Global Datasets on Human Inadequate Nutrient Intakes

For extensive details, data dictionaries, and hyperlinks to associated articles, source materials, and GitHub repositories, please view the Full Description pdf in the attachments of this website. As a note, Simone Passarelli and Christopher Free are joint first authors and Ty Beal and Christopher Golden are joint senior authors for this publication. Overview This Dataverse page provides access to three related datasets that describe the prevalence of inadequate nutrient intakes for subnational age-sex groups in 185 countries globally. These datasets originated from three related papers with similar underlying methodologies, building off of each other to add new layers of information, including the role of fortification and protein in inadequate nutrient intakes. The variable names, subnational groups, and methodologies across the three papers have been harmonized, allowing users to select and download the dataset(s) that best meet their needs. Dataset 1: Diet The first dataset is from Passarelli et al. (2022), which estimated the prevalence of inadequate intakes for 15 micronutrients for 34 age-sex groups in 185 countries. These estimates did not include fortification and therefore represent the prevalence of inadequate intakes based on intrinsic nutrients in foods alone. The estimates were generated using estimates of mean micronutrient intakes from the Global Dietary Database and estimates in the variability of micronutrient intakes from Passarelli et al. (2022). Overall, inadequate intakes were described for nine vitamins (vitamin E, riboflavin, folate, vitamin C, vitamin B6, vitamin A, vitamin B12, thiamin, niacin) and six minerals (iodine, calcium, iron, zinc, selenium, and magnesium). Dataset 2: Fortification The second dataset is from Friesen et al. (in press), which used the methodology developed by Passarelli et al. (2022) to estimate the prevalence of inadequate intakes for 13 micronutrients in the same 34 age-sex groups in 185 countries accounting for current fortification programs as well as potential expanded fortification programs. Vitamin C and magnesium were excluded because they are not commonly fortified. The levels of current fortification were described using data from the Global Fortification Data Exchange (GFDx), which describes the fortification of five food vehicles (salt, oil, wheat flour, maize flour, rice) in nearly every country. Friesen et al. (in press) also estimated the prevalence of inadequate intake under improved fortification scenarios. Thus, results are presented for the following: ● Scenario 1-Current fortification: Evaluates the prevalence of inadequate intakes under current fortification programs. ● Scenario 2-Improved compliance: Evaluates the prevalence of inadequate intakes in a scenario in which compliance with current fortification programs increases to 90%. ● Scenario 3-Aligned standards: Evaluates the prevalence of inadequate intakes in a scenario in which country-specific fortification standards are increased to match international standards. ● Scenario 4-Aligned standards with improved compliance: Evaluates the prevalence of inadequate intakes in a scenario in which country-specific fortification standards are increased to match international standards and compliance is increased to 90%. ● Scenario 5-Aligned standards, improved compliance, and expanded coverage: Evaluates the prevalence of inadequate intakes in a scenario in which country-specific fortification standards are increased to match international standards, compliance is increased to 90%, and more countries adopt fortification programs at international standards. Friesen et al. (in press) also estimated the prevalence of excessive intakes under the current and improved fortification programs. Dataset 3: Protein The third dataset is from De Nicola et al. (in preparation), which estimates the prevalence of inadequate dietary protein intake for 40 age–sex groups across 185 countries in 2018. This dataset extends the distribution-based framework developed by Passarelli et al. (2024) by explicitly linking protein intake to modeled caloric intake distributions and physiological, body-weight–scaled protein requirements. Because protein intake is intrinsically coupled to energy intake, protein inadequacy is evaluated under both a counterfactual energy-adequate scenario and a set of realistic caloric intake scenarios. Protein inadequacy is assessed relative to the Estimated Average Requirement (EAR), defined in grams per kilogram of body weight per day and converted to absolute daily requirements using country-, age-, and sex-specific body weight data. Intake distributions are reconstructed probabilistically using harmonized estimates of mean intake, variability, and distributional form. The dataset includes results under three caloric intake scenarios (low, medium, and high), derived from FAO Food Balance Sheet data after adjusting for varying levels of downstream food waste. The medium scenario is...