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Background: The consumption of legumes is promoted as part of a healthy diet in many countries but associations of total and types of legume consumption with type 2 diabetes (T2D) are not well established. Analyses across diverse populations are lacking despite the availability of unpublished legume consumption data in prospective cohort studies. Objective: To examine the prospective associations of total and types of legume intake with the risk of incident T2D. Methods: Meta-analyses of associations between total legume, pulse, and soy consumption and T2D were conducted using a federated approach without physical data-pooling. Prospective cohorts were included if legume exposure and T2D outcome data were available and the cohort investigators agreed to participate. We estimated incidence rate ratios (IRRs) and CIs of associations using individual participant data including ≤42,473 incident cases among 807,785 adults without diabetes in 27 cohorts across the Americas, Eastern Mediterranean, Europe, and Western Pacific. Random-effects meta-analysis was used to combine effect estimates and estimate heterogeneity. Results: Median total legume intake ranged from 0-140 g/d across cohorts. We observed a weak positive association between total legume consumption and T2D (IRR = 1.02, 95% CI: 1.01 to 1.04) per 20 g/d higher intake, with moderately high heterogeneity (I2 = 74%). Analysis by region showed no evidence of associations in the Americas, Eastern Mediterranean, and Western Pacific. The positive association in Europe (IRR = 1.05, 95% CI: 1.01 to 1.10, I2 = 82%) was mainly driven by studies from Germany, UK, and Sweden. No evidence of associations was observed for the consumption of pulses or soy. Conclusions: These findings suggest no evidence of an association of legume intakes with T2D in several world regions. The positive association observed in some European studies warrants further investigation relating to overall dietary contexts in which legumes are consumed, including accompanying foods which may be positively associated with T2D. Funding for the InterConnect project was provided by the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 602068. Additionally, investigators acknowledge funding from the following agencies: NJW, NGF, FI, and MP acknowledge funding from the Medical Research Council Epidemiology Unit (MC_UU_12015/1 and MC_UU_12015/5); NJW and NGF acknowledge support from National Institute of Health Research (NIHR) Biomedical Research Centre Cambridge: Nutrition, Diet, and Lifestyle Research Theme (IS-BRC-1215-20014). TB acknowledges funding from EUCAN-Connect under the European Union's Horizon 2020 research and innovation programme (grant agreement no. 824989). MBR and MAMG acknowledge funding from the Spanish Government Instituto de Salud Carlos III and the European Regional Development Fund (FEDER) (PI17/01795). JK acknowledges funding from the Korea Centers for Disease Control and Prevention, Ministry for Health and Welfare, Republic of Korea (4845-301 and 4851-302), and the Collaborative Genome Program for Fostering New Post-Genome Industry of the National Research Foundation (NRF) funded by the Ministry of Science and ICT (NRF-2017M3C9A6047623). RM acknowledges funding from the Tehran University of Medical Sciences (grant number: 81/15), Cancer Research UK (grant number: C20/A5860), the Intramural Research Program of the U.S. National Cancer Institute, NIH, and the International Agency for Research on Cancer. LB acknowledges that the Cohort of Swedish Men (COSM) and the Swedish Mammography Cohort (SMC) are part of the Swedish Infrastructure for Medical Population-Based Life-Course and Environmental Research (SIMPLER), which receives funding from the Swedish Research Council (2017-00644). BD is an investigator of the Brazilian National Health Technology Assessment Institute and SC received a fellowship from Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), the Brazilian National Council for Scientific and Technological Development Fund (FEDER) (PI17/01795). The Zutphen Elderly Study was funded by The Netherlands Prevention Foundation, The Hague, The Netherlands and the National Institute of Aging, Bethesda, MD, USA. The funding sources did not participate in the design or conduct of the study; collection, management, analysis, or interpretation of the data; or preparation, review, or approval of the manuscript.

Harmonization of data for pooled analysis relies on the principle of inferential equivalence between variables from different sources. Ideally, this is achieved using models of the direct relationship with gold standard criterion measures, but the necessary validation study data are often unavailable. This study examines an alternative method of network harmonization using indirect models. Starting methods were self-report or accelerometry, from which we derived indirect models of relationships with doubly labelled water (DLW)-based physical activity energy expenditure (PAEE) using sets of two bridge equations via one of three intermediate measures. Coefficients and performance of indirect models were compared to corresponding direct models (linear regression of DLW-based PAEE on starting methods). Indirect model beta coefficients were attenuated compared to direct model betas (10%–63%), narrowing the range of PAEE values; attenuation was greater when bridge equations were weak. Directly and indirectly harmonized models had similar error variance but most indirectly derived values were biased at group-level. Correlations with DLW-based PAEE were identical after harmonization using continuous linear but not categorical models. Wrist acceleration harmonized to DLW-based PAEE via combined accelerometry and heart rate sensing had the lowest error variance (24.5%) and non-significant mean bias 0.9 (95%CI: −1.6; 3.4) kJ·day−1·kg−1. Associations between PAEE and BMI were similar for directly and indirectly harmonized values, but most fell outside the confidence interval of the criterion PAEE-to-BMI association. Indirect models can be used for harmonization. Performance depends on the measurement properties of original data, variance explained by available bridge equations, and similarity of population characteristics.

Online food delivery services facilitate ‘online’ access to food outlets selling food prepared away-from-home. Online food outlet access has not previously been investigated in England or across an entire country. Systematic differences in online food outlet access could exacerbate existing health inequalities, which is a public health concern. However, this is not known. Across postcode districts in England (n = 2118), we identified and described the number of food outlets and unique cuisine types accessible online from the market leader (Just Eat). We investigated associations with area-level deprivation using adjusted negative binomial regression models. We also compared the number of food outlets accessible online with the number physically accessible in the neighbourhood (1600m Euclidean buffers of postcode district geographic centroids) and investigated associations with deprivation using an adjusted general linear model. For each outcome, we predicted means and 95% confidence intervals. In November 2019, 29,232 food outlets were registered to accept orders online. Overall, the median number of food outlets accessible online per postcode district was 63.5 (IQR; 16.0–156.0). For the number of food outlets accessible online as a percentage of the number accessible within the neighbourhood, the median was 63.4% (IQR; 35.6–96.5). Analysis using negative binomial regression showed that online food outlet access was highest in the most deprived postcode districts (n = 106.1; 95% CI: 91.9, 120.3). The number of food outlets accessible online as a percentage of those accessible within the neighbourhood was highest in the least deprived postcode districts (n = 86.2%; 95% CI: 78.6, 93.7). In England, online food outlet access is socioeconomically patterned. Further research is required to understand how online food outlet access is related to using online food delivery services., Highlights • Online food delivery services provide access to food prepared away-from-home. • We describe ‘online’ access to outlets selling this food across England. • Around one-third of food outlets were registered to accept orders online. • Online food outlet access increases existing neighbourhood food outlet access. • Online food outlet access was greatest in the most deprived areas.

Objective: Evidence on the impact of leisure time physical activity (LTPA) in pregnancy on birth size is inconsistent. We aimed to examine the association between LTPA during early and late pregnancy and newborn anthropometric outcomes.Design: Individual level meta‐analysis, which reduces heterogeneity across studies.Setting: A consortium of eight population‐based studies (seven European and one US) comprising 72 694 participants.Methods: Generalised linear models with consistent inclusion of confounders (gestational age, sex, parity, maternal age, education, ethnicity, BMI, smoking, and alcohol intake) were used to test associations between self‐reported LTPA at either early (8–18 weeks gestation) or late pregnancy (30+ weeks) and the outcomes. Results were pooled using random effects meta‐analyses.Main outcome measures: Birth weight, large‐for‐gestational age (LGA), macrosomia, small‐for‐gestational age (SGA), % body fat, and ponderal index at birth.Results: Late, but not early, gestation maternal moderate to vigorous physical activity (MVPA), vigorous activity, and LTPA energy expenditure were modestly inversely associated with BW, LGA, macrosomia, and ponderal index, without heterogeneity (all: I2 = 0%). For each extra hour/week of MVPA, RR for LGA and macrosomia were 0.97 (95% CI: 0.96, 0.98) and 0.96 (95% CI: 0.94, 0.98), respectively. Associations were only modestly reduced after additional adjustments for maternal BMI and gestational diabetes. No measure of LTPA was associated with risk for SGA.Conclusions: Physical activity in late, but not early, pregnancy is consistently associated with modestly lower risk of LGA and macrosomia, but not SGA.Tweetable abstract: In an individual participant meta‐analysis, late pregnancy moderate to vigorous physical activity modestly reduced birth size outcomes.

The association between fish consumption and new-onset type 2 diabetes is inconsistent and differs according to geographical location. We examined the association between the total and types of fish consumption and type 2 diabetes using individual participant data from 28 prospective cohort studies from the Americas (6), Europe (15), the Western Pacific (6), and the Eastern Mediterranean (1) comprising 956,122 participants and 48,084 cases of incident type 2 diabetes. Incidence rate ratios (IRRs) for associations of total fish, shellfish, fatty, lean, fried, freshwater, and saltwater fish intake and type 2 diabetes were derived for each study, adjusting for a consistent set of confounders and combined across studies using random-effects meta-analysis. We stratified all analyses by sex due to observed interaction (p = 0.002) on the association between fish and type 2 diabetes. In women, for each 100 g/week higher intake the IRRs (95% CIs) of type 2 diabetes were 1.02 (1.01-1.03, I2 = 61%) for total fish, 1.04 (1.01-1.07, I2 = 46%) for fatty fish, and 1.02 (1.00-1.04, I2 = 33%) for lean fish. In men, all associations were null. In women, we observed variation by geographical location: IRRs for total fish were 1.03 (1.02-1.04, I2 = 0%) in the Americas and null in other regions. In conclusion, we found evidence of a neutral association between total fish intake and type 2 diabetes in men, but there was a modest positive association among women with heterogeneity across studies, which was partly explained by geographical location and types of fish intake. Future research should investigate the role of cooking methods, accompanying foods and environmental pollutants, but meanwhile, existing dietary regional, national, or international guidelines should continue to guide fish consumption within overall healthy dietary patterns.

Harmonisation of data for pooled analysis relies on the principle of inferential equivalence between variables from different sources. Ideally, this is achieved using models of the direct relationship with gold standard criterion measures, but the necessary validation data are often unavailable. This study examines an alternative method of harmonisation by indirect validation. Starting methods were self-report or accelerometry, from which we derived indirect models of relationships with doubly labelled water (DLW)-measured physical activity energy expenditure (PAEE) using sets of two bridge equations via one of three intermediate measures. Coefficients and performance of indirect models were compared to corresponding direct validation models (linear regression of DLW-measured PAEE on starting methods). Indirect model beta coefficients were attenuated compared to direct model betas (10-63%), narrowing the range of PAEE values; attenuation was greater when bridge equations were weak. Directly and indirectly harmonised models had similar error variance but most indirectly derived values were biased at group-level. Correlations with DLW-measured PAEE were identical after harmonisation using continuous linear but not categorical models. Wrist acceleration harmonised to DLW-measured PAEE via combined accelerometry and heart rate sensing had lowest error variance (24.5%) and non-significant mean bias 0.9 (95%CI: −1.6; 3.4) kJ•day−1•kg−1. Associations between PAEE and BMI were similar for directly and indirectly harmonised values, but most fell outside the confidence interval of the criterion PAEE-to-BMI association. Indirect models can be used for harmonisation. Performance depends on the measurement properties of original data, variance explained by available bridge equations, and similarity of population characteristics.

We present coupled sulfur and oxygen isotope data from sulfur nodules and surrounding gypsum, as well as iron and manganese concentration data, from the Lisan Formation near the Dead Sea (Israel). The sulfur isotope composition in the nodules ranges between -9 and -11‰, 27 to 29‰ lighter than the surrounding gypsum, while the oxygen isotope composition of the gypsum is constant around 24‰. The constant sulfur isotope composition of the nodule is consistent with formation in an ‘open system’. Iron concentrations in the gypsum increase toward the nodule, while manganese concentrations decrease, suggesting a redox boundary at the nodule-gypsum interface during aqueous phase diagenesis. We propose that sulfur nodules in the Lisan Formation are generated through bacterial sulfate reduction, which terminates at elemental sulfur. We speculate that the sulfate-saturated pore fluids, coupled with the low availability of an electron donor, terminates the trithionate pathway before the final two-electron reduction, producing thionites, which then disproportionate to form abundant elemental sulfur.

Objective Achieving sufficient statistical power in a survival analysis usually requires large amounts of data from different sites. Sensitivity of individual-level data, ethical and practical considerations regarding data sharing across institutions could be a potential challenge for achieving this added power. Hence we implemented a federated meta-analysis approach of survival models in DataSHIELD, where only anonymous aggregated data are shared across institutions, while simultaneously allowing for exploratory, interactive modelling. In this case, meta-analysis techniques to combine analysis results from each site are a solution, but an analytic workflow involving local analysis undertaken at individual studies hinders exploration. Thus, the aim is to provide a framework for performing meta-analysis of Cox regression models across institutions without manual analysis steps for the data providers. Results We introduce a package (dsSurvival) which allows privacy preserving meta-analysis of survival models, including the calculation of hazard ratios. Our tool can be of great use in biomedical research where there is a need for building survival models and there are privacy concerns about sharing data.