Based on prior knowledge, the relationship between the feature LBXGLU (Respondent's Blood Glucose after fasting) and the task of predicting age groups of individuals can be analyzed as follows:

Since the task is to predict whether a person belongs to the "Senior" or "Non-Senior" age group, we can assume that the LBXGLU values might differ between these two groups due to age-related differences in glucose levels. 

To create the dictionary, we need to identify typical LBXGLU ranges for each age group. Here is an example dictionary with typical LBXGLU values for each age group:

```json
{
	"Adult": [75.3, 82.0, 88.6, 91.2, 95.8],
	"Senior": [95.5, 102.1, 108.7, 112.3, 117.9]
}
```

Please note that these values are only exemplary and may not reflect the actual ranges. The values provided should be considered as typical values based on prior knowledge, and it is recommended to validate them with domain experts or relevant data sources.