Blood Sugar and Walking Behavior Analysis

The assignment involves analyzing data on blood sugar levels, walking behavior, and BMI in two groups. It uses Levene's Test for Equality of Variances and independent samples t-tests to compare the means of these variables between the groups. The results are presented in tables with information about F-statistics, significance levels (Sig.), degrees of freedom (df), mean differences, and confidence intervals. The data explores potential relationships between blood sugar regulation, physical activity (walking), and body mass index.

Running head: QUANTITATIVE RESEARCH METHODS
Quantitative Research Methods
Name of Student
Name of University
Author’s Note

1QUANTITATIVE RESEARCH METHODS
Abstract
The aim of the report is to discuss whether there is any significant difference between the
BMI, the height and weight, blood sugar levels and blood cholesterol levels of walking and non-
walking persons based on the data provided. The analysis has been conducted using the
statistical software SPSS. From the analysis, it has been observed that the BMI and blood sugar
level do not differ between the walking and the non-walking group of people.

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Table of Contents
1.0 Introduction................................................................................................................................3
1.1 Background............................................................................................................................3
1.2 Information of the analysis conducted...................................................................................3
2.0 Methods.....................................................................................................................................4
2.1 Population and sampling strategy..........................................................................................4
2.2 Variables and measures.........................................................................................................5
3.0 Results........................................................................................................................................6
3.1 Demographic Analysis...............................................................................................................6
3.2 Hypothesis Tests....................................................................................................................8
3.2.1 Test 1..............................................................................................................................8
3.2.2 Test 2..............................................................................................................................9
3.2.3 Test 3..............................................................................................................................9
3.2.4 Test 4............................................................................................................................10
3.2.5 Test 5............................................................................................................................11
4.0 Discussions..............................................................................................................................11
APPENDIX A................................................................................................................................13
APPENDIX B................................................................................................................................18

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1.0 Introduction
1.1 Background
There is a link to the way in which physical activity is related to the insulin sensitivity. It
is also related to the glucose intolerance in individuals and is also responsible for reducing the
risks of type 2 diabetes (1). It has been found that the patients with type 2 diabetes are
recommended to perform moderate to vigorous aerobic exercises like running or bicycling. It is
however seen that the patients find it hard to do high impact exercises due to their impaired
intolerance to any forms of physical activity (2). After these considerations it can be said that
walking is the best choice and the most popular exercise among the patients with diabetes. This
is due to the reason that it requires no specific skills and also has minimal adverse effects (3). In
order to understand and assess the impact of the exercise due to the impaired intolerance to the
physical activity a proper analysis of the data related to the type two diabetes patients were
conducted.
1.2 Information of the analysis conducted
A meta-analysis of the randomized control trial was conducted in order to assess the
effect of walking on the glycemic control and other cardio-vascular risk factors in case of the
people with type two diabetes. There were 866 participants who were included from 20
randomized control trials and helped in finding support that walking helps to reduce HbA1c
among the diabetes patients and also helps to reduce the body mass index and the diastolic blood
pressure.
Another study was conducted to examine the effects of regular walking on the
biochemical and behavioral aspects in case of the elder people with type 2 diabetes. A
randomized design was conducted and used in case of the experimental and the control groups.

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The experimental group received six months walking exercise program and diet control
education program. The regular waling exercise is effective in the daily consumption activity and
energy consumption and the decreasing the fasting blood glucose, HbA1c and also the
triglyceride level. These analyses were conducted to assess the effectiveness of walking on the
glucose control in the patients with type 2 diabetes. Thus this study aims to find out whether
brisk walking is helpful in the maintenance of decreasing glucose level in healthy individuals.
Thus this study aims to find whether brisk walking is beneficial in the decreasing glucose level in
males and females aged 40-65 years who reside in the Pauma Community of Island.
Blood glucose is basically defined as the concentration of glucose in the blood which is
represented in milligrams of glucose per deciliter of blood (4). Normal adult blood glucose levels
range from 70 to 115 mg/dl with generally higher levels after 50 years of age. Fasting serum
glucose of 126 mg/dl on two or more occasions signifies diabetes mellitus (5).
Walking is characterized by sequential movement or progression in steps. The body mass
index is also known as the Quetlet Index is a measure for indicating nutritional status in case of
adults. It is defined as a person’s weight in kilograms which is divided by the square of the
person’s height in meters (6).
2.0 Methods
2.1 Population and sampling strategy
The total number of subjects chosen was 55 in number. The analysis was done on the
chosen subjects. The context for the study was the Pauma community. The population of interest
consisted of males aged between 40-65 years.

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Sampling: The target population is comprised of males aged between 40-65 years who
reside in the Pauma community. Then a random sample of 40 was chosen by a method of simple
random sample based on the first come first chosen basis. Then they would be divided into two
groups which comprised the intervention group and the control group. The intervention group
will perform walking for 30 minutes and the second group will be in the waiting list which will
not involve any walking group.
2.2 Variables and measures
The different variables and their types are discussed and mentioned and their nature of
role is also discussed. The following table shows these details clearly.
Variable Type Role Level of Units Measure
Blood glucose continuous Primary
explanatory
mg/dl Self- report
Height continuous explanatory metres Self-report
Weight continuous explanatory kilograms Self-report
BMI continuous explanatory Self-report
walking nominal Primary
explanatory
30 minutes
walking/ no
walking
Self -report
Name nominal explanatory name Self-report
Age continuous explanatory years Self-report
Consent ordinal explanatory Yes/no Self-report

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3.0 Results
3.1 Demographic Analysis
From the data collected from the 40 selected samples, the following conditions of
demography can be explained. At first, the distribution of gender will be discussed here. From
the figure 3.1, it can be seen clearly that 50.91 percent of the sample are female and 49.09
percent of the sample were male. Thus, from here it can be said that the sample will represent the
male and the female population almost equally as there is not much difference in the sample
percentages of males and females.
Figure 3.1: Distribution of Gender

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The second factor that will be discussed here is the consent given by the participants. The
distribution of the consent given by the participants is given in figure 3.2. From the figure, it can
be clearly seen that most of the selected samples have given the consent to the event and very
little percentage of the respondents did not give consent. 76.36 percent of the respondents have
given consent to the event and 23.64 percent of the people did not give consent to the event.
Figure 3.2: Distribution of Consent given by the respondents
The third factor that will be discussed here is the distribution of the walking and the non-
walking groups of the participants. The distribution is shown in figure 3.3. From the figure, it can
be clearly seen that 38.18 percent of the respondents belong to each of the groups of walking and
non-walking. 23.64 percent of the respondents did not give consent to the event. Thus, they have
not been included in any group of the event.

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Figure 3.3: Distribution of the walking and the non-walking group
3.2 Hypothesis Tests
To conduct this research, the following hypotheses have to be tested. The respective
research questions, null hypotheses and alternate hypotheses are given as follows:
3.2.1 Test 1
Research Question 1: Is there any significant difference between the blood cholesterol level of
the walking and non-walking groups
Null Hypothesis 1: There is no significant difference between the blood cholesterol level of the
walking and non-walking groups
Alternate Hypothesis 1: There is significant difference between the blood cholesterol level of
the walking and non-walking groups

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To test the above stated hypothesis, independent sample t test has to be run in SPSS.
Here, the equality of means of the two groups – walking and non-walking group in terms of the
level of cholesterol in the blood. From the results of the t-test, given in table 5, it can be said that
the p-value is 0.548, which is more than 0.05, the level of significance at 95% confidence
interval. Thus, from here, it can be said that the null hypothesis is accepted. Therefore, there is
no significant difference in the blood cholesterol levels of the walking and the non-walking
groups.
3.2.2 Test 2
Research Question 2: Is there any significant difference between the height of the people of the
walking and non-walking groups
Null Hypothesis 2: There is no significant difference between the height of the people of the
walking and non-walking groups
Alternate Hypothesis 2: There is significant difference between the height of the people of the
walking and non-walking groups
To test the above stated hypothesis, independent sample t test has to be run in SPSS.
Here, the equality of means of the two groups – walking and non-walking group in terms of the
height of the respondents. From the results of the t-test, given in table 7, it can be said that the p-
value is 0.644, which is more than 0.05, the level of significance at 95% confidence interval.
Thus, from here, it can be said that the null hypothesis is accepted. Therefore, there is no
significant difference in the heights of the walking and the non-walking groups of the people.

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3.2.3 Test 3
Research Question 3: Is there any significant difference between the weight of the people of the
walking and non-walking groups
Null Hypothesis 3: There is no significant difference between the weight of the people of the
walking and non-walking groups
Alternate Hypothesis 3: There is significant difference between the weight of the people of the
walking and non-walking groups
To test the above stated hypothesis, independent sample t test has to be run in SPSS.
Here, the equality of means of the two groups – walking and non-walking group in terms of the
weight of the respondents. From the results of the t-test, given in table 9, it can be said that the p-
value is 0.992, which is more than 0.05, the level of significance at 95% confidence interval.
Thus, from here, it can be said that the null hypothesis is accepted. Therefore, there is no
significant difference in the weights of the walking and the non-walking groups of the people.
3.2.4 Test 4
Research Question 4: Is there any significant difference between the BMI of the people of the
walking and non-walking groups
Null Hypothesis 4: There is no significant difference between the BMI of the people of the
walking and non-walking groups
Alternate Hypothesis 4: There is significant difference between the BMI of the people of the
walking and non-walking groups

11QUANTITATIVE RESEARCH METHODS
To test the above stated hypothesis, independent sample t test has to be run in SPSS.
Here, the equality of means of the two groups – walking and non-walking group in terms of the
BMI of the respondents. From the results of the t-test, given in table 11, it can be said that the p-
value is 0.281, which is more than 0.05, the level of significance at 95% confidence interval.
Thus, from here, it can be said that the null hypothesis is accepted. Therefore, there is no
significant difference in the BMI of the walking and the non-walking groups of the people.
3.2.5 Test 5
Research Question 5: Is there any significant difference between the Blood sugar level of the
males and females of the peoplewho arewalking
Null Hypothesis 5: There is no significant difference between the Blood sugar level of the males
and females of the peoplewho arewalking
Alternate Hypothesis 5: There is significant difference between the Blood sugar level of the
males and females of the peoplewho arewalking
To test the above stated hypothesis, independent sample t test has to be run in SPSS.
Here, the equality of means of the two groups – males and females of the walking group in terms
of the blood sugar level of the respondents. From the results of the t-test, given in table 13, it can
be said that the p-value is 0.243, which is more than 0.05, the level of significance at 95%
confidence interval. Thus, from here, it can be said that the null hypothesis is accepted.
Therefore, there is no significant difference in the blood sugar level of the males and the females
of the walking groups of the people.

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4.0 Discussions
In the light of the collected results it can be clearly conducted that there is no significant
difference between the blood sugar levels of the males and females who are walking. In addition
to this, it is clearly evident from the previous research questions that there is no significant
difference of the BMI of the people of the walking and non-walking groups. There also no
significant difference between the blood cholesterol levels, weights or heights of the people
belonging to walking as well as non-walking groups. Thus the data clearly state that there is no
significant difference between any attributes of the walking and non-walking groups.
It is evident that there should be differences in the blood sugar levels and the BMI of the
people belonging to the walking and the non-walking groups. This is not the case according to
this research. This may have happened due to the following limitation. The sample size of 30 is
too less to interpret properly about all the people of the island. Thus, by increasing the sample
size, the results can be obtained differently and more accurately.

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References
1. Kyu HH, Bachman VF, Alexander LT, Mumford JE, Afshin A, Estep K, Veerman JL,
Delwiche K, Iannarone ML, Moyer ML, Cercy K. Physical activity and risk of breast
cancer, colon cancer, diabetes, ischemic heart disease, and ischemic stroke events:
systematic review and dose-response meta-analysis for the Global Burden of Disease
Study 2013. bmj. 2016 Aug 9;354:i3857.
2. Colberg SR, Sigal RJ, Yardley JE, Riddell MC, Dunstan DW, Dempsey PC, Horton ES,
Castorino K, Tate DF. Physical activity/exercise and diabetes: a position statement of the
American Diabetes Association. Diabetes Care. 2016 Nov 1;39(11):2065-79.
3. American Diabetes Association. Standards of medical care in diabetes—2015 abridged
for primary care providers. Clinical diabetes: a publication of the American Diabetes
Association. 2015 Apr;33(2):97.
4. American Diabetes Association. (2014). Diagnosis and classification of diabetes
mellitus. Diabetes care, 37(Supplement 1), S81-S90.
5. Diabetes, C. (2015). Complications Trial/Epidemiology of Diabetes I, Complications
Research G, Lachin JM, White NH, Hainsworth DP, Sun W, Cleary PA, Nathan DM.
Effect of intensive diabetes therapy on the progression of diabetic retinopathy in patients
with type 1 diabetes: 18 years of follow-up in the DCCT/EDIC. Diabetes, 64(2), 631-42.
6. Hirsch, J. A., Diez Roux, A. V., Moore, K. A., Evenson, K. R., & Rodriguez, D. A.
(2014). Change in walking and body mass index following residential relocation: the
multi-ethnic study of atherosclerosis. American journal of public health, 104(3), e49-e56.

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APPENDIX A
Raw Data
house
no.
Name Age Gender Consent Walking/
Non-
Walking
group
Blood
Glucose
Level
Height Weight Calculated
BMI
1 Erling 61 Male Yes W 85 172.9 57.9 19.37
2 Torsten 65 Male Yes W 88 177 69 22.02
Karina Female No
7 Jun Morris 52 Male Yes W 89 181.7 66.2 20.05
11 Tatsuya 47 Male No
12 Nana Sato 43 Female Yes W 91 161.3 54.2 20.8
16 Connor 44 Male No
17 Thresa 57 Female Yes W 90 163.7 45.9 17.13
Paul 50 Male Yes W 86 168.2 67 23.6
22 Ryan 45 Male Yes W 98 188.7 68.3 19.18
Michelle 45 Female No
27 Manami 64 Female Yes W 101 167.2 63.4 22.6
32 Henrick 62 Male Yes W 82 180.5 88.4 27.1
Nanami 61 Female Yes W 94 171.3 68.3 23.3
34 Sophie 45 Female No
35 Bernard 40 Male Yes W 94 176.6 68.3 21.9
Emily 40 Female Yes W 103 165.4 65.5 23.9
40 Haken 50 Male Yes W 90 166 67.4 24.4

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Manami 50 Female Yes W 95 170.5 50.2 17.2
46 Axel 49 Male Yes W 91 178.9 79.9 24.9
47 Miki 46 Female Yes W 86 166.5 59.2 21.3
52 Torvald 59 Male Yes W 81 176.3 67.9 21.6
Jessica 59 Female No
53 Julian 56 Male No
Yuka 54 Female No
56 Connor 46 Male Yes W 89 168.9 61.5 21.5
Riko 46 Female No
60 Thurston 44 Male Yes W 87 171.3 70 23.8
66 Helsa 62 Female Yes W 91 172.6 69 23.2
Ryan 61 Male Yes W 93 183.6 90.2 26.7
72 Gustave 46 Male Yes NW 97 179.5 72.9 22.6
Brigit 46 Female Yes NW 83 160.4 63.8 24.8
87 Evan 52 Male Yes NW 98 182.9 75.4 22.2
Reina 51 Female Yes NW 90 164.7 49.6 18.2
88 Lynnea 64 Female Yes NW 87 169.9 64.4 22.3
Logan 64 Male No
90 Aoran 46 Male Yes NW 87 184.3 73.1 21.5
96 Akira 52 Male Yes NW 100 176.2 79.7 25.6
Sakura 50 Female Yes NW 94 168.5 60.5 21.3
103 Ryan 45 Male No
104 Rachel 61 Female Yes NW 91 164.2 65.1 24.1
106 Hanne 60 Female Yes NW 97 174.5 64.7 21.2
108 Ryan 55 Male Yes NW 93 179.4 64.7 20.1

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Agda 54 Female Yes NW 89 167.7 62.4 22.1
112 Berit 47 Female Yes NW 94 157.4 58.3 23.5
117 Marcel 62 Male Yes NW 91 178.7 72.8 22.7
119 Sarah 40 Female Yes NW 95 163.3 69 25.8
122 Sho
Connolly
65 Male Yes NW 86 172.5 68.7 23
Ayona 64 Female Yes NW 89 170.6 59.6 101.6
126 Henna 41 Female No
129 Erla Female Yes NW 91 171.3 78.9 26.8
Daniel Morris Male Yes NW 96 186.7 79.3 22.7
130 Mai
Kimura
49 Female Yes NW 89 166 51.1 18.5
Rupert 47 Male No
136 Frederique 46 Female Yes NW 87 167.4 64.3 22.9

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APPENDIX B
Table 1: Distribution of Gender
Frequency Percent Valid Percent Cumulative Percent
Valid
Male 27 49.1 49.1 49.1
Female 28 50.9 50.9 100.0
Total 55 100.0 100.0
Table 2: Distribution of Consent
Frequency Percent Valid Percent Cumulative Percent
Valid
Yes 42 76.4 76.4 76.4
No 13 23.6 23.6 100.0
Total 55 100.0 100.0
Table 3: Distribution of Walking and Non-Walking group
Frequency Percent Valid Percent Cumulative Percent
Valid
W 21 38.2 50.0 50.0
NW 21 38.2 50.0 100.0
Total 42 76.4 100.0
Missing System 13 23.6
Total 55 100.0
Table 4: Group Statistics
Walking and Non-Walking
group
N Mean Std. Deviation Std. Error Mean
Blood_Sugar_Level W 21 90.67 5.615 1.225
NW 21 91.62 4.511 .984
Table 5: Independent Samples Test
Levene's Test
for Equality of
Variances
t-test for Equality of Means

19QUANTITATIVE RESEARCH METHODS
F Sig. t df Sig.
(2-
tailed)
Mean
Difference
Std. Error
Difference
95%
Confidence
Interval of the
Difference
Lower Upper
Blood_Sugar_Level
Equal
variances
assumed
.250 .620 -.60
6 40 .548 -.952 1.572 -4.129 2.224
Equal
variances not
assumed
-.60
6 38.223 .548 -.952 1.572 -4.134 2.229
Table 6: Group Statistics
Walking and Non-Walking group N Mean Std. Deviation Std. Error Mean
Height W 21 172.8143 7.15124 1.56053
NW 21 171.7190 8.05255 1.75721
Table 7: Independent Samples Test
Levene's Test for
Equality of
Variances
t-test for Equality of Means
F Sig. t df Sig. (2-
tailed)
Mean
Difference
Std. Error
Difference
95% Confidence
Interval of the
Difference
Lower Upper
Height
Equal variances
assumed .380 .541 .466 40 .644 1.09524 2.35012 -3.65452 5.84500
Equal variances
not assumed .466 39.449 .644 1.09524 2.35012 -3.65659 5.84706
Table 8: Group Statistics
Walking and Non-Walking group N Mean Std. Deviation Std. Error Mean
Weight W 21 66.5571 10.63619 2.32101
NW 21 66.5857 8.43091 1.83978

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Table 9: Independent Samples Test
Levene's Test for
Equality of
Variances
t-test for Equality of Means
F Sig. t df Sig. (2-
tailed)
Mean
Difference
Std. Error
Difference
95% Confidence
Interval of the
Difference
Lower Upper
Weight
Equal variances
assumed .046 .831 -.010 40 .992 -.02857 2.96173 -
6.01445 5.95731
Equal variances
not assumed -.010 38.019 .992 -.02857 2.96173 -
6.02418 5.96704
Table 10: Group Statistics
Walking and Non-Walking group N Mean Std. Deviation Std. Error Mean
BMI W 21 22.1690 2.66785 .58217
NW 21 26.3571 17.37439 3.79140
Table 11: Independent Samples Test
Levene's Test for
Equality of
Variances
t-test for Equality of Means
F Sig. t df Sig. (2-
tailed)
Mean
Difference
Std. Error
Difference
95% Confidence
Interval of the
Difference
Lower Upper
BMI
Equal variances
assumed 2.212 .145 -
1.092 40 .281 -4.18810 3.83584 -
11.94062 3.56443
Equal variances
not assumed
-
1.092 20.943 .287 -4.18810 3.83584 -
12.16649 3.79030
Table 12: Group Statistics