Evidence map›Paper›PMID 33413469›Full record

ArticlePopulation health metrics2021

Comparisons of individual- and area-level socioeconomic status as proxies for individual-level measures: evidence from the Mortality Disparities in American Communities study.

Jennifer L Moss, Norman J Johnson, Mandi Yu, Sean F Altekruse, Kathleen A Cronin

Open access · goldAbstract read
In one paragraph

Article in Population health metrics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 103 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
103citing papers in PubMed, 2 pooled it
12.9field-weighted citation impact, top 1% 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

103 citing papers in PubMed, 2 syntheses or guidelines pooled it, 163 citations in OpenAlex.

  1. Pooled it
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  4. Trial
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  8. Rurality and long-term outcomes after critical illness.Annals of the American Thoracic Society · 2026
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  11. Income Persistence and the Risk of Hepatocellular Carcinoma in Individuals with Type 2 Diabetes.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2026
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  13. Review
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  15. California mortality and the Healthy Places Index.American journal of epidemiology · 2026
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  19. Observational
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43 more citing papers are in PubMed but not listed here.

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

5 authors at 4 institutions in 1 country.

Jennifer L MossCancer Prevention Fellowship Program, Surveillance Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD, USA. jmoss1@pennstatehealth.psu.edu.ORCID 0000-0002-3794-1344
Norman J JohnsonCenter for Administrative Records Research and Applications, Research & Methodologies Directorate, US Bureau of the Census, Suitland, MD, USA.
Mandi YuStatistical Research & Applications Branch, Surveillance Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD, USA.
Sean F AltekruseCardiovascular Epidemiology Branch, National Heart, Lung, and Blood Institute, Bethesda, MD, USA.
Kathleen A CroninOffice of the Associate Director, Surveillance Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD, USA.
National Cancer Institute · USNational Heart Lung and Blood Institute · USPennsylvania State University · USUnited States Census Bureau · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundArea-level measures are often used to approximate socioeconomic status (SES) when individual-level data are not available. However, no national studies have examined the validity of these measures in approximating individual-level SES.

methodsData came from ~ 3,471,000 participants in the Mortality Disparities in American Communities study, which links data from 2008 American Community Survey to National Death Index (through 2015). We calculated correlations, specificity, sensitivity, and odds ratios to summarize the concordance between individual-, census tract-, and county-level SES indicators (e.g., household income, college degree, unemployment). We estimated the association between each SES measure and mortality to illustrate the implications of misclassification for estimates of the SES-mortality association.

resultsParticipants with high individual-level SES were more likely than other participants to live in high-SES areas. For example, individuals with high household incomes were more likely to live in census tracts (r = 0.232; odds ratio [OR] = 2.284) or counties (r = 0.157; OR = 1.325) whose median household income was above the US median. Across indicators, mortality was higher among low-SES groups (all p < .0001). Compared to county-level, census tract-level measures more closely approximated individual-level associations with mortality.

conclusionsModerate agreement emerged among binary indicators of SES across individual, census tract, and county levels, with increased precision for census tract compared to county measures when approximating individual-level values. When area level measures were used as proxies for individual SES, the SES-mortality associations were systematically underestimated. Studies using area-level SES proxies should use caution when selecting, analyzing, and interpreting associations with health outcomes.

Indexed as

Social ClassHumansSocioeconomic FactorsSurveys and QuestionnairesUnited StatesCensus tractsCountiesIndividualsMortalitySocial epidemiologySocioeconomic status

Identifiers

PMID33413469
PMCPMC7792135
OpenAlexW3121122407

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.