#datalinks

A recent study that makes use of Fitbit sleep data finds links between illness and sleep. The largest study of its sort emphasizes how valuable it may be to use Fitbit sleep data that is collected over time for research on health and illness.

They can all agree that getting a good night’s sleep is crucial, but most individuals might not be aware of the long-term health effects of daily fluctuations in sleep duration and quality. Based on data from Fitbit users, a recent study published in Nature Medicine provides insight into the ways that sleep regularity, quality, and length affect a variety of health consequences.

Researchers from Google, the NIH’s All of Us Research Program, and Vanderbilt University Medical Centre collaborated on the largest study of its kind to date. This work deviates from earlier sleep research, which were frequently small-scale and focused on self-reported sleep diaries, short-term movement monitor sessions, or costly in-lab sleep studies that lasted for a short while.

Rather, the study was based on about 6.5 million sleep nights gathered over an average of 4.5 years of wear from over 6,700 Fitbit sleep data users who were part of the All of Us Research Program.

Fitbit sleep data analysis

The study does not concentrate on a specific group of health outcomes; rather, it examines the connections between sleep and the full range of human diseases. Six major conclusions from the studies on the effects of sleep on people’s health are as follows:

Sleep duration: A substantial reduction in the likelihood of obesity and sleep apnoea was found for every additional hour of sleep. It has been discovered that numerous illnesses are linked not only to insufficient sleep but also to excessive sleep.

Sleep stages: Heart health and mental wellness appear to be significantly impacted by the balance of REM, light, and deep sleep, as indicated by Fitbit sleep data.

Sleep disturbances: Elevations in the Fitbit restlessness measure have been associated with an increased risk of hypothyroidism and sleep difficulties.

Sleep irregularity: A variety of problems affecting almost all organ systems have been linked to irregular sleep patterns. High blood pressure, obesity, psychiatric problems (depression, anxiety, bipolar disorder), and migraine headaches were found to have strong correlations with irregular sleep patterns.

Demographic variations: The study discovered notable variations in the median amount of sleep time among various groups. For instance, White participants slept longer than Black participants, and women tended to sleep longer than men. This emphasises that when studying and improving sleep health, individual variables and potential health inequities must be taken into account.

Lifestyle role: The research discovered a correlation between variations in sleep duration and lifestyle factors such as alcohol and tobacco use. This emphasises how interrelated health behaviours are and how crucial it is to address a variety of lifestyle factors in order to enhance sleep and general well-being.

The study also provided a very fascinating look at the typical time that people sleep. The average time for participants to fall asleep was 11:10 pm, and throughout their primary sleep window of the day, they slept for almost 6.7 hours. A considerable number of people even sneak in a nap in the afternoon, usually about 2:30.

Although the purpose of this study is not to propose Fitbit sleep data as a therapeutic tool, we believe that some of these findings will demonstrate to researchers the value of using affordable wearables and sleep monitors to investigate the potential effects of changing sleep patterns on population health over time.

The study also serves as a reminder that getting regular sleep is just as crucial as getting enough sleep.

A Complete Guide to Fitbit Sleep Data

Sleep is essential to health. Wearable technology makes sleep tracking easier and more enlightening. Wearable fitness technology leader Fitbit offers thorough sleep tracking to help customers understand and improve their sleep patterns. Fitbit sleep data, interpretation, and sleep improvement strategies will be covered in this guide.

How Fitbit Sleep Data

Fitbits measure sleep stages via heart rate and accelerometers. Fitbit Sleep Data can identify if you’re asleep, waking, or experiencing different sleep stages.

Fitbit Sleep Data Stages

Fitbit tracks four sleep stages:

Nighttime awakeness.

Light sleep is non-REM when your heart rate slows and you relax.

Immune function and recovery depend on deep sleep, the most peaceful non-REM state.

Memory and learning depend on dreaming and REM sleep.

Understanding Sleep Score

Fitbit’s Sleep Score evaluates sleep quality. This score is 0–100 and based on:

Total sleep time.

Restoration: Deep and REM sleep duration.

Consistency and balance of sleep stages.

The Meaning of Your Sleep Score.

Great (90-100): Your sleep is restful and regulated.

Good (80-89): Restful sleep with few disruptions.

Fair (60-79): Your sleep could be enhanced for greater repair.

Poor (<60): Restorative sleep requires significant improvements.

Detailed Sleep Analysis

Sleep Time: Total sleep time per night. Adults should sleep 7-9 hours per night, per Fitbit.

In Bed vs. Asleep: This measure relates in-bed time to sleep time. Significant differences may suggest sleep disruptions or trouble falling asleep.

Sleep Regularity: Sleep quality is affected by schedule consistency. Fitbit measures bedtime and wake-up time to promote sleep.

Fitbit measures HRV during sleep: To assess autonomic nervous system function. Better health and recovery are linked to higher HRV.

Improve Sleep Using Fitbit: Fitbit monitors your sleep and provides personalized advice to improve it.

Establish Sleep Routine: The same bedtime and waketime enhances your body’s schedule and sleep consistency.

Make Bedtime Relaxing: To relax your body, try reading, meditating, or having a warm bath before bed.

Optimize Sleep Environment: Keep your bedroom dark, quiet, and cold for sleep. Buying a comfy mattress and pillows can also improve sleep.

Restrict Screen Time: Phones, tablets, and laptops emit blue light that disrupts melatonin. Avoid screens an hour before bed.

Watch Your Coffee and Alcohol: Caffeine and alcohol affect sleep. Reduce intake, especially before bed.

Fitbit Premium Improves Sleep Insights

Advanced features like: Fitbit Premium provides deeper insights and assistance.

Personalized Sleep Reports: Long-term sleep analysis.

Guided programs: Customized sleep programs.

Advanced sleep metrics include respiration and oxygen saturation.

Conclusion

Sleep tracking from Fitbit helps you understand and improve sleep. Understand and use Fitbit data to improve sleep and health.

Privacy

I discovered Cracked Labs the other day and have been reading their reports and books. They're thorough research pieces about corporate uses of our data, and should be read by everybody that wants to have a precise picture of how data brokers work.    Corporate surveillance in everyday life.  How companies use personal data against people.  Networks of Control.  

Privacy

Germany edges toward Chinese-style rating of citizens.

In Germany, he points out, it starts out with the universal credit rating system known as a Schufa. Very much like its US counterpart FICO, Schufa is a private company that assesses the creditworthiness of about three-quarters of all Germans and over 5 million companies in the country. Anyone wanting to rent a house or loan money is required to produce their Schufa rating in Germany – or their FICO score in the US. Additionally, factors like “geo-scoring” can also lower your overall grade if you happen to live in a low-rent neighborhood, or even if a lot of your neighbors have bad credit ratings.

In other areas, German health insurers will offer you lower premiums if you don’t get sick as much. They may offer you even better premiums if you share data from your fitness-tracking device to show you’re doing your part to stay healthy. Anyone using websites like Amazon, eBay or Airbnb is asked to rate others and is rated themselves. Those who try to avoid being rated are looked at askance. An increasing number of consumers will be denied certain services or, say, mortgages if they don’t present some kind of rating.

Tech

Tired of texting? Google tests robot to chat with friends for you. At some point we'll just set our phones on autopilot mode and leave them on the table. Which is not necessarily bad.

Are you tired of the constant need to tap on a glass keyboard just to keep up with your friends? Do you wish a robot could free you of your constant communication obligations via WhatsApp, Facebook or text messages? Google is working on an AI-based auto-reply system to do just that.

Someone Is Sending Amazon Sex Toys to Strangers. Amazon Has No Idea How to Stop It. Another example of here is this algo, let's fool it now by feeding it some input we can control. Two relevant paragraphs:

Nikki’s story is part of a broiling internal mystery that is flummoxing Amazon, according to a source at the company: Someone is shipping out unsolicited products, frequently sex toys, to seemingly random customers, and the company does not yet know why they’re being purchased, and why they’re being shipped to people like Nikki.

[...]

Sources both in and out of Amazon have one theory. It’s called, in Amazon-speak, verified review hacking.

Amazon uses a review system that heavily weights “verified purchases”—reviews by users who have purchased a specific product through Amazon—over other reviews.

This could give sellers incentive to buy and ship their own products to strangers from dummy accounts. Those dummy accounts could then give the product a 5-star review and, in turn, help it surface higher in Amazon and Google searches.

Solutions to this have been proposed, however. On Dave Farber's IP list, this post appeared a few days ago:

The 'fix' is for Amazon to inject itself into the pipe in a way that the seller and vendor are unable to defeat. That is the 'card in the box.' Every order has an order number and Amazon can generate a URL through an Amazon URL shortening service that would indicate the order was fraudulent. If the recipient visits the URL you look for the review, if you find it you change it to "Fraudulent Reviewer" (you could remove it but public seller shaming is even better)

This is another example of how the information economy influences the goods economy. There the marginal value of the bogus review can be computed in terms of lifetime product sales affected.

AI-Moderators Fighting AI-Generated Porn Is the Harbinger of the Fake News Apocalypse. It begins with porn, will continue with everything else. I was talking to some friends in Madrid a few months ago about this topic, before the deepfake porn was a thing, and we concluded that we are walking towards a society in which the only news you'll believe are those aligned to what you already believe. It's going to be fun for all the wrong reasons.

This sounds great in theory, but as Wired points out, there are a few scenarios where deepfakes will slip through the cracks. If someone makes a deepfake of a private citizen—think vindictive exes or harassers scraping someone’s private Facebook page—and no images or videos of them appear publicly online, these algorithms won’t be able to find videos, and will categorize it as the original.

Data Links is a periodic blog post published on Sundays (specific time may vary) which contains interesting links about data science, machine learning and related topics. You can subscribe to it using the general blog RSS feed or this one, which only contains these articles, if you are not interested in other things I might publish.