The role of political, economic, and biocultural processes in producing sexual dimorphism and health disparities in recent human populations Ashley C. Dafoe 1 , Mary C. McAlpine 1 , and Molly K. Zuckerman 1 1 Department of Anthropology and Middle Eastern Cultures, Mississippi State University Introduction Sexual dimorphism (SD) in Holocene human populations is often attributed to sexual selection pressures, with an emphasis on male-male competition and male dominance ( 1) and to differential access to resources and exposure to stressors related to gender inequality (2-4). But biological and cultural factors often work synergistically, either amplifying or reducing SD (5, 6). Skeletally, phenotypic SD is typically assessed via non-metric and metric traits, such as stature and robusticity, often to enable sex estimation (7). Here, we employ an expanded range of phenotypic variables that can exhibit SD (see Methods). We also propose a set of parameters that could be used to both identify and potentially disentangle the contributions of sex and gender to SD in past populations based on a set of skeletally identifiable, population- level variables. Sex and gender exhibit intersectionality with other aspects of identity in shaping phenotypes (8, 9), but for the scope of this work, we analytically prioritize sex and gender. Here, sex is defined as the skeletally identifiable biological state of being male, female, or intersex, as produced by sex chromosomes; gender is the culturally contingent range of biological, physical, behavioral, and psychological characteristics associated with a given sex. Methods We conducted a review of papers (N=46) published from the past c. 25 years in peer reviewed academic journals and edited volumes which document disparities in phenotypic traits between males and females, men and women, and boys and girls due to biological difference and/or social inequalities in both modern and past populations. Using these papers, seven population-level variables were established; mortality (age at death); susceptibility to morbidity and mortality (frailty); trauma (fracture); stature; diet ( δ 15 N evidence of protein consumption); disease frequency; and pubertal timing (pubertal growth spurt, menarche). The cumulative results of are summarized in Table 1. Discussion & Conclusion The parameters (column A & B) attempt to incorporate both sex and gender as socially constructed, and temporally and culturally contingent. They should only be applied cautiously and when some degree of contextual data (i.e. historical, ethnographic, archaeological) on sex, gender, sexuality, and other intersectional aspects of identity are available. These parameters should only be applied to past populations when all statistical biases (e.g., sample size, preservation, underlying sub-groups) that may explain different patterns in these parameters have been explored. Among others, the following criteria should guide the application of these parameters to data sets generated from skeletal assemblages: • Population-specific stature calculations must be employed (3, 29) • Age-adjusted frailty estimations (31) • Recognition that the variables ‘gender’ and ‘sex’ intersect with other aspects of social identity (e.g., social race, socio- economic status) in producing phenotypic traits. • Acknowledgement that biological ‘norms’ (i.e. pubertal timing, stature) are population-specific. Overall, rapid shifts in the frequency, severity, or demographic distribution of these parameters through time (e.g., within a generation) are likely attributable to social and/or environmental factors, as biological mechanisms are unlikely change this rapidly (2). Future work should explore the applications of BMI estimation within these parameters in terms of stunting, wasting, and fracture (15, 32-35) as well as skeletal asymmetry as an indicator of gen- dered divisions of labor. Often, the influences of biological sex and gender on the pheno- type cannot be analytically disentangled. But, as these parameters indicate, supported by the reviewed works (3, 11), it is possible to do so for some other traits, in some conditions. By using these parame- ters to interpret skeletal data, we anticipate that scholars may be able to more regularly identify SD and interpret sex and gender based contributions to patterns of SD in the past. References 1. S. B. Hrdy, The woman that never evolved. (Cambridge, Mass. : Harvard University Press, 1981., 1981). 2. R. M. Griffin, A. D. Hayward, E. Bolund, A. A. Maklakov, V. Lummaa, Sex differences in adult mortality rate mediated by early‐life environmental conditions. Ecology Letters 21, 235-242 (2018). 3. S. N. Dewitte, Stress, sex, and plague: Patterns of developmental stress and survival in pre- and post-Black Death London. American Journal of Human Biology, (2017). 4. J. Lukacs, Fertility and Agriculture Accentuate Sex Differences in Dental Caries Rates. Current Anthropology 49, 901-914 (2008). 5. A. A. Macintosh, R. Pinhasi, J. T. Stock, Early Life Conditions and Physiological Stress following the Transition to Farming in Central/Southeast Europe: Skeletal Growth Impair- ment and 6000 Years of Gradual Recovery. PLoS ONE 11, 1-27 (2016). 6. T. B. Herbert, S. Cohen, Stress and immunity in humans: A meta-analytic review. Psychosomatic Medicine 55, 364-379 (1993). 7. K. Krishan et al., A review of sex estimation techniques during examination of skeletal remains in forensic anthropology casework. Forensic Science International 261, (2016). 8. R. L. Gowland, Entangled lives: Implications of the developmental origins of health and disease hypothesis for bioarchaeology and the life course. American Journal of Physical Anthropology 158, 530-540 (2015). 9. H. D. Klaus, Frontiers in the bioarchaeology of stress and disease: Cross-disciplinary perspectives from pathophysiology, human biology, and epidemiology. American Journal of Physical Anthropology 155, 294-308 (2014). 10. J. n. G. Read, B. K. Gorman, Gender and Health Inequality. Annual Review of Sociology 36, 371-386 (2010). 11. M. Fields, R. P. Harrod, D. L. Martin. (ScholarWorks@UMass Amherst, 2010-10-01T07:00:00Z., 2010). 12. S. Eyigor et al., Frailty prevalence and related factors in the older adult—FrailTURK Project. Age 37, 1-13 (2015). 13. D. Guatelli-Steinberg, J. R. Lukacs, Interpreting sex differences in enamel hypoplasia in human and non-human primates: Developmental, environmental, and cultural considera- tions. Yearbook of Physical Anthropology, 73-126 (1999). 14. M. Pietrusewsky, M. T. Douglas, M. K. Swift, R. A. Harper, M. A. Fleming, Sex and Geographic Differences in Health of the Early Inhabitants of the Mariana Islands. 28 (2016). 15. M. Nasiri, Y. Luo, Study of sex differences in the association between hip fracture risk and body parameters by DXA-based biomechanical modeling. Bone 90, 90-98 (2016). 16. T. J. Beck et al., SEX DIFFERENCES IN GEOMETRY OF THE FEMORAL NECK WITH AGING A STRUCTURAL ANALYSIS OF BONE MINERAL DATA. Calcified Tissue Inter- national 50, 24-29 (1992). 17. J. Nielsen, Does human sexual dimorphism influence fracture frequency, types and distribution? Anthropological Review 74, 13-23 (2011). 18. R. Sonti et al., Men with celiac disease are shorter than their peers in the general population. European Journal of Gastroenterology & Hepatology 25, 1033-1037. 19. S. Kanazawa, D. L. Novak. (BIOSOCIAL SOC - CAMBRIDGE, Great Britain, 2005), pp. 657. 20. S. H. Ambrose, J. Buikstra, H. W. Krueger, Status and gender differences in diet at Mound 72, Cahokia, revealed by isotopic analysis of bone. Journal of Anthropological Archae- ology 22, 217-226 (2003). 21. J. R. Lukacs, Bioarchaeology of oral health: Sex and gender differences in dental disease. (The University of New Mexico Press, 2017), pp. 263-290. 22. C. Iezzi, Regional Differences in the Health Status of the Mycenaean Women of East Lokris. Hesperia Supplements 43, 175-192 (2009). 23. C. Giefing-Kröll, P. Berger, G. Lepperdinger, B. Grubeck-Loebenstein, How sex and age affect immune responses, susceptibility to infections, and response to vaccination. Aging Cell 14, 309-321 (2015). 24. D. E. Michael, S. K. Manolis, C. Eliopoulos, Exploring sex differences in diets and activity patterns through dental and skeletal studies in populations from ancient Corinth, Greece. HOMO- Journal of Comparative Human Biology 68, 378-392 (2017). 25. J. Delanghe, R. , M. L. De Buyzere, M. M. Speeckaert, M. R. Langlois, Genetic Aspects of Scurvy and the European Famine of 1845–1848. Nutrients, Vol 5, Iss 9, Pp 3582-3588 (2013), 3582 (2013). 26. A. S. Parent et al. (ENDOCRINE SOCIETY, United States, 2003), pp. 668. 27. C. Wohlfahrt-Veje et al., Pubertal onset in boys and girls is influenced by pubertal timing of both parents. Journal of Clinical Endocrinology and Metabolism 101, 2667-2674 (2016). 28. C. Buzney, J. DeCaro, Explanatory Models of Female Pubertal Timing: Discordances Between Cultural Models of Maturation and the Recollection and Interpretation of Personal Developmental Experiences. Culture, Medicine & Psychiatry 36, 601-620 (2012). 29. A. A. Macintosh, R. Pinhasi, J. T. Stock, Divergence in male and female manipulative behaviors with the intensification of metallurgy in Central Europe. PLoS One 2014, (2014). 30. S. H. Hogue, V. Dongarra, BIOMECHANICAL CHANGES IN LONG BONE STRUCTURE: A STUDY OF PREAGRICULTURAL AND AGRICULTURAL POPULATIONS IN NORTHEASTERN MISSISSIPPI AND NORTHWESTERN ALABAMA. Midcontinental Journal of Archaeology (Rowman & Littlefield Publishers, Inc.) 27, 69-88 (2002). 31. K. E. Marklein, R. E. Leahy, D. E. Crews, In sickness and in death: Assessing frailty in human skeletal remains. American Journal of Physical Anthropology 161, 208-225 (2016). 32. C. B. Ruff et al. (John Wiley & Sons, Ltd, United States, 2012), pp. 601. 33. J. Sadvari et al., Bioarchaeology of Neolithic Catalhoyuk: Lives and Lifestyles of an Early Farming Society in Transition. Journal of World Prehistory 28, 27-68 (2015). 34. K. Sorensen, L. Aksglaede, J. H. Petersen, A. Juul, Recent Changes in Pubertal Timing in Healthy Danish Boys: Associations with Body Mass Index. Journal of Clinical Endocri- nology & Metabolism 95, 263-270 (2010). 35. T. Ong, O. Sahota, W. Tan, L. Marshall, A United Kingdom perspective on the relationship between body mass index (BMI) and bone health: a cross sectional analysis of data from the Nottingham Fracture Liaison Service. Bone 59, 207-210 (2014). 36. D. Khan, S. A. Ahmed, The Immune System is a natural target for Estrogen action: Opposing effects of Estrogen in two prototypical Autoimmune Diseases. Frontiers in Immunol- ogy, Vol 6 (2016), (2016). 37. J. Geber, E. Murphy, Scurvy in the great irish famine: Evidence of vitamin C deficiency from a mid-19th century skeletal population. American Journal of Physical Anthropology 148, 512-524 (2012). 38. V. S. Sparacello, G. Vercellotti, V. d'Ercole, A. Coppa, Social reorganization and biological change: An examination of stature variation among Iron Age Samnites from Abruzzo, central Italy. International Journal of Paleopathology 18, 9-20 (2017). 39. M. R. G. Araneta, D. Von Mühlen, E. Barrett-Connor, Sex differences in the association between adiponectin and BMD, bone loss, and fractures: The rancho bernardo study. Journal of Bone and Mineral Research 24, 2016-2022 (2009). 40. R. J. Gilmour et al., Gendered Differences in Accidental Trauma to Upper and Lower Limb Bones at Aquincum, Roman Hungary. International Journal of Paleopathology 11, 75- 91 (2015). 41. S. C. Agarwal, J. K. Wesp, 7. Understanding Sex- and Gender-Related Patterns of Bone Loss and Health in the Past: A Case Study from the Neolithic Community of Çatalhöyk. (University of New Mexico Press, Albuquerque, 2017), pp. 165. 42. K. J. Jepsen, E. M. R. Bigelow, S. H. Schlecht, Women Build Long Bones With Less Cortical Mass Relative to Body Size and Bone Size Compared With Men. Clinical Orthopae- dics and Related Research 473, 2530-2539 (2015). 43. J. F. Guegan, A. T. Teriokhin, F. Thomas, Human Fertility Variation, Size-Related Obstetrical Performance and the Evolution of Sexual Stature Dimorphism. Proceedings: Biolog- ical Sciences, 2529 (2000). 44. N. Tsugawa et al., Association between vitamin D status and serum parathyroid hormone concentration and calcaneal stiffness in Japanese adolescents: sex differences in sus- ceptibility to vitamin D deficiency. Journal of Bone and Mineral Metabolism 34, 464-474 (2016). 45. S. N. Pei et al., TMPRSS6 rs855791 polymorphism influences the susceptibility to iron deficiency anemia in women at reproductive age. International Journal of Medical Sciences 11, 614-619 (2014). 46. J. Belsky et al., Family Rearing Antecedents of Pubertal Timing. Child Development, 1302 (2007). Figures 47. C. L. Bekvalac J., Mikulski R., Kausmally T., MIN86_6674_1.jpg, Ed. (Museum of London: Wellcome Osteological Research Database, 1986). 48. B. J., BA84_2876_22.jpg, Ed. (Museum of London: Wellcome Osteological Research Database, 1984). 49. C. L. Bekvalac J., Kausmally T., Mikulski R. , PIC87_243_1.jpg, Ed. (Museum of London: Wellcome Osteological Research Database, 1987). 50. L. C. J. Bekvalac, ONE94_672_1.jpg, Ed. (Museum of London: Wellcome Osteological Research Database, 1994). Results Table 1 presents generalized parameters representing patterns that, if detected in a given skeletal assemblage, may be attributable more to the influences of biological sex or more to the influences of gender roles, including differential access to nutrients, occupational differences, differential societal and biological demands (i.e. reproductive). For each population-level variable, differences in observed patterns of phenotypic traits (e.g. fractures, caries) potentially attributable to sex related conditions and characteristics are in column A; those potentially attributable to gender related conditions are in column B. For brevity, a two-sex, two-gender model is employed here but detected patterns —and the parameters – could be spread across multiple nodes for sex and gender (i.e. intersex, third gender). See the Footnotes for the supporting evidence for each of these variable-specific parameters. Variable A. Pattern potentially attributable to biologically-based sex characteristics B. Pattern potentially indicative of gender- based social inequality Mortality 1 Female life expectancy > male life expectancy (2) Male life expectancy > female life expectancy indicates prejudice against women/girls (10) Female death rate > male death rate during reproductive years (15-44 yrs) (11) Male death rate > female death rate during female reproductive years (15-44 yrs) indicates prejudice against men/boys (11) Frailty 2 Females are likely to meet more categorical qualifications of frailty (e.g., a higher biomarker-based skeletal frailty index score (SFI)), but are less likely to have high mortality rates (12) Female frailty indicators AND mortality rates surpass male rates indicates prejudice against women/girls (12) Males and females manifest equivalent frequencies of LEH (13, 14) Males and females do not manifest equivalent frequencies of LEH (e.g., female frequencies elevated) (13, 14) Trauma 3 Frequencies of fractures (not including those inflicted by interpersonal violence) are positively correlated with age in females; frequencies of fractures are inversely correlated with age in males (i.e. higher in sub-adults & early adults) (15, 16) Male fracture rates > female fracture rates indicates prejudice against men/boys (e.g., prejudice related to heavier/riskier labor practices) ( 17) Stature 4 Stunting in males > stunting in females (3, 18) Stunting in females > stunting in males indicates prejudice against women/girls (19) Diet 5 Males and females have equivalently enriched δ 15 N signatures (20) Either males of females have greater δ 15 N signatures than the other, indicating differential availability of dietary protein (20) Males and females have equivalent δ 13 C and δ 14 C signatures (20) One sex has greater δ 13 C and δ 14 C signatures than the other, indicating differential availability of dietary vegetation (20) Males and females have equivalent rates of dental attrition (attributable to diet) (21) Males and females have non-equivalent rates of dental attrition (attributable to diet) (21) Disease 6 Females have elevated rates of caries relative to males due to biological predisposition (21) Prejudice against men/boys indicated by elevated rates of caries relative to females (22) Females have elevated rates of antemortem tooth loss caused by carries relative to males (21) Prejudice against men/boys indicated by elevated rates of antemortem tooth loss males relative to females (21) Age-adjusted, older adult males and females (≤45 years) have equalized disease susceptibility (23) Age-adjusted, older adult males and females (≤45 years) have non-equivalent disease susceptibility (23) Females have elevated rates of anemia (e.g., porotic hyperostosis) relative to males (22) Prejudice against men/boys indicated by elevated rates of porotic hyperostosis in males relative to females (22) Females have higher rates of osteoarthritis than males (24) Higher rates of osteoarthritis in males indicates prejudice against men/boys (24) In some populations, males may have higher frequencies of Vitamin C deficiency (i.e. scorbutic lesions) than may females (25) In some populations, females may have higher frequencies of Vitamin C deficiency (i.e. scorbutic lesions) than males ( 25) Pubertal Timing 7 Pubertal timing is population specific, varying up to 6 years between populations (26). However, universally, if a parent began puberty early, it is more likely that their offspring will have earlier puberty (27) Females manifest much younger age at puberty than do males (28) Footnotes 1 Mortality: Because of differential selective pressure (2) and estrogen buffering (36) female life expectancy should surpass male life expectancy. During reproductive years (ages 15-44), female mortality may surpass male mortality due to the high demands of pregnancy and associated immunosuppression ( 4, 37). Gender inequality is indicated when female life expectancy is lower than male expectancy when females have higher death rates than males during reproductive years. 2 Frailty: While females are generally more frail due to a higher allostatic load, high frailty is less likely to lead to premature death given that the female body is better evolved to cope with long- term stress (12). Low female survivorship on a population level likely results from gender based inequality ( 12, 31, 38). Neither sex is biologically more susceptible to LEH despite female hormones and longer enamel development in males ( 13, 14). 3 Trauma: Females have greater susceptibility to fracture (Figure 1), particularly in the femoral neck, due to decreased bone mineral density (15, 16), muscle mass, and cortical bone thickness as well as limited functionality of adiponectin and loss of balance later in life (16, 39-42). Higher fracture frequency in males indicates differential social activity, (ex. occupational hazards, or societal buffering of females ) (17). 4 Stature: Male stature is more sensitive to stressors, both environmental and societal (43). Sexual dimorphism is lessened in well-nourished populations as male height decreases more significantly than female height. If female height decreases while male height does not, gender inequality is likely buffering males. 5 Diet: Dietary studies using isotopes or dental wear patterns are uniquely suited to eliminate variables of biological difference, as both males and females fractionate isotopes in the same ratios and have comparable enamel strength (21). Female bone health may be more reactive to vitamin D deficiency ( 44) and females may have high variability in susceptibility to iron anemia based on genetic factors (45). 6 Disease: While higher rates of caries and antemortem tooth loss (see Figure 2) in females is not universal (9), females are more susceptible to these pathologies due to decreased saliva pro-duction, reduced microbial function of saliva, immunosuppression during pregnancy, and higher levels of estrogen (21). Higher levels of estrogen in females regulate the immune system, generally increasing female immunity and immune system responses, but also correlates to higher rates of autoimmune diseases (36). With age, immune system suppression by testosterone decreases and female estrogen protection drops after menopause, decreasing immune protection. Therefore, in older age cohorts, disease susceptibility will equalize between the sexes (23). Females are also more susceptible to anemia, related to menstruation, and osteoporosis (Figures 3 & 4). 7 Pubertal Timing: Early onset puberty has known associations with high parental/societal control, environmental stressors, and parental age at puberty (19, 27, 46). These stressors tend to have a greater impact on female pubertal timing (28). Social inequality may be indicated by significantly reduced stature in females due to early onset puberty. Figure 3: Roof of left orbital showing evidence of cribra orbitalia. From the Dominican Friary Carter Lane Cemetery (49). Figure 4: Exterior surface of the parietal bones. Ectocranial evi- dence of porotic hyperostosis. From the St. Benet Sherehog Cemetery (50). Figure 2: Antemortem loss in the mandible from the Bermondsey Abbey Cemetery (48). Figure1: Healed fractures of the right tibia and distal fibula from the East Smithfield Black Death Cemetery (47). Table 1: See the Footnotes for the supporting evidence for each of these variable-specific parameters.