Quantitative Morphometric Analysis of Carpal Bones in Endemic Populations

Thesis Abstract

Quantitative morphometric analysis of carpal bones is essential for understanding population-specific variation in skeletal architecture and its implications for clinical assessment, forensic identification, and anthropological inference. This study addresses the problem of limited quantitative morphometric data for carpal elements in endemic populations where chronic environmental factors, nutritional status, and habitual activities may influence bone morphology. The aim is to quantify inter- and intra-population variation in carpal bone dimensions and shape, and to assess associations with demographic, environmental, and activity-related variables. Specific objectives are to (1) establish a standardized morphometric protocol for carpals using high-resolution radiographs and three-dimensional surface scans, (2) estimate mean values, variance, and allometric scaling patterns of the scaphoid, lunate, triquetrum, pisiform, trapezium, trapezoid, capitate, and hamate, (3) test for sex- and age-related differences, (4) evaluate the influence of endemic environmental factors such as chronic nutrient deficiency and habitual occupational loading on carpal morphometry, and (5) develop a predictive model incorporating morphometric indices to distinguish population groups. The study adopts a cross-sectional, observational design integrating quantitative morphometrics with demographic and environmental data. The population comprises adults aged 18–65 from three endemic regions with distinct environmental pressures and activity profiles. A stratified random sample of 600 individuals (200 per region; 300 males and 300 females total) is targeted to achieve sufficient statistical power for multivariate analyses. Data collection combines radiographic imaging (standardized PA and lateral wrist views) and 3D surface scanning to capture comprehensive carpal geometry. Morphometric measures include lengths, widths, carpal height ratios, indices of carpal convergence, and geometric morphometric landmarks to quantify shape variation. A structured questionnaire collects anthropometric data, dietary history, socioeconomic status, occupational activities, and health indicators. Instrument validity and reliability are ensured via pilot testing, intra- and inter-observer repeatability assessments (ICC > 0.85 for key measurements), and cross-validation of 3D scanning protocols against radiographic measurements. Data analysis proceeds in sequential stages. Descriptive statistics summarize central tendency and dispersion of morphometric variables. Multivariate analysis of variance (MANOVA) tests for region, sex, and age effects on morphometric profiles, followed by discriminant function analysis to evaluate the capacity to classify individuals by region based on carpal metrics. Allometric scaling is assessed through regression of log-transformed morphometric measures on log body size metrics (e.g., height, forearm length). Principal components analysis (PCA) and geometric morphometric (GM) methods extract shape variation independent of size. Mixed-effects models account for potential clustering by region and family structure, with region treated as a fixed effect and individuals as random effects. Regression analyses examine associations between environmental factors (nutritional markers, occupation-related loading) and morphometric indices, controlling for age and sex. The theoretical framework integrates allometry and functional adaptation models, supported by the biomechanical theory of bone remodeling and the Wolff’s law extension for repetitive loading. Expected findings include pronounced regional differences in carpal dimensions and shape configurations, with endemic regions exhibiting distinct allometric patterns linked to nutritional status and habitual manual labor. Sex and age effects are anticipated but moderated by environmental exposures. The predictive model is expected to achieve significant discrimination between populations (AUC > 0.75) based on integrated morphometric indices. The study contributes to knowledge by providing a robust, replicable morphometric catalog of carpal bones in endemic populations, clarifying how environment and activity shape skeletal structure at the carpus, and offering practical implications for clinical diagnosis, forensic anthropology, and population-specific reference data. Limitations include potential imaging artifacts, cross-sectional design constraints on causal inference, and variation in recall-based environmental data. Recommendations emphasize expanding longitudinal follow-up to monitor morphometric changes over time, integrating paleodemographic data to contextualize observed variation, and applying the developed morphometric framework to other skeletal regions to enhance population-specific skeletal databases. The conclusion underscores the relevance of regionally grounded morphometrics for improving diagnostic accuracy, improving anthropological inference, and informing public health strategies addressing endemic environmental challenges.