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Objective: The present paper aimed to demonstrate how 24 h dietary recall data can be used to generate a nutrition-relevant food list for household consumption and expenditure surveys (HCES) using contribution analysis and stepwise regression., Design: The analysis used data from the 2011/12 Bangladesh Integrated Household Survey (BIHS), which is nationally representative of rural Bangladesh. A total of 325 primary sampling units (PSU=village) were surveyed through a two-stage stratified sampling approach. The household food consumption module used for the analysis consisted of a 24 h open dietary recall in which the female member in charge of preparing and serving food was asked about foods and quantities consumed by the whole household., Setting: Rural Bangladesh.ParticipantsA total of 6500 households., Results: The original 24 h open dietary recall data in the BIHS were comprised of 288 individual foods that were grouped into ninety-four similar food groups. Contribution analysis and stepwise regression were based on nutrients of public health interest in Bangladesh (energy, protein, fat, Fe, Zn, vitamin A). These steps revealed that a list of fifty-nine food items captures approximately 90 % of the total intake and up to 90 % of the between-person variation for the key nutrients based on the diets of the population., Conclusions: The study illustrates how 24 h open dietary recall data can be used to generate a country-specific nutrition-relevant food list that could be integrated into an HCES consumption module to enable more accurate and comprehensive household-level food and nutrient analyses.

This paper hypothesizes that there is a common "core" to the household food insecurity experience that goes beyond insufficient food quantity and that transcends culture. The paper for the first time employs an exploratory approach to identify cross-cultural commonalities of the food insecurity experience as captured in 22 scales and related ethnographies derived from 15 different countries. The constant comparative method was used to code elements of the food insecurity experience expressed in the ethnographies and to regroup them into domains and subdomains. This typology was then applied to ascertain which experiential domains and subdomains were measured (or not) across all 22 studies. Survey data from 11 of the studies were then analyzed to assess similarities in the relative frequency with which culturally diverse households responded to questionnaire items related to these common domains/subdomains. The analysis confirmed that insufficient food quantity, inadequate food quality, and uncertainty and worry about food were a significant part of the food insecurity experience in all sampled cultures; concerns about social unacceptability emerged in all ethnographic accounts. Several subdomains were identified, such as concern over food safety and meal pattern disruption, with potentially important consequences for physical and psychological well-being. The comparative survey data showed that the relative frequency at which populations responded to domain-related questionnaire items was similar across all but a few cultures. Future food insecurity assessments should consider these core domains and subdomains as the starting point for measures that can generate rich information to inform food security policies and programs.

This paper compares a qualitative and a quantitative (Rasch) method of item assessment for developing the content of a food insecurity scale for Bangladesh. Data are derived from the Bangladesh Food Insecurity Measurement and Validation Study, in which researchers collected 2 rounds of ethnographic information and 3 rounds of conventional household survey data between 2001 and 2003. The qualitative method of scale development relied on content experts and respondents themselves to evaluate household food insecurity items generated through ethnographic research. The quantitative method applied the Rasch model to assess the fit of the same items using representative survey data. The Rasch model was then used to test for differential item functioning (DIF) across diverse demographic and geographic subgroups. The qualitative assessment flagged and discarded 10 items, leaving 13. The Rasch assessment of infit and outfit flagged 3 items, and the Rasch DIF test discarded another 10 items, leaving a total of 10 items in the Rasch-derived scale. The 2 scales contained 8 of the same items. The qualitatively and quantitatively derived scales were highly correlated (r = 0.96, P < 0.01), and the 2 methods located 90% of households in the same food insecurity tercile. This convergence lends added confidence to the use of either scale for identifying food-insecure households in different regions of Bangladesh. Multiple methods should continue to be applied in a systematic and transparent way to lend additional credence to the results when they converge and to pinpoint directions for further clarification where they do not.