16.2.13 Variable Interactions

Table 27: Variable Interactions Scoring

Characteristics	Score
Only Events (minimum of 5), Time, and Population (Residence/Service Geography or Insurance Coverage	-5
Only Events (minimum of 3), Time, and Population (Residence/Service Geo. or Insurance Coverage)	-3
Only Events (no minimum), Time, and Population (Residence/Service Geo. or Insurance Coverage)	0
Events, Time, and Population (Residence/Service Geo. or Insurance Coverage) + 1 variable	+1
Events, Time, and Population (Residence/Service Geo. or Insurance Coverage) + 2 variables	+2
Events, Time, and Population (Residence/Service Geo. or Insurance Coverage) + 3 variables	+4

These criteria specifically address the interaction of the variables in a given data presentation and require the analyst to identify dependent as opposed to independent variables. These criteria are used with respect to dependent variables. This is demonstrated in the two tables below.

Illustration A: Dependent Variables

In this example the Event (counts of Disease A) is shown for Males who are also 0-17 years old or Males who are also 18-25 years old. In this case Sex and Age are dependent because the stratification for each variable is stacked. This commonly occurs in pivot tables.

Table 28: Illustration A: Dependent Variables Example

Counts of disease A by year	Males and 0-17 years old	Males and 18-25 years old	Females and 0-17 years old	Females and 18-25 years old
Year 1	6	10	5	8
Year 2	8	14	3	20

Illustration B: Independent Variables

In this example the Event (counts of Disease A) is for Males or Females which is shown side by side to a table with ages 0-17 years old or 18-25 years old. In this case Sex and Age are independent because the stratification for each variable is not stacked. Although the two variables Sex and Age are shown in the same table, they are presented independently of each other. While you can compile the data in Example B from Example A, the reverse is not true.

Table 29: Illustration B: Independent Variables Example

Counts of disease A by year	Males	Females	0-17 years old	18-25 years old
Year 1	16	13	11	18
Year 2	22	23	11	34

These criteria are structured to have less impact if personal characteristics outside of time and geography are excluded and more impact if multiple personal characteristics are included. This provides for a subtraction of points if the only variables presented are the events (numerator), time and geography and an addition of points for including more variables in a given presentation. With respect to the subtraction of points, the score is based on the minimum value for the Events variable. For example, if the smallest value for the Events is 5 or more, then the score would be -5. However, if the smallest value for the Events is 2, then the score would be 0.

The minimum value for Events of 3 (Only Events (minimum of 3), Time, and Geography (Residence or Service)) is used as a threshold to address concern for pre-existing knowledge by users about individuals. For example, if an entity knows who one person is with disease A and the count for Events is “1” or “2”, then the entity could identify the person they know of or the person they know of plus information about the other person. The use of a minimum of 3 does not protect against two entities colluding to determine a third person.[40] For this reason, the threshold of 5 for Events is also given. The threshold of 5 is frequently used in public health reporting regarding various events.

In contrast, if additional demographic variables are added, then the risk increases significantly. For example, for Events, Time and Geography (Residence or Service) with three additional variables, a table would show how many individuals are female by age group by race for a given time period and geography. This allows for a more detailed comparison to census data and assessment of the number of individuals with a particular set of characteristics.[41] For this reason, additional points are added because of the inclusion of multiple dependent variables.