Physiological and metabolic characterization of older adults. Especial focus on cardiorespiratory fitness and its role on cognitive function

Resumen

Advances in modern medicine from developing countries have caused an increase in overall life expectancy and consequently among the older adults population. Ageing is a multifactorial and multi-organic process characterized by decreases in physiological functions, among others, causing deterioration of the physical integrity, and increases in the incidence of health-related problems and non-communicable diseases. Dementia is one of the most common and relevant non-communicable diseases, and in fact, it is one of the main causes of dependency and disability in older adults. Scientific evidence supports that regular exercise has positive effects on ageing process and promotes brain health in older adults. There is a special interest on the relationship between physical fitness and brain health, particularly, the role of cardiorespiratory fitness (CRF) as a powerful health marker in different population groups. Scientific literature has clearly shown an inverse association of CRF with the incidence of many chronic diseases and all-cause mortality. Therefore, to better know the factors that determine and predict CRF level is essential to develop interventions for enhancing both determinants and CRF. Since these factors have been identified in young and middle-aged adults but not clearly in older adults, additional investigation on this topic is needed. Therefore, the main aim of this International Doctoral Thesis was to analyse the physiological, metabolic and cardiovascular determinants of CRF and to develop new and specific equations to predict CRF in older adults. Additionally, the current thesis aimed to study the associations of CRF, both objectively-measured and estimated using new equations, with cognitive function in this population. The sample comprised of 92 people (41 females) between 65 and 75 years from the EFFICOM project (NCT03923712), recruited through the Public Health Care Centers of the province of Cadiz. Participants completed 4 measurements sessions including: i) laboratory measurements of body composition, resting cardiovascular, metabolic and spirometry parameters, and CRF by the modified Bruce incremental test; ii) field assessments of Senior Fitness Test Battery and handgrip test; iii) self-reported questionnaires and interviews on sociodemographic characteristics, activities of daily living and physical activity; and iv) a complete battery of neuropsychological tests to evaluate cognitive function. The main findings of this thesis indicate that: i) The physiological, metabolic and cardiovascular characteristics of older adults were different between males and females, ii) body composition, resting cardiovascular and metabolic parameters, spirometry values and physical fitness performance were identified as relevant and independent determinants of CRF, iii) fifteen equations have been developed with the high prediction values for CRF of older adults. Three different complexity levels were considered; Level 1) basic variables such as body composition parameters, meeting physical activity recommendations, field tests and basal metabolic and cardiovascular parameters; Level 2) basic variables plus spirometry parameters; and Level 3) basic variables, spirometry parameters and simple cardiopulmonary exercise test (CPET) information. The best equation models proposed, from levels 1 and 2, explain 80% of the variability of CRF and, when using maximum HR and time to exhaustion from the CPET (level 3), the best model proposed reach to explain 87% of the variability of CRF, and iv) CRF, both objectively-measured and estimated, were associated with better performance on language, fluency and cognitive flexibility independently of sex, age and education level. The findings of the present International Doctoral Thesis identify key determinants and predictors of CRF, and suggest CRF may be a protective factor against the deterioration of cognitive function associated with ageing in older adults, providing different predictive equations for CRF with low cost and high feasibility.