Purpose Excess body fat is a commonly known risk factor for type 2 diabetes. However, whether lean body mass, or fat free mass, could have a protective effect against type 2 diabetes, remains unclear. The aim of this study was to explore the association between lean body mass, fat mass and type 2 diabetes. Methods This study used data from the Danish Diet, Cancer and Health cohort of 37,053 men and women, aged 50-64 years at baseline (1993)(1994)(1995)(1996)(1997). The exposure was measurements of body composition using bioelectrical impedance analysis. Incident diabetes during follow-up was determined through linkage to the Danish National Diabetes Register. Cox proportional hazards regression analysis was used to estimate HR and 95%CI for the association between lean body mass and incident type 2 diabetes, with and without adjustment for fat mass. A sensitivity analysis was performed, excluding cases of incident type 2 diabetes within the first 2 years of follow-up. Results When adjusted for fat mass, the main analysis showed non-linear inverse association between lean body mass and risk of diabetes for men, but not for women. However, the sensitivity analysis found no association for either men or women. Conclusions Lean body mass was not associated with incident type 2 diabetes when excluding cases that may have been subclinical at baseline. The results imply that public health should focus on reduction of fat mass for diabetes prevention.

Research suggests that scientists based at prestigious institutions receive more credit for their work than scientists based at less prestigious institutions, as do scientists working in certain countries. We examined the extent to which country- and institution-related status signals drive such differences in scientific recognition. In a preregistered survey experiment, we asked 4,147 scientists from six disciplines (astronomy, cardiology materials science, political science, psychology and public health) to rate abstracts that varied on two factors: i) author country (high status vs lower status in science); ii) author institution (high status vs lower status university). We found only weak evidence of country- or institution-related status bias, and mixed regression models with discipline as random-effect parameter indicated that any plausible bias not detected by our study must be small in size.

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