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4_stats_deaths_sample_excluded.R
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4_stats_deaths_sample_excluded.R
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#################################################################################
##################################Analyses######################################
##############################Air pollution ####################################
################################################################################
################################################################################
#working paper Cortes et al.
#load packages
if(!require(dplyr)) install.packages("dplyr"); library(dplyr)
if(!require(lubridate)) install.packages("lubridate"); library(lubridate)
if(!require(data.table)) install.packages("data.table"); library(data.table)
if(!require(tidyr)) install.packages("tidyr"); library(tidyr)
library(tidyverse)
#stats fo all deaths, sample and excluded
# read air pollution data (case crossover)
pm10_inf= fread( "exposure_pm10_backtlog_cc_lag0_10_2012_2017_5NOna.csv")
pm10_inf=pm10_inf[,-1]
names(pm10_inf)
pm10_inf=pm10_inf[,-c(10:15)]
names(pm10_inf)=gsub("lag", "pm10.lag", names(pm10_inf))
ozone_inf= fread( "exposure_ozone_backtlog_cc_lag0_10_2012_2017_5NOna.csv")
ozone_inf=ozone_inf[,-1]
names(ozone_inf)
ozone_inf=ozone_inf[,-c(10:15)]
names(ozone_inf)=gsub("lag", "ozone.lag", names(ozone_inf))
###########################################covariate data
temp= fread("exposure_temperature_cc_lag0_10_2012_2017_5NOna.csv")
temp=temp[,-1]
temp=temp[,-c(10:14)]
names(temp)
names(temp)=gsub("lag", "temp.lag", names(temp))
humid=fread("exposure_humidity_cc_lag0_10_2012_2017_5NOna.csv")
humid=humid[,-1]
names(humid)
humid=humid[,-c(10:15)]
names(humid)=gsub("lag", "humid.lag", names(humid))
#inf km
data_inf=merge(pm10_inf, ozone_inf, by=c("rec_number", "case", "Lag0_date"), all = T)
data_inf=merge(data_inf, temp, by=c("rec_number", "case", "Lag0_date"), all = T)
data_inf=merge(data_inf, humid, by=c("rec_number", "case", "Lag0_date"), all = T)
covar=fread("covariate_data.csv")
data_inf=merge(data_inf, covar, by="rec_number")
data_inf_cvd=subset(data_inf, data_inf$cause_group=="CVD")
data_inf_resp=subset(data_inf, data_inf$cause_group=="Resp")
names(data_inf)
data_inf=data_inf[,c(1,2,3,29:48)]
data_inf=data_inf %>% group_by(rec_number) %>%
mutate(count2 = length(rec_number[case==1]))
table(data_inf$count2)
see=subset(data_inf, data_inf$count2==0)
data_inf=subset(data_inf, !data_inf$count2==0)
data=data_inf
data=subset(data, data$case==1)
table(data$cause_group)
names(data)
cvd=subset(data, data$cause_group=="CVD")
resp=subset(data, data$cause_group=="Resp")
table(resp$causes_ctg)
table(cvd$causes_ctg)
round(prop.table(table(resp$causes_ctg))*100, digits = 0)
round(prop.table(table(cvd$causes_ctg))*100, digits = 0)
data$age_ctg2=ifelse(data$age_edit<65, "<65",
ifelse(data$age_edit>64, "elderly (>=65 y)", "other"))
table(data$death_race_ctg)
round(prop.table(table(data$death_race_ctg))*100, digits = 0)
#Tem categoria 0???????????Grau de instrução (Escolaridade em anos.
#Valores: 1 – Nenhuma; 2 – de 1 a 3 anos; 3 –de 4 a 7 anos;
#4 – de 8 a 11 anos; 5 – 12 anos e mais; 9 – Ignorado)
data$education_years
data$school_ctg=ifelse(data$education_years<4, "primary or none" ,
ifelse(data$education_years==9, "primary or none", ">7y"))
table(data$school_ctg)
round(prop.table(table(data$school_ctg))*100, digits = 0)
round(prop.table(table(cvd$causes_ctg))*100, digits = 0)
round(prop.table(table(resp$causes_ctg))*100, digits = 0)
table(data$age_ctg2)
table(is.na(data$age_ctg2))
round(prop.table(table(data$age_ctg2))*100)
round(prop.table(table(resp$causes_ctg))*100, digits = 0)
table(data$gender)
table(is.na(data$gender))
round(prop.table(table(data$gender))*100)
names(data)
table(data$education_years)
data$season=ifelse(month(data$Date)==5, "5-10 winter",
ifelse(month(data$Date)==6, "5-10 winter",
ifelse(month(data$Date)==7, "5-10 winter",
ifelse(month(data$Date)==8, "5-10 winter",
ifelse(month(data$Date)==9, "5-10 winter",
ifelse(month(data$Date)==10, "5-10 winter",
ifelse(month(data$Date)==12, "12-03 warm",
ifelse(month(data$Date)==1, "12-03 warm",
ifelse(month(data$Date)==2, "12-03 warm",
ifelse(month(data$Date)==3, "12-03 warm", "other")))) ))))))
table(data$season)
round(prop.table(table(data$season))*100)
data$status="included"
###########################################################
cvd=read.csv("geocoded_cvd_final.csv", stringsAsFactors = F)
cvd=cvd[,-1]
names(cvd)
cvd=cvd[,c(1,2,3,4,5,6,7,8,9,10,11,12,17,18,20,21)]
cvd=subset(cvd, !is.na(cvd$latitude))
cvd=subset(cvd, cvd$non_Geocoded_reason=="geocoded")
#plot(cvd$longitude)
resp=read.csv("geocoded_resp_final.csv", stringsAsFactors = F)
names(resp)
resp=resp[,-1]
resp=resp[,c(1,2,3,4,5,6,7,8,9,10,11,12,17,18,20,21)]
resp=subset(resp, !is.na(resp$latitude))
resp=subset(resp, resp$non_Geocoded_reason=="geocoded")
death_all=rbind.data.frame(cvd, resp)
#############################################################
data_red=data[,c(1,3,26)]
death_all=merge(death_all, data_red, by="rec_number", all.x = T)
head(death_all)
death_all$status=ifelse(is.na(death_all$status), "excluded", death_all$status)
death_excluded=subset(death_all, death_all$status=="excluded")
death_excluded$cause_death
death_excluded$Date=death_excluded$date_death
death_excluded$Date=ifelse(nchar(death_excluded$Date)<8, paste0("0",death_excluded$Date), death_excluded$Date)
death_excluded$Date=dmy(death_excluded$Date)
#write.csv(death, "death_all.csv")
names(death_excluded)
table(death_excluded$gender)
table(death_excluded$race_color)
table(death_excluded$marital)
table(death_excluded$education_years)
death_excluded$marital_ctg=ifelse(death_excluded$marital==2, "married", ifelse(death_excluded$marital==5, "married",
ifelse(death_excluded$marital==9,NA, "not married")))
table(death_excluded$marital_ctg)
death_excluded$cause_group=death_excluded$cause_death
death_excluded$cause_group=substr(death_excluded$cause_group, 1,1)
death_excluded$cause_group= ifelse(death_excluded$cause_group=='J', "Resp", "CVD")
table(death_excluded$cause_group)
cvd=subset(death_excluded, death_excluded$cause_group=="CVD")
resp=subset(death_excluded, death_excluded$cause_group=="Resp")
#J44 DPOC
#j45 ASMA
# J20 acute bronchitis
#J21 Bronquiolite Aguda
death_excluded$causes_ctg=death_excluded$cause_death
death_excluded$causes_ctg
death_excluded$causes_ctg=ifelse(substring(death_excluded$cause_death,1,3)=="I20", "Doencas isquemicas do coracao (I20- I25)",
ifelse(substring(death_excluded$cause_death,1,3)=="I21", "Doencas isquemicas do coracao (I20- I25)",
ifelse(substring(death_excluded$cause_death,1,3)=="I22", "Doencas isquemicas do coracao (I20- I25)",
ifelse(substring(death_excluded$cause_death,1,3)=="I23","Doencas isquemicas do coracao (I20- I25)",
ifelse(substring(death_excluded$cause_death,1,3)=="I24","Doencas isquemicas do coracao (I20- I25)",
ifelse(substring(death_excluded$cause_death,1,3)=="I25","Doencas isquemicas do coracao (I20- I25)",
ifelse(substring(death_excluded$cause_death,1,3)=="I50","Insuficiencia Cardiaca (I50)",
ifelse(substring(death_excluded$cause_death,1,3)=="I60","Doencas Cerebrovasculares I60-I69)",
ifelse(substring(death_excluded$cause_death,1,3)=="I61","Doencas Cerebrovasculares I60-I69)",
ifelse(substring(death_excluded$cause_death,1,3)=="I62","Doencas Cerebrovasculares I60-I69)",
ifelse(substring(death_excluded$cause_death,1,3)=="I63","Doencas Cerebrovasculares I60-I69)",
ifelse(substring(death_excluded$cause_death,1,3)=="I64","Doencas Cerebrovasculares I60-I69)",
ifelse(substring(death_excluded$cause_death,1,3)=="I65","Doencas Cerebrovasculares I60-I69)",
ifelse(substring(death_excluded$cause_death,1,3)=="I66","Doencas Cerebrovasculares I60-I69)",
ifelse(substring(death_excluded$cause_death,1,3)=="I67","Doencas Cerebrovasculares I60-I69)",
ifelse(substring(death_excluded$cause_death,1,3)=="I68","Doencas Cerebrovasculares I60-I69)",
ifelse(substring(death_excluded$cause_death,1,3)=="I69","Doencas Cerebrovasculares I60-I69)",
ifelse(substring(death_excluded$cause_death,1,3)=="J44", "DPOC",
ifelse(substring(death_excluded$cause_death,1,3)=="J45", "Asma",
ifelse(substring(death_excluded$cause_death,1,3)=="J20", "Bronquite Aguda",
ifelse(substring(death_excluded$cause_death,1,3)=="J21", "Bronquiolite Aguda", "outras")))))))))))))))))))))
table(death_excluded$causes_ctg)
names(death_excluded)
summary(death_excluded$birth_date)
death_excluded$birth_date_ctg=death_excluded$birth_date
death_excluded$birth_date_ctg=ifelse(nchar(death_excluded$birth_date)<8, paste0("0",death_excluded$birth_date), death_excluded$birth_date)
death_excluded$birth_date_ctg=dmy(death_excluded$birth_date_ctg)
death_excluded$birth_date_ctg=as.Date(death_excluded$birth_date_ctg, format="%Y-%m-%d")
death_excluded$birth_date_ctg
death_excluded$Date=as.Date(death_excluded$Date, format="%Y-%m-%d")
death_excluded$Date
death_excluded$age_edit = year(as.period(interval(start = death_excluded$birth_date_ctg, end = death_excluded$Date)))
# infants <5 20–64 years; the elderly: ≥ 65 years
# death_excluded$age_ctg=ifelse(death_excluded$age_edit<5, "infants-preschoolers (<5y)",
# ifelse(death_excluded$age_edit>19 &
# death_excluded$age_edit<65, "adults (20-64 y)",
# ifelse(death_excluded$age_edit>64, "elderly (>64 y)", "other")))
#
death_excluded$age_ctg=ifelse(death_excluded$age_edit<65, "adults (20-64 y)",
ifelse(death_excluded$age_edit>64, "elderly (>64 y)", "other"))
table(death_excluded$age_ctg)
round(prop.table(table(death_excluded$age_ctg))*100, digits = 0)
names(death_excluded)
table(death_excluded$race_color)
death_excluded$death_race_ctg=ifelse(death_excluded$race_color==1, "white","non white")
table(death_excluded$death_race_ctg)
table(death_excluded$death_race_ctg)
round(prop.table(table(death_excluded$death_race_ctg))*100, digits = 0)
#Tem categoria 0???????????Grau de instrução (Escolaridade em anos.
#Valores: 1 – Nenhuma; 2 – de 1 a 3 anos; 3 –de 4 a 7 anos;
#4 – de 8 a 11 anos; 5 – 12 anos e mais; 9 – Ignorado)
death_excluded$education_years
death_excluded$school_ctg=ifelse(death_excluded$education_years<4, "primary or none" ,
ifelse(death_excluded$education_years==9, "primary or none", ">7y"))
table(death_excluded$school_ctg)
round(prop.table(table(death_excluded$school_ctg))*100, digits = 0)
table(cvd$causes_ctg)
table(resp$causes_ctg)
round(prop.table(table(cvd$causes_ctg))*100, digits = 0)
round(prop.table(table(resp$causes_ctg))*100, digits = 0)
table(death_excluded$age_ctg2)
table(is.na(death_excluded$age_ctg2))
round(prop.table(table(death_excluded$age_ctg2))*100)
round(prop.table(table(resp$causes_ctg))*100, digits = 0)
table(death_excluded$gender)
table(is.na(death_excluded$gender))
round(prop.table(table(death_excluded$gender))*100)
names(death_excluded)
table(death_excluded$education_years)
death_excluded$season=ifelse(month(death_excluded$Date)==5, "5-10 winter",
ifelse(month(death_excluded$Date)==6, "5-10 winter",
ifelse(month(death_excluded$Date)==7, "5-10 winter",
ifelse(month(death_excluded$Date)==8, "5-10 winter",
ifelse(month(death_excluded$Date)==9, "5-10 winter",
ifelse(month(death_excluded$Date)==10, "5-10 winter",
ifelse(month(death_excluded$Date)==12, "12-03 warm",
ifelse(month(death_excluded$Date)==1, "12-03 warm",
ifelse(month(death_excluded$Date)==2, "12-03 warm",
ifelse(month(death_excluded$Date)==3, "12-03 warm", "other")))) ))))))
table(death_excluded$season)
round(prop.table(table(death_excluded$season))*100)