Caesarean section rates and peripartum outcomes

- 4 mins

I recently saw an interesting Tweet which got me to thinking what the associations were between Caesarean section rates in different countries and maternal and baby outcomes:

So I went away and looked for the OECD data which might help with looking at this question. I found 2 sources from the OECD website, one for the Caesarean section rates and another for the outcomes. I used the 2015 data (the most recent available).

#Load the required packages
library(tidyverse)
library(readr)
library(ggrepel)

#Load the data
Caesarean_rates <- read_csv("../data/DP_LIVE_13042018135921941.csv")
Outcomes <- read_csv("../data/HEALTH_STAT_13042018135958973.csv")

#Join the two sources
Caesarean_rates <- Caesarean_rates %>% filter(TIME == 2015) %>%
  select(LOCATION, TIME, Caesarean_rate = Value)

Outcomes <- Outcomes %>% filter(Year == 2015, VAR != "MATINETW", VAR != "MATIINTW") %>%
  select(COU, VAR, Country, Variable, Year, Outcome_Value = "Value") %>%
#rename the variables into something more understandable
  mutate(VAR = recode(VAR, `MATIINFA` = "Infant mortality",
                      `MATIMATM` = "Maternal mortality",
                      `MATINEON` = "Neonatal mortality",
                      `MATIPERI` = "Perinatal mortality"))

Combined <- left_join(Outcomes, Caesarean_rates, by = c(COU = "LOCATION"))

#Plot the data
ggplot(data = Combined , aes(x = Caesarean_rate, y = Outcome_Value)) + 
  geom_point() +
  geom_smooth(method = "lm") +
  geom_text_repel(aes(label = Country)) +
  facet_wrap(~ VAR, nrow = 2) +
  labs(x = "Caesarean sections (per 1,000 live births)",
       y = "Deaths (per 1,000 live births)") +
  theme_light()

center

So it seems that all outcomes are worse in countries with higher Caesarean section rates. Of course this is not causal. But it’s an interesting association. Also Latvia seems to have a huge maternal mortality compared to all the other OECD countries, and is not an outlier for baby deaths. I wonder what that’s all about.

sessionInfo()
## R version 3.4.2 (2017-09-28)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows >= 8 x64 (build 9200)
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## Matrix products: default
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## locale:
## [1] LC_COLLATE=English_United Kingdom.1252 
## [2] LC_CTYPE=English_United Kingdom.1252   
## [3] LC_MONETARY=English_United Kingdom.1252
## [4] LC_NUMERIC=C                           
## [5] LC_TIME=English_United Kingdom.1252    
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
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## other attached packages:
##  [1] knitr_1.17      ggrepel_0.7.0   bindrcpp_0.2    forcats_0.2.0  
##  [5] stringr_1.2.0   dplyr_0.7.4     purrr_0.2.4     tidyr_0.7.2    
##  [9] tibble_1.4.2    ggplot2_2.2.1   tidyverse_1.2.1 readr_1.1.1    
## [13] sp_1.2-3       
## 
## loaded via a namespace (and not attached):
##  [1] tidyselect_0.2.3 reshape2_1.4.3   haven_1.1.0      lattice_0.20-35 
##  [5] colorspace_1.2-6 htmltools_0.3.6  yaml_2.1.14      rlang_0.2.0     
##  [9] pillar_1.2.1     foreign_0.8-66   glue_1.1.1       modelr_0.1.1    
## [13] readxl_1.0.0     bindr_0.1        plyr_1.8.4       munsell_0.4.3   
## [17] gtable_0.2.0     cellranger_1.1.0 rvest_0.3.2      psych_1.6.9     
## [21] evaluate_0.10.1  labeling_0.3     parallel_3.4.2   highr_0.6       
## [25] broom_0.4.2      Rcpp_0.12.14     scales_0.5.0     backports_1.0.5 
## [29] jsonlite_1.5     mnormt_1.5-5     hms_0.4.2        digest_0.6.14   
## [33] stringi_1.1.7    grid_3.4.2       rprojroot_1.2    cli_1.0.0       
## [37] tools_3.4.2      magrittr_1.5     lazyeval_0.2.0   crayon_1.3.4    
## [41] pkgconfig_2.0.1  rsconnect_0.7    xml2_1.1.1       lubridate_1.7.1 
## [45] assertthat_0.2.0 rmarkdown_1.7    httr_1.3.1       rstudioapi_0.7  
## [49] R6_2.1.2         nlme_3.1-131     compiler_3.4.2
Danny Wong

Danny Wong

Anaesthetist & Health Services Researcher

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