Evidence map›Paper›PMID 30375516›Full record

ArticleJournal of exposure science & environmental epidemiology2019

An algorithm for quantitatively estimating non-occupational pesticide exposure intensity for spouses in the Agricultural Health Study.

Nicole C Deziel, Laura E Beane Freeman, Jane A Hoppin, Kent Thomas, Catherine C Lerro, Rena R Jones, Cynthia J Hines, Aaron Blair, Barry I Graubard, Jay H Lubin and 5 more

Open access · greenAbstract read
In one paragraph

Article in Journal of exposure science & environmental epidemiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
3.0field-weighted citation impact, top 8% 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

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. A case-control study of breast cancer risk and ambient exposure to pesticides.Environmental epidemiology (Philadelphia, Pa.) · 2019
    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

15 authors at 7 institutions in 1 country.

Nicole C DezielYale School of Public Health, Yale University, New Haven, CT, USA. nicole.deziel@yale.edu.
Laura E Beane FreemanDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Jane A HoppinDepartment of Biological Sciences, Center for Human Health and the Environment, North Carolina State University, Raleigh, NC, USA.
Kent ThomasNational Exposure Research Laboratory, U.S. Environmental Protection Agency, Research Triangle Park, Durham, NC, USA.
Catherine C LerroDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Rena R JonesDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Cynthia J HinesDivision of Surveillance, Hazard Evaluation and Field Studies, National Institute for Occupational Safety and Health, Cincinnati, OH, USA.
Aaron BlairDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Barry I GraubardDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Jay H LubinDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Dale P SandlerDepartment of Health and Human Services, Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, Durham, NC, USA.
Honglei ChenDepartment of Health and Human Services, Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, Durham, NC, USA.
Gabriella AndreottiDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Michael C AlavanjaDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Melissa C FriesenDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
National Cancer Institute · USNational Institutes of Health · USMichigan State University · USNational Institute for Occupational Safety and Health · USNorth Carolina State University · USResearch Triangle Park Foundation · USYale University · US

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Studies of Occupational Cancer (Pesticides)ZIACP010119 · NCI · DIVISION OF CANCER EPIDEMIOLOGY AND GENETICS · PI BEANE FREEMAN, LAURA · 2009 to 2025
$46.1M
Health Effects Of Exposures In AgricultureZIAES049030 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI SANDLER, DALE P · 2009 to 2025
$11.2M
STUDIES OF OCCUPATIONAL CANCER--PESTICIDESZ01CP010119 · NCI · DIVISION OF CANCER EPIDEMIOLOGY AND GENETICS · PI ALAVANJA, MICHAEL · 1996 to 2008
$5.0M
HEALTH EFFECTS OF EXPOSURES IN AGRICULTUREZ01ES049030 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI SANDLER, DALE P · 1997 to 2008
$889k
Intramural NIH HHS Z01 CP010119Intramural NIH HHS Z01 ES049030Intramural NIH HHS ZIA CP010119NCATS NIH HHS UL1 TR001863
6 · The paper itself

Abstract

Residents of agricultural areas experience pesticide exposures from sources other than direct agricultural work. We developed a quantitative, active ingredient-specific algorithm for cumulative (adult, married lifetime) non-occupational pesticide exposure intensity for spouses of farmers who applied pesticides in the Agricultural Health Study (AHS). The algorithm addressed three exposure pathways: take-home, agricultural drift, and residential pesticide use. Pathway-specific equations combined (i) weights derived from previous meta-analyses of published pesticide exposure data and (ii) information from the questionnaire on frequency and duration of pesticide use by applicators, home proximity to treated fields, residential pesticide usage (e.g., termite treatments), and spouse's off-farm employment (proxy for time at home). The residential use equation also incorporated a published probability matrix that documented the likelihood active ingredients were used in home pest treatment products. We illustrate use of these equations by calculating exposure intensities for the insecticide chlorpyrifos and herbicide atrazine for 19,959 spouses. Non-zero estimates for ≥1 pathway were found for 78% and 77% of spouses for chlorpyrifos and atrazine, respectively. Variability in exposed spouses' intensity estimates was observed for both pesticides, with 75th to 25th percentile ratios ranging from 7.1 to 7.3 for take-home, 6.5 to 8.5 for drift, 2.4 to 2.8 for residential use, and 3.8 to 7.0 for the summed pathways. Take-home and drift estimates were highly correlated (≥0.98), but were not correlated with residential use (0.01‒0.02). This algorithm represents an important advancement in quantifying non-occupational pesticide relative exposure differences and will facilitate improved etiologic analyses in the AHS spouses. The algorithm could be adapted to studies with similar information.

Indexed as

AgricultureAlgorithmsSpousesAdultEnvironmental ExposureFarmersFemaleHumansMalePesticidesSurveys and QuestionnairesPesticides

Identifiers

PMID30375516
PMCPMC6470005
OpenAlexW2898738435

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.