Evidence map›Paper›PMID 30693449›Full record

ArticleDemography2019

Misreporting Month of Birth: Diagnosis and Implications for Research on Nutrition and Early Childhood in Developing Countries.

Anna Folke Larsen, Derek Headey, William A Masters

Abstract read
In one paragraph

Article in Demography, 2019. 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
–field-weighted citation impact
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.

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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

3 authors.

Anna Folke LarsenDepartment of Economics, University of Copenhagen, Harespringet 3, Copenhagen NV, Denmark. afl@rfintervention.dk.
Derek HeadeyPoverty, Health, and Nutrition Division, International Food Policy Research Institute, 1201 Eye Street, Washington, DC, 20005-3915, USA.
William A MastersFriedman School of Nutrition and Department of Economics, Tufts University, Boston, MA, 02111, USA.

Funding

EPA EP-C-15-008
6 · The paper itself

Abstract

A large literature has used children's birthdays to identify exposure to shocks and estimate their impacts on later outcomes. Using height-for-age z scores (HAZ) for more than 990,000 children in 62 countries from 163 Demographic and Health Surveys (DHS), we show how random errors in birth dates create artifacts in HAZ that can be used to diagnose the extent of age misreporting. The most important artifact is an upward gradient in HAZ by recorded month of birth (MOB) from start to end of calendar years, resulting in a large HAZ differential between December- and January-born children of -0.32 HAZ points. We observe a second artifact associated with round ages, with a downward gradient in HAZ by recorded age in months, and then an upward step after reaching ages 2, 3, and 4. These artifacts have previously been interpreted as actual health shocks. We show that they are not related to agroclimatic conditions but are instead linked to the type of calendar used and arise mainly when enumerators do not see the child's birth registration cards. We explain the size of the December-January gap through simulation in which 11 % of children have their birth date replaced by a random month. We find a minor impact on the average stunting rate but a larger impact in specific error-prone surveys. We further show how misreporting MOB causes attenuation bias when MOB is used for identification of shock exposure as well as systematic bias in the impact on HAZ of events that occur early or late in each calendar year.

Indexed as

BiasAge FactorsChild DevelopmentChild Nutrition SciencesChild, PreschoolComputer SimulationDeveloping CountriesFemaleGrowth DisordersHealth SurveysHumansInfantMaleResearchTimeChild ageHeight-for-ageMeasurement errorNutritionStunting

Identifiers

PMID30693449
PMCPMC6449488

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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.