Association between body mass index and pupillary light reflex indices

Omri Segal, Sapir Barak Lanciano, Udi Nussinovitch

Research output: Contribution to journalArticlepeer-review


Background: Elevated body mass index (BMI) is a major risk factor for morbidity and mortality, and associated with autonomic nervous system (ANS) dysregulation, principally due to sympathetic over-activity. ANS is commonly evaluated using heart rate variability assay, which remains impractical for most clinical settings. Objectives: To examine whether pupillometry indices reflective of dysautonomia correlates with high BMI levels in otherwise healthy individuals. Methods: In this cross-sectional study, 101 healthy participants were tested using an automated infrared pupilometer. Pupillary light reflex (PLR) parameters were acquired and averaged. Statistical analysis included a hierarchical linear regression, controlling for possible covariates. Results: BMI values ranging 18.2–47.1 (mean 25.3 ± 4.4 kg/m2) were positively correlated with average pupil dilatation velocity (ADV; r = 0.20, p = 0.05). After controlling for possible covariates, the results remained significant (β = 0.21, t = 2.13, p = 0.04). Separate analysis of participants with normal and increased BMI showed that ADV was significantly abnormal in the overweight group (p = 0.04). Conclusions: In seemingly healthy adults, BMI had a significant positive correlation with sympathetic over-activity manifested by pupillometry ADV values. ANS dysregulation is present even in individuals with moderate overweight. Further research is needed to establish standardized guidelines for PLR use as a marker for ANS dysfunction in individuals with cardiovascular risk factors.

Original languageEnglish
Article number100417
JournalObesity Medicine
StatePublished - Jun 2022
Externally publishedYes


  • Autonomic nervous system (ANS)
  • Obesity
  • Overweight
  • Pupillary light reflex (PLR)


Dive into the research topics of 'Association between body mass index and pupillary light reflex indices'. Together they form a unique fingerprint.

Cite this