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):
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.