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Contribution of foods consumed away from home to energy intake in Brazilian urban areas: the 2008–9 Nationwide Dietary Survey

Published online by Cambridge University Press:  31 July 2012

Ilana Nogueira Bezerra*
Affiliation:
Department of Epidemiology, Institute of Social Medicine, State University of Rio de Janeiro, Rua São Francisco Xavier, 524, 7 ° andar, Bloco E, Cep20550-900, Rio de Janeiro, RJ, Brazil
Amanda de Moura Souza
Affiliation:
Department of Epidemiology, Institute of Social Medicine, State University of Rio de Janeiro, Rua São Francisco Xavier, 524, 7 ° andar, Bloco E, Cep20550-900, Rio de Janeiro, RJ, Brazil
Rosangela Alves Pereira
Affiliation:
Department of Nutrition, Federal University of Rio de Janeiro, Avenida Carlos Chagas Filho, 373, Edifício do Centro de Ciências da Saúde, Bloco J, 2 ° andar, Cidade Universitária, Cep21941-590, Rio de Janeiro, RJ, Brazil
Rosely Sichieri
Affiliation:
Department of Epidemiology, Institute of Social Medicine, State University of Rio de Janeiro, Rua São Francisco Xavier, 524, 7 ° andar, Bloco E, Cep20550-900, Rio de Janeiro, RJ, Brazil
*
*Corresponding author: I. N. Bezerra, fax +55 21 2334 2152, E-mail: ilana.bezerra@yahoo.com.br
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Abstract

The objectives of the present study were to estimate the dietary contribution of away-from-home food consumption, to describe the contribution of away-from-home foods to energy intake, and to investigate the association between eating away from home and total energy intake in Brazilian urban areas. In the first Brazilian Nationwide Dietary Survey, conducted in 2008–9, food records were collected from 25 753 individuals aged 10 years or older, living in urban areas of Brazil. Foods were grouped into thirty-three food groups, and the mean energy intake provided by away-from-home food consumption was estimated. Linear regression models were used to evaluate the association between away-from-home food consumption and total energy intake. All analyses considered the sample design effect. Of the total population, 43 % consumed at least one food item away from home. The mean energy intake from foods consumed away from home was 1408 kJ (337 kcal), averaging 18 % of total energy intake. Eating away from home was associated with increased total energy intake, except for men in the highest income level. The highest percentage of away-from-home energy sources was for food with a high content of energy, such as alcoholic beverages (59 %), baked and deep-fried snacks (54 %), pizza (42 %), soft drinks (40 %), sandwiches (40 %), and sweets and desserts (30 %). The consumption of foods away from home was related to a greater energy intake. The characterisation of away-from-home food habits is necessary in order to properly design strategies to promote healthy food consumption in the away-from-home environment.

Type
Full Papers
Copyright
Copyright © The Authors 2012

Several factors contribute to energy intake that exceeds daily requirements(1). Available data suggest that foods from away-from-home sources are higher in energy than foods prepared at home(Reference Clemens, Slawson and Klesges2Reference Bowman and Vinyard4). Cross-sectional studies have shown positive associations between eating away from home and total energy intake. Many studies have indicated that consumers of away-from-home foods present higher energy and higher-energy-dense food intake than non-consumers(Reference Lachat, Nago and Verstraeten5). In addition, eating away from home is associated with a higher consumption of sugar-sweetened beverages and a lower consumption of milk, fruits and vegetables(Reference Paeratakul, Ferdinand and Champagne6, Reference Bowman, Gortmaker and Ebbeling7).

Longitudinal studies have suggested that frequent away-from-home food consumption is associated with higher energy intake and excessive weight gain. The data from a prospective Spanish dynamic cohort of 9182 university graduates who were followed for an average of 4·4 years indicated that those who ate away from home two or more times per week had a higher risk of gaining 2 kg or more per year than those who did not eat away from home(Reference Bes-Rastrollo, Basterra-Gortari and Sanchez-Villegas8). Among a population of 891 healthy adult women, increases in fast-food meal intake per week over a 3-year period were associated with an increase in total energy intake of 234 kJ/d (56 kcal/d)(Reference Bowman and Vinyard4).

Studies on energy and nutrient intakes related to away-from-home eating have only been conducted in the past few years and mainly in developed countries, such as the USA, Australia and various European countries(Reference Kearney, Hulshof and Gibney9Reference Orfanos, Naska and Trichopoulou14). There have been some studies conducted in low- and middle-income countries(Reference van't Riet, den Hartog and van Staveren15Reference Lachat, Khanh le and Khan17), but little is known about the impact of away-from-home food consumption on the total energy intake of individuals from a country undergoing rapid socio-economic development.

Since 1970, Brazil has experienced an increase in the prevalence of overweight and obesity. Trends in household food availability clearly indicate important changes that might be contributing to the increasing prevalence of overweight and obesity. The inclusion of sugar-sweetened beverages and processed food in household expenses is increasing along with the decrease in the household availability of traditional Brazilian foods, such as rice and beans(Reference Levy-Costa, Sichieri and Pontes18). Moreover, in the same period, expenditure on foods consumed away from home has increased while the energy obtained from the consumption of household food has decreased(Reference Bezerra and Sichieri19). As budget data indicate that the inclusion of away-from-home foods in total household food expenditures has become more important, the energy content associated with such foods may play an important role in the dietary profile of the Brazilian population.

In Brazil, household food availability and expenditure data, including data on foods consumed away from home, have been used to estimate food consumption(Reference Levy-Costa, Sichieri and Pontes18, Reference Bezerra and Sichieri19). This is the first study to estimate energy intake from foods consumed away from home based on data from an individual dietary intake survey carried out in a representative sample of the Brazilian urban population aged 10 years or older. The objectives of the present study were to estimate the population-based prevalence of away-from-home food consumption, to describe the contribution of away-from-home foods to energy intake, and to investigate the association between eating away from home and total energy intake.

Methods

The present study analysed the data obtained from the Brazilian Nationwide Dietary Survey, which was conducted along with the 2008–9 Household Budget Survey by the Brazilian Office of Geography and Statistics. A representative sample of Brazilian households was selected using a two-stage cluster sampling design. In the first stage, census tracts, the primary sampling units, were selected by systematic sampling with proportional probability to the number of households. In the second stage, households were selected by simple random sampling. The primary sampling units were stratified to include representives of all Brazilian regions, urban and rural areas, and different socio-economic levels. The 2008–9 Household Budget Survey sample included 55 970 households from 4696 census tracts. The Brazilian Nationwide Dietary Survey investigated 13 569 households, randomly selected from the 2008–9 Household Budget Survey sample, assuring that all sectors selected for the Household Budget Survey 2008–9 were represented in the dietary survey sample. Individuals aged 10 years or older (n 34 003) living in the selected households were included in the dietary survey. Most of the away-from-home eating occurs in urban areas, since in rural areas, only 9 % of total energy intake came from away-from-home eating. Therefore, for the purpose of the present paper, we included only individuals living in the urban areas of Brazil, yielding a final sample of 25 753 individuals.

Assessment of dietary intake

Dietary intake data were obtained by trained interviewers during the household survey. Individuals aged 10 years or older were requested to keep records of all foods and beverages consumed on two non-consecutive days. All respondents received a booklet with explanations on how to fill out the records and with pictures of tableware to help them estimate the amount of food consumed. Interviewers reviewed the records and entered the data in a computer database at the household. In addition, interviewers probed respondents with questions over usually forgotten items, such as small snacks, sweets and beverages, and verified that all 3 h periods without food intake and records with less than five items were corrected, following the multiple-pass method to accurately record all possible foods consumed(Reference Moshfegh, Rhodes and Baer20). This allowed the filling-in of incomplete data by interviewing family members. Reported food amounts were transformed to grams or millilitres, and energy intake was estimated using a food composition table and a food portion table specially developed for the survey(21, 22). Standard recipes were created and nutritional information was based on the Brazilian Table of Food Composition and the Nutrient Data System for Research.

The definition of away-from-home foods consumed includes all foods and drinks, except water, that were purchased and consumed away from home. This definition has been used in other studies(Reference Bezerra and Sichieri19, Reference Bezerra and Sichieri23) and does not include foods that were prepared at home and consumed away from home and ready-to-eat foods that were purchased away from home, but consumed at home. For this analysis, we evaluated the 1st day dietary record, which is typically better recorded than the following days(Reference Subar, Kipnis and Troiano24).

Other variables

Sociodemographic characteristics were collected during the household interviews. Monthly per capita income was calculated from all household monetary and non-monetary incomes, including gifts, donations, employment, self-employment and participation in cash transfer programmes. The total household income was divided by the number of members in the household to calculate the per capita household income and was evaluated in quartiles: up to US$127; between US$127 and 236; between US$236 and 499; more than 499 dollars per capita per month.

Analyses

Analyses were stratified by age groups of adolescents (10–19 years old), adults (20–59 years old) and elderly (60 years old or more). All foods reported in the survey were grouped into thirty-three food groups, according to their nutritional content and to the way they are commonly consumed. We also grouped foods together that are usually consumed away from home. The energy intake from each food group was calculated and the mean amount corresponding to away-from-home eating was estimated. The percentage of energy consumed away from home was estimated according to sex, age groups and income levels.

Linear regression models were used to evaluate the association between away-from-home eating (independent variable) and energy intake (dependent variable). The consumption of food away from home was evaluated as a dichotomous variable (yes/no), identifying whether individuals consumed at least one item away from home. Energy intake was log-transformed to better approximate a normal distribution. The models were adjusted for age and income. Both age and income were treated as continuous variables, and the interactions between away-from-home eating and income were tested.

Linear trends for away-from-home energy intake across the income levels were tested using linear regression models with away-from-home energy intake as the dependent variable and income as the independent continuous variable.

All statistical analyses were weighted and performed using survey procedures from SAS release 9.1.3 (2003, SAS Institute) to take into account the sample design effect. Subpopulation analyses were carried out with the domain statement, and smsub and sregsub SAS macros were used to properly incorporate the domain statement into the ratio and linear regression analyses, respectively. Weight factors were corrected for non-response, thus allowing population-representative estimates.

Results

The mean age of the population was 36·7 (se 0·2) years. Of the study population, 21 % were adolescents (10–19 years old), 66 % were adults (20–59 years old) and 13 % were elderly (60 years old or above). The mean per capita household income was US$378 (se 9·5). Women comprised 52·5 % of the population. The prevalence of overweight (BMI ≥ 25 kg/m2 and < 30 kg/m2) and obesity (BMI ≥ 30 kg/m2) for all individuals aged 19 years or more was 35 and 15 %, respectively. Among adolescents (10–19 years old), 23 % were overweight and 6 % obese, according to the WHO cut-offs for BMI-for-age (z-scores >+1 sd and >+2 sd, respectively).

The mean total energy intake was 8024 kJ (1919 kcal) and increased with income (P< 0·0001). The contribution of macronutrients to energy intake was very similar across all age groups, varying from 15·4 to 17·3 % for proteins, 26·9 to 27·8 % for lipids and 55·6 to 57·0 % for carbohydrates. The contribution of carbohydrates to energy intake reduced with income (57·5 % in the first quartile, 56·1 % in the second quartile, 55·5 % in the third quartile and 54·6 % in the fourth quartile). Conversely, the contribution of lipids to energy intake increased according to income (25·9 % in the first quartile, 27·2 % in the second quartile, 27·9 % in the third quartile and 28·4 % in the fourth quartile). There was no significant variation in the contribution of proteins to energy intake according to income (16·5 % in the first quartile, 16·6 % in the second quartile, 16·4 % in the third quartile and 16·9 % in the fourth quartile).

Of the study sample, 43 % consumed at least one food away from home. The mean energy intake from foods consumed away from home was 1408 kJ (337 kcal), averaging 18 % of total energy intake.

Energy consumed away from home increased with income for both sexes in all age categories, except among elderly women (Table 1). Among men, adults presented the highest percentage of energy consumed from away-from-home foods in all income levels. Among women, the contribution of away-from-home food consumption to energy intake was greater for adolescents in the first two income quartiles and very similar for adolescents and adults in the third income quartile. Only at the highest income level did adult women present a higher percentage of energy from foods consumed away from home compared with adolescents and the elderly.

Table 1 Contribution (%) of away-from-home eating to the total energy intake by sex, age groups and income level of individuals living in urban areas in the 2008–9 Brazilian Nationwide Dietary Survey

Alcoholic beverages and baked and deep-fried snacks were more often consumed away from home than at home (more than 50 % of the energy consumed from these groups came from away-from-home sources). Away-from-home energy sources were also high for pizza, soft drinks, sandwiches, and sweets and desserts. The lowest percentages of away-from-home energy intake (less than 10 %) were observed for breads, soups, milk, oils, spreads, sauces and condiments, salty meat/fish, and eggs/egg dishes (Table 2).

Table 2 Description of food groups, total energy intake from each food group (kJ/d), percentage and standard error of energy obtained from the away-from-home consumption of the respective food group among individuals living in urban areas in the 2008–9 Brazilian Nationwide Dietary Survey

Of the energy consumed away from home, 50 % came from rice/rice dishes, meat/meat dishes, beans/legumes, sweets and desserts, fruit juices, and baked and deep-fried snacks. The food groups that provided the lowest contributions to away-from-home energy intake were breakfast cereals, nuts, vegetables and salty meat/fish (Table 3).

Table 3 Contribution (%) of food groups to away-from-home energy intake of individuals living in urban areas in the 2008–9 Brazilian Nationwide Dietary Survey

* Values below 0·1 were not reported.

Individuals who reported consuming foods away from home presented, on average, higher energy intake than individuals who did not eat away from home (8670 v. 7541 kJ (2072 v. 1802 kcal); P< 0·0001). Even after controlling for age and income, away-from-home eating was positively associated with increased total energy intake for both men and women. The interaction between income and away-from-home eating was tested and a statistical significance was found among men (P< 0·0001), but not among women (P= 0·96). Stratifying the analyses by income levels, we found that the relationship between total energy intake and eating away from home remained positively significant among the first three income quartiles in men. Total energy intake was not related to foods consumed away from home only among men in the highest income level (Table 4). Although income did not change the relationship between away-from-home eating and energy intake among women, we also evaluated the relationship between eating away from home and total energy intake by income levels and found that among women, only in the third quartile was there no significant association (Table 4).

Table 4 Weighted regression coefficients (β) of linear model with log of total energy intake as the dependent variable and eating away from home (yes/no) as the independent variable, according to sex and income levels of individuals living in urban areas in the 2008–9 Brazilian Nationwide Dietary Survey* (β Coefficients and 95 % confidence intervals)

* Interaction terms between away-from-home eating and total energy intake were significant only among men (P< 0·0001 for men and 0·96 for women).

Models are adjusted for age continuously.

Discussion

The present study is based on the first Brazilian Nationwide Dietary Survey, and describes all foods prepared and consumed away from home and points out the major energy sources from away-from-home food consumption in urban areas. Of the study sample, 43 % reported consuming at least one food away from home. The fraction of mean energy intake from away-from-home eating was 18 %, varying between 2 % among elderly women in the second quartile of income and 29 % among adult men in the highest income level. In the multivariate analysis, even after controlling for age and income, eating away from home was positively associated with increased total energy intake among both men and women.

Direct comparisons with other studies are limited due to different methods applied as well as differences in the definition of away-from-home food, and the age and socio-economic profiles of the samples. In other studies, the contribution of energy from away-from-home foods to total energy intake ranged from 11 % among adults between 35 and 74 years old investigated in ten European countries using a more restrictive definition of substantial away-from-home consumers (individuals consuming ≥ 25 % of their daily energy intake from away-from-home food sources reported in one 24 h recall) to 50 % among adolescents between 13 and 19 years old as evaluated by the average of two 24 h dietary recalls collected only on their school days in Cotonou, Benin(Reference Paeratakul, Ferdinand and Champagne6, Reference Kearney, Hulshof and Gibney9, Reference van't Riet, den Hartog and van Staveren15, Reference Nago, Lachat and Huybregts16, Reference Burke, McCarthy and O'Neill25, Reference Orfanos, Naska and Trichopoulos26). Previous studies(Reference French, Harnack and Jeffery3, Reference Bowman and Vinyard4, Reference Kearney, Hulshof and Gibney9, Reference Guthrie, Lin and Frazao11, Reference van't Riet, den Hartog and van Staveren15, Reference McCrory, Fuss and Hays27Reference Mancino, Todd and Lin31) also reported that individuals who consumed foods away from home presented higher energy intake than non-consumers.

Many mechanisms have been suggested to explain the pathway between the consumption of food away from home and excessive energy intake including high energy density, high fat content, low fibre content, large portion sizes, high palatability and high variability(Reference McCrory, Fuss and Saltzman32Reference Rolls39). Although the results of the studies that investigated the relationship of away-from-home eating and weight gain are controversial(Reference Clemens, Slawson and Klesges2, Reference van't Riet, den Hartog and van Staveren15, Reference Bezerra and Sichieri23, Reference Binkley, Eales and Jekanowski40Reference Naska, Orfanos and Trichopoulou42), it can be stated that away-from-home food consumers present higher energy intake than non-consumers.

In the present study, the percentage of energy from away-from-home food was generally higher in adults and men, as well as among high-income individuals. The role of income as an important factor with away-from-home eating has previously been reported(Reference Lachat, Khanh le and Khan17, Reference Bezerra and Sichieri19, Reference Claro, Levy and Bandoni43). In addition, other studies have reported on the higher intake of away-from-home foods among men and young adults(Reference Bezerra and Sichieri19, Reference Anderson, Rafferty and Lyon-Callo44).

The present data indicate that socio-economic status modified the association between away-from-home eating and total energy intake among men, suggesting that those in the lowest income levels select more energy-dense foods when eating away from home than men in the highest income level. Although the percentage of away-from-home energy intake within food groups increased with income for almost all food groups, important differences according to the type of group consumed were observed. The contribution of rice/rice dishes, beans/legumes and vegetables to away-from-home energy intake among men in the highest income level is almost three times higher than among men in the lowest income level. However, this same trend is not observed when we evaluated the contribution of soft drinks, pizza, baked and deep-fried snacks, and sandwiches consumed away from home. The energy from pizza consumed away from home among men in the lowest income level was higher than the energy from away-from-home pizza among men in the highest income level (73 v. 45 %, respectively). The percentage of energy from away-from-home soft drinks on the total energy consumed from soft drinks was 41 % among men in the lowest income level and 52 % among men in the highest income level. For baked and deep-fried snacks, the percentages were 54 and 57 %, respectively, while for sandwiches the percentage was the same (data not shown).

These findings are particularly important from a public health perspective, considering that away-from-home food consumption might be related to total energy intake differently according to the income levels, which must be taken into account in the design of food and nutrition policies, for example facilitating the access to healthy food items to low- and middle-income people.

Alcoholic beverages and baked and deep-fried snacks were consumed in greater proportions away from home than at home. Pizzas, soft drinks, sandwiches, and sweets and desserts were also highly consumed away from home. These results are consistent with other studies(Reference Kearney, Hulshof and Gibney9, Reference van't Riet, den Hartog and van Staveren15, Reference Lachat, Khanh le and Khan17, Reference French, Story and Neumark-Sztainer45, Reference Vandevijvere, Lachat and Kolsteren46) and raise important concerns regarding the role of foods consumed away from home on the quality of the diet in Brazilian urban areas. The consumption of baked and deep-fried snacks and pizza can add important amounts of saturated fat, trans-fat and Na to the diet, which are known to increase the risk of weight gain, insulin resistance and CVD(Reference Burns, Jackson and Gibbons10, Reference Satia, Galanko and Siega-Riz28, Reference Binkley, Eales and Jekanowski40). Several studies have found that away-from-home eating is associated with higher total fat and Na consumption than the eating of at-home foods(Reference Kearney, Hulshof and Gibney9, Reference Burns, Jackson and Gibbons10, Reference Kant and Graubard12, Reference van't Riet, den Hartog and van Staveren15, Reference Lin, Frazão and Guthrie47). Additionally, the high consumption of soft drinks away from home is another important aspect that can have a negative impact on health, since it is suggested that the intake of energy in liquid form confers less satiety, decreasing the mechanisms of energy intake compensation in comparison with solid foods, thus contributing to high energy intake and weight gain(Reference Bellisle and Drewnowski48Reference Wolf, Bray and Popkin50).

In the present study, the consumption of sandwiches should be evaluated with caution due to a possible underestimation that may have happened as respondents could detail the ingredients of their sandwiches or simply report a whole sandwich, for example a grilled cheese sandwich. In the present analysis, in the sandwich group, we only included sandwiches that were reported as single items.

We calculated the ratio of away-from-home energy intake by food group to total away-from-home energy intake, and found that rice/rice dishes, meat/meat dishes and beans/legumes were the groups that most contributed to the total energy consumed away from home. The combination of rice, beans and meat represents a traditional meal in Brazil, mostly consumed at lunch and dinner, indicating that away-from-home food may be mostly consumed during these meal occasions and most probably related to time constraints encountered during working hours(Reference Jabs and Devine51).

The inclusion of alcoholic beverages in analyses of away-from-home food consumption has been questioned since there are individuals who consumed only alcoholic beverages away from home and because alcoholic beverages can contain non-ethanol energy sources(Reference Orfanos, Naska and Trichopoulou14). Nevertheless, excluding alcoholic beverages from the analysis did not change the contribution of foods consumed away from home to the total energy intake (from 18 to 17 %, respectively) nor the rank of food groups in the contribution to away-from-home energy intake.

A negative aspect of foods consumed away from home in Brazilian urban areas is the high level of sweets and desserts, leading to both a high percentage of energy consumed away from home and important contributions to away-from-home energy intake. Diets with high amounts of sugars and sweet foods usually have high contents of energy and low amounts of vitamins and minerals(Reference Kearney, Hulshof and Gibney9).

The limitations of the present study are the effects of under-reporting of specific subgroups, such as women and obese individuals, and the inherent limitations of food records, in that they are subject to modification by the intake of individuals on reporting days(Reference Rebro, Patterson and Kristal52, Reference Scagliusi, Ferriolli and Pfrimer53). Another limitation is the definition used to identify away-from-home foods in the survey, which does not include foods that were prepared away from home and consumed at home, such as takeaway and home delivery foods, which are known to be rich in fat and energy(Reference Lin, Frazão and Guthrie47). Another important issue in terms of public health nutrition and policy perspective is the evaluation of the places where people eat out, but this information was not collected in the dietary survey.

We found evidence that away-from-home food consumption is associated with increased energy intake, except for men in the highest income level. Additionally, socio-economic status was positively associated with a greater contribution of foods consumed away from home to the total energy intake. These observations suggest that the influence of away-from-home food consumption on diet quality varies according to socio-economic status. Overall, the present findings highlight the high intake of foods with a high content of energy in away-from-home settings, such as alcoholic beverages, baked and deep-fried snacks, pizza, soft drinks, and sweets and desserts. Consequently, away-from-home food consumption may be linked to adverse health outcomes, in particular weight gain. More in-depth studies on the nutritional contributions of foods consumed away from home to the overall Brazilian diet and the socio-economic differences related to this issue are necessary to properly design and target strategies for moderating energy intake and enhancing diet quality in this country.

Acknowledgements

The survey was funded by the Ministry of Health of Brazil. I. N. B. received a fellowship from the Brazilian Federal Agency for the Improvement of Higher Education (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; CAPES) – process no. 6748-10-4. R. S. and R. A. P. contributed to the design of the study. I. N. B. and A. d. M. S. contributed to the analysis and interpretation of the data, and the drafting of the manuscript. All authors read and approved the final manuscript. None of the authors has conflicts of interest.

References

1US Department of Agriculture (2010) Report of the Dietary Guidelines Advisory Committee on the Dietary Guidelines for Americans, 2010. Washington, DC: US Department of Agriculture.Google Scholar
2Clemens, LH, Slawson, DL & Klesges, RC (1999) The effect of eating out on quality of diet in premenopausal women. J Am Diet Assoc 99, 442444.Google Scholar
3French, SA, Harnack, L & Jeffery, RW (2000) Fast food restaurant use among women in the Pound of Prevention study: dietary, behavioral and demographic correlates. Int J Obes Relat Metab Disord 24, 13531359.Google Scholar
4Bowman, SA & Vinyard, BT (2004) Fast food consumption of U.S. adults: impact on energy and nutrient intakes and overweight status. J Am Coll Nutr 23, 163168.Google Scholar
5Lachat, C, Nago, E, Verstraeten, R, et al. (2012) Eating out of home and its association with dietary intake: a systematic review of the evidence. Obes Rev 13, 329346.CrossRefGoogle ScholarPubMed
6Paeratakul, S, Ferdinand, DP, Champagne, CM, et al. (2003) Fast-food consumption among US adults and children: dietary and nutrient intake profile. J Am Diet Assoc 103, 13321338.Google Scholar
7Bowman, SA, Gortmaker, SL, Ebbeling, CB, et al. (2004) Effects of fast-food consumption on energy intake and diet quality among children in a national household survey. Pediatrics 113, 112118.Google Scholar
8Bes-Rastrollo, M, Basterra-Gortari, FJ, Sanchez-Villegas, A, et al. (2010) A prospective study of eating away-from-home meals and weight gain in a Mediterranean population: the SUN (Seguimiento Universidad de Navarra) cohort. Public Health Nutr 13, 13561363.Google Scholar
9Kearney, JM, Hulshof, KF & Gibney, MJ (2001) Eating patterns-temporal distribution, converging and diverging foods, meals eaten inside and outside of the home-implications for developing FBDG. Public Health Nutr 4, 693698.Google Scholar
10Burns, C, Jackson, M, Gibbons, C, et al. (2002) Foods prepared outside the home: association with selected nutrients and body mass index in adult Australians. Public Health Nutr 5, 441448.Google Scholar
11Guthrie, JF, Lin, BH & Frazao, E (2002) Role of food prepared away from home in the American diet, 1977–78 versus 1994–96: changes and consequences. J Nutr Educ Behav 34, 140150.Google Scholar
12Kant, AK & Graubard, BI (2004) Eating out in America, 1987–2000: trends and nutritional correlates. Prev Med 38, 243249.Google Scholar
13O'Dwyer, NA, Gibney, MJ, Burke, SJ, et al. (2005) The influence of eating location on nutrient intakes in Irish adults: implications for developing food-based dietary guidelines. Public Health Nutr 8, 258265.CrossRefGoogle ScholarPubMed
14Orfanos, P, Naska, A, Trichopoulou, A, et al. (2009) Eating out of home: energy, macro- and micronutrient intakes in 10 European countries. The European Prospective Investigation into Cancer and Nutrition. Eur J Clin Nutr 63, Suppl. 4, S239S262.Google Scholar
15van't Riet, H, den Hartog, AP & van Staveren, WA (2002) Non-home prepared foods: contribution to energy and nutrient intake of consumers living in two low-income areas in Nairobi. Public Health Nutr 5, 515522.Google Scholar
16Nago, ES, Lachat, CK, Huybregts, L, et al. (2010) Food, energy and macronutrient contribution of out-of-home foods in school-going adolescents in Cotonou, Benin. Br J Nutr 103, 281288.Google Scholar
17Lachat, C, Khanh le, NB, Khan, NC, et al. (2009) Eating out of home in Vietnamese adolescents: socioeconomic factors and dietary associations. Am J Clin Nutr 90, 16481655.CrossRefGoogle ScholarPubMed
18Levy-Costa, RB, Sichieri, R, Pontes, NS, et al. (2005) Household food availability in Brazil: distribution and trends (1974–2003). Rev Saude Publica 39, 530540.Google Scholar
19Bezerra, IN & Sichieri, R (2010) Characteristics and spending on out-of-home eating in Brazil. Rev Saude Publica 44, 221229.Google Scholar
20Moshfegh, A, Rhodes, D, Baer, D, et al. (2008) The US Department of Agriculture Automated Multiple-Pass Method reduces bias in the collection of energy intakes. Am J Clin Nutr 88, 324332.Google Scholar
21Instituto Brasileiro de Geografia e Estatística (IBGE) (2011) Pesquisa de Orçamentos Familiares 2008–2009: Tabelas de Composição Nutricional de Alimentos Consumidos no Brasil (Consumer Expenditure Survey: Tables of Nutritional Composition of Food Consumed in Brazil). Rio de Janeiro: Instituto Brasileiro de Geografia e Estatística (IBGE), Ministério do Planejamento, Orçamento e Gestão.Google Scholar
22Instituto Brasileiro de Geografia e Estatística (IBGE) (2011) Pesquisa de Orçamentos Familiares 2008–2009: Tabela de Medidas Referidas para os Alimentos Consumidos no Brasil (Consumer Expenditure Survey: Table of Reference measures for Food Consumed in Brazil). Rio de Janeiro: Instituto Brasileiro de Geografia e Estatística (IBGE), Ministério do Planejamento, Orçamento e Gestão.Google Scholar
23Bezerra, IN & Sichieri, R (2009) Eating out of home and obesity: a Brazilian nationwide survey. Public Health Nutr 12, 20372043.Google Scholar
24Subar, AF, Kipnis, V, Troiano, RP, et al. (2003) Using intake biomarkers to evaluate the extent of dietary misreporting in a large sample of adults: the OPEN study. Am J Epidemiol 158, 113.Google Scholar
25Burke, SJ, McCarthy, SN, O'Neill, JL, et al. (2007) An examination of the influence of eating location on the diets of Irish children. Public Health Nutr 10, 599607.CrossRefGoogle ScholarPubMed
26Orfanos, P, Naska, A, Trichopoulos, D, et al. (2007) Eating out of home and its correlates in 10 European countries. The European Prospective Investigation into Cancer and Nutrition (EPIC) study. Public Health Nutr 10, 15151525.CrossRefGoogle ScholarPubMed
27McCrory, MA, Fuss, PJ, Hays, NP, et al. (1999) Overeating in America: association between restaurant food consumption and body fatness in healthy adult men and women ages 19 to 80. Obes Res 7, 564571.Google Scholar
28Satia, JA, Galanko, JA & Siega-Riz, AM (2004) Eating at fast-food restaurants is associated with dietary intake, demographic, psychosocial and behavioural factors among African Americans in North Carolina. Public Health Nutr 7, 10891096.Google Scholar
29Schmidt, M, Affenito, SG, Striegel-Moore, R, et al. (2005) Fast-food intake and diet quality in black and white girls: the National Heart, Lung, and Blood Institute Growth and Health Study. Arch Pediatr Adolesc Med 159, 626631.CrossRefGoogle ScholarPubMed
30Taveras, EM, Berkey, CS, Rifas-Shiman, SL, et al. (2005) Association of consumption of fried food away from home with body mass index and diet quality in older children and adolescents. Pediatrics 116, 518524.CrossRefGoogle ScholarPubMed
31Mancino, L, Todd, J & Lin, B-H (2009) Separating what we eat from where: measuring the effect of food away from home on diet quality. Food Policy 34, 557562.Google Scholar
32McCrory, MA, Fuss, PJ, Saltzman, E, et al. (2000) Dietary determinants of energy intake and weight regulation in healthy adults. J Nutr 130, 276S279S.Google Scholar
33Young, LR & Nestle, M (2002) The contribution of expanding portion sizes to the US obesity epidemic. Am J Public Health 92, 246249.Google Scholar
34Nielsen, SJ & Popkin, BM (2003) Patterns and trends in food portion sizes, 1977–1998. JAMA 289, 450453.Google Scholar
35Prentice, AM & Jebb, SA (2003) Fast foods, energy density and obesity: a possible mechanistic link. Obes Rev 4, 187194.Google Scholar
36Sorensen, LB, Moller, P, Flint, A, et al. (2003) Effect of sensory perception of foods on appetite and food intake: a review of studies on humans. Int J Obes Relat Metab Disord 27, 11521166.Google Scholar
37Isganaitis, E & Lustig, RH (2005) Fast food, central nervous system insulin resistance, and obesity. Arterioscler Thromb Vasc Biol 25, 24512462.Google Scholar
38Norton, GN, Anderson, AS & Hetherington, MM (2006) Volume and variety: relative effects on food intake. Physiol Behav 87, 714722.CrossRefGoogle ScholarPubMed
39Rolls, BJ (2009) The relationship between dietary energy density and energy intake. Physiol Behav 97, 609615.Google Scholar
40Binkley, JK, Eales, J & Jekanowski, M (2000) The relation between dietary change and rising US obesity. Int J Obes Relat Metab Disord 24, 10321039.Google Scholar
41Pereira, MA, Kartashov, AI, Ebbeling, CB, et al. (2005) Fast-food habits, weight gain, and insulin resistance (the CARDIA study): 15-year prospective analysis. Lancet 365, 3642.Google Scholar
42Naska, A, Orfanos, P, Trichopoulou, A, et al. (2011) Eating out, weight and weight gain. A cross-sectional and prospective analysis in the context of the EPIC-PANACEA study. Int J Obes (Lond) 35, 416426.Google Scholar
43Claro, RM, Levy, RB & Bandoni, DH (2009) [Influence of income on food expenditures away from home among Brazilian families, 2002–2003]. Cad Saude Publica 25, 24892496.CrossRefGoogle ScholarPubMed
44Anderson, B, Rafferty, AP, Lyon-Callo, S, et al. (2011) Fast-food consumption and obesity among Michigan adults. Prev Chronic Dis 8, A71.Google Scholar
45French, SA, Story, M, Neumark-Sztainer, D, et al. (2001) Fast food restaurant use among adolescents: associations with nutrient intake, food choices and behavioral and psychosocial variables. Int J Obes Relat Metab Disord 25, 18231833.Google Scholar
46Vandevijvere, S, Lachat, C, Kolsteren, P, et al. (2009) Eating out of home in Belgium: current situation and policy implications. Br J Nutr 102, 921928.Google Scholar
47Lin, BH, Frazão, E & Guthrie, J (1999) Away-from-home foods increasingly important to quality of American diet. In Agriculture Information Bulletin no. 749. Washington, DC: US Department of Agriculture, Economic Research Service.Google Scholar
48Bellisle, F & Drewnowski, A (2007) Intense sweeteners, energy intake and the control of body weight. Eur J Clin Nutr 61, 691700.Google Scholar
49Drewnowski, A & Bellisle, F (2007) Liquid calories, sugar, and body weight. Am J Clin Nutr 85, 651661.Google Scholar
50Wolf, A, Bray, GA & Popkin, BM (2008) A short history of beverages and how our body treats them. Obes Rev 9, 151164.Google Scholar
51Jabs, J & Devine, CM (2006) Time scarcity and food choices: an overview. Appetite 47, 196204.Google Scholar
52Rebro, SM, Patterson, RE, Kristal, AR, et al. (1998) The effect of keeping food records on eating patterns. J Am Diet Assoc 98, 11631165.Google Scholar
53Scagliusi, FB, Ferriolli, E, Pfrimer, K, et al. (2008) Underreporting of energy intake in Brazilian women varies according to dietary assessment: a cross-sectional study using doubly labeled water. J Am Diet Assoc 108, 20312040.Google Scholar
Figure 0

Table 1 Contribution (%) of away-from-home eating to the total energy intake by sex, age groups and income level of individuals living in urban areas in the 2008–9 Brazilian Nationwide Dietary Survey

Figure 1

Table 2 Description of food groups, total energy intake from each food group (kJ/d), percentage and standard error of energy obtained from the away-from-home consumption of the respective food group among individuals living in urban areas in the 2008–9 Brazilian Nationwide Dietary Survey

Figure 2

Table 3 Contribution (%) of food groups to away-from-home energy intake of individuals living in urban areas in the 2008–9 Brazilian Nationwide Dietary Survey

Figure 3

Table 4 Weighted regression coefficients (β) of linear model with log of total energy intake as the dependent variable and eating away from home (yes/no) as the independent variable, according to sex and income levels of individuals living in urban areas in the 2008–9 Brazilian Nationwide Dietary Survey* (β Coefficients and 95 % confidence intervals)