Associations between screen time, exercise habits, and the onset of dementia, Parkinson's disease, and depression

In a recent study published in the International Journal of Behavioral Nutritional and Physical Activity, researchers explore the prospective link between various screen time behaviors and changes in brain structure, as well as the risk of developing dementia, Parkinson's disease (PD), and depression.

Study: Different types of screen time, physical activity, and incident dementia, Parkinson’s disease, depression and multimorbidity status. Image Credit: Dean Drobot / Shutterstock.com

Background 

The prevalence of neurodegenerative diseases including dementia and PD is rising due to an aging population, with over 55 million people currently living with dementia and an annual increase of 10 million new cases. Likewise, PD diagnoses have more than doubled to 6.1 million since 1990. Depression often co-occurs with these conditions and currently affects nearly 350 million people throughout the world, thus significantly contributing to economic losses.

Further research is crucial to clarify the unclear relationships between screen time and PD, depression, and multimorbidity, especially as neurodegenerative disorders share modifiable risk factors with depression that could be influenced by screen habits and physical activity (PA).

About the study 

The study population comprised men and women between 39 and 72 years of age. Over 500,000 study participants were recruited from the general population for the United Kingdom (UK) Biobank, a prospective cohort study conducted between 2006 and 2010. 

The UK Biobank identified dementia, PD, depression, and multimorbidity cases through inpatient records using International Classification of Diseases, Tenth Revision (ICD-10) codes. Multimorbidity was defined as two or more concurrent chronic diseases. Health records were updated until September 2021 in England, July 2021 in Scotland, and February 2018 in Wales.

The UK Biobank collected data on screen time by querying participants about daily hours spent watching television and using computers recreationally. Durations reported outside of the zero to 24 hour range were excluded, with high usage prompting confirmation and responses indicating less than one hour recorded as 30 minutes each day.

Participants of the UK Biobank reported their PA including walking, moderate, and vigorous exercises using a modified International Physical Activity Questionnaire, which was validated for reliability. Magnetic resonance imaging (MRI) data were captured with a Siemens Skyra 3 T scanner, and brain volumes were analyzed, accounting for head size normalization. To ensure strong associations between screen time, PA, and health outcomes, the study adjusted for socio-demographic, lifestyle, and anthropometric factors as covariates. 

Follow-up time was noted from participants' initial dietary assessment to the occurrence of dementia, PD, or depression, death, or study's end, with multimorbidity tracked until a second illness emerged. Data normality was evaluated with Q-Q plots and participant traits were presented statistically and differentiated by screen time categories.

Hazard ratios (HRs) for disease incidence by screen time were calculated using Cox regression and confirmed by Schoenfeld residuals for assumption adherence. Dose-responses were explored with restricted cubic splines.

The impact of PA as a substitute for screen time on disease risk was examined through isotemporal substitution models. Interactions between screen time and PA were analyzed, with participants grouped by PA and screen time levels. To mitigate potential biases and reverse causation effects, analyses were stratified by gender and age.

Study findings 

About 1.29%, 0.65%, and 4.99% of study participants developed dementia, PD, and depression, respectively, with a smaller percentage developing multimorbidities involving these conditions.

The participants exhibited varying characteristics based on their screen time habits. Those with higher TV viewing times were generally older, predominantly male, had higher body mass indices (BMIs), lower PA levels, and were more likely to be smokers. Conversely, individuals with higher computer use were typically younger, predominantly male, with similar BMIs and PA profiles to the high TV viewers.

A detailed examination of screen time revealed an association with certain health risks. For example, higher computer use was associated with a lower risk of dementia up to a certain point, beyond which the risk increased.

For TV viewing, the risk of dementia, PD, and depression increased with the duration of exposure. This pattern remained consistent, even after adjusting for confounding factors, and was supported by non-linear associations observed in restricted cubic spline models.

The researchers also utilized isotemporal substitution analyses to explore whether PA could mitigate the health risks associated with screen time. These results were promising, as substituting even a half-hour of screen time with PA, whether daily-life activities or structured exercise, significantly reduced the risks of dementia, PD, and depression.

Joint analyses suggested that high PA levels could mitigate some of the risks associated with screen time. However, the combination of low PA and high TV viewing time correlated with a significantly heightened risk for dementia and depression.

Moderate computer use was attributed to healthier brain markers, such as lower white matter hyperintensities and larger hippocampal volume; however, excessive use was correlated with reduced brain volumes. High TV viewing time was associated with smaller hippocampal volumes, despite an initial increase in total brain and gray matter volumes.

Conclusions

The study findings highlight a complex relationship between screen time, PA, and health outcomes. These results emphasize the potential protective effects of moderate computer use and PA against cognitive decline and mental health issues.

Written by

Vijay Kumar Malesu

Vijay holds a Ph.D. in Biotechnology and possesses a deep passion for microbiology. His academic journey has allowed him to delve deeper into understanding the intricate world of microorganisms. Through his research and studies, he has gained expertise in various aspects of microbiology, which includes microbial genetics, microbial physiology, and microbial ecology. Vijay has six years of scientific research experience at renowned research institutes such as the Indian Council for Agricultural Research and KIIT University. He has worked on diverse projects in microbiology, biopolymers, and drug delivery. His contributions to these areas have provided him with a comprehensive understanding of the subject matter and the ability to tackle complex research challenges.