Evidence map›Paper›PMID 42482952›Full record

ArticleJournal of the Endocrine Society2026

Low testosterone is a phenotype of visceral adiposity.

Karl E Friedl, Adam W Potter

Abstract read
In one paragraph

Article in Journal of the Endocrine Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

2 authors.

Karl E FriedlU.S. Army Research Institute of Environmental Medicine, Natick, MA 01760-5007, USA.ORCID https://orcid.org/0000-0002-3134-8427
Adam W PotterU.S. Army Research Institute of Environmental Medicine, Natick, MA 01760-5007, USA.ORCID https://orcid.org/0000-0003-4980-8353

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Context: Low testosterone in men is associated with obesity. However, body mass index (BMI) and waist circumference (WC), the most common measures of obesity, do not account for fat distribution. Visceral adipose tissue (VAT) may be the more precise metabolic determinant of androgen suppression. Objective: To determine if visceral adiposity better explains variations in testosterone levels than BMI or WC. Design and Participants: This was a cross-sectional analysis of 4948 US men, aged 20-59, from the 2011-2016 National Health and Nutrition Examination Survey (NHANES). All participants had morning total testosterone measurements and 4492 had valid VAT measures from dual-energy X-ray absorptiometry. VAT discordance phenotypes were defined as the lowest vs highest quartile of VAT within BMI and (WC) categories. Main Outcome Measures: Serum total testosterone and sex hormone-binding globulin. Results: Visceral adiposity was strongly and inversely associated with total testosterone. Although VAT, BMI, and WC showed similar overall explanatory value, visceral adiposity identified substantial differences in testosterone among men with similar BMI or WC. Within each BMI category (normal-weight, overweight, and obese), men with high VAT had 33-36% lower testosterone than men with low VAT. Within WC strata, corresponding reductions were 25-39%. Normal-weight men with high VAT had testosterone levels comparable to obese men with low VAT. Conclusion: Visceral adiposity, rather than BMI- or WC-defined obesity, is the primary adiposity correlate of low testosterone in US men. Testosterone deficiency in some men appears to be a phenotype of visceral fat biology rather than obesity per se.

Indexed as

body mass indexhypogonadismNHANEStestosteronevisceral adiposity

Identifiers

PMID42482952
PMCPMC13386011

What OpenQuestion holds

Textmetadata
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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.