scholarly journals Sex estimation using foot measurements, stature and body mass index (BMI) in a Nigerian population

2018 ◽  
Vol 5 (2) ◽  
pp. 32-37 ◽  
Author(s):  
Iroanya Onyekachi Ogbonnaya ◽  
Egwuatu Tochukwu Frank ◽  
Sonaike Adeola Olasubomi ◽  
Uwaezuoke Nduka David
Keyword(s):  
Multiple Regression ◽  
Pearson Correlation ◽  
Regression Equation ◽  
Multiple Regression Equation ◽  
Sex Estimation ◽  
Linear Regression Equation ◽  
Foot Length ◽  
Sex Limitation ◽  
Nigerian Population ◽  
Better Than

Abstract Identification of dismembered bodies recovered in disasters or crime scene is very important in forensic. This study was carried out to ascertain if foot size, body weight, height, stature and BMI can be used to predict sex using tape rule and Stadiometer scale. 150 subjects between 18 - 25yrs were recruited. Independent T-test, Pearson Correlation, Linear and Multiple Regression Analysis were determined using SPSS version 23. All measurements were higher in male than female and there was significant (p≤0.05) difference in the sex. The average foot length of 257.39mm was used to determine sex of the subjects. All foot lengths ≤ 257.39mm were presumed to belong to females while all values > 257.39mm was presumed males. Foot size and weight had the highest correlation values. Foot length gave better estimation of sex than foot breadth, BMI and weight. Results of Multiple regression equation was better than linear regression equation. In forensic anthropology, foot size has been used to predict sex. Limitation of this study is the formulae generated can only be applied to Nigerians aged 18-25 yrs. Studies should be carried out on diverse population for future inferences

scholarly journals Prediksi Tinggi Badan Ditentukan dari Panjang Rentang Lengan dan Panjang Telapak Kaki Pada Mongoloid Feminina Khususnya Etnis Jawa

2018 ◽  
Vol 2 (2) ◽  
Author(s):  
Nur Mujaddidah Mochtar
Keyword(s):  
Clinical Medicine ◽  
Pearson Correlation ◽  
Body Height ◽  
Regression Equation ◽  
The Body ◽  
Regression Equations ◽  
Foot Length ◽  
Arm Span ◽  
Knee Height ◽  
The Mean

Background: There are various circumstances where measurements are not actually possible, replacement parameters can be used to estimate body height. Many characteristics of body height measurement and how to measure it. These include anthropometric measurements that can be used for the identification of medicolegal-forensic processes. Body height in clinical medicine and in the field of scientific research can be easily estimated using various anthropometric parameters such as arm span, knee height, foot length and foot breadth, and others. The arm span and foot length has proved to be one of the most reliable predictors. This study was conducted to estimate of body height from arm span and foot length using the regression equation and to determine the correlation between the body height and arm span and foot length.Methods: This study was conducted at Universitas Muhammadiyah Surabaya with 182 Javanese female students. Stature, arm span and foot length measured directly using anthropometric technique and measuring tape. The data obtained were then analyzed with SPSS version 16. The regression equation was derived for the estimate of body height and the relationship between stature, arm span and foot length determined by the Pearson correlation.               Results: We found that the mean body height of Javanese women was 1534,45 ± 47,623  mm, mean of arm span 1543,25 ± 60,468 mm and the mean of foot length 226,14 ± 9,586 mm. The correlation between stature and arm span was positive and significant (r = 0,715  , p <0,05). The correlation between stature and foot length was positive and significant (r = 0,726 , p <0,05). The correlation between stature and arm span and foot length was positive and significant (r = 0,798, p <0,05).               Conclusion: Body height correlates well with the arm span and foot length so that it can be used as a reliable marker for high estimates using regression equations.

scholarly journals Correlation of 3-Dimensional Shoulder Kinematics to Function in Subjects With Idiopathic Loss of Shoulder Range of Motion

2005 ◽  
Vol 85 (7) ◽  
pp. 636-647 ◽  
Author(s):  
Peter J Rundquist ◽  
Paula M Ludewig
Keyword(s):  
Range Of Motion ◽  
Multiple Regression ◽  
External Rotation ◽  
Regression Equation ◽  
Multiple Regression Equation ◽  
3 Dimensional ◽  
Shoulder Range Of Motion ◽  
Shoulder Kinematics ◽  
And Function ◽  
Shoulder Range

AbstractBackground and Purpose. People with idiopathic loss of shoulder range of motion (ROM) have difficulty completing activities of daily living. This investigation was performed to determine the association between active glenohumeral ROM and function and to develop a multiple regression equation to explain variation in function in people with idiopathic loss of shoulder motion. Subjects and Methods. This was a comparative study of 21 subjects (18 female, 3 male), using measurements of shoulder kinematics and administration of the Shoulder Rating Questionnaire (SRQ). Electromagnetic tracking sensors monitored the 3-dimensional position of the scapula and humerus throughout active shoulder motions. Correlations were performed between the active ROMs of interest and various demographic factors and the SRQ. A multiple regression equation was generated. Results. A multiple regression equation including scapular-plane abduction, external rotation at the side, external rotation at 90 degrees of abduction, and weight explained 69% of the variation in the SRQ scores. Discussion and Conclusion. The results suggest that active ROM can be used to predict function in people with idiopathic loss of shoulder ROM.

Analysis of Cloud Seeding Efforts in the Tri-County Area,* Oregon, 1950–54

1957 ◽  
Vol 38 (3) ◽  
pp. 134-137 ◽  
Author(s):  
Fred W. Decker ◽  
Russell L. Lincoln ◽  
John A. Day
Keyword(s):  
Multiple Regression ◽  
Regression Equation ◽  
Multiple Regression Equation ◽  
Cloud Seeding ◽  
North Central ◽  
Natural Rainfall ◽  
Cent Level

Using an 11-variable multiple regression equation to compute the “natural” rainfall, it is concluded that commercial cloud seeding during 1950–54 in three north central Oregon counties failed to produce departures in precipitation which are statistically significant at the 5 per cent level of acceptance.

The Use of Econometric Analysis in Forecasting Macroeconomic Processes

2021 ◽  
pp. 28-33
Author(s):  
Aleksandr Kalyanov ◽  
Andrey Shishkin
Keyword(s):  
Multiple Regression ◽  
Econometric Model ◽  
Econometric Analysis ◽  
Regression Equation ◽  
Multiple Regression Equation ◽  
Linear Multiple Regression ◽  
Consumer Prices ◽  
Macroeconomic Indicators ◽  
Primary Impact ◽  
Selection Of

The article discusses the issues related to the influence of various price categories of goods on the level of inflation. The possibility of using econometric analysis for predictive purposes is considered. An econometric model of multiple regression of the influence of consumer prices on the level of inflation is formed. A linear multiple regression equation is constructed. The selection of factors for the construction of an econometric model is made. The main groups of goods are identified, the prices of which form the level of inflation and can have a primary impact. The viability of the model and the possibility of forecasting macroeconomic indicators based on econometric analysis are proved.

Variation in nutrient content of feedingstuffs rich in protein and reassessment of the chemical method for metabolizable energy estimation for poultry

1976 ◽  
Vol 86 (2) ◽  
pp. 293-303 ◽  
Author(s):  
G. N. Lodhi ◽  
Daulat Singh ◽  
J. S. Ichhponani
Keyword(s):  
Multiple Regression ◽  
Crude Protein ◽  
Regression Equation ◽  
Metabolizable Energy ◽  
Multiple Regression Equation ◽  
Regression Equations ◽  
Ether Extract ◽  
Crude Fibre ◽  
Energy Estimation ◽  
Short Period

SummaryA series of five metabolism trials was made to determine apparent nitrogen digestibility and metabolizable energy (ME) contents of protein rich feedingstuffs. The mean nitrogen digestibilities of fish meal, groundnut, mustard, sesame and cottonseed cakes were 66, 69, 68, 57 and 40%, respectively. Corresponding values for metabolizable energy values were 1820, 2460, 2330, 1870 and 1530 kcal/kg, respectively. The metabolizable energy contents of coconut cake, niger cake and blood meal were 1190, 2360 and 2190 kcal/kg, respectively. The quantity of protein, its digestibility and crude fibre content in the cakes are the prime factors for this trend in MB. Simple and multiple regression equations were derived from biologically assayed metabolizable energy and chemically analysed energy-yielding nutrient contents of the feedingstuffs. The simple regression equation is:ME kcal/kg = 32·95 (% crude protein + % ether extract × 2·25+ % available carbohydrate)–29·20.The multiple regression equation is:ME kcal/kg = 370·29 + (24·47 × % crude protein)+ (65·77 × % ether extract)+ (44·07 × % available carbohydrate)- (8·15 × % crude fibre).The correlation coefficients of simple and multiple regression equations were 0·72 and 0·73, respectively, indicating that there is very little advantage for prediction in using the multiple regression equation. The usefulness of the equation for routine checking of poultry feeds for ME is apparent since the nutrients required to predict metabolizable energy can be analysed within a short period of time.

scholarly journals A Multiple Regression Equation for Prediction of Posthepatectomy Liver Failure

1984 ◽  
Vol 200 (5) ◽  
pp. 658-663 ◽  
Author(s):  
NAOKI YAMANAKA ◽  
EIZO OKAMOTO ◽  
KEIJI KUWATA ◽  
NOBUTAKA TANAKA
Keyword(s):  
Liver Failure ◽  
Multiple Regression ◽  
Regression Equation ◽  
Multiple Regression Equation ◽  
Posthepatectomy Liver Failure
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