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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.