library(tidyverse)
library(meta)
library(dmetar)

# Meta-analysis to calculate the prevalence of hypertension
m.prop <- metaprop(
  event = events,           # Number of events (cases of hypertension)
  n = population,           # Study population size
  studlab = paste(id_article),  # Study labels
  data = hiper,             # Dataset
  method = "GLMM",          # Estimation method (generalized linear mixed model)
  sm = "PLOGIT",            # Effect measure using logit of the proportion
  fixed = FALSE,            # Do not apply fixed effects model
  random = TRUE,            # Apply random effects model
  method.random.ci = "HK",  # Confidence interval method (Hartung-Knapp)
  prediction = FALSE,       # Disable prediction for new studies
  title = "Prevalence of Hypertension"  # Title of the analysis
)

# Generate the forest plot for the meta-analysis
forest(m.prop)



# Meta-regression to evaluate the impact of the "Year_publi_categ" variable
m.prop.reg <- metareg(m.prop, ~Year_publi) 

# Generate bubble plot to visualize the meta-regression
bubble(m.prop.reg, studlab = TRUE)


Year_publi <- c(2014, 2010, 2014, 
          2019, 2010, 1982, 2020, 1978, 2001,
          2018, 2002, 2009, 2011, 2011, 2013)