Prostate cancer risk related to foods, food groups, macronutrients and micronutrients derived from the UK Dietary Cohort Consortium food diaries.

BACKGROUND/OBJECTIVES: The influence of dietary factors remains controversial for screen-detected prostate cancer and inconclusive for clinically detected disease. We aimed to examine these associations using prospectively collected food diaries. SUBJECTS/METHODS: A total of 1,717 prostate cancer cases in middle-aged and older UK men were pooled from four prospective cohorts with clinically detected disease (n=663), with routine data follow-up (means 6.6-13.3 years) and a case-control study with screen-detected disease (n=1054), nested in a randomised trial of prostate cancer treatments (ISCTRN 20141297). Multiple-day food diaries (records) completed by men prior to diagnosis were used to estimate intakes of 37 selected nutrients, food groups and items, including carbohydrate, fat, protein, dairy products, fish, meat, fruit and vegetables, energy, fibre, alcohol, lycopene and selenium. Cases were matched on age and diary date to at least one control within study (n=3528). Prostate cancer risk was calculated, using conditional logistic regression (adjusted for baseline covariates) and expressed as odds ratios in each quintile of intake (±95% confidence intervals). Prostate cancer risk was also investigated by localised or advanced stage and by cancer detection method. RESULTS: There were no strong associations between prostate cancer risk and 37 dietary factors. CONCLUSIONS: Prostate cancer risk, including by disease stage, was not strongly associated with dietary factors measured by food diaries in middle-aged and older UK men.Medical Research Council (Grant ID: MC_UU_12019/1), Medical Research Council Population Health Sciences Research Network, British Heart Foundation, Cancer Research UK (Grant ID: C8221/A19170), Department of Health, Food Standards Agency, Stroke Association, WCRF, National Institute for Health Research Health Technology Assessment Programme (Project IDs: 96/20/06, 96/20/99), National Cancer Research Institute (formed by Cancer Research UK, Medical Research Council, Department of Health)This is the final version of the article. It first appeared from Nature Publishing Group via http://dx.doi.org/10.1038/ejcn.2016.16

Synthesis of the land carbon fluxes of the Amazon region between 2010 and 2020

The Amazon is the largest continuous tropical forest in the world and plays a key role in the global carbon cycle. Human-induced disturbances and climate change have impacted the Amazon carbon balance. Here we conduct a comprehensive synthesis of existing state-of-the-art estimates of the contemporary land carbon fluxes in the Amazon using a set of bottom-up methods (i.e., dynamic vegetation models and bookkeeping models) and a top-down inversion (atmospheric inversion model) over the Brazilian Amazon and the whole biogeographical Amazon domain. Over the whole biogeographical Amazon region bottom-up methodologies suggest a small average carbon sink over 2010-2020, in contrast to a small carbon source simulated by top8 down inversion (2010-2018). However, these estimates are not significantly different from one another when accounting for their large individual uncertainties, highlighting remaining knowledge gaps, and the urgent need to reduce such uncertainties. Nevertheless, both methodologies agreed that the Brazilian Amazon has been a net carbon source during recent climate extremes and that the south-eastern Amazon was a net land carbon source over the whole study period (2010-2020). Overall, our results point to increasing human-induced disturbances (deforestation and forest degradation by wildfires) and reduction in the old-growth forest sink during drought

Synthesis of the land carbon fluxes of the Amazon region between 2010 and 2020

This is the final version. Available on open access from Nature Research via the DOI in this recordData availability: The spatial dataset of the main figures are available in a raster format and can be found at https://doi.org/10.5281/zenodo.10423522. The annual carbon fluxes from each model used in this research (disturbances, old-growth sink and net flux) for the Brazilian Amazon and whole Biogeographical Amazon are available at https://doi.org/10.5281/zenodo.8348434.Code availability: The code and tables used to reproduce the main paper graphics of Figs. 2a, b, 3a, b, 4a and 5a are available in Zenodo https://doi.org/10.5281/zenodo.8348435. Further editions to combine the layout of graphics and maps were made in a design software (InkScape).The Amazon is the largest continuous tropical forest in the world and plays a key role in the global carbon cycle. Human-induced disturbances and climate change have impacted the Amazon carbon balance. Here we conduct a comprehensive synthesis of existing state-of-the-art estimates of the contemporary land carbon fluxes in the Amazon using a set of bottom-up methods (i.e., dynamic vegetation models and bookkeeping models) and a top-down inversion (atmospheric inversion model) over the Brazilian Amazon and the whole Biogeographical Amazon domain. Over the whole biogeographical Amazon region bottom-up methodologies suggest a small average carbon sink over 2010-2020, in contrast to a small carbon source simulated by top-down inversion (2010-2018). However, these estimates are not significantly different from one another when accounting for their large individual uncertainties, highlighting remaining knowledge gaps, and the urgent need to reduce such uncertainties. Nevertheless, both methodologies agreed that the Brazilian Amazon has been a net carbon source during recent climate extremes and that the south-eastern Amazon was a net land carbon source over the whole study period (2010-2020). Overall, our results point to increasing human-induced disturbances (deforestation and forest degradation by wildfires) and reduction in the old-growth forest sink during drought.Newton FundRECCAP2 projectEuropean Union Horizon 2020UK National Centre for Earth ObservationState of Sao Paulo Science Foundation (FAPESP