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Jornal de Pediatria

Print version ISSN 0021-7557

J. Pediatr. (Rio J.) vol.86 no.5 Porto Alegre Oct. 2010

http://dx.doi.org/10.1590/S0021-75572010000500008 

ORIGINAL ARTICLE

 

Misreporting of dietary energy intake in adolescents

 

 

Luana C. dos Santos;I Mariana N. Pascoal;II Mauro Fisberg;III Isa de P. Cintra;IV Lígia A. MartiniV

IDoutora, Saúde Pública. Nutricionista. Professora adjunta, Departamento de Enfermagem Materno-Infantil e Saúde Pública, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, MG, Brazil
IINutricionista, Departamento de Enfermagem Materno-Infantil e Saúde Pública, UFMG, Belo Horizonte, MG, Brazil
IIIDoutor, Pediatria. Médico, Professor associado, Centro de Atendimento e Apoio ao Adolescente, Universidade Federal de São Paulo (UNIFESP), São Paulo, SP, Brazil
IVDoutora, Nutrição. Nutricionista. Professora adjunta, Centro de Atendimento e Apoio ao Adolescente, UNIFESP, São Paulo, SP, Brazil
VDoutora, Nutrição. Nutricionista. Professora associada, Departamento de Nutrição, Faculdade de Saúde Pública, Universidade de São Paulo (USP), São Paulo, SP, Brazil

 

 


ABSTRACT

OBJECTIVES: To examine the prevalence of under and overreporting of energy intake in adolescents and their associated factors.
METHODS: Cross-sectional study with 96 postpubertal adolescents (47 normal-weight and 49 obese), mean age of 16.6±1.3 years. Weight and height were measured, and body mass index was calculated. Body composition was assessed by dual energy X-ray absorptiometry. Dietary intake was evaluated by a 3-day dietary record. Biochemical assessment was performed (serum total cholesterol, LDL-cholesterol, HDL-cholesterol, plasma glucose, and insulin). Underreporters reported energy intake < 1.35 x basal metabolic rate (BMR), whereas overreporters reported energy intake > 2.4 x BMR.
RESULTS: Energy intake misreporting (under or overreporting) was identified in 65.6% of adolescents (64.6 and 1% of under and overreporting, respectively). Obese adolescents were 5.0 times more likely to underreport energy intake (95%CI 2.0-12.7) than normal-weight participants. Underreporters showed higher rates of insufficient intake of carbohydrate (19.3 vs. 12.1%, p = 0.046) and lipids (11.3 vs. 0%, p < 0.001) than plausible reporters. Cholesterol intake was also lower in underreporters (p = 0.017). There were no significant differences in body composition and biochemical parameters in relation to misreporting.
CONCLUSIONS: The results obtained demonstrated a high percentage of misreporting of energy intake among adolescents, especially among obese subjects, which suggests that energy-adjusted nutrient intake values should be employed in diet-disease risk analysis in order to contribute to a reduction in errors associated with misreporting.

Keywords: Adolescents, dietary assessment, energy intake, misreporting, underreporting.

 

Correspondence

 

 


 

 

Introduction

Understanding the relationship between diet and health outcomes requires accurate self-reporting of dietary intake. Although misreporting occurs in both directions, underestimation of energy intake is more prevalent.1,2 It is well known from large-scale studies that underreporting is pervasive and associated with body mass index (BMI), female gender, low income, older age, and higher social desirability.2 However, few studies have examined issues regarding the accuracy of dietary intake measurements in an adolescent population.

Adolescence is a transition period that often results in changes in dietary habits, such as higher consumption of sweets and fast food and lower fruit and vegetable intake, as a sign of increasing independence.3,4 Kourlaba et al.5 evaluated 2,118 Greek adolescents and observed that unhealthy dietary behavior was associated with unhealthy lifestyle and increased obesity prevalence.

Adolescent obesity tends to persist into adulthood and is associated with an increase in adult morbidity and mortality, including type 2 diabetes mellitus, cardiovascular, orthopedic and respiratory disease.6 Pearson et al.,7 after monitoring Copenhagen schoolchildren for four years, identified a potential stagnation in the obesity epidemic among children, but a continuing increase among adolescents.

Adolescents' food habits may contribute to misreporting of food intake during dietary assessment, regardless of the method of measurement. Commonly used methods, including 24-hour dietary recall interviews, food frequency questionnaires, and food diaries, are all associated with challenges for an accurate assessment. The magnitude of underreporting varies widely among studies.1,7-9 Thus, the purpose of this study was to examine the prevalence of under and overreporting among obese and normal-weight adolescents and their associated factors.

 

Methods

A cross-sectional study was conducted with normal-weight and obese adolescents. Estimated sample size was 80 participants based on the proposed evaluation period (three months) and service capacity. Adolescents were defined as the target population due to an interest in studying misreporting at this stage of life and the scarcity of similar studies. Subjects were recruited through community service agencies and newspaper advertisements. Those adolescents who met the inclusion criteria (sedentary lifestyle,10 postpubertal according to Tanner stages,11 non-pregnant, and healthy) were invited to participate, and a sample of 96 adolescents was obtained.

Anthropometric measurements of body height and body mass were performed according to standard procedures.12 Body composition (bone mineral and soft tissue mass) was assessed by dual energy X-ray absorptiometry (DXA), Hologic QDR-4500 (Hologic Inc., Waltham, USA). Soft tissue mass was divided into fat mass and lean body mass. Fat mass was determined in the trunk region, arms and legs (both were considered peripheral fat).

The adolescents were then divided into two groups according to BMI-for-age percentiles:13 47 normal-weight (BMI < 85th percentile for age and gender) and 49 obese (BMI > 95th percentile) subjects. The groups were matched for age and gender.

Furthermore, a venous blood sample was obtained after a 12-hour fast to measure triglycerides, total cholesterol, low-density lipoprotein cholesterol (LDL-c), high-density lipoprotein cholesterol (HDL-c), plasma glucose, and insulin. Blood lipids and triacylglycerol were measured by enzymatic colorimetric methods; LDL-c was calculated by the Friedlander equation; serum glucose concentrations were determined using a spectrophotometer UV-1601PC (Shimadzu Corp., Kyoto, Japan); and serum insulin levels were determined with a radioimmunoassay kit (Molecular Research Center, Inc., Cincinnati, USA).

Dietary intake was assessed by a three-day food record obtained over three non-consecutive days. The food record method for evaluation of nutrient intake was used due to its high specificity for describing foods and food preparation methods.14

All subjects were instructed to write down their total daily food intake, in household measures, describing the amount consumed of each food during three non-consecutive days. When subjects returned their records, a dietitian reviewed the records and clarified information with the participants.

Nutrient intake was calculated using NutWin 1.5 software (Universidade Federal de São Paulo, São Paulo, Brazil) and macronutrient distribution was evaluated based on proposed values for this life stage.9

To recognize misreporting a comparison between total energy intake and basal metabolic rate (BMR) was performed for each participant.15 Underreporters reported energy intake < 1.35 x BMR, whereas overreporters reported energy intake > 2.4 x BMR.1,15 BMR was calculated using formulas proposed by FAO/WHO/ONU16 according to the adolescent's age, gender, weight, and height.

All data were analyzed using SPSS 13.0 for Windows (SPSS Inc., Chicago, USA). The Kolmogorov-Smirnov normality test was performed. The Student t test was used to compare means between groups. The chi-square or Fisher's exact test was used to compare proportions. Odds ratio was used to verify the probability of underreporting among participants.

Results were expressed as mean ± standard deviation for continuous data with normal distribution and as median [95% confidence interval (CI)] for other variables. A p value of < 0.05 was considered to be significant.

The study was approved by the Ethics Committee of Universidade de São Paulo (USP) and by the Ethics Committee of Universidade Federal de São Paulo (UNIFESP), Brazil. Written informed consent was obtained from both the parents and adolescents in the study group.

 

Results

A total of 96 postpubertal adolescents (47 normal-weight and 49 obese), mean age of 16.6 (±1.3) years, participated in the study. Mean energy intake of the sample was 1895.2 (±630.3) kcal/day, with no differences between groups (p = 0.881). Percentage distribution of macronutrients was also similar between obese and normal-weight adolescents (p > 0.05) (Table 1).

 


Energy intake misreporting was identified in 65.6% of participants, with a significantly higher frequency among obese adolescents (Table 1). Under and overreporting were observed in 64.6 and 1% of adolescents, respectively.

Since only one adolescent was classified as overreporter, the following analyses considered only underreporting as misreporting, that is, the adolescent classified as overreporter was excluded.

Age (p = 0.182) and gender were not associated with underreporting (p = 0.327). In contrast, obese adolescents were 5.0 times more likely to underreport energy intake (95%CI 2.0-12.7) than normal-weight participants.

Underreporters showed higher rates of insufficient intake of carbohydrate (19.3 vs. 12.1%, p = 0.046) and lipids (11.3 vs. 0%, p < 0.001) than plausible reporters. Protein intake was statistically similar between underreporters and plausible reporters (Figure 1). None of the groups showed excessive protein intake.
 


 

Cholesterol intake was lower in underreporters than in those not underreporting: 174.1 (78.8) mg/day vs. 215.4 (78.5) mg/day, respectively (p = 0.017). Saturated fat intake was also lower in underreporters, although without statistically significant difference: 9.5 (2.8) mg/day vs. 10.7 (2.9) mg/day, p = 0.054.

There were no significant differences in body composition and biochemical parameters between underreporters and plausible reporters (Table 2).

 

Discussion

The results showed high frequency of misreporting among adolescents in this study, especially among obese subjects. Similar to other studies, underreporting was higher than overreporting.1,7

The frequency of underreporters was higher than that observed in studies with adults, probably due to a high participation rate of obese individuals in this study and sample differences between studies. Bazanelli et al.1 evaluated 40 patients treated by peritoneal dialysis and verified that 52.5% of the overall patients studied underreported against 83.3% in the overweight group. Nielsen et al.17 found that, in 309 Danish men, aged 40 to 65 years, 35% underreported.

The few studies found in the literature on underreporting of energy intake among adolescents show diverse results. Lanctot et al.18 evaluated 284 girls, aged 8 to 10 years, and 54.8% of the girls were classified as underreporters. Similarly, Singh et al.19 identified underreporting by 35±20% among girls and boys, aged 12-15 and 12-14 years, respectively. However, Lazarou et al.20 found that 72% of 50 Brazilian adolescents, aged 11-18 years, underreported. The scarce data for this life stage demonstrates the importance of conducting further studies with adolescents.

Gender-related underreporting differences have been reported in the literature. Some authors have identified greater prevalence of underreporting among women.8,9 Differently, in the present study gender was not associated with underreporting (p = 0.327). The small number of men may have contributed to this result.

Likewise, underreporting was not associated with age (p = 0.182), in contrast to other studies.2,9 In adult and elderly populations, compromised dietary intake and health status may offer alternative explanations for underreporting.21 In the present study, the homogeneity of sample, with only postpubertal adolescents, aged 13.3 to 19.8 years, may explain this lack of association.

In this study, underreporting was positively associated with obesity, corroborating the findings by Nielsen et al.17 Overweight appears to be one of the most consistent factors in predicting underreporting of energy intake in nutritional assessment studies, since perceptions of body weight and the desire to lose weight influence how obese individuals report their dietary intake.8,9,22

The underreporters evaluated in this study had lower dietary intake of carbohydrate (p = 0.046), total and saturated fat (p = 0.054), and cholesterol (p = 0.017). Similar results have been reported showing that underreporters have dietary habits that more closely resemble dietary guidelines.8,23 Among female Japanese students, the percentage of energy from carbohydrate was significantly higher, whereas energy from fat and protein was significantly lower among underreporters.24 Probably, these subjects estimated lower energy from potentially socially undesirable food groups (e.g., snacks, sweets, and fried foods) than did plausible reporters.

The present study found 1% of overreporting, and only a few studies have evaluated overreporting of energy intake. Biltoft-Jensen et al.25 identified values similar to those found in the present study. Furthermore, in a study with Danish men aged 40-65 years, Nielsen et al.17 found that 7% were overreporters. Among adults, Bazelmans et al.8 identified that 7.9% of participants overreported. Age differences between samples and different cutoff points for overreporting may explain these results and provide directions for further investigation.

This study has some limitations. First, this is a cross-sectional study and a temporal relationship could not be established between underreporting and its associated factors. Second, we did not have a biomarker of energy intake. However, the validity of using the ratio of energy intake to BMR (EI:BMR) to estimate underreporting has been demonstrated in previous studies. Although our sample is not representative of the population of Brazilian adolescents, it is the only national study evaluating postpubertal adolescents with different nutritional status.

The results obtained demonstrated a high percentage of misreporting of energy intake among adolescents, especially among obese subjects. Underreporting was more prevalent than overreporting, suggesting that energy-adjusted nutrient intake values, according to the nutrient residual model, should be employed in diet-disease risk analysis in order to contribute to a reduction in errors associated with misreporting.

 

Acknowledgments

The authors would like to acknowledge Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) for the research grant.

 

References

1. Bazanelli AP, Kamimura MA, Vasselai P, Draibe SA, Cuppari L. Underreporting of energy intake in peritoneal dialysis patients. J Ren Nutr. 2009.         [ Links ] [Epub ahead of print].

2. Olendzki BC, Ma Y, Hébert JR, Pagoto SL, Merriam PA, Rosal MC, et al. Underreporting of energy intake and associated factors in a Latino population at risk of developing type 2 diabetes. J Am Diet Assoc. 2008;108:1003-8.         [ Links ]

3. Olson AL, Gaffney CA, Lee PW, Starr P. Changing adolescent health behaviors: the healthy teens counseling approach. Am J Prev Med. 2008;35:S359-64.         [ Links ]

4. Boone-Heinonen J, Gordon-Larsen P, Adair LS. Obesogenic clusters: multidimensional adolescent obesity-related behaviors in the U.S. Ann Behav Med. 2008;36:217-30.         [ Links ]

5. Kourlaba G, Panagiotakos DB, Mihas K, Alevizos A, Marayiannis K, Mariolis A, et al. Dietary patterns in relation to socio-economic and lifestyle characteristics among Greek adolescents: a multivariate analysis. Public Healthy Nutr. 2009;12:1366-72.         [ Links ]

6. Mamun AA, O'Callaghan MJ, Cramb SM, Najman JM, Williams GM, Bor W. Childhood behavioral problems predict young adults' BMI and obesity: evidence from a birth cohort study. Obesity (Silver Spring). 2009;17:761-6.         [ Links ]

7. Pearson S, Hansen B, Sorensen TI, Baker JL. Overweight and obesity trends in Copenhagen schoolchildren from 2002 to 2007. Acta Pediatr. 2010.         [ Links ] [Epub ahead of print].

8. Bazelmans C, Matthys C, De Henauw S, Dramaix M, Kornitzer M, De Backer G, et al. Predictors of misreporting in an elderly population: the 'Quality of life after 65' study. Public Health Nutr. 2007;10:185-91.         [ Links ]

9. Yannakoulia M, Panagiotakos DB, Pitsavos C, Bathrellou E, Chrysohoou C, Skoumas Y, et al. Low energy reporting related to lifestyle, clinical, and psychosocial factors in a randomly selected population sample of Greek adults: the ATTICA Study. J Am Coll Nutr. 2007;26:327-33.         [ Links ]

10. Food and Nutrition Boar, Institute of Medicine. Dietary reference intakes for energy, carbohydrate, fiber, fat, fatty acids, cholesterol, protein, and amino acids (macronutrients). Washington, D.C.: National Academy Press; 2006.         [ Links ]

11. Tanner JM. Growth at adolescence. 2nd ed. Oxford: Blackwell; 1962.         [ Links ]

12. Frisancho AR. Anthropometric standards for the assessment of growth and nutritional status. Ann Arbor: The University of Michigan Press; 1993.         [ Links ]

13. de Onis M, Onyango AW, Borghi E, Siyam A, Nishida C, Siekmann J. Development of a WHO growth reference for school-aged children and adolescents. Bull World Health Organ. 2007;85:660-7.         [ Links ]

14. Johnson RK. Dietary intake - how do we measure what people are really eating? Obes Res. 2002;10 Suppl 1: 63S-68S.         [ Links ]

15. Goldberg GR, Black AE, Jebb SA, Cole TJ, Murgatroyd PR, Coward WA, et al. Critical evaluation of energy intake data using fundamental principles of energy physiology: 1. Derivation of cut-off limits to identify under-recording. Eur J Clin Nutr. 1991;45:569-81.         [ Links ]

16. Energy and protein requirements. Report of a joint FAO/WHO/UNU Expert Consultation. World Health Organ Tech Rep Ser. 1985;724:1-206.         [ Links ]

17. Nielsen BM, Nielsen MM, Toubro S, Pederson O, Astrup A, Sorensen TI, et al. Past and current body size affect validity of reported energy intake among middle-age Danish men. J Nutr. 2009;139:2337-43.         [ Links ]

18. Lanctot JQ, Klesges RC, Stockton MB, Klesges LM. Prevalence and characteristics of energy underreporting in African-American girls. Obesity (Silver Spring). 2008;16:1407-12.         [ Links ]

19. Singh R, Martin BR, Hickey Y, Teegarden D, Campbell WW, Craig BA, et al. Comparison of self-reported, measured, metabolized energy intake with total energy expenditure in overweight teens. Am J Clin Nutr. 2009;89:1744-50.         [ Links ]

20. Lazarou VE, Dussin DS, Farhat CP, Navarro F. Subnotificação do consumo alimentar de adolescentes. RBONE. 2007;1:35-49.         [ Links ]

21. Karelis AD, Lavoie ME, Fontaine J, Messier V, Strychar I, Rabasa-Lhoret R, et al. Anthropometric, metabolic, dietary and psychosocial profiles of underreporters of energy intake: a doubly labeled water study among overweight/obese postmenopausal woman - a Montreal Ottawa New Emerging Team Study. Eur J Clin Nutr. 2010;64:68-74.         [ Links ]

22. Bailey RL, Mitchell DC, Miller C, Smiciklas-Wright H. Assessing the effect of underreporting energy intake on dietary patterns and weight status. J Am Diet Assoc. 2007;107:64-71.         [ Links ]

23. Olafsdottir AS, Thorsdottir I, Gunnarsdottir I, Thorgeirsdottir H, Steingrimsdottir L. Comparison of women's diet assessed by FFQs and 24-hour recalls with and without underreporters: associations with biomarkers. Ann Nutr Metab. 2006;50:450-60.         [ Links ]

24. Okubo H, Sasaki S. Underreporting of energy intake among Japanese women aged 18-20 years and its association with reported nutrient and food group intakes. Public Health Nutr. 2004;7:911-7.         [ Links ]

25. Biltoft-Jensen A, Matthiessen J, Rasmussen LB, Fagt S, Groth MV, Hels O. Validation of the Danish 7-day pre-coded food diary among adults: energy intake v. energy expenditure and recording length. Br J Nutr. 2009;102:1838-46.         [ Links ]

 

 

Correspondence:
Luana Caroline dos Santos
Departamento de Enfermagem Materno-Infantil e Saúde Pública
Escola de Enfermagem, Universidade Federal de Minas Gerais
Av. Prof. Alfredo Balena, 190
CEP 30130-100 - Belo Horizonte, MG - Brazil
E-mail: luanacs@enf.ufmg.br

Manuscript submitted Apr 05 2010, accepted for publication Jun 30 2010.

 

 

No conflicts of interest declared concerning the publication of this article.
Suggested citation: dos Santos LC, Pascoal MN, Fisberg M, Cintra IP, Martini LA. Misreporting of dietary energy intake in adolescents. J Pediatr (Rio J). 2010;86(5):400-404.