Evidence map›Paper›PMID 28858828›Full record

ArticleEnvironmental health perspectives2017

Arsenic and Obesity: A Comparison of Urine Dilution Adjustment Methods.

Catherine M Bulka, Sithembile L Mabila, James P Lash, Mary E Turyk, Maria Argos

Open access · diamondAbstract readComparative Study
In one paragraph

Article in Environmental health perspectives, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
4.7field-weighted citation impact, top 5% 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

34 citing papers in PubMed, 83 citations in OpenAlex.

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  8. Metal mixtures and adiposity indicators in women from Northern Mexico.Biometals : an international journal on the role of metal ions in biology, biochemistry, and medicine · 2025
    Article
  9. Article
  10. Article
  11. Metabolic Derangement by Arsenic: a Review of the Mechanisms.Biological trace element research · 2024
    Review
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  13. Article
  14. Review
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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

5 authors at 1 institution in 1 country.

Catherine M BulkaDivision of Epidemiology and Biostatistics, School of Public Health, University of Illinois at Chicago , Chicago, Illinois, USA.
Sithembile L MabilaDivision of Environmental and Occupational Health Sciences, School of Public Health, University of Illinois at Chicago , Chicago, Illinois, USA.
James P LashDivision of Nephrology, Department of Medicine, University of Illinois at Chicago , Chicago, Illinois, USA.
Mary E TurykDivision of Epidemiology and Biostatistics, School of Public Health, University of Illinois at Chicago , Chicago, Illinois, USA.
Maria ArgosDivision of Epidemiology and Biostatistics, School of Public Health, University of Illinois at Chicago , Chicago, Illinois, USA.
University of Illinois Chicago · US

Funding

Occupational Safety and Health, ERC, University of Illinois at ChicagoT42OH008672 · OH · UNIVERSITY OF ILLINOIS AT CHICAGO · PI BUCHANAN, SUSAN NATHALIE · 2005 to 2025
$32.7M
Training in CVD Epidemiology & Related Chronic Diseases in Minority PopulationsT32HL125294 · NHLBI · UNIVERSITY OF ILLINOIS AT CHICAGO · PI DAVIGLUS, MARTHA L · 2015 to 2019
$1.3M
NHLBI NIH HHS T32 HL125294NIOSH CDC HHS T42 OH008672
6 · The paper itself

Abstract

introductionA commonly used approach to adjust for urine dilution in analyses of biomarkers is to adjust for urinary creatinine. However, creatinine is a product of muscle mass and is therefore associated with body mass. In studies of urinary analytes and obesity or obesity-related outcomes, controlling for creatinine could induce collider stratification bias. We illustrate this phenomenon with an analysis of urinary arsenic.

objectiveWe aimed to evaluate various approaches of adjustment for urinary dilution on the associations between urinary arsenic concentration and measures of obesity.

methodsUsing data from the National Health and Nutrition Examination Survey, we regressed body mass index (BMI) and waist-to-height ratios on urinary arsenic concentrations. We compared eight approaches to account for urine dilution, including standardization by urinary creatinine, osmolality, and flow rates, and inclusion of these metrics as independent covariates. We also used a recently proposed method known as covariate-adjusted standardization.

resultsInverse associations between urinary arsenic concentration with BMI and waist-to-height ratio were observed when either creatinine or osmolality were used to standardize or as covariates. Not adjusting for dilution, standardizing or adjusting for urinary flow rate, and using covariate-adjusted standardization resulted in null associations observed between arsenic concentration in relation to BMI and waist-to-height ratio.

conclusionsOur findings suggest that arsenic exposure is not associated with obesity, and that urinary creatinine and osmolality may be colliders on the causal pathway from arsenic exposure to obesity, as common descendants of hydration and body composition. In studies of urinary biomarkers and obesity or obesity-related outcomes, alternative metrics such as urinary flow rate or analytic strategies such as covariate-adjusted standardization should be considered. https://doi.org/10.1289/EHP1202.

Indexed as

UrinalysisAdultArsenicBiomarkersBody Mass IndexCreatinineEnvironmental ExposureEnvironmental MonitoringFemaleHumansMaleMiddle AgedNutrition SurveysObesityWaist-Height RatioYoung AdultArsenicBiomarkersCreatinine

Identifiers

PMID28858828
PMCPMC5783631
OpenAlexW2753670185

What OpenQuestion holds

Textmetadata
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.