This study evaluated the impact of a 6-month school nutrition intervention on changes in dietary knowledge, attitude, behavior (KAB) and nutritional status of Syrian refugee children. A quasi-experimental design was followed; Syrian refuge children in grades 4 to 6 were recruited from three informal primary schools (two intervention and one control) located in the rural Bekaa region of Lebanon. The intervention consisted of two main components: classroom-based education sessions and provision of locally-prepared healthy snacks. Data on household socio-demographic characteristics, KAB, anthropometric measures and dietary intake of children were collected by trained field workers at baseline and post-intervention. Of the 296 school children enrolled, 203 (68.6%) completed post-intervention measures. Significant increases in dietary knowledge (β = 1.22, 95% CI: 0.54, 1.89), attitude (β = 0.69, 95% CI: 0.08, 1.30), and body mass index-for-age-z-scores (β = 0.25, 95% CI = 0.10, 0.41) were observed among intervention vs. control groups, adjusting for covariates (p < 0.05). Compared to the control, the intervention group had, on average, significantly larger increases in daily intakes of total energy, dietary fiber, protein, saturated fat, and several key micronutrients, p < 0.05. Findings suggest a positive impact of this school-based nutrition intervention on dietary knowledge, attitude, and nutritional status of Syrian refugee children. Further studies are needed to test the feasibility and long-term impact of scaling-up such interventions.

The coronavirus (COVID-19) pandemic has had serious repercussions on the global economy, work force, and food systems. In Lebanon, the pandemic overlapped with an economic crisis, which threatened to exacerbate food insecurity (FI). The present study aims to evaluate the trends and projections of FI in Lebanon due to overlapping health and economic crises. Data from Gallup World Poll (GWP) 2015–2017 surveys conducted in Lebanon on nationally representative adults (n = 3000) were used to assess FI trends and explore its sociodemographic correlates. Predictive models were performed to forecast trends in FI (2018–2022), using GWP data along with income reduction scenarios to estimate the impact of the pandemic and economic crises. Pre crises, trend analyses showed that FI could reach 27% considering wave year and income. Post crises, FI was estimated to reach on average 36% to 39%, considering 50–70% income reduction scenarios among Lebanese population. FI projections are expected to be higher among females compared to males and among older adults compared to younger ones (p < 0.05). These alarming findings call for emergency food security policies and evidence-based programs to mitigate the burden of multiple crises on the FI of Lebanese households and promote resilience for future shocks.

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Objectives: The SF-6D is a preference-based measure of health developed to generate utility values from the SF-36. The aim of this pilot study was to examine the feasibility and acceptability of using the standard gamble (SG) technique to generate preference-based values for the Arabic version of SF-6D in a Lebanese population. Methods: The SF-6D was translated into Arabic using forward and backward translations. Forty-nine states defined by the SF-6D were selected using an orthogonal design and grouped into seven sets. A gender-occupation stratified sample of 126 Lebanese adults from the American University of Beirut were recruited to value seven states and the pits using SG. The sample size is appropriate for a pilot study, but smaller than the sample required for a full valuation study. Both interviewers and interviewees reported their understanding and effort levels in the SG tasks. Mean and individual level multivariate regression models were fitted to estimate preference weights for all SF-6D states. The models were compared with those estimated in the UK. Results: Interviewers reported few problems in completing SG tasks (0.8% with a lot of problems) and good respondent understanding (5.6% with little effort and concentration), and 25% of respondents reported the SG task was difficult. A total of 992 SG valuations were useable for econometric modeling. There was no significant change in the test–retest values from 21 subjects. The mean absolute errors in the mean and individual level models were 0.036 and 0.050, respectively, both of which were lower than the UK results. The random effects model adequately predicts the SG values, with the worst state having a value of 0.322 compared to 0.271 in the UK. Conclusion: This pilot confirmed that it was feasible and acceptable to generate preference values with the SG method for the Arabic SF-6D in a Lebanese population. However, further work is needed to extend this to a more representative population, and to explore why no utility values below zero were observed.