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Open Access Research

A cross-sectional analysis of light at night, neighborhood sociodemographics and urinary 6-sulfatoxymelatonin concentrations: implications for the conduct of health studies

Susan Hurley1*, David O Nelson1, Erika Garcia1, Robert Gunier1, Andrew Hertz1 and Peggy Reynolds12

Author Affiliations

1 Cancer Prevention Institute of California, 2001 Center Street, Suite 700, Berkeley, CA 94704, USA

2 Department of Health Research and Policy, Stanford University School of Medicine, Stanford, CA 94305, USA

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International Journal of Health Geographics 2013, 12:39  doi:10.1186/1476-072X-12-39

Published: 30 August 2013

Abstract

Background

There is accumulating evidence that circadian disruption, mediated by alterations in melatonin levels, may play an etiologic role in a wide variety of diseases. The degree to which light-at-night (LAN) and other factors can alter melatonin levels is not well-documented. Our primary objective was to evaluate the degree to which estimates of outdoor environmental LAN predict 6-sulftoxymelatonin (aMT6s), the primary urinary metabolite of melatonin. We also evaluated other potential behavioral, sociodemographic, and anthropomorphic predictors of aMT6s.

Methods

Study participants consisted of 303 members of the California Teachers Study who provided a 24-hour urine specimen and completed a self-administered questionnaire in 2000. Urinary aMT6s was measured using the Bühlmann ELISA. Outdoor LAN levels were estimated from satellite imagery data obtained from the U.S. Defense Meteorological Satellite Program’s (DMSP) Operational Linescan System and assigned to study participants’ geocoded residential address. Information on other potential predictors of aMT6s was derived from self-administered surveys. Neighborhood socioeconomic status (SES) was based on U.S. Census block group data.

Results

Lower aMT6s levels were significantly associated with older age, shorter nights, and residential locations in lower SES neighborhoods. Outdoor sources of LAN estimated using low-dynamic range DMSP data had insufficient variability across urban neighborhoods to evaluate. While high-dynamic range DMSP offered much better variability, it was not significantly associated with urinary aMT6s.

Conclusions

Future health studies should utilize the high-dynamic range DMSP data and should consider other potential sources of circadian disruption associated with living in lower SES neighborhoods.

Keywords:
Circadian disruption; Light at night; Melatonin; aMT6s; Socioeconomic status; Women