The main theories on population aging based on recent data on human longevity, life expectancy, morbidity changes, disability trends, and mortality decrease are presented and discussed within their own geographic, cultural, socioeconomic, and medical contexts. The complex interactions between all these components do not facilitate trend forecasting of aging population (healthy aging versus disability pandemic). In the context of population aging, four elements were introduced with their implications: 1) an increase in the survival rates of sick persons, which would explain the expansion of morbidity, 2) a control of the progression of chronic diseases, which would explain a subtle equilibrium between the decrease in mortality and the increase in disability, 3) an improvement of the health status and health behaviors of new cohorts of elderly people, which would explain the compression of morbidity, and eventually 4) an emergence of very old and frail populations, which would explain a new expansion of morbidity. Obviously, all these elements coexist today, and future trend scenarios-expansion or compression of disability-depend on their respective weights leading to the need of elaborating ''a general theory on population aging.'' This theory has to be based on a world harmonization of functional decline measurements and a periodic ''International Aging Survey'' to monitor global aging through a sample of carefully selected countries.

By showing the independent and combined effects of polypharmacy and frailty on mortality risk, this study should reinforce the awareness of clinicians with regard to these factors, rather prevalent in old people.

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This paper examines and demonstrates the importance of the adult modal age at death (M) in longevity research. Unlike life expectancy at birth (e 0) and median age at death, M is determined solely by old-age mortality as far as mortality follows a bathtub curve. It represents the location of old-age death heap in the age distribution of deaths, and captures mortality shifts more accurately than conditional life expectancies such as e 65. Although M may not be directly determined from erratic mortality data, a recently developed method for deriving M from the P-spline-smoothed mortality curve based on penalised Poisson likelihood is highly effective in estimating M. Patterns of trends and differentials in M can be noticeably different from those in other lifespan measures, as indicated in some examples. In addition, major mathematical models of adult mortality such as the Gompertz, logistic and Weibull models can be reformulated using M, which plays a critical role as the mortality level parameter in those models.

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Background: The global number of centenarians is still strongly growing and information about the health and healthcare needs of this segment of the population is needed. This study aimed to estimate the prevalence of frailty among centenarians included in a multinational study and to investigate associated factors. Methods: The 5-COOP study is a cross-sectional survey including 1,253 centenarians in 5 countries (Japan, France, Switzerland, Denmark, and Sweden). Data were collected using a standardized questionnaire during a face-to-face interview (73.3%), telephone interview (14.5%), or by postal questionnaire (12.2%). The 5 dimensions of the frailty phenotype (weight loss, fatigue, weakness, slow walking speed, and low level of physical activity) were assessed by using self-reported data. Factors associated with frailty criteria were investigated by using multivariate regression models. Results: Almost 95% of the participants had at least 1 frailty criterion. The overall prevalence of frailty (3 criteria or more) was 64.7% (from 51.5% in Sweden to 77.6% in Switzerland), and 32.2% of the participants had 4 or 5 criteria. The most frequent criteria were weakness (84.2%), slow walking speed (77.6%), and low level of physical activity (72.5%), followed by fatigue (43.8%) and weight loss (23.8%). Factors associated with frailty included data collection modes, country of residence, gender, living in institution, depression, dementia, disability, falls, and sensory impairments. Conclusions: This study shows that reaching 100 years of age rarely goes without frailty and sheds light on factors associated with frailty at a very old age.

In the absence of data, and particularly of chronological series on the health status of elderly populations, three theories about the future health status of old people were

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