**Graph of the Week**, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)

Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

*enjoy*it. Do this daily for years and your joints will be set up perfectly for a lifetime of pain and stiffness.

BMI

Average weight for adult men. |

That’s about 0.6 lbs (0.27 kg) per year. Like many trends, it doesn’t seem so bad when describing the rate, but over time it adds up rather quickly.

Since 1960, people have grown taller – about 0.9 inches (2.29 cm) taller for women and about 1.1 inches (2.79 cm) taller for men. So we are taller *and* heavier. That would explain some weight gain, but does it account for all 25 lbs? A little bit of math will reveal the answer:

→

**2.43 lbs/inch**

→

**2.75 lbs/inch**

*would*weigh in 1960 given our extra height, it would come out to about

**169 lbs**! Compare that to 191 lbs – a difference of

**22 lbs**(10 Kg)!

Conclusion

People in the United States are getting taller and heavier. The rate of the former (height) is much slower than the latter (weight). People are becoming more unhealthy as a result. Additionally, it can be difficult to enjoy life when toting around those extra pounds. The only resolution to this problem is to lose weight – permanently. The next two articles will present information why this trend has occurred while also shedding light on ways to possibly reverse it.

**Questions:**

1) How long can this trend continue?

2) What is the burden on health care due to obesity?

3) Are other countries experiencing similar problems?

**Data:**

**Code:**

These graphs were generated using the ‘ggplot2‘ and ‘maps‘ packages within the R programming language. Additional graphics were created/edited using GIMP.

```
```**1st graph:**
ggplot() +
geom_line(data = subset(bmi.frame, Description == "Obese (BMI >= 30.0)"), aes(x=Year, y=Median, color="Obese (BMI >= 30.0)"), size=2) +
geom_line(data = subset(bmi.frame, Description == "Overweight (BMI >= 25.0 and BMI <= 29.9)"), aes(x=Year, y=Median, color="Overweight (BMI >= 25.0 and BMI <= 29.9)"), size=1) +
geom_line(data = subset(bmi.frame, Description == "Neither overweight nor obese (BMI <= 24.9)"), aes(x=Year, y=Median, color="Neither overweight nor obese (BMI <= 24.9)"), size=1) +
geom_point(data = subset(bmi.frame, Description == "Obese (BMI >= 30.0)"), aes(x=Year, y=Median, color="Obese (BMI >= 30.0)"), size=3) +
geom_point(data = subset(bmi.frame, Description == "Overweight (BMI >= 25.0 and BMI <= 29.9)"), aes(x=Year, y=Median, color="Overweight (BMI >= 25.0 and BMI <= 29.9)"), size=2) +
geom_point(data = subset(bmi.frame, Description == "Neither overweight nor obese (BMI <= 24.9)"), aes(x=Year, y=Median, color="Neither overweight nor obese (BMI <= 24.9)"), size=2) +
ylab("% of Population") +
xlab("Year") +
scale_colour_manual(values=cbPaletteNoGray) +
opts(title="Body Mass Index (BMI) in the United States",
legend.title = theme_blank(),
panel.background = theme_blank(),
axis.line = theme_segment())

```
```**2nd graph:**
ggplot(weight.frame, aes(x=Date.Range, y=Weight.lb)) +
geom_point(aes(size=Weight.lb), color="dark red") +
geom_line(aes(group=1, size=Weight.lb), color="dark red") +
geom_smooth(aes(group=1), size=1, color="black", method="lm", na.rm=FALSE, fill=NA, linetype=2) +
ylab("Weight (pounds)") +
xlab("Year Range") +
opts(title="Weight Gain in the United States",
legend.title = theme_blank(),
panel.background = theme_blank(),
axis.line = theme_segment())

**Further Reading:**

**leave a comment**for the author, please follow the link and comment on their blog:

**Graph of the Week**.

R-bloggers.com offers

**daily e-mail updates**about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.

Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.