SMART Methodology Manual 2.0
- Follows the latest best practices in the field.
- Provides more guidance on survey teams training, such as interpreting the standardisation test report to better prepare enumerators and assign roles more effectively.
- Features the full chapter on the Plausibility Check for Anthropometry and Mortality and Demography, providing expanded guidance in interpreting and acting on its results, both to improve data collection during surveys and to refine data analysis for decision-making.
- Presents an expanded and updated section on Mortality and Demography surveys, including a more user-friendly questionnaire template and interview guidelines.
- Contains specific directives for using chronic malnutrition as the main indicator for the sample size calculation and the interpretation of results.
- Adds an appendix on the use of the combined Epi info/ENA for SMART Software.
Measuring Mortality, Nutritional Status, and Food Security in Crisis Situations: SMART Methodology. SMART Manual Version 2 published in 2017. Printer Friendly
Measuring Mortality, Nutritional Status, and Food Security in Crisis Situations: SMART Methodology. SMART Manual Version 1 published in 2006.
Mesure de la Mortalité, du Statut Nutritionnel et de la Sécurité Alimentaire en Situations de Crise: Le protocol SMART.
For other nutrition manuals, refer to Resources
Rapid SMART Methodology
Borrowing from the SMART methodology, Rapid SMART allows for the quick collection of reliable nutrition data under certain contexts. Rapid SMART surveys are only appropriate when the situation requires a rapid estimate of the nutritional status in small geographical areas. This is most often in emergency contexts with high insecurity that limits the team’s access to survey areas.
Rapid SMART has limitations compared to the standard full SMART methodology. It cannot be used to assess GAM/SAM for larger geographical areas, cannot be extrapolated to larger than the zone of assessment, and can only be used to inform emergency responses, not long-term programs.
For more information, please refer to the Rapid SMART guidelines and accompanying annexes below.
Rapid SMART Guidelines (English)
Rapid SMART Guidelines (French)
Rapid SMART Annexes (English only)
Rapid SMART Annexes (English only)
Sampling for SMART including considerations for urban sampling
To help you better understand the sampling module of SMART:
Sampling Methods & Sample size calculation for the SMART methodology.
Méthodes d’échantillonnage et calcul de la taille de l’échantillon selon la méthodologie SMART.
Sampling in Urban Areas: Approaches and Case Studies.
The Plausibility Check is a key SMART innovation used to analyse the overall quality of anthropometric survey data. Explanations on the logic behind the statistical tests used to analyse anthropometric data and a step-by-step approach on how to interpret the different sections of the Plausibility Check are provided in this newly published chapter:
SMART Plausibility Check for Anthropometry
Contrôle de plausibilité SMART pour l’anthropométrie
Interpreting SMART results (CDC calculator)
The CDC Statistical Calculators (in Excel format) are used to help interpret prevalence results from nutritional surveys, which are often expressed as an estimate with a confidence interval..
The calculator for one survey allows you to know the probability that your true prevalence value exceeds a certain threshold; in other words, it helps you know where the true value lies within the confidence interval. The calculator for one survey is useful for comparing survey results to global benchmarks (e.g., what’s the probability that the true prevalence of malnutrition exceeds 10%?).
The calculator for two surveys allows you to know the probability that the prevalence estimate from one survey is significantly different from that of a second survey. For example, the calculator for two surveys can be used to compare prevalence in different areas, or during different time periods.
There are three sheets in both of these Excel tools, two of which are for cluster surveys (depending whether design effect is known or not) and one for simple or systematic random sampling.
Download the entire English set here.
Download the entire French set here.
Download individual files below:
One Survey (Une Enquête)
CDC Statistical Calculator (one survey).
Instructions for calculator (one survey)
Calculatrice Statistique du CDC (une enquête).
Comment utiliser la Calculatrice Statistique (une enquête)
Two Surveys (Deux Enquête)
CDC Statistical Calculator (two surveys).
Instructions for calculator (two surveys)
Calculatrice Statistique du CDC (deux enquête).
Comment utiliser la Calculatrice Statistique (deux enquête)
SMART can be used to assess prevalence of both acute and chronic malnutrition. This document explains how to calculate sample size and use the Plausibility Check when chronic malnutrition is the main indicator in your survey.
SMART Methodology: Chronic Malnutrition as the Main Indicator