Skip to contents

Every year, the US releases to the public a large data set containing information on births recorded in the country. This data set has been of interest to medical researchers who are studying the relation between habits and practices of expectant mothers and the birth of their children. This is a random sample of 1,000 cases from the data set released in 2014.

Usage

births14

Format

A data frame with 1,000 observations on the following 13 variables.

fage

Father's age in years.

mage

Mother's age in years.

mature

Maturity status of mother.

weeks

Length of pregnancy in weeks.

premie

Whether the birth was classified as premature (premie) or full-term.

visits

Number of hospital visits during pregnancy.

gained

Weight gained by mother during pregnancy in pounds.

weight

Weight of the baby at birth in pounds.

lowbirthweight

Whether baby was classified as low birthweight (low) or not (not low).

sex

Sex of the baby, female or male.

habit

Status of the mother as a nonsmoker or a smoker.

marital

Whether mother is married or not married at birth.

whitemom

Whether mom is white or not white.

Source

United States Department of Health and Human Services. Centers for Disease Control and Prevention. National Center for Health Statistics. Natality Detail File, 2014 United States. Inter-university Consortium for Political and Social Research, 2016-10-07. doi:10.3886/ICPSR36461.v1 .

Examples


library(ggplot2)

ggplot(births14, aes(x = habit, y = weight)) +
  geom_boxplot() +
  labs(x = "Smoking status of mother", y = "Birth weight of baby (in lbs)")


ggplot(births14, aes(x = whitemom, y = visits)) +
  geom_boxplot() +
  labs(x = "Mother's race", y = "Number of doctor visits during pregnancy")
#> Warning: Removed 56 rows containing non-finite values (stat_boxplot).


ggplot(births14, aes(x = mature, y = gained)) +
  geom_boxplot() +
  labs(x = "Mother's age category", y = "Weight gained during pregnancy")
#> Warning: Removed 42 rows containing non-finite values (stat_boxplot).