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Recent studies have shown that there are some advantages in forecasting mortality with other indicators than death rates. In particular, the age-at-death distribution provides readily available information on central longevity measures: mean, median and mode, as well as information on lifespan variation. The modal age at death has been increasing linearly since the second half of the 20th century, providing a strong basis to extrapolate past trends. We develop a model to forecast the age-at-death distribution that directly forecasts the modal age at death and lifespan variation while accounting for dependence between ages. We forecast mortality at age 40 and above in six Western European countries. The introduced model increases forecast accuracy compared with other forecasting models and provides consistent trends in life expectancy and lifespan variation at age 40 over time.

Previous research has shown differentiated effects of living arrangement types on mortality. However, little is known about this phenomenon in Latin America and its multigenerational households. This study measures the relationship between older adults’ living arrangement types and subsequent mortality. Gompertz event history models were performed to estimate mortality differences across living arrangements. We used the Costa Rica Longevity and Aging Study (CRELES) pre-1945 cohort in the 2005, 2007, and 2009 waves. The results show that older adults who live with a partner have the highest survival rates among the categories tested. When controlling for sex and age in the model, the effect of living alone is not different from partnered living. When controlling for socioeconomic and health factors as well, older adults living with their children or others show an increased risk of death by at least 40% (p-value<0.05). The study demonstrates an association between living arrangements and older adult mortality in Costa Rica. Results show that the highest survival chances rely on being partnered and suggest that support exchanges with other family members are not equally effective. Including this variable type in mortality studies is crucial to better understanding how household conditions relate to health and mortality outcomes.

BACKGROUND The modal age at death (mode) is an important indicator of longevity, that is associated with different mortality regularities. Accurate estimates of the mode are essential, but existing methods are not always able to provide them. OBJECTIVE Our objective is to develop a method to estimate the modal age at death, using its mathematical properties, in an assumptions-free setting. METHODSThe mode maximizes the density of the age-at-death distribution. In addition, at the mode, the rate of aging equals the force of mortality. Using these properties, we developed a discrete procedure to estimate the mode. We compare our estimates with those of other models.RESULTS Both the modal age at death and the rate of aging have been increasing since 1960 in low-mortality countries. The method we suggest produces close estimates to the ones generated by the P-splines smoothing. CONCLUSIONSThe modal age at death plays a central role in estimating progress in longevity, quantifying mortality postponement, and estimating the rate of aging. The novel method proposed here allows for a simple and assumptions-free estimation of the modal age at death, which fulfills its mathematical properties and is not computationally demanding.CONTRIBUTION Our research was motivated by James W. Vaupel, who wanted to find a way to estimate the mode based on its mathematical properties as a part of one of his latest research grants. This article also expands on some of his last research papers that link the modal age at death for populations to the one for individuals.