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Table 4 Binary logistic regression model for predictors of uptake of precautionary measures

From: Socio-economic characteristics of the community that determine ability to uptake precautionary measures to mitigate flood disaster in Kano Plains, Kisumu County, Kenya

Factors

Odds Ratio Estimates

95 % confidence intervals

Lower

Upper

P value

Marital status

0.718

0.537

0.96

0.0251

Have Ever Heard of flood

1.495

0.902

2.478

0.1185

Enough Action by Stakeholders

3.412

1.977

5.891

<0.0001

Construction of Wall

0.849

0.647

1.115

0.2389

Construction of Floor

0.933

0.7

1.243

0.6357

Closeness to river

0.745

0.568

0.978

0.0342

Highest Education Level

1.24

0.964

1.594

0.0935

Occupation

1.04

0.881

1.227

0.6454

Income level

1.94

1.599

2.355

<0.0001

  1. Source: Fieldwork (2014)
  2. All variables of study put together, a binary logistic regression analysis was performed to identify the most significant predictors of uptake of precautionary measures to mitigate floods. Results show the most significant predictors as stakeholder involvement (p < 0.0001); income level (p < 0.0001); marital status (p = 0.0251) and closeness of residence to river Nyando (p = 0.0342)