Estimating the post-mortem interval using accumulated degree-days in a South African setting

Abstract

Providing a presumptive identification of badly decomposed or skeletonized remains is the responsibility of a forensic anthropologist. An important component of identification is the estimation of a post-mortem interval (PMI) for the deceased. This information can: provide a window period for death, reduce the number of potential victims, exclude possible assailants and substantiate witness testimony. Due to a large number of open and relatively desolate fields in South Africa, human remains are frequently discovered in an advanced stage of decomposition. The aim of this study was to evaluate the usability of the method of Megyesi and associates (2005) in which Total Body Score (TBS) and Accumulated Degree-Days (ADD) were retrospectively applied to estimate the post-mortem interval (PMI). To achieve this, a longitudinal examination of quantitative variables, TBS and ADD, was conducted over a period of 8 months. This period included both summer and winter seasons. Scatter plots between TBS and PMI, and TBS and ADD were used to illustrate patterns in decomposition. Patterns of decay differed in winter and summer, with winter exhibiting distinct inactivity. Using Loglinear Random-effects Maximum Likelihood Regression, the r2 values for ADD (0.6227) and PMI (0.5503) for combined seasons were less than r2 values for separated seasons (ADD 0.7652; PMI 0.7677). In contrast to other studies, seasonality influenced the ADD model and PMI. Linear regression formulae for ADD and PMI as well as 95% confidence interval charts for TBS for ADD were developed. These equations, along with data from a local weather station, can be used to estimate the PMI with relative accuracy. AFRIKAANS : Verskaffing van 'n vermoedelike identifikasie van erg ontbinde of skeletale oorskot is die verantwoordelikheid van ‘n forensiese antropoloog. ‘n Belangrike deel van identifikasie is die beraming van ‘n post-mortem interval (PMI) vir die oorledene. Hierdie inligting verskaf 'n venster tydperk van dood, verminder die aantal potensiële slagoffers, sluit moontlike aanvallers uit en ondersteun getuienis. As gevolg van 'n groot aantal relatief verlate en oop velde in Suid-Afrika, word menslike oorskot dikwels aangetref in ‘n gevorderde stadium van ontbinding. Die doel van hierdie studie was om die bruikbaarheid van die metode van Megyesi en medewerkers (2005) wat gebruik maak van Totale Liggaams Telling (TLT) en Opgehoopte Graad-Dae (OGD) om die postmortem interval (PMI) te skat, terugwerkend te evalueer. Hiervoor was 'n longitudinale studie van kwantitatiewe veranderlikes, TBS en ADD, oor ‘n tydperk van 8 maande gedoen. Hierdie tydperk sluit beide somer en winter in. Verspreidingsgrafieke tussen TBS en PMI, en TBS en ADD is gebruik om patrone in ontbinding te illustreer. Ontbindingspatrone het verskil tussen winter en somer met duidelike onaktiwiteit in die winter. Logliniêre Tweekansige-effek Maksimum Waarskynlikheid Regressie was gebruik om die r2 waardes van die gekombineerde en geskeide seisoene te bepaal. The r2 waardes vir die OGD (0.6227) en PMI (0.5503) vir gekombineer seisoene was minder as die r2 waardes vir seisoene apart (OGD 0.7652; PMI 0.7677). In teenstelling met ander studies, het seisoenaliteit die OGD model en PMI beinvloed. Lineêre regressie formules vir OGD en PMI sowel as 95% vertrouensinterval kaarte vir TLT vir OGD was saamgestel. Hierdie formules saam met data vanaf ‘n plaaslike weerstasie kan gebruik word om die PMI met relatiewe akkuraatheid te skat.