Evidence map›Paper›PMID 19142225›Full record

ArticlePloS one2009

A Trivers-Willard effect in contemporary humans: male-biased sex ratios among billionaires.

Elissa Z Cameron, Fredrik Dalerum

Abstract read
In one paragraph

Article in PloS one, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing 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

30 citing papers in PubMed.

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  13. The Trivers-Willard hypothesis: sex ratio or investment?Proceedings. Biological sciences · 2016
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  17. Predictions for sex of first born child reflect masculine and feminine characteristics in male and female undergraduates.Evolutionary psychology : an international journal of evolutionary approaches to psychology and behavior · 2013
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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

2 authors.

Elissa Z CameronMammal Research Institute, Department of Zoology and Entomology, University of Pretoria, Pretoria, South Africa. ezcameron@zoology.up.ac.za
Fredrik Dalerum

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNatural selection should favour the ability of mothers to adjust the sex ratio of offspring in relation to the offspring's potential reproductive success. In polygynous species, mothers in good condition would be advantaged by giving birth to more sons. While studies on mammals in general provide support for the hypothesis, studies on humans provide particularly inconsistent results, possibly because the assumptions of the model do not apply. METHODOLOGY/PRINCIPAL

findingsHere, we take a subset of humans in very good condition: the Forbe's billionaire list. First, we test if the assumptions of the model apply, and show that mothers leave more grandchildren through their sons than through their daughters. We then show that billionaires have 60% sons, which is significantly different from the general population, consistent with our hypothesis. However, women who themselves are billionaires have fewer sons than women having children with billionaires, suggesting that maternal testosterone does not explain the observed variation. Furthermore, paternal masculinity as indexed by achievement, could not explain the variation, since there was no variation in sex ratio between self-made or inherited billionaires. CONCLUSIONS/SIGNIFICANCE: Humans in the highest economic bracket leave more grandchildren through sons than through daughters. Therefore, adaptive variation in sex ratios is expected, and human mothers in the highest economic bracket do give birth to more sons, suggesting similar sex ratio manipulation as seen in other mammals.

Indexed as

ReproductionSelection, GeneticSex RatioFemaleHumansMaleSocioeconomic Factors

Identifiers

PMID19142225
PMCPMC2614476

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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.