Ultra-processed food consumption and obesity in the Australian adult population

Background: Rapid simultaneous increases in ultra-processed food sales and obesity prevalence have been observed worldwide, including in Australia. Consumption of ultra-processed foods by the Australian population was previously shown to be systematically associated with increased risk of intakes of nutrients outside levels recommended for the prevention of obesity. This study aims to explore the association between ultra-processed food consumption and obesity among the Australian adult population and stratifying by age group, sex and physical activity level. Methods: A cross-sectional analysis of anthropometric and dietary data from 7411 Australians aged ≥20 years from the National Nutrition and Physical Activity Survey 2011–2012 was performed. Food consumption was evaluated through 24-h recall. The NOVA system was used to identify ultra-processed foods, i.e. industrial formulations manufactured from substances derived from foods and typically added of flavours, colours and other cosmetic additives, such as soft drinks, confectionery, sweet or savoury packaged snacks, microwaveable frozen meals and fast food dishes. Measured weight, height and waist circumference (WC) data were used to calculate the body mass index (BMI) and diagnosis of obesity and abdominal obesity. Regression models were used to evaluate the association of dietary share of ultra-processed foods (quintiles) and obesity indicators, adjusting for socio-demographic variables, physical activity and smoking. Results: Significant (P-trend ≤ 0.001) direct dose–response associations between the dietary share of ultra-processed foods and indicators of obesity were found after adjustment. In the multivariable regression analysis, those in the highest quintile of ultra-processed food consumption had significantly higher BMI (0.97 kg/m2; 95% CI 0.42, 1.51) and WC (1.92 cm; 95% CI 0.57, 3.27) and higher odds of having obesity (OR = 1.61; 95% CI 1.27, 2.04) and abdominal obesity (OR = 1.38; 95% CI 1.10, 1.72) compared with those in the lowest quintile of consumption. Subgroup analyses showed that the trend towards positive associations for all obesity indicators remained in all age groups, sex and physical activity level. Conclusion: The findings add to the growing evidence that ultra-processed food consumption is associated with obesity and support the potential role of ultra-processed foods in contributing to obesity in Australia

Rationale, design, and analysis of combined Brazilian household budget survey and food intake individual data

<p>Abstract</p> <p>Background</p> <p>Data on food intake at the individual level and its statistical distribution in population groups defined by age, gender, or geographic areas are important in planning public health and nutrition programs. However, individual-based surveys in representative population samples are expensive to perform.</p> <p>Methods/Design</p> <p>In Brazil, an individual based survey is under consideration to be conducted alongside the household budget survey (HBS), which will be carried out in 2008–2009. This paper presents the methodological framework of dietary data collection and indicates the directions to combining both sources of data.</p> <p>The 2008–2009 Brazilian HBS sample will include 60,000 households. Of the selected HBS households, 30% will be randomly sampled to gather data on individual food intake. Therefore, individual dietary intake data is expected to be gathered for 70,000 individuals. Data collection procedures will comprise: completion of a diary with information regarding food purchases during a seven-day period; registration of all items consumed during two non-consecutive days for all 10 year-old or older members of the household. The sample will be large enough to capture the variation between individuals, and the two records will assure the estimation of the variation within individuals for food groups, energy and nutrients. Data on individual dietary intake and food family budget will be stratified by the five regions of the country and by rural or urban. A pilot study has been conducted in two states, and it indicated that combining individual and budgetary data in a survey is feasible.</p> <p>Discussion</p> <p>This kind of study will allow us to estimate correlations between individual intake and household purchases, overcoming the limitations of individual dietary surveys, and enhancing the HBS with information on eating out and intra-familiar distribution of food.</p

Greenhouse gas emissions, water footprint, and ecological footprint of food purchases according to their degree of processing in Brazilian metropolitan areas: a time-series study from 1987 to 2018

Copyright © 2021 The Author(s). Background The consumption of ultra-processed foods has increased worldwide and has been related to the occurrence of obesity and other non-communicable diseases. However, little is known about the environmental effects of ultra-processed foods. We aimed to assess the temporal trends in greenhouse gas emissions (GHGE), water footprint, and ecological footprint of food purchases in Brazilian metropolitan areas, and how these are affected by the amount of food processing. Methods In this time-series study, we used data from five Brazilian Household Budget Surveys (1987–88, 1995–96, 2002–03, 2008–09, 2017–18) to calculate GHGE, water footprint, and ecological footprint per 1000 kcal of food and beverages purchased. Food items were classified into NOVA food groups: unprocessed or minimally processed foods (G1); processed culinary ingredients (G2); processed foods (G3); and ultra-processed foods (G4). We calculated the proportion each NOVA food group contributes to daily kcal per person. Linear regression was performed to evaluate trends of the environmental impacts across the years. Findings Between 1987–88 and 2017–18, diet-related GHGE increased by 21% (from 1538·6 g CO2 equivalent [CO2e] per 1000 kcal [95% CI 1473·3–1604·0] to 1866·0 g CO2e per 1000 kcal [1788·0–1944·0]; ptrend<0·0001), diet-related water footprint increased by 22% (from 1447·2 L/1000 kcal [95% CI 1400·7–1493·8] to 1769·1 L/1000 kcal [1714·5–1823·7]; ptrend<0·0001), and diet-related ecological footprint increased by 17% (from 9·69 m2/1000 kcal [95% CI 9·33–10·05] to 11·36 m2/1000 kcal [10·91–11·81]; ptrend<0·0001). We found that the change in the environmental indicators over time varied between NOVA food groups. We did not find evidence of a change in the environmental indicators for G1 foods over time. GHGE from G2 foods decreased by 18% (ptrend<0·0001), whereas GHGE from G4 foods increased by 245% (ptrend<0·0001). The water footprint from G2 foods decreased by 17% (ptrend<0·0001) whereas the water footprint from G4 foods increased by 233% (ptrend<0·0001). The ecological footprint from G2 foods decreased by 13% (ptrend<0·0001), whereas the ecological footprint from G3 foods increased by 49% (ptrend<0·0001) and from G4 foods increased by 183% (ptrend<0·0001). We found no significant change in contribution by any other NOVA food groups to any of the three environmental indicators over the study period. Interpretation The environmental effects of the Brazilian diet have increased over the past three decades along with increased effects from ultra-processed foods. This means that dietary patterns in Brazil are becoming potentially more harmful to human and planetary health. Therefore, a shift in the current trend would be needed to enhance sustainable healthy food systems.Science and Technologies Facilities Council—Global Challenges Research Fund

Dietary availability patterns of the brazilian macro-regions

<p>Abstract</p> <p>Introduction</p> <p>Epidemiological studies have raised concerns about the role of dietary patterns on the risk of chronic diseases and also in the formulation of better informed nutrition policies.</p> <p>Objective</p> <p>The development of a dietary availability patterns according to geographic regions in Brazil.</p> <p>Methodology</p> <p>The 2002-2003 Brazilian Household Budget Survey was conducted in 48,470 households. Dietary availability patterns were identified by Principal Component Analysis using as a unit of analysis the survey's Primary Sampling Units (PSUs) and purchased amounts for 21 food groups. Each of the extracted dietary availability patterns was regressed on socioeconomics categories.</p> <p>Results</p> <p>There were no differences in dietary availability patterns between urban and rural areas. In all regions, a rice and beans pattern was identified. This pattern explained 15% to 28% of the variance dependent on the region of the country. In South, Southeast and Midwest regions, a mixed pattern including at least 10 food groups explaining 8% to 16% of the variance. In the North region (Amazon forest included) the first pattern was based on fish and nuts and then it was designed as regional pattern. In multiple linear regression the rice and beans pattern was associated with the presence of adolescents in the households, except for North region, whereas the presence of adolescents was associated with the Regional pattern. A mixed patterns were associated with a higher income and education (p < 0.05), except in the South region.</p> <p>Conclusion</p> <p>The rice and beans and regional dietary availability patterns, both considered healthy eating patterns are still important in the country. Brazil has taken many actions to improve nutrition as part of their public health policies, the data of the Household Budget Survey could help to recognize the different food choices in the large regions of the country.</p