Being an avid coffee drinker since the age of ten has caused me to hear the statement “coffee stunts your growth” many more times than I’d like to hear over the last eight years. When I was younger, any place I requested coffee someone immediately said it. Now that I’m older no one makes that comment when I’m enjoying a nice cup of coffee. I personally can’t see how this would even be possible. How could a little bit of caffeine prevent you from growing into your full potential. Are people saying that I would be 5’6 or maybe 5’4 instead of my 5’3 self if I had not drank coffee throughout these years?
The immediate answer I got was “No, coffee does not stunt your growth” according to kids health.org. But then why do I hear this all the time? Studies show that there is absolutely no correlation between coffee drinking and growth rate. A study was done on 81 teenagers over the course of six years. By the end of the study, there was no difference in bone density between the ones who were avid coffee drinkers and ones who drank the least amount of caffeine. Although this study disproved that a cup of coffee day will stunt your growth, doesn’t mean that coffee doesn’t have any negative side effects on growing children, but they are all minor. For example, headaches, irritability, and fatigue. So according to the studies done on coffee and growth stunt, I didn’t lose any inches due to my coffee addiction, which is exactly what I had predicted in the first place. In that case, I will continue to drink as much coffee as I’d like.
http://kidshealth.org/teen/expert/nutrition/coffee.html
http://science.howstuffworks.com/innovation/edible-innovations/coffee-stunt-growth1.htm
I also heard “coffee will stunt your growth” as a child. But I was never a big coffee drinker. The results gathered could very much be due to chance. Also does genetics play a part in this at all. With this study we must think about many of the other possibilities, such as diet and daily activities. Because this study does not show there was a correlation between the two variables we can not assume causation like you mentioned. In this study, with the lack of evidence supporting a correlation, we fail to reject the null hypothesis. This is a great example of a key feature in science; an acceptance that strongly held beliefs might be wrong.