The case for negative senescence

Negative senescence is characterized by a decline in mortality with age after reproductive maturity, generally accompanied by an increase in fecundity. Hamilton (1966) ruled out negative senescence: we adumbrate the deficiencies of his model. We review empirical studies of various plants and some kinds of animals that may experience negative senescence and conclude that negative senescence may be widespread, especially in indeterminate-growth species for which size and fertility increase with age. We develop optimization models of life-history strategies that demonstrate that negative senescence is theoretically possible. More generally, our models contribute to understanding of the evolutionary and demographic forces that mold the agetrajectories of mortality, fertility and growth.

The cost of population aging: forecasting future hospital expenses in Germany

Forecasts are always wrong. Still, they paint potential future scenarios and provide a platform for policy decisions today. This is what gives forecast such a high salience in political debates about the effects of population aging. The paper aims at gauging the effect of population aging on hospital expenses in Germany. We use a probabilistic forecast model comprising a stochastic demographic component that exploits historical mortality trends, a stochastic cost component based on typical hospital costs over the life-course, and a quality measure of medical progress, which builds on past advances in hospital treatment. Three different scenarios are constructing, yielding 3 important results. Firstly, there is an increase in overall hospital expenditure until the German baby boomers will die out (2040 to 2050). Secondly, the increase is comparably moderate because the average individual costs are likely to decline as elderly health improves and since medical progress has an ambiguous influence on hospital expenditures. Finally, the cost increase varies significantly by gender and disease.

Modelling trends in digit preference patterns

Digit preference is the habit of reporting certain end digits more often than others. If such a misreporting pattern is a concern, then measures to reduce digit preference can be taken and monitoring changes in digit preference becomes important. We propose a two-dimensional penalized composite link model to estimate the true distributions unaffected by misreporting, the digit preference pattern and a trend in the preference pattern simultaneously. A transfer pattern is superimposed on a series of smooth latent distributions and is modulated along a second dimension. Smoothness of the latent distributions is enforced by a roughness penalty. Ridge regression with an L1-penalty is used to extract the misreporting pattern, and an additional weighted least squares regression estimates the modulating trend vector. Smoothing parameters are selected by the Akaike information criterion. We present a simulation study and apply the model to data on birth weight and on self-reported weight of adults

Do men avoid seeking medical advice? A register-based analysis of gender-specific changes in primary healthcare use after first hospitalisation at ages 60+ in Denmark

The work was supported by the US National Institute of Health (P01AG031719, R01AG026786, and 2P01AG031719), the VELUX Foundation and the Max Planck Society within the framework of the project “On the edge of societies: New vulnerable populations, emerging challenges for social policies and future demands for social innovation. The experience of the Baltic Sea States (2016-2021)”.Background  It remains unclear whether women’s greater primary healthcare use reflects a lower treatment-seeking threshold or a health disadvantage. We address this question by studying primary healthcare use surrounding a major health shock. Methods  This cohort study utilises routinely-collected healthcare data covering the Danish population aged 60+ years between 1996 and 2011. Using a hurdle model, we investigate levels of non-use and levels of primary healthcare use before and after first inpatient hospitalisation for stroke, myocardial infarction (MI), chronic obstructive pulmonary disease (COPD) and gastrointestinal cancers (GIC). Results  Before hospitalisation, irrespective of cause, men were more likely than women to be non-users of primary healthcare (OR (95% CI): stroke 1.802 (1.731 to 1.872); MI 1.841 (1.760 to 1.922); COPD 2.160 (2.028 to 2.292); GIC 1.609 (1.525 to 1.693)). Men who were users had fewer primary healthcare contacts than women (proportional change (eβ) (95% CI): stroke 0.821 (0.806 to 0.836); MI 0.796 (0.778 to 0.814); COPD 0.855 (0.832 to 0.878); GIC 0.859 (0.838 to 0.881)). Following hospitalisation, changes in the probability of being a non-user (OR (95% CI): stroke 0.965 (0.879 to 1.052); MI 0.894 (0.789 to 0.999); COPD 0.755 (0.609 to 0.900); GIC 0.895 (0.801 to 0.988)) and levels of primary healthcare use (eβ (95% CI): stroke 1.113 (1.102 to 1.124); MI 1.112 (1.099 to 1.124); COPD 1.078 (1.063 to 1.093); GIC 1.097 (1.079 to 1.114)) were more pronounced among men. Gender differences widened after accounting for survival following hospitalisation. Conclusion  Women’s consistently higher levels of primary healthcare use are likely to be explained by a combination of a lower treatment-seeking threshold and a health disadvantage resulting from better survival in bad health.Publisher PDFPeer reviewe

Rejoinder to “The Prevalence of Cognitive Impairment Is Not Increasing in the United States: A Critique of Hale et al. (2020)”

Non peer reviewe

Is who you ask important? Concordance between survey and registry data on medication use among self- and proxy-respondents in the longitudinal study of aging Danish twins and the Danish 1905-cohort study

This work was supported by the U.S. National Institute of Health (P01AG031719, R01AG026786 and 2P01AG031719), the VELUX Foundation, and the Max Planck Society within the framework of the project “On the edge of societies: New vulnerable populations, emerging challenges for social policies and future demands for social innovation. The experience of the Baltic Sea States (2016–2021).”Background This study investigates the accuracy of the reporting of medication use by proxy- and self-respondents, and it compares the prognostic value of the number of medications from survey and registry data for predicting mortality across self- and proxy-respondents. Methods The study is based on the linkage of the Longitudinal Study of Aging Danish Twins and the Danish 1905–Cohort Study with the Danish National Prescription Registry. We investigated the concordance between survey and registry data, and the prognostic value of medication use when assessed using survey and registry data, to predict mortality for self- and proxy-respondents at intake surveys. Results Among self-respondents, the agreement was moderate (κ = 0.52–0.58) for most therapeutic groups, whereas among proxy-respondents, the agreement was low to moderate (κ = 0.36–0.60). The magnitude of the relative differences was, generally, greater among proxies than among self-respondents. Each additional increase in the total number of medications was associated with 7%–8% mortality increase among self- and 4%–6% mortality increase among proxy-respondents in both the survey and registry data. The predictive value of the total number of medications estimated from either data source was lower among proxies (c-statistic = 0.56–0.58) than among self-respondents (c-statistic = 0.74). Conclusions The concordance between survey and registry data regarding medication use and the predictive value of the number of medications for mortality were lower among proxy- than among self-respondents.Publisher PDFPeer reviewe

Bilinear modulation models for seasonal tables of counts

We propose generalized linear models for time or age-time tables of seasonal counts, with the goal of better understanding seasonal patterns in the data. The linear predictor contains a smooth component for the trend and the product of a smooth component (the modulation) and a periodic time series of arbitrary shape (the carrier wave). To model rates, a population offset is added. Two-dimensional trends and modulation are estimated using a tensor product B-spline basis of moderate dimension. Further smoothness is ensured using difference penalties on the rows and columns of the tensor product coefficients. The optimal penalty tuning parameters are chosen based on minimization of a quasi-information criterion. Computationally efficient estimation is achieved using array regression techniques, avoiding excessively large matrices. The model is applied to female death rate in the US due to cerebrovascular diseases and respiratory diseases