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prevalencias.R
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library(plyr)
library(tidyverse)
library(scales)
library(broom)
library(survey)
library(lubridate)
library(lme4)
library(broom.mixed)
library(mixedup)
library(glmmTMB)
library(srvyr)
rm(list=ls())
load("joined_dta.RData")
ccaas <- read_delim("ccaas.csv", delim = ";",
escape_double = FALSE, trim_ws = TRUE)
# Invertimos alcohol
dta <- dta %>%
mutate(alcohol=(alcohol-1)*-1)
prevalencias_peso_ccaa_overall <- dta %>%
as_survey_design(weights = c(factor2)) %>%
group_by(ccaa, education_3, encuesta) %>%
summarize(diabetes = survey_mean(diabetes, na.rm = T, vartype = "ci"),
hta = survey_mean(hta, na.rm = T, vartype = "ci"),
col = survey_mean(col, na.rm = T, vartype = "ci"),
obesity = survey_mean(obesity, na.rm = T, vartype = "ci"),
sobrepeso = survey_mean(sobrepeso, na.rm = T, vartype = "ci"),
smoking = survey_mean(smoking, na.rm = T, vartype = "ci"),
alcohol = survey_mean(alcohol, na.rm = T, vartype = "ci"),
sedentarismo = survey_mean(sedentarismo, na.rm = T, vartype = "ci"),
food = survey_mean(food, na.rm = T, vartype = "ci")) %>%
left_join(ccaas) %>%
mutate(sexo="Overall")
prevalencias_peso_ccaa_sexo <- dta %>%
as_survey_design(weights = c(factor2)) %>%
group_by(ccaa, education_3, encuesta, sexo) %>%
summarize(diabetes = survey_mean(diabetes, na.rm = T, vartype = "ci"),
hta = survey_mean(hta, na.rm = T, vartype = "ci"),
col = survey_mean(col, na.rm = T, vartype = "ci"),
obesity = survey_mean(obesity, na.rm = T, vartype = "ci"),
sobrepeso = survey_mean(sobrepeso, na.rm = T, vartype = "ci"),
smoking = survey_mean(smoking, na.rm = T, vartype = "ci"),
alcohol = survey_mean(alcohol, na.rm = T, vartype = "ci"),
sedentarismo = survey_mean(sedentarismo, na.rm = T, vartype = "ci"),
food = survey_mean(food, na.rm = T, vartype = "ci")) %>%
left_join(ccaas)
prevalencias_ccaa <- prevalencias_peso_ccaa_sexo %>%
mutate(sexo=as.character(sexo)) %>%
rbind(prevalencias_peso_ccaa_overall)
write.csv(prevalencias_ccaa, "prevalencias_ccaa.csv")
prevalencias_peso_spain_overall <- dta %>%
as_survey_design(weights = c(factor2)) %>%
group_by(education_3, encuesta) %>%
summarize(diabetes = survey_mean(diabetes, na.rm = T, vartype = "ci"),
hta = survey_mean(hta, na.rm = T, vartype = "ci"),
col = survey_mean(col, na.rm = T, vartype = "ci"),
obesity = survey_mean(obesity, na.rm = T, vartype = "ci"),
sobrepeso = survey_mean(sobrepeso, na.rm = T, vartype = "ci"),
smoking = survey_mean(smoking, na.rm = T, vartype = "ci"),
alcohol = survey_mean(alcohol, na.rm = T, vartype = "ci"),
sedentarismo = survey_mean(sedentarismo, na.rm = T, vartype = "ci"),
food = survey_mean(food, na.rm = T, vartype = "ci")) %>%
mutate(sexo="Overall")
prevalencias_peso_spain_sexo <- dta %>%
as_survey_design(weights = c(factor2)) %>%
group_by(sexo, education_3, encuesta) %>%
summarize(diabetes = survey_mean(diabetes, na.rm = T, vartype = "ci"),
hta = survey_mean(hta, na.rm = T, vartype = "ci"),
col = survey_mean(col, na.rm = T, vartype = "ci"),
obesity = survey_mean(obesity, na.rm = T, vartype = "ci"),
sobrepeso = survey_mean(sobrepeso, na.rm = T, vartype = "ci"),
smoking = survey_mean(smoking, na.rm = T, vartype = "ci"),
alcohol = survey_mean(alcohol, na.rm = T, vartype = "ci"),
sedentarismo = survey_mean(sedentarismo, na.rm = T, vartype = "ci"),
food = survey_mean(food, na.rm = T, vartype = "ci"))
prevalencias_spain <- prevalencias_peso_spain_sexo %>%
mutate(sexo=as.character(sexo)) %>%
rbind(prevalencias_peso_spain_overall)
write.csv(prevalencias_spain, "prevalencias_spain.csv")
# Para los informes
prevalencias_spain <- prevalencias_spain %>%
mutate(sexo=(case_when(sexo==0~"Mujeres", sexo==1~"Hombres", sexo=="Overall"~"Global")),
abreviatura="ES",
nombre_notilde="Espana",
ccaa=0)
prevalencias_ccaa <- prevalencias_ccaa %>%
select(-c(id_mapa, nombre)) %>%
mutate(sexo=(case_when(sexo==0~"Mujeres", sexo==1~"Hombres", sexo=="Overall"~"Global")))
prevalencias <- prevalencias_spain %>%
rbind(prevalencias_ccaa)
prevalencias$ccaa <- as.factor(prevalencias$ccaa)
prevalencias <- prevalencias %>%
filter(encuesta != 2009) %>%
filter(encuesta != 2001) %>%
mutate(Sedentarismo=sedentarismo)
save(prevalencias, file = "Informes_CCAA/prevalencias_informes.RData")