Evidence map›Paper›PMID 18381676›Full record

ArticleStatistics in medicine2008

Modeling epilepsy disparities among ethnic groups in Philadelphia, PA.

David C Wheeler, Lance A Waller, John O Elliott

Open access · greenAbstract read
In one paragraph

Article in Statistics in medicine, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
0.3field-weighted citation impact, top 38% 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

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.

  1. Pooled it
  2. Identifying Area-Level Disparities in Human Papillomavirus Vaccination Coverage Using Geospatial Analysis.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2021
    Article
  3. Observational
  4. Spatial Analysis of the Impact of a School-Level Youth Violence Prevention Program on Violent Crime Incidents in the Community.Prevention science : the official journal of the Society for Prevention Research · 2019
    Article
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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 at 1 institution in 1 country.

David C WheelerDepartment of Biostatistics, Rollins School of Public Health, Emory University, Atlanta, GA, USA. dcwheel@sph.emory.edu
Lance A Waller
John O Elliott
Emory University · US

Funding

Environmental Biostatistics Training GrantT32ES012160 · NIEHS · EMORY UNIVERSITY · PI WALLER, LANCE A · 2006 to 2015
$1.3M
NIEHS NIH HHS T32 ES012160
6 · The paper itself

Abstract

The Centers for Disease Control and Prevention defined epilepsy as an emerging public health issue in a recent report and emphasized the importance of epilepsy studies in minorities and people of low socioeconomic status. Previous research has suggested that the incidence rate for epilepsy is positively associated with various measures of social and economic disadvantage. In response, we utilize hierarchical Bayesian models to analyze health disparities in epilepsy and seizure risks among multiple ethnicities in the city of Philadelphia, Pennsylvania. The goals of the analysis are to highlight any overall significant disparities in epilepsy risks between the populations of Caucasians, African Americans, and Hispanics in the study area during the years 2002--2004 and to visualize the spatial pattern of epilepsy risks by ethnicity to indicate where certain ethnic populations were most adversely affected by epilepsy within the study area. Results of the Bayesian model indicate that Hispanics have the highest epilepsy risk overall, followed by African Americans, and then Caucasians. There are significant increases in relative risk for both African Americans and Hispanics when compared with Caucasians, as indicated by the posterior mean estimates of 2.09 with a 95 per cent credible interval of (1.67, 2.62) for African Americans and 2.97 with a 95 per cent credible interval of (2.37, 3.71) for Hispanics. Results also demonstrate that using a Bayesian analysis in combination with geographic information system (GIS) technology can reveal spatial patterns in patient data and highlight areas of disparity in epilepsy risk among subgroups of the population.

Indexed as

Health Status DisparitiesModels, StatisticalBayes TheoremCluster AnalysisData Interpretation, StatisticalEpilepsyEthnicityGeographic Information SystemsHumansPhiladelphiaPoisson DistributionRisk FactorsSocioeconomic Factors

Identifiers

PMID18381676
PMCPMC4106683
OpenAlexW2055326925

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.