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探討心血管疾病與糖尿病之關係

醫技三 B04404013 吳嘉峻

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因心血管疾病的死亡的人數(圖一):台灣於1994年實施全民健保，2000年被保人涵蓋率達96%，對於病人就醫幫忙很大，間接對於心血管診療的發展有貢獻，但由於近年來國人的飲食習慣，導致心血管死亡人數的上升 因糖尿病而死亡的人數(圖二):由於國人的飲食習慣，加上台灣國人平均壽命的延長，導致因糖尿病而死亡人數有上升的趨勢

multiplot <- function(..., plotlist=NULL, file, cols=1, layout=NULL) { 
  library(grid) 
 
  # Make a list from the ... arguments and plotlist 
  plots <- c(list(...), plotlist) 
 
  numPlots = length(plots) 
 
  # If layout is NULL, then use 'cols' to determine layout 
  if (is.null(layout)) { 
    # Make the panel 
    # ncol: Number of columns of plots 
    # nrow: Number of rows needed, calculated from # of cols 
    layout <- matrix(seq(1, cols * ceiling(numPlots/cols)), 
                    ncol = cols, nrow = ceiling(numPlots/cols)) 
  } 
 
 if (numPlots==1) { 
    print(plots[[1]]) 
 
  } else { 
    # Set up the page 
    grid.newpage() 
    pushViewport(viewport(layout = grid.layout(nrow(layout), ncol(layout)))) 
 
    # Make each plot, in the correct location 
    for (i in 1:numPlots) { 
      # Get the i,j matrix positions of the regions that contain this subplot 
      matchidx <- as.data.frame(which(layout == i, arr.ind = TRUE)) 
 
      print(plots[[i]], vp = viewport(layout.pos.row = matchidx$row, 
                                      layout.pos.col = matchidx$col)) 
    } 
  } 
} 
library(dplyr)

## Warning: package 'dplyr' was built under R version 3.3.3

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

library(ggplot2)

## Warning: package 'ggplot2' was built under R version 3.3.3

data = read.csv("Death.csv", header = T, sep = ",")
data$Year = factor(data$Year)
data$Heart.Disease = data$Heart.Disease
data$Diabetes = data$Diabetes
p3=qplot(Year,Heart.Disease,data = data,ylab = "death toll of heart.disease",group = 1)+geom_line()+ggtitle("圖一")
p4=qplot(Year,Diabetes, data = data,ylab = "death toll of Diabetes",group = 1)+geom_line()+ggtitle("圖二")
multiplot(p3,p4)

進一步確認此兩種疾病佔所有死亡人數的比例變化

因心血管疾病的死亡的人數比例(圖三):可以看出，在1992年以前，占死亡人數的總比例都比之後的年度高出許多，但大致還是跟其死亡人數趨勢相同 因糖尿病而死亡的人數比例(圖四):大致與其死亡人數的趨勢相同

data = read.csv("Death.csv", header = T, sep = ",")
data$Year = factor(data$Year)
data$Heart.Disease.rate = data$Heart.Disease/data$Death
data$Diabetes.rate = data$Diabetes/data$Death
p1=qplot(Year,Heart.Disease.rate,data = data,group = 1,ylab ="mortality rate of heart.disease")+geom_line()+ggtitle("圖三")
p2=qplot(Year,Diabetes.rate,data = data,group = 1,ylab ="mortality rate of diabete")+geom_line()+ggtitle("圖四")
multiplot(p1,p2)

探討心血管疾病死亡人數與糖尿病死亡人數的關係

大致呈現正比的關係: 1.糖尿病較易發生動脈硬化 2.糖尿病患者常合併有高血壓，第1型糖尿病有25%合併高血壓，第2型糖尿病則有超過50% 3.。嚴格控制血糖在第1型糖尿病可減少顯微血管併發症與心血管疾病；在第2型糖尿病嚴格血糖控制可減少顯微血管併發症，但是否能減少心血管疾病尚不確定

data = read.csv("Death.csv", header = T, sep = ",")
data$Year = factor(data$Year)
fatdata = select(data, Heart.Disease, Diabetes)
qplot(Heart.Disease, Diabetes, data = data)+scale_x_continuous(limit =c(3000,16000))+scale_y_continuous(limit = c(3000,16000))

## Warning: Removed 1 rows containing missing values (geom_point).

探討心血管疾病占死亡比例與糖尿病死亡占死亡比例之關係

兩者成反比: 由於糖尿病患者有很大的機率會併發心血管疾病，可以知道糖尿病與心血管疾病的患者有很大的比例會重複，而這些病患可能死於心血管疾病或者糖尿病，故因心血管疾病死亡的人數比例上升，因糖尿病死亡的人數比例就會下降

data = read.csv("Death.csv", header = T, sep = ",")
data$Year = factor(data$Year)
data$Heart.Disease.rate = data$Heart.Disease/data$Death
data$Diabetes.rate = data$Diabetes/data$Death
qplot(Diabetes.rate,data = data,Heart.Disease.rate)+geom_smooth()+ geom_point(aes(colour = Year))+scale_x_continuous(limit = c(0.03,0.12))+scale_y_continuous(limit = c(0.03,0.12))

## `geom_smooth()` using method = 'loess'

data$logheart = log(data$Heart.Disease.rate)
data$logdiabetes = log(data$Diabetes.rate)
qplot(logdiabetes,logheart,data = data) + geom_point(aes(colour = Year))