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Correlation of a 140-year global time signature in cancer mortality birth cohorts with galactic cosmic ray variation

Published online by Cambridge University Press:  29 October 2007

David A. Juckett
David A. Juckett
Affiliation:
Barros Research Institute, 2430 College Road, Holt, MI 48842, USA and Department of Chemistry, Michigan State University, East Lansing, MI 48824, USA e-mail: juckett@msu.edu
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Abstract

An understanding of the cosmic ray modulation of life processes is critical to space exploration, evolution and current medical science. Previous evidence has implicated a role for cosmic rays in US female cancer, involving a possible cross-generational foetal effect. This study explores the global nature of that effect by examining cancer time variations for population cohorts in five countries on three continents. Age–period–cohort analysis was used to separate cohort-related effects from period-related effects, generating time signatures for comparisons among both male and female populations in the United States (US), United Kingdom (UK), Australia (AU), Canada (CA) and New Zealand (NZ). The available cancer mortality data spanned most of the 20th century for US, UK and AU, with shorter periods for CA and NZ. The longest cohort series spanned 1825 to 1965 and exhibited two peaks of higher mortality likelihood approximately 75 years apart in all countries and in both sexes. The constancy of this oscillation on three continents and both hemispheres suggests the presence of a global environmental effect. To explore a possible source for this effect, the birth cohort oscillation is shown to correlate with the variations in background cosmic radiation one generation prior to the birth cohorts. This confirms an earlier study correlating human breast cancer mortality and galactic cosmic rays. A corroborating correlation is also noted between the latitude dependences of cancer incidence in 42 countries and the intensity of background cosmic rays. The role of germ cells as a possible target of this radiation is discussed, emphasizing the amplification that must occur to make this weak radiation relevant to human health. Germ cell timing for this effect has profound implications for evolution, long-distance space travel and the colonization of planets with high background radiation.

Keywords

cancercohort effectcosmic radiationevolutionincidencemortalityspace travel
Type
Research Article
Information
International Journal of Astrobiology , Volume 6 , Issue 4 , October 2007 , pp. 307 - 319
Copyright
Copyright © Cambridge University Press 2007

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References

Archer, V.E. (1979). Am. J. Epidemiol. 109, 88–99.CrossRefGoogle Scholar
Bard, E., Raisbeck, G.M. & Yiou, F. (1997). Earth Planet. Sci. Lett. 150, 453–462.CrossRefGoogle Scholar
Bard, E., Raisbeck, G., Yiou, F. & Jouzel, J. (2000). Tellus B – Chem. Phys. Meteor. 52, 985–992.CrossRefGoogle Scholar
Barendregt, J.J., Looman, C.W.N. & Bronnum-Hansen, H. (2002). Bull. World Health Org. 80, 26–32.Google Scholar
Barlow, J.S. (1962). Response of the Nervous System to Ionizing Radiation, ed. Haley, T.J. & Snider, R.S., pp. 123–162. Academic Press, New York.Google Scholar
Beer, J., Baumgartner, S.T., Dittrich-Hannen, B., Hauenstein, J., Kubik, P., Lukasczyk, C.H., Mende, W., Stellmacher, R. & Suter, M. (1994). The Sun As a Variable Star: Solar and Stellar Irradiance Variations, ed. Pap, J.M., Frohlich, C., Hudson, H.S. & Solanki, S.K., pp. 291–300. Cambridge University Press, Cambridge.Google Scholar
Beer, J. et al. (1990). Nature 347, 164–166.CrossRefGoogle Scholar
Board on Radiation Effects Research (BRER) (2006). Health Risks from Exposure to Low Levels of Ionizing Radiation: BEIR VII Phase 2. The National Academies Press, Washington, DC.Google Scholar
Bergstrom, R., Adami, H.-O., Mohner, M., Zatonski, W., Storm, H., Ekbom, A., Tretli, S., Teppo, L., Akre, O. & Hakulinen, T. (1996). J. Natl. Cancer Inst. 88, 727–733.CrossRefGoogle Scholar
Chie, W.C., Chen, C.F., Lee, W.C., Chen, C.J. & Lin, R.S. (1995). Anticancer Res. 15, 511–515.Google Scholar
Chirpaz, E., Colonna, M., Menegoz, F., Grosclaude, P., Schaffer, P., Arveux, P., Lesech, J.M., Exbrayat, C. & Schaerer, R. (2002). Int. J. Cancer 97, 372–376.CrossRefGoogle Scholar
Clayton, D. & Schifflers, E. (1987a). Stat. Med. 6, 449–467.CrossRefGoogle Scholar
Clayton, D. & Schifflers, E. (1987b). Stat. Med. 6, 469–481.CrossRefGoogle Scholar
Duncan, S.R., Scott, S. & Duncan, C.J. (1993). J. Theoret. Biol. 160, 231–248.CrossRefGoogle Scholar
Garland, C.F., Garland, F.C., Gorham, E.D., Lipkin, M., Newmark, H., Mohr, S.B. & Holick, M.F. (2006). Am. J. Publ. Health 96, 252–261.CrossRefGoogle Scholar
Hajkova, P., Erhardt, S., Lane, N., Haaf, T., El-Maarri, O., Reik, W., Walter, J. & Surani, M.A. (2002). Mech Dev 117, 15–23.CrossRefGoogle Scholar
Heston, J.F., Kelly, J.A.B. & Meigs, J. (1986). Forty five years of cancer incidence in Connecticut: 1935–79. National Cancer Institute Monograph 70 (NIH Publication 86–2652).Google Scholar
Holford, T.R. (1999). Ann. Rev. Publ. Health 12, 425–457.CrossRefGoogle Scholar
Holford, T.R.Zhang, Z.X. & Mckay, L.A. (1994). Stat. Med. 13, 23–41.CrossRefGoogle Scholar
IAGA (1995). IAGA Division V Working Group 8 International Geomagnetic Reference Field 1995, Revision. J. Geomagn. Geoelectr. 47, 1257–1261.CrossRefGoogle Scholar
Janssen, F. & Kunst, A.E. (2005). Int. J. Epidemiol. 34, 1149–1159.CrossRefGoogle Scholar
JemalA,M. A,M., Chu, K.C. & Tarone, R.E. (2001). J. Natl. Cancer Inst. 93, 277–283.CrossRefGoogle Scholar
Juckett, D.A. & Rosenberg, B. (1997). Int. J. Biometeorol. 40, 206–222.CrossRefGoogle Scholar
Koturbash, I., Pogribny, I. & Kovalchuk, O. (2005). Biochem. Biophys. Res. Comm. 337, 526–533.CrossRefGoogle Scholar
Kuo, C., Lindberg, C. & Thomson, D.J. (1990). Nature 1343, 709–714.CrossRefGoogle Scholar
LaVecchia, C., Lucchini, F., Negri, E., Boyle, P., Maisonneuve, P. & Levi, F. (1992). Eur. J. Canc. 28A, 927–998.CrossRefGoogle Scholar
LaVecchia, C., Lucchini, F., Negri, E., Boyle, P. & Levi, F. (1993). Eur. J. Canc. 29A, 431–470.CrossRefGoogle Scholar
Lee, W.C. & Lin, R.S. (1996). Biom. J. 38, 97–106.CrossRefGoogle Scholar
Liaw, Y.-P., Huang, Y.-C. & Lien, G.-W. (2005). BMC Publ. Health 5, doi: 10.1186/1471-2458-5-22CrossRefGoogle Scholar
Llorca, J. & Delgado-Rodriguez, M. (2006). Int. J. Epidemiol. 10, 99–101.Google Scholar
Llorca, J., Prieto, M.D. & Delgado-Rodriguez, M. (1999). J. Epidemiol. Comm. Health 53, 408–411.CrossRefGoogle Scholar
Lutz, W. (1989). Distributional Aspects of Human Fertility: A Global Comparative Study. Academic Press, London.Google Scholar
Mandl, A.M. & Beaumont, H.M. (1964). Proc Int. Symp. on Effects of Ionizing Radiation on the Reproductive System, Colorado State University, Fort Collins, CO, 1964, ed. Carlson, W.D. & Gassner, F.X., pp. 311–321. Pergamon Press, Norwich.Google Scholar
Morris, P.A. & Nickerson, W.J. (1948). Experientia 4, 251–255.CrossRefGoogle Scholar
NCRP (1987). Exposure of the population in the United States and Canada from natural background radiation. NCRP Report No. 94, National Council on Radiation Protection and Measurement, Bethesda, MD.Google Scholar
Parkin, D.M., Whelan, S.L., Ferlay, J., Teppo, L. & Thomas, D.B. (eds (2002). Cancer Incidence in Five Continents, Vol. VIII (IARC Scientific Publication, No. 155). International Agency for Research on Cancer, Lyon.Google Scholar
Petrauskaite, R. & Gurevicius, R. (1996). Int. J. Cancer 66, 294–296.3.0.CO;2-U>CrossRefGoogle Scholar
Pogribny, I., Koturbash, I., Tryndyak, V., Hudson, D., Stevenson, S.M.L., Sedelnikova, O., Bonner, W. & Kovalchuk, O. (2005). Mol. Cancer Res. 3, 553–561.CrossRefGoogle Scholar
Robertson, C. & Boyle, P. (1998a). Stat. Med. 17, 1305–1323.3.0.CO;2-W>CrossRefGoogle Scholar
Robertson, C. & Boyle, P. (1998b). Stat. Med. 17, 1325–1340.3.0.CO;2-R>CrossRefGoogle Scholar
Robertson, C., Gandini, S. & Boyle, P. (1999). J. Clin. Epidemiol. 52, 569–583.CrossRefGoogle Scholar
Ruston, D., Hoare, J., Henderson, L., Gregory, J., Bates, C.J., Prentice, A., Birch, M., Swan, G. & Farron, M. (2004). The National Diet and Nutrition Survey: Adults Aged 19–64. Years. Volume 4: Nutritional Status (Anthropometry and Blood Analytes), Blood Pressure and Physical Activity. HMSO, London.Google Scholar
Savitzky, A. & Golay, M.J.E. (1964). Anal. Chem. 36, 1627–1639.CrossRefGoogle Scholar
Tarone, R.E. & Chu, K.C. (1992). J. Natl Canc. Inst. 84, 1402–1410.CrossRefGoogle Scholar
Upshur, R.E.G., Knight, K. & Goel, V. (1999). Am. J. Epidemiol. 149, 85–92.CrossRefGoogle Scholar
US Bureau of the Census (1945). Population differential fertility 1940 and 1910. In: Sixteenth Census of the United States, 1940. US Department of Commerce/US Government Printing Office, Washington, DC.Google Scholar
Weinkam, J.J. & Sterling, T.D. (1991). Epidemiology 2, 133–137.CrossRefGoogle Scholar
Wesley, J.P. (1960). Int. J. Rad. Biol. 2, 97–118.Google Scholar
Williamson, C.S. (2006). Nutr. Bull. 31, 77–80.CrossRefGoogle Scholar