Chronobiology International, 2014; 31(6): 779–786 ! Informa Healthcare USA, Inc. ISSN: 0742-0528 print / 1525-6073 online DOI: 10.3109/07420528.2014.900501
ORIGINAL ARTICLE
Association between light exposure at night and nighttime blood pressure in the elderly independent of nocturnal urinary melatonin excretion Kenji Obayashi1, Keigo Saeki1, Junko Iwamoto2, Yoshito Ikada3, and Norio Kurumatani1 1
Department of Community Health and Epidemiology, Nara Medical University School of Medicine, Nara, Japan, Department of Nursing, Tenri Health Care University, Nara, Japan, and 3Department of Surgery, Nara Medical University School of Medicine, Nara, Japan
Chronobiol Int Downloaded from informahealthcare.com by Michigan University on 04/19/15 For personal use only.
2
Circadian misalignment between internal and environmental rhythms dysregulates blood pressure (BP) variability because of disruption of the biological clock, resulting in increased nighttime BP. Although exposure to light-at-night is associated with the circadian misalignment, it remains unclear whether exposure to light-at-night in home settings is associated with nighttime BP. In this cross-sectional analysis of 528 elderly individuals (mean age: 72.8 years), we measured bedroom light intensity at 1-min intervals on two consecutive nights along with ambulatory BP, overnight urinary melatonin excretion and actigraphy. With regard to adjusted mean comparisons using analysis of covariance, the light-at-night group (average: 5 lux; n ¼ 109) showed significantly higher nighttime systolic BP (SBP; adjusted mean: 120.8 vs. 116.5 mmHg, p ¼ 0.01) and diastolic BP (70.1 vs. 67.1 mmHg, p50.01) compared with the Darker group (average: 55 lux; n ¼ 419) independently of potential confounding factors including overnight urinary melatonin excretion and actigraphic sleep quality. We observed consistent associations between light-at-night and nighttime BP in different cutoff values for light-at-night intensity (i.e. 3 and 10 lux). In conclusion, exposure to light-atnight in home settings is significantly associated with increased nighttime BP in elderly individuals independently of overnight urinary melatonin excretion. A 4.3 mmHg increase in nighttime SBP is associated with a 6.1% increase in total mortality, which corresponds to approximately 10 000 annual excess deaths in Japanese elderly population. Keywords: Actigraphy, circadian rhythm, elderly, light at night, melatonin, nighttime blood pressure
INTRODUCTION
modern society (Navara & Nelson, 2007; Wyse et al., 2011). Recently, intrinsically photosensitive retinal ganglion cells and its photopigment melanopsin were identified as primary receptors of environmental light, and the mechanisms underlying the association between LAN exposure and SCN function are being solved (Berson et al., 2002; Provencio et al., 1998). Physiologically, LAN exposure is the most important environmental cue for the disruption of SCN function, leading to circadian misalignment (Brzezinski, 1997; Zeitzer et al., 2000). Melatonin, a pineal gland hormone, is hypothesized to be a major contributor to the association between LAN exposure and circadian misalignment; however, epidemiological studies have reported that LAN exposure in home settings is not significantly associated with nocturnal total melatonin levels (Davis et al., 2001; Levallois et al., 2001;
Nighttime blood pressure (BP) is a stronger predictor of cardiovascular risk and mortality than daytime BP and night-to-day BP ratio because of its high reproducibility (Boggia et al., 2007; Fagard et al., 2008; Sega et al., 2005). Circadian BP variability is regulated by the suprachiasmatic nucleus (SCN) of the hypothalamus, which contains the master biological clock (Paschos & FitzGerald, 2010). Chronic misalignment between internal and environmental rhythms is typically found in night shift workers, who are exposed to increased light at night (LAN), resulting in the disruption of SCN function and increased nighttime BP (Chau et al., 1989; Lo et al., 2008; Yamasaki et al., 1998). Exposure to LAN is globally increasing not only in night shift workers but also in normal-living humans because of the increased use of artificial lighting in
Submitted October 31, 2013, Returned for revision February 24, 2014, Accepted February 28, 2014
Correspondence: Kenji Obayashi, MD, PhD, Department of Community Health and Epidemiology, Nara Medical University School of Medicine, 840 Shijocho, Kashiharashi, Nara 634-8521, Japan. Tel: +81-744-22-3051. Fax: +81-744-25-7657. E-mail: [email protected]
779
780
K. Obayashi et al.
Obayashi et al., 2012). Thus, LAN exposure in home settings may cause circadian misalignment and increased nighttime BP through a mechanism independent of changing in nocturnal total melatonin levels, though it remains unclear whether LAN exposure in home settings is associated with increased nighttime BP. We cross-sectionally examined the association between LAN exposure objectively measured in home settings and nighttime BP in elderly individuals.
Chronobiol Int Downloaded from informahealthcare.com by Michigan University on 04/19/15 For personal use only.
METHODS Participants A total of 537 elderly subjects were voluntarily recruited between September 2010 and April 2012 in a study entitled Housing Environments and Health Investigation among Japanese Older People in Nara, Kansai Region: a prospective community-based cohort (HEIJO-KYO) study. Of these, 528 home-dwelling participants met the inclusion criteria requiring an age 60 years and a record of LAN measurements. All the participants provided written informed consent, and the study protocol was performed in accordance with the ethics committee of Nara Medical University and the ethical standards of the Journal (Portaluppi et al., 2010). Study protocol Our previously reported study included the protocols for measuring LAN (Obayashi et al., 2013). In brief, we visited the participants’ homes, collected overnight fasting venous blood samples and gathered demographic and medical information using a standardized questionnaire. In addition, we simultaneously initiated 48-h measurements of LAN exposure, ambulatory BP (ABP) and actigraphy. We instructed participants to collect their urine the following night and to maintain a standardized sleep diary logging the time they went to bed and the amount of time they spent in bed. Measurement of LAN LAN exposure was measured at 1-min intervals using a portable light meter (LX-28SD; Sato Shouji Inc., Kanagawa, Japan) with a sensor positioned 60 cm above the floor, near the head of the bed and facing the ceiling. The optical sensor has a spectral sensitivity approximating that of the human eye, the illuminance sensitivity of which ranges from 0 to 100 000 lux. Three parameters of LAN exposure were used in the analysis and were defined as follows: (1) The average light intensity during the in-bed period (NLavg). (2) The duration of light intensity 10 lux during the in-bed period (NL 10). (3) The duration of light intensity 100 lux during the in-bed period (NL 100). The participants were divided into the LAN and darker groups on the basis of NLavg cutoff values (3, 5 and 10 lux) predefined by a study conducted in a
controlled setting demonstrating the effects of LAN exposure 3 lux on human physiology (Zeitzer et al., 2000).
ABP monitoring ABP monitoring (ABPM) was performed using a validated ambulatory recorder (TM-2430; A&D Co. Ltd., Tokyo, Japan) and cuff on the non-dominant arm. BP was measured at 30-min intervals for 48 h. Nighttime was defined as the in-bed period based on sleep diaries. Erroneous BP data were excluded as were values with a systolic BP (SBP) 550 or 4250 mmHg and a diastolic BP530 or 4160 mmHg. BP and heart rate (HR) data, which were lost for 450% of the study period by errors and artifacts, were excluded from analyses. Urinary 6-sulfatoxymelatonin excretion The urine collection protocol involved discarding the last void at bedtime and collecting each subsequent void until the first morning void. The samples were stored in a dark bottle at room temperature, the total volume was measured and then stored at 20 C until assay. Urinary 6-sulfatoxymelatonin concentration was measured at a commercial laboratory (SRL, Inc., Tokyo, Japan) using a highly sensitive enzyme-linked immunosorbent assay kit (RE54031; IBL International, Hamburg, Germany). Urinary 6-sulfatoxymelatonin excretion (UME) was calculated as follows: UME (mg) ¼ 6-sulfatoxymelatonin concentration (mg/mL) total overnight urine volume (mL). UME data were considered missing if the urine was not collected according to the protocol. We used UME as an index of melatonin secretion because it correlates closely with the amount of nocturnal melatonin secretion (Baskett et al., 1998). Physical activity and sleep measurements Physical activity and sleep measurements were recorded at 1-min intervals for 48 h using an actigraph (Actiwatch 2; Respironics Inc., Murrysville, PA) that was worn on the non-dominant wrist. Four actigraphic parameters were determined using Actiware version 5.5 (Respironics Inc.), with a default wake threshold value used to identify periods of wake or sleep (Philips Respironics Actiware Tutorials, 2013): (1) daytime physical activity, the average valid physical activity counts per min during the out-of-bed period; (2) sleep efficiency, the total sleep time divided by the duration in bed; (3) total sleep time, the sleep time during the in-bed period; and (4) probable sleep-disordered breathing (SDB), sleep efficiency 570% or total sleep time 55 h (Mehra et al., 2008). Other measurements Body mass index (BMI) was calculated as weight (kg)/ height (m2). Current smoking status, habitual alcohol consumption and drug use were evaluated by a questionnaire. Diabetes mellitus was diagnosed based on medical history or current antidiabetic treatment or if Chronobiology International
Association between LAN and nighttime BP
Chronobiol Int Downloaded from informahealthcare.com by Michigan University on 04/19/15 For personal use only.
fasting plasma glucose was 7.0 mmol/L and HbA1c level was 6.5% of the National Glycohemoglobin Standardization Program value. The estimated glomerular filtration rate (eGFR) was calculated according to the Japanese Society of Nephrology–Chronic Kidney Disease Practice Guide (Irie et al., 2005). Time to bed, duration in bed and nocturia frequency were obtained from the sleep diary. Day length in Nara (latitude: 34 N) from sunrise to sunset on measurement days was extracted from the National Astronomical Observatory of Japan website (2013).
Statistical analyses Variables with a normal distribution were reported as means (SD), whereas variables with asymmetric distribution were reported as medians and interquartile ranges. Mean and median were compared between the LAN and darker groups using the unpaired t-test and Mann–Whitney U test, respectively. The Chi-square test was performed for comparison of categorical data. For LAN, ABPM, actigraphy, sleep diary and day length data, the average of two consecutive days was used for further analyses. UME values were naturally log-transformed for analysis. We evaluated associations between nighttime BP and predictive variables including age, gender, BMI, current smoking status, habitual alcohol consumption, medication use, eGFR, diabetes, duration in bed, time to bed, day length, LAN, daytime physical activity, sleep quality, probable SDB, nocturia and UME using univariate linear regression models. Mean nighttime BP adjusted for all predictive variables, which were marginally to significantly associated with nighttime BP (p50.20) in univariate models, were compared between the LAN and darker groups using analysis of covariance (ANCOVA). Statistical analyses were performed using SPSS version 19.0 for Windows (IBM SPSS Inc., Chicago, IL), and a two-sided p value of 50.05 considered statistically significant. RESULTS Mean participants’ age was 72.8 (6.5) years, and 247 (46.8%) were male. The mean duration in bed was significantly longer, and the mean time to bed was significantly earlier in the LAN group (average: 5 lux) than the darker group (average: 55 lux; Table 1). Dichotomous comparisons of LAN, BP, actigraphic, nocturia and melatonin parameters at three cutoff values of LAN are presented in Table 2. NLavg in the darker group was 51/20, 51/30 and 51/30 of NLavg in the LAN group at cutoff values of 3, 5 and 10 lux, respectively. NL 10 in the darker group was 51/25, 51/25 and 51/19 of NL 10 in the LAN group at cutoff values of 3, 5 and 10 lux, respectively. In the Darker group, 81%, 78% and 73% of the participants at the cutoff values of 3, 5 and 10 lux, respectively, were never exposed to LAN 100 lux. Night-to-night correlation of NLavg between the two nights in the measurement !
Informa Healthcare USA, Inc.
781
TABLE 1. Basic and clinical characteristics stratified by LAN exposure. Characteristics No. of participants Basic parameters Age, mean, years Gender, number, male BMI, mean, kg/m2 Current smoker, number Alcohol consumption (30 g/day), number
LAN 5 (5 lux) 109 72.5 54 23.2 8 14
Darker 5 (55 lux)
p
419 (6.8) (49.5) (2.9) (7.3) (12.8)
72.9 193 22.8 26 52
(6.4) (46.1) (3.1) (6.2) (12.4)
0.58 0.52 0.20 0.12 0.90
Clinical parameters Use of antihypertensive 50 (45.9) 185 (44.2) 0.75 drug, number Evening use of 15 (13.8) 45 (10.7) 0.38 antihypertensive drug, number Sleep medication, number 16 (14.8) 41 (9.8) 0.14 eGFR, mean, mL/min/1.73 m2 71.7 (14.0) 71.9 (15.0) 0.90 Diabetes, number 17 (15.6) 50 (11.9) 0.31 Duration in bed*, mean, min 518.7 (79.0) 491.0 (75.2) 50.01 Time to bed*, mean, 22:16 (1:18) 22:34 (1:04) 0.03 clock time Day length (511 hours)*, 57 (52.3) 200 (47.7) 0.40 number Data are expressed as means (SD) or number (%). LAN, light at night; eGFR, estimated glomerular filtration rate. *Average for two days.
period was moderately high (Spearman’s rank correlation coefficient: 0.64). Compared with the darker group, the LAN group showed significantly higher nighttime SBP and DBP and lower sleep efficiency. In contrast, HR and UME did not significantly differ between the LAN and darker groups. Univariate linear regression analyses using nighttime BP data from 524 participants (four missing) showed significant associations between nighttime SBP and age; gender; diabetes; duration in bed; time to bed; LAN 3, 5 and 10; daytime physical activity; sleep efficiency; and nocturia (Table 3). Antihypertensive drug use (p ¼ 0.09), evening use of antihypertensive drugs (p ¼ 0.07), probable SDB (p ¼ 0.07) and log-transformed UME (p ¼ 0.13) were marginally but insignificantly associated with nighttime SBP. Gender; LAN 3, 5 and 10; daytime physical activity; and frequent nocturia were significantly associated with nighttime DBP. Current smoking status (p ¼ 0.07), habitual alcohol consumption (p ¼ 0.06), time to bed (p ¼ 0.18), duration in bed (p ¼ 0.16) and sleep efficiency (p ¼ 0.16) were marginally but insignificantly associated with nighttime DBP. In multivariate analysis using ANCOVA (Table 4), the LAN group showed significantly higher nighttime SBP (LAN 3 vs. darker 3: adjusted mean nighttime SBP: 119.8 vs. 116.5 mmHg, p ¼ 0.04; LAN 5 vs. darker 5: 120.8 vs. 116.5 mmHg, p ¼ 0.01; LAN 10 vs. darker 10: 121.5 vs. 116.8 mmHg, p ¼ 0.03) and DBP (LAN 3 vs. Darker 3: adjusted mean nighttime DBP: 69.4 vs. 67.1 mmHg,
(9.4) (86.9) (8.5) (76.6) (4.3–10.4)
(7.7) (77.9) (6.9) (72.1) (3.9–9.5)
85.1 435.5 26 276 6.5
(13.7) (7.6) (7.5) (15.8) (8.3) (7.3)
81.8 440.3 12 111 6.8
135.4 79.4 72.6 116.5 67.0 59.9 298.1 (108.0)
(14.2) (7.8) (7.5) (15.8) (8.8) (7.4)
285.9 (97.7)
137.6 80.6 73.1 120.4 69.8 60.8
0.4 (0.04–1.1) 2.0 (0.0–9.0) 0.0 (0.0–2.0)
383
Darker 3 (53 lux)
50.01 0.55 0.54 0.30 0.42
0.24
0.11 0.13 0.47 0.01 50.01 0.21
50.01 50.01 50.01
p
(14.0) (7.9) (7.4) (16.1) (9.0) (7.9)
81.4 449.2 10 89 6.8
(8.3) (78.2) (9.4) (81.7) (4.5–10.4)
285.8 (102.3)
138.4 81.0 72.7 121.8 70.5 60.5
13.3 (7.8–21.1) 62.5 (36.3–111.3) 24.0 (7.0–55.3)
109
LAN 5 (5 lux)
(13.8) (7.6) (7.5) (15.7) (8.3) (7.2)
84.9 433.6 28 298 6.6
(8.2) (80.7) (6.8) (71.1) (3.9–9.6)
297.1 (106.1)
135.4 79.4 72.7 116.4 67.1 60.0
0.4 (0.06–1.5) 2.5 (0.0–13.0) 0.0 (0.0–0.0)
419
Darker 5 (55 lux)
50.01 0.07 0.36 0.03 0.65
0.32
0.045 0.06 0.96 50.01 50.01 0.57
50.01 50.01 50.01
p
(14.0) (7.7) (7.7) (17.3) (9.4) (7.8)
81.0 456.7 7 52 6.2
(9.0) (76.0) (10.8) (76.5) (4.3–9.8)
286.8 (104.8)
138.5 80.9 72.7 121.8 70.2 60.5
20.0 (13.9–28.1) 83.5 (53.6–132.1) 45.0 (23.6–76.8)
68
LAN 10 (10 lux)
(13.8) (7.7) (7.5) (15.6) (8.4) (7.2)
84.7 433.9 31 335 6.6
(8.1) (80.7) (6.9) (72.8) (3.9–9.7)
295.9 (105.5)
135.7 79.6 72.7 116.9 67.4 60.1
0.6 (0.09–2.2) 4.3 (0.0–16.5) 0.0 (0.0–0.5)
460
Darker 10 (510 lux)
50.01 0.03 0.26 0.53 0.88
0.51
0.12 0.20 0.99 0.02 0.01 0.64
50.01 50.01 50.01
p
Data are expressed as means (SD), medians (interquartile range), or numbers (%). LAN, light at night; BP, blood pressure; NLavg average night light exposure during the in-bed period; NL 410, duration of night light exposure410 lux during the in-bed period; and NL4100, duration of night light exposure4100 lux during the in-bed period; SBP, systolic blood pressure; DBP, diastolic blood pressure; HR, heart rate; SDB, sleep-disordered breathing; UME, urinary 6-sulfatoxymelatonin excretion. *Average for two days. ySleep efficiency 570% and/or total sleep time 55 hours.
Actigraphic parameters* Daytime physical activity, mean, count/min Sleep efficiency, mean, % Total sleep time, mean, min Probable SDBy, number Nocturia (1 time/night), number UME, median, mg
Ambulatory BP parameters* Daytime SBP, mmHg, mean Daytime DBP, mmHg, mean Daytime HR, beats per min, mean Nighttime SBP, mmHg, mean Nighttime DBP, mmHg, mean Nighttime HR, beats per min, mean
145
No. of participants LAN parameters*, median NLavg, lux NL 410, min NL 4100, min 8.7 (5.1–18.2) 50.5 (26.5–146.7) 14.5 (0.0–42.3)
LAN 3 (3 lux)
Characteristics
TABLE 2. Comparisons of LAN, BP, actigraphic, nocturia and melatonin parameters between LAN and Darker Groups.
Chronobiol Int Downloaded from informahealthcare.com by Michigan University on 04/19/15 For personal use only.
782 K. Obayashi et al.
Chronobiology International
Association between LAN and nighttime BP
783
TABLE 3. Univariate linear regression analysis for the association between variables and nighttime SBP and DBP. Nighttime SBP Variables
Chronobiol Int Downloaded from informahealthcare.com by Michigan University on 04/19/15 For personal use only.
Demographic parameters Age (per years) Gender (male vs. female) BMI (per kg/m2) Current smoker (yes vs. no) Alcohol consumption (430 vs. 530 g/day) Clinical parameters Use of antihypertensive drug (yes vs. no) Evening use of antihypertensive drug (yes vs. no) Sleep medication (yes vs. no) eGFR (per mL/min/1.73 m2) Diabetes (yes vs. no) Duration in bed* (per min) Time to bed* (per min delay) Day length* (511 vs. 411 hours) LAN parameters* LAN3 (NLavg 43 vs. 53 lux) LAN5 (NLavg 45 vs. 55 lux) LAN10 (NLavg 410 vs. 510 lux) Actigraphic parameters* Daytime physical activity (per count/min) Sleep efficiency (per %) Total sleep time (per min) Probable SDBy (yes vs. no) Nocturia (41 vs. 51 time/night) log-transformed UME (per log mg)
95% CI
Nighttime DBP p
95% CI
p
0.558 5.454 0.190 3.945 2.559
0.351 2.754 0.261 2.588 1.557
0.765 8.154 0.641 10.478 6.674
50.01 50.01 0.41 0.24 0.22
0.017 3.558 0.151 3.238 2.099
0.131 2.121 0.091 0.259 0.104
0.097 4.995 0.393 6.734 4.301
0.77 50.01 0.22 0.07 0.06
2.413 3.967 0.017 0.040 4.437 0.030 0.025 0.958
0.337 0.315 4.444 0.134 0.360 0.013 0.045 1.777
5.164 8.248 4.410 0.053 8.515 0.048 0.005 3.692
0.09 0.07 0.99 0.40 0.03 50.01 0.02 0.49
0.290 0.751 0.448 0.006 0.943 0.007 0.007 0.280
1.189 1.551 2.821 0.056 3.137 0.003 0.018 1.747
1.769 3.053 1.925 0.044 1.252 0.016 0.003 1.187
0.70 0.64 0.71 0.82 0.40 0.16 0.18 0.71
3.922 5.395 4.935
0.870 2.034 0.835
6.973 8.755 9.035
0.01 50.01 0.02
2.773 3.472 2.825
1.145 1.678 0.629
4.402 5.267 5.022
50.01 50.01 0.01
0.027 0.202 0.008 4.871 6.318 1.545
0.040 0.368 0.009 0.474 3.725 3.545
0.014 0.035 0.025 10.217 9.361 0.454
50.01 0.02 0.38 0.07 50.01 0.13
0.009 0.064 0.0003 1.355 2.320 0.493
0.016 0.152 0.009 1.472 0.675 0.574
0.003 0.024 0.009 4.183 3.965 1.560
50.01 0.16 0.94 0.35 50.01 0.37
SBP, systolic blood pressure; DBP, diastolic blood pressure; CI, confidence interval; BMI, body mass index; eGFR, estimated glomerular filtration rate; NLavg, average intensity of night light; SDB, sleep-disordered breathing; UME, urinary 6-sulfatoxymelatonin excretion. *Average for two days. ySleep efficiency 570% and/or total sleep time 55 hours. TABLE 4. Comparisons of adjusted mean nighttime BP between LAN and Darker groups using ANCOVA. BP parameters mean (95% CI), mmHg
LAN 3 (n ¼ 145)
Nighttime SBPx Nighttime DBPô
119.8 (117.1–122.4) 69.4 (68.0–70.8) LAN 5 (n ¼ 109)
Nighttime SBPx Nighttime DBPô
120.8 (117.8–123.9) 70.1 (68.5–71.7) LAN 10 (n ¼ 68)
Nighttime SBPx Nighttime DBPô
121.5 (117.7–125.4) 70.0 (67.9–72.1)
Darker 3 (n ¼ 383) 116.5 (114.9–118.1) 67.1 (66.2–67.9) Darker 5 (n ¼ 419) 116.5 (115.0–118.0) 67.1 (66.3–67.9) Darker 10 (n ¼ 460) 116.8 (115.4–118.2) 67.4 (66.6–68.1)
Adjusted difference (LAN3-Darker3, 95% CI) 3.3 (0.2–6.4) 2.3 (0.7–4.0)
p 0.04 50.01
Adjusted difference (LAN5-Darker5, 95% CI) 4.3 (0.9–7.8) 2.9 (1.1–4.7)
0.01 50.01
Adjusted difference (LAN10-Darker10, 95% CI) 4.7 (0.6–8.9) 2.6 (0.4–4.8)
0.03 0.02
BP, blood pressure; LAN, light at night; ANCOVA, analysis of covariance; CI, confidence interval; SBP, systolic blood pressure; DBP, diastolic blood pressure. xData adjusted for age, gender, use of antihypertensive drug, evening use of antihypertensive drug, diabetes, duration in bed, time to bed, daytime physical activity, sleep efficiency, probable sleep-disordered breathing, nocturia, and log-transformed urinary 6-sulfatoxymelatonin excretion. ôData adjusted for gender, current smoking status, alcohol consumption, duration in bed, time to bed, daytime physical activity, sleep efficiency, and nocturia.
p50.01; LAN 5 vs. Darker 5: 70.1 vs. 67.1 mmHg, p50.01; LAN 10 vs. Darker 10: 70.0 vs. 67.4 mmHg, p ¼ 0.02) than the Darker group consistently in comparisons using three different cutoff values of LAN 3, 5 and 10 lux. These associations were independent of potential confounding factors such as age, gender, !
Informa Healthcare USA, Inc.
antihypertensive drug use, diabetes, time to bed, duration in bed, daytime physical activity, sleep efficiency, probable SDB, nocturia and log-transformed UME in the nighttime SBP model and were independent of gender, current smoking status, alcohol consumption, time to bed, duration in bed, daytime physical activity,
784
K. Obayashi et al.
Chronobiol Int Downloaded from informahealthcare.com by Michigan University on 04/19/15 For personal use only.
sleep efficiency and nocturia in the nighttime DBP model. Furthermore, we have conducted additional analyses with regard to the LAN-BP association in the actual sleep period defined by actigraphy. After adjustment for age and gender, all LAN groups (i.e. LAN3, LAN5 and LAN10) consistently showed higher SBP and DBP than the Darker groups (LAN 3 vs. Darker 3: adjusted mean nighttime SBP: 120.6 vs. 115.5 mmHg, p50.01, DBP: 69.5 vs. 66.6 mmHg, p50.01; LAN 5 vs. Darker 5: SBP: 119.9 vs. 115.8 mmHg, p ¼ 0.049, DBP: 69.1 vs. 66.7 mmHg, p ¼ 0.03; LAN 10 vs. Darker 10: SBP: 122.0 vs. 115.9 mmHg, p ¼ 0.02 and DBP: 69.6 vs. 66.8 mmHg, p ¼ 0.047).
DISCUSSION Our findings that LAN exposure in home settings is significantly associated with increased nighttime BP independent of UME are, to the best of our knowledge, the first report in humans and consistent with those of previous studies demonstrating an association between night-shift work and increased nighttime BP. In a previous study using ABPM, evening-shift/night-shift workers were shown to have 6.0 mmHg higher nighttime SBP and 2.8 mmHg higher nighttime DBP than day-shift workers (Yamasaki et al., 1998). Similarly, we demonstrated that the LAN group exhibited 3.3–4.7 mmHg higher nighttime SBP and 2.3–2.9 mmHg higher nighttime DBP than the Darker group. Night-shift workers are exposed to higher-intensity LAN than the LAN group in this study (Grundy et al., 2009); thus, the results of this study indicate that even dimmer LAN (average 8.7– 20.0 lux) than that experienced by night-shift workers can significantly affect nighttime BP in the general elderly population. Although the mechanisms by which LAN exposure may increase nighttime BP remain unclear, previous epidemiological and experimental studies support a negative effect of LAN exposure on nighttime BP by changing in endogenous melatonin levels, sleep quality and/or patterns of sympathetic nerve activity. Decreased endogenous melatonin levels and impaired sleep quality are observed in night-shift workers (Drake et al., 2004; Grundy et al., 2011), and night-shift workers have higher nighttime BP (Chau et al., 1989; Lo et al., 2008; Yamasaki et al., 1998). Several experimental studies have shown that melatonin administration reduces nighttime BP (Arangino et al., 1999; Lusardi et al., 1997; Scheer et al., 2004). Circadian misalignment between sleep/wake cycles is associated with increased nighttime BP and increased endogenous catecholamine levels as well as impaired sleep quality (Scheer et al., 2009). In the present study, LAN exposure was found to be associated with lower actigraphic sleep efficiency and increased nighttime SBP; furthermore, we demonstrated by multivariate analysis that LAN exposure is significantly associated with increased nighttime BP
independently of actigraphic sleep efficiency. In contrast, UME was not significantly associated with LAN exposure. Although it is well established that LAN exposure suppresses melatonin secretion in controlled setting (Brainard et al., 2008), epidemiological studies have reported that LAN exposure in home settings is not significantly associated with nocturnal total melatonin levels (Davis et al., 2001; Levallois et al., 2001; Obayashi et al., 2012). In the present study, the final multivariate model showed that LAN exposure is significantly associated with increased nighttime BP independently of UME. Next, night-shift work diminishes a normal decrease in urinary norepinephrine and epinephrine levels during the non-work period, causing higher urinary catecholamine levels during the non-work period in night-shift workers than in day-shift workers (Yamasaki et al., 1998). Moreover, night-shift work is associated with increased low-frequency power and low–high-frequency power ratio in HR variability, indicating changes in sympathovagal cardiac modulation (Chung et al., 2009). Among normal-living young humans, it was also demonstrated that LAN exposure increases the nighttime HR in controlled laboratory settings (Scheer et al., 1999). However, in the present study, there were no significant associations between LAN exposure and HR in our elderly participants. Similar differences in response to environmental factors between BP and HR were reported to be influenced by age (Itoh et al., 2013). The clinical implications of increased nighttime SBP observed in the present study for cardiovascular events and total mortality could be interpreted by metaanalysis of population-based prospective studies. A 3.3–4.7 mmHg increase in nighttime SBP is predicted to increase cardiovascular events by 4.5%–6.4% and total mortality by 4.7%–6.7% (Boggia et al., 2007). LAN is a common exposure, to which 145 (27.5%) of 528 elderly individuals have been exposed to LAN 3 lux in our study. Approximately, 10 000 annual excess deaths could be estimated from additional mortality, exposed population for dim LAN and the Japanese national data of annual deaths for individuals aged 60-years-old (The Statistics and Information Department, Minister’s secretariat, Ministry of Health, Labour and Welfare of Japan, 2010). Although some behavior in bed before/after sleep may be associated with both LAN exposure and nighttime BP, the association between LAN exposure and nighttime BP was independent of light exposure in bed before sleep-onset and after sleep-offset. In our elderly population, we observed three phenotypes of LAN exposure patterns during the in-bed period (the firstsided, constant and the last-sided). The first-sided pattern of LAN exposure is more likely to be exposed to light in the first hour of the in-bed period and may be associated with early bedtime and behavior in bed before sleep such as reading and watching TV. The lastsided pattern of LAN exposure is more likely to be Chronobiology International
Chronobiol Int Downloaded from informahealthcare.com by Michigan University on 04/19/15 For personal use only.
Association between LAN and nighttime BP exposed to light in the last hour of the in-bed period and may be associated with sunlight through the window due to late wake time. However, in the present study, the association between LAN exposure and nighttime BP was independent of bedtime and duration in bed and was consistent with those in the actual sleep period defined by actigraphy. In the present study, BMI was not significantly associated with nighttime BP, whereas, we previously reported that LAN exposure 3 lux is associated with obesity (Obayashi et al., 2013). In previous epidemiological studies in elderly individuals, the associations of BMI with cardiovascular and all-cause mortality were not linear but U-shaped (Corrada et al., 2006; RomeroCorral et al., 2006). In addition, the prevalence of obese elderly (BMI 30 kg/m2) and underweight elderly (BMI518.5 kg/m2) were not high (1.3% and 7.4%, respectively) in our study. Considering together, it is possible that BMI was not significantly associated with nighttime BP in the present elderly population. However, LAN-associated obesity may partially explain the association between LAN exposure and nighttime BP. Further epidemiological research with a longitudinal design is required to better understand the associations among LAN exposure, obesity and nighttime BP. The present study has several limitations. First, the measurement of LAN exposure was performed on only two consecutive nights; however, we showed the correlation between LAN exposure on different nights to be moderately high. Thus, the average values may be accurate measure of the central tendency. In addition, ABP devices may differentially disturb sleep quality between the first and second nights; however, consistent associations between LAN exposure and nighttime BP were observed both on the first and second night (data were not shown). Second, the photometers used in this study were not ambulatory devices, and LAN exposure may be underestimated because it did not record light exposure in rooms other than the bedroom, e.g. during nocturia. In addition, LAN exposure in this study included light intensity from a variety of lighting sources, e.g. bedroom light, light from the other room, TV screen and street light; therefore, horizontal measurement of LAN was not perfect to measure actual exposure of LAN. Further research using ambulatory photometers at cornea level is required to better assess the association between LAN exposure and nighttime BP. Furthermore, human circadian physiology is more closely correlated to shorter wave length rather than intensity (Brainard et al., 2008); therefore, ambulatory devices which can measure a power of the short wave length are also needed. Third, we evaluated sleep quality by actigraphy and may ignore the residual confounding effect of obstructive sleep apnea (OSA), an important condition that could increase nighttime BP (Becker et al., 2003). In the present study, probable SDB defined by actigraphy (sleep efficiency 570% or total sleep time 55 h), a predictor of SDB including OSA (Mehra et al., !
Informa Healthcare USA, Inc.
785
2008), did not differ significantly between the LAN and Darker groups. Finally, we selected this aging group with most retired to minimize the effect of current night-shift work on the association between LAN exposure and BP; however, we did not include any information about prior history of night-shift work in the analysis. In conclusion, LAN exposure in home settings is significantly associated with increased nighttime BP in elderly individuals independently of UME. To the best of our knowledge, this is the first possible report on LAN exposure as a novel and common risk factor for increased nighttime BP in elderly individuals.
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.
DECLARATION OF INTEREST All authors report no conflicts of interest. 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.
REFERENCES Arangino S, Cagnacci A, Angiolucci M, et al. (1999). Effects of melatonin on vascular reactivity, catecholamine levels, and blood pressure in healthy men. Am J Cardiol. 83:1417–19. Baskett JJ, Cockrem JF, Antunovich TA. (1998). Sulphatoxymelatonin excretion in older people: Relationship to plasma melatonin and renal function. J Pineal Res. 24:58–61. Becker HF, Jerrentrup A, Ploch T, et al. (2003). Effect of nasal continuous positive airway pressure treatment on blood pressure in patients with obstructive sleep apnea. Circulation. 107: 68–73. Berson DM, Dunn FA, Takao M. (2002). Phototransduction by retinal ganglion cells that set the circadian clock. Science. 295: 1070–3. Boggia J, Li Y, Thijs L, et al. (2007). Prognostic accuracy of day versus night ambulatory blood pressure: A cohort study. Lancet. 370:1219–29. Brainard GC, Sliney D, Hanifin JP, et al. (2008). Sensitivity of the human circadian system to short-wavelength (420-nm) light. J Biol Rhythms. 23:379–86. Brzezinski A. (1997). Melatonin in humans. N Engl J Med. 336: 186–95. Chau NP, Mallion JM, de Gaudemaris R, et al. (1989). Twentyfour-hour ambulatory blood pressure in shift workers. Circulation. 80:341–7. Chung MH, Kuo TB, Hsu N, et al. (2009). Sleep and autonomic nervous system changes – Enhanced cardiac sympathetic
Chronobiol Int Downloaded from informahealthcare.com by Michigan University on 04/19/15 For personal use only.
786
K. Obayashi et al.
modulations during sleep in permanent night shift nurses. Scand J Work Environ Health. 35:180–7. Corrada MM, Kawas CH, Mozaffar F, Paganini-Hill A. (2006). Association of body mass index and weight change with all-cause mortality in the elderly. Am J Epidemiol. 163:938–49. Davis S, Kaune WT, Mirick DK, et al. (2001). Residential magnetic fields, light-at-night, and nocturnal urinary 6-sulfatoxymelatonin concentration in women. Am J Epidemiol. 154:591–600. Drake CL, Roehrs T, Richardson G, et al. (2004). Shift work sleep disorder: Prevalence and consequences beyond that of symptomatic day workers. Sleep. 27:1453–62. Fagard RH, Celis H, Thijs L, et al. (2008). Daytime and nighttime blood pressure as predictors of death and cause-specific cardiovascular events in hypertension. Hypertension. 51:55–61. Grundy A, Sanchez M, Richardson H, et al. (2009). Light intensity exposure, sleep duration, physical activity, and biomarkers of melatonin among rotating shift nurses. Chronobiol Int. 6: 1443–61. Grundy A, Tranmer J, Richardson H, et al. (2011). The influence of light at night exposure on melatonin levels among Canadian rotating shift nurses. Cancer Epidemiol Biomarkers Prev. 20: 2404–12. Irie F, Iso H, Sairenchi T, et al. (2005). The relationships of proteinuria, serum creatinine, glomerular filtration rate with cardiovascular disease mortality in Japanese general population. Kidney Int. 69:1264–71. Itoh H, Ajisaka R, Koike A, et al. (2013). Heart rate and blood pressure response to ramp exercise and exercise capacity in relation to age, gender, and mode of exercise in a healthy population. J Cardiol. 61:71–8. Levallois P, Dumont M, Touitou Y, et al. (2001). Effects of electric and magnetic fields from high-power lines on female urinary excretion of 6-sulfatoxymelatonin. Am J Epidemiol. 154:601–9. Lo SH, Liau CS, Hwang JS, Wang JD. (2008). Dynamic blood pressure changes and recovery under different work shifts in young women. Am J Hypertens. 21:759–64. Lusardi P, Preti P, Savino S, et al. (1997). Effect of bedtime melatonin ingestion on blood pressure of normotensive subjects. Blood Press Monit. 2:99–103. Mehra R, Stone KL, Ancoli-Israel S, et al. (2008). Interpreting wrist actigraphic indices of sleep in epidemiologic studies of the elderly: The Study of Osteoporotic Fractures. Sleep. 31:1569–76. National Astronomical Observatory of Japan. (2013). Available at: http://eco.mtk.nao.ac.jp/koyomi/index.html.en. Accessed on 30 October 2013. Navara KJ, Nelson RJ. (2007). The dark side of light at night: Physiological, epidemiological, and ecological consequences. J Pineal Res. 43:215–24.
Obayashi K, Saeki K, Iwamoto J, et al. (2012). Positive effect of daylight exposure on nocturnal urinary melatonin excretion in the elderly: A cross-sectional analysis of the HEIJO-KYO study. J Clin Endocrinol Metab. 97:4166–73. Obayashi K, Saeki K, Iwamoto J, et al. (2013). Exposure to light at night, nocturnal urinary melatonin excretion, and obesity/ dyslipidemia in the elderly: A cross-sectional analysis of the HEIJO-KYO study. J Clin Endocrinol Metab. 98:337–44. Paschos GK, FitzGerald GA. (2010). Circadian clocks and vascular function. Circ Res. 106:8337–41. Philips Respironics Actiware Tutorials. (2013). Available at: http:// learnactiware.com/tutorials/. Accessed on 30 October 2013. Portaluppi F, Smolensky MH, Touitou Y. (2010). Ethics and methods for biological rhythm research on animals and human beings. Chronobiol Int. 27:1911–29. Provencio I, Jiang G, De Grip WJ, et al. (1998). Melanopsin: An opsin in melanophores, brain, and eye. Proc Natl Acad Sci USA. 95:340–5. Romero-Corral A, Montori VM, Somers VK, et al. (2006). Association of bodyweight with total mortality and with cardiovascular events in coronary artery disease: A systematic review of cohort studies. Lancet. 368:666–78. Scheer FA, van Doornen LJ, Buijs RM. (1999). Light and diurnal cycle affect human heart rate: Possible role for the circadian pacemaker. J Biol Rhythms. 14:202–12. Scheer FA, Van Montfrans GA, van Someren EJ, et al. (2004). Daily nighttime melatonin reduces blood pressure in male patients with essential hypertension. Hypertension. 3: 192–7. Scheer FA, Hilton MF, Mantzoros CS, Shea SA. (2009). Adverse metabolic and cardiovascular consequences of circadian misalignment. Proc Natl Acad Sci USA. 106:4453–8. Sega R, Facchetti R, Bombelli M, et al. (2005). Prognostic value of ambulatory and home blood pressures compared with office blood pressure in the general population: Follow-up results from the Pressioni Arteriose Monitorate e Loro Associazioni (PAMELA) study. Circulation. 111:1777–83. The Statistics and Information Department, Minister’s secretariat, Ministry of Health, Labour and Welfare of Japan. (2010). Vital Statistics of Japan 2010. 3:122–3. Wyse CA, Selman C, Page MM, et al. (2011). Circadian desynchrony and metabolic dysfunction; did light pollution make us fat? Med Hypotheses. 77:1139–44. Yamasaki F, Schwartz JE, Gerber LM, et al. (1998). Impact of shift work and race/ethnicity on the diurnal rhythm of blood pressure and catecholamines. Hypertension. 32:417–23. Zeitzer JM, Dijk D, Kronauer RE, et al. (2000). Sensitivity of the human circadian pacemaker to nocturnal light: Melatonin phase resetting and suppression. J Physiol. 526:695–702.
Chronobiology International
ORIGINAL ARTICLE
Association between light exposure at night and nighttime blood pressure in the elderly independent of nocturnal urinary melatonin excretion Kenji Obayashi1, Keigo Saeki1, Junko Iwamoto2, Yoshito Ikada3, and Norio Kurumatani1 1
Department of Community Health and Epidemiology, Nara Medical University School of Medicine, Nara, Japan, Department of Nursing, Tenri Health Care University, Nara, Japan, and 3Department of Surgery, Nara Medical University School of Medicine, Nara, Japan
Chronobiol Int Downloaded from informahealthcare.com by Michigan University on 04/19/15 For personal use only.
2
Circadian misalignment between internal and environmental rhythms dysregulates blood pressure (BP) variability because of disruption of the biological clock, resulting in increased nighttime BP. Although exposure to light-at-night is associated with the circadian misalignment, it remains unclear whether exposure to light-at-night in home settings is associated with nighttime BP. In this cross-sectional analysis of 528 elderly individuals (mean age: 72.8 years), we measured bedroom light intensity at 1-min intervals on two consecutive nights along with ambulatory BP, overnight urinary melatonin excretion and actigraphy. With regard to adjusted mean comparisons using analysis of covariance, the light-at-night group (average: 5 lux; n ¼ 109) showed significantly higher nighttime systolic BP (SBP; adjusted mean: 120.8 vs. 116.5 mmHg, p ¼ 0.01) and diastolic BP (70.1 vs. 67.1 mmHg, p50.01) compared with the Darker group (average: 55 lux; n ¼ 419) independently of potential confounding factors including overnight urinary melatonin excretion and actigraphic sleep quality. We observed consistent associations between light-at-night and nighttime BP in different cutoff values for light-at-night intensity (i.e. 3 and 10 lux). In conclusion, exposure to light-atnight in home settings is significantly associated with increased nighttime BP in elderly individuals independently of overnight urinary melatonin excretion. A 4.3 mmHg increase in nighttime SBP is associated with a 6.1% increase in total mortality, which corresponds to approximately 10 000 annual excess deaths in Japanese elderly population. Keywords: Actigraphy, circadian rhythm, elderly, light at night, melatonin, nighttime blood pressure
INTRODUCTION
modern society (Navara & Nelson, 2007; Wyse et al., 2011). Recently, intrinsically photosensitive retinal ganglion cells and its photopigment melanopsin were identified as primary receptors of environmental light, and the mechanisms underlying the association between LAN exposure and SCN function are being solved (Berson et al., 2002; Provencio et al., 1998). Physiologically, LAN exposure is the most important environmental cue for the disruption of SCN function, leading to circadian misalignment (Brzezinski, 1997; Zeitzer et al., 2000). Melatonin, a pineal gland hormone, is hypothesized to be a major contributor to the association between LAN exposure and circadian misalignment; however, epidemiological studies have reported that LAN exposure in home settings is not significantly associated with nocturnal total melatonin levels (Davis et al., 2001; Levallois et al., 2001;
Nighttime blood pressure (BP) is a stronger predictor of cardiovascular risk and mortality than daytime BP and night-to-day BP ratio because of its high reproducibility (Boggia et al., 2007; Fagard et al., 2008; Sega et al., 2005). Circadian BP variability is regulated by the suprachiasmatic nucleus (SCN) of the hypothalamus, which contains the master biological clock (Paschos & FitzGerald, 2010). Chronic misalignment between internal and environmental rhythms is typically found in night shift workers, who are exposed to increased light at night (LAN), resulting in the disruption of SCN function and increased nighttime BP (Chau et al., 1989; Lo et al., 2008; Yamasaki et al., 1998). Exposure to LAN is globally increasing not only in night shift workers but also in normal-living humans because of the increased use of artificial lighting in
Submitted October 31, 2013, Returned for revision February 24, 2014, Accepted February 28, 2014
Correspondence: Kenji Obayashi, MD, PhD, Department of Community Health and Epidemiology, Nara Medical University School of Medicine, 840 Shijocho, Kashiharashi, Nara 634-8521, Japan. Tel: +81-744-22-3051. Fax: +81-744-25-7657. E-mail: [email protected]
779
780
K. Obayashi et al.
Obayashi et al., 2012). Thus, LAN exposure in home settings may cause circadian misalignment and increased nighttime BP through a mechanism independent of changing in nocturnal total melatonin levels, though it remains unclear whether LAN exposure in home settings is associated with increased nighttime BP. We cross-sectionally examined the association between LAN exposure objectively measured in home settings and nighttime BP in elderly individuals.
Chronobiol Int Downloaded from informahealthcare.com by Michigan University on 04/19/15 For personal use only.
METHODS Participants A total of 537 elderly subjects were voluntarily recruited between September 2010 and April 2012 in a study entitled Housing Environments and Health Investigation among Japanese Older People in Nara, Kansai Region: a prospective community-based cohort (HEIJO-KYO) study. Of these, 528 home-dwelling participants met the inclusion criteria requiring an age 60 years and a record of LAN measurements. All the participants provided written informed consent, and the study protocol was performed in accordance with the ethics committee of Nara Medical University and the ethical standards of the Journal (Portaluppi et al., 2010). Study protocol Our previously reported study included the protocols for measuring LAN (Obayashi et al., 2013). In brief, we visited the participants’ homes, collected overnight fasting venous blood samples and gathered demographic and medical information using a standardized questionnaire. In addition, we simultaneously initiated 48-h measurements of LAN exposure, ambulatory BP (ABP) and actigraphy. We instructed participants to collect their urine the following night and to maintain a standardized sleep diary logging the time they went to bed and the amount of time they spent in bed. Measurement of LAN LAN exposure was measured at 1-min intervals using a portable light meter (LX-28SD; Sato Shouji Inc., Kanagawa, Japan) with a sensor positioned 60 cm above the floor, near the head of the bed and facing the ceiling. The optical sensor has a spectral sensitivity approximating that of the human eye, the illuminance sensitivity of which ranges from 0 to 100 000 lux. Three parameters of LAN exposure were used in the analysis and were defined as follows: (1) The average light intensity during the in-bed period (NLavg). (2) The duration of light intensity 10 lux during the in-bed period (NL 10). (3) The duration of light intensity 100 lux during the in-bed period (NL 100). The participants were divided into the LAN and darker groups on the basis of NLavg cutoff values (3, 5 and 10 lux) predefined by a study conducted in a
controlled setting demonstrating the effects of LAN exposure 3 lux on human physiology (Zeitzer et al., 2000).
ABP monitoring ABP monitoring (ABPM) was performed using a validated ambulatory recorder (TM-2430; A&D Co. Ltd., Tokyo, Japan) and cuff on the non-dominant arm. BP was measured at 30-min intervals for 48 h. Nighttime was defined as the in-bed period based on sleep diaries. Erroneous BP data were excluded as were values with a systolic BP (SBP) 550 or 4250 mmHg and a diastolic BP530 or 4160 mmHg. BP and heart rate (HR) data, which were lost for 450% of the study period by errors and artifacts, were excluded from analyses. Urinary 6-sulfatoxymelatonin excretion The urine collection protocol involved discarding the last void at bedtime and collecting each subsequent void until the first morning void. The samples were stored in a dark bottle at room temperature, the total volume was measured and then stored at 20 C until assay. Urinary 6-sulfatoxymelatonin concentration was measured at a commercial laboratory (SRL, Inc., Tokyo, Japan) using a highly sensitive enzyme-linked immunosorbent assay kit (RE54031; IBL International, Hamburg, Germany). Urinary 6-sulfatoxymelatonin excretion (UME) was calculated as follows: UME (mg) ¼ 6-sulfatoxymelatonin concentration (mg/mL) total overnight urine volume (mL). UME data were considered missing if the urine was not collected according to the protocol. We used UME as an index of melatonin secretion because it correlates closely with the amount of nocturnal melatonin secretion (Baskett et al., 1998). Physical activity and sleep measurements Physical activity and sleep measurements were recorded at 1-min intervals for 48 h using an actigraph (Actiwatch 2; Respironics Inc., Murrysville, PA) that was worn on the non-dominant wrist. Four actigraphic parameters were determined using Actiware version 5.5 (Respironics Inc.), with a default wake threshold value used to identify periods of wake or sleep (Philips Respironics Actiware Tutorials, 2013): (1) daytime physical activity, the average valid physical activity counts per min during the out-of-bed period; (2) sleep efficiency, the total sleep time divided by the duration in bed; (3) total sleep time, the sleep time during the in-bed period; and (4) probable sleep-disordered breathing (SDB), sleep efficiency 570% or total sleep time 55 h (Mehra et al., 2008). Other measurements Body mass index (BMI) was calculated as weight (kg)/ height (m2). Current smoking status, habitual alcohol consumption and drug use were evaluated by a questionnaire. Diabetes mellitus was diagnosed based on medical history or current antidiabetic treatment or if Chronobiology International
Association between LAN and nighttime BP
Chronobiol Int Downloaded from informahealthcare.com by Michigan University on 04/19/15 For personal use only.
fasting plasma glucose was 7.0 mmol/L and HbA1c level was 6.5% of the National Glycohemoglobin Standardization Program value. The estimated glomerular filtration rate (eGFR) was calculated according to the Japanese Society of Nephrology–Chronic Kidney Disease Practice Guide (Irie et al., 2005). Time to bed, duration in bed and nocturia frequency were obtained from the sleep diary. Day length in Nara (latitude: 34 N) from sunrise to sunset on measurement days was extracted from the National Astronomical Observatory of Japan website (2013).
Statistical analyses Variables with a normal distribution were reported as means (SD), whereas variables with asymmetric distribution were reported as medians and interquartile ranges. Mean and median were compared between the LAN and darker groups using the unpaired t-test and Mann–Whitney U test, respectively. The Chi-square test was performed for comparison of categorical data. For LAN, ABPM, actigraphy, sleep diary and day length data, the average of two consecutive days was used for further analyses. UME values were naturally log-transformed for analysis. We evaluated associations between nighttime BP and predictive variables including age, gender, BMI, current smoking status, habitual alcohol consumption, medication use, eGFR, diabetes, duration in bed, time to bed, day length, LAN, daytime physical activity, sleep quality, probable SDB, nocturia and UME using univariate linear regression models. Mean nighttime BP adjusted for all predictive variables, which were marginally to significantly associated with nighttime BP (p50.20) in univariate models, were compared between the LAN and darker groups using analysis of covariance (ANCOVA). Statistical analyses were performed using SPSS version 19.0 for Windows (IBM SPSS Inc., Chicago, IL), and a two-sided p value of 50.05 considered statistically significant. RESULTS Mean participants’ age was 72.8 (6.5) years, and 247 (46.8%) were male. The mean duration in bed was significantly longer, and the mean time to bed was significantly earlier in the LAN group (average: 5 lux) than the darker group (average: 55 lux; Table 1). Dichotomous comparisons of LAN, BP, actigraphic, nocturia and melatonin parameters at three cutoff values of LAN are presented in Table 2. NLavg in the darker group was 51/20, 51/30 and 51/30 of NLavg in the LAN group at cutoff values of 3, 5 and 10 lux, respectively. NL 10 in the darker group was 51/25, 51/25 and 51/19 of NL 10 in the LAN group at cutoff values of 3, 5 and 10 lux, respectively. In the Darker group, 81%, 78% and 73% of the participants at the cutoff values of 3, 5 and 10 lux, respectively, were never exposed to LAN 100 lux. Night-to-night correlation of NLavg between the two nights in the measurement !
Informa Healthcare USA, Inc.
781
TABLE 1. Basic and clinical characteristics stratified by LAN exposure. Characteristics No. of participants Basic parameters Age, mean, years Gender, number, male BMI, mean, kg/m2 Current smoker, number Alcohol consumption (30 g/day), number
LAN 5 (5 lux) 109 72.5 54 23.2 8 14
Darker 5 (55 lux)
p
419 (6.8) (49.5) (2.9) (7.3) (12.8)
72.9 193 22.8 26 52
(6.4) (46.1) (3.1) (6.2) (12.4)
0.58 0.52 0.20 0.12 0.90
Clinical parameters Use of antihypertensive 50 (45.9) 185 (44.2) 0.75 drug, number Evening use of 15 (13.8) 45 (10.7) 0.38 antihypertensive drug, number Sleep medication, number 16 (14.8) 41 (9.8) 0.14 eGFR, mean, mL/min/1.73 m2 71.7 (14.0) 71.9 (15.0) 0.90 Diabetes, number 17 (15.6) 50 (11.9) 0.31 Duration in bed*, mean, min 518.7 (79.0) 491.0 (75.2) 50.01 Time to bed*, mean, 22:16 (1:18) 22:34 (1:04) 0.03 clock time Day length (511 hours)*, 57 (52.3) 200 (47.7) 0.40 number Data are expressed as means (SD) or number (%). LAN, light at night; eGFR, estimated glomerular filtration rate. *Average for two days.
period was moderately high (Spearman’s rank correlation coefficient: 0.64). Compared with the darker group, the LAN group showed significantly higher nighttime SBP and DBP and lower sleep efficiency. In contrast, HR and UME did not significantly differ between the LAN and darker groups. Univariate linear regression analyses using nighttime BP data from 524 participants (four missing) showed significant associations between nighttime SBP and age; gender; diabetes; duration in bed; time to bed; LAN 3, 5 and 10; daytime physical activity; sleep efficiency; and nocturia (Table 3). Antihypertensive drug use (p ¼ 0.09), evening use of antihypertensive drugs (p ¼ 0.07), probable SDB (p ¼ 0.07) and log-transformed UME (p ¼ 0.13) were marginally but insignificantly associated with nighttime SBP. Gender; LAN 3, 5 and 10; daytime physical activity; and frequent nocturia were significantly associated with nighttime DBP. Current smoking status (p ¼ 0.07), habitual alcohol consumption (p ¼ 0.06), time to bed (p ¼ 0.18), duration in bed (p ¼ 0.16) and sleep efficiency (p ¼ 0.16) were marginally but insignificantly associated with nighttime DBP. In multivariate analysis using ANCOVA (Table 4), the LAN group showed significantly higher nighttime SBP (LAN 3 vs. darker 3: adjusted mean nighttime SBP: 119.8 vs. 116.5 mmHg, p ¼ 0.04; LAN 5 vs. darker 5: 120.8 vs. 116.5 mmHg, p ¼ 0.01; LAN 10 vs. darker 10: 121.5 vs. 116.8 mmHg, p ¼ 0.03) and DBP (LAN 3 vs. Darker 3: adjusted mean nighttime DBP: 69.4 vs. 67.1 mmHg,
(9.4) (86.9) (8.5) (76.6) (4.3–10.4)
(7.7) (77.9) (6.9) (72.1) (3.9–9.5)
85.1 435.5 26 276 6.5
(13.7) (7.6) (7.5) (15.8) (8.3) (7.3)
81.8 440.3 12 111 6.8
135.4 79.4 72.6 116.5 67.0 59.9 298.1 (108.0)
(14.2) (7.8) (7.5) (15.8) (8.8) (7.4)
285.9 (97.7)
137.6 80.6 73.1 120.4 69.8 60.8
0.4 (0.04–1.1) 2.0 (0.0–9.0) 0.0 (0.0–2.0)
383
Darker 3 (53 lux)
50.01 0.55 0.54 0.30 0.42
0.24
0.11 0.13 0.47 0.01 50.01 0.21
50.01 50.01 50.01
p
(14.0) (7.9) (7.4) (16.1) (9.0) (7.9)
81.4 449.2 10 89 6.8
(8.3) (78.2) (9.4) (81.7) (4.5–10.4)
285.8 (102.3)
138.4 81.0 72.7 121.8 70.5 60.5
13.3 (7.8–21.1) 62.5 (36.3–111.3) 24.0 (7.0–55.3)
109
LAN 5 (5 lux)
(13.8) (7.6) (7.5) (15.7) (8.3) (7.2)
84.9 433.6 28 298 6.6
(8.2) (80.7) (6.8) (71.1) (3.9–9.6)
297.1 (106.1)
135.4 79.4 72.7 116.4 67.1 60.0
0.4 (0.06–1.5) 2.5 (0.0–13.0) 0.0 (0.0–0.0)
419
Darker 5 (55 lux)
50.01 0.07 0.36 0.03 0.65
0.32
0.045 0.06 0.96 50.01 50.01 0.57
50.01 50.01 50.01
p
(14.0) (7.7) (7.7) (17.3) (9.4) (7.8)
81.0 456.7 7 52 6.2
(9.0) (76.0) (10.8) (76.5) (4.3–9.8)
286.8 (104.8)
138.5 80.9 72.7 121.8 70.2 60.5
20.0 (13.9–28.1) 83.5 (53.6–132.1) 45.0 (23.6–76.8)
68
LAN 10 (10 lux)
(13.8) (7.7) (7.5) (15.6) (8.4) (7.2)
84.7 433.9 31 335 6.6
(8.1) (80.7) (6.9) (72.8) (3.9–9.7)
295.9 (105.5)
135.7 79.6 72.7 116.9 67.4 60.1
0.6 (0.09–2.2) 4.3 (0.0–16.5) 0.0 (0.0–0.5)
460
Darker 10 (510 lux)
50.01 0.03 0.26 0.53 0.88
0.51
0.12 0.20 0.99 0.02 0.01 0.64
50.01 50.01 50.01
p
Data are expressed as means (SD), medians (interquartile range), or numbers (%). LAN, light at night; BP, blood pressure; NLavg average night light exposure during the in-bed period; NL 410, duration of night light exposure410 lux during the in-bed period; and NL4100, duration of night light exposure4100 lux during the in-bed period; SBP, systolic blood pressure; DBP, diastolic blood pressure; HR, heart rate; SDB, sleep-disordered breathing; UME, urinary 6-sulfatoxymelatonin excretion. *Average for two days. ySleep efficiency 570% and/or total sleep time 55 hours.
Actigraphic parameters* Daytime physical activity, mean, count/min Sleep efficiency, mean, % Total sleep time, mean, min Probable SDBy, number Nocturia (1 time/night), number UME, median, mg
Ambulatory BP parameters* Daytime SBP, mmHg, mean Daytime DBP, mmHg, mean Daytime HR, beats per min, mean Nighttime SBP, mmHg, mean Nighttime DBP, mmHg, mean Nighttime HR, beats per min, mean
145
No. of participants LAN parameters*, median NLavg, lux NL 410, min NL 4100, min 8.7 (5.1–18.2) 50.5 (26.5–146.7) 14.5 (0.0–42.3)
LAN 3 (3 lux)
Characteristics
TABLE 2. Comparisons of LAN, BP, actigraphic, nocturia and melatonin parameters between LAN and Darker Groups.
Chronobiol Int Downloaded from informahealthcare.com by Michigan University on 04/19/15 For personal use only.
782 K. Obayashi et al.
Chronobiology International
Association between LAN and nighttime BP
783
TABLE 3. Univariate linear regression analysis for the association between variables and nighttime SBP and DBP. Nighttime SBP Variables
Chronobiol Int Downloaded from informahealthcare.com by Michigan University on 04/19/15 For personal use only.
Demographic parameters Age (per years) Gender (male vs. female) BMI (per kg/m2) Current smoker (yes vs. no) Alcohol consumption (430 vs. 530 g/day) Clinical parameters Use of antihypertensive drug (yes vs. no) Evening use of antihypertensive drug (yes vs. no) Sleep medication (yes vs. no) eGFR (per mL/min/1.73 m2) Diabetes (yes vs. no) Duration in bed* (per min) Time to bed* (per min delay) Day length* (511 vs. 411 hours) LAN parameters* LAN3 (NLavg 43 vs. 53 lux) LAN5 (NLavg 45 vs. 55 lux) LAN10 (NLavg 410 vs. 510 lux) Actigraphic parameters* Daytime physical activity (per count/min) Sleep efficiency (per %) Total sleep time (per min) Probable SDBy (yes vs. no) Nocturia (41 vs. 51 time/night) log-transformed UME (per log mg)
95% CI
Nighttime DBP p
95% CI
p
0.558 5.454 0.190 3.945 2.559
0.351 2.754 0.261 2.588 1.557
0.765 8.154 0.641 10.478 6.674
50.01 50.01 0.41 0.24 0.22
0.017 3.558 0.151 3.238 2.099
0.131 2.121 0.091 0.259 0.104
0.097 4.995 0.393 6.734 4.301
0.77 50.01 0.22 0.07 0.06
2.413 3.967 0.017 0.040 4.437 0.030 0.025 0.958
0.337 0.315 4.444 0.134 0.360 0.013 0.045 1.777
5.164 8.248 4.410 0.053 8.515 0.048 0.005 3.692
0.09 0.07 0.99 0.40 0.03 50.01 0.02 0.49
0.290 0.751 0.448 0.006 0.943 0.007 0.007 0.280
1.189 1.551 2.821 0.056 3.137 0.003 0.018 1.747
1.769 3.053 1.925 0.044 1.252 0.016 0.003 1.187
0.70 0.64 0.71 0.82 0.40 0.16 0.18 0.71
3.922 5.395 4.935
0.870 2.034 0.835
6.973 8.755 9.035
0.01 50.01 0.02
2.773 3.472 2.825
1.145 1.678 0.629
4.402 5.267 5.022
50.01 50.01 0.01
0.027 0.202 0.008 4.871 6.318 1.545
0.040 0.368 0.009 0.474 3.725 3.545
0.014 0.035 0.025 10.217 9.361 0.454
50.01 0.02 0.38 0.07 50.01 0.13
0.009 0.064 0.0003 1.355 2.320 0.493
0.016 0.152 0.009 1.472 0.675 0.574
0.003 0.024 0.009 4.183 3.965 1.560
50.01 0.16 0.94 0.35 50.01 0.37
SBP, systolic blood pressure; DBP, diastolic blood pressure; CI, confidence interval; BMI, body mass index; eGFR, estimated glomerular filtration rate; NLavg, average intensity of night light; SDB, sleep-disordered breathing; UME, urinary 6-sulfatoxymelatonin excretion. *Average for two days. ySleep efficiency 570% and/or total sleep time 55 hours. TABLE 4. Comparisons of adjusted mean nighttime BP between LAN and Darker groups using ANCOVA. BP parameters mean (95% CI), mmHg
LAN 3 (n ¼ 145)
Nighttime SBPx Nighttime DBPô
119.8 (117.1–122.4) 69.4 (68.0–70.8) LAN 5 (n ¼ 109)
Nighttime SBPx Nighttime DBPô
120.8 (117.8–123.9) 70.1 (68.5–71.7) LAN 10 (n ¼ 68)
Nighttime SBPx Nighttime DBPô
121.5 (117.7–125.4) 70.0 (67.9–72.1)
Darker 3 (n ¼ 383) 116.5 (114.9–118.1) 67.1 (66.2–67.9) Darker 5 (n ¼ 419) 116.5 (115.0–118.0) 67.1 (66.3–67.9) Darker 10 (n ¼ 460) 116.8 (115.4–118.2) 67.4 (66.6–68.1)
Adjusted difference (LAN3-Darker3, 95% CI) 3.3 (0.2–6.4) 2.3 (0.7–4.0)
p 0.04 50.01
Adjusted difference (LAN5-Darker5, 95% CI) 4.3 (0.9–7.8) 2.9 (1.1–4.7)
0.01 50.01
Adjusted difference (LAN10-Darker10, 95% CI) 4.7 (0.6–8.9) 2.6 (0.4–4.8)
0.03 0.02
BP, blood pressure; LAN, light at night; ANCOVA, analysis of covariance; CI, confidence interval; SBP, systolic blood pressure; DBP, diastolic blood pressure. xData adjusted for age, gender, use of antihypertensive drug, evening use of antihypertensive drug, diabetes, duration in bed, time to bed, daytime physical activity, sleep efficiency, probable sleep-disordered breathing, nocturia, and log-transformed urinary 6-sulfatoxymelatonin excretion. ôData adjusted for gender, current smoking status, alcohol consumption, duration in bed, time to bed, daytime physical activity, sleep efficiency, and nocturia.
p50.01; LAN 5 vs. Darker 5: 70.1 vs. 67.1 mmHg, p50.01; LAN 10 vs. Darker 10: 70.0 vs. 67.4 mmHg, p ¼ 0.02) than the Darker group consistently in comparisons using three different cutoff values of LAN 3, 5 and 10 lux. These associations were independent of potential confounding factors such as age, gender, !
Informa Healthcare USA, Inc.
antihypertensive drug use, diabetes, time to bed, duration in bed, daytime physical activity, sleep efficiency, probable SDB, nocturia and log-transformed UME in the nighttime SBP model and were independent of gender, current smoking status, alcohol consumption, time to bed, duration in bed, daytime physical activity,
784
K. Obayashi et al.
Chronobiol Int Downloaded from informahealthcare.com by Michigan University on 04/19/15 For personal use only.
sleep efficiency and nocturia in the nighttime DBP model. Furthermore, we have conducted additional analyses with regard to the LAN-BP association in the actual sleep period defined by actigraphy. After adjustment for age and gender, all LAN groups (i.e. LAN3, LAN5 and LAN10) consistently showed higher SBP and DBP than the Darker groups (LAN 3 vs. Darker 3: adjusted mean nighttime SBP: 120.6 vs. 115.5 mmHg, p50.01, DBP: 69.5 vs. 66.6 mmHg, p50.01; LAN 5 vs. Darker 5: SBP: 119.9 vs. 115.8 mmHg, p ¼ 0.049, DBP: 69.1 vs. 66.7 mmHg, p ¼ 0.03; LAN 10 vs. Darker 10: SBP: 122.0 vs. 115.9 mmHg, p ¼ 0.02 and DBP: 69.6 vs. 66.8 mmHg, p ¼ 0.047).
DISCUSSION Our findings that LAN exposure in home settings is significantly associated with increased nighttime BP independent of UME are, to the best of our knowledge, the first report in humans and consistent with those of previous studies demonstrating an association between night-shift work and increased nighttime BP. In a previous study using ABPM, evening-shift/night-shift workers were shown to have 6.0 mmHg higher nighttime SBP and 2.8 mmHg higher nighttime DBP than day-shift workers (Yamasaki et al., 1998). Similarly, we demonstrated that the LAN group exhibited 3.3–4.7 mmHg higher nighttime SBP and 2.3–2.9 mmHg higher nighttime DBP than the Darker group. Night-shift workers are exposed to higher-intensity LAN than the LAN group in this study (Grundy et al., 2009); thus, the results of this study indicate that even dimmer LAN (average 8.7– 20.0 lux) than that experienced by night-shift workers can significantly affect nighttime BP in the general elderly population. Although the mechanisms by which LAN exposure may increase nighttime BP remain unclear, previous epidemiological and experimental studies support a negative effect of LAN exposure on nighttime BP by changing in endogenous melatonin levels, sleep quality and/or patterns of sympathetic nerve activity. Decreased endogenous melatonin levels and impaired sleep quality are observed in night-shift workers (Drake et al., 2004; Grundy et al., 2011), and night-shift workers have higher nighttime BP (Chau et al., 1989; Lo et al., 2008; Yamasaki et al., 1998). Several experimental studies have shown that melatonin administration reduces nighttime BP (Arangino et al., 1999; Lusardi et al., 1997; Scheer et al., 2004). Circadian misalignment between sleep/wake cycles is associated with increased nighttime BP and increased endogenous catecholamine levels as well as impaired sleep quality (Scheer et al., 2009). In the present study, LAN exposure was found to be associated with lower actigraphic sleep efficiency and increased nighttime SBP; furthermore, we demonstrated by multivariate analysis that LAN exposure is significantly associated with increased nighttime BP
independently of actigraphic sleep efficiency. In contrast, UME was not significantly associated with LAN exposure. Although it is well established that LAN exposure suppresses melatonin secretion in controlled setting (Brainard et al., 2008), epidemiological studies have reported that LAN exposure in home settings is not significantly associated with nocturnal total melatonin levels (Davis et al., 2001; Levallois et al., 2001; Obayashi et al., 2012). In the present study, the final multivariate model showed that LAN exposure is significantly associated with increased nighttime BP independently of UME. Next, night-shift work diminishes a normal decrease in urinary norepinephrine and epinephrine levels during the non-work period, causing higher urinary catecholamine levels during the non-work period in night-shift workers than in day-shift workers (Yamasaki et al., 1998). Moreover, night-shift work is associated with increased low-frequency power and low–high-frequency power ratio in HR variability, indicating changes in sympathovagal cardiac modulation (Chung et al., 2009). Among normal-living young humans, it was also demonstrated that LAN exposure increases the nighttime HR in controlled laboratory settings (Scheer et al., 1999). However, in the present study, there were no significant associations between LAN exposure and HR in our elderly participants. Similar differences in response to environmental factors between BP and HR were reported to be influenced by age (Itoh et al., 2013). The clinical implications of increased nighttime SBP observed in the present study for cardiovascular events and total mortality could be interpreted by metaanalysis of population-based prospective studies. A 3.3–4.7 mmHg increase in nighttime SBP is predicted to increase cardiovascular events by 4.5%–6.4% and total mortality by 4.7%–6.7% (Boggia et al., 2007). LAN is a common exposure, to which 145 (27.5%) of 528 elderly individuals have been exposed to LAN 3 lux in our study. Approximately, 10 000 annual excess deaths could be estimated from additional mortality, exposed population for dim LAN and the Japanese national data of annual deaths for individuals aged 60-years-old (The Statistics and Information Department, Minister’s secretariat, Ministry of Health, Labour and Welfare of Japan, 2010). Although some behavior in bed before/after sleep may be associated with both LAN exposure and nighttime BP, the association between LAN exposure and nighttime BP was independent of light exposure in bed before sleep-onset and after sleep-offset. In our elderly population, we observed three phenotypes of LAN exposure patterns during the in-bed period (the firstsided, constant and the last-sided). The first-sided pattern of LAN exposure is more likely to be exposed to light in the first hour of the in-bed period and may be associated with early bedtime and behavior in bed before sleep such as reading and watching TV. The lastsided pattern of LAN exposure is more likely to be Chronobiology International
Chronobiol Int Downloaded from informahealthcare.com by Michigan University on 04/19/15 For personal use only.
Association between LAN and nighttime BP exposed to light in the last hour of the in-bed period and may be associated with sunlight through the window due to late wake time. However, in the present study, the association between LAN exposure and nighttime BP was independent of bedtime and duration in bed and was consistent with those in the actual sleep period defined by actigraphy. In the present study, BMI was not significantly associated with nighttime BP, whereas, we previously reported that LAN exposure 3 lux is associated with obesity (Obayashi et al., 2013). In previous epidemiological studies in elderly individuals, the associations of BMI with cardiovascular and all-cause mortality were not linear but U-shaped (Corrada et al., 2006; RomeroCorral et al., 2006). In addition, the prevalence of obese elderly (BMI 30 kg/m2) and underweight elderly (BMI518.5 kg/m2) were not high (1.3% and 7.4%, respectively) in our study. Considering together, it is possible that BMI was not significantly associated with nighttime BP in the present elderly population. However, LAN-associated obesity may partially explain the association between LAN exposure and nighttime BP. Further epidemiological research with a longitudinal design is required to better understand the associations among LAN exposure, obesity and nighttime BP. The present study has several limitations. First, the measurement of LAN exposure was performed on only two consecutive nights; however, we showed the correlation between LAN exposure on different nights to be moderately high. Thus, the average values may be accurate measure of the central tendency. In addition, ABP devices may differentially disturb sleep quality between the first and second nights; however, consistent associations between LAN exposure and nighttime BP were observed both on the first and second night (data were not shown). Second, the photometers used in this study were not ambulatory devices, and LAN exposure may be underestimated because it did not record light exposure in rooms other than the bedroom, e.g. during nocturia. In addition, LAN exposure in this study included light intensity from a variety of lighting sources, e.g. bedroom light, light from the other room, TV screen and street light; therefore, horizontal measurement of LAN was not perfect to measure actual exposure of LAN. Further research using ambulatory photometers at cornea level is required to better assess the association between LAN exposure and nighttime BP. Furthermore, human circadian physiology is more closely correlated to shorter wave length rather than intensity (Brainard et al., 2008); therefore, ambulatory devices which can measure a power of the short wave length are also needed. Third, we evaluated sleep quality by actigraphy and may ignore the residual confounding effect of obstructive sleep apnea (OSA), an important condition that could increase nighttime BP (Becker et al., 2003). In the present study, probable SDB defined by actigraphy (sleep efficiency 570% or total sleep time 55 h), a predictor of SDB including OSA (Mehra et al., !
Informa Healthcare USA, Inc.
785
2008), did not differ significantly between the LAN and Darker groups. Finally, we selected this aging group with most retired to minimize the effect of current night-shift work on the association between LAN exposure and BP; however, we did not include any information about prior history of night-shift work in the analysis. In conclusion, LAN exposure in home settings is significantly associated with increased nighttime BP in elderly individuals independently of UME. To the best of our knowledge, this is the first possible report on LAN exposure as a novel and common risk factor for increased nighttime BP in elderly individuals.
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.
DECLARATION OF INTEREST All authors report no conflicts of interest. 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.
REFERENCES Arangino S, Cagnacci A, Angiolucci M, et al. (1999). Effects of melatonin on vascular reactivity, catecholamine levels, and blood pressure in healthy men. Am J Cardiol. 83:1417–19. Baskett JJ, Cockrem JF, Antunovich TA. (1998). Sulphatoxymelatonin excretion in older people: Relationship to plasma melatonin and renal function. J Pineal Res. 24:58–61. Becker HF, Jerrentrup A, Ploch T, et al. (2003). Effect of nasal continuous positive airway pressure treatment on blood pressure in patients with obstructive sleep apnea. Circulation. 107: 68–73. Berson DM, Dunn FA, Takao M. (2002). Phototransduction by retinal ganglion cells that set the circadian clock. Science. 295: 1070–3. Boggia J, Li Y, Thijs L, et al. (2007). Prognostic accuracy of day versus night ambulatory blood pressure: A cohort study. Lancet. 370:1219–29. Brainard GC, Sliney D, Hanifin JP, et al. (2008). Sensitivity of the human circadian system to short-wavelength (420-nm) light. J Biol Rhythms. 23:379–86. Brzezinski A. (1997). Melatonin in humans. N Engl J Med. 336: 186–95. Chau NP, Mallion JM, de Gaudemaris R, et al. (1989). Twentyfour-hour ambulatory blood pressure in shift workers. Circulation. 80:341–7. Chung MH, Kuo TB, Hsu N, et al. (2009). Sleep and autonomic nervous system changes – Enhanced cardiac sympathetic
Chronobiol Int Downloaded from informahealthcare.com by Michigan University on 04/19/15 For personal use only.
786
K. Obayashi et al.
modulations during sleep in permanent night shift nurses. Scand J Work Environ Health. 35:180–7. Corrada MM, Kawas CH, Mozaffar F, Paganini-Hill A. (2006). Association of body mass index and weight change with all-cause mortality in the elderly. Am J Epidemiol. 163:938–49. Davis S, Kaune WT, Mirick DK, et al. (2001). Residential magnetic fields, light-at-night, and nocturnal urinary 6-sulfatoxymelatonin concentration in women. Am J Epidemiol. 154:591–600. Drake CL, Roehrs T, Richardson G, et al. (2004). Shift work sleep disorder: Prevalence and consequences beyond that of symptomatic day workers. Sleep. 27:1453–62. Fagard RH, Celis H, Thijs L, et al. (2008). Daytime and nighttime blood pressure as predictors of death and cause-specific cardiovascular events in hypertension. Hypertension. 51:55–61. Grundy A, Sanchez M, Richardson H, et al. (2009). Light intensity exposure, sleep duration, physical activity, and biomarkers of melatonin among rotating shift nurses. Chronobiol Int. 6: 1443–61. Grundy A, Tranmer J, Richardson H, et al. (2011). The influence of light at night exposure on melatonin levels among Canadian rotating shift nurses. Cancer Epidemiol Biomarkers Prev. 20: 2404–12. Irie F, Iso H, Sairenchi T, et al. (2005). The relationships of proteinuria, serum creatinine, glomerular filtration rate with cardiovascular disease mortality in Japanese general population. Kidney Int. 69:1264–71. Itoh H, Ajisaka R, Koike A, et al. (2013). Heart rate and blood pressure response to ramp exercise and exercise capacity in relation to age, gender, and mode of exercise in a healthy population. J Cardiol. 61:71–8. Levallois P, Dumont M, Touitou Y, et al. (2001). Effects of electric and magnetic fields from high-power lines on female urinary excretion of 6-sulfatoxymelatonin. Am J Epidemiol. 154:601–9. Lo SH, Liau CS, Hwang JS, Wang JD. (2008). Dynamic blood pressure changes and recovery under different work shifts in young women. Am J Hypertens. 21:759–64. Lusardi P, Preti P, Savino S, et al. (1997). Effect of bedtime melatonin ingestion on blood pressure of normotensive subjects. Blood Press Monit. 2:99–103. Mehra R, Stone KL, Ancoli-Israel S, et al. (2008). Interpreting wrist actigraphic indices of sleep in epidemiologic studies of the elderly: The Study of Osteoporotic Fractures. Sleep. 31:1569–76. National Astronomical Observatory of Japan. (2013). Available at: http://eco.mtk.nao.ac.jp/koyomi/index.html.en. Accessed on 30 October 2013. Navara KJ, Nelson RJ. (2007). The dark side of light at night: Physiological, epidemiological, and ecological consequences. J Pineal Res. 43:215–24.
Obayashi K, Saeki K, Iwamoto J, et al. (2012). Positive effect of daylight exposure on nocturnal urinary melatonin excretion in the elderly: A cross-sectional analysis of the HEIJO-KYO study. J Clin Endocrinol Metab. 97:4166–73. Obayashi K, Saeki K, Iwamoto J, et al. (2013). Exposure to light at night, nocturnal urinary melatonin excretion, and obesity/ dyslipidemia in the elderly: A cross-sectional analysis of the HEIJO-KYO study. J Clin Endocrinol Metab. 98:337–44. Paschos GK, FitzGerald GA. (2010). Circadian clocks and vascular function. Circ Res. 106:8337–41. Philips Respironics Actiware Tutorials. (2013). Available at: http:// learnactiware.com/tutorials/. Accessed on 30 October 2013. Portaluppi F, Smolensky MH, Touitou Y. (2010). Ethics and methods for biological rhythm research on animals and human beings. Chronobiol Int. 27:1911–29. Provencio I, Jiang G, De Grip WJ, et al. (1998). Melanopsin: An opsin in melanophores, brain, and eye. Proc Natl Acad Sci USA. 95:340–5. Romero-Corral A, Montori VM, Somers VK, et al. (2006). Association of bodyweight with total mortality and with cardiovascular events in coronary artery disease: A systematic review of cohort studies. Lancet. 368:666–78. Scheer FA, van Doornen LJ, Buijs RM. (1999). Light and diurnal cycle affect human heart rate: Possible role for the circadian pacemaker. J Biol Rhythms. 14:202–12. Scheer FA, Van Montfrans GA, van Someren EJ, et al. (2004). Daily nighttime melatonin reduces blood pressure in male patients with essential hypertension. Hypertension. 3: 192–7. Scheer FA, Hilton MF, Mantzoros CS, Shea SA. (2009). Adverse metabolic and cardiovascular consequences of circadian misalignment. Proc Natl Acad Sci USA. 106:4453–8. Sega R, Facchetti R, Bombelli M, et al. (2005). Prognostic value of ambulatory and home blood pressures compared with office blood pressure in the general population: Follow-up results from the Pressioni Arteriose Monitorate e Loro Associazioni (PAMELA) study. Circulation. 111:1777–83. The Statistics and Information Department, Minister’s secretariat, Ministry of Health, Labour and Welfare of Japan. (2010). Vital Statistics of Japan 2010. 3:122–3. Wyse CA, Selman C, Page MM, et al. (2011). Circadian desynchrony and metabolic dysfunction; did light pollution make us fat? Med Hypotheses. 77:1139–44. Yamasaki F, Schwartz JE, Gerber LM, et al. (1998). Impact of shift work and race/ethnicity on the diurnal rhythm of blood pressure and catecholamines. Hypertension. 32:417–23. Zeitzer JM, Dijk D, Kronauer RE, et al. (2000). Sensitivity of the human circadian pacemaker to nocturnal light: Melatonin phase resetting and suppression. J Physiol. 526:695–702.
Chronobiology International
