Innovative methods of dietary assessment and analysis
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Understanding people’s eating patterns—including what they eat and drink and the contextual...
Professor of Epidemiology and Nutrition at Harvard T.H. Chan School of Public Health
Dr. Willett studied food science at Michigan State University, and graduated from the University of Michigan Medical...
Professor of Nutrition at Simmons University
Teresa Fung received her BS and MS in nutrition from Cornell University, and her ScD in both nutrition and epidemiology...
Dr. Bromage’s research has focused on nutritional epidemiology in low- and middle-income countries, with emphasis...
Methods for assessing and analyzing human diets are often costly, laborious, and require special training. As a result, most countries do not regularly conduct diet surveys; only 36% of surveys are nationally-representative, and only 38% include pregnant and nursing women. Furthermore, less than half of countries have national food composition data, much of which are outdated. Poor diets are the leading cause of death globally, and a lack of quality data poses a challenge to evidence-based efforts for improving diets, particularly in low- and middle-income countries where research infrastructure is often limited, and where 84% of diet-related deaths occur. This collection will describe novel methods, tools, and datasets that facilitate assessment and analysis of diet and food consumption. Articles describing economical methods that may be used in or applied to limited-resource settings are encouraged.
Articles may describe:
1. How innovative dietary assessment methods, instruments, or technologies may be developed, validated, taught, collected, or integrated in existing platforms,
2. Application of novel software or statistical methods for: compilation or use of food composition data, analysis of diet quality or diet patterns, prediction of food or nutrient intake, the translation of dietary data to the formulation of empirical strategies, or guidance for improving diet and nutrition, or
3. Methods for applying nonconventional datasets (e.g. household consumption and expenditure, food balance, commercial datasets, geospatial data, or agriculture and other food systems data) to the analysis of diet, diet quality, and food security