Evidence map›Paper›PMID 27649842›Full record

ArticleJournal of exposure science & environmental epidemiology2017

A novel approach for measuring residential socioeconomic factors associated with cardiovascular and metabolic health.

Jaime E Mirowsky, Robert B Devlin, David Diaz-Sanchez, Wayne Cascio, Shannon C Grabich, Carol Haynes, Colette Blach, Elizabeth R Hauser, Svati Shah, William Kraus and 2 more

Open access · bronzeAbstract readComparative Study
In one paragraph

Article in Journal of exposure science & environmental epidemiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
2.4field-weighted citation impact, top 11% 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

14 citing papers in PubMed, 23 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
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  5. Article
  6. Article
  7. Article
  8. Article
  9. Relationship Between Multiple Measures of Financial Hardship and Glycemic Control in Older Adults With Diabetes.Journal of applied gerontology : the official journal of the Southern Gerontological Society · 2021
    Article
  10. Article
  11. Development of TracMyAir Smartphone Application for Modeling Exposures to Ambient PMInternational journal of environmental research and public health · 2019
    Article
  12. Neighborhood sociodemographic effects on the associations between long-term PMEnvironmental epidemiology (Philadelphia, Pa.) · 2019
    Article
  13. Review
  14. Modeling individual exposures to ambient PMThe Science of the total environment · 2018
    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

12 authors at 5 institutions in 1 country.

Jaime E MirowskyCurriculum in Toxicology, University of North Carolina, Chapel Hill, North Carolina, USA.
Robert B DevlinNational Health and Environmental Effects Laboratory, US Environmental Protection Agency, Chapel Hill, North Carolina, USA.
David Diaz-SanchezNational Health and Environmental Effects Laboratory, US Environmental Protection Agency, Chapel Hill, North Carolina, USA.
Wayne CascioNational Health and Environmental Effects Laboratory, US Environmental Protection Agency, Chapel Hill, North Carolina, USA.
Shannon C GrabichNational Health and Environmental Effects Laboratory, US Environmental Protection Agency, Chapel Hill, North Carolina, USA.
Carol HaynesDuke Molecular Physiology Institute, Duke University Medical Center, Durham, North Carolina, USA.
Colette BlachDuke Molecular Physiology Institute, Duke University Medical Center, Durham, North Carolina, USA.
Elizabeth R HauserDuke Molecular Physiology Institute, Duke University Medical Center, Durham, North Carolina, USA.
Svati ShahDuke Molecular Physiology Institute, Duke University Medical Center, Durham, North Carolina, USA.
William KrausDuke Molecular Physiology Institute, Duke University Medical Center, Durham, North Carolina, USA.
Kenneth OldenNational Center for Environmental Assessment, US Environmental Protection Agency, Chapel Hill, North Carolina, USA.
Lucas NeasNational Health and Environmental Effects Laboratory, US Environmental Protection Agency, Chapel Hill, North Carolina, USA.
Environmental Protection Agency · USDuke Medical Center · USDuke University · USDuke University Hospital · USUniversity of North Carolina at Chapel Hill · US

Funding

The Genetics Of Biobehavioral Risk Factors For CVDP01HL036587 · NHLBI · DUKE UNIVERSITY · PI KRAUS, WILLIAM E · 1986 to 2020
$35.9M
SNP discoveryP01HL073042 · NHLBI · DUKE UNIVERSITY · PI VANCE, JEFFERY MARVIN · 2002 to 2006
$13.5M
TOXICOLOGYT32ES007126 · NIEHS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI ILONA JASPERS, Bernard E. Weissman · 1985 to 2026
$13.0M
Metabolomic Quantitative Trait Locus (mQTL) Genetic Mapping in Human CVDR01HL095987 · NHLBI · DUKE UNIVERSITY · PI SHAH, SVATI H. · 2009 to 2013
$3.4M
NHLBI NIH HHS P01 HL036587NHLBI NIH HHS P01 HL073042NHLBI NIH HHS R01 HL095987NIEHS NIH HHS T32 ES007126
6 · The paper itself

Abstract

Individual-level characteristics, including socioeconomic status, have been associated with poor metabolic and cardiovascular health; however, residential area-level characteristics may also independently contribute to health status. In the current study, we used hierarchical clustering to aggregate 444 US Census block groups in Durham, Orange, and Wake Counties, NC, USA into six homogeneous clusters of similar characteristics based on 12 demographic factors. We assigned 2254 cardiac catheterization patients to these clusters based on residence at first catheterization. After controlling for individual age, sex, smoking status, and race, there were elevated odds of patients being obese (odds ratio (OR)=1.92, 95% confidence intervals (CI)=1.39, 2.67), and having diabetes (OR=2.19, 95% CI=1.57, 3.04), congestive heart failure (OR=1.99, 95% CI=1.39, 2.83), and hypertension (OR=2.05, 95% CI=1.38, 3.11) in a cluster that was urban, impoverished, and unemployed, compared with a cluster that was urban with a low percentage of people that were impoverished or unemployed. Our findings demonstrate the feasibility of applying hierarchical clustering to an assessment of area-level characteristics and that living in impoverished, urban residential clusters may have an adverse impact on health.

Indexed as

Social ClassAdultAgedAged, 80 and overCardiac CatheterizationCardiovascular DiseasesCensusesCluster AnalysisCohort StudiesDatabases, FactualDiabetes MellitusFemaleHealth StatusHeart FailureHumansHypertension

Identifiers

PMID27649842
PMCPMC5373927
OpenAlexW2522642027

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.