R/combined_rr_ap_pa.R

In danielgils/cobeneficioswwf: Evaluación de Cobeneficios WWF

#' Combine relative risks from AP and PA
#'
#' Combine relative risks from AP and PA through multiplication for crossover diseases
#'
#' @param ind_pa data frame of individual RRs for diseases affected by PA
#' @param ind_ap data frame of individual RRs for diseases affected by AP
#'
#' @return combined RR for diseases after accounted for AP and PA exposures
#'
#' @export
combined_rr_ap_pa <- function(ind_pa,ind_ap){

  # Replace NaNs with 1
  ind_ap[is.na(ind_ap)] <- 1

  # Replace Na with 1
  ind_pa[is.na(ind_pa)] <- 1

  # join pa and ap datasets (all data.frames)
  ind_ap_pa <- dplyr::left_join(ind_pa, ind_ap, by = c('participant_id','age','sex','age_cat'))

  ### iterating over all all disease outcomes
  for (j in c(1:nrow(DISEASE_INVENTORY))[DISEASE_INVENTORY$physical_activity == 1 &
                                         DISEASE_INVENTORY$air_pollution == 1]) {
    ac <- as.character(DISEASE_INVENTORY$acronym[j])
    for (scen in SCEN_SHORT_NAME) {
      # For those causes that are related to both AP and PA, their RR is multiplied
      ind_ap_pa[[paste('RR_pa_ap', scen, ac, sep = '_')]] <- ind_ap_pa[[paste('RR_pa', scen, ac, sep = '_')]] * ind_ap_pa[[paste('RR_ap', scen, ac, sep = '_')]]
    }
  }

  ind_ap_pa
}