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Table 4 Multivariate multiple logistic regression analysis on the determinants of maternal, child and reproductive services

From: Impact of a bottom-up community engagement intervention on maternal and child health services utilization in Ghana: a cluster randomised trial

  Baseline data (2012) Follow-up data (2014)
Dependent variables (Model 1) Dependent variables (Model 2)
SVDs Immunizations Condom utilization SVDs Immunizations Condom utilization
Independent variables Coef.[(95% CI] Coef.[(95% CI] Coef.[(95% CI] Coef.[(95% CI] Coef.[(95% CI] Coef.[(95% CI]
Intervention status
 CEI −1.83[−9.40 5.74] −44.87[− 176.8 87.07] −2.75[−90.06 4.58] −8.90[− 87.72 9.91] 519.5[−599.5 1638.5] 72.16[− 143.6 287.10]
 No CEI Ref Ref Ref Ref Ref Ref
Ownership
 Private −7.31[−15.70 1.08]* −167.58[−313.8−21.39]+ − 182.5[− 279.2−85.7]* 15.61[− 120.6 51.8] − 558.4[− 2492.4 375.5] − 78.33[− 451.3 294.6]
 Public Ref Ref Ref Ref Ref Ref
Location
 Rural 5.97[−1.95 13.89] -75.89[-213.9 62.13] −6.0[−97.4 85.3] 9.20[−83.81 102.2] 380.2[− 940.4 1700.8] 48.11[−206.6 302.8]
 Urban Ref Ref Ref Ref Ref Ref
Region
 GAR −10.36[−18.80−1.93]+ −231.18[−378.2−84.19]+ −66.4[− 163.7 30.9] −40.17[− 240.0 159.7] 608.6[− 2228.9 3446.1] 101.8[− 445.4 648.9]
 WR Ref Ref Ref Ref Ref Ref
Distance to nearest referral FH
 30–60 min 0.18[−0.00 0.37]* 1.01[−2.21 4.24] 0.76[−1.38 2.89] .264 [1.88 2.41] 2.91[−27.58 33.41] −0.21[−6.09 5.67]
  > 60 min Ref Ref Ref Ref Ref Ref
Income group of clients
 Low income 13.55 [4.56 22.54]+ 148.1[−8.56 304.8]* 45.76[−57.95 149.5] 40.8[− 155.4 237.0] −692.9[− 3478.7 2092.8] −71.78[− 608.10 465.4]
 High income group Ref Ref Ref Ref Ref Ref
 Staff capacity −.007[−0.20 0.19] − 0.50[−3.88 2.88] −0.50[−2.74 1.73] − 0.77[−4.99 3.45] −4.82[−64.69 55.05] − 0.86[−12.40 10.69]
  1. Source: Field Data Greater Accra and Western Regions (2014); Legend: SVDs (Spontaneous vaginal deliveries); HF (Health Facility); *p < 0.05; +p < 0.01
  2. Model 1 Equation: Outcome variable 1 (RMSE = 14.16; “R-sq” = 0.36; F = 4.35; p = 0.0007); Outcome variable 2 (RMSE = 246.70; “R-sq” = 0.28; F = 2.97; p = 0.01047); Outcome variable 3 (RMSE = 163.28; “R-sq” = 0.28; F = 2.93; p = 0.0114)
  3. Model 2 Equation: Outcome variable 1 (RMSE = 40.30; “R-sq” = 0.32; F = 0.27; p = 0.9355); Outcome variable 2 (RMSE = 572.15; “R-sq” = 0.44; F = 0.45; p = 0.8327); Outcome variable 3 (RMSE = 110.34; “R-sq” = 0.31; F = .256; p = 0.9439)