Raw Data
Data collected from the eating behavior surveys are presented in the table below;
| Participant # | Age | Height (cm) | Weight (kg) | BMI (kg/m 2 ) | Emotional overeating | Emotional Undereating | Eating Frequency |
|
1 |
45 |
187 |
131 |
37 |
Yes | No |
3 |
|
2 |
60 |
184 |
139 |
41 |
Yes | No |
3 |
|
3 |
44 |
187 |
100 |
29 |
No | Yes |
5 |
|
4 |
47 |
182 |
86 |
26 |
No | Yes |
2 |
|
5 |
46 |
147 |
86 |
40 |
Yes | No |
3 |
|
6 |
52 |
163 |
92 |
35 |
Yes | No |
3 |
|
7 |
55 |
192 |
89 |
24 |
No | Yes |
3 |
|
8 |
49 |
160 |
102 |
40 |
Yes | No |
5 |
|
9 |
60 |
157 |
114 |
46 |
Yes | No |
6 |
|
10 |
62 |
156 |
108 |
44 |
Yes | No |
5 |
|
11 |
65 |
177 |
82 |
26 |
Yes | No |
5 |
|
12 |
45 |
175 |
75 |
24 |
Yes | No |
5 |
|
13 |
45 |
180 |
155 |
48 |
Yes | No |
5 |
|
14 |
47 |
183 |
120 |
36 |
No | Yes |
3 |
|
15 |
54 |
156 |
135 |
55 |
Yes | No |
6 |
|
16 |
55 |
151 |
108 |
47 |
Yes | No |
5 |
|
17 |
57 |
152 |
90 |
39 |
Yes | No |
5 |
|
18 |
65 |
180 |
103 |
32 |
No | Yes |
3 |
|
19 |
62 |
172 |
115 |
39 |
No | Yes |
3 |
|
20 |
47 |
150 |
87 |
39 |
No | Yes |
5 |
|
21 |
47 |
148 |
80 |
37 |
Yes | No |
5 |
|
22 |
58 |
146 |
95 |
45 |
Yes | No |
5 |
|
23 |
60 |
155 |
92 |
38 |
Yes | No |
5 |
|
24 |
59 |
157 |
78 |
32 |
Yes | No |
5 |
|
25 |
43 |
182 |
75 |
23 |
No | Yes |
3 |
| Mean |
53 |
167 |
101 |
37 |
|||
| Mode |
47 |
187 |
86 |
#N/A |
|||
| Median |
54 |
163 |
95 |
38 |
Table 1: Eating Behavior and BMI Data.
Obesity in this study is defined as a BMI that exceeds 30kg/m 2 . A normal BMI falls within 18-25. A BMI between 25 and 30 indicates that the person is obese (Nuttall, 2015).
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Frequency Distribution
| BMI Class | Class Center | Frequency |
| 20-24 |
22 |
3 |
| 25-29 |
27 |
3 |
| 30-34 |
32 |
2 |
| 35-39 |
37 |
8 |
| 40-44 |
42 |
4 |
| 45-49 |
47 |
4 |
| 50-54 |
52 |
0 |
| 55-59 |
57 |
1 |
|
25 |
Table 2. Frequency Distribution Table
Graphical Representation of Data
The histogram below provides a graphical representation of BMI rates among middle-aged women selected for the study.
Figure 1. BMI
A combines the clustered column and line chart was used to represent the correlation between eating frequency and obesity.
Figure 2. BMI and Eating Frequency
Calculation of Statistics
|
Age |
Height (cm) |
Weight (kg) |
BMI (kg/m 2 ) |
Eating Frequency |
|
| Mean |
53 |
167 |
101 |
37 |
4 |
| Mode |
47 |
187 |
86 |
#N/A |
5 |
| Median |
54 |
163 |
95 |
38 |
5 |
| Standard Deviation |
7.261 |
15.233 |
21.440 |
8.436 |
1.165 |
| Standard Error |
1.452 |
3.047 |
4.288 |
1.687 |
0.233 |
| Variance |
52.723 |
232.057 |
459.677 |
71.163 |
1.357 |
| Range |
45-65 |
150-192 |
75-155 |
23-55 |
3-5 |
Table 3. Calculation of Statistics
The range was used to indicate the various values included in the data set for age, height, weight, BMI, and eating frequency. Women chosen in the study were middle-aged women. Therefore, their age ranges from 45-46. BMI values range between 23-55 (Normal-Obese). Women in the study had 2-5 meals daily. The range is not considered as a suitable statistic to use in this study. The mean, mode, and median of the data sets were calculated. The mean indicates the average value in a set of data. The mode indicated the most frequently occurring number in the data set, and the median indicated the central value. The mean is the most suitable descriptive statistic since it gives the typical value for the data set. The mode was not suitable since it was not appliable in two data sets. Additionally, the mode has no significance in this study. The median was also calculated using excel to indicate the central value. It is insignificant in this study (Mertler & Reinhart, 2016).
The standard deviation for the various data sets was calculated using Excel. A low standard deviation indicates that the data points are close to the mean, while a high standard deviation indicates that the data points are spread over a wide range of values. The standard error measures how far the sample mean is from the true population mean. The variance indicates how far a data set is spread out.
95% Confidence Interval (BMI)
Z=1.96
Mean = 37
Standard deviation σ=8.436
Sample size n=25
Confidence interval (CI)= ±1.96*(8.436/25) =37±3.3
Results
Calculation of the mean age showed that the average age of the women sampled was 53. The mean BMI for these women was 37, which indicates that the majority of the women were overweight or obese. The mean eating frequency for women sampled in the study was 4. The histogram indicates that the majority of women have a BMI range between 32 and 42. The combined clustered column and line chart shows that eating frequency corresponds to high BMI rates. The study results indicate that there is a positive relationship between eating frequency and BMI.
References
Mertler, C. A., & Reinhart, R. V. (2016). Advanced and multivariate statistical methods: Practical application and interpretation . Taylor & Francis.
Nuttall, F. Q. (2015). Body mass index: obesity, BMI, and health: a critical review. Nutrition today , 50 (3), 117.
