Fast Food and Childhood Obesity
Name
Institution
Fast Food and Childhood Obesity
Introduction
In this particular research, we are going to focus so much on the study pertaining the Fast food and childhood obesity. Food is an essential basic need for children, especially those below five years of age. Food plays a critical role as far as the growth and development of a given child is concerned. Childhood obesity is a condition whereby a child becomes extremely overweight as compared to its height and age due to the excess body fats. Childhood obesity refers to the health condition that is very delicate and dangerous to the life of a given child (Bleich, 2018). This is simply because childhood obesity can result in high blood pressure, diabetes, and high-level cholesterol accumulation in the body parts of a given child. This condition can cause obesity at the childhood level, and also be maintained at the adulthood level when it is not properly managed neither cured.
Childhood obesity is an epidemic problem that is usually experienced by both developed nations and the developing countries across the world. Even though childhood obesity is a global challenge, it is commonly found and experienced in the western world and some parts of Asia, like the United States of America and China (Bleich, 2018). The actual mechanism of the development of childhood obesity is not clearly understood, but it is perceived to be caused by multiple disorders of the body system. The lifestyle preferences of a person or a child, environmental factors, together with the cultural factors, play a significant role in connection to the rising obesity prevalence in the whole world. On the other hand, several arguments have it that childhood obesity can be caused by taking too much sugary food, primarily through soft drinks, a steady decline of carrying out physical exercise, and an increased proportion of body size (Lanas et al., 2016). Childhood obesity also has some negative impacts on the actual life of the children that have been victimized. Obesity can affect the physical health of a given child, emotional well-being, and also the self-esteem of a given child. All these conditions can, therefore, result in poor performance in academic endeavors and a lower life condition quality by a child.
The fast-food that is given to the child matters a lot since it dramatically determines the health status of a child as far as obesity is concerned. Having the fact that the dietary factors have made various contributions to the increasing rate of obesity prevalence. Increased fast food consumption has been directly linked to the rising price of this epidemic of obesity (Hammigsson, 2018). Food served at the restaurants that provide fast food usually contains a high level of calories with very minimal distribution values. In this research, a survey is conducted on the online platform on a given sample of the population.
Data collection methodology
The data was collected from this particular research in fast food, and child obesity was collected through the online platform. A Questionnaire sheet with relevant questions pertaining to this topic study was well formulated in terms of fast food and behavior in relationship to childhood obesity. The Questionnaire paper was so subjected to a population of 50 individuals, but only a sample size of 50 individuals was used to carry out the statistical analysis of this particular research.
The decision of the sample size of the 30 individuals was critically selected in terms of the population distribution of the 50 individuals. The selection of the sample distribution was based in terms of gender, age, and social status. These three aspects are fundamental as far as the study of fast food and behavior concerning childhood obesity is concerned. Therefore, all these essential criteria were carefully implemented to carry out a significant analysis of the sample that is not biased in terms of gender, age, and social status.
Further, the collected data was well-recorded on the spreadsheet, ready to carry out any form of statistical analysis of the collected data. The gender balancing was enabled were in the selected sample; there were 18 individuals in the female gender and 12 individuals from the male gender. People from the different age groups were considered where there were eight individuals from the age bracket of 18 years to 25 years, ten individuals from the age bracket of 26 years to 35 years, and 12 individuals who are 36 years and above (Lanas et al., 2016). Taking into consideration that the lifestyle matters as far the childhood obesity is concerned, the distribution of the sample was also done in terms of the social class. In the data, nine individuals came from the lower class families, 12 in the middle economic class, and nine from the royal families.
Hypotheses
Hypothesis refers to a Statistical claim or a proposed explanation, which is usually based on sufficient or limited evidence for further investigation. There are two main types of hypothesis, that is the null hypothesis and the alternative hypothesis. Therefore, the hypothesis of this particular research will be based on fast food and behavior in relation to childhood obesity. The null hypothesis is denoted by H0, and the alternative hypothesis will be denoted as H1. The two hypotheses will be formulated, as shown below:
- H0:The fast-food has got some significant impacts on Childhood obesity prevalence.
Verses,
H1: Fast food does not have any significant impact on childhood obesity prevalence.
- H0:The behavior of an individual has got some significant impact on childhood obesity prevalence.
Verses,
H1: The behavior of an individual does not have any significant impact on the childhood obesity prevalence.
Data Analysis and Interpretation
The recorded data pertaining the fast food and behavior in relation to the childhood obesity on the excel spreadsheet will be analysed using the statistical software of the R studio. The data was saved in form of CSV in to order to enhance easy exportation of the data to the R script to carry out the statistical analysis. The range of 1 to 10 was used on all the three variables.
The output of the data in terms of mean, standard deviations are as shown below:
Data=read.csv(“C:/Users/Admin/Desktop/INE2002 OBESITY.csv”);data
Obesity.level Value.of.the.fast.food Value.of.the.behavior
1 6 6 6
2 3 4 2
3 4 4 4
4 7 9 5
5 6 7 5
6 5 5 5
7 4 5 3
8 8 5 8
9 8 8 7
10 8 6 9
11 6 2 8
12 7 4 9
13 6 4 8
14 7 3 8
15 7 6 7
16 8 8 7
17 8 7 8
18 8 8 6
19 7 7 6
20 9 8 9
21 8 6 9
22 9 9 9
23
24 9 9 9
25 6 4 7
26 8 7 8
27 7 7 8
28 7 7 7
29 7 8 6
30 7 6 7
> attach(data)
> y=c(Obesity.level)
> y
[1] 6 3 4 7 6 5 4 8 8 8 6 7 6 7 7 8 8 8 7 9 8 9 8 9 6 8 7 7 7 7
> x1=c(Value.of.the.fast.food)
> x1
[1] 6 4 4 9 7 5 5 5 8 6 2 4 4 3 6 8 7 8 7 8 6 9 9 9 4 7 7 7 8 6
> x2=c(Value.of.the.behavior)
> mean(y)
[1] 6.933333
> var(y)
[1] 2.202299
> sd(y)
[1] 1.484014
> mean(x1)
[1] 6.266667
> var(x1)
[1] 3.71954
> sd(x1)
[1] 1.928611
> mean(x2)
[1] 6.9
> var(x2)
[1] 3.334483
> sd(x2)
[1] 1.826057
> plot(y~x1)
> Data=read.csv(“C:/Users/Admin/Desktop/INE2002 OBESITY.csv”);data
Obesity.level Value.of.the.fast.food Value.of.the.behavior
1 6 6 6
2 3 4 2
3 4 4 4
4 7 9 5
5 6 7 5
6 5 5 5
7 4 5 3
8 8 5 8
9 8 8 7
10 8 6 9
11 6 2 8
12 7 4 9
13 6 4 8
14 7 3 8
15 7 6 7
16 8 8 7
17 8 7 8
18 8 8 6
19 7 7 6
20 9 8 9
21 8 6 9
22 9 9 9
23 8 9 7
24 9 9 9
25 6 4 7
26 8 7 8
27 7 7 8
28 7 7 7
29 7 8 6
30 7 6 7
> attach(data)
The following objects are masked from data (pos = 3):
Obesity.level, Value.of.the.behavior, Value.of.the.fast.food
> y=c(Obesity.level)
> y
[1] 6 3 4 7 6 5 4 8 8 8 6 7 6 7 7 8 8 8 7 9 8 9 8 9 6 8 7 7 7 7
> x1=c(Value.of.the.fast.food)
> x1
[1] 6 4 4 9 7 5 5 5 8 6 2 4 4 3 6 8 7 8 7 8 6 9 9 9 4 7 7 7 8 6
> x2=c(Value.of.the.behavior)
> mean(y)
[1] 6.933333
> var(y)
[1] 2.202299
> sd(y)
[1] 1.484014
> mean(x1)
[1] 6.266667
> var(x1)
[1] 3.71954
> sd(x1)
[1] 1.928611
> mean(x2)
[1] 6.9
> var(x2)
[1] 3.334483
> sd(x2)
[1] 1.826057
Graph Showing the Relationship between Fast Food and Childhood Obesity
The graph was plotted on the R program which clearly shows that the relationship between the fast food and the prevalence of childhood prevalence. he R code is plot(y~x1).
Fig 1.1
From the figure 1.1 above, the value of fast food is represented by X1, and the value of Childhood obesity is represented by Y. This figure clearly shows that the values of fast-food have some significant impacts on the prevalence of childhood obesity prevalence.
Graph Showing the Relationship between the Behaviors of Individuals and Childhood Obesity
The graph below is plotted by the R command Plot(y~x2).
Figure 1.1
From the graph of figure 1.1, the value of X2 represents the behaviors of individuals, and y represents the value of the prevalence of childhood obesity. The distribution of the values of the behaviors of the individuals clearly shows that there is a significant impact on the behaviors of individuals on the prevalence of childhood obesity.
The goodness of Fit Test
A model was fitted appropriately on the values of fast food and the value of childhood obesity prevalence. The model is obtained from the R program using the R code of modelfit=glm(y~x1+x2) and Summary( model fit), respectively. The model obtained is as shown below:
Deviance Residuals:
Min 1Q Median 3Q Max
-0.88790 -0.27898 -0.08069 0.11489 0.92210
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.27060 0.35926 0.753 0.458
x1 0.40500 0.03951 10.250 8.35e-11 ***
x2 0.59779 0.04173 14.324 3.91e-14 ***
—
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
(Dispersion parameter for gaussian family taken to be 0.1648823)
Null deviance: 63.8667 on 29 degrees of freedom
Residual deviance: 4.4518 on 27 degrees of freedom
AIC: 35.9
Number of Fisher Scoring iterations: 2
The above model above is very significant since it has got three stars on both the variable of X1, which represents the value of the fast-food X2, which represents the value of the prevalence of childhood obesity.
Summary and Conclusion
As per the analysis carried out on the R studio, the model best fit is highly significant because of the three stars. As per this output whereby the value of the fast food is represented by X1, and the value of behaviors is represented by X2. The two variables of X1 and X2 are highly significant as per the model fit. Therefore, there is sufficient evidence to accept the null hypothesis, which states that fast food has a considerable impact on childhood obesity. On the other hand, there is also enough evidence to accept the second null hypothesis that states that the behavior of a given individual has got some significant impact on childhood obesity prevalence.
References
Bleich, S. N., Vercammen, K. A., Zatz, L. Y., Frelier, J. M., Ebbeling, C. B., & Peeters, A. (2018). Interventions to prevent global childhood overweight and obesity: a systematic review. The Lancet Diabetes & Endocrinology, 6(4), 332-346.
Hemmingsson, E. (2018). Early childhood obesity risk factors: socioeconomic adversity, family dysfunction, offspring distress, and junk food self-medication. Current obesity reports, 7(2), 204-209.
Lanas, F., Bazzano, L., Rubinstein, A., Calandrelli, M., Chen, C. S., Elorriaga, N., … & Poggio, R. (2016). Prevalence, distributions and determinants of obesity and central obesity in the Southern Cone of America. PloS one, 11(10).
Team, R. C. (2017). R: a language and environment for statistical computing. R Found. Stat. Comput. Vienna, Austria.
Appendix
The coding of the R program is as shown below:
data=read.csv(“C:/Users/Admin/Desktop/INE2002 OBESITY.csv”);data
read=attach(data)
y=c(Obesity.level)
y
x1=c(Value.of.the.fast.food)
x1
x2=c(Value.of.the.behavior)
x
mean(y)
var(y)
sd(y)
mean(x1)
var(x1)
sd(x1)
mean(x2)
var(x2)
sd(x2)
plot(y~x1)
plot(y~x2)
modelfit=glm(y~x1+x2)
summary(modelfit)