Can osteophytes be used as age at death estimators? Testing correlations in skeletonized human remains with known age-at-death

Radiographic age estimation based on degenerative changes of vertebrae

Age estimation is an important component of decedent identification. When assessing adult remains, anthropologists frequently use gross examination of skeletal elements, such as clavicles, ribs, and pubic symphyses. For fleshed bodies, this requires the removal of these elements and maceration prior to analysis. A new method was developed using radiographic imaging to estimate age from degenerative changes of the lower thoracic and upper lumbar vertebrae. This technique will complement anthropological age estimation methods in young and middle-aged adults and may serve as a stand-alone method for older individuals. Digital radiographs from 240 medical examiner cases were evaluated. The sample included 120 females and 120 males between the ages of 18 and 101 years. A 3-phased scoring system was used for the target vertebrae. Transition analysis was conducted on binned average scores and a Bayesian approach was used to assign age intervals. At the 90% credible interval, individuals in Bin 1 were under 36 years of age while those in Bin 3 were over 47 years of age. Individuals in Bin 2 showed too much age variation to be informative. No significant differences were found between males and females. These findings will be especially useful in the age estimation of older adults and may eliminate the need for skeletal sampling in medicolegal cases where advanced degenerative changes are radiographically observed in the lower thoracic and/or upper lumbar vertebrae. This method was developed for use on fleshed individuals but may also be applicable to skeletonized remains.

Predicting chronological age based on age-related osteophyte development in the superior and inferior vertebral centrum margins of T12-L5

The purpose of this study was to determine the relationship between vertebral margins at individual vertebral levels between T12-L5 vertebra and chronological age and develop predictive models. Three hundred and nineteen CT scans from a medical imaging database in North America were randomly selected. Three superior and inferior vertebral margin sites were scored based on observable age-related changes. All individual vertebral margin site scores significantly correlated with age at death with Pearson r values ranging from 0.47 to 0.77. Totaling the individual vertebral margin site scores for L1-L5 improved Pearson r to 0.92. All resulting predictive models were significant, and the best models predicted age at death within 10 years 70%-76% of the time for males, females, and combined male and females. In conclusion, this study produced accurate and reliable models to predict age at death using age-related changes in the spine for a North American population.

Adult Skeletal Age-at-Death Estimation through Deep Random Neural Networks: A New Method and Its Computational Analysis

Age-at-death assessment is a crucial step in the identification process of skeletal human remains. Nonetheless, in adult individuals this task is particularly difficult to achieve with reasonable accuracy due to high variability in the senescence processes. To improve the accuracy of age-at-estimation, in this work we propose a new method based on a multifactorial macroscopic analysis and deep random neural network models. A sample of 500 identified skeletons was used to establish a reference dataset (age-at-death: 19–101 years old, 250 males and 250 females). A total of 64 skeletal traits are covered in the proposed macroscopic technique. Age-at-death estimation is tackled from a function approximation perspective and a regression approach is used to infer both point and prediction interval estimates. Based on cross-validation and computational experiments, our results demonstrate that age estimation from skeletal remains can be accurately (~6 years mean absolute error) inferred across the entire adult age span and informative estimates and prediction intervals can be obtained for the elderly population. A novel software tool, DRNNAGE, was made available to the community.

Estimation of adult age-at-death from entheseal robusticity: A test using an identified Italian skeletal collection

OBJECTIVES

The present study tests the effectiveness of entheseal robusticity (ER) as a potential predictor of adult age-at-death by applying multiple regression models to a large contemporary identified skeletal sample.

MATERIALS AND METHODS

ER was recorded for 23 bilateral postcranial entheses on 481 adult individuals (271 females and 210 males) from the Frassetto identified skeletal collection of Sassari (Italy), following the method of Mariotti et al. 2007. ER scores were used as predictors in multiple regression analyses with age as the dependent variable; the performance of the resulting models was tested through standard error of estimate, the correlation coefficient between predicted and documented age, and the percentage of correctly classified individuals.

RESULTS

ER show a higher correlation with age in females, resulting in more accurate estimates when compared with those obtained for males. Age-at-death is overestimated for male individuals under 45 years old and underestimated for older individuals. Regression models including a reduced set of ER sites result in better estimates compared with those using the complete set of variables.

DISCUSSION

Results suggest the potential usefulness of ER for the estimation of age, especially for female skeletal remains. If used with caution, ER may be a valid complement to existing methods for the reconstruction of the biological profile of skeletal remains of archaeological and forensic interest.

Reconsidering osteoarthritis as a skeletal indicator of age at death

OBJECTIVES

Osteoarthritis (OA) generally increases with age, but it is a complex, multifactorial disease. This study investigated whether obesity, physical activity, and antemortem trauma preclude the use of OA for skeletal age estimation.

MATERIALS AND METHODS

The temporomandibular joint (TMJ) and all appendicular joints were scored for skeletal indicators of OA in 408 modern European-Americans (Bass Collection, TN). Binomial generalized linear models (GLMs) assessed the contributions of self-reported demographic data to OA, including: age; body mass index (BMI); and metabolic values for physical activities. Repeated resampling tested whether observed mean OA scores for joints with trauma consistently exceeded mean scores for unaffected joints. Single-variable GLM probit models were generated for OA presence/absence data in relevant joints.

RESULTS

Age was the only statistically significant predictor of OA in most multivariable GLMs. Occupation and age were both significant predictors of male hand OA; BMI was the only significant predictor of female ankle OA. Trauma significantly affected OA in most joints. Age cut-offs calculated from the single-variable probit models (representing ages of transition to "OA present") ranged from 29.7 to 77.3 years (90%) and 32.7 to 96.6 years (95%), but were problematic for the male TMJ.

DISCUSSION

Ankle OA should not be used to age females; TMJ OA should not be used to age males. For other joints, using OA to inform age estimates appears valid (in absence of antemortem trauma). While skeletal evidence of OA is not a primary age indicator, its presence can refine age ranges and provide essential age data in fragmentary cases.

Estimation of age in forensic anthropology: historical perspective and recent methodological advances

Estimation of age represents a central focus of forensic anthropological analysis of human skeletal remains and of the living. Advances registered in recent research include the topics of taphonomic impact, new anatomical areas of interest, histology, population variation, the dental pulp chamber, technology, mathematical approaches, biochemical analysis and techniques specifically targeting the living. This article reviews the historical development of age estimation methods and considers likely future directions.

Bone Mineral Density Adult Age Estimation in Forensic Anthropology: A Test of the DXAGE Application

Estimating age-at-death of individuals represented only by skeletonized human remains is a fundamental aspect of forensic anthropological casework. Recently, several researchers have proposed that bone mineral density (BMD) is a useful predictor of age-at-death in forensic contexts. Navega et al. (JFS 63(2):497-503) developed an online application called DXAGE for calculating age-at-death from BMD parameters. This study tests the utility of DXAGE by utilizing data from the National Health and Nutrition Examination Survey (NHANES). BMD data from a female subsample (n = 470) of the NHANES 2007-2008 dataset were analyzed, and the relationship between predicted age and real age was examined. Inaccuracy was 14.25 years, and bias was -7.20 years. Results show that there is a weak correlation between predicted and actual age (r = 0.47) using the DXAGE application. While BMD data are potentially useful for predicting age age-at-death, the DXAGE application should be used cautiously in forensic anthropological contexts.

Validation of the Acetabulum As a Skeletal Indicator of Age at Death in Modern European-Americans

Progressive changes in the acetabulum have been used in modern skeletal age estimation, but they have not been completely understood. If their age correlations are weakened by the influence of factors like physical activity and obesity, acetabular changes should not be used for age estimation. To investigate their utility for aging, the acetabular variables of Rissech et al. (2006) were analyzed in 409 modern European-Americans (Bass Collection, Tennessee). Correlation tests assessed potential associations between acetabular data, osteoarthritis scores (collected per Jurmain, 1990), and documented demographic information (age, body mass index [BMI], metabolic intensity of physical activities). Acetabular changes had statistically significant, positive correlations with osteoarthritis (p < 0.001 in most joints/regions) and age (p < 0.001), indicating their degenerative nature and relevance for age estimation. Acetabular changes showed no associations with BMI or metabolic values, suggesting resistance to obesity and activity effects. These results suggest that acetabular degeneration is a valid skeletal age-at-death indicator.