Research Article

Tweedie Model for Predicting Factors Associated with Distance Traveled to Access Inpatient Services in Kenya

Table 3

Exploratory data analysis of the covariates considered in the analysis.

VariableNumberPercentage

Days admitted
 1–5 days25857.21
 6–20 days12026.61
 21 days and above7316.19
Residence
 Rural29966.30
 Urban15233.70
Satisfied
 Yes40289.14
 No4910.86
Wealth quintiles
 Poorest13028.82
 Poor11124.61
 Middle10623.50
 Rich6614.63
 Richest388.43
Age group
15 and 6514031.04
 15–24204.43
 25–5422850.55
 55–646313.97
Household size group
 1–3 members (small)17939.69
 4–6 members (medium)18641.24
 7 + members (large)8619.07
School category
 Never went to school14031.04
 Lower education21647.89
 Intermediate education8919.73
 Higher education61.33
Employment category
 Employed30768.07
 Not employed14431.93
Access to health insurance
 Yes5812.86
 No39387.14
Had cash
 Yes14832.82
 No30367.18
Paid category
 1–3000 KES (low)19042.13
 3001–10,000 KES (medium)13730.38
 Above 10,0001 (high)12427.49
Facility admitted
 Levels 5 and 65712.63
 Level 435678.93
 Level 3388.42