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Solid-Tumor Mortality in the Vicinity of Uranium Cycle Facilities and Nuclear Power Plants in Spain.

To ascertain solid tumor mortality in towns near Spain's four nuclear power plants and four nuclear fuel facilities from 1975 to 1993, we conducted a mortality study based on 12,245 cancer deaths in 283 towns situated within a 30-km radius of the above installations. As nonexposed areas, we used 275 towns lying within a 50- to 100-km radius of each installation, matched by population size and sociodemographic characteristics (income level, proportion of active population engaged in farming, proportion of unemployed, percentage of illiteracy, and province). Using log-linear models, we examined relative risk for each area and trends in risk with increasing proximity to an installation. The results reveal a pattern of solid-tumor mortality in the vicinity of uranium cycle facilities, basically characterized by excess lung [relative risk (RR) 1.12, 95% confidence interval (CI), 1.02-1.25] and renal cancer mortality (RR 1.37, 95% CI, 1.07-1.76). Besides the effects of natural radiation, these results could well be evincing the influence on public health exerted by the environmental impact of mining. No such well-defined pattern appeared in the vicinity of nuclear power plants. Monitoring of cancer incidence and mortality is recommended in areas surrounding nuclear fuel facilities and nuclear power plants, and more specific studies are called for in areas adjacent to installations that have been fully operational for longer periods. In this regard, it is important to use dosimetric information in all future studies. Key words: environment, epidemiology, ionizing, mortality, neoplasms, nuclear facilities, radiation, uranium mines. Environ Health Perspect 109:721-729 (2001). [Online 11 July 2001] http://ehpnet1.niehs.nih.gov/docs/2001/109p721-729lopez-abente/abstract .html

The report that appeared in late 1983 of a cluster of leukemias in young residents living near a nuclear fuel reprocessing plant in Sellafield, England, triggered a considerable amount of investigation into cancer incidence and mortality in areas near nuclear installations. The nuclear industry generates a great deal of social concern, exacerbated recently by the serious accidents that have affected nuclear power plants, such as that of Chernobyl in 1986, and uranium processing facilities, such as the one at Tokaimura in 1999.

Cancer incidence and mortality studies in areas near nuclear facilities have failed to eliminate doubts about possible adverse population effects attributable to routine operations, despite the fact that numerous studies performed in different countries have reported an absence of cancer risk in areas around nuclear fuel facilities and power plants (1-4). In the main, epidemiologic studies have targeted hematologic tumors and young age groups, and very few have sought to assess in depth the remaining malignant tumors. The concern voiced by society regarding the consequences of industry in its immediate vicinity has essentially focused on nuclear power plants. With respect to industries linked to uranium production, considerable effort has been made to ascertain the risk in cohorts of miners (5-7), and although the environmental impact of nearby uranium mines, particularly of uranium mill tailings (8-10), has been studied, the related public health consequences have received scant attention.

Spain currently has seven nuclear power plants, with a total of 10 reactors (nine fully operational and one being dismantled) and nine nuclear fuel facilities (three fully operational, one shut down, and five being dismantled). We therefore performed a cancer mortality study covering towns near nuclear power plants and fuel facilities. Death certificates were the only nationwide source of information on mortality in Spain on which a first analysis of this nature could be based.

In a previous study we reported the results for hematologic tumors (11). In this article we report the results of that study for solid tumors. The analysis presented here sought to quantify the relative risk of death in the vicinity of such installations; to ascertain said risk before and after the date on which these installations first came into operation; to study changes in risk according to subjects' relative proximity to the respective installations; and, given the descriptive and exploratory nature of this study, to provide further pointers for new research.

Materials and Methods

A more detailed description of the methodology may be found in a previous study (11). Here we present results on mortality caused by stomach cancer [International Classification of Diseases-9 (ICD) 151] and colorectal (ICD 153-154), lung (ICD 162), bone (ICD 170), connective tissue (ICD 171), breast (in women, ICD 174), brain (ICD 191), thyroid (ICD 193), bladder (ICD 188), kidney (ICD 189), ovary (ICD 183), and all malignant tumors (ICD 140-208), in towns situated near nuclear facilities. We included towns near four nuclear power plants (NPP) with six reactors that had been operational from 1975 to 1993, and four nuclear fuel facilities (NFF) that had likewise been operational in the same period. With the exception of El Cabril, a nuclear waste storage facility (NWSF) built on the site of an abandoned uranium mine, the NFF are uranium-concentrate-processing facilities located in mining areas where the ore is extracted. The latency periods used were 10 years. This lag rules out the possibility of study for the areas surrounding the Asco, Cofrentes, Trillo, and Juzbado facilities, since all these plants were inaugurated relatively recently.

Figure 1 shows the site and year of startup of these installations. This was a spatial mortality study whose population base comprised inhabitants of towns neighboring the nuclear installations under review. For description and analysis, the area within a 30-km radius of any such installation was called the "exposed zone"; and towns (selected as outlined below) lying within a 50- to 100-km radius of the installation were called the "reference zone." With a Geographic Information System, we used the UTM (Universal Transversa Mercator projection) centroid coordinates for towns to measure the distance from the population centroids to the nuclear installations.

[ILLUSTRATION OMITTED]

Follow-up took place from 1 January 1975 through 31 December 1993. For all four nuclear power plants, 184 towns within a 30-km radius and 178 within a 50- to 100-km radius were included in the study, matched by income level, number of inhabitants, proportion of the active population engaged in farming, proportion of unemployed, percentage of illiteracy, and province. We selected reference towns at random from among all those that met the matching conditions. For all four nuclear fuel facilities, 99 and 97 towns in the exposed and reference zones respectively were included in the study, matched as above. The study covered 513,248 persons in the exposed zone for all types of installations. We took sociodemographic data from the 1991 census (12) and information on income levels from the Spanish Market Yearbook (Anuario del Mercado Espanol) (13).

Data specific to this study were supplied on computer files by the National Statistics Institute (Instituto Nacional de Estadistica, Madrid, Spain). Individual records were broken down by cause of death, sex, age group, year of death, and town of residence. Town-of-residence data for deceased persons are treated as confidential in Spain for towns having fewer than 10,000 inhabitants, so we obtained special permission from the National Statistics Institute for this study.

To obtain a population breakdown by sex, age, and year for towns included in the study, we referred to the 1981 population census, 1986 municipal roll, and 1991 census, as furnished by the National Statistics Institute. Relying on a log-linear polynomial regression model, we used interpolation to estimate annual municipal population figures for 1981-1991 (14). We extrapolated pre-1981 and post-1991 populations by adopting a linear procedure, allocating more weight to the nearest census year. With the annual population estimates for each town, we calculated person-years for each age band (0-4, 5-14, 15-24, 25-34, 35-44, 45-54, 55-64, 65-74, 75+), sex, and period (1975-1978, 1979-1983, 1984-1988, 1989-1993), taking into account variables that had changed over time, such as operational start-up of reactors and installations.

We fitted log-linear models on the assumption that the number of deaths per stratum followed a Poisson distribution. In these models, observed cases were the dependent variable. As an external standard (15), we used concurrent Spanish cause-specific mortality rates, with expected cases computed by age, sex, and period for each town in the exposed and reference (control) zones. Expected cases were included as offset in the models. A term we called "exposure" (a radius of 30 km or less from the facility), was included as the independent variable. The regression coefficient of this exposure term gave us the logarithm of the ratio between the respective standard mortality ratios (SMRs) for the exposed and reference zones, which we called "relative risk" (RR). This estimator was adjusted for age, sex, period, and matching variables.

We fitted similar models to study the effect of distance on mortality. We constructed this variable by categorizing distances in the 0- to 30-km belt into five levels (consisting of circular sectors having equal surface areas), and using towns situated at a distance of 50-100 km as the reference level. Expressed in kilometers, the cut-off points for the intervals were 0-, 13.4-, 19.6-, 23.2-, 26.8-30, and 50-100. This was included in all models both as a categoric and as a continuous variable (in kilometers). Thus, it was possible, for the former, to estimate the effect for the respective distances and, for the latter, to ascertain the existence of radial effects (rise in RR with increasing proximity to an installation) and, by applying the likelihood ratio test, the statistical significance of such distance-induced effects. The test was also applied to the 0-30-km area with the reference area excluded. We included matching variables in this analysis to ensure control of possible gradients in these variables with proximity to the installation. Given the heterogeneity of the installations, we ran specific analyses on individual and a joint analysis on all installations.

We studied changes in risk by comparing the positions before and after the date on which nuclear power plants and fuel facilities first came into operation (start-up), taking latency periods into account. These periods were included in the assessment of risk before start-up. The statistical significance of this change was obtained following two criteria: fitting a model that compares the SMRs before versus after start-up only for the 0-30 km areas; and a likelihood ratio test, which evaluates the interaction term--exposure x plant operation--in regression models, also including reference areas. The former evaluates time trends in exposed areas in contrast with trends at the national level, and the latter evaluates time trend differences between exposed and unexposed areas (reference areas).

We calculated relative risk confidence intervals (CIs) using the standard errors of the parameters yielded by the model. We checked and corrected model results for overdispersion problems (16) using the robust methods recommended by Breslow, because these methods are insensitive to the form adopted by variance (17).

Results

The socioeconomic characteristics and contribution in terms of person-years of populations residing near nuclear installations are described elsewhere (11). According to the 1991 census, the study population in the 30-km belt totaled 204,672 and 308,576 for nuclear power plants and fuel facilities, respectively.

Tables 1 and 2 show the number of observed deaths, SMRs, for the reference zones and areas in a radius of 0-15 and 0-30 km of each installation, and the RRs and CIs yielded by comparison with the reference zones, for both sexes and across all age groups, for the different causes studied. Table 3 shows relative risk by distance from the respective installations, for tumors causing at least 10 deaths in the study period. The results of the pre- and poststart-up analysis appear in Table 4.
Table 1. Comparison of cause-specific mortality in areas within a
15- and 30-km radius of nuclear power plants against that in reference
(control) towns lying within a radius of 50-100 km.

 Control 0-15 km 0-30 km
Installation/cause Obs SMR(a) Obs SMR(a) Obs SMR(a)

All power plants
 Lung 551 0.740 96 0.688 690 0.692
 Bones 28 0.956 7 1.289 38 0.966
 Breast (women) 206 0.834 23 0.538 298 0.911
 Brain 116 1.371 8 0.529 128 1.128
 Thyroid 11 0.921 0 0.000 8 0.507
 Bladder 142 0.800 21 0.619 197 0.835
 Ovary 40 0.771 3 0.336 55 0.804
 Connective tissue 10 0.655 3 1.120 24 1.180
 Kidney 66 1.089 14 1.251 75 0.931
 Stomach 460 1.088 86 1.076 612 1.085
 Colorectal 360 0.880 67 0.883 483 0.892
 All cancers 3,552 0.854 598 0.775 4,686 0.846
Zorita (1979-1993)
 Lung 128 0.621 35 0.644 145 0.647
 Bones 7 0.804 2 0.874 7 0.741
 Breast (women) 52 0.812 12 0.717 49 0.734
 Brain 42 1.790 2 0.327 26 1.068
 Thyroid 4 1.238 0 0.000 2 0.571
 Bladder 35 0.690 8 0.600 47 0.825
 Ovary 9 0.683 1 0.290 8 0.585
 Connective tissue 0 0.000 2 1.993 6 1.484
 Kidney 16 0.969 3 0.690 13 0.723
 Stomach 145 1.174 36 1.099 161 1.167
 Colorectal 91 0.810 31 1.046 117 0.943
 All cancers 947 0.817 247 0.810 1,040 0.820
Garona (1981-1993)
 Lung 208 0.762 16 0.410 234 0.613
 Bones 11 0.990 0 0.000 7 0.460
 Breast (women) 75 0.808 3 0.282 104 0.819
 Brain 46 1.441 2 0.525 50 1.134
 Thyroid 5 1.128 0 0.000 2 0.328
 Bladder 55 0.854 5 0.503 64 0.717
 Ovary 16 0.826 0 0.000 14 0.527
 Connective tissue 7 1.235 1 1.495 6 0.776
 Kidney 27 1.215 3 0.971 31 1.007
 Stomach 170 1.082 38 1.667 314 1.448
 Colorectal 111 0.739 13 0.609 161 0.778
 All cancers 1,354 0.882 128 0.597 1,709 0.805
Vandellos (1982-1993)
 Lung 163 0.793 38 1.006 264 0.790
 Bones 9 1.140 5 3.409 22 1.675
 Breast (women) 65 0.937 7 0.549 131 1.156
 Brain 22 0.949 4 0.909 46 1.175
 Thyroid 2 0.609 0 0.000 4 0.763
 Bladder 41 0.845 7 0.809 79 1.033
 Ovary 10 0.685 1 0.378 29 1.227
 Connective tissue 3 0.694 0 0.000 5 0.692
 Kidney 18 1.077 8 2.638 26 0.968
 Stomach 102 0.894 10 0.488 112 0.613
 Colorectal 126 1.121 19 0.945 171 0.960
 All cancers 980 0.858 187 0.901 1,656 0.900
Almaraz (1991-1993)
 Lung 52 0.863 7 0.823 47 0.824
 Bones 1 0.631 0 0.000 2 1.296
 Breast (women) 14 0.678 1 0.378 14 0.703
 Brain 6 0.994 0 0.000 6 1.025
 Bladder 11 0.788 1 0.502 7 0.528
 Ovary 5 1.064 1 1.636 4 0.885
 Connective tissue 0 0.000 0 0.000 7 5.215
 Kidney 5 0.969 0 0.000 5 1.016
 Stomach 43 1.537 2 0.517 25 0.939
 Colorectal 32 0.932 4 0.845 34 1.039
 All cancers 271 0.843 36 0.812 281 0.917

 0-15 km 0-30 km
Installation/cause RR(b) 95% CI RR(b) 95% CI

All power plants
 Lung 0.947 0.750-1.195 0.929 0.791-1.090
 Bones 1.355 0.590-3.112 0.967 0.593-1.577
 Breast (women) 0.633 0.412-0.974 1.066 0.892-1.273
 Brain 0.376 0.183-0.770 0.833 0.647-1.072
 Thyroid 0.000 -- 0.543 0.218-1.353
 Bladder 0.788 0.498-1.246 1.028 0.829-1.276
 Ovary 0.450 0.141-1.436 1.021 0.678-1.536
 Connective tissue 1.970 0.536-7.243 1.903 0.908-3.986
 Kidney 1.178 0.660-2.102 0.845 0.607-1.178
 Stomach 0.989 0.761-1.285 1.019 0.879-1.182
 Colorectal 0.995 0.766-1.293 1.010 0.881-1.158
 All cancers 0.911 0.825-1.006 0.987 0.918-1.063
Zorita (1979-1993)
 Lung 1.038 0.683-1.577 1.042 0.814-1.332
 Bones 1.087 0.227-5.205 0.922 0.324-2.620
 Breast (women) 0.884 0.475-1.646 0.905 0.614-1.334
 Brain 0.183 0.044-0.752 0.597 0.366-0.973
 Thyroid 0.000 -- 0.461 0.085-2.509
 Bladder 0.870 0.404-1.871 1.195 0.773-1.848
 Ovary 0.425 0.055-3.278 0.856 0.331-2.216
 Connective tissue -- -- -- --
 Kidney 0.713 0.208-2.445 0.747 0.359-1.552
 Stomach 0.936 0.648-1.351 0.994 0.785-1.259
 Colorectal 1.291 0.859-1.940 1.164 0.886-1.531
 All cancers 0.991 0.859-1.143 1.003 0.901-1.118
Garona (1981-1993)
 Lung 0.538 0.324-0.894 0.805 0.668-0.970
 Bones 0.000 -- 0.465 0.180-1.199
 Breast (women) 0.349 0.113-1.076 1.014 0.753-1.364
 Brain 0.364 0.089-1.485 0.786 0.528-1.170
 Thyroid 0.000 -- 0.291 0.057-1.495
 Bladder 0.590 0.238-1.458 0.839 0.586-1.203
 Ovary 0.000 -- 0.638 0.312-1.305
 Connective tissue 1.211 0.149-9.814 0.628 0.212-1.865
 Kidney 0.799 0.242-2.631 0.828 0.494-1.387
 Stomach 1.541 1.057-2.247 1.338 1.055-1.698
 Colorectal 0.823 0.464-1.461 1.053 0.827-1.341
 All cancers 0.677 0.535-0.857 0.913 0.776-1.075
Vandellos (1982-1993)
 Lung 1.269 0.963-1.672 0.996 0.768-1.292
 Bones 2.989 1.003-8.904 1.469 0.679-3.180
 Breast (women) 0.586 0.277-1.240 1.233 0.889-1.711
 Brain 0.958 0.330-2.780 1.239 0.593-2.587
 Thyroid 0.000 -- 1.254 0.230-6.842
 Bladder 0.958 0.430-2.133 1.223 0.839-1.781
 Ovary 0.551 0.071-4.290 1.792 0.879-3.653
 Connective tissue 0.000 -- 0.997 0.241-4.120
 Kidney 2.450 1.066-5.633 0.899 0.493-1.638
 Stomach 0.546 0.285-1.045 0.686 0.510-0.924
 Colorectal 0.843 0.567-1.254 0.857 0.669-1.097
 All cancers 1.050 0.925-1.193 1.049 0.946-1.163
Almaraz (1991-1993)
 Lung 0.953 0.384-2.368 0.954 0.619-1.469
 Bones 0.000 -- 2.054 0.189-22.370
 Breast (women) 0.557 0.074-4.180 1.036 0.494-2.172
 Brain 0.000 -- 1.032 0.333-3.199
 Bladder 0.638 0.085-4.795 0.670 0.260-1.726
 Ovary 1.537 0.182-12.989 0.832 0.223-3.097
 Connective tissue -- --
 Kidney 0.000 -- 1.048 0.303-3.620
 Stomach 0.337 0.083-1.372 0.611 0.339-1.100
 Colorectal 0.907 0.321-2.564 1.115 0.688-1.807
 All cancers 0.964 0.693-1.340 1.087 0.894-1.322

Obs, Observed cases. Latency period of 10 years.

(a) SMR is the ratio of the number of deaths observed and expected at
concurrent death rates in Spain. (b) RR compares the risk in study
versus control areas. The RR for combined facilities is obtained from
a regression model including the facilities as a factor, and differs
from the simple ratio of the SMRs.
Table 2. Comparison of cause-specific mortality in areas within a 15-
and 30-km radius of nuclear fuel facilities against that in reference
(control) towns lying within a radius of 50-100 km.

 Control 0-15 km 0-30 km
Installation/cause Obs SMR(a) Obs SMR(a) Obs SMR(a)

Nuclear fuel
facilities
 Lung 1,429 0.895 379 0.915 1,424 1.022
 Bones 51 0.685 18 0.918 66 1.017
 Breast (women) 471 0.789 122 0.805 436 0.858
 Brain 185 0.879 41 0.740 140 0.777
 Thyroid 17 0.619 7 0.998 24 1.002
 Bladder 331 0.887 56 0.581 251 0.760
 Ovary 70 0.578 22 0.720 95 0.925
 Connective tissue 38 1.100 4 0.452 20 0.684
 Kidney 114 0.856 32 0.932 136 1.171
 Stomach 892 0.892 225 0.869 752 0.849
 Colorectal 667 0.733 199 0.853 677 0.847
 All cancers 8,124 0.870 2,139 0.889 7,559 0.927
Andujar (1975-1993)
 Lung 686 0.768 291 0.927 670 0.954
 Bones 39 0.821 15 0.899 39 1.039
 Breast (women) 237 0.705 97 0.838 206 0.790
 Brain 111 0.877 34 0.749 75 0.747
 Thyroid 8 0.517 4 0.756 8 0.663
 Bladder 160 0.759 42 0.583 113 0.688
 Ovary 25 0.382 18 0.797 43 0.848
 Connective tissue 16 0.868 4 0.606 10 0.683
 Kidney 56 0.760 18 0.702 52 0.899
 Stomach 524 0.858 174 0.836 377 0.791
 Colorectal 342 0.672 138 0.795 320 0.806
 All cancers 4,282 0.799 1,617 0.873 3,646 0.870
El Cabril(c)
(1975-1993)
 Lung 259 1.124 -- -- 351 1.210
 Bones 5 0.410 -- -- 15 0.979
 Breast (women) 64 0.742 -- -- 117 1.094
 Brain 34 1.020 -- -- 37 0.964
 Thyroid 2 0.506 -- -- 6 1.149
 Bladder 55 1.035 -- -- 73 1.010
 Ovary 17 1.009 -- -- 30 1.456
 Connective tissue 5 1.018 -- -- 9 1.618
 Kidney 13 0.685 -- -- 31 1.279
 Stomach 100 0.651 -- -- 161 0.763
 Colorectal 93 0.720 -- -- 152 0.874
 All cancers 1,269 0.928 -- -- 1,845 1.037
La Haba (1987-1993)
 Lung 421 1.141 49 0.842 336 1.103
 Bones 7 0.578 1 0.553 10 1.044
 Breast (women) 150 1.068 10 0.481 87 0.798
 Brain 33 0.804 4 0.678 25 0.769
 Thyroid 5 0.792 3 2.998 9 1.782
 Bladder 98 1.174 7 0.497 54 0.777
 Ovary 21 0.680 3 0.650 20 0.827
 Connective tissue 16 1.781 0 0.000 1 0.143
 Kidney 44 1.400 13 2.595 49 1.911
 Stomach 183 0.983 31 1.021 162 1.070
 Colorectal 184 0.874 43 1.248 163 0.954
 All cancers 2,117 1.036 315 0.968 1,662 1.002
Ciudad Rodrigo
(1989-1993)
 Lung 63 0.603 39 0.930 67 0.699
 Bones 0 0.000 2 1.812 2 0.824
 Breast (women) 20 0.586 15 1.005 26 0.819
 Brain 7 0.725 3 0.732 3 0.341
 Thyroid 2 1.162 0 0.000 1 0.621
 Bladder 18 0.694 7 0.683 11 0.453
 Ovary 7 0.893 1 0.297 2 0.277
 Connective tissue 1 0.454 0 0.000 0 0.000
 Kidney 1 0.110 1 0.271 4 0.475
 Stomach 85 1.704 20 0.982 52 1.110
 Colorectal 48 0.779 18 0.714 42 0.725
 All cancers 456 0.809 207 0.898 406 0.774

 0-15 km 0-30 km
Installation/cause RR(b) 95% CI RR(b) 95% CI

Nuclear fuel
facilities
 Lung 1.123 0.953-1.324 1.124 1.015-1.246
 Bones 1.209 0.699-2.091 1.512 1.048-2.182
 Breast (women) 1.059 0.783-1.432 1.077 0.921-1.259
 Brain 0.862 0.609-1.220 0.875 0.702-1.090
 Thyroid 1.721 0.693-4.274 1.604 0.860-2.993
 Bladder 0.707 0.531-0.943 0.837 0.690-1.015
 Ovary 1.481 0.895-2.449 1.525 1.119-2.078
 Connective tissue 0.462 0.163-1.313 0.608 0.353-1.046
 Kidney 1.220 0.816-1.825 1.374 1.071-1.763
 Stomach 0.930 0.782-1.105 0.963 0.865-1.073
 Colorectal 1.205 0.989-1.470 1.153 1.009-1.317
 All cancers 1.064 0.964-1.175 1.056 1.000-1.114
Andujar (1975-1993)
 Lung 1.207 1.000-1.456 1.242 1.056-1.461
 Bones 1.095 0.604-1.984 1.265 0.813-1.970
 Breast (women) 1.188 0.856-1.649 1.121 0.887-1.416
 Brain 0.854 0.605-1.205 0.851 0.641-1.130
 Thyroid 1.461 0.444-4.810 1.281 0.481-3.413
 Bladder 0.768 0.581-1.015 0.906 0.718-1.145
 Ovary 2.087 1.141-3.819 2.220 1.358-3.628
 Connective tissue 0.698 0.234-2.082 0.787 0.359-1.722
 Kidney 0.924 0.543-1.570 1.184 0.812-1.726
 Stomach 0.975 0.805-1.180 0.922 0.792-1.073
 Colorectal 1.183 0.904-1.549 1.200 0.966-1.491
 All cancers 1.093 0.970-1.231 1.088 1.002-1.183
El Cabril(c)
(1975-1993)
 Lung -- -- 1.077 0.858-1.351
 Bones -- -- 2.389 0.870-6.557
 Breast (women) -- -- 1.476 1.085-2.007
 Brain -- -- 0.945 0.594-1.506
 Thyroid -- -- 2.270 0.459-11.236
 Bladder -- -- 0.976 0.661-1.442
 Ovary -- -- 1.443 0.796-2.615
 Connective tissue -- -- 1.590 0.533-4.744
 Kidney -- -- 1.866 0.853-4.082
 Stomach -- -- 1.171 0.911-1.505
 Colorectal -- -- 1.214 0.940-1.567
 All cancers -- -- 1.117 0.993-1.257
La Haba (1987-1993)
 Lung 0.738 0.553-0.984 0.967 0.835-1.120
 Bones 0.957 0.118-7.764 1.806 0.691-4.718
 Breast (women) 0.451 0.187-1.089 0.747 0.554-1.009
 Brain 0.844 0.302-2.363 0.957 0.569-1.608
 Thyroid 3.787 0.905-15.838 2.251 0.755-6.713
 Bladder 0.424 0.158-1.134 0.662 0.396-1.104
 Ovary 0.956 0.285-3.199 1.216 0.660-2.243
 Connective tissue 0.000 -- 0.080 0.011-0.602
 Kidney 1.853 0.999-3.439 1.365 0.852-2.189
 Stomach 1.038 0.709-1.519 1.088 0.881-1.344
 Colorectal 1.428 1.025-1.989 1.091 0.870-1.369
 All cancers 0.935 0.817-1.070 0.967 0.894-1.047
Ciudad Rodrigo
(1989-1993)
 Lung 1.544 1.036-2.302 1.160 0.764-1.762
 Bones -- -- -- --
 Breast (women) 1.716 0.879-3.351 1.398 0.781-2.505
 Brain 1.010 0.262-3.894 0.471 0.122-1.820
 Thyroid 0.000 -- 0.534 0.048-5.879
 Bladder 0.984 0.411-2.356 0.653 0.309-1.382
 Ovary 0.332 0.042-2.646 0.310 0.065-1.492
 Connective tissue -- -- -- --
 Kidney 2.463 0.154-39.367 4.314 0.496-37.546
 Stomach 0.576 0.354-0.938 0.651 0.461-0.920
 Colorectal 0.917 0.533-1.576 0.930 0.615-1.407
 All cancers 1.109 0.885-1.391 0.956 0.745-1.226

Obs, Observed cases. Latency period of 10 years.

(a) SMR is the ratio of the number of deaths observed and expected at
concurrent death rates in Spain. (b) RR compares the risk in study
versus control areas. The RR for combined facilities is obtained from
a regression model including the facilities as a factor, and differs
from the simple ratio of the SMRs.
(c) No towns within 15 km of the installation.
Table 3. Relative risks according to distance of population centroids
from nuclear power plants and fuel facilities, with test for trend.

 Distance
Reference > 50 km 19-23.1 13.4-18.9
Installation/cause 26.8-30 km 23.2-26.7 km km km

All power plants
 Lung 0.816 0.896 1.034 0.827
 Bones 0.541 1.223 1.026 1.215
 Breast (women) 0.965 1.108 1.233 1.008
 Brain 0.870 0.415 0.912 0.993
 Bladder 1.096 1.231 1.039 0.982
 Ovary 0.844 1.345 0.961 1.527
 Kidney 0.588 0.404 0.798 1.478
 Stomach 1.042 0.980 0.992 1.074
 Colorectal 1.129 0.917 0.992 0.916
 All cancers 0.929 0.984 1.021 1.030
Zorita
 Lung 1.052 0.982 1.258 0.892
 Breast (women) 1.008 0.633 0.938 0.649
 Brain 0.893 0.000 0.599 1.556
 Bladder 1.393 1.197 1.601 0.918
 Kidney 0.296 0.737 0.678 3.150
 Stomach 1.263 0.947 0.981 0.951
 Colorectal 1.220 0.984 1.274 1.188
 All cancers 0.978 0.973 1.094 1.046
Garona
 Lung 0.559 0.854 0.957 0.905
 Breast (women) 0.652 0.492 1.232 0.769
 Brain 0.889 0.925 0.899 0.313
 Bladder 0.615 0.665 0.505 0.970
 Kidney 0.686 0.002 0.714 0.492
 Stomach 1.215 1.455 1.206 1.643
 Colorectal 1.092 1.772 1.087 0.714
 All cancers 0.808 0.948 0.880 0.862
Vandellos
 Lung 0.904 1.067 1.104 1.058
 Bones 0.808 3.519 1.632 3.054
 Breast (women) 1.540 1.607 1.162 1.001
 Brain 1.123 1.012 1.862 1.290
 Bladder 1.407 1.733 1.085 0.907
 Ovary 1.673 3.040 1.494 3.554
 Kidney 0.463 0.193 0.555 0.839
 Stomach 0.764 0.870 0.715 1.065
 Colorectal 1.272 0.752 0.732 0.910
 All cancers 1.068 1.106 1.068 1.139
Almaraz
 Lung 0.742 0.001 1.376 0.739
 Breast (women) 1.629 3.496 1.174 0.785
 Stomach 0.371 0.001 0.199 1.207
 Colorectal 0.947 0.001 3.064 0.842
 All cancers 0.988 0.378 1.393 1.055
Nuclear fuel
facilities
 Lung 1.077 1.164 1.073 1.172
 Bones 1.953 1.487 1.276 1.816
 Breast (women) 0.920 1.487 1.014 0.979
 Brain 0.898 0.603 0.838 1.026
 Thyroid 1.880 0.002 1.852 1.937
 Bladder 0.744 1.090 0.778 1.026
 Ovary 1.821 1.563 1.451 1.058
 Kidney 1.434 2.113 1.210 1.327
 Stomach 0.916 1.028 1.026 0.939
 Colorectal 1.072 1.361 1.045 1.268
 All cancers 1.010 1.139 1.014 1.073
Andujar
 Lung 1.060 1.361 1.254 1.415
 Bones 2.189 2.329 0.966 1.721
 Breast (women) 0.778 1.126 1.115 2.052
 Brain 0.810 0.732 1.006 0.414
 Bladder 1.096 0.952 0.907 1.536
 Ovary 2.204 3.464 2.325 1.439
 Kidney 2.013 2.013 1.054 0.437
 Stomach 0.919 1.045 0.955 0.606
 Colorectal 1.349 1.377 1.110 1.737
 All cancers 1.026 1.127 1.091 1.277
El Cabril
 Lung 0.880 1.941 0.689 1.922
 Bones 2.283 0.039 9.312 31.621
 Breast (women) 1.276 6.283 1.694 3.320
 Brain 0.940 1.027 0.892 1.481
 Bladder 0.574 1.305 0.644 2.207
 Ovary 1.702 3.376 0.169 1.186
 Kidney 4.620 6.760 10.837 11.892
 Stomach 0.898 1.848 0.957 2.806
 Colorectal 0.996 2.060 1.234 1.487
 All cancers 0.962 2.202 0.921 1.587
La Haba
 Lung 0.943 0.856 1.101 0.956
 Bones 3.590 0.002 1.299 1.651
 Breast (women) 0.817 0.728 1.048 0.648
 Brain 0.396 0.003 0.906 1.094
 Bladder 0.586 2.290 0.416 0.811
 Ovary 1.807 0.010 2.611 0.919
 Kidney 0.995 0.002 1.653 1.330
 Stomach 0.921 1.402 1.364 1.010
 Colorectal 1.002 0.001 1.042 1.198
 All cancers 0.910 0.781 1.073 0.961
Ciudad Rodrigo
 Lung 0.714 0.582 1.851 1.334
 Breast (women) 0.593 1.266 0.737 2.287
 Bladder 0.000 1.090 1.007 0.000
 Stomach 0.784 0.874 0.806 0.671
 Colorectal 1.183 1.007 0.268 1.588
 All cancers 0.889 0.974 1.029 0.964

 p-Value for trend
Reference > 50 km Distance Exposed area Exposed and
Installation/cause 0-13.3 km only reference areas

All power plants
 Lung 1.049 0.4881 0.0854
 Bones 1.595 0.1210 0.6447
 Breast (women) 0.721 0.3767 0.3594
 Brain 0.427 0.1993 0.1802
 Bladder 0.728 0.1612 0.8061
 Ovary 0.521 0.7689 0.2773
 Kidney 1.284 0.0065 0.2872
 Stomach 1.004 0.9288 0.9314
 Colorectal 1.010 0.3452 0.8983
 All cancers 0.961 0.4573 0.2080
Zorita
 Lung 1.136 0.9719 0.8483
 Breast (women) 0.981 0.9948 0.4642
 Brain 0.194 0.2467 0.4857
 Bladder 0.876 0.2522 0.5501
 Kidney 0.549 0.3246 0.2937
 Stomach 0.983 0.2101 0.5722
 Colorectal 1.230 0.9011 0.1626
 All cancers 1.013 0.7640 0.8231
Garona
 Lung 0.727 0.0903 0.0631
 Breast (women) 0.693 0.0787 0.3924
 Brain 0.515 0.3521 0.2508
 Bladder 0.611 0.9103 0.0128
 Kidney 1.527 0.1577 0.2624
 Stomach 1.749 0.0280 0.0036
 Colorectal 0.829 0.1475 0.7998
 All cancers 0.846 0.2270 0.0001
Vandellos
 Lung 1.315 0.5478 0.7494
 Bones 3.622 0.0740 0.0432
 Breast (women) 0.519 0.0296 0.3359
 Brain 1.415 0.3156 0.6061
 Bladder 0.952 0.5487 0.4473
 Ovary 0.427 0.1842 0.6466
 Kidney 2.039 0.0019 0.4970
 Stomach 0.553 0.8251 0.0344
 Colorectal 0.918 0.2919 0.7669
 All cancers 1.044 0.7296 0.0849
Almaraz
 Lung 1.443 0.6561 0.4659
 Breast (women) 0.766 0.3761 0.7295
 Stomach 0.541 0.7098 0.0249
 Colorectal 0.940 0.3765 0.6772
 All cancers 1.102 0.3850 0.7145
Nuclear fuel
facilities
 Lung 1.113 0.6564 0.2313
 Bones 1.233 0.2510 0.0353
 Breast (women) 1.182 0.1435 0.7317
 Brain 0.866 0.8540 0.1153
 Thyroid 1.402 0.5036 0.1987
 Bladder 0.713 0.6837 0.0098
 Ovary 1.485 0.2658 0.0209
 Kidney 1.317 0.3683 0.0066
 Stomach 0.962 0.7711 0.7905
 Colorectal 1.121 0.9606 0.0510
 All cancers 1.073 0.3005 0.1819
Andujar
 Lung 1.106 0.7278 0.1446
 Bones 1.484 0.4531 0.0852
 Breast (women) 1.188 0.1533 0.4396
 Brain 0.796 0.7472 0.2566
 Bladder 0.792 0.5245 0.2361
 Ovary 2.381 0.8357 0.0010
 Kidney 1.019 0.0455 0.3409
 Stomach 1.059 0.7610 0.7349
 Colorectal 1.232 0.9096 0.0716
 All cancers 1.087 0.3930 0.0305
El Cabril
 Lung -- 0.5973 0.6611
 Bones -- 0.6478 0.0769
 Breast (women) -- 0.8897 0.1916
 Brain -- 0.5623 0.6127
 Bladder -- 0.3417 0.0125
 Ovary -- 0.2202 0.3496
 Kidney -- 0.5855 0.0015
 Stomach -- 0.1553 0.8829
 Colorectal -- 0.5405 0.5016
 All cancers -- 0.5087 0.9713
La Haba
 Lung 0.920 0.8782 0.4601
 Bones 0.001 0.3149 0.1859
 Breast (women) 0.768 0.6401 0.0188
 Brain 1.136 0.2393 0.4265
 Bladder 0.373 0.5640 0.1575
 Ovary 1.068 0.3564 0.3906
 Kidney 3.281 0.2138 0.0498
 Stomach 1.130 0.9893 0.5535
 Colorectal 1.260 0.2678 0.3414
 All cancers 1.089 0.2641 0.3495
Ciudad Rodrigo
 Lung 1.493 0.0502 0.1446
 Breast (women) 1.742 0.3510 0.1627
 Bladder 0.799 0.6358 0.3950
 Stomach 0.518 0.3541 0.0173
 Colorectal 0.987 0.9753 0.9677
 All cancers 1.061 0.9377 0.6539

Only tumor sites with 10 or more observed deaths are shown. Estimates
have been adjusted for matching variables. The most distant towns
(radius 50-100 km) are taken as reference.
Table 4. Estimated relative risk for study areas (0-30 km) before and
after the date on which nuclear facilities first came into operation
(before and after start-up).

 Before start-up After start-up
Installation/cause Obs SMR(a) Obs SMR

Zorita 1975-1978(d) 1979-1993
 Lung 21 0.435 145 0.647
 Bones 7 1.752 7 0.741
 Breast (women) 9 0.576 49 0.734
 Brain 8 1.135 26 1.068
 Thyroid 0 0.000 2 0.571
 Bladder 5 0.346 47 0.825
 Ovary 1 0.472 8 0.585
 Connective tissue 0 0.000 6 1.484
 Kidney 4 1.014 13 0.723
 Stomach 67 1.159 161 1.167
 Colorectal 27 0.791 117 0.943
 All cancers 269 0.777 1,040 0.820
Garona 1975-1980 1981-1993
 Lung 53 0.425 234 0.613
 Bones 7 0.685 7 0.460
 Breast (women) 35 0.760 104 0.819
 Brain 22 0.982 50 1.134
 Thyroid 0 0.000 2 0.328
 Bladder 20 0.620 64 0.717
 Ovary 6 0.858 14 0.527
 Connective tissue 1 0.560 6 0.776
 Kidney 4 0.396 31 1.007
 Stomach 152 1.197 314 1.448
 Colorectal 53 0.683 161 0.778
 All cancers 632 0.743 1,709 0.805
Vandellos 1975-1981 1982-1993
 Lung 80 0.583 264 0.790
 Bones 7 0.631 22 1.675
 Breast (women) 20 0.399 131 1.156
 Brain 28 1.085 46 1.175
 Thyroid 2 0.815 4 0.763
 Bladder 26 0.753 79 1.033
 Ovary 4 0.513 29 1.227
 Connective tissue 2 0.935 5 0.692
 Kidney 13 1.178 26 0.968
 Stomach 80 0.608 112 0.613
 Colorectal 64 0.792 171 0.960
 All cancers 683 0.747 1,656 0.900
Almaraz 1975-1990 1991-1993
 Lung 244 1.075 47 0.824
 Bones 10 0.738 2 1.296
 Breast (women) 62 0.750 14 0.703
 Brain 24 0.718 6 1.025
 Thyroid 2 0.504 0 0.000
 Bladder 31 0.559 7 0.528
 Ovary 13 0.849 4 0.885
 Connective tissue 3 0.675 7 5.215
 Kidney 21 1.132 5 1.016
 Stomach 216 1.261 25 0.939
 Colorectal 104 0.793 34 1.039
 All cancers 1,359 0.968 281 0.917
La Haba 1975-1986 1987-1993
 Lung 424 1.106 336 1.103
 Bones 33 1.227 10 1.044
 Breast (women) 136 0.923 87 0.798
 Brain 54 0.834 25 0.769
 Thyroid 2 0.289 9 1.782
 Bladder 51 0.556 54 0.777
 Ovary 19 0.741 20 0.827
 Connective tissue 2 0.288 1 0.143
 Kidney 30 0.969 49 1.911
 Stomach 346 1.082 162 1.070
 Colorectal 215 0.976 163 0.954
 All cancers 2,301 0.937 1,662 1.002

Ciudad Rodrigo 1975-1988 1989-1993
 Lung 103 0.511 67 0.699
 Bones 14 1.121 2 0.824
 Breast (women) 53 0.770 26 0.819
 Brain 35 1.283 3 0.341
 Thyroid 1 0.284 1 0.621
 Bladder 28 0.525 11 0.453
 Ovary 5 0.411 2 0.277
 Connective tissue 1 0.297 0 0.000
 Kidney 17 1.050 4 0.475
 Stomach 250 1.491 52 1.110
 Colorectal 111 0.922 42 0.725
 All cancers 1,052 0.821 406 0.774

 After vs. before Trend
 start-up differences
Installation/cause RR(b) p-Value p-Value(c)
Zorita
 Lung 1.486 0.0893 0.9677
 Bones 0.423 0.1070 0.7483
 Breast (women) 1.274 0.5008 0.9585
 Brain 0.942 0.8815 0.2386
 Thyroid -- 0.7805 0.3726
 Bladder 2.384 0.0617 0.1470
 Ovary 1.240 0.8393 --(e)
 Connective tissue -- 0.7687 --
 Kidney 0.713 0.5540 0.1634
 Stomach 1.008 0.9579 0.7370
 Colorectal 1.192 0.4095 0.5082
 All cancers 1.055 0.4310 0.4772
Garona
 Lung 1.443 0.0158 0.4047
 Bones 0.672 0.4566 0.6727
 Breast (women) 1.077 0.7027 0.9374
 Brain 1.154 0.5745 0.5616
 Thyroid -- 0.6062 --
 Bladder 1.156 0.5691 0.3785
 Ovary 0.614 0.3179 0.1555
 Connective tissue 1.386 0.7613 --
 Kidney 2.544 0.0785 0.6044
 Stomach 1.210 0.0539 0.0700
 Colorectal 1.140 0.4070 0.4535
 All cancers 1.084 0.0840 0.3868
Vandellos
 Lung 1.355 0.0173 0.7829
 Bones 2.655 0.0232 0.2687
 Breast (women) 2.893 0.0000 0.0028
 Brain 1.083 0.7370 0.5890
 Thyroid 0.936 0.9387 --
 Bladder 1.372 0.1615 0.8312
 Ovary 2.392 0.1003 0.0812
 Connective tissue 0.740 0.7167 0.9176
 Kidney 0.822 0.5613 0.1109
 Stomach 1.009 0.9509 0.2727
 Colorectal 1.213 0.1873 0.6208
 All cancers 1.205 0.0000 0.7180
Almaraz
 Lung 0.766 0.0943 0.4455
 Bones 1.757 0.4662 0.3927
 Breast (women) 0.937 0.8265 0.6404
 Brain 1.428 0.4354 0.4406
 Thyroid 0.000 0.8094 --
 Bladder 0.945 0.8918 0.4909
 Ovary 1.043 0.9413 0.6632
 Connective tissue 7.730 0.0030 --
 Kidney 0.897 0.8276 0.9145
 Stomach 0.744 0.1616 0.2143
 Colorectal 1.311 0.1708 0.1766
 All cancers 0.947 0.4010 0.3964
La Haba
 Lung 0.997 0.9769 0.7334
 Bones 0.851 0.6533 0.4513
 Breast (women) 0.865 0.2901 0.4998
 Brain 0.922 0.7361 0.8611
 Thyroid 6.173 0.0198 0.0364
 Bladder 1.397 0.0866 0.2231
 Ovary 1.116 0.7312 0.6459
 Connective tissue 0.495 0.5651 0.4995
 Kidney 1.973 0.0033 0.1476
 Stomach 0.989 0.9054 0.3746
 Colorectal 0.977 0.8264 0.9546
 All cancers 1.069 0.0389 0.0727
Ciudad Rodrigo
 Lung 1.370 0.0451 0.1229
 Bones 0.735 0.6840 --
 Breast (women) 1.063 0.7993 0.7471
 Brain 0.266 0.0256 0.0875
 Thyroid 2.184 0.5807 0.7158
 Bladder 0.863 0.6781 0.1765
 Ovary 0.675 0.6383 0.5592
 Connective tissue 0.000 0.7792 --
 Kidney 0.453 0.1484 0.1459
 Stomach 0.745 0.0530 0.0478
 Colorectal 0.786 0.1842 0.5707
 All cancers 0.942 0.3034 0.9700

Obs, observed deaths. (a) SMR is the ratio of the number of deaths
observed and expected at concurrent death rates in Spain. (b) RR
compares SMRs after versus before start-up in the exposed areas;
p-value corresponds to the statistical significance of this RR.
(c) Statistical significance for time trend differences between
exposed and unexposed areas. (d) Years included. (e) No cases in the
reference area.


In the vicinity of the Sta M. de Garona nuclear power plant (Burgos) (Table 1) an RR of 1.34 (95% CI, 1.06-1.70) was observed for stomach cancer, with the relative risk similar for men and women (data not shown). In Vandellos, excess renal and bone cancer was in evidence in the 15-km belt. For the Zorita area, six deaths occurred from connective tissue tumors, versus no deaths in the reference area. Four of these were men and two were women. Four of the cases resided in towns more than 19 km from the plant. Almaraz had somewhat similar conditions, with seven deaths from connective tissue tumors versus none in the reference area. Six of these cases were men and occurred in towns lying 26-30 km from the plant. Three people died before start-up (Table 4).

Overall, we observed no excess mortality for tumor sites as a whole in areas around nuclear power plants in Spain (Table 1). The highest relative risk was registered for connective tissue tumors (RR 1.90 95%; CI, 0.91-3.99), with 13 cases reported in the Almaraz and Zorita areas.

In the near-versus-far analysis of all fuel cycle facilities as a whole (Table 2), we detected statistically significant excess mortality for lung, bone, ovarian, renal, and colorectal cancer.

Examination of the results by facility showed excess cancer mortality of almost 9% in the area surrounding the Andujar plant. This excess was attributable to higher-than-expected lung, ovarian, and colorectal cancer mortality.

The El Cabril area registered a statistically significant excess breast cancer mortality among women (RR 1.48; 95% CI, 1.09-2.01). Comparison between the 15-km radius around the La Haba plant and the reference area showed a higher risk of colorectal cancer mortality (RR 1.43; 95% CI, 1.03-1.49), an RR of 1.85 (95% CI, 1.00-3.44) for renal cancer, and an RR of 3.79 (95% CI, 0.91-15.84) for thyroid cancer. Renal cancer registered an SMR that was almost 2 vis-a-vis the national reference and was statistically significant.

The most noteworthy finding in the Ciudad Rodrigo area was the higher risk of death from lung cancer observed for all towns nearest (0-15 km) the installation (RR 1.54; 95% CI, 1.04-2.30).

The RR point estimator for renal cancer exceeded 1 for all areas surrounding uranium cycle facilities. Overall, we observed excess cancer mortality (for all tumor sites as a whole) for fuel cycle facilities, in great measure reflecting excess lung cancer among men.

Analysis of mortality in relation to distance from any given installation yielded results that differed widely according to the radius of application of the statistical test used. Two different tests are included in Table 3: The first ascertains the statistical significance of the slope of relative risk solely in the exposed area, whereas the second addresses the entire study area. In Garona, stomach cancer plotted a statistically significant gradient with both tests. Similarly, for bone cancer, there appears to be a risk gradient proportional to the proximity to Vandellos. For renal cancer in Garona and Vandellos, the highest risks corresponded to the area closest to the installation, thus accounting for the statistical significance of the test for the exposed area in Vandellos and for the joint analysis of all four nuclear power plants (Table 3).

The different limitations of these two statistical tests can be observed better in Table 3, in which analysis of all fuel cycle facilities is displayed jointly. The statistical significance of the test covering the entire study area is in sharp contrast to the RR estimators for the different distances, in that these show no gradient with proximity to the installation. None of the statistical tests covering the entire study area were confirmed when applied to the 30-km radius. The El Cabril risk estimators for renal cancer were determined by the low number of cases in towns lying nearest the plant and the stringent stratification applied in the analysis. The greatest number of cases (22 of 31) occurred in the most distant towns ([is greater than] 26 km), so that estimates in the nearest sectors were made on the basis of 2, 4, and 3 deaths respectively and thus exhibit a very low degree of accuracy.

Analysis of nuclear power plants before and after start-up in Garona showed an increase in stomach cancer after the plant began operating, though this increase was just on the limit of statistical significance (Table 4). In Vandellos, we observed a rise in breast cancer mortality in women after the plant's commissioning, and in Almaraz an increase of connective tissue cancer mortality. Regarding uranium cycle facilities, no statistically significant changes could be demonstrated for any of the tumors studied, except for thyroid cancer in the vicinity of La Haba.

In evaluating time trends, it is advisable to highlight the different results obtained by the two analyses proposed. Thus, lung cancer mortality showed a greater increase in the exposed areas of Garona, Vandellos, and Zorita, compared with the national trend, and the same was true for renal cancer in La Haba. However, it would be risky to attribute these increases to the effect of the nuclear facilities, since the corresponding unexposed areas presented a similar pattern, as is suggested by the p-value in the last column of Table 4.

Discussion

Overall, the results of the study indicate a cancer mortality pattern in areas adjacent to uranium cycle facilities that is basically characterized by excess deaths due to renal and lung cancer [and leukemias (11)]. These results may well be evincing the influence exerted on public health by the environmental impact of mining activities and the effects of natural radiation.

In this exploratory study, we have sought to estimate risk of death for 11 different tumor sites in the vicinity of 8 installations. For many of these, we analyzed different areas and time periods, thereby allowing for numerous comparisons. The results must therefore be interpreted with caution, because some of the statistically significant mortality excesses or deficits found may be attributable to chance.

The validity of death-certificate diagnoses for investigating cancer is generally accepted (2,3,18,19). Except for Tarragona, none of the provinces studied are equipped with population-based cancer registries that would otherwise enable cancer incidence to be studied in these areas. In the calculation of person-years, interpolation and extrapolation techniques had to be employed. We applied these techniques in the same way to all provinces and towns included in the various studies. Hence, any possible deviations inherent in the estimates, will be equally present in all areas compared.

Specific methodologic problems are posed by investigation into relatively rare diseases in areas adjacent to sources of contamination. The importance of ascertaining disease-frequency and -distribution in other areas similar in size to those being studied has been stressed (20), which we followed in our design. In general, the areas compared in this study were rural. We matched reference towns to exposed towns by sociodemographic variables; the towns would thus indirectly maintain their comparability in diagnostic accuracy and accessibility to the health care system. Sociodemographic information for the entire study period was not available. However, bearing in mind the universal character of the Spanish National Health System, there would be no reason to suspect differential access to health care and diagnosis between exposed and reference areas.

In theoretical terms, comparison of SMRs is open to criticism in that, internally, the SMRs use different standard populations. Nevertheless, analysis based on comparison of mortality rates (rate ratios) via models that use person-years as offset and include age yielded equivalent results.

The study of the distance variable seeks to associate mortality with the nuclear installation as the putative source of contamination. Distance to the installation tends to be used as a surrogate variable for exposure in cases where dosimetric information or the radiologic history of an installation's environs is not forthcoming (21,22). Indeed in this respect the study is ecologic, in that individual levels of exposure are unknown and the inhabitants of any given town are thus implicitly assumed to have received similar exposures. There will inevitably be persons who have resided for part of their lives in exposed towns and then moved to nonexposed areas, and vice versa, which would produce nondifferential misclassification errors. Moreover, information is lacking on other risk factors associated with these tumors, such as smoking or exposure to chemical agents, although we sought to control for these partly by the town matching incorporated into the overall design.

In the Garona area an unexpected, higher risk of stomach cancer was detected in both sexes, apparently linked to proximity to the nuclear power plant. Moreover, there was a parallel deficit in lung cancer mortality in this same area. This coincidence is reminiscent of the documented cancer mortality pattern in farmers (23) and could be interpreted as a design failure (matching by proportion of farmers) to control for this component. Yet it is strange that this should occur solely in the Garona area and not in the surroundings of other installations. This, coupled with the fact that Garona is situated in Burgos province--a province with the highest stomach cancer mortality in Spain--impels us to recommend an in-depth study. It would also be advisable to analyze bone and renal cancer incidence in the vicinity of Vandellos, because associated mortality proved higher than expected in towns lying nearest the plant, although admittedly this observation was based on very few cases.

The Zorita and Almaraz areas display an excess of cases of connective tissue cancer. Taking Spain as reference, the respective SMRs are 1.48 (95% CI, 0.55-3.23) for Zorita and 5.22 (95% CI, 2.09-10.75) for Almaraz. Nonetheless, the location of these cases (mostly residents of towns situated on the limits of the study area) and the fact that cases had already been reported in this sector before start-up (Table 4), leads us to think that the causes probably lie outside the Almaraz plant, although this result, too, would appear to call for closer study.

In the literature, it is difficult to find studies that have evaluated and published nonhematologic tumor incidence and/or mortality for areas neighboring NPP, and more difficult still for areas neighboring NFF. The standard practice is to group these under the heading of "other tumors" or "solid tumors," and the findings published for this umbrella group are generally negative. Consequently, the information to which we could turn to compare our results was very limited.

We should like to stress the differences in our results between the mortality patterns around NPP and those around NFF. In the vicinity of NFF, we detected an excess risk of cancer-related death of 5.6%. This excess is, in great part, determined by lung cancer mortality, which we observed exclusively in men (RR 1.14; 95% CI, 1.03-1.27) and has been detected in the Andujar and Ciudad Rodrigo areas. In the previous study, we reported a higher risk of leukemias in these same areas (11). To challenge the feasibility that tobacco use has any influence on this result--and given that smoking frequencies could not be included in the analysis--one could point to the fact that there was no parallel rise in bladder cancer mortality, a tumor likewise associated with cigarette smoking.

NFF are located in areas with uranium deposits, areas where mining operations are carried out and nuclear fuel is manufactured. A cytogenetic analysis showed a greater frequency of chromosomal aberrations and an abnormal DNA-repair response for a population residing near mines/uranium processing plants versus an unexposed population, though this was based on a small study (24,25).

Underlying the findings for areas near NFF are two phenomena: One concerns the lung-cancer--related deaths observed in men, which could be occupational in origin; this problem has been well documented (26) thanks to cohort studies covering miners in the uranium industry (27) and (underground) miners in general (28). The other phenomenon stems from environmental exposure to radon produced by the degradation of uranium-238 present in the soil of granite areas, and to natural radiation (an aspect that could not be controlled for in this study) and radioactive waste; and from the consequences of mining activities on the population (24). Arguably, each installation might have its own peculiarities, thus highlighting the limits on the ability of any generic radiobiologic-impact assessment to reflect the conditions of all uranium facilities (10).

In refining the ore to produce uranium concentrates, a great volume of hazardous waste is generated, known as tailings. These tailings are often dumped outdoors. Such waste contains most of the radionuclides that are produced by uranium degradation and continue to be radioactive for hundreds of years, plus variable quantities of other toxic substances, which are either present in the mineral (e.g., heavy metals) or used in extraction. Radionuclides and chemical toxics can be dispersed more easily from such dumps than they could from their original state in the ore, as a result of hydrologic and atmospheric processes (29), containment-dam disasters, and the possibility of improper use in the preparation of construction materials. Danger of contamination from tailings is heightened when dumps are abandoned following mine closure. To our knowledge, there is not one single site anywhere in the world in which a uranium mine has been satisfactorily cleaned.

Residential exposure to radon is an important cause of lung cancer in the general population (7,26). The interaction between radon exposure and smoking with regard to lung cancer exceeded additivity and approaches a multiplicative effect (30).

Similarly noteworthy is the higher risk of death due to renal cancer, a tumor that registers point effect indicators exceeding 1 for all NFF studied. Excess risk is higher in women (RR 1.81; 95% CI, 1.21-2.73) than in men (RR 1.16; 95% CI, 0.84-1.59). Although these results are difficult to interpret in environmental terms, renal toxicity is known to be the most adverse side effect of exposure to uranium (31). Dosimetric studies of radon exposure have shown that the kidney receives the second highest doses after the lung (7), and animal studies have shown that radon exposure can cause renal cancer (32). Furthermore, some results indicate that residence in the proximity of mill tailings raises the frequency of chromosomal aberrations and DNA-repair deficiencies (29).

In addition to lung cancer, exposure to radon has been associated with other types of tumors (33-35), though there are studies that conclude the contrary (7). International incidence of myeloid leukemia, renal cancer, and certain childhood cancers shows a significant correlation with radon exposure in the home (33). In one case--control study undertaken in Italy to evaluate the effect of radon levels, odds ratios of 2-3 were found for renal cancer, in tandem with a statistically significant dose--response relationship (34). The existence of a high risk for this tumor has also been reported for employees of the atomic weapons establishment (35).

Given the nature of our study, any comments that we might advance to explain these findings would, in part, be speculative. Nevertheless, we believe that besides the effects of natural radiation, the results for NFF could well be evincing the influence exerted on public health by the environmental impact of uranium mining. It is therefore essential that mechanisms be established to monitor the incidence of cancer in provinces in which these two types of facilities are found. We likewise recommend that besides nuclear power plants as such, all radiologic and environmental monitoring devices and systems deployed in areas adjacent to installations should also cover uranium cycle facilities and mill tailings, and that the ensuing measurements be made public. Design of any future studies will require dosimetric measurements for areas surrounding such facilities, efforts to reconstruct history of exposure, and an attempt to study the problem from a multidisciplinary point of view, using biologic exposure markers.

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Address correspondence to G. Lopez-Abente, Area de Epidemiologia Ambiental y Cancer, Centro Nacional de Epidemiologia, Instituto de Salud Carlos III, Sinesio Delgado 6, 28029 Madrid, Spain. Telephone: 34-91-387 78 02. Fax: 34-91-387 78 15. E-mail: glabente@isciii.es

This study was financed in part by grant 96/300 from the Fondo de Investigacion Sanitaria (Health Research Fund). The work of N. Aragones was supported by the Instituto de Salud Carlos III (grant No 97/4004).

Received 21 November 2000; accepted 12 January 2001.

Gonzalo Lopez-Abente, Nuria Aragones, and Marina Pollan

Cancer Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain
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Date:Jul 1, 2001
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