Breastfeeding and Language
Mike Frank
9/28/2018
Investigation of the relationship between children’s knowledge of the word “bottle” and breastfeeding rates? Prediction is a negative correlation.
Specific questions (from email with Lee Saunders):
- Across nations: Is there an independent correlation between expressive vocabulary (age of onset of using the word “bottle”) and rates of exclusive breastfeeding?
- Across nations: Is there an independent correlation between expressive vocabulary (age of onset of using the word “bottle”) and rates of obesity during early childhood?
- Do socioeconomic factors partially or completely moderate either association?
library(tidyverse)## ── Attaching packages ─────────────────────────────────────────────── tidyverse 1.2.1 ──## ✔ ggplot2 3.0.0 ✔ purrr 0.2.5
## ✔ tibble 1.4.2 ✔ dplyr 0.7.5
## ✔ tidyr 0.8.1 ✔ stringr 1.3.1
## ✔ readr 1.1.1 ✔ forcats 0.3.0## ── Conflicts ────────────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()library(wordbankr)
library(here)## here() starts at /Users/mcfrank/Projects/breastfeedingWHO by-country data.
breastfeeding <- read_csv(here("WHOSIS_000006.csv"))## Parsed with column specification:
## cols(
## Country = col_character(),
## Year = col_character(),
## `Infants exclusively breastfed for the first six months of life (%)` = col_double()
## )For simplicity, take the country average, ignoring rate changes across eras. Obviously this should be re-examined.
names(breastfeeding) <- c("country","year","rate")
breastfeeding %<>%
group_by(country) %>%
summarise(rate = mean(rate))Get cross-linguistic data on bottle.
words <- get_crossling_data("bottle")## Warning in .local(conn, statement, ...): Decimal MySQL column 6 imported as
## numeric
## Warning in .local(conn, statement, ...): Decimal MySQL column 6 imported as
## numeric## Getting data for British Sign Language...## Warning in .local(conn, statement, ...): Decimal MySQL column 6 imported as
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## numeric## Getting data for Croatian...## Warning in .local(conn, statement, ...): Decimal MySQL column 6 imported as
## numeric
## Warning in .local(conn, statement, ...): Decimal MySQL column 6 imported as
## numeric## Getting data for Danish...## Warning in .local(conn, statement, ...): Decimal MySQL column 6 imported as
## numeric
## Warning in .local(conn, statement, ...): Decimal MySQL column 6 imported as
## numeric## Getting data for English (American)...## Warning in .local(conn, statement, ...): Decimal MySQL column 6 imported as
## numeric
## Warning in .local(conn, statement, ...): Decimal MySQL column 6 imported as
## numeric## Getting data for French (French)...## Warning in .local(conn, statement, ...): Decimal MySQL column 6 imported as
## numeric
## Warning in .local(conn, statement, ...): Decimal MySQL column 6 imported as
## numeric## Getting data for French (Quebecois)...## Warning in .local(conn, statement, ...): Decimal MySQL column 6 imported as
## numeric
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## numeric## Getting data for Hebrew...## Warning in .local(conn, statement, ...): Decimal MySQL column 6 imported as
## numeric
## Warning in .local(conn, statement, ...): Decimal MySQL column 6 imported as
## numeric## Getting data for Italian...## Warning in .local(conn, statement, ...): Decimal MySQL column 6 imported as
## numeric
## Warning in .local(conn, statement, ...): Decimal MySQL column 6 imported as
## numeric## Getting data for Kiswahili...## Warning in .local(conn, statement, ...): Decimal MySQL column 6 imported as
## numeric
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## numeric## Getting data for Norwegian...## Warning in .local(conn, statement, ...): Decimal MySQL column 6 imported as
## numeric
## Warning in .local(conn, statement, ...): Decimal MySQL column 6 imported as
## numeric## Getting data for Russian...## Warning in .local(conn, statement, ...): Decimal MySQL column 6 imported as
## numeric
## Warning in .local(conn, statement, ...): Decimal MySQL column 6 imported as
## numeric## Getting data for Slovak...## Warning in .local(conn, statement, ...): Decimal MySQL column 6 imported as
## numeric
## Warning in .local(conn, statement, ...): Decimal MySQL column 6 imported as
## numeric## Getting data for Spanish (Mexican)...## Warning in .local(conn, statement, ...): Decimal MySQL column 6 imported as
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## Warning in .local(conn, statement, ...): Decimal MySQL column 6 imported as
## numeric## Getting data for Swedish...## Warning in .local(conn, statement, ...): Decimal MySQL column 6 imported as
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## numeric## Getting data for Turkish...## Warning in .local(conn, statement, ...): Decimal MySQL column 6 imported as
## numeric
## Warning in .local(conn, statement, ...): Decimal MySQL column 6 imported as
## numericCountry averages, for comprehension.
ggplot(words,
aes(x = age, y = comprehension, col = definition)) +
geom_point() +
facet_wrap(~language) +
scale_color_discrete(guide = FALSE)
Production.
ggplot(words,
aes(x = age, y = production, col = definition)) +
geom_point() +
facet_wrap(~language) +
scale_color_discrete(guide = FALSE)
Average comprehension and production and merge.
avg_bottle <- words %>%
group_by(language, definition) %>%
filter(age > 9, age < 15) %>%
summarise(comprehension = mean(comprehension),
production = mean(production)) %>%
group_by(language) %>%
filter(comprehension == max(comprehension)) %>%
mutate(country = case_when(
language == "Croatian" ~ "Croatia",
language == "Danish" ~ "Denmark",
language == "English (American)" ~ "United States of America",
language == "French (French)" ~ "France",
language == "French (Quebecois)" ~ "Canada",
language == "Hebrew" ~ "Israel",
language == "Italian" ~ "Italy",
language == "Kiswahili" ~ "Kenya",
language == "Norwegian" ~ "Norway",
language == "Russian" ~ "Russia",
language == "Slovak" ~ "Slovakia",
language == "Spanish (Mexican)" ~ "Mexico",
language == "Swedish" ~ "Sweden",
language == "Turkish" ~ "Turkey"))
bottle_breastfeeding <- inner_join(avg_bottle, breastfeeding)## Joining, by = "country"Plot.
bb <- bottle_breastfeeding %>%
rename(breastfeeding_rate = rate) %>%
gather(language_measure, language_rate, comprehension, production)
ggplot(bb,
aes(x = breastfeeding_rate, y = language_rate, col = country)) +
geom_point() +
geom_smooth(aes(group = 1), method = "lm") +
ggrepel::geom_label_repel(aes(label = country), size = 3) +
facet_wrap(~language_measure) +
xlab("Average Rate of Breastfeeding") +
ylab("Average Rate of 'Bottle' 10-14mo") +
theme_bw() +
scale_color_discrete(guide = FALSE)
A major challenge is that we lost data from a lot of countries, including Russia, France, and Canada. This is likely due to the WHO not having data on these?