## 3 Results and Discussion
### The Effect of Health Behavior and Eating Habits on the Dyslipidemia Prevalence
Regarding the health behavior characteristics, the alcohol intake frequency and aerobic exercise frequency were found to have statistically significant effects, and in terms of eating habits, the breakfast frequency and dining out frequency were found to be significant factors in terms of the presence or absence of dyslipidemia. \begin{table}
\begin{tabular}{l c c c c c c c} \hline \hline
**Variables** & **Coef** & **Std Err** & **z** & **\(p\) \(>\) \(\mid\)z\(\mid\)** & **[0.025 (CI)** & **0.975 (CI)** & **Odds Ratio** \\ \hline Age & 0.4732 & 0.045 & 10.629 & 0.000 *** & 0.386 & 0.560 & 1.605178 \\ Gender & \(-\)0.1400 & 0.081 & \(-\)1.724 & 0.085 & \(-\)0.299 & 0.019 & 0.869377 \\ Marital Status & \(-\)1.9933 & 0.188 & \(-\)10.586 & 0.000 *** & \(-\)2.362 & \(-\)1.624 & 0.136242 \\ Subjective health status & 0.3594 & 0.049 & 7.376 & 0.000 *** & 0.264 & 0.455 & 1.432420 \\ Drinking alcohol & \(-\)0.1432 & 0.026 & \(-\)5.588 & 0.000 *** & \(-\)0.193 & \(-\)0.093 & 0.866616 \\ Smoking & \(-\)0.1478 & 0.083 & \(-\)1.776 & 0.076 & \(-\)0.311 & 0.015 & 0.862626 \\ Stress perception & 0.0687 & 0.052 & 1.311 & 0.190 & \(-\)0.034 & 0.171 & 1.071074 \\ BMI & 0.3900 & 0.059 & 6.647 & 0.000 *** & 0.275 & 0.505 & 1.477005 \\ Family history & 0.3741 & 0.072 & 5.231 & 0.000 *** & 0.234 & 0.514 & 1.453676 \\ Breakfast frequency & \(-\)0.1305 & 0.034 & \(-\)3.839 & 0.000 *** & \(-\)0.197 & \(-\)0.064 & 0.877618 \\ Lunch frequency & \(-\)0.0807 & 0.058 & \(-\)1.392 & 0.164 & \(-\)0.194 & 0.033 & 0.922498 \\ Dinner frequency & \(-\)0.1578 & 0.084 & \(-\)1.874 & 0.061 & \(-\)0.323 & 0.007 & 0.853980 \\ Dining out & \(-\)0.1008 & 0.031 & \(-\)3.295 & 0.001 *** & \(-\)0.161 & \(-\)0.041 & 0.904153 \\ High-intensity activity & \(-\)0.0934 & 0.316 & \(-\)0.296 & 0.767 & \(-\)0.712 & 0.525 & 0.910874 \\ Medium-intensity activity & \(-\)0.1323 & 0.123 & \(-\)1.071 & 0.284 & \(-\)0.374 & 0.110 & 0.876100 \\ Aerobic exercise & \(-\)0.2139 & 0.070 & \(-\)3.055 & 0.002 *** & \(-\)0.351 & \(-\)0.077 & 0.807455 \\ Strength training days & 0.0185 & 0.043 & 0.428 & 0.668 & \(-\)0.066 & 0.103 & 1.018680 \\ Walking days & \(-\)0.0346 & 0.048 & \(-\)0.717 & 0.473 & \(-\)0.129 & 0.060 & 0.965952 \\ Walking duration & 0.0406 & 0.047 & 0.866 & 0.387 & \(-\)0.051 & 0.132 & 1.041410 \\ \hline \hline \end{tabular}
\begin{tabular}{l c c c c c c} \hline \hline CI = confidence interval; * \(p<0.05\), ** \(p<0.01\), *** \(p<0.001\).  
\end{table} 
Table 4: Logistic regression. Figure 2: Correlation analysis between independent variables (health behavior). In Table 4, coef is the logit function coefficient of each independent variable and is the log (odds ratio) value (Equation (1)). The closer this value is to 0, the less influence it has on the dependent variable, and the further it is from 0, the greater influence it has on the dependent variable. The odds ratio is the probability of an event occurring divided by the probability of it not occurring. In this study, the presence or absence of dyslipidemia is the dependent variable, so the ratio is of the number of people with risk factors for dyslipidemia to the number of people without risk factors for dyslipidemia. \[\log\left(odds\right)=\log\left(\frac{p}{1-p}\right)=\beta_{0}+ \beta_{1}X_{1}+\ldots+\beta_{n}X_{n},\;\;P(y=1|X)=p=\frac{e^{\beta_{0}+\beta_{1 }X_{1}+\ldots+\beta_{n}X_{n}}}{1+e^{\beta_{0}+\beta_{1}X_{1}+\ldots+\beta_{n}X _{n}}} \tag{1}\] \[\beta_{n}\;:\;\text{when}\;X_{n}\;\text{increases by}\;1,\;\text{the change in the logit value}\] \[\text{e}^{\beta_{n}}\;:\;\text{when}\;X_{n}\;\text{increases by}\;1,\;\text{the change in the $e^{\text{logit}}=$ odds value}\]  
Equation (1) shows the calculation formulas for the coefficients and odds ratio. Since the odds ratio indicates the presence or absence of dyslipidemia, the logit function is a conversion function that takes the log function of the odds ratio. In Equation (1), the influence of the independent variable can be confirmed with the beta value.