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      Relationship of anthropometric indices with rate pressure product, pulse pressure and mean arterial pressure among secondary adolescents of 12–17 years

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          Abstract

          Objectives

          To determine the correlation between anthropometric indices and the selected hemodynamic parameters among secondary adolescents aged 12–17 years.

          Results

          Our findings showed weak positive correlation between generally body surface area, neck circumference and conicity index with the hemodynamic parameters (systolic blood pressure, diastolic blood pressure, resting pulse rate, mean arterial pressure, rate pressure product and pulse pressure). However, the ponderosity index, body mass index and waist hip ratio showed negative weak correlations with the hemodynamic parameters. There was a significant difference in pulse pressure among the BMI categories. All parameters showed significant (p < 0.05) differences across the categories of neck circumference and waist hip ratio. Generally, in multivariate regression analysis, anthropometric indices showed significant prediction of the hemodynamic parameters.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s13104-021-05515-w.

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          Most cited references25

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          Development of a WHO growth reference for school-aged children and adolescents

          OBJECTIVE: To construct growth curves for school-aged children and adolescents that accord with the WHO Child Growth Standards for preschool children and the body mass index (BMI) cut-offs for adults. METHODS: Data from the 1977 National Center for Health Statistics (NCHS)/WHO growth reference (1-24 years) were merged with data from the under-fives growth standards' cross-sectional sample (18-71 months) to smooth the transition between the two samples. State-of-the-art statistical methods used to construct the WHO Child Growth Standards (0-5 years), i.e. the Box-Cox power exponential (BCPE) method with appropriate diagnostic tools for the selection of best models, were applied to this combined sample. FINDINGS: The merged data sets resulted in a smooth transition at 5 years for height-for-age, weight-for-age and BMI-for-age. For BMI-for-age across all centiles the magnitude of the difference between the two curves at age 5 years is mostly 0.0 kg/m² to 0.1 kg/m². At 19 years, the new BMI values at +1 standard deviation (SD) are 25.4 kg/m² for boys and 25.0 kg/m² for girls. These values are equivalent to the overweight cut-off for adults (> 25.0 kg/m²). Similarly, the +2 SD value (29.7 kg/m² for both sexes) compares closely with the cut-off for obesity (> 30.0 kg/m²). CONCLUSION: The new curves are closely aligned with the WHO Child Growth Standards at 5 years, and the recommended adult cut-offs for overweight and obesity at 19 years. They fill the gap in growth curves and provide an appropriate reference for the 5 to 19 years age group.
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            Neck circumference: a useful screening tool of cardiovascular risk in children.

            Early identification of cardiovascular risk factors consists an essential target for public health. The current study aims to examine the association between neck circumference and several cardiovascular risk factors and to compare it with well-established anthropometric indices. Demographic, anthropometric (body weight and height, waist, hip and neck circumference [WC, HC and NC, respectively]), biochemical (total cholesterol, high-density lipoprotein [HDL] cholesterol, low-density lipoprotein [LDL] cholesterol, triglycerides [TG], fasting plasma glucose and serum insulin), clinical (pubertal stage, systolic and diastolic blood pressure [SBP and DBP, respectively]) and lifestyle (dietary intake, physical activity level) data were collected from 324 children (51.5% boys; 48.5% girls) aged 9-13 in Greece. Body mass index z-score (BMI z-score), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), homeostasis model assessment (HOMA-IR), quantitative insulin sensitivity check index (QUICKI) and fasting glucose to insulin ratio (FGIR) were calculated. All indices (BMI z-score, NC, WC, HC, WHR and WHtR) were correlated with SBP, HDL and insulin-related indices (insulin, HOMA-IR, QUICKI and FGIR) and all indices except WHR with TG. LDL was correlated with BMI z-score, WC, WHR and WHtR, whereas DBP was correlated with BMI z-score, WC, HC and WHtR. In multivariate analysis, HDL, TG, SBP, insulin, HOMA-IR, QUICKI and FGIR were associated with all anthropometric indices; DBP with WC, HC, NC and WHtR; LDL with BMI z-score, WC, HC and WHtR. NC is associated with most cardiovascular disease risk factors. These associations are comparable with those observed for BMI z-score, WC, HC, WHR and WHtR. NC could be a simple, alternative screening tool of cardiovascular risk in children. © 2012 The Authors. Pediatric Obesity © 2012 International Association for the Study of Obesity.
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              Association between simple anthropometric indices and cardiovascular risk factors.

              To identify which of the three simple anthropometric indices, body mass index (BMI), waist-to-hip ratio (WHR) and waist circumference (WC), best predicts cardiovascular risk factors, and to determine if the association between the anthropometric indices and cardiovascular risk factors varies with gender. A cross-sectional population-based survey was carried out during 1995-1996. One thousand and ten Chinese people (500 men and 510 women) aged 25-74 y were recruited as subjects for the study. Metabolic profiles and anthropometric indices were measured. Partial correlation and co-variance analyses showed that WC exhibited the highest degree of association with almost all of the studied metabolic profiles for both men and women. We observed significant gender differences in the association between central or general obesity with cardiovascular risk factors. BMI had an independent and significant association with metabolic risks in men, but not in women, whereas WHR was more strongly correlated with metabolic risks for women than for men. Logistic regression analysis further confirmed the magnitude of the association between the obesity indices and metabolic risks. Among the studied metabolic variables, serum insulin showed the highest degree of association with the obesity indices, followed by plasma glucose, triglyceride, HDL and blood pressure. Total cholesterol and LDL-cholesterol had a small but significant correlation with obesity. No threshold values in the relation between either the anthropometric indices and metabolic values, or with hypertension, diabetes and dislipidemia were observed. The association of central or general obesity and metabolic syndrome varied with gender. In addition, the useful anthropometric predictors for cardiovascular risk factors were BMI and WC for men, and WC and WHR for women.
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                Author and article information

                Contributors
                cgmkats13@gmail.com
                Journal
                BMC Res Notes
                BMC Res Notes
                BMC Research Notes
                BioMed Central (London )
                1756-0500
                17 March 2021
                17 March 2021
                2021
                : 14
                : 101
                Affiliations
                [1 ]Department of Physiology, College of Health, Medicine and Life Sciences, King Ceasor University, Kampala, Uganda
                [2 ]Department of Biochemistry, College of Health, Medicine and Life Sciences, King Ceasor University, Kampala, Uganda
                [3 ]Department of Anatomy, College of Health, Medicine and Life Sciences, King Ceasor University, Kampala, Uganda
                [4 ]GRID grid.448602.c, ISNI 0000 0004 0367 1045, Department of Physiology, Faculty of Health Sciences, , Busitema University, ; Mbale, Uganda
                [5 ]GRID grid.442626.0, ISNI 0000 0001 0750 0866, Department of Physiology, Faculty of Health Sciences, , Gulu University, ; Gulu, Uganda
                Author information
                http://orcid.org/0000-0002-7456-0786
                Article
                5515
                10.1186/s13104-021-05515-w
                7968204
                33731195
                94bfbeff-5584-43e8-bbc8-3b69c2a7eb8f
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 2 November 2020
                : 5 March 2021
                Categories
                Research Note
                Custom metadata
                © The Author(s) 2021

                Medicine
                anthropometric indices,rate pressure product,pulse pressure,mean arterial pressure
                Medicine
                anthropometric indices, rate pressure product, pulse pressure, mean arterial pressure

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