Diet misreporting can be corrected: confirmation of the association between energy intake and fat-free mass in adolescents

Vainik, Uku; Konstabel, Kenn; Lätt, Evelin; Mäestu, Evelin; Purge, Priit; Jürimäe, Jaak

doi:10.1017/s0007114516003317

Cited by 34 publications

(32 citation statements)

References 60 publications

(122 reference statements)

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“…Similarly, Wang et al (13) found that the association between evening EI and overweight or obesity disappeared after excluding energy misreporters. However, these findings should be interpreted with caution, because evidence suggests that the exclusion of energy misreporters may introduce selection bias (62). Indeed, post hoc analysis of our data found that energymisreporting status was significantly associated with weight status (x 2 = 32.22, P = 0.0002) and 29% of overweight or women compared with 17% of healthy-weight women were classified as energy underreporters.…”

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confidence: 59%

Temporal eating patterns: associations with nutrient intakes, diet quality, and measures of adiposity

Leech

Timperio

Livingstone

et al. 2017

The American Journal of Clinical Nutrition

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Background: Some evidence suggests that higher energy intake (EI) later in the day is associated with poor diet quality and obesity. However, EI at one eating occasion (EO) is also dependent on EI at surrounding EOs. Studies that examine the distribution of EOs across the day are rare. Objective: The aim of this study was to examine associations between temporal eating patterns, nutrient intakes, diet quality, and measures of adiposity in a representative sample of Australian adults. Design: Dietary data from two 24-h recalls collected during the crosssectional 2011-2012 Australian National Nutrition and Physical Activity Survey were analyzed (n = 4544 adults, aged $19 y). Temporal eating patterns, based on the distribution of EOs across the day, were determined by using latent class analysis. Diet quality estimated adherence to healthy eating recommendations and was assessed by using the 2013 Dietary Guidelines Index (DGI). Multivariate regression models assessed associations between temporal eating patterns, nutrient intakes, diet quality, and adiposity (body mass index, waist circumference, weight status, and central weight status). Models were adjusted for potential confounders and energy misreporting. Results: Three patterns, labeled "conventional," "later lunch," and "grazing," were identified. Compared with a "conventional" or "later lunch" pattern, men and women with a "grazing" pattern had lower DGI scores and higher intakes of discretionary (noncore) foods (P , 0.05). Among women, the "grazing" pattern was associated with overweight or obesity (OR: 1.57; 95% CI: 1.15, 2.13) and central overweight or obesity (OR: 1.73; 95% CI: 1.19, 2.50). These associations were attenuated after the exclusion of energy misreporters and adjustment for total EI. Conclusions: This study found that a "grazing" temporal eating pattern was modestly but significantly associated with poorer diet quality and adiposity among women, after adjustment for covariates and energy misreporting. Future research should consider the impact of energy misreporting on the relation between temporal eating patterns and adiposity. This secondary analysis was registered at anzctr.org.au as ACTRN12617001029381.

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confidence: 59%

Temporal eating patterns: associations with nutrient intakes, diet quality, and measures of adiposity

Leech

Timperio

Livingstone

et al. 2017

The American Journal of Clinical Nutrition

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“…These data were not available to us due to the design of the questionnaires used in the study. However, because subjective energy intake is often misreported, adjustment for external predictors such as BMI and physical activity could be a better method than energy intake estimated from FFQs or another subjective dietary assessment method [24,25]. Lastly, we used a self-constructed questionnaire to assess dietary restrictions.…”

Section: Discussionmentioning

confidence: 99%

Self-Reported Dietary Restrictions and Dietary Patterns in Polish Girls: A Short Research Report (GEBaHealth Study)

et al. 2016

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Dietary restraint is a commonly reported practice observed among young females. The practice remains controversial and can be interpreted as a beneficial self-regulating behavior or the opposite, an eating disorder that may have a detrimental effect on health. The aim of this short report was to investigate if dietary restrictions are associated with dietary patterns in a representative sample of Polish girls. Analyses were carried out on data from the Girls’ Eating Behavior and Health (GEBaHealth) study. The sample included 1107 girls, ranging in age from 13 to 21 years old. Restrictions regarding food quantities and selected food groups were assessed using a standardized interview. Dietary patterns were identified with Principal Component Analysis (PCA), based on dietary data collected with Food Frequency Questionnaires (FFQs). Logistic regression analysis was used to study the associations between self-reported restrictions and each dietary pattern. In the total sample, 30.5% of girls reported following some food restrictions. The most common restrictions regarded consumption of sugar and/or sweets (23.7%), high-fat foods (22.4%), and fats (21.3%). Girls who declared following any restrictions, restrictions in food quantity and restrictions in the consumption of sugar and/or sweets, high-fat foods, fats, cereals and/or bread and/or potatoes were more likely to adhere to the “fruit and vegetables” (considered pro-healthy) dietary pattern (adjusted odds ratios (ORs): 1.55, 95% CI: 1.14–2.12; 1.61, 95% CI: 1.17–2.21; 1.81, 95% CI: 1.30–2.52; 1.46, 95% CI: 1.04–2.06; 1.96, 95% CI: 1.38–2.80 and 3.25, 95% CI: 1.97–5.37, respectively), and less likely to adhere to the “fast foods and sweets” (unhealthy) and “traditional Polish” (rather unhealthy) patterns, compared to girls who declared no restrictions. Declared restrictions in the consumption of foods high in sugar, fat, and starch were observed in girls in the “fruit and vegetables” pattern and were uncommon in girls with unhealthy dietary patterns. Although cautious interpretation is needed when considering restrictions in the overall quantity of food consumed, the results indicate that dietary restrictions of sugar, high-fat foods, fats, and starch may be considered predictors of both pro-healthy and unhealthy dietary patterns in the population of Polish girls.

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“…One can then statistically determine whether an individual is likely to be under‐reporting by comparing their energy intake as a multiple of their BMR (Goldberg method); or as a multiple of their estimated energy requirement (EER) . Once these individuals are identified, the bias due to under‐reporting can be addressed by excluding these implausible reporters, although exclusion may lead to selection bias; or by the use of statistical techniques that adjust for total caloric intake, dietary composition, or the energy density of nutrients, for example, by including these variables or predictors of them as control variables in the regression model …”

Section: Introductionmentioning

confidence: 99%

Prevalence and characteristics of energy intake under‐reporting among Australian adults in 1995 and 2011 to 2012

Tam

Veerman

2019

Nutrition & Dietetics

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Aim Misreporting of energy intake is a common source of measurement error found in dietary surveys, resulting in biased estimates and a reduction in statistical power. The present study aims to refine the conventional cut‐off methods and to examine the extent to which Australian adults misreport their energy intake, and the characteristics of under‐reporters between two time points. Methods A revised Goldberg cut‐off approach was used to identify those who reported implausible intake amounts in a secondary analysis of two large cross‐sectional surveys. Identified low energy reporters were then used as the outcome variable in Poisson regressions to examine association with sex, age, body mass index (BMI), weight perceptions, education, relative household income, geographic remoteness and relative socioeconomic disadvantage. Results The prevalence of under‐reporting increased from 32% in 1995 to 41% in 2012, most of which can be attributed to an increase in men. Under‐reporting has a positive association with BMI and relative socioeconomic disadvantage, but an inverse association with age, education, relative household income and residence in inner regional areas. Conclusions Under‐reporting of energy intake is high in Australian adults, and appears have worsened over time in men, which could be partly explained by the upward trend in obesity. The use of conventional Goldberg method to identify under‐reporters can greatly underestimate the prevalence of under‐reporting, future studies should consider selecting a lower critical value to improve accuracy.

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Diet misreporting can be corrected: confirmation of the association between energy intake and fat-free mass in adolescents

Cited by 34 publications

References 60 publications

Temporal eating patterns: associations with nutrient intakes, diet quality, and measures of adiposity

Temporal eating patterns: associations with nutrient intakes, diet quality, and measures of adiposity

Self-Reported Dietary Restrictions and Dietary Patterns in Polish Girls: A Short Research Report (GEBaHealth Study)

Prevalence and characteristics of energy intake under‐reporting among Australian adults in 1995 and 2011 to 2012

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