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Table 2 Regression coefficients (b), concentration index (C) and contribution of determinants to wealth-related inequality in skilled birth attendance and measles immunization, Kenya, DHS 2008/09

From: Decomposing Kenyan socio-economic inequalities in skilled birth attendance and measles immunization

  

Skilled birth attendance (N = 3506)

 

Measles immunization (N = 892)

Determinants

b

C

Overall C = 0.14% contribution

b

C

Overall C = 0.08% contribution

Wealth quintile (ref: 1)

  

39.49

  

60.20

 2

0.21

−0.38

−2.00

0.22

−0.37

−2.99

 3

0.46

0.01

0.15

0.68

0.02

0.36

 4

0.60*

0.39

5.58

1.25

0.38

15.95

 5 (richest)

1.70*

0.79

35.77

1.43

0.78

46.88

Skilled antenatal care visits (ref: No)

  

9.38

  

5.07

 1-3

1.49*

−0.11

−8.75

0.96

−0.10

−8.25

 4+

2.09*

0.14

18.13

1.00

0.14

13.32

Sex : male

-

-

-

0.01

−0.06

−0.07

Age

-

-

-

0.15*

0.01

2.99

Birth order

−0.10

−0.12

5.62

−0.37*

−0.13

32.96

Mother’s age <20

0.02

0.03

0.04

−0.31

0.00

0.05

Rural residence

−0.06

−0.18

1.08

0.65

−0.20

−18.97

Province (ref: Nairobi)

  

5.66

  

−2.50

 Central

−0.43

0.30

−1.60

0.92

0.35

4.32

 Coast

−0.10

0.07

−0.07

2.22

0.04

1.58

 Eastern

−0.03

−0.09

0.05

−0.11

−0.11

0.36

 North Eastern

0.41

−0.62

−0.81

1.69

−0.57

−4.06

 Nyanza

−0.29

−0.09

0.58

0.04

−0.03

−0.04

 Rift Valley

−1.64*

−0.11

5.92

1.38

−0.07

−5.52

 Western

−0.83

−0.13

1.59

−0.31

−0.12

0.87

Ethnic group (ref: Kikuyu)

  

4.99

  

−5.74

 Kalenijn

−0.03

−0.32

0.18

0.50

−0.31

−4.60

 Kamba

−1.80*

−0.04

0.88

1.71

0.00

−0.12

 Kisii

−1.05

−0.02

0.22

1.41

−0.03

−0.47

 Luhya

−1.48*

0.01

−0.20

1.05

0.03

1.00

 Luo

−1.24*

0.02

−0.50

0.65

0.05

1.06

 Masai

−0.27

−0.33

0.16

−1.05

−0.41

1.40

 Meru/Embu

−0.10

0.12

−0.09

1.99

−0.02

−0.40

 Mijikenda

−1.70*

−0.13

1.45

0.71

−0.21

−1.57

 Taita

−1.78

0.47

−1.07

−1.03

0.46

−1.18

 Other

−1.59*

−0.26

3.96

0.23

−0.28

−0.87

Religion (ref : Protestant)

  

−0.55

  

−0.54

 Catholic

−0.27

0.05

−0.34

0.06

0.02

0.03

 Muslim

0.49

−0.13

−0.65

0.49

−0.09

−0.66

 Other

−0.27

−0.42

0.44

−0.03

−0.46

0.09

Married

0.10

0.00

0.03

−0.27

0.00

−0.19

Mother’s education (ref : Higher)

  

20.48

  

6.54

 Secondary

−1.91*

0.44

−11.73

−0.39

0.50

−4.09

 Secondary. incomplete

−2.19*

0.14

−3.48

−0.80

0.15

−1.60

 Primary

−2.41*

0.06

−5.75

−0.96

0.05

−3.16

 Primary incomplete

−2.82*

−0.19

22.33

−0.72

−0.19

9.00

 No education

−2.92*

−0.47

19.11

−0.78

−0.42

6.39

Father’s education (ref : Higher)

  

7.71

  

21.68

 Secondary

0.06

0.23

0.42

−0.95

0.36

−14.72

 Secondary. incomplete

−0.24

0.11

−0.27

−1.30

0.00

0.05

 Primary

−0.40

−0.04

0.66

−1.42

−0.06

4.98

 Primary incomplete

−0.62

−0.24

4.02

−1.75

−0.24

18.85

 No education

−0.53

−0.54

2.88

−1.55

−0.53

12.52

Mother’s occupation (ref : Professional)

  

1.40

  

1.74

 Sales

−0.06

0.12

−0.07

−0.80

0.07

−0.68

 Agriculture

−0.13

−0.20

0.95

−0.17

−0.22

1.88

 Domestic

−0.47

0.16

−0.25

0.14

0.01

0.00

 Manual

−0.05

0.04

−0.01

0.81

0.05

0.45

 Services

0.88

0.41

0.69

0.36

0.40

0.41

 Not working

−0.10

−0.02

0.09

0.34

−0.01

−0.32

Father’s occupation (ref : Professional)

  

1.21

  

2.22

 Sales

0.48

0.01

0.06

−0.50

0.04

−0.30

 Agriculture

0.02

−0.29

−0.18

−0.40

−0.34

7.49

 Domestic

−0.32

−0.09

0.10

−0.10

−0.05

0.03

 Manual

0.38

0.10

1.33

−0.81

0.11

−4.66

 Services

0.73

−0.02

−0.03

−2.07

0.27

−0.83

 Not working

0.99

−0.33

−0.07

−4.58

−0.55

0.49

Insurance coverage

0.79

0.59

3.47

−1.05

0.58

−5.44

  1. *p-value < 0.01. Regression coefficients were computed using a multivariate logistic regression model.