Evidence map›Paper›PMID 33603207›Full record

ReviewPediatric research2021

A new era: improving use of sociodemographic constructs in the analysis of pediatric cohort study data.

Aruna Chandran, Emily Knapp, Tiange Liu, Lorraine T Dean

Open access · greenAbstract readReview
In one paragraph

Review in Pediatric research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
4.6field-weighted citation impact, top 5% 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

13 citing papers in PubMed, 22 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Observational
  6. Article
  7. Article
  8. Article
  9. An Ethics and Social-Justice Approach to Collecting and Using Demographic Data for Psychological Researchers.Perspectives on psychological science : a journal of the Association for Psychological Science · 2023
    Article
  10. Young Children's Dietary Quality in Family Child Care and in Their Own Home.Journal of the Academy of Nutrition and Dietetics · 2023
    Article
  11. Article
  12. Article
  13. Article
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

4 authors at 1 institution in 1 country.

Aruna ChandranDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA. achandr3@jhu.edu.
Emily KnappDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Tiange LiuDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Lorraine T DeanDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Johns Hopkins University · US

Funding

ECHODAC (Environmental Influences on Child Health Outcomes Data Analysis Center)U24OD023382 · OD · JOHNS HOPKINS UNIVERSITY · PI Diane J Catellier, LISA P JACOBSON · 2016 to 2026
$148.4M
The Brown Initiative in HIV and AIDS Clinical Research for Minority CommunitiesR25MH083620 · NIMH · MIRIAM HOSPITAL · PI NUNN, AMY STEWART · 2008 to 2025
$3.7M
Social Determinants of Breast Cancer SurvivorshipK01CA184288 · NCI · UNIVERSITY OF PENNSYLVANIA · PI DEAN, LORRAINE TIERA · 2014 to 2018
$767k
NCI NIH HHS K01 CA184288NIH HHS U24 OD023382NIMH NIH HHS R25 MH083620
6 · The paper itself

Abstract

Given the diversity of sex, gender identity, race, ethnicity, and socioeconomic position (SEP) in children across the United States, it is incumbent upon pediatric and epidemiologic researchers to conduct their work in ways that promote inclusivity, understanding and reduction in inequities. Current child health research often utilizes an approach of "convenience" in how data related to these constructs are collected, categorized, and included in models; the field needs to be more systematic and thoughtful in its approach to understand how sociodemographics affect child health. We offer suggestions for improving the discourse around sex, gender identity, race, ethnicity, and SEP in child health research. We explain how analytic models should be driven by a conceptual framework grounding the choices of variables that are included in analyses, without the automatic "adjusting for" all sociodemographic constructs. We propose to leverage newly available data from large multi-cohort consortia as unique opportunities to improve the current standards for analyzing and reporting core sociodemographic constructs. Improving the characterization and interpretation of child health studies with regards to core sociodemographic constructs is critical for optimizing child health and reducing inequities in the health and well-being of all children across the United States. IMPACT: Current child health research often utilizes an approach of "convenience" in how data related to sex, race/ethnicity, and SEP are collected, categorized, and included in models. We offer suggestions for how scholars can improve the discourse around sex, gender identity, race, ethnicity, and SEP in child health research. We explain how analytic models should be driven by a conceptual framework grounding the choices of variables that are included in analyses. We propose to leverage newly available large cohort consortia of child health studies as opportunities to improve the current standards for analyzing and reporting core sociodemographic constructs.

Indexed as

DemographySocial ClassChildCohort StudiesFemaleHealthcare DisparitiesHumansMale

Identifiers

PMID33603207
PMCPMC8371054
OpenAlexW3131239342

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.