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A balanced robertsonian translocation (rob) results from fusion of 2 acrocentric chromosomes. Carriers are phenotypically normal and are often diagnosed because of recurrent miscarriages, infertility, or aneuploid offspring. Mortality and site-specific cancer risks in carriers have not been prospectively investigated. We followed 1,987 carriers diagnosed in Great Britain for deaths and cancer risk, over an average of 24.1 years. Standardized mortality and incidence ratios were calculated comparing the number of observed events against population rates. Overall mortality was higher for carriers diagnosed before age 15 years (standardized mortality ratio (SMR) = 2.00, 95% confidence interval (CI): 1.09, 3.35), similar for those diagnosed aged 15–44 years (SMR = 1.06, 95% CI: 0.86–1.28), and lower for those diagnosed aged 45–84 years (SMR = 0.81, 95% CI: 0.68, 0.95). Cancer incidence was higher for non-Hodgkin lymphoma (standardized incidence ratio (SIR) = 1.90, 95% CI: 1.01, 3.24) and childhood leukemia (SIR = 14.5, 95% CI: 1.75, 52.2), the latter particularly in rob(15;21) carriers (SIR = 447.8, 95% CI: 11.3, 2,495). Rob(13;14) carriers had a higher breast cancer risk (SIR = 1.58, 95% CI: 1.12, 2.15). Mortality risks relative to the population in diagnosed carriers depend on age at cytogenetic diagnosis, possibly reflecting age-specific cytogenetic referral reasons. Carriers might be at greater risk of childhood leukemia and non-Hodgkin lymphoma and those diagnosed with rob(13;14) of breast cancer.

There has been a worldwide epidemic of obesity in recent decades. In animal studies, there is convincing evidence that light exposure causes weight gain, even when calorie intake and physical activity are held constant. Disruption of sleep and circadian rhythms by exposure to light at night (LAN) might be one mechanism contributing to the rise in obesity, but it has not been well-investigated in humans. Using multinomial logistic regression, we examined the association between exposure to LAN and obesity in questionnaire data from over 100,000 women in the Breakthrough Generations Study, a cohort study of women aged 16 years or older who were living in the United Kingdom and recruited during 2003-2012. The odds of obesity, measured using body mass index, waist:hip ratio, waist:height ratio, and waist circumference, increased with increasing levels of LAN exposure (P < 0.001), even after adjustment for potential confounders such as sleep duration, alcohol intake, physical activity, and current smoking. We found a significant association between LAN exposure and obesity which was not explained by potential confounders we could measure. While the possibility of residual confounding cannot be excluded, the pattern is intriguing, accords with the results of animal experiments, and warrants further investigation.

The energy absorbed from the radio-frequency fields of mobile telephones depends strongly on distance from the source. The authors' objective in this study was to evaluate whether gliomas occur preferentially in the areas of the brain having the highest radio-frequency exposure. The authors used 2 approaches: In a case-case analysis, tumor locations were compared with varying exposure levels; in a case-specular analysis, a hypothetical reference location was assigned for each glioma, and the distances from the actual and specular locations to the handset were compared. The study included 888 gliomas from 7 European countries (2000-2004), with tumor midpoints defined on a 3-dimensional grid based on radiologic images. The case-case analyses were carried out using unconditional logistic regression, whereas in the case-specular analysis, conditional logistic regression was used. In the case-case analyses, tumors were located closest to the source of exposure among never-regular and contralateral users, but not statistically significantly. In the case-specular analysis, the mean distances between exposure source and location were similar for cases and speculars. These results do not suggest that gliomas in mobile phone users are preferentially located in the parts of the brain with the highest radio-frequency fields from mobile phones.

Prospective cohort studies examining sex hormones in relation to cancer risk have generally collected blood samples at 1 time point, with an assumption that hormone levels measured in these samples will be reliable markers of true levels at other times. In postmenopausal women, body fat is a major source of estradiol; therefore, changes in adiposity may affect the correlation of single measurements to more relevant long-term averages. To estimate the intraclass correlation coefficient (ICC) for estradiol and testosterone, we collected repeat blood samples from 119 postmenopausal women (average age = 59.4 (standard deviation, 4.7) years) from the United Kingdom during 2004-2005 and again during 2010-2011. The ICCs (adjusted for assay variation) were 0.73 (95% confidence interval: 0.63, 0.82) for total estradiol and 0.59 (95% confidence interval: 0.47, 0.72) for total testosterone. The ICCs were 3%-5% larger after adjustment for change in body mass index (weight (kg)/height (m)(2)) or leptin, which are 2 markers of change in adiposity. There was no increase in ICCs after adjustment for change in age, alcohol consumption, smoking, exercise, time between waking and blood collection, or season. The results suggest that other factors account for within-woman variation in these sex hormones.

The authors examined the effect of women's lifestyles on the timing of natural menopause using data from a cross-sectional questionnaire used in the United Kingdom-based Breakthrough Generations Study in 2003-2011. The analyses included 50,678 women (21,511 who had experienced a natural menopause) who were 40-98 years of age at study entry and did not have a history of breast cancer. Cox competing risks proportional hazards models were fitted to examine the relation of age at natural menopause to lifestyle and anthropometric factors. Results were adjusted for age at reporting, smoking status at menopause, parity, and body mass index at age 40 years, as appropriate. All P values were 2-sided. High adult weight (P(trend) < 0.001), high body mass index (P(trend) < 0.001), weight gain between the ages of 20 and 40 years (P(trend) = 0.01), not smoking (P < 0.001), increased alcohol consumption (P(trend) < 0.001), regular strenuous exercise (P < 0.01), and not being a vegetarian (P < 0.001) were associated with older age at menopause. Neither height nor history of an eating disorder was associated with menopausal age. These findings show the importance of lifestyle factors in determining menopausal age.

An inverse association between allergic conditions and glioma risk has been reported previously. In this large population-based case-control study, the authors identified cases diagnosed with glioma or meningioma in Denmark, Norway, Finland, Sweden, and southeast England between 2000 and 2004. Detailed information on self-reported physician-diagnosed allergic conditions was collected from 1,527 glioma cases, 1,210 meningioma cases, and 3,309 randomly selected controls. Logistic regression showed an odds ratio of 0.70 (95% confidence interval: 0.61, 0.80) for glioma associated with a diagnosis of any of asthma, hay fever, eczema, or other type of allergy. The risk estimates for glioma were around 0.65 for each allergic condition (asthma, eczema, hay fever, and food allergy), and the 95% confidence intervals were equally consistent, at around 0.55, 0.80. The reduced risks of glioma related to eczema, hay fever, and allergy overall, but not asthma, were confined to current rather than past conditions. Meningioma risk was not associated with allergic conditions, except for eczema (odds ratio = 0.74, 95% confidence interval: 0.60, 0.91). Our results show a reduced risk for glioma associated primarily with current allergic conditions. If this is etiologic, it has implications for the understanding of how allergic conditions might reduce the tumor risk.

Epidemiologic studies have consistently shown inverse associations of allergic disease with risk of glioma, but it is unclear whether this association also applies to meningioma. The authors conducted a pooled analysis of meningioma risk in relation to a history of allergic disease based on data from two population-based, case-control studies with 475 cases and 1,716 controls in the United Kingdom (2001-2004). Meningioma risk was significantly reduced in relation to self-reported, physician-diagnosed allergic disease (odds ratio = 0.76, 95% confidence interval (CI): 0.61, 0.96) but was nonsignificantly reduced for individual conditions: asthma (odds ratio = 0.85, 95% CI: 0.61, 1.18), hay fever (odds ratio = 0.81, 95% CI: 0.62, 1.06), and eczema (odds ratio = 0.72, 95% CI: 0.51, 1.02). Risk reductions were greatest for asthma (odds ratio = 0.43, 95% CI: 0.21, 0.89) and hay fever (odds ratio = 0.50, 95% CI: 0.25, 1.00) with an early age at onset (