Forensic Research and Toxicology 2021 Presentation by Chandrakant M Kokatanur

Estimation of stature from
percutaneous length of radius
among the people belonging
to Gadag, Karnataka
Dr Chandrakant M Kokatanur
Professor
Department of FMT
Krishna Institute of Medical Sciences Karad.

INTRODUCTION
• Identification of an individual, living or dead is
important in forensic practice.
• It can be complete or partial.
• Complete identification
– all the information of a person is available.
8/24/2021 Dr CMK KIMS Karad 2

INTRODUCTION
Partial
Identification
Age Sex Race Stature

INTRODUCTION
Stature
Anatomical
methods
Mathematical
methods

INTRODUCTION
• Estimation of stature is important criteria in
identifying an individual .
• The regression equations and correlation
coefficients vary from one geographical
location to another as stature depends on
multiple factors such as race, nutritional,
regional and geographical factors.

INTRODUCTION
• Regression equations of one population are
not applicable to another population for
stature estimation as they are population
specific.

INTRODUCTION
• Stature is defined as “natural height of a
person in standing position”.
• It varies at different times of the day by one
and half centimeters. It is less in evening and
afternoon due to reduced elasticity of the
inter-vertebral disc and longitudinal vertebral
muscle.

INTRODUCTION
• Many studies have revealed the relationship
between stature and some parts of the
skeleton and the body parts in consideration.
• Radius bone is suitable for determination of
stature as it is convenient to measure
percutaneous length
• Considering this fact, the present study was
conducted to estimate stature from
percutaneous length of radius

OBJECTIVE
Estimation of stature from percutaneous
length of radius bone

MATERIALS & METHODS
• A cross sectional study
• Period of 3 months (Jun 2018 – Aug 2018)
• Inclusion criteria
– Subjects who born and brought up in Gadag
district of Karnataka
– Age between 21 to 60 years
– Both male and female

MATERIALS & METHODS
• Exclusion criteria
– Subjects with history of accident,
– head/spinal injury
– congenital deformity
– hormonal imbalance
– kyphosis
– scoliosis
– Dwarfism/gigantism
– Steroid therapy

MATERIALS & METHODS
• Sample size- The minimum number of subjects to
be included was calculated as follows
• n = [za+zb]2 + 3 where, c = 0.5ln[1+r]
c 1-r
• Hence, using r = 0.6(male) and 0.6(female), with
95% confidence and 95% power,
• n =30 for males and 30 for females.
• 100 males and 100 females were assessed in
present study.

MATERIALS & METHODS
• Informed consent
• The height of an individual was measured with
help of stadiometer as a distance between
vertex and standing platform. Subject will be
standing in anatomical position, with palm
facing medially and head in Frankfurt plane.

MATERIALS & METHODS
• All measurements were taken between 9am
to 11am by single observer to eliminate
diurnal as well as inter-observer variations.
• All measurements were taken in centimeters
up to two decimal points.
• The percutaneous length of radius was
measured using spreading calipers

Stature Percutaneous length of radius
MATERIALS & METHODS

MATERIALS & METHODS
• Statistical analysis-Data was collected in pre-
structured pro-forma, and analyzed using
descriptive statistics: correlation coefficient
was calculated.
• Regression equation was formulated to
estimate the stature, independent student’s t-
test to define significance by using software
Statistical Package for the Social Science
(SPSS) 20.

RESULTS
Frequency of males and females according to age.
Age
(years)
Male Female
Frequency Percent Frequency Percent
21-30 33 33 50 50
31-40 25 25 13 13
41-50 24 24 19 19
51-60 18 18 18 18
Total 100 100 100 100

RESULTS
Descriptive statistics for age, length of radius and stature.
Parameter
Male Females
Min Max
Mean± Std.
Deviation
Min Max
Mean± Std.
Deviation
Age (years) 22 60 39.03±11.078 25 60 37.30±11.908
Right
radius (cm)
21.90 26.60 23.657±1.008 19 23.80 21.205±1.190
Left radius
(cm)
21.90 26.50 23.635±1.0214 18.50 23.60 21.166±1.142
Stature (cm) 153 181 164.74±5.526 141 167 152.8±5.965

RESULTS
Regression equations for estimation of stature
Correlation
Coefficient
(r)
p value
(2-
tailed)
Regression Equation SEE
Male
0.85 0.01* Stature=54.576+4.657 x Length of right radius 2.930
0.836 0.01* Stature=57.830+4.523x Length of left radius 3.047
Female
0.673 0.01* Stature=81.320+3.371x Length of right radius 4.434
0.668 0.01* Stature=79.007+3.486x Length of left radius 4.463

DISCUSSION
• Identification of an individual is one of the important
aims in any medico-legal investigation. It becomes
extremely difficult when incomplete skeletal remains
or highly decomposed bodies are brought for
examination.
• In such situations, the main aim of the investigation is
to determine the stature, age, sex, and race.
• Estimation of stature from fragmented body remains is
of great importance in forensic investigation especially
when only long bones are available.
• For such estimation, the regression analysis is
considered as the most reliable and the best method

DISCUSSION
• Anthropometric characteristics have direct
relationship with gender, shape and form of an
individual and these factors are closely linked
with each other and manifestation of the internal
structure and tissue components which in turn
are governed by environmental and genetic
factors.
• It is a known fact that trunks and limbs exhibit
consistent ratios among themselves and are
relative to total height. The ratios are linked to
age, sex and race.

DISCUSSION
• The present study included 100 males and 100
females between 21 to 60 years from Gadag
district of Karnataka.
• The age restriction was made between 21 to
60 years as the ossification of radius is usually
complete by 20 years of age and after 60
years, there could be the possibility of
degenerative changes affecting stature.

DISCUSSION
• In the present study it was observed that
length of radius is more for males than
females.
• Similar observation was found in a studies
conducted by Borkar M in Maharashtra, Issa
SY, Mall G with mean length of radius 24.6 cm
in males and 22 cm in females.

DISCUSSION
• This could be due to effect of sex steroids on
bone growth and delayed entry of puberty by
males for about 2 years than females so that
males can acquire greater long bone length
before puberty

DISCUSSION
• Mean stature for males is more compared to
females because males are taller than
females.
• This could be due to association of Y
chromosome with stature and the age of
puberty being two years later in males, giving
extra time for growth.

DISCUSSION
• Similar findings were noticed in studies conducted by
Kanchankumar P Agnihotri AK,
• Borkar MP (173.8+8.80 cm for male and 157.6+7.98 cm
for females),
• Issa S Y (172.3 cm for males and 158.5 cm females),
• Mall G in Munich population (168cm for males and
156 cm for female),
• Dolan Champa Pal in Bengali population (164.2 ± 7.50
for males and 153.8 ± 6.79 for females)17,18
• Celbis O in Turkish population (169.9 cm for males and
156.8 cm for females)

DISCUSSION
• It is obvious from the present study that
length of radius is good parameter for
estimation of stature of a person in males [(r)
0.85] as well as females [(r) 0.673], as the
correlation coefficient (r) is considered to be
significant only above 0.5.
• correlation between stature and radius length
is stronger in males than in females

DISCUSSION
• Stature estimation in the present study was
determined by using the calculated regression
coefficient and constant values for each sex
from measured bone lengths.

DISCUSSION
• The standard error of estimate in the present
study is 2.93 to 3.04 for males and 4.43 to 4.46
for females.
• The regression equations when tested on 20
randomly selected males and females, estimated
stature values are in strong agreement with
directly measured stature with average error less
than 2cm.
• The equation derived from our study can safely
be used in Gadag population to predict stature
from percutaneous length of radius.

CONCLUSION
• There is a positive correlation between the
length of radius and stature.
• Race and gender specific regression equations
are needed for the accurate stature
reconstruction.
• The regression equations of present study can
be used upon the Gadag population,
Karnataka with fair degree of accuracy.

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• Kokatanur CM, Hallikeri VR, Manjulabai KH. Estimation of stature
from head length of adults belonging to Soligas-a genetically
isolated tribe from southern India. Indian J Forensic Med Toxicol
2018;12(2):48-53.
• Kokatanur CM, Hallikeri VR, Manjulabai KH. Estimation of stature
from the inter-acromial length of adults belonging to the Soliga-a
genetically isolated tribe from southern India. Medico-Legal Update
2017;17(2):64-9.
• Mishra KD, Kokatanur CM. Estimation of stature from Bi-mastoid
breadth. J Indian Acad Forensic Med. 2020 Apr-Jun; 42(2): 84-8.
• Kokatanur CM, Patil, AV, Bannur, V, Mishra KD. Estimation of
stature from head length in medical students. Indian J Forensic Med
Toxicol 2020 Oct;14(4):108-14.
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THANK YOU

T
H
A
N
K
Y
O
U
Dr CMK KIMS Karad
8/24/2021

Forensic Research and Toxicology 2021 Presentation by Chandrakant M Kokatanur

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