ArticlePloS one2018
Assessing dietary intakes from household budget surveys: A national analysis in Bangladesh.
Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 32 citations in OpenAlex.
- Impact of consumption of vitamin D fortified foods on serum vitamin D concentrations and vitamin D status in families living in Pune, India: an effectiveness study.European journal of nutrition · 2025Trial
- Assessment of dietary patterns and macronutrient intake among the adult population of Armenia.Frontiers in nutrition · 2026Article
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- Adolescent girls in aquaculture ecozones at risk of nutrient deficiency in Bangladesh development and validation of an integrated metric.BMC public health · 2023Article
- Dietary patterns derived using principal component analysis and associations with sociodemographic characteristics and overweight and obesity: A cross-sectional analysis of Iranian adults.Frontiers in nutrition · 2023Article
- Update on Analytical Methods and Research Gaps in the Use of Household Consumption and Expenditure Survey Data to Inform the Design of Food-Fortification Programs.Advances in nutrition (Bethesda, Md.) · 2022Article
- Comparing estimated cost-effectiveness of micronutrient intervention programs using primary and secondary data: evidence from Cameroon.Annals of the New York Academy of Sciences · 2022Article
- Household-level consumption data can be redistributed for individual-level Optifood diet modeling: analysis from four countries.Annals of the New York Academy of Sciences · 2022Article
- A review of harmonization methods for studying dietary patterns.Smart health (Amsterdam, Netherlands) · 2022Article
- Associations between diet quality and obesity in a nationally representative sample of Iranian households: A cross-sectional study.Obesity science & practice · 2022Article
- Analyzing the Drivers of Household Dietary Diversity: Evidence from Burkina Faso.Food and nutrition bulletin · 2021Article
- RawJournal of food composition and analysis : an official publication of the United Nations University, International Network of Food Data Systems · 2021Article
- The complexity of producing and interpreting dietary vitamin A statistics.Journal of food composition and analysis : an official publication of the United Nations University, International Network of Food Data Systems · 2021Article
- Current calcium fortification experiences: a review.Annals of the New York Academy of Sciences · 2021Review
- A comparison of diet quality indices in a nationally representative cross-sectional study of Iranian households.Nutrition journal · 2020Article
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Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
Abstract
backgroundAccurate national information on dietary intakes, including heterogeneity among individuals, is critical to inform health implications and policy priorities. In low- and middle-income countries, household expenditure surveys constitute the major source of food data, but with uncertain validity for individual-level intakes.
objectiveTo investigate how individualized dietary consumption estimated from household survey data compared with individual-level 24-hr dietary recalls (24hR); and to assess potential heterogeneity by method for individualizing household intakes, dietary indicator, and individual characteristics (age, sex, education, religion, household income).
methodsWe evaluated data from the 2011-2012 Bangladesh Household Integrated Survey (BIHS), which included household-level consumption data (5,503 households) and individual-level dietary data based on 24hR from these households (22,173 participants). Household and 24hR estimates were standardized and harmonized for 33 dietary indicators, including 9 food groups, total energy, 8 macronutrients, and 15 micronutrients. Individual consumption was estimated from household data using two approaches, the Adult Male Equivalent (AME) and per capita (PC) approach. For each dietary indicator, differences in household vs. individual mean estimates were evaluated overall and by strata of individual characteristics, using Spearman's correlations and univariate and multivariate linear regression models.
resultsIndividualized household estimates overestimated individual intakes from 24hR for all dietary factors using either estimation method (P<0.001 for each), except for starchy vegetables (AME: P = 0.15; PC: P = 0.85). For foods, overestimation ranged from 4% for seafood to about 240% for fruits, and for nutrients from 11% for carbohydrates and poly-unsaturated fats to 55% for vitamin C, with similar overestimation for the AME and the PC method. By strata, overestimation was modestly higher in men vs. women, in children (0-10y) vs. adolescents (11-19y) and adults (20-44y, ≥45y), among adults of higher (≥6y) vs. lower (<6y) education, in Muslims vs. other religions (Christians, Hindus), and for the lowest vs. all other income groups. This overestimation was notably higher in young children (0-5y) vs. all other age groups and in the lowest vs. all other income groups. Underestimation was rarely observed, for example for milk intake (-56%) in young children (0-5y). The PC approach did not capture heterogeneity in validity of estimation of different dietary factors by age, mainly in children (0-5y, 6-10y). Spearman's correlations between individualized household estimates and 24hR data were higher for the AME (0.30-0.70) than PC (0.20-0.50) approach. Findings were similar with and without multivariate regression, with proportions of variance (R2) in 24hR intakes explained by the AME being generally greater than PC estimates, yet still low to modest.
conclusionsIn this national survey, established methods for estimating individual level intakes from household surveys produce overestimation of intakes of nearly all dietary indicators, with significant variation depending on the dietary factor and modest variation depending on individual characteristics. These findings suggest a need for new methods to estimate individual-level consumption from household survey estimates.
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