Title: Comparison of Methods for Estimating Dietary Food and Nutrient Intakes and Intake Densities from Household Consumption and Expenditure Data in Mongolia.

Authors: Bromage, Sabri; Rosner, Bernard; Rich-Edwards, Janet W; Ganmaa, Davaasambuu; Tsolmon, Soninkhishig; Tserendejid, Zuunnast; Odbayar, Tseye-Oidov; Traeger, Margaret; Fawzi, Wafaie W

Published In Nutrients, (2018 May 31)

Abstract: Household consumption and expenditure surveys are frequently conducted around the world and they usually include data on household food consumption, but their applicability to nutrition research is limited by their collection at the household level. Using data from Mongolia, this study evaluated four approaches for estimating diet from household surveys: direct inference from per-capita household consumption; disaggregation of household consumption using a statistical method and the "adult male equivalent" method, and direct prediction of dietary intake. Per-capita household consumption overestimated dietary energy in single- and multi-person households by factors of 2.63 and 1.89, respectively. Performance of disaggregation methods was variable across two household surveys analyzed, while the statistical method exhibited less bias in estimating intake densities (per 100 kcal) of most dietary components in both of the surveys. Increasingly complex prediction models explained 54% to 72% of in-sample variation in dietary energy, with consistent benefits incurred by inclusion of basic dietary measurements. In conclusion, in Mongolia and elsewhere, differences in how household and dietary measurements are recorded make their comparison challenging. Validity of disaggregation methods depends on household survey characteristics and the dietary components that are considered. Relatively precise prediction models of dietary intake can be achieved by integrating basic dietary assessment into household surveys.

PubMed ID: 29857536

MeSH Terms: Adult; Algorithms; Consumer Behavior*/economics; Databases, Factual; Diet, Healthy*/economics; Diet, Healthy*/ethnology; Diet/adverse effects; Diet/ethnology; Energy Intake/ethnology; Family Characteristics; Female; Food Preferences*/ethnology; Humans; Male; Models, Economic*; Mongolia; Nutrition Surveys*; Patient Compliance*/ethnology; Reproducibility of Results; Statistics as Topic