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      Vitamin D status is associated with cardiometabolic markers in 8–11-year-old children, independently of body fat and physical activity

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          Abstract

          Vitamin D status has been associated with cardiometabolic markers even in children, but the associations may be confounded by fat mass and physical activity behaviour. This study investigated associations between vitamin D status and cardiometabolic risk profile, as well as the impact of fat mass and physical activity in Danish 8–11-year-old children, using baseline data from 782 children participating in the Optimal well-being, development and health for Danish children through a healthy New Nordic Diet (OPUS) School Meal Study. We assessed vitamin D status as serum 25-hydroxyvitamin D (25(OH)D) and measured blood pressure, fasting plasma glucose, homoeostasis model of assessment-insulin resistance, plasma lipids, inflammatory markers, anthropometry and fat mass by dual-energy X-ray absorptiometry, and physical activity by 7 d accelerometry during August–November. Mean serum 25(OH)D was 60·8 ( sd18·7) nmol/l. Each 10 mmol/l 25(OH)D increase was associated with lower diastolic blood pressure (−0·3 mmHg, 95 % CI −0·6, −0·0) ( P=0·02), total cholesterol (−0·07 mmol/l, 95 % CI −0·10, −0·05), LDL-cholesterol (−0·05 mmol/l, 95 % CI −0·08, −0·03), TAG (−0·02 mmol/l, 95 % CI −0·03, −0·01) ( P≤0·001 for all lipids) and lower metabolic syndrome (MetS) score ( P=0·01). Adjustment for fat mass index did not change the associations, but the association with blood pressure became borderline significant after adjustment for physical activity ( P=0·06). In conclusion, vitamin D status was negatively associated with blood pressure, plasma lipids and a MetS score in Danish school children with low prevalence of vitamin D deficiency, and apart from blood pressure the associations were independent of body fat and physical activity. The potential underlying cause–effect relationship and possible long-term implications should be investigated in randomised controlled trials.

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          Most cited references43

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          Validation of a self-administered instrument to assess stage of adolescent development.

          Drawings were made from Tanner's photographs illustrating five stages of development each for male genitalia, testicular size, male pubic hair, female breasts, and female pubic hair. Forty-seven females and forty-eight males aged 12-16 years indicated on questionnaires which stage they were most like, and answered other questions related to their physical development. Afterwards they were examined by physicians who had not seen their answers. Pearson correlation coefficients were 0.6 or above for the physician's observations compared with the adolescents' answers for the drawings, with the exception of testicular size. Answers to questions concerning amount of underarm hair and general development also yielded high correlations.
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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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              Tracking of serum lipid levels, blood pressure, and body mass index from childhood to adulthood: the Cardiovascular Risk in Young Finns Study.

              To examine tracking and predictiveness of childhood lipid levels, blood pressure, and body mass index for risk profile in adulthood and the best age to measure the childhood risk factor levels. Study subjects were participants of the longitudinal Cardiovascular Risk in Young Finns Study, started in 1980 (age 3, 6, 9, 12, 15, and 18 years). A total of 2204 subjects participated to the 27-year follow-up in 2007 (age, 30 to 45 years). In both sex groups and in all age groups, childhood risk factors were significantly correlated with levels in adulthood. The correlation coefficients for cholesterol levels and body mass index were 0.43 to 0.56 (P < .0001), and for blood pressure and triglyceride levels, they were 0.21 to 0.32 (P < .0001). To recognize children with abnormal adult levels, the National Cholesterol Education Program and the National High Blood Pressure Education Program cutoff points for lipid and blood pressure values and international cutoff points for overweight and obesity were used. Age seemed to affect associations. The best sensitivity and specificity rates were observed in 12- to 18-year-old subjects. Childhood blood pressure, serum lipid levels, and body mass index correlate strongly with values measured in middle age. These associations seemed to be stronger with increased age at measurements. Copyright © 2011 Mosby, Inc. All rights reserved.
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                Author and article information

                Journal
                applab
                British Journal of Nutrition
                Br J Nutr
                Cambridge University Press (CUP)
                0007-1145
                1475-2662
                November 28 2015
                September 18 2015
                : 114
                : 10
                : 1647-1655
                Article
                10.1017/S0007114515003372
                26382732
                ddd7d26a-ae11-412c-aa99-6b4fd8dc102a
                © 2015
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