Health status and 6 years survival of 552 90+ Italian sib-ships recruited within the EU Project GEHA (GEnetics of Healthy Ageing)

Abstract

In a scenario of increasing life expectancy worldwide, it is mandatory to identify the characteristics of a healthy aging phenotype, including survival predictors, and to disentangle those related to environment/ lifestyle versus those related to familiarity/genetics. To this aim we comprehensively characterised a cohort of 1,160 Italian subjects of 90 years and over (90+, mean age 93 years; age range 90-106 years) followed for 6 years survival, belonging to 552 sib-ships (familiar longevity) recruited (2005)(2006)(2007)(2008) within the EU-funded GEHA project in three Italian geographic areas (Northern, Central and Southern Italy) different for urban/rural and socio-economical characteristics. On the whole, the following factors emerged as significant predictors of survival after 90 years of age: absence of cognitive impairment and physical disability, high hand grip strength scores and body mass index (BMI) values, "excellent/good" self-reported health, high haemoglobin and total cholesterol levels and low creatinine levels. These parameters, excluding BMI values, were also significantly associated within sib-ships, suggesting a strong familial/genetic component. Geographical micro-heterogeneity of survival predictors emerged, such as functional and physical status being more important in Southern than in Central and Northern Italy. In conclusion, we identified modifiable survival predictors related to specific domains, whose role and importance vary according to the geographic area considered and which can help in interpreting the genetic results obtained by the GEHA project, whose major aim is the comprehensive evaluation of phenotypic and genetic data.

Circulating levels and assessment of clinical laboratory analytes, in >80-year-old, apparently healthy, moderately healthy, and frail individuals

“…Moreover, there were substantial differences in health status between the included individuals in the present investigations, reflecting the need for individual evaluation. As seen in the present thesis, when developing reference intervals and studying elderly individuals, there is a high risk that moderately healthy or frail elderly people are excluded while an elite of the healthiest individuals remains (107). However, ordinary senior reference populations without any diseases, medication and supplementation are too rare and cannot be regarded as representative of the entire elderly population (108).…”

Development of a Pilot Project on Data Sharing among Partners of the Italian Hub of Population Biobanks (HIBP): Association between Lipid Profile and Socio-Demographic Variables

“…These data support the results of a recent study on Italian nonagenarians, whose lipid parameters were largely normal, falling within the standard ranges valid for the adult population. 35 On the whole, many of the observed associations suggest that geographical differences affect the analyzed parameters, except for subjects older than 80 years, although the results of this study require further experimental validation. In fact, this prototype is a data-sharing study and, as such, it can only identify associations, but cannot provide insight on causation.…”

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“…Mental working ability increases and the mood improves; several kinds of metabolism, lipid in particular, are normalized: cholesterol level in the blood decreases and high-density lipoproteins level increases. It has been proved that the level of risk factors of cardio-vascular and nervous diseases correlate inversely with the level of physical activity [26,27].…”