Women of reproductive age living in resource-poor settings are at high risk of inadequate micronutrient intakes when diets lack diversity and are dominated by staple foods. Yet comparative information on diet quality is scarce and quantitative data on nutrient intakes is expensive and difficult to gather. We assessed the potential of simple indicators of dietary diversity, such as could be generated from large household surveys, to serve as proxy indicators of micronutrient adequacy for population-level assessment. We used 5 existing data sets (from Burkina Faso, Mali, Mozambique, Bangladesh, and the Philippines) with repeat 24-h recalls to construct 8 candidate food group diversity indicators (FGI) and to calculate the mean probability of adequacy (MPA) for 11 micronutrients. FGI varied in food group disaggregation and in minimum consumption required for a food group to count. There were large gaps between intakes and requirements across a range of micronutrients in each site. All 8 FGI were correlated with MPA in all sites; regression analysis confirmed that associations remained when controlling for energy intake. Assessment of dichotomous indicators through receiver-operating characteristic analysis showed moderate predictive strength for the best choice indicators, which varied by site. Simple FGI hold promise as proxy indicators of micronutrient adequacy.

bstractThe distribution of usual intakes of dietary components is important to individuals formulating food policy and to persons designing nutrition education programs. Usual intake of a dietary component for a person is the long run average of daily intakes of that component for that person. Because it is impossible to directly observe usual intake of an individual, it is necessary to develop an estimator of the distribution of usual intakes based on a sample of individuals with a small number of daily observations on each individual. Daily intake data for individuals are nonnegative and often very skewed. Also, there is large day-to-day variation relative to the individual-to-individual variation and the within-individual variance is correlated with the individual means. We suggest a methodology for estimating usual intake distributions that allows for varying degrees of departure from normality and recognizes the measurement error associated with daily dietary intakes. The estimation method contains four steps. First, the original data are standardized by adjusting for weekday and interview sequence effects. Second, the daily intake data are transformed to normality using a combination of power and grafted polynomial transformations. Third, using a normal components-of-variance model, the distribution of usual intakes is constructed for the transformed data. Finally, a transformation of normal usual intakes to the original scale is defined. The approach works well for a set of dietary components selected from the [1985][1986]

bstractThe distribution of usual intakes of dietary components is important to individuals formulating food policy and to persons designing nutrition education programs. Usual intake of a dietary component for a person is the long run average of daily intakes of that component for that person. Because it is impossible to directly observe usual intake of an individual, it is necessary to develop an estimator of the distribution of usual intakes based on a sample of individuals with a small number of daily observations on each individual. Daily intake data for individuals are nonnegative and often very skewed. Also, there is large day-to-day variation relative to the individual-to-individual variation and the within-individual variance is correlated with the individual means. We suggest a methodology for estimating usual intake distributions that allows for varying degrees of departure from normality and recognizes the measurement error associated with daily dietary intakes. The estimation method contains four steps. First, the original data are standardized by adjusting for weekday and interview sequence effects. Second, the daily intake data are transformed to normality using a combination of power and grafted polynomial transformations. Third, using a normal components-of-variance model, the distribution of usual intakes is constructed for the transformed data. Finally, a transformation of normal usual intakes to the original scale is defined. The approach works well for a set of dietary components selected from the [1985][1986]

Objective:To describe an approach for assessing the prevalence of nutrient inadequacy in a group, using daily intake data and the new Estimated Average Requirement (EAR).Design:Observing the proportion of individuals in a group whose usual intake of a nutrient is below their requirement for the nutrient is not possible in general. We argue that this proportion can be well approximated in many cases by counting, instead, the number of individuals in the group whose intakes are below the EAR for the nutrient.Setting:This is a methodological paper, and thus emphasis is not on analysing specific data sets. For illustration of one of the statistical methods presented herein, we have used the 1989–91 Continuing Survey on Food Intakes by Individuals.Results:We show that the EAR and a reliable estimate of the usual intake distribution in the group of interest can be used to assess the proportion of individuals in the group whose usual intakes are not meeting their requirements. This approach, while simple, does not perform well in every case. For example, it cannot be used on energy, since intakes and requirements for energy are highly correlated. Similarly, iron in menstruating women presents some difficulties, due to the fact that the distribution of iron requirements in this group is known to be skewed.Conclusions:The apparently intractable problem of assessing the proportion of individuals in a group whose usual intakes of a nutrient are not meeting their requirements can be solved by comparing usual intakes to the EAR for the nutrient, as long as some conditions are met. These are: (1) intakes and requirements for the nutrient must be independent, (2) the distribution of requirements must be approximately symmetric around its mean, the EAR, and (3) the variance of the distribution of requirements should be smaller than the variance of the usual intake distribution.

The large number of available HIV-1 protease structures provides a remarkable sampling of conformations of the different conformational states, which can be viewed as direct structural information about the dynamics of the HIV-1 protease. After structure matching, we apply principal component analysis (PCA) to obtain the important apparent motions for both bound and unbound structures. There are significant similarities between the first few key motions and the first few low-frequency normal modes calculated from a static representative structure with an elastic network model (ENM), strongly suggesting that the variations among the observed structures and the corresponding conformational changes are facilitated by the low-frequency, global motions intrinsic to the structure. Similarities are also found when the approach is applied to an NMR ensemble, as well as to molecular dynamics (MD) trajectories. Thus, a sufficiently large number of experimental structures can directly provide important information about protein dynamics, but ENM can also provide similar sampling of conformations.