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Method development for ageing research

We develop novel demographic models and statistical methods to explore the causes and consequences of the age-specific trajectories of survival across the tree of life.


The aim of the Methods Research Section is to develop novel demographic models and statistical methods to explore the causes and consequences of the age-specific trajectories of survival and fecundity in humans and across the tree of life. We are a group of interdisciplinary researchers spanning mathematics, statistics, formal demography and biology most of whom have strong mathematical and statistical interests and skills. Our work can be divided into three main research areas:

  1. Statistical inference, where we are developing Bayesian inference models for age-specific survival and fecundity when age information is missing, and models to estimate smooth distributions of ages at death from grouped demographic data (e.g. life tables);
  2. Mortality forecasting, where we are exploring novel methods to predict future life expectancy and their societal implications in terms of current policies and future reforms, as well as developing integrated population models to understand the population dynamics of species of conservation and commercial value;
  3. Mathematical demography, where we are deriving the mathematical framework that explains the surprising linear relationship between life expectancy and lifespan equality found in humans and other species, as well as developing discrete approximations to continuous demographic functions (e.g. life table entropy).

Our methods and their applications have been featured in wide range of scientific journals, from high impact journals such as PNAS, to specialized journals such as Aging Cell or Methods in Ecology and Evolution.

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We summarized the findings of some of the most significant demographic publications on human longevity. We discuss diverse theories on longevity and place current levels of life expectancy in a historical context. Despite general beliefs of a limit to human longevity, there is a sustained increase in life expectancy since the 19th century. In the countries doing best each year, life expectancy started to increase around 1840 at a pace of almost 2.5 years per decade and this trend has continued in the recent past. If the current pace of progress in life expectancy continues, most children born this millennium will celebrate their 100th birthdays. However, considerable uncertainty clouds forecasts of life expectancy. We discuss possible future development in health and longevity, as well as forecasting approaches and their limitations. As further increase in longevity would bring important social, economic, health, cultural and political repercussions, the development of more powerful methods of forecasting should be a priority.

Best-practice life expectancy at birth, 1840-2017
Figure: Best-practice life expectancy at birth, 1840-2017
Note: Adapted from Oeppen and Vaupel (2002) using the most recent data from the Human Mortality Database.

"How long will I live?" This is a question of interest to individuals, physicians, public health officials, actuaries, demographers and policy makers.

Mortality forecasts support social, economic, and medical decisions as well as individuals’ choices, for example, about savings and retirement. Because future life expectancy and life tables estimates have such economic and political implications, they are subject to intense scrutiny and accurate forecasts are crucial.

Our methodologies address important challenges in forecasting and provide innovative alternatives, generally showing increased accuracy compared to commonly used methods. We have been especially interested in the use of different life table statistics to forecasting and finding practical ways to include health information into the forecasts, such as causes of death.

We also assess the consequences that the different forecasting methods have for individuals, but also for the health care system and for the economy and society more generally – and the implications for policy. Our findings have implications for employment, education, and the various far-reaching changes resulting from longer, healthier lives and population aging.

Actual and forecast life expectancy at birth generated by the Double-Gap Model for Swedish females and males, 1950–2050.

Our methodologies address important challenges in forecasting and provide innovative alternatives, generally showing increased accuracy compared to commonly used methods. We have been especially interested in the use of different life table statistics to forecasting and finding practical ways to include health information into the forecasts, such as causes of death.

 

We also assess the consequences that the different forecasting methods have for individuals, but also for the health care system and for the economy and society more generally – and the implications for policy. Our findings have implications for employment, education, and the various far-reaching changes resulting from longer, healthier lives and population aging.

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