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Renata Bertazzi Levy - One of the best experts on this subject based on the ideXlab platform.
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Ultra-Processed Food consumption and obesity in the Australian adult population.
Nutrition & diabetes, 2020Co-Authors: Priscila Pereira Machado, Timothy Gill, Euridice Martinez Steele, Anna Rangan, Julie Woods, Gyorgy Scrinis, Renata Bertazzi Levy, Maria Laura Da Costa-louzada, Carlos Augusto MonteiroAbstract: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.
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Ultra-Processed Food consumption and risk of obesity: a prospective cohort study of UK Biobank
European Journal of Nutrition, 2020Co-Authors: Fernanda Rauber, Maria Laura Da Costa-louzada, Carlos Augusto Monteiro, Kiara Chang, Eszter P. Vamos, Christopher Millett, Renata Bertazzi LevyAbstract:Objective The objective of this study was to examine the associations between ultra-Processed Food consumption and risk of obesity among UK adults. Methods Participants aged 40–69 years at recruitment in the UK Biobank (2006–2019) with dietary intakes collected using 24-h recall and repeated measures of adiposity––body mass index (BMI), waist circumference (WC) and percentage of body fat (% BF)––were included ( N = 22,659; median follow-up: 5 years). Ultra-Processed Foods were identified using the NOVA classification and their consumption was expressed as a percentage of total energy intake. Multivariable Cox proportional hazards regression models were used to estimate hazard ratios (HR) of several indicators of obesity according to ultra-Processed Food consumption. Models were adjusted for sociodemographic and lifestyle characteristics. Results 947 incident cases of overall obesity (BMI ≥ 30 kg/m^2) and 1900 incident cases of abdominal obesity (men: WC ≥ 102 cm, women: WC ≥ 88 cm) were identified during follow-up. Participants in the highest quartile of ultra-Processed Food consumption had significantly higher risk of developing overall obesity (HR 1.79; 95% CI 1.06─3.03) and abdominal obesity (HR 1.30; 95% CI 1.14─1.48). They had higher risk of experiencing a ≥ 5% increase in BMI (HR 1.31; 95% CI 1.20─1.43), WC (HR 1.35; 95% CI 1.25─1.45) and %BF (HR 1.14; 95% CI 1.03─1.25), than those in the lowest quartile of consumption. Conclusions Our findings provide evidence that higher consumption of ultra-Processed Food is strongly associated with a higher risk of multiple indicators of obesity in the UK adult population. Policy makers should consider actions that promote consumption of fresh or minimally Processed Foods and reduce consumption of ultra-Processed Foods.
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Eating context and its association with ultra-Processed Food consumption by British children
Appetite, 2020Co-Authors: Bianca M. Onita, Renata Bertazzi Levy, Catarina Machado Azeredo, Patrícia Constante Jaime, Fernanda RauberAbstract:Abstract This study aimed to investigate the patterns of eating context and its association with ultra-Processed Food consumption by British children. This cross-sectional study was conducted with a representative sample of UK children aged 4–10 years old (n = 1772) from the National Diet and Nutrition Survey 2008/2014. Data on Food consumption, meal context and ultra-Processed Food consumption were assessed through a four-day Food diary. Exploratory factor analysis was used to identify the patterns of eating context and these patterns’ association with the daily consumption of ultra-Processed Food was verified by linear regression analyses. Ultra-Processed Foods comprised 65.4% of the total daily energy intake. At lunch, higher ultra-Processed Food consumption was associated with the patterns “Eating with family while watching TV” (64.9% in the lowest tertile to 68.1% in the highest tertile) and “Eating away from home” (65.2%–67.7%, respectively), while the eating pattern “Eating at school with friends” was associated with lower ultra-Processed Food consumption (66.6%–64.7%, respectively). At dinner, higher ultra-Processed Food consumption was associated with the patterns “Eating with family while watching TV” (64.6%–67.1%, respectively) and “Eating alone in the bedroom” (63.9%–66.5%, respectively). Eating alone, eating whilst watching TV, and eating away from home stood out as patterns of eating context associated with the increased consumption of ultra-Processed Food.
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ultra Processed Food consumption and indicators of obesity in the united kingdom population 2008 2016
PLOS ONE, 2020Co-Authors: Fernanda Rauber, Euridice Martinez Steele, Maria Laura Da Costa-louzada, Carlos Augusto Monteiro, Christopher Millett, Renata Bertazzi LevyAbstract:We examined the association between the consumption of ultra-Processed Foods and adiposity in a nationally representative sample of the UK adult population. We studied 6,143 participants (19 to 96 years, 51.6% female) sampled by the UK National Diet and Nutrition Survey (2008-16). Food items reported in four-day Food diary were classified according to the NOVA system. Multiple linear and logistic regressions were used to evaluate associations between the dietary contribution of ultra-Processed Foods (sex-specific quartile and continuous) and Body Mass Index (BMI), Waist Circumference (WC) and obesity (BMI>30kg/m2) and abdominal obesity (men: WC≥102cm, women: WC≥88cm) status. Models were adjusted for sociodemographic and lifestyle characteristics. In multivariable analyses, the highest consumption of ultra-Processed Food was associated with 1.66 kg/m2 higher BMI (95%CI 0.96-2.36), 3.56 cm greater WC (95%CI 1.79-5.33) and 90% higher odds for being obese (OR = 1.90, 95%CI 1.39-2.61), compared with the lowest consumption. A 10% increase in the consumption of ultra-Processed Foods was associated with an increase of 0.38 kg/m2 in BMI (95%CI 0.20-0.55), 0.87 cm in WC (95%CI 0.40-1.33) and 18% higher odds of being obese (OR = 1.18, 95%CI 1.08-1.28). The consumption of ultra-Processed Food was associated with an increase in BMI, WC and prevalence of obesity in both sexes. A dose response relationship was observed in both sexes, with a 10% increase in the consumption of ultra-Processed Foods being associated with a 18% increase in the prevalence of obesity in men and a 17% increase in women. Higher consumption of ultra-Processed Food is associated with greater adiposity in the UK adult population. Policy makers should consider actions that promote consumption of unProcessed or minimally Processed Foods and reduce consumption of ultra-Processed Foods.
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Ultra-Processed Food consumption drives excessive free sugar intake among all age groups in Australia
European Journal of Nutrition, 2019Co-Authors: Priscila Pereira Machado, Timothy Gill, Euridice Martinez Steele, Anna Rangan, Maria Laura Da Costa Louzada, Julie Woods, Renata Bertazzi Levy, Gyorgy ScrinisAbstract:ObjectiveTo analyze the contribution of ultra-Processed Foods to the intake of free sugars among different age groups in Australia.MethodsDietary intakes of 12,153 participants from the National Nutrition and Physical Activity Survey (2011–12) aged 2+ years were evaluated. Food items collected through two 24-h recalls were classified according to the NOVA system. The contribution of each NOVA Food group and their subgroups to total energy intake was determined by age group. Mean free sugar content in diet fractions made up exclusively of ultra-Processed Foods, or of Processed Foods, or of a combination of un/minimally Processed Foods and culinary ingredients (which includes table sugar and honey) were compared. Across quintiles of the energy contribution of ultra-Processed Foods, differences in the intake of free sugars, as well as in the prevalence of excessive free sugar intake (≥ 10% of total energy) were examined.ResultsUltra-Processed Foods had the highest energy contribution among children, adolescents and adults in Australia, with older children and adolescents the highest consumers (53.1% and 54.3% of total energy, respectively). The diet fraction restricted to ultra-Processed items contained significantly more free sugars than the two other diet fractions. Among all age groups, a positive and statistically significant linear association was found between quintiles of ultra-Processed Food consumption and both the average intake of free sugars and the prevalence of excessive free sugar intake.ConclusionUltra-Processed Food consumption drives excessive free sugar intake among all age groups in Australia.
Carlos Augusto Monteiro - One of the best experts on this subject based on the ideXlab platform.
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Ultra-Processed Food consumption and obesity in the Australian adult population.
Nutrition & diabetes, 2020Co-Authors: Priscila Pereira Machado, Timothy Gill, Euridice Martinez Steele, Anna Rangan, Julie Woods, Gyorgy Scrinis, Renata Bertazzi Levy, Maria Laura Da Costa-louzada, Carlos Augusto MonteiroAbstract: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.
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Ultra-Processed Food consumption and risk of obesity: a prospective cohort study of UK Biobank
European Journal of Nutrition, 2020Co-Authors: Fernanda Rauber, Maria Laura Da Costa-louzada, Carlos Augusto Monteiro, Kiara Chang, Eszter P. Vamos, Christopher Millett, Renata Bertazzi LevyAbstract:Objective The objective of this study was to examine the associations between ultra-Processed Food consumption and risk of obesity among UK adults. Methods Participants aged 40–69 years at recruitment in the UK Biobank (2006–2019) with dietary intakes collected using 24-h recall and repeated measures of adiposity––body mass index (BMI), waist circumference (WC) and percentage of body fat (% BF)––were included ( N = 22,659; median follow-up: 5 years). Ultra-Processed Foods were identified using the NOVA classification and their consumption was expressed as a percentage of total energy intake. Multivariable Cox proportional hazards regression models were used to estimate hazard ratios (HR) of several indicators of obesity according to ultra-Processed Food consumption. Models were adjusted for sociodemographic and lifestyle characteristics. Results 947 incident cases of overall obesity (BMI ≥ 30 kg/m^2) and 1900 incident cases of abdominal obesity (men: WC ≥ 102 cm, women: WC ≥ 88 cm) were identified during follow-up. Participants in the highest quartile of ultra-Processed Food consumption had significantly higher risk of developing overall obesity (HR 1.79; 95% CI 1.06─3.03) and abdominal obesity (HR 1.30; 95% CI 1.14─1.48). They had higher risk of experiencing a ≥ 5% increase in BMI (HR 1.31; 95% CI 1.20─1.43), WC (HR 1.35; 95% CI 1.25─1.45) and %BF (HR 1.14; 95% CI 1.03─1.25), than those in the lowest quartile of consumption. Conclusions Our findings provide evidence that higher consumption of ultra-Processed Food is strongly associated with a higher risk of multiple indicators of obesity in the UK adult population. Policy makers should consider actions that promote consumption of fresh or minimally Processed Foods and reduce consumption of ultra-Processed Foods.
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ultra Processed Food consumption and indicators of obesity in the united kingdom population 2008 2016
PLOS ONE, 2020Co-Authors: Fernanda Rauber, Euridice Martinez Steele, Maria Laura Da Costa-louzada, Carlos Augusto Monteiro, Christopher Millett, Renata Bertazzi LevyAbstract:We examined the association between the consumption of ultra-Processed Foods and adiposity in a nationally representative sample of the UK adult population. We studied 6,143 participants (19 to 96 years, 51.6% female) sampled by the UK National Diet and Nutrition Survey (2008-16). Food items reported in four-day Food diary were classified according to the NOVA system. Multiple linear and logistic regressions were used to evaluate associations between the dietary contribution of ultra-Processed Foods (sex-specific quartile and continuous) and Body Mass Index (BMI), Waist Circumference (WC) and obesity (BMI>30kg/m2) and abdominal obesity (men: WC≥102cm, women: WC≥88cm) status. Models were adjusted for sociodemographic and lifestyle characteristics. In multivariable analyses, the highest consumption of ultra-Processed Food was associated with 1.66 kg/m2 higher BMI (95%CI 0.96-2.36), 3.56 cm greater WC (95%CI 1.79-5.33) and 90% higher odds for being obese (OR = 1.90, 95%CI 1.39-2.61), compared with the lowest consumption. A 10% increase in the consumption of ultra-Processed Foods was associated with an increase of 0.38 kg/m2 in BMI (95%CI 0.20-0.55), 0.87 cm in WC (95%CI 0.40-1.33) and 18% higher odds of being obese (OR = 1.18, 95%CI 1.08-1.28). The consumption of ultra-Processed Food was associated with an increase in BMI, WC and prevalence of obesity in both sexes. A dose response relationship was observed in both sexes, with a 10% increase in the consumption of ultra-Processed Foods being associated with a 18% increase in the prevalence of obesity in men and a 17% increase in women. Higher consumption of ultra-Processed Food is associated with greater adiposity in the UK adult population. Policy makers should consider actions that promote consumption of unProcessed or minimally Processed Foods and reduce consumption of ultra-Processed Foods.
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Association between ultra-Processed Food consumption and the nutrient profile of the Colombian diet in 2005
Salud Publica De Mexico, 2019Co-Authors: Diana C. Parra, Maria Laura Da Costa-louzada, Jean-claude Moubarac, Renata Bertazzi-levy, Neha Khandpur, Gustavo Cediel, Carlos Augusto MonteiroAbstract:Abstract: Objective: To evaluate the consumption of ultra-Processed Food and drink products and its association with the nutrient profile of the Colombian diet in 2005. Materials and methods: Food consumption based on 24-hour dietary records from 38 643 men and women was classified into four NOVA groups according to the extent and purpose of Food processing. Results: Ultra-Processed Food and drink products represented 15.9% of the total energy daily intake, compared to 63.3% from minimally Processed Food, 15.8% from Processed culinary ingredients, and 4.9% from Processed Food. Non-ultra-Processed Food items had a healthier nutritional profile compared to ultra-Processed items in terms of contribution to total calories from protein, carbohydrates, total fat, saturated fat, free sugar, fiber and energy density. Conclusions: Ultra-Processed Food products have a less healthy nutrient profile than non-ultra-Processed ones. An increase in the consumption of these Foods must be prevented within Colombia.
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ultra Processed Food consumption and excess weight among us adults
British Journal of Nutrition, 2018Co-Authors: Filippa Juul, Carlos Augusto Monteiro, Euridice Martinezsteele, Niyati Parekh, Virginia W ChangAbstract:Ultra-Processed Foods provide 58 % of energy intake and 89 % of added sugars in the American diet. Nevertheless, the association between ultra-Processed Foods and excess weight has not been investigated in a US sample. The present investigation therefore aims to examine the association between ultra-Processed Foods and excess weight in a nationally representative sample of US adults. We performed a cross-sectional analysis of anthropometric and dietary data from 15 977 adults (20-64 years) participating in the National Health and Nutrition Examination Survey 2005-2014. Dietary data were collected by 24-h recall. Height, weight and waist circumference (WC) were measured. Foods were classified as ultra-Processed/non-ultra-Processed according to the NOVA classification. Multivariable linear and logistic regression was used to evaluate the association between ultra-Processed Food consumption (% energy) and BMI, WC and odds of BMI≥25 kg/m2, BMI≥30 kg/m2 and abdominal obesity (men: WC≥102 cm, women: WC≥88 cm). Prevalence of BMI≥25 kg/m2, BMI≥30 kg/m2 and abdominal obesity was 69·2, 36·1 and 53·0 %, respectively. Consuming ≥74·2 v. ≤36·5 % of total energy from ultra-Processed Foods was associated with 1·61 units higher BMI (95 % CI 1·11, 2·10), 4·07 cm greater WC (95 % CI 2·94, 5·19) and 48, 53 and 62 % higher odds of BMI≥25 kg/m2, BMI≥30 kg/m2 and abdominal obesity, respectively (OR 1·48; 95 % CI 1·25, 1·76; OR 1·53; 95 % CI 1·29, 1·81; OR 1·62; 95 % CI 1·39, 1·89, respectively; P for trend<0·001 for all). A significant interaction between being female and ultra-Processed Food consumption was found for BMI (F 4,79=4·89, P=0·002), WC (F 4,79=3·71, P=0·008) and BMI≥25 kg/m2 (F 4,79=5·35, P<0·001). As the first study in a US population, our findings support that higher consumption of ultra-Processed Food is associated with excess weight, and that the association is more pronounced among women.
Fernanda Rauber - One of the best experts on this subject based on the ideXlab platform.
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Ultra-Processed Food consumption and risk of obesity: a prospective cohort study of UK Biobank
European Journal of Nutrition, 2020Co-Authors: Fernanda Rauber, Maria Laura Da Costa-louzada, Carlos Augusto Monteiro, Kiara Chang, Eszter P. Vamos, Christopher Millett, Renata Bertazzi LevyAbstract:Objective The objective of this study was to examine the associations between ultra-Processed Food consumption and risk of obesity among UK adults. Methods Participants aged 40–69 years at recruitment in the UK Biobank (2006–2019) with dietary intakes collected using 24-h recall and repeated measures of adiposity––body mass index (BMI), waist circumference (WC) and percentage of body fat (% BF)––were included ( N = 22,659; median follow-up: 5 years). Ultra-Processed Foods were identified using the NOVA classification and their consumption was expressed as a percentage of total energy intake. Multivariable Cox proportional hazards regression models were used to estimate hazard ratios (HR) of several indicators of obesity according to ultra-Processed Food consumption. Models were adjusted for sociodemographic and lifestyle characteristics. Results 947 incident cases of overall obesity (BMI ≥ 30 kg/m^2) and 1900 incident cases of abdominal obesity (men: WC ≥ 102 cm, women: WC ≥ 88 cm) were identified during follow-up. Participants in the highest quartile of ultra-Processed Food consumption had significantly higher risk of developing overall obesity (HR 1.79; 95% CI 1.06─3.03) and abdominal obesity (HR 1.30; 95% CI 1.14─1.48). They had higher risk of experiencing a ≥ 5% increase in BMI (HR 1.31; 95% CI 1.20─1.43), WC (HR 1.35; 95% CI 1.25─1.45) and %BF (HR 1.14; 95% CI 1.03─1.25), than those in the lowest quartile of consumption. Conclusions Our findings provide evidence that higher consumption of ultra-Processed Food is strongly associated with a higher risk of multiple indicators of obesity in the UK adult population. Policy makers should consider actions that promote consumption of fresh or minimally Processed Foods and reduce consumption of ultra-Processed Foods.
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Eating context and its association with ultra-Processed Food consumption by British children
Appetite, 2020Co-Authors: Bianca M. Onita, Renata Bertazzi Levy, Catarina Machado Azeredo, Patrícia Constante Jaime, Fernanda RauberAbstract:Abstract This study aimed to investigate the patterns of eating context and its association with ultra-Processed Food consumption by British children. This cross-sectional study was conducted with a representative sample of UK children aged 4–10 years old (n = 1772) from the National Diet and Nutrition Survey 2008/2014. Data on Food consumption, meal context and ultra-Processed Food consumption were assessed through a four-day Food diary. Exploratory factor analysis was used to identify the patterns of eating context and these patterns’ association with the daily consumption of ultra-Processed Food was verified by linear regression analyses. Ultra-Processed Foods comprised 65.4% of the total daily energy intake. At lunch, higher ultra-Processed Food consumption was associated with the patterns “Eating with family while watching TV” (64.9% in the lowest tertile to 68.1% in the highest tertile) and “Eating away from home” (65.2%–67.7%, respectively), while the eating pattern “Eating at school with friends” was associated with lower ultra-Processed Food consumption (66.6%–64.7%, respectively). At dinner, higher ultra-Processed Food consumption was associated with the patterns “Eating with family while watching TV” (64.6%–67.1%, respectively) and “Eating alone in the bedroom” (63.9%–66.5%, respectively). Eating alone, eating whilst watching TV, and eating away from home stood out as patterns of eating context associated with the increased consumption of ultra-Processed Food.
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ultra Processed Food consumption and indicators of obesity in the united kingdom population 2008 2016
PLOS ONE, 2020Co-Authors: Fernanda Rauber, Euridice Martinez Steele, Maria Laura Da Costa-louzada, Carlos Augusto Monteiro, Christopher Millett, Renata Bertazzi LevyAbstract:We examined the association between the consumption of ultra-Processed Foods and adiposity in a nationally representative sample of the UK adult population. We studied 6,143 participants (19 to 96 years, 51.6% female) sampled by the UK National Diet and Nutrition Survey (2008-16). Food items reported in four-day Food diary were classified according to the NOVA system. Multiple linear and logistic regressions were used to evaluate associations between the dietary contribution of ultra-Processed Foods (sex-specific quartile and continuous) and Body Mass Index (BMI), Waist Circumference (WC) and obesity (BMI>30kg/m2) and abdominal obesity (men: WC≥102cm, women: WC≥88cm) status. Models were adjusted for sociodemographic and lifestyle characteristics. In multivariable analyses, the highest consumption of ultra-Processed Food was associated with 1.66 kg/m2 higher BMI (95%CI 0.96-2.36), 3.56 cm greater WC (95%CI 1.79-5.33) and 90% higher odds for being obese (OR = 1.90, 95%CI 1.39-2.61), compared with the lowest consumption. A 10% increase in the consumption of ultra-Processed Foods was associated with an increase of 0.38 kg/m2 in BMI (95%CI 0.20-0.55), 0.87 cm in WC (95%CI 0.40-1.33) and 18% higher odds of being obese (OR = 1.18, 95%CI 1.08-1.28). The consumption of ultra-Processed Food was associated with an increase in BMI, WC and prevalence of obesity in both sexes. A dose response relationship was observed in both sexes, with a 10% increase in the consumption of ultra-Processed Foods being associated with a 18% increase in the prevalence of obesity in men and a 17% increase in women. Higher consumption of ultra-Processed Food is associated with greater adiposity in the UK adult population. Policy makers should consider actions that promote consumption of unProcessed or minimally Processed Foods and reduce consumption of ultra-Processed Foods.
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ultra Processed Food consumption and its effects on anthropometric and glucose profile a longitudinal study during childhood
Nutrition Metabolism and Cardiovascular Diseases, 2019Co-Authors: C S Costa, Fernanda Rauber, Paula Dos Santos Leffa, Caroline Nicola Sangalli, Paula Dal Bo Campagnolo, Marcia Regina VitoloAbstract:Abstract Background and aims Obesity and insulin resistance development are related to known risk factors (such as diet) that begin in childhood. Among dietary factors, the consumption of ultra-Processed Foods has received attention. The present study investigated the association between ultra-Processed Foods consumption at preschool age and changes in anthropometric measurements from preschool to school age and glucose profile at school age. Methods and results The present study was a follow-up of a randomized controlled trial, conducted with 307 children of low socioeconomic status from Sao Leopoldo, Brazil. At ages 4 and 8 years, children's anthropometric assessments were collected from preschool to school age including body-mass index (BMI) for-age, waist circumference (WC), waist-to-height ratio (WHtR) and skinfold. At the age 8 years, blood tests were performed to measure glucose profile. Dietary data were collected through 24-h recalls and the children's ultra-Processed Food intake was assessed. Linear regression analysis was used to assess the relationship between ultra-Processed Food consumption and the outcomes. The percentage of daily energy provided by ultra-Processed Foods was 41.8 ± 8.7 (753.8 ± 191.0 kcal) at preschool age and 47.8 ± 8.9 (753.8 ± 191.0 kcal) at school age, on average. The adjusted linear regression analyses showed that ultra-Processed Food consumption at preschool age was a predictor of an increase in delta WC from preschool to school age (β = 0.07; 95%CI 0.01–0.14; P = 0.030), but not for glucose metabolism. Conclusion Our data suggest that early ultra-Processed Food consumption played a role in increasing abdominal obesity in children. These results reinforce the importance of effective strategies to prevent the excessive consumption of ultra-Processed Foods, especially in early ages.
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ultra Processed Food consumption and chronic non communicable diseases related dietary nutrient profile in the uk 2008 2014
Nutrients, 2018Co-Authors: Fernanda Rauber, Euridice Martinez Steele, Maria Laura Da Costa-louzada, Carlos Augusto Monteiro, Christopher Millett, Renata Bertazzi LevyAbstract:We described the contribution of ultra-Processed Foods in the U.K. diet and its association with the overall dietary content of nutrients known to affect the risk of chronic non-communicable diseases (NCDs). Cross-sectional data from the U.K. National Diet and Nutrition Survey (2008–2014) were analysed. Food items collected using a four-day Food diary were classified according to the NOVA system. The average energy intake was 1764 kcal/day, with 30.1% of calories coming from unProcessed or minimally Processed Foods, 4.2% from culinary ingredients, 8.8% from Processed Foods, and 56.8% from ultra-Processed Foods. As the ultra-Processed Food consumption increased, the dietary content of carbohydrates, free sugars, total fats, saturated fats, and sodium increased significantly while the content of protein, fibre, and potassium decreased. Increased ultra-Processed Food consumption had a remarkable effect on average content of free sugars, which increased from 9.9% to 15.4% of total energy from the first to the last quintile. The prevalence of people exceeding the upper limits recommended for free sugars and sodium increased by 85% and 55%, respectively, from the lowest to the highest ultra-Processed Food quintile. Decreasing the dietary share of ultra-Processed Foods may substantially improve the nutritional quality of diets and contribute to the prevention of diet-related NCDs.
Maria Laura Da Costa-louzada - One of the best experts on this subject based on the ideXlab platform.
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Ultra-Processed Food consumption and obesity in the Australian adult population.
Nutrition & diabetes, 2020Co-Authors: Priscila Pereira Machado, Timothy Gill, Euridice Martinez Steele, Anna Rangan, Julie Woods, Gyorgy Scrinis, Renata Bertazzi Levy, Maria Laura Da Costa-louzada, Carlos Augusto MonteiroAbstract: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.
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Ultra-Processed Food consumption and risk of obesity: a prospective cohort study of UK Biobank
European Journal of Nutrition, 2020Co-Authors: Fernanda Rauber, Maria Laura Da Costa-louzada, Carlos Augusto Monteiro, Kiara Chang, Eszter P. Vamos, Christopher Millett, Renata Bertazzi LevyAbstract:Objective The objective of this study was to examine the associations between ultra-Processed Food consumption and risk of obesity among UK adults. Methods Participants aged 40–69 years at recruitment in the UK Biobank (2006–2019) with dietary intakes collected using 24-h recall and repeated measures of adiposity––body mass index (BMI), waist circumference (WC) and percentage of body fat (% BF)––were included ( N = 22,659; median follow-up: 5 years). Ultra-Processed Foods were identified using the NOVA classification and their consumption was expressed as a percentage of total energy intake. Multivariable Cox proportional hazards regression models were used to estimate hazard ratios (HR) of several indicators of obesity according to ultra-Processed Food consumption. Models were adjusted for sociodemographic and lifestyle characteristics. Results 947 incident cases of overall obesity (BMI ≥ 30 kg/m^2) and 1900 incident cases of abdominal obesity (men: WC ≥ 102 cm, women: WC ≥ 88 cm) were identified during follow-up. Participants in the highest quartile of ultra-Processed Food consumption had significantly higher risk of developing overall obesity (HR 1.79; 95% CI 1.06─3.03) and abdominal obesity (HR 1.30; 95% CI 1.14─1.48). They had higher risk of experiencing a ≥ 5% increase in BMI (HR 1.31; 95% CI 1.20─1.43), WC (HR 1.35; 95% CI 1.25─1.45) and %BF (HR 1.14; 95% CI 1.03─1.25), than those in the lowest quartile of consumption. Conclusions Our findings provide evidence that higher consumption of ultra-Processed Food is strongly associated with a higher risk of multiple indicators of obesity in the UK adult population. Policy makers should consider actions that promote consumption of fresh or minimally Processed Foods and reduce consumption of ultra-Processed Foods.
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ultra Processed Food consumption and indicators of obesity in the united kingdom population 2008 2016
PLOS ONE, 2020Co-Authors: Fernanda Rauber, Euridice Martinez Steele, Maria Laura Da Costa-louzada, Carlos Augusto Monteiro, Christopher Millett, Renata Bertazzi LevyAbstract:We examined the association between the consumption of ultra-Processed Foods and adiposity in a nationally representative sample of the UK adult population. We studied 6,143 participants (19 to 96 years, 51.6% female) sampled by the UK National Diet and Nutrition Survey (2008-16). Food items reported in four-day Food diary were classified according to the NOVA system. Multiple linear and logistic regressions were used to evaluate associations between the dietary contribution of ultra-Processed Foods (sex-specific quartile and continuous) and Body Mass Index (BMI), Waist Circumference (WC) and obesity (BMI>30kg/m2) and abdominal obesity (men: WC≥102cm, women: WC≥88cm) status. Models were adjusted for sociodemographic and lifestyle characteristics. In multivariable analyses, the highest consumption of ultra-Processed Food was associated with 1.66 kg/m2 higher BMI (95%CI 0.96-2.36), 3.56 cm greater WC (95%CI 1.79-5.33) and 90% higher odds for being obese (OR = 1.90, 95%CI 1.39-2.61), compared with the lowest consumption. A 10% increase in the consumption of ultra-Processed Foods was associated with an increase of 0.38 kg/m2 in BMI (95%CI 0.20-0.55), 0.87 cm in WC (95%CI 0.40-1.33) and 18% higher odds of being obese (OR = 1.18, 95%CI 1.08-1.28). The consumption of ultra-Processed Food was associated with an increase in BMI, WC and prevalence of obesity in both sexes. A dose response relationship was observed in both sexes, with a 10% increase in the consumption of ultra-Processed Foods being associated with a 18% increase in the prevalence of obesity in men and a 17% increase in women. Higher consumption of ultra-Processed Food is associated with greater adiposity in the UK adult population. Policy makers should consider actions that promote consumption of unProcessed or minimally Processed Foods and reduce consumption of ultra-Processed Foods.
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Association between ultra-Processed Food consumption and the nutrient profile of the Colombian diet in 2005
Salud Publica De Mexico, 2019Co-Authors: Diana C. Parra, Maria Laura Da Costa-louzada, Jean-claude Moubarac, Renata Bertazzi-levy, Neha Khandpur, Gustavo Cediel, Carlos Augusto MonteiroAbstract:Abstract: Objective: To evaluate the consumption of ultra-Processed Food and drink products and its association with the nutrient profile of the Colombian diet in 2005. Materials and methods: Food consumption based on 24-hour dietary records from 38 643 men and women was classified into four NOVA groups according to the extent and purpose of Food processing. Results: Ultra-Processed Food and drink products represented 15.9% of the total energy daily intake, compared to 63.3% from minimally Processed Food, 15.8% from Processed culinary ingredients, and 4.9% from Processed Food. Non-ultra-Processed Food items had a healthier nutritional profile compared to ultra-Processed items in terms of contribution to total calories from protein, carbohydrates, total fat, saturated fat, free sugar, fiber and energy density. Conclusions: Ultra-Processed Food products have a less healthy nutrient profile than non-ultra-Processed ones. An increase in the consumption of these Foods must be prevented within Colombia.
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ultra Processed Food consumption and chronic non communicable diseases related dietary nutrient profile in the uk 2008 2014
Nutrients, 2018Co-Authors: Fernanda Rauber, Euridice Martinez Steele, Maria Laura Da Costa-louzada, Carlos Augusto Monteiro, Christopher Millett, Renata Bertazzi LevyAbstract:We described the contribution of ultra-Processed Foods in the U.K. diet and its association with the overall dietary content of nutrients known to affect the risk of chronic non-communicable diseases (NCDs). Cross-sectional data from the U.K. National Diet and Nutrition Survey (2008–2014) were analysed. Food items collected using a four-day Food diary were classified according to the NOVA system. The average energy intake was 1764 kcal/day, with 30.1% of calories coming from unProcessed or minimally Processed Foods, 4.2% from culinary ingredients, 8.8% from Processed Foods, and 56.8% from ultra-Processed Foods. As the ultra-Processed Food consumption increased, the dietary content of carbohydrates, free sugars, total fats, saturated fats, and sodium increased significantly while the content of protein, fibre, and potassium decreased. Increased ultra-Processed Food consumption had a remarkable effect on average content of free sugars, which increased from 9.9% to 15.4% of total energy from the first to the last quintile. The prevalence of people exceeding the upper limits recommended for free sugars and sodium increased by 85% and 55%, respectively, from the lowest to the highest ultra-Processed Food quintile. Decreasing the dietary share of ultra-Processed Foods may substantially improve the nutritional quality of diets and contribute to the prevention of diet-related NCDs.
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what is under the hump mass spectrometry based analysis of complex mixtures in Processed Food lessons from the characterisation of black tea thearubigins coffee melanoidines and caramel
Food & Function, 2013Co-Authors: Nikolai Kuhnert, Farnoosh Dairpoosh, Ghada H. Yassin, Agnieszka Golon, Rakesh JaiswalAbstract:In this contribution we review our work on the characterisation of Processed Food. We review novel methods and analysis strategies developed to account for the composition of extraordinarily complex materials such as black tea thearubigins, coffee melanoidines and thermally treated carbohydrates. Our methods are mainly based on modern mass spectrometry and are introduced and critically discussed. A series of novel previously unpublished data interpretation strategies are presented as well. Finally an evaluation of the insight obtained in the composition of selected Processed Foods is given discussing potential consequences for assessing beneficial and adverse health effects of Processed Food.
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What is under the hump? Mass spectrometry based analysis of complex mixtures in Processed Food – lessons from the characterisation of black tea thearubigins, coffee melanoidines and caramel
Food & function, 2013Co-Authors: Nikolai Kuhnert, Farnoosh Dairpoosh, Ghada H. Yassin, Agnieszka Golon, Rakesh JaiswalAbstract:In this contribution we review our work on the characterisation of Processed Food. We review novel methods and analysis strategies developed to account for the composition of extraordinarily complex materials such as black tea thearubigins, coffee melanoidines and thermally treated carbohydrates. Our methods are mainly based on modern mass spectrometry and are introduced and critically discussed. A series of novel previously unpublished data interpretation strategies are presented as well. Finally an evaluation of the insight obtained in the composition of selected Processed Foods is given discussing potential consequences for assessing beneficial and adverse health effects of Processed Food.