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Table 4 Logistic regressions on being malnourished with background variables

From: Risk factors for malnutrition among school-aged children: a cross-sectional study in rural Madagascar

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)