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Table 4 Effect of intervention on childrenā€™s dehydration status

From: School water, sanitation, and hygiene (WaSH) intervention to improve malnutrition, dehydration, health literacy, and handwashing: a cluster-randomised controlled trial in Metro Manila, Philippines

Outcome

Study arm

Baseline

Endline

Effect of intervention

(95% CI)

p-value

n

%

n

%

Severe dehydration*

Control

57

74

63

80.8

Ā Ā 

Low-intensity education

55

53.4

85

81.7

0.84 (0.25, 2.84)**

0.78

Medium-intensity education

217

64.2

190

57.9

0.02 (0.01, 0.04)**

pā€‰<ā€‰0.01

High-intensity education

116

56.6

123

68.3

0.01 (0.00, 0.16)**

pā€‰<ā€‰0.01

Moderate dehydration

Control

8

10.4

10

12.8

Ā Ā 

Low-intensity education

26

25.2

4

3.9

0.13 (0.08, 0.22)***

pā€‰<ā€‰0.01

Medium-intensity education

63

18.6

42

12.8

0.73 (0.32, 1.70)***

0.47

High-intensity education

42

20.5

23

12.8

0.62 (0.08, 5.04)***

0.66

Mild dehydration

Control

4

5.2

3

3.9

Ā Ā 

Low-intensity education

10

9.7

8

7.7

0.52 (0.02, 16.1)**

0.71

Medium-intensity education

25

7.4

40

12.2

0.70 (0.04, 11.9)**

0.80

High-intensity education

26

12.7

14

7.8

0.41 (0.03, 5.87)**

0.51

  1. aIRRā€‰=ā€‰adjusted incidence-rate ratio. aORā€‰=ā€‰adjusted odds ratio. CGā€‰=ā€‰control group. CIā€‰=ā€‰confidence interval. IGā€‰=ā€‰intervention group. SESā€‰=ā€‰socioeconomic status. Usg = urine specific gravity
  2. The p-value refers to the difference in intervention effect between the respective IG and the CG
  3. *We defined dehydration according to Usg. Any dehydration, Usg ā‰„ 1.020. Mild dehydration, Usg = 1.020. Moderate dehydration, Usg = 1.025. Severe dehydration, Usg = 1.030
  4. **We used a multilevel mixed-effects Poisson regression model to estimate intervention effects, which can be interpreted as the aIRR of a desired follow-up outcome between the respective IG and the CG. The model included the respective IG, random intercept for the city, and robust standard errors. We adjusted for the childā€™s sex, age, and SES
  5. ***We used a multilevel mixed-effects logistic regression model to estimate intervention effects, which can be expressed as the aOR of change in prevalence of a desired follow-up outcome between the respective IG and CG. The model included the respective IG, random intercept for the city, and robust standard errors. We adjusted for the childā€™s sex, age, and SES