A case-referent study: light at night and breast cancer risk in Georgia

International Journal of Health Geographics

John E Vena¹  Rana Bayakly²  Jim Burch³  Sara E Wagner¹  Sarah E Bauer¹ 

[1] Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, GA, Georgia;Georgia Department of Public Health, Georgia Comprehensive Cancer Registry, Atlanta, GA, Georgia;Department of Epidemiology and Biostatistics, Cancer Prevention and Control Program, University of South Carolina, Columbia, SC, USA

关键词: Circadian disruption;    Breast cancer;    Artificial LAN;    Light at night (LAN);   

Others  :  810164
DOI  :  10.1186/1476-072X-12-23

 received in 2013-02-11, accepted in 2013-04-10,  发布年份 2013

【 摘 要 】

Background

Literature has identified detrimental health effects from the indiscriminate use of artificial nighttime light. We examined the co-distribution of light at night (LAN) and breast cancer (BC) incidence in Georgia, with the goal to contribute to the accumulating evidence that exposure to LAN increases risk of BC.

Methods

Using Georgia Comprehensive Cancer Registry data (2000–2007), we conducted a case-referent study among 34,053 BC cases and 14,458 lung cancer referents. Individuals with lung cancer were used as referents to control for other cancer risk factors that may be associated with elevated LAN, such as air pollution, and since this cancer type was not previously associated with LAN or circadian rhythm disruption. DMSP-OLS Nighttime Light Time Series satellite images (1992–2007) were used to estimate LAN levels; low (0–20 watts per sterradian cm²), medium (21–41 watts per sterradian cm²), high (>41 watts per sterradian cm²). LAN levels were extracted for each year of exposure prior to case/referent diagnosis in ArcGIS.

Results

Odds ratios (OR) and 95% confidence intervals (CI) were estimated using logistic regression models controlling for individual-level year of diagnosis, race, age at diagnosis, tumor grade, stage; and population-level determinants including metropolitan statistical area (MSA) status, births per 1,000 women aged 15–50, percentage of female smokers, MSA population mobility, and percentage of population over 16 in the labor force. We found that overall BC incidence was associated with high LAN exposure (OR = 1.12, 95% CI [1.04, 1.20]). When stratified by race, LAN exposure was associated with increased BC risk among whites (OR = 1.13, 95% CI [1.05, 1.22]), but not among blacks (OR = 1.02, 95% CI [0.82, 1.28]).

Conclusions

Our results suggest positive associations between LAN and BC incidence, especially among whites. The consistency of our findings with previous studies suggests that there could be fundamental biological links between exposure to artificial LAN and increased BC incidence, although additional research using exposure metrics at the individual level is required to confirm or refute these findings.

【 授权许可】

   
2013 Bauer et al.; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

Figure 2.

【 参考文献 】

• [1]Stevens R: Light-at-night, circadian disruption and breast cancer: Assessment of existing evidence. Int J Epidemiol 2009, 38(4):963-970.
• [2]Falchi F, Cinzano P, Elvidge CD, Keith DM, Haim A: Limiting the impact of light pollution on human health, environment and stellar visibility. J Environ Manage 2011, 92(10):2714-2722.
• [3]Cinzano P, Falchi F, Elvidge CD: The first world atlas of the artificial night sky brightness. Mon Not R Astron Soc 2001, 328(3):689-707.
• [4]Parkin D, Bray F, Devesa S: Cancer burden in the year 2000; the global picture. Eur J Canc 2001, 37(supplement):4-66.
• [5]Stevens R: Electric-power use and breast cancer-a hypothesis. Am J Epidemiol 1987, 125(4):556-561.
• [6]Burch JB, Hrushesky W: The protective role of melatonin in breast cancer vol. 20. 2009.
• [7]Glickman G, Levin R, Brainard GC: Ocular input for human melatonin regulation: Relevance to breast cancer. Neuroendocrinol Lett 2002, 23:17-22.
• [8]Haim A, Yukler A, Harel O, Schwimmer H, Fares F: Effects of chronobiology on prostate cancer cells growth in vivo. Sleep Sci J 2010, 3(1):25-32.
• [9]Kloog I, Haim A, Stevens RG, Portnov BA: Global co-distribution of light at night (LAN) and cancers of prostate, colon, and lung in men. Chronobiol Int 2009, 26(1):108-125.
• [10]Kloog I, Haim A, Portnov BA: Investigating the link between nighttime light pollution and breast cancer: A geographic information system (gis)-assisted analysis. Chronobiol Int 2005, 22(6):1240.
• [11]Kloog I, Haim A, Portnov BA: Using kernel density function as an urban analysis tool: Investigating the association between nightlight exposure and the incidence of breast cancer in haifa, israel. Comput Environ Urban Syst 2009, 33(1):55-63.
• [12]Kloog I, Haim A, Stevens RG, Barchana M, Portnov BA: Light at night co-distributes with incident breast but not lung cancer in the female population of Israel. Chronobiol Int 2008, 25(1):65-81.
• [13]Kloog I, Portnov BA, Rennert HS, Haim A: Does the modern urbanized sleeping habitat pose a breast cancer risk? Chronobiol Int 2011, 28(1):76-80.
• [14]Kloog I, Stevens R, Haim A, Portnov B: Nighttime light level co-distributes with breast cancer incidence worldwide. Canc Causes Contr 2010, 21(12):2059-2068.
• [15]Stevens RG, Blask DE, Brainard GC, Hansen J, Lockley SW, Provencio I, Rea MS, Reinlib L: Meeting report: The role of environmental lighting and circadian disruption in cancer and other diseases. Environ Health Perspect 2007, 115(9):1357-1362.
• [16]Bullough JD, Rea MS, Figueiro MG: Of mice and women: Light as a circadian stimulus in breast cancer research. Canc Causes Contr 2006, 17(4):375-383.
• [17]IARC: Painting, firefighting, and shiftwork. IARC Monographs on the Evaluation of Carcinogenic Risks to Humans. Volume 98 2010, 1-818.
• [18]Smith MR, Burgess H, Fogg L, Eastman C: Racial differences in the human endogenous circadian period. PLoS One 2009, 4(6):e6014.
• [19]Johnson K: Demographic trends in rural america. In Reports on Rural America. Durham, New Hampshire: Carsey Institute; 2006.
• [20]Blask D, Sauer L, Dauchy R: Melatonin as a chronobiotic/anticancer agent: Cellular, biochemical, and molecular mechanisms of action and their implications for circadian-based cancer therapy. Curr Top Med Chem 2002, 2:113-132.
• [21]Vijayalaxmi , Reiter R, Leal B, Meltz M: Effect of melatonin on mitotic and proliferation indices, and sister chromatid exchange in human blood lymphocytes. Mutat Res Fundam Mol Mech Mutag 1996, 351:187-191.
• [22]Hanahan D, Weinberg R: The hallmarks of cancer. Cell 2000, 100:57-70.
• [23]Stevens R: Circadian disruption and breast cancer from melatonin to clock genes. Epidemiology 2005, 16(2):254-258.
• [24]Stevens RG, Rea MS: Light in the built environment: Potential role of circadian disruption in endocrine disruption and breast cancer. Canc Causes Contr 2001, 12(3):279-287.
• [25]Fu L, Lee CC: The circadian clock: Pacemaker and tumor suppressor. Nat Rev Canc 2003, 3:350-361.
• [26]Girschik J, Heyworth J, Fritschi L: Re: “Night-shift work and breast cancer risk in a cohort of chinese women” [letter]. Am J Epidemiol 2010, 172(7):865-866.
• [27]Higuchi S, Motohashi Y, Ishibashi K, Maeda T: Influence of eye colors of caucasians and asians on suppression of melatonin secretion by light. Am J Physiol Regul Integr Comp Physiol 2007, 292:R2352-R2356.
• [28]Sturm R, Frudakis T: Eye colour: Portals into pigmentation genes and ancestry. Trends Genet 2004, 20(8):327-332.
• [29]CDC: Population distribution and change 2000 to 2010. 2010 Census Briefs 2011, 1-12.
• [30]Butt MJ: Estimation of light pollution using satellite remote sensing and geographic information system techniques. GISci Rem Sens 2012, 49(4):609-621.
• [31]Imhoff ML, Lawrence WT, Stutzer DC, Elvidge CD: A technique for using composite dmsp/ols ''city lights'' satellite data to map urban area. Remote Sens Environ 1997, 61(3):361-370.
• [32]Berman SM, Clear RD: Past vision studies can support a novel human photoreceptor. Light Eng 2008, 16(2):88-94.
• [33]Brainard GC, Hanifin JP, Greeson JM, Byrne B, Glickman G, Gerner E, Rollag MD: Action spectrum for melatonin regulation in humans: Evidence for a novel circadian photoreceptor. J Neurosci 2001, 21(16):6405-6412.
• [34]Hankins MW, Lucas RJ: The primary visual pathway in humans is regulated accordina to long-term light exposure through the action of a nonclassical photopigment. Curr Biol 2002, 12(3):191-198.
• [35]He SG, Dong W, Deng QD, Weng SJ, Sun WZ: Seeing more clearly: Recent advances in understanding retinal circuitry. Science 2003, 302(5644):408-411.
• [36]Kayumov L, Casper RF, Hawa RJ, Perelman B, Chung SA, Sokalsky S, Shapiro CM: Blocking low-wavelength light prevents nocturnal melatonin suppression with no adverse effect on performance during simulated shift work. J Clin Endocrinol Metab 2005, 90(5):2755-2761.
• [37]Thapan K, Arendt J, Skene DJ: An action spectrum for melatonin suppression: Evidence for a novel non-rod, non-cone photoreceptor system in humans. J Physiol 2001, 535(Pt 1):261-267.
• [38]Cajochen C, Munch M, Kobialka S, Krauchi K, Steiner R, Oelhafen P, Orgul S, Wirz-Justice A: High sensitivity of human melatonin, alertness, thermoregulation, and heart rate to short wavelength light. J Clin Endocrinol Metab 2005, 90(3):1311-1316.
• [39]Brainard GC, Sliney D, Hanifin JP, Glickman G, Byrne B, Greeson JM, Jasser S, Gerner E, Rollag MD: Sensitivity of the human circadian system to short-wavelength (420-nm) light. J Biol Rhythms 2008, 23(5):379-386.
• [40]Bierman A, Klein TRea M: The daysimeter: A device for measuring optical radiation as a stimulus for the human circadian system. Meas Sci Technol 2005, 16:2292-2299.
• [41]Rea MS, Brons JA, Figueiro MG: Measurements of light at night (lan) for a sample of female school teachers. Chronobiol Int 2011, 28(8):673-680.
• [42]Gregorio DI, Cromley E, Mrozinski R, Walsh SJ: Subject loss in spatial analysis of breast cancer. Health Place 1999, 5:173-177.
• [43]Cayo MR, Talbot TO: Positional error in automated geocoding of residential addresses. Int J Health Geogr 2003, 2:10. BioMed Central Full Text
• [44]Oliver MN, Matthews KA, Siadaty M, Hauck FR, Pickle LW: Geographic bias related to geocoding in epidemiologic studies. Int J Health Geogr 2005, 4:29. BioMed Central Full Text
• [45]Ward MH, Nuckols JR, Giglierano J, Bonner MR, Wolter C, Airola M, Mix W, Colt JS, Hartge P: Postional accuracy of two methods of geocoding. Epidemiology 2005, 16(4):542-547.
• [46]Zimmerman D: Estimating spatial intensity and variation in risk from locations coarsened by incomplete geocoding. Biometrics 2008, 64(1):262-270.
• [47]Hay G, Kypri K, Whigham P, Langley J: Potential biases due to geocoding error in spatial analyses of official data. Health Place 2009, 15(2):562-567.
• [48]Parent ME, El-Zein M, Rousseau MC, Pintos J, Siemiatycki J: Night work and the risk of cancer among men. Am J Epidemiol 2012, 176(9):751-759.
• [49]Copeland G, Lake A, Firth R: Cancer in North America: 2003–2007. In Registry-specific Cancer Incidence in the United States and Canada. Volume 2. Illinois: North American Association of Central Cancer Registries, Inc; 2011:1-10.
• [50]Days of sunshine per year in Georgia. http://www.currentresults.com/Weather/Georgia/annual-days-of-sunshine.php webcite
• [51]Georgia Climate. http://www.georgia.org/COMPETITIVE-ADVANTAGES/LIFESTYLE/Pages/climate.aspx webcite
• [52]Operational linescan system. http://www.ngdc.noaa.gov/dmsp/sensors/ols.html webcite
• [53]Jenks GF: The data model concept in statistical mapping. Int Yearbook Cartography 1967, 7:186-190.
• [54]Mcmaster R: In memoriam: George F. Jenks (1916–1996). Cartogr Geogr Inf Sci 1997, 24(1):56-59.
• [55]United States Census Bureau: American FactFinder. http://factfinder2.census.gov/faces/nav/jsf/pages/searchresults.xhtml?refresh=t webcite
• [56]Bryan L, Thompson S, Patel M, Kanny D: 2004 georgia behavioral risk factor surveillance system report. Georgia Department of Human Resources, Division of Public Health, Chronic Disease, Injury, and Environmental Epidemiology Section 2006. Publication number DPH06/008HW