Using simulation method and survey data to determine the relationship between BMI and risk factors in the United States

Obesity is continuously making a major impact on the public health in the United States. Obesity is a leading factor that contributes to the development of major health issue including hypertension, type 2 diabetes, coronary heart disease, asthma, and arthritis. Since the 1970’s, obesity rates have continuously risen in the United States. Currently, more than one-third of U.S. adults are obese. Body Mass Index (BMI) is a value used to link body weight to various categories to help with the classification of potential health problems. Studies have shown risk factors such as age, socioeconomic status, inactivity, and lifestyle can play a major role in the development of obesity. In the study, potential risk factors are tested to determine if a correlation is present amongst the risk factors and BMI. The data was collected from the 2013 National Health and Nutrition Exam Survey (NHANES). The sample size was 4,865 surveyed adults.  Analysis of the data will be generated consecutively using factor analysis, linear regression model, and simulation modeling in SPSS to evaluate and determine the most influential risk factor has on adult BMI. A correlation was determined and more than 75% of the survey respondents were considered overweight. The insight gained from the study helps in determining areas to target in order to improve the impact each risk factor has on BMI. Reducing the impact of risk factors will lead to a decrease in the high levels of BMI and improve the public health in the United States.