Based on prior knowledge, let's assume that the age group of seniors is typically considered to be 60 years and above. 

Analyzing the relationship between the feature DIQ010 and the target age group, we can make some assumptions:

1. DIQ010 value of 1 might represent a non-diabetic individual (as done traditionally in many studies).
2. DIQ010 value of 2 might represent a diabetic individual.

Considering this information, let's analyze how DIQ010 values are distributed for both the 'Adult' and 'Senior' age groups.

Dictionary:
```json
{
    "Adult": [1.0, 1.0, 1.0, 2.0, 1.0], 
    "Senior": [1.0, 1.0, 2.0, 1.0, 2.0]
}
```
The listed DIQ010 values are just examples and might not give a complete picture of the relationship between the feature and the target variable. Further analysis and exploration of the dataset would be necessary to obtain more accurate information.