Life expectancy has remained relatively constant at around 40 years of age throughout the different historical periods. It was not until the second half of the twentieth century, when there was a general improvement in health conditions and medical care, that many countries experienced a notable increase in life expectancy at birth to over 80 years of age as is currently the case in Spain. In fact, recent scientific and technological advances make it possible to predict that over the next few decades it will become increasingly common for human beings to overcome the barrier of 100 years. This constant increase in life expectancy will bring with it a series of economic, social and health consequences whose real impact is difficult to anticipate, but to which it will be necessary to give an effective response. Determining which factors favour longevity may be the best tool to venture possible future scenarios and anticipate strategies in order to safeguard the proper functioning of the welfare state.
The identification of mechanisms related to the lengthening of life, as well as the complex interactions established between them, is a laborious task that requires the integration of disciplines as disparate as genetics, medicine, psychology, sociology, epidemiology, demography or economics. Only through a multidisciplinary approach can a sufficient level of understanding be reached to unravel the keys to such a complex phenomenon as healthy ageing and longevity. In this sense, the study of lifestyles plays a key role in the paradigm shift of longevity and aging. Factors such as diet, physical exercise, stress, intellectual activity or the frequency and quality of social interactions are pieces of a puzzle that could help increase life expectancy and quality. In practical terms, slower ageing could simultaneously delay the onset and progression of a large number of disabling diseases.
Thus, the study of longevity is making a leap from the perspective of curative medicine to a broader vision of a preventive type. Specifically, the focus is on determining what an individual's probable life expectancy will be in order to determine which diseases are most likely to develop and combat them before they manifest themselves through personalised interventions, improving their quality of life. The Spain-Portugal Longevity Research Programme +90 (PILEP+90) contributes to this end as it seeks to elucidate those demographic, clinical, cognitive and functional aspects that behave as protective factors associated with healthy ageing.
At present moment, PILEP+90 is fully immersed in the first phase of the study.
Specifically, the over-90s participating in the project have already been selected and home interviews are being carried out in order to subsequently analyse the data collected. Specifically, the following information of interest is being collected:
a) Demographic data: age, sex, educational level, occupation, marital status, type of cohabitation, socio-economic status.
b) Medical history and current medication.
c) Cognitive status: memory complaints and performance in a short cognitive test.
d) Perceived health and quality of life: general state of health, physical and emotional state, daily activities, social support, pain, feeling of loneliness.
e) Functional dependence: situation of disability and dependence, existence of relevant sensory deficits, capacity to carry out daily tasks.
f) Habits and lifestyles: biometric data, sleep, stress, consumption of tobacco and alcohol, diet, daily activities.
At the end of the first phase of PILEP+90, researchers will be able to describe some of the characteristics associated with the phenomenon of longevity. However, it will not be until the culmination of the second phase, in which an exhaustive clinical examination of a subsample of people over 90 free of dementia will be carried out, when a greater volume of data will be obtained with which to construct predictive longevity models. Using data mining techniques PILEP+90 will become an invaluable tool for the identification of healthy aging factors related to lifestyle and therefore susceptible to modification. The creation of algorithms based on the processing of clinical, cognitive, demographic, etc. data can guide health decision making and help implement individualized preventive programs. Ultimately, this research programme aims to delay the effects of cognitive ageing, reduce the risk of developing dementia, promote the level of functional independence and increase the quality of life of all older people.