The Roles of Physical Activity and Electric Blankets in Breast Cancer Occurrence
Bibliographic record
Abstract
ArticlePlus Click on the links below to access all the ArticlePlus for this article. Please note that ArticlePlus files may launch a viewer application outside of your web browser. https://links.lww.com/EDE/A12 Breast cancer is a devastating disease. The specter of breast cancer frightens most women because it causes substantial morbidity and mortality despite our ever-increasing ability to provide earlier diagnosis and improved treatments. Breast cancer incidence rates are increasing worldwide, yet the relatively well-established risk factors account for no more than 50 to 55% of the breast cancer risk of westernized populations. 1–3 As a result, breast cancer epidemiologists have continued to search for additional risk factors, particularly lifestyle and environmental exposures, that are amenable to intervention. Ovarian hormones, and particularly estrogens, play a major role in the development of breast cancer. 4 In fact, most accepted breast cancer risk factors can be interpreted as surrogate measures of a woman’s cumulative exposure to estrogen and possibly, progesterone. These risk factors include early age at menarche, late age at menopause, nulliparity or late age at first birth, lack of or short-term breast feeding, alcohol intake of at least one drink per day, obesity after menopause, and long-term use of hormone replacement therapy. 5–7 During the 1980s and early 1990s new hypotheses related to potentially hazardous exposures (those that might result in greater accumulative exposure to estrogen) and potentially protective exposures (those that might result in decreased estrogen exposure) were proposed. Two of these hypotheses, one related to a potentially putative environmental exposure and the other related to a potentially protective lifestyle modification, are evaluated in population-based case-control studies published in this issue of Epidemiology. McElroy and colleagues 8 have investigated the effects of use of electrically heated blankets or mattress covers on the breast cancer risk of women ages 50 to 79 years who live in Massachusetts, New Hampshire and Wisconsin. Friedenreich and colleagues 9 have evaluated the effects of physical activity on the breast cancer risk of women ages 25 to 70 years living in Alberta, Canada. The hypothesis that forms the basis for the paper by McElroy et al. 8 was initially proposed by Cohen and colleagues in 1978 10 and extended by Stevens in 1987. 11 Cohen et al. argued that light at night, which suppresses pineal gland production of melatonin, might lead to increased breast cancer risk because lower levels of melatonin would be associated with increased circulating estrogen levels. Stevens argued that electric power use would have similar effects, specifically that low frequency electromagnetic fields (EMF) produced by electricity would decrease pineal gland production of melatonin. Thus the secular increase in availability and use of electrical power might explain increasing breast cancer incidence. Stevens based his hypothesis on the results of studies available at that time showing that 60 Hz electrical fields suppressed the nocturnal rise of melatonin in animal models and that the lower melatonin production increased the frequency of carcinogen-induced mammary tumors. More recent animal and mechanistic studies are not consistently supportive of the hypothesis. In 1992, the National Toxicology Program initiated a series of animal studies of 60 Hz EMF. 12 These studies provide no evidence of a carcinogenic effect, and in particular, no evidence of an effect on mammary carcinogenesis. Although low frequency EMF blocks the oncostatic action of melatonin on estrogen receptor positive MCF-7 cells, 13 EMF does not stimulate growth-arrested MCF-7 cells to enter the cell cycle. 14 Studies in humans are also inconsistent. Although evidence exists to show that light affects melatonin levels, we have little human evidence of an effect of EMF on melatonin levels. 15,16 The first epidemiologic studies addressing the possible effect of EMF on breast cancer development were assessments of male breast cancer risk in association with work in occupations where EMF exposure would be expected. 17 Some, but not all, of these studies found an elevated risk for men in high-risk occupations. Studies of female breast cancer and EMF-exposed occupations have been conducted with both positive and null results. In the positive studies, 40% increases in risk were observed. Studies of residential exposure as measured by wiring configuration or distance from the residence to overhead transmission lines have been similarly equivocal. All of these studies have a high likelihood of exposure misclassification because exposures to EMF are ubiquitous and difficult to measure accurately. This concern led to efforts to identify exposure sources that present high, prolonged exposure and reflect variability in the population. Electric blanket use is such an exposure. Vena and colleagues conducted the first two studies of electric blanket use and breast cancer risk. 18,19 Both studies were reported as negative (separate results for premenopausal and postmenopausal women showed a modest 40% elevation in risk 20). Since these publications, four other studies of this issue have been published;21–24 all are considered negative and none has shown an elevation in risk as great as 40% for any subgroup. McElroy and colleagues add to this literature of null results using questions that show relatively high reliability in repeat testing. 8 Given the lack of consistent results in mechanistic and carcinogenicity studies, the relative paucity of evidence that EMF affect melatonin levels in humans, and the difficulties in assessing exposure, it is unlikely that future studies will alter the weight of the current evidence. Are we any better off in assessing the effects of physical activity on breast cancer risk? History of physical activity is not easy to measure in epidemiologic studies. 25 Methods for collecting information on this exposure have varied from the use of surrogate measures (occupation, avocation as an athlete) – to single questions – to asking respondents to summarize hours of activity over decades - to using cognitive methods to obtain lifetime history as has been done by Friedenreich and colleagues. 9 All rely on the ability of women to recall and represent accurately the duration, intensity and frequency of their physical activities. We do have strong evidence that physical activity affects endogenous estrogen exposure. Strenuous physical activity is known to affect menstrual cycle function, particularly among athletes in training who may experience secondary amenorrhea, reduced luteal phase length, oligomenorrhea and anovulation. 26–29 Young female athletes and ballet dancers experience a delay in onset of menarche. 30,31 Even moderate levels of physical activity affect the menstrual cycle patterns and frequency of ovulation of adolescent girls. 32 Thus, given the strength of the evidence for a hormonal basis for breast cancer, one would expect that physical activity should affect a woman’s breast cancer risk. One of the first hints that physical activity, and particularly exercise activity, might affect breast cancer risk came from a study by Frisch and her colleagues published in 1985. 33 This study, which compared the female breast cancer prevalence of former college athletes with that of their classmates, showed that the classmates had substantially greater prevalence of breast cancer. The first publication to assess the lifetime exercise activities of women in detail was published in 1994. 34 This case-control study of women 40 years of age or younger used methods similar to those of Friedenreich et al., 9 but did not collect information on occupational or household activity, although it did control for socioeconomic factors. These same methods were used to study the breast cancer risk of postmenopausal women ages 55 to 64 years. 35 Both of these studies demonstrated an inverse relation between breast cancer risk and lifetime history of exercise activity and both found measures of lifetime activity to be stronger risk predictors than activity during any particular age period. 34,35 Evidence continues to accumulate in support of a protective effect of physical activity on breast cancer risk with risk reductions observed in both case-control and cohort studies, although studies do vary in terms of which subgroups of women benefit the most and whether lifetime or more recent activity provides the greatest protection. 36,37 To be fair, one must acknowledge that several null studies of this issue exist. The quality of the information collected on physical activity varies widely and this may account for some variation in results. 25 The study by Friedenreich and colleagues is unique in its attempt to integrate all sources of physical activity (with the exception of “fidgeting”). Measurement of occupational activity is subjective at best and assumes the accurate reporting of jobs and the dates employed in those jobs; Fryzek and colleagues have shown that the reliability of recall for work history is poor. 38 Several classifications have been used to infer level of activity based on occupation, with investigators either asking the individual to rate the energy requirements, deriving activity from job title, or assigning a score representing level of energy expenditure using a published classification for tasks involved in the occupation. 25,36,39 None is ideal. Although occupational activity is difficult to collect, household activity appears to be even more problematic. How does one recall exactly the amount of time spent scrubbing floors, washing windows, folding clothes, or chasing preschoolers in a typical week for every year of one’s life? Although we cannot generally validate the historical reporting of physical activity, we can ensure that our methods of data collection are reliable. Friedenreich and colleagues have done this with their questionnaire. 40 Although overall, physical activity performed after menopause reduced risk of postmenopausal women in the study reported by Friedenreich et al., 9 recreational activity did not have the strong protective effects that occupational and household activity had. This result is perplexing; does it have something to do with the distribution of energy expenditure activities in the daily lives of women living in Alberta? This activity must be heavily weighted toward expenditure of most energy through occupational and household activities. Because no details are provided on the separate contributions of each type of activity, it is difficult to know whether women in Alberta engage in exercise activities to the extent that women in Los Angeles might. No reduction in risk is observed for premenopausal women in this study. These women appear to span a broad age range and statistical precision is limited. From the tables it appears that only 231 cases and 243 controls were under age 45 years, so that the ability to examine hypotheses relevant to younger women, as has been done in other studies (eg, references 34 and 41), is extremely limited. Nevertheless, this study adds to the quickly growing literature confirming that physically active women (whether it be activity from exercise, occupation or homemaking) experience lower breast cancer risk.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".