Summary: A new study has revealed a link between sunshine publicity, physical activity, and melancholy using wrist-based action sensors. Researchers found that people with depression had lower real activity levels, particularly in shorter daylight hours, compared to those without sadness over the course of two weeks.
According to the investigation, people who suffer from depression may have altered reactions to sunlight, which could affect their ability to take advantage of its mood-boosting results. The findings might help develop digital tools that can model feelings patterns and customize mental health interventions based on sunlight exposure data.
Important Information:
- Lower real action was observed in depressed people, particularly during shorter light times.
- In individuals who were n’t depressed, real activity levels were more affected by sun exposure.
- The study was aid in the development of online tools that can use sunlight and exercise data to forecast mood shifts.
Origin: PLOS
Wrist-based action cameras worn by people with depression and those without over the course of two days provided information for the connection between everyday sunlight exposure and physical activity,  , according to a research published , September 25, 2024,  , in the open-access journal , PLOS Mental Health , by Oleg Kovtun and Sandra Rosenthal from Vanderbilt University, U. S.
Mood disorders are the leading cause of’ disability’ worldwide. Up to 30 % of those who have major depressive and bipolar disorder experience seasonal symptoms.
Official diagnostic manuals now acknowledge this occurrence. Yet very little is known about the influence of day length ( i. e., photoperiod ) and sunlight intensity ( i. e., solar insolation ) on seasonal patterns in major depressive disorder and bipolar disorder.
To begin examining the relationship between sunlight measurements and objectively measured movement activity patterns, Kovtun and Rosenthal used a quantitative approach in their new study to begin examining the environmental factors driving seasonality in major depressive disorder and bipolar disorder.
They used accelerometers to record motor-activity in recordings from 32 people with unipolar or bipolar depression and 23 people without depression. They measure the rate at which an object’s velocity changes over time. Participants were recruited at the University of Bergen, Norway.
The findings revealed relationships between daytime physical activity, depressed state, photoperiod and solar insolation. In particular, more depressed states were associated with lower daytime activity,  , whilst daytime activity increased with photoperiod and solar insolation.
Additional research suggests that depressed, depressed, and non-depressed individuals may have different physical activity effects depending on solar insolation. This finding might point to the possible link between energy input ( i .e., solar insolation ) and physical activity in depressed individuals.
On the other hand, it is also possible that more sedentary behavior results in less outdoor time, which does not allow depressed people to take advantage of the advantages of sunlight exposure.
According to the authors, the study presents a generalizable strategy to understand the complex interplay between sunlight, physical activity, and depressed state using open-source digital tools.
The ability to , identify mood disturbances, particularly in seasonally susceptible individuals, using passive digital biomarker data offers promise in informing next-generation predictive, personalized diagnostics in mental health.
Specifically, a digital biomarker, such as accelerometer-derived motor activity patterns, could form the basis of an early warning system that alerts a clinician to initiate a timely intervention.
Using objectively measured sunlight exposure markers, such as those collected by NASA or those whose light exposure was measured by accelerometers, could strengthen these tools’ predictive power and lay the groundwork for personalized models geared toward people who are susceptible to mood swings influenced by seasonal patterns.
According to Rosenthal and Kovtun, “individuals with seasonal mood disorders may not yet recognize the pattern of their illness.” One of the objectives of our study is to encourage the development of digital tools to support clinicians and assist patients in managing their symptoms themselves.
Funding:  , This work was supported by Velux Stiftung ( grant No. 1821 to SJR and OK ). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
About this news about mental health and depression
Author: Charlotte Bhaskar
Source: PLOS
Contact: Charlotte Bhaskar – PLOS
Image: The image is credited to Neuroscience News
Original Research: Open access.
” Seasonality in mood disorders: Probing association of accelerometer-derived physical activity with daylength and solar insolation” by Oleg Kovtun et al. PLOS Mental Health
Abstract
Seasonality in mood disorders: Probing association of accelerometer-derived physical activity with daylength and solar insolation
Worldwide, the main cause of disability is mood disorders. A seasonal pattern of onset is now recognized in the official diagnostic manuals ( DSM-5 and ICD-11 ), which accounts for up to 30 % of those who have major depressive disorder ( MDD ) and bipolar disorder ( BD ).
Very little is known about the influence of day length ( photoperiod ) and sunlight intensity ( solar insolation ) on seasonal patterns in MDD and BD.
To understand environmental factors driving seasonality in MDD and BD, we present a quantitative approach to examine the relationship between sunlight measurements and objectively measured motor activity patterns.
Our generalized linear model ( GLM) assessment of the Depresjon dataset, which includes short-term (up to two weeks ) motor activity recordings of 23 unipolar and bipolar depressed patients and 32 healthy controls recruited to the study at the University of Bergen Norway (60.4° N latitude, 5.3° E longitude ), revealed significant association of accelerometer-derived daytime physical activity with participant’s depressed state ( p<, 0.001 ), photoperiod ( p<, 0.001 ), and solar insolation ( p<, 0.001 ).
Our study uses open-source digital tools to generalize a method for understanding the complex interactions between sunlight, physical activity, and depression.
The ability to identify mood disturbances, particularly in seasonally susceptible individuals, using passive digital biomarker data offers great promise in informing next-generation predictive, personalized diagnostics in mental health.
