## 3 Results and Discussion
### The Effect of Health Behavior and Eating Habits on the Dyslipidemia Prevalence  
In this study, a logistic regression analysis was performed to determine the influence on the dyslipidemia prevalence. The logistic regression model uses the maximum likelihood estimation method, so it is an analysis method suitable for a sufficiently large sample such as the subject of this study to obtain a reliable estimate. The logistic regression model does not require assumptions on normality and homoscedasticity because the relationship between the dependent variable and the independent variables is identified as nonlinear, but nonlinearity between the independent variables must be assumed. Since the linear relationship between two variables is expressed in the form of a straight line, the larger the correlation, the stronger the linearity between the two variables. As a result of analyzing the correlation between the independent variables to improve the accuracy of the prediction model, the variable that was most relatively highly correlated with the dyslipidemia prevalence regarding the general characteristics of the subjects was found to be age (Figure 1). \begin{table}
\begin{tabular}{l c c c c c c c c c} \hline \hline
**Variables and Categories** & **19-34 (\%)** & **\(p\)** & **35-49 (\%)** & **\(p\)** & **50-64 (\%)** & **\(p\)** & \(\geq\)65 (\%)** & **\(p\)** & **Rao-Scott \(\chi^{2}\)** \\ \hline Breakfast Frequency & & & & & & & & & 215.485 \\ Almost Never & 838 (36.3) & \(<\)0.001 & 825 (24.8) & \(<\)0.001 & 436 (12.3) & \(<\)0.001 & 104 (3.6) & \(<\)0.001 & (\(<\)0.001) \\
1–2 times a week & 541 (23.4) & & 609 (18.3) & & 288 (8.2) & & 64 (2.2) & & \\
3–4 times a week & 352 (15.2) & & 440 (13.2) & & 283 (8.0) & & 66 (2.3) & & \\
5–7 times a week & 579 (25.1) & & 1456 (43.7) & & 2526 (71.5) & & 2621 (91.8) & & \\ \hline Lunch Frequency & & & & & & & & 7.988 \\ Almost Never & 37 (1.6) & \(<\)0.001 & 61 (1.8) & 0.055 & 82 (2.3) & \(<\)0.001 & 90 (3.2) & \(<\)0.001 & (\(<\)0.001) \\
1–2 times a week & 66 (2.9) & & 97 (2.9) & & 75 (2.1) & & 50 (1.8) & & \\
3–4 times a week & 191 (8.3) & & 227 (6.8) & & 149 (4.2) & & 99 (3.5) & & \\
5–7 times a week & 2016 (87.3) & & 2945 (88.4) & & 3227 (91.3) & & 2616 (91.6) & & \\ \hline Dinner Frequency & & & & & & & & 18.498 \\ Almost Never & 21 (0.9) & \(<\)0.001 & 27 (0.8) & 0.036 & 25 (0.7) & \(<\)0.001 & 21 (0.7) & \(<\)0.001 & (\(<\)0.001) \\
1–2 times a week & 55 (2.4) & & 89 (2.7) & & 65 (1.8) & & 30 (1.1) & & \\
3–4 times a week & 271 (11.7) & & 293 (8.8) & & 169 (4.8) & & 68 (2.4) & & \\
5–7 times a week & 1963 (85.0) & & 2921 (87.7) & & 3274 (92.7) & & 2736 (95.8) & & \\ \hline Dining out & & & & & & & & 162.134 \\ Almost never & 758 (32.8) & \(<\)0.001 & 1207 (36.2) & \(<\)0.001 & 1641 (46.4) & \(<\)0.001 & 1594 (55.8) & \(<\)0.001 & (\(<\)0.001) \\
1–3 times a month & 372 (16.1) & & 396 (11.9) & & 379 (10.7) & & 253 (8.9) & & \\
1–4 times a week & 758 (32.8) & & 874 (26.2) & & 726 (20.5) & & 433 (15.2) & & \\
5–6 times a week & 345 (14.9) & & 639 (19.2) & & 512 (14.5) & & 348 (12.2) & & \\ More than once a day & 77 (3.3) & & 214 (6.4) & & 275 (7.8) & & 227 (8.0) & & \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Differences by eating habit of the selected sample. Figure 1: Correlation analysis between independent variables (general characteristics). In addition, although the problem of multicollinearity between the variables was not specifically observed (Figure 2), the purpose of this study was to identify the relationship between the dyslipidemia prevalence and health behavior and eating habits by age, and, thus, the variables of household income and education level, which showed relatively high correlations, were excluded from the logistic regression analysis. The logistic regression analysis results (Table 4) showed that the age, marital status, subjective health perception, body mass index, and family history significantly affected the presence or absence of dyslipidemia in terms of the general characteristics.