Based on my prior knowledge, I can analyze the relationship between the feature LBXIN (Respondent's Blood Insulin Levels) and the target task of predicting the person's age group (Senior or non-senior).

Typically, insulin levels tend to increase with age. Therefore, it is expected that the LBXIN values would be higher for the senior age group compared to the non-senior age group.

However, it is important to note that the exact ranges of LBXIN values for each age group might vary depending on the specific dataset and population being analyzed. Consequently, it is advisable to use data from the given record to determine the appropriate ranges of values.

To create the desired dictionary, let's assume the following approximate ranges for the target age groups:
- Adult age group: LBXIN values below 100 units
- Senior age group: LBXIN values above or equal to 100 units

Based on this, we can generate a dictionary as follows:

```json
{
	"Adult": [75.6, 82.3, 93.1, 87.5, 71.2],
	"Senior": [102.8, 120.5, 98.2, 111.0, 108.6]
}
```

Please note that these values are just examples and should be replaced with actual LBXIN values from the given record.