---
title: "Fetal Deaths Analysis"
output: 
  flexdashboard::flex_dashboard:
    theme:
      version: 4
      bootswatch: journal
      primary: "#2be1ef"
    orientation: columns
    vertical_layout: fill
    source_code: embed
---

<style type="text/css">
.chart-title {  /* chart_title  */
font-size: 16px;
}
</style>

```{r setup, include=FALSE}
library(flexdashboard)
```

Fetal Death Analysis
===

Column {data-width=550}
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### The Data

I analyzed a dataset that showed the amount of fetal deaths for women with specific characteristics. The characteristics that I will be studying are state of residency, age group, race, weight of the fetus(group), and delivery method in relation to fetal deaths. I will answer five research questions: What states have the highest and lowest fetal death counts? Show age group's affect on fetal death number. Show distribution of fetal deaths in relation to race. Fetus weight group in relation to fetal deaths. Lastly, delivery method in relation to fetal deaths. I will be providing analysis for these questions.

The signifigance of this study is that it can help to determine the major factors in fetal deaths. Knowing what factors affect the liklihood of fetal deaths could help to prevent them in the future.

```{r package_data}
library(tidyverse)
Fetal_Deaths <- read_tsv("Fetal_Deaths.txt")
Fetal_Deaths <- Fetal_Deaths[-c(1,3)]
colnames(Fetal_Deaths) <- c("State", "Age", "Age_Code", "Race", "Race_Code", "Weight", "Weight_Code", "Method", "Method_Code", "Deaths")
Fetal_Deaths <- mutate(Fetal_Deaths,
      Deaths_num = as.numeric(Deaths))
Fetal_Deaths[-c(1),] %>% glimpse()
```

Column {data-width=450}
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### Fetal Deaths by States

```{r}
By_State <- Fetal_Deaths %>%
  group_by(State) %>%
  summarise(Total_Deaths = sum(Deaths_num))
arrange(By_State, Total_Deaths, desc(52))
  #California, Texas, Florida
#Rhode Island, Vermont, Alaska
#Probably would correlate highly with total population of state
#The top 3 states for fetal deaths are California, Texas, and Florida respectively. There are 136,915 fetal deaths total in every state. From that we can tell that California makes up 12% of all fetal deaths in the US, while making up 12% of the US population. Texas makes up 9% of both fetal deaths and US population. Lastly, Florida makes up 6.4% of the US population and 7.4% of fetal deaths. This data shows us that the state in which the mother has little to no affect on the risk of a fetal death.
```

The top 3 states for fetal deaths are California, Texas, and Florida respectively. There are 136,915 fetal deaths total in every state. From that we can tell that California makes up 12% of all fetal deaths in the US, while making up 12% of the US population. Texas makes up 9% of both fetal deaths and US population. Lastly, Florida makes up 6.4% of the US population and 7.4% of fetal deaths. This data shows us that the state in which the mother has little to no affect on the risk of a fetal death.

Results
===

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### Age Group in Relation to Fetal Death Count

```{r}
By_Age <- Fetal_Deaths %>%
  group_by(Age) %>%
  summarise(Total_Deaths = sum(Deaths_num))
arrange(By_Age, Total_Deaths, desc(52))
#The average age to give birth in the US is 30 years old. The average age to give birth for the first time is 27 years old. This data seems to show that fetal deaths are not correlated to the age of the mother, rather the amount of mothers giving birth at that age. This information is helpful because it shows that, within reason, the age at which a woman has a child will not affect the likliehood of a fetal death. 
```

The average age to give birth in the US is 30 years old. The average age to give birth for the first time is 27 years old. This data seems to show that fetal deaths are not correlated to the age of the mother, rather the amount of mothers giving birth at that age. This information is helpful because it shows that, within reason, the age at which a woman has a child will not affect the likelihood of a fetal death.

Column {data-width=500}
-----------------------------------------------------------------------

### Race in Relation to Fetal Deaths

```{r}
By_Race <- Fetal_Deaths %>%
  group_by(Race) %>%
  summarise(Total_Deaths = sum(Deaths_num))
arrange(By_Race, Total_Deaths, desc(52))
```

There are 136,915 fetal deaths accounted for in this study. 44% of fetal deaths come from white mothers, however 60% of females in the United States are white. This suggests that white females are less likely to have a fetal death, have less children on average, or make up a large percentage of the unknown or unlisted race group. Black females account for 27% of fetal deaths, while being 13% of the US female population. This very large discrepancy appears to be due to the long lasting effects of racism. Interestingly white women are projected to make up only 44% of the US female population by 2060, while the population of black women is projected to grow to 15% in the same time. This could mean this discrepancy is slowly becoming more even. Hispanic women account for 19% of fetal deaths and are 18% of the US female population. Asian women make up 5% of the US female population and have 3% of US fetal deaths. These are very close and suggest that being Asian or Hispanic has no effect on likelihood of a fetal death.


Results Continued
===

Column {data-width=500}
---   

### Fetal Weight in Relation to Fetal Deaths

```{r}
By_Weight <- Fetal_Deaths %>%
  group_by(Weight) %>%
  summarise(Total_Deaths = sum(Deaths_num))
arrange(By_Weight, Total_Deaths, desc(52))
# The average birth weight is 3000-3499 grams, while low birth weight is defined as less than 2500 grams. The most fetal deaths occur with fetus' born at 1499 grams or less. This makes sense because this is significantly lower than both the average and a low birth weight. This is where the data gets interesting: The 2500-8165 grams group has a higher death count than the 1500-2499 grams group. This suggests that as weight increases dramatically, fetal deaths would increase. This data would be much more useful if the 2500-8165 grams group was broken up into two groups, making it possible to see the relevance of high weight in fetal deaths.
```

The average birth weight is 3000-3499 grams, while low birth weight is defined as less than 2500 grams. The most fetal deaths occur with fetus' born at 1499 grams or less. This makes sense because this is significantly lower than both the average and a low birth weight. This is where the data gets interesting: The 2500-8165 grams group has a higher death count than the 1500-2499 grams group. This suggests that as weight increases dramatically, fetal deaths would increase. This data would be much more useful if the 2500-8165 grams group was broken up into two groups, making it possible to see the relevance of high weight in fetal deaths.

Column {data-width=500}
---

### Delivery Method in Relation to Fetal Deaths

```{r}
By_Method <- Fetal_Deaths %>%
  group_by(Method) %>%
  summarise(Total_Deaths = sum(Deaths_num))
arrange(By_Method, Total_Deaths, desc(52))
#In the US in 2020, there were approximately 2.5 million vaginal deliveries and there were 1.149 million cesarean deliveries. Using this additional data, we can tell that vaginal deliveries have a 4.6% fetal death rate and cesarean deliveries have a 1.8% fetal death rate. I have decided to not analyze the fetal deaths that do not have a delivery method stated. This data is incredibly useful, as it shows that the cesarean delivery method is much safer than the vaginal delivery method.
```

In the US in 2020, there were approximately 2.5 million vaginal deliveries and there were 1.149 million cesarean deliveries. Using this additional data, we can tell that vaginal deliveries have a 4.6% fetal death rate and cesarean deliveries have a 1.8% fetal death rate. I have decided to not analyze the fetal deaths that do not have a delivery method stated. This data is incredibly useful, as it shows that the cesarean delivery method is much safer than the vaginal delivery method.    

Limitations
===

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---

This study does have limitations, as what appears to be the cause of more fetal deaths, might not be at all. Of the assumptions I made, I believe that most are reasonable assumptions, however this could be argued by others. There are many other factors that could imapct the likelihood of fetal deaths. Further study should include more factors, comparing new factors to old factors. If data is available, it could be interesting to compare fetal deaths across different countries instead of different states across the US.


References
===

https://wonder.cdc.gov/wonder/help/Fetal-Deaths.html

https://www.verywellfamily.com/baby-birth-weight-statistics-2633630#:~:text=The%20average%20weight%20at%20birth%20was%20between%206,less%20than%205%20pounds%2C%208%20ounces%20%282%2C500%20grams%29

https://www.cdc.gov/nchs/fastats/delivery.htm#:~:text=Number%20of%20Cesarean%20deliveries%3A%201%2C148%2C692%20Percent%20of%20all,for%202020%2C%20table%2017%20%5BPDF%20%E2%80%93%201%20MB%5D

https://www.catalyst.org/research/women-of-color-in-the-united-states/#:~:text=Percentage%20of%20Total%20Women%20in%20US%20Population%20%282019%29,Native%20Hawaiian%20and%20Other%20Pacific%20Islander%3A%200.2%25%3A%200.3%25

https://www.nbcnews.com/news/motherhood-deferred-us-median-age-giving-birth-hits-30-rcna27827

https://www.cia.gov/the-world-factbook/field/mothers-mean-age-at-first-birth/