The primary differences between the two are that the One measures flights climbed as well as sleep. While the flights climbed is a pretty good data point considering the work is more vertical than walking on flat ground, the biggest benefit of the Fitbit One is the sleep data. This data is useful to help identify issues you may be having with:
- Identifying lifestyle factors that can impact sleep
- Identifying food sensitivities you may have
- Not getting enough physical activity
- Getting too much physical activity
- How your sleep changes over time
- How your sleep changes over the week
As you can see, the app gives you data on how long you were asleep, when you went to bed and when you woke up, and when you were restless or awake throughout the night. All of this is good data to have and can illustrate things that you may be doing that aren't particularly good for your health. However, one of the knocks on the sleep data the Fitbit collects is that it isn't really measuring if you are asleep. Since it is merely worn on your wrist, all it is measuring is whether or not you are moving. In other words, you can just lie still and it will measure you as asleep. This is really isn't a problem if you look at the data.
Anyone can see the difference between these two sleep patterns. Whether you are attempting to stay as still as possible or not, there is something going on in night 1 that isn't in night 2. Keep in mind that these are both Thursday's sleep which means they were recorded on Wednesday night in to Thursday morning. First, we can see that while the first Thursday's sleep was almost 45 minutes longer, it was of much poorer quality. There was more than likely something going on either on this day or leading up to this day that led to poor sleep. There are several reasons why this may happen when comparing the same day of the week over time.
1) Hidden food sensitivities
It is possible that something or some things were eaten on the first Thursday that weren't on the second Thursday that negatively impacted sleep. A common symptom of a food sensitivity is poor sleep, and not all food sensitivities will have overt GI symptoms. Since the best way to identify a food sensitivity is to make a food journal, you can compare the two. Luckily, the Fitbit allows you to log all of your food so you can easily enter it in the App or Dashboard and access it from either. Over time you can narrow down foods you are sensitive to by eliminating foods one at a time and watching how they affect your sleep cycle.2)Stress
Too much stress can also negatively impact sleep. Maybe you were approaching a deadline at the end of the week of the first night but not the second. Obviously you can look at this and see the effect stress has on sleep quality, even if you get to sleep in. You can also record subjective info like this on your Fitbit Dashboard or in the App. The benefit in this situation is that you can see that you should take active steps to manage stress or your sleep will suffer.3)Too little physical activity or too much
You can compare the sleep data from both days to the step data on both days and see if you may have slacked on getting your steps in. Too little physical activity during the day can lead to a surplus of energy at night and difficulty sleeping. On the flip side, you could be entering a state of overtraining by overexercising. This will cause your body to shift in to fight or flight mode which will make it more difficult for you to get in to rest and digest mode. In this instance you will want to cut back on your exercise for a while until your sleep improves.4)Whether an intervention is working over time
Most people associate the word intervention with a drug or alcohol problem. What I am referring to here is a health intervention you apply to a health condition. If you are having problems and try to remedy the situation, looking at how the intervention affects your sleep can be a huge benefit. In this instance you wouldn't use just two data points, but if all of the other data points trend in the right direction you know you are on the right path.You can also look at the data over the course of a week to find trends.
