Satellite-based residential light exposure was associated with opposing biological aging signals: PhenoAge indicated accelerated aging, while KDM-BA suggested the opposite.

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.

Biological Aging in the Modern Era

Aging is a multifaceted biological process characterized by a gradual decline in physiological function, leading to heightened vulnerability to disease and mortality. As populations worldwide continue to age, unraveling the mechanisms behind aging and its related conditions has become increasingly important.

Unlike chronological age, biological age (BA) reflects accumulated cellular and molecular changes, potentially offering a more functionally informative measure of physiological health and disease risk. Individuals of the same chronological age often differ widely in their susceptibility to age-related diseases, highlighting the importance of functional rather than temporal measures of aging.

Biological aging involves a gradual decline in function across various organs and physiological systems. Assessment methods range from single biomarkers, such as telomere length, to integrated multi-omics platforms, with approaches such as the KDM and PhenoAge algorithms providing valuable predictions for mortality and disease risk. However, no single method is considered a gold standard, and different algorithms may capture distinct dimensions of aging.

Urbanization has made artificial NTL exposure nearly universal in industrialized regions. Night shift work, which involves circadian disruption and differs from residential ambient light exposure, is classified as a probable human carcinogen, underscoring broader health concerns about night-time light exposure. Growing evidence links NTL exposure to increased risks of obesity, diabetes, cardiovascular disease, cancer, mental health disorders, and sleep disturbances. However, its association with biological aging, a key risk factor for chronic diseases, remains largely unstudied and unclear.

Exploring the Intersection of Biological Aging and Artificial Night-time Light

The current study analyzed baseline data from the UK Biobank, comprising over 500,000 adults aged 37-73 years, recruited between 2006 and 2010. After excluding participants with missing data, 296,372 participants were included in the analysis.

BA was assessed by two methods: the KDM and PhenoAge. KDM-BA used a regression model with nine clinical biomarkers, while PhenoAge used a mortality hazard model with nine biomarkers and chronological age. BA acceleration was defined as the residuals from these models, adjusted for chronological age, and analyzed as both a continuous and a binary variable, identifying individuals as biologically older if BA acceleration was greater than zero.

NTL exposure was assessed using validated satellite data, matched to participants’ residential addresses, and averaged over five years (2006-2010) as a proxy for ambient exposure. This measure reflected outdoor residential-area brightness rather than participants’ personal or indoor light exposure.

Potential confounders included sociodemographic, lifestyle, and health factors derived from questionnaires and baseline measurements. These covered personal characteristics, socioeconomic status, health conditions, and behaviors such as smoking, drinking, diet, sleep, sun exposure, and physical activity. Income and deprivation were categorized, while diet, sleep, and physical activity were scored according to healthy behaviors. The analyses also accounted for obesity, hypertension, diabetes, and the assessment center.

Contrasting Associations of NTL With Biological Aging Metrics

Of the 296,372 adults included in the analysis, 45% were men, and the average age of the cohort was 56.5 years. NTL exposure was divided into four groups: Q1, Q2, Q3, and Q4. Compared to people in the lowest NTL group (Q1), those in the highest group (Q4) were generally younger, had more education, but faced greater socioeconomic disadvantage, and showed more unhealthy habits such as higher rates of smoking, worse sleep, less sun exposure, and higher prevalence of obesity and diabetes. However, the Q4 group also drank less alcohol and was more physically active. These differences highlight how greater NTL exposure coincided with distinct backgrounds and health patterns.

When first analyzed without adjusting for other factors, people with higher night-time light exposure had lower biological ages and were less likely to show signs of accelerated aging. However, after accounting for differences in demographic, socioeconomic, lifestyle, and health factors, the results became more complex. Higher night-time light exposure was linked to lower biological age and lower age-acceleration scores when measured with KDM-BA, but to higher biological age and higher age-acceleration scores with PhenoAge. For instance, people in the highest exposure group (Q4) had 5% lower odds of accelerated aging using KDM-BA, but 3% higher odds with PhenoAge.

The exposure-response relationships were also nonlinear, indicating that the associations did not change uniformly across increasing levels of NTL. Different inflection points were observed for KDM-BA, PhenoAge, and their corresponding acceleration measures.

Subgroup analyses found that age, obesity, and smoking modified some of the observed associations, but overall trends remained generally similar across most groups. People exposed to more NTL tended to show lower KDM-BA and KDM-BA acceleration, but higher PhenoAge and PhenoAge acceleration.

Sensitivity tests, including removing people with diabetes or hypertension and excluding extreme NTL values, generally supported several of the main associations. Distributed-lag analyses found inverse associations for KDM-BA and KDM-BA acceleration for exposure estimates from 2007 to 2009, but not for 2006 or 2010. No significant year-specific associations were detected for PhenoAge or PhenoAge acceleration. When using an alternative aging measure, called Homeostatic Dysregulation (HD), results aligned with those for PhenoAge acceleration. The agreement between HD and PhenoAge suggested a potentially adverse aging pattern, although the conflicting KDM-BA findings prevented a definitive overall interpretation.

The Need for Further Research on NTL and Aging

The large population-based study highlights the complex relationship between residential NTL exposure and biological aging. Higher NTL exposure was associated with lower KDM-BA and KDM-BA acceleration, but with higher PhenoAge and PhenoAge acceleration. These mixed findings suggest that the observed association between NTL and biological aging varies according to the biological dimensions captured by different biomarkers and aging algorithms.

Because the analysis was cross-sectional and biological age was assessed at only one time point, it did not directly measure changes in the rate of aging over time or establish causality. Residential satellite data also did not capture indoor light, curtain use, sleep schedules, personal light sensitivity, or individual exposure patterns. The predominantly middle-aged and older UK Biobank population, healthy volunteer bias, missing biological-aging data, and possible residual confounding may further limit the findings.

Further longitudinal, population-based research is necessary to clarify how NTL exposure relates to biological aging and to understand the underlying mechanisms.