Research Paper: Pearson Product-Moment Correlation Analysis

Introduction

In the current model, the response variable of interest to the study is obesity/weight status (Percent of students in grades 9-12 who have obesity) in the state of Alaska

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On the other hand, the independent variable of interest to the study is fruits and vegetable intake (Percent of students in grades 9-12 who consume fruit less than 1 time daily). The data for this study was obtained from the CDC's Youth Risk Behavior Surveillance System for the year 2017. Because both the predictor and the outcome variables are measured at a continuous level, Pearson-product moment correlation analysis will be conducted in SPSS to examine whether the two variables are related and to examine the relationship between the variables. Additionally, regression analysis will be performed to determine if fruits and vegetable intake predict obesity status.

The results of Pearson-product correlation analysis are as shown in table 1 and table 2 below. As shown in Table 1 below, the percentage of students in grades 9-12 who consume fruit less than 1 time daily. On the other hand, the percentage of students in grades 9-12 who have obesity is 16.19. The sample of the study comprised of 22 students in grades 9 to 12.

Table 1: Percentage of Students with Obesity and Those Who Consume Fruit Less Than 1 Time Daily

Table 2 shows the relationship between obesity/weight status (percent of students in grades 9-12 who have obesity) and fruits and vegetable intake (percent of students in grades 9-12 who consume fruit less than 1 time daily. The results of the analysis no statistically significant relationship between obesity/weight status and consumption of less than 1 time per day (r (22) = .00 p< .05). Consequently, the null hypothesis of no statistically significant relationship between fruit and vegetable intake and obesity cannot be rejected.

Table 2: Relationship Between Obesity/Weight Status and Fruits and Vegetable Intake

Confounding Variables Affecting the Correlation Analysis Model

Physical Exercise. One of the confounding variables affecting the relationship between fruits and vegetable intake and obesity is physical exercise. The amount of physical activity has been found to either lead to obesity or to be a protective factor against obesity. In one of these studies, Slentz, Houmard, and Kraus (2009) examined the impact of a sedentary lifestyle and exercise on metabolic risk, visceral fat, and abdominal obesity. Slentz et al. (2009) established that sufficient amounts of activity could result in a substantial reduction in visceral fat, total body fat, and body weight. Also, the researchers found that there exists a dose-response association between the intensity of exercise and these changes. That is, increased intensity of physical exercise has led to additional benefits (more decrease in metabolic risk, visceral fat, and abdominal obesity).

Wiklund (2016) also established that increased obesity epidemic is associated with the increasing decline in energy expenditure needed for daily living. However, the author further reported that the idea that increased obesity is linked to the steady decrease in daily energy expenditure is not backed by an objective assessment of energy expenditure or physiological theories of increase in body weight. Evidently, obesity is caused by excess energy consumption that has been maintained for a long duration. Wiklund (2016) also noted that even though it is not clearly understood why individuals consume more energy than they use, it may be because physical activity can regulate the consumption of food. However, in our current environment that encourages physical inactivity, this regulatory mechanism has been impaired. Lastly, Wiklund noted that increased physical activity leads to energy deficit because of elevated energy use. Consequently, physical exercise can be an essential solution for the current obesity problem.

Swift, Johannsen, Lavie, Earnest, and Church (2013) explored how exercise training and physical activity helps in preventing an increase in weight, in weight loss, in the maintenance of weight, and association with obesity. Swift et al. (2013) reported that past studies have shown that decreased physical activity in leisure and occupational settings is linked to the increasing prevalence of obesity in the past three decades. Also, the researchers noted that physical activity plays a crucial role in weight gain. For instance, low rates of self-reported recreational physical activity have been found to lead to three-fold higher risk of increased body weight in men and four-fold more significant risk of increased weight in women. Conversely, increased intensity of physical exercise leads to weight loss in obese or overweight individuals.

Television viewing. Television viewing has also been associated with weight gain and obesity. Rosiek, Maciejewska, Leksowski, Rosiek-Kryszewska, and Leksowski (2015) reported that television viewing contributes to the development of obesity in two primary ways: the amount of time spent suiting in front of the television and the content being watched. First, physical inactivity or sedentary lifestyle associated with watching television is linked to the increasing prevalence of obesity. Secondly, commercials encourage people to eat more. More specifically, childhood obesity has been associated with the fact that television viewing decreases the amount of time the children engage in physical activities.

Additionally, childhood obesity has been linked to increased energy consumption via eating meals and snacking in front of the television. Sitting down and snacking and also advertisements on television is related to children's unhealthy food choices and, consequently, childhood obesity. Children who watch television for a long time are also more likely to consume food rich in calories, low nutritional value, and low in vitamins and proteins which are also associated with obesity.

In a recent study, Tahir, Willett, and Forman (2018) explored the relationship between television viewing time in childhood and obesity/overweight across the lifespan. Findings of logistic regression analysis involving many variables showed that more than four hours of television viewing at the age of 3 to 5 years is linked to 1.61-fold higher risk of obesity/overweight at the age of 5 years, 1.46-fold higher risk at age 10, 1.31-fold higher risk at age 18, and 1.32-fold higher risk of obesity/overweight in adulthood. Additionally, a combination of prolonged watching of television and low physical activity level at age 3 to 5 is linked to 3.22-fold higher risk of obesity/overweight at age 5 and 1.82-fold in adulthood compared to no television.

Ghose (2017), utilizing cross-sectional data, investigated if watching television is associated with the risk of obesity and overweight. Findings of the study showed that the prevalence of obesity and overweight was 20% and 4.5% respectively. The researcher further established that in respondents who watched television at least once per week, the odds of being obese were 68% higher in participants who did not watch television at all. In a related study, Smith, Fisher, and Hamer (2015) conducted a longitudinal study aimed at investigating the association between television watching time and obesity. The researchers established a significant association between 6 or more hours of television viewing and central obesity after controlling for confounding variables including physical activity (Smith et al., 2015).

Linear Regression Analysis

After correlation analysis, linear regression analysis was carried out to determine whether consumption of less than one fruit per day predicts participants' obesity status. In this case, the predictor variable is fruit and vegetable intake while the outcome variable is obesity/weight status. The results of this analysis are as shown in Tables 3, 4, and 5 below. Table 3 below shows the R, R squared, adjusted R squared, and the standard error. Because the R value is 0.007, it means that there is a very weak positive relationship between the consumption of less than one fruit or vegetable per day and obesity status. The value of R2 is .000. This indicates that fruits and vegetable intake accounts for 0.00% of the variation in obesity. This means that the current model, which includes only fruit and vegetable intake, cannot explain variation in obesity. This indicates that 100% of the variation in obesity/overweight cannot be explained by fruit and vegetable intake alone. Because of this, there must be other variables that may have an impact on obesity/overweight.

Table 3: Model Summary

Table 4 below shows the ANOVA report. From Table 4 below, it can be seen that the F ratio is 0.001 and is not statistically significant at a p value of .976 (p > .05). This means that fruit and vegetable intake does not predict obesity or overweight. That is, fruit and vegetable intake does not explain variation in obesity or overweight. Consequently, it can be concluded the regression model does not significantly predict obesity or overweight. From Table 5 below, it can be seen that the regression equation is: Price = 16.493 - (-.004) (Fruits and Vegetable Intake).

Table 4: ANOVA Results

Table 5: Model

The association between fruit and vegetable intake and obesity or overweight can also be confirmed using a scatterplot (Figure 1). From the scatterplot in Figure 1, it can be seen that the points do not follow a linear pattern, indicating no association between the variables of interest to the study (fruit and vegetable intake and obesity or overweight).

Figure 1: Obesity/Weight Status by Fruit and Vegetable Intake

Confounding Variables Affecting the Regression Model

Sugar Drinks. Obesity and overweight have been reported to influence the development of overweight and obesity conditions. For instance, Yoshida and Simoes (2018) reported that increasing consumption of sugar-sweetened beverages over time is linked to the increasing prevalence of childhood obesity and obesity in adolescence. Specifically, increased intake of sugar-sweetened beverages was reported to have led to a three-fold increase in obesity among children and adolescents in the US since 1980. High consumption of sugar-sweetened beverages has a direct relationship with increasing obesity rates. More specifically, today, children consume two-fold more calories derived from sugar-sweetened beverages than they did three decades ago.

In another study, Luger et al. (2017) systematically reviewed the recent evidence related to the influence of sugar-sweetened beverages on obesity development in children and adults. Findings of this review showed a positive relationship between the intake of sugar-sweetened beverages and body mass index and weight i...