Colleen M. Cheverko

Sufficient evidence supports arguments that early life conditions can influence adult morbidity and mortality in the past and present. Critical periods in which individuals are more susceptible to stressors leading to long‐term effects vary, but how often and to what degree these long‐term effects occur is less certain. To evaluate skeletal stress markers that fully develop during different life history stages (i.e., childhood and adolescence) and explore their influence on adult morbidity and mortality, we constructed four growth trajectory categories to estimate the effect of developmental timing of stress indicators on adult mortality risk in skeletal samples from post‐medieval London ( n = 118 individuals). To construct these growth trajectory categories, linear enamel hypoplasia and tibial length were used as evidence of early life stress during childhood and extended into adolescence. Pairwise relationships between growth trajectory scores and variables such as age, sex, and cemetery were explored using Chi‐square and Fisher's exact tests. Long‐term effects were also evaluated using Factorial ANOVA as a multifactorial method to test correlations between categorical variables of early life stress and adult mortality risk. Results suggest there was no relationship between age‐at‐death and growth trajectory score, with the only significance in growth disruption score being between tibial stunting and age‐at‐death in males. Socioeconomic status did not impact results of this study, with only two statistically significant relationships noted for one cemetery. Results comparing males and females also yielded no significant differences, indicating sex was not a significant covariate. Overall, this paper presents a model that can help investigate differences between various developmental origins frameworks and be built upon by future researchers using different stress indicators, datasets, and skeletal samples to investigate potential change through time in lived experiences and how that change through time impacts patterns of mortality risk.