Biodemography of human and non-human populations

One of the most important questions in research on the biodemography of human aging involves the extent to which early life conditions affect frailty and mortality at advanced ages. We addressed this question experimentally by manipulating dietary conditions of Mexican fruit fly cohorts at younger and older ages. The study yielded five main results: (1) frailty at transfer age (55 days) was far greater in flies maintained on lower quality diet (sugar) at early ages than those maintained on full diets for both sexes; (2) using mortality as a proxy, within-treatment frailty was far greater in males than in females at all advanced ages; (3) remaining life expectancy at advanced ages depended on both past and current dietary conditions for both sexes. Thus the mortality was not memoryless as has been reported in several other studies;. (4) after the initial 1- to 3-day mortality spike due to transfer stress, age-specific mortality for many treatments differed in scale but not in pattern—several were largely age-independent; (5) egg production in older females was drastically affected by past and current conditions. Implications for understanding the effects of early life experience on old age frailty and mortality in human populations will be discussed.

Low levels of fertility in Western countries are often attributed to men and women pursuing careers first and babies later. Research has shown considerable similarity between parents-children and siblings in completed fertility and education. This raises the possibility that the effect of education on fertility is not causal, but has a genetic basis and/or arises due to non-genetic factors of the family of origin. Relatively little research investigates the (common) genetic origin of these outcomes. Most of the existing bio-demographic research on fertility uses the Danish Twin Study (cf. Kohler and Rodgers). It is crucial to extend this line of research to other contexts to generalize findings and gain insight into possible environmental variability. Unfortunately, twin data are not readily available for most contexts, but genetic origins can also be investigated using information from multi-generation surveys using the so-called ‘animal model’. This is a mixed model that takes advantage of information on the relatedness of all individuals in a pedigree to estimate the genetic merit of an individual. We apply this model to the Netherlands Kinship Panel Study (8,200 families and 56,000 individuals) to investigate the role of additive genetic effects, maternal and paternal effects on (the co-variation of) fertility and education.

We present a theoretical model of behavior and nutrient allocation for organisms with discrete juvenile (larval) and adult stages, each with distinct diets, nutritional needs and foraging strategies. We predict optimal schedules of foraging and reproduction across a limited lifespan and examine the consequences for nutrient dynamics, paying particular attention to conditions under which it is optimal to tolerate starvation or to conserve resources and how these decisions affect mortality across the life cycle. We derive these optimal behavioral schedules assuming two alternative scenarios of environmental conditions, in which we do or do not impose deterioration in survival with age (senescence). We find that even in the absence of imposed senescence, terminal investment near the end of reproductive lifespans reduced survival probabilities of older individuals. We predicted earlier terminal investment and earlier senescence when reproductive overheads are low and when the survival costs of carbon depletion are small. Our findings suggest that resource allocation decisions alone are sufficient to produce signals of senescence and other age-patterns of mortality in animals optimizing decision schedules across their reproductive life cycles. We conclude that behavioral patterns of individuals can be strong drivers of observed d

The Gompertz distribution is often fitted to lifespan data, however testing whether the fit satisfies theoretical criteria was neglected. Here five goodness-of-fit measures, the Anderson-Darling statistic, the Kullback-Leibler discrimination information, the correlation coefficient test, testing for the mean of the sample hazard and a nested test against the generalized extreme value distributions are discussed. Along with an application to laboratory rat data, critical values calculated by the empirical distribution
of the test statistics are also presented.

At adult ages x, the force of mortality increases more or less exponentially with age, and the parameter associated with age, Beta, can be used to gauge the rate of senescence (ageing) of a generation. The hypothesis has recently been advanced that, with rare exceptions, the rate of senescence at the individual level is constant through space and time, and not far from 0.1.
We contribute to this discussion in two ways: first, we propose a new and simpler method to estimate the rate of senescence Beta when frailty and period effects operate, and, secondly, we offer a few empirical estimates for Beta, for various cohorts, in different countries (all data taken from the Human Mortality Database). The transformation that we suggest leads to a linear estimation, which is considerably simpler than all the others we are aware of, characterized by non-linear equations, numerical recursive likelihood maximization, etc.
Our estimates of the rate of senescence Beta are all very close to 0.1, but most of the differences that we detect (e.g. by country) are statistically significant, and there appears to be a decreasing trend of Beta over time.

Many industrialized societies experienced massive changes in both the postponement of age at first birth (tempo) and a drop in the total number of offspring (quantum) (Kohler, Billari & Ortega 2002; Mills et al. 2011). We carry out the first genome-wide-association-search (GWAS) meta-analysis to identify genes associated with age at first birth (AFB) and number of children ever born (NEB). GWAS represents a considerable methodological advance from previous approaches such as candidate-gene studies (Ku, Pawitan & Chia 2009). Previous research has demonstrated a genetic component to biological fecundity (Stolk et al, 2009) with twin studies estimating heritability of fertility behavior at approximately 40% (Kohler et al. 1999). Although research suggests an underlying genetic architecture of fertility behavior, the identification of genes is yet to be determined. Our meta-analysis combines GWAS findings of approximately 100,000 individuals from 52 cohorts, with preliminary results of the discovery stage completed by the IUSSP Conference.

It is a common assumption that men desire more children than women do in high fertility countries. Evolutionary demographers have tried to explain females’ relatively lower desired fertility by invoking the larger costs faced by women, a woman’s desire to invest more in each child, and a woman’s certainty that her children are genetically related to her. There are known trade-offs between the quantity and quality of children, but no clear reason why women and men should experience these differently. Furthermore, in the simplest scenario, in the case of strict (i.e. life-long) monogamy, since a man’s lifetime reproductive success is tied to that of his reproductive partner, both individuals should have the same optimal family size. In this paper we develop a theoretical framework for examining the circumstances under which we expect conflicts of interest between partnered men and women in their fitness-maximizing optimal number of offspring. Using evolutionary simulations and dynamic programming to model behaviour, we examine the effects of paternity uncertainty, reproductive senescence, and the ability to switch or acquire more partners on the extent to which women and men will have different optima regarding the numbers of offspring and the pace of reproduction.

We present a theoretical model of behavior and nutrient allocation for organisms with discrete juvenile (larval) and adult stages, each with distinct diets, nutritional needs and foraging strategies. We predict optimal schedules of foraging and reproduction across a limited lifespan and examine the consequences for nutrient dynamics, paying particular attention to conditions under which it is optimal to tolerate starvation or to conserve resources and how these decisions affect mortality across the life cycle. We derive these optimal behavioral schedules assuming two alternative scenarios of environmental conditions, in which we do or do not impose deterioration in survival with age (senescence). We find that even in the absence of imposed senescence, terminal investment near the end of reproductive lifespans reduced survival probabilities of older individuals. We predicted earlier terminal investment and earlier senescence when reproductive overheads are low and when the survival costs of carbon depletion are small. Our findings suggest that resource allocation decisions alone are sufficient to produce signals of senescence and other age-patterns of mortality in animals optimizing decision schedules across their reproductive life cycles. We conclude that behavioral patterns of individuals can be strong drivers of observed d

Many biodemographic studies incorporate biomarkers of physiological dysregulation and/or allostatic load. However, it is not clear how well these measures represent a global process of dysregulation, nor whether the various biomarkers incorporated into summary measures have been appropriately weighted or considered. Here we introduce a measure based on statistical distance – how common or rare a combination of variables is, according to its multivariate distribution – as an alternative approach to measuring physiological dysregulation. The measure is based on the principle that the more “strange” an individual’s biomarker profile is relative to a baseline population (used to define the distribution, ideally composed of young, healthy individuals), the more dysregulation is occurring. We use three examples to show strengths and limitations of the method. The biomarkers included must be chosen carefully (based on statistical or biological criteria) and the interpretation should be made in light of the variables included. Suites of appropriately chosen variables can help illuminate underlying physiology as well as serve as useful proxies for both mortality risk and biological age. Individual trajectories of statistical distance and in multivariate space are extensions that may help in understanding mortality and disease risk.

We explain how upward transfers from adult children to their elderly parents might evolve as an interrelated feature of a deepening intergenerational division of labor. Humans have a particularly long period of juvenile dependence requiring both food and care time provided mainly by younger and older adults. We suggest that the division of labor evolves to exploit comparative advantage between young and old adults in fertility, childcare and foraging. Eventually the evolving division of labor hits a corner when the grandmother's fertility reaches zero (menopause). Continuing, it may hit another corner when the grandmother's foraging time has been reduced to her subsistence needs. Further specialization can occur only with food transfers to the grandmother, enabling her to reduce her foraging time to concentrate on additional childcare. We prove that this outcome can arise only after menopause has evolved. We describe the conditions necessary for both group selection (comparative steady state reproductive fitness) and individual selection (successful invasion by a mutation), and interpret these conditions in terms of comparative advantages.