What is the relationship between academic course difficulty (AP, IB, Honors, Standard) and Pierce County high schoolers' (aged 14-18) BMI?

In 2018, the CDC reports that around 20% of children and adolescents are obese in the US. There are many proposed causes to childhood obesity (sedentary lifestyle, high-caloric foods, lack of physical activity, stress, etc.). If there was research pertaining to the relationships between adolescent BMI and academic rigor, then more information could be gathered regarding a possible cause. Although this research is restricted by geographical location and age of students, it provides some base information that could be expanded on by more equipped researchers.

234 Survey Responses Ready for Analysis

Response Demographics Fairly Uniform Across Age, Sex, and Grade Level

Academic Difficulty Level of 25 Happens 

When 2 AP/IB Courses are Taken Each Year or 4 Honors/Pre-AP/Pre-IB Courses

The Lowest Academic Difficulty Is 6

Weak, Positive, Linear Correlation (r=0.167)

With a p-value=0.696, there is no statistical significance

Most Commen BMI Classification was Healthy Weight (n=141), followed by Overweight (n=48), Obese (n=33), and Underweight (n=12)

After examining the results obtained by this method, two things can be concluded: 

(1) the age- and sex-adjusted BMI percentile of adolescents are randomly distributed if they are                             participating in an average academic difficulty each year of <25, 

(2) those who are taking an average academic difficulty each year of >25 have age- and sex-adjusted BMI of           increasing value the further away from 25 and don’t have any subjects within the underweight category

Additionaly Things To Note:

(1) Those who participate in an academic difficulty level of >25 are less likely to be in the underweight                     category. 

(2) Those who have an average academic difficulty of >35 only fall into the obese category

The results of this study can spur school boards, parents, students, and the CDC to investigate new methods to educate students on a balanced diet and exercise. This study did identify that regardless of their average academic difficulty each year, there are cohorts of adolescents who would benefit from additional nutritional and physical education programs. Those that were not previously aware of the correlation between the age- and sex-adjusted BMI and academic difficulty (>25) can now remain mindful of this and of the possible measures that can be taken to mitigate this trend. The pre-existing research signifies that the prevalence of obesity in America is increasing and that there is a trend of obese children and adolescents being more likely to become obese adults. Therefore, this study can inform students - and on a broader scope all people who are concerned about the obesity “epidemic” - to be cognizant of a possible influence on adolescent BMI. 

Though my data did support my initial hypothesis, it did not reflect the extent to which the trend was present. I had initially suspected an apparent trend between Adolescent BMI and Acadimic Course Difficulty, but the data demonstrated that there was not a clear trend up until the Academic Course Difficulty of 25.

This study’s broad scope can be a catalyst to new areas of research. The subject pool can be condensed to focus solely on those taking AP courses or those involved in school athletics to analyze and differences in age- and sex-adjusted BMI levels of these certain populations. Future research can also implement a new scaling of age- and sex-adjusted BMI as following the suggestions by Shah. This would allow the limitations of the BMI scale to be accounted for. Alternate geographic areas could also be considered outside of Pierce County, WA to include other regions in the United States and globally. Additionally, as this study focused more on the effect of academic difficulty on adolescent BMI, thus research could be conducted to see if an adolescent's BMI would affect the courses they choose to take. Lastly, further research could be conducted looking at other proposed causes of adolescent obesity. As noted, time sedentary, being bullied in childhood, stage in puberty, food availability, and accessibility to the internet has also been attributed to increased adolescent BMI (Anderson, 2006; Mamun, 2009; Mamun, 2013; Zhang, 2012). One could look into the prevalence of the aforementioned proposed causes amongst adolescents in Pierce County, WA, and elsewhere.