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<p>With the global population aging, understanding the aging process and its contributing factors is increasingly crucial. Nighttime light (NTL), a pervasive but understudied urban environmental factor, may accelerate biological aging. We conducted a cross-sectional analysis using baseline data from the UK Biobank (UKB). The NTL data were obtained from the National Earth System Science Data Center. Biological age (BA) was assessed using the Klemera–Doubal method (KDM-BA) and the PhenoAge algorithms. Multivariable linear and logistic regression models were used to evaluate the associations between the NTL exposure and biological aging. Additionally, restricted cubic splines, subgroup analyses, and sensitivity analyses were conducted to assess the robustness of the findings. A total of 296,372 participants (mean age 56.5 ± 8.1&#xa0;years; 55.1% female) were included. We observed divergent associations between NTL exposure and biological aging metrics: inverse relationships with KDM-BA (<i>β</i> = -0.07, 95% CI: -0.09 to -0.06) and KDM-BA acceleration (<i>β</i> = −&#xa0;0.03, 95% CI: −&#xa0;0.04  to −&#xa0;0.01), versus positive associations with PhenoAge (<i>β</i> = 0.07, 95% CI: 0.03–0.12) and PhenoAge acceleration (<i>β</i> = 0.24, 95% CI: 0.20–0.28). Restricted cubic splines revealed nonlinear dose–response associations between NTL exposure and biological aging measures (<i>P</i> for non-linearity &lt; 0.001). Higher residential-area NTL exposure was associated with reduced KDM-BA and slower KDM-BA acceleration, but with elevated PhenoAge and faster PhenoAge acceleration.</p>

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Residential-area nighttime light exposure and biological aging patterns in the UK Biobank

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年8月5日

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  • Xiaojuan Liu,
  • Junru Wang,
  • Yongbin Zhu,
  • Yuhua Wu,
  • Jiangping Li

摘要

With the global population aging, understanding the aging process and its contributing factors is increasingly crucial. Nighttime light (NTL), a pervasive but understudied urban environmental factor, may accelerate biological aging. We conducted a cross-sectional analysis using baseline data from the UK Biobank (UKB). The NTL data were obtained from the National Earth System Science Data Center. Biological age (BA) was assessed using the Klemera–Doubal method (KDM-BA) and the PhenoAge algorithms. Multivariable linear and logistic regression models were used to evaluate the associations between the NTL exposure and biological aging. Additionally, restricted cubic splines, subgroup analyses, and sensitivity analyses were conducted to assess the robustness of the findings. A total of 296,372 participants (mean age 56.5 ± 8.1 years; 55.1% female) were included. We observed divergent associations between NTL exposure and biological aging metrics: inverse relationships with KDM-BA (β = -0.07, 95% CI: -0.09 to -0.06) and KDM-BA acceleration (β = − 0.03, 95% CI: − 0.04  to − 0.01), versus positive associations with PhenoAge (β = 0.07, 95% CI: 0.03–0.12) and PhenoAge acceleration (β = 0.24, 95% CI: 0.20–0.28). Restricted cubic splines revealed nonlinear dose–response associations between NTL exposure and biological aging measures (P for non-linearity < 0.001). Higher residential-area NTL exposure was associated with reduced KDM-BA and slower KDM-BA acceleration, but with elevated PhenoAge and faster PhenoAge acceleration.