Background Vast sample sizes are often essential in the quest to disentangle the complex interplay of the genetic, lifestyle, environmental and social factors that determine the aetiology and progression of chronic diseases. The pooling of information between studies is therefore of central importance to contemporary bioscience. However, there are many technical, ethico-legal and scientific challenges to be overcome if an effective, valid, pooled analysis is to be achieved. Perhaps most critically, any data that are to be analysed in this way must be adequately ‘harmonized’. This implies that the collection and recording of information and data must be done in a manner that is sufficiently similar in the different studies to allow valid synthesis to take place.Methods This conceptual article describes the origins, purpose and scientific foundations of the DataSHaPER (DataSchema and Harmonization Platform for Epidemiological Research; http://www.datashaper.org), which has been created by a multidisciplinary consortium of experts that was pulled together and coordinated by three international organizations: P3G (Public Population Project in Genomics), PHOEBE (Promoting Harmonization of Epidemiological Biobanks in Europe) and CPT (Canadian Partnership for Tomorrow Project).Results The DataSHaPER provides a flexible, structured approach to the harmonization and pooling of information between studies. Its two primary components, the ‘DataSchema’ and ‘Harmonization Platforms’, together support the preparation of effective data-collection protocols and provide a central reference to facilitate harmonization. The DataSHaPER supports both ‘prospective’ and ‘retrospective’ harmonization.Conclusion It is hoped that this article will encourage readers to investigate the project further: the more the research groups and studies are actively involved, the more effective the DataSHaPER programme will ultimately be.

High insulin levels have been associated with increased risk of breast cancer and poorer survival after a breast cancer diagnosis. Waist-to-hip ratio (WHR) is a marker for insulin resistance and hyperinsulinemia. In this study, the authors tested the hypothesis that elevated WHR is directly related to breast cancer mortality. For identification of modifiable factors affecting survival, data were collected on 603 patients with incident breast cancer who visited the Vancouver Cancer Centre of the British Columbia Cancer Agency (Vancouver, British Columbia, Canada) in 1991-1992, including body measurements and information on demographic, medical, reproductive, and dietary factors. These patients were followed for up to 10 years. Cox proportional hazards regression models were used to relate the variables to breast cancer mortality (n = 112). After adjustment for age, body mass index, family history, estrogen receptor (ER) status, tumor stage at diagnosis, and systemic treatment (chemotherapy or tamoxifen), WHR was directly related to breast cancer mortality in postmenopausal women (for highest quartile vs. lowest, relative risk = 3.3, 95% confidence interval: 1.1, 10.4) but not in premenopausal women (relative risk = 1.2, 95% confidence interval: 0.4, 3.4). Stratification according to ER status showed that the increased mortality was restricted to ER-positive postmenopausal women. Elevated WHR was confirmed as a predictor of breast cancer mortality, with menopausal status and ER status at diagnosis found to be important modifiers of that relation.

This analysis suggests that high SES is a true risk factor for childhood leukemia and that inconsistent results from other studies may be related to differences in case ascertainment or study participation.

Long-term, night shiftwork has been identified as a potential carcinogenic risk factor. It is hypothesized that increased light at night exposure during shiftwork reduces melatonin production, which is associated with increased cancer risk. Sleep duration has been hypothesized to influence both melatonin levels and cancer risk, and it has been suggested that sleep duration could be used as a proxy for melatonin production. Finally, physical activity has been shown to reduce cancer risk, and laboratory studies indicate it may influence melatonin levels. A cross-sectional study of light exposure, sleep duration, physical activity, and melatonin levels was conducted among 61 female rotating shift nurses (work schedule: two 12 h days, two 12 h nights, five days off). Light intensity was measured using a light-intensity data logger, and sleep duration and physical activity were self-reported in a study diary and questionnaire. Melatonin concentrations were measured from urine and saliva samples. The characteristics of nurses working day and night shifts were similar. Light intensity was significantly higher during sleep for those working at night (p< 0.0001), while urinary melatonin levels following sleep were significantly higher among those working days (p = 0.0003). Mean sleep duration for nurses working during the day (8.27 h) was significantly longer than for those working at night (4.78 h, p< 0.0001). An inverse association (p = 0.002) between light exposure and urinary melatonin levels was observed; however, this was not significant when stratified by shift group. There was no significant correlation between sleep duration and melatonin, and no consistent relationship between physical activity and melatonin. Analysis of salivary melatonin levels indicated that the circadian rhythms of night workers were not altered, meaning peak melatonin production occurred at night. This study indicates that two nights of rotating shift work may not change the timing of melatonin production to the day among those working at night. Additionally, in this study, sleep duration was not correlated with urinary melatonin levels, suggesting it may not be a good proxy for melatonin production.