Targeting mechanisms for cash transfers using regional aggregates

We propose an empirical method for improving food assistance scoring and targeting, which minimizes under-coverage and leakage of food and cash assistance programs. The empirical strategy relies on a joint econometric estimation of food insecurity and economic vulnerability indicators at the household level, using data-driven instead of predetermined quantiles.We apply the method to recent micro data on Syrian refugees in Lebanon, to explore how regional and community-based aggregates can improve the targeting effectiveness of aid programs, notably food aid by the World Food Program in Lebanon. Our results confirm that using regional aggregates are useful for augmenting the Balanced Poverty Accuracy Criterion, and our method performs much better than the current policy in terms of targeting effectiveness and accuracy for economically vulnerable households

Food Insecurity and Subjective Wellbeing Among Arab Youth Living in Varying Contexts of Political Instability.

PURPOSE: To investigate associations between food insecurity experience and subjective wellbeing in Arab youth, across different political stability settings. METHODS: Data from the Gallup World Poll (2014-2015) were extracted for youth aged 15-24 years living in 19 Arab countries (n = 8,162). Food insecurity was assessed using the Food Insecurity Experience Scale. Life Evaluation Score and Affect Balance were used as indicators of youth wellbeing. The 2014 Political Stability and Absence of Violence and Terrorism score was used to stratify Arab countries into three categories; high, medium, and low political stability. Multivariable regressions were performed to explore the relationship between food insecurity and wellbeing indices adjusting for socio-demographic and socio-economic factors, across different political stability settings. RESULTS: The prevalence of food insecurity among Arab youth ranged between 3.1% in Lebanon to 91.3% in South Sudan. Food insecurity (moderate and severe) was negatively correlated with life evaluation (β: -0.74 for moderate food insecurity; -1.28 for severe food insecurity, p-value <0.001), and affect balance (β: -22.03 for moderate food insecurity; -33.88 for severe food insecurity, p-value <0.001). These results were consistent across political stability groups, independently from socio-demographic and socio-economic factors. Fewer factors were correlated with life evaluation and affect balance in low as compared to medium and high political stability settings. CONCLUSIONS: Food insecurity is an independent risk factor for Arab youth wellbeing. Efforts to improve youth wellbeing can be channelled through food security interventions

Child‐level double burden of malnutrition in the MENA and LAC regions: Prevalence and social determinants

Although the prevalence of obesity has rapidly increased in the low‐ and middle‐income countries of the Middle East and North Africa (MENA) and Latin America and the Caribbean (LAC) regions, child undernutrition remains a public‐health challenge. We examined region‐specific sociodemographic determinants of this double burden of malnutrition, specifically, the co‐occurrence of child stunting and overweight, using Demographic and Health Survey and Multiple Indicator Cluster Survey data (2003–2016) from 11 countries in the MENA (n = 118,585) and 13 countries in the LAC (n = 77,824) regions. We used multiple logistic regressions to model region‐specific associations of maternal education and household wealth with child nutritional outcomes (6–59 months). The prevalence of stunting, overweight, and their co‐occurrence was 24%, 10%, and 4.3% in children in the MENA region, respectively, and 19%, 5%, and 0.5% in children in the LAC region, respectively. In both regions, higher maternal education and household wealth were significantly associated with lower odds of stunting and higher odds of overweight. As compared with the poorest wealth quintiles, decreased odds of co‐occurring stunting and overweight were observed among children from the second, third, and fourth wealth quintiles in the LAC region. In the MENA region, this association was only statistically significant for the second wealth quintile. In both regions, double burden was not statistically significantly associated with maternal education. The social patterning of co‐occurring stunting and overweight in children varied across the two regions, indicating potential differences in the underlying aetiology of the double burden across regions and stages of the nutrition transition.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154671/1/mcn12923_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154671/2/mcn12923.pd

Syrian Refugees and Digital Health in Lebanon

There are currently over 1.1 million Syrian refugees in need of healthcare services from an already overstretched Lebanese healthcare system. Access to antenatal care (ANC) services presents a particular challenge. We conducted focus groups with 59 refugees in rural Lebanon to identify contextual and cultural factors that can inform the design of digital technologies to support refugee ANC. Previously identified high utilization of smartphones by the refugee population offers a particular opportunity for using digital technology to support access to ANC as well as health advocacy. Our findings revealed a number of considerations that should be taken into account in the design of refugee ANC technologies, including: refugee health beliefs and experiences, literacy levels, refugee perceptions of negative attitudes of healthcare providers, and hierarchal and familial structures

Rapid turnover of T cells in acute infectious mononucleosis.

During acute infectious mononucleosis (AIM), large clones of Epstein-Barr virus-specific T lymphocytes are produced. To investigate the dynamics of clonal expansion, we measured cell proliferation during AIM using deuterated glucose to label DNA of dividing cells in vivo, analyzing cells according to CD4, CD8 and CD45 phenotype. The proportion of labeled CD8(+)CD45R0(+) T lymphocytes was dramatically increased in AIM subjects compared to controls (mean 17.5 versus 2.8%/day; p<0.005), indicating very rapid proliferation. Labeling was also increased in CD4(+)CD45R0(+) cells (7.1 versus 2.1%/day; p<0.01), but less so in CD45RA(+) cells. Mathematical modeling, accounting for death of labeled cells and changing pool sizes, gave estimated proliferation rates in CD8(+)CD45R0(+) cells of 11-130% of cells proliferating per day (mean 47%/day), equivalent to a doubling time of 1.5 days and an appearance rate in blood of about 5 x 10(9) cells/day (versus 7 x 10(7) cells/day in controls). Very rapid death rates were also observed amongst labeled cells (range 28-124, mean 57%/day),indicating very short survival times in the circulation. Thus, we have shown direct evidence for massive proliferation of CD8(+)CD45R0(+) T lymphocytes in AIM and demonstrated that rapid cell division continues concurrently with greatly accelerated rates of cell disappearance

COVID-19 vaccine acceptance in older Syrian refugees : Preliminary findings from an ongoing study

Funding source This work was supported by ELRHA’s Research for Health in Humanitarian Crisis (R2HC) Programme, which aims to improve health outcomes by strengthening the evidence base for public health interventions in humanitarian crises. R2HC is funded by the UK Foreign, Commonwealth and Development Office (FCDO), Wellcome, and the UK National Institute for Health Research (NIHR). The views expressed herein should not be taken, in any way, to reflect the official opinion of the NRC or ELRHA. The funding agency was not involved in the data collection, analysis or interpretation.Peer reviewedPublisher PD

Capturing children food exposure using wearable cameras and deep learning

Children’s dietary habits are influenced by complex factors within their home, school and neighborhood environments. Identifying such influencers and assessing their effects is traditionally based on self- reported data which can be prone to recall bias. We developed a culturally acceptable machine-learning-based data-collection system to objectively capture school-children’s exposure to food (including food items, food advertisements, and food outlets) in two urban Arab centers: Greater Beirut, in Lebanon, and Greater Tunis, in Tunisia. Our machine-learning-based system consists of 1) a wearable camera that captures continuous footage of children’s environment during a typical school day, 2) a machine learning model that automatically identifies images related to food from the collected data and discards any other footage, 3) a second machine learning model that classifies food-related images into images that contain actual food items, images that contain food advertisements, and images that contain food outlets, and 4) a third machine learning model that classifies images that contain food items into two classes, corresponding to whether the food items are being consumed by the child wearing the camera or whether they are consumed by others. This manuscript reports on a user-centered design study to assess the acceptability of using wearable cameras to capture food exposure among school children in Greater Beirut and Greater Tunis. We then describe how we trained our first machine learning model to detect food exposure images using data collected from the Web and utilizing the latest trends in deep learning for computer vision. Next, we describe how we trained our other machine learning models to classify food-related images into their respective categories using a combination of public data and data acquired via crowdsourcing. Finally, we describe how the different components of our system were packed together and deployed in a real-world case study and we report on its performance

DeepNOVA : a deep learning NOVA classifier for food images

Assessing the healthiness of food items in images has gained attention in both the computer vision and the nutrition fields. However, such task is generally a difficult one as food images are captured in various settings and thus are usually non-homogeneous. Moreover, assessing how healthy a food item is requires nutritional expertise and knowledge of the constituents of the food item and how it is processed. In this manuscript, we propose an end-to-end deep learning approach that can detect and localize various food items in a given food image using a customized object detection model. Our approach then assesses how healthy each detected food item is by classifying it into one or more of the four NOVA groups (Unprocessed Food, Processed Culinary Ingredients, Processed Food, and Ultra-processed Food). To train our food item detection model, we used two public datasets and a custom one we created ourselves and which contains images of food taken using wearable cameras. To train the NOVA food classifier, we use the custom dataset we created ourselves and that was manually labeled by expert nutritionists. Our food item detection model achieved a mAP of 0.90 and the NOVA food classifier achieved an average F1-score of 0.86 on test data

Predictors of complementary feeding practices among children aged 6-23 months in five countries in the Middle East and North Africa region

Ensuring diets of children aged 6-23 months meet recommended guidance is crucial for growth and development and for the prevention of malnutrition including stunting, wasting and micronutrient deficiencies. Despite some improvement, indicators related to undernutrition and overnutrition fall short of global targets in the Middle East and North Africa (MENA) region that consist of low- and middle-income countries witnessing political and social changes and a nutrition transition. This research aims at reviewing the situation related to the diets of children aged 6-23 months in five selected countries in the MENA region, examining factors affecting complementary feeding and providing recommendations for guiding effective strategies to improve it. The study triangulated data on complementary feeding status and predictors from semistructured interviews with 30 key informants, and multivariable analysis of household surveys in Egypt, Jordan, Lebanon, State of Palestine and Sudan including data on refugees in Lebanon and Jordan. There remain considerable gaps in complementary feeding differing noticeably among geographic areas. Findings from qualitative and quantitative analyses showed that maternal factors, including maternal education and age, household level factors such as paternal education and wealth, community-level factors (culture and geographic location), and utilization of health services, were associated with minimum dietary diversity (MDD), minimum meal frequency (MMF) and minimum acceptable diet (MAD) at varied levels in the five countries. Interventions to improve complementary feeding practices should include actions tailored to the needs of the population at multiple levels including at the caregiver's level, household, service use, community and policy level

The determinants of sustained adherence to COVID-19 preventive measures among older Syrian refugees in Lebanon

Acknowledgments The authors thank the participants at the Economic Research Forum annual conference in March 2022 for comments. Funding: SA and HG received the ELRHA Research for Health in Humanitarian Crises award (Number 51538) for "Tracking adherence of older refugees to COVID-19 preventive measures in response to changing vulnerabilities: A multi-level, panel study to inform humanitarian response in Lebanon". This work was supported by ELRHA’s Research for Health in Humanitarian Crisis (R2HC) Programme, which aims to improve health outcomes by strengthening the evidence base for public health interventions in humanitarian crises. R2HC is funded by the UK Foreign, Commonwealth and Development Office (FCDO), Wellcome, and the UK National Institute for Health Research (NIHR). The views expressed herein should not be taken, in any way, to reflect the official opinion of the NRC or ELRHA. The funding agency was not involved in the data collection, analysis or interpretation. ELRHA: https://www.elrha.org/programme/research-for-health-in-humanitarian-crises/ The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.Peer reviewedPublisher PD