Evidence map›Paper›PMID 26068905›Full record

ArticleEnvironmental health : a global access science source2015

A cross-sectional analysis of polycyclic aromatic hydrocarbons and diesel particulate matter exposures and hypertension among individuals of Mexican origin.

Komal S Bangia, Elaine Symanski, Sara S Strom, Melissa Bondy

Abstract read
In one paragraph

Article in Environmental health : a global access science source, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 2 pooled it
–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

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

19 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
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  7. Review
  8. Article
  9. Metabolic Syndrome and Endocrine Disrupting Chemicals: An Overview of Exposure and Health Effects.International journal of environmental research and public health · 2021
    Review
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  15. PMEnvironmental science & technology · 2019
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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

4 authors.

Komal S BangiaOffice of Environmental Health Hazard Assessment, 1515 Clay St. Suite 1600, Oakland, CA, 94612, USA. Komal.bangia@oehha.ca.gov.
Elaine SymanskiDepartment of Epidemiology, Human Genetics and Environmental Sciences, Southwest Center for Occupational and Environmental Health, 1200 Herman Pressler St. Suite W-1028, Houston, TX, 77030, USA. elaine.symanski@uth.tmc.edu.
Sara S StromDepartment of Epidemiology, The University of Texas MD Anderson Cancer Center, Unit 1340, 1155 Pressler Street, Houston, TX, 77030-4009, USA. sstrom@mdanderson.org.
Melissa BondyBaylor College of Medicine, One Baylor Plaza, Houston, TX, 77030, USA. mbondy@bcm.edu.

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI DIANE BODURKA · 1985 to 2026
$290.8M
NCI NIH HHS P30 CA016672
6 · The paper itself

Abstract

backgroundEpidemiological studies have found that particulate matter is associated with increases in blood pressure. Yet, less is known about the effects of specific sources or constituents of particulate matter, such as diesel particulate matter or polycyclic aromatic hydrocarbons (PAHs). We evaluated associations between self-reported hypertension and residential air levels of diesel particulate matter and PAHs among individuals of Mexican origin living in a large inner city.

methodsThe Mano a Mano cohort (established in 2001 by the University of Texas MD Anderson Cancer Center) is comprised of individuals of Mexican origin residing in Houston, Texas. Using geographical information systems, we linked modeled annual estimates of PAHs and diesel particulate matter at the census tract level from the 2002 and 2005 U.S. Environmental Protection Agency's National-Scale Air Toxics Assessment to baseline residential addresses of cohort members who enrolled from 2001 to 2003 or 2004 to 2006, respectively. For each enrollment period, we applied mixed-effects logistic regression models to determine associations between diesel particulate matter and PAHs, separately, and self-reported hypertension while adjusting for confounders and the clustering of observations within census tracts and households.

resultsThe study population consisted of 11218 participants of which 77% were women. The mean participant age at baseline was 41 years. Following adjustment for age, there was a dose-dependent, positive association between PAHs and hypertension (medium exposure, adjusted odds ratio (OR) = 1.09, 95% CI: 0.88-1.36; high exposure, OR = 1.40, 95% CI: 1.01-1.94) for individuals enrolled during 2001-2003; associations were generally similar in magnitude, but less precise, following adjustment for age, gender, smoking, and BMI. No association was detected for the later period. There was no evidence of an association between residential levels of diesel particulate matter and hypertension.

conclusionsThis study builds on a limited number of prior investigations of the association between ambient air levels of PAHs or diesel particulate matter and hypertension by focusing on a relatively young cohort of predominantly adult women of Mexican origin. Future analyses are warranted to explore associations in the cohort using incident hypertension when sufficient data become available and to further examine associations between specific chemical constituents of particulate matter and hypertension in this and other populations.

Indexed as

AdultAgedAge FactorsAir PollutantsCohort StudiesCross-Sectional StudiesEnvironmental MonitoringFemaleGasolineHumansHypertensionLogistic ModelsMaleMexican AmericansMiddle AgedOdds RatioAir PollutantsGasolineParticulate MatterPolycyclic Aromatic HydrocarbonsVehicle Emissions

Identifiers

PMID26068905
PMCPMC4471931

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LicenceCC BY
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Registered trials

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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.