1.Post mortem changes in relation to different types of clothing
Chee HauTeo ; Sri Pawita Amir Hamzah ; Khairul Osman ; Atiah Ayunni Abdul Ghani ; Noor Hazfalinda Hamzah
The Malaysian Journal of Pathology 2013;35(1):77-85
Post mortem changes are important in estimating post mortem interval (PMI). This project’s aim
was to study the effect of burial and type of clothing on rate of decomposition, which can contribute
to estimating PMI for victims. 12 rabbits (Oryctolagus cuniculus) carcasses were separated into
3 groups: no clothing, light clothing and heavy clothing. Control subjects were placed on the
ground surface while test subjects were buried at 30 cm depth graves. Soil samples prior and after
decomposition were collected for soil pH and moisture analysis. Post mortem change was assessed
using a Total Body Score system. The head, neck and limb regions were found to decay faster than
the body trunk region. Mummifi cation occurred on body parts that were exposed directly to the
atmosphere while adipocere formed on some buried subjects. Burial delayed decomposition due
to lower insect activity and lower soil temperature. The soil layer also blocked the accessibility of
majority of the arthropods, causing further delay in decomposition. Clothing enhanced decay for
bodies on ground surface because it provided protection for maggots and retained moisture on tissues.
However, clothing delayed decomposition in buried bodies because it physically separated the bodies
from soil and arthropods. Higher sun exposure and repetitive exhumation showed acceleration of
decomposition. The decomposition process increased soil pH and moisture percentage values. Soil
pH initially increased until pH 8.0-8.4 followed by a slight decrease while soil moisture percentage
changed inconsistently. Burial was signifi cant in affecting post mortem change, F(1,11)=12.991,
p<0.05 while type of clothing was not signifi cant, F(2,9)=0.022, p=0.978 and combination of both
type of clothing and burial factors were also not signifi cant, F(2,3)=0.429, p=0.686. For validation,
an accuracy of 83.33% was achieved based on soil pH and soil moisture percentage analysis.