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Ageing and Longevity
The population of centenarians represents the maximum exponent of longevity. hese people are characterised by the late emergence (more than ninety years) of age-related diseases in their lives, its associated disability and its irreversible process towards death. The study of the biomarkers which characterise this population is of high scientific value. The exceptional phenotype of centenarians is determined both by environmental factors and genetic ones. In this study, 62 genetic variants related to cardio-metabolic diseases, cancer and longevity have been compared in a group of Spanish people older than 100 and the healthy controls of the same ethnic origin. The Genetic Score (GC) of the people over 100 showed a lower predisposition to hypertension, ‘overall cancer risk and to ‘other types of cancer’, but did not show differences in the rest of the genetic variants among which were related to cardiovascular disease, thrombotic stroke, dyslipidemia, lung cancer, breast cancer or extreme longevity. In conclusion, environmental factors (nutrition, stress, exercise, control of biomarkers, etc.) powerfully determine longevity. The main objective of Neolife’s age management programmes is not to increase life expectancy but to prolong a good quality of life and delay the emergence of age-related diseases through the intervention of environmental factors. However, this intervention is precisely what characterises the population of people over 100.
The aim of this study is to study mortality predictors in 498,103 individuals whose data is collected in the UK Biobank (United Kingdom biomarkers database) during a period of five years. 655 parameters related to demography, health and lifestyles and their relation with all causes of mortality were studied, with six specific causes of mortality separately. Among these parameters, there are data such as the number of cars in the family, smoking habits, if they live alone, diabetes diagnosis, cancer or hypertension, pulse, etc. The average age of the sample was between 37 and 73, 54% were women. During the five years of the study, 8,532 people died (39% women). The self-perception of their own state of health, previous diagnosis of cancer, and smoking were the most important mortality predictors. From all the accumulated information, the authors provide a simple online questionnaire at http://www.ubble.co.uk/ (for people between 40 and 70 years old) made up of 13 questions for men and 11 questions for women, whose algorithm provides the risk of dying in the following five years and their biological age at that moment (UbbLE age; UK Biobank Longevity Explorer).
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