Overview
hello, so my thesis statement is: To compare the rates of depression in different smoking status among the U.S. population of adult individuals aged 18 and above. In particular, this research will examine how gender might attenuate, strengthen, or not affect the link between smoking and depression, statistically controlling for age, education level, and race/ethnicity. The general hypothesis is that U.S. adults who smoked are more likely to report depressive symptoms, controlling for age, education level, and race/ethnicity, and this relationship will be moderated by gender, with female smokers being more likely to report depressive symptoms than male smokers.The dataset that I will be using is he NHANES 2017-March 2020 Pre-pandemic dataset (attached below, I also attached the codebook as well.)
The main exposure of interest is smoking status. This variable is based on the question posed in the NHANES survey regarding lifetime smoking behavior (SMQ020), where individuals are normatively identified as smokers if they have smoked more than one hundred cigarettes: “have you smoked at least 100 cigarettes in your life?”. Participants are instructed to respond either (Yes): If they have smoked at least 100 cigarettes in their lifetime they must go to the next question; otherwise, they must go to the last question but one or (No): this element applies only if the respondent has not smoked a hundred cigarettes in his or her lifetime.
The main outcome of interest is depressive symptoms. In the NHANES dataset, depression is asssessed using the PHQ-9 survey and scale, which is designed to diagnose and evaluate the severity of depression over the past two weeks. The PHQ-9 consists of nine questions about the presence and frequency of depressive symptoms, such as having little interest in activities, feeling down or hopeless, feeling bad about oneself, and having difficulty concentrating, etc. Responses are scored on a scale from 0 ("not at all") to 3 ("nearly every day").18 To determine depression status, the scores for all nine questions are summed, resulting in a total score ranging from 0 to 27, with scores categorized as follows: 0–4: Minimal depression, 5–9: Mild depression, 10–14: Moderate depression, 15–19: Moderately severe depression and 20–27: Severe depression. It is important to mention that individuals with a PHQ-9 score below 10 are classified as not having depression, while those with a score of 10 or higher are categorized as having depression.18 How are you using the PHQ-9 score in YOUR study? Need to be clear.
I am wondering what kind of data analysis method should I using to examine this thesis statement? Cross-sectional regression? Or what? I am confused.
Thank you.