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+# NHANES
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+# install.packages("caret", repos="https://mirrors.ustc.edu.cn/CRAN/")
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+library(caret)
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+library(nhanesA)
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+library(knitr)
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+library(tidyverse)
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+library(plyr)
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+library(dplyr)
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+library(foreign)
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+
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+path = "NHANES/2017-2018/"
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+year = "_J"
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+# year_ = "2001-2002"
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+
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+DEMO <- read.xport(paste0(path , "DEMO",year,".XPT"))
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+
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+#选取数据发布号、样本人员的访谈和检查状态、性别、年龄、种族、出生地
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+#社会经济地位数据：家庭 PIR、家庭年度收入
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+if(year =="" || year == "_B" || year == "_C" || year == "_D"){
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+ DEMO <- DEMO %>% select(SEQN, SDDSRVYR, RIDSTATR, RIAGENDR, RIDAGEYR, RIDRETH1, DMDBORN, INDFMPIR, INDFMINC)
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+}else if(year =="_E" || year == "_F"){
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+ DEMO <- DEMO %>% select(SEQN, SDDSRVYR, RIDSTATR, RIAGENDR, RIDAGEYR, RIDRETH1, DMDBORN2, INDFMPIR, INDHHIN2)
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+}else{
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+ DEMO <- DEMO %>% select(SEQN, SDDSRVYR, RIDSTATR, RIAGENDR, RIDAGEYR, RIDRETH1, DMDBORN4, INDFMPIR, INDHHIN2)
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+}
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+print(names(DEMO)[9])
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+names(DEMO)[7] <- "DMDBORN"
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+names(DEMO)[9] <- "INDFMINC"
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+
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+# #收入
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+# if(year=="_E" | year=="_F" | year=="_H" | year=="_G" |year=="_I" | year=="_J"){
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+# INQ <- read.xport(paste0(path, "INQ",year,".XPT"))
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+# data <- join_all(list(data, INQ), by = "SEQN", type = "left")
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+# }
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+
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+
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+#重量、站立高度、体重指数
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+BMX <- read.xport(paste0(path, "BMX",year,".XPT"))
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+BMX <- BMX %>% select(SEQN, BMXWT , BMXHT , BMXBMI )
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+
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+data <- join_all(list(DEMO, BMX), by = "SEQN", type = "left")
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+
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+#收缩压平均值、舒张压平均值、60 秒心率
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+BPX <- read.xport(paste0(path, "BPX",year,".XPT"))
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+BPX <- BPX %>% select(SEQN, BPXSY1, BPXDI1, BPXCHR)
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+data <- join_all(list(data, BPX), by = "SEQN", type = "left")
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+
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+#空腹血浆葡萄糖
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+if(year ==""){
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+ LAB10AM <- read.xport(paste0(path, "LAB10AM",year,".XPT"))
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+ LAB10AM <- LAB10AM %>% select(SEQN, LBXGLUSI )
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+}else if (year == "_B"){
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+ LAB10AM <- read.xport(paste0(path, "L10AM",year,".XPT"))
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+ LAB10AM <- LAB10AM %>% select(SEQN, LBXGLUSI )
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+}else if (year == "_C"){
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+ LAB10AM <- read.xport(paste0(path, "L10AM",year,".XPT"))
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+ LAB10AM <- LAB10AM %>% select(SEQN, LBDGLUSI)
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+}else{
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+ LAB10AM <- read.xport(paste0(path, "GLU",year,".XPT"))
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+ LAB10AM <- LAB10AM %>% select(SEQN, LBDGLUSI)
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+}
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+names(LAB10AM)[2] <- "LBDGLUSI"
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+
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+data <- join_all(list(data, LAB10AM), by = "SEQN", type = "left")
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+
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+#尿白蛋白
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+if (year == ""){
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+ LAB16 <- read.xport(paste0(path, "LAB16",year,".XPT"))
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+}else if(year == "_B" | year == "_C"){
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+ LAB16 <- read.xport(paste0(path, "L16",year,".XPT"))
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+}else{
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+ LAB16 <- read.xport(paste0(path, "ALB_CR",year,".XPT"))
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+}
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+LAB16 <- LAB16 %>% select(SEQN, URXUMA)
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+
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+data <- join_all(list(data, LAB16), by = "SEQN", type = "left")
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+
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+#血常规：白细胞计数 （SI）1000 个细胞/uL、淋巴细胞计数、单核细胞数、红细胞计数 SI（百万细胞/uL）、血红蛋白 （g/dL）、血小板计数 （1000 个细胞/uL）
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+#、嗜酸性粒细胞数、嗜碱性粒细胞数、Segmented neutrophils number（分叶中性粒细胞数量）1000 细胞/uL
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+if (year == ""){
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+ LAB25 <- read.xport(paste0(path, "LAB25",year,".XPT"))
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+}else if(year == "_B" | year == "_C"){
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+ LAB25 <- read.xport(paste0(path, "L25",year,".XPT"))
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+}else{
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+ LAB25 <- read.xport(paste0(path, "CBC",year,".XPT"))
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+}
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+LAB25 <- LAB25 %>% select(SEQN, LBXWBCSI, LBDLYMNO, LBDMONO, LBXRBCSI, LBXHGB, LBXPLTSI, LBDEONO, LBDBANO, LBDNENO)
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+#计算炎症指标
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+LAB25$SIRI <- LAB25$LBDNENO*LAB25$LBDMONO/LAB25$LBDLYMNO
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+LAB25$SII <- LAB25$LBXPLTSI*LAB25$LBDNENO/LAB25$LBDLYMNO
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+
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+data <- join_all(list(data, LAB25), by = "SEQN", type = "left")
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+
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+#血脂：甘油三酯(mmol/L))、低密度脂蛋白胆固醇(mmol/L))、总胆固醇、高密度脂蛋白胆固醇（mmol/L）、总胆固醇、甘油三酯
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+#肾功能：血尿素氮、肌酐
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+#肝功能:ALT、AST、总胆红素
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+if (year == ""){
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+ LAB13AM <- read.xport(paste0(path, "LAB13AM",year,".XPT"))
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+}else if(year == "_B" | year == "_C"){
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+ LAB13AM <- read.xport(paste0(path, "L13AM",year,".XPT"))
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+}else{
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+ LAB13AM <- read.xport(paste0(path, "TRIGLY",year,".XPT"))
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+}
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+LAB13AM <- LAB13AM %>% select(SEQN, LBDTRSI, LBDLDLSI)
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+data <- join_all(list(data, LAB13AM), by = "SEQN", type = "left")
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+
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+if(year ==""){
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+ LAB13 <- read.xport(paste0(path, "LAB13",year,".XPT"))
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+}else if(year == "_B" | year == "_C"){
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+ LAB13 <- read.xport(paste0(path, "L13",year,".XPT"))
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+}else{
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+ LAB13 <- read.xport(paste0(path, "TCHOL",year,".XPT"))
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+}
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+if(year=="" | year=="_B"){
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+ LAB13 <- LAB13 %>% select(SEQN, LBDTCSI, LBDHDLSI)
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+}else if(year == "_C"){ #Direct HDL-Cholesterol
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+ LAB13 <- LAB13 %>% select(SEQN, LBDTCSI, LBDHDDSI)
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+}else{
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+ LAB13 <- LAB13 %>% select(SEQN, LBDTCSI)
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+ HDL <- read.xport(paste0(path, "HDL",year,".XPT"))
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+ HDL <- HDL %>% select(SEQN, LBDHDDSI)
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+ LAB13 <- join_all(list(LAB13, HDL), by = "SEQN", type = "left")
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+}
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+names(LAB13)[3] <- "LBDHDDSI"
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+data <- join_all(list(data, LAB13), by = "SEQN", type = "left")
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+
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+#计算炎症指标
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+data$MHR <- data$LBDMONO/data$LBDHDDSI
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+data$NHR <- data$LBDNENO/data$LBDHDDSI
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+data$PHR <- data$LBXPLTSI/data$LBDHDDSI
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+data$LHR <- data$LBDLYMNO /data$LBDHDDSI
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+
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+# 同型半胱氨酸(1999-2006),其他年份为空
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+if(year == "" || year == "_D" || year == "_C" || year == "_B"){
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+ if(year == ""){
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+ LAB06 <- read.xport(paste0(path, "LAB06",year,".XPT"))
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+ LAB06 <- LAB06 %>% select(SEQN, LBXHCY)
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+ }else if(year == "_B"){
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+ LAB06 <- read.xport(paste0(path, "L06",year,".XPT"))
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+ LAB06 <- LAB06 %>% select(SEQN, LBDHCY)
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+ }else if(year == "_C"){
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+ LAB06 <- read.xport(paste0(path, "L06MH",year,".XPT"))
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+ LAB06 <- LAB06 %>% select(SEQN, LBXHCY)
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+ }else{
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+ LAB06 <- read.xport(paste0(path, "HCY",year,".XPT"))
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+ LAB06 <- LAB06 %>% select(SEQN, LBXHCY)
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+ }
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+ names(LAB06)[2] <- "LBXHCY"
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+ data <- join_all(list(data, LAB06), by = "SEQN", type = "left")
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+}else{
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+ data$LBXHCY <- NA
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+}
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+
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+if(year == ""){
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+ LAB18 <- read.xport(paste0(path, "LAB18",year,".XPT"))
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+}else if(year == "_B" || year == "_C"){
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+ LAB18 <- read.xport(paste0(path, "L40",year,".XPT"))
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+}else{
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+ LAB18 <- read.xport(paste0(path, "BIOPRO",year,".XPT"))
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+}
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+LAB18 <- LAB18 %>% select(SEQN, LBDSCHSI, LBDSTRSI, LBDSBUSI, LBDSCRSI, LBXSATSI, LBXSASSI, LBDSTBSI )
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+data <- join_all(list(data, LAB18), by = "SEQN", type = "left")
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+
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+#甲状腺功能：促甲状腺激素
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+if(year == "" || year == "_B" ||year =="_E" || year =="_F" || year =="_G"){
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+ if(year == ""){
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+ LAB18T4 <- read.xport(paste0(path, "LAB18T4",year,".XPT"))
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+ LAB18T4 <- LAB18T4 %>% select(SEQN, LBXTSH)
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+ }else if(year == "_B"){
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+ LAB18T4 <- read.xport(paste0(path, "L40T4",year,".XPT"))
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+ LAB18T4 <- LAB18T4 %>% select(SEQN, LBXTSH)
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+ }else if (year =="_E" || year =="_F" || year =="_G"){
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+ LAB18T4 <- read.xport(paste0(path, "THYROD",year,".XPT"))
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+ LAB18T4 <- LAB18T4 %>% select(SEQN, LBXTSH1)
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+ }
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+ names(LAB18T4)[2] <- "LBXTSH"
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+ data <- join_all(list(data, LAB18T4), by = "SEQN", type = "left")
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+}else{
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+ data$LBXTSH <- NA
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+}
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+
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+#甲状腺功能：游离甲状腺素(2007-2012)
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+if(year == "_E" || year == "_F" || year == "_G"){
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+ THYROD <- read.xport(paste0(path, "THYROD",year,".XPT"))
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+ THYROD <- THYROD %>% select(SEQN, LBDT4FSI)
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+ data <- join_all(list(data, THYROD), by = "SEQN", type = "left")
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+}else{
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+ data$LBDT4FSI <- NA
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+}
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+
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+#吸烟史
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+#成人 20+
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+SMQ <- read.xport(paste0(path, "SMQ",year,".XPT"))
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+SMQ <- SMQ %>% select(SEQN, SMQ020, SMD030, SMQ040, SMQ050Q, SMQ050U, SMD057)
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+data <- join_all(list(data, SMQ), by = "SEQN", type = "left")
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+
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+#饮酒史 20+
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+ALQ <- read.xport(paste0(path, "ALQ",year,".XPT"))
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+if(year == "" || year == "_B" ||year =="_E" || year =="_F" || year =="_C" || year =="_D"){
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+ ALQ <- ALQ %>% select(SEQN, ALQ150, ALQ130)
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+}else{
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+ ALQ <- ALQ %>% select(SEQN, ALQ151, ALQ130)
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+}
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+names(ALQ)[2] <- "ALQ150"
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+data <- join_all(list(data, ALQ), by = "SEQN", type = "left")
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+
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+#饮食习惯
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+DBQ <- read.xport(paste0(path, "DBQ",year,".XPT"))
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+if(year == "" || year == "_B" ||year =="_E" || year =="_C" || year =="_D"){
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+ if(year == ""){
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+ DBQ <- DBQ %>% select(SEQN, DBQ010, DBD030, DBD040, DBD050, DBD060, DBQ070A, DBQ070B, DBQ070C, DBQ390, DBD400, DBD410, DBQ420,
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+ DBQ070D, DBD195, DBQ220A, DBQ220B, DBQ220C, DBQ220D, DBD235A, DBD235B, DBD235C, DBQ300, DBQ330, DBD360, DBD370, DBD380)
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+ }else if (year == "_B"){
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+ DBQ <- DBQ %>% select(SEQN, DBQ010, DBD030, DBD040, DBD050, DBD060, DBD071A, DBD071B, DBD071C, DBQ390, DBQ400, DBD411, DBD421,
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+ DBD071D, DBD196, DBD221A, DBD221B, DBD221C, DBD221D, DBD235AE, DBD235BE, DBD235CE, DBD301, DBQ330, DBQ360, DBQ370, DBD381)
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+ }else if(year == "_C"){
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+ DBQ <- DBQ %>% select(SEQN, DBQ010, DBD030, DBD040, DBD050, DBD060, DBQ071A, DBQ071B, DBQ071C, DBQ390, DBQ400, DBD411, DBQ421,
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+ DBQ071D, DBD197, DBQ221A, DBQ221B, DBQ221C, DBQ221D, DBQ235A, DBQ235B, DBQ235C, DBQ301, DBQ330, DBQ360, DBQ370, DBD381)
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+ }else if(year == "_D" || year == "_E"){
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+ DBQ <- DBQ %>% select(SEQN, DBQ010, DBD030, DBD040, DBD050, DBD060, DBD072A, DBD072B, DBD072C, DBQ390, DBQ400, DBD411, DBQ421,
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+ DBD072D, DBQ197, DBD222A, DBD222B, DBD222C, DBD222D, DBQ235A, DBQ235B, DBQ235C, DBQ301, DBQ330, DBQ360, DBQ370, DBD381)
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+ }
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+}else{
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+ DBQ <- DBQ %>% select(SEQN, DBQ010, DBD030, DBD041, DBD050, DBD061, DBQ073A, DBQ073B, DBQ073C, DBQ390, DBQ400, DBD411, DBQ421,
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+ DBQ073D, DBQ197, DBQ223A, DBQ223B, DBQ223C, DBQ223D, DBQ235A, DBQ235B, DBQ235C, DBQ301, DBQ330, DBQ360, DBQ370, DBD381)
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+}
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+names(DBQ) <- c("SEQN", "DBQ010", "DBD030", "DBD041", "DBD050", "DBD061", "DBQ073A", "DBQ073B", "DBQ073C", "DBQ390", "DBQ400", "DBD411", "DBQ421",
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+ "DBQ073D", "DBQ197", "DBQ223A", "DBQ223B", "DBQ223C", "DBQ223D", "DBQ235A", "DBQ235B", "DBQ235C", "DBQ301", "DBQ330", "DBQ360", "DBQ370", "DBD381")
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+data <- join_all(list(data, DBQ), by = "SEQN", type = "left")
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+
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+#体力活动
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+PAQ <- read.xport(paste0(path, "PAQ",year,".XPT"))
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+PAQ[is.na(PAQ)] <- 0
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+if(year == ""){
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+ PAQ_s <- PAQ %>% select(SEQN, PAD020, PAQ100, PAQ180, PAD440, PAQ480, PAQ560, PAD570, PAQ580)
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+ PAQ_s$PAD020 <- ifelse(PAQ_s$PAD020 == 1, 4, 0)
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+ PAQ_s$PAQ100 <- ifelse(PAQ_s$PAQ100 == 1, 4.5, 0)
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+ PAQ_s$PAQ180 <- ifelse(PAQ_s$PAQ180 == 1, 1.4, ifelse(PAQ_s$PAQ180 == 2, 1.5, ifelse(PAQ_s$PAQ180 == 3, 1.6, ifelse(PAQ_s$PAQ180 == 4, 1.8, 0))))
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+ PAQ_s$PAD440 <- ifelse(PAQ_s$PAD440 == 1, 4, 0)
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+ PAQ_s$PAQ480 <- ifelse(PAQ_s$PAQ480 < 6, 1.2 * PAQ_s$PAQ480, 0)
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+ PAQ_s$PAQ560 <- ifelse(PAQ_s$PAQ560 < 78, 7 * PAQ_s$PAQ560, 0)
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+ PAQ_s$PAD570 <- ifelse(PAQ_s$PAD570 < 6, PAQ_s$PAD570, 0)
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+ PAQ_s$PAQ580 <- ifelse(PAQ_s$PAQ580 < 6, 1.5 * PAQ_s$PAQ580, 0)
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+ PAQ$SCORE <- apply(PAQ_s[, -1], 1, function(x) sum(x))
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+}else if(year =="_B"){
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+ PAQ_s <- PAQ %>% select(SEQN, PAD020, PAQ100, PAQ180, PAD440, PAQ560, PAD590, PAD600)
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+ PAQ_s$PAD020 <- ifelse(PAQ_s$PAD020 == 1, 4, 0)
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+ PAQ_s$PAQ100 <- ifelse(PAQ_s$PAQ100 == 1, 4.5, 0)
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+ PAQ_s$PAQ180 <- ifelse(PAQ_s$PAQ180 == 1, 1.4, ifelse(PAQ_s$PAQ180 == 2, 1.5, ifelse(PAQ_s$PAQ180 == 3, 1.6, ifelse(PAQ_s$PAQ180 == 4, 1.8, 0))))
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+ PAQ_s$PAD440 <- ifelse(PAQ_s$PAD440 == 1, 4, 0)
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+ PAQ_s$PAQ560 <- ifelse(PAQ_s$PAQ560 < 78, 7 * PAQ_s$PAQ560, 0)
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+ PAQ_s$PAD590 <- ifelse(PAQ_s$PAD590 < 6, PAQ_s$PAD590, 0)
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+ PAQ_s$PAD600 <- ifelse(PAQ_s$PAD600 < 6, 1.5 * PAQ_s$PAD600, 0)
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+ PAQ$SCORE <- apply(PAQ_s[, -1], 1, function(x) sum(x))
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+}else if(year =="_C" || year =="_D"){
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+ PAQ_s <- PAQ %>% select(SEQN, PAD020, PAQ100, PAQ180, PAD440, PAQ560, PAD590, PAD600)
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+ PAQ_s$PAD020 <- ifelse(PAQ_s$PAD020 == 1, 4, 0)
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+ PAQ_s$PAQ100 <- ifelse(PAQ_s$PAQ100 == 1, 4.5, 0)
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+ PAQ_s$PAQ180 <- ifelse(PAQ_s$PAQ180 == 1, 1.4, ifelse(PAQ_s$PAQ180 == 2, 1.5, ifelse(PAQ_s$PAQ180 == 3, 1.6, ifelse(PAQ_s$PAQ180 == 4, 1.8, 0))))
|
|
|
+ PAQ_s$PAD440 <- ifelse(PAQ_s$PAD440 == 1, 4, 0)
|
|
|
+ PAQ_s$PAQ560 <- ifelse(PAQ_s$PAQ560 < 78, 7 * PAQ_s$PAQ560, 0)
|
|
|
+ PAQ_s$PAD590 <- ifelse(PAQ_s$PAD590 < 6, PAQ_s$PAD590, 0)
|
|
|
+ PAQ_s$PAD600 <- ifelse(PAQ_s$PAD600 < 6, 1.5 * PAQ_s$PAD600, 0)
|
|
|
+ PAQ$SCORE <- apply(PAQ_s[, -1], 1, function(x) sum(x))
|
|
|
+}else{
|
|
|
+ PAQ_s <- PAQ %>% select(SEQN, PAD615, PAD630, PAD645, PAD660, PAD675)
|
|
|
+ PAQ_s$PAD615 <- ifelse(PAQ_s$PAD615 < 841, 8 * PAQ_s$PAD615, 0)
|
|
|
+ PAQ_s$PAD630 <- ifelse(PAQ_s$PAD630 < 841, 4 * PAQ_s$PAD630, 0)
|
|
|
+ PAQ_s$PAD645 <- ifelse(PAQ_s$PAD645 < 661, 4 * PAQ_s$PAD645, 0)
|
|
|
+ PAQ_s$PAD660 <- ifelse(PAQ_s$PAD660 < 481, 8 * PAQ_s$PAD660, 0)
|
|
|
+ PAQ_s$PAD675 <- ifelse(PAQ_s$PAD675 < 541, 4 * PAQ_s$PAD675, 0)
|
|
|
+ PAQ$SCORE <- apply(PAQ_s[, -1], 1, function(x) sum(x))
|
|
|
+ PAQ$PAAQUEX <- NA
|
|
|
+}
|
|
|
+PAQ <- PAQ %>% select(SEQN, SCORE, PAAQUEX)
|
|
|
+data <- join_all(list(data, PAQ), by = "SEQN", type = "left")
|
|
|
+
|
|
|
+#睡眠问题
|
|
|
+if(year != "" && year != "_B" && year != "_C"){
|
|
|
+ SLQ <- read.xport(paste0(path, "SLQ",year,".XPT"))
|
|
|
+ SLQ <- SLQ %>% select(SEQN, SLQ050)
|
|
|
+ data <- join_all(list(data, SLQ), by = "SEQN", type = "left")
|
|
|
+}else{
|
|
|
+ data$SLQ050 <- NA
|
|
|
+}
|
|
|
+
|
|
|
+
|
|
|
+#心理健康
|
|
|
+if (year =="" || year == "_B" || year == "_C"){
|
|
|
+ #心理健康 - 抑郁症:抑郁评分
|
|
|
+ if(year==""){
|
|
|
+ CIQMDEP <- read.xport(paste0(path, "CIQMDEP",year,".XPT"))
|
|
|
+ }else if (year == "_B" | year == "_C"){
|
|
|
+ CIQMDEP <- read.xport(paste0(path, "CIQDEP",year,".XPT"))
|
|
|
+ }
|
|
|
+ CIQMDEP <- CIQMDEP %>% select(SEQN, CIDDSCOR)
|
|
|
+ data <- join_all(list(data, CIQMDEP), by = "SEQN", type = "left")
|
|
|
+
|
|
|
+ # #精神健康 - 广泛性焦虑症：焦虑评分
|
|
|
+ # CIQGAD <- read.xport(paste0(path, "CIQGAD",year,".XPT"))
|
|
|
+ # CIQGAD <- CIQGAD %>% select(SEQN, CIDGSCOR)
|
|
|
+ # data <- join_all(list(data, CIQGAD), by = "SEQN", type = "left")
|
|
|
+
|
|
|
+ # #心理健康 - 恐慌症：恐慌评分
|
|
|
+ # if(year==""){
|
|
|
+ # CIQPANIC <- read.xport(paste0(path, "CIQPANIC",year,".XPT"))
|
|
|
+ # }else{
|
|
|
+ # CIQPANIC <- read.xport(paste0(path, "CIQPAN",year,".XPT"))
|
|
|
+ # }
|
|
|
+ # CIQPANIC <- CIQPANIC %>% select(SEQN, CIDPSCOR)
|
|
|
+ # data <- join_all(list(data, CIQPANIC), by = "SEQN", type = "left")
|
|
|
+}else{
|
|
|
+ DPQ <- read.xport(paste0(path, "DPQ",year,".XPT"))
|
|
|
+ DPQ <- DPQ[, -which(names(DPQ) == "DPQ100")]
|
|
|
+ DPQ <- na.omit(DPQ)
|
|
|
+ DPQ$CIDDSCOR <- apply(DPQ[, -1], 1, function(x) sum(x[x < 7]))
|
|
|
+ DPQ <- DPQ %>% select(SEQN, CIDDSCOR)
|
|
|
+ data <- join_all(list(data, DPQ), by = "SEQN", type = "left")
|
|
|
+}
|
|
|
+
|
|
|
+#社会支持
|
|
|
+if(year =="" || year == "_B" || year == "_C"){
|
|
|
+ SSQ <- read.xport(paste0(path, "SSQ",year,".XPT"))
|
|
|
+}else if(year =="_D" || year == "_E"){
|
|
|
+ SSQ <- read.xport(paste0(path, "SSQ",year,".XPT"))
|
|
|
+ SSQ <- SSQ[, !(names(SSQ) == "SSD044")]
|
|
|
+}else{
|
|
|
+ SSQ[c("SEQN", "SSQ011", "SSQ021A", "SSQ021B", "SSQ021C", "SSQ021D", "SSQ021E", "SSQ021F", "SSQ021G", "SSQ021H", "SSQ021I", "SSQ021J", "SSQ021K",
|
|
|
+ "SSQ021L", "SSQ021M", "SSQ021N", "SSQ031", "SSQ041", "SSQ051", "SSQ061")] <- NA
|
|
|
+}
|
|
|
+names(SSQ) <- c("SEQN", "SSQ011", "SSQ021A", "SSQ021B", "SSQ021C", "SSQ021D", "SSQ021E", "SSQ021F", "SSQ021G", "SSQ021H", "SSQ021I", "SSQ021J", "SSQ021K",
|
|
|
+ "SSQ021L", "SSQ021M", "SSQ021N", "SSQ031", "SSQ041", "SSQ051", "SSQ061")
|
|
|
+data <- join_all(list(data, SSQ), by = "SEQN", type = "left")
|
|
|
+
|
|
|
+#疾病诊断记录（有高血压、冠心病、心绞痛、心力衰竭、心脏病发作）
|
|
|
+MCQ <- read.xport(paste0(path, "MCQ",year,".XPT"))
|
|
|
+if(year =="" || year == "_B" || year == "_C" || year =="_D" || year == "_E" || year == "_F"){
|
|
|
+ MCQ <- MCQ %>% select(SEQN, MCQ160B, MCQ180B, MCQ160C, MCQ180C, MCQ160D, MCQ180D, MCQ160E, MCQ180E)
|
|
|
+}else if(year =="_G" || year == "_H" || year == "_I" ){
|
|
|
+ MCQ <- MCQ %>% select(SEQN, MCQ160B, MCQ180B, MCQ160C, MCQ180C, MCQ160D, MCQ180D, MCQ160E, MCQ180E)
|
|
|
+}else{
|
|
|
+ MCQ <- MCQ %>% select(SEQN, MCQ160B, MCD180B, MCQ160C, MCD180C, MCQ160D, MCD180D, MCQ160E, MCD180E)
|
|
|
+}
|
|
|
+names(MCQ) <- c("SEQN", "MCQ160B", "MCD180B", "MCQ160C", "MCD180C", "MCQ160D", "MCD180D", "MCQ160E", "MCD180E")
|
|
|
+data <- join_all(list(data, MCQ), by = "SEQN", type = "left")
|
|
|
+
|
|
|
+#用药记录，天数、用量
|
|
|
+#心内常用药
|
|
|
+medicine = c("HYDROCHLOROTHIAZIDE", "VALSARTAN", "AMIODARONE", "AMLODIPINE", "ATORVASTATIN",
|
|
|
+ "BENAZEPRIL", "OLMESARTAN", "PERINDOPRIL","TELMISARTAN","BENAZEPRIL","BENDROFLUMETHIAZIDE",
|
|
|
+ "BEZAFIBRATE","BISOPROLOL","Captopril","Carvedilol", "EPINEPHRINE", "QUINIDINE", "Digoxin",
|
|
|
+ "Diltiazem", "Enalapril", "Eprosartan", "ERTUGLIFLOZIN", "SITAGLIPTIN", "EZETIMIBE", "SIMVASTATIN",
|
|
|
+ "FENOFIBRIC ACID", "Furosemide", "GLICLAZIDE", "GLIPIZIDE", "METFORMIN", "HYDRALAZINE", "ISOSORBIDE DINITRATE",
|
|
|
+ "IRBESARTAN", "METOPROLOL", "PROPRANOLOL", "ISOSORBIDE MONONITRATE", "NIFEDIPINE", "NITROGLYCERIN",
|
|
|
+ "PITAVASTATIN", "PRAVASTATIN", "PRAZOSIN", "PROCAINAMIDE", "PROPAFENONE", "SACUBITRIL", "SOTALOL", "SPIRONOLACTONE",
|
|
|
+ "TICAGRELOR", "TORSEMIDEMIDE", "VERAPAMIL", "TRIAMTERENE", "WARFARIN")
|
|
|
+RXQ_RX <- read.xport(paste0(path, "RXQ_RX",year,".XPT"))
|
|
|
+if(year == "" || year == "_B"){
|
|
|
+ day_RXQ_RX <- RXQ_RX %>%
|
|
|
+ select(SEQN, RXD240B, RXD260) %>%
|
|
|
+ na.omit(.) %>%
|
|
|
+ pivot_wider(names_from = RXD240B, values_from = RXD260,
|
|
|
+ names_prefix = "day_",values_fill = 0, values_fn = list(RXD260 = sum))
|
|
|
+ number_RXQ_RX <- RXQ_RX %>%
|
|
|
+ select(SEQN, RXD240B, RXD295) %>%
|
|
|
+ na.omit(.) %>%
|
|
|
+ pivot_wider(names_from = RXD240B, values_from = RXD295,
|
|
|
+ names_prefix = "number_",values_fill = 0, values_fn = list(RXD295 = sum))
|
|
|
+}else{
|
|
|
+ day_RXQ_RX <- RXQ_RX %>%
|
|
|
+ select(SEQN, RXDDRUG, RXDDAYS) %>%
|
|
|
+ na.omit(.) %>%
|
|
|
+ pivot_wider(names_from = RXDDRUG, values_from = RXDDAYS,
|
|
|
+ names_prefix = "day_",values_fill = 0, values_fn = list(RXDDAYS = sum))
|
|
|
+ number_RXQ_RX <- RXQ_RX %>%
|
|
|
+ select(SEQN, RXDDRUG, RXDCOUNT) %>%
|
|
|
+ na.omit(.) %>%
|
|
|
+ pivot_wider(names_from = RXDDRUG, values_from = RXDCOUNT,
|
|
|
+ names_prefix = "number_",values_fill = 0, values_fn = list(RXDCOUNT = sum))
|
|
|
+}
|
|
|
+for (item in medicine){
|
|
|
+ med_columns <- grep(item, names(day_RXQ_RX), value = TRUE)
|
|
|
+ tmp = day_RXQ_RX[, c("SEQN", med_columns)]
|
|
|
+ tmp[[paste0("day_", item)]] <- apply(tmp[, -1], 1, function(x) sum(x))
|
|
|
+ tmp <- tmp %>% select(SEQN, paste0("day_", item))
|
|
|
+ data <- join_all(list(data, tmp), by = "SEQN", type = "left")
|
|
|
+ med_columns <- grep(item, names(number_RXQ_RX), value = TRUE)
|
|
|
+ tmp = number_RXQ_RX[, c("SEQN", med_columns)]
|
|
|
+ tmp[[paste0("num_", item)]] <- apply(tmp[, -1], 1, function(x) sum(x))
|
|
|
+ tmp <- tmp %>% select(SEQN, paste0("num_", item))
|
|
|
+ data <- join_all(list(data, tmp), by = "SEQN", type = "left")
|
|
|
+}
|
|
|
+
|
|
|
+#就诊情况
|
|
|
+HUQ <- read.xport(paste0(path, "HUQ",year,".XPT"))
|
|
|
+if(year == "" || year == "_B" ||year =="_E" || year =="_C" || year =="_D" || year =="_F"|| year =="_G"){
|
|
|
+ if(year == ""){
|
|
|
+ HUQ <- HUQ %>% select(SEQN, HUQ010, HUQ020, HUQ030, HUQ040, HUQ050, HUQ060, HUQ070, HUD080, HUQ090)
|
|
|
+ }else if(year == "_B"){
|
|
|
+ HUQ <- HUQ %>% select(SEQN, HUQ010, HUQ020, HUQ030, HUQ040, HUQ050, HUQ060, HUD070, HUQ080, HUQ090)
|
|
|
+ }else{
|
|
|
+ HUQ <- HUQ %>% select(SEQN, HUQ010, HUQ020, HUQ030, HUQ040, HUQ050, HUQ060, HUQ071, HUD080, HUQ090)
|
|
|
+ }
|
|
|
+}else{
|
|
|
+ HUQ <- HUQ %>% select(SEQN, HUQ010, HUQ020, HUQ030, HUQ041, HUQ051, HUQ061, HUQ071, HUD080, HUQ090)
|
|
|
+}
|
|
|
+names(HUQ) <- c("SEQN", "HUQ010", "HUQ020", "HUQ030", "HUQ041", "HUQ051", "HUQ061", "HUQ071", "HUD080", "HUQ090")
|
|
|
+data <- join_all(list(data, HUQ), by = "SEQN", type = "left")
|
|
|
+
|
|
|
+#健康状况 胃病、肠病、HIV病毒、流感等 最近献血
|
|
|
+HSQ <- read.xport(paste0(path, "HSQ",year,".XPT"))
|
|
|
+if(year == ""){
|
|
|
+ HSQ <- HSQ %>% select(SEQN, HSQ500, HSQ510, HSQ520, HSQ570, HSQ580, HSQ590, HSAQUEX)
|
|
|
+}else if(year == "_B"){
|
|
|
+ HSQ <- HSQ %>% select(SEQN, HSQ500, HSQ510, HSQ520, HSD570, HSQ580, HSQ590, HSAQUEX)
|
|
|
+}else{
|
|
|
+ HSQ <- HSQ %>% select(SEQN, HSQ500, HSQ510, HSQ520, HSQ571, HSQ580, HSQ590, HSAQUEX)
|
|
|
+}
|
|
|
+names(HSQ) <- c("SEQN", "HSQ500", "HSQ510", "HSQ520", "HSQ571", "HSQ580", "HSQ590", "HSAQUEX")
|
|
|
+data <- join_all(list(data, HSQ), by = "SEQN", type = "left")
|
|
|
+
|
|
|
+#身体机能
|
|
|
+PFQ <- read.xport(paste0(path, "PFQ",year,".XPT"))
|
|
|
+if(year == ""){
|
|
|
+ PFQ <- PFQ %>% select(SEQN, PFQ020, PFQ030, PFQ040, PFQ048, PFQ050, PFQ055, PFQ056,
|
|
|
+ PFQ059, PFQ060A, PFQ060B, PFQ060C,PFQ060D,PFQ060E,PFQ060F,PFQ060G,PFQ060H,PFQ060I,PFQ060J,PFQ060K,
|
|
|
+ PFQ060L,PFQ060M,PFQ060N,PFQ060O,PFQ060P,PFQ060Q,PFQ060R,PFQ060S, PFD067A, PFD067B,PFD067C,PFD067D,
|
|
|
+ PFD067E, PFQ090)
|
|
|
+}else if(year == "_B"){
|
|
|
+ PFQ <- PFQ %>% select(SEQN, PFQ020, PFQ030, PFD040, PFQ048, PFQ050, PFQ055, PFQ056,
|
|
|
+ PFQ059, PFQ060A, PFQ060B, PFQ060C,PFQ060D,PFQ060E,PFQ060F,PFQ060G,PFQ060H,PFQ060I,PFQ060J,PFQ060K,
|
|
|
+ PFQ060L,PFQ060M,PFQ060N,PFQ060O,PFQ060P,PFQ060Q,PFQ060R,PFQ060S, PFD067A, PFD067B,PFD067C,PFD067D,
|
|
|
+ PFD067E, PFQ090)
|
|
|
+}else{
|
|
|
+ PFQ <- PFQ %>% select(SEQN, PFQ020, PFQ030, PFQ041, PFQ049, PFQ051, PFQ054, PFQ057,
|
|
|
+ PFQ059, PFQ061A, PFQ061B,PFQ061C,PFQ061D,PFQ061E,PFQ061F,PFQ061G,PFQ061H,PFQ061I,PFQ061J,PFQ061K,
|
|
|
+ PFQ061L,PFQ061M,PFQ061N,PFQ061O,PFQ061P,PFQ061Q, PFQ061R,PFQ061S, PFQ063A, PFQ063B,PFQ063C,PFQ063D,
|
|
|
+ PFQ063E, PFQ090)
|
|
|
+}
|
|
|
+names(PFQ) <- c("SEQN", "PFQ020", "PFQ030", "PFQ041", "PFQ049", "PFQ051", "PFQ054", "PFQ057",
|
|
|
+ "PFQ059", "PFQ061A", "PFQ061B","PFQ061C","PFQ061D","PFQ061E","PFQ061F","PFQ061G","PFQ061H","PFQ061I","PFQ061J","PFQ061K",
|
|
|
+ "PFQ061L","PFQ061M","PFQ061N","PFQ061O","PFQ061P","PFQ061Q", "PFQ061R","PFQ061S", "PFQ063A", "PFQ063B","PFQ063C","PFQ063D",
|
|
|
+ "PFQ063E", "PFQ090")
|
|
|
+data <- join_all(list(data, PFQ), by = "SEQN", type = "left")
|
|
|
+
|
|
|
+#认知功能
|
|
|
+if(year=="" | year=="_B" | year=="_H" | year=="_G"){
|
|
|
+ CFQ <- read.xport(paste0(path, "CFQ",year,".XPT"))
|
|
|
+ if(year == "" || year == "_B"){
|
|
|
+ CFQ <- CFQ %>% select(SEQN, CFDRIGHT)
|
|
|
+ }else{
|
|
|
+ CFQ <- CFQ %>% select(SEQN, CFDDS)
|
|
|
+ }
|
|
|
+ names(CFQ) <- c("SEQN", "CFDDS")
|
|
|
+ data <- join_all(list(data, CFQ), by = "SEQN", type = "left")
|
|
|
+}else{
|
|
|
+ data$CFDDS <- NA
|
|
|
+}
|
|
|
+
|
|
|
+mortality_result = read.csv(file = paste0(path, "mortality_result.csv"))
|
|
|
+
|
|
|
+data <- join_all(list(data, mortality_result), by = "SEQN", type = "left")
|
|
|
+
|
|
|
+write.csv(data, file = paste0(path, "result", year, ".csv"), row.names = FALSE)
|
|
|
+
|
|
|
+csv_files <- list.files(path = "NHANES", pattern = "\\.csv$", recursive = TRUE, full.names = TRUE)
|
|
|
+df_combined <- NA
|
|
|
+# 确保读取文件的路径是完整的
|
|
|
+if (length(csv_files) > 0) {
|
|
|
+ for (file in csv_files) {
|
|
|
+ if (grepl("mortality", file)){
|
|
|
+ next
|
|
|
+ }
|
|
|
+ # 读取每个.csv文件
|
|
|
+ data <- read.csv(file, stringsAsFactors = FALSE)
|
|
|
+ print(ncol(data))
|
|
|
+ if (length(df_combined) == 0){
|
|
|
+ df_combined <- data
|
|
|
+ }else{
|
|
|
+ df_combined <- rbind(data, df_combined)
|
|
|
+ }
|
|
|
+ # 这里可以添加代码进行数据处理
|
|
|
+ print(paste("Read file:", file))
|
|
|
+ }
|
|
|
+}
|
|
|
+write.csv(df_combined, file = paste0("NHANES/", "result_all", ".csv"), row.names = FALSE)
|
|
|
+# data = read.csv(file = paste0(path, "result.csv"))
|
|
|
+
|
|
|
+# head(data)
|
|
|
+
|
|
|
+#加入污染物
|
|
|
+library(ncdf4)
|
|
|
+library(raster)
|
|
|
+
|
|
|
+nc <- nc_open("CHAP_PM2.5_Y1K_2009_V4.nc")
|
|
|
+
|
|
|
+data <- ncvar_get(nc, "PM2.5")
|
|
|
+print(data)
|
|
|
+lon <- ncvar_get(nc, "lon")
|
|
|
+tori <- ncvar_get(nc, "time")
|
|
|
+
|
|
|
+tunites <- ncatt_get(nc, "time", )
|
|
|
+
|
|
|
+
|
|
|
+writeRaster(x = nc, filename = 'pre1.tif', format='GTiff', overwrite=TRUE)
|
|
|
+
|
|
|
+
|
|
|
+
|
|
|
+
|
|
|
+
|
|
|
+# China_Health_and_Retirement_Longitudinal_Study_CHARLS
|
|
|
+# demo_china <- read.dta("CHARLS/CHARLS2011_Dataset/demographic_background.dta")
|
|
|
+
|
|
|
+# household_income_china <- read.dta("CHARLS/CHARLS2011_Dataset/household_income.dta")
|
|
|
+
|
|
|
+# # UKDA
|
|
|
+# demo_UK <- read.dta("UKDA-5050-stata/stata/stata13_se/wave_0_1998_data.dta")
|
