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Table 1 Variables used to build Models

From: Multiobjective grammar-based genetic programming applied to the study of asthma and allergy epidemiology

Variables

Type

Freq %

N=1046

Target variables

IgE (positives)

Boolean

38.6%

SPT(positives)

Boolean

30.3%

Asthma (positives)

Boolean

22.9%

 

Input variables

Gender (males)

Boolean

52.7%

Age

Categorical

 

4 and 5

 

35.9%

6 and 7

 

35.1%

8 to 11

 

29.0%

Parental asthma (presence)

Boolean

12.6%

HSV (positives)

Boolean

54.9%

HZV (positives)

Boolean

45.8%

EBV (positives)

Boolean

88.4%

HAV (positives)

Boolean

16.7%

T. gondii (positives)

Boolean

18.4%

H. pylori (positives)

Boolean

27.6%

A. lumbricoides (positives)

Boolean

16.2%

T. trichiura (positives)

Boolean

11.2%

Sibling number

Categorical

 

none

 

18.9%

1

 

35.2%

2

 

24.0%

3 or more

 

21.9%

Daycare ever (yes)

Boolean

15.4%

Smoke at home (presence)

Boolean

27.1%

Sewage disposal system (presence)

Boolean

83.5%

Change bed linen ≥ 1 per week

Boolean

45.0%

Cat at home (presence)

Boolean

17.6%

Dog at home (presence)

Boolean

39.8%

Mold/moisture at home (presence)

Boolean

68.6%

Piped water system (presence)

Boolean

91.9%

Paving of the street (absence)

Boolean

35.1%

Fly at home (presence)

Boolean

51.5%

Mother Psychological disorder

  

(suspect)

Boolean

37.2%

Dietary patterns 1 to 4

Categorical

Split by tertiles

Daily calories (Kcalmean(sd))

Numerical

2210(929)

BMI

Categorical

 

Overweight / Obesity

 

12.2%

Eutrophic

 

75.1%

Slimness

 

12.7%

GNI

Categorical

Split by tertiles