How Long Can I Live

The (How long can I live) app is served as an interactive tool which helps you to
1. understand how many years left (Life Expectancy) for you at your age
2. how likely you would die (Moratility Rate) within this year

Also and more importantly, you can use several sliders (exercise, walk, cigarette consumption, and driving mileage) to see how the change in the life style can make a difference.

1. Dataset
   1.1 The foundamental dataset comes from Australian Bureau of Statistics.
   1.2 It is in a format of life table, with a list of important parameters, such as death rate, life expectancy.
   
2. Fomula and calculation
   1.1 Based on the life table, motality rate (mx(x)) is calcualtd with the below formula:
   \[ L(x) = l(x) + \frac {1} {2} l(x) q(x) \] \[ m(x) = \frac {l(x) q(x)} {L(x)} \] p.s.
   l(x) is the total number of people survised at a certain year
   q(x) is the death rate at a certain year
   L(x) is the total number of people who are alive between a certain age and age + 1
   

1. More parameters are added as they strongly contribute to the life span
   

1.1 Exercise:
1 more hour on exercise per week will result in 4 days more in life expectancy each year

1.2 30-min Brisk Walk:
More than 6 times of 30-min Brisk walk per month will result in 44% decrease in death rate

1.3 Cigarette Consumption:
1 more cigarette per week will result in 3 days less in life expectancy each year

1.4 Driving Mileage
1000 miles more per year will result in .00365 day less in life expectancy each year

par(mfrow=c(1,2))
plot(x = df_life$Age, y = df_life$ex, col = df_life$gender, main = "Age and Life Expectancy", xlab = "Age", ylab = "Life Expectancy")
plot(x = df_life$Age, y = df_life$mx, col = df_life$gender, main = "Age and Motality Rate", xlab = "Age", ylab = "Motality Rate")