Representation of adults with class III obesity in studies assessing validity of self-reported energy intake using doubly labeled water: A systematic review.

The measurement of habitual energy intake remains a challenge in nutrition research. High levels of misreporting, particularly among adults with obesity, have been observed when comparing self-reported energy intake to energy expenditure assessed via the doubly labeled water technique. Little is known about misreporting in adults with class III obesity (body mass index ≥40 kg/m2). This systematic review assessed the representation of adults with class III obesity in dietary validation studies and the validity of self-reported dietary energy intake for this group. Studies were included in this review if they: compared self-reported energy intake assessment method(s) to doubly labeled water, had participants ≥18 years old, and included participants with class III obesity. Fifteen studies met these criteria. Of those, eight included information about the number of participants with class III obesity. Out of 1784 participants across eight studies, 63 (3.5%) participants had class III obesity, compared to 9.2% of US adults with class III obesity. Six studies provided data on validity of energy intake assessment for class III obesity, with five of these showing underreporting. Participants with class III obesity are underrepresented in dietary validation studies. Future research should explore the role of weight status on dietary reporting accuracy.

Ultra-processed food intake, gut microbiome, and glucose homeostasis in mid-life adults: Background, design, and methods of a controlled feeding trial.

BACKGROUND: Aging is associated with gut dysbiosis, low-grade inflammation, and increased risk of type 2 diabetes (T2D). Prediabetes, which increases T2D and cardiovascular disease risk, is present in 45-50% of mid-life adults. The gut microbiota may link ultra-processed food (UPF) with inflammation and T2D risk. METHODS: Following a 2-week standardized lead-in diet (59% UPF), adults aged 40-65 years will be randomly assigned to a 6-week diet emphasizing either UPF (81% total energy) or non-UPF (0% total energy). Measurements of insulin sensitivity, 24-h and postprandial glycemic control, gut microbiota composition/function, fecal short chain fatty acids, intestinal inflammation, inflammatory cytokines, and vascular function will be made before and following the 6-week intervention period. Prior to recruitment, menus were developed in order to match UPF and non-UPF conditions based upon relevant dietary factors. Menus were evaluated for palatability and costs, and the commercial additive content of study diets was quantified to explore potential links with outcomes. RESULTS: Overall diet palatability ratings were similar (UPF = 7.6 ± 1.0; Non-UPF = 6.8 ± 1.5; Like Moderately = 7, Like Very Much = 8). Cost analysis (food + labor) of the 2000 kcal menu (7-d average) revealed lower costs for UPF compared to non-UPF diets ($20.97/d and $40.23/d, respectively). Additive exposure assessment of the 2000 kcal UPF diet indicated that soy lecithin (16×/week), citric acid (13×/week), sorbic acid (13×/week), and sodium citrate (12×/week) were the most frequently consumed additives. CONCLUSIONS: Whether UPF consumption impairs glucose homeostasis in mid-life adults is unknown. Findings will address this research gap and contribute information on how UPF consumption may influence T2D development.

Validation of predictive equations to estimate resting metabolic rate of females and males across different activity levels.

OBJECTIVES: Using equations to predict resting metabolic rate (RMR) has yielded different degrees of validity, particularly when sex and different physical activity levels were considered. Therefore, the purpose of the present study was to determine the validity of several different predictive equations to estimate RMR in female and male adults with varying physical activity levels. METHOD: We measured the RMR of 50 adults (26 females and 24 males) evenly distributed through activity levels varying from sedentary to ultra-endurance. Body composition was measured by dual X-ray absorptiometry and physical activity was monitored by accelerometry. Ten equations to predict RMR were applied (using Body Mass [BM]: Harris & Benedict, 1919; Mifflin et al., 1990 [MifflinBM]; Pontzer et al., 2021 [PontzerBM]; Schofield, 1985; FAO/WHO/UNU, 2004; and using Fat-Free Mass (FFM): Cunningham, 1991; Johnstone et al., 2006; Mifflin et al., 1990 [MifflinFFM]; Nelson et al. 1992; Pontzer et al., 2021 [PontzerFFM]). The accuracy of these equations was analyzed, and the effect of sex and physical activity was evaluated using different accuracy metrics. RESULTS: Equations using BM were less accurate for females, and their accuracy was influenced by physical activity and body composition. FFM equations were slightly less accurate for males but there was no obvious effect of physical activity or other sample parameters. PontzerFFM provides higher accuracy than other models independent of the magnitude of RMR, sex, activity levels, and sample characteristics. CONCLUSION: Equations using FFM were more accurate than BM equations in our sample. Future studies are needed to test the accuracy of RMR prediction equations in diverse samples.