ISSN: 2074-8132
Recieved: 06/21/2025
Accepted: 08/11/2025
Published: 11/18/2025
Keywords: paleopathology; bioarchaeology; metabolic disease; vitamin C and D deficiency; classification trees; Bronze Age; Southern Urals
Available online: 18.11.2025
Kufterin Vladimir V., Karapetian Marina K. Paleopathological diagnosis of non-adult scurvy and rickets using decision tree analysis. // Lomonosov Journal of Anthropology 2025. Issue 4. 108-124 https://doi.org/10.55959/MSU2074-8132-25-4-9.
Introduction. This publication has a twofold aim: (1) to present a probable case of a metabolic disease in a Late Bronze Age child skeleton from the Southern Trans-Urals, and (2) to examine the diagnostic potential of classification tree algorithms for differentiating infantile scurvy and rickets in osteological material.
Materials and methods. The skeleton of a 4–8-month-old child with pathological changes was found in Kurgan 1 of the Nepluyevsky cemetery, attributed to the Srubnaya-Alakul cultural type. The observed pathological changes are consistent with rickets and/or scurvy. Differential diagnosis between these two conditions was performed using classification tree analysis (Statistica 12.0 package), based on 13 parameters and a dataset of 110 paleopathological cases of metabolic disorders (72 cases of rickets and 38 of scurvy). Two classification models were constructed using CHAID algorithm, each employing a different approach to handling missing data. Accuracy, sensitivity, specificity, and positive likelihood ratio were calculated to assess classification quality. In addition, correlation coefficients were computed for all input variables.
Results and discussion. The combination of macroscopic and radiographic features indicates that the child was suffering from a metabolic disorder, most consistent with rickets. The obtained decision trees demonstrate high classification accuracy (93.6%) and a high positive likelihood ratio.
Conclusion. The child from Kurgan 1 represents one of the earliest and the first reliably documented paleopathological case of rickets from the study region. The resulting decision trees show that rickets and scurvy can be differentiated using three features: long-bone deformity and general thickening, and abnormalities on bone underlying growth plates.
Acknowledgements. The article has been written in accordance with the research plans of the N.N. Miklukho-Maklai Institute of Ethnology and Anthropology RAS (Theme No. 5. Human ultrasociality: Biosocial and cross-cultural aspects – R & D No. 124112200079-1) (V.V. Kufterin). The study was conducted under the state assignment of Lomonosov Moscow State University (M.K. Karapetian).
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