Sara Maidaa HLTH 511 Research Methods Liberty University Methods Sample: A population-based cross-sectional study was conducted on a sample of 20 primary school children, aged 4 to 15 years old. Equipment: Flexible inextensible tape: Task Force Hand Tools 25-foot tape measure. Pediatric Height/Weight Scale Measurements: Weight and height were measured. Written consent for physical examination was obtained from the parents. All measurements were performed by trained research assistants, and under standard protocols. Weight and height were measured twice to the nearest 0.1 cm and 0.1 kg, respectively, with children being barefoot and lightly dressed, and standing straight and immobile on the scale. BMI was calculated as weight in kilograms divided by the square of height in meters (kg/m²). Statistical Procedures: Mean, median, standard deviation, minimum and maximum will be calculated for the sample. Data will be examined for outliers. Pearson product moment correlation was used to determine the magnitude and significance of the relationship between food marketing and obesity in school children. Hypotheses Being Tested: Null Hypothesis: ρ (rho) =0 There is no significant relationship between food marketing and childhood obesity. Alternative Hypothesis: ρ (rho) ≠0 There is a significant relationship between food marketing and childhood obesity. Hypotheses tested at the 0.05 level of significance. If a significant relationship between food marketing and childhood obesity is established then regression analysis was used to derive an equation to predict food marketing from obesity. The Suitability of Arm Span as a Substitute Measurement for Height HLTH 501 David M. Barton Abstract Many anthropometric equations rely on individual height. Accurate height is not obtainable when various skeletal abnormalities exist. Arm span is proposed as a possible substitute for height. Thirteen subjects’ arm span and height were measured. The Pearson R for arm span and height was 0.96 (p<0.05). Regression analysis was used to build and equation predicting height from arm span (Height = 0.8655 x Arm Span + 9.3368). Results of this study show that arm span and height are strongly correlated and arm span can be used as a reliable predictor of height. Introduction In many medical, physiological, and human performance measurements the height of human subjects is used as a predictive and/or classification variable. Equations predicting Body Mass Index, pulmonary function, caloric expenditure, and body fat percentage are just a few of the many equations using height as a predictive variable.1 However, spinal curvature conditions such as kyphosis, scoliosis, lordosis, and kyphoscoliosis make it difficult to determine the correct height of the individual and thereby necessitating the need to identify a substitute anthropometric measurement.2 The need for an anthropometric measurement to serve as a substitute for height has long been recogn.

1. Sara Maidaa
HLTH 511
Research Methods
Liberty University
Methods
Sample:
A population-based cross-sectional study was conducted on a
sample of 20 primary school children, aged 4 to 15 years old.
Equipment:
Flexible inextensible tape: Task Force Hand Tools 25-foot tape
measure.
Pediatric Height/Weight Scale
Measurements:
Weight and height were measured.
Written consent for physical examination was obtained from the
parents.
All measurements were performed by trained research
assistants, and under standard protocols.
Weight and height were measured twice to the nearest 0.1 cm
and 0.1 kg, respectively, with children being barefoot and
lightly dressed, and standing straight and immobile on the scale.
BMI was calculated as weight in kilograms divided by the
square of height in meters (kg/m²).
Statistical Procedures:
Mean, median, standard deviation, minimum and maximum will
be calculated for the sample. Data will be examined for
outliers.

2. Pearson product moment correlation was used to determine the
magnitude and significance of the relationship between food
marketing and obesity in school children.
Hypotheses Being Tested:
Null Hypothesis: ρ (rho) =0 There is no significant relationship
between food marketing and childhood obesity.
Alternative Hypothesis: ρ (rho) ≠0 There is a significant
relationship between food marketing and childhood obesity.
Hypotheses tested at the 0.05 level of significance.
If a significant relationship between food marketing and
childhood obesity is established then regression analysis was
used to derive an equation to predict food marketing from
obesity.
The Suitability of Arm Span as a Substitute Measurement for
Height
HLTH 501
David M. Barton
Abstract
Many anthropometric equations rely on individual height.
Accurate height is not obtainable when various skeletal

3. abnormalities exist. Arm span is proposed as a possible
substitute for height.
Thirteen subjects’ arm span and height were measured.
The Pearson R for arm span and height was 0.96 (p<0.05).
Regression analysis was used to build and equation predicting
height from arm span (Height = 0.8655 x Arm Span + 9.3368).
Results of this study show that arm span and height are strongly
correlated and arm span can be used as a reliable predictor of
height.
Introduction
In many medical, physiological, and human performance
measurements the height of human subjects is used as a
predictive and/or classification variable. Equations predicting
Body Mass Index, pulmonary function, caloric expenditure, and
body fat percentage are just a few of the many equations using
height as a predictive variable.1
However, spinal curvature conditions such as kyphosis,
scoliosis, lordosis, and kyphoscoliosis make it difficult to
determine the correct height of the individual and thereby
necessitating the need to identify a substitute anthropometric
measurement.2
The need for an anthropometric measurement to serve as a
substitute for height has long been recognized. One possible
substitute measurement is arm span, that is – the distance from
the left middle finger tip to the right middle fingertip of
outstretched arms parallel to the ground.
This relationship is notably shown in the drawing Vitruvian
Man by Leanardo da Vinci (See Figure 1.).
Figure 1. Vitruvian Man by Leonard da Vinci.
The purpose of this cross-sectional observational study
was to determine if there was a significant relations ship
between arm span and height to determine if a arm span could
serve as a valid and reliable substitute for height.

4. Methods
Sample:
A convenience sample of 12 high school seniors and 1 senior
high school teacher will be used.
Equipment:
Task Force Hand Tools 25 foot tape measure.
Measurements:
Each subject height (with shoes off) will be determined with the
subject standing flat footed and with erect posture.
The arm span will be taken with arms outstretched, parallel to
the ground, from the tip of the right middle finger to the left
middle finger across the back.
All measurements will be recorded to the nearest ½ inch.
Statistical Procedures:
Mean, median, standard deviation, minimum and maximum will
be calculated for the sample. Data will be examined for outliers.
Pearson product moment correlation was used to determine the
magnitude and significance of the relationship between arm
span and height.
Hypotheses tested:
Null Hypothesis: ρ (rho) =0 There is no significant relationship
between arm span and height.
Alternative Hypothesis: ρ (rho) ≠0 There is a significant
relationship between arm span and height.
Hypotheses tested at the 0.05 level of significance.
If a significant relationship between arm span and height is
determined then regression analysis was used to derive an

5. equation to predict height from arm span.
Data analysis and graph creation were accomplished using SPSS
20.0
Results
Arm span and height measurement are shown in Table 1.
Table 1. Raw data and correlation parameters
Student Name
Arm Span
(Inches)
Height
(Inches)
A
61.5
63.5
B
70.5
70.0
C
66.5
66.0
D
68.0
65.5
Dr. Barton
67.0
68.0
E
60.5
61.5
F
71.5
72.5
G
77.0

6. 76.5
H
62.0
64.5
I
64.0
65.0
J
64.0
64.5
K
72.5
71.0
L
71.0
72.0
Descriptive statistics for arm span and height are shown in
Table 2.
Table 2. Descriptive Statistics
ArmSpan
Height
N
Valid
13
13
Missing
0
0
Mean
67.38
67.73
Median
67.00
66.00

7. Mode
64
65
Std. Deviation
4.946
4.347
Variance
24.465
18.901
Skewness
.330
.582
Std. Error of Skewness
.616
.616
Kurtosis
-.625
-.439
Std. Error of Kurtosis
1.191
1.191
Range
17
15
Minimum
61
62
Maximum
77
77
Percentiles
25
63.00
64.50
50

8. 67.00
66.00
75
71.25
71.50
Figure 2. Box plot of arm spam measurements.
Figure 3. Box plot of height measurements.
Correlation between armspan and height are shown in Table 3.
Table 3. Correlations
ArmSpan
Height
Spearman's rho
ArmSpan
Correlation Coefficient
1.000
.963**
Sig. (2-tailed)
.
.000
N
13
13
Height
Correlation Coefficient
.963**

9. 1.000
Sig. (2-tailed)
.000
.
N
13
13
**. Correlation is significant at the 0.01 level (2-tailed).
Scatterplot of arm span and height is shown in Figure 3.
Figure 3. Scatterplot of Arm Span and Height
Results of regression analysis is shown in Table 4.
Table 4. Regression Analysis
r²
0.925
n
12

10. r
0.962
k
1
Std. Error
1.249
Dep. Var.
Height
ANOVA table
Source
SS
df
MS
F
p-value
Regression
191.8190

11. 1
191.8190
122.98
6.11E-07
Residual
15.5977
10
1.5598
Total
207.4167
11
confidence interval
Regression output

12. 95% upper
variables
coefficients
std. error
t (df=10)
p-value
95% lower
21.1675
Intercept
9.3368
5.3097
1.758
.1092
-2.4940
1.0394
Arm Span
0.8655
0.0780
11.090
6.11E-07
0.6916
Discussion
In an effort to determine whether or not a significant correlation
between arm span and height, measurements were obtained from
13 “normal” subjects.
The results shown in Table 2 and Figures 2 and 3 indicate there
were no outliers and that the data were almost normally
distributed. Therefore all data were included in the statistical
analyses.
Results of the correlation analysis in Table 3 indicate a
significant (p<0.05) strong positive (r=0.925) correlation
between arm span and height. This strength and direction of the
correlation is further demonstrated by the scatterplot shown in

13. Figure 3.
The significant correlation between arm span and height
allowed for subsequent regression analysis, the results of which
are shown in Table 4. The resulting regression equation is as
follows:
Height = 0.8655 x Arm Span + 9.3368
The results of this study suggest that arm span measurement can
be used as a substitute for height in normal subjects.
Limitations of this study include the small sample size, narrow
range of arm spans and height, and the fact that all subjects
were healthy and had no observable spinal curvature. Caution
must be exercised in generalizing these results to populations
other than described above.
1. Use of anthropometric measures to assess weight loss;George
A. Bray,4 M.D., Frank L. Greenway,5 M.D., Mark E. Molitch,6
M.D., William T. Dahms,7 M.D., Richard L. Atkinson,8 M.D.,
and Kare
2. The use of arm span as a predictor of height: A study of
South Indian Women
SP Mohanty, S Suresh Babu and N Sreekumaran NairKasturba
Medical College and Hospital, Manipal, Karnataka, India
�Introduction
�Methods
�Results

14. �Conclusion
�Foundation
�Need
�Historical refereence, not always necessary, but often of
interest
�Type of study
�Purpose statement
�Summary statement
�Final conclusion
�Limitations of the study
�At least one reference required.
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