Satellite-based residential light exposure was associated with opposing biological aging signals, with PhenoAge indicating accelerated aging and KDM-BA suggesting the opposite, according to an Aug. 6 report.
A recent Scientific Reports study examined the associations between residential-area night-time light (NTL) exposure and biological aging metrics using the Klemera–Doubal method (KDM) and the PhenoAge algorithm in a large UK Biobank cohort. The study analyzed baseline data from over 500,000 adults aged 37-73 years recruited between 2006 and 2010, ultimately including 296,372 participants after excluding those with missing data.
Biological age was assessed by two methods: KDM-BA used a regression model based on nine clinical biomarkers, while PhenoAge applied a mortality hazard model using nine biomarkers plus chronological age. NTL exposure was determined using validated satellite data matched to participants’ addresses and averaged over five years as a proxy for ambient outdoor brightness. The analysis adjusted for various sociodemographic, lifestyle, and health factors such as income, deprivation status, smoking habits, diet quality, sleep patterns, sun exposure, physical activity levels, obesity status, hypertension history, diabetes diagnosis, and assessment center location.
The findings showed that individuals in areas with higher night-time light exposure were generally younger but faced greater socioeconomic disadvantage and exhibited more unhealthy behaviors such as higher rates of smoking and poorer sleep. They also had higher prevalence of obesity and diabetes but drank less alcohol and were more physically active compared to those in lower-exposure areas.
When first analyzed without adjustment for confounders, people exposed to more NTL had lower biological ages overall. However, after adjusting for other factors in multivariable models, results diverged depending on which aging metric was used: Higher NTL correlated with lower KDM-BA scores (suggesting slower aging), but higher PhenoAge scores (suggesting faster aging). For example, those in the highest NTL group had 5% lower odds of accelerated aging by KDM-BA but 3% higher odds by PhenoAge. Subgroup analyses indicated some modification by age group or health status; however, overall trends remained similar across most groups.
The researchers noted that their cross-sectional design could not determine causality or changes over time. Satellite-based measures did not account for indoor lighting conditions or individual differences such as curtain use or personal sensitivity to light. Other limitations included potential healthy volunteer bias within the UK Biobank sample population and possible residual confounding from unmeasured variables.
The authors concluded that further longitudinal research is needed to clarify how night-time light relates to different aspects of biological aging.
