Dietary intakes assessed by 24-h recalls in peri-urban African adolescents: validity of energy intake compared with estimated energy expenditure

Abstract

Background/Objective: The objective of this study is to determine the relative validity of reported energy intake (EI) derived from multiple 24-h recalls against estimated energy expenditure (EE est ). Basal metabolic rate (BMR) equations and physical activity factors were incorporated to calculate EE est . Subjects/Methods: This analysis was nested in the multidisciplinary PhysicaL Activity in the Young study with a prospective study design. Peri-urban black South African adolescents were investigated in a subsample of 131 learners (87 girls and 44 boys) from the parent study sample of 369 (211 girls and 158 boys) who had all measurements taken. Pearson correlation coefficients and Bland-Altman plots were calculated to identify the most accurate published equations to estimate BMR (Po0.05 statistically significant). EE est was estimated using BMR equations and estimated physical activity factors derived from Previous Day Physical Activity Recall questionnaires. After calculation of EE est , the relative validity of reported energy intake (EI rep ) derived from multiple 24-h recalls was tested for three data subsets using Pearson correlation coefficients. Goldberg's formula identified cut points (CPs) for under and over reporting of EI. Results: Pearson correlation coefficients between calculated BMRs ranged from 0.97 to 0.99. Bland-Altman analyses showed acceptable agreement (two equations for each gender). One equation for each gender was used to calculate EE est . Pearson correlation coefficients between EI rep and EE est for three data sets were weak, indicating poor agreement. CPs for physical activity groups showed under reporting in 87% boys and 95% girls. Conclusion: The 24-h recalls measured at five measurements over 2 years offered poor validity between EI rep and EE est .

Evidence of an Overweight/Obesity Transition among School-Aged Children and Youth in Sub-Saharan Africa: A Systematic Review

“…Of the 96 studies [16]–[18], [20], [24]–[26], [29], [36], [39], [40], [43], [45], [46], [48], [51], [53]–[56], [59]–[61], [63]–[68], [70]–[72], [74], [76]–[80], [83], [85], [86], [89], [91], [92], [95], [96], [98], [103]–[105], [107], [109]–[114], [116]–[120], [123], [124], [126], [128], [129], [132], [133], [135], [136], [140], [143], [147], [149]–[152], [163], [169], [170], [214], [215], [218], [225], [281], [287], [289], [292], …”

Quantitative Ultrasound and Dual X-Ray Absorptiometry as Indicators of Bone Mineral Density in Young Women and Nutritional Factors Affecting It

“…Under or over-reporting is a concern in dietary assessment, however the 13% of possible “under-reporters” in this study (energy intake below calculated expenditure) were considered to have plausible intakes, since research suggests that tertiary students often have poor quality diets [38], experience food insecurity [39,40,41], and that restrictive eating is commonly practised in this age group [42]. Therefore, it was decided not to exclude suspected “under-reporters” from the study [43]. The current study estimated that 4% were over-reporters, which is consistent with that previously reported [24].…”

Analysis Effect of Nutrition Intake on Lung Function of Active Smoker and Non Smoker

“…Based on research by Rothuosen (2012), 24 hours recall method has better performance compare to food report when assesting individual nutrition intake. 24 hours recall is conducted three times since three time measurement can represent individual eating habit for a month (Rankin et al, 2011). Weekend nutrition data taken can indicate macronutrient intake larger than work days (Sun et al, 2010).…”