Irregular sleep patterns and lack of REM sleep are linked to increased risk of chronic diseases

A recent study published in the journal Nature MedicineA team of US researchers used longitudinal, objective measurements of sleep patterns and duration from wearable devices and electronic health records from the National Institutes of Health's (NIH) All of Us research programme to investigate associations between the development of chronic diseases and sleep duration, patterns and sleep stages.

study: Sleep patterns and risk of chronic disease measured by long-term monitoring with commercially available wearable devices in the All of Us research programImage credit: Feelimage / Shutterstock

background

A growing body of evidence supports the association between unhealthy sleep duration and the incidence of cardiometabolic, psychiatric, and chronic diseases, and all-cause mortality. Studies have shown a J-shaped association between sleep duration and health, with either too little or too much sleep associated with poorer health outcomes. The recommended sleep duration for adults is 7-9 hours per night.

However, the associations between sleep patterns, including regularity and sleep stages, and the incidence of chronic diseases remain unclear. Studies investigating these associations have relied heavily on self-reported data on sleep patterns, which are often inaccurate regarding longitudinal patterns and sleep stages.

Additionally, polysomnography, which records brainwaves, blood oxygen levels, and heart rate, has financial and time constraints and a lack of long-term studies, and actigraphy, which uses a non-invasive accelerometer, also has limitations in obtaining longitudinal data on sleep patterns and changes.

About the Research

In this study, the researchers used sleep data obtained from a commercially available wearable device to investigate whether sleep stages, including rapid eye movement (REM), N1, N2 and N3 stages, and sleep regularity, are associated with the development of chronic diseases.

The study used electronic health records obtained from the NIH's All of Us initiative, which aims to collect longitudinal health data from a diverse study population of more than 1 million U.S. residents.

The program asked individuals who regularly use Fitbit devices to share data from their wearable devices that was linked to their electronic health records, allowing clinical outcomes to be objectively measured against sleep patterns and physical activity data over time.

The researchers targeted association studies across phenotypes and assessment of chronic diseases to uncover links between sleep patterns and health in the general population.

Sleep data from the Fitbit devices consisted of time asleep, time spent asleep based on sleep movements, and sleep stages divided into REM, deep, and light sleep. Fitbit devices use movement and heart rate to estimate sleep patterns. From this data, the researchers calculated sleep irregularities and percentage of time in each sleep stage.

Incident diagnoses in the electronic health record were the primary outcomes examined in this study and included hypertension, obesity, generalized anxiety disorder, major depressive disorder, cardiovascular disease, hyperthyroidism, hyperlipidemia, and many other chronic conditions.

A survey was administered at the start of the study to collect demographic data, including gender, age, education level, race and ethnicity, as well as information on lifestyle factors such as alcohol consumption and smoking. This information was included as covariates when analyzing the association between sleep patterns and the incidence of chronic diseases.

result

The study found that deep sleep and REM sleep were inversely correlated with the likelihood of developing atrial fibrillation, while increased sleep irregularity increased the risk of hyperlipidemia, obesity, depression, hypertension, and anxiety disorders.

A heatmap of sleep duration is plotted against sleep onset time across every person's nights. All sleep periods were flagged as “main sleep” by their Fitbit device.

Consistent with previous studies, we found a J-shaped correlation between sleep duration and the incidence of anxiety disorders, hypertension, and major depression. There was also an association between the onset of insomnia and other sleep disorders and increased duration of insomnia.

People who did not regularly fall asleep between 8 pm and 2 am were at higher risk of circadian rhythm disorders, hypersomnia and insomnia. Results showed that people whose sleep onset times were within the “traditional” range of 8 pm to 2 am also had a lower risk of psychiatric disorders and high blood pressure.

Additionally, sleep irregularity was associated with more chronic disease risk than other sleep pattern changes. Researchers believe that sleep irregularity leads to desynchronization of circadian rhythms and sleep-wake cycles, affecting factors such as inflammation, insulin sensitivity, and serotonin receptor function.

A decreased percentage of deep or REM sleep was associated with an increased risk of atrial fibrillation and was further associated with a higher prevalence of obesity and coronary heart disease after adjusting the analysis for body mass index, sex, and age, suggesting that reduced deep or REM sleep patterns may be a potential indicator of atrial fibrillation and poorer overall cardiac health.

Conclusion

The study used longitudinal data from wearable devices and electronic health records to investigate associations between sleep stages and patterns and increased odds of chronic disease.

The results show that sleep duration, regularity and quality, including adequate time for each stage of sleep, are also essential for health. Insufficient deep and REM sleep, and irregular sleep patterns, have been found to increase the likelihood of atrial fibrillation, obesity, high blood pressure, and mental disorders such as depression and anxiety.