Censored Data Analysis Reveals Effects of Age and Hepatitis C Infection on C-Reactive Protein Levels in Healthy Adult Chimpanzees (Pan troglodytes)

Age-related physiological dysregulation progresses slowly in semi-free-ranging chimpanzees

Background and objectives

Lifestyle has widespread effects on human health and aging. Prior results from chimpanzees (Pan troglodytes), one of humans' closest evolutionary relatives, indicate that these lifestyle effects may also be shared with other species, as semi-free-ranging chimpanzees fed a naturalistic diet show healthier values in several specific health biomarkers, compared with their sedentary, captive counterparts. Here, we examined how lifestyle factors associated with different environments affect rates of physiological aging in closely related chimpanzees.

Methodology

We compared physiological dysregulation, an index of biological aging, in semi-free-ranging chimpanzees in an African sanctuary versus captive chimpanzees in US laboratories. If the rate of aging is accelerated by high-calorie diet and sedentism, we predicted greater age-related dysregulation in the laboratory populations. Conversely, if costs of a wild lifestyle accelerate aging, then semi-free-ranging chimpanzees at the sanctuary, whose environment better approximates the wild, should show greater age-related dysregulation. We further tested whether dysregulation differed based on sex or body system, as in humans.

Results

We found that semi-free-ranging chimpanzees showed lower overall dysregulation, as well as lower age-related change in dysregulation, than laboratory chimpanzees. Males experienced lower dysregulation than females in both contexts, and the two populations exhibited distinct aging patterns based on body system.

Conclusions and implications

Our results support the conclusion that naturalistic living conditions result in healthier aging in chimpanzees. These data provide support for the proposal that lifestyle effects on human health and aging are conserved from deeper into our evolutionary history.

Demography and epidemiology of captive former biomedical research chimpanzees (Pan troglodytes) 1: Survival and mortality

Accurate and up-to-date data on longevity and mortality are essential for describing, analyzing, and managing animal populations in captivity. We assembled a comprehensive demography data set and analyzed survival and mortality patterns in a population of captive former biomedical research chimpanzees. The study synthesized over 51,000 life-years of demographic data collected on 2349 individuals between 1923 and 2014. Our goal was to assess the population's current age-sex composition, estimate rates of survivorship, mortality and life expectancy, and compare findings with other chimpanzee populations of interest. Results indicated an increasingly geriatric contemporary population declining in size. The median life expectancy (MLE) of the entire population was 32.6 years (males 29.1, females 36.1). For chimpanzees who reached 1 year of age, the MLE increased to 34.9 years (males 31.0, females 38.8). Survival probability was influenced by both sex and birth type. Females exhibited greater survivorship than males (β₁  = -0.34, z = -5.74, p < 0.001) and wild-born individuals exhibited greater survivorship than captive-born individuals (β₂  = -0.55, z = -5.89, p < 0.001). There was also a seasonal trend in mortality, wherein more individuals died during the winter months (December-February) compared with other seasons. Analyses of life expectancy over time showed continual increases in both median age of living individuals and median age at death, suggesting that these chimpanzees have yet to reach their full aging potential in a postresearch environment. As they continue to age, ongoing monitoring and analysis of demographic changes will be necessary for science-based population and program management until extinction occurs some decades in the future.

Missing data in bioarchaeology II: A test of ordinal and continuous data imputation

OBJECTIVES

Previous research has shown that while missing data are common in bioarchaeological studies, they are seldom handled using statistically rigorous methods. The primary objective of this article is to evaluate the ability of imputation to manage missing data and encourage the use of advanced statistical methods in bioarchaeology and paleopathology. An overview of missing data management in biological anthropology is provided, followed by a test of imputation and deletion methods for handling missing data.

MATERIALS AND METHODS

Missing data were simulated on complete datasets of ordinal (n = 287) and continuous (n = 369) bioarchaeological data. Missing values were imputed using five imputation methods (mean, predictive mean matching, random forest, expectation maximization, and stochastic regression) and the success of each at obtaining the parameters of the original dataset compared with pairwise and listwise deletion.

RESULTS

In all instances, listwise deletion was least successful at approximating the original parameters. Imputation of continuous data was more effective than ordinal data. Overall, no one method performed best and the amount of missing data proved a stronger predictor of imputation success.

DISCUSSION

These findings support the use of imputation methods over deletion for handling missing bioarchaeological and paleopathology data, especially when the data are continuous. Whereas deletion methods reduce sample size, imputation maintains sample size, improving statistical power and preventing bias from being introduced into the dataset.