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Revista Brasileira de Epidemiologia

Print version ISSN 1415-790X

Rev. bras. epidemiol. vol.12 n.3 São Paulo Sep. 2009 



Socioeconomic, demographic, environmental and behavioral factors associated with overweight in adolescents: a systematic literature review



Letícia de Oliveira CardosoI; Elyne Montenegro EngstromI, II; Iuri da Costa LeiteI; Inês Rugani Ribeiro de CastroII, III

IEscola Nacional de Saúde Pública Sérgio Arouca - Fundação Oswaldo Cruz
IIInstituto Annes Dias-Secretaria Municipal de Saúde do Rio de Janeiro
IIIInstituto de Nutrição - Universidade do Estado do Rio de Janeiro

Correspondence to




OBJECTIVE: To identify socioeconomic, environmental and behavioral factors associated with overweight (OW) in adolescents through a systematic literature review.
METHODS: Six databases were consulted (Lilacs, Adolec, SciELO, Medline via Pubmed, ISI Web of Knowlwdge and Cochrane Library) between January 3 and 13, 2008. The following key-words and respective MeSH terms were used: "overweight", "obesity", "adolescence", "adolescents", "risk factors", "associated factors". Articles in English, Spanish and Portuguese published between 1997 and 2007 were evaluated, and only observational studies with adolescents aged from 10 to 19 years, diagnosed with OW using international criteria were included. Studies based on convenience samples or that did not investigate social, environmental and psycho-behavioral factors as independent variables were excluded.
RESULTS: 202 articles were selected by reading the titles and abstracts and applying initial eligibility criterion. The review of complete publications allowed including and analyzing 56 articles. Socioeconomic level was found to be inversely associated with OW in developed countries and directly associated in developing countries. The habit of going on weight loss diets, the number of hours per day watching TV/video, having an obese mother and/or father and the occurrence of OW in childhood were directly associated with OW. The habit of having breakfast and physical activity were observed to be protective factors.
CONCLUSION: Socioeconomic, behavioral, family, and childhood variables were associated with OW and should be considered in interventions directed toward the problem among adolescents.

Key Words: Overweight. Obesity. Risk factors. Adolescent.




Overweight (including obesity) has become increasingly more important in the global epidemiological scenario, not only as a function of its growing prevalence, but mainly because it is associated with a series of deleterious effects on health. Data published by the World Health Organization - WHO in 2004 suggests that the prevalence of overweight and obesity has been growing at an alarming pace, both in developed and developing countries. In most European countries, the prevalence of excess weight (overweight and obesity together) in adults ranges between 50 and 75%. In the United States, obesity affects about 20% of men and 25% of women(1). In Africa and Latin America, with the fast urbanization and growth of the socioeconomic level in some countries, obesity has been growing and surpassing the prevalence of underweight, as is the case of Cape Town, in South Africa, and of Brazil. In these countries, 44 and 13.1% of women and 10 and 8.9% of men, respectively, are obese(1,2).

Another striking feature of the epidemic growth of overweight is the increase of this disorder in increasingly younger ages. In 2004, 10% of children and adolescents in the world were already estimated to be overweight and, among them, one fourth to be obese3. A study performed by Wang et al.(4) in countries in different stages of social and economic development revealed a significant increase in the prevalence of overweight children and adolescents in past decades. Major increments of magnitude have been observed, especially among adolescents: 62% in the United States (from 16.8 to 27.3% in the US) and 240% in Brazil (from 3.7 to 12.6%).

Longitudinal studies have identified obesity in childhood and adolescence, particularly during the second decade of life, as an important predictor of obesity in adult life, especially for extremely obese children with obese parents(5-8). The literature has documented some consequences of obesity, such as substantial risk for hypertension, type II diabetes mellitus, respiratory and muscular-skeletal complications, in addition to major psychosocial repercussions (9-12).

The changes in diet and exercise patterns that occurred in several societies, have contributed to an increased overweight population(13) . It should be pointed out, however, that the determinants of overweight comprise a complex set of biological, behavioral and environmental inter-related factors that mutually augment each other. For children and adolescents, conditions and situations present in the school, family and neighborhood environment are examples of these factors. Characteristics present during pregnancy and in the beginning of life, such as mother's nutritional status previous to pregnancy, smoking during pregnancy and nutritional status in childhood also stand out(14-19) .

In face of the complexity of the process that determines the condition, a set of interventions aimed at preventing obesity during childhood and adolescence has been proposed. Interventions involve actions oriented toward habits, family and individual choices and collective measures, such as for example, regulation of food commercial practices and publicity, and reorganization of the urban space. Nonetheless, in order to formulate actions, it is necessary to acknowledge the network of determinants and to identify the set of factors that can respond to interventions targeted at overweight in adolescents(20-22).

In past years, some systematic revisions on the efficacy or effectiveness of interventions oriented toward prevention or treatment of overweight and obesity in childhood have been published, although specific studies on adolescents were not found(23-28). So far, systematic revisions on risk factors for overweight in this specific group of the population have not been found either. Thus, the objective of the present study was to identify the socioeconomic, environmental and behavioral factors associated with overweight (OW) in adolescents by means of a systematic literature review.



Databases and search strategies

The following databases were consulted: Lilacs, Adolec, SciELO, Medline via Pubmed, ISI Web of Knowlwdge and Cochrane Library between January 03 and 13, 2008. The keywords and respective MeSH terms used for the search were: "overweight", "obesity", "adolescence", "adolescents", "risk factors", "associated factors", in the title/abstract words field of the reference bases. In the Medline database, six search equations were built to which the term "Major" was added to the side of each keyword alternately: "Overweight"[Majr] OR "Obesity"[Majr] AND "Adolescent"[Mesh] OR "risk factor"[Mesh]; Overweight"[Mesh] OR "Obesity"[Mesh] AND "Adolescent"[Majr] OR "risk factor"[Mesh]; Overweight"[Mesh] OR "Obesity"[Mesh] AND "Adolescent"[Mesh] OR "risk factor"[Majr]; Overweight"[Majr] OR "Obesity"[Majr] AND "Adolescent"[Majr] OR "risk factor"[Mesh]; Overweight"[Majr] OR "Obesity"[Majr] AND "Adolescent"[Mesh] OR "risk factor"[Majr]; Overweight"[Majr] OR "Obesity"[Majr] AND "Adolescent"[Majr] OR "risk factor"[Majr]. This strategy enabled the utilization of equations with different levels of specificity, which expanded the range for selecting the studies to be examined. The period of publication ranged between 1997 and 2007 and articles published in English, Spanish and Portuguese were selected. Such period was defined because, in mid 1995, the WHO recommended using the Body Mass Index (BMI, weight (kg)/height2 (m)) associated with skin fold measurements as a new diagnostic criteria for overweight and obesity among adolescents of the population, since then an international recommendation for defining overweight and obesity for this age group(29).

Selection criteria

Complete articles that met the following criteria were included in the present revision: population in the 10 to 19 year-old age group; observational (cross-sectional, cohort or case-control) study design; subjects selected with a probabilistic sample in cross sectional studies or an article with a sample design used in the remaining study designs; having as the main or secondary objective the identification of factors (environmental, social, demographic or psycho-behavioral) associated with overweight or obesity, analyzed as a categorical variable.

It is worth explaining that there is no consensus in the literature as to the anthropometric diagnosis of overweight and/or obesity in adolescents. For the present study, only articles that used at least one of the following criteria were included:

i) World Health Organization(29): BMI by sex and age above percentile 85 of the American population (data of the National Health and Nutrition Examination Survey, 1971/05), associated or not with skin fold values above percentile 90 of the same reference population;

ii) Cole et al.(30): BMI by sex and age above the values that correspond to 25.0 and 30.0kg/m2 at 18 years of age, which is the equivalent to the cut-off points that define overweight and obesity in adults. Values were obtained in a database built with six population studies: Great Britain, Brazil, The Netherlands, Hong Kong, Singapore, and the United States. This is the criterion recommended by the International Obesity Task Force - IOTF;

iii) Centers for Disease Control and Prevention(31): BMI by age and sex above percentile 85 or 95 of the American population (data from the National Health and Nutrition Examination Survey collected between 1963 and 1994);

iv) World Health Organization(32): BMI by sex and age above 1 or 2 standard deviations (SD), using the American standard as reference (data of the National Health and Nutrition Examination Survey of 1977 supplemented with those of the growth standard of children less than 5 years old).

We excluded studies whose population assessed included pregnant or puerperal women, adolescents or individuals with any disease, and those published as editorials, comments, letters, validation, and intervention studies.

Data extraction

Studies were selected and information extracted by two independent revisers, with the help of a standardized tool. Information on the country where the study was conducted, characteristics of individuals studied (age, sex, ethnicity), sample size, study design, independent variables measured, parameters used to define overweight, statistical analysis technique used, and results obtained were collected. Independent variables were grouped into demographic, socioeconomic, dietetic, exercise, other behaviors, psychological, previous, family, and environmental. Whenever available, the results of the adjusted models were chosen for the present study. In the absence of this information, results from the univariate analysis were collected.

After data extraction, the STROBE (Strengthening the reporting of observational studies in epidemiology)(33) report was used as a guideline to assess availability of information and the methodological procedures adopted in selected articles. This report aims to help building observational study publications and has a checklist of items that should be observed by authors and that varies from the wording of the title to the mention of funding sources of the study. Each one of the items considered in the articles selected received points (integral (1,0), partial (0,5) or non existing (0)) according to the availability of information and/or adoption of the procedure studied in that specific item. Afterwards, points were summed and the percentage of points over the total items applicable was calculated.

The aim of the present study was to identify factors associated with OW among adolescents without the intention of quantifying the magnitudes of existing associations or producing a summary measure, and for this reason, a meta-analytical synthesis was not performed in the present systematic revision.

As the information analyzed was obtained from studies already performed, the present study was not submitted to the Human Research Ethics Committee.



Initially, 942 studies were identified. Of these, 741were excluded after reading titles and abstracts (when available), mainly when they identified overweight as an exposure variable or because they were merely descriptive studies (376 articles) or, still, when they were intervention, revision or tool validation studies, notes or opinions of researchers (261 publications). As a result, 202 articles were left. When abstracts were not available in the databases consulted, a complete manuscript was sought and a first reading performed. In this second stage, after reading complete articles, 59 articles were selected. Afterwards, 3 studies were excluded: 2 because they did not inform the age group of participants and 1 because it did not present the reference population used for diagnosing overweight, even after two attempts to contact the authors. Therefore, 56 articles remained, selected by consensus for analysis. Figure 1 presents the study selection process flow.



General characteristics of studies

Studies analyzed were conducted between 1971 and 2005, with a higher number of studies done after the 1990's. Most studies (n=37) were conducted in developed countries, mainly in the United States (n=20). Among developing countries, Brazil had an expressive representation among the studies selected (n=14). Results analyzed in this article came mostly from cross-sectional studies (n=38), whose main data sources were surveys with representativeness of population segments, 10 of which with national representativeness. This characteristic is partly reflected in the wide range observed in the number of participants: from 281,630 adolescents assessed in the "Avena Study"(34) to the 173 adolescents examined in a case-control study conducted in Brazil(35). Only 5 studies assessed adolescents between 10 and 19 years of age. The age group studied most frequently was that between 12 and 19 years.

Table 1 presents in detail the variables and indicators analyzed, criteria for defining overweight and/or obesity, statistical techniques used, main results, STROBE scores, and the limitations of the 56 studies assessed.

The group of independent variables studied most frequently were socioeconomic variables, followed by dietary ones, then exercising, and other behaviors related to lifestyle followed by demographics. Most studies used calibrated weight and height data (n=40) and adjusted regression models in statistical analysis (n=46). None of the studies assessed adopted the WHO's recommended (2007) diagnostic criteria for overweight.

The percentage of points obtained by studies according to the STROBE report guide ranged between 38.7 and 84.4% with a mean of 64.5%. Small differences were observed when comparing characteristics of designs and methods of the publications that presented the highest point percentage (above 75%) with those that obtained the lowest results (below 25%). In the group of studies with highest points, the cohort design was observed to be more frequent in comparison to the lowest point group. Socioeconomic variables were assessed more frequently in the group of studies with lowest points.

Most studies found a statistically significant association between factors studied and OW, and only in three studies (36-38) no association was found. Fourteen studies that assessed obesity as outcome, presented, in general, results similar to those observed for OW.

Socioeconomic, demographic and environmental variables and EP

Of all studies, 45 studied socioeconomic variables: 28, demographic and 9, environmental. In general, the direction of the association between socioeconomic level (assessed by individual and/or clustered variables, ex: family income, parents' schooling, type of health insurance, type of school (public or private) etc.) and OW was distinct between developed and developing countries. An inverse association between socioeconomic level and OW was observed in developed countries(34,39-51), while a direct relation was observed in developing countries. The fact that these results were also found in studies with a higher point percentage according to the STROBE report checklist(44,48,51) should also be pointed out. Environmental variables that characterize geographical areas as sites of higher or lower development (living in cities with 10,000 or more inhabitants; living in urban areas and mean income of neighborhood) were also inversely associated with OW in developed countries. In three studies, two of them conducted in Brazil(52,53) and one in China(54), a direct association between living in an urban area and OW was observed.

This pattern of association was similar when analyses were stratified by sex. However, in two studies carried out in developed countries whose specific objective was to identify the association between socioeconomic level and OW, no statistically significant association was observed among girls (34,48).

Behavioral variables and OW

Among behavioral variables, 30 studies assessed dietary variables, 31 evaluated factors related to physical exercise (PE) and 29 measured other behaviors. Being or having been on a diet to lose weight or having a restrictive diet behavior had a direct association with OW in all studies analyzed (14, 35, 55-59), except for a study conducted in Brazil(60). Attitudes related to weight loss (ex: taking pills, laxatives to lose weight without medical guidance)(55), consumption of soft drinks 3 days or more per week(40), and the habit of buying a snack at school(51) were also positively associated with OW. There was an inverse association with OW for: habit of having breakfast(59, 61-63), amount of energy, fibers and cholesterol consumed in the past 24 hours (47), consumption of fruit and greenery in the past seven days (63), habit of having cereal for breakfast(64), and having more meals during the day(14,60,65). By comparing these findings to those found in analyses stratified by sex, a study presented discordant result among girls: being on a diet to lose weight was inversely associated with OW(60. The habit of having dinner with family was inversely associated with OW in one of the two studies that analyzed this behavior(36, 66).

Exercising (PE) and its frequency at and outside school, especially more intense PE (vigorous and intense exercise), assessed by different tools, were inversely associated with OW in 12 studies (40, 51, 55, 59, 61, 62, 67-72). In a longitudinal study conducted by Gordon-Larsen et al.(67), the increase in the intensity of PE, taken as a time-dependent variable, was also shown to protect against OW. Only two studies identified a positive association between PE and OW(55,73).

When other behaviors were assessed, a direct association was observed between the number of hours spent in front of the TV, video-game or computer and OW in all studies that showed statistical significance in the analysis of the relation(39,60,61,67,68,71-76).

The number of hours of night sleep was inversely associated with OW in two of the six studies that assessed this variable(72,75). Smoking, using alcohol and other drugs, investigated by 11 studies, did not show association with OW, except for the study of Carrière(62), that observed a positive association between OW and a smoking experience sometime in life.

Psychological variables and OW

Seven studies(19,37,44,55,57,59,77) assessed psychological variables and, of these, three presented significant associations with OW. Directly associated with OW, both in boys and girls were: a higher score of depressive symptoms(77); presence of a food disorder characterizing a restrictive behavior(59) and the presence of trace of anxiety(19). However, OW was inversely associated with the presence of eating disorders due to external stimuli, when only girls were taken into consideration(59).

History and family characteristics and OW

Initial living conditions and family characteristics that were directly associated with OW were: occurrence of overweight in some phase of childhood(14,40,58,78,79,); fast weight gain up to the second year of life(78); smoking during pregnancy(17,18), and maternal pre-gestational BMI (18); overweight mother and/or father(17,35,44,54,58,62,69,72,73,79,80) . One article identified a direct association between parents currently smoking and OW(62). A similar result was observed when analyses were stratified by sex. Duration of breastfeeding for two or more months had a protecting effect on OW in three studies(14,17,81). However, in the study conducted by Salsberry & Reagan (17) this association was observed only among obese mothers.

The main limitations mentioned by authors for the articles selected were: utilization of cross-sectional data, which does not guarantee that exposure preceded outcome (even if in some articles the original design was a cohort study); utilization, in some studies, of weight and height referred by adolescents and/or parents; compromise of external validity in some studies and incomplete adjustment because of not accounting for potential confounders in the relationship of interest.



The major socioeconomic, environmental and behavioral factors associated directly or inversely with OW among adolescents in the present revision were: socioeconomic level of families; certain behaviors related to food, mainly referring to restriction of food consumption and having breakfast; frequency and intensity of physical exercise and time spent in sedentary activities. Previous nutritional status of adolescents and nutritional status of parents also proved as relevant conditions for the occurrence of OW in adolescence.

Despite the heterogeneity observed in the design and in the selection of variables and exposure indicators, patterns of association between socioeconomic variables and OW were shown to be consistent, highlighting the difference of the direction of this association between developed and developing countries, observed in some surveys with nationwide representativeness(2,38,80). Studies using data from the past three decades in the United States (USA) showed that the increase in the prevalence of overweight is higher in families who live below the poverty line, especially among older adolescents (15 to 17 years) and Afro-American individuals (in comparison to white and Hispanic individuals of the same socioeconomic level). In a more recent period (1999 - 2002), an inverse association between socioeconomic level and OW was observed to be statistically significant only among girls(40,82). In Brazil, for example, in a period similar to that of the studies performed in the US, a direct relation between family income and OW was observed among adolescents and the relation is becoming weaker among girls(2).

Regarding dietary variables, a large number of studies identified the variable "dieting/or having dieted to lose weight" as a risk factor for OW. Methodological explanations may justify this finding, apparently without biological plausibility. Among the studies that identified this association, all had a cross-sectional design and/or analysis. Such design does not guarantee that exposure preceded outcome. Another explanation is the possible occurrence of systematic error in assessment, given OW adolescents would tend to give more socially expected answers, underestimating their food consumption and answering this question positively. Neumark et al.(83) questioned the validity and a reliability of the question "be on a diet", that could have several meanings to adolescents and they recommend performing qualitative studies to improve its understanding. In addition to methodological explanations, in the longitudinal study where this association was observed, the authors assessed characteristics associated with restrictive eating behaviors that are associated with the occurrence of OW. Adolescents with these behaviors limit their food intake, skip meals, feel very hungry and have little control over their eating and for this reason may be more susceptible to overweight(59).

We also identified eating behaviors that protect against the study's outcome, such as the habit of having breakfast and having more meals during the day. These behaviors are related to a more regular and defined meal pattern and are inversely associated with the habit of "snacking" foods with high energetic density throughout the day and, directly with vigorous physical exercise(20,56,84). Skipping breakfast is also suggested to be directly associated with other restrictive eating behaviors(59,61).

Despite the heterogeneity observed in variables and indicators presented by studies to measure exercising and intensity of physical activity (ex.: frequency, time, king and intensity of physical activities, participating in team sports, exercising at and outside school, etc.), this behavior seems to to protect against OW (except in the studies of Pérez et al.(55) and Suñe et al. 2007 (73). These findings are corroborated by recent systematic revisions that identified the efficacy and effectiveness of exercising and reduction in TV watching time in the prevention of OW in childhood and adolescence(23,25,26).

Few studies have identified association between psychological variables and OW. In the process of selecting studies, many articles were excluded because they assessed OW as a risk factor for psychological disorders, suggesting that psychological disorders are studied more as consequences than determinants of OW among adolescents.

Although it was not the objective of the present revision, some of the studies selected pointed toward a higher likelihood of OW among adolescents with at least one parent that was obese or that had been overweight during childhood. A survey with children also identified the presence of OW in parents as a risk factor for obesity(7). The interaction between a complex network of genes associated with obesity and the environments that favor their expression has been appointed as the background for the occurrence of obesity among individuals of the same family (85).

Among studies selected, distinct criteria were adopted for the diagnosis of OW. Wang & Wang(86) compared the prevalences of overweight and obesity in American, Chinese and Russian adolescents, according to the first three criteria adopted in the present study. The authors observed considerable differences among prevalences and recommend care in the comparison of results when distinct criteria are used. Despite this limitation, criteria for the diagnosis of OW used internationally were considered in the present revision aimed at expanding the selection of relevant literature to comply with the objective of the study. Moreover, the objective of the present study was to revise the association between certain factors and OW and not to compare the magnitude of the condition in diverse scenarios. The agreement between results of studies that utilized different criteria for diagnosing OW corroborates the consistency of the associations described in them.

As to the quality of studies, Khan et al.(87) listed some aspects that should be assessed and that relate directly to the level of evidence of results found in a systematic revision: the kind of study design and care adopted while it was conducted and analysis of results. Regarding the first aspect, most (n=53) studies included in the present revision have a cross-sectional design and/or cross-sectional analyses (level of evidence considered weak, according to these authors). However, comparing the results observed in studies with cross-sectional design and/or analyses with those of longitudinal analyses, a general similarity in patterns of association was observed. It should be also pointed out that, for some factors, it is possible to guarantee preceding time relations, as, for example, for variables that assess the socioeconomic level of families and those that relate to initial life.

On the conduction of studies, great heterogeneity in the selection and methods utilized for assessment of independent variables was observed, and also in the criteria adopted for diagnosis of OW, which makes their joint analysis difficult. This limitation seems to compromise, mainly, the analysis of association between eating behaviors and consumption variables with OW. Eleven of the 25 articles that assessed food consumption did not present any information on the validity or reliability of the tool used toward that end(14,18,39,40,47,62,64,66,69,76,88). However, for certain variables, there seems to not have been an influence of this limitation, given the similarity of the results observed, as was the case of variables related to exercise.

As to the care adopted in the analysis of results, nine studies carried out univariate analyses, without adjustment for potential confounding variables. The results of these studies, in general terms, were similar to those found in the studies that performed adjusted analyses. It should be pointed out that few studies included adjustments to correct the effect of the sample design and/or commented on the quality inspection of adjustment.

Some limitations of the present revision should be pointed out. The first one refers to the possibility of a relevant study being ignored, as only publications in English, Spanish or Portuguese were analyzed. No search was performed to identify unpublished studies or those published in annals of congresses, symposiums, etc. The second limitation refers to the interpretation of results of articles that assessed previous characteristics, given the initial objective of the present study was not to identify factors of initial life nor behaviors or nutritional status of parents; therefore, search strategies were not specified with that aim. Consequently, articles that studied this association may have been missed.



The growth in the magnitude of OW among youth of several regions of the world is an unquestionable reality. The acknowledgement of the complexity of its determinants and involvement of several sectors of society to prepare actions to promote health and prevent the condition is one of the current challenges in the global public health agenda. Despite the limitations in the comparison and analysis of selected studies, the revision points out a set of socioeconomic and behavioral factors that were shown to be associated with OW among adolescents and that are prone to intervention, and also highlights population groups in which the likelihood of the condition occurring is higher. The present authors, therefore, recommend that interventions oriented toward adolescents, both at the collective and individual level, take into account the factors herein identified, that is: socioeconomic level of families; food restriction behaviors; the habit of having breakfast; frequency and intensity of exercise, and time spent in sedentary activities. In addition to these, other factors of environmental, cultural and political nature are still little explored and should be considered, given the complexity and dynamics of the network that determines overweight in this age group still very susceptible to the changes experienced by societies.

Last, it should be pointed out that other eating behaviors, such as the consumption of certain foods and nutrients, habit of family meals, psychological variables, and environmental characteristics were little studied or did not present consistent associations between selected studies and, therefore, require further investigation.



1. World Health Organization. Obesity: Preventing and Managing the Global Epidemic. Report of a WHO Consultation. Geneva; 2004.WHO Technical Report Series no. 894.         [ Links ]

2. Instituto Brasileiro de Geografia e Estatística. Pesquisa de Orçamentos Familiares 2002-2003 - Análise da disponibilidade domiciliar de alimentos e do estado nutricional no Brasil. Rio de Janeiro; 2004.         [ Links ]

3. Lobstein T, Baur L, Uauy R. Obesity in children and young people: a crisis in public health. Obes Rev 2004; 5: S4-S85.         [ Links ]

4. Wang Y, Monteiro CA, Popkin BM. Trends of obesity and underweight in older children and adolescents in the United States, Brazil, China and Rússia. Am J Clin Nutr 2002; 74: 971-7.         [ Links ]

5. Power C, Lake JK, Cole TJ. Body mass index and height from childhood to adulthood in the 1958 British born cohort. Am J Clin Nutr 1997; 66: 1094-101.         [ Links ]

6. Serdula MK, Ivery D, Coates RJ, Freedman DS, Williamsson DF, Byers T. Do obese children become obese adults? A review of the literature. Am J Prev Med 1993; 22: 167-77.         [ Links ]

7. Whitaker RC, Wright JÁ, Pepe MS, Seidel KD, Dietz WH. Predicting obesity in young adulthood from childhood and parenteral obesity. N Engl J Med 1997; 337: 869-73.         [ Links ]

8. Freedman DS, Khan LK, Dietz WH. Relationship of Childhood Obesity to Coronary Heart Disease Risk Factors in Adulthood: The Bogalusa Heart Study. Pediatrics 2001; 108: 712-8.         [ Links ]

9. Must A. Morbidity and mortality associated with elevated body weight in children and adolescents. Am J Clin Nutr 1996; 63: S445-S7.         [ Links ]

10. Must A, Strauss RS. Risks and consequences of childhood and adolescent obesity. Int J Obes Relat Metab Disord 1999; 23: S2-S11.         [ Links ]

11. Wright CM, Parker L, Lamont D, Craft AW. Implications of childhood obesity for adult health: Findings from thousand families cohort study. BMJ 2001; 323: 1280-4.         [ Links ]

12. Ebbeling CB, Pawlak DB, Ludwig DS Childhood obesity: public-health crisis, common sense cure. Lancet 2002; 360: 473-82.         [ Links ]

13. Popkin BM. The nutrition transition and obesity in the developing world. J Nutr 2001; 131: 871-3.         [ Links ]

14. Neutzling MB, Taddei JA, Gigante DP. Risk factors of obesity among Brazilian adolescents: a case-control study. Public Health Nutr 2003; 6: 743-9.         [ Links ]

15. British Medical Association/ Internationa Obesity Task Force (BMA/IOTF). Preventing childhood obesity 2005. Disponível em [Acessado em 31 de janeiro de 2008]         [ Links ].

16. Nelson MC, Gordon-Larsen P, Song Y, Popkin BM. Associations with Adolescent Overweight and Activity Built and Social Environments. Am J Prev Med 2006; 31: 109-17.         [ Links ]

17. Salsberry PJ, Reagan PB. Taking the long view: the prenatal environment and early adolescent overweight. Res Nurs Health 2007; 30: 297-307.         [ Links ]

18. Mamun AA, Lawlor DA, Alati R, o'Callaghan MJ, Williams, GM, Najman JM. Does maternal smoking during pregnancy have a direct effect on future offspring obesity? Evidence from a prospective birth cohort study. Am J Epidemiol 2006; 164: 317-25.         [ Links ]

19. Monteiro P, Victora C, Barros F. Social, familial, and behavioral risk factors for obesity in adolescents. Rev Panam Salud Publica 2004; 16: 250-8.         [ Links ]

20. Lobstein T, Baur L, Uauy R. Obesity in children and young people: a crisis in public health. Obes Rev 2004; 5: S4-S85.         [ Links ]

21. Swinburn B, Kumanyika S. Obesity prevention: a proposed framework for translating evidence into action. Obes Rev 2005; 6: 23-33.         [ Links ]

22. World Health Organization (WHO). Diet, nutrition and the prevention of chronic diseases. Joint WHO/ FAO Expert Consultation. WHO Technical Report Series no. 916. Geneva; 2003.         [ Links ]

23. Connely JB, Duaso MJ, Butler G. A systematic review of controlled trials of interventions to prevent childhood obesity and overweight: a realistic synthesis of the evidence. Public Health 2007; 121: 510-7.         [ Links ]

24. Cole K, Waldrop J, D'Auria J, Garner H. An integrative research review: effective school-based childhood overweight interventions. J Spec Pediatr Nurs 2006; 11: 166-77.         [ Links ]

25. Atlantis E, Barnes EH, Singh MA. Efficacy of exercise for treating overweight in children and adolescents: a systematic review. Int J Obes 2006; 30: 1027-40.         [ Links ]

26. Doak CM, Visscher TL, Renders CM, Seidell JC. The prevention of overweight and obesity in children and adolescents: a review of interventions and programmes. Obes Rev 2006; 7: 111-36.         [ Links ]

27. Flodmark CE, Marcus C, Britton M. Interventions to prevent obesity in children and adolescents: a systematic literature review. Int J Obes 2006; 30: 579-89.         [ Links ]

28. Steinbeck KS. The importance of physical activity in the prevention of overweight and obesity in childhood: a review and an opinion. Obes Rev 2001; 2: 117-30.         [ Links ]

29. World Health Organization. Physical status: the use and interpretation of anthropometry. Geneva; 1995. WHO Technical Reports Series no. 854.         [ Links ]

30. Cole TJ, Bellizzi M, Flegal KM, Dietz WH. Establishing a standard definition of child overweight and obesity worldwide: International survey. BMJ 2000; 320: 1-6.         [ Links ]

31. Centers for Disease Control and Prevention. CDC Growth Charts: United States. 2000. Disponível em [Acessado em 12 de fevereiro de 2008]         [ Links ].

32. World Health Organization. The WHO Child Growth Standards. 2000. Disponível em [Acessado em 13 de fevereiro de 2008]         [ Links ].

33. Elm E, Altman DG, Egger M, Pocock SJ, Gotzsche PC, Vandenbroucke JP. Strengthening the reporting of observational studies in epidemiology (STROBE) statement: guidelines for reporting observational studies. BMJ 2007; 335: 806-8.         [ Links ]

34. Moreno LA, Mesana MI, Fleta J, Ruiz JR, Gonzalez-Gross, M, Sarría A, Marcos Ascension, Bueno M. Overweight, obesity and body fat composition in Spanish adolescents- The Avena Study. Ann Nutr Metab 2005; 49: 71-6.         [ Links ]

35. Silveira D, Taddei JAAAC, Escrivão MAMS, Oliveira FLC, Ancona-Lopez F. Risk factor for overweight among Brazilian adolescents of low-income families: a case-control study. Public Health Nutr 2005; 9: 421-8.         [ Links ]

36. Taveras EM, Rifas-Shiman SL, Berkey CS, Rockett HR, Field AE, Frazier AL, Colditz GA, Gillman MW Family dinner and adolescent overweight. Obes Res 2005; 13: 900-6.         [ Links ]

37. Ho C, Kingree JB, Thompson MP. Association between juvenile delinquency and weight-related variables: analyses from a national sample of high school students. Int J Eat Disord 2006; 39: 477-83.         [ Links ]

38. Boutelle KN, Fulkerson JA, Neumark-Sztainer D, Story M, French SA. Fast food for family meals: relationships with parent and adolescent food intake, home food availability and weight status. Public Health Nutr 2007: 10: 16-23.         [ Links ]

39. Miech RA, Kumanyika SK, Stettler N, Link BG, Phelan JC, Chang VW. Trends in the association of poverty with overweight among US adolescents, 1971-2004. JAMA 2006; 295: 2385-93.         [ Links ]

40. Mamun AA, Lawlor DA, O'Callaghan MJ, Williams GM, Najman JM. Positive maternal attitude to the family eating together decreases the risk of adolescent overweight. Obes Res 2005; 13: 1422-30.         [ Links ]

41. Moreno LA, Sarría A, Fleta J, Rodríguez G, González JM, Bueno M. Sociodemographic factors and trends on overweight prevalence in children and adolescents in Aragón (Spain) from 1985 to 1995. J Clin Epidemiol 2001; 54: 921-7.         [ Links ]

42. Wang Y, Liang H, Tussing L, Braunschweig C, Caballero B, Flay B. Obesity and related risk factors among low socio-economic status minority students in Chicago. Public Health Nutr 2007; 10: 927-38.         [ Links ]

43. O'Malley PM, Johnston LD, Delva J, Bachman JG, Schulenberg JE. Variation in obesity among American secondary school students by school and school characteristics. Am J Prev Med 2007; 33: S187-S94.         [ Links ]

44. Goodman E, Whitaker RC. A prospective study of the role of depression in the development and persistence of adolescent obesity. Pediatrics 2002; 110: 497-504.         [ Links ]

45. Haas JS, Lee LB, Kaplan CP, Sonneborn D, Phillips KA, Liang SY. The association of race, socioeconomic status, and health insurance status with the prevalence of overweight among children and adolescents. Am J Public Health 2003; 93: 2105-10.         [ Links ]

46. Johnson CA, Xie B, Liu C, Reynolds KD, Chou CP, Koprowski C et al. Socio-demographic and cultural comparison of overweight and obesity risk and prevalence in adolescents in Southern California and Wuhan, China. J Adolesc Health 2006; 39: 925.         [ Links ]

47. Forrest KYZ, Leeds MJ Prevalence and Associated Factors of Overweight among Mexican-American Adolescents. J Am Diet Assoc 2007; 107: 1797-800.         [ Links ]

48. Lien N, Kumar BN, Holmboe-Ottesen G, Klepp KI, Wandel M. Assessing social differences in overweight among 15- to 16-year-old ethnic Norwegians from Oslo by register data and adolescent self-reported measures of socio-economic status. Int J Obes 2007; 31: 30-8.         [ Links ]

49. Lee NE, Anindya K, Simon PA. School-based Physical Fitness Testing Identifies Large Disparities in Childhood Overweight in Los Angeles. J Am Diet Assoc 2006; 106: 118-21.         [ Links ]

50. Klein-Platat C, Wagner A, Haan MC, Arveiler D, Schlienger JL, Simon C. Prevalence and sociodemographic determinants of overweight in young French adolescents. Diabetes Metab Res Rev 2003; 19: 153-8.         [ Links ]

51. Veugelers PJ, Fitzgerald AL. Prevalence of and risk factors for childhood overweight and obesity. CMAJ 2005; 173: 607-13.         [ Links ]

52. Neutzling MB, Taddei JA, Rodrigues EM, Sigulem DM. Overweight and obesity in Brazilian adolescents. Int J Obes Relat Metab Disord 2000; 24: 869-74.         [ Links ]

53. Magalhães VC, Azevedo G, Mendonça S. Prevalence of overweight and obesity and associated factors among adolescents in the Northeast and Southeast regions of Brazil, 1996 to 1997. Cad Saude Publica 2003; 19: S129-39.         [ Links ]

54. Li M, Dibley MJ, Sibbritt D, Yan H. An assessment of adolescent overweight and obesity in Xi'an City, China. Int J Pediatr Obes 2006; 1: 50-8.         [ Links ]

55. Pérez A, Reininger BM, Flores MI, Sanderson R, Roberts RE. Physical activity and overweight among adolescents on the Texas-Mexico border. Pan Am J Public Health 2006; 19: 244-51.         [ Links ]

56. Kumar BN, Holmboe-Ottesen G, Lien N, Wandel M. Ethnic differences in body mass index and associated factors of adolescents from minorities in Oslo, Norway: a cross-sectional study. Public Health Nutr 2004; 7: 999-1008.         [ Links ]

57. Terres NG, Pinheiro RT, Horta BL, Pinheiro KA, Horta LL. Prevalence and factors associated to overweight and obesity in adolescents. Rev Saude Publica 2006; 40: 627-33.         [ Links ]

58. Cobayashi F, Lopes LA, Taddei JA. Bone mineral density in overweight and obese adolescents. J Pediatr 2005; 81: 337-42.         [ Links ]

59. Snoek HM, van Strien T, Janssens JM, Engels RC. Emotional, external, restrained eating and overweight in Dutch adolescents. Scand J Psychol 2007; 48: 23-32.         [ Links ]

60. Dutra CL, Araújo CL, Bertoldi AD. Prevalence of overweight in adolescents: a population-based study in a southern Brazilian city. Cad Saude Publica 2006; 22: 151-62.         [ Links ]

61. Delva J, Johnston LD, O'Malley PM. The epidemiology of overweight and related lifestyle behaviors: racial/ethnic and socioeconomic status differences among American youth. Am J Prev Med 2007; S178-86.         [ Links ]

62. Carrière G. Parent and child factors associated with youth obesity. Health Rep 2003; 14: 29-39.         [ Links ]

63. Roseman MG, Yeung WK, Nickelsen J. Examination of weight status and dietary behaviors of middle school students in Kentucky. J Am Diet Assoc 2007; 107: 1139-45.         [ Links ]

64. Kosti RI, Panagiotakos DB, Mihas CC, Alevizos A, Zampelas A, Mariolis A, Tountas Y. Dietary habits, physical activity and prevalence of overweight/obesity among adolescents in Greece: the Vyronas study. Med Sci Monit 2007; 13: 437-44.         [ Links ]

65. Costa MCD, Cordoni Junior L, Matsuo T. Sobrepeso em adolescents de 14 a 19 anos em um município da região Sul do Brasil. Rev Bras Saúde Matern Infant 2007; 7: 263-70.         [ Links ]

66. Sen B. Frequency of family dinner and adolescent body weight status: evidence from the national longitudinal survey of youth, 1997. Obesity 2006; 14: 2266-76.         [ Links ]

67. Gordon-Larsen P, Adair LS, Popkin BM. Ethnic differences in physical activity and inactivity patterns and overweight status. Obes Res 2002; 10: 141-9.         [ Links ]

68. Delva J, O'Malley PM, Johnston LD. Health-related behaviors and overweight: a study of Latino adolescents in the United States of America. Rev Panam Salud Publica 2007; 21:11-20.         [ Links ]

69. Savva SC, Kourides Y, Tornaritis M, Epiphaniou-Savva M, Chadjigeorgiou C, Kafatos A. Obesity in children and adolescents in Cyprus. Prevalence and predisposing factors. Int J Obes Relat Metab Disord 2002; 26: 1036-45.         [ Links ]

70. Raja'a YA, Bin Mohanna MA. Overweight and obesity among schoolchildren in Sana'a City, Yemen. Ann Nutr Metab 2005; 49: 342-5.         [ Links ]

71. Laxmaiah A, Nagalla B, Vijayaraghavan K, Nair M. Factors affecting prevalence of overweight among 12- to 17-year-old urban adolescents in Hyderabad, India. Obesity 2007; 15: 1384-90.         [ Links ]

72. Ramos E, Barros H Family and school determinants of overweight in 13-year-old Portuguese adolescents. Acta Paediatrica 2007; 96: 281-6.         [ Links ]

73. Suñé FR, Dias-da-Costa JS, Olinto MT, Pattussi MP. Prevalence of overweight and obesity and associated factors among schoolchildren in a southern Brazilian city. Cad Saude Publica 2007; 23: 1361-71.         [ Links ]

74. Utter J, Scragg R, Schaaf D. Associations between television viewing and consumption of commonly advertised foods among New Zealand children and young adolescents. Public Health Nutr 2006; 9: 606-12.         [ Links ]

75. Knutson KL, Lauderdale DS. Sleep Duration and Overweight in adolescents: self-reported sleep hours versus time diaries. Pediatrics 2006; 119: 1056-62.         [ Links ]

76. Moyaeri H, Bidad K, Aghamohammadi A, Rabbani A, Anari S, Nazemi L, Gholami N, Zadhoush S, Hatmi ZN. Overweight and obesity and their associated factors in adolescents in Tehran, Iran, 2004-2005. Eur J Pediatr 2006; 165: 489-93.         [ Links ]

77. Richardson LP, Garrison MG, Drangsholdt M Mancl L, LeResche. Associations between depressive symptoms and obesity during puberty. Gen Hosp Psychiatry 2006; 28: 313-20.         [ Links ]

78. Monteiro PO, Victora CG, Barros FC, Monteiro LM. Birth size, early childhood growth, and adolescent obesity in a Brazilian birth cohort. Int J Obes Relat Metab Disord 2003; 27: 1274-82.         [ Links ]

79. Ramos AMPP, Filho AAB. Prevalência de obesidade em adolescentes de Bragança Paulista e sua relação com a obesidade dos pais. Arq Bras Endocrinol Metab 2003; 47: 663-8.         [ Links ]

80. Savva SC, Kourides Y, Epiphaniou-Savva M, Tornaritis M, Kafatos A. Short-term predictors of overweight in early adolescence. Int J Obes Relat Metab Disord 2004; 28: 451-8.         [ Links ]

81. Kvaavik E, Grethe ST, Knut-Inge Klepp. Surveys of Norwegian youth indicated that breast feeding reduced subsequent risk of obesity. J Clin Epidemiol 2005; 58: 849-55.         [ Links ]

82. Wang Y, Zhang Q. Are American children and adolescents of low socioeconomic status at increased risk of obesity? Changes in the association between overweight and family income between 1971 and 2002. Am J Clin Nutr 2006; 84: 707-16.         [ Links ]

83. Neumark-Sztainer D, Wall M, Guo J, Story M, Haines J, Eisenberg M. Obesity, disordered eating, and eating disorders in a longitudinal study of adolescents: how do dieters fare 5 years later? J Am Diet Assoc 2006; 106: 559-68.         [ Links ]

84. Boutelle K, Neumark-Sztainer D, Story M, Resnick M. Weight control behaviors among obese, overweight, and nonoverweight adolescents. J Pediatr Psychol 2002; 27: 531-40.         [ Links ]

85. Allison DB, Matz PE, Pietrobelli A, Zannoli R, Faith MS. Genetic and environmental influences on obesity. In: Bendicch A, Deckelbaum RJ (eds). Primary and Secundary Preventive Nutrition. Totowa, New Jersey: Humana Press; 1999. p. 147-64.         [ Links ]

86. Wang Y, Wang JQ. A comparison of international references for the assessment of child and adolescent overweight and obesity in different populations. Eur J Clin Nutr 2002; 56: 973-82.         [ Links ]

87. Khan SK, Kunz R, Kleijnen J, Antes G. Systematic reviews to support evidence-based medicine: how to review and apply findingd of healthcare research. London: Royal Society of Medicine Press Ltd; 2003.         [ Links ]

88. Nunes MM, Figueiroa JN, Alves JG. Overweight, physical activity and food habits in adolescents from different economic levels, Campina Grande (PB). Rev Assoc Med Bras 2007; 53: 130-4.         [ Links ]

89. Campos LA, Leite AJM, Almeida PC. Nível socioeconômico e sua influência sobre a prevalência de sobrepeso e obesidade em escolares adolescentes do município de Fortaleza. Rev Nutr 2006; 19: 531-8.         [ Links ]

90. Pérez-Cueto A, Almanza M, Kolsteren PW. Female gender and wealth are associated to overweight among adolescents in La Paz, Bolivia. Eur J Clin Nutr 2005; 59: 82-7.         [ Links ]



Correspondence to:
Letícia de Oliveira Cardoso
Escola Nacional de Saúde Pública Sérgio Arouca - FIOCRUZ
Departamento de Epidemiologia e Métodos Quantitativos em Saúde
Rua Leopoldo Bulhões, 1480, sala 813
Manguinhos - Rio de Janeiro. CEP: 21041-210
Tel: 55 21 25982619; 55 21 98301814. Fax: 55 21 22706772



No aid was received from funding agencies in order to develop the present study
The authors declare there were no potential or actual conflicts of interest in the development of the present work.