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Body Circumferences, Body Mass Index, Waist-HipRatio, and 2D:4D Ratios are Nutritional Screening Tools for Cardiovascular Diseases; A Study for Ethnic Minority in Developing Country

Obaje GS, B. Danborno, Akuyam SA, Timbuak JA

Body Circumferences, Body Mass Index, Waist-HipRatio, and 2D:4D Ratios are Nutritional Screening Tools for Cardiovascular Diseases; A Study for Ethnic Minority in Developing Country

Cardiovascular risk diseases (CVDs), which are among the most difficult health issues, are of global concern in emerging nations. However, among the ethnic minorities in Nigeria, the best screening tools for this nutritional relationship, including the hip and neck circumferences (HC and NC), waist-to-hip ratio (WHR), body mass index (BMI), second and fourth digit lengths (L2 and L4), and digit ratios have not been well presented. This study set out to identify local predictive models between dietary characteristics and digit lengths in the Idoma population, as well as to offer nutritional markers of CVDs. After receiving, filling out, and returning informed permission forms, 617 healthy Idoma individuals between the ages of 11 and 19 were randomly selected. The Ahmadu Bello University Zaria research committee provided an ethical report, and the study was carried out between February 11, 2021, and November 19, 2022. Digital stadiometer and inelastic measuring tape were used to measure the nutritional parameters, which include HC, NC, BMI, WHR, and L2, L4 and 2D:4D ratios, respectively. When digit lengths and ratios (L2, L4, and 2D:4D) are known, none of the nutritional status screening tests used to identify CVDs in Idoma participants appeared to be outside of normal ranges, and the predictor (R2 Adjusted) was greater in females than in males (R2 = 0.67 and 0.52, P<0.05). In conclusion, there is a connection between nutritional characteristics and the 2D:4D ratios in both sexes, and nutritional indicators demonstrated that the ethnic group is not at risk of CVDs.

Key Words: nutrition, ethnicity, cardiovascular disease, sex, regression models, stature

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