% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/visualizations.R
\name{build_steps_plots}
\alias{build_steps_plots}
\title{Build publication-ready STEPS visualizations}
\usage{
build_steps_plots(indicators, key_indicators, country_name, survey_year)
}
\arguments{
\item{indicators}{A list of indicator results from \code{\link[=compute_all_indicators]{compute_all_indicators()}}.}

\item{key_indicators}{A data frame with key indicators (domain, indicator, estimate, lower, upper).}

\item{country_name}{Country name for plot titles.}

\item{survey_year}{Survey year for plot titles.}
}
\value{
A named list of ggplot2 objects:
\itemize{
\item \code{overview}: Horizontal bar chart of key indicators
\item \code{tobacco_by_sex}: Sex-stratified tobacco use
\item \code{bp_by_sex}: Sex-stratified blood pressure
\item \code{obesity_by_sex}: Sex-stratified overweight/obesity
\item \code{glucose_by_sex}: Sex-stratified blood glucose
\item \code{bp_by_age}: Age-stratified blood pressure with ribbon CI
\item \code{obesity_by_age}: Age-stratified overweight/obesity with ribbon CI
\item \code{sex_dashboard}: Combined 2x2 dashboard of sex-stratified charts (if >=2 sex plots available)
NULL entries are preserved in the list.
}
}
\description{
Generates a list of ggplot2 plots showing key NCD risk factor prevalence
with 95\% confidence intervals, stratified by sex and age group.
}
\details{
All plots use the WHO STEPS colour scheme and professional styling.
Error bars represent 95\% confidence intervals.
Prevalence values are displayed on bars/points with light background text.
}
\examples{
\donttest{
  test_data <- generate_test_data(n = 500, seed = 42)
  cols <- detect_steps_columns(test_data)
  clean <- clean_steps_data(test_data, cols)
  design <- setup_survey_design(clean)
  all_ind <- compute_all_indicators(design)
  plots <- build_steps_plots(all_ind$results, all_ind$key_indicators, "Test", 2023)
  names(plots)
}

}
