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Study Finds Significant Associations Between Sunlight Exposure, Physical Activity, and Depressive States
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Key Takeaways
- Sunlight exposure and physical activity are significantly associated with mood disorders, influencing seasonal symptom patterns in MDD and BD.
- Accelerometer data revealed lower daily activity in individuals with MDD compared to healthy controls, correlating with photoperiod and solar insolation.
According to the authors, being able to identify mood disturbances through passive digital biomarker data can be promising in next-generation predictive, personalized mental health diagnostics.
New research published in PLOS Mental Health demonstrates evidence of a relationship between daily sunlight exposure and physical activity in individuals with and without depression. Mood disorders such as major depressive disorder (MDD) and bipolar disorder (BD) often display a seasonal pattern of symptoms, but prior to this study, little was known about the influence of day length (photoperiod) and sunlight intensity (solar insolation) on seasonal patterns in these conditions.1
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In this study, authors used a quantitative approach to evaluate the relationship between sunlight measures and objectively measured movement activity patterns to better understand environmental factors that drive seasonality in MDD and BD. Patients were enrolled from the Depresjon dataset, which consists of motor activity series recorded for 23 patients with depression who have unipolar disorder or BD, as well as 32 healthy controls. Motor-activity recordings that were collected via wrist-based accelerometers—which measured the rate of change in the velocity of an object with respect to time—were gathered from all participants and were recorded up to 2 weeks.1,2
“Individuals with seasonal mood disorders may not yet recognize the pattern of their illness. One of the goals of our study is to motivate the development of digital tools to assist clinicians and help affected individuals with self-management of their symptoms,” explained the authors in a news release.1
According to the findings, the recorded motor activity demonstrates a significant association of daytime physical activity that was recorded by the accelerometer with the participants’ depressed states (p < .001), photoperiod (p < .001), and solar insolation (p < .001). Individuals with MDD had a significantly lower daily activity compared with the healthy controls. Daily activity was also observed to have a visually linear correlation with daily solar insolation and photoperiod for both depressed and healthy individuals. According to the authors, these findings could indicate that those who are depressed might exhibit an altered physiological link between energy input and physical activity. Alternatively, it is possible that those who have an increased sedentary behavior results in a reduced amount of time spent outdoors, and therefore does not allow people with MDD to properly gain the benefits of sunlight exposure.1,2
The observation that depressed state was associated with lower accelerometer-derived daytime activity is similar to findings of other studies, the authors noted. Additionally, this was often accompanied with positive associations between photoperiod and daytime activity, as well as solar insolation and daytime activity, both of which were comparable in magnitude.2
Further, the authors noted that the ability to distinguish between depressed and health state through the use of passive sensor data can be promising for next-generation predictive depressive diagnostics. Digital biomarkers have the potential to form the basis of an “early warning system” that can alert health care professionals to initiate timely interventions. Additionally, the incorporation of objectively measured sunlight exposure markers could also enhance the predictive power of tools, laying the foundation for personalized models targeted at the individuals susceptible to mood disturbances with seasonal patterns.2
Limitations of the study include the detection of association rather than causality, the small sample size (N = 55), limited information provided by the dataset on confounding variables for all participants (eg, race, ethnicity, medication data, body mass index), and the patients’ depression status at the study’s beginning was not based on clinical interviews or establish the presence of distinct depressive symptoms. Further, the authors noted that 5 patients were in an inpatient facility during actigraph measurement, which could have influenced their activity and lowered acceleration counts.2
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