Load graph library and custom plot theme.

```
library(ggplot2)
science_theme = theme(panel.background=element_blank(), panel.grid.major = element_line(size = 0.5, color = "grey"),
axis.line = element_line(size = 0.7, color = "black"), legend.position = c(0.9,
0.2), text = element_text(size = 14))
```

```
nutritional_indices <- data.frame(
nutritional_indicator = factor(c("Height-for-age-WHO","Weight-for-age-WHO","Weight-for-height-WHO","BMI-for-age-WHO","Stunting-WHO","Underweight-WHO","Wasting-WHO","Height-for-age-NCHS","Weight-for-age-NCHS","Weight-for-height-NCHS","Weight/month"),
levels=c("Height-for-age-WHO","Weight-for-age-WHO","Weight-for-height-WHO","BMI-for-age-WHO","Stunting-WHO","Underweight-WHO","Wasting-WHO","Height-for-age-NCHS","Weight-for-age-NCHS","Weight-for-height-NCHS","Weight/month")),
frequency = c(5,2,2,2,2,1,2,2,2,1,1)
)
age_groups <- data.frame(
age_group = factor(c("0-12 Months","6-36 Months","6-59 Months","> 6 Years"),
levels=c("0-12 Months","6-36 Months","6-59 Months","> 6 Years")),
frequency = c(2,3,2,2)
)
sample_size <- data.frame(
sample_size = factor(c("Gasana (2002)","Mulugeta (2009)","Mahmud (2013)","Medhin (2010)","Asefa (1998)","Egata (2010)","Esrey (1996)","Fenn (2012)","Silva (2005)"),
levels=c("Gasana (2002)","Mulugeta (2009)","Mahmud (2013)","Medhin (2010)","Asefa (1998)","Egata (2010)","Esrey (1996)","Fenn (2012)","Silva (2005)")),
frequency = c(55,213,600,873,1502,2352,4888,5552,10449)
)
pref_methods <- data.frame(
pref_method = factor(c("Linear Regression","Logistic Regression","Probit Regression","Reed Model"),
levels=c("Linear Regression","Logistic Regression","Probit Regression","Reed Model")),
frequency = c(4,4,1,1)
)
```

When dichotomized (Continuous mapped to “Yes” or “No” variable):

**Height-for-age**is defined as Stunting**Weight-for-age**is defined as Underweight**Weight-for-height**is defined as Wasting

Furthermore, the indicators were counted separately for WHO and NCHS as they compare the actual values to **distinct** reference populations provided from the World Health Organization and the U.S. National Center for Health Statistics.

Four age groups were observed across the included sutdies.

Smallest sample size used on a given study to draw conclusions on sanitation practices effect on malnutrition.

Frequency of statistical methods across included studies.