Linganisha mbinu

	Dietary Pattern Analysis	Individual Dietary Diversity Score
Nyanja	Food Agriculture Studies	Food Agriculture Studies
Familia	Process / pipeline	Process / pipeline
Mwaka wa asili	2002	2011
Mwanzilishi	Frank B. Hu; P. K. Newby & Katherine L. Tucker	Gina Kennedy, Terri Ballard & Marie Claude Dop (FAO)
Aina	Multivariate pipeline for deriving empirical dietary patterns from food intake	Qualitative 24-hour recall pipeline for individual diet-quality assessment
Chanzo asilia	Hu, F. B. (2002). Dietary pattern analysis: a new direction in nutritional epidemiology. Current Opinion in Lipidology, 13(1), 3-9.	Kennedy, G., Ballard, T., & Dop, M. C. (2011). Guidelines for Measuring Household and Individual Dietary Diversity. Nutrition and Consumer Protection Division, Food and Agriculture Organization of the United Nations, Rome.
Majina mbadala	Empirical Dietary Patterns, A Posteriori Dietary Patterns, Data-Driven Dietary Patterns, Eating Pattern Analysis	IDDS, Individual Dietary Diversity, FAO Dietary Diversity Score, Dietary Diversity Score
Zinazohusiana	4	4
Muhtasari	Dietary pattern analysis is the nutritional-epidemiology application of multivariate statistics that identifies how foods are actually eaten together, summarizing the whole diet into a few empirical patterns rather than studying single nutrients in isolation. Introduced as a research direction by Frank Hu in his 2002 Current Opinion in Lipidology review and surveyed methodologically by Newby and Tucker in 2004, the approach takes a matrix of food-group intakes and applies factor (principal component) analysis, cluster analysis, or reduced-rank regression to extract a posteriori patterns such as a 'prudent' pattern rich in fruits, vegetables, and whole grains and a 'Western' pattern high in red meat and refined foods. While the underlying algebra is generic principal component or cluster analysis, what makes this a distinct method is its substantive construction: the input is the food-group intake matrix of the whole diet, and the output is interpretable eating patterns linked to disease.	The Individual Dietary Diversity Score (IDDS) is a simple, rapid count of the number of distinct food groups an individual consumed over the previous 24 hours, used as a population-level proxy for diet quality and micronutrient adequacy. Standardized in the FAO's 2011 Guidelines for Measuring Household and Individual Dietary Diversity by Kennedy, Ballard and Dop, the IDDS rests on the observation, reviewed by Ruel, that more diverse diets tend to be more nutritionally adequate. The score is obtained from a qualitative recall of everything eaten, mapping foods to a standard set of nine food groups and counting how many groups appear. Because it requires no portion weighing or food-composition tables, it is cheap to collect at scale and has become a workhorse indicator in nutrition surveys, food-security monitoring, and program evaluation.