Evidence map›Paper›PMID 25534510›Full record

ArticleAnnals of epidemiology2015

Cumulative socioeconomic disadvantage and cardiovascular disease mortality in the Alameda County Study 1965 to 2000.

Vicki Johnson-Lawrence, Sandro Galea, George Kaplan

Abstract read
In one paragraph

Article in Annals of epidemiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

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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

9 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.

Vicki Johnson-LawrenceDepartment of Public Health and Health Sciences, University of Michigan-Flint, Flint, MI. Electronic address: vickij@umich.edu.
Sandro GaleaDepartment of Epidemiology, Columbia University, New York, NY.
George KaplanDepartment of Epidemiology, University of Michigan, Ann Arbor, MI.

Funding

MI Interdisciplinary Ctr-Social Inequality, Mind &BodyR24HD047861 · NICHD · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI KAPLAN, GEORGE A. · 2004 to 2008
$5.0M
HEALTH AND FUNCTION OVER THREE DECADES IN ALAMEDA COUNTYR37AG011375 · NIA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI KAPLAN, GEORGE A. · 1993 to 2002
$1.3M
NIA NIH HHS 5R37AG011375NIA NIH HHS R37 AG011375NICHD NIH HHS R24 HD047861
6 · The paper itself

Abstract

purposeSocioeconomic disadvantage is often evaluated at single points in the adult life course in health research. Social mobility models suggest that socioeconomic patterns may also influence disease risk. This study examines cumulative socioeconomic disadvantage (CSD) in relation to cardiovascular disease mortality (CVDM).

methodsData were from the Alameda County Study (n = 2530). The CSD indices included father's education, the respondent's education, and either average or latent variable trajectory models of adulthood household income (1965-1994). Proportional hazards models were used to assess the associations between CSD and CVDM.

resultsThe CSD measures were not associated with CVDM in men. Among women, the magnitude of the association between CSD and CVDM was greater for the income trajectory (hazard ratio3 vs 0 = 4.73, 95% confidence interval = 2.20-10.18) compared with the average income (hazard ratio3 vs 0 = 3.78, 95% confidence interval = 1.67-8.53) CSD measure.

conclusionsMeasures of CSD that incorporate patterning of resources over the life course were associated with CVDM for women but not men. Patterning of available socioeconomic resources may differentially influence chronic disease risk and mortality by gender, and future work should continue to investigate how greater patterns variability in available resources influences health outcomes.

Indexed as

AdolescentAdultAgedAged, 80 and overCaliforniaCardiovascular DiseasesFemaleHealth Status DisparitiesHumansMaleMiddle AgedProportional Hazards ModelsRisk FactorsSex FactorsSocioeconomic FactorsYoung AdultCardiovascular diseaseIncomeMortalitySocial mobilitySocioeconomic

Identifiers

PMID25534510
PMCPMC4312003

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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.