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The role of under- and overreporting of energy intake in determining the dietary patterns is yet unclear, especially in the Middle Eastern countries. This study identifies the prevalence of misreporting among Tehranian women aged 18-45 years and to compare the dietary intake patterns of plausible and all energy reporters. Dietary intakes and anthropometric data were collected. FitMate metabolic analyzer and Goldberg equation were used in determining the under/overreporting of energy intake. Underreporters were more likely to be overweight and older compared to plausible reporters. Three dietary patterns emerged for all reporters, and two were identified for plausible reporters. Using only plausible reporters to determine dietary patterns was not similar to using all reporters. The proportion of underreporters was 59.3% in the mixture cluster, 30.4% in the unhealthy cluster, and 35.3% in the healthy cluster (p < 0.05). Underreporting of energy intake is not uniformly distributed among dietary pattern clusters and tends to be less severe among subjects in the unhealthy cluster. Our data suggested that misreporting of energy intake might affect the dietary pattern analysis. [ABSTRACT FROM AUTHOR]

The role of under- and overreporting of energy intake in determining the dietary patterns is yet unclear, especially in the Middle Eastern countries. This study identifies the prevalence of misreporting among Tehranian women aged 18-45 years and to compare the dietary intake patterns of plausible and all energy reporters. Dietary intakes and anthropometric data were collected. FitMate™ metabolic analyzer and Goldberg equation were used in determining the under/overreporting of energy intake. Underreporters were more likely to be overweight and older compared to plausible reporters. Three dietary patterns emerged for all reporters, and two were identified for plausible reporters. Using only plausible reporters to determine dietary patterns was not similar to using all reporters. The proportion of underreporters was 59.3% in the mixture cluster, 30.4% in the unhealthy cluster, and 35.3% in the healthy cluster (p<0.05). Underreporting of energy intake is not uniformly distributed among dietary pattern clusters and tends to be less severe among subjects in the unhealthy cluster. Our data suggested that misreporting of energy intake might affect the dietary pattern analysis. [ABSTRACT FROM AUTHOR]

Background: This study assesses the accuracy of energy intake (El) reporting and its relation to anthropometric characteristics and sociodemographic factors. In addition, we attempt to identify foods for which under- or over-reporting is more prevalent. Methods: El was assessed for 187 women using a semi-quantitative 168-item food frequency questionnaire (FFQ). Resting metabolic rate (RMR) was measured with an indirect calorimeter. We calculated the EI/RMR ratio to assess the accuracy of El reporting. This study defined under-reporters as those with an EI/RMR of ≤ 1.34 and over-reporters as those with an EI/RMR of ≥ 2.4. We measured anthropo-metric characteristics and collected sociodemographic information. The chi-square test, ANOVA and multiple linear regressions were used for statistical analyses. Results: Among participants, the under-reporting rate was 35.5% and the over-reporting rate was 7.5%. The EI/RMR ratio was signifi-cantly higher for younger women compared to older women (P < 0.04). Under-reporters had higher weight, waist circumference (WC), body mass index (BMI) and resting metabolism compared to accurate reporters (P< 0.05). Resting metabolism was significantly lower among over-reporters than accurate reporters. After adjusting for energy, the consumption offish, high-fat dairy products, hydrogenated oil, sweets and coffee was lower, whereas consumption of unsaturated oils, tea, salt and yellow vegetables was higher among under-reporters com-pared to accurate reporters. Conclusion: Under-reporting of El is more frequent than over-reporting among Iranian women. Among various factors that may affect the accuracy of El reporting, age and anthropometric characteristics might have a significant effect. [ABSTRACT FROM AUTHOR]

Background: This study assesses the accuracy of energy intake (El) reporting and its relation to anthropometric characteristics and sociodemographic factors. In addition, we attempt to identify foods for which under- or over-reporting is more prevalent. Methods: El was assessed for 187 women using a semi-quantitative 168-item food frequency questionnaire (FFQ). Resting metabolic rate (RMR) was measured with an indirect calorimeter. We calculated the EI/RMR ratio to assess the accuracy of El reporting. This study defined under-reporters as those with an EI/RMR of ≤ 1.34 and over-reporters as those with an EI/RMR of ≥ 2.4. We measured anthropo-metric characteristics and collected sociodemographic information. The chi-square test, ANOVA and multiple linear regressions were used for statistical analyses. Results: Among participants, the under-reporting rate was 35.5% and the over-reporting rate was 7.5%. The EI/RMR ratio was signifi-cantly higher for younger women compared to older women (P < 0.04). Under-reporters had higher weight, waist circumference (WC), body mass index (BMI) and resting metabolism compared to accurate reporters (P< 0.05). Resting metabolism was significantly lower among over-reporters than accurate reporters. After adjusting for energy, the consumption offish, high-fat dairy products, hydrogenated oil, sweets and coffee was lower, whereas consumption of unsaturated oils, tea, salt and yellow vegetables was higher among under-reporters com-pared to accurate reporters. Conclusion: Under-reporting of El is more frequent than over-reporting among Iranian women. Among various factors that may affect the accuracy of El reporting, age and anthropometric characteristics might have a significant effect. [ABSTRACT FROM AUTHOR]

Objectives: To determine the resting metabolic rate (RMR) in a sample of Iranian women, and to evaluate the validity of predictive equations for estimating RMR in normal and obese subjects. Methods: This cross-sectional study was conducted on a total of 187 healthy women aged 18-45 years. Anthropometric data were collected and subjects' RMR was measured by indirect calorimetry for 15 minutes following an overnight fast. RMR was also predicted using various types of formulas based on subjects' height, age, weight or fat-free mass. Body composition was estimated by bioelectric impedance analysis (BIA). Results: Measured RMR (mean ± SD) was found to be 1473 ± 296 kcal/day. The abbreviation formula overestimated RMR, while other formulas underestimated it. Harris-Benedict formula was valid among all BMI categories (normal weight, overweight, obese and morbidly obese). Two Schofield formulas were valid in normal weight, overweight and morbidly obese subjects; and Cunningham formula was valid only among overweight and obese women. Overweight and obese Iranian women had higher RMR in comparison with normal weight subjects (p<0.01); although after age and weight adjustment, the differences were not significant in any of the BMI categories. Conclusions: The Harris-Benedict for mula provides a valid estimation of RMR at the group level in a range of normal-weight to morbidly obese Iranians. However, at the individual level, errors might be so high that using a measured value has to be preferred over an estimated value. [ABSTRACT FROM AUTHOR]

Objectives: To determine the resting metabolic rate (RMR) in a sample of Iranian women, and to evaluate the validity of predictive equations for estimating RMR in normal and obese subjects. Methods: This cross-sectional study was conducted on a total of 187 healthy women aged 18-45 years. Anthropometric data were collected and subjects' RMR was measured by indirect calorimetry for 15 minutes following an overnight fast. RMR was also predicted using various types of formulas based on subjects' height, age, weight or fat-free mass. Body composition was estimated by bioelectric impedance analysis (BIA). Results: Measured RMR (mean ± SD) was found to be 1473 ± 296 kcal/day. The abbreviation formula overestimated RMR, while other formulas underestimated it. Harris-Benedict formula was valid among all BMI categories (normal weight, overweight, obese and morbidly obese). Two Schofield formulas were valid in normal weight, overweight and morbidly obese subjects; and Cunningham formula was valid only among overweight and obese women. Overweight and obese Iranian women had higher RMR in comparison with normal weight subjects (p<0.01); although after age and weight adjustment, the differences were not significant in any of the BMI categories. Conclusions: The Harris-Benedict for mula provides a valid estimation of RMR at the group level in a range of normal-weight to morbidly obese Iranians. However, at the individual level, errors might be so high that using a measured value has to be preferred over an estimated value. [ABSTRACT FROM AUTHOR]