Skip to main content

Table 1 Features identified for low birth weight classification

From: Machine learning algorithms for predicting low birth weight in Ethiopia

No.

Variable name

Variable label

1

Residence

Type of place of residence (Urban/ Rural)

2

Education

educational level (no education/primary/secondary or higher)

3

Iron

Taking iron pills, sprinkles or syrup (No/ Yes)

4

Wealth

wealth index combined (Poorest/poorer/middle/richer/richest)

5

BMI

Body mass index (numerical)

6

Agem

Women's age in years (numerical)

7

Anaemia

Anemia level (severe/ moderate /mild/not anemic)

8

Orderbirth

Birth order number (numerical)

9

Twin

The child is a twin (single/multiple)

10

Gender

Sex of child (male/female)

11

Visits

Number of antenatal visits during pregnancy (numerical)

12

Delivery

Delivery by caesarean section (no/yes)

13

Smoking

Smokes cigarettes (no/yes)

14

Insurance

Covered by health insurance (no/yes)

15

Occuptiion

Occupation (No/Yes)

16

Sex of child

Sex of child (Male/Female)

17

Ethnicity

Ethnicity (Amahara/Oromo/Tigrie/Somali/Guragie/Others

18

Parity

Parity lab (1/2/3/4/5 +)

19

BTI

Birth Interval (Numeric)

20

Marital

Current marital status

21

Religion

Religion(orthodox/muslim/protestant/others)

22

Region

Region (11 categories)

23

Desirability

Desirability of the pregnancy (then/later/no more)

24

Sign in ANC

Sign Complexity during Antenatal care visit(s) (No/Yes)

25

Nutritional

Nutritional counseling (No/Yes)