# Table 4 Logistic regressions on being malnourished with background variables

Logistic regression model Adjusted OR 95% CI P-value
Logistic regression on being stunteda
v5: Seller, trader or commercial business (dummy variable for ‘Major income sources’) 2.173 1.120–4.219 0.022*
v43: Milk and milk products (dummy variable for ‘Food consumption during last 24 h’) 0.671 0.309–1.458 0.313
v45: Sweets (dummy variable for ‘Food consumption during last 24 h’) 0.616 0.382–0.994 0.047*
v47: Age [year] 1.392 1.164–1.664 < 0.001**
v48: Total number of household members [person] 1.172 1.031–1.333 0.015*
Logistic regression on being underweightb
v5: Seller, trader or commercial business (dummy variable for ‘Major income sources’) 2.654 1.339–5.261 0.005**
v25: Plastic bag (dummy variable for ‘Rice storage’) 1.923 0.962–3.844 0.064
v39: Meats (dummy variable for ‘Food consumption during last 24 h’) 0.711 0.410–1.233 0.224
v43: Milk and milk products (dummy variable for ‘Food consumption during last 24 h’) 0.725 0.321–1.634 0.437
v47: Age [year] 1.474 1.189–1.827 <  0.001**
v48: Total number of household members [person] 1.189 1.043–1.356 0.010*
v51: Household dietary diversity score (HDDS) [pt] 0.832 0.701–0.993 0.043*
Logistic regression on being thinc
v30: In open-space without cleaning (dummy variable for ‘Utensil maintenance’) 0.298 0.069–1.284 0.104
v47: Age [year] 1.348 1.092–1.663 0.005**
v48: Total number of household members [person] 1.240 1.038–1.481 0.018*
1. *P < 0.05
2. **P < 0.01
3. aThe dichotomous independent variable (i.e. stunted or not stunted)
4. bThe dichotomous independent variable (i.e. underweight or not underweight)
5. cThe dichotomous independent variable (i.e. thin or not thin)