Library and Theme for Plots

Load graph library and custom plot theme.

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"), 
  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)


Nutricional Indices

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

Four age groups were observed across the included sutdies.

Sample Size

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