Depression is a major health problem in the United States, impacting individuals in emotionally and physically damaging ways. Several studies have utilized large datasets to identify risk factors that contribute to the epidemic, as well as methods to alleviate depressive symptoms. Past studies have identified folate intake as a promising method of alleviating depressive symptoms, with reported associations between low levels of folate intake and severe depressive symptoms. While research has considered the role of physical activity in addressing depression, few studies have accounted for all three variables, namely physical activity levels, folate intake, and depressive symptoms. The current study aims to address the gap in the literature by examining the relationship among the three variables of interest, as well as account for other possible predictors of depression. Specifically, my hypothesis comprises of the following: Physical activity levels and food folate significantly predict depressive symptoms.
The study will utilize data from years 2007 to 2012, obtained through the National Health and Nutrition Examination Survey (NHANES). NHANES documents and articles examining our variables of interest have provided insight on how to best code and measure them for data analysis. Depression, for example, was measured via the Patient Health Questionnaire (PHQ-9), which is a tool used for measuring the severity of mental health disorders, and participants were asked to rate their depressive symptoms on a scale ranging from 0, meaning “Not at all,” to 3, meaning “Nearly every day.” Composite scores will be totaled, ranging from 0 to 27 for each individual. Physical activity will comprise of the reported minutes of activities that are of vigorous intensity and moderate intensity. Finally, food folate will be reported in micrograms. Measures for the additional predictors have yet to be determined, and cut-off points will be derived from literature.
As far as exploratory analyses, the study will utilize correlations and frequencies. Ideally, the study aims for a type of regression; in this case, a multiple logistic regression may work, with depression being the nominal dependent variable and the other predictors as the independent variables/predictors. The study will apply sample weights used by NHANES, and I may run chi-square tests with the categorical variables if not conduct a regression. Preliminary navigation of the datasets has outlined steps necessary to prepare the data; for example, I will need to address missing data in order to create accurate composite scores for specific variables (i.e., depression) and run tests.
