Association of Body Mass Index With Blood Pressure

MAT 135 Project One

Population and selection of response and explanatory variables

Target Population People with obesity
Study’s explanatory variable Body mass index
Study’s response variable Systolic blood pressure

Description of relationships

The body mass index has a strong positive relationship with systolic blood pressure among individuals. Obesity is a significant risk factor for hypertension because fat deposits restrict the blood flow in arteries and increase blood pressure. Moreover, obesity changes the metabolic mechanism of blood sugar regulation, absorption of ions by kidneys, and hormonal levels, resulting in increased blood pressure among obese individuals. The body mass index is an appropriate parameter for measuring weight because it considers the height of individuals. In this case, the study hypothesizes that an increase in body mass index causes a significant increase in systolic blood pressure.

Collected data

Individual Number Body Mass Index Systolic Blood Pressure
1 31 125
2 37 142
3 30 124
4 35 136
5 36 132
6 34 131
7 32 135
8 40 145
9 39 143
10 35 136
11 32 132
12 34 134
13 36 138
14 36 135
15 35 138
16 32 133
17 38 139
18 37 131
19 34 135
20 32 132
21 31 136
22 35 132
23 33 134
24 39 143
25 38 142
26 37 141
27 35 138
28 36 137
29 34 134
30 32 131

Descriptive Statistics

Table 1 offers a summary of descriptive statistics of body mass index and systolic blood pressure. The body mass index of individuals has a mean of 34.8, mode of 35.0, and median of 35.0. As the measures of spread, the body mass index has a range of 10 with a maximum value of 40 and minimum one of 30, a standard deviation of 2.6, and variance of 6.9. Systolic blood pressure has a mean of 135.5, median of 135.0, and mode of 132. The range of systolic blood pressure is 21 with a maximum value of 145 and minimum one of 124 with a standard deviation of 5.0 and variance of 24.7.

Table 1: Descriptive Statistics of Body Mass Index and Systolic Blood Pressure

Body Mass Index Systolic Blood Pressure
Mean 34.8 135.5
Median 35.0 135.0
Mode 35.0 132.0
Standard Deviation 2.6 5.0
Sample Variance 6.9 24.7
Range 10.0 21.0
Minimum 30.0 124.0
Maximum 40.0 145.0
Count 30.0 30.0

Graphs

Histograms of body mass index (Figure 1) and systolic blood pressure (Figure 2) show that their data follow the normal distribution. In body mass index, most individuals were between 34 and 36, while in systolic blood pressure, the group of 134-136 had the highest frequencies.

Histogram showing distribution of individuals based on body mass index
Figure 1: Histogram showing distribution of individuals based on body mass index
Histogram showing the distribution of individuals based on systolic blood pressure
Figure 2: Histogram showing the distribution of individuals based on systolic blood pressure

Linear regression

Scatterplot of my data

The scatterplot (Figure 3) shows that the systolic blood pressures have a linear relationship with body mass index because of the consistent trend of data points. Additionally, the linear relationship is a positive one since the systolic blood pressure increases with the rise in the body mass index.

Scatterplot showing distribution of data points
Figure 3: Scatterplot showing distribution of data points

Correlation

Correlation outcomes (Table 2) show that the body mass index and systolic blood pressure have a strong positive relationship (r = 0.803). The correction coefficient implies that systolic blood pressure rises as the body mass index increases among individuals. Since body mass index is an explanatory variable, it has a positive influence on systolic blood pressure among individuals. Linderman et al. (2018) aver that body mass index is a causal factor of hypertension among individuals. Therefore, the strong relationship confirms that body mass index in people with obesity contributes to high blood pressure.

Table 2: Correlation between body mass index and systolic blood pressure

Body Mass Index Systolic Blood Pressure
Body Mass Index 1
Systolic Blood Pressure 0.803 1

The linear regression equation for my data.

Regression coefficients (Table 3) indicate that a unit increase in the body mass index causes the systolic blood pressure to increase by 1.52 units. Hence, the following is the linear regression equation:

  • Systolic blood pressure = 82.51 + 1.52 (systolic blood pressure)

Table 3: Regression Output

Regression Statistics
Multiple R 0.803
R Square 0.645
Adjusted R Square 0.632
Standard Error 3.016
Observations 30
ANOVA
df SS MS F Significance F
Regression 1 462.708 462.708 50.855 0.000
Residual 28 254.758 9.099
Total 29 717.467
Coefficients Standard Error t Stat P-value Lower 95% Upper 95%
Intercept 82.506 7.447 11.079 0.000 67.252 97.760
Body Mass Index 1.520 0.213 7.131 0.000 1.084 1.957

The meaning of the y-intercept from part c means in terms of your two variables.

The y-intercept in the regression equation means that the systolic blood pressure would be 82.51 when the body mass index is zero.

The meaning of slope

The slope of the regression equation shows is a positive relationship where a unit increase in the body mass index makes the systolic blood pressure to increase by 1.52 units.

Scatter plot with the regression line (Figure 4):

Scatter plot with the regression line
Figure 4

Two random individuals (Table 4):

Table 4: Residual values of two random variables

Explanatory value Estimated response value Actual response value Residual value
32 131.15 133 1.85
38 140.27 142 1.73

Description of results and assumptions

The analysis of the relationship between variables matches the assumption of the study that an increase in body mass index causes a significant increase in systolic blood pressure. The scatterplot shows a trend of data points depicting a positive relationship between the body mass index and the systolic blood pressure. The regression output (Table 2) confirms that the body mass index has a strong relationship with the systolic blood pressure (R = 0.803). It also reveals that the body mass index accounts for 64.5% of the variation in the systolic blood pressure in people with obesity. The regression model used is statistically significant in predicting the impact of body mass index on the systolic blood pressure among people with obesity, F(1,28) = 50.86, p = 0.000. The regression coefficient shows that a unit increase in the body mass index results in an increase of the systolic blood pressure by 1.52 units among people with obesity.

Reference

Linderman, G. C., Lu, J., Lu, Y., Sun, X., Xu, W., Nasir, K.,… & Krumholz, H. M. (2018). Association of body mass index with blood pressure among 1.7 million Chinese adults. JAMA Network Open, 1(4), 1-11.

Cite this paper

Select style

Reference

StudyCorgi. (2022, September 9). Association of Body Mass Index With Blood Pressure. https://studycorgi.com/association-of-body-mass-index-with-blood-pressure/

Work Cited

"Association of Body Mass Index With Blood Pressure." StudyCorgi, 9 Sept. 2022, studycorgi.com/association-of-body-mass-index-with-blood-pressure/.

* Hyperlink the URL after pasting it to your document

References

StudyCorgi. (2022) 'Association of Body Mass Index With Blood Pressure'. 9 September.

1. StudyCorgi. "Association of Body Mass Index With Blood Pressure." September 9, 2022. https://studycorgi.com/association-of-body-mass-index-with-blood-pressure/.


Bibliography


StudyCorgi. "Association of Body Mass Index With Blood Pressure." September 9, 2022. https://studycorgi.com/association-of-body-mass-index-with-blood-pressure/.

References

StudyCorgi. 2022. "Association of Body Mass Index With Blood Pressure." September 9, 2022. https://studycorgi.com/association-of-body-mass-index-with-blood-pressure/.

This paper, “Association of Body Mass Index With Blood Pressure”, was written and voluntary submitted to our free essay database by a straight-A student. Please ensure you properly reference the paper if you're using it to write your assignment.

Before publication, the StudyCorgi editorial team proofread and checked the paper to make sure it meets the highest standards in terms of grammar, punctuation, style, fact accuracy, copyright issues, and inclusive language. Last updated: .

If you are the author of this paper and no longer wish to have it published on StudyCorgi, request the removal. Please use the “Donate your paper” form to submit an essay.