Project Proposal
Overview:
Infant Mortality is when an infant dies before their first birthday. According to the cdc, "In addition to giving us key information about maternal and infant health, the infant mortality rate is an important marker of the overall health of a society." (1). Many factors contribute to the health of a child in their first year. The most important determining factor for infant mortality is income (2). As such, we decided to look at infant mortality rate by state in the US and compare it to average income in these states and see if there exists a negative correlation between income and infant mortality. As time permits, we will also use webscraped data from the CDC where a separate page will hold an interactive graph that can compare income to a number of regional statistics such as fertility rate, teen birth rate, marriage rate, etc. These additional comparisons could garner insight into how differing median incomes across states affect quality of life and health in those states.
Datasets:
income data: table h-8 from census bureau https://www.census.gov/data/tables/time-series/demo/income-poverty/historical-income-households.html
infant mortality by state:
raw data from kidscount.com https://datacenter.kidscount.org/data/tables/6051-infant-mortality?loc=1&loct=1#detailed/1/any/false/37,871,870,573,869,36,868,867,133,38/any/12718,12719
cdc infant mortality map: https://www.cdc.gov/nchs/pressroom/sosmap/infant_mortality_rates/infant_mortality.htm
cdc infant cause of death: scrape each state page for additional data https://www.cdc.gov/nchs/pressroom/states/washington/wa.htm
Inspiration:
Leaflet state map:
Dropdown menu in bootstrap:
D3 interactive scatter plot:
sketch:
Link to github:
https://github.com/yutamoxley/Infant_Mortality
citations: (1) “Infant Mortality.” Centers for Disease Control and Prevention, Centers for Disease Control and Prevention, 27 Mar. 2019, www.cdc.gov/reproductivehealth/maternalinfanthealth/infantmortality.htm.
(2) O'Hare, Bernadette et al. “Income and child mortality in developing countries: a systematic review and meta-analysis.” Journal of the Royal Society of Medicine vol. 106,10 (2013): 408-14. doi:10.1177/0141076813489680