Measuring Tooth Color: A Key for Age Estimation

Abstract

Background/Objectives: A global approach to age estimation is being refined to integrate the contributions of skeletal and dental structures. Teeth represent a unique and durable tool for assessing age, particularly valuable when other biological indicators are unavailable. However, age estimation becomes increasingly difficult in older individuals. This study aims to evaluate whether colorimetric analysis of teeth can serve as a reliable and accurate method for estimating chronological age in both living individuals and cadavers. Methods: The study explores the measurement of tooth color as a non-ionizing and non-invasive alternative to conventional age estimation techniques. The approach emphasizes the preservation of forensic evidence and the feasibility of prospective data collection. The methodological framework involves colorimetric assessment supported by emerging technological instruments designed to standardize and improve the objectivity of measurements. Results: Recent advances in color analysis technology have enhanced the precision and reproducibility of dental color measurement. Preliminary findings suggest that age-related color changes in teeth show measurable and consistent patterns, supporting their potential use as indicators of chronological age. Conclusions: Tooth color measurement appears to be a promising complementary tool for age estimation in forensic and clinical contexts. Its non-invasive and reproducible nature offers significant advantages, provided that standardized protocols and validated instruments continue to evolve to ensure accuracy and reliability in practical applications.

1. Introduction

Chronological age estimation is a cornerstone of human identification in living and cadavers. The global socio-economic context and the migratory flows have led to a pressing call for age assessment in compliance with ethical and legal principles [1,2]. Today, there is an urgent demand for a legal and civil framework for undocumented individuals [3,4]. Therefore, age assessment methods increasingly require greater accuracy and accessibility. Age estimation requires multidisciplinary approaches and critical discussion [2,4,5]. In adults, it is grounded in complex degenerative phenomena [6,7,8]. The International Organization for Migration (IOM) advocates a three-step approach based, initially, on existing documentation, interviews, and physical appearance, followed, if needed, by a physical examination and radiographs of bones and/or teeth, and by the integration of medical and non-medical data in a multidisciplinary discussion [9]. The contribution of dental structures to estimating the age of cadavers is crucial, as teeth remain intact for a considerable period. Different techniques may be used, and they can be biochemical, histological, or physiological, and are selected according to the body preservation state, time, and cost [1]. In some countries, legal and cultural reasons do not allow post-mortem tooth extraction, highlighting the relevance of methods aimed primarily at the living [10]. Dental physiological methods are the most widely used approach for age estimation in living adults, based on the progressive deposition of secondary dentin and pulp narrowing. Currently, image techniques are regarded as the gold standard [11]. Archival dental radiographs can assess the age of living and dead individuals. Yet, the prospective exposure of living to ionizing radiation is prohibited, except if by legal demand [1,12,13]. In 2008, the Study Group for Forensic Age Diagnosis (AGFAD) systematized the most relevant procedures for living age estimation (Box 1), updated periodically [12].

Box 1. AGFAD recommendations for living age estimation.

• A medical history collection
• A physical examination, including vital signs, anthropometric data, sexual maturation, and age-relevant developmental disorders
• A radiographic examination of the left hand and wrist
• A radiographic examination of the sternal and clavicle, if the hand and wrist bones have fully developed
• An oral exam with panoramic radiography evaluation

In some countries, radiation exposure is classified as unethical if performed for reasons other than diagnostic or therapeutic indications [12,14]. The European Asylum Support Office (EASO) advocates the use of methods that are as accurate as possible and as non-invasive as possible, both physically and psychologically. It prioritizes the use of non-ionizing methods and recommends the radiation-based approaches only when necessary [9]. New trends have emerged related to the introduction of non-ionizing techniques [11,15]. Recently, algorithms for analyzing and combining regions of interest have been introduced to imaging methods [11]. This can reduce subjectivity, time spent, and also increase repeatability. Several European research groups have intensified their research into age prediction, exploring four optimization concepts for the current forensic field (Box 2) [11].

Box 2. Four strategies for age estimation optimization.

• Increasing the sample size of reference populations
• Matching information from a single anatomic area with multifactorial data
• Avoiding ionizing radiation
• Carrying out a fully automated assessment

As tooth color changes with age (Figure 1) [16,17], tooth color analysis could become a reliable alternative for age estimation [18] as a non-invasive and radiation-free approach. However, teeth color is not uniform, varying with the tooth type and area examined [16]. Testing all color parameters on different teeth and different populations is advisable to adapt the color measurement procedure to specific forensic contexts [19]. It is worth noting that equations not geared to population features often have significantly higher errors than equations modeled for population trends [20]. Rather than the standard error associated with the technique, it is more crucial that it has been tested on as many different populations as possible [5]. In the meantime, there has been considerable development in technological resources, providing the most accurate methods possible, evolving towards automatic age evaluation [5,11,15,20,21].

The main purpose of this study is to deepen knowledge of age estimation methods based on tooth color, aiming to enhance their accuracy by leveraging technological advances and the potential of utilizing multifactorial information, while adhering to ethical and legal principles.

2. Methods

A literature review was conducted on tooth color measurement in age estimation, using the PubMed, Web of Science, and Scopus databases. The keywords used were forensic identification, age estimation, adult, tooth, color, and dental methods. The inclusion criteria were articles written in English, studies on humans, and participants aged 14 or older. The exclusion criteria were articles written in languages other than English, studies on non-human subjects. The research was performed with no time limits imposed.

3. Results

The literature search led to 83 articles from the databases mentioned above. After removing duplicates, the titles and abstracts were analyzed, leaving 33 eligible articles that met the inclusion and exclusion criteria (Chart 1).

4. Discussion

This review examined the following topics to integrate the physiological, technological, and forensic dimensions of tooth color analysis:

(a)

The biological mechanisms linking age to changes in dentin and enamel;

(b)

The evolution and performance of color measurement devices;

(c)

The methodological implications of these processes for forensic age estimation.

Through the articulation of these three axes, the review attempted to provide interpretative connections that help explain why specific parameters behave as they do, which devices work best, and how these factors influence applicability in living individuals and cadavers.

Dental color analysis involves complex physiological, optical, and methodological parameters. In this work, we have identified three major dimensions: physiological mechanisms driving color change with age; technological developments and comparative performance of color-measuring devices; and methodological implications for forensic age estimation, including tooth- and surface-specific variation, post-mortem effects, and constraints in living individuals.

4.1. Physiological Processes Underlying Tooth Color Change

Color perception is multifactorial and inherently complex, influenced by illumination, light dispersion, and the translucency or opacity of dental tissues, as well as by observer-related variability [16,22].

As teeth age, biological and structural changes in enamel, dentin, and pulp progressively modify their optical behavior. The consistent finding that teeth darken with age [23] reflects cumulative alterations in the enamel and in the dentin. The enamel becomes thinner, more fissured, and less translucent, which increases light scattering and shifts the color towards higher chroma values [15,24,25]. Simultaneously, dentin undergoes continuous secondary dentin deposition, organic matrix modification, and increased pigmentation, which steeply enhances saturation and reduces luminosity [15,24,26,27,28]. Because dentin contributes more heavily to overall tooth color, age-dependent changes in dentin composition, tubule density, and mineral content are the dominant drivers of chromatic evolution across adulthood.

Aging also produces predictable gradients: teeth tend to become redder and more yellowish with age, with women generally presenting lighter and less chromatic teeth than men [17,29,30]. Translucency typically decreases from the incisal to the cervical regions [31], and root surfaces, which are less exposed to environmental factors, exhibit more stable chromatic behavior over time [15]. Devitalised teeth, which exhibit lower luminosity and greater chroma, further illustrate the influence of internal tissue changes on optical outputs [32].

These physiological mechanisms underpin why specific CIE (Commission Internationale de l’Éclairage) parameters, particularly L* (luminosity) and b* (yellow–blue axis), show the strongest correlations with chronological age [15,24,32].

4.2. Technological Developments Across Measurement Devices

A central analytical dimension of this review concerns the evolution and comparative performance of colorimetric technologies, specifically colorimeters, spectrophotometers, and spectroradiometers. Before addressing these, we will make a brief approach regarding some color concepts and standardization.

4.2.1. Color Spaces and Standardization

To standardize interpretation across studies, several color notation systems have been adopted. The Munsell system describes hue, value, and chroma [33,34], while the CIE color spaces (Figure 2), particularly CIELab, CIELCh, and CIEXYZ, allow fine quantification of luminosity (L*), red-green (a*), and yellow-blue (b*) components [15,25,34].

Each of these models enables repeatability, although heterogeneity in sampling protocols has produced variable outcomes across studies. L* and b* consistently show the strongest correlation with age [15,24,30], but differences in tooth type, lighting, and surface measurement area result in inconsistent correlations between studies.

4.2.2. Comparative Performance of Color Measurement Devices

These instruments differ in spectral resolution, sensitivity to illumination, and reproducibility:

• Colorimeters measure tristimulus RGB (red, green, and blue) values using filters. They are affordable and straightforward to operate [16,35,36], but their limited spectral capture and susceptibility to filter aging reduce precision [22]. The Shade Eye NCC (Natural Esthetics, Fussen, Germany), for instance, explained only 48–56% of age variance and is constrained by small measurement windows and surface-specific variability [35].
• Spectrophotometers offer the most precise and reproducible measurements, capturing full spectral reflectance curves and demonstrating superior accuracy, approximately 33% higher than colorimeters and far closer to real color perception than visual assessment [16,37]. Their robustness against illumination changes, reduced observer subjectivity, and capacity to detect metamerism make them the current technological standard for forensic applications [15,22,36].
• Spectroradiometers, although less frequently used, provide detailed chromaticity coordinates (CIEXYZ) and yield strong correlations with age when paired with whiteness and yellowing indices [38]. Their primary limitation is the need for carefully controlled illumination environments.

4.2.3. Variability Arising from Tooth Type and Surface Selection

The accuracy of any device is strongly influenced by the tooth and surface being measured. Enamel translucency at incisal edges, gingival effects on cervical regions, and the curved anatomy of crowns introduce variation not attributable to age alone [24,30]. Most studies converge on the upper central incisors as the most stable anatomical reference due to their accessibility, uniformity, and sensitivity to age-related trends [15,17,24,29,39,40]. Root surfaces often exhibit stronger associations with age [16,19,35,40], but cannot be accessed in living individuals.

Furthermore, whole-surface scans reduce error introduced by curvature but require devices with large measurement apertures or integrated scanning functions [35,41].

4.3. Methodological Implications for Forensic Age Estimation

4.3.1. Age-Estimation Performance and Error Patterns

A consistent pattern is the tendency for underestimation in older adults and overestimation in younger individuals [15,35]. This reflects non-linear biological aging, as dentin saturation accelerates up to midlife but stabilizes thereafter, highlighting the need for non-linear models or age-group-specific predictors.

Although most studies report statistically significant correlations between colorimetric parameters and chronological age, these coefficients must be interpreted cautiously. Reported r or ρ values, typically ranging from moderate (0.4–0.6) to moderately strong (0.6–0.8), do not imply high predictive precision [15,24,30,35,40]. When examined alongside the standard errors and prediction intervals provided in the literature, it becomes evident that color-based age estimates usually entail average errors of approximately 10–12 years, even under controlled measurement conditions [15,25,35,38]. This uncertainty is comparable to, and sometimes greater than, the error margins reported for established radiographic or morphological methods, particularly in adult age estimation, where degenerative variability naturally increases [1,5,11].

Moreover, a high correlation does not necessarily translate into accurate individual-level predictions. Multiple studies show marked intra-age-group heterogeneity in L*, a*, and b* values—reflecting biological variability, environmental influences, and methodological inconsistencies—which broadens the confidence intervals of regression-based age estimations [15,24,29,38]. Consequently, although colorimetric techniques offer significant advantages as non-ionizing and non-invasive tools, their predictive uncertainty must be explicitly recognized, and they should be integrated with complementary forensic age-estimation methods whenever possible [11,19,42].

4.3.2. Sex Effects

Sex-related differences, although generally modest, manifest primarily in L* and b* parameters, with women tending to have lighter and less chromatic incisors [19,24,29]. Even if slight, accuracy improves if sex-specific modeling is used.

4.3.3. Tooth Type and Surface Selection

As stated, tooth type and surface affect accuracy. Therefore, standardization is needed regarding vestibular middle third measurements; exclusion of incisal and cervical extremes; and prioritization of single-rooted anterior teeth. Failure to control these variables contributes substantially to heterogeneity across studies [15,16,17,19,24,29,37,38,39,40].

4.3.4. Post-Mortem Interval and Cadaveric Effects

Post-mortem interval (PMI) can significantly influence color outputs, with recently extracted teeth showing stronger correlations with age than long-term skeletal remains [38,43]. Dehydration alters refractive indices and can distort L*, a*, and b* values [18]. Thus, moisture control and PMI documentation are essential for forensic reproducibility.

4.3.5. Forensic Constraints: Living Individuals vs. Cadavers

Some of the most informative measurement surfaces (e.g., mesial or vestibular root surfaces) are only available in cadaveric research, limiting the applicability of these findings to living individuals. Ethics guidelines prevent invasive procedures on living subjects, reinforcing the need for models calibrated specifically on the crown surfaces of anterior teeth.

4.3.6. Ethical Issues

Colorimetric techniques comply with ethical requirements prohibiting unnecessary ionizing radiation in living individuals, particularly asylum seekers, minors, and vulnerable populations [12,14,42]. Unlike radiographic approaches, tooth color measurement is non-invasive, repeatable in longitudinal designs, applicable to both living and deceased, and compliant with European medico-legal recommendations [42].

These advantages position colorimetric age estimation as an increasingly relevant complementary method within multidisciplinary forensic practice.

4.4. Limitations

One problem within the available studies is the influence of multiple biological, behavioral, and environmental confounders on tooth color, many of which are insufficiently controlled. Diet-related chromogens (coffee, tea, red wine) have long been recognized as contributors to extrinsic staining [26]. Although some authors report minimal effects of smoking on color parameters [24], others highlight that lifestyle factors may still produce measurable shifts in L*, a*, and b* values. Tooth vitality is another major confounder: devitalized teeth consistently exhibit wider color variation and higher chroma than vital teeth [32], complicating comparisons when vitality status is unknown or inconsistently reported. Similarly, restorations, fluorosis, enamel defects, or whitening procedures can significantly alter optical properties; yet many studies exclude such teeth without detailing the screening procedures.

A further constraint arises from hydration status. Dehydration increases enamel opacity and alters refractive indices, leading to artefactual changes in shade and chroma [18,36]. This is especially problematic in cadaveric samples, where hydration cannot be standardized. The PMI introduces additional color shifts [44,45], with stronger age-color correlations reported in recently extracted teeth compared with skeletal remains [38,43], suggesting that PMI-dependent degradation in the organic matrix may distort expected optical behavior [45].

Beyond biological factors, there are primary instrument-related sources of variability. Inter-device differences between colorimeters, spectrophotometers, and spectroradiometers can lead to non-comparable outputs due to variations in illumination geometry, spectral bandwidth, measurement area, and metamerism sensitivity [16,22,36]. Even within the same device type, lack of regular calibration, use of inconsistent white references, probe angulation, and absence of positioning aids lead to decreased repeatability and reproducibility [15,17,30]. Illumination conditions are rarely harmonized, and measurement protocols differ in the number of readings, the chosen tooth region, and the background color, all of which directly affect chromatic coordinates.

Taken together, these limitations illustrate why standardized calibration protocols, controlled environments, and explicit reporting of confounders are essential prerequisites for advancing colorimetric age estimation. They also help explain the substantial heterogeneity observed across the literature.

5. Conclusions

Colorimetric assessment of teeth represents a promising adjunct within multidisciplinary forensic age estimation, particularly because it is non-invasive, non-ionizing, and applicable to both living individuals and cadavers. Current evidence indicates that tooth color changes systematically with age due to well-documented physiological alterations in enamel and dentin, making these parameters useful in forensic age estimation.

However, important limitations remain. Existing studies demonstrate considerable variability related to ethnicity, sex, tooth type, vitality, and environmental or behavioral factors, all of which can influence color measurements and introduce uncertainty. Furthermore, methodological inconsistencies—such as differences in calibration procedures, illumination conditions, measurement surfaces, and device specifications—pose ongoing challenges to the comparability of results across studies.

Given these constraints, colorimetric techniques should not be interpreted as stand-alone methods but rather as complementary tools whose predictive value depends on rigorous standardization. Future research should prioritize controlled studies exploring key confounders and inter-device variability; harmonization of measurement protocols, including reporting standards; and broader population sampling to refine reference data.