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Beyond hunger: Monitoring food insecurity in the SDG era

Carlo Cafiero
IFPRI-FAO conference, "Accelerating the End of Hunger and Malnutrition"
November 28–30, 2018
Bangkok, Thailand

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Beyond hunger: Monitoring food insecurity in the SDG era

  1. 1. BEYOND HUNGER Monitoring food insecurity in the SDG era Carlo Cafiero, PhD, Project Manager, Statistics Division FAO, 30 November 2018, Bangkok
  2. 2. From MDG-1 to SDG-2: much more than continuation of an advocacy campaign  MDG-1: Eradicate extreme poverty and hunger o Target 1.C: To halve the proportion of individuals suffering from hunger in the period between 1990 and 2015 o Indicator 1.8 Prevalence of underweight children under-five years of age o Indicator 1.9 Proportion of population below minimum level of dietary energy consumption  SDG-2: End hunger, achieve food security and improved nutrition and promote sustainable agriculture o Target 2.1: By 2030, end hunger and ensure access by all people, in particular the poor and people in vulnerable situations, including infants, to safe, nutritious and sufficient food all year round o Indicator 2.1.1 Prevalence of undernourishment o Indicator 2.1.2 Prevalence of moderate or severe food insecurity in the population, based on the Food Insecurity Experience Scale (FIES)
  3. 3. The SDG monitoring framework  Broader, more ambitious, and potentially more effective o242 indicators, many targets aim at “zero” or “100%”, leaving no one behind, with national authorities in the driving seat But…  More demanding in terms of methods, standards and tools oMany new areas of interest, that are still not part of national statistical systems oComparability of the indicators across countries is essential, to ensure meaningful aggregation oIndicators must be timely, relevant, scalable and reliable
  4. 4. Measuring food insecurity in a relevant, timely, reliable, cross-country comparable way  Existing indicators for MDGs did not fulfil the need created by the new demands o E.g., malnutrition: Children underweight largely insufficient as it confounds acute and chronic malnutrition, therefore many new indicators: stunting, wasting+overweight in children, anaemia in WRA, low-birthweight, exclusive breastfeeding, adolescent and adult overweight  Food access: o PoU: only national level, 2-3 years delay, insufficiently precise to capture very low levels (< 5%) o FCS, HDDS: lacking a basis for ensuring cross-country comparability o CSI, rCSI: measures of resilience to shock/intensity of shocks o HFIAS/HHS: lack cross-country comparability; relevant for acute f.i.  New indicator: FIES-based prevalence of food insecurity
  5. 5. A critical review of food insecurity measures  Food security as a ‘complex’ phenomenon oAvailability, Access, Utilization, Stability … useful conceptual framework, but not conducive to operational definitions of a measurable attribute  Whose food security? (The object) oGlobal? A country? A population group? An individual?  What to measure? (The measurand) oAdequacy of food consumption? In quantity? Quality? Security of access? oNutritional consequences of food consumption? Psychological implications of the inability to access food? Social status? oAll of the above?
  6. 6. A critical review of food insecurity measures (continued)  In defining indicators, with one notable exception, there has never been a discussion of the probabilistic model that links the “data” to the “measure”  Attempts at quantification have led to either deny the possibility to measure (“there is no ‘gold standard’ ”) or arbitrarily define numeric “scores” or “indexes”, assumed – without proof – that they “measure”something oEx-post validation has been attempted by combining (confusing?) issues of validity (e.g., definition of the attribute being measured and relevance of the data uses) with those of reliability (that is, whether the measures obtained were good enough for the purpose at hand)
  7. 7. The severity of the food insecurity condition as a latent trait  Through ethnographic research, Radimer and colleagues (Radimer et al 1990, 1992) established consistency of typical experiences associated with food insecurity  In 1995, using Rasch model, USDA proposed creating a measurement scale using 18 survey items that were included in the Current Population Survey, creating the HFSSM, used officially in the US since 1997  Other scales (HFIAS, ELCSA, EBIA, EMSA) have been derived as adaptations of the HFSSM  In 2014, FAO established the Food Insecurity Experience Scale (FIES) as a global reference standard, to measure the severity of food insecurity of households and individuals in a consistent, cross-country comparable, valid manner
  8. 8. Household Food Insecurity Access Scale HFIAS ELCSA Guatemala, 2011 EMSA Mexico, 2008 EBIA Brazil, 2004 FIES A global reference standard Colombia Venezuela U.S. Household Food Security Survey Module USA, 1995; Canada, 2004 FIES genealogy HHS
  9. 9. The Food Insecurity Experience Scale survey module During the last 12 MONTHS, was there a time when, because of a lack of money or other resources: 1. You (or others in the hh) were worried you would run out of food? 2. You (or others in the hh) were unable to eat healthy and nutritious food? 3. You (or others in the hh) ate only a few kinds of foods? 4. You (or others in the hh) had to skip a meal? 5. You (or others in the hh) ate less than you thought you should? 6. Your household ran out of food? 7. You (or others in the hh) were hungry but did not eat? 8. You (or others in the hh) went without eating for a whole day?
  10. 10. Added value of the FIES  The FIES is easy to implement and at a very low cost oCan be included in virtually any population survey oIt takes less than 5 minutes of survey time  It permits timely assessments of the food insecurity situation in a population group, from sub-national to the global level  When available from integrated surveys, FIES data can be used to study the specific determinants of food insecurity and the potential role of food insecurity in determining nutrition outcomes, in different contexts
  11. 11. Promoting country ownership of FIES methodology  The ideal sources of FIES data are large population surveys  For SDG monitoring, the goal is to have many countries reporting food insecurity prevalence estimates based on FIES data collected by national institutions, every year  Thus far (as of November 2018): o11 countries are using a comparable tool o42 countries have already included the FIES in national surveys o17 countries have concrete plans to do so
  12. 12. Promoting country ownership of FIES methodology Stage of FIES adoption N Countries Using their own FIES- compatible national EBFS Scale 12 Bolivia, Brazil, Canada, Colombia, Ecuador, Guatemala, Malaysia, Mexico, Philippines*, South Korea, Sri Lanka, USA FIES has been included in national surveys and government plans to collect FIES data regularly 6 Indonesia, Jordan, Kenya, Pakistan, Seychelles, Vietnam FIES has been included in national surveys 36 Bahrain, Bangladesh, Benin, Botswana, Burkina Faso, Cabo Verde, Chile, Cote d'Ivoire, Dominican Republic, El Salvador, Ethiopia, Ghana, Guinea-Bissau, Honduras, Israel, Lesotho, Malawi, Mali, Marshall Islands, Mauritius, Mozambique, Namibia, Niger, Nigeria, Palestine, Rwanda, Senegal, Sierra Leone, St. Lucia, Samoa, Sudan, South Sudan, Swaziland, Togo, Uganda, Zimbabwe Plans are in place to include FIES in national surveys 17 Afghanistan, Chad, Egypt, Gabon, Guinea, Kiribati, Mauritania, Micronesia (Federal State of), Nepal, Nicaragua, Panama, Solomon Islands, South Africa, Tokelau, Tonga, Vanuatu
  13. 13. Challenges  Statistical capacity oIntegrating the FIES module in national surveys  Analytic capacity oCalibrating measures of food insecurity against the FIES global reference scale oRecognizing the differences between the “old” and the “new” indicators  Broadening the scope oFood insecurity at moderate levels has significant implications for various forms of malnutrition, relevant for emerging and medium-high income economies too.
  14. 14. Thanks