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Reporting from CNN on Wednesday (16/9), a link between lack of sleep and a greater body mass index (BMI) has been shown in a number of studies, but researchers usually rely on participants’ memories to record how well they sleep. (Read Also: Natural and Halal Ingredients, Trulife by Tupperware Essential Oil Is Here To Fulfill Community Needs)
Sleep apps on fitness trackers, smartphones and watches have changed all that. In a Education published in JAMA Internal Medicine, researchers tracked the sleep quality of 120,000 people over two years. The results showed that sleep duration and patterns varied widely between people.
Nonetheless, the study found people with a BMI of 30 or more – considered obese by the US Centers for Disease Control and Prevention – had slightly shorter sleep durations and more varied sleep patterns. No need for sleep deprivation to see the effect. People with a BMI above 30 slept about 15 minutes less than their less weighty counterparts.
There are several limitations to this study. Naps are excluded, other health conditions cannot be taken into account, and people using wearable tracking devices are generally younger, healthier, and of higher socioeconomic status than those who do not use the tracker.
“These are quite expensive devices, and remember, they are not approved by the US Food and Drug Administration,” says sleep specialist Dr. Raj Dasgupta, Program Director of the Association’s Sleep Medicine Fellowship at Keck Medicine, University of Southern California.
“The results need to be validated by an FDA-approved device, and since the study was most likely conducted on young, economically wealthier people, does that really apply to older people we worry about having poor sleep?” (Read Also: Study: Pneumothorax Emerges as a New Complication of COVID-19)
Although unable to determine the direction of the association from the study results, these findings provide further support for the idea that sleep patterns are associated with management body weight and health overall. The findings also support potential values, including sleep duration and individual sleep patterns when studying sleep-related health outcomes.
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