Independent associations of exposure to evening light and nocturnal urinary melatonin excretion with diabetes in the elderly

Abstract

Circadian misalignment between internal and environmental rhythms dysregulates glucose homeostasis because of disruption of the biological clock, and increases risk of diabetes. Although exposure to evening light and decreased melatonin secretion are both associated with the circadian misalignment, it remains unclear whether they are associated with diabetes. In this cross-sectional study on 513 elderly individuals (mean age, 72.7 years), we measured ambulatory light intensity during the 4 h prior to bedtime at 1-min intervals during two consecutive days and overnight urinary 6-sulfatoxymelatonin excretion (UME) along with glucose metabolism. The median average intensity of evening light exposure and UME were 25.4 lux (interquartile range 17.5–37.6) and 6.6 μg (interquartile range 3.9–9.7), respectively. Both log-transformed average intensity of evening light exposure and log-transformed UME were significantly associated with diabetes in a multivariate logistic regression model adjusted for covariates, including gender, body mass index, duration in bed, and night-time light exposure [adjusted odds ratio (OR), 1.72; 95% confidence interval (CI), 1.12–2.64; p = 0.01; and adjusted OR, 0.66; 95% CI, 0.44–0.97; p = 0.04; respectively]. An increase in evening light exposure from 17.5 to 37.6 lux (25–75th percentiles) was associated with a 51.2% (95% CI, 8.2–111.4%) increase in prevalent diabetes, and an increase in UME from 3.9 to 9.7 μg (25–75th percentiles) was associated with a 32.0% (95% CI, 1.9–52.8%) decrease in prevalent diabetes. In conclusion, this study in elderly individuals demonstrated that evening light exposure in home settings and UME were significantly and independently associated with diabetes.

• Circadian rhythm
• diabetes
• elderly
• evening light
• melatonin

Acknowledgments

We are indebted to all the participants of this study. We would also like to thank Sachiko Uemura and Naomi Takenaka for their valuable support during data collection.