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      Consumption of ultra-processed food and obesity: cross sectional results from the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) cohort (2008–2010)

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          Abstract

          Objective

          To verify if the intake of ultra-processed foods is associated with higher BMI and waist circumference (WC) among participants of the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) cohort.

          Design

          Cross-sectional analysis of the ELSA-Brasil baseline (2008–2010). Dietary information obtained through an FFQ was classified according to characteristics of food processing (NOVA) and used to estimate the percentage energy contribution from ultra-processed foods (i.e. industrial formulations, elaborated from food processing, synthetic constituents and food additives) to individuals’ total energy intake. BMI and WC and their respective cut-off points served as response variables. Associations were estimated through linear and multinomial logistic regression models, after adjusting for confounders and total energy intake.

          Setting

          Six Brazilian capital cities, 2008–2010.

          Subjects

          Active and retired civil servants, aged 35–64 years, from universities and research organizations ( n 8977).

          Results

          Ultra-processed foods accounted for 22·7 % of total energy intake. After adjustments, individuals in the fourth quartile of percentage energy contribution from ultra-processed foods presented ( β; 95 % CI) a higher BMI (0·80; CI 0·53, 1·07 kg/m 2) and WC (1·71; 1·02, 2·40 cm), and higher chances (OR; 95 % CI) of being overweight (1·31; 1·13, 1·51), obese (1·41; 1·18, 1·69) and having significantly increased WC (1·41; 1·20, 1·66), compared with those in the first quartile. All associations suggest a dose–response gradient.

          Conclusions

          Results indicate the existence of associations between greater energy contribution from ultra-processed foods and higher BMI and WC, which are independent of total energy intake. These findings corroborate public policies designed to reduce the intake of this type of food.

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          Most cited references9

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          Ultra-Processed Food Products and Obesity in Brazilian Households (2008–2009)

          Background Production and consumption of industrially processed food and drink products have risen in parallel with the global increase in overweight and obesity and related chronic non-communicable diseases. The objective of this study was to analyze the relationship between household availability of processed and ultra-processed products and the prevalence of excess weight (overweight plus obesity) and obesity in Brazil. Methods The study was based on data from the 2008–2009 Household Budget Survey involving a probabilistic sample of 55,970 Brazilian households. The units of study were household aggregates (strata), geographically and socioeconomically homogeneous. Multiple linear regression models were used to assess the relationship between the availability of processed and ultra-processed products and the average of Body Mass Index (BMI) and the percentage of individuals with excess weight and obesity in the strata, controlling for potential confounders (socio-demographic characteristics, percentage of expenditure on eating out of home, and dietary energy other than that provided by processed and ultra-processed products). Predictive values for prevalence of excess weight and obesity were estimated according to quartiles of the household availability of dietary energy from processed and ultra-processed products. Results The mean contribution of processed and ultra-processed products to total dietary energy availability ranged from 15.4% (lower quartile) to 39.4% (upper quartile). Adjusted linear regression coefficients indicated that household availability of ultra-processed products was positively associated with both the average BMI and the prevalence of excess weight and obesity, whereas processed products were not associated with these outcomes. In addition, people in the upper quartile of household consumption of ultra-processed products, compared with those in the lower quartile, were 37% more likely to be obese. Conclusion Greater household availability of ultra-processed food products in Brazil is positively and independently associated with higher prevalence of excess weight and obesity in all age groups in this cross-sectional study.
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            Food Composition of the Diet in Relation to Changes in Waist Circumference Adjusted for Body Mass Index

            Background Dietary factors such as low energy density and low glycemic index were associated with a lower gain in abdominal adiposity. A better understanding of which food groups/items contribute to these associations is necessary. Objective To ascertain the association of food groups/items consumption on prospective annual changes in “waist circumference for a given BMI” (WCBMI), a proxy for abdominal adiposity. Design We analyzed data from 48,631 men and women from 5 countries participating in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Anthropometric measurements were obtained at baseline and after a median follow-up time of 5.5 years. WCBMI was defined as the residuals of waist circumference regressed on BMI, and annual change in WCBMI (ΔWCBMI, cm/y) was defined as the difference between residuals at follow-up and baseline, divided by follow-up time. The association between food groups/items and ΔWCBMI was modelled using centre-specific adjusted linear regression, and random-effects meta-analyses to obtain pooled estimates. Results Higher fruit and dairy products consumption was associated with a lower gain in WCBMI whereas the consumption of white bread, processed meat, margarine, and soft drinks was positively associated with ΔWCBMI. When these six food groups/items were analyzed in combination using a summary score, those in the highest quartile of the score – indicating a more favourable dietary pattern –showed a ΔWCBMI of −0.11 (95% CI −0.09 to −0.14) cm/y compared to those in the lowest quartile. Conclusion A dietary pattern high in fruit and dairy and low in white bread, processed meat, margarine, and soft drinks may help to prevent abdominal fat accumulation.
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              Association of dietary patterns with BMI and waist circumference in a low-income neighbourhood in Brazil.

              Traditional analysis of food intake usually fails to show an association between energy and nutrient intake and indicators of obesity. The analysis of food patterns can contribute to the understanding of the association between eating habits and anthropometric indicators. A population-based cross-sectional study was carried out on a low-income neighbourhood in the Rio de Janeiro metropolitan area, and 1009 subjects between 20 and 65 years of age completed an FFQ. Dietary patterns were identified by means of factor analysis, and their associations with BMI and waist circumference (WC) were ascertained by applying a linear regression analysis. Three main dietary patterns were identified: a mixed pattern, which included cereals, fish and shrimp, vegetables, roots, fruits, eggs, meat and caffeinated beverages; a Western pattern, which consisted of 'fast foods', soft drinks, juices, cakes, cookies, milk and dairy, sweets and snacks; a traditional pattern, which included rice, beans, bread, sugar, fats and salad dressings. After adjusting for age and energy intake, we found that the traditional dietary pattern was inversely associated with BMI (beta = - 1.14, P < 0.001) and WC (beta = - 14.9, P = 0.002) among females. Additionally, a positive association between the Western pattern and WC (beta = 12.8, P = 0.02) was observed for females. A diet based on rice and beans may have a protective role against weight gain in women.
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                Author and article information

                Journal
                applab
                Public Health Nutrition
                Public Health Nutr.
                Cambridge University Press (CUP)
                1368-9800
                1475-2727
                April 12 2018
                : 1-9
                Article
                10.1017/S1368980018000861
                29642958
                67fbd306-9722-4819-86ec-86505218679a
                © 2018
                History

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