ncmp-obesity-imd.R

t11_raw = readxl::read_excel("nat-chil-meas-prog-eng-2020-2021-tab.xlsx", sheet = "Table 11", skip = 13)
t11 = t11_raw %>% 
  janitor::clean_names()
# names(t11)
names(t11)[1:2] = c("class", "year")
t11_most_deprived = t11 %>%
  select(class, year, prevalence_3) %>% 
  fill(class) %>% 
  filter(str_detect(string = class, pattern = "Reception|Year")) %>% 
  slice(-c(1:2)) %>% 
  mutate(year = as.numeric(str_sub(string = year, start = 1, end = 4))) %>% 
  mutate(`IMD decile` = "Most deprived IMD decile")
t11_least_deprived = t11 %>%
  select(class, year, prevalence_3 = prevalence_7) %>% 
  fill(class) %>% 
  filter(str_detect(string = class, pattern = "Reception|Year")) %>% 
  slice(-c(1:2)) %>% 
  mutate(year = as.numeric(str_sub(string = year, start = 1, end = 4))) %>% 
  mutate(`IMD decile` = "Least deprived IMD decile")

t11_most_least = bind_rows(t11_most_deprived, t11_least_deprived)
# t11$class
t11_most_least %>% 
  ggplot(aes(year, prevalence_3, colour = class)) +
  geom_line() +
  geom_vline(xintercept = 2019, colour = "grey", lty = 2) +
  xlab("Academic year starting") +
  ylab("% Obese") +
  ylim(c(0, NA)) +
  ggthemr::rotate_x_text(90) +
  scale_x_continuous(breaks = seq(from = 2006, to = 2020, by = 2)) +
  facet_grid(~ `IMD decile`) +
  labs(caption = "Source: National Child Measurement Programme.\nGraph: by Robin Lovelace with the R package ggplot2")