Predicting dietary intakes with simple food recall information: a case study from rural Mozambique.
OBJECTIVE
Improving dietary status is an important development objective, but monitoring of progress in this area can be too costly for many low-income countries. This paper demonstrates a simple, inexpensive technique for monitoring household diets in Mozambique.


METHODS
Secondary analysis of data from an intensive field survey on household food consumption and agricultural practices, known as the Nampula/Cabo Delgado Study (NCD).


METHODS
In total, 388 households in 16 villages from a stratified random sample of rural areas in Nampula and Cabo Delgado provinces in northern Mozambique.


METHODS
The NCD employed a quantitative 24-h food recall on two nonconsecutive days in each of the three different seasons. A dietary intake prediction model was developed with linear regression techniques based on NCD nutrient intake data and easy-to-collect variables, such as food group consumption and household size The model was used to predict the prevalence of low intakes among subsamples from the field study using only easy-to-collect variables.


RESULTS
Using empirical data for the harvest season from the original NCD study, 40% of the observations on households had low-energy intakes, whereas rates of low intake for protein, vitamin A, and iron, were 14, 94, and 39, respectively. The model developed here predicted that 42% would have low-energy intakes and that 12, 93, and 35% would have low-protein, vitamin A, and iron intakes, respectively. Similarly, close predictions were found using an aggregate index of overall diet quality.


CONCLUSIONS
This work demonstrates the potential for using low-cost methods for monitoring dietary intake in Mozambique.
D003625:Data Collection / Q000379:methods* / Q000592:standards; D004032:Diet / Q000592:standards / Q000639:trends; D004034:Diet Surveys; D004044:Dietary Proteins / Q000008:administration & dosage; D002149:Energy Intake; D005191:Family Characteristics; D006801:Humans; D016014:Linear Models; D011939:Mental Recall; D009073:Mozambique; D015596:Nutrition Assessment; D011237:Predictive Value of Tests; D012424:Rural Population; D012621:Seasons; D012680:Sensitivity and Specificity
D004044:Dietary Proteins