BackgroundEarlier epidemiological studies indicate that associations between obesity and breast cancer risk may not only depend on menopausal status and use of exogenous hormones, but might also differ by tumor subtype. Here, we evaluated whether obesity is differentially associated with the risk of breast tumor subtypes, as defined by 6 immunohistochemical markers (ER, PR, HER2, Ki67, Bcl-2 and p53, separately and combined), in the prospective EPIC-Germany Study (n = 27,012).MethodsFormalin-fixed and paraffin-embedded (FFPE) tumor tissues of 657 incident breast cancer cases were used for histopathological analyses. Associations between BMI and breast cancer risk across subtypes were evaluated by multivariable Cox regression models stratified by menopausal status and hormone therapy (HT) use.ResultsAmong postmenopausal non-users of HT, higher BMI was significantly associated with an increased risk of less aggressive, i.e. ER+, PR+, HER2-, Ki67low, Bcl-2+ and p53- tumors (HR per 5 kg/m2: 1.44 [1.10, 1.90], p = 0.009), but not with risk of more aggressive tumor subtypes. Among postmenopausal users of HT, BMI was significantly inversely associated with less aggressive tumors (HR per 5 kg/m2: 0.68 [0.50, 0.94], p = 0.018). Finally, among pre- and perimenopausal women, Cox regression models did not reveal significant linear associations between BMI and risk of any tumor subtype, although analyses by BMI tertiles showed a significantly lower risk of less aggressive tumors for women in the highest tertile (HR: 0.55 [0.33, 0.93]).ConclusionOverall, our results suggest that obesity is related to risk of breast tumors with lower aggressiveness, a finding that requires replication in larger-scale analyses of pooled prospective data.Electronic supplementary materialThe online version of this article (10.1186/s12885-018-4548-6) contains supplementary material, which is available to authorized users.

Analysis of organic residues in pottery vessels has been successful in detecting a range of animal and plant products as indicators of food preparation and consumption in the past. However, the identification of plant remains, especially grain crops in pottery, has proved elusive. Extending the spectrum is highly desirable, not only to strengthen our understanding of the dispersal of crops from centres of domestication but also to determine modes of food processing, artefact function and the culinary significance of the crop. Here, we propose a new approach to identify millet in pottery vessels, a crop that spread throughout much of Eurasia during prehistory following its domestication, most likely in northern China. We report the successful identification of miliacin (olean-18-en-3β-ol methyl ether), a pentacyclic triterpene methyl ether that is enriched in grains of common/broomcorn millet (Panicum miliaceum), in Bronze Age pottery vessels from the Korean Peninsula and northern Europe. The presence of millet is supported by enriched carbon stable isotope values of bulk charred organic matter sampled from pottery vessel surfaces and extracted n-alkanoic acids, consistent with a C4 plant origin. These data represent the first identification of millet in archaeological ceramic vessels, providing a means to track the introduction, spread and consumption of this important crop.

This paper aims at reconstructing the population dynamics during the Neolithic and Bronze Age, c. 4500–500 cal. BC, in north-western Central Europe. The approach is based on the assumption that increased population density is positively linked with human activity and human impact on the environment, respectively. Therefore, we use archaeological 14C dates and palaeoenvironmental data from northern Germany and south-western Denmark to construct and compare independent proxies of human activity. The latter involves relative quantification of human impact based on pollen analysis and soil erosion history inferred from summarizing of dated colluvial layers. Concurring patterns of changes in human activity are frequently recorded on a multi-centennial scale. Whereas such multi-proxy patterns are interpreted to indicate relative population changes, divergent patterns are discussed in the context of proxy-related uncertainties and potential biases. Patterns of temporal distribution of increasing and decreasing human activity are understood as ‘boom and bust’ phases in population density/size. Based on the comparison of the three proxies, we identify five phases of growing (boom) and four phases of decreasing (bust) population. The boom phases date to ca. 4000–3500, 3000–2900, 2200–2100, 1450–1300 and 1000–750 cal. BC. The bust phases to ca. 3200–3000, 2400–2300, 1650–1500 and 1200–1100 cal. BC.

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