Evidence map›Paper›PMID 30148863›Full record

ArticlePloS one2018

Assessing dietary intakes from household budget surveys: A national analysis in Bangladesh.

Dimitra Karageorgou, Fumiaki Imamura, Jianyi Zhang, Peilin Shi, Dariush Mozaffarian, Renata Micha

Open access · goldAbstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
2.0field-weighted citation impact, top 15% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 32 citations in OpenAlex.

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  10. A review of harmonization methods for studying dietary patterns.Smart health (Amsterdam, Netherlands) · 2022
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  13. RawJournal of food composition and analysis : an official publication of the United Nations University, International Network of Food Data Systems · 2021
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  14. 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 · 2021
    Article
  15. Current calcium fortification experiences: a review.Annals of the New York Academy of Sciences · 2021
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 2 countries.

Dimitra KarageorgouFriedman School of Nutrition Science and Policy, Tufts University, Boston, MA, United States of America.
Fumiaki ImamuraMRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom.
Jianyi ZhangFriedman School of Nutrition Science and Policy, Tufts University, Boston, MA, United States of America.
Peilin ShiFriedman School of Nutrition Science and Policy, Tufts University, Boston, MA, United States of America.
Dariush MozaffarianFriedman School of Nutrition Science and Policy, Tufts University, Boston, MA, United States of America.
Renata MichaFriedman School of Nutrition Science and Policy, Tufts University, Boston, MA, United States of America.
Tufts University · USMRC Epidemiology Unit · GB

Funding

Medical Research Council MC_UU_12015/5
6 · The paper itself

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.

Indexed as

DietDiet SurveysEnergy IntakeFamily CharacteristicsIncomeNutrition SurveysAdolescentAdultBangladeshChildFeeding BehaviorFemaleHumansMaleMicronutrientsMiddle AgedMicronutrients

Identifiers

PMID30148863
PMCPMC6110494
OpenAlexW2889318470

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.