Light exposure behaviors predict mood, memory and sleep quality

Effects of evening smartphone use on sleep and declarative memory consolidation in male adolescents and young adults

Exposure to short-wavelength light before bedtime is known to disrupt nocturnal melatonin secretion and can impair subsequent sleep. However, while it has been demonstrated that older adults are less affected by short-wavelength light, there is limited research exploring differences between adolescents and young adults. Furthermore, it remains unclear whether the effects of evening short-wavelength light on sleep architecture extend to sleep-related processes, such as declarative memory consolidation. Here, we recorded polysomnography from 33 male adolescents (15.42 ± 0.97 years) and 35 male young adults (21.51 ± 2.06 years) in a within-subject design during three different nights to investigate the impact of reading for 90 min either on a smartphone with or without a blue-light filter or from a printed book. We measured subjective sleepiness, melatonin secretion, sleep physiology and sleep-dependent memory consolidation. While subjective sleepiness remained unaffected, we observed a significant melatonin attenuation effect in both age groups immediately after reading on the smartphone without a blue-light filter. Interestingly, adolescents fully recovered from the melatonin attenuation in the following 50 min before bedtime, whereas adults still, at bedtime, exhibited significantly reduced melatonin levels. Sleep-dependent memory consolidation and the coupling between sleep spindles and slow oscillations were not affected by short-wavelength light in both age groups. Nevertheless, adults showed a reduction in N3 sleep during the first night quarter. In summary, avoiding smartphone use in the last hour before bedtime is advisable for adolescents and young adults to prevent sleep disturbances. Our research empirically supports general sleep hygiene advice and can inform future recommendations regarding the use of smartphones and other screen-based devices before bedtime.

Photophobia is associated with lower sleep quality in individuals with migraine: results from the American Registry for Migraine Research (ARMR)

BACKGROUND

Patients with migraine often have poor sleep quality between and during migraine attacks. Furthermore, extensive research has identified photophobia as the most common and most bothersome symptom in individuals with migraine, second only to headache. Seeking the comfort of darkness is a common strategy for managing pain during an attack and preventing its recurrence between episodes. Given the well-established effects of daily light exposure on circadian activity rhythms and sleep quality, this study aimed to investigate the relationship between photophobia symptoms and sleep quality in a cohort of patients with migraine.

METHODS

A cross-sectional observational study was conducted using existing data extracted from the American Registry for Migraine Research (ARMR). Participants with a migraine diagnosis who had completed the baseline questionnaires (Photosensitivity Assessment Questionnaire (PAQ), Generalized Anxiety Disorder-7 (GAD-7), Patient Health Questionnaire-2 (PHQ-2)), and selected questions of the ARMR Sleep questionnaire were included. Models were created to describe the relationship of photophobia and photophilia with various sleep facets, including sleep quality (SQ), sleep disturbance (SDis), sleep onset latency (SOL), sleep-related impairments (SRI), and insomnia. Each model was controlled for age, sex, headache frequency, anxiety, and depression.

RESULTS

A total of 852 patients meeting the inclusion criteria were included in the analysis (mean age (SD) = 49.8 (13.9), 86.6% (n = 738) female). Those with photophobia exhibited significantly poorer sleep quality compared to patients without photophobia (p < 0.001). Photophobia scores were associated with SQ (p < 0.001), SDis (p < 0.001), SOL (p = 0.011), SRI (p = 0.020), and insomnia (p = 0.005) after controlling for age, sex, headache frequency, depression, and anxiety, signifying that higher levels of photophobia were associated with worse sleep-related outcomes. Conversely, photophilia scores were associated with better sleep-related outcomes for SQ (p < 0.007), SOL (p = 0.010), and insomnia (p = 0.014).

CONCLUSION

Results suggest that photophobia is a significant predictor of poor sleep quality and sleep disturbances in migraine. These results underscore the necessity for comprehensive and systematic investigations into the intricate interplay between photophobia and sleep to enhance our understanding and develop tailored solutions for individuals with migraine.

An inventory of human light exposure behaviour

Light exposure is an essential driver of health and well-being, and individual behaviours during rest and activity modulate physiologically relevant aspects of light exposure. Further understanding the behaviours that influence individual photic exposure patterns may provide insight into the volitional contributions to the physiological effects of light and guide behavioural points of intervention. Here, we present a novel, self-reported and psychometrically validated inventory to capture light exposure-related behaviour, the Light Exposure Behaviour Assessment (LEBA). An expert panel prepared the initial 48-item pool spanning different light exposure-related behaviours. Responses, consisting of rating the frequency of engaging in the per-item behaviour on a five-point Likert-type scale, were collected in an online survey yielding responses from a geographically unconstrained sample (690 completed responses, 74 countries, 28 time zones). The exploratory factor analysis (EFA) on an initial subsample (n = 428) rendered a five-factor solution with 25 items (wearing blue light filters, spending time outdoors, using a phone and smartwatch in bed, using light before bedtime, using light in the morning and during daytime). In a confirmatory factor analysis (CFA) performed on an independent subset of participants (n = 262), we removed two additional items to attain the best fit for the five-factor solution (CFI = 0.95, TLI = 0.95, RMSEA = 0.06). The internal consistency reliability coefficient for the total instrument yielded McDonald's Omega = 0.68. Measurement model invariance analysis between native and non-native English speakers showed our model attained the highest level of invariance (residual invariance CFI = 0.95, TLI = 0.95, RMSEA = 0.05). Lastly, a short form of the LEBA (n = 18 items) was developed using Item Response Theory on the complete sample (n = 690). The psychometric properties of the LEBA indicate the usability for measuring light exposure-related behaviours. The instrument may offer a scalable solution to characterise behaviours that influence individual photic exposure patterns in remote samples. The LEBA inventory is available under the open-access CC-BY license. Instrument webpage: https://leba-instrument.org/ GitHub repository containing this manuscript: https://github.com/leba-instrument/leba-manuscript .