Evidence map›Paper›PMID 26232757›Full record

ArticleThe Science of the total environment2015

Modeling groundwater nitrate concentrations in private wells in Iowa.

David C Wheeler, Bernard T Nolan, Abigail R Flory, Curt T DellaValle, Mary H Ward

Open access · greenAbstract read
In one paragraph

Article in The Science of the total environment, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 1 pooled it
8.2field-weighted citation impact, top 2% 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

35 citing papers in PubMed, 1 synthesis or guideline pooled it, 158 citations in OpenAlex.

  1. Validating a continental-scale groundwater diffuse pollution model using regional datasets.Environmental science and pollution research international · 2019
    Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Article
  7. A review of geospatial exposure models and approaches for health data integration.Journal of exposure science & environmental epidemiology · 2025
    Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. US drinking water quality: exposure risk profiles for seven legacy and emerging contaminants.Journal of exposure science & environmental epidemiology · 2024
    Review
  14. Nutrient Explorer: An analytical framework to visualize and investigate drivers of surface water quality.Environmental modelling & software : with environment data news · 2023
    Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Drinking water sources and water quality in a prospective agricultural cohort.Environmental epidemiology (Philadelphia, Pa.) · 2022
    Article
  20. 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

5 authors at 5 institutions in 1 country.

David C WheelerDepartment of Biostatistics, Virginia Commonwealth University, 830 East Main St, Richmond, VA 23298, United States. Electronic address: dcwheeler@vcu.edu.
Bernard T NolanU.S. Geological Survey, Reston, VA, United States.
Abigail R FloryWestat, Rockville, MD, United States.
Curt T DellaValleOccupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, United States.
Mary H WardOccupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, United States.
Division of Cancer Epidemiology and GeneticsNational Cancer Institute · USUnited States Geological Survey · USVirginia Commonwealth University · USWestat (United States) · US

Funding

Studies of Occupational Cancer (Pesticides)ZIACP010119 · NCI · DIVISION OF CANCER EPIDEMIOLOGY AND GENETICS · PI BEANE FREEMAN, LAURA · 2009 to 2025
$46.1M
Cancer Risk and Environmental ExposuresZIACP010125 · NCI · DIVISION OF CANCER EPIDEMIOLOGY AND GENETICS · PI PURDUE, MARK · 2009 to 2025
$41.3M
CLINICAL/IMMUNOLOGIC/GENETIC ANALYSES OF AUTOIMMUNE LYMPHOPROLIFERATIVE SYNDROMEZ01AI000732 · NIAID · NIAID EXTRAMURAL ACTIVITIES · PI RAO, VEMULKONDA · 1995 to 2008
$1.1M
INVESTIGATIONS OF ENVIRONMENTAL EXPOSURES AND CANCERZ01CP010125 · NCI · DIVISION OF CANCER EPIDEMIOLOGY AND GENETICS · PI CANTOR, KENNETH · 1996 to 2008
$108k
Intramural NIH HHS Z01 CP010125PHS HHS HHSN261201300355P
6 · The paper itself

Abstract

Contamination of drinking water by nitrate is a growing problem in many agricultural areas of the country. Ingested nitrate can lead to the endogenous formation of N-nitroso compounds, potent carcinogens. We developed a predictive model for nitrate concentrations in private wells in Iowa. Using 34,084 measurements of nitrate in private wells, we trained and tested random forest models to predict log nitrate levels by systematically assessing the predictive performance of 179 variables in 36 thematic groups (well depth, distance to sinkholes, location, land use, soil characteristics, nitrogen inputs, meteorology, and other factors). The final model contained 66 variables in 17 groups. Some of the most important variables were well depth, slope length within 1 km of the well, year of sample, and distance to nearest animal feeding operation. The correlation between observed and estimated nitrate concentrations was excellent in the training set (r-square=0.77) and was acceptable in the testing set (r-square=0.38). The random forest model had substantially better predictive performance than a traditional linear regression model or a regression tree. Our model will be used to investigate the association between nitrate levels in drinking water and cancer risk in the Iowa participants of the Agricultural Health Study cohort.

Indexed as

Drinking WaterEnvironmental ExposureGroundwaterHumansModels, ChemicalNitratesWater Pollutants, ChemicalWater SupplyDrinking WaterNitratesWater Pollutants, ChemicalGroundwater contaminationNitrateRandom forest

Identifiers

PMID26232757
PMCPMC6397646
OpenAlexW976499782

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.