Comparison Of Wallets And Waistline

1266 Words 6 Pages
Of Wallets and Waistlines: A relationship between body mass index and annual income
In our society today, there is a common trend is able to be seen across the United States, the expansion of the American waistline. As waistlines increase so does the prevalence of people becoming overweight or obese. Obesity has a major public health concern in the United States as almost two-thirds of the population has become obese (Marks, 2004). Someone is considered overweight if their BMI is within the range of 25 to 30 (Defining, 2016). In regards to someone being obese, there are three different classifications, class 1, class 2 and class 3 obese. If someone has a BMI within 30 to 34.99, they care considered to be class 1 obese (Defining,
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The surveys were collected from participants in January 2009 until December 2010. The qualifying participants then had personal interviews, physical examinations, laboratory tests, nutritional assessments and DNA repositories performed on them (Summary, 2015). The information gathered from these tests and examinations were compiled to form the database that was used for this experiment. The main variables utilized for this experiment were the body mass index, or BMI, and income levels of the participants.
The study design of this experiment was a cross sectional study. The relationship between diseases and exposures are able to be assessed for one set moment in time between January 2009 and December 2010. The income levels and BMI’s were used to determine the prevalence of obesity during this time frame. In order to investigate the potential relationship between the BMI’s and income levels, a one-way ANOVA test was conducted. An ANOVA test is a statistical technique that is used to explore variations in mean values within or between groups to see if they are the
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Due to 0 being lower than the set p-value of 0.5, it can be said that there is no difference between the mean values of the BMI’s and income levels. This also means that BMI’s are directly proportional to income levels. From both table one and table two, it can be seen that the mean BMI for each income level varies by only 0.3 kilograms per meters squared, which
With every experiment that is done, there is always a chance of limitations occurring. One limitation that occurred, which may have affected the results was the removal of 931 of the surveys. This could have affected the results by allowing one group to skew the results from having a larger number of people fall into one income level compared to the rest. Another limitation could be that the ANOVA test only shows that at least one group is different from the others that were under analysis and not how many or which one(s) truly are (Davies). The variances of each group could have caused additional limitations to this experiment was well. After reviewing the results of the test, the variances were not as similar as they should have

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