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


To ascertain solid tumor tumor: see neoplasm.  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 illiteracy, inability to meet a certain minimum criterion of reading and writing skill. Definition of Illiteracy


The exact nature of the criterion varies, so that illiteracy must be defined in each case before the term can be used in a meaningful
, and province). Using log-linear models log-linear model

a statistical model which models frequency counts in contingency tables by using an analysis of variance approach.
, 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 uranium (yrā`nēəm), radioactive metallic chemical element; symbol U; at. no. 92; at. wt. 238.0289; m.p. 1,132°C;; b.p. 3,818°C;; sp. gr. 19.  cycle facilities, basically characterized char·ac·ter·ize  
tr.v. character·ized, character·iz·ing, character·iz·es
1. To describe the qualities or peculiarities of: characterized the warden as ruthless.

2.
 by excess lung [relative risk (RR) 1.12, 95% confidence interval confidence interval,
n a statistical device used to determine the range within which an acceptable datum would fall. Confidence intervals are usually expressed in percentages, typically 95% or 99%.
 (CI), 1.02-1.25] and renal renal /re·nal/ (re´n'l) pertaining to the kidney.

re·nal
adj.
Of or in the region of the kidneys.


Renal
Relating to the kidney.
 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 well-de·fined
adj.
1. Having definite and distinct lines or features: a well-defined silhouette.

2.
 pattern appeared in the vicinity of nuclear power plants. Monitoring of cancer incidence and mortality is recommended in areas surrounding sur·round  
tr.v. sur·round·ed, sur·round·ing, sur·rounds
1. To extend on all sides of simultaneously; encircle.

2. To enclose or confine on all sides so as to bar escape or outside communication.

n.
 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 epidemiology, field of medicine concerned with the study of epidemics, outbreaks of disease that affect large numbers of people. Epidemiologists, using sophisticated statistical analyses, field investigations, and complex laboratory techniques, investigate the cause , ionizing, mortality, neoplasms, nuclear facilities, radiation, uranium mines Uranium mining is presently carried out in more than 25 countries around the world. An estimated 100 or more uranium mines in different stages of development are reported. Major uranium mines are located in Canada, Australia and Kazakhstan that contribute more than half of world's uranium . Environ en·vi·ron  
tr.v. en·vi·roned, en·vi·ron·ing, en·vi·rons
To encircle; surround. See Synonyms at surround.



[Middle English envirounen, from Old French environner
 Health Perspect 109:721-729 (2001). [Online 11 July July: see month.  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 Reprocessing may refer to:
  • Nuclear reprocessing
  • Recycling
 plant in Sellafield, England England, the largest and most populous portion of the United Kingdom of Great Britain and Northern Ireland (1991 pop. 46,382,050), 50,334 sq mi (130,365 sq km). It is bounded by Wales and the Irish Sea on the west and Scotland on the north. , 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 Chernobyl (chĭrnō`byēl), Ukr. Chornobyl, abandoned city, N Ukraine, near the Belarus border, on the Pripyat River. Ten miles (16 km) to the north, in the town of Pripyat, is the Chernobyl nuclear power station, site of the worst  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 epidemiologic study A study that compares 2 groups of people who are alike except for one factor, such as exposure to a chemical or the presence of a health effect; the investigators try to determine if any factor is associated with the health effect  have targeted hematologic hematological, hematologic

pertaining to or emanating from blood cells.


hematological tests
total and differential white cell counts, hematocrit estimation, erythrocyte count.
 tumors and young age groups, and very few have sought to assess in depth the remaining malignant tumors malignant tumor
n.
A tumor that invades surrounding tissues, is usually capable of producing metastases, may recur after attempted removal, and is likely to cause death unless adequately treated.
. 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 Tailings (also known as tailings pile, tails, leach residue, or slickens[1]) are the materials left over[2] after the process of separating the valuable fraction from the worthless fraction of an ore.  (8-10), has been studied, the related public health consequences have received scant scant  
adj. scant·er, scant·est
1. Barely sufficient: paid scant attention to the lecture.

2. Falling short of a specific measure: a scant cup of sugar.
 attention.

Spain Spain, Span. España (āspä`nyä), officially Kingdom of Spain, constitutional monarchy (2005 est. pop. 40,341,000), 194,884 sq mi (504,750 sq km), including the Balearic and Canary islands, SW Europe.  currently has seven nuclear power plants, with a total of 10 reactors (nine fully operational and one being dismantled dis·man·tle  
tr.v. dis·man·tled, dis·man·tling, dis·man·tles
1.
a. To take apart; disassemble; tear down.

b.
) 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 Quantify - A performance analysis tool from Pure Software.  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 according to
prep.
1. As stated or indicated by; on the authority of: according to historians.

2. In keeping with: according to instructions.

3.
 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 ICD International Classification of Diseases (of the World Health Organization); intrauterine contraceptive device.

ICD
abbr.
) 151] and colorectal co·lo·rec·tal
adj.
Relating to the colon and the rectum, or to the entire large bowel.



colorectal

pertaining to or of the nature of the colon and the rectum.
 (ICD 153-154), lung (ICD 162), bone (ICD 170), connective connective - An operator used in logic to combine two logical formulas. See first order logic.  tissue (ICD 171), breast (in women, ICD 174), brain (ICD 191), thyroid thyroid /thy·roid/ (thi´roid)
1. the thyroid gland; see under gland.

2. pertaining to the thyroid gland.

3. scutiform.

4.
 (ICD 193), bladder bladder /blad·der/ (blad´er)
1. a membranous sac, such as one serving as receptacle for a secretion.

2. urinary bladder.
 (ICD 188), kidney (ICD 189), ovary ovary, ductless gland of the female in which the ova (female reproductive cells) are produced. In vertebrate animals the ovary also secretes the sex hormones estrogen and progesterone, which control the development of the sexual organs and the secondary sexual  (ICD 183), and all malignant tumors (ICD 140-208), in towns situated near nuclear facilities. We included towns near four nuclear power plants (NPP NPP Nuclear Power Plant
NPP Net Primary Production
NPP Net Primary Productivity
NPP Notice of Privacy Practices (US HIPAA medical patient privacy)
NPP National Priorities Project
NPP New Patriotic Party (Ghana) 
) with six reactors that had been operational from 1975 to 1993, and four nuclear fuel facilities (NFF NFF Neutral File Format
NFF National Farmers Federation (Australia)
NFF National Football Foundation
NFF National Forest Foundation
NFF No Fault Found
NFF National Folk Festival
NFF Nantucket Film Festival
) that had likewise been operational in the same period. With the exception of El Cabril There are parishes that have the name Cabril in Portugal:
  • Cabril, a parish in the municipality of Castro Daire
  • Cabril, a parish in the municipality of Montalegre
  • Cabril, a parish in the municipality of Pampilhosa da Serra
  • Cabril
, a nuclear waste storage facility (NWSF NWSF Nuclear Weapons Storage Facility
NWSF Naval Weather Service Facility
NWSF Northwest Super Fours
) 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 latency period
n.
In psychoanalytic theory, the fourth stage of psychosexual development, extending from about age 5 to puberty, when a child apparently represses sexual urges and prefers to associate with members of the same sex.
 used were 10 years. This lag rules out the possibility of study for the areas surrounding the Asco, Cofrentes Cofrentes (Valencian: Cofrents) is a town in the province of Valencia.

There is a nuclear power plant in Cofrentes. External links
  • Official site

, Trillo Tril´lo

n. 1. (Mus.) A trill or shake. See Trill.
, and Juzbado Juzbado is a village and municipality in the province of Salamanca, western Spain, part of the autonomous community of Castile-Leon. It is located 24 kilometres from the provincial capital city of Salamanca and has a population of 274 people.  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
:This article is about the video game. For Inhabitants of housing, see Residency
Inhabitants is an independently developed commercial puzzle game created by S+F Software. Details
The game is based loosely on the concepts from SameGame.
 of towns neighboring neigh·bor  
n.
1. One who lives near or next to another.

2. A person, place, or thing adjacent to or located near another.

3. A fellow human.

4. Used as a form of familiar address.

v.
 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 geographic information system (GIS)

Computerized system that relates and displays data collected from a geographic entity in the form of a map. The ability of GIS to overlay existing data with new information and display it in colour on a computer screen is used primarily to
, we used the UTM (Unified Threat Management) Refers to a stand-alone appliance or a software package that combines a firewall, antivirus, spam and content filtering as well as intrusion detection. See firewall, antivirus, antispam and IDS.  (Universal Transversa Mercator MERCATOR Cardiology A clinical trial–Multicenter European Research Trial with Cilazapril After Angioplasty to Prevent Transluminal Coronary Obstruction & Restenosis that evaluated ACE inhibition with Cilizapril in preventing restenosis after PCTA in Pts  projection) centroid centroid

In geometry, the centre of mass of a two-dimensional figure or three-dimensional solid. Thus the centroid of a two-dimensional figure represents the point at which it could be balanced if it were cut out of, for example, sheet metal.
 coordinates for towns to measure the distance from the population centroids The following diagrams depict a list of centroids. A centroid of an object in  to the nuclear installations.

[ILLUSTRATION OMITTED]

Follow-up follow-up,
n the process of monitoring the progress of a patient after a period of active treatment.


follow-up

subsequent.


follow-up plan
 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 Spanish, river, c.150 mi (240 km) long, issuing from Spanish Lake, S Ont., Canada, NW of Sudbury, and flowing generally S through Biskotasi and Agnew lakes to Lake Huron opposite Manitoulin island. There are several hydroelectric stations on the river.  Market Yearbook (Anuario del Mercado For the hispanic surname "Mercado", please see de Mercado.

Mercado first originated in Spain. In English it means 'market'.

Is the last name of the 'Great' Fifa Soccer player Eswold.
 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 deceased 1) adj. dead. 2) n. the person who has died, as used in the handling of his/her estate, probate of will and other proceedings after death, or in reference to the victim of a homicide (as: "The deceased had been shot three times.  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 fur·nish  
tr.v. fur·nished, fur·nish·ing, fur·nish·es
1. To equip with what is needed, especially to provide furniture for.

2.
 by the National Statistics Institute. Relying on a log-linear polynomial polynomial, mathematical expression which is a finite sum, each term being a constant times a product of one or more variables raised to powers. With only one variable the general form of a polynomial is a0xn+a  regression regression, in psychology: see defense mechanism.
regression

In statistics, a process for determining a line or curve that best represents the general trend of a data set.
 model, we used interpolation interpolation

In mathematics, estimation of a value between two known data points. A simple example is calculating the mean (see mean, median, and mode) of two population counts made 10 years apart to estimate the population in the fifth year.
 to estimate annual municipal population figures for 1981-1991 (14). We extrapolated pre- pre- word element [L.], before (in time or space).

pre-
pref.
1. Earlier; before; prior to: prenatal.

2.
1981 and post- post- word element [L.], after; behind.

post-
pref.
1. After; later: postpartum.

2. Behind; posterior to: postaxial.
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 Start-up

The earliest stage of a new business venture.
 of reactors and installations.

We fitted log-linear models on the assumption that the number of deaths per stratum stratum /stra·tum/ (strat´um) (stra´tum) pl. stra´ta   [L.] a layer or lamina.

stratum basa´le
 followed a Poisson distribution A statistical method developed by the 18th century French mathematician S. D. Poisson, which is used for predicting the probable distribution of a series of events. For example, when the average transaction volume in a communications system can be estimated, Poisson distribution is used . In these models, observed cases were the dependent variable. As an external standard (15), we used concurrent Spanish cause-specific mortality rates cause-specific mortality rate Epidemiology The mortality rate from a specified cause for a population; the numerator is the number of deaths attributed to a specific cause during a specified time interval; the denominator is the size of the population at the , 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 Regression coefficient

Term yielded by regression analysis that indicates the sensitivity of the dependent variable to a particular independent variable. See: Parameter.


regression coefficient 
 of this exposure term gave us the logarithm logarithm (lŏg`ərĭthəm) [Gr.,=relation number], number associated with a positive number, being the power to which a third number, called the base, must be raised in order to obtain the given positive number.  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 A circular sector or circle sector also known as a pie piece is the portion of a circle enclosed by two radii and an arc. Its area can be calculated as described below.

Let θ be the central angle, in radians, and
 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 cut-off Anesthesiology The point at which elongation of the carbon chain of the 1-alkanol family of anesthetics results in a precipitous drop in the anesthetic potential of these agents–eg, at > 12 carbons in length, there is little anesthetic activity,  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 radial /ra·di·al/ (ra´de-al)
1. pertaining to the radius of the arm or to the radial (lateral) aspect of the arm as opposed to the ulnar (medial) aspect; pertaining to a radius.

2.
 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 het·er·o·ge·ne·i·ty
n.
The quality or state of being heterogeneous.



heterogeneity

the state of being heterogeneous.
 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 in·sen·si·tive  
adj.
1. Not physically sensitive; numb.

2.
a. Lacking in sensitivity to the feelings or circumstances of others; unfeeling.

b.
 to the form adopted by variance The discrepancy between what a party to a lawsuit alleges will be proved in pleadings and what the party actually proves at trial.

In Zoning law, an official permit to use property in a manner that departs from the way in which other property in the same locality
 (17).

Results

The socioeconomic so·ci·o·ec·o·nom·ic  
adj.
Of or involving both social and economic factors.


socioeconomic
Adjective

of or involving economic and social factors

Adj. 1.
 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 ovarian /ovar·i·an/ (o-var´e-an) pertaining to an ovary or ovaries.

ovarian

pertaining to an ovary.


ovarian agenesis
, renal, and colorectal cancer colorectal cancer

Malignant tumour of the large intestine (colon) or rectum. Risk factors include age (after age 50), family history of colorectal cancer, chronic inflammatory bowel diseases, benign polyps, physical inactivity, and a diet high in fat.
.

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 La Haba is a municipality located in the province of Badajoz, Extremadura, Spain. According to the 2005 census (INE), the municipality has a population of 1441 inhabitants.


[ edit ] Municipalities in Badajoz
 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 Thyroid Cancer Definition

Thyroid cancer is a disease in which the cells of the thyroid gland become abnormal, grow uncontrollably, and form a mass of cells called a tumor.
. Renal cancer registered an SMR (Specialized Mobile Radio) The communications services used by police, ambulances, taxicabs, trucks and other delivery vehicles. Throughout the U.S., approximately 3,000 independent operators are licensed by the FCC to offer this service, which provides always-on  that was almost 2 vis-a-vis the national reference and was statistically significant.

The most noteworthy finding in the Ciudad Rodrigo Ciudad Rodrigo (thythäth` rôthrē`gō), town (1990 pop. 15,985), Salamanca prov.  area was the higher risk of death from lung cancer lung cancer, cancer that originates in the tissues of the lungs. Lung cancer is the leading cause of cancer death in the United States in both men and women. Like other cancers, lung cancer occurs after repeated insults to the genetic material of the cell.  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 gradient

In mathematics, a differential operator applied to a three-dimensional vector-valued function to yield a vector whose three components are the partial derivatives of the function with respect to its three variables. The symbol for gradient is ∇.
 with both tests. Similarly, for bone cancer, there appears to be a risk gradient proportional proportional

values expressed as a proportion of the total number of values in a series.


proportional dwarf
the patient is a miniature without disproportionate reductions or enlargements of body parts.
 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 stratification (Lat.,=made in layers), layered structure formed by the deposition of sedimentary rocks. Changes between strata are interpreted as the result of fluctuations in the intensity and persistence of the depositional agent, e.g.  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 ad·vis·a·ble  
adj.
Worthy of being recommended or suggested; prudent.



ad·visa·bil
 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 p-value,
n in statistics, the probability that a random variable will be found to have a value equal to or greater than the observed value by chance alone. This value provides an objective basis from which to assess the relative change in the data.
 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 an·a·lyze  
tr.v. an·a·lyzed, an·a·lyz·ing, an·a·lyz·es
1. To examine methodically by separating into parts and studying their interrelations.

2. Chemistry To make a chemical analysis of.

3.
 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 A cancer registry is a systematic collection of data about cancer and tumor diseases. The data is collected by Cancer Registrars. Cancer Registrars capture a complete summary of patient history, diagnosis, treatment, and status for every cancer patient in the United States, and  that would otherwise enable cancer incidence to be studied in these areas. In the calculation of person-years, interpolation and extrapolation (mathematics, algorithm) extrapolation - A mathematical procedure which estimates values of a function for certain desired inputs given values for known inputs.

If the desired input is outside the range of the known values this is called extrapolation, if it is inside then
 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 Alleged; supposed; reputed.

A putative father is the individual who is alleged to be the father of an illegitimate child.

A putative marriage is one that has been contracted in Good Faith and pursuant to ignorance, by one or both parties, that certain
 source of contamination. Distance to the installation tends to be used as a surrogate surrogate n. 1) a person acting on behalf of another or a substitute, including a woman who gives birth to a baby of a mother who is unable to carry the child. 2) a judge in some states (notably New York) responsible only for probates, estates, and adoptions.  variable for exposure in cases where dosimetric information or the radiologic radiologic Radiological adjective Referring to radiology  history of an installation's environs is not forthcoming (21,22). Indeed in this respect the study is ecologic e·col·o·gy  
n. pl. e·col·o·gies
1.
a. The science of the relationships between organisms and their environments. Also called bionomics.

b. The relationship between organisms and their environment.
, 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 VICE VERSA. On the contrary; on opposite sides. , 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 Coincidence is the noteworthy alignment of two or more events or circumstances without obvious causal connection. The word is derived from the Latin co- ("in", "with", "together") and incidere ("to fall on").  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 bladder cancer

Malignant tumour of the bladder. The most significant risk factor associated with bladder cancer is smoking. Exposure to chemicals called arylamines, which are used in the leather, rubber, printing, and textiles industries, is another risk factor.
 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 cytogenetic /cy·to·ge·net·ic/ (-je-net´ik)
1. pertaining to chromosomes.

2. pertaining to cytogenetics.


cytogenetic

pertaining to or originating from the origin and development of the cell.
 analysis showed a greater frequency of chromosomal aberrations Noun 1. chromosomal aberration - any change in the normal structure or number of chromosomes; often results in physical or mental abnormalities
chromosomal anomaly, chromosonal disorder, chrosomal abnormality
 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 A cohort study is a form of longitudinal study used in medicine and social science. It is one type of study design.

In medicine, it is usually undertaken to obtain evidence to try to refute the existence of a suspected association between cause and disease; failure to refute
 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 DEGRADATION, punishment, ecclesiastical law. A censure by which a clergy man is deprived of his holy orders, which he had as a priest or deacon.  of uranium-238 present in the soil of granite granite, coarse-grained igneous rock of even texture and light color, composed chiefly of quartz and feldspars. It usually contains small quantities of mica or hornblende, and minor accessory minerals may be present.  areas, and to natural radiation (an aspect that could not be controlled for in this study) and radioactive waste radioactive waste, material containing the unusable radioactive byproducts of the scientific, military, and industrial applications of nuclear energy. Since its radioactivity presents a serious health hazard (see radiation sickness), disposing of such material is a ; and from the consequences of mining activities on the population (24). Arguably ar·gu·a·ble  
adj.
1. Open to argument: an arguable question, still unresolved.

2. That can be argued plausibly; defensible in argument: three arguable points of law.
, 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 refining, any of various processes for separating impurities from crude or semifinished materials. It includes the finer processes of metallurgy, the fractional distillation of petroleum into its commercial products, and the purifying of cane, beet, and maple sugar  the ore to produce uranium concentrates, a great volume of hazardous waste Hazardous waste

Any solid, liquid, or gaseous waste materials that, if improperly managed or disposed of, may pose substantial hazards to human health and the environment. Every industrial country in the world has had problems with managing hazardous wastes.
 is generated, known as tailings. These tailings are often dumped dump  
v. dumped, dump·ing, dumps

v.tr.
1. To release or throw down in a large mass.

2.
a.
 outdoors. Such waste contains most of the radionuclides that are produced by uranium degradation and continue to be radioactive ra·di·o·ac·tive
adj.
Of or exhibiting radioactivity.



radioactive

characterized by radioactivity.


radioactive decay
 for hundreds of years, plus variable quantities of other toxic substances, which are either present in the mineral (e.g., heavy metals heavy metals,
n.pl metallic compounds, such as aluminum, arsenic, cadmium, lead, mercury, and nickel. Exposure to these metals has been linked to immune, kidney, and neurotic disorders.
) or used in extraction. Radionuclides and chemical toxics can be dispersed dis·perse  
v. dis·persed, dis·pers·ing, dis·pers·es

v.tr.
1.
a. To drive off or scatter in different directions: The police dispersed the crowd.

b.
 more easily from such dumps DUMPS

a lethal inherited disorder of Holstein cattle that causes infertility. The name is an acronym of Deficiency of Uridine MonoPhosphate S
 than they could from their original state in the ore, as a result of hydrologic and atmospheric atmospheric /at·mos·pher·ic/ (at?mos-fer´ik) of or pertaining to the atmosphere.

atmospheric

of or pertaining to the atmosphere.
 processes (29), containment-dam disasters, and the possibility of improper
In mathematics
  • Improper rotation
  • Improper integral
  • Improper fraction
  • Improper prior
  • Improper distribution
  • Improper point
  • Improper limits
Other
  • Improper English
  • Improper motion
  • Improper noun
 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 mul·ti·pli·ca·tive  
adj.
1. Tending to multiply or capable of multiplying or increasing.

2. Having to do with multiplication.



mul
 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 toxicity /tox·ic·i·ty/ (tok-sis´i-te) the quality of being poisonous, especially the degree of virulence of a toxic microbe or of a poison.  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 myeloid leukemia
n.
See myelogenous 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 Adv. 1. in tandem - one behind the other; "ride tandem on a bicycle built for two"; "riding horses down the path in tandem"
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 The Atomic Weapons Establishment (AWE) is responsible for the design, manufacture and support of warheads for the United Kingdom's nuclear deterrent. AWE plc is responsible for the day-to-day operations of AWE.  (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 Uranium mining is the process of extraction of uranium ore from the ground. As uranium ore is mostly present at relatively low concentrations, most uranium mining is very volume-intensive, and thus tends to be undertaken as open-pit 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 en·sue  
intr.v. en·sued, en·su·ing, en·sues
1. To follow as a consequence or result. See Synonyms at follow.

2. To take place subsequently.
 measurements be made public. Design of any future studies will require dosimetric measurements for areas surrounding such facilities, efforts to reconstruct re·con·struct  
tr.v. re·con·struct·ed, re·con·struct·ing, re·con·structs
1. To construct again; rebuild.

2.
 history of exposure, and an attempt to study the problem from a multidisciplinary mul·ti·dis·ci·pli·nar·y  
adj.
Of, relating to, or making use of several disciplines at once: a multidisciplinary approach to teaching. 
 point of view, using biologic exposure markers.

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2. tumor marker.


bi·o·mark·er
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caus
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induction, in electricity and magnetism, common name for three distinct phenomena.

Electromagnetic induction
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1. medullary; pertaining to, derived from, or resembling bone marrow or the spinal cord.

2. having the appearance of myelocytes, but not derived from bone marrow.
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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 Carlos III may refer to:
  • Charles III of Spain, King of Spain from 1716 to 1788.
  • Universidad Carlos III de Madrid, a Spanish university bearing his name.
, 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 Marina

“a piece of virtue.” [Br. Lit.: Pericles]

See : Virtuousness
 Pollan

Cancer Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain
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