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Estimating the date of bone remains: a multivariate study.

M A Castellano, E C Villanueva, R von Frenckel

    Journal of Forensic Sciences
    |April 1, 1984
    PubMed
    Summary
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    Forensic scientists can estimate bone age using biochemical markers like proteins, triglycerides, and cholesterol. Statistical formulas derived from these elements improve the accuracy of determining the time since death.

    Area of Science:

    • Forensic Science
    • Biochemistry
    • Anthropology

    Background:

    • Previous research identified various biochemical markers in bone residuals for estimating time since death.
    • These markers include total lipids, triglycerides, cholesterol, and proteins, among others.
    • Bones from different postmortem intervals (1-20 years) were previously analyzed.

    Purpose of the Study:

    • To statistically analyze previously collected bone biochemical data.
    • To develop predictive formulas for estimating the time since death using key biochemical parameters.
    • To assess the improvement in correlation by using logarithmic transformations of variables.

    Main Methods:

    • Stepwise regression analysis was employed to identify the most significant predictors of time since death.

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  • The analysis iteratively selected variables based on their correlation with postmortem interval.
  • Three predictive formulas were developed using combinations of proteins, triglycerides, and cholesterol.

    • Main Results:

    • Three distinct formulas were established to estimate the time of death (Y) based on biochemical markers.
    • Formula 1: Y = 40.0014 - 7.4275(Protein)
    • Formula 2: Y = 45.5970 - 10.8096(Protein) + 0.4104(Triglycerides)
    • Formula 3: Y = 52.2032 - 7.8213(Protein) + 0.6355(Triglycerides) - 3.4930(Cholesterol)
    • Logarithmic transformation of variables significantly improved the correlation coefficients in all formulas.

    Conclusions:

    • Biochemical analysis of bone residuals, particularly proteins, triglycerides, and cholesterol, provides a viable method for estimating time since death.
    • Stepwise regression effectively identifies key biochemical markers for developing predictive models.
    • Utilizing logarithmic transformations of these biochemical markers enhances the accuracy of postmortem interval estimation.