key: cord-1053862-vfxgb19k authors: Picchioni, Fiorella; Goulao, Luis F.; Roberfroid, Dominique title: The impact of COVID-19 on diet quality, food security and nutrition in Low and Middle Income Countries: A systematic review of the evidence date: 2021-08-27 journal: Clin Nutr DOI: 10.1016/j.clnu.2021.08.015 sha: 9fae4b47d6f1220663c70a70b9013b2370675699 doc_id: 1053862 cord_uid: vfxgb19k Background & Aims The current global pandemic of Coronavirus (COVID-19), and measures adopted to reduce its spread, threaten the nutritional status of populations in Low- and middle-income countries (LMICs). Documenting how the COVID-19 affects diets, nutrition and food security can help generating evidence-informed recommendations for mitigating interventions and policies. Methods We carried out a systematic literature review. A structure search strategy was applied in MEDLINE (Pubmed®), EMBASE®, Scopus® and Web of Science®. Grey literature was retrieved by screening a pre-set list of institutions involved in monitoring the impact of COVID-19 pandemic on nutrition and food security. The first search was done on 20th August 2020, and updated in mid-November 2020 and mid-January 2021. All research steps were described as recommended in the PRISMA statement. Results Out of the 2085 references identified, thirty-five primary studies were included. In spite of their heterogeneity, studies converge to demonstrate a detrimental effect of COVID-19 pandemic and associated containment measures on diet quality and food insecurity. One of the major direct effects of COVID-19 on food and nutrition outcomes has been through its impact on employment, income generating activities and associated purchasing power. Other channels of impact, such as physical access, availability and affordability of food provided a heterogeneous picture and were assessed via binary and often simplistic questions. The impacts of COVID-19 manifested with various intensity degrees, duration and in different forms. Factors contributing to these variations between and within countries were: 1) timing, duration and stringency of national COVID-19 restriction measures and policies to mitigate their adverse impacts; 2) context specific food value chain responses to domestic and international containment measures; 3) differentiated impacts of restriction measures on different groups, along lines of gender, age, socio-economic status and employment conditions. Dietary changes and food insecurity manifested various intensity degrees, duration and in different forms between and within countries. Shorter value chains and traditional smallholder farms were somewhat more resilient in the face of COVID-19 pandemic. Additionally, the impact of the pandemic has been particularly adverse on women, individuals with a low socio-economic status, informal workers and young adults that relied on daily wages. Finally, there were heterogeneous government responses to curb the virus and to mitigate the damaging effects of the pandemic. It has been demonstrated that existing and well-functioning social protection programmes and public distribution of food can buffer the adverse effects on food insecurity. But social safety nets cannot be effective on their own and there is a need for broader food systems interventions and investments to support sustainable and inclusive food systems to holistic achieve food and nutrition security. Conclusion In conclusion, the current economic and heath crisis impact diet quality and food security, and this raises concerns about long term impacts on access to and affordability of nutrient-rich, healthy diets and their health implications. Women and individuals with a low socio-economic are the most at risk of food insecurity. Social safety nets can be effective to protect them and must be urgently implemented. We advocate for improved data collection to identify vulnerable groups and measure how interventions are successful in protecting them. pre-set list of institutions involved in monitoring the impact of COVID-19 pandemic on nutrition and food security. The first search was done on 20 th August 2020, and updated in mid-November 2020 24 and mid-January 2021. All research steps were described as recommended in the PRISMA 25 statement. 26 Results 27 Out of the 2085 references identified, thirty-five primary studies were included. In spite of their 28 heterogeneity, studies converge to demonstrate a detrimental effect of COVID-19 pandemic and 29 associated containment measures on diet quality and food insecurity. One of the major direct effects 30 of COVID-19 on food and nutrition outcomes has been through its impact on employment, income 31 generating activities and associated purchasing power. Other channels of impact, such as physical 32 access, availability and affordability of food provided a heterogeneous picture and were assessed via 33 binary and often simplistic questions. The impacts of COVID-19 manifested with various intensity 34 degrees, duration and in different forms. Factors contributing to these variations between and 35 within countries were: 1) timing, duration and stringency of national COVID-19 restriction measures 36 and policies to mitigate their adverse impacts; 2) context specific food value chain responses to 37 domestic and international containment measures; 3) differentiated impacts of restriction measures 38 on different groups, along lines of gender, age, socio-economic status and employment conditions. 39 Dietary changes and food insecurity manifested various intensity degrees, duration and in different 40 forms between and within countries. Shorter value chains and traditional smallholder farms were 41 somewhat more resilient in the face of COVID-19 pandemic. Additionally, the impact of the 42 pandemic has been particularly adverse on women, individuals with a low socio-economic status, 43 informal workers and young adults that relied on daily wages. Finally, there were heterogeneous 44 government responses to curb the virus and to mitigate the damaging effects of the pandemic. It has 45 been demonstrated that existing and well-functioning social protection programmes and public 46 distribution of food can buffer the adverse effects on food insecurity. But social safety nets cannot 47 be effective on their own and there is a need for broader food systems interventions and 48 security. 50 Conclusion 51 In conclusion, the current economic and heath crisis impact diet quality and food security, and this 52 raises concerns about long term impacts on access to and affordability of nutrient-rich, healthy diets 53 and their health implications. Women and individuals with a low socio-economic are the most at risk 54 of food insecurity. Social safety nets can be effective to protect them and must be urgently 55 implemented. We advocate for improved data collection to identify vulnerable groups and measure 56 how interventions are successful in protecting them. 57 Keywords: Food Security, Nutrition, Social Safety conducted for countries and reports already in the list. 121 All references were imported into Mendeley (© 2020 Mendeley) where duplicates were detected 122 and eliminated. Title and abstract screening was carried out on Rayyan 2 and irrelevant material 123 eliminated. All remaining reports and studies identified as potentially eligible were assessed on full-124 text. 125 The quality appraisal of included studies was based on the grids for observational studies proposed 126 by the Joanna Briggs Institute 3 . These grids serve to appraise a number of items (e.g. appropriate 127 sampling) in a systematic way with no aim of yielding an overall quality score. Data extraction 128 included: 1) information about study reference(s) and author(s); 2) verification of study eligibility; 3) 129 study characteristics; 4) study methods; 5) participants; 6) interventions; 7) outcomes measures and 130 results. Studies selection, quality appraisal, and data extraction were done by one researcher (FP). A 131 second researcher (DR) independently checked a sub-sample of publications and any doubtful 132 inclusion/exclusion and the final decision was made by consensus. No meta-analysis was 133 undertaken because of the wide variety of study designs and heterogeneity of outcomes reported. 134 Three searches -end of August and mid-November 2020, mid-January 2021 -for both the peer-138 reviewed and grey literature were conducted. The first search yielded 1079 and 139 peer-reviewed 139 and grey literature citations respectively, of which 16 (2 peer-reviewed and 14 grey literature 140 studies) were included. The second search yielded 308 peer-reviewed and 48 grey literature papers 141 and reports, of which 11 (5 peer-reviewed and 6 grey literature studies) were retained. The last 142 search in January 2021, yielded 508 peer-reviewed papers and 29 grey literature citations, of which 143 10 (5 each for both types of studies) were included. Therefore, 35 primary studies were included, of 144 which 10 were peer-reviewed and 25 were studies and report retrieved from grey literature sources. 145 The overall selection process is presented in the PRISMA flow chart (Figure 1 ). Excluded studies after 146 full text examination are presented in Annex 3, with reasons for exclusion. 147 Most studies were single or repeated cross-sectional studies. The vast majority of them presented 155 the common weaknesses of not describing the sampling process nor the proportion of no 156 respondents. Therefore, included studies were evaluated low quality except the interrupted time 157 series study in Bangladesh (25) which was rated high quality. Table 3 summarises the main 158 information of the search results, including outcomes measured and study design. We did not find 159 any study designed to explicitly monitor the diet quality and nutrition of children under-5 years old 160 or and women/girls of childbearing age, although they were the priority groups. Few studies 161 included the gender and urban-rural breakdown of results. In terms of geographical coverage, the 162 selected papers included Bangladesh (two studies) (25,33), Ivory Coast (two studies) (34,35), 163 Ethiopia (15 papers) (12) (13) (14) (15) 17, 19, 20, 22, 26, 31) , India (two papers) (16,27), Kenya (one paper) (18), 164 Zambia (one paper) (30). The 15 studies on Ethiopia include 6 rounds of the World Bank high-167 frequency phone survey conducted between May-October 2020. The 7 studies on Nigeria include 6 168 rounds of the World Bank high-frequency phone survey conducted between May-November 2020. 169 Each of these 2 batches was referenced in the table as one unique entry for space reason. 170 The majority of the studies were longitudinal (7 studies) and cross-sectional phone surveys (13 171 studies). The remaining studies were: interrupted time series (1 study), phone exploratory 172 qualitative assessment (2 studies) and repeated cross-sectional (3 studies). 173 Data extraction tables and quality appraisal can be found in a separate document (available on 174 demand). 175 5 All participants were mothers or female guardians of children enrolled in the "Benefits and risks of iron interventions in children" (BRISC) trial-a randomised controlled trial of preventive iron supplementation or placebo given to infants aged 8 months (ACTRN12617000660381) with a primary outcome of child cognitive development after 3 months of intervention. The BRISC trial was set in Rupganj upazila (county) of Narayanganj district, a rural area about 35 km northeast of Dhaka, which covers about 235 km² and comprises about 82000 households. 6 Face-to-face survey was conducted in areas where contagion rates were low (green and yellow zones) while online surveys were conducted in areas with high contation rates (red zones). Data from 1164 (62 %) participants were collected randomly via face-to-face interviews, and data from 712 (38 %) participants were collected using online platforms. 7 The study was conducted in 30 districts of Abidjan. 8 By the time this study was finalised, the World Bank High-frequency Phone Survey in Ethiopia had conducted 6 survey rounds (early May-October 2020). Each round included a different sample sizes: Round1: 3,249; Round 2: 3,107; Round 3: 3,058; Round 4: 2,878; Round 5: 2,770; Round 6: 2,704. 13 100 commercial and small dairy farmers dairy processors, traders, development agents, urban retailers, and consumers in rural and urban Ethiopia. 14 Respondents were all beneficiaries of the fourth phase of Ethiopia's Productive Safety Net Program (PSNP4) and who also participate in the USAID-funded Strengthening PSNP4 Institutions and Resilience (SPIR) project. 15 The study setting was rural Ethiopia: North Wollo and Wag Himra zones in Amhara, and primarily in East and West Hararghe zones in Oromia. 16 The study included one question asked about the variations of children's egg and fresh dairy product consumption. 17 Farmers included smallholders and investors (depending on the amount of land they were renting in) and they resided in the four major vegetable producing districts in East Shewa zone in the Oromia region (Adami Tulu, Bora, Dugda, and Lume). Urban wholesalers operated in Addis Ababa and urban retailers were located in five sub-cities in Addis Ababa. The population sample included urban poor households and "special segment" population (i.e. particularly vulnerable groups such as day labourers). The study was conducted in 10 selected cities in Ethiopia: Addis Ababa, Mekelle, Dire Dawa, Adama, Gambela, Bahir Dar, Jigjiga, Bulehora, Logia, and Semera. Participants were part of the Urban Productive Safety Net Project (UPSNP), households who own a small-scale business (SSB), and refugees/IDPs/returnees. 19 The study was conducted in Jharkhand, Assam, Andhra Pradesh, and Karnataka. 20 All respondents were farmers and producing vegetables. The questionnaire was sent to random respondents in Kenya and Uganda using social media (WhatsApp, Facebook, Telegram, and Twitter), and via email. 23 The study was included in 3 survey rounds with different sample sizes: Round1: 833; Round2: 850; Round3: 1,674. 24 The monthly surveys were collected based on a one-stage probabilistic sample of mobile telephone numbers which are randomly selected from the publicly available National Dialing Plan. 25 ENCOVID-19 is a monthly telephone cross-sectional survey, representative at a national level of individuals 18 years and older who have a mobile phone. 26 Farmers in rural Nepal (Dang district of Province 5) and rural Senegal (across the country) healthy diets (12, 13, (15) (16) (17) (18) . In Addis Ababa (Ethiopia), Food Consumption Score (FCS) collected over 192 three survey rounds (May-July 2020) (12) (13) (14) 17) showed that compared to pre-pandemic baseline 193 (January-February 2020) households were consuming fruit and animal source foods less frequently. 194 In a study conducted in rural Ethiopia (regions of Oromia and Amhara), 70% and 68% of interviewed 195 parents reported children's consumption of eggs and dairy had decreased, respectively, between 196 February and June 2020 (15). In India, Harris et al. (16) showed that, 62% of surveyed farm 197 households reported changes in their diets as a result of COVID-19 33 ; 17% of households did report a 198 fall in ability to procure staple foods; approximately 50% and 25% reported falls in consumption of 199 33 The study was conducted in May 2020, six weeks into the national lockdown and in the early stages of various states' relief packages. The paper reports that the question was asked in binary terms as: "Has your household diet changed as a result of COVID-19?" Therefore, it was unclear if the effects of COVID-19 are intended from when the first cases were registered in India (Jan 2020) or since lockdown measures took place (24th March 2020). study conducted in April 2020 reported that 40% and 55% of respondents in the respective countries 201 changed their diets involuntarily (especially to the detriment of nutritious foods) since the outbreak of 202 the virus (18). 203 When gendered disaggregated data was available, evidence on dietary degradations, since the COVID-204 19 outbreak and imposition of restriction measures, showed women were affected to a larger degree 205 than men. HDDS and FCS in Addis Ababa was consistently lower among female-headed households 206 between May and July 2020(12-14); in India, women farmers were significantly more likely than men 207 to report a stronger reduction in consumption of vegetables, fruit, and dairy products (16). Since the 208 pandemic 16% and 30% of women farmers reported that they were eating less and purchasing 209 cheaper foods, respectively, (compared to 5% and 6% of men, respectively) 210 Eleven 34 studies assessed the status of food security since the outbreak of [18] [19] [20] [21] [22] [23] [24] [25] . 212 Food Insecurity Access Scale (HFIAS) (60) and non-standard food insecurity questions. The reviewed 214 studies agree that levels of food insecurity during the pandemic were high; when pre-pandemic data 215 were available, food insecurity indicators worsened during the COVID-19 outbreak (18,21,23-25) 216 (Table 4) . 217 The impact of food insecurity was differentiated among different demographic groups, such as 221 female-headed households, poorer families, young adults and workers in the informal sector. In 222 Addis Ababa, where the percentage of households in moderate and severe food insecurity status in 223 July 2020 reduced compared to May and June 2020 (by approximately 5%), food insecurity remained 224 higher among female-headed and poorer households (12) (13) (14) . In Ethiopia, a longitudinal study 225 conducted among young individuals (June-July 2020) the likelihood of experiencing food insecurity 226 was 27% higher among those that suffered food insecurity in the baseline survey (2016) and that 227 lived in urban areas (19) . Similarly, urban vulnerable households, whose survival depends on daily 228 generated income, restrictions and lockdowns led to food insecurity: the percentage of households 229 who consumed an average of three meals a day reduced from 87.6% before COVID-19 to 62.2% at 230 the time of the interview (22) 36 . A study conducted in Mexico (23) for which socio-economic status 231 data disaggregation was available showed that, even though mild food insecurity was present at 232 every SES level, moderate and severe food insecurity increased among lower socio-economic groups. 233 35 ELCSA is an adapted version of HFIAS and has been extensively validated for Mexico to measure multidimensional poverty (23). 36 The 10 selected cities in Ethiopia include: Addis Ababa, Mekelle, Dire Dawa, Adama, Gambela, Bahir Dar, Jigjiga, Bulehora, Logia, and Semera. The study was conducted among 436 households part of Urban Productive Safety Net Project (UPSNP), households who own a small-scale business (SSB), and refugees/IDPs/returnees. The study had planned to conduct monthly interviews between July-December 2020. J o u r n a l P r e -p r o o f indicators, food access was not measured in a uniform way among studies. Overall, the reviewed 236 studies indicated food access was affected negatively since the start of the pandemic and hit poorer 237 household to a larger degree (32). Therefore, even if at later stages of the pandemic food access 238 improved (i.e. when lockdown measures are lifted), the percentages of households having difficulties 239 to access food are higher among lower income quintiles (21). In Bangladesh, Kundu et al. (33) 240 illustrated that 45.3% and 61.0% of interviewed households in September 2020 reported that they 241 did not access the same quantity or type of food respectively as they did prior to 242 respectively. The studies that reported access to different food items show that the changes were 243 product specific, suggesting heterogeneous impacts across different food value chains. For example, 244 yams and teff were the commodities less accessible by households in Nigeria and Ethiopia, 245 respectively (20, 21) . We observed that in Ethiopia there was a recovery a few months after the 246 beginning of the pandemic(20), likely due to the easing of lockdown measures and distribution 247 agricultural inputs. 248 approximately 5% of farmers reported difficulties to afford sufficient variety of food, and the poorer 266 state of Odisha, where baseline instances of food unaffordability were already high (approximately 267 90%), and no significant difference in affordability before and after the lockdown was found. Authors 268 suggested more diverse cropping patterns, a higher prevalence of homestead gardens, and shorter 269 value chains for agricultural products helped food affordability of farmers in Odisha (27). 270 There is much consensus among the studies that the major direct effect of COVID-19 and the 272 measures put in place by local and national authorities has been through its impact on employment 273 and, in turn, on income (22 studies (12) (13) (14) (15) (16) (17) (18) (19) (20) (21) (22) 24, 25, 27, 29, (32) (33) (34) (35) 37) ). Between 80% and 58% of 274 respondents interviewed across Ethiopia, Nigeria, Kenya, Uganda, South Africa and Senegal reported 275 either their incomes had decreased compared to the pre-pandemic baseline period directly affecting 276 their food affordability due to adverse impacts on their regular source of income caused by 277 reduction or closure of business activities, cessation of remittances, and government restrictions 278 measures (12) (13) (14) (15) 18, 20, 21, 32, 37) . In Bangladesh, studies reported income decreased due to COVID-279 19 among 71,8 % of respondents (33); 96% of surveyed women reported a reduction in paid work 280 and median monthly family income fall of 72% (USD 212 was the baseline level) (25). 281 85% of rural Nepalese households interviewed in June and mid-July 2020 (32). Several of the 284 reviewed studies highlighted that the figures are usually higher for informal workers and younger 285 adults in urban areas (19, 22, 37) , and in remote areas (29). 286 3.6.2 Food prices 287 The review of the impacts of the Covid-19 pandemic on food prices suggests a nuanced picture. Food 288 price increases were reported in Nigeria (24) 38 , where, since the outbreak of COVID-19, the food 289 consumer price index (CPI) increased by 24% and between April/May 2020 90% of households 290 reported facing food price increase, compared to 85% in mid-March, and 19% between January 2017 291 and January 2018 (21). In the capital of Côte d'Ivoire (Abidjan), 61 % of respondents reported 292 significant increases in food prices since the outbreak of the pandemic (35). In Bangladesh (33), 94% 293 of the 1876 households that took part in the study reported that they faced food price increases due 294 to Other studies suggested a more heterogeneous and variable food price situation, where prices can 296 fluctuate over the course of several weeks. For example in Ethiopia, prices was the main reason to 297 explain households' inability to purchase food items at the start of the pandemic (approx. 40% of 298 respondents) (20). However, this gradually decreased so by October 2020, high food prices were 299 mentioned by <10% of respondents (mainly in urban areas). 300 various pathways (2). There is a large consensus among the literature that one of the major direct 317 effects of COVID-19 on food and nutrition outcomes has been through its impact on the 318 employment, income and associated purchasing power. This is corroborated by the studies we 319 assessed in the report (12) (13) (14) (19) (20) (21) (22) 25, 32, 33, 37) as well as by commentaries and reports produced 320 by international organisations (38,39). However, the link between a fall in income and changes in 321 consumption behaviours and diet quality, although plausible, was not studied as such. Other 322 channels of impact, such as physical access, availability and affordability of food provided a 323 heterogeneous picture and were assessed via binary (and often simplistic) questions 324 (20, 21, 27, 32, 33) . 325 A shift from relatively more nutritious foods groups and expensive sources of calories (e.g., legumes, 326 nuts, animal source foods) to relatively nutrient poor and cheaper ones (staples) was observed since 327 the start of . The production and distribution of perishable and more nutritious 328 sources of calories and decreased levels of dietary diversity, are increasing concerns about the 330 deepening of the triple burden of malnutrition (i.e. undernutrition; overweight and obesity; and 331 micronutrient deficiencies) especially in light of rapid urbanization in LMICs (42,43). Studies have 332 described the incidence of elevated consumption of ultra-processed foods, alcohol and lack of 333 physical activity during lockdown (44, 45) . While these issues were not included in the primary 334 outcomes of this review, there is urgent need to systematically assess the effects of COVID-19 on 335 overweight and obesity, as a result of changes in consumers' behaviour, access to healthy diets and 336 a general degradation in healthy diets environments. 337 Interacting factors 339 Dietary changes and food insecurity manifested various intensity degrees, duration and in different 340 forms between and within countries. Several interacting factors can contribute to these. Firstly, the 341 few studies on food value chains assessments suggested that shorter value chains and traditional 342 smallholder farms were somewhat more resilient in the face of COVID-19. They depended on local 343 inputs (local indigenous seeds, compost, and family and community labour exchange) as opposed to 344 commercial or semi-commercial farms, more severely hit (26, 28, 46) . However, with the exception of 345 one article (27), to our knowledge there were no other studies that linked the impacts of COVID-19 346 on agricultural processes and the dynamics and implications on rural households' incomes and food 347 insecurity. Despite food systems thinking and analysis is recognised as an important and meaningful 348 framework to conduct food security analysis, studies tended to focus separately either on food 349 production or on aspects related to food consumption. 350 Secondly, different food systems actors and groups have experienced and suffered from the 351 pandemic in different ways. Studies in Ethiopia and India have illustrated that poorer and female 352 headed households were among those with the lowest levels of dietary diversity and food security 353 young adults that relied on daily wages (19, 22) . Given the informal nature of large sections of the 356 food system in LMICs (where women represent large sections of food processing and sales in wet 357 and formal markets), assessing the impacts on informal actors and defining targeted policies is 358 considered a top priority to build back more resilient food systems (42) in Ethiopia has also demonstrated to be effective measures to protect vulnerable population food 369 security during the pandemic (48). But social safety nets cannot be effective on their own and there 370 is a need for broader food systems interventions and investments to support food and nutrition 371 security (49). These include (and not limited to): i) building resilience of health and food systems to 372 withstand shocks such as the COVID-19 pandemic; ii) strengthening and ring-fencing maternal and 373 child essential health and nutrition services so that they are not sacrificed for emergency measures; 374 iii) enhancing nutrition programme coordination and implementation; iv) engaging effectively with 375 young people and women to support both the immediate COVID-19 efforts and the long-term aim of 376 building back better (50). For example, actions on external food environment domains can go from 377 monitoring food prices, diet diversity, food security and malnutrition indicators to adopting subsidies 378 accessibility and affordability of foods by social protection programmes, or the promotion of 381 sustainable healthy diets. Finally, this crisis can represent a window of opportunity for positive 382 reforms to achieve the SDGs, including: enhancing shorter, sustainable and local food systems; 383 investing in primary care, especially at the local level; valuing the role of informal workers in the 384 food system (and other sectors). 385 The situation is still multifaceted and sometimes difficult to interpret. A limited set of studies 387 included baseline pre-COVID -19 data (17,21,23,25) . Without comprehensive longitudinal pre-388 pandemic data, it may be difficult to disentangle the effect of the pandemic and annual and seasonal 389 dietary diversity fluctuations or other factors to COVID-19 (e.g. Orthodox fasting in Ethiopia or 390 infestations from armyworm and desert locusts (52)). 391 COVID-19 has also posed significant obstacles to collecting information on maternal and child 392 nutritional outcomes (53), or standardized indices such as the MDD-W. We retrieved no data on 393 such outcomes. Diet diversity and food security data were collected via phone and online surveys. 394 While valuable in times of social distancing and movement restrictions such methods may have led 395 to a bias toward easily or quickly 'measurable' or quantifiable data/indicators and respondents 396 accessing digital devices. Also more data is needed from other countries and specific groups, e.g. 397 under-5 children or women of child-bearing age. The nutrition status of populations also needs to be 398 monitored and remote anthropometric assessment be done (54), possibly complemented by COVID-399 19 safe in-person visits. A thorough appraisal of mitigating policies is also needed. We acknowledge 400 that such appraisal is difficult for complex interventions in time of crisis. However, we advocate for 401 improved data collection to identify vulnerable groups and measure how interventions are 402 successful in protecting them. 403 In conclusion, the current economic and heath crisis impact diet quality and food security, and this 406 raises concerns about long term impacts on access to and affordability of nutrient-rich, healthy diets 407 and their health implications (40, 41, 55) . Women and individuals with a low socio-economic are the 408 most at risk of food insecurity. Social safety nets can be effective to protect them and must be 409 urgently implemented. We advocate for improved data collection to identify vulnerable groups and 410 measure how interventions are successful in protecting them. 411 selection, quality appraisal, and data extraction; FP and DR wrote the paper; DR and LG made the 428 necessary recommendations; and FP, DR, LG revised the manuscript. 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