Dying of starvation if not from bombs: Assessing measurement properties of the Food Insecurity Experiences Scale (FIES) in Gaza's civilian population experiencing the world’s worst hunger crisis

Dying of starvation if not from bombs: Assessing measurement properties of the Food Insecurity Experiences Scale (FIES) in Gaza's civilian population experiencing the world’s worst hunger crisis | 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 Dying of starvation if not from bombs: Assessing measurement properties of the Food Insecurity Experiences Scale (FIES) in Gaza's civilian population experiencing the world’s worst hunger crisis Feten Fekih-Romdhane, Kamel Jebreen, Tasnim Swaitti, Mohammed Jebreen, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5359207/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 20 Mar, 2025 Read the published version in International Journal for Equity in Health → Version 1 posted 7 You are reading this latest preprint version Abstract Background: Since October 2023, the humanitarian crisis in Gaza has dramatically escalated and food insecurity (FI) has rapidly deteriorated. In the face of such situation, it has been recommended that accurate information on FI should be integrated in emergency reporting systems in order to better target and assess the impact of humanitarian aid. To achieve this, field practitioners, researchers and decision-makers should be equipped with user-friendly and psychometrically sound measures tailored to real-life war situations and the Palestinian context. Therefore, the present study aimed to test the psychometric properties of the Food Insecurity Experiences Scale (FIES) in a sample of Arabic-speaking community adults currently living in the Gaza Strip during the war. Methods: This study used a cross-sectional design, snowball sampling as a recruiting strategy, and a self-administered online questionnaire to collect data from participants. It was performed during the period from September 1st to 30th, 2024. A total of 534 valid responses were received and were included in the final analysis. Results: Approximately one out of two people in Gaza were experiencing any FI. Fit indices in confirmatory factor analysis indicated that a one-factor solution fit the data with acceptable factor loadings. Furthermore, our findings indicated that the Arabic version of the FIES presented an excellent level of reliability, with both Cronbach's alpha and McDonald omega coefficients of .94. Cross-sex measurement invariance in the FIES was established at scalar and metric levels. Finaly, concurrent validity was evidenced by FIES's positive correlations with water insecurity experiences, post-traumatic stress, depression and anxiety symptoms. Conclusion: Altogether, our findings showed that the FIES fulfils requirements of validity and reliability, and may thus be considered as appropriate tool for assessing FI in war-affected populations currently suffering from hunger. The FIES is simple, short, economic and time-effective. It could therefore be easily implemented in war settings to measure and monitor FI for clinical, research and policy-making purposes. Food Insecurity Experiences Scale FIES Psychometric properties war hunger Arabic INTRODUCTION Soon after the current war started in October 2023, the population in Gaza has been experiencing unprecedent levels of food insecurity (FI) and hunger, described as a “humanitarian catastrophe”. Since then, nearly every agricultural land and bakery were bombed and damaged or even razed; and all means of food production were destroyed [ 1 ]. Famine has been used “as a weapon of war”, causing humanitarian food assistance to be minimal and inadequate to survive, or not allowed to reach starving people [ 1 ]. Adults have been risking gunfire and death to access aid convoys; children have been suffering from lack of food and dying of malnutrition [ 2 ]. As hunger reached catastrophic levels in Gaza, people resorted to eating weeds and animal feed to survive [ 1 ]. According to the United Nations, an estimated 576,000 people in the Gaza Strip were “at imminent risk of famine” by February 2024 [ 1 ]. The Integrated Food Security Phase Classification (IPC) categorized Gaza as being at Phase 4 (Emergency Acute Food Insecurity) for both the current and projection periods (up to 30 September 2024), with the presence of households in IPC Phase 5 (Catastrophe/Famine) [ 3 ]. Phase 4 reflects extreme food shortages, acute malnutrition, excessively high disease levels, and rapidly increasing risk of hunger-related death. Phase 5 indicates an extreme lack of food leading to extremely critical levels of acute malnutrition and death. As such, the situation in Gaza over the past months have been qualified by human rights organizations and experts as the world’s worst hunger crisis, and its reach is anticipated to extend far beyond those whose lives are directly threatened, to encompass the global food security [ 4 ]. Preceding October 2023, Gaza was already facing a vulnerable food security situation because of war, occupation, the long blockade of the Strip. A sizeable portion of people in Gaza became, for years now, dependent on humanitarian food aid for their survival and lacking access to a nutritious sufficient diet. Gazans have been suffering high malnutrition rates and related health complications, including low-birth weight, malnutrition, micronutrient deficiency, anemia and weakened immunity [ 5 ]. Since October 2023, the humanitarian crisis in Gaza has dramatically escalated and FI has rapidly deteriorated. In the face of such situation, it has been recommended that, in the short term, accurate information on FI and its indicators should be integrated in emergency reporting systems in order to better target and assess the impact of humanitarian aid [ 4 ]. In the long term, measuring FI could also be relevant and useful for informing decision-making about how to resolve challenges to food and nutrition security during the recovery phase after the war had ended. To achieve this, Field practitioners, researchers and decision-makers should be equipped with user-friendly and psychometrically sound measurement instrument tailored to real-life war situations and the Palestinian context. Measurement instruments of FI Many definitions are used for FI in the scientific literature, varying widely within and across disciplines, and significant differences exist in methods of assessing the FI construct [ 6 ]. There is some consensus on defining food security as “when all people, at all times, have physical, social and economic access to sufficient, safe and nutritious food to meet their dietary needs and food preferences for an active and healthy life” [7]. Hunger is thus a possible and not a necessary outcome of FI [8]. A range of different measures have been developed and implemented worldwide to assess FI, each capturing different aspects of FI experiences. The Global Food Security Index (GFSI) assesses the quality, availability, affordability, safety, and resiliency of foods available in a given nation [9]; it is, therefore, a macro-measure that assesses FI at the national level rather than the at household and individual level. The Household Dietary Diversity Scores (HDDS) [10] and the Food Consumption Score (FCS) [11] measure the quantity and/ or quality of foods consumed by an individual and/or a household. However, their reference periods are very limited (the previous 24 h and the last seven days, respectively) compared to other measures (typically the past year or the past 30 days) [ 6 ]. In addition, the FCS only detects the household dietary diversity without accounting for variations in the intrahousehold consumption of foods [11]. The Household Food Insecurity Access Scale (HFIAS) is a 9-item measure that assesses the intensity and frequency of psychological and behavioural challenges that a household confronted in accessing foods in the last month [10]. The HFIAS was largely criticized due to its subjective nature and its varying applications across contexts [12]. Besides, the HFIAS fails to appropriately assess other pillars of food security, including utilization, stability, or availability [ 6 ]. Household Pulse Survey (HPS) assesses whether and how often households had sufficient food to eat over the past one, two or four weeks through only one question [13]; hence, the HPS has the limitations inherent in single-item assessments. Finally, the Household Food Security Survey Module (HFSSM) is a 18-item measure that evaluates the prevalence of FI in households in the specific context of the United States [14]; thus, it fails to assess FI at a cross-national level [ 6 ]. To address some of the shortcomings of existing measures described above, the Food and Agriculture Organization (FAO) developed the Food Insecurity Experience Scale (FIES) in 2014 through the Voices of the Hungry Project [15]. The Food Insecurity Experience Scale (FIES) Although no agreement has been made among practitioners or scientists on one best evaluation measure for FI [16, 17], the FIES was one of the most commonly used worldwide. The FIES was designed to assess the severity of FI based on individuals’ experiences to access adequate food using a reference period of the past 12 months [15, 18], as well as the percentage of individuals in a given population who have experienced moderate-to-severe levels of FI [15, 19]. It is composed of eight yes-no questions assessing different levels of FI, from the least severe (i.e. worry about obtaining food; “In the last year was there a time that you were worried you would not have enough food to eat because of a lack of money or other resources?”) to the more serious (i.e. hunger; “In the last year was there a time that you were hungry but did not eat because there was not enough money or other resources for food?”) [20]. The FIES has been acknowledged as a short, standardized and valuable global tool to assess FI. It has been translated into 170 languages, and was found to be accepted worldwide and suitable for use across countries and cultures [15, 20]. Using multi-country data and nationally representative adult populations, the one-parameter logistic Rasch model was applied to examine the psychometric performance of the FIES and showed that the scale performed adequately in each country [21]. Although the suitability and usefulness of the FIES has been well-established, and despite its increasing widespread application in international and national population surveys, there has been a call for more validation studies of the scale across different nations to extend knowledge on its applicability in cross-national and cross-cultural settings [22]. This paper sought to add new psychometric information to existing knowledge about the FIES by evaluating its measurement properties in a population of Palestinians suffering from war-induced hunger. Rationale and aim of this study Over the past years, measuring FI has evolved from detecting perceptions to lived experiences [23]. This study proposes to assess the relevance of the FIES in assessing FI as a “lived experience” in a population facing acute, entirely man-made hunger due to the ongoing war in Gaza. Recognizing FI as experiences lived by war-affected people may help researchers comprehend the changes in these experiences across various contexts and settings, as well as over time because of war [22]. Therefore, the present study aimed to test the psychometric properties of the FIES in a sample of Arabic-speaking community adults currently living in the Gaza Strip during the war. It is hypothesized that the FIES will show a unidimensional factor structure assuming that the set of eight questions reflect a single underlying factor in both sexes with acceptable internal consistency. Further it is expected that the FIES will have good concurrent validity against measures of water insecurity, PTSD, depression, and anxiety. METHODS Sample and procedure This study used a cross-sectional design, snowball sampling as a recruiting strategy, and a self-administered online questionnaire to collect data from participants. It was performed during the period from September 1st to 30th, 2024. The questionnaire was distributed to potential participants through various social media sites, including Facebook, Instagram, and WhatsApp. Participants were included if they fulfilled the following inclusion criteria: (1) being aged 18 and over; (2) currently living in the Gaza strip (i.e. Gaza City, North Gaza, Deir Al Balah, Khan Younis, Rafah); and (3) willing to participate. The research protocol was granted by the scientific and ethics committee of Deanship of scientific research, Palestine Technical university – Kadoorie, Palestine. The first section of the survey questionnaire contained an informed consent statement. Each respondent was asked whether they agree to participate in this study. Only an affirmative response to this question gave them access to the main part of the survey. The voluntary nature of participation was clearly stated. Participants were also informed about the confidentiality of their personal data. Of the 546 participants who accessed the survey link, 12 (0.4%) responded negatively to the consent question, and were therefore directly withdrawn from the survey. A total of 534 valid responses were received and were included in the final analysis. Measures Socio-demographic information Data regarding basic sociodemographic information of participants was collected, including sex (male, female), age, education (primary, middle, secondary, university), marital status (single, married, divorced, widowed), and current residency (refugee camps, village, city). The Food Insecurity Experience Scale (FIES) The FIES contains eight items which assess the extent to which a given population is endorsing different self-reported experiences of FI (e.g., limiting food intake, altering food quality, anxiety), and how severe their experiences with FI can be [24]. at the individual level [20]. The scale has undergone careful translation and linguistic adaptation in many languages (including Arabic [25]) before its application, to ensure that it can be correctly understood and universally meaningful wherever it is applied [24]. Each negative response is attributed the score of “0”, and each affirmative response is attributed the score of “1”. Total scores vary from 0 to 8. The following cutoff scores were used to categorize respondents based on their FI status: food secure (0), mild FI (1–3), moderate FI (4–6), and severe FI (7–8) [26]. The Four-Item Household Water Insecurity Experiences Scale (HWISE-4) The HWISE-4 contains four items measuring water insecurity experiences (e.g., “In the last 4 weeks, how frequently did you or anyone in your household worry you would not have enough water for all of your household needs?”) [27]. Items are scored on a five-point Likert type scale ranging from 0 (never, 0 times) to 4 (always (more than 20 times). A score of 4 or above is set as the cut off which accurately dichotomizes participants into water-insecure and water-secure. The Arabic validated version was used [28] (Cronbach’s alpha = 0.91 in this sample). The Impact of Event Scale-6 (IES-6) The IES-6 [29] is a shortened version of the Impact of Event Scale – Revised (IES-R) [30]. It assesses the severity of post-traumatic stress disorder (PTSD) symptoms through six items and three dimensions: intrusion (2 items), avoidance (2 items) and hyper-arousal (2 items). Response options vary on a five-point scale from 0 (not at all) to 4 (extremely). Higher total scores reflect greater levels of PTSD reactions. The Arabic validated version of the IES-6 was used in the present study [31] (Cronbach’s alpha = 0.83). The Patient Health Questionnaire-9 (PHQ-9) The PHQ-9 is a valid and reliable scale composed of 9 items, which was used to measure the severity of depression symptoms over the last two weeks [32]. Participants are asked to indicate how often they have been bothered by nine problems (e.g., “Feeling bad about yourself or that you are a failure or have let yourself or your family down” or “Thoughts that you would be better off dead, or of hurting yourself”), with response options varying from “not at all” = 0 to “nearly every day” = 3. Total scores range between 0 and 27, with greater scores indicating higher levels of depression. We used the Arabic validated version of the PHQ-9 in this study [33, 34], which yielded a Cronbach’s alpha of 0.93 in the present sample. The Generalized Anxiety Disorder 7-item (GAD-7) This scale is self-administered and composed of seven items, each of them asks the respondents on whether they have experienced one of seven generalized anxiety symptoms (e.g., “Not being able to stop or control worrying” or “Worrying too much about different things”) over the past 2 weeks [35]. Response options are the following: “Not at all” = 0, “Several days” = 1, “More than half the days” = 2, and “Nearly every day” = 3. Total scores vary between 0 and 21, with higher scores referring to more severe anxiety. The Arabic validated version was adopted in this study [33, 36], with a Cronbach’s alpha of 0.94. Analytic Strategy There were no missing responses in the dataset. The total sample (n = 534) was divided into two subsamples; subsample 1 (1/3 of the total sample; n = 179) was used for the exploratory factor analysis (EFA), whereas subsample 2 (2/3 of the total sample; n = 355) was used for the confirmatory factor analysis (CFA). We used FACTOR 12.04.01 [37] to perform the EFA. The Kaiser-Meyer-Olkin (KMO) and the Bartlett’s statistic were used to confirm the suitability of the data. The Measure of Sampling Adequacy (MSA) at the item level value ranges from 0 to 1, with values below .50 indicate the need to eliminate the item [38]. The Expected Residual correlation direct Change (EREC) index was used to assess the residual correlation between two items (called doublets); items that appear repeatedly in different doublets should be removed [39]. Since the items are scored on a Likert scale, a polychoric correlation matrix was conducted [40]. We used the Unweighted Least Squares (ULS) as the method of estimation [41], with the parallel analysis used to determine the optimal number of factors to retain [42, 43]. A minimum sample of 80 participants was needed following the recommendations of Comree and Lee (ten participants per scale’s item) [44]. Consequently, we conducted a CFA via the SPSS AMOS v.28 software. We estimated a minimum sample of 160 participants based on the recommendation of 20 times per scale’s variables [45]. The maximum likelihood method was used to obtain parameters estimate. Multiple fit indices were calculated: root mean square error of approximation (RMSEA) (≤ 0.08), standardized root mean square residual (SRMR) (≤ 0.05), Tucker-Lewis Index (TLI) and Comparative Fit Index (CFI) (≥ .90 for both) [46]. Additionally, convergent validity was checked via the average variance extracted (AVE) ≥ .50 [47]. Multivariate normality was not verified at first (Bollen-Stine bootstrap p = 0.002); therefore, we performed non-parametric bootstrapping procedure. A multi-group CFA was conducted to examine measurement invariance of FIES scores between genders [48] at the configural, metric, and scalar levels [49]. ΔCFI ≤ .010 and ΔRMSEA ≤ .015 or ΔSRMR ≤ .010 supported the evidence of invariance [50]. Comparison of FIES scores between genders was done using the Student’s t test. Composite reliability was assessed using McDonald’s ω and Cronbach’s α, with values greater than 0.70 reflecting adequate composite reliability [51]. The FIES scores were considered normally distributed as shown by skewness and kurtosis values between − 1 and + 1 [52]. The association between the FIES scores and other scores was evaluated using the Pearson test. RESULTS In total, 534 participants participated in this study, with a majority of participants aged 19 years and 71.9% married. A total of 227 participants (42.5%) were categorized as water-insecure. The prevalence of any FI was 50.2%, with 31.3% being classified as moderately-to-severely food insecure. Other descriptive statistics of the sample can be found in Table 1 . Table 1 Sociodemographic and other characteristics of the sample (N = 534). Variable N (%) Sex Female 384 (71.9%) Male 150 (28.1%) Marital status Married 128 (24.0%) Unmarried 406 (76.0%) Education level University 498 (93.3%) Secondary or less 36 (6.70%) Residency Refugee camps 62 (11.60%) City 105 (87.5%) Village 15 (12.5%) Water insecurity Water-insecure 227 (42.5%) Water-secure 307 (57.5%) Food insecurity Food secure (0) 266 (49.8%) Mild FI (1–3) 113 (21.2%) Moderate FI (4–6) 65 (12.2%) Severe FI (7–8) 90 (19.1%) Moyenne ± SD Age (years) 23.74 ± 7.92 Food insecurity experiences (FIES total score) 2.27 ± 2.97 Water insecurity experiences (HWISE-4 scores) 4.21 ± 4.52 PTSD (IES-6 scores) 13.78 ± 5.40 Depression (PHQ-9 scores) 12.27 ± 8.04 Anxiety (GAD-7 scores) 8.85 ± 6.39 FIES: Food Insecurity Experiences Scale; HWISE-4: Four-Item Household Water Insecurity Experiences Scale; IES-6: Impact of Event Scale-6 ; PHQ-9: Patient Health Questionnaire-9 ; GAD-7: Generalized Anxiety Disorder 7-item. Exploratory and Confirmatory Factor Analyses (subsample 1 and subsample 2 respectively) The KMO (= .91) and Bartlett’s test ( p ≤ .001) affirmed the suitability of the data. None of the items was removed according to the MSA or EREC indices, with the parallel analysis advising a unidimensional structure (explained variance of 69.72%) supported by the Goodness of Fit Index (GFI = .99) being greater than .95, TLI = 1.01, CFI = 1.00, the UniCo (= .99) index greater than .95, the I-ECV (I-ECV = .93) greater than .85 and MIREAL (MIREAL = .17) lower than .30. We ran a CFA using the one-factor structure obtained from the EFA. The fit indices were good (RMSEA = 0.103 (90% CI 0.083, 0.124), SRMR = 0.034, CFI = 0.963, TLI = 0.948). The standardized estimates of factor loadings deriving from the EFA and CFA were all adequate (Table 2 ). Composite reliability of scores was adequate in the total sample (ω = .91 / α = .90). The convergent validity for this model was confirmed (AVE = .64). Table 2 Factor loadings deriving from the exploratory factor analysis (EFA) and standardized loading factors deriving from the confirmatory factor analysis (CFA) of the Food Insecurity Experience Scale in Arabic. Item number Question EFA CFA Q1. You were worried you would run out of food because of a lack of money or other resources? .71 .79 Q2. You were unable to eat healthy and nutritious food because of a lack of money or other resources? .82 .74 Q3. You ate only a few kinds of foods because of a lack of money or other resources? .82 .83 Q4. You had to skip a meal because there was not enough money or other resources to get food? .82 .81 Q5. You ate less than you thought you should because of a lack of money or other resources? .88 .87 Q6. Your household ran out of food because of a lack of money or other resources? .86 .83 Q7. You were hungry but did not eat because there was not enough money or other resources for food? .85 .78 Q8. You went without eating for a whole day because of a lack of money or other resources? .71 .75 Cronbach’s α .93 .94 McDonald’s ω .94 .94 Sex Invariance (total sample) Invariance was shown at the metric and scalar levels in terms of genders (Table 2 ). No significant difference was found in FIES scores between males and females (2.41 ± 3.01 vs 2.21 ± 2.96; t (532) = .72; p = 0.474, Cohen’s d = 0.069). Table 2 Measurement Invariance of the Food Insecurity Experience Scale across gender. Model CFI RMSEA SRMR Model Comparison ΔCFI ΔRMSEA ΔSRMR Configural .963 .074 .047 Metric .965 .067 .048 Configural vs metric .002 .007 .001 Scalar .962 .065 .048 Metric vs scalar .003 .002 < .001 Note. CFI = Comparative fit index; RMSEA = root mean square error of approximation; SRMR = Standardised root mean square residual. Concurrent validity Higher FIES scores were significantly associated with higher water insecurity experience (r = 0.56; p < 0.001), higher PTSD (r = 0.25; p < 0.001), higher depression (r = 0.42; p < 0.001), and higher anxiety (r = 0.41; p < 0.001). DISCUSSION Before the ongoing war, the population in Gaza was already dealing with a longstanding FI and constrained access to nutritious food. Since October 7th 2023, civilians in Gaza have been facing high levels of acute FI, along with a denial of humanitarian access and assistance. Our study had as a main goal to examine psychometric properties of the FIES among Gazan adults during the ongoing war. Findings showed that approximately one out of two people in Gaza were experiencing any FI. Fit indices in CFA indicated that a one-factor solution fit the data with acceptable factor loadings, and multigroup invariance tests demonstrated that this solution fit largely equivalently across sexes. Overall, results suggest that the FIES is a valid and reliable FI measurement instrument for the Arabic-speaking Palestinian population enduring war-related starvation. The FIES conceptualizes FI as the inability to freely acquire the food needed to conduct an active, dignified and healthy life. The FIES responses are dichotomous in nature (Yes – No), providing enough information to construct a one-dimensional measurement tool [20]. The current study extends previous research by using an EFA-to-CFA approach to explore the best-fitting model of the FIES in a group of civilians in Gaza being starved due to war. The eight FIES items loaded onto a single overall factor, suggesting that all items reflect a single continuous latent variable underlying the responses. Unidimensionality is a necessary condition for the use of summated scores and for any analyses based on FIES total scores. Unidimensionality is, therefore, an important attribute of the scale as it enables to report a single score representing the same underlying construct of experience-based FI at the individual level over the past year. This eases the interpretability of FIES scores, and lends supports to the assertion that the FIES can easily be adaptable across different populations and contexts, enabling standardized comparisons of prevalence data via the use of a single metric [53, 54]. Furthermore, our findings indicated that the Arabic version of the FIES presented an excellent level of reliability, with both Cronbach's alpha and McDonald omega coefficients of .94. Our results are similar to those of a study by Helmi et al. [55] showing that the Malay-language version of FIES had acceptable internal consistency (Cronbach's alpha = 0.759) in a population-based sample aged 15-year-old and above. Multi-group CFA was used to examine whether the FIES was invariant across sex groups (male or female). Cross-sex measurement invariance in the FIES was established at scalar and metric levels. This means that the eight FIES questions and their response options were understood similarly across male and female respondents. Evidence of invariance should be recognized as an important consideration before arriving at any conclusions regarding sex differences in FI. This psychometric property is relevant, especially as some empirical evidence suggested that males and females may respond to FI questions differently because of their divergent food-related responsibilities and roles [56]. Finaly, concurrent validity was evidenced by FIES's positive correlations with water insecurity experiences, PTSD, depression and anxiety symptoms. This is consistent with previous evidence from the 2014 Gallup World Poll that individual-level FI, as assessed using the FIES, and at any degree of severity, was positively correlated with specific psychosocial stressors and poorer mental health status (e.g., stress, sadness, anger, worry) across 149 countries and different global regions [57]. Study limitations There are some limitations to this study that merit acknowledgment. The sample was gathered using snowball sampling and an online questionnaire, which might have affected the generalizability of findings. Due to the cross-sectional nature of our data, causality could not be inferred. Moreover, the stability of the FIES over time could not be verified, as data were collected at a single point in time. In addition, findings could be subject to response and social desirability biases, as only self-administered measures were used. Clinical and research implications To the best of our knowledge, this study is among the first to undertake EFA and CFA to demonstrate construct validity of the single-factor structure of the FIES. As a unidimensional measure, the FIES offers a unique opportunity to compare prevalence estimates of FI across countries and over time using computed total scores obtained by summing the scores for all eight items. The international FIES thresholds defined by FAO to classify respondents based on their FI experiences levels are also made comparable across populations and different environmental settings [20], and can thus be successfully adopted to produce estimates of the prevalence of FI in Palestine during and after war [58]. Additionally, this study addresses the prominent measurement issue of invariance across sex groups, as it ensures that FIES items are being interpreted identically between males and females, and allows to accurately evaluate sex differences in FI experiences in future clinical and research practices. Measurement invariance is a highly valuable, yet often neglected step in psychometric research, and only a very few studies using the FIES have provided evidence in this regard. Future studies are recommended to conduct invariance tests that enable researchers to explore and to justify cross-group comparisons of mean FIES scores. This study is also among the very limited studies to investigate the link between FI and mental health variables using standardized measures and a war-affected population. Although FI has been implicated as a causal factor for the development of mental health problems, yet the direction of this relationship remains unknown. Future longitudinal and experimental research are still needed to address this issue. CONCLUSION Altogether, our findings showed that the FIES fulfils requirements of validity and reliability, and may thus be considered as appropriate tool for assessing FI in war-affected populations currently suffering from hunger. The FIES is simple, short, economic and time-effective. It could therefore be easily implemented in war settings to measure and monitor FI for clinical, research and policy-making purposes. evaluating other psychometric aspects of the Arabic version of the FIES, such as inter-rater reliability and convergent validity, could be prolific directions for future research. Declarations Ethics Approval and Consent to Participate : The ethical approval for this project was granted by the scientific and ethics committee of Deanship of scientific research, Palestine Technical university – Kadoorie. A written informed consent was obtained from each participant when completing the online form. All methods were performed in accordance with the relevant guidelines and regulations (in accordance with the Declaration of Helsinki). Consent for publication: Not applicable. Availability of data and materials: The data that support the findings of this study are available from the corresponding author but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of the ethics committee. Competing interests: The authors have nothing to disclose. Funding: None. Author contributions: FFR designed the study; KJ, TS, MJ, ER, and MAAS collected the data, FFR drafted the manuscript; SH, KJ carried out the analysis and interpreted the results; KJ, WKR, IN, OS and SO reviewed the paper for intellectual content; all authors reviewed the final manuscript and gave their consent. Clinical trial number : Not applicable Acknowledgments: Author KJ would like to acknowledge support through the ICTP-Arab Fund Associates Programme (2024-2026). References United Nations: Famine Imminent in Gaza, Humanitarian Officials Tell Security Council, Calling for Immediate Ceasefire . In . ; 2024. UNRWA UNRaWAfPRitNE: Frontline heroes: The Race Against the Clock to Avert Famine . 2024. IPC IFSPC: FAMINE REVIEW COMMITTEE: GAZA STRIP, JUNE 2024 . 2024. 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Brunelli C, Viviani S, Ballard T, Viviani S, Nord M, Grossi M: Exploring gender-based disparities with the FAO Food Insecurity Experience Scale . In: Reporte en Global Forum on Gender Statistics Aguascalientes, Mexico: 2014 ; 2014. Saint Ville A, Po JYT, Sen A, Bui A, Melgar-Quiñonez H: Food security and the Food Insecurity Experience Scale (FIES): ensuring progress by 2030 . In . , vol. 11: Springer; 2019: 483-491. Frongillo EA: Confronting myths about household food insecurity and excess weight . In . , vol. 29: SciELO Public Health; 2013: 229-230. Ballard TJ, Kepple, A.W., Cafiero, C.: The food insecurity experience scale: development of a global standard for monitoring hunger worldwide. . In . ; 2013. FAO FaAOotUN: The Food Insecurity Experience Scale (FIES) Guidance for translation: intended meanings of the questions and specific terms (Arabic) . 2018. FAO: Modeling Food Insecurity in Bivariate and Regression Analyses, Guidelines Prepared by the Voices of the Hungry Team . In . : FAO Rome; 2015. Young SL, Miller JD, Frongillo EA, Boateng GO, Jamaluddine Z, Neilands TB: Validity of a Four-Item Household Water Insecurity Experiences Scale for Assessing Water Issues Related to Health and Well-Being . Am J Trop Med Hyg 2021, 104 (1):391-394. Ghattas H, Jamaluddine, Z., Khabsa, J.: The Household Water InSecurity Experiences (HWISE) Scale Study Manual (Arabic) . 2018. Thoresen S, Tambs K, Hussain A, Heir T, Johansen VA, Bisson JI: Brief measure of posttraumatic stress reactions: impact of Event Scale-6 . Soc Psychiatry Psychiatr Epidemiol 2010, 45 (3):405-412. Weiss DS, Marmar CR: The Impact of Event Scale—Revised . In: Assessing psychological trauma and PTSD. edn. New York, NY, US: The Guilford Press; 1997: 399-411. Hemade A, Hallit R, Malaeb D, El Dine AS, Moawad M, Obeid S, Hallit S, Fekih-Romdhane F: Psychometric validation of an Arabic translation of the Impact of Event Scale-6 (IES-6) . 2024. Kroenke K, Spitzer RL, Williams JB: The PHQ-9: validity of a brief depression severity measure . J Gen Intern Med 2001, 16 (9):606-613. Sawaya H, Atoui M, Hamadeh A, Zeinoun P, Nahas Z: Adaptation and initial validation of the Patient Health Questionnaire - 9 (PHQ-9) and the Generalized Anxiety Disorder - 7 Questionnaire (GAD-7) in an Arabic speaking Lebanese psychiatric outpatient sample . Psychiatry Res 2016, 239 :245-252. Dagher D, Samaha S, Mhanna M, Azzi R, Mina A, Soufia M, Hallit S, Obeid S, Haddad G: Depressive symptoms among a sample of Lebanese adolescents: Scale validation and correlates with disordered eating . Arch Pediatr 2023, 30 (6):401-407. Spitzer RL, Kroenke K, Williams JB, Löwe B: A brief measure for assessing generalized anxiety disorder: the GAD-7 . Archives of internal medicine 2006, 166 (10):1092-1097. 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Calderón Garrido C, Navarro González D, Lorenzo Seva U, Ferrando Piera PJ: Multidimensional or essentially unidimensional? A multi-faceted factoranalytic approach for assessing the dimensionality of tests and items . Psicothema 2019. Timmerman ME, Lorenzo-Seva U: Dimensionality assessment of ordered polytomous items with parallel analysis . Psychological methods 2011, 16 (2):209. Comrey AL, Lee HB: A first course in factor analysis : Psychology press; 2013. Mundfrom DJ, Shaw DG, Ke TL: Minimum sample size recommendations for conducting factor analyses . International journal of testing 2005, 5 (2):159-168. Hu Lt, Bentler PM: Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives . Structural equation modeling: a multidisciplinary journal 1999, 6 (1):1-55. Malhotra N, Dash S: Marketing Research: An Applied Orientation (; Pearson, Ed.) . In . : Delhi; 2011. Chen FF: Sensitivity of goodness of fit indexes to lack of measurement invariance . Structural equation modeling: a multidisciplinary journal 2007, 14 (3):464-504. Vadenberg R, Lance C: A review and synthesis of the measurement in variance literature: Suggestions, practices, and recommendations for organizational research . Organ Res Methods 2000, 3 :4-70. Swami V, Todd J, Azzi V, Malaeb D, El Dine AS, Obeid S, Hallit S: Psychometric properties of an Arabic translation of the Functionality Appreciation Scale (FAS) in Lebanese adults . Body Image 2022, 42 :361-369. Dunn TJ, Baguley T, Brunsden V: From alpha to omega: A practical solution to the pervasive problem of internal consistency estimation . British journal of psychology 2014, 105 (3):399-412. Hair Jr JF, Sarstedt M, Ringle CM, Gudergan SP: Advanced issues in partial least squares structural equation modeling : saGe publications; 2017. Wambogo EA, Ghattas H, Leonard KL, Sahyoun NR: Validity of the food insecurity experience scale for use in sub-Saharan Africa and characteristics of food-insecure individuals . Current developments in nutrition 2018, 2 (9):nzy062. Depa J, Gyngell F, Müller A, Eleraky L, Hilzendegen C, Stroebele-Benschop N: Prevalence of food insecurity among food bank users in Germany and its association with population characteristics . Preventive medicine reports 2018, 9 :96-101. Helmi NZ, Isa KAM, Masuri MG: Exploratory factor analysis on Food Insecurity Experience Scale (FIES): latest food insecurity measurement tool by FAO . Healthscope: The Official Research Book of Faculty of Health Sciences, UiTM 2020, 3 (2):31-34. Coates JC, Webb P, Houser RF, Rogers BL, Wilde P: “He said, she said”: who should speak for households about experiences of food insecurity in Bangladesh? Food Security 2010, 2 :81-95. Jones AD: Food insecurity and mental health status: a global analysis of 149 countries . American journal of preventive medicine 2017, 53 (2):264-273. FAO: Methods for estimating comparable rates of food insecurity experienced by adults throughout the world . Rome 2016. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 20 Mar, 2025 Read the published version in International Journal for Equity in Health → Version 1 posted Editorial decision: Revision requested 16 Nov, 2024 Reviews received at journal 16 Nov, 2024 Reviewers agreed at journal 01 Nov, 2024 Reviewers invited by journal 31 Oct, 2024 Editor assigned by journal 31 Oct, 2024 Submission checks completed at journal 30 Oct, 2024 First submitted to journal 30 Oct, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Since then, nearly every agricultural land and bakery were bombed and damaged or even razed; and all means of food production were destroyed [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Famine has been used \u0026ldquo;as a weapon of war\u0026rdquo;, causing humanitarian food assistance to be minimal and inadequate to survive, or not allowed to reach starving people [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Adults have been risking gunfire and death to access aid convoys; children have been suffering from lack of food and dying of malnutrition [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. As hunger reached catastrophic levels in Gaza, people resorted to eating weeds and animal feed to survive [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. According to the United Nations, an estimated 576,000 people in the Gaza Strip were \u0026ldquo;at imminent risk of famine\u0026rdquo; by February 2024 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The Integrated Food Security Phase Classification (IPC) categorized Gaza as being at Phase 4 (Emergency Acute Food Insecurity) for both the current and projection periods (up to 30 September 2024), with the presence of households in IPC Phase 5 (Catastrophe/Famine) [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Phase 4 reflects extreme food shortages, acute malnutrition, excessively high disease levels, and rapidly increasing risk of hunger-related death. Phase 5 indicates an extreme lack of food leading to extremely critical levels of acute malnutrition and death. As such, the situation in Gaza over the past months have been qualified by human rights organizations and experts as the world\u0026rsquo;s worst hunger crisis, and its reach is anticipated to extend far beyond those whose lives are directly threatened, to encompass the global food security [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePreceding October 2023, Gaza was already facing a vulnerable food security situation because of war, occupation, the long blockade of the Strip. A sizeable portion of people in Gaza became, for years now, dependent on humanitarian food aid for their survival and lacking access to a nutritious sufficient diet. Gazans have been suffering high malnutrition rates and related health complications, including low-birth weight, malnutrition, micronutrient deficiency, anemia and weakened immunity [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Since October 2023, the humanitarian crisis in Gaza has dramatically escalated and FI has rapidly deteriorated. In the face of such situation, it has been recommended that, in the short term, accurate information on FI and its indicators should be integrated in emergency reporting systems in order to better target and assess the impact of humanitarian aid [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. In the long term, measuring FI could also be relevant and useful for informing decision-making about how to resolve challenges to food and nutrition security during the recovery phase after the war had ended. To achieve this, Field practitioners, researchers and decision-makers should be equipped with user-friendly and psychometrically sound measurement instrument tailored to real-life war situations and the Palestinian context.\u003c/p\u003e\n\u003ch3\u003eMeasurement instruments of FI\u003c/h3\u003e\n\u003cp\u003eMany definitions are used for FI in the scientific literature, varying widely within and across disciplines, and significant differences exist in methods of assessing the FI construct [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. There is some consensus on defining food security as \u0026ldquo;when all people, at all times, have physical, social and economic access to sufficient, safe and nutritious food to meet their dietary needs and food preferences for an active and healthy life\u0026rdquo; [7]. Hunger is thus a possible and not a necessary outcome of FI [8]. A range of different measures have been developed and implemented worldwide to assess FI, each capturing different aspects of FI experiences. The Global Food Security Index (GFSI) assesses the quality, availability, affordability, safety, and resiliency of foods available in a given nation [9]; it is, therefore, a macro-measure that assesses FI at the national level rather than the at household and individual level. The Household Dietary Diversity Scores (HDDS) [10] and the Food Consumption Score (FCS) [11] measure the quantity and/ or quality of foods consumed by an individual and/or a household. However, their reference periods are very limited (the previous 24 h and the last seven days, respectively) compared to other measures (typically the past year or the past 30 days) [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In addition, the FCS only detects the household dietary diversity without accounting for variations in the intrahousehold consumption of foods [11]. The Household Food Insecurity Access Scale (HFIAS) is a 9-item measure that assesses the intensity and frequency of psychological and behavioural challenges that a household confronted in accessing foods in the last month [10]. The HFIAS was largely criticized due to its subjective nature and its varying applications across contexts [12]. Besides, the HFIAS fails to appropriately assess other pillars of food security, including utilization, stability, or availability [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Household Pulse Survey (HPS) assesses whether and how often households had sufficient food to eat over the past one, two or four weeks through only one question [13]; hence, the HPS has the limitations inherent in single-item assessments. Finally, the Household Food Security Survey Module (HFSSM) is a 18-item measure that evaluates the prevalence of FI in households in the specific context of the United States [14]; thus, it fails to assess FI at a cross-national level [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. To address some of the shortcomings of existing measures described above, the Food and Agriculture Organization (FAO) developed the Food Insecurity Experience Scale (FIES) in 2014 through the Voices of the Hungry Project [15].\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eThe Food Insecurity Experience Scale (FIES)\u003c/h2\u003e \u003cp\u003eAlthough no agreement has been made among practitioners or scientists on one best evaluation measure for FI [16, 17], the FIES was one of the most commonly used worldwide. The FIES was designed to assess the severity of FI based on individuals\u0026rsquo; experiences to access adequate food using a reference period of the past 12 months [15, 18], as well as the percentage of individuals in a given population who have experienced moderate-to-severe levels of FI [15, 19]. It is composed of eight yes-no questions assessing different levels of FI, from the least severe (i.e. worry about obtaining food; \u0026ldquo;In the last year was there a time that you were worried you would not have enough food to eat because of a lack of money or other resources?\u0026rdquo;) to the more serious (i.e. hunger; \u0026ldquo;In the last year was there a time that you were hungry but did not eat because there was not enough money or other resources for food?\u0026rdquo;) [20]. The FIES has been acknowledged as a short, standardized and valuable global tool to assess FI. It has been translated into 170 languages, and was found to be accepted worldwide and suitable for use across countries and cultures [15, 20]. Using multi-country data and nationally representative adult populations, the one-parameter logistic Rasch model was applied to examine the psychometric performance of the FIES and showed that the scale performed adequately in each country [21]. Although the suitability and usefulness of the FIES has been well-established, and despite its increasing widespread application in international and national population surveys, there has been a call for more validation studies of the scale across different nations to extend knowledge on its applicability in cross-national and cross-cultural settings [22]. This paper sought to add new psychometric information to existing knowledge about the FIES by evaluating its measurement properties in a population of Palestinians suffering from war-induced hunger.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eRationale and aim of this study\u003c/h3\u003e\n\u003cp\u003eOver the past years, measuring FI has evolved from detecting perceptions to lived experiences [23]. This study proposes to assess the relevance of the FIES in assessing FI as a \u0026ldquo;lived experience\u0026rdquo; in a population facing acute, entirely man-made hunger due to the ongoing war in Gaza. Recognizing FI as experiences lived by war-affected people may help researchers comprehend the changes in these experiences across various contexts and settings, as well as over time because of war [22]. Therefore, the present study aimed to test the psychometric properties of the FIES in a sample of Arabic-speaking community adults currently living in the Gaza Strip during the war. It is hypothesized that the FIES will show a unidimensional factor structure assuming that the set of eight questions reflect a single underlying factor in both sexes with acceptable internal consistency. Further it is expected that the FIES will have good concurrent validity against measures of water insecurity, PTSD, depression, and anxiety.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eSample and procedure\u003c/h2\u003e \u003cp\u003eThis study used a cross-sectional design, snowball sampling as a recruiting strategy, and a self-administered online questionnaire to collect data from participants. It was performed during the period from September 1st to 30th, 2024. The questionnaire was distributed to potential participants through various social media sites, including Facebook, Instagram, and WhatsApp. Participants were included if they fulfilled the following inclusion criteria: (1) being aged 18 and over; (2) currently living in the Gaza strip (i.e. Gaza City, North Gaza, Deir Al Balah, Khan Younis, Rafah); and (3) willing to participate. The research protocol was granted by the scientific and ethics committee of Deanship of scientific research, Palestine Technical university \u0026ndash; Kadoorie, Palestine. The first section of the survey questionnaire contained an informed consent statement. Each respondent was asked whether they agree to participate in this study. Only an affirmative response to this question gave them access to the main part of the survey. The voluntary nature of participation was clearly stated. Participants were also informed about the confidentiality of their personal data. Of the 546 participants who accessed the survey link, 12 (0.4%) responded negatively to the consent question, and were therefore directly withdrawn from the survey. A total of 534 valid responses were received and were included in the final analysis.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMeasures\u003c/h3\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSocio-demographic information\u003c/h2\u003e \u003cp\u003eData regarding basic sociodemographic information of participants was collected, including sex (male, female), age, education (primary, middle, secondary, university), marital status (single, married, divorced, widowed), and current residency (refugee camps, village, city).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eThe Food Insecurity Experience Scale (FIES)\u003c/h3\u003e\n\u003cp\u003eThe FIES contains eight items which assess the extent to which a given population is endorsing different self-reported experiences of FI (e.g., limiting food intake, altering food quality, anxiety), and how severe their experiences with FI can be [24]. at the individual level [20]. The scale has undergone careful translation and linguistic adaptation in many languages (including Arabic [25]) before its application, to ensure that it can be correctly understood and universally meaningful wherever it is applied [24]. Each negative response is attributed the score of \u0026ldquo;0\u0026rdquo;, and each affirmative response is attributed the score of \u0026ldquo;1\u0026rdquo;. Total scores vary from 0 to 8. The following cutoff scores were used to categorize respondents based on their FI status: food secure (0), mild FI (1\u0026ndash;3), moderate FI (4\u0026ndash;6), and severe FI (7\u0026ndash;8) [26].\u003c/p\u003e\n\u003ch3\u003eThe Four-Item Household Water Insecurity Experiences Scale (HWISE-4)\u003c/h3\u003e\n\u003cp\u003eThe HWISE-4 contains four items measuring water insecurity experiences (e.g., \u0026ldquo;In the last 4 weeks, how frequently did you or anyone in your household worry you would not have enough water for all of your household needs?\u0026rdquo;) [27]. Items are scored on a five-point Likert type scale ranging from 0 (never, 0 times) to 4 (always (more than 20 times). A score of 4 or above is set as the cut off which accurately dichotomizes participants into water-insecure and water-secure. The Arabic validated version was used [28] (Cronbach\u0026rsquo;s alpha\u0026thinsp;=\u0026thinsp;0.91 in this sample).\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eThe Impact of Event Scale-6 (IES-6)\u003c/h2\u003e \u003cp\u003eThe IES-6 [29] is a shortened version of the Impact of Event Scale \u0026ndash; Revised (IES-R) [30]. It assesses the severity of post-traumatic stress disorder (PTSD) symptoms through six items and three dimensions: intrusion (2 items), avoidance (2 items) and hyper-arousal (2 items). Response options vary on a five-point scale from 0 (not at all) to 4 (extremely). Higher total scores reflect greater levels of PTSD reactions. The Arabic validated version of the IES-6 was used in the present study [31] (Cronbach\u0026rsquo;s alpha\u0026thinsp;=\u0026thinsp;0.83).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eThe Patient Health Questionnaire-9 (PHQ-9)\u003c/h2\u003e \u003cp\u003eThe PHQ-9 is a valid and reliable scale composed of 9 items, which was used to measure the severity of depression symptoms over the last two weeks [32]. Participants are asked to indicate how often they have been bothered by nine problems (e.g., \u0026ldquo;Feeling bad about yourself or that you are a failure or have let yourself or your family down\u0026rdquo; or \u0026ldquo;Thoughts that you would be better off dead, or of hurting yourself\u0026rdquo;), with response options varying from \u0026ldquo;not at all\u0026rdquo; = 0 to \u0026ldquo;nearly every day\u0026rdquo; = 3. Total scores range between 0 and 27, with greater scores indicating higher levels of depression. We used the Arabic validated version of the PHQ-9 in this study [33, 34], which yielded a Cronbach\u0026rsquo;s alpha of 0.93 in the present sample.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eThe Generalized Anxiety Disorder 7-item (GAD-7)\u003c/h2\u003e \u003cp\u003eThis scale is self-administered and composed of seven items, each of them asks the respondents on whether they have experienced one of seven generalized anxiety symptoms (e.g., \u0026ldquo;Not being able to stop or control worrying\u0026rdquo; or \u0026ldquo;Worrying too much about different things\u0026rdquo;) over the past 2 weeks [35]. Response options are the following: \u0026ldquo;Not at all\u0026rdquo; = 0, \u0026ldquo;Several days\u0026rdquo; = 1, \u0026ldquo;More than half the days\u0026rdquo; = 2, and \u0026ldquo;Nearly every day\u0026rdquo; = 3. Total scores vary between 0 and 21, with higher scores referring to more severe anxiety. The Arabic validated version was adopted in this study [33, 36], with a Cronbach\u0026rsquo;s alpha of 0.94.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eAnalytic Strategy\u003c/h2\u003e \u003cp\u003eThere were no missing responses in the dataset. The total sample (n\u0026thinsp;=\u0026thinsp;534) was divided into two subsamples; subsample 1 (1/3 of the total sample; n\u0026thinsp;=\u0026thinsp;179) was used for the exploratory factor analysis (EFA), whereas subsample 2 (2/3 of the total sample; n\u0026thinsp;=\u0026thinsp;355) was used for the confirmatory factor analysis (CFA). We used FACTOR 12.04.01 [37] to perform the EFA. The Kaiser-Meyer-Olkin (KMO) and the Bartlett\u0026rsquo;s statistic were used to confirm the suitability of the data. The Measure of Sampling Adequacy (MSA) at the item level value ranges from 0 to 1, with values below .50 indicate the need to eliminate the item [38]. The Expected Residual correlation direct Change (EREC) index was used to assess the residual correlation between two items (called doublets); items that appear repeatedly in different doublets should be removed [39]. Since the items are scored on a Likert scale, a polychoric correlation matrix was conducted [40]. We used the Unweighted Least Squares (ULS) as the method of estimation [41], with the parallel analysis used to determine the optimal number of factors to retain [42, 43]. A minimum sample of 80 participants was needed following the recommendations of Comree and Lee (ten participants per scale\u0026rsquo;s item) [44].\u003c/p\u003e \u003cp\u003eConsequently, we conducted a CFA via the SPSS AMOS v.28 software. We estimated a minimum sample of 160 participants based on the recommendation of 20 times per scale\u0026rsquo;s variables [45]. The maximum likelihood method was used to obtain parameters estimate. Multiple fit indices were calculated: root mean square error of approximation (RMSEA) (\u0026le;\u0026thinsp;0.08), standardized root mean square residual (SRMR) (\u0026le;\u0026thinsp;0.05), Tucker-Lewis Index (TLI) and Comparative Fit Index (CFI) (\u0026ge;\u0026thinsp;.90 for both) [46]. Additionally, convergent validity was checked via the average variance extracted (AVE)\u0026thinsp;\u0026ge;\u0026thinsp;.50 [47]. Multivariate normality was not verified at first (Bollen-Stine bootstrap p\u0026thinsp;=\u0026thinsp;0.002); therefore, we performed non-parametric bootstrapping procedure.\u003c/p\u003e \u003cp\u003eA multi-group CFA was conducted to examine measurement invariance of FIES scores between genders [48] at the configural, metric, and scalar levels [49]. ΔCFI\u0026thinsp;\u0026le;\u0026thinsp;.010 and ΔRMSEA\u0026thinsp;\u0026le;\u0026thinsp;.015 or ΔSRMR\u0026thinsp;\u0026le;\u0026thinsp;.010 supported the evidence of invariance [50]. Comparison of FIES scores between genders was done using the Student\u0026rsquo;s t test.\u003c/p\u003e \u003cp\u003eComposite reliability was assessed using McDonald\u0026rsquo;s ω and Cronbach\u0026rsquo;s α, with values greater than 0.70 reflecting adequate composite reliability [51]. The FIES scores were considered normally distributed as shown by skewness and kurtosis values between \u0026minus;\u0026thinsp;1 and +\u0026thinsp;1 [52]. The association between the FIES scores and other scores was evaluated using the Pearson test.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eIn total, 534 participants participated in this study, with a majority of participants aged 19 years and 71.9% married. A total of 227 participants (42.5%) were categorized as water-insecure. The prevalence of any FI was 50.2%, with 31.3% being classified as moderately-to-severely food insecure. Other descriptive statistics of the sample can be found in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\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\u003eSociodemographic and other characteristics of the sample (N\u0026thinsp;=\u0026thinsp;534).\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\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e384 (71.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e150 (28.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e128 (24.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnmarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e406 (76.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUniversity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e498 (93.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary or less\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36 (6.70%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRefugee camps\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62 (11.60%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e105 (87.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVillage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (12.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWater insecurity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWater-insecure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e227 (42.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWater-secure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e307 (57.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFood insecurity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFood secure (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e266 (49.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMild FI (1\u0026ndash;3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e113 (21.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate FI (4\u0026ndash;6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65 (12.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSevere FI (7\u0026ndash;8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e90 (19.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eMoyenne\u003c/b\u003e\u0026thinsp;\u0026plusmn;\u0026thinsp;\u003cb\u003eSD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.74\u0026thinsp;\u0026plusmn;\u0026thinsp;7.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFood insecurity experiences (FIES total score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.27\u0026thinsp;\u0026plusmn;\u0026thinsp;2.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWater insecurity experiences (HWISE-4 scores)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.21\u0026thinsp;\u0026plusmn;\u0026thinsp;4.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePTSD (IES-6 scores)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.78\u0026thinsp;\u0026plusmn;\u0026thinsp;5.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDepression (PHQ-9 scores)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.27\u0026thinsp;\u0026plusmn;\u0026thinsp;8.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnxiety (GAD-7 scores)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.85\u0026thinsp;\u0026plusmn;\u0026thinsp;6.39\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\u003e \u003cem\u003eFIES: Food Insecurity Experiences Scale; HWISE-4: Four-Item Household Water Insecurity Experiences Scale; IES-6: Impact of Event Scale-6 ; PHQ-9: Patient Health Questionnaire-9 ; GAD-7: Generalized Anxiety Disorder 7-item.\u003c/em\u003e \u003c/p\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eExploratory and Confirmatory Factor Analyses (subsample 1 and subsample 2 respectively)\u003c/h2\u003e \u003cp\u003eThe KMO (=\u0026thinsp;.91) and Bartlett\u0026rsquo;s test (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026le;\u0026thinsp;.001) affirmed the suitability of the data. None of the items was removed according to the MSA or EREC indices, with the parallel analysis advising a unidimensional structure (explained variance of 69.72%) supported by the Goodness of Fit Index (GFI\u0026thinsp;=\u0026thinsp;.99) being greater than .95, TLI\u0026thinsp;=\u0026thinsp;1.01, CFI\u0026thinsp;=\u0026thinsp;1.00, the UniCo (=\u0026thinsp;.99) index greater than .95, the I-ECV (I-ECV\u0026thinsp;=\u0026thinsp;.93) greater than .85 and MIREAL (MIREAL\u0026thinsp;=\u0026thinsp;.17) lower than .30.\u003c/p\u003e \u003cp\u003eWe ran a CFA using the one-factor structure obtained from the EFA. The fit indices were good (RMSEA\u0026thinsp;=\u0026thinsp;0.103 (90% CI 0.083, 0.124), SRMR\u0026thinsp;=\u0026thinsp;0.034, CFI\u0026thinsp;=\u0026thinsp;0.963, TLI\u0026thinsp;=\u0026thinsp;0.948). The standardized estimates of factor loadings deriving from the EFA and CFA were all adequate (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Composite reliability of scores was adequate in the total sample (ω\u0026thinsp;=\u0026thinsp;.91 / α\u0026thinsp;=\u0026thinsp;.90). The convergent validity for this model was confirmed (AVE\u0026thinsp;=\u0026thinsp;.64).\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\u003eFactor loadings deriving from the exploratory factor analysis (EFA) and standardized loading factors deriving from the confirmatory factor analysis (CFA) of the Food Insecurity Experience Scale in Arabic.\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=\"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\u003eItem number\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQuestion\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEFA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCFA\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ1.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYou were worried you would run out of food because of a lack of money or other resources?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ2.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYou were unable to eat healthy and nutritious food because of a lack of money or other resources?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ3.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYou ate only a few kinds of foods because of a lack of money or other resources?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ4.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYou had to skip a meal because there was not enough money or other resources to get food?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ5.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYou ate less than you thought you should because of a lack of money or other resources?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ6.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYour household ran out of food because of a lack of money or other resources?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ7.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYou were hungry but did not eat because there was not enough money or other resources for food?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ8.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYou went without eating for a whole day because of a lack of money or other resources?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCronbach\u0026rsquo;s α\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMcDonald\u0026rsquo;s ω\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.94\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=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eSex Invariance (total sample)\u003c/h2\u003e \u003cp\u003eInvariance was shown at the metric and scalar levels in terms of genders (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e2\u003c/span\u003e). No significant difference was found in FIES scores between males and females (2.41\u0026thinsp;\u0026plusmn;\u0026thinsp;3.01 vs 2.21\u0026thinsp;\u0026plusmn;\u0026thinsp;2.96; \u003cem\u003et\u003c/em\u003e(532)\u0026thinsp;=\u0026thinsp;.72; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.474, Cohen\u0026rsquo;s d\u0026thinsp;=\u0026thinsp;0.069).\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 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eMeasurement Invariance of the Food Insecurity Experience Scale across gender.\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\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=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCFI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRMSEA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSRMR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eModel Comparison\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eΔCFI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eΔRMSEA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eΔSRMR\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConfigural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.963\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetric\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.965\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eConfigural vs metric\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScalar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.962\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMetric vs scalar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003cem\u003eNote.\u003c/em\u003e CFI\u0026thinsp;=\u0026thinsp;Comparative fit index; RMSEA\u0026thinsp;=\u0026thinsp;root mean square error of approximation; SRMR\u0026thinsp;=\u0026thinsp;Standardised root mean square residual.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eConcurrent validity\u003c/h2\u003e \u003cp\u003eHigher FIES scores were significantly associated with higher water insecurity experience (r\u0026thinsp;=\u0026thinsp;0.56; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), higher PTSD (r\u0026thinsp;=\u0026thinsp;0.25; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), higher depression (r\u0026thinsp;=\u0026thinsp;0.42; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and higher anxiety (r\u0026thinsp;=\u0026thinsp;0.41; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eBefore the ongoing war, the population in Gaza was already dealing with a longstanding FI and constrained access to nutritious food. Since October 7th 2023, civilians in Gaza have been facing high levels of acute FI, along with a denial of humanitarian access and assistance. Our study had as a main goal to examine psychometric properties of the FIES among Gazan adults during the ongoing war. Findings showed that approximately one out of two people in Gaza were experiencing any FI. Fit indices in CFA indicated that a one-factor solution fit the data with acceptable factor loadings, and multigroup invariance tests demonstrated that this solution fit largely equivalently across sexes. Overall, results suggest that the FIES is a valid and reliable FI measurement instrument for the Arabic-speaking Palestinian population enduring war-related starvation.\u003c/p\u003e \u003cp\u003eThe FIES conceptualizes FI as the inability to freely acquire the food needed to conduct an active, dignified and healthy life. The FIES responses are dichotomous in nature (Yes \u0026ndash; No), providing enough information to construct a one-dimensional measurement tool [20]. The current study extends previous research by using an EFA-to-CFA approach to explore the best-fitting model of the FIES in a group of civilians in Gaza being starved due to war. The eight FIES items loaded onto a single overall factor, suggesting that all items reflect a single continuous latent variable underlying the responses. Unidimensionality is a necessary condition for the use of summated scores and for any analyses based on FIES total scores. Unidimensionality is, therefore, an important attribute of the scale as it enables to report a single score representing the same underlying construct of experience-based FI at the individual level over the past year. This eases the interpretability of FIES scores, and lends supports to the assertion that the FIES can easily be adaptable across different populations and contexts, enabling standardized comparisons of prevalence data via the use of a single metric [53, 54]. Furthermore, our findings indicated that the Arabic version of the FIES presented an excellent level of reliability, with both Cronbach's alpha and McDonald omega coefficients of .94. Our results are similar to those of a study by Helmi et al. [55] showing that the Malay-language version of FIES had acceptable internal consistency (Cronbach's alpha\u0026thinsp;=\u0026thinsp;0.759) in a population-based sample aged 15-year-old and above.\u003c/p\u003e \u003cp\u003eMulti-group CFA was used to examine whether the FIES was invariant across sex groups (male or female). Cross-sex measurement invariance in the FIES was established at scalar and metric levels. This means that the eight FIES questions and their response options were understood similarly across male and female respondents. Evidence of invariance should be recognized as an important consideration before arriving at any conclusions regarding sex differences in FI. This psychometric property is relevant, especially as some empirical evidence suggested that males and females may respond to FI questions differently because of their divergent food-related responsibilities and roles [56]. Finaly, concurrent validity was evidenced by FIES's positive correlations with water insecurity experiences, PTSD, depression and anxiety symptoms. This is consistent with previous evidence from the 2014 Gallup World Poll that individual-level FI, as assessed using the FIES, and at any degree of severity, was positively correlated with specific psychosocial stressors and poorer mental health status (e.g., stress, sadness, anger, worry) across 149 countries and different global regions [57].\u003c/p\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eStudy limitations\u003c/h2\u003e \u003cp\u003eThere are some limitations to this study that merit acknowledgment. The sample was gathered using snowball sampling and an online questionnaire, which might have affected the generalizability of findings. Due to the cross-sectional nature of our data, causality could not be inferred. Moreover, the stability of the FIES over time could not be verified, as data were collected at a single point in time. In addition, findings could be subject to response and social desirability biases, as only self-administered measures were used.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eClinical and research implications\u003c/h2\u003e \u003cp\u003eTo the best of our knowledge, this study is among the first to undertake EFA and CFA to demonstrate construct validity of the single-factor structure of the FIES. As a unidimensional measure, the FIES offers a unique opportunity to compare prevalence estimates of FI across countries and over time using computed total scores obtained by summing the scores for all eight items. The international FIES thresholds defined by FAO to classify respondents based on their FI experiences levels are also made comparable across populations and different environmental settings [20], and can thus be successfully adopted to produce estimates of the prevalence of FI in Palestine during and after war [58].\u003c/p\u003e \u003cp\u003eAdditionally, this study addresses the prominent measurement issue of invariance across sex groups, as it ensures that FIES items are being interpreted identically between males and females, and allows to accurately evaluate sex differences in FI experiences in future clinical and research practices. Measurement invariance is a highly valuable, yet often neglected step in psychometric research, and only a very few studies using the FIES have provided evidence in this regard. Future studies are recommended to conduct invariance tests that enable researchers to explore and to justify cross-group comparisons of mean FIES scores.\u003c/p\u003e \u003cp\u003eThis study is also among the very limited studies to investigate the link between FI and mental health variables using standardized measures and a war-affected population. Although FI has been implicated as a causal factor for the development of mental health problems, yet the direction of this relationship remains unknown. Future longitudinal and experimental research are still needed to address this issue.\u003c/p\u003e \u003c/div\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eAltogether, our findings showed that the FIES fulfils requirements of validity and reliability, and may thus be considered as appropriate tool for assessing FI in war-affected populations currently suffering from hunger. The FIES is simple, short, economic and time-effective. It could therefore be easily implemented in war settings to measure and monitor FI for clinical, research and policy-making purposes. evaluating other psychometric aspects of the Arabic version of the FIES, such as inter-rater reliability and convergent validity, could be prolific directions for future research.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics Approval and Consent to Participate\u003c/strong\u003e:\u0026nbsp;The ethical approval for this project was granted by the scientific and ethics committee of Deanship of scientific research, Palestine Technical university \u0026ndash; Kadoorie.\u0026nbsp;A written informed consent was obtained from each participant when completing the online form. All methods were performed in accordance with the relevant guidelines and regulations (in accordance with the Declaration of Helsinki).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u0026nbsp;\u003c/strong\u003eThe data that support the findings of this study are available from the corresponding author but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of the ethics committee.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e The authors have nothing to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eNone.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u003c/strong\u003e FFR\u0026nbsp;designed the study; KJ, TS, MJ, ER, and MAAS collected the data, FFR drafted the manuscript; SH, KJ carried out the analysis and interpreted the results; KJ, WKR, IN, OS and SO reviewed the paper for intellectual content; all authors reviewed the final manuscript and gave their consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e: Not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u0026nbsp;\u003c/strong\u003eAuthor KJ would like to acknowledge support through the ICTP-Arab Fund Associates Programme (2024-2026).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eUnited Nations: \u003cstrong\u003eFamine Imminent in Gaza, Humanitarian Officials Tell Security Council, Calling for Immediate Ceasefire\u003c/strong\u003e. In\u003cem\u003e.\u003c/em\u003e; 2024.\u003c/li\u003e\n\u003cli\u003eUNRWA UNRaWAfPRitNE: \u003cstrong\u003eFrontline heroes: The Race Against the Clock to Avert Famine\u003c/strong\u003e. 2024.\u003c/li\u003e\n\u003cli\u003eIPC IFSPC: \u003cstrong\u003eFAMINE REVIEW COMMITTEE: GAZA STRIP, JUNE 2024\u003c/strong\u003e. 2024.\u003c/li\u003e\n\u003cli\u003eHassoun A, Al-Muhannadi K, Hassan HF, Hamad A, Khwaldia K, Buheji M, Al Jawaldeh A: \u003cstrong\u003eFrom acute food insecurity to famine: how the 2023/2024 war on Gaza has dramatically set back sustainable development goal 2 to end hunger\u003c/strong\u003e. \u003cem\u003eFrontiers in Sustainable Food Systems \u003c/em\u003e2024, \u003cstrong\u003e8\u003c/strong\u003e:1402150.\u003c/li\u003e\n\u003cli\u003eA. 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To achieve this, field practitioners, researchers and decision-makers should be equipped with user-friendly and psychometrically sound measures tailored to real-life war situations and the Palestinian context. Therefore, the present study aimed to test the psychometric properties of the Food Insecurity Experiences Scale (FIES) in a sample of Arabic-speaking community adults currently living in the Gaza Strip during the war.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e This study used a cross-sectional design, snowball sampling as a recruiting strategy, and a self-administered online questionnaire to collect data from participants. It was performed during the period from September 1st to 30th, 2024. A total of 534 valid responses were received and were included in the final analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Approximately one out of two people in Gaza were experiencing any FI. Fit indices in confirmatory factor analysis indicated that a one-factor solution fit the data with acceptable factor loadings. Furthermore, our findings indicated that the Arabic version of the FIES presented an excellent level of reliability, with both Cronbach's alpha and McDonald omega coefficients of .94. Cross-sex measurement invariance in the FIES was established at scalar and metric levels. Finaly, concurrent validity was evidenced by FIES's positive correlations with water insecurity experiences, post-traumatic stress, depression and anxiety symptoms.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eAltogether, our findings showed that the FIES fulfils requirements of validity and reliability, and may thus be considered as appropriate tool for assessing FI in war-affected populations currently suffering from hunger. The FIES is simple, short, economic and time-effective. It could therefore be easily implemented in war settings to measure and monitor FI for clinical, research and policy-making purposes.\u003c/p\u003e","manuscriptTitle":"Dying of starvation if not from bombs: Assessing measurement properties of the Food Insecurity Experiences Scale (FIES) in Gaza's civilian population experiencing the world’s worst hunger crisis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-11 06:03:34","doi":"10.21203/rs.3.rs-5359207/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-11-17T03:08:26+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-11-16T09:03:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"246062136751836918759957091605144014652","date":"2024-11-01T04:10:03+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-10-31T12:08:15+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-10-31T12:06:27+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-10-30T09:43:03+00:00","index":"","fulltext":""},{"type":"submitted","content":"International Journal for Equity in Health","date":"2024-10-30T07:20:48+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"international-journal-for-equity-in-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ijeh","sideBox":"Learn more about [International Journal for Equity in Health](http://equityhealthj.biomedcentral.com)","snPcode":"12939","submissionUrl":"https://submission.nature.com/new-submission/12939/3","title":"International Journal for Equity in Health","twitterHandle":"@equityhealthj","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e006af4a-4651-48be-92b3-f1f6e1660d47","owner":[],"postedDate":"November 11th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-03-24T16:05:01+00:00","versionOfRecord":{"articleIdentity":"rs-5359207","link":"https://doi.org/10.1186/s12939-024-02365-3","journal":{"identity":"international-journal-for-equity-in-health","isVorOnly":false,"title":"International Journal for Equity in Health"},"publishedOn":"2025-03-20 15:58:29","publishedOnDateReadable":"March 20th, 2025"},"versionCreatedAt":"2024-11-11 06:03:34","video":"","vorDoi":"10.1186/s12939-024-02365-3","vorDoiUrl":"https://doi.org/10.1186/s12939-024-02365-3","workflowStages":[]},"version":"v1","identity":"rs-5359207","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5359207","identity":"rs-5359207","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}