Prevalence and related factors of Active and Healthy Ageing in Europe according to two models: Results from the Survey of Health, Ageing and Retirement in Europe (SHARE)

Abstract

BackgroundActive and Healthy Ageing (AHA) is the process of optimizing opportunities related to health, participation, and safety in order to improve quality of life. The approach most often used to measure AHA is Rowe and Kahn’s Satisfactory Ageing model. Nonetheless, this model has limitations. One of the strategic objectives of the WHO Global Strategy and Action Plan (2016) is to improve Healthy Ageing measurement. Our objectives were to compare two models of assessing AHA and further compare the results by country and sociodemographic variables.MethodsThis was a cross-sectional, observational analysis of a representative sample of the general population aged 50 years and older in Europe. The data analysed were obtained by the Study of Health, Ageing and Retirement in Europe (SHARE). The dependent variable was AHA and its dimensions, measured using the Rowe and Kahn AHA model (AHA-B) and the authors’ model based on the WHO definition (AHA-BPS). A descriptive analysis and multivariate models of binary logistical regression were developed.ResultsThe sample consisted of 52,641 participants (mean age 65.24 years [SD = 10.18; Range = 50–104], 53.2% women). Healthy Ageing prevalence in the AHA-B model was 23.5% (95%CI = 23.1%-23.9%). In the AHA-BPS model, this prevalence was 38.9%. In both models, significant variations were observed between countries, and were distributed along a north-western to south-eastern gradient. The sociodemographic variables associated with the absence of AHA were advanced age, female sex, death of spouse, low educational level, lack of employment, and low financial status. Comparing the two models, the strength of association between absence of AHA and advanced age (85 years and older) was four times greater in the AHA-B model.ConclusionsOur results showing differences between these two models provide evidence that the AHA-BPS model does not penalize older age and is more likely to characterize AHA from a health promotion perspective.

Applying machine learning methods to develop a successful aging maintenance prediction model based on physical fitness tests

“…Compared with the rest of China, the SA prevalence in the present study was similar to that reported in Taiwan (26.5%), 12 higher than that in Hong Kong (0.7~33.1%) and lower than that in Shanghai (46.2%) . When compared with the rest of the world, these rates were higher than those reported in Brazil (25%) and in Europe (23.5%) . This discrepancy is likely related to different regions and economic levels.…”

The Impact of Population Aging and Public Health Support on EU Labor Markets

“…For the EU-15 countries, the focus has to be on the following policy interventions: A rethinking of passive labor market policies in order to sustain the 55-65-year-old working group, but also to target increases of active labor market policies for this age cohort; keeping up the R&D expenditure, oriented toward labor skills of the 55-64-year-old working group; reconsideration of EDU for 55-64-year-olds, levels 3-8, oriented towards migrants' inclusion in educational programs (since, in these countries, there is a large flow of migrants from developing countries) [73], and also to 55-64-year-olds for native working people by reshaping their skills as requirements are transformed by the emergence of new digital technologies [68,74]; oriented hospital services to boost healthy conditions and perceptions of people, and thus, making them confident in the public health expenditure in the case of child birth and care, therefore indirectly sustaining birth rates and life expectancy; further government health expenditure aimed at tackling the population aging phenomenon correlated with increasing long-term healthcare in the case of the elderly; and promoting and supporting preventive health actions among people aged 55-64 and low-and medium-educated people, since these categories are the most distant from health prevention, as Bremer et al [27] demonstrated. Under these cumulative interventions, labor productivity within developed EU MS will increase, with direct effects on wellbeing and overall economic development [10,20,[35][36][37][38].…”

“…When examining how this phenomenon influences policies within the EU-28 MS, it becomes obvious that, as some researchers have pointed out, "gloom and doom" predictions are frequently misplaced, and population aging does not present as heavy a social and economic burden as once considered [19,33,34]. On the contrary, aging populations have favorable impacts on labor productivity, as evidenced in multiple studies [10,20,[35][36][37][38]. Aging generates increases in the needs of old cohorts that are not as high as originally thought, and older individuals in good health tend to contribute long after retiring by providing compensated and uncompensated labor.…”

“…Based on these facts, the links between population aging and increases in healthcare costs [18][19][20], as well as their implications for labor productivity [21][22][23], have been intensively debated and documented in the scientific literature, but, to the best of our knowledge, comparisons of the EU's developed and developing countries have not been undertaken.…”

Healthy Ageing in Place: Enablers and Barriers from the Perspective of the Elderly. A Qualitative Study

“…HA is equated to life quality, which is relevantly determined by emotional, social and financial factors. Therefore, HA is mainly conditioned by the physical and emotional health, as well as by social aspects, encompassing a multidimensional perspective of the concept of health [ 45 ]. It is worth mentioning that, in 2018, the number of healthy life years at birth was estimated at 64.2 years for women and 63.7 years for men [ 46 ], while the life expectancy at birth in Europe for the same year was 81.0 years (78.3 years for men and 83.6 years for women) [ 47 ].…”