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Objective: Studies on child malnutrition find no evidence of gender difference in childhood stunting (48% for both boys and girls) in India. Several States show a better nutritional status of girls than boys. Therefore, we argued that in an environment of high mortality among girls, the surviving girls are highly wanted and thus are healthier. Therefore, child nutritional status cannot be studied independent of mortality. Methods: We used three rounds of data from the National Family Health Survey 1992-93,1998-99,2015-16 to examine whether Indian girls are really better nourished than boys. Height for age z-score (HAZ), as defined by the World Health Organization was used to measure the health of children. We first imputed the HAZ for dead boys and girls using multiple imputation techniques. Second, these imputed HAZ for dead boys and girls were combined with HAZ of surviving boys and girls to provide a simulated HAZ separately for boys and girls. Results: Results show that relative reduction in average HAZ was slightly higher for girls than boys in each of three rounds of NFHS. Although the relative decline in average HAZ was higher for girls than boys, the simulated z-scores after incorporating the average HAZ for dead children suggest no significant difference between the overall HAZ of boys and girls in any of the three surveys. Conclusion: We do not find enough evidence to establish the effect of mortality selection in explaining the better nutritional status of girls compared with boys in India. Our findings are consistent across the three rounds of NFHS and at different levels of mortality.

What is the average lifespan in a stationary population viewed at a single moment in time? Even though periods and cohorts are identical in a stationary population, we show that the answer to this question is not life expectancy but a length-biased version of life expectancy. That is, the distribution of lifespans of the people alive at a single moment is a self-weighted distribution of cohort lifespans, such that longer lifespans have proportionally greater representation. One implication is that if death rates are unchanging, the average lifespan of the current population always exceeds period life expectancy. This result connects stationary population lifespan measures to a well-developed body of statistical results; provides new intuition for established demographic results; generates new insights into the relationship between periods, cohorts, and prevalent cohorts; and offers a framework for thinking about mortality selection more broadly than the concept of demographic frailty. [ABSTRACT FROM AUTHOR]

Theoretical models of mortality selection have great utility in explaining otherwise puzzling phenomena. The most famous example may be the Black-White mortality crossover: at old ages, Blacks outlive Whites, presumably because few frail Blacks survive to old ages while some frail Whites do. Yet theoretical models of unidimensional heterogeneity, or frailty, do not speak to the most common empirical situation for mortality researchers: the case in which some important population heterogeneity is observed and some is not. I show that, when one dimension of heterogeneity is observed and another is unobserved, neither the observed nor the unobserved dimension need behave as classic frailty models predict. For example, in a multidimensional model, mortality selection can increase the proportion of survivors who are disadvantaged, or "frail," and can lead Black survivors to be more frail than Whites, along some dimensions of disadvantage. Transferring theoretical results about unidimensional heterogeneity to settings with both observed and unobserved heterogeneity produces misleading inferences about mortality disparities. The unusually flexible behavior of individual dimensions of multidimensional heterogeneity creates previously unrecognized challenges for empirically testing selection models of disparities, such as models of mortality crossovers. [ABSTRACT FROM AUTHOR]

Prenatal exposures have meaningful effects on health across the life course. Innovations in causal inference have shed new light on these effects. Here, we motivate the importance of innovation in the characterization of fecundity, and prenatal selection in particular. We argue that such innovation is crucial for expanding knowledge of the fetal origins of later life health. Pregnancy loss is common, responsive to environmental factors, and closely related to maternal and fetal health outcomes. As a result, selection into live birth is driven by many of the same exposures that shape the health trajectories of survivors. Life course effects that are inferred without accounting for these dynamics may be significantly distorted by survival bias. We use a set of Monte Carlo simulations with realistic parameters to examine the implications of prenatal survival bias. We find that even in conservatively specified scenarios, true fetal origin effects can be underestimated by 50% or more. In contrast, effects of exposures that reduce the probability of prenatal survival but improve the health of survivors will be overestimated. The absolute magnitude of survival bias can even exceed small-effect sizes, resulting in inferences that beneficial exposures are harmful or vice versa. We also find reason for concern that moderately sized true effects, underestimated due to failure to account for selective survival, are missing from scientific knowledge because they do not clear statistical significance filters. This bias has potential real-world costs; policy decisions about interventions to improve maternal and infant health will be affected by underestimated program impact. [ABSTRACT FROM AUTHOR]

About 200 million children globally are not meeting their growth potential, and as a result will suffer the consequences in terms of future outcomes. I examine the effects of birth weight on child health and growth using information from 66 countries. I account for missing data and measurement error using instrumental variables and adopt an identification strategy based on siblings and twins. I find a consistent effect of birth weight on mortality risk, stunting, wasting, and coughing, with some evidence for fever, diarrhoea, and anaemia. Bounds analysis indicates that coefficients may be substantially underestimated due to mortality selection. Improving the pre-natal environment is likely to be important for helping children reach their full potential. [ABSTRACT FROM AUTHOR]

Background: A growing body of literature has reported widening educational health disparities across birth cohorts or time periods in the United States, but research has paid little attention to the implication of mortality selection on the cohort trend in health disparities. Objective: This study investigates how changes in the variance of unobserved frailty over time may complicate the interpretation of cohort trends in health disparities and life expectancy. Methods: We use the microsimulation method to test the effect of mortality selection and further propose a counterfactual simulation procedure to estimate its contribution. Data used in the simulations are based on Panel Studies of Income Dynamics 1968-2013, National Health and Nutrition Examination Survey data 1999‒2012, and National Health Interview Survey data 1986‒2011. Results: Simulation shows that mortality selection may generate seemingly contradictory trends in health disparities and life expectancy across birth cohorts at the group and individual level. Life expectancy can change even when the individual mortality curve is fixed. In the absence of a change in the causal effect of education on mortality at the individual level, an educational life expectancy gap can change across cohorts as a result of the change in frailty variance. Empirical analysis shows that mortality selection accounts for a sizeable amount of contribution to the widening educational life expectancy gap from the 1950s to 1960s birth cohorts in the United States. Contribution: We demonstrate how mortality selection can complicate the cohort trend in health disparities and life expectancy and propose a counterfactual simulation method to evaluate its contribution.

With the rapid increase in the population of the oldest old (those aged 80 and over), there is some concern how longer life might be associated with a loss of independence in daily living. Addressing the trajectory of loss of independence for the oldest old is challenging, not only because the oldest old are heterogeneous, but also because the health trajectories at the population level may noticeably differ from those at the individual level. We used the 1998, 2000, 2002, 2005 and 2008 waves of the Chinese Longitudinal Healthy Longevity Study to assess the age trajectories of the loss of independence for three cohorts born in 1909-1918, 1899-1908 and 1893-1898, respectively, both at the individual and the population levels. Independence was measured by combining the activities of daily living and the Chinese version of the mini-mental state examination. Controlling for various confounding factors, particularly the selectivity due to death and loss to follow-up, we found that, while more recent cohorts had higher initial levels of independence, this was followed by a faster decline compared to the earlier cohorts. Also, their level of independence fell below that of their earlier born counterparts at the same ages. Decomposition analysis further illustrated that the decline of independence at the population level is more gradual than that at the individual level. This finding can be largely attributed to selective mortality and loss to follow-up. For instance, the population prevalence of independence for the 1893-1898 female cohort declined slightly, from 19.7 to 11.1% in 1998-2008, while the proportion for females who survived from 1998 to 2008 dropped from 66.7 to 11.1%. For the population as a whole, a longer life expectancy does not necessarily result in a rapid decline of independence. For individuals, longer life expectancy accompanies deterioration of independence. [ABSTRACT FROM AUTHOR]

A shorter lifespan as a potential cost of high reproductive effort in humans has intrigued researchers for more than a century. However, the results have been inconclusive so far and despite strong theoretical expectations we do not currently have compelling evidence for the longevity costs of reproduction. Using Monte Carlo simulation, it is shown here that a common practice in human reproduction-longevity studies using historical data (the most relevant data sources for this question), the omission of women who died prior to menopausal age from the analysis, results in severe underestimation of the potential underlying trade-off between reproduction and lifespan. In other words, assuming that such a trade-off is expressed also during reproductive years, the strength of the trade-off between reproduction and lifespan is progressively weakened when women dying during reproductive ages are sequentially and non-randomly excluded from the analysis. In cases of small sample sizes (e.g. few hundreds of observations), this selection bias by reducing statistical power may even partly explain the null results commonly found in this field. Future studies in this field should thus apply statistical approaches that account for or avoid selection bias in order to recover reliable effect size estimates between reproduction and longevity. [ABSTRACT FROM AUTHOR]

Objective: Several studies have suggested that cancer is associated with a reduced risk of the development of Alzheimer's disease (AD). This study seeks to improve our understanding of the association between cancer and the development of AD by showing how mortality selection alters this relationship. Method: A retrospective cohort study was carried out examining 92,425 individuals (47,873 women and 44,552 men) from the Utah Population Database with and without a history of any primary cancer identified by the Utah Cancer Registry. All individuals were aged 65-79 years and free of dementia in 1992 and followed for upwards of 18 years (1992-2009) for AD ascertainment, which was identified using diagnostic information from Medicare claims data. Results: We replicate previous results suggesting that cancer is associated with reduced risk of subsequent AD under specific statistical model specifications. However, these results should not be interpreted as evidence of an etiological association. We conclude that higher rates of overall mortality among individuals with cancer relative to those without cancer induce the widely reported putative protective association with cancer. Conclusion: Careful consideration of model specification and the profound effects of mortality selection in the older adult population is essential when investigating the relationship between aging-related diseases such as cancer and AD. We show that cancer does not provide protection from AD as previously described in the literature. Social scientists seeking to understand social disparities in disease outcomes among older adults may therefore want to strongly consider the role of mortality selection which, if uncorrected, may generate biased associations. [ABSTRACT FROM AUTHOR]

Existing estimates of sociodemographic disparities in chronic pain in the United States are based on cross-sectional data, often treat pain as a binary construct, and rarely test for nonresponse or other types of bias. This study uses 7 biennial waves of national data from the Health and Retirement Study (1998-2010; n = 19,776) to describe long-term pain disparities among older (age 51+) American adults. It also investigates whether pain severity, reporting heterogeneity, survey nonresponse, and/or mortality selection might bias estimates of social disparities in pain. In the process, the article clarifies whether 2 unexpected patterns observed cross-sectionally-plateauing of pain above age 60, and lower pain among racial/ethnic minorities-are genuine or artefactual. Findings show high prevalence of chronic pain: 27.3% at baseline, increasing to 36.6% thereafter. Multivariate latent growth curve models reveal extremely large disparities in pain by sex, education, and wealth, which manifest primarily as differences in intercept. Net of these variables, there is no racial/ethnic minority disadvantage in pain scores, and indeed a black advantage vis-à-vis whites. Pain levels are predictive of subsequent death, even a decade in the future. No evidence of pain-related survey attrition is found, but surveys not accounting for pain severity and reporting heterogeneity are likely to underestimate socioeconomic disparities in pain. The lack of minority disadvantage (net of socioeconomic status) appears genuine. However, the age-related plateauing of pain observed cross-sectionally is not replicated longitudinally, and seems partially attributable to mortality selection, as well as to rising pain levels by birth cohort. [ABSTRACT FROM AUTHOR]

This paper shows that the effects of causal SNPs on lifespan, estimated through GWAS, may be confounded and the genetic structure of the study population may be responsible for this effect. Simulation experiments show that levels of linkage disequilibrium (LD) and other parameters of the population structure describing connections between two causal SNPs may substantially influence separate estimates of the effect of the causal SNPs on lifespan. This study suggests that differences in LD levels between two causal SNP loci within two study populations may contribute to the failure to replicate previous GWAS findings. The results of this paper also show that successful replication of the results of genetic association studies does not necessarily guarantee proper interpretation of the effect of a causal SNP on lifespan.

This paper shows that the effects of causal SNPs on lifespan, estimated through GWAS, may be confounded and the genetic structure of the study population may be responsible for this effect. Simulation experiments show that levels of linkage disequilibrium (LD) and other parameters of the population structure describing connections between two causal SNPs may substantially influence separate estimates of the effect of the causal SNPs on lifespan. This study suggests that differences in LD levels between two causal SNP loci within two study populations may contribute to the failure to replicate previous GWAS findings. The results of this paper also show that successful replication of the results of genetic association studies does not necessarily guarantee proper interpretation of the effect of a causal SNP on lifespan. [ABSTRACT FROM AUTHOR]

When investigating relationships between education and health, one has to take age into account. Conditioning on age entails conditioning on surviving, which has been argued to lead to a potential selection bias. In this note, I argue that surviving should be considered as a necessary precondition for the relationships of interest and, therefore, not as a possible source of bias. I criticize models of health trajectories that do not condition on surviving. [ABSTRACT FROM AUTHOR]

This paper investigates historical changes in both single-year-of-age adult mortality rates and variation of the single-year mortality rates around expected values within age intervals over the past two centuries in 15 developed countries. We apply an integrated hierarchical age-period-cohort-variance function regression model to data from the human mortality database. We find increasing variation of the single-year rates within broader age intervals over the life course for all countries, but the increasing variation slows down at age 90 and then increases again after age 100 for some countries; the variation significantly declined across cohorts born after the early 20th century; and the variation continuously declined over much of the last two centuries but has substantially increased since 1980. Our further analysis finds the recent increases in mortality variation are not due to increasing proportions of older adults in the population, trends in mortality rates, or disproportionate delays in deaths from degenerative and man-made diseases, but rather due to increasing variations in young and middle-age adults. [ABSTRACT FROM AUTHOR]

Background: The impact of extreme conditions on survival has been the focus of mortality studies using military data. However, in countries at peace, the military live in favorable conditions, being positively selected with respect to health. In this type of context, military data may help to improve our understanding of mortality differentials, particularly in countries where defective vital systems are still cumbersome for mortality studies. Methods: We estimate death rates for Brazilian Air Force (BAF) officers through Poisson regression models, compute life expectancies, and compare them with those of average Brazilians and people in low-mortality countries. We also examine causes of death and mortality differentials through a competing risks framework and Fine and Gray regression models. Results: BAF life expectancy is higher than that of the average Brazilian and comparable to Sweden, France, and Japan in 2000. Younger pilots have a higher risk of dying on duty when compared with other officers but experience lower mortality rates from other causes at advanced ages. Conclusions: BAF officers are a population subgroup in Brazil with a life expectancy comparable to the one in advanced societies. There is no association between mortality and place of birth, which indicates that different childhood backgrounds did not affect BAF mortality differentials later in life. Contribution: This paper takes a novel approach focusing on a specific subgroup with lower mortality rates than the general population and good-quality longitudinal information available, a rarity in developing countries. We argue that this approach can be an interesting strategy to study mortality differentials in developing countries.

This paper considers whether short-term variation in exposure to disease early in life, as measured by a variety of mortality rates, has an effect on the height of young adults. Height information for men born in southern Sweden, 1814–1948, and included in the Scanian Economic Demographic Database (SEDD), was obtained from records of medical inspections carried out as part of Sweden’s system of universal conscription. Community-level infant mortality rates were calculated not only by year of birth but also for time in utero and in the first year of life. Comparison between brothers was used to remove the influence of confounding factors. The results suggest that any effect that exposure to disease in early life, as measured by mortality rates, may have had on height, either through selection or scarring, is likely to have been very weak. Supplementary material for this article is available at: http://dx.doi.org/10.1080/00324728.2015.1045545 [ABSTRACT FROM PUBLISHER]

Blacks experience morbidity and mortality earlier in the life course compared to whites. Such premature declines in health may be indicative of an acceleration of the aging process. The current study uses data on 7644 black and white participants, ages 30 and above, from the third National Health and Nutrition Examination Survey, to compare the biological ages of blacks and whites as indicated from a combination of ten biomarkers and to determine if such differences in biological age relative to chronological age account for racial disparities in mortality. At a specified chronological age, blacks are approximately 3 years older biologically than whites. Differences in biological age between blacks and whites appear to increase up until ages 60–65 and then decline, presumably due to mortality selection. Finally, differences in biological age were found to completely account for higher levels of all-cause, cardiovascular and cancer mortality among blacks. Overall, these results suggest that being black is associated with significantly higher biological age at a given chronological age and that this is a pathway to early death both overall and from the major age-related diseases. [ABSTRACT FROM AUTHOR]

This study examines historical patterns of aging through the perspectives of cohort evolution and mortality selection, where the former emphasizes the correlation across cohorts in the age dependence of mortality rates, and the latter emphasizes cohort change in the acceleration of mortality over the life course. In the analysis of historical cohort mortality data, I find support for both perspectives. The rate of demographic aging, or the rate at which mortality accelerates past age 70, is not fixed across cohorts; rather, it is affected by the extent of mortality selection at young and late ages. This causes later cohorts to have higher rates of demographic aging than earlier cohorts. The rate of biological aging, approximating the rate of the senescence process, significantly declined between the mid- and late-nineteenth century birth cohorts and stabilized afterward. Unlike the rate of demographic aging, the rate of biological aging is not affected by mortality selection earlier in the life course but rather by cross-cohort changes in young-age mortality, which cause lower rates of biological aging in old age among later cohorts. These findings enrich theories of cohort evolution and have implications for the study of limits on the human lifespan and evolution of aging. [ABSTRACT FROM AUTHOR]

Provocative studies have reported that in the United States, marriages producing firstborn daughters are more likely to divorce than those producing firstborn sons. The findings have been interpreted as contemporary evidence of fathers' son preference. Our study explores the potential role of another set of dynamics that may drive these patterns: namely, selection into live birth. Epidemiological evidence indicates that the characteristic female survival advantage may begin before birth. If stress accompanying unstable marriages has biological effects on fecundity, a female survival advantage could generate an association between stability and the sex composition of offspring. Combining regression and simulation techniques to analyze real-world data, we ask, How much of the observed association between sex of the firstborn child and risk of divorce could plausibly be accounted for by the joint effects of female survival advantage and reduced fecundity associated with unstable marriage? Using data from the National Longitudinal Survey of Youth (NLSY79), we find that relationship conflict predicts the sex of children born after conflict was measured; conflict also predicts subsequent divorce. Conservative specification of parameters linking pregnancy characteristics, selection into live birth, and divorce are sufficient to generate a selection-driven association between offspring sex and divorce, which is consequential in magnitude. Our findings illustrate the value of demographic accounting of processes which occur before birth-a period when many outcomes of central interest in the population sciences begin to take shape. [ABSTRACT FROM AUTHOR]

Unobserved heterogeneity in mortality risk is pervasive and consequential. Mortality deceleration-the slowing of mortality's rise with age-has been considered an important window into heterogeneity that otherwise might be impossible to explore. In this article, I argue that deceleration patterns may reveal surprisingly little about the heterogeneity that putatively produces them. I show that even in a very simple model-one that is composed of just two subpopulations with Gompertz mortality-(1) aggregate mortality can decelerate even while a majority of the cohort is frail; (2) multiple decelerations are possible; and (3) mortality selection can produce acceleration as well as deceleration. Simulations show that these patterns are plausible in model cohorts that in the aggregate resemble cohorts in the Human Mortality Database. I argue that these results challenge some conventional heuristics for understanding the relationship between selection and deceleration; undermine certain inferences from deceleration timing to patterns of social inequality; and imply that standard parametric models, assumed to plateau at most once, may sometimes badly misestimate deceleration timing-even by decades. [ABSTRACT FROM AUTHOR]

The gradual changes in cohort composition that occur as a result of selective mortality processes are of interest to all aging research. We present the first illustration of changes in the distribution of specific cohort characteristics that arise purely as a result of selective mortality. We use data on health, wealth, education, and other covariates from two cohorts (the AHEAD cohort, born 1900-1923 and the HRS cohort, born 1931-1941) included in the Health and Retirement Survey, a nationally representative panel study of older Americans spanning nearly two decades ( N = 14,466). We calculate sample statistics for the surviving cohort at each wave. Repeatedly using only baseline information for these calculations so that there are no changes at the individual level (what changes is the set of surviving respondents at each specific wave), we obtain a demonstration of the impact of mortality selection on the cohort characteristics. We find substantial changes in the distribution of all examined characteristics across the nine survey waves. For instance, the median wealth increases from about $90,000 to $130,000 and the number of chronic conditions declines from 1.5 to 1 in the AHEAD cohort. We discuss factors that influence the rate of change in various characteristics. The mortality selection process changes the composition of older cohorts considerably, such that researchers focusing on the oldest old need to be aware of the highly select groups they are observing, and interpret their conclusions accordingly. [ABSTRACT FROM AUTHOR]

Abstract: Empirical research and the theory of natural selection assert that male mortality more than female mortality responds to ambient stressors in utero. Although population stressors may adversely damage males that survive to birth, the rival culled cohort hypothesis contends that males born during stressful times may exhibit better health than males in other cohorts because fetal loss has “culled” the frailest males. We tested these hypotheses by examining child developmental outcomes in a U.S. birth cohort reportedly affected in utero by the September 11, 2001 attacks. We used as outcomes the Bayley cognitive score and child height-for-age from the Early Childhood Longitudinal Study-Birth Cohort. Previous research demonstrates a male-specific effect of 9/11 on California infants born in December 2001. We, therefore, compared cognition and height of this cohort with males born prior to the 9/11 attacks. We controlled for unobserved confounding across gender, season, and region by using triple-difference regression models (N = 6950). At 24 months, California males born in December scored greater than expected in cognitive ability (coef = 9.55, standard error = 3.37; p = 0.004). We observed no relation with height. Results remained robust to alternative specifications. Findings offer partial support for the culled cohort hypothesis in that we observed greater than expected cognitive scores at two years of age among a cohort of males affected by 9/11 in utero. Contemporary population stressors may induce male-specific culling, thereby resulting in relatively improved development among males that survive to birth. [Copyright &y& Elsevier]

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Abstract: Age of tooth emergence is a useful measure of the pace of life for primate species, both living and extinct. A recent study combining wild chimpanzees of the Taï Forest, Gombe, and Bossou by suggested that wild chimpanzees erupt teeth much later than captives, bringing into question both comparisons within the hominin fossil record and assessment of chimpanzees. Here, we assess the magnitude of the “wild effect” (the mean difference between captive and wild samples expressed in standard deviation units) in these chimpanzees. Tooth emergence in these wild individuals is late, although at a more moderate level than previously recorded, with a mean delay conservatively estimated at about 1 SD compared to the captive distributions. The effect rises to 1.3 SD if we relax criteria for age estimates. We estimate that the mandibular M1 of these wild chimpanzees emerges at about 3 2/3–3 ¾ years of age. An important point, often ignored, is that these chimpanzees are largely dead of natural causes, merging the effect of living wild with the effect of early death. Evidence of mortality selection includes, specifically: younger deaths appear to have been more delayed than the older in tooth emergence, more often showed evidence of disease or debilitation, and revealed a higher occurrence of dental anomalies. Notably, delay in tooth emergence for live-captured wild baboons appears lower in magnitude (ca. 0.5 SD) and differs in pattern. Definitive ages of tooth emergence times in living wild chimpanzees must be established from the study of living animals. The fossil record, of course, consists of many dead juveniles; the present study has implications for how we evaluate them. [ABSTRACT FROM AUTHOR]

Abstract: Evidence shows that exposure to nutritional adversity in early life has larger long-term impacts on women than on men. Consistent with these findings, our paper shows a higher incidence of disability and illiteracy among female survivors of the Great Chinese Famine (1959–1961). Moreover we find that the better health of male survivors most plausibly reflects higher male excess mortality during the famine, whereas the observed gender difference in illiteracy rate is probably better explained by the culture of son preference. [Copyright &y& Elsevier]

Abstract: The cumulative advantage hypothesis suggests diverging socioeconomic status (SES) based gaps in health with age. However, previous studies yield inconsistent findings regarding the association between SES and health across the adult life span. Dealing with the issue of mortality selection bias, this study utilizes latent growth-curve modeling to comprehensively examine age trajectories of both physical and mental health by SES using panel data based on a national probability sample of 3617 US adults. We find that education- and income-based gaps in physical impairment and the education-based gap in depression diverge over time for all adult age groups, supporting the hypothesis of cumulative advantage. In contrast, we find that the income-based gap in depression converges in older age, supporting the hypothesis of age-as-leveler. Mortality selection bias is unlikely to be a major part of the explanation for the convergence. These results indicate that age-related patterns in health trajectories may differ by various dimensions of SES and health. Finally, we take into account persistence or change in income over time to examine the relationship between trajectories of income and health across adulthood, highlighting the importance of considering the temporal patterns of income in understanding age trajectories of health. [Copyright &y& Elsevier]

Current methods for measuring selection with longitudinal data have been developed with the assumption that episodes of selection are sequential. However, a number of empirical examinations have demonstrated that natural and sexual selection may act concurrently and in opposing directions. Other recent work has highlighted the difficulty of assigning fitness values for survival when reproduction and mortality within a population temporally overlap. I treat these as facets of a single problem; how to analyze selection where mortality and reproduction are concurrent. To address this problem, I formalize a method to estimate total fitness of individuals over a period of time utilizing longitudinal data. I then show how the fitness may be partitioned to provide two separate estimates of fitness for reproductive opportunity and reproductive success. In addition, another total fitness estimate for the period can be obtained from the two partitioned estimates. This procedure will allow calculation of total fitness where there are some missing datapoints for reproductive success of an individual. A simulation indicates that bias is generally low for the various fitness estimates. These methods should expand our ability to understand the interaction of different selection episodes. [ABSTRACT FROM AUTHOR]

Analyses of human mortality data classified according to cause of death frequently are based on competing risk theory. In particular, the times to death for different causes often are assumed to be independent. In this paper, a competing risk model with a weaker assumption of conditional independence of the times to death, given an assumed stochastic covariate process, is developed and applied to cause specific mortality data from the Framingham Heart Study. The results generated under this conditional independence model are compared with analogous results under the standard marginal independence model. Under the assumption that this conditional independence model is valid, the comparison suggests that the standard model overestimates by 4% the effect on life expectancy at age 30 due to the hypothetical elimination of cancer and by 7% the effect for cardiovascular/cerebrovascular disease. By age 80 the overestimates were 11% for cancer and 16% for heart disease. These results suggest the importance of avoiding the marginal independence assumption when appropriate data are available - especially when focusing on mortality at advanced ages. [ABSTRACT FROM AUTHOR]

Photosynthetic and water relations characteristics of small juvenile and large reproductive plants were investigated during one growing season for four woody species native to Red Butte Canyon, Utah, USA: Acer negundo, Artemisia tridentata, Chrysothamnus nauseosus, and Salix exigua. For all species, juvenile plants differed from reproductive plants in at least one of the following characters: water potential, stomatal conductance, photosynthetic rate, or water-use efficiency. Late in the growing season, mortality occurred within juvenile plants (apparently due to a lack of water), but not within reproductive plants. The observed differences between juvenile and reproductive classes are discussed in terms of environment, development, and mortality selection. [ABSTRACT FROM AUTHOR]

Background: A growing body of literature has reported widening educational health disparities across birth cohorts or time periods in the United States, but has paid little attention to the implication of mortality selection on the cohort trend in health disparities., Objective: This study investigates how changes in the variance of unobserved frailty over time may complicate the interpretation of cohort trends in health disparities and life expectancy., Methods: We use the microsimulation method to test the effect of mortality selection and further propose a counterfactual simulation procedure to estimate its contribution. Data used in the simulations are based on Panel Studies of Income Dynamics 1968-2013, National Health and Nutrition Examination Survey data 1999-2012, and National Health Interview Survey data 1986-2011., Results: Simulation shows that mortality selection may generate seemingly contradictory trends in health disparities and life expectancy across birth cohorts at the group and individual level. Life expectancy can change even when individual mortality curve is fixed. In the absence of a change in the causal effect of education on mortality at the individual level, an educational life expectancy gap can change across cohorts as a result of the change in frailty variance. Empirical analysis shows that mortality selection accounts for a sizeable amount of contribution to the widening educational life expectancy gap from the 1950s to 1960s birth cohorts in the United States., Contribution: We demonstrate mortality selection can complicate the cohort trend in health disparities and life expectancy and propose a counterfactual simulation method to evaluate its contribution.

The author discusses aspects of genetics of inheritance and response to selection against mortality. It explains the development of whole-genome resequencing in domestic fowls that are often overlooked by genecists as common sense solution. The author thinks that the selection for layers with feather picking characteristics in aggressive hens may not be a very efficient criteria for production traits.

Background: Correcting for the potential effects of population stratification is an important issue in genome wide association studies (GWAS) of complex traits. Principal component analysis (PCA) of the genetic structure of the population under study with subsequent incorporation of the first several principal components (PCs) in the GWAS regression model is often used for this purpose., Problem: For longevity related traits such a correction may negatively affect the accuracy of genetic analyses. This is because PCs may capture genetic structure induced by mortality selection processes in genetically heterogeneous populations., Data and Methods: We used the Framingham Heart Study data on life span and on individual genetic background to construct two sets of PCs. One was constructed to separate population stratification due to differences in ancestry from that induced by mortality selection. The other was constructed using genetic data on individuals of different ages without attempting to separate the ancestry effects from the mortality selection effects. The GWASs of human life span were performed using the first 20 PCs from each of the selected sets to control for possible population stratification., Results: The results indicated that the GWAS that used the PC set separating population stratification induced by mortality selection from differences in ancestry produced stronger genetic signals than the GWAS that used PCs without such separation., Conclusion: The quality of genetic estimates in GWAS can be improved when changes in genetic structure caused by mortality selection are taken into account in controlling for possible effects of population stratification.