Humans are sexually dimorphic, but not to the extreme that is seen in some other primates. In most populations, differences between males and females exist in several physical traits and may emerge prominently after puberty, though the extent varies by trait and population. Key points
- General concept: Sexual dimorphism refers to consistent differences between the sexes in morphology or physiology beyond the reproductive organs. In humans, this includes stature, body composition, and certain facial and skeletal features, among others.
- Typical dimorphic traits in humans:
- Body size and composition: On average, men are taller and have higher lean mass and bone density, while women tend to have higher body fat percentage and different fat distribution patterns.
* Skeletal and muscular traits: Differences in limb proportions, muscle distribution, and musculature are common, with men often exhibiting greater absolute muscle mass and strength on average.
* Craniofacial and vocal traits: Some studies show measurable differences in facial structure and voice pitch, influenced by hormonal factors during development and puberty.
* Other traits: Some research highlights differences in hormonal profiles, reproductive anatomy, and certain secondary sexual characteristics, though these are highly variable and influenced by environment and genetics.
- Variation across populations: The degree and direction of dimorphism can differ among populations and individuals; some traits show more pronounced differences in certain groups, while others may be very similar.
- Evolutionary perspective: In humans, sexual dimorphism is relatively moderate compared with species with strong mating competition, such as some primates. Values often cited place average male–female size differences around the low teens to mid-teens in terms of overall body size, though this can vary by metric.
If you’d like, I can tailor a concise summary focused on a specific trait (e.g., height, muscle mass, facial structure) or on how modern lifestyle and health factors influence observed differences.
