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      Waist-to-Height Ratio Percentiles and Cutoffs for Obesity: A Cross-sectional Study in Brazilian Adolescents

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          ABSTRACT

          This study aimed to describe the distribution of waist-to-height ratio (WHtR) percentiles and cutoffs for obesity in Brazilian adolescents. A cross-sectional study including adolescents aged 10 to 15 years was conducted in the city of São Paulo, Brazil; anthropometric measurements (weight, height, and waist-circumference) were taken, and WHtRs were calculated and then divided into percentiles derived by using Least Median of Squares (LMS) regression. The receiver operating characteristic (ROC) curve was used in determining cutoffs for obesity (BMI ≥97th percentile) and Mann-Whitney and Kruskal-Wallis tests were used for comparing variables. The study included 8,019 adolescents from 43 schools, of whom 54.5% were female, and 74.8% attended public schools. Boys had higher mean WHtR than girls (0.45±0.06 vs 0.44±0.05; p=0.002) and higher WHtR at the 95th percentile (0.56 vs 0.54; p<0.05). The WHtR cutoffs according to the WHO criteria ranged from 0.467 to 0.506 and 0.463 to 0.496 among girls and boys respectively, with high sensitivity (82.8-95%) and specificity (84-95.5%). The WHtR was significantly associated with body adiposity measured by BMI. Its age-specific percentiles and cutoffs may be used as additional surrogate markers of central obesity and its co-morbidities.

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          Most cited references46

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          The LMS method for constructing normalized growth standards.

          T. J. Cole (1990)
          It is now common practice to express child growth status in the form of SD scores. The LMS method provides a way of obtaining normalized growth centile standards which simplifies this assessment, and which deals quite generally with skewness which may be present in the distribution of the measurement (eg height, weight, circumferences or skinfolds). It assumes that the data can be normalized by using a power transformation, which stretches one tail of the distribution and shrinks the other, removing the skewness. The optimal power to obtain normality is calculated for each of a series of age groups and the trend summarized by a smooth (L) curve. Trends in the mean (M) and coefficient of variation (S) are similarly smoothed. The resulting L, M and S curves contain the information to draw any centile curve, and to convert measurements (even extreme values) into exact SD scores. A table giving approximate standard errors for the smoothed centiles is provided. The method, which is illustrated with US girls' weight data, should prove useful both for the construction and application of growth standards.
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            Growth at Adolescence

            (1962)
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              Metabolic syndrome in childhood predicts adult metabolic syndrome and type 2 diabetes mellitus 25 to 30 years later.

              To prospectively assess the association of the metabolic syndrome in childhood with adult metabolic syndrome and type 2 diabetes mellitus (T2DM) 25 to 30 years later. Data from the National Heart Lung and Blood Institute Lipid Research Clinics (LRC) Princeton Prevalence Study (1973-1976) and the Princeton Follow-up Study (PFS, 2000-2004) were used. Body mass index (BMI = kg/m(2)) was used as the obesity measure in childhood because waist circumference was not measured at the LRC. The adult T2DM status of participants and their parents was obtained by participant report or fasting blood glucose >/=126 mg/dL. A logistic analysis for clustered samples was used to predict adult metabolic syndrome and T2DM, taking into account sibling correlations in the cohort. Pediatric metabolic syndrome, age at PFS, sex, race, change in BMI percentile, parental history of diabetes, and the interaction of pediatric metabolic syndrome and parental diabetes were explanatory variables. Ages ranged from 5 to 19 years in the LRC and from 30 to 48 years in the PFS. Pediatric metabolic syndrome, parental diabetes, age at follow-up, and change in age-specific BMI percentile were significant predictors of metabolic syndrome in adulthood, and pediatric metabolic syndrome, age at follow-up, black race, and parental diabetes were significant predictors of T2DM. Evaluating 5- to 19-year-old children for metabolic syndrome and family history of diabetes could identify children at increased risk of adult metabolic syndrome and T2DM, allowing prospective primary prevention of these outcomes.
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                Author and article information

                Journal
                J Health Popul Nutr
                J Health Popul Nutr
                JHPN
                Journal of Health, Population, and Nutrition
                International Centre for Diarrhoeal Disease Research, Bangladesh
                1606-0997
                2072-1315
                September 2014
                : 32
                : 3
                : 411-419
                Affiliations
                [1] 1Adolescent Sector, Department of Pediatrics, Universidade Federal de São Paulo, São Paulo, SP, Brazil
                [2] 2Department of Nutrition, School of Nursing, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil
                [3] 3Statistics Division, Universidade Estadual de Campinas, Brazil
                Author notes
                Correspondence and reprint requests: Dr. Isa de Pádua Cintra, Centro de Atendimento e Apoio ao Adolescente, Rua Botucatu, 715–Vila Clementino–04023 062, São Paulo/SP, Brazil, Email: ipcintra@ 123456uol.com.br , Fax: (55) (11) 5576-4360
                Article
                jhpn0032-0411
                4221447
                5a76ea0e-938d-4550-b480-558d69cd9005
                © INTERNATIONAL CENTRE FOR DIARRHOEAL DISEASE RESEARCH, BANGLADESH

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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                Original Papers

                Nutrition & Dietetics
                adolescents,central adiposity,obesity,waist-to-height ratio,brazil
                Nutrition & Dietetics
                adolescents, central adiposity, obesity, waist-to-height ratio, brazil

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