Graph 2 H.pylori prevalence in Japanese stratified by gender

Men and Women together

source("function for multiplot by ggplot.R")
data_sex <- subset(data, !is.na(men))
data_sex$Author <- droplevels(data_sex$Author)
Men <- ggplot(data_sex, aes(x = birth.year_high, 
                  y = men,
                  color = Author, 
                  size = n_m)) + 
  geom_line(linetype = "dashed", size = 1.2) + 
  geom_point() +
  scale_x_continuous(breaks = seq(1900, 2005, 5)) + 
  scale_y_continuous(limits=c(0,100),breaks = seq(0,100,5))+
  scale_colour_manual(name = "",
                      values = c("#EE1289", "#7FFFD4", "#838B8B", "#000000", "#0000EE", "#8B2323", "#32CD32", "#4F94CD", "#CD4F39", "#CD853F"), 
                      limits=c("Kikuchi, 1998 ,  1996", 
                               "Ogihara, 2000 ,  1990",
                               "Yamagata, 2000 ,  1988",
                               "Kikuchi, 2005 ,  1988",
                               "Tamura, 2012 ,  2009",
                               "Hirayama, 2014 ,  2008",
                               "Shiotani, 2008 ,  2005",
                               "Shibata, 2002 ,  1993",
                               "Fukao, 1993 ,  1985",
                               "loess"), 
                      labels = c("Kikuchi,1998,1996",
                                 "Ogihara,2000,1990",
                                 "Yamagata,2000,1988",
                                 "Kikuchi,2005,1988",
                                 "Tamura,2012,2009",
                                 "Hirayama,2014,2008",
                                 "Shiotani,2008,2005",
                                 "Shibata,2002,1993",
                                 "Fukao,1993,1985",
                                 "TOTAL MEN")) + 
  ylab("Prevalence in Japanese men (%)") + 
  xlab("Birth Year") + 
  geom_smooth(aes(colour = "loess"), method = "loess") + 
  theme_bw()+
  theme(legend.position = "bottom", 
        axis.text.x = element_text(size = rel(1.3)), 
        axis.text.y = element_text(size = rel(1.5)), 
        axis.title.x = element_text(size = rel(1.5)), 
        axis.title.y = element_text(size = rel(1.5)), 
        legend.text = element_text(size = rel(1.2)),
        axis.text = element_text(size = 12, face = "bold"), 
        legend.direction = "horizontal") 
Women <- ggplot(data_sex, aes(x = birth.year_high, 
                  y = women,
                  color = Author,
                  size = n_f)) + 
  geom_line(linetype = "dashed", size = 1.2) + 
  geom_point() +
  scale_x_continuous(breaks = seq(1900, 2005, 5)) + 
  scale_y_continuous(limits=c(0,100),breaks = seq(0,100,5))+
  scale_colour_manual(name = "",
                      values = c("#EE1289", "#7FFFD4", "#838B8B", "#000000", "#0000EE", "#8B2323", "#32CD32", "#4F94CD", "#CD4F39", "#CD853F"), 
                      limits=c("Kikuchi, 1998 ,  1996", 
                               "Ogihara, 2000 ,  1990",
                               "Yamagata, 2000 ,  1988",
                               "Kikuchi, 2005 ,  1988",
                               "Tamura, 2012 ,  2009",
                               "Hirayama, 2014 ,  2008",
                               "Shiotani, 2008 ,  2005",
                               "Shibata, 2002 ,  1993",
                               "Fukao, 1993 ,  1985",
                               "loess"), 
                      labels = c("Kikuchi,1998,1996",
                                 "Ogihara,2000,1990",
                                 "Yamagata,2000,1988",
                                 "Kikuchi,2005,1988",
                                 "Tamura,2012,2009",
                                 "Hirayama,2014,2008",
                                 "Shiotani,2008,2005",
                                 "Shibata,2002,1993",
                                 "Fukao,1993,1985",
                                 "TOTAL WOMEN")) + 
  ylab("Prevalence in Japanese women (%)") + 
  xlab("Birth Year") + 
  geom_smooth(aes(colour = "loess"), method = "loess") + 
  theme_bw()+
  theme(legend.position = "bottom", 
        axis.text.x = element_text(size = rel(1.3)), 
        axis.text.y = element_text(size = rel(1.5)), 
        axis.title.x = element_text(size = rel(1.5)), 
        axis.title.y = element_text(size = rel(1.5)), 
        legend.text = element_text(size = rel(1.2)),
        axis.text = element_text(size = 12, face = "bold"), 
        legend.direction = "horizontal")
multiplot(Men, Women, cols = 2)

Men only

library(plotly)
Men <- ggplot(data_sex, aes(x = birth.year_high, 
                  y = men,
                  color = Author, 
                  size = n_m)) + 
  geom_line(linetype = "dashed", size = 1.2) + 
  geom_point() +
  scale_x_continuous(breaks = seq(1900, 2005, 5)) + 
  scale_y_continuous(limits=c(0,100),breaks = seq(0,100,5))+
  scale_colour_manual(name = "",
                      values = c("#EE1289", "#7FFFD4", "#838B8B", "#000000", "#0000EE", "#8B2323", "#32CD32", "#4F94CD", "#CD4F39", "#CD853F"), 
                      limits=c("Kikuchi, 1998 ,  1996", 
                               "Ogihara, 2000 ,  1990",
                               "Yamagata, 2000 ,  1988",
                               "Kikuchi, 2005 ,  1988",
                               "Tamura, 2012 ,  2009",
                               "Hirayama, 2014 ,  2008",
                               "Shiotani, 2008 ,  2005",
                               "Shibata, 2002 ,  1993",
                               "Fukao, 1993 ,  1985",
                               "loess"), 
                      labels = c("Kikuchi,1998,1996",
                                 "Ogihara,2000,1990",
                                 "Yamagata,2000,1988",
                                 "Kikuchi,2005,1988",
                                 "Tamura,2012,2009",
                                 "Hirayama,2014,2008",
                                 "Shiotani,2008,2005",
                                 "Shibata,2002,1993",
                                 "Fukao,1993,1985",
                                 "TOTAL MEN")) + 
  ylab("Prevalence in Japanese men (%)") + 
  xlab("Birth Year") + 
  geom_smooth(aes(colour = "loess"), method = "loess") + 
  theme_bw()+
  theme(legend.position = "none", 
        axis.text.x = element_text(size = rel(1.3)), 
        axis.text.y = element_text(size = rel(1.5)), 
        axis.title.x = element_text(size = rel(1.5)), 
        axis.title.y = element_text(size = rel(1.5)), 
        legend.text = element_text(size = rel(1.2)),
        axis.text = element_text(size = 12, face = "bold"), 
        legend.direction = "horizontal") 
ggplotly(Men) 

Women only

Women <- ggplot(data_sex, aes(x = birth.year_high, 
                  y = women,
                  color = Author,
                  size = n_f)) + 
  geom_line(linetype = "dashed", size = 1.2) + 
  geom_point() +
  scale_x_continuous(breaks = seq(1900, 2005, 5)) + 
  scale_y_continuous(limits=c(0,100),breaks = seq(0,100,5))+
  scale_colour_manual(name = "",
                      values = c("#EE1289", "#7FFFD4", "#838B8B", "#000000", "#0000EE", "#8B2323", "#32CD32", "#4F94CD", "#CD4F39", "#CD853F"), 
                      limits=c("Kikuchi, 1998 ,  1996", 
                               "Ogihara, 2000 ,  1990",
                               "Yamagata, 2000 ,  1988",
                               "Kikuchi, 2005 ,  1988",
                               "Tamura, 2012 ,  2009",
                               "Hirayama, 2014 ,  2008",
                               "Shiotani, 2008 ,  2005",
                               "Shibata, 2002 ,  1993",
                               "Fukao, 1993 ,  1985",
                               "loess"), 
                      labels = c("Kikuchi,1998,1996",
                                 "Ogihara,2000,1990",
                                 "Yamagata,2000,1988",
                                 "Kikuchi,2005,1988",
                                 "Tamura,2012,2009",
                                 "Hirayama,2014,2008",
                                 "Shiotani,2008,2005",
                                 "Shibata,2002,1993",
                                 "Fukao,1993,1985",
                                 "TOTAL WOMEN")) + 
  ylab("Prevalence in Japanese women (%)") + 
  xlab("Birth Year") + 
  geom_smooth(aes(colour = "loess"), method = "loess") + 
  theme_bw()+
  theme(legend.position = "none", 
        axis.text.x = element_text(size = rel(1.3)), 
        axis.text.y = element_text(size = rel(1.5)), 
        axis.title.x = element_text(size = rel(1.5)), 
        axis.title.y = element_text(size = rel(1.5)), 
        legend.text = element_text(size = rel(1.2)),
        axis.text = element_text(size = 12, face = "bold"), 
        legend.direction = "horizontal")
ggplotly(Women)