Self-reported aggressiveness does not follow facial masculinization in diverse South Asian populations

Abstract It has been suggested that sexually dimorphic facial traits are related to competitive behavior and aggression, but empirical evidence remains inconsistent and is based on a small number of populations and culturally homogeneous samples. We have combined geometric morphometric analyses with hierarchical Bayesian modeling of sixteen culturally and geographically diverse but understudied ethnic groups in order to test whether self-reported aggression covaries with facial sexual shape dimorphism within and between populations. Across populations, we found no consistent association between the individual level of facial sexual dimorphism and self-reported aggression in either sex. Although populations did differ in mean aggression levels, mean self-reported aggression covaried neither with the magnitude of sexual dimorphism nor with overall facial masculinization. Finally, sex differences in self-reported aggression did not reflect morphological sex differences. These findings challenge the generalizability of claims that aggression is encoded in the sexually dimorphic facial structure.

Authors

Institutions

Publication Details

Journal
PNAS Nexus
Published
2026-09-04
DOI
https://doi.org/10.1093/pnasnexus/pgag299
Primary Topic
Evolutionary Psychology and Human Behavior
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Self-reported aggressiveness does not follow facial masculinization in diverse South Asian populations

Stanzin Namga, Karel Kleisner, Vojtěch Fiala, Eliška Podgorná et al.
PNAS Nexus
Evolutionary Psychology and Human Behavior
article

Self-reported aggressiveness does not follow facial masculinization in diverse South Asian populations

Stanzin Namga, Karel Kleisner, Vojtěch Fiala, Eliška Podgorná, Zuzana Štěrbová, Kewal Krishan, Viktor Černý, Deepika Rani, Abhishikta Ghosh Roy, Sanzida Khatun, Banita Behera, Abdul Hameed, Abdul Raheem Jesmil
article en

Abstract

Abstract It has been suggested that sexually dimorphic facial traits are related to competitive behavior and aggression, but empirical evidence remains inconsistent and is based on a small number of populations and culturally homogeneous samples. We have combined geometric morphometric analyses with hierarchical Bayesian modeling of sixteen culturally and geographically diverse but understudied ethnic groups in order to test whether self-reported aggression covaries with facial sexual shape dimorphism within and between populations. Across populations, we found no consistent association between the individual level of facial sexual dimorphism and self-reported aggression in either sex. Although populations did differ in mean aggression levels, mean self-reported aggression covaried neither with the magnitude of sexual dimorphism nor with overall facial masculinization. Finally, sex differences in self-reported aggression did not reflect morphological sex differences. These findings challenge the generalizability of claims that aggression is encoded in the sexually dimorphic facial structure.

PNAS Nexus
Visva-Bharati University (IN), Ministry of Culture (IN), Anthropological Survey of India (IN), University of Jammu (IN), Charles University (CZ), Hazara University (PK), Bir Hospital (NP), Nicolaus Copernicus University (PL), Czech Academy of Sciences, Institute of Archaeology, Prague (CZ), Panjab University (IN)
Grantová Agentura České Republiky, Akademie Věd České Republiky
Gender equality
Openalex Percentile: Top 7%
Evolutionary Psychology and Human Behavior
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.