Submit Manuscript | http://medcraveonline.com Abbreviations: SEER, surveillance epidemiology and end results database; OTSI, orbital total solar irradiation; GTSI, ground total solar irradiation; KZ, kolmogorov-zurbenko Introduction Skin cancer and total solar irradiance Skin Cancer is the most common form of cancer. 1 The incidence of skin cancers are rising in today’s populations. 2 Approximately 5 million will be treated for skin cancer in the United States alone. 3 Prior research correlates ultraviolet exposure with increased skin cancer risk. 4 The pronounced seasonal component in the diagnosis of skin cancer is a frequent subject of research in order to examine the effect of UV exposure. 5 Accurately measuring a coeffcient linking exposure to solar irradiation with the increase in skin cancer rates would is of immense value to research, prediction and prevention. While possible to measure irradiation at the ground level, records on monthly or shorter time scales are susceptible to strong random regional short term fuctuations in weather patterns affecting atmospheric conditions. 6 These changes in weather can greatly change irradiation reaching at risk populations on very short time scales. Satellite based instruments measuring total solar irradiation are not obscured by random weather patterns and their measurements may be of greater research potential in this analysis. Orbital total solar irradiation (OTSI) seasonally adjusted by latitude to refect peak potential ground level irradiation (GTSI) is used to replicate the level of exposure at a given location averaged over many seasons. Separation of time scales and the seasonal component The skin cancer time series exhibits several principal component sources of variability operating at different frequencies. The seasonal component is second in total variability only to a long term increasingly upward trend. To isolate and properly investigates the seasonal component and possible relationships with the sources of variation in skin cancer incidence it is necessary to separate uncorrelated obscuring time scales such as random noise and the long term trend. 7 Separation is achieved using a combination of low pass Kolmogorov-Zurbenko Filters. 8 Filter parameters are selected to separate and remove the long term components and short term noise from the seasonal time scale. 9 The principal component of variability in solar activity and irradiation occurs during at an approximate 11 year cycle, known as the solar cycle. 10 Methods of time scale separation, cross-correlation, and regression previously produced a coeffcient of infuence for the solar cycle effect upon skin cancer prevalence. 11 The small but unique effect at this fngerprint frequency provided a measure of infuence at this time scale upon skin cancer rates. The seasonal or one year time scale component in skin cancer by comparison is more pronounced than that associated with the solar cycle. Here seasonal patterns are not associated with fuctuations in solar activity but the axial tilt of the earth which greatly affects the levels of irradiation reaching the ground level and at risk populations. OTSI measurements must be seasonally adjusted for irradiation reaching the ground level. This adjustment to OTSI is accomplished by compensating both for a reduction in irradiation passing through the atmosphere as well as the spread of irradiation on the earth’s surface consistent with the angle of incidence given the combination of Earth’s axial tilt, season and latitude. 12 Cross-correlations between skin cancer rates and irradiation must account for possible latencies both in effect and detection. 13 Therefore cross-correlations are calculated across all possible latencies or lags in time and peak correlations are used to synchronize datasets on the candidate latency. Regression analysis is used to characterize the resulting irradiation and skin cancer incidence relationship and produces a numerical coeffcient of infuence. This original approach produces a coeffcient appropriate for modeling and predicting skin cancer incidence at a regional level based on season, location and irradiation levels. Methods Data sources Skin cancer records are extracted from monthly case diagnosis data in the SEER or Surveillance, Epidemiology, and End Results database, 1973-2010. 14 The SEER sites included for this study are the states of Connecticut, Hawaii, Iowa, New Mexico, and Utah, and the cities of San Francisco-Oakland and Detroit beginning with the initiation of the database in 1973 until the most recent data published. Additional sites are available but these sites exclusively represent the earliest commencement and the longest continuous time series datasets in the SEER database. The cancer database includes all diagnoses at these Biom Biostat Int J. 2014;1(3):93‒98. 93 ©2014 Valachovic et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and build upon your work non-commercially. Solar irradiation and the annual component of skin cancer incidence Volume 1 Issue 3 - 2014 Edward Valachovic, Igor Zurbenko Department of Epidemiology and Biostatistics, State University of New York at Albany School of Public Health, USA Correspondence: Edward Valachovic, Department of Epidemiology and Biostatistics, State University of New York at Albany School of Public Health, One University Place, Rensselaer, NY 12144, USA, Tel: (518) 402-0283 Email Received: December 13, 2014 | Published: December 23, 2014 Abstract The skin cancer incidence time series is composed of principal components operating in uncorrelated time scales. This study investigates the relationship between the substantial seasonal component of skin cancer diagnoses and seasonal fuctuations in solar irradiation. After Kolmogorov-Zurbenko separation and fltration of uncorrelated time scales, cross- correlation analysis accounts for latency between irradiation and associated skin cancer detection. This study derives a coeffcient of infuence between changes in irradiation and skin cancer incidence, quantifying the relationship and modeling increasing risk to increased exposure. The development of this coeffcient provides new opportunities to model and predict skin cancer incidence. Keywords: skin cancer, irradiation, time series, seasonal component, kolmogorov- zurbenko flters Biometrics & Biostatistics International Journal Research Article Open Access