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- Veronese, N., et al.
(författare)
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Inverse relationship between body mass index and mortality in older nursing home residents : a meta-analysis of 19,538 elderly subjects
- 2015
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Ingår i: Obesity Reviews. - : Wiley. - 1467-7881 .- 1467-789X. ; 16:11, s. 1001-1015
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Forskningsöversikt (refereegranskat)abstract
- Body mass index (BMI) and mortality in old adults from the general population have been related in a U-shaped or J-shaped curve. However, limited information is available for elderly nursing home populations, particularly about specific cause of death. A systematic PubMed/EMBASE/CINAHL/SCOPUS search until 31 May 2014 without language restrictions was conducted. As no published study reported mortality in standard BMI groups (<18.5, 18.5-24.9, 25-29.9, 30kg/m(2)), the most adjusted hazard ratios (HRs) according to a pre-defined list of covariates were obtained from authors and pooled by random-effect model across each BMI category. Out of 342 hits, 20 studies including 19,538 older nursing home residents with 5,223 deaths during a median of 2 years of follow-up were meta-analysed. Compared with normal weight, all-cause mortality HRs were 1.41 (95% CI=1.26-1.58) for underweight, 0.85 (95% CI=0.73-0.99) for overweight and 0.74 (95% CI=0.57-0.96) for obesity. Underweight was a risk factor for higher mortality caused by infections (HR=1.65 [95% CI=1.13-2.40]). RR results corroborated primary HR results, with additionally lower infection-related mortality in overweight and obese than in normal-weight individuals. Like in the general population, underweight is a risk factor for mortality in old nursing home residents. However, uniquely, not only overweight but also obesity is protective, which has relevant nutritional goal implications in this population/setting.
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- Grossmann, Igor, et al.
(författare)
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Insights into the accuracy of social scientists' forecasts of societal change
- 2023
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Ingår i: Nature Human Behaviour. - : Springer Nature. - 2397-3374. ; 7, s. 484-501
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Tidskriftsartikel (refereegranskat)abstract
- How well can social scientists predict societal change, and what processes underlie their predictions? To answer these questions, we ran two forecasting tournaments testing the accuracy of predictions of societal change in domains commonly studied in the social sciences: ideological preferences, political polarization, life satisfaction, sentiment on social media, and gender-career and racial bias. After we provided them with historical trend data on the relevant domain, social scientists submitted pre-registered monthly forecasts for a year (Tournament 1; N = 86 teams and 359 forecasts), with an opportunity to update forecasts on the basis of new data six months later (Tournament 2; N = 120 teams and 546 forecasts). Benchmarking forecasting accuracy revealed that social scientists' forecasts were on average no more accurate than those of simple statistical models (historical means, random walks or linear regressions) or the aggregate forecasts of a sample from the general public (N = 802). However, scientists were more accurate if they had scientific expertise in a prediction domain, were interdisciplinary, used simpler models and based predictions on prior data. How accurate are social scientists in predicting societal change, and what processes underlie their predictions? Grossmann et al. report the findings of two forecasting tournaments. Social scientists' forecasts were on average no more accurate than those of simple statistical models.
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- Finan, B, et al.
(författare)
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Unimolecular dual incretins maximize metabolic benefits in rodents, monkeys, and humans
- 2013
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Ingår i: Science translational medicine. - : American Association for the Advancement of Science (AAAS). - 1946-6242 .- 1946-6234. ; 5:209, s. 209ra151-
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Tidskriftsartikel (refereegranskat)abstract
- Compared to best-in-class GLP-1 mono-agonists, unimolecular co-agonists of GLP-1 and GIP with optimized pharmacokinetics enhance glycemic and metabolic benefits in mammals.
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