Evidence map›Paper›PMID 31934310›Full record

ArticleComputational and structural biotechnology journal2020

Causal inference for the effect of environmental chemicals on chronic kidney disease.

Jing Zhao, Paige Hinton, Junyi Chen, Jing Jiang

Abstract read
In one paragraph

Article in Computational and structural biotechnology journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–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

10 citing papers in PubMed.

  1. Chronic exposure to low levels of glyphosate and metals induces kidney dysfunction.Toxicological sciences : an official journal of the Society of Toxicology · 2026
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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.

Jing ZhaoDepartment of Biomedical Informatics, The Ohio State University, Columbus, OH 43210, USA.
Paige HintonDepartment of Mathematics and Statistics, South Dakota State University, Brookings, SD 57006, USA.
Junyi ChenDepartment of Biomedical Informatics, The Ohio State University, Columbus, OH 43210, USA.
Jing JiangDepartment of Biomedical Informatics, The Ohio State University, Columbus, OH 43210, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The impacts of environmental chemicals on the decline of kidney function have been suggested by a limited number of statistical and animal studies. Thus, those exposures may be modifiable risk factors for chronic kidney disease. Some of the chemicals, such as Perfluoroalkyl acid (PFA), are pervasive throughout our environment, determining their health effects is an important public health concern. In this study, we examined cross-sectional data from the 2009-2010 cycle of the National Health and Nutrition Examination Survey (NHANES) using a statistical causal inference method-generalized propensity score method, to determine the links between concentrations of several major environmental chemicals and kidney function measured by the estimated glomerular filtration rate (eGFR). Various generalized propensity score estimation methods including Hirano-Imbens, additive spline, and a generalized additive model were compared. Among the examined environmental chemicals, each of the statistical models used associated an increase in PFA concentration with a decline in eGFR. We conclude that PFA is a modifiable risk factor for chronic kidney disease and the statistical causal method produces credible results in estimating the effect of chemical exposures on a continuous measure of kidney functions with an observational dataset.

Indexed as

Causal inferenceChronic kidney diseaseCKD, chronic kidney diseaseeGFR, estimated glomerular filtration rateEnvironmental chemicalGPS, generalized propensity scoreObservational dataPerfluoroalkyl acidsPFAs, perfluoroalkyl acidsPropensity score

Identifiers

PMID31934310
PMCPMC6951480

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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.