Impact of Everyday Light Exposure Patterns on Metabolic, Cardiovascular, and Psychological Health in Younger and Older Adults

This study is designed as an observatory field study of characterizing younger and older adults' everyday life in terms of light exposure patterns as well as cardiovascular, metabolic and psychological health parameters over 10 days continuously through wearables and smartphone-based self-reports (ambulatory assessment period). On the first day of data collection, each participant will undergo an extensive eye examination at the Institute of Ophthalmology, particularly an Optical Coherence Tomography (OCT) scan will conducted and by means of a macular pigment reflectometer the difference between the light entering and leaving the eye across the visual spectrum will be determined as a marker of lense yellowing. Thereafter, participants start wearing the wearable sensors (continuous glucose monitors, light loggers worn as a necklace) and instructions on how to complete the smartphone-based self-report forms are provided. Participants are asked to take pictures of every food or drink (except of water) and upload these pictures through the m-Path app, these photos will be later linked to the continuous glucose monitor data. Data will be collected from the first evening onwards (ca. 18:00 h). After the ambulatory assessment period under free-living conditions, participants will spend the 11th and 12th day in a controlled office room environment from 08:30 to 17:00 h. In a randomized cross-over design, the 11th and 12th day will be spent in either bright (1250 lux) or dim office lighting (10 lux). On these days, participants will continue to wear the wearables and complete the expanded smartphone-based self-reports mostly similar to the 10-day ambulatory assessment period. Between day 11 and 12, participants will leave controlled conditions from 17:00 h on day 11 to 08:30 h on day 12. On day 11 and 12, participants will receive a standardized fluid meals for breakfast and lunch, and are otherwise instructed to avoid any food, caloric or caffeinated beverages between 08:30 and 17:00 h. On these two days, skin temperature sensors will be placed on four different skin regions, and blood pressure will be manually measured at regular intervals between 08:30 h and 17:00 h. After removing all wearables on day 12, the study ends at 17:30 h. Over these 12 days of data collection, participants will be asked to keep their bedtimes at home as consistent as possible between days, and on day 11 and 12 they will be instructed to come to the office facilities fasted without any caloric intake after 22:00 h on the previous evening of day 10 and 11, respectively.

The two comparative groups formed in this study consist of 30 younger adults (18-35 years) and 30 older adults (60-80 years), both females and males will be included, and the aim is to match both groups with respect to sex (i.e. ideally 15 women and 15 men per group). The age contrast in the two groups is chosen, as substantial differences in degeneration of the lenses and retina within the eye can be expected.

For the sample size calculation of n = 30 per group, we refer to Zauner et al. (Zauner et al., 2023), who created a procedure to calculate statistical power and required sample size for wearable light-logging data. For most light-logging metrics, their approach shows that for strong differences in light exposure patterns (i.e., winter vs. summer) even smaller samples are sufficient (n = 3-24). We do not expect that differences between age groups are that strong as seasonal differences. However, we are confident that effects of about d = 0.7 could be detected with our design (n = 30 per group). Considering some drop-out, we anticipate that we will have to enroll 70 participants in total.

With the primary hypothesis of this study being that younger and older individuals differ in their light exposure patterns in everyday life, the two main explorative goals of the AgeLight study are to:

• characterize light exposure patterns in younger and older adults and their link to cardiovascular, metabolic, and psychological health
• identify determining factors of an individual's sensitivity to light and its health effects (such as degeneration of the lens and retina)