Development of a Dichotomous Indicator for Population-Level Assessment of Dietary Diversity in Women of Reproductive Age

Abstract

Background: Dietary diversity is a key element of diet quality, but diets of women of reproductive age (WRA; aged 15–49 y) in resource-poor settings are often deficient in a range of micronutrients. Previous work showed associations between simple food-group diversity indicators (FGIs) and micronutrient adequacy among WRA. For operational and advocacy purposes, however, there is strong demand for a dichotomous indicator reflecting an acceptable level of dietary diversity.

Objective: The aim of the study was to develop a dichotomous indicator of dietary diversity in WRA.

Methods: We performed a secondary analysis of 9 data sets containing quantitative dietary data from WRA in resource-poor settings (total n = 4166). From the raw dietary data, we calculated an individual “mean probability of adequacy” (MPA) across 11 micronutrients. Several candidate FGIs were constructed. Indicator performance in predicting an MPA >0.60 was assessed within each data set by using receiver-operating characteristic analysis and sensitivity and specificity analysis at various FGI cutoffs. The analysis was performed separately for nonpregnant and nonlactating (NPNL) women and for lactating women.

Results: We identified 2 “best candidate” dichotomous indicators on the basis of 9- or 10-point food-group scores (FGI-9 and FGI-10) with a cutoff of ≥5 food groups. Both were significantly correlated to MPA in each site ( P < 0.001). Areas under the curve were moderate, ranging from 0.62 to 0.82 among NPNL women and from 0.56 to 0.90 among lactating women. Comparisons of results slightly favored FGI-10 for all women.

Conclusions: When resource-intensive dietary methods are not feasible, a simple dichotomous indicator based on a cutoff of ≥5 of 10 defined food groups reflects “minimum dietary diversity for women of reproductive age.” According to the conclusions of a consensus meeting of experts, this indicator is well suited for population-level assessment, advocacy, and possibly also for tracking of change in dietary diversity across time.