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The ageing of the population is an issue in wealthy countries worldwide because of increasing costs for health care and welfare. Survival curves taken from demographic life tables may help shed light on the hypotheses that humans are living longer and that human populations are growing older. We describe a methodology that enables us to obtain separate measurements of scale and shape variances in survival curves. Specifically, 'living longer' is associated with the scale variance of survival curves, whereas 'growing older' is associated with the shape variance. We show how the scale and shape of survival curves have changed over time during recent decades, based on period and cohort female life tables for selected wealthy countries. Our methodology will be useful for performing better tracking of ageing statistics and it is possible that this methodology can help identify the causes of current trends in human ageing.

The existence of maximum human lifespan remains a puzzle in aging research. Maximum human lifespan is believed to be around 125 years, whereas current demographic trends seem to show no limitation. To reconcile this contrast, the estimation of maximum human lifespan requires an adequate mathematical model. However, sparse data of available old-age mortality pattern make the estimation impossible. Here we suggest an extended Weibull model for the estimation using a proper mathematical method based on survival probability pattern. We find a tendency that survival probability is maximized in modern human survival curves. Based on such tendency, we develop an estimation method for maximum human lifespan and indeed obtain about 126 years from periodic life tables for Swedish female between 1950 and 2005. Despite uncertainty from available mortality data, our approach may offer quantitative biodemographic opportunities linking aging and survival kinetics.