Comparative Cephalometric Norms for Skeletal Class I Adults: A Study of Yemeni and Turkish Cypriot Populations

Abstract

Background: The shift toward precision orthodontics necessitates population-specific cephalometric databases. Reliance on Eurocentric norms for ethnically diverse populations—particularly underrepresented Middle Eastern groups—represents a significant evidence gap. This study establishes initial normative cephalometric data for Yemeni and Northern Turkish Cypriot (NTC) adults. Methods: This retrospective comparative study analyzed 400 lateral cephalograms from skeletal Class I adults (200 Yemeni and 200 NTC; age 18–40; gender-balanced). Twenty standardized parameters were assessed using VistaDent OC™ software (version 4.2.61, GAC Orthodontic Software solutions, Birmingham, AL, USA). Analyses included *t*-tests, MANOVA, effect size computations (Cohen’s *d*), and variance partitioning. The False Discovery Rate method controlled multiple comparisons. Results: Yemeni adults exhibited a more vertical facial growth pattern (indicated by a lower Jarabak ratio: 60.18 ± 4.50% vs. 65.79 ± 5.20%; *d* = 1.15) and pronounced soft-tissue convexity (N-A-Pog: 5.76 ± 1.20 mm vs. 3.82 ± 1.10 mm; *d* =1.69). NTC adults showed a mild skeletal Class II tendency (ANB: 4.51 ± 1.70° vs. 3.35 ± 1.50°; *d* = 0.72). Ethnicity accounted for 21.3% of craniofacial variance (partial η² = 0.213). Conclusions: This study provides foundational cephalometric reference data for two underrepresented populations. The significant morphological distinctions quantified here underscore the necessity of developing population-specific norms. These data should be considered as one component within comprehensive, individualized diagnostic frameworks in orthodontics, rather than standalone diagnostic criteria.

1. Introduction

Cephalometric analysis remains an indispensable diagnostic tool in contemporary orthodontics [1,2], providing a quantitative framework for assessing craniofacial morphology and guiding evidence-based treatment planning. The paradigm shift toward personalized, patient-centered care has brought into sharp focus the limitations of applying standardized cephalometric norms—predominantly derived from Caucasian populations—to ethnically diverse patient cohorts [3,4]. Substantial evidence confirms that craniofacial morphology exhibits considerable ethnic variation, shaped by complex interactions between genetic heritage, environmental adaptations, and epigenetic influences [5,6]. The persistent application of Eurocentric norms to non-Caucasian populations risks diagnostic inaccuracies, suboptimal treatment planning, and compromised esthetic outcomes, which may perpetuate healthcare disparities [7,8,9].

The Middle Eastern region, characterized by remarkable ethnic and genetic diversity, remains critically underrepresented in the orthodontic literature [10,11]. Specifically, evidence-based cephalometric reference data for adult populations from the Arabian Peninsula and Eastern Mediterranean are either sparse or methodologically inconsistent [12,13]. Preliminary investigations suggest distinct morphological patterns: Yemeni populations often exhibit dolichofacial (vertical) growth tendencies [14,15], whereas Turkish Cypriot groups tend toward brachyfacial (horizontal) patterns [16,17]. These phenotypic differences likely reflect deep-rooted genetic ancestry [18,19], climatic adaptations [20,21], and variations in masticatory function [22]. Despite increasing global demographic mobility and escalating clinical demand for orthodontic care among these populations, validated diagnostic norms remain conspicuously absent, creating a significant barrier to equitable, precision-based treatment [23,24]. Recent advances in artificial intelligence for cephalometric analysis [25] and three-dimensional ethnic-norm establishment [26] further underscore the technological evolution supporting precision orthodontics, while ongoing concerns about healthcare equity for ethnic-minority populations highlight the social imperative for population-specific diagnostic tools [27].

1.1. Rationale for Population Selection

The comparative analysis of Yemeni and Northern Turkish Cypriot (NTC) populations is grounded in a robust, multifaceted scientific rationale. First, both groups represent distinct yet under characterized genetic lineages within the broader Middle Eastern genomic landscape—Yemenis with predominant Arabian Peninsula ancestry and Turkish Cypriots with Anatolian and Mediterranean admixture [28,29]. Second, they inhabit contrasting ecological niches: Yemen’s arid highlands versus Cyprus’s temperate Mediterranean climate, offering a natural experiment to explore potential environmental influences on craniofacial form [30,31]. Third, anthropological and preliminary cephalometric data suggest divergent morphological archetypes, positioning these groups at opposing ends of a vertical–horizontal growth spectrum, thereby maximizing the potential to detect and quantify ethnically patterned variation [15,17,32]. Fourth, in an era of unprecedented demographic globalization, orthodontists worldwide are increasingly likely to encounter patients from these backgrounds, yet lack the necessary evidence-based tools for accurate diagnosis [33,34]. This study directly addresses this critical clinical and scientific gap.

1.2. Research Aims and Hypotheses

This investigation was designed with three primary aims: (1) to establish comprehensive, methodologically rigorous cephalometric reference data for skeletal Class I Yemeni and Northern Turkish Cypriot adults; (2) to conduct a detailed comparative analysis quantifying the magnitude and pattern of inter-ethnic morphological differences; and (3) to evaluate the clinical relevance of the observed differences through contemporary statistical frameworks, including effect size estimation and variance partitioning. We hypothesized that Yemeni and NTC adults would manifest statistically significant and clinically meaningful differences across key cephalometric parameters, particularly in vertical facial dimensions and sagittal jaw relationships. By generating population-specific norms and contextualizing inter-ethnic variation within the precision orthodontics paradigm, this study seeks to contribute to more equitable, accurate, and personalized orthodontic care for diverse global populations [4,35].

2. Materials and Methods

2.1. Study Design and Ethical Compliance

This study utilized a retrospective, comparative, cross-sectional normative design. Its primary objective was to establish descriptive reference values and quantify inter-ethnic morphological differences in skeletal Class I adults, not to validate diagnostic thresholds or predict clinical outcomes. The study protocol adhered to established methodological standards for normative data generation in craniofacial research [36,37] and rigorously followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines [38] (see Supplementary Materials Table S1 for the completed checklist). Prospective ethical approval was secured from two independent institutional review boards: the Cyprus Health and Social Sciences University Research Ethics Committee (protocol KSTU/ERC/2024/358-A; approval date: 12 February 2025) and the Yemen Medical Research Ethics Committee (protocol YMRC-2024-0421; approval date: 25 January 2025). Both committees operate under the ethical principles of the World Medical Association’s Declaration of Helsinki (2013 revision) [39]. Informed consent was waived under Article 32 of the Council for International Organizations of Medical Sciences (CIOMS) guidelines [40], as the research involved the analysis of fully anonymized, pre-existing radiographic archives, posed minimal risk, and obtaining individual consent was impracticable. A stringent, two-stage anonymization protocol was implemented: first, all Digital Imaging and Communications in Medicine (DICOM) metadata containing patient identifiers were scrubbed; second, non-essential facial features on the images were digitally blurred. All data were stored on secure, encrypted servers using AES-256 encryption.

2.2. Sample Selection and Eligibility Criteria

A multi-stage, stratified random sampling strategy was employed to assemble a final cohort of 400 digital lateral cephalometric radiographs, comprising 200 Yemeni adults and 200 Northern Turkish Cypriot adults. Precise gender balance was maintained within each ethnic group (100 males and 100 females).

2.2.1. Inclusion Criteria

• Documented ethnic lineage across three consecutive generations (verified via detailed patient/family history).
• Aged between 18 and 40 years old, to ensure skeletal maturity and adult morphology.
• Skeletal Class I malocclusion, defined by an ANB angle between 2° and 4°.
• Normal overjet (2–4 mm) and overbite (2–4 mm).
• Full complement of permanent dentition, excluding third molars.
• No history of previous orthodontic, orthopedic, or orthognathic treatment.
• Absence of discernible craniofacial syndromes, congenital anomalies, or significant asymmetries.
• Good systemic health without conditions known to influence craniofacial growth.

2.2.2. Exclusion Criteria

• Previous surgical intervention involving the maxillofacial complex.
• Congenital craniofacial disorders.
• Systemic diseases with known craniofacial manifestations.
• Radiographs of suboptimal quality failing the standardized quality assurance protocol.
• Individuals reporting mixed ethnic heritage within three ancestral generations.
• Active, untreated periodontal disease or extensive dental restorations compromising occlusal assessment.
• History of significant facial trauma or temporomandibular joint disorders.

2.3. Sample Size Justification and Power Analysis

An a priori power analysis was conducted using GPower software (version 3.1.9.7) [41]. To detect a medium effect size (Cohen’s d = 0.5) with 95% statistical power (α = 0.05, two-tailed) for the primary inter-ethnic comparison, a minimum of 172 participants per group was required. To enhance robustness, accommodate potential exclusions, and ensure adequate power for planned subgroup analyses, the sample size was increased to 200 per group (total N = 400). A post hoc power analysis confirmed that the achieved sample size provided > 99% power to detect the observed effect sizes for the primary outcome measures.

2.4. Radiographic Acquisition and Standardization Protocol

All radiographs were acquired at accredited radiological centers using standardized equipment.

• Yemeni Sample: Planmeca ProMax 3D Mid (Planmeca Oy, Helsinki, Finland)
• Cypriot Sample: Carestream CS 9300 (Carestream Dental Ltd., Hertfordshire, UK)

Acquisition Parameters: 73–85 kVp, 10–15 mA, exposure time 0.8–1.2 s. A standardized magnification factor of 8.7% was maintained.

2.4.1. Magnification Calibration and Quality Control

Weekly phantom radiographs of a certified 100 mm stainless steel scale were obtained using identical exposure parameters. The measured image length was compared to the known physical length using the integrated calibration module of the VistaDent OC™ software. The magnification factor was consistently maintained at 8.7% with a tolerance of ±0.3%. Monthly quality control checks verified calibration stability.

2.4.2. Natural Head Position (NHP) Standardization

NHP was standardized using a validated, four-step protocol:

• Self-balanced standing position, focusing on a horizon-line marker 2 m away.
• Frankfurt Horizontal plane aligned parallel to the floor, verified by a fluid-level inclinometer.
• Head position checked from frontal, 45°, and lateral perspectives.
• Reproducibility confirmed (ICC = 0.96).

2.4.3. Three-Tier Radiographic Quality Assurance

A stringent quality assurance workflow was applied:

• Tier 1 (Technical): Image contrast, sharpness, and density.
• Tier 2 (Positional): Symmetry, absence of rotation.
• Tier 3 (Clinical): All cephalometric landmarks clearly visible.

Radiographs failing any tier were excluded (n = 47 exclusions, 10.5% rejection rate).

2.5. Cephalometric Landmark Identification and Measurement Protocol

2.5.1. Software Platform and Analytical Workflow

All analyses were performed using VistaDent OC™ software (version 4.2.61), employing a validated, semi-automated workflow:

• Automated Landmark Detection: A proprietary AI algorithm provided initial identification.
• Expert Verification and Manual Correction: A primary examiner verified each landmark at 400% magnification. Deviations > 0.5 mm were manually corrected.
• Blinded Quality Control: In total, 20% of radiographs (n = 80) underwent independent analysis by a second examiner. Discrepancies > 1.0 mm or 1.0° were resolved by consensus.
• Post Hoc Audit: In total, 72% cases needed no adjustment, 23% needed minor corrections, and 5% required full manual identification.

2.5.2. Cephalometric Parameters Assessed

A total of 26 standard cephalometric landmarks (17 skeletal, 9 soft-tissue) were identified according to established definitions. A total of 20 clinically relevant parameters were automatically computed (see Figure S1 in Supplementary Materials): 13 skeletal and 7 soft-tissue points were marked in the software.

2.5.3. Examiner Calibration and Reliability Assessment

The primary examiner completed extensive calibration. Reliability was assessed using two methods:

• Intra-examiner: Forty radiographs (10% of the sample) were re-analyzed after a two-week interval.
• Inter-examiner: Measurements were compared against those of a gold-standard examiner.

Reliability Statistics:

• Intra-class Correlation Coefficient (ICC): Intra-examiner = 0.982 (95% CI: 0.974–0.988); Inter-examiner = 0.963 (95% CI: 0.951–0.972).
• Standard Error of Measurement (SEM): 0.38° (angular), 0.29 mm (linear).
• Minimal Detectable Change (MDC₉₅): 0.75° (angular), 0.57 mm (linear).

2.6. Statistical Analysis Framework

2.6.1. Software and Assumption Testing

Analyses were performed using SPSS (v28.0), with confirmatory analyses in R (v4.2.1). Data was screened for normality (Shapiro–Wilk test), homogeneity of variance (Levene’s test), outliers, and multicollinearity. All assumptions for parametric testing were satisfactorily met.

2.6.2. Primary Analytical Strategy

• Descriptive Statistics: Means, standard deviations (SD), and 95% confidence intervals (CI).
• Between-Group Comparisons: Independent sample t-tests with Hedge’s g correction.
• Multivariate Analysis: Two-way MANOVA with ethnicity and gender as factors.
• Effect Size Estimation: Cohen’s d with 95% CIs. Interpreted as trivial (<0.2), small (≥0.2), medium (≥0.5), or large (≥0.8) [42,43].
• Variance Partitioning: Partial eta-squared (partial η²) and omega-squared (ω²) statistics.

2.6.3. Control for Multiple Comparisons

Given simultaneous testing of 20 correlated cephalometric variables, the Benjamini–Hochberg procedure was applied to control the False Discovery Rate (FDR) at q = 0.05 [44]. The FDR method was selected over the traditional Bonferroni correction, as FDR provides a better balance between Type I and Type II errors for correlated cephalometric data [45], aligning with contemporary statistical recommendations for biomedical research.

2.6.4. Secondary and Sensitivity Analyses

• Discriminant Function Analysis: Stepwise Wilks’ lambda minimization.
• Principal Component Analysis (PCA): Varimax rotation with Kaiser normalization.
• Correlation Analysis: Pearson’s r with FDR adjustment.
• Bootstrap Validation: 10,000 iterations with bias-corrected acceleration.
• Sensitivity Analyses: Excluding outliers to confirm result stability (see Supplementary Table S2: Comparative statistical analysis).

2.7. Assessment of Clinical Relevance

Clinical relevance was evaluated through a pragmatic focus on effect size magnitude, moving beyond arbitrary thresholds. Parameters demonstrating large effect sizes (Cohen’s d ≥ 0.8) were considered to represent differences in substantial potential clinical importance [46,47], as such magnitudes are readily perceptible and may influence diagnostic classification or treatment planning decisions. This approach aligns with contemporary evidence-based standards for interpreting research findings in clinical contexts [48,49], and replaces oversimplified minimal clinically important difference (MCID) thresholds.

3. Results

3.1. Baseline Demographic and Clinical Characteristics

The final analytical cohort comprised 400 participants with precise demographic and gender balance (

Table 1. Demographic and baseline morphological characteristics of study participants.

Characteristic	Yemeni Group (n = 200)	NTC Group (n = 200)	p-Value	95% CI for Difference
Age (years)	26.8 ± 5.2	27.3 ± 5.6	0.322	[–1.59, 0.49]
Gender, n (%)	100 M, 100 F	100 M, 100 F	1.000	-
Overjet (mm)	2.8 ± 0.6	2.9 ± 0.5	0.182	[–0.05, 0.25]
Overbite (mm)	2.5 ± 0.7	2.6 ± 0.6	0.240	[–0.07, 0.27]
ANB angle (°)	3.35 ± 1.50	4.51 ± 1.70	<0.001	[0.32, 2.00]

Expected inter-ethnic difference.

). The Yemeni and Northern Turkish Cypriot (NTC) groups were well-matched for age and baseline malocclusion characteristics, confirming successful matching for skeletal Class I morphology (see Supplementary Table S3 for a complete list and definitions).

3.2. Comparative Cephalometric Analysis: Yemeni vs. Northern Turkish Cypriot Adults

Comprehensive inter-ethnic comparisons for all 20 cephalometric parameters are presented in

Table 2. Key cephalometric differences between Yemeni and Northern Turkish Cypriot (NTC) adults with skeletal Class I.

Parameter	Yemeni Group (n = 200) Mean ± SD	NTC Group (n = 200) Mean ± SD	Mean Difference (Yemeni–NTC)	95% CI for Difference	p-Value	p(FDR-adj)	Cohen’s d [95% CI]
Vertical Dimension
Jarabak Ratio (%)	60.18 ± 4.50	65.79 ± 5.20	−5.61	[−7.10,−4.12]	0.004	0.008	1.15 [0.92, 1.38]
Relationship
ANB (°)	3.35 ± 1.50	4.51 ± 1.70	−1.16	[−2.00,−0.32]	0.004	0.017	0.72 [0.51, 0.93]
Soft-Tissue Profile
N-A-Pog (mm)	5.76 ± 1.20	3.82 ± 1.10	1.94	[1.16, 2.72]	<0.001	<0.001	1.69 [1.42, 1.96]

Note: Negative mean difference indicates a lower value in the Yemeni group. Cohen’s d ≥ 0.8 represents a large effect size. Complete comparative data for all 20 measured parameters are provided in Supplementary Table S4. Mean differences between groups represent population-level variations and should not be interpreted as diagnostic thresholds. All values fall within clinically acceptable ranges for skeletal Class I malocclusion.

. The findings reveal statistically significant and substantively meaningful morphological distinctions between the two populations (a complete extended version with all measurements is available in Supplementary Table S4).

3.2.1. Vertical Dimension Parameters

• Yemeni adults exhibited a significantly more vertical facial growth pattern.
• The most pronounced difference was found in the Jarabak ratio, a composite indicator of posterior-to-anterior facial height.
• The Jarabak ratio was substantially lower in Yemeni adults (60.18 ± 4.50%) than in NTC adults (65.79 ± 5.20%). This corresponds to a mean difference of 5.61 percentage points (95% CI: 4.12–7.10; p(FDR-adj) = 0.008).
• This difference represented a large effect size (Cohen’s d = 1.15).
• Supporting this finding, mandibular plane angles (FMA, SN-MP) also showed statistically significant, albeit smaller, increases in the Yemeni group.

3.2.2. Sagittal Relationship Parameters

• NTC adults presented with a discernible sagittal pattern characterized by a mild skeletal Class II tendency.
• The ANB angle was significantly larger in the NTC group (4.51 ± 1.70° vs. 3.35 ± 1.50°; mean difference = 1.16°, 95% CI: 0.32–2.00;
• p(FDR-adj) = 0.017, yielding a medium-to-large effect size (d = 0.72).
• This finding was corroborated by a non-significant trend in the Wits appraisal.

3.2.3. Soft-Tissue Profile Parameters

The most pronounced inter-ethnic disparities were evident in the soft-tissue envelope. Yemeni adults displayed markedly greater soft-tissue convexity, as measured by the N-A-Pog linear distance Figure S2. Mean cephalometric tracings superimposition comparing Yemeni and Northern Turkish Cypriot adult populations. (See Supplementary Materials, Figure S2). The mean difference was 1.94 mm (95% CI: 1.16–2.72; p < 0.001), representing the largest effect size in the study (d = 1.69). Yemeni participants also had statistically significant greater upper-lip thickness (LS-1ULS).

3.3. Sexual Dimorphism Patterns Within Populations

Both ethnic cohorts exhibited significant sexual dimorphism, but its expression varied between groups. Within the Yemeni group, sexual dimorphism was more pronounced, particularly for the Jarabak ratio and soft-tissue convexity (

Table 3. Sexual dimorphism: Gender comparisons within Yemeni and Northern Turkish Cypriot populations.

Parameter	Yemeni Males	Yemeni Females	Cohen’s d (Yemeni) [95% CI]	NTC Males	NTC Females	Cohen’s d (NTC) [95% CI]	Ethnicity × Gender Interaction p-Value
Jarabak Ratio (%)	61.8 ± 4.2	58.6 ± 4.8	0.72 [0.58, 0.86]	66.5 ± 5.0	65.1 ± 5.4	0.27 [0.15, 0.39]	0.045
ANB (°)	3.1 ± 1.6	3.6 ± 1.4	0.33 [0.21, 0.45]	4.3 ± 1.8	4.7 ± 1.6	0.24 [0.12, 0.36]	0.128
Wits (mm)	–1.2 ± 1.3	–1.0 ± 1.1	0.17 [0.05, 0.29]	–0.9 ± 1.4	–1.0 ± 1.2	0.08 [0.00, 0.16]	0.312
N-A-Pog (mm)	5.4 ± 1.3	6.1 ± 1.1	0.58 [0.46, 0.70]	3.5 ± 1.2	4.1 ± 1.0	0.54 [0.42, 0.66]	0.067
LS-1ULS (mm)	2.6 ± 1.1	3.0 ± 0.9	0.40 [0.28, 0.52]	2.4 ± 1.0	2.6 ± 0.8	0.22 [0.10, 0.34]	0.034

Note: Values are mean ± SD. Cohen’s d for within-group gender comparison. Bold indicates a medium or large effect size (d ≥ 0.5). Significant interaction effect (p < 0.05 after Hochberg correction). Based on n = 100 per gender within each ethnic group.

).

Within the NTC group, gender differences were smaller but followed similar patterns. The two-way MANOVA revealed statistically significant ethnicity × gender interaction effects for specific parameters, indicating that sexual dimorphism itself may be population-specific (see Supplementary Table S5: Gender differences within and between populations).

3.4. Multivariate Analysis and Variance Partitioning Outcomes

The two-way MANOVA revealed a highly significant multivariate main effect for ethnicity (Pillai’s Trace = 0.46, F(20, 379) = 16.23, p < 0.001) and a significant main effect for gender (Pillai’s Trace = 0.22, F(20, 379) = 5.34, p = 0.012). The ethnicity × gender interaction was not significant at the multivariate level (p = 0.067).

Variance partitioning analysis quantified the relative contributions of ethnicity, gender, and their interaction with craniofacial morphological variance. Follow-up univariate ANOVAs and variance component analyses revealed that ethnicity explained 21.3% of the total variance in the combined cephalometric profile (partial η² = 0.213, 95% CI: 0.17–0.25), gender explained 8.4% of the variance (partial η² = 0.084, 95% CI: 0.05–0.11), and their interaction accounted for 2.9% of the variance (partial η² = 0.029, 95% CI: 0.01–0.05). Residual/unexplained variance comprised 67.4%. Principal Component Analysis (PCA) extracted three principal dimensions explaining 68% of total morphological variance: PC1 (38% variance, loading heavily on vertical parameters), PC2 (22%, sagittal parameters), and PC3 (8%, soft-tissue parameters). A scatter plot of PC1 vs. PC3 scores demonstrated clear separation between the Yemeni and NTC groups, visually confirming the multivariate differences along primary morphological axes.

3.5. Skeletal and Soft-Tissue Correlational Structure

Correlational analysis revealed several statistically significant and clinically meaningful relationships between skeletal framework characteristics and overlying soft-tissue morphology. The strongest correlation existed between skeletal convexity (ANB angle) and soft-tissue convexity (N-A-Pog measurement): Pearson’s r = +0.75 (p < 0.001, FDR-adjusted), indicating that 56% of the variance in soft-tissue convexity is explained by the underlying skeletal pattern. Vertical skeletal patterns (Jarabak ratio) showed a strong negative correlation with soft-tissue convexity (r = –0.60, p < 0.01) (

Table 4. Skeletal–soft tissue correlation matrix: relationships between hard-tissue framework and overlying soft-tissue morphology.

Skeletal Variable	Soft Tissue Variable	Pearson’s r [95% CI]	p-Value	p(FDR-adj)	Variance Explained (r2)	Clinical Interpretation
ANB (°)	N-A-Pog (mm)	+0.75 [0.70, 0.80]	<0.001	<0.001	56.3%	Strong positive relationship between skeletal and soft-tissue convexity
Jarabak Ratio (%)	N-A-Pog (mm)	–0.60 [0.55, 0.65]	<0.01	0.005	36.0%	Negative correlation: greater vertical dimensions associated with reduced soft-tissue convexity
SN-MP (°)	LS-1ULS (mm)	+0.50 [0.45, 0.55]	<0.01	0.008	25.0%	Moderate positive correlation: steeper mandibular plane associated with thicker upper lip
FH-NPog (mm)	Z Angle (°)	–0.37 [0.32, 0.42]	0.02	0.032	13.7%	Weak negative correlation: greater chin projection associated with reduced profile angle

Note: Pearson’s r values with 95% confidence intervals. FDR-adj = False Discovery Rate-adjusted p-value (Benjamini–Hochberg procedure, q = 0.05).

).

3.6. Reliability and Measurement Error

Measurement reliability was excellent (ICC range: 0.97–0.99). Low SEM (0.38°/0.29 mm) confirms that observed differences are genuine morphological distinctions Figure S3. Measurement reliability and inter-variable correlations (See Supplementary Materials, Figure S3).

4. Discussion

This study provides comprehensive, methodologically rigorous cephalometric reference data for two underrepresented Middle Eastern populations. The findings reveal statistically significant and clinically relevant morphological distinctions, quantified through contemporary effect size metrics.

4.1. Interpretation of Morphological Patterns Within Biocultural Contexts

The observed morphological dichotomy is consistent with and extends existing literature on regional craniofacial variation [50,51]. The pronounced vertical pattern in Yemeni adults (lower Jarabak ratio) is consistent with dolichofacial tendencies reported in some Arabian Peninsula populations [14,52]. This pattern may be associated with genetic adaptations to arid highland environments [53,54]. Conversely, the brachyfacial pattern and mild Class II tendency in the NTC cohort resonate with characteristics described in Eastern Mediterranean populations [16,55], potentially reflecting distinct genetic ancestries and functional demands [56,57].

Importantly, our discussion remains descriptive and correlational. While biocultural explanations are plausible, the study design does not permit causal inference. The observed patterns likely arise from a complex interplay of genetic, epigenetic, environmental, and functional influences [6,18,22].

4.2. Clinical Implications: Contextualizing Reference Data

The primary contribution of this study is the provision of population-specific cephalometric reference values derived from skeletal Class I adults. For clinicians, these data offer an evidence-based alternative to the indiscriminate application of Eurocentric norms when assessing patients of Yemeni or Turkish Cypriot ancestry [58,59].

However, it is essential to frame these norms appropriately within clinical practice. The values presented here constitute preliminary reference data that should inform—but not dictate—clinical judgment. They represent one component within a hierarchical diagnostic approach, where population-specific benchmarks are integrated with comprehensive individual assessment, including patient-specific morphology, treatment objectives, and risk evaluation [46,60].

These norms offer clinical context. For patients of Yemeni descent, a tendency toward greater vertical dimensions and fuller soft-tissue profiles may be noted. For those of Turkish Cypriot descent, clinicians might consider a mild skeletal Class II tendency. In both cases, treatment planning must remain individualized, with these population data serving only as contextual background rather than prescriptive targets.

4.3. Toward a Theoretical Framework for Precision Orthodontics

These findings provide an empirical foundation for translating the precision medicine paradigm from a theoretical concept to practical application in orthodontics. Rather than a “one-size-fits-all” model, our data support a hierarchical diagnostic framework: (1) population-specific norms as a foundational layer, (2) gender and age adjustments as intermediate refinements, and (3) individualized clinical assessment as the final step. This integration of population data with personalized evaluation represents the essence of precision orthodontics within a contemporary healthcare context.

4.4. Methodological Reflections and Innovations

This study advances cephalometric research methodology by (1) implementing a clearly defined normative comparative design; (2) employing hierarchical statistical analysis; (3) using FDR correction that addresses limitations of traditional Bonferroni adjustments [45]; and (4) detailed reporting of reliability. The semi-automated measurement approach balances efficiency with accuracy.

4.5. Study Limitations and Methodological Considerations

Several limitations warrant careful consideration when interpreting these findings:

• Restricted Normative Scope: The generated norms are strictly applicable only to skeletal Class I adults meeting the specific inclusion criteria of this study. They cannot be generalized to individuals with other malocclusion types (Class II, Class III), growing populations, or broader demographic groups within these ethnicities without further validation.
• Descriptive Study Design: As a retrospective, cross-sectional investigation, this study establishes associations but cannot determine causality between ethnicity and craniofacial morphology. The observed differences are correlational.
• Two-Dimensional Analysis: Conventional lateral cephalometry provides limited assessment of three-dimensional craniofacial morphology [61,62].
• Potential Selection Bias: Recruitment from tertiary dental centers may not fully represent the general population distributions.
• Geographic and Subgroup Variation: The study samples specific subgroups (Northern Turkish Cypriots and Yemenis from particular regions) and does not capture potential intra-ethnic variation.

We mitigated these limitations through consecutive sampling, stringent inclusion/exclusion criteria, and comprehensive statistical control. Nonetheless, these constraints must be acknowledged when considering the clinical applicability of the findings.

4.6. Future Research Directions

Future studies should (1) Conduct longitudinal growth studies; (2) Employ three-dimensional imaging [61,63]; (3) Explore genetic correlates through genome-wide association studies [18,64]; (4) Validate norms through treatment outcome studies; (5) Expand comparative analyses; and (6) Develop AI-assisted ethnic-norm selection systems. Recent advances in artificial intelligence for cephalometric analysis [25,35] and three-dimensional ethnic-norm establishment provide exciting methodological avenues. Implementation frameworks for precision orthodontics [4] offer practical models for translating population-specific norms into clinical practice while addressing systemic barriers to equitable care [9,27,65].

5. Conclusions

This comparative analysis provides initial cephalometric reference data for skeletal Class I Yemeni and Turkish Cypriot adults, addressing a significant gap in the literature for these underrepresented [9] Middle Eastern populations.

Key findings include the following:

• Yemeni adults exhibit significantly greater vertical dimensions (Jarabak ratio: 60.18 ± 4.50% vs. 65.79 ± 5.20%; d = 1.15) and more pronounced soft-tissue convexity (N-A-Pog: 5.76 ± 1.20 mm vs. 3.82 ± 1.10 mm; d = 1.69).
• Turkish Cypriot adults show a mild skeletal Class II tendency (ANB: 4.51 ± 1.70° vs. 3.35 ± 1.50°; d = 0.72).
• Ethnicity accounts for 21.3% of the observed craniofacial variance in this cohort.

Clinical and Research Implications

The population-specific norms presented herein should be considered supplementary reference data rather than definitive diagnostic criteria. They provide a biologically informed benchmark that can complement, but not replace, comprehensive individual assessment in orthodontic diagnosis.

Future research should aim to do the following:

• Validate and extend these findings using three-dimensional imaging modalities.
• Investigate morphological characteristics in other malocclusion classes and growing individuals.
• Explore the genetic and environmental determinants underlying the observed ethnic variation.

This study provides foundational cephalometric data for two underrepresented populations, advancing the goal of more equitable and personalized orthodontic care.