Maternal mortality is a public health issue because it determines the health of the future generation. Maternal mortality rates in the United States are rising and this often reflects inequalities and gaps in the system as approximately two-thirds of these deaths could have been prevented.
The disparities in our system can be highlighted with the scope of data collected from the National Vital Statistics System mortality file.
This data, if successful, could show potential risks for maternal mortality in the United States. This could be helpful in highlighting factors among patients that are correlated with maternal mortality.
It is important to note that this may indicate potential risks for mortality among mothers but it is not possible to tell for sure through this data whether it is a cause of death or just correlated with rates of death.
This displays a row and column of the pregnancy-related mortality ratio among different ethnicities.
import pandas as pd
raceethnicitydata = pd.read_csv('pregnancy_related_mortality_ratio_by_race_ethnicity__2016_2018.csv')
dfi = pd.DataFrame(raceethnicitydata)
dfi.head()
| Unnamed: 0 | Non-Hispanic Black | Non-Hispanic American Indian or Alaska Native | Non-Hispanic Asian or Pacific Islander | Non-Hispanic White | Hispanic | |
|---|---|---|---|---|---|---|
| 0 | Pregnancy-related mortality ratio | 41.4 | 26.5 | 14.1 | 13.7 | 11.2 |
Pregnancy related deaths will be observed among several different categories.
It was difficult to find a single dataset encompassing how the mortality ratios differ among various groups. This is one part of what we will include in our dataset. I am still looking for a better dataset or I might decide to combine multiple data sets into one dataframe to show a clearer picture of what indicates higher risks for pregnancy-related death such as education, wealth, age, etc.