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Development of the Anthropometric Grouping Index for the Eastern Caribbean Population Using the Eastern Caribbean Health Outcomes Research Network (ECHORN) Cohort Study Data.
Almodóvar-Rivera, Israel A; Rosario-Rosado, Rosa V; Nazario, Cruz M; Hernández-Santiago, Johan; Ramírez-Marrero, Farah A; Nunez, Maxime; Maharaj, Rohan; Adams, Peter; Martinez-Brockman, Josefa L; Tessier-Sherman, Baylah; Nunez-Smith, Marcella.
Afiliação
  • Almodóvar-Rivera IA; Department of Mathematical Sciences, University of Puerto Rico at Mayagüez, Mayagüez 00681, Puerto Rico.
  • Rosario-Rosado RV; Department of Biostatistics and Epidemiology, Graduate School of Public Health, University of Puerto Rico at Medical Sciences Campus, San Juan 00936, Puerto Rico.
  • Nazario CM; Department of Biostatistics and Epidemiology, Graduate School of Public Health, University of Puerto Rico at Medical Sciences Campus, San Juan 00936, Puerto Rico.
  • Hernández-Santiago J; Department of Biostatistics and Epidemiology, Graduate School of Public Health, University of Puerto Rico at Medical Sciences Campus, San Juan 00936, Puerto Rico.
  • Ramírez-Marrero FA; Department of Exercise Physiology, University of Puerto Rico at Río Piedras, San Juan 00925, Puerto Rico.
  • Nunez M; School of Nursing, University of the Virgin Islands, St. Thomas, VI 00802, USA.
  • Maharaj R; Department of Paraclinical Sciences, University of the West Indies, Saint Augustine, Trinidad and Tobago.
  • Adams P; Department of Family Medicine, Faculty of Medical Sciences, University of the West Indies, Cave Hill BB11000, Barbados.
  • Martinez-Brockman JL; Equity Research and Innovation Center, Yale School of Medicine, New Haven, CT 06510, USA.
  • Tessier-Sherman B; Equity Research and Innovation Center, Yale School of Medicine, New Haven, CT 06510, USA.
  • Nunez-Smith M; Equity Research and Innovation Center, Yale School of Medicine, New Haven, CT 06510, USA.
Article em En | MEDLINE | ID: mdl-36012047
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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Glicemia / Grupos Populacionais Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Glicemia / Grupos Populacionais Idioma: En Ano de publicação: 2022 Tipo de documento: Article