Intergenerational Mobility in Self-Reported Health Status in the US

We present estimates of intergenerational mobility in self-reported health status (SRHS) in the US using data from the PSID. We estimate that the rank-rank slope in SRHS is 0.26. We show that including both parent health and income in models of intergenerational mobility increases the explanatory power of child outcomes. We construct a monetary metric for health and then use this to combine income and health into a measure of welfare and estimate the rank-rank slope to be about 0.4 for this new measure. Finally, we document striking health mobility gaps by race, region and parent education.

Unobserved Population Heterogeneity and Dynamics of Health Disparities

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 intergenerational transmission of health in the United States: A latent variables analysis

Social scientists have long documented that many components of socioeconomic status such as income and education have strong ties across generations. However, health status, arguably a more critical component of welfare, has largely been ignored. We fill this void by providing the first estimates of the Intergenerational Health Association (IHA) that are explicitly based on a nonlinear latent variable model. We develop an estimation procedure for a nonlinear model with categorical outcomes in which the latent index is a mixed linear model and contains covariates that might not vary within cross-sectional units. Adjusting for only age and gender, we estimate an IHA of 0.3 indicating that about one third of a parent's health status gets transmitted to their children. Once we add additional mediators to the model, we show that education, and particularly children's education, is an important transmission channel in that it reduces the IHA by one third. Finally, we show that estimates of the IHA from nonlinear models are only moderately higher than those from linear models, whereas rank-based mobility estimates are identical.

The Oddity of Heterogeneity: A Blessing in Disguise

Damage accumulation is widely accepted as the central dogma of ageing, and it has been a long-standing belief that tobacco smokers must experience a faster rate of ageing than non-smokers. It is therefore puzzling as to why proportional hazard model is a popular choice in longitudinal studies given that its assumption assumes a constant hazard with increasing time. If the rate of ageing is accelerated, the hazard gradient of smokers d(log(μ(x)))/dx obtained from frailty parametric fit has to be steeper than non-smokers. This study examines the relative derivative for mortality d(log(μ(x)))/dx of British doctors born 1900–1909, and obtained estimates indicate that the rate of ageing is similar between smokers and non-smokers. A brief theorem is also elaborated to present the difference in life-years gained from interventions and policies by life-detrimental risk exposure; e.g. smokers 0.8; non-smokers 5.3 mins/day. The controversial assumption made in the central dogma of ageing, heterogeneity axiom and the application of proportional hazard models are unveiled in this condensed parametric analyses.

A simulation study of the role of cohort forces in mortality patterns

This study uses the micro-simulation method to investigate the role of cohort forces in age-dependent mortality pattern. We test the micro mechanisms for cohort evolution and mortality selection, and how these two biological and demographic forces may interact with epidemiologic transition to shape the cohort age-dependence of mortality pattern in both early- and later-transition countries. We show that cohort evolution is due to the declining rate of mortality acceleration at the individual level, which is associated with lower initial mortality rates but not smaller variance of frailty distribution in later birth cohorts. The steeper slope of mortality acceleration at the population level among later birth cohorts is due to mortality selection mechanism associated with smaller variance of frailty distribution but not lower initial mortality rates. These two forces jointly shape the non-crossover cohort age-dependence of mortality pattern regardless of the differential mechanisms of epidemiologic transition in early- and later-transition countries.

AFT survival model to capture the rate of aging and age-specific mortality trajectories among first-allogeneic hematopoietic stem cells transplant patients

Accelerated failure time (AFT) model is commonly applied in engineering studies to address the failure rate of a machine. In humans, survival profile of transplant patients is among the rare scenarios whereby AFT is applicable. To date, it is uncertain whether reliable risk estimates and age-specific mortality trajectories have been published using conventional statistics approach. By investigating mortality trajectory, the rate of aging d(log(μ(x)))/dx of Hematopoietic Stem Cells Transplants (HSCTs) patients who had underwent first-allogeneic transplants can be obtained, and to unveil the possibility of elasticity of human aging rate in HSCTs. A modified parametric frailty survival model was introduced to the survival profiles of 11,160 patients who had underwent first-allogeneic HSCTs in the United States between 1995 and 2006; data was shared by Center for International Bone and Marrow Transplant Research. In comparison to stratification, the modification permits two entities in relation to time to be presented; age and calendar time. To consider its application in empirical studies, the data contains arbitrary right-censoring, a statistical condition which is preferred by choice in many transplant studies. The finalized multivariate AFT model was adjusted for clinical and demographic covariates, and age-specific mortality trajectories were presented by donor source and post-transplant time-lapse intervals. Two unexpected findings are presented: i) an inverse J-shaped hazard in unrelated donor-source t≤100-day; ii) convergence of unrelated-related hazard lines in 100-day365-day) must consider for periodic medical improvements, and transplant year as a standalone time-variable is not sufficient for statistical adjustment in the finalized multivariate model. In relevance to clinical studies, biennial event-history analysis and age-specific mortality trajectories of long-term survivors provide a more relevant intervention audit report for transplant protocols than the popular statistical presentation; i.e. survival probabilities among donor-source.

Examining the Impact of Maternal Health, Race, and Socioeconomic Status on Daughter's Self-Rated Health Over Three Decades

This study examines the role of mother's health and socioeconomic status on daughter's self-rated health using data spanning three decades from the National Longitudinal Surveys of Mature Women and Young Women (N = 1,848 matched mother-daughter pairs; 1,201 White and 647 African American). Using nested growth curve models, we investigated whether mother's self-rated health affected the daughter's self-rated health and whether socioeconomic status mediated this relationship. Mother's health significantly influenced daughters' self-rated health, but the findings were mediated by mother's socioeconomic status. African American daughters reported lower self-rated health and experienced more decline over time compared with White daughters, accounting for mother's and daughter's covariates. Our findings reveal maternal health and resources as a significant predictor of daughters' self-rated health and confirm the role of socioeconomic status and racial disparities over time.

Infant mortality and intra-household competition in the Northern Islands of Orkney, Scotland, 1855-2001

This study applies principles from the theory of household life cycles to the study of early childhood mortality in the population of the Northern Orkney Islands, Scotland. The primary hypothesis is that unfavorable household economic conditions resulting from changes in household demographic composition increase the risk of death for children under the age of 5 years because of limited resources and intra-household competition. We apply Cox proportional hazards models to nearly 5,000 linked birth and death records from the Northern Orkney Islands, Scotland, from the period 1855 to 2001. The dependent variable is the child's risk of death before age 5. Findings suggest that children in households with unfavorable age compositions face higher risk of death. This elevated risk of death continues once heterogeneity among children, islands, and households is controlled. Results also show differential risk of death for male children, children of higher birth orders, and twin births. The analyses present evidence for intra-household competition in this historic setting. The most convincing evidence of competition is found in the effects of household consumer/producer ratios and twinning on child mortality risks.

The Heritability of CHD Mortality in Danish Twins After Controlling for Smoking and BMI

Cause-specific mortality data on Danish monozygotic and dizygotic twins are used to analyze heritability estimates of susceptibility to coronary heart disease (CHD) after controlling for smoking and Body Mass Index (BMI). The sample includes 1209 like-sexed twin pairs born between 1890 and 1920, where both individuals were still alive in 1966. The participants completed a questionnaire in 1966 which included questions on smoking, height and weight. The analysis was conducted with both sexes pooled due to the relatively small number of twin pairs. Follow-up was conducted from January 1, 1966 to December 31, 1993. The correlated gammafrailty model with observed covariates was used for the genetic analysis of frailty to account for censoring and truncation in the lifetime data. During the follow-up, 1437 deaths occurred, including 435 deaths due to CHD. Proportions of variance of frailty attributable to genetic and environmental factors were analyzed using the structural equation model approach. Different standard biometric models are fitted to the data to evaluate the magnitude and nature of genetic and environmental factors on mortality. Using the best-fitting model without covariates, heritability of frailty to CHD was found to be 0.45 (0.11). This result changes only slightly to 0.55 (0.13) in a DE model after controlling for smoking and BMI. This analysis underlines the existence of a substantial genetic influence on individual frailty associated with mortality caused by CHD.

Health Inequalities, General Trends in Mortality and Morbidity, and Associated Factors

All measures of health status are ultimately derived from observations of individuals. At the field level we have such measures as self-assessed health status, report of a specific disease, record of a particular death, or an individual’s test on a biomarker, such as blood pressure or serum cholesterol. The observations for individuals are combined and summarized to represent subnational geographic areas, demographic or socioeconomic groups within countries, or national populations. The summary measures, whether they are percentages, averages, or rates, apply to groups. A problem arises when the measures that are based on groups are assumed to represent individuals. The analysis becomes especially problematic when the units analyzed are geographic areas and inferences are being made about individuals from the analysis for these geographic areas.

Biodemography: new approaches to understanding trends and differences in population health and mortality

The incorporation of biological information in large population surveys has expanded demographic analysis to clarify the meaning of observed trends and differences in population health and mortality. Levels of measured biological risk in the population were reduced in recent years largely because of the expanded use of prescription drugs. The increased use of antihypertensives and, to a lesser extent, lipid-lowering drugs was a likely cause of significant mortality reduction. Blacks and persons with lower educational attainment experience higher levels of biological risk factors, more diseases, and more frailty; these differences are the sources of higher mortality for these groups. Hispanics are less likely to have a higher prevalence of risk factors and diseases than the non-Hispanic population, providing further understanding of the "Hispanic paradox." Almost every examined indicator of biological risk, disease, and frailty is related to higher mortality, indicating how incorporation of this information provides a fuller understanding of the morbidity process.

Testing the influenza-tuberculosis selective mortality hypothesis with Union Army data

Using Cox regression, this paper shows a weak association between having tuberculosis and dying from influenza among Union Army veterans in late nineteenth-century America. It has been suggested elsewhere [Noymer, A. and M. Garenne (2000). The 1918 influenza epidemic's effects on sex differentials in mortality in the United States. Population and Development Review 26(3), 565-581.] that the 1918 influenza pandemic accelerated the decline of tuberculosis, by killing many people with tuberculosis. The question remains whether individuals with tuberculosis were at greater risk of influenza death, or if the 1918/post-1918 phenomenon arose from the sheer number of deaths in the influenza pandemic. The present findings, from microdata, cautiously point toward an explanation of Noymer and Garenne's selection effect in terms of age-overlap of the 1918 pandemic mortality and tuberculosis morbidity, a phenomenon I term "passive selection". Another way to think of this is selection at the cohort, as opposed to individual, level.

The exceptionally high life expectancy of Costa Rican nonagenarians

Robust data from a voter registry show that Costa Rican nonagenarians have an exceptionally high live expectancy. Mortality at age 90 in Costa Rica is at least 14% lower than an average of 13 high-income countries. This advantage increases with age by 1% per year Males have an additional 12% advantage. Age-90 life expectancy for males is 4.4 years, one-half year more than any other country in the world. These estimates do not use problematic data on reported ages, but ages are computed from birth dates in the Costa Rican birth-registration ledgers. Census data confirm the exceptionally high survival of elderly Costa Ricans, especially males. Comparisons with the United States and Sweden show that the Costa Rican advantage comes mostly from reduced incidence of cardiovascular diseases, coupled with a low prevalence of obesity, as the only available explanatory risk factor Costa Rican nonagenarians are survivors of cohorts that underwent extremely harsh health conditions when young, and their advantage might be just a heterogeneity in frailty effect that might disappear in more recent cohorts. The availability of reliable estimates for the oldest-old in low-income populations is extremely rare. These results may enlighten the debate over how harsh early-life health conditions affect older-age mortality.

The influence of social relations on mortality in later life: a study on elderly Danish twins

PURPOSE

We examined whether the presence of a spouse and the frequency of interaction with children, relatives, and friends significantly influence the risk of dying in late life. We assessed these effects separately by gender, controlling for self-reported health. In addition, we examined whether interaction with the co-twin has a different impact on mortality for identical and fraternal twins.

DESIGN AND METHODS

The data set consists of 2,147 Danish twins aged 75 years and older, who were followed prospectively from 1995 to 2001. We modeled the effect of social ties on mortality by using event history analysis.

RESULTS

Survival is extended by having a spouse and close ties with friends and the co-twin. However, contact frequency with friends and the co-twin is significant, respectively, only for women and identical twins.

IMPLICATIONS

Investigating social relations sheds light on the life span of individuals older than 75 years of age. We stress the importance of social relations beyond the presence of the spouse for survival even at very old ages.

Estimating haplotype relative risks on human survival in population-based association studies

Association-based linkage disequilibrium (LD) mapping is an increasingly important tool for localizing genes that show potential influence on human aging and longevity. As haplotypes contain more LD information than single markers, a haplotype-based LD approach can have increased power in detecting associations as well as increased robustness in statistical testing. In this paper, we develop a new statistical model to estimate haplotype relative risks (HRRs) on human survival using unphased multilocus genotype data from unrelated individuals in cross-sectional studies. Based on the proportional hazard assumption, the model can estimate haplotype risk and frequency parameters, incorporate observed covariates, assess interactions between haplotypes and the covariates, and investigate the modes of gene function. By introducing population survival information available from population statistics, we are able to develop a procedure that carries out the parameter estimation using a nonparametric baseline hazard function and estimates sex-specific HRRs to infer gene-sex interaction. We also evaluate the haplotype effects on human survival while taking into account individual heterogeneity in the unobserved genetic and nongenetic factors or frailty by introducing the gamma-distributed frailty into the survival function. After model validation by computer simulation, we apply our method to an empirical data set to measure haplotype effects on human survival and to estimate haplotype frequencies at birth and over the observed ages. Results from both simulation and model application indicate that our survival analysis model is an efficient method for inferring haplotype effects on human survival in population-based association studies.

Genealogical data and the biodemography of human longevity

Biodemography of human longevity is an emerging interdisciplinary field of sociobiological research with deep historical roots. Two research questions are examined in this article: (1) What evidence is there for the familial transmission of human longevity?, and (2) what are the effects of parental age at reproduction on offspring longevity, and in particular, are there long-term adverse health consequences associated with the trend toward delayed reproduction? The ability of scientists to conduct biodemographic studies depends not only on merging theoretical and methodological elements from the biological and demographic/actuarial sciences, but unique sources of data and statistical methods must also be developed. In this article we describe how gencalogical data have been used for over a century to explore basic questions about human longevity, and how similar kinds of data now being developed are driving the formation of new testable research hypotheses in the field of biodemography.

Between nurture and nature: the shifting determinants of female fertility in Danish twin cohorts

Behaviors related to fertility constitute primary candidates for investigating the relevance of evolutionary influences and biological dispositions on contemporary human behaviors. Using female Danish twin cohorts born 1870-1968, we document important transformations in the relative contributions of "nurture" and "nature" to within-cohort variations in early and complete fertility, and we point toward a systematic relation between the socioeconomic context of cohorts and the relevance of genetic and shared environmental factors. This transformation is most striking for early fertility where genetic factors strengthen over time and are consistent with up to 50 percent of the variation in early fertility in most recent cohorts. Understanding this emerging relevance of genetic factors is of central importance because early fertility constitutes an important determinant of complete fertility levels in low-fertility societies, and because teenage motherhood and early childbearing are often associated with negative life-cycle consequences. Moreover, our results emphasize the need for socially and contextually informed analyses of nature and nurture that allow both factors to influence human reproductive behavior over time.

Two-level proportional hazards models

We extend the proportional hazards model to a two-level model with a random intercept term and random coefficients. The parameters in the multilevel model are estimated by a combination of EM and Newton-Raphson algorithms. Even for samples of 50 groups, this method produces estimators of the fixed effects coefficients that are approximately unbiased and normally distributed. Two different methods, observed information and profile likelihood information, will be used to estimate the standard errors. This work is motivated by the goal of understanding the determinants of contraceptive use among Nepalese women in the Chitwan Valley Family Study (Axinn, Barber, and Ghimire, 1997). We utilize a two-level hazard model to examine how education and access to education for children covary with the initiation of permanent contraceptive use.

Heat shock changes the heterogeneity distribution in populations of Caenorhabditis elegans: does it tell us anything about the biological mechanism of stress response?

In this paper we analyze survival data of populations of sterilized nematodes, Caenorhabditis elegans, exposed to heat shocks of different duration at the beginning of their adult lives. There are clear hormesis effects after short exposure to heat and clear debilitation effects after long exposure. Intermediate durations result in a mixture of these two effects. In this latter case, the survival curves for the control and experimental populations intersect. We show that observed effects may be explained by using a model of discrete heterogeneity. According to this model, each population of worms in the experiment is a mixture of subcohorts of frail, normal, and robust individuals; exposure to heat changes the initial proportion of worms in the subcohorts (heterogeneity distribution); and these changes depend on the duration of exposure. In other words, exposure to heat does not influence mortality rates (survival functions) in the subcohorts but does cause individuals to move from one subcohort to another. In a biological interpretation of this finding we hypothesize that, when coping with stress, the organisms of worms use several lines of defense. Switching these lines on and off in response to stress in individual organisms generates the spectrum of observed survival effects at the population level. We discuss possible molecular biological mechanisms of stress response and directions for further research.

Empirical laws of survival and evolution: their universality and implications

Presented analysis of human and fly life tables proves that with the specified accuracy their entire survival and mortality curves are uniquely determined by a single point (e.g., by the birth mortality q(0)), according to the law, which is universal for species as remote as humans and flies. Mortality at any age decreases with the birth mortality q(0). According to life tables, in the narrow vicinity of a certain q(0) value (which is the same for all animals of a given species, independent of their living conditions), the curves change very rapidly and nearly simultaneously for an entire population of different ages. The change is the largest in old age. Because probability to survive to the mean reproductive age quantifies biological fitness and evolution, its universal rapid change with q(0) (which changes with living conditions) manifests a new kind of an evolutionary spurt of an entire population. Agreement between theoretical and life table data is explicitly seen in the figures. Analysis of the data on basic metabolism reduces it to the maximal mean lifespan (for animals from invertebrates to mammals), or to the maximal mean fission time (for bacteria), and universally scales them with the total number of body atoms only. Phenomenological origin of this unification and universality of metabolism, survival, and evolution is suggested. Their implications and challenges are discussed.

Phenomenological theory of mortality evolution: its singularities, universality, and superuniversality

The probability to survive to the age x universally increases with the mean lifespan x(bar). For species as remote as humans and flies, for a given x the rate of its evolution with x is constant, except for the narrow vicinity of a certain x(bar) = x* (which equals 75 years for humans and 32 days for flies and which is independent of age, population, and living conditions). At x(bar) approximately x* the evolution rate jumps to a different value. Its next jump is predicted at x(bar) approximately 87 years for humans and approximately 59 days for flies. Such singularities are well known in physics and mathematics as phase transitions. In the considered case different population "phases" have significantly different survival evolution rates. The evolution is rapid-life expectancy may double within a lifespan of a single generation. Survival probability depends on age x and mean longevity x(bar) only (for instance, survival curves of 1896 Swedes and 1947 Japanese with approximately equal x(bar) are very close, although they are related to different races in different countries at different periods in their different history.) With no adjustable parameters, its presented universal law quantitatively agrees with all lifetable data. According to this law, the impact of all factors but age reduces to the mean lifespan only. In advanced and old age, this law is superuniversal--it is approximately the same for species as remote as humans and flies. It yields survival probability that linearly depends on the mean lifespan x(bar). As a result, when human x(bar) almost doubles (from 35.5 to 69.3 years), life expectancy at 70 years increases from 8 to 9.5 years only. Other implications of the universal law are also considered.

A Danish population-based twin study on general health in the elderly

OBJECTIVES

To study the relative influence of genetic and environmental factors on self-rated health and hospitalization patterns in the elderly.

METHODS

A survey among all 3,099 Danish twins ages 75 years and older identified in the Danish Twin Registry. An interview was conducted with 77% of the twins. The number of hospitalizations in the previous 18 years was obtained through register linkage, thereby obtaining health information on 96% of the study population, including all nonresponders.

RESULTS

Structural equation modeling suggested that approximately a quarter of the variation in the liability to self-reported health and the number of hospitalizations could be attributed to genetic factors. The remaining variation was most likely due to nonfamilial environment. Analyses of the hospitalization patterns of proxy responders and nonresponders suggest that the estimates of the genetic influence on health outcomes in the study are conservative.

DISCUSSION

The present study indicates that variation in general health among the elderly is partly explained by genetic factors.

Biodemographic trajectories of longevity

Old-age survival has increased substantially since 1950. Death rates decelerate with age for insects, worms, and yeast, as well as humans. This evidence of extended postreproductive survival is puzzling. Three biodemographic insights--concerning the correlation of death rates across age, individual differences in survival chances, and induced alterations in age patterns of fertility and mortality--offer clues and suggest research on the failure of complicated systems, on new demographic equations for evolutionary theory, and on fertility-longevity interactions. Nongenetic changes account for increases in human life-spans to date. Explication of these causes and the genetic license for extended survival, as well as discovery of genes and other survival attributes affecting longevity, will lead to even longer lives.