in rural areas of Southern\u0026ensp;Somalia, using the Household Food Insecurity Access Scale (HFIAS) and the Household Hunger Scale (HHS) as major instruments of analysis. The HFIAS, a validated proxy for measuring food insecurity at the household level, gave a\u0026ensp;full view of how households in the study area perceive various experiences of food insecurity including uncertainty and anxiety over food availability to inadequacy of dietary quality and quantity. The progression of the HFIAS questions indicated an incremental\u0026ensp;deterioration of household food access, starting with pervasive worry about whether food was available and affordable, followed by compromises on the quality of food consumed, and then engaging in severe coping strategies such as skipping meals, going to bed hungry, or enduring entire days without food. These results highlight the complex multi-faceted food insecurity situation, and especially in areas susceptible to\u0026ensp;climate variability, economic vulnerability, and poor market infrastructure.\u003c/p\u003e \u003cp\u003eThe sum of the responses to the HFIAS items not only served as an indicator of the severity of food insecurity but also as a\u0026ensp;basis for classification of households by tier of food security. The categories ranged from food-secure households, who had no major problems\u0026ensp;in obtaining food, to those classified as mildly insecure, moderately insecure, and, most disturbingly, severely food insecure. Households classified\u0026ensp;as severely food insecure revealed patterns of hunger, meal skipping, and entire lack of food consistent with systemic failure of food access. These classifications mirror wider structural impediments in the Somali context, with livelihood options being relatively narrow,\u0026ensp;value chain development being limited, and continued susceptibility to climate shocks. In this respect, the HFIAS is an important diagnostic\u0026ensp;instrument, not just saying that people are food insecure, but how and to what extent they are affected, and one which allows a more nuanced policy and programmatic response.\u003c/p\u003e \u003cp\u003eThe HHS results supplemented the results of the HFIAS by providing\u0026ensp;an explicit focus on the severity of hunger within households. The HHS, which measures behavioral and experiential manifestations of hunger, found that a significant number of households are experiencing moderate forms\u0026ensp;of hunger, where cutting a meal, sleeping without eating, and spending the entire day without eating are frequent experiences. While a lower share of HHs reported no or low hunger, the context in which hunger is low indicates that many households are\u0026ensp;probably at risk of food insecurity if there is a worsening of shocks. The reinforcing relationship between HFIAS and HHS measures emphasizes about a chronic emergency of limited access to food\u0026ensp;that is limited not only in terms of the quality of types of foods consumed and their variety, but the actual sufficiency of caloric consumption. These findings indicate that food deprivation in southern Somalia\u0026ensp;is not occasional or seasonal but persists as a chronic systemic inadequacy.\u003c/p\u003e \u003cp\u003eThe\u0026ensp;results indicate that there are noticeable differences between males and females in the levels of food insecurity and hunger among rural households. Male head households have presence in all four food insecurity categories\u0026ensp;(including those who are food secure and mild insecure), thus showing relatively wider access to food. All female-headed households are found in the moderate and severe food insecurity, none are food-secure or mildly food\u0026ensp;insecure. This pattern underscores a particularly vulnerable group of female-headed households\u0026ensp;that may be at increased risk for both limited access to food and more severe food insecurity. The same tendency is observed in the HHS\u0026ensp;outcome. Most male-headed households are in the little or no hunger category, which contrasts with nearly\u0026ensp;all female headed households that fall in the moderate hunger classification. The results indicated that gender is an important determinant for household\u0026rsquo;s food security status and that female headed households suffer from structural constraints, such as limited productive asset access, less income opportunities and socio-cultural restrictions, which increase\u0026ensp;their vulnerability to food insecurity and hunger. To be able to design inclusive and\u0026ensp;effective food security interventions in Southern Somalia, there is a need to address these gendered differences.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe results of this study indicate an alarming degree of household food\u0026ensp;insecurity and hunger among rural groups in Southern Somalia. Examination of the HFIAS and HHS show that a significant proportion of households are moderately or severely food\u0026ensp;insecure. The high prevalence of extreme responses, such as decrease in meal size, skipping meals, going to bed without food or fasting for a day are\u0026ensp;indicative of chronic and structural dimensions to food deprivation in the region. These trends are closely linked with restricted access to livelihood opportunities, low dietary diversity, poverty and recurring\u0026ensp; exposure of climate-induced shocks. Households headed by females in particular are disproportionately affected, with both a greater level of food\u0026ensp;insecurity and prevalence of hunger, highlighting the gender differentiated nature of food access and vulnerability within Somalia.\u003c/p\u003e \u003cp\u003eGoing forward, an over-arching approach to increase long-term resilience and decrease chronic\u0026ensp;hunger is required. Developing and implementing gender-sensitive policies into national food security frameworks, community-based early warning and\u0026ensp;response systems, strengthening institutional capacity for monitoring food security using standardized tools such as HFIAS and HHS. Policymakers and development actors need to move from\u0026ensp;short-term relief to long-term solutions addressing the underlying causes of food insecurity including poverty, inequality, environmental degradation and fragile rural economies. These results reinforce the importance of using evidence to design and implement more effective\u0026ensp;strategies for improving food security and reducing hunger in Southern Somalia.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eUPM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eUniversiti Putra Malaysia\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHFIAS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHousehold Food Insecurity Access Scale\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHHS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHousehold Hunger Scale\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eUSAID\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eUnited States Agency for International Development\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFANTA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFunded Food and\u0026ensp;Nutrition Technical Assistance\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eEthics approval\u003c/h2\u003e \u003cp\u003e This study was conducted in compliance with all applicable ethical guidelines\u0026ensp;emphasizing safety, respect, and the rights of the participants. The methodology of this study has\u0026ensp;been approved by the Ethics Committee for Research Involving Human Subjects, Universiti Putra Malaysia (UPM) in compliance with ethical research practice according to international standards. All participants\u0026ensp;included in the study provided written informed consent.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eClinical trial number\u003c/h2\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eConsent to publish\u003c/h2\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis research was not supported by any specific grant from funding agencies in the public, commercial or not-for-profit sectors.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eThe work proposal concept and design, data collection and analysis as well as drafting of the\u0026ensp;manuscript was done by MYA and NNR. Revising the manuscript for\u0026ensp;important intellectual content and final approval was performed by MNS, MB and AFA. The manuscript was critically\u0026ensp;reviewed by all authors, who also read and approved the final version.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eNot applicable\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data supporting the findings of this study are available upon reasonable request from the corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAddai KN, Ng\u0026rsquo;ombe JN, Temoso O. (2024) Can farmer organization membership improve household food security and nutrition? Evidence from Northern Ghana. 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Household food security, determinants and coping strategies among small-scale farmers in Kedida Gamela district, Southern Ethiopia. J Agric Food Res. 2023;12. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jafr.2023.100597\u003c/span\u003e\u003cspan address=\"10.1016/j.jafr.2023.100597\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXu F, Crush J, Zhong T. Pathways to food insecurity: Migration, hukou and COVID-19 in Nanjing, China. Popul Space Place. 2023;29. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/psp.2640\u003c/span\u003e\u003cspan address=\"10.1002/psp.2640\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-food","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"discoverfood","sideBox":"Learn more about [Discover Food](https://www.springer.com/44187)","snPcode":"","submissionUrl":"","title":"Discover Food","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Food insecurity, HFIAS, HHS, Rural Households, Southern Somalia","lastPublishedDoi":"10.21203/rs.3.rs-9172675/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9172675/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn Southern Somalia, food insecurity remains an ongoing concern as climate variability and economic instability, coupled with limited livelihood options, continue to compromise household access to adequate and nutritious food. Using experience-based indicators, this study assesses the prevalence and severity of household food insecurity and hunger among rural households. The study specifically adopts the Household Food Insecurity Access Scale (HFIAS) and the Household Hunger Scale (HHS) to measure food insecurity and hunger in different socioeconomic and demographic groups. The analysis used for this study is a cross-sectional analysis, where primary data were collected through household survey across three states in Southern Somalia. Using a multistage sampling approach, 420 rural households were selected to be representative of\u0026ensp;all livelihood zones. Descriptive statistics was used to determine the factors related to food insecurity. Households were categorized by food access and consumption patterns as measured by HFIAS and HHS. The proportion of households with food insecurity was 96.4%, among which mild, moderate, and severe food insecurity accounted for 6.0%, 35.0%, and 55.4%, respectively. According to HHS results,\u0026ensp;26.43% of households had moderate to severe hunger and 73.57% had little or no hunger, indicating continued challenges to food access in rural Somalia. Female-headed households witnessed a disproportionate impact from their struggle for livelihoods, confirming the deep-seated inequality in access to economic resources and opportunities. These results expose the abiding structural dimensions of food insecurity in rural Southern Somalia and point to a clear need for policy responses that address integrated livelihoods resilience, agricultural productivity improvement and gender implicating food security interventions.\u003c/p\u003e","manuscriptTitle":"Empirical Analysis of Household Food Insecurity and Hunger Among Rural Communities in Southern Somalia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-22 20:27:53","doi":"10.21203/rs.3.rs-9172675/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-13T18:08:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"41508935118701248511211401559841726952","date":"2026-04-26T06:49:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"146614856103880881479962797020233363295","date":"2026-04-23T08:38:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"283189840380647181578030476811537369166","date":"2026-04-22T10:38:10+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-13T13:28:43+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-13T13:17:27+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-04T06:54:32+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-03T08:06:52+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Food","date":"2026-04-03T07:46:17+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-food","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"discoverfood","sideBox":"Learn more about [Discover Food](https://www.springer.com/44187)","snPcode":"","submissionUrl":"","title":"Discover Food","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"84cbe3c8-e8a8-4bf5-85ac-0d6ec027c359","owner":[],"postedDate":"April 22nd, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-13T18:08:20+00:00","index":32,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-22T20:27:53+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-22 20:27:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9172675","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9172675","identity":"rs-9172675","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}