Carlsbad Environmental Monitoring & Research Center

Cancer Incidence Rates in Eddy and Lea Counties

New Mexico, 1970-1994 PAGE 1

Issued: April 6, 1998

List of Tables

Table 1. Epidemiology & Cancer Control Program Project Staff
Table 2. Selected Components of Mixed Waste to be Emplaced at the WIPP, and Associated Cancers
Table 3. Selected Known or Suspected Carcinogenic Substances to be Disposed of at the WIPP, and Associated Cancers
Table 4. Cancer Sites Assessed and Their Corresponding SEER Site Categories
Table 5. Cancer All Sites, 1970-1992 (Non-Hispanic and Hispanic White Males and Females)
Table 6. Cancer all Sites, 1970-1992 (Non-Hispanic White Males and Females)
Table 7. Cancer All Sites, 1970-1992 (Hispanic White Males and Females)
Table 8. Bladder Cancer, 1970-1992 (Non-Hispanic and Hispanic White Males and Females)
Table 9. Bladder Cancer, 1970-1992 (Non-Hispanic White Males and Females)
Table 10. Bladder Cancer, 1970-1992 (Hispanic White Males and Females)
Table 11. Bone and Joint Cancer, 1970-1992 (Non-Hispanic and Hispanic White Males and Females)
Table 12. Bone and Joint Cancer, 1970-1992 (Non-Hispanic White Males and Females)
Table 13. Bone and Joint Cancer, 1970-1992 (Hispanic White Males and Females)
Table 14. Brain/Other Nervous System Cancer, 1970-1992 (Non-Hispanic and Hispanic White Males and Females)
Table 15. Brain/Other Nervous System Cancer, 1970-1992 (Non-Hispanic White Males and Females)
Table 16. Brain/Other Nervous System Cancer, 1970-1992 (Hispanic White Males and Females)
Table 17. Breast Cancer, 1970-1992 (Non-Hispanic and Hispanic White Females)
Table 18. Colon Cancer, 1970-1992 (Non-Hispanic and Hispanic White Males and Females)
Table 19. Colon Cancer, 1970-1992 (Non-Hispanic White Males and Females)
Table 20. Colon Cancer, 1970-1992 (Hispanic White Males and Females)
Table 21. Larynx Cancer, 1970-1992 (Non-Hispanic and Hispanic White Males and Females)
Table 22. Larynx Cancer, 1970-1992 (Non-Hispanic White Males and Females)
Table 23. Larynx Cancer, 1970-1992 (Hispanic White Males and Females)
Table 24. Leukemia, 1970-1992 (Non-Hispanic and Hispanic White Males and Females)
Table 25. Leukemia, 1970-1992 (Non-Hispanic White Males and Females)
Table 26. Leukemia, 1970-1992 (Hispanic White Males and Females)
Table 27. Liver Cancer, 1970-1992 (Non-Hispanic and Hispanic White Males and Females)
Table 28. Liver Cancer, 1970-1992 (Non-Hispanic White Males and Females)
Table 29. Liver Cancer, 1970-1992 (Hispanic White Males and Females)
Table 30. Lung and Bronchus Cancer, 1970-1992 (Non-Hispanic and Hispanic White Males and Females)
Table 31. Lung and Bronchus Cancer, 1970-1992 (Non-Hispanic White Males and Females)
Table 32. Lung and Bronchus Cancer, 1970-1992 (Hispanic White Males and Females)
Table 33. Non-Hodgkin’s Lymphomas, 1970-1992 (Non-Hispanic and Hispanic White Males and Females)
Table 34. Non-Hodgkin’s Lymphomas, 1970-1992 (Non-Hispanic White Males and Females)
Table 35. Non-Hodgkin’s Lymphomas, 1970-1992 (Hispanic White Males and Females)
Table 36. Ovarian Cancer, 1970-1992 (Non-Hispanic and Hispanic White Females)
Table 37. Prostate Cancer, 1970-1992 (Non-Hispanic and Hispanic White Males)
Table 38. Stomach Cancer, 1970-1992 (Non-Hispanic and Hispanic White Males and Females)
Table 39. Stomach Cancer, 1970-1992 (Non-Hispanic White Males and Females)
Table 40. Stomach Cancer, 1970-1992 (Hispanic White Males and Females)
Table 41. Thyroid Cancer, 1970-1992 (Non-Hispanic and Hispanic White Males and Females)
Table 42. Thyroid Cancer, 1970-1992 (Non-Hispanic White Males and Females)
Table 43. Thyroid Cancer, 1970-1992 (Hispanic White Males and Females)
Table 44. Corpus Uteri Cancer, 1970-1992 (Non-Hispanic and Hispanic White Females)
Table 45. Childhood Cancer*, All Sites, 1970-1992 (Non-Hispanic and Hispanic White Males and Females)
Table 46. Childhood Cancer*, All Sites, 1970-1992 (Non-Hispanic White Males and Females)
Table 47. Childhood Cancer*, All Sites, 1970-1992 (Hispanic White Males and Females)
Table 48. Childhood Cancer*, Leukemia, All Sites, 1970-1992 (Non-Hispanic and Hispanic White Males and Females)
Table 49. Childhood Cancer*, Leukemia, All Sites, 1970-1992 (Non-Hispanic White Males and Females)
Table 50. Childhood Cancer*, Leukemia, All Sites, 1970-1992 (Hispanic White Males and Females)

List of Figures

(Note: Figures are not available in electronic format. Please use our information request form to order a report copy, if desired.)

Figure 1. 5 Leading Cancers in New Mexico Males and Females, Incidence and Mortality Rates, 1993
Figure 2. 5 Leading Cancers in Non-Hispanic White Males and Females, Incidence and Mortality Rates, New Mexico, 1993
Figure 3. 5 Leading Cancers in Hispanic Males and Females, Incidence and Mortality Rates, New Mexico, 1993
Figure 4. 3 Year Moving Age Adjusted Incidence Rates All Sites for New Mexico Residents
Figure 5. 3 Year Moving Age Adjusted Incidence Rates All Sites for Eddy County Residents
Figure 6. 3 Year Moving Age Adjusted Incidence Rates All Sites for Lea County Residents
Figure 7. 3 Year Moving Age Adjusted Incidence Rates Urinary Bladder for New Mexico Residents
Figure 8. 3 Year Moving Age Adjusted Incidence Rates Urinary Bladder for Eddy County Residents
Figure 9. 3 Year Moving Age Adjusted Incidence Rates Urinary Bladder for Lea County Residents
Figure 10. 3 Year Moving Age Adjusted Incidence Rates Bones and Joints for New Mexico Residents
Figure 11. 3 Year Moving Age Adjusted Incidence Rates Bones and Joints for Eddy County Residents
Figure 12. 3 Year Moving Age Adjusted Incidence Rates Bones and Joints for Lea County Residents
Figure 13. 3 Year Moving Age Adjusted Incidence Rates Brain/Other Nervous Systems for New Mexico Residents
Figure 14. 3 Year Moving Age Adjusted Incidence Rates Brain/Other Nervous Systems for Eddy County Residents
Figure 15. 3 Year Moving Age Adjusted Incidence Rates Brain/Other Nervous Systems for Lea County Residents
Figure 16. 3 Year Moving Age Adjusted Incidence Rates Female Breast for New Mexico Residents
Figure 17. 3 Year Moving Age Adjusted Incidence Rates Female Breast for Eddy County Residents
Figure 18. 3 Year Moving Age Adjusted Incidence Rates Female Breast for Lea County Residents
Figure 19. 3 Year Moving Age Adjusted Incidence Rates Colon Excluding Rectum for New Mexico Residents
Figure 20. 3 Year Moving Age Adjusted Incidence Rates Colon Excluding Rectum for Eddy Count Residents
Figure 21. 3 Year Moving Age Adjusted Incidence Rates Colon Excluding Rectum for Lea County Residents
Figure 22. 3 Year Moving Age Adjusted Incidence Rates Larynx for New Mexico Residents
Figure 23. 3 Year Moving Age Adjusted Incidence Rates Larynx for Eddy County Residents
Figure 24. 3 Year Moving Age Adjusted Incidence Rates Larynx for Lea County Residents
Figure 25. 3 Year Moving Age Adjusted Incidence Rates Leukemias for New Mexico Residents
Figure 26. 3 Year Moving Age Adjusted Incidence Rates Leukemias for Eddy County Residents
Figure 27. 3 Year Moving Age Adjusted Incidence Rates Leukemias for Lea County Residents
Figure 28. 3 Year Moving Age Adjusted Incidence Rates Liver for New Mexico Residents
Figure 29. 3 Year Moving Age Adjusted Incidence Rates Liver for Eddy County Residents
Figure 30. 3 Year Moving Age Adjusted Incidence Rates Liver for Lea County Residents
Figure 31. 3 Year Moving Age Adjusted Incidence Rates Lung and Bronchus for New Mexico Residents
Figure 32. 3 Year Moving Age Adjusted Incidence Rates Lung and Bronchus for Eddy County Residents
Figure 33. 3 Year Moving Age Adjusted Incidence Rates Lung and Bronchus for Lea County Residents
Figure 34. 3 Year Moving Age Adjusted Incidence Rates Non-Hodgkin Lymphoma for New Mexico Residents
Figure 35. 3 Year Moving Age Adjusted Incidence Rates Non-Hodgkin Lymphoma for Eddy County Residents
Figure 36. 3 Year Moving Age Adjusted Incidence Rates Non-Hodgkin Lymphoma for Lea County Residents
Figure 37. 3 Year Moving Age Adjusted Incidence Rates Ovary for New Mexico Residents
Figure 38. 3 Year Moving Age Adjusted Incidence Rates Ovary for Eddy County Residents
Figure 39. 3 Year Moving Age Adjusted Incidence Rates Ovary for Lea County Residents
Figure 40. 3 Year Moving Age Adjusted Incidence Rates Prostate Gland for New Mexico Residents
Figure 41. 3 Year Moving Age Adjusted Incidence Rates Prostate Gland for Eddy County Residents
Figure 42. 3 Year Moving Age Adjusted Incidence Rates Prostate Gland for Lea County Residents
Figure 43. 3 Year Moving Age Adjusted Incidence Rates Stomach for New Mexico Residents
Figure 44. 3 Year Moving Age Adjusted Incidence Rates Stomach for Eddy County Residents
Figure 45. 3 Year Moving Age Adjusted Incidence Rates Stomach for Lea County Residents
Figure 46. 3 Year Moving Age Adjusted Incidence Rates Thyroid Gland for New Mexico Residents
Figure 47. 3 Year Moving Age Adjusted Incidence Rates Thyroid Gland for Eddy County Residents
Figure 48. 3 Year Moving Age Adjusted Incidence Rates Thyroid Gland for Lea County Residents
Figure 49. 3 Year Moving Age Adjusted Incidence Rates Corpus Uteri for New Mexico Residents
Figure 50. 3 Year Moving Age Adjusted Incidence Rates Corpus Uteri for Eddy County Residents
Figure 51. 3 Year Moving Age Adjusted Incidence Rates Corpus Uteri for Lea County Residents
Figure 52. 3 Year Moving Age Adjusted Incidence Rates All Causes for New Mexico Residents
Figure 53. 3 Year Moving Age Adjusted Incidence Rates All Causes for Eddy County Residents
Figure 54. 3 Year Moving Age Adjusted Incidence Rates All Causes for Lea County Residents
Figure 55. 3 Year Moving Age Adjusted Incidence Rates Leukemias for New Mexico Residents
Figure 56. 3 Year Moving Age Adjusted Incidence Rates Leukemias for Eddy County Residents
Figure 57. 3 Year Moving Age Adjusted Incidence Rates Leukemias for Lea County Residents

CANCER INCIDENCE RATES IN EDDY AND LEA COUNTIES

NEW MEXICO, 1970-1994

INTRODUCTION

This study was conducted by investigators with the Epidemiology & Cancer Control Program, University of New Mexico Health Sciences Center (Table 1), under a contract with New Mexico State University (NMSU), with funding by the Carlsbad Environmental Monitoring & Research Program (CEMRP), under a grant from the U.S. Department of Energy (DOE) to NMSU (DE-FG04-91AL74167). This research is part of a larger CEMRP project to implement independent health and environmental monitoring in the vicinity of the WIPP, and to make the monitoring results available to all interested parties.

The purpose of this study was to present an assessment of baseline cancer rates in Eddy and Lea counties. Cancers related to exposure to ionizing radiation and hazardous chemicals were stratified by sex and ethnicity, and analyzed by (1) describing geographic variation in cancer incidence found in New Mexico for the period 1970 to 1992, and (2) describing temporal variation in cancer incidence in Eddy and Lea counties for the period between 1970 and 1994.

Cancer and Toxic Exposure

For an individual to experience adverse health effects from an exposure to a substance, the substance must be toxic to humans, the individual must come into contact with the substance, and the individual must come into contact with high enough concentrations of the substance for a long enough duration to cause a biological effect (OTA 1991). Exposure to chemically hazardous and radioactive materials is associated with a variety of acute and chronic health conditions such as irritation and burning of the skin, eyes, and respiratory system; organ and nervous system damage; exacerbation of pre-existing conditions such as infections and allergies; birth defects; and cancer (Sax 1981; Sax 1987). In addition, exposure to a combination of toxic and radioactive materials may result in compounded adverse health effects, and some chemicals sensitize tissues to radioactive materials (Mettler 1995). Of these adverse health effects, cancer, a group of diseases distinguished by the uncontrolled growth of abnormal cells, is of paramount concern.

About 1 in 3 people alive today will develop cancer (Brownson 1993); at least 8 million Americans presently living have had or do have the disease (ACS 1995). Cancer cells may be created when a cell undergoes a permanent change by internal means or outside exposure. If a cell is damaged by exposure to a carcinogenic substance and survives but cannot repair itself, it is permanently altered and has the potential to become cancerous. It is likely that most adults develop many altered cells in their lifetimes that don't become cancerous (Craighead 1995). However, if a cell becomes cancerous it ceases to react normally to signals from the body, and begins to multiply rapidly and destroy healthy tissue (ACS 1995). If this growth is not stopped by treatment such as surgery, radiation therapy, or chemotherapy, the cancer can be fatal.

The likelihood of developing cancer increases with age (ACS 1995); Americans over the age of 65 have 10 times the risk of developing cancer than Americans under 65 (NCI 1993). In addition, in the US, men have a higher risk of developing cancer than women; blacks have a higher risk than whites; and Hispanics, American Indians, and Asians have a lower risk than other ethnic and racial groups (NCCDPHP 1992). However, there are some exceptions. For instance, some types of cancer occur frequently at a younger age, such as leukemia, Hodgkin's and non-Hodgkin's lymphoma, and cancer of the brain and nervous system, kidney, and bone (NCI 1993; Schofield and Cotran 1994; ACS 1995); females have a higher risk than males for particular cancers, such as thyroid cancer (NCI 1993); and American Indians have higher incidence rates for stomach, cervical, kidney, and gallbladder cancer than non-Hispanic whites (NCCDPHP 1992).

Other factors affecting the risk of developing cancer include tobacco use; lifestyle; diet; occupational and other exposures to ionizing radiation and toxic chemicals; and exposure to certain viruses including human immunodeficiency virus (HIV), Epstein-Barr virus, hepatitis-B and C, human papillomavirus, and human T-lymphotropic virus (NCI 1993). In the early 1980s, tobacco alone was estimated to be responsible for as many as 30% of all cancer cases (Doll and Peto 1981). In 1995, tobacco use was estimated to be responsible for 87% of lung cancers in the US (ACS 1995) (the leading type of cancer death in both sexes), and tobacco use also causes mouth, larynx, pharynx, esophagus, pancreas, cervix, kidney, and bladder cancers. On the other end of the scale, viruses and occupational exposures to toxic chemicals are each thought to account for about 5% of cancer deaths (NCI 1993). Environmental exposures, including contamination of air, water, and food are believed to account for a relatively small portion of cancer deaths (probably about 2 to 5%) (Doll and Peto 1981).

Although the risk of developing cancer generally increases with age, childhood cancers are of concern. One reason for this is that children are more sensitive to toxic substances and environmental exposures than adults (Bearer 1995). Children experience different and sometimes higher exposures than adults because they breathe air from lower zones where there are heavier gases and particles; they have a different metabolic rate, causing oxygen consumption and rates of absorption of nutrients and contaminants to be greater; they consume more food, and thus more contaminants, per unit of body weight; they consume more dairy products and produce, and the contaminants associated with these foods; young children are more likely than adults to put inedible items, such as dirt and paint, in their mouths; and infants have more absorptive stomachs and skin and less effective kidneys than adults. In addition, children are more susceptible than adults to exposures simply because they are growing and their cells are multiplying rapidly.

Because any cancer cases resulting from exposure to radioactive and hazardous waste from the WIPP would be superimposed on the much larger number of cancers caused by exposure to other carcinogens and the lifestyle factors described above, it may be difficult to determine whether the WIPP is contributing to cancer risk in the surrounding counties. Two ways to measure cancer occurrence in a community are to monitor counts of cancer cases and to monitor cancer incidence rates. Cancer incidence rates are the number of newly diagnosed cases of cancer occurring in a population over a period of time, divided by the number of people at risk for a particular cancer or cancers (Hennekens and Buring 1987). Cancer incidence rates are often the preferred method to monitor cancer in a community because they allow the comparison of cancer occurrence among populations of different sizes and may be adjusted to account for different age distributions. To investigate trends in cancer incidence rates after waste is placed in the WIPP, it is crucial to understand the history of incidence rates in the region surrounding the facility, both geographically and temporally.

Potentially Impacted Population

The people who live and/or work in Eddy and Lea counties are at the greatest risk of exposure in the event of release of radioactive and hazardous materials from the WIPP. The area surrounding the WIPP is rural, with approximately 36 people living within ten miles of the WIPP facility at the time of this study (Westinghouse 1995). Communities in Eddy and Lea counties include Carlsbad, Artesia, Hope, Jal, Eunice, Hobbs, Loving, Malaga, and Lovington. According to unpublished New Mexico Tumor Registry (NMTR) population estimates derived from US Bureau of Census figures (1990), Eddy County had a 1994 population of 52,789 people (including 31,759 non-Hispanic whites (i.e., Anglos) and 19,429 Hispanics), and Lea County had a 1994 population of 57,110 people (including 34,897 non-Hispanic whites and 18,887 Hispanics). All other races and ethnicities in 1994 comprised only about 2.5% of the population in Eddy County and 5.5% in Lea County. In Bureau of Census surveys, individuals identify their own race and ethnicity, and are asked whether they are of Hispanic origin.

At the time of this study, the WIPP employed about 1,000 people from surrounding communities (DOE 1996). Major industries in Eddy and Lea counties include oil and natural gas production and potash mining. Eddy County is one of the world's largest potash producers and one of New Mexico's largest oil and natural gas producers, and Lea County is New Mexico's largest oil and natural gas producer (BBER 1995). For the past two decades, population trends appear to have followed trends in the oil, natural gas, and potash industries in these counties. In general, in the 1970s, trends in industry and population fluctuated, with some overall increase. In the decade between 1980 and 1990, trends in industry and population rose to peak levels by about 1983, and then followed a fluctuating decline to the end of the decade. Since 1990, these trends have shown a slight increase. Although the number of people in the labor force remained fairly steady between 1980 and 1990, the number of people employed in mining decreased by 35.3% in Eddy County and by 31.8% in Lea County (BBER 1995). Lea County also experienced decreases in the number of people employed in agriculture; construction; manufacturing; transportation, communications, and public utilities; and finance, insurance, and real estate. The unemployment rate increased from 5.0 to 7.6 in Eddy County and from 2.8 to 7.2 in Lea County in this period. Possibly due to these economic factors, both counties experienced greater out-migration in the late 1980s than in-migration. In Lea County, natural population growth (births minus deaths) could not compensate for this out-migration, and the total population dropped down to the 1980 level.

Community Concerns

While there are some benefits, such as increased employment opportunities, of living near DOE facilities and nuclear power plants, residents in these communities often have a variety of associated concerns. The public may be worried about social issues, such as the stigma of living near a nuclear or hazardous waste facility, and economic issues, such as falling property values if a community is perceived as contaminated or unsafe (Guidotti and Jacobs 1993). In addition, concerns are voiced about the potential for adverse health effects from the daily operation of nuclear power plants and DOE facilities, as well as from accidents such as the radioactive emissions at the Three Mile Island nuclear plant in 1979 (Hatch et al. 1990; Jablon et al. 1990), and from the release of contaminants into the environment from accidents and improper disposal of waste at DOE facilities (OTA 1991).

These concerns are supported by a 1991 report by the Congress of the United States’ Office of Technology Assessment (OTA) which found that the DOE had a poor environmental record. At almost every facility in the DOE weapons manufacturing network, soil, air, and water are contaminated with both radioactive waste and hazardous chemical waste. In addition, the OTA found that issues have not been sufficiently investigated regarding the health impacts of this contamination. Thus, the public's concerns about the potential adverse health effects of contamination are difficult to alleviate because they cannot be substantiated or disproved. In its report, the OTA concluded that the DOE cannot have credibility with the public until, among other things, efforts are made to allow for independent oversight of public health and environmental safety issues, information about these issues is made readily accessible to the public, and the public is included in decision-making.

MATERIALS AND METHODS

This report presents cancer incidence rates, analyzed both temporally and spatially, for Eddy and Lea counties. The cancer data used to calculate incidence rates in this report were collected by the NMTR. The NMTR was established in 1966. In 1973, the NMTR received funding from the National Cancer Institute (NCI) Surveillance, Epidemiology, and End Results (SEER) Program to become one of a network of 11 registries across the US. This network is the primary source of cancer incidence data for the nation. The NMTR serves as a repository and data collection agent for confidential medical abstracts of cancer cases, and reports data on incidence, treatment, mortality, and survival to the NCI. These cases are followed on a yearly basis. The NMTR maintains a 95% follow-up rate of all cancer patients. Each of the SEER registries is a population-based registry and collects data in a standard manner so that it can be compared and combined with the data from other registries in the network. The SEER registries are distributed throughout the US as an accurate representation of the US population, and were chosen for their ability to meet the NCI's standards. The membership of the SEER network has changed slightly over the years, but at the time of this study, data were reported from the states of New Mexico, Connecticut, Iowa, Utah, and Hawaii, and the cities of, and areas surrounding, Detroit, San Francisco, Seattle-Puget Sound, Atlanta, San José, and Los Angeles, representing approximately 14% of the US population.

NMTR tumor registrars and abstractors work with tumor registrars at hospitals and treatment centers to collect cancer data. NMTR's database includes information submitted by hospitals and physician's offices, and data collected during site visits to facilities in New Mexico and other states by NMTR staff. The information used for this report includes data collected at the Guadalupe Medical Center (now Columbia Medical Center of Carlsbad) in Carlsbad, New Mexico, as well as at healthcare facilities and pathology laboratories statewide and in adjacent Texas counties. NMTR staff abstract and code information on the patient (name, maiden name, date of birth, ethnicity, social security number, place of birth, and place of residence); information on the cancer (date diagnosed, location of the cancer, stage, size, and lymph node involvement); information on any surgical treatment, radiation, or chemotherapy the patient receives; and the outcome (survival or death).

The data used for spatial analysis in this report include the NMTR's data set of cases of invasive cancers newly diagnosed in the period between 1970 and 1992, and data used for temporal analysis includes cases newly diagnosed in the period between 1970 and 1994. The data set used for the spatial analysis was extracted from the database on December 8, 1995, and the data set used for the temporal analysis was extracted from the database on January 11, 1996. It is important to note that these data sets reflect cases ascertained at the time the data were analyzed. For more recent years, a small percentage of cases (1 to 2%) may be added or redistributed geographically.

Historically, invasive and in situ cancers have been counted separately (ACS 1995). One reason for this is that in situ cancers are often removed in a physician's office instead of a hospital, and so may be reported differently. Also, after an in situ cancer has been removed, it is not known whether the cancer would have become invasive (i.e., spread). Thus, a reliable way to assess patterns in cancer incidence rates is to compare rates of invasive cancers only. An exception to this is bladder cancer (NCI 1993). Because of biological properties of tumors in the bladder, the line between when a tumor is considered in situ and when it is considered invasive is not clear. The medical community's definition of in situ and invasive bladder cancer may have changed slightly over the years, but the NMTR and SEER definition has remained consistent. Thus, SEER bladder cancer data are comparable through the years, but may not be comparable with international data.

Study Design

A large number of contaminants are present in the waste to be placed at the WIPP (Table 2). Known and suspected carcinogens slated for disposal at the WIPP, and the cancers they may cause, are presented in Table 3. This study addressed cancers of major anatomic sites caused by exposure to radionuclides and substances classified by IARC as Group 1 , indicating that there is sufficient evidence that the substance is carcinogenic to humans (IARC 1987). In addition, to provide a frame of reference, we assessed several cancers of tissues less sensitive to the types of hazardous and radioactive wastes to be disposed of at the WIPP. These sites and the corresponding SEER Program site categories used are presented in Table 4.

Cancer incidence rates are known to vary by sex and ethnicity. Rates were stratified to examine and control for the differences resulting from this variation. Because Eddy and Lea counties are comprised mainly of non-Hispanic whites and Hispanic whites, the study focused on these two ethnic groups. In addition, the study employed only age-adjusted rates. However, the study did analyze data for childhood (under 15 years old) cancers of all sites and for childhood leukemia. Leukemia is of interest because it is a radiation-sensitive cancer and comprises about one-third of all childhood cancers (NCI 1993).

Several limitations are inherent in the interpretation of cancer incidence data for small populations like those in Eddy and Lea counties. The limitations include the variability of cancer incidence data for small numbers of cancer cases and/or small populations, and the differences in the magnitude of the effects caused by various risk factors. For example, smoking the equivalent of 20 pack years (i.e., one pack per day for 20 years, 2 packs per day for 10 years, etc.) increases lung cancer risk by ten times (CCDPHP 1989). Another additive exposure that increased lung cancer risk by 50% in non-smokers would produce a 10.5-fold increase in the same group of smokers. Thus, even a relatively large increase in risk (50%) would be difficult to detect using standard epidemiologic methods.

Data Analysis

The population estimates for New Mexico used to calculate incidence rates were derived from the censuses of 1960, 1970, 1980, and 1990. Estimates of the Hispanic population in 1960 and 1970 were adjusted for systematic errors in census data processing and for the different techniques used to identify individuals of Hispanic ethnicity (Howard et al. 1983). Age-adjusted incidence rates were calculated by the direct method, using the age distribution of the 1970 US population as a standard to weight age-specific incidence rates in the populations of interest (NCI 1993).

The cancer incidence rates presented are estimates of the average annual number of people who will be diagnosed with cancer per 100,000 people (per 1,000,000 people for childhood cancers). To provide a more accurate picture of the inherent variability in incidence rate estimates, 95% confidence intervals are presented, which are estimates of the range of values within which there is 95% certainty that the true rate lies (Shambaugh et al. 1994). The calculated incidence rates are averages (called means) and approximate a bell-shaped or normal curve when plotted on a graph. Normal curves are highest in the middle at the mean, and fall off symmetrically to the sides. The standard deviation of a normal curve quantifies the dispersion of values to the left and right of the mean. In a normal curve, 95% of the values lie between the center of the curve and 1.96 standard deviations in either direction (Hennekens and Buring 1987). The standard error of the mean measures the variability of the mean as an estimate of its true value. In this study standard errors were calculated for the cancer incidence rate estimates, assuming a Poisson distribution and using the method described by Keyfitz (1966), by dividing each incidence rate by the square-root of the corresponding number of cases (incidence rate/(cases)1/2) (NCI 1993). Confidence intervals are a function of both standard deviation and standard error (Hennekens and Buring 1987). The upper 95% confidence interval was calculated by adding the product of 1.96 and the standard error to the incidence rate (incidence rate + 1.96 * standard error). The lower 95% confidence interval was calculated by subtracting the product of 1.96 and the standard error from the incidence rate (incidence rate - 1.96 * standard error). When the lower 95% confidence interval was negative, the value was truncated at zero.

Data for spatial and temporal analyses were stratified by ethnicity and sex. Spatial trends in incidence rates were assessed by comparing incidence rates from 1970 to 1992 for Eddy and Lea counties with average rates for New Mexico and all other New Mexican counties. Temporal trends in incidence rates were assessed by calculating 3-year moving average incidence rates using data from 1970 to 1994 for Eddy and Lea counties and comparing them with rates for New Mexico and the US. Moving average incidence rates, derived by calculating the mean of rates over a specified time period (3 years, in this report), were used to minimize the sharp fluctuations typical when calculating rates for small populations such as those in Eddy and Lea counties. Confidence bounds for the moving averages were not calculated; thus descriptions of "trends" or other temporal patterns are descriptive rather than statistical interpretations.

Limitations of the Data

Beyond the factors discussed above, a number of potential limitations must be considered in interpreting these data, including random variation, bias, and confounding. These factors are discussed below.

Random Variation

One way to assess the precision of a rate estimate for a given population is by calculating a confidence interval for that rate (Hennekens and Buring 1987). The narrower the confidence interval, the more precise the estimate of the rate, and the less likely it is that the rate is due to random variation (i.e., chance). Cancer cases often seem to occur in groups or clusters, and because of the large number of people who will eventually develop some type of cancer, clusters may be expected to occur for no other reason than chance (NCCC 1994). Clusters can be defined spatially, geographically, or by some other aspect that individuals may have in common, such as age, sex, or occupation. This concept is especially important when analyzing small samples (such as the populations of Eddy and Lea counties) because a few cases of cancer may result in a comparatively large and misleading incidence rate.

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Bias

A number of biases are possible in surveillance systems such as cancer registries, including biases due to incomplete case ascertainment, abstracting or coding inconsistencies, problems with assignment of ethnicity, and changes in population estimates resulting in changes in cancer incidence rates. The NMTR and SEER registries work to minimize these biases, producing the most comprehensive cancer data available nationally (Brownson et al. 1993) and making a valuable contribution worldwide (IARC 1993). The NMTR's efforts to avoid bias are discussed below.

Case Ascertainment: The NMTR uses a variety of methods to collect all diagnosed cases of malignant cancer. Within one month, 85% of reported cases are identified. Within 6 months, 99% of reported cases are identified and completely abstracted. Although it is almost certain that all histologically confirmed cancers have been collected by this time, a few cases may not be documented in routine resources such as hospital records, outpatient clinic records, and pathology laboratory records. To identify any missing cancer cases, the NMTR uses death information from New Mexico and other states which accounts for about 3% of the total yearly reported cases. In addition, physician's offices and treatment facilities are visited on a regular basis by NMTR staff to identify potential cases. Quality assurance measures include repeating case finding procedures using hospital, clinic, or laboratory records, for a specified time period.

Abstracting/Coding: Abstracted and coded data include information about patient demographics, cancer site and histology, extent of the disease, treatment, and survival (NCI 1993). Although errors are rare, the NMTR implements a rigorous quality control and quality assurance process to correct any abstracting or coding errors. Quality control measures include yearly audits by NCI personnel, monthly audits of randomly selected cases by NMTR personnel, utilization of computer programs that check for implausible data combinations, and a focus on education of NMTR abstractors and tumor registrars.

By Ethnicity: Assignment of ethnicity is an important issue in New Mexico because of the state's comparatively large Hispanic and Native American populations. To ensure correct assignment of ethnicity, NMTR has initiated routine verification procedures that provide a high percentage of accuracy for ethnic identification. The NMTR uses multiple sources to assign or verify ethnicity. The sources used to help assign ethnicity include hospital charts, death records, Health Care Financing Administration records, Indian Health Service records, information collected during SEER special studies, the 1980 Census list of Spanish surnames, and the GUESS program (a computer program designed by a former NMTR staff member, that assigns ethnicity based on parts of, and whole, last names). Sources used to verify ethnicity include many of the same, and some additional sources, including data supplied by the next of kin when a patient has died, records from the Health Care Financing Administration (only for people over 65 years old, and only for the race distinctions of white, black, or other), Indian Health Service records (only for Native Americans), follow-up letters to doctors asking for confirmation of ethnicity, and information gathered during SEER special studies. The GUESS program alone successfully assigned ethnicity for 93.3% of Hispanic males residing in New Mexico who died during the period between 1985 and 1993, and 89.4% of Hispanic females who died during this period (Darling 1996).

Population Estimates: Population estimates are periodically adjusted, resulting in a change in cancer incidence rates (calculated by dividing the number of reported cases for a specified time period by the population at risk). In an effort to minimize variation, the NMTR uses Bureau of Census population data, divided into ethnic groups by the University of New Mexico's Bureau of Business and Economic Research (BBER), to estimate population (including for the years between censuses). The BBER publishes yearly population estimates for New Mexico. The NMTR uses this information to calculate changes in population estimates for standard ethnicities used by the NMTR and SEER program. Population estimates may be readjusted for past years after the decennial census is completed.

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Confounding

The data sets analyzed in this report were age-adjusted and stratified for sex and ethnicity. Associations found between cancer incidence rates and sex or ethnicity may actually be due, in whole or in part, to other factors that were not measured such as tobacco use, lifestyle, occupation, eating habits, or socioeconomic status.