Development of the Anthropometric Grouping Index for the Eastern Caribbean Population Using the Eastern Caribbean Health Outcomes Research Network (ECHORN) Cohort Study Data

Israel A. Almodóvar-Rivera (), Rosa V. Rosario-Rosado, Cruz M. Nazario, Johan Hernández-Santiago, Farah A. Ramírez-Marrero, Maxime Nunez, Rohan Maharaj, Peter Adams, Josefa L. Martinez-Brockman, Baylah Tessier-Sherman and Marcella Nunez-Smith
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Israel A. Almodóvar-Rivera: Department of Mathematical Sciences, University of Puerto Rico at Mayagüez, Mayagüez 00681, Puerto Rico
Rosa V. Rosario-Rosado: Department of Biostatistics and Epidemiology, Graduate School of Public Health, University of Puerto Rico at Medical Sciences Campus, San Juan 00936, Puerto Rico
Cruz M. Nazario: Department of Biostatistics and Epidemiology, Graduate School of Public Health, University of Puerto Rico at Medical Sciences Campus, San Juan 00936, Puerto Rico
Johan Hernández-Santiago: Department of Biostatistics and Epidemiology, Graduate School of Public Health, University of Puerto Rico at Medical Sciences Campus, San Juan 00936, Puerto Rico
Farah A. Ramírez-Marrero: Department of Exercise Physiology, University of Puerto Rico at Río Piedras, San Juan 00925, Puerto Rico
Maxime Nunez: School of Nursing, University of the Virgin Islands, St. Thomas, VI 00802, USA
Rohan Maharaj: Department of Paraclinical Sciences, University of the West Indies, Saint Augustine, Trinidad and Tobago
Peter Adams: Department of Family Medicine, Faculty of Medical Sciences, University of the West Indies, Cave Hill BB11000, Barbados
Josefa L. Martinez-Brockman: Equity Research and Innovation Center, Yale School of Medicine, New Haven, CT 06510, USA
Baylah Tessier-Sherman: Equity Research and Innovation Center, Yale School of Medicine, New Haven, CT 06510, USA
Marcella Nunez-Smith: Equity Research and Innovation Center, Yale School of Medicine, New Haven, CT 06510, USA

IJERPH, 2022, vol. 19, issue 16, 1-9

Abstract: Improving public health initiative requires an accurate anthropometric index that is better suited to a specific community. In this study, the anthropometric grouping index is proposed as a more efficient and discriminatory alternative to the popular BMI for the Eastern Caribbean population. A completely distribution-free cluster analysis was performed to obtain the 11 categories, leading to AGI-11. Further, we studied these groups using novel non-parametric clustering summaries. Finally, two generalized linear mixed models were fitted to assess the association between elevated blood sugar, AGI-11 and BMI. Our results showed that AGI-11 tends to be more sensitive in predicting levels of elevated blood sugar compared to BMI. For instance, individuals identified as obese III according to BMI are (POR: 2.57; 95% CI: (1.68, 3.74)) more likely to have elevated blood sugar levels, while, according to AGI, individuals with similar characteristics are (POR: 3.73; 95% CI: (2.02, 6.86)) more likely to have elevated blood sugar levels. In conclusion, the findings of the current study suggest that AGI-11 could be used as a predictor of high blood sugar levels in this population group. Overall, higher values of anthropometric measures correlated with a higher likelihood of high blood sugar levels after adjusting by sex, age, and family history of diabetes.

Keywords: anthropometric grouping index; cluster analysis; distribution-free pairwise overlap; ECHORN; Caribbean population (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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