Research reportExposure to light at night and risk of depression in the elderly
Introduction
Epidemiological data have demonstrated a higher prevalence of major depressive disorder (MDD) in recent decades, which is associated with increased risk of dementia and cardiovascular diseases and worse mortality outcomes (Compton et al., 2006, Saczynski et al., 2010, Ariyo et al., 2000). Nevertheless, the etiology of MDD remains poorly understood. Recent advances in the knowledge of fundamental links between chronobiology and MDD have led to exploring novel risk factors for depression in the field of biological rhythms (Bunney and Bunney, 2000, McClung, 2013). MDD is frequently accompanied by circadian misalignment such as abnormal sleep/wake cycles and altered melatonin secretion and signaling, which are related to disruption of the master biological clock, typically found in night-shift workers (Boivin, 2000, Crasson et al., 2004, Wu et al., 2013, Schernhammer et al., 2004).
Physiologically, light exposure is the most important entraining environmental cue for the circadian timing system which is regulated by the suprachiasmatic nucleus (SCN) of the master biological clock (Brzezinski, 1997). The circadian phase–response curve to light suggests that exposure to daytime light advances the subsequent circadian phase and that exposure to light at night (LAN) delays the subsequent circadian phase (Khalsa et al., 2003). In modern society, several individuals are exposed to relatively lower levels of daytime light because they spend most of their daytime hours indoors. In contrast, increased LAN exposure is observed because of artificial lighting, not only in night-shift workers but also in individuals with normal circadian lifestyles (Navara and Nelson, 2007). Therefore, the light exposure patterns in modern life may be more closely related to circadian phase delay and circadian misalignment compared with that in naturalistic life.
Although the beneficial effects of daytime bright light therapy in patients with MDD have been confirmed by recent randomized controlled studies, humans are insufficiently exposed to daytime bright light in real life situations (Lieverse et al., 2011, Riemersma-van der Lek et al., 2008). For example, about a half of the elderly population receives only 1 h of daytime light exceeding 1000 lx, and females receive a much shorter duration of daytime bright light compared with that in males (Obayashi et al., 2012, Campbell et al., 1998). Less daytime light exposure may consequently increase the risk for MDD, but it remains unclear whether daytime light exposure in home settings is associated with MDD.
Recent experimental studies conducted in mammals indicate that chronic exposure to dim LAN (5 lx) causes mood impairments compared with complete darkness during nighttime, and the intensity of dim LAN exposure, such as half as that of a candle, is common in bedrooms (Bedrosian et al., 2012, Fonken et al., 2012). In addition, dim LAN is effective at resetting the circadian phase and suppressing melatonin secretion in human physiology, and melatonin is hypothesized to be one of the major contributors to the association between LAN exposure and mood impairments (Zeitzer et al., 2000). Therefore, LAN exposure in home settings may cause the risk of MDD by altering the melatonin secretion; nevertheless, it remains unclear whether LAN exposure is associated with MDD in humans.
In this cross-sectional study of 516 elderly individuals, we evaluated the associations of daytime and nighttime light exposure in home settings and melatonin secretion with depressive symptoms. Ambulatory daytime light intensity and nighttime bedroom intensity were measured using light meters, and urinary 6-sulfatoxymelatonin excretion (UME), the major melatonin metabolite, was used as an index of melatonin secretion because there is evidence that UME correlates closely with secreted levels (Baskett et al., 1998).
Section snippets
Participants and study protocol
Between September 2010 and April 2012, 537 elderly subjects voluntarily enrolled in a study titled “Housing Environments and Health Investigation among Japanese Older People in Nara, Kansai Region: a prospective community-based cohort (HEIJO-KYO) study.” Of these, 516 home-dwelling participants met the inclusion criteria of age ≥60 years and completed light measurement records and a questionnaire regarding depressive symptoms. All the participants provided written informed consent, and the
Results
The mean age of the participants was 72.8 (SD, 6.5) years, and 239 (46.3%) were males. Of the 516 participants, 101 belonged to the depressed group (including six on the basis of their medical history and current therapy; 95 from the GDS score). The depressed group revealed marginally to significantly higher prevalence of insomnia (P<0.01) and hypertension compared with that in the nondepressed group (P=0.09; Table 1).
The median DLavg and DL1000 were 349.0 lx (IQR, 176.1–784.3) and 50.3 min (IQR,
Discussion
We demonstrated that LAN exposure is significantly associated with depressive symptoms in a large elderly sample, as evidenced by the significantly higher prevalence of NLavg ≥5 lx in the depressed group compared with that in the nondepressed group (adjusted OR, 1.89; 95% CI, 1.10–3.25; P=0.02). This result was supported by a consistent and significant association between another parameter of LAN exposure (NL10 ≥30 min) and depressive symptoms (adjusted OR, 1.71; 95% CI, 1.01–2.89; P=0.046).
Role of funding source
This work was supported by Grants from the Department of Indoor Environmental Medicine, Nara Medical University; Scientific Research from the Ministry of Education, Culture, Sports, Science and Technology; Mitsui Sumitomo Insurance Welfare Foundation; Meiji Yasuda Life Foundation of Health and Welfare; Osaka Gas Group Welfare Foundation; Japan Diabetes Foundation; and the Japan Science and Technology Agency.
Conflict of interest
All authors report no conflicts of interest.
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.
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