Cell Phone and CA

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multivitamins, vitamins B6, and folic acid, as well as minerals iron, magnesium, zinc, and copper,

were associated with a higher risk of total mortality."

"Although we cannot rule out benefits of supplements, such as improved quality of life, our study

raises a concern regarding their long-term safety," the authors add.

In a related editorial, Goran Bjelakovic, MD, DMSc, and Christian Gluud, MD, DMSc, from theCentre for Clinical Intervention Research, Cochrane Hepato-Biliary Group, Rigshospitalet,

Copenhagen University Hospital, Denmark, note that the current study adds "to the growing

evidence demonstrating that certain antioxidant supplements, such as vitamin E, vitamin A, andbeta-carotene, can be harmful."

"We cannot recommend the use of vitamin and mineral supplements as a preventive measure, at

least not in a well-nourished population," they add. "Those supplements do not replace or add tothe benefits of eating fruits and vegetables and may cause unwanted health consequences."

This study was partially supported by the National Cancer Institute and the Academy of Finland,

the Finnish Cultural Foundation, and the Fulbright programs Research Grant for a JuniorScholar. One study author is an unpaid member of the Scientific Advisory Board of the California

Walnut Commission. The other authors and editorialists have disclosed no relevant financialrelationships.

Arch Intern Med. 2011;171:1625-1633,1633-1634.

Medscape Medical News 2011 WebMD, LLCSend comments and news tips to [email protected].

LESS IS MORE

Dietary Supplements and Mortality Rate in Older Women

The Iowa Women's Health Study

Jaakko Mursu, PhD; Kim Robien, PhD; Lisa J. Harnack, DrPH, MPH; Kyong Park, PhD; DavidR. Jacobs Jr, PhD

Arch Intern Med. 2011;171(18):1625-1633. doi:10.1001/archinternmed.2011.445

Background Although dietary supplements are commonly taken to prevent chronic disease,

the long-term health consequences of many compounds are unknown.

Methods We assessed the use of vitamin and mineral supplements in relation to total

mortality in 38 772 older women in the Iowa Women's Health Study; mean age was 61.6years at baseline in 1986. Supplement use was self-reported in 1986, 1997, and 2004.

Through December 31, 2008, a total of 15 594 deaths (40.2%) were identified through the

State Health Registry of Iowa and the National Death Index.

Results In multivariable adjusted proportional hazards regression models, the use ofmultivitamins (hazard ratio, 1.06; 95% CI, 1.02-1.10; absolute risk increase, 2.4%),

vitamin B6 (1.10; 1.01-1.21; 4.1%), folic acid (1.15; 1.00-1.32; 5.9%), iron (1.10; 1.03-

1.17; 3.9%), magnesium (1.08; 1.01-1.15; 3.6%), zinc (1.08; 1.01-1.15; 3.0%), andcopper (1.45; 1.20-1.75; 18.0%) were associated with increased risk of total mortality

when compared with corresponding nonuse. Use of calcium was inversely related (hazard

ratio, 0.91; 95% confidence interval, 0.88-0.94; absolute risk reduction, 3.8%). Findings foriron and calcium were replicated in separate, shorter-term analyses (10-year, 6-year, and
http://archinte.ama-assn.org/cgi/content/extract/171/18/1633http://archinte.ama-assn.org/cgi/content/short/171/18/1625http://archinte.ama-assn.org/cgi/content/extract/171/18/1633mailto:[email protected]://archinte.ama-assn.org/cgi/content/extract/171/18/1633http://archinte.ama-assn.org/cgi/content/short/171/18/1625http://archinte.ama-assn.org/cgi/content/extract/171/18/1633mailto:[email protected]


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4-year follow-up), each with approximately 15% of the original participants having died,starting in 1986, 1997, and 2004.

Conclusions In older women, several commonly used dietary vitamin and mineralsupplements may be associated with increased total mortality risk; this association is

strongest with supplemental iron. In contrast to the findings of many studies, calcium isassociated with decreased risk.

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Medical radiation exposure and breast cancer risk: findings

from the Breast Cancer Family Registry.

Int J Cancer. 2007 Jul 15; 121(2):386-94.

From British Medical Journal

Use of Mobile Phones and Risk of Brain

TumoursUpdate of Danish Cohort Study

Patrizia Frei; Aslak H Poulsen; Christoffer Johansen; Jrgen H Olsen; Marianne Steding-Jessen;

Joachim Schz

Authors and Disclosures

Posted: 11/10/2011; BMJ 2011 BMJ Publishing Group

Abstract

Objective To investigate the risk of tumours in the central nervous system among Danish mobile

phone subscribers.

Design Nationwide cohort study.

Setting Denmark.
http://index/list_4742_0http://index/list_4742_0


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Participants All Danes aged 30 and born in Denmark after 1925, subdivided into subscribers and

non-subscribers of mobile phones before 1995.

Main outcome measures Risk of tumours of the central nervous system, identified from thecomplete Danish Cancer Register. Sex specific incidence rate ratios estimated with log linear

Poisson regression models adjusted for age, calendar period, education, and disposable income.

Results 358 403 subscription holders accrued 3.8 million person years. In the follow-up period1990-2007, there were 10 729 cases of tumours of the central nervous system. The risk of such

tumours was close to unity for both men and women. When restricted to individuals with the

longest mobile phone usethat is, 13 years of subscriptionthe incidence rate ratio was 1.03(95% confidence interval 0.83 to 1.27) in men and 0.91 (0.41 to 2.04) in women. Among those

with subscriptions of 10 years, ratios were 1.04 (0.85 to 1.26) in men and 1.04 (0.56 to 1.95) in

women for glioma and 0.90 (0.57 to 1.42) in men and 0.93 (0.46 to 1.87) in women for

meningioma. There was no indication of dose-response relation either by years since firstsubscription for a mobile phone or by anatomical location of the tumourthat is, in regions of the

brain closest to where the handset is usually held to the head.

Conclusions In this update of a large nationwide cohort study of mobile phone use, there were no

increased risks of tumours of the central nervous system, providing little evidence for a causalassociation.

Introduction

The number of mobile phone users is constantly increasing with more than five billion

subscriptions worldwide in 2010.[1] The widespread use of mobile phones has led to concernsregarding potential adverse health effects, particularly tumours of the central nervous system, of

which the brain is the part most exposed to the radio frequency electromagnetic fields emitted by

an operating mobile phone held to the ear. So far, the mechanism of potential non-thermal

interaction between radio frequency electromagnetic fields and living systems is unknown.[2] Theresults of the Interphone study, the largest international case-control study on this topic, generally

suggest no increased risk of glioma or meningioma.[3] For glioma, however, an increased risk (odds

ratio 1.40, 95% confidence interval 1.03 to 1.89) was observed in 364 people with more than 1640hours of cumulative use. Results for long term mobile phone users (10 years) remain scarce, and

all epidemiological studies are based on few cases.[4] In addition, most studies have been

retrospective case-control studies with self reported data on mobile phone use, which are prone tobias, particularly random reporting bias and differential recall bias for cases and controls, which

hampers the risk estimation and precludes firm conclusions.[5,6]

The only cohort study investigating mobile phone use and cancer to date is a Danish nationwidestudy comparing cancer risk of all 420 095 people who had signed a mobile phone contract with a

phone company (subscribers) from 1982 (the year such phones were introduced in Denmark) until

1995, with the corresponding risk in the rest of the adult population with follow-up to 1996[7]and

then 2002.[8]

The study found no evidence of any increased risk of brain or nervous system tumoursor any cancer among mobile phone subscribers. There was, however, a decreased risk

(standardised incidence ratio 0.66, 0.44 to 0.95) of developing a tumour of the brain or nervous

system in people who had had a subscription for more than 10 years, but this result was based ononly 28 cases.[8]In addition, it was observed that male mobile phone subscribers were at a lower

risk (standardised incidence ratio 0.88, 0.86 to 0.91) of developing tobacco related cancers.

Additional investigations showed that early male subscribers probably constituted a unique


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subgroup of people with a higher income and therefore a potentially distinct risk profile,

particularly lower tobacco consumption.[8]

We followed up the mobile phone subscriber study to 2007, with a focus on tumours of the central

nervous system. Longer follow-up increased the numbers of person years for subscribers,

particularly in long term subscribers (10 years), in whom the total of person years under risk

increased from 170 000 to 1.2 million. This allowed more detailed analysis of long termsubscribers and topographical and morphological subtypes of intracranial central nervous system

tumours. In addition, we were able to obtain information on socioeconomic status on an individual

level, allowing adjustment for education and income when estimating risks related to mobile phoneuse.

Methods

Since 1 April 1968, all Danish residents have been registered in the central population register. At

birth they are assigned a unique personal identification number that is used in all national registers,

ensuring accurate linkage of information among these registers.[9] This system enables researchersto conduct purely register based cohort studies for exposure data available from respective

registries, as the follow-up of vital status, migration, and many health outcomes, in particularcancer, can be done by computerised linkage on an individual level with an exact calculation of

person years at risk. Such a design has been used to follow adult people with a mobile phonecontract (subscribers) for risk of disease compared with the rest of the Danish adult population; in

other words, the whole Danish adult population was subdivided into subscribers and non-

subscribers of mobile phones and followed up for incidence of cancer and other diseases. [7,8,10,11]

Identification of Mobile Phone Subscribers

The collection of mobile phone subscription records has been described in detail previously. [7] Inbrief, 723 421 records for 1982-95 were obtained from the Danish network operators. Exclusion

criteria included corporate subscriptions (n=200 507) and others, as shown in Figure 1. In the

present analysis focusing on central nervous system tumours, we left censored the subscriptiondate of individuals with a subscription before 1987 (1.8% of all subscribers) to 1 January 1987

because handheld handsets were introduced in Denmark only in 1987 and cranial exposure from

car phones (available from 1982) is much lower than exposure from mobile phones held to the

head.

Cohort Definition

In the previous follow-ups of the subscriber study information on socioeconomic factors was notavailable on an individual level, and the comparison of the average income of subscribers and non-

subscribers showed higher average income in the subscriber group, thereby suggesting potential

confounding.[8] To overcome this limitation by obtaining access to individual data onsocioeconomic factors, we conducted our study in the CANULI ("cancer og social ulighed")

cohort, a register based Danish cohort study conducted at the Institute of Cancer Epidemiology onsocial inequality and cancer.[9] This approach of restricting the mobile phone study to the CANULI

cohort has been applied previously.[12]The CANULI study included all Danes born in Denmark in1925 or later and alive in 1990 who did not emigrate from the country before 1 January 1990.

Entry into the CANULI cohort was at age 30 because younger people might have still been in the

educational system. Descendants of immigrants were not included, as they comprised a small andheterogeneous group, and information on their education, if acquired abroad, was not

systematically recorded in the register. The CANULI cohort is therefore a nationwide cohort of all


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Danes aged 30 or older and born after 1925 in Denmark. Because of the eligibility criteria of

CANULI, not all original members of the mobile phone study were part of CANULI and therefore

the original sample size became somewhat smaller. We had 3.21 million Danes for follow-up andthe number of the mobile phone subscribers was reduced by 54 350 individuals compared with the

previous design. We decided that the advantage of obtaining individual level socioeconomic data

and keeping a national representative cohort study clearly outweighed the seeming disadvantage ofa reduction of the still large sample size.

From the CANULI study we obtained information on highest attained education and disposable

income from the population based Integrated Database for Labour Market Research [9] from 1990onwards. Disposable income was calculated from household income after taxation and the number

of people in the household, deflated according to the 2000 value of the Danish Crown. Information

on cancer diagnosis was available from the Danish Cancer Register, which provides accurate andvirtually complete nationwide ascertainment of cancers since 1943, including benign tumours of

the central nervous system.[13] Cancers were classified according to a modified Danish version of

ICD-10 (the international classification of diseases, 10th revision). [14] Topography and morphologywere categorised according to the first revision (ICD-O1) (until 2003) and third revision (ICD-O3)

(2004-2007) of the international classification of diseases for oncology. [15] Date of birth, sex, dateof emigration, or date of death were available for each cohort member from the Danish central

population register.

For the present analysis, follow-up for the occurrence of cancer started at age 30 or 1 January

1990, whichever occurred later, and ended on the date of first diagnosis of cancer (except for non-melanoma skin cancer), date of death, date of emigration, or 31 December 2007, whichever came

first. Figure 2 shows the definition of the observation periods of collection of exposure data and

follow-up for cancer outcome by age and calendar time in the study cohort. We excluded from

analyses any people with a history of cancer before entry into the study (except for non-melanomaskin cancer); this led to the exclusion of 3117 subscribers from analyses (370 of whom had cancer

after their first subscription). To reduce the potential for reverse causation biasthat is, people

purchasing a mobile phone because of early symptoms of their diseasewe defined the persontime within the first year of subscription as unexposed in the analyses. Some 4216 mobile phone

subscribers who met the CANULI eligibility criteria were censored either before their first

subscription (2660 subscribers) or within the first year of subscription (1556 subscribers); theytherefore did not contribute any exposed person time to the study. In the present analyses, 358 403

people therefore contributed to exposed person time at risk.

Statistical Analysis

We used log linear Poisson regression models to estimate incidence rate ratios for cancer diagnoses

for exposed person time (in people who had had mobile phone subscriptions for at least a year)

compared with unexposed person time (non-subscribers or subscribers of less than a year). To

investigate a potential dose-response relation between exposure and outcome, we furthercategorised the exposed person time according to years since first subscription, as in our previous

analyses and most of the case-control studies (1-4, 5-9, 10 years of subscription). [3,7,8] When thenumber of cases allowed it, we subdivided the 10 years category into 10-12 years and 13 years

to allow a separate investigation of an even longer period.

All analyses were stratified by sex and adjusted for age in five year age groups (30-34, 35-40, etc,to 75) and by calendar period (1990-5, 1996-2002, 2003-7) (basic model). Additionally, we

adjusted analyses for highest attained education (basic school/high school, vocational training,


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higher education, unknown (3.7%)) and disposable income (lowest (1st quarter), middle (2nd-3rd

quarter), highest (4th quarter), and unknown (4.1%)) (fully adjusted model). In the results, we have

shown only the fully adjusted models, unless the results for basic and fully adjusted modelsdiffered substantially. All covariates and exposure variables were included categorically, and

people were allowed to change between category levels over time.

We looked at all cancers combined (ICD-10 C00-D48), cancers related to smoking (as this grouphas shown a reduced risk in previous follow-ups; ICD-10 C09-16, C22, C25, C32-34, C39, C53,

C64, C67, D09.0, D30.3, D41.4),[7,8] and, most importantly, the group of tumours of the central

nervous system (including benign tumours) because of exposure of the brain when the phone isheld to the head (ICD-10 C70-72, C75, D32-33, D35, D42, D44). We separately investigated

intracranial tumours categorised according to ICD-O morphology and topography codes (glioma,

meningioma, and others/unspecified). Among gliomas, we separately examined the differentanatomical sites to investigate whether the risk is highest for the temporal lobe with highest

absorption of energy emitted from a mobile phone held to the ear.[16] All anatomical sites with less

than 10 exposed cases and the groups without specification of the topography (C71.8 (overlappinglesion of brain) and C71.9 (brain, unspecified)) were classified into the group "other and

unspecified." Smoking related cancers were classified according to the system of Olsen et al, [17]covering cancers of the buccal cavity and pharynx, digestive organs, respiratory system, urinary

tract, and cervix.

The study was entirely based on record linkage, and therefore required no personal contact with

participants. All statistical analyses were performed in SAS 9.1.

Results

From 1990 to 2007, 358 403 subscription holders beyond the first year of subscription accrued 3.8

million person years, with male subscribers providing nearly all person years (3.2 million). Duringfollow-up, 122 302 cases of cancer occurred in men and 133 713 in women (Table 1 ); in 5111

men and 5618 women these were tumours of the central nervous system.

The incidence rate ratio for all cancers was slightly decreased in men (incidence rate ratio 0.96,

95% confidence interval 0.95 to 0.98) but not in women (1.02, 0.98 to 1.06). When we restricted

the outcome to smoking related cancers, the estimate in men was decreased (0.93, 0.90 to 0.96),

decreasing to 0.87 (0.81 to 0.93) in people with 13 or more years of subscription. Further analysesshowed that the decreased incidence rate ratio for smoking related cancers was restricted to men

with basic or vocational training (0.91, 0.89 to 0.94). In the higher education group (men with >12

years of education), the association between mobile phone use and smoking related cancers wasclose to unity (1.01, 0.93 to 1.09), strongly suggesting a lack of confounding by smoking in this

subgroup. For tumours of the central nervous system, the incidence rate ratio was consistently

close to 1 in women and men, both overall and when stratified by years since first subscription,and also when restricted to men in the highest education group (Table 1 ).

Analyses by morphological subtype of intracranial central nervous system tumours found a slightly

but non-significantly increased incidence rate ratio for glioma in men (1.08, 0.96 to 1.22). Theincidence rate ratio was highest in the shortest term users (1-4 years: 1.20, 0.96 to 1.22), and

beyond five years of use numbers were only slightly raised, and there was no dose-response effect

with increasing years of subscription ( Table 2 ). In women, there was no association betweenmobile phone subscription and glioma regardless of duration (Table 2). For meningioma, there

was a reduction in risk of 22% for male subscribers, with some variations by years of follow-up


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but again no indication of dose-response relation. In women, numbers were small, but there was no

sign of increased incidence rate ratios for meningioma (1.02, 0.71 to 1.47). With regard to other

and unspecified intracranial tumours of the central nervous system, estimates were non-significantly increased in men (incidence rate ratio 1.12, 0.95 to 1.33) and women (1.19, 0.85 to

1.67), but with no clear indication of a dose-response effect ( Table 2).

Further subdivision of gliomas in men by site ( Table 3 ) showed a marginally increased incidencerate ratio for the temporal lobe (1.13, 0.86 to 1.48; n=65). When we stratified data by duration of

follow-up, the highest estimates were seen in the periods 1-4 and 5-9 years of follow-up (incidence

rate ratio 1.35, 0.83 to 2.20, n=18; and 1.31, 0.89 to 1.92, n=29, respectively), but decreased forsubscribers of 10 or more years (0.81, 0.50 to 1.32, n=18). For other sites, the highest incidence

rate ratio was found for the occipital lobe (1.47, 0.87 to 2.48, n=18), with the highest estimate for

the shortest time users (1-4 years) (2.50, 1.18 to 5.31, n=8), and a non-significantly increasedincidence rate ratio of 1.36 (0.57 to 3.23, n=6) for subscribers of 10 or more years. The incidence

rate ratio for parietal lobe tumours was non-significantly decreased (0.73, 0.50 to 1.05, n=33). A

significantly increased estimate was seen for "other and unspecified" sites (1.35, 1.05 to 1.75,n=77), which persisted when restricted to 10 years of exposure (1.44, 1.00 to 2.06, n=35). To

further investigate this finding, we estimated the incidence rate ratios for each subgroup separately.The highest estimate was found for the cerebral ventricle (2.58, 1.08 to 6.15) but was based on

only eight cases. Non-significantly increased incidence rate ratios were found for the unspecificgroups "overlapping lesion of brain" (1.34, 0.92 to 1.95, n=35) and "brain, unspecified" (1.31, 0.86

to 1.99, n=29) respectively. In long term subscribers (10 years), incidence rate ratios for these

groups were 1.48 (0.92 to 2.67, n=13) and 1.62 (1.00 to 2.60, n=21), respectively.

Discussion

In this second update of a large nationwide cohort of 358 403 mobile phone subscribers inDenmark, we observed no overall increased risk of tumours of the central nervous system or for all

cancers combined associated with use of mobile phones. With regard to the major histological

subtypes of intracranial tumours of the central nervous system, there were decreased risk estimatesfor meningioma and non-significantly increased risks for glioma in men only, but there was no

increase in risk estimates with increasing time since first subscription. Importantly, there was no

increase of glioma in the temporal lobes in long term subscribers, as the temporal lobe has been

described as the region of the brain with highest absorption of energy emitted from mobile phones.[16]

Comparison with Previous Follow-ups and Other Studies

Most results of the present study are comparable with the results of the previous follow-up of

mobile phone subscribers up to 2002.[8]That study, however, found a significant reduction in risk

of tumours of the brain and nervous system in long term subscribers (standardised incidence ratio0.66, 95% confidence interval 0.44 to 0.95), based on 28 cases, which was suggested to be a result

of chance. Our present study supports this interpretation as we also found an incidence rate ratio

close to unity based on 316 cases when we investigated 10 years of exposure. We had sufficiently

large numbers to simultaneously investigate risk by tumour type (especially glioma), duration offollow-up, and sex. We found no dose-response relation with regard to years of subscription or to

the anatomical site of the glioma (temporal lobe). With regard to other epidemiological studies, in

2010 Hardell et al found increased risks for glioma for both short and long term users.[18] For thosewho had died, data on exposure were collected from relatives up to 11 years after death. No


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validation of this approach was conducted, making it impossible to assess the impact of the likely

and potentially large recall bias. Most other studies to date have found no evidence for an increased

risk of glioma in short term users (10 years), and for longer latencies results were limited bysmall numbers.[3,4] The largest case-control study to date (Interphone, including 13 countries) found

a significantly increased risk of glioma for the highest tenth of cumulative time that mobile phones

were used (call time), but bias and error prevented a causal interpretation.[3]

Regardingmeningioma, our results are consistent with most studies in finding no increased risk. [4] The risk

estimate was even slightly decreased in men, which was also observed in some other studies. [3,19]

The risk in women was close to unity. Also, population level ecological studies of central nervoussystem tumours and incidence rates for glioma after the introduction of mobile phones rule out

mobile phones as a strong independent risk factor.[20-23] Moreover, results from in vivo and in vitro

studies do not provide convincing evidence for an effect of exposure to radio frequency

electromagnetic fields at non-thermal intensity levels on carcinogenicity or genotoxicity, and apotential biological mechanism has not yet been identified.[2]

Strengths and Limitations of the Study

Our nationwide cohort study with objective register based data on both exposure and cancer

outcome practically eliminates loss to follow-up, which was only 2.2%, and provides accurate and

virtually complete nationwide ascertainment of cancers. Compared with the follow-up to 2002, [8]

the additional five years of follow-up increased the number of person years in people with a mobile

phone subscription for at least 10 years by a factor of seven (1.2 million versus 170 000 person

years). Also, the number of cases of tumours of the central nervous system in long term subscribersincreased from 28 to 316that is, by a factor greater than 10. These marked increases allowed

calculation of more robust estimates and allowed both analyses of subtypes of intracranial tumours

of the central nervous system and separate investigation of men and women. A further

improvement is that we had information on socioeconomic indicators for each individual, whichwas not available previously.[7,8]This allowed the identification of a subpopulation that can be

expected to be unbiased by smoking. As the results for central nervous system tumours in this

group were similar to those we found in all men or women (see Table 1 ), this suggests thatsmoking or other lifestyle factors represented by education and income are not confounders.

A limitation of the study is potential misclassification of exposure. Subscription holders who are

not using their phone will erroneously be classified as exposed and people without a subscriptionbut still using a mobile phone will erroneously be classified as unexposed. Because we excluded

corporate subscriptions, mobile phone users who do not have a subscription in their own name will

have been misclassified as unexposed. Also, as data on mobile phone subscriptions were availableonly until 1995, individuals with a subscription in 1996 or later were classified as non-users. No

increased risks for central nervous system tumours or glioma, however, were found for

subscription holders of 13 years compared with non-subscribers, where there is the strongest

contrast between exposed and unexposed. Moreover, we conducted an additional analysisrestricting follow-up until 31 December 1996, which minimised misclassification of exposure.

Although this enormously reduced the number of cases, the results were similar. For example, the

incidence rate ratio in men for central nervous system tumours was 1.07 (95% confidence interval0.86 to 1.34; n=83), and for glioma it was 1.08 (0.77 to 1.51; n=36). In addition, using a one year

latency for mobile phone use reduced potential bias from reverse causation.

Another limitation of our study is that the dose- response analyses are based on years since first

subscription and we did not have information on the actual amount of mobile phone use.


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Therefore, we could not examine the risk restricted to the subgroup of heaviest users. One might

assume that the high costs related to mobile phone use during the introduction period might have

caused subscribers to refrain from extensive use of their mobile phones. Interestingly, we foundindications that early subscription holders before 1995 were in fact heavier users (based on

outgoing calls) compared with all subscription holders in the years 1996-2002.[24] The weekly

average length of outgoing calls was 23 minutes for subscribers in 1987-95 and 17 minutes in1996-2002. In addition, early subscription holders were on average more exposed to radio

frequency electromagnetic fields from their mobile phones as the early phones had a higher output

power than newer generation phones.[25] As handheld mobile phones were introduced only in 1987and we focused on central nervous system tumours, assessment of exposure was improved by left

censoring exposure data to 1987, thereby reducing misclassification of exposure from car phones.

Car phones were available in Denmark from 1982 but in terms of cranial exposure to radio

frequency electromagnetic fields are several orders of magnitude lower than handheld mobilephones. We did not, however, have information on the use of cordless phones, which operate in a

similar frequency range to mobile phones, or on the use of hands-free kits, with which exposure to

the head and therefore the brain is greatly reduced.[26] Misclassification of exposure in this study is

likely to be non-differential, leading to a dilution of effects, whereas in the existing case-controlstudies there are biases that inflate or deflate effect estimates, which severely limits the

interpretation of the findings.[5,6] In addition, a validation study using self reported mobile phoneuse from 822 people in the control group in the Danish Interphone study showed that subscription

holders were about four times more likely to report regular mobile phone use (defined as making

or receiving at least one call a week over a period of six months or more) before 1996 comparedwith the general Danish population.[8] Moreover, the results of this validation study confirmed that

our approach to classifying exposure is appropriate to show or rule out moderate or large risks

related to mobile phone use.[11]

Conclusions and Outlook

In conclusion, in this update of a nationwide study of mobile phone subscribers in Denmark we

found no indication of an increased risk of tumours of the central nervous system. The extendedfollow-up allowed us to investigate effects in people who had used mobile phones for 10 years or

more, and this long term use was not associated with higher risks of cancer. Furthermore, we found

no increased risk in temporal glioma, which would be the most plausible tumour location if mobilephone use was a risk. As a small to moderate increase in risk for subgroups of heavy users or after

even longer induction periods than 10-15 years cannot be ruled out, however, further studies with

large study populations, where the potential for misclassification of exposure and selection bias is

minimised, are warranted.

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Schz J, Steding-Jessen M, Hansen S, Stangerup SE, Caye-Thomasen P, Poulsen AH, et al.Long-term mobile phone use and the risk of vestibular schwannoma: a Danish nationwide

cohort study.Am J Epidemiol2011;174:416-22.

Storm HH, Michelsen EV, Clemmensen IH, Pihl J. The Danish Cancer Registryhistory,content, quality and use.Dan Med Bull1997;44:535-9.

National Board of Health. Cancer incidence in Denmark 2001; health statistics 2006. NationalBoard of Health (Denmark), 2006.

World Health Organization. International classification of diseases for oncology (ICD-O).

WHO, 1976.

Cardis E, Deltour I, Mann S, Moissonnier M, Taki M, Varsier N, et al. Distribution of RF

energy emitted by mobile phones in anatomical structures of the brain. Phys Med Biol

2008;53:2771-83.

Olsen JH, Friis S, Frederiksen K, McLaughlin JK, Mellemkjr L, Moller H. A typical cancer

pattern in patients with Parkinson's disease.Br J Cancer2005;92:201-5.

Hardell L, Carlberg M, Hansson MK. Mobile phone use and the risk for malignant brain

tumors: a case-control study on deceased cases and controls.Neuroepidemiology

2010;35:109-14.

Inskip PD, Tarone RE, Hatch EE, Wilcosky TC, Shapiro WR, Selker RG, et al. Cellular-

telephone use and brain tumors.N Engl J Med2001;344:79-86.


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Deltour I, Johansen C, Auvinen A, Feychting M, Klaeboe L, Schuz J. Time trends in brain

tumor incidence rates in Denmark, Finland, Norway, and Sweden, 1974-2003.J Natl

Cancer Inst2009;101:1721-4.

Inskip PD, Hoover RN, Devesa SS. Brain cancer incidence trends in relation to cellular

telephone use in the United States.Neuro Oncol2010;12:1147-51.

Lnn S, Klaeboe L, Hall P, Mathiesen T, Auvinen A, Christensen HC, et al. Incidence trends

of adult primary intracerebral tumors in four Nordic countries.Int J Cancer2004;108:450-

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Rsli M, Michel G, Kuehni CE, Spoerri A. Cellular telephone use and time trends in brain

tumour mortality in Switzerland from 1969 to 2002.Eur J Cancer Prev 2007;16:77-82.

National IT and Telecom Agency. Tele yearbook, Denmark. National IT and Telecom Agency,2001.

Neubauer G, Cecil S, Giczi W, Petric B, Preiner P, Frohlich J, et al. The association betweenexposure determined by radiofrequency personal exposimeters and human exposure: a

simulation study.Bioelectromagnetics 2010;31:535-45.

Khn S, Cabot E, Christ A, Capstick M, Kuster N. Assessment of the radio-frequencyelectromagnetic fields induced in the human body from mobile phones used with hands-

free kits.Phys Med Biol2009;54:5493-508.

[ CLOSE WINDOW ]

Table 1. Overall incidence rate ratios (95% confidence intervals) for all cancers, smoking

related cancers, and tumours of central nervous system among mobile phone subscribers in

Denmark, 1987-95, followed up to 31 December 2007, for men, women, and men with more

than 12 years of education

Site of

cancer

Men* Women

Men with

>12 years ofeducation

CasesIncidence rate

ratioCases

Incidence rate

ratioCases

Incidence rate

ratio

All

cancers

Non-

subscribers

107

8401 130 918 1 17 063 1

Subscribers 14 4620.96 (0.95 to0.98)

2795 1.02 (0.98 to1.06)

2402 1.02 (0.97 to1.06)

Years of

subscription:

1-4 28550.96 (0.92 to1.00)

7171.02 (0.95 to1.10)

4821.06 (0.97 to1.16)


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5-9 52910.93 (0.91 to0.96)

12031.03 (0.97 to1.09)

8901.00 (0.94 to1.07)

10 63160.99 (0.97 to

1.02)875

1.00 (0.93 to

1.06)1030

1.01 (0.95 to

1.08)

10-12 40330.99 (0.96 to

1.02)721

0.99 (0.92 to

1.07)647

0.99 (0.91 to

1.07)

13 22831.00 (0.96 to

1.04)154

1.00 (0.85 to

1.17)383

1.04 (0.94 to

1.16)

All smoking

related

sites**

Non-

subscribers

44 2471 33 175 1 5449 1

Subscribers 54220.93 (0.90 to

0.96)685

1.06 (0.98 to

1.14)731

1.01 (0.93 to

1.09)

Years ofsubscription:

1-4 11180.93 (0.87 to0.99)

1851.17 (1.02 to1.36)

1521.04 (0.88 to1.23)

5-9 20410.93 (0.89 to

0.97)

2921.06 (0.95 to

1.19)

2851.05 (0.93 to

1.18)

10 22630.93 (0.89 to

0.97)208

0.97 (0.85 to

1.12)294

0.95 (0.85 to

1.08)

10-12 14950.97 (0.92 to

1.02)165

0.94 (0.80 to

1.09)199

1.02 (0.88 to

1.17)

13 7680.87 (0.81 to0.93)

431.15 (0.85 to1.55)

950.85 (0.69 to1.04)

Central

nervoussystem

Non-

subscribers4397 1 5486 1 850 1

Subscribers 7141.02 (0.94 to1.10)

1321.02 (0.86 to1.22)

1201.00 (0.83 to1.22)


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1-4 1801.07 (0.92 to

1.24)34

0.97 (0.69 to

1.36)38

1.29 (0.92 to

1.79)

5-9 2580.95 (0.83 to

1.08)58

1.05 (0.81 to

1.37)44

0.95 (0.70 to

1.29)

10 2761.06 (0.94 to

1.20)40

1.03 (0.75 to

1.40)38

0.86 (0.62 to

1.20)

10-12 1871.08 (0.93 to1.25)

341.05 (0.75 to1.47)

240.82 (0.55 to1.24)

13 891.03 (0.83 to1.27)

60.91 (0.41 to2.04)

140.94 (0.55 to1.60)

*Men: 18 829 804 person years for non-subscribers, 3 229 589 person years for subscribers

(person years by years of subscription: 1-4=893 248, 5-9=1 284 238, 10=1 052 103, 10-

12: 747 444, 13=304 659).Women: 21 304 186 person years for non-subscribers, 533 733 person years for

subscribers (person years by years of subscription: 1-4=164 507, 5-9=225 864, 10=143

361, 10-12=121 529, 13=21 832).

Subgroup: 3 645 725 person years for non-subscribers, 503 162 person years forsubscribers (person years by years of subscription: 1-4=145 818, 5-9=197 710, 10=159

634, 10-12=111 053, 13=48 582).

Adjusted for age, calendar period, level of education, and disposable income.ICD-10 codes C00-D48.

**ICD-10 codes C09-16, C22, C25, C32-34, C39, C53, C64, C67, D09.0, D30.3, D41.4.

ICD-10 codes C70-72, C75, D32-33, D35, D42, D44.

[ CLOSE WINDOW ]

Table 2. Incidence rate ratios (95% confidence intervals) for intracranial tumours of central

nervous system categorised according to ICD-O morphology and topography codes among

men and women with mobile phone subscriptions in Denmark, 1987-95, followed up to 31

December 2007

Tumour categoryMen* Women*

Cases Incidence rate ratio Cases Incidence rate ratio

Glioma

Non-subscribers 1853 1 1455 1

Subscribers 324 1.08 (0.96 to 1.22) 32 0.98 (0.69 to 1.40)

Years of


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subscription:

1-4 85 1.20 (0.96 to 1.50) 8 0.87 (0.43 to 1.75)

5-9 122 1.05 (0.87 to 1.26) 14 1.02 (0.60 to 1.72)

10 117 1.04 (0.85 to 1.26) 10 1.04 (0.56 to 1.95)

10-12 80 1.06 (0.85 to 1.34) NA

13 37 0.98 (0.70 to 1.36) NA

Meningioma




1-4 15 0.92 (0.55 to 1.56) 9 1.08 (0.56 to 2.09)

5-9 14 0.56 (0.33 to 0.96) 13 1.04 (0.60 to 1.79)

10 21 0.90 (0.57 to 1.42) 8 0.93 (0.46 to 1.87)

Other and

unspecified



Years of

subscription:

1-4 37 1.09 (0.78 to 1.53) 7 0.95 (0.45 to 2.00)

5-9 60 1.08 (0.83 to 1.40) 16 1.28 (0.78 to 2.09)

10 65 1.19 (0.92 to 1.55) 12 1.27 (0.72 to 2.25)

NA=not applicable (numbers too small for analyses).*See table 1 for person years for men and women.

Adjusted for age, calendar period, level of education, and disposable income.ICD-O topography codes C71.0-71.9 and morphology codes 93803-94813.

ICD-O topography codes C70 and morphology codes 93803-94813.

Pineal gland (C75.3) and other morphologies for C70 and C71.0-9.

[ CLOSE WINDOW ]


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Table 3. Incidence rate ratios (95% confidence intervals) for gliomas by anatomical site

among male mobile phone subscribers* in Denmark, 1987-95, followed up to 31 December

2007

Site (code) Cases Incidence rate ratio

Cerebrum (C71.0)

Non-subscribers 375 1

Subscribers 52 0.90 (0.67 to 1.22)

Frontal lobe (C71.1)


Subscribers 79 1.13 (0.89 to 1.45)

Temporal lobe (C71.2)


Subscribers 65 1.13 (0.86 to 1.48)

Parietal lobe (C71.3)


Subscribers 33 0.73 (0.50 to 1.05)

Occipital lobe (C71.4)


Subscribers 18 1.47 (0.87 to 2.48)

Others and unspecified

(C71.5-C71.9)


Subscribers 77 1.35 (1.05 to 1.75)

*See table 1 for person years.Adjusted for age, calendar period, level of education, and disposable income.

[CLOSE WINDOW]

BMJ 2011 BMJ Publishing Group


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Cell Phones Possibly Carcinogenic, WHO

SaysRoxanne Nelson

May 31, 2011 The World Health Organization (WHO) announced today that radiation from

cell phones can possibly cause cancer. According to the WHO's International Agency for Researchon Cancer (IARC), radiofrequency electromagnetic fields have been classified as possibly

carcinogenic to humans (group 2B) on the basis of an increased risk for glioma that some studies

have associated with the use of wireless phones.

This announcement was based on an extensive review of studies on cell phone safety by a working

group of 31 scientists from 14 countries, who have been meeting regularly to evaluate the potential


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carcinogenic hazards from exposure to radiofrequency electromagnetic fields. They reviewed

exposure data, studies of cancer in humans and experimental animal models, and other relevant

data.

More specifically, the IARC Monograph Working Group discussed and evaluated literature that

included several exposure categories involving radiofrequency electromagnetic fields:

Occupational exposures to radar and to microwaves;

Environmental exposures associated with transmission of signals for radio, television, and

wireless telecommunication; and

Personal exposures associated with the use of wireless telephones.

"Given the potential consequences for public health of this classification and findings," said IARC

Director Christopher Wild, PhD, in a news release, "it is important that additional research be

conducted into the long-term, heavy use of mobile phones. Pending the availability of such

information, it is important to take pragmatic measures to reduce exposure such as hands-freedevices or texting."

Inconsistent Data and Opinions

Cellular telephones have become an integral part of everyday life, and the number of users is

estimated at 5 billion globally. However, aspreviously reported byMedscape Medical News, there

has been growing concern over possible health risks associated with the use of cell phones. Inparticular, some data have suggested that their use, especially over the long term, represent a

"significant" risk for brain tumors.

But study results have been inconsistent, although some European countries have takenprecautionary measures aimed specifically at children.

Some of the strongest evidence supporting a link between brain tumors and cell phone use comes

from a series of Swedish studies, led by Lennart Hardell, MD, PhD, from the Department of

Oncology, Orebro Medical Center. These studies showed that risk increased with the number ofcumulative hours of use, higher radiated power, and length of cell phone use. They also reported

that younger users had a higher risk. (Int J Oncol.2006;28:509-518; Int Arch Occup EnvironHealth. 2006;79:630-639; Arch Environ Health. 2004;59:132-137;Pathophysiology. 2009;16:113-

122).

The issue of cell phone safety was to have been settled once and for all by the huge 13-nationindustry-funded Interphone study. But to date, the industry-funded Interphone studies found no

increased riskfor brain tumors from cell phone use, with only 4 exceptions. The findings

contradicted the Swedish studies, which were independent of industry funding.

Consistent with the literature, there is no consensus among physicians and scientists about the

severity of risk, or if one even exists. One issue in attempting to evaluate the potential connectionbetween brain tumors and cell phone use is the relatively short period of time that these deviceshave been heavily used in a large population and the long latency period for many tumors.

The National Cancer Institute, for example, has stated that although aconsistent link has not been

establishedbetween cell phone use and cancer, "scientists feel that additional research is neededbefore firm conclusions can be drawn." In a similar fashion, the American Cancer Society points

out that even though the weight of the evidence has shown no association between cell phone use
http://www.medscape.com/viewarticle/710492http://www.ncbi.nlm.nih.gov/pubmed/16391807http://www.ncbi.nlm.nih.gov/pubmed/16391807http://www.ncbi.nlm.nih.gov/pubmed/16541280http://www.ncbi.nlm.nih.gov/pubmed/16121902http://www.ncbi.nlm.nih.gov/pubmed/19268551http://www.ncbi.nlm.nih.gov/pubmed/19268551http://www.medscape.com/viewarticle/710492http://www.medscape.com/viewarticle/710492http://www.cancer.gov/cancertopics/factsheet/Risk/cellphoneshttp://www.cancer.gov/cancertopics/factsheet/Risk/cellphoneshttp://www.cancer.gov/cancertopics/factsheet/Risk/cellphoneshttp://www.cancer.gov/cancertopics/factsheet/Risk/cellphoneshttp://www.medscape.com/viewarticle/710492http://www.ncbi.nlm.nih.gov/pubmed/16391807http://www.ncbi.nlm.nih.gov/pubmed/16541280http://www.ncbi.nlm.nih.gov/pubmed/16121902http://www.ncbi.nlm.nih.gov/pubmed/19268551http://www.ncbi.nlm.nih.gov/pubmed/19268551http://www.medscape.com/viewarticle/710492http://www.medscape.com/viewarticle/710492http://www.cancer.gov/cancertopics/factsheet/Risk/cellphoneshttp://www.cancer.gov/cancertopics/factsheet/Risk/cellphones


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and brain cancer, information on the potential health effects of very long-term use, or use in

children, is simply not available.

Evidence Strong Enough

The WHO established the International Electromagnetic Fields (EMF) Project in 1996, in response

to public and governmental concern, with the goal of evaluating the possibility of adverse healtheffects from electromagnetic fields. In apress release issued last year, the WHO stated that it

would conduct a formal health risk assessment of radiofrequency fields exposure by 2012, but in

the interim, the IARC would review the carcinogenic potential of mobile phones this year.

Jonathan Samet, MD, chairman of the working group, notes that "the evidence, while still

accumulating, is strong enough to support a conclusion and the 2B classification.

"The conclusion means that there could be some risk, and therefore we need to keep a close watchfor a link between cell phones and cancer risk," he said in a news release.

A full report summarizing the main conclusions and evaluations of the IARC Working Group isslated to be published online soon in The Lancet Oncology and in print in its July 1 issue.

Medscape Medical News 2011 WebMD, LLCSend comments and news tips to [email protected].

From Medscape Medical News > Neurology

Cell Phone Use Affects Brain Glucose Metabolism

Susan Jeffrey

February 23, 2011 Use of a cell phone for as little as 50 minutes at a time appears

to affect brain glucose metabolism in the region closest to the phone's antenna, a

new study shows.

Investigators used positron emission tomography (PET) during cell phone use in the

on and then off positions and found that although whole-brain metabolism was not

affected, metabolism was increased in the orbitofrontal cortex and the temporal pole

areas of the brain while the cell phone was on, areas that are close to where phone's

antenna meets the head.

Dr. Nora Volkow

"We do not know what the clinical significance of this finding is, both with respect to

potential therapeutic effect of this type of technology but also potential negative

consequences from cell phone exposure," said lead study author Nora D. Volkow, MD,

from the National Institute on Drug Abuse in Bethesda, Maryland, during a

teleconference.
http://www.cancer.org/Cancer/CancerCauses/OtherCarcinogens/AtHome/cellular-phoneshttp://www.who.int/mediacentre/factsheets/fs193/en/mailto:[email protected]://www.cancer.org/Cancer/CancerCauses/OtherCarcinogens/AtHome/cellular-phoneshttp://www.who.int/mediacentre/factsheets/fs193/en/mailto:[email protected]


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In the interim though, she recommends using hands-free devices or speaker-phone

mode to avoid direct contact of the telephone with the head. Previous work suggests

that if the phone is a foot or more away it is very unlikely to have any effects, she

said. "So there are some very easy solutions that don't cost anything for those who

want to play it safe."

Caution may be particularly necessary for children and adolescents whose neural

tissue is still developing, Dr. Volkow noted. This is also a population who started their

lives with cell phones and can expect to be exposed for years to come, she added.

Their report appears in the February 23 issue of the Journal of the American Medical

Association.

Effect of Imaging Tools?

The proliferation of cell phone use has raised the question of the effects of

radiofrequency-modulated electromagnetic fields (RF-EMFs), particularly carcinogenic

effects. Epidemiologic studies looking at the relationship between cell phones and

brain tumors have been inconsistent with some, but not all, studies finding increased

risk, "and the issue remains unresolved," the study authors write.

Dr. Volkow is well known for her work in the area of addictions, not generally adverse

effects of cell phone use, but this new study nevertheless stemmed from that

research, she said. They have been studying whether imaging technologies, including

PET and magnetic resonance imaging (MRI), that are used to study the brain can

directly affect brain function. "For the past 15 years, we've done a series of studies to

try to actually assess whether magnetic fields affect brain glucose metabolism," Dr.

Volkow explained.

They found, for example, that the static magnetic field of a 4-T MRI does not affect

brain metabolism, she said. However, when the magnetic fields were changed rapidly,

which produces electrical currents, there was a significant increase in glucose

metabolism in the brain. They wondered whether the RF-EMFs produced by cell

phones might do the same thing.

The current study was a randomized, crossover study that enrolled 47 healthy,

community-dwelling subjects. All underwent PET with (18F)fluorodeoxyglucose

injection twice for 50 minutes at a time, once with a cell phone at each ear but only

the right phone on, although it was muted, and once with both cell phones off.

They found that whole brain metabolism was not significantly different with the phone

on vs off. However, metabolism in the regions closest to the antenna, the

orbitofrontal cortex and temporal pole, was significantly higher when the cell phone

was on.

Table. Brain Metabolism in Area Closest to Antenna With Cell Phone On vs Off


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Endpoint On Mode Off Mode Mean Difference (95% CI) P

Metabolism in area closest to antenna, mol/100 g per minute 35.7 33.3 2.4 (0.67

4.2) .004

CI = confidence interval

The difference between off and on modes was about a 7% increase in glucose

metabolism, within the range of physiologic activation during speaking, for example,

she said.

The increases in activation also correlated significantly with the estimated

electromagnetic field amplitudes for both absolute metabolism (R = 0.95) and for

normalized metabolism (R = 0.89, P < .001 for both).

It's possible that the activation would be even higher in subjects who are actually

talking on the phone, but in this study they did not want the subjects to talk during

imaging, which might have activated other brain areas and confounded the cellphone's effects, she said.

Unfortunately, Dr. Volkow noted, these findings don't shed any light on the

controversy of whether cell phone exposure produces or does not produce cancer.

"What it does say to us is that the human brain is sensitive to this electromagnetic

radiation," she said. Whether this has any negative consequences needs to be

evaluated.

They powered the study to detect even small effects, Dr. Volkow added. If they had

not seen any effect after 50 minutes of exposure, "it would have been much easier to

dismiss any concern about potential negatives of cell phones," she said. "But the factthat we are observing changes really highlights the need to do the studies to be

properly able to answer the question of whether cell phone exposure can have

harmful effects or not."

It's also possible that if there may be beneficial effects, she speculated. "Could one

use, for example, this type of technology to activate areas of the brain that may not

be properly activated and explore potential therapeutic applications of this type of

technology? But that would require that one show there are no untoward effects."

Add to the Concern

In an editorial accompanying the publication, Henry Lai, PhD, from the Department of

Bioengineering at the University of Washington, Seattle, and Lennart Hardell, MD,

PhD, from the Department of Oncology at University Hospital, Orebro, Sweden, point

out that this is the first investigation in humans of glucose metabolism in the brain

after cell phone use.


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"The results by Volkow et al add to the concern about possible acute and long-term

health effects of radiofrequency emissions from wireless phones, including both

mobile and cordless desktop phones," they write.

"Although the biological significance, if any, of increased glucose metabolism from

acute cell phone exposure is unknown, the results warrant further investigation."

The effects are unlikely to be mediated by the substantial increase in temperature

seen with cell phones given the activation was "quite distant" from where the cell

phone made contact, they speculate. Further, since the subjects were only listening

rather than talking on the phone, "the effect observed could thus potentially be more

pronounced in normal-use situations."

The study was supported by the Intramural Research Program of the National

Institutes of Health and by infrastructure support from the US Department of Energy.

The researchers and editorialists have disclosed no relevant financial relationships.

JAMA. 2011;305:808-814, 828-829.

Cancer Risks Near Nuclear FacilitiesThe Importance of Research Design and Explicit Study Hypotheses

Steve Wing; David B. Richardson; Wolfgang Hoffmann

Authors and Disclosures


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Posted: 04/26/2011; Environmental Health Perspectives. 2011;119(4):417-421. 2011 National

Institute of Environmental Health Sciences

Abstract and Introduction

Abstract

Background: In April 2010, the U.S. Nuclear Regulatory Commission asked the National

Academy of Sciences to update a 1990 study of cancer risks near nuclear facilities. Prior research

on this topic has suffered from problems in hypothesis formulation and research design.

Objectives: We review epidemiologic principles used in studies of generic exposureresponse

associations and in studies of specific sources of exposure. We then describe logical problems with

assumptions, formation of testable hypotheses, and interpretation of evidence in previous research

on cancer risks near nuclear facilities.

Discussion: Advancement of knowledge about cancer risks near nuclear facilities depends on

testing specific hypotheses grounded in physical and biological mechanisms of exposure and

susceptibility while considering sample size and ability to adequately quantify exposure, ascertain

cancer cases, and evaluate plausible confounders.Conclusions: Next steps in advancing knowledge about cancer risks near nuclear facilities require

studies of childhood cancer incidence, focus on in utero and early childhood exposures, use ofspecific geographic information, and consideration of pathways for transport and uptake of

radionuclides. Studies of cancer mortality among adults, cancers with long latencies, large

geographic zones, and populations that reside at large distances from nuclear facilities are better

suited for public relations than for scientific purposes.

Introduction

The possibility that radiation releases from nuclear facilities could cause cancer in surroundingpopulations has been of interest for more than two decades. Epidemiologic studies of spatial

variation in cancer incidence or mortality have been conducted to investigate effects of unplannedreleases as well as routine operations. For example, a casecontrol study of cancer among children< 5 years of age found that residence within 5 km of a nuclear facility was associated with a 61%

[one-sided lower bound of the 95% confidence interval (CI), 26%] increased incidence of all

cancer (Spix et al. 2008) and a 119% (lower bound of the 95% CI, 51%) excess risk of leukemia(Kaatsch et al. 2008a). A meta-analysis of geographic studies reported 23% (95% CI, 740%)

higher incidence of leukemia among children 09 years of age living within 16 km of nuclear

facilities (Baker and Hoel 2007). Other studies have compared risks among populations whose

radiation doses have been estimated based on releases and transport of radiation or deposition ofradionuclides. A study of thyroid disease among people who were exposed to radioactive iodine

from the Hanford site in Washington State found that the risk of thyroid disease was similar

regardless of the estimated doses from radioiodine (Davis et al. 2004), whereas a study ofchildhood leukemia after the Chernobyl accident, which classified radiation doses based on soil

radioactivity and diet, reported an excess relative risk per gray of radiation of 32.4 (95% CI, 8.8

84.0) (Davis et al. 2006).

In April 2010 the U.S. Nuclear Regulatory Commission (NRC) asked the National Academy of

Sciences (NAS) to analyze "radiogenic cancer mortality and total cancer mortality in populations

living near past, present, and possible future commercial nuclear facilities for all age groups," andto conduct the same analyses for cancer incidence (Sheron 2010). Nuclear power, weapons, and


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fuel-cycle plants are to be included. Before beginning the full study in late 2011, the NAS is to

conduct a scoping study to determine availability of data, feasibility of considering geographic

units smaller than counties, and the best study design for assessing risks. The NRC requestunderscores the need to evaluate logical problems with previous studies of cancer around nuclear

facilities and to consider the appropriateness of specific hypotheses and design options. In the

United States these issues are of interest, in part, because of continued nuclear weapons productionand federal support for construction of new nuclear power plants.

Currently, the NRC relies on a 1990 report from the National Cancer Institute (NCI 1990) as its

primary source for information about cancer risk from nuclear facilities (NRC 2010). That studycompared cancer death rates in 107 counties that either contained, or neighbored a county that

contained, a nuclear facility, with rates in 292 matched counties. For the period 19501984,

investigators enumerated approximately 900,000 cancer deaths in nuclear facility counties and 1.8million deaths in matched counties. A study of cancer incidence was restricted to Iowa and

Connecticut, states that included four nuclear facilities. Jablon et al. (1991) summarized the

findings from this study and concluded that "if nuclear facilities posed a risk to neighboringpopulations, that risk was too small to be detected by a survey such as this one."

The NRC request for an "update" of the NCI study requires that NAS wrestle with several logical

and methodological problems that have plagued the literature on cancer risks around nuclearfacilities. Here we identify some key issues that must be addressed in order for the new study to

advance science more than public relations.

Next Steps in Research on Cancer Risks Near Nuclear Facilities

Many studies of cancer near nuclear facilities have been conducted since the 1990 NCI study. An

update of that study should build on what has been learned. Two recent childhood cancer studies

have relatively large sample sizes: the meta-analysis of childhood leukemia in proximity to nuclearfacilities conducted by Baker and Hoel (2007) and the Kinderkrebs in der Umgebung von

Kernkraftwerken (KiKK) casecontrol study of childhood leukemia (Kaatsch et al. 2008a, 2008b)

and childhood cancer (Spix et al. 2008) in the vicinity of German nuclear facilities. These studiesare of particular interest because of the high radiosensitivity of the embryo, fetus, and infant, the

use of incidence rather than mortality data, and the ability to discriminate populations in close

proximity to nuclear reactors (Fairlie 2009a, 2009b, 2010; Nussbaum 2009). After intake, tworadionuclides emitted by nuclear reactors, 3H (tritium in the form of heavy water) and 14C, are

distributed throughout the body, and concentrations are 5060% higher in fetal than in maternal

tissues (Stather et al. 2002). Nuclear reactors routinely emit tritium and 14C, and spikes areobserved during refueling (Fairlie 2010). From these observations, we suggest several key

considerations for research on cancer risks near U.S. nuclear facilities.

Exposure Assessment

Studies of cancer risks around nuclear facilities under routine operations have focused on distanceof residence from the facilities as the primary measure of exposure. Baker and Hoel (2007) focused

on populations within 16 km (10 miles) of nuclear facilities. Studies based on large administrativedistricts, such as U.S. counties, including the 1990 NCI study (Jablon et al. 1991), do not have

sufficient spatial specificity to produce meaningful findings.

The KiKK study compared the distance from the nearest nuclear facility of the residences ofchildhood cancer cases at the time of diagnosis and distances of residences of disease-free controls

in high geographic resolution (100 m) (Kaatsch et al. 2008a; Spix et al. 2008). KiKK researchers


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analyzed risk as a continuous function with an a priori model of the reciprocal of distances 70

km, but the effects primarily reflect excesses in the vicinity of approximately 10 km of nuclear

facilities. Several authors have emphasized the KiKK study's precise distance measures as anadvantage of the study (Fairlie 2010; Nussbaum 2009). Although such precision is desirable, the

KiKK study did not analyze residence at birth or conception, which would be more relevant to fetal

dose, nor did it evaluate residential history from conception to diagnosis, which would be relevantto exposure history. Other casecontrol studies should be designed to obtain such information.

However, residential distance is not a measure of dose, nor is it a good proxy unless all nuclear

facilities have the same quantities and types of releases, pregnant mothers and children stay athome all the time, house construction and time outdoors do not affect exposure, and wind direction

and diet are unimportant. These factors could be considered by conducting dose reconstructions

based on environmental data for each facility and behavioral data from the populations beingstudied. This type of approach has been taken to a greater or lesser extent in some studies of single

facilities (Davis et al. 2004, 2006; Hatch et al. 1990), but great effort and adequate data would be

required to make such assessments for many facilities over long periods of time. An alternativestrategy would be to classify exposure based on residential histories and to use mixed regression

models to model the interfacility variability in distancecancer relationships.

Measuring exposure during the correct time period is critical. Studies of young children have anadvantage in this regard because the lag time between exposure and diagnosis of cancer is

restricted compared with adults and there is less opportunity for children to change residences.

Especially in studies of childhood cancer, the operations history of a facility must be considered.For example, a child diagnosed with cancer at 4 years of age who lived near a nuclear power plant

that began operations 2 years earlier could not have experienced in utero exposure to emissions

from that plant. Similarly, air emissions from an operating reactor could not affect a child

diagnosed at 4 years of age if the plant ceased operation 5 years earlier, but drinking watercontaminated by radionuclides with sufficient half-lives could be important from conception

through the date of diagnosis. These scenarios underscore the need to consider time periods of

operation, releases, environmental pathways, uptake, and internal doses, including the physicalhalf-lives, environmental transformations, and biokinetics of radionuclides of interest. Such efforts

have been made for studies of cancer risks near Chernobyl and Hanford (Davis et al. 2004, 2006),

although not without problems (Hoffman et al. 2007).

Outcome Assessment

Studies of cancer risks near nuclear facilities should rely on incidence data; however, only

mortality data are available nationally for the locations and time periods of operation of all nuclearfacilities in the United States. Unlike some countries where this research question has been

addressed, the United States lacks a medical insurance system that could be used to track cancer

incidence nationally. States have instituted cancer registries at different times and with varying

degrees of regional coverage and quality. A new study should be restricted to locations and timeperiods for which adequate cancer incidence data can be assembled. Additionally, because the

ability to ascertain incident cancers among people who live near nuclear facilities declines withtime and movement outside areas covered by state cancer registries, the short exposure lag for

children improves the prospects for complete ascertainment of childhood cancers.


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Dose Response

The inability of previous investigators to interpret positive findings as evidence in support of thehypothesis under investigation results, in part, from the belief that the dose response is too small to

be detectable. One remedy for this problem is to select a sensitive subpopulation for investigation.

In their meta-analysis, Baker and Hoel (2007) included only populations < 25 years of age, and

they focused on children < 10 years of age. The KiKK study includes only children < 5 years ofage. The focus on young ages is justified because of theory and evidence of greater risks from in

utero and childhood than adult exposures, and because previous studies have found the strongest

associations for children.

Sample Size

Childhood cancer occurs infrequently, so nuclear facilities with few children nearby cannotcontribute many cases to an epidemiologic study. However, population size has little effect on the

effort required to evaluate historical releases and environmental pathways. The most efficient

expenditure of time and money would be to give priority to inclusion of facilities with largernearby populations. Although population size is an important consideration, selection of facilities

with larger nearby populations could be problematic if it led to systematic exclusion of facilitieswith larger estimated releases (Krblein and Hoffmann 1999).

Potential Confounders

Other causes of cancer could bias estimates of cancer risk from nuclear facilities if they are more

or less common among populations around nuclear facilities than in comparison populations. Oneadvantage of restricting a study to children is that they are less exposed to potentially confounding

occupational and lifestyle carcinogens than are adults. Although the KiKK study did not achieve a

high enough response rate among control children to use data on other cancer risk factors inprimary analyses, ambient pesticide exposure, medical X rays (child and mother, diagnostic and

therapeutic), fertility treatment, infections, medical drugs during pregnancy, and hair dye use were

not associated with distance from nuclear power plants (Kaatsch et al. 2008b). Measurements of

medical radiation, other sources of radiation, or other carcinogenic exposures, even if they areobtained from independent surveys, could be used to evaluate whether these factors are strongly

enough correlated with nuclear facilities to result in an appreciable bias that could create or mask

distancecancer relationships observed in an epidemiologic study.

Although not yet identified, viruses may play a role in the development of childhood leukemia.

Studies of time in day care during infancy, a measure of potential viral exposure, show protective

effects for childhood leukemia (Petridou et al. 1993; Urayama et al. 2008), whereas studies of in-migration to rural areas, another possible source of viral exposure, suggest that population mixing

increases risk (Kinlen et al. 1995; Wartenberg et al. 2004). A casecontrol study could obtain

history of day-care exposures, and in-migration could be evaluated in either a casecontrol or area-

based design.Another method of evaluating confounding is to measure cancer incidence near nuclear facilities

during the time period preceding startup. If one or more confounding factors, known or unknown,is associated with proximity, a relationship between proximity and cancer would be observed

before startup. The prestartup doseresponse estimate, which quantifies the degree of confounding

under the assumption that the spatial distribution of the confounding factors is the same before andafter startup, can then be subtracted from the poststartup dose response to control this source of

bias (Hatch et al. 1990; Wing et al. 1997).


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A Bayesian Perspective

One way to minimize problems of circular logic in the interpretation of epidemiological results(the null hypothesis cannot be rejected because we assume the exposure was too small to cause an

effect), and to better inform power calculations for any future study, is to encourage investigators

to explicitly state their prior beliefs. In a Bayesian framework, assumptions about dose and dose

response are made explicit in prior distributions and then updated based on new evidence. If theinvestigators hold strong prior beliefs about the magnitudes of dose and the dose effects, then it

may be helpful to recognize at the outset that a proposed study may have little ability to shift

posterior estimates of effect. Then researchers could avoid conducting studies that have littleability to affect strong prior convictions about the association of interest.

Conclusions

The NRC has asked the NAS to study mortality from all types of cancer, cancer at all ages, and

cancer at sites where nuclear facilities might be licensed in the future. The considerations reviewed

here suggest that such an approach could lead to an excessive number of comparisons. Effects insubgroups of interest could be discounted if considered in the context of a large number of

extraneous comparisons. Fortunately, the NRC has also asked the NAS to evaluate radiation dosesto off-site populations and to recommend the best epidemiologic study design.

The only scientific reason to conduct studies of cancer around nuclear facilities is to evaluate

whether radiation doses to neighboring populations result in a detectable increase in cancer risk. It

is not logical to test a hypothesis of elevated cancer near facilities if it is decided a priori thatresults cannot be interpreted as evidence in support of the hypothesis. Such an exercise would

amount to a public relations effort masquerading as a scientific study. Authors of a study of doses

from the 1979 radiation releases at Three Mile Island were explicit about the intent of their

methodology, which they described as having been developed "for educational, public relationsand defensive epidemiology purposes" (Gur et al. 1983). This is apparently the scenario that is

envisioned by Ralph Andersen of the Nuclear Energy Institute in reference to the NRC's request to

the NAS: "These types of studies simply cannot even imply causality, and I would be disappointedif this study undertook to believe that it was a study of causality" [Andersen 2010; see

Supplemental Material for audio recording of the 15th meeting of the Nuclear and Radiation

Studies Board of the National Academies, Washington, DC, 26 April 2010(doi:10.1289/ehp.1002853)].

On the contrary, we believe the only reason to conduct a study is to address causal hypotheses

regarding cancer risks near nuclear facilities. To preserve the integrity of scientific research in thisarea, there must be careful engagement with issues of the physical and biological mechanisms of

interest and selection of populations for study based on the ability to obtain adequate

measurements and sample sizes.

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