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To evaluate cross-sectional and longitudinal associations of consumption of dairy products and physical activity (PA) with bone mineral density (BMD).
Cohort study with children from the 2004 Pelotas (Brazil) Birth Cohort.
Pelotas, a medium-sized Brazilian city.
The study started in 2004 and mothers/children were interviewed/measured periodically from birth to age 6 years. PA was measured by maternal proxy at 4 and 6 years and by accelerometry at 6 years. Consumption of dairy products was measured using 24 h food recall (at 4 years) and FFQ (at 6 years). Total-body and lumbar-spine BMD (g/cm2) were measured by dual-energy X-ray absorptiometry.
At 6 years, BMD was measured in 3444 children and 2636 children provided data on objectively measured PA by accelerometry. Consumption of dairy products at 4 years was associated with higher lumbar-spine BMD at 6 years in boys, while current consumption was positively associated with BMD in both sexes (P < 0·001). PA assessed by maternal report at 4 and 6 years of age was associated with higher BMD at 6 years in boys. PA assessed by accelerometry was positively related to total-body and lumbar-spine BMD in boys and lumbar-spine BMD in girls. We did not find evidence for an interaction between PA and consumption of dairy products on BMD.
We observed positive and independent longitudinal and cross-sectional associations between consumption of dairy products and PA with BMD in the total body and at the lumbar spine in young children.
The present study aimed to assess the effects of an early childhood nutrition counselling intervention on intelligence (as measured by the intelligence quotient (IQ)) at age 15–16 years.
A single-blind, cluster-randomised trial.
In 1998, in Southern Brazil, mothers of children aged 18 months or younger were enrolled in a nutrition counselling intervention (n 424). Counselling included encouragement and promotion of exclusive breast-feeding until 6 months of age and continued breast-feeding supplemented by protein-, lipid- and carbohydrate-rich foods after age 6 months up to age 2 years. The control group received routine feeding advice. In 2013, the fourth round of follow-up of these individuals, at the age of 15–16 years, was undertaken. IQ was assessed using the short form of the Wechsler Adult Intelligence Scale (WAIS-III). Mental disorders (evaluated using the Development and Well-Being Assessment (DAWBA)) and self-reported school failure, smoking and alcohol use were also investigated. Adjusted analyses were conducted using a multilevel model in accordance with the sampling process.
Adolescents, mean (sd) age of 15·4 (0·5) years (n 339).
Mean (sd) total IQ score was lower in the intervention group than the control group (93·4 (11·4) and 95·8 (11·2), respectively) but the association did not persist after adjustment. The prevalence of any mental disorders was similar between intervention and control groups (23·1 and 23·5 %, respectively). There were no differences between groups regarding school failure, smoking and alcohol use.
Nutrition counselling intervention in early childhood had no effect on intelligence measured during adolescence.
To evaluate the adequacy and accuracy of cut-off values currently recommended by the WHO for assessment of cardiovascular risk in southern Brazil.
Population-based study aimed at determining the predictive ability of waist circumference for cardiovascular risk based on the use of previous medical diagnosis for hypertension, diabetes mellitus and/or dyslipidaemia. Descriptive analysis was used for the adequacy of current cut-off values of waist circumference, receiver operating characteristic curves were constructed and the most accurate criteria according to the Youden index and points of optimal sensitivity and specificity were identified.
Pelotas, southern Brazil.
Individuals (n 2112) aged ≥20 years living in the city were selected by multistage sampling, since these individuals did not report the presence of previous myocardial infarction, angina pectoris or stroke.
The cut-off values currently recommended by WHO were more appropriate in men than women, with overestimation of cardiovascular risk in women. The area under the receiver operating characteristic curve showed moderate predictive ability of waist circumference in men (0·74, 95 % CI 0·71, 0·76) and women (0·75, 95 % CI 0·73, 0·77). The method of optimal sensitivity and specificity showed better performance in assessing the accuracy, identifying the values of 95 cm in men and 87 cm in women as the best cut-off values of waist circumference to assess cardiovascular risk.
The cut-off values currently recommended for waist circumference are not suitable for women. Longitudinal studies should be conducted to evaluate the consistency of the findings.
To investigate the association of family income at birth with BMI among young adults who have been followed since birth.
A birth cohort study.
In 1982, all children born in Pelotas, southern Brazil, were included in a perinatal survey and visited at ages 1, 2, 4, 15, 18–19 and 23 years.
Cohort members (n 4297) were traced and interviewed in 2004–2005. In all follow-ups, participants were weighed and measured, and BMI and prevalence of obesity were calculated for each age. Family income was obtained in minimum wages in 1982 and as a continuous variable, in reais, in later follow-ups. Skin colour was self-reported in 2004–2005.
Mean BMI and prevalence of obesity differed between males and females. In males, a direct relationship was found throughout life and among females this relationship was modified by age. During childhood, BMI was higher among girls from higher income groups and this association was inversed at age 23 years. At this same age, mean BMI among black women was 1·3 kg/m2 higher than among white women, even after adjustment for current family income.
The findings show in men that the relationship between income and BMI is similar to that seen in less developed areas, whereas among adult women the relationship is similar to that observed in developed countries. In addition to the effect of socio-economic status, skin colour also has an influence on the BMI of adult women.
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