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000178822 041__ $$aEnglish
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000178822 1001_ $$0P:(DE-He78)0644671d309776d45e0fc705d1156cac$$aSrour, Bernard$$b0$$eFirst author$$udkfz
000178822 245__ $$aSerum markers of biological ageing provide long-term prediction of life expectancy-a longitudinal analysis in middle-aged and older German adults.
000178822 260__ $$aOxford$$bOxford Univ. Press$$c2022
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000178822 520__ $$alifestyle behaviours and chronic co-morbidities are leading risk factors for premature mortality and collectively predict wide variability in individual life expectancy (LE). We investigated whether a pre-selected panel of five serum markers of biological ageing could improve predicting the long-term mortality risk and LE in middle-aged and older women and men.we conducted a case-cohort study (n = 5,789 among which there were 2,571 deaths) within the European Prospective Investigation into Cancer-Heidelberg cohort, a population cohort of middle-aged and older individuals, followed over a median duration of 18 years. Gompertz models were used to compute multi-adjusted associations of growth differentiation factor-15, N-terminal pro-brain natriuretic peptide, glycated haemoglobin A1c, C-reactive protein and cystatin-C with mortality risk. Areas under estimated Gompertz survival curves were used to estimate the LE of individuals using a model with lifestyle-related risk factors only (smoking history, body mass index, waist circumference, alcohol, physical inactivity, diabetes and hypertension), or with lifestyle factors plus the ageing-related markers.a model including only lifestyle-related factors predicted a LE difference of 16.8 [95% confidence interval: 15.9; 19.1] years in men and 9.87 [9.20; 13.1] years in women aged ≥60 years by comparing individuals in the highest versus the lowest quintiles of estimated mortality risk. Including the ageing-related biomarkers in the model increased these differences up to 22.7 [22.3; 26.9] years in men and 14.00 [12.9; 18.2] years in women.serum markers of ageing are potentially strong predictors for long-term mortality risk in a general population sample of older and middle-aged individuals and may help to identify individuals at higher risk of premature death, who could benefit from interventions to prevent further ageing-related health declines.
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000178822 650_7 $$2Other$$aageing biomarkers
000178822 650_7 $$2Other$$abiological ageing
000178822 650_7 $$2Other$$alife expectancy
000178822 650_7 $$2Other$$alifestyle factors
000178822 650_7 $$2Other$$aprevention older people
000178822 7001_ $$0P:(DE-He78)f55fe2dee9fdef0b4db17187de23a9bf$$aHynes, Lucas Cory$$b1$$udkfz
000178822 7001_ $$0P:(DE-He78)79ab945544e5bc017a2317b6146ed3aa$$aJohnson, Theron$$b2$$udkfz
000178822 7001_ $$0P:(DE-He78)0907a10ba1dc8f53f04907f54f6fdcfe$$aKühn, Tilman$$b3
000178822 7001_ $$0P:(DE-He78)fb68a9386399d72d84f7f34cfc6048b4$$aKatzke, Verena A$$b4$$udkfz
000178822 7001_ $$0P:(DE-He78)4b2dc91c9d1ac33a1c0e0777d0c1697a$$aKaaks, Rudolf$$b5$$eLast author$$udkfz
000178822 773__ $$0PERI:(DE-600)2065766-3$$a10.1093/ageing/afab271$$gVol. 51, no. 2, p. afab271$$n2$$pafab271$$tAge & ageing$$v51$$x0002-0729$$y2022
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