I picked the three variables: obesity, diabetes, and no medical care due to costs. Obesity is a growing problem for Americans of all ages. Diabetes statistics are also increasing due to unhealthy eating habits, which can be linked with obesity as well. The map is a clear representation of correlation between these two variables because the areas that have a high percentage diabetic residents are also having problems with obesity. Finally, the last factor shows how people in certain areas are suffering from these conditions yet they do not receive medical care because of the cost. These people might also not have the money to buy organic food and instead, they have to turn to cheaper alternatives. This variable seems to affect people from all over the borough of Manhattan.

The reason why I chose the variable “those who tried to quit smoking” was because I was not aware that so many people in my neighborhood, Greenpoint, wanted to quit smoking.  Not only that, Greenpoint is actually one of the top five neighborhoods in the borough that wanted to quit.  As I was doing my research, I read about the pollution, the toxic waste, and the developmental plans but nothing about smoking.  Thus, it caught me by surprise.  I compared it with those who smoked at least 100 cigarettes in their entire life to get a sense of the size of the population of smokers.  Interestingly enough, there weren’t quite as much as I expected in Greenpoint.

Based on the map, the shades of black shows the different neighborhoods and the percentage people wanted to quit smoking.  Since Greepoint is one of the darkest, it is one of the neighborhoods that have tried to quit smoking the most.  Along with that, the red helps display the spread of smokers who had at least 100 cigarettes in their entire life throughout the borough. The darker the shade of red, the more smokers there are.