Journal of health research in community

Introduction
Dermatoglyphics, a study of epidermal ridge configurations, provides a stable set of biological markers formed during early fetal development. Since fingerprint patterns remain unchanged throughout life, they are important non-invasive markers of prenatal factors that may contribute to later metabolic disorders. Obesity, a rapidly increasing global concern, is affected by genetic, environmental, and developmental factors. As obesity continues to rise among young adults, identifying early developmental indicators that reflect susceptibility is important. Previous studies have reported significant associations between fingerprint patterns and obesity-related conditions in children and adults across different populations. Despite these findings, little is known about this relationship among young women in Iran. Therefore, the present study aimed to investigate the association between fingerprint patterns and obesity among female college students in Mazandaran, north of Iran, to evaluate whether fingerprints may serve as a potential early screening measure for obesity risk.

Methods 
This case–control study was conducted on 200 female students aged 19–30 years at the University of Mazandaran. A multi-stage cluster sampling method was used to select samples from different faculties and academic courses. Based on the World Health Organization criteria for Asian populations, participants were divided into two groups: normal-weight (BMI:18.5–22.9 kg/m², n=100) and obese (BMI≥27.5 kg/m², n=100). Individuals with chronic diseases, dermatological abnormalities affecting finger patterns, or those following active weight-loss diets were excluded. Anthropometric measurements included measuring height with a wall-mounted stadiometer, weight with a calibrated digital scale, and BMI calculation.
Fingerprint samples were collected using a SecuGen Hamster Plus biometric scanner, compliant with ISO/IEC fingerprint imaging standards and capable of producing high-resolution images suitable for pattern analysis. Before scanning, participants washed and dried their hands thoroughly to improve image clarity. Each finger was scanned twice, and the clearest image was selected. Fingerprint patterns were categorized into arch, loop, and whorl types, according to the Galton–Henry classification system, and further classified into seven recognized subtypes. Quantitative dermatoglyphic indices, including total finger ridge count (TFRC) and absolute finger ridge count (AFRC), were also assessed. Data analysis was performed in IBM SPSS software, version 27. The Kolmogorov–Smirnov test assessed normality of the data distribution, while the Chi-square test evaluated differences in fingerprint patterns between groups. The independent t-test was used to compare ridge counts between groups.

Results 
Examination of fingerprint subtypes revealed notable differences between the two groups. The ulnar loop was the most common subtype overall, appearing in 54.9% of fingerprint patterns in the normal-weight group and 49.4% in the obese group. The plain arch was the least frequent pattern in the normal-weight group (1.4%), while the radial loop was the least frequent pattern in the obese group (1.3%). Arch patterns were more prevalent in the obese group (7.5%) than in the normal-weight group (4%), and this difference was statistically significant (P=0.001). Conversely, loop patterns were significantly more common in the normal-weight group than in the obese group (57.4% vs. 50.7%; P=0.049). Whorl patterns did not differ significantly between the groups (P=0.673), although there were slightly higher among obese participants (41.8% vs. 38.6%).
Further analysis of the right and left hands provided additional insights into fingerprint pattern distribution. Arch patterns in both hands differed significantly between the two groups, with obese participants showing higher frequencies (P=0.017 for the right hand; P=0.012 for the left hand). In contrast, loop patterns in the left hand were significantly more common in the normal-weight group (P=0.012). 
The Kolmogorov–Smirnov test indicated that the ridge count data followed a normal distribution (P>0.05). Independent t-test results demonstrated a significant difference in mean AFRC values between groups (P=0.047), with the normal-weight group showing higher values (200.06 ±7.93) compared to the obese group (179.15±6.86). Maximum AFRC was 379 in the normal-weight group and 330 in the obese group. Although mean TFRC values did not differ significantly between groups (P=0.222), mean values were higher in the normal-weight group. 

Conclusion
The findings of this study demonstrate clear associations between fingerprint patterns and obesity status among young women in Iran. Obese participants had more arch patterns, fewer loop patterns, and fewer ridge counts, suggesting that dermatoglyphic characteristics may reflect underlying developmental and biological differences associated with obesity status. Although the study included only female samples (limiting generalizability) and relied on BMI as the primary measure of adiposity, the strong fingerprint pattern differences suggest that dermatoglyphics have potential as an inexpensive, stable, and non-invasive screening tool for identifying individuals at elevated risk of obesity. Future longitudinal studies integrating genetic and metabolic biomarkers are recommended.

Ethical Considerations
Compliance with ethical guidelines
Written informed consent was obtained from all participants. Confidentiality and voluntary participation were ensured throughout the study.

Funding
This study was part of research project funded by the University of Mazandaran (Project ID: 2024465). 

Conflicts of interest
The authors declared no conflict of interest.

Acknowledgments
The author would like to thank all participants as well as  Ms. Fatemeh Fazl-Ali and Ms. Niloofar Mohammadian for their assistance during fingerprint data collection.

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