Technical Voices Of The Hungry
Voices of the HungryThe Voices of the Hungry project has developedthe Food Insecurity Experience Scale,a new metric for household and individual food insecurity.It brings us a step closer to hearing the voices of the peoplewho struggle every day to have access to safe and nutritious food.TechnicalReportNumber 1/August 2016(Revised Version)
Photo cover: FAO/Giulio Napolitano
VOICES of the HUNGRYMethods for estimatingcomparable prevalence rates of food insecurityexperienced by adults throughout the world.Carlo Cafiero*, Mark Nord, Sara Viviani, Mauro Eduardo Del Grossi, Terri Ballard,Anne Kepple, Meghan Miller, Chiamaka Nwosu*Carlo.Cafiero@fao.orgFOOD AND AGRICULTURE ORGANIZATION OF THE UNITED NATIONSRome, 2016
Recommended citation:FAO. 2016. Methods for estimating comparable rates of food insecurity experienced by adults throughout theworld. Rome, FAO.Note to the reader:In this version of the report, statistics for Mexico have been revised due to a processing errorfor Mexico national survey data in the earlier release. Minor typos have also been corrected,but the only changes in statistical results are those for Mexico prevalence rates.The designations employed and the presentation of material in this information product do not imply theexpression of any opinion whatsoever on the part of the Food and Agriculture Organization of the UnitedNations (FAO) concerning the legal or development status of any country, territory, city or area or of itsauthorities, or concerning the delimitation of its frontiers or boundaries. The mention of specific companiesor products of manufacturers, whether or not these have been patented, does not imply that these havebeen endorsed or recommended by FAO in preference to others of a similar nature that are not mentioned.The views expressed in this information product are those of the author(s) and do not necessarily reflectthe views or policies of FAO.ISBN 978-92-5-108835-7 FAO, 2016FAO encourages the use, reproduction and dissemination of material in this information product. Exceptwhere otherwise indicated, material may be copied, downloaded and printed for private study, research andteaching purposes, or for use in non-commercial products or services, provided that appropriate acknowledgement of FAO as the source and copyright holder is given and that FAO’s endorsement of users’ views,products or services is not implied in any way.All requests for translation and adaptation rights and for resale and other commercial use rights should bemade via www.fao.org/contact-us/licence-request or addressed to copyright@fao.org.FAO information products are available on the FAO website (www.fao.org/publications) and can bepurchased through publications-sales@fao.org.ii
ContentsTables . ivFigures . ivAcknowledgments . vA formidable challenge . 11. The concept: food insecurity seen through the lens of people’sexperiences. 32. The Food Insecurity Experience Scale Survey Module (FIES-SM) . 73. Data collection through the Gallup World Poll . 94. Analyzing FIES data with the Rasch model . 115. Developing the FIES global standard scale . 156. Computing comparable prevalence rates . 177. Results to date: data quality . 218. Results to date: prevalence rates . 27Filling a gap in our ability to measure food insecurity . 31References . 34Appendix . 36Annex I - Prevalence Rates Based on National Government Survey Data . 41Annex II - Number of food insecure adults and number of individuals in thetotal population affected by food insecurity . 48iii
TablesTable 2-1 Questions in the Food Insecurity Experience Scale Survey Module forIndividuals (FIES SM-I) as fielded in the 2014GWP . 7Table 7-1 Summary of missing responses to food security questions in the first 146datasets for which 2014 GWP data were available . 21Table 7-2 Summary of item infit statistics for 136 datasets in the 2014 GWP . 22Table 7-3 Summary of item outfit statistics for 136 datasets in the 2014 GWP . 22Table 7-4 Mean residual correlations between items (136 datasets from the 2014GWP) . 23Table 8-1 Descriptive statistics of the food insecurity prevalence rates (143datasets in 2014) . 27Table 8-2 Distribution of countries, areas or territories for different classes ofFImod sev and FIsev . 28Table 8-3 Spearman’s rank correlation between food insecurity indicators andselected indicators of development at country level. . 28Table 8-4 Regression analysis of food security and poverty indicators on childmortality rates . 29Table A-1 Prevalence rates of food insecurity in 146 countries, areas or territoriesin 2014 . 36Table A-2 Selected Indicators of Development used in the correlation analysis . 40Table A-3 Prevalence rates calculated from national government survey data andfrom FAO- GWP data. . 47FiguresFigure 1-1 Food insecurity experiences and associated severity levels . 4Figure 6-1 Estimated distributions of true severity among respondents with eachraw score . 18Figure 7-1 Distributions of standardized values of item severity across countries. . 25Figure 7-2 The FIES global standard . 25iv
AcknowledgmentsThis publication is the revision of a preliminary version of the technical report that was circulated forcomments with a restricted list of reviewers in March 2015, in preparation for a technical expert meetingthat was hosted at FAO headquarters on May 21-22 2015.We wish to thank Ricardo Aparicio, Luis Beccaria, Jennifer Coates, Luis Pérez Melgar, Rafael PérezEscamilla, Giovanni Battista Rossi, Ana Maria Segall-Corrêa, Mark Wilson, Andrea Leigh McMillan (whocoordinated the review conducted by Stats Canada), and Steve Crutchfield (who coordinated the oneconducted at USDA – ERS) for the input provided.Thanks are due to Pietro Gennari, Josef Schmidhuber, Piero Conforti and Vikas Rawal, in addition to allparticipants in the expert meeting in May 2015, for useful comments and suggestions.Our gratitude also goes to the members of the original “Experience-Based Measures of Food InsecurityTechnical Advisory Group”, including Angus Deaton, Lawrence Haddad, Romulo Paes de Sousa, HugoMelgar-Quiñonez and Bob Tortora, whose encouragement and guidance put us on what has proven to bethe right path.The authors wish to thank Dana Glori, Elizabeth Graham, Elisa Miccinilli, Aymeric Songy and Verena Wilkefor their valuable contribution throughout the process of data collection and analysis, and Barbara Sbroccafor the skillful graphic design of the publication. Special thanks are due to Andrew Rzepa and Mike Ileckiand to the entire Gallup Inc. team for the continued and competent support and for the patience inanswering all our questions regarding the details of data collection.Implementation of the Voices of the Hungry project has been made possible by the direct financial supportfrom the United Kingdom Department for International Development (DfID) and by the financial supportfrom the Kingdom of Belgium through FAO Multipartner Programme Support Mechanism (FMM).The responsibility for all statements, comments, opinions or judgments included in thistechnical report rests with the authors only and do not imply any official position by FAO orby the Statistics Divisionv
FAO/Franco Mattioli
A formidable challengeHow to estimate national prevalence rates of foodinsecurity that are comparable across countriesand population groups.“Food security exists when all people, at all times, havephysical, social and economic access to sufficient safe andnutritious food that meets their dietary needs and food preferences for an active and healthy life.” (FAO, 2009).A key objective of the Voices of the Hungry project (VoH) is to estimate comparableprevalence rates of food insecurity in national populations for more than 140 countriesevery year. These estimates are based on conditions and behaviors reported by adultsthrough the Food Insecurity Experience Scale survey module (FIES-SM). The data collected in nationally representative surveys of the adult population in each country areused to compute a measure of severity of the food insecurity status for each respondent,focusing on conditions reflecting limited access to food. Individual measures are thencalibrated against a common global reference scale of severity, thus allowing classifications and estimates of prevalence rates that are comparable across countries and population groups.Defining the global reference scale and appropriate methods for calibration is aformidable challenge, given the differences in languages, cultures, and livelihood arrangements that exist across countries. Though statistical theory and methods for latenttrait analysis based on Item Response Theory (IRT) provide a general approach andmany of the statistical tools needed to accomplish this task, some adaptation and extension of those methods is required. This report describes the adaptations and extensionsof IRT methods developed by VoH, providing details of the process from data collectionto the production of comparable national statistics. It then presents the results of theanalyses of data collected through the Gallup World Poll (GWP) in 146 different countries, areas or territories in 2014, leading to preliminary estimates of the prevalence ofmoderate and severe food insecurity.The main purpose of the report is to allow food security analysts to evaluate the statistical soundness and adequacy of the methods described. Descriptions assume that thereader has a basic understanding of statistical measurement methods based on Item Response Theory, and in particular on the Rasch measurement model. Readers lacking thisbackground may want to consult Nord (2014) as an introduction to those methods.1
Sections are as follows:1. Overview of the concepts of food security and food insecurity and the roleof experience-based measures within the field of food security assessment.2. Description of the questionnaire module, the FIES-SM.3. Data collection: sampling, interviewing, editing and weighting.4. Analysis of each country’s food security data: Measurement model estimation—calculation of the FIES, assessment of each item and of the scale for each country.5. Development of the VoH global reference scale—the bridge by which prevalencerates in countries will be compared.6. Adjusting each country’s scale to the global reference scale and calculatingprevalence rates of food insecurity at two levels of severity.7. Results to date: measures of item and model fit, assessment of conditionalindependence of items, parameters and robustness of the global reference scale,summary of consistency of country-level scales to the global reference scale8. Results to date: preliminary analysis of correlations between estimated prevalencerates and other indicators of development at country level.
1. The concept: food insecurity seen throughthe lens of people’s experiencesOverview of the concepts of food securityand food insecurity, and the use of experience-based measuresfor food security assessments.Combined scientific and political efforts haveconverged on a growing consensus regardingconceptual frameworks and measures of foodsecurity. Because no single indicator can accountfor the multiple dimensions of food security,the discussion has focused on defining a suite ofindicators based on measures of aspects rangingfrom food production and availability, to dietary quality and the prevalence of nutrition-related outcomes in the population (FAO, 2012a;Coates, 2013; Jones et al, 2013; FAO, IFAD &WFP, 2014).The Food Insecurity Experience Scale (FIES) isexpected to make an important contribution inthe area of food security assessment by bettercapturing the access dimension of food security.It does so by providing the set of tools needed tocompute valid and reliable indicators of theprevalence of food insecurity, at different levelsof severity, in a population reached by a representative survey. By gauging the scope anddepth of limited access to food, such indicatorswill be a valuable addition to the suite of existing food security indicators at country level,(Ballard et al., 2013).The FIES establishes an experience-based metric for the severity of the food insecurity condition of individuals or households. The metric iscalculated from data on people’s direct responses to questions regarding their access tofood of adequate quality and quantity. The construct it measures is thus fully consistent with aview that the key defining characteristic of foodsecurity is “secure access at all times to sufficientfood” (Maxwell & Frankenberger, 1992, p. 8).Ethnographic research carried out in the USA tounderstand the lived experience of hunger revealed it to be a process characterized initiallyby anxiety about having enough food, followedby dietary changes to make limited food resources last, and finally, decreased consumptionof food in the household (Radimer, Olson &Campbell, 1990; Radimer et al, 1992). Althoughthe original ethnographic study was based on asmall number of households in a wealthy country, a review conducted years later of studies derived from many countries in different regionsof the world concluded that these dimensions ofthe experience of hunger appear to be commonacross cultures (Coates et al., 2006).This theoretical construct of food insecurityformed the basis for the U.S. Household FoodSecurity Survey Module (US HFSSM), whichhas been applied annually in the United Statessince 1995 and has served as a model for theFIES. Numerous other experience-based foodinsecurity scales emerged from the same theoretical basis in diverse countries around theworld.1 Two measures in particular, the Household Food Insecurity Access Scale (HFIAS)(Coates, Swindale & Bilinsky, 2007) and theEscala Latinoamericana y Caribena de Seguridad Alimentaria (ELCSA) (Pérez-Escamilla et al., 2007;FAO, 2012b) included analytic methods to makethe measures comparable across countries. TheFIES builds heavily on the ELCSA as well asother scales by providing an analytic frameworkto improve the precision of comparability acrosscountries and to extend comparability to allcountries.The first one was the Escala Brasileira de Insegurança Alimentar (EBIA) used in Brazil since 2004 (Segall-Corrêa et al., 2004), fo-llowedby the Escala Mexicana de Seguridad Alimentaria (EMSA) adapted for use in Mexico (Pérez-Escamilla).13
Figure 1-1Food insecurity experiences and associated severity levelsFood insecurity experiences and associated severity levelsmild food insecurityworrying aboutabilityto obtain foodmoderate food insecuritycompromisingquality and varietyof foodreducing quantities,skipping mealssevere food insecurityexperiencinghungerThe measurement theory behind theFIESof the former using data collected on any sampleof individuals.Research has revealed how different experiential domains are typically associated with different levels of food insecurity, with possible associations shown in Figure 1-1. This observationpaved the way towards identifying potentialquestions to be included in a questionnaire toform a proper basis for measurement scales offood insecurity, such as the FIES.The simplest of such models that preserves alldesirable qualities of a proper measurementmodel is the Rasch model, named for the Danishmathematician Georg Rasch, who first proposedit, which is also referred to as the one-parameterlogistic (1PL) model. (Rasch, 1960; Fischer & Molenaar, 1995).The fundamental assumption behind the FIESand similar food security scales is that the severity of the food insecurity condition of a household or an individual can be analysed as a latenttrait. Latent traits cannot be observed directly,but their measure can be inferred from observable evidence through application of measurement models based on Item Response Theory(IRT), a set of methods rooted in statistics withbroad application to measurement problems inthe human and social science domains.In applying IRT models to the measurement offood insecurity, we postulate that: (a) the severityof the food insecurity condition of the respondentand that associated with each of the experiencescan be located on the same one-dimensionalscale, and that: (b) higher severity of the food insecurity condition of a respondent will increasethe probability of reporting occurrence of experiences associated with food insecurity.By defining a probabilistic model that links the(unknown) measure of food insecurity to the(observable) responses to experience-basedquestionnaires, it is possible to obtain estimatesIn this model, the probability that a respondentwill report a given experience is a logistic function of the distance between the respondent’sand the item’s positions on the severity scale:Prob(𝑥ℎ,𝑖 1 𝜃ℎ , 𝛽𝑖 ) 𝑒 𝜃ℎ 𝛽𝑖1 𝑒 𝜃ℎ 𝛽𝑖,where 𝑥ℎ,𝑖 is the response given by respondent ℎto item 𝑖, coded as 1 for “yes” and 0 for “no”.The relative severity associated with each of theexperiences (the parameters 𝛽𝑖 in the formulaabove) can be inferred from the frequency withwhich they are reported by a large sample of respondents, assuming that, all else being equal,more severe experiences are reported by fewerrespondents. Once the severity of each experience is estimated, the severity of a respondent’scondition (the 𝜃ℎ parameter) can be computedby noting how many of the items have been affirmed. The rationale for this is that, on average,it is expected that a respondent will answer affirmatively to all questions that refer to experiences that are less severe of their food insecuritysituation, and negatively to questions that referto situations that are more severe.2Notice that,
Voices of the Hungry The Voices of the Hungry project has developed the Food Insecurity Experience Scale, a new metric for household and individual food insecurity. Number 1/ It brings us a step closer to hearing the voices of the people who struggle every day to have access to safe and nutritious food. August 2016 (Revised Version) Technical .
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