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Objective:To evaluate energetic contribution according to the degree of industrial food processing and its association with sociodemographic, anthropometric, biochemical, clinical and behavioural characteristics in adolescents.Design:Cross-sectional study (Adolescent Lifestyle Study). Food consumption was assessed using 24-h dietary recalls, with foods classified by degree of industrial progressing. The usual diet was estimated using the Multiple Source Method. In a linear regression model, the energy percentage (E %) was associated with sociodemographic, anthropometric, biochemical, clinical and behavioural characteristics, after adjustment for sex and age.Setting:Juiz de Fora, Brazil.Participants:Eight hundred and four adolescents, of both sexes, 14–19 years of age, enrolled in public schools.Results:The E % of unprocessed or minimally processed foods corresponded to 43·1 %, processed foods to 11·0 % and the ultraprocessed foods to 45·9 %. E % of unprocessed foods was associated with socio-economic stratum (adjusted β = −0·093; P = 0·032), neck circumference (adjusted β = 0·017; P = 0·049), screen time (adjusted β = −0·247; P = 0·036) and HDL-cholesterol (adjusted β = −0·156; P = 0·003). E % of ultraprocessed foods was associated with socio-economic stratum (adjusted β = 0·118; P = 0·011), screen time (adjusted β = 0·375; P = 0·003), BMI (adjusted β = −0·029; P = 0·025), neck circumference (adjusted β = −0·017; P = 0·028) and HDL-cholesterol (adjusted β = 0·150; P = 0·002).Conclusions:There was a high E % of ultraprocessed foods in the diet of the adolescents. Actions are needed to raise the awareness of adopting healthy eating habits.

BackgroundObesity is defined as an excess of total body fat and may be assessed by different methods. The objective of the present study was to establish the discriminatory power of anthropometric data in determining obesity.MethodsThe subjects comprised 685 individuals, aged 20–79 years, sampled from a population-based survey. The following indicators were used: body mass index (BMI), waist circumference (WC) and total body fat percentage estimated with both Siri's equation (%BF Siri) and foot-to-foot bioelectrical impedance analysis (%BF BIA). Sensitivity and specificity of different cut-off points for each method were determined using %BF BIA as reference.ResultsOf 685 participants, 57.6% were aged ≥ 40 years, 69.9% were women and 72.6% self-referred themselves as non-white. To classify obesity based on sex and age among women aged − 2, WC of 84.0 cm and %BF Siri of 34.0%; in those aged ≥ 40 years, the cut-off points were 28.0 kg m− 2, 90.0 cm and 37.4%, respectively. The cut-off points among men aged − 2, WC of 86.0 cm and %BF Siri of 22.5%, and in those aged ≥ 40 years, 26.3 kg m− 2, 89.0 cm and 24.5%, respectively. BMI was the method with the largest area under the curve (AUC) independent of sex and sex/age, yet no differences were observed in AUC between BMI and WC (P>0.05). Classifying according to skin colour did not change cut-off points in any indicator.ConclusionBMI and WC better discriminate obesity among women and men aged ≥ 40 years from a mixed-race population.