## 3 Results and Discussion
### Prediction of Risk Factors for Dyslipidemia Based on Health Behavior by Age
Drinking alcohol, smoking, walking days, and eating habits also appeared as significant predictors for classifying dyslipidemia. This supports the research result that the dyslipidemia prevalence increases with age [2]. The root node was classified into the 19-34, 35-49, 50-64, and 65 or older groups based on the age variable. A proportion of 70% of the samples was used for model learning. At the second level, the 19-34 and 35-49 groups were classified based on age as a classification criterion that affects whether or not dyslipidemia is diagnosed, and the 50-64 and 65 or older groups were classified based on the body mass index. At the third level and above, the 19-34 and 35-49 groups were classified as not having dyslipidemia. The actual dyslipidemia rates in the 19-34 and 35-49 groups were 16.7% and 12.8%, respectively, which were lower than those in the 50-64 and 65 or older groups. In the 50-64 and 65 or older groups, those who were underweight or had a normal BMI (obesity \(\leq\) 2.438) showed dyslipidemia according to their drinking frequency, and a poor subjective health awareness and walking frequency of less than 1 day affected the dyslipidemia classification. When the alcohol intake frequency exceeded 2-4 times a month and 2-3 times a week or less (drinking > 2.152 and drinking \(\leq\) 4.424), and lunch frequency was 3-4 times a week or more (lunch_PQ > 2.537), this combination was classified as dyslipidemia. In particular, in the 50 or older group, those who were obese and had poor health awareness were classified as having dyslipidemia, and when they were female (gender > 1.903) and had an alcohol intake frequency of 2.524 or less, dyslipidemia was predicted. We examined the combination of factors affecting dyslipidemia by age group. Figure 5 shows the results of the decision tree analysis targeting the 19-34 age group; the dyslipidemia prevalence in this group was 1% (22 people) out of 2310 people. As shown in Figure 5, a good prediction model with a relatively low impurity and no need for pre-pruning was presented. In this age group, the BMI was found to be the most important prediction factor. In cases where the BMI indicated underweight/healthy weight, dyslipidemia was classified in 2 people, but in cases where the BMI indicated obesity, it was classified in 12 people. Most of these cases were in the group that felt a lot of stress, and looking at the following separation criteria, it was found that the higher the dinner frequency, the more the dyslipidemia prevalence was affected. Figure 6 shows the results of the decision tree analysis for the 35-49 age group. The dyslipidemia prevalence in the 35-49 age group was 8.3% (278 people) out of a total of 3330 people. In this group, the most important predictor variable for the presence or absence of dyslipidemia was gender, and the next most important variable was subjective health perception. In the case of men with a \"bad\" health perception, their perceived stress and dinner frequency were found to be related to the dyslipidemia prevalence. In the case of women with a \"bad\" health perception, a higher lunch frequency predicted dyslipidemia. Figure 5: Decision tree analysis results for the 19-34 age group. Figure 6: Decision tree analysis results for the 35-49 age group. Figure 7 shows the results of the decision tree analysis of the 50-64 age group. The dyslipidemia prevalence in the 50-64 age group was 30.7% (1085 people) out of a total of 3533 people. The most important factor for dyslipidemia in this group was the subjective health perception. In cases where health was perceived as \"bad\", the second-level separation criterion was the BMI. If the BMI indicated obesity, looking at the third-level node, we can see that there were more samples predicted as having dyslipidemia (\"No\" (148 people) and \"Yes\" (165 people). In this node, dyslipidemia was predicted when the dining out frequency was 1-4 times a week or more.