A computational model to determine energy intake during weight loss.
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ABSTRACT: Background
Energy intake (EI) during weight loss is difficult and costly to measure accurately.Objective
The objective was to develop and validate a computational energy balance differential equation model to determine individual EI during weight loss.Design
An algorithm was developed to quantify EI during weight loss based on a validated one-dimensional model for weight change. By using data from a 24-wk calorie-restriction study, we tested the validity of the EI model against 2 criterion measures: 1) EI quantified through food provision from weeks 0-4 and 4-12 and 2) EI quantified through changes in body energy stores [measured with dual-energy X-ray absorptiometry (DXA)] and energy expenditure [measured with doubly labeled water (DLW)] from weeks 4-12 and 12-24.Results
Compared with food provision, the mean (±SD) model errors were 41 ± 118 kcal/d and -22 ± 230 kcal/d from weeks 0-4 and 4-12, respectively. Compared with EI measured with DXA and DLW, the model errors were -71 ± 272 kcal/d and -48 ± 226 kcal/d from weeks 4-12 and 12-24, respectively. In every comparison, the mean error was never significantly different from zero (P values > 0.10). Furthermore, Bland and Altman analysis indicated that error variance did not differ significantly over amounts of EI (P values > 0.26). Almost all individual participants' values were within CI limits.Conclusion
The validity of the newly developed EI model was supported by experimental observations and can be used to determine an individual participant's EI during weight loss.
SUBMITTER: Thomas DM
PROVIDER: S-EPMC2980958 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectiveThis study aimed to determine whether different measures of habitual physical activity (PA) at baseline predict weight change, weight compensation, and changes in energy intake (EI) during a 24-week supervised aerobic exercise intervention.MethodsData from 108 participants (78 women; 48.7 [SD: 11.6] years; BMI 31.4 [SD: 4.6] kg/m2 ), randomly assigned to either the moderate-dose exercise group (8 kcal/kg of body weight per week) or the high-dose exercise group (20 kcal/kg of body weight per week) of the Examination of Mechanisms of Exercise-induced Weight Compensation (E-MECHANIC) trial, were analyzed. Moderate-to-vigorous PA (MVPA), steps per day, and PA energy expenditure (PAEE) were measured with SenseWear armbands (BodyMedia, Pittsburgh, Pennsylvania), and total activity energy expenditure and EI were estimated with doubly labeled water, all over 2 weeks, before and toward the end of the intervention. Multiple linear regression models, adjusted for sex, exercise group, and baseline value of the outcome, were used.ResultsBaseline habitual MVPA levels predicted weight change (β = -0.275; P = 0.020), weight compensation (β = -0.238; P = 0.043), and change in EI (β = -0.318; P = 0.001). Associations between baseline PAEE and outcomes were comparable, whereas steps per day and, importantly, total activity energy expenditure (via doubly labeled water) did not significantly predict change in weight-related outcomes.ConclusionsWhile acknowledging substantial variability in the data, on average, lower baseline habitual MVPA and PAEE levels were associated with less weight loss from exercise, higher compensation, and increased EI.
| S-EPMC7180105 | biostudies-literature
Project description:BackgroundIndividuals with overweight or obesity commonly underreport energy intake (EI), but it is unknown if the tendency to underreport persists in formerly obese individuals who lose significant weight and maintain their weight loss over long periods of time.ObjectiveAssess the accuracy of self-reported EI in successful weight loss maintainers (WLM) compared with controls of normal body weight (NC) and controls with overweight/obesity (OC).MethodsParticipants for this case-controlled study were recruited in 3 groups: WLM [n = 26, BMI (in kg/m2) 24.1 ± 2.3; maintaining ≥13.6 kg weight loss for ≥1 y], NC (n = 33, BMI 22.7 ± 1.9; similar to current BMI of WLM), and OC (n = 32, BMI 34.0 ± 4.6; similar to pre-weight loss BMI of WLM). Total daily energy expenditure (TDEE) was measured over 7 d using the doubly labeled water (DLW) method, and self-reported EI was concurrently measured from 3-d diet diaries. DLW TDEE and self-reported EI were compared to determine accuracy of self-reported EI.ResultsWLM underreported EI (median, interquartile range) (-605, -915 to -314 kcal/d) to a greater degree than NC (-308, -471 to -68 kcal/d; P < 0.01) but not more than OC (-310, -970 to 18 kcal/d; P = 0.21). WLM also showed a greater degree of relative underreporting (-25.3%, -32.9% to -12.5%) compared with NC (-14.3%, -19.6% to -3.1%; P = 0.02) but not OC (-11.2%, -34.1% to -0.7%; P = 0.16). A greater proportion of WLM was classified as underreporters (30.8%) than NC (9.1%; P = 0.05) but not OC (28.1%; P = 1.00).ConclusionsWLM underreported EI in both absolute and relative terms to a greater extent than NC but not OC. These findings call into question the accuracy of self-reported EI in WLM published in previous studies and align with recent data suggesting that WLM rely less on chronic EI restriction and more on high levels of physical activity to maintain weight loss. This trial was registered at clinicaltrials.gov as NCT03422380.
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Project description:BackgroundEstimates of energy intake (EI) in humans have limited validity.ObjectiveThe objective was to test the accuracy and precision of the intake-balance method to estimate EI during weight gain induced by overfeeding.DesignIn 2 studies of controlled overfeeding (1 inpatient study and 1 outpatient study), baseline energy requirements were determined by a doubly labeled water study and caloric titration to weight maintenance. Overfeeding was prescribed as 140% of baseline energy requirements for 56 d. Changes in weight, fat mass (FM), and fat-free mass (FFM) were used to estimate change in energy stores (ΔES). Overfeeding EI was estimated as the sum of baseline energy requirements, thermic effect of food, and ΔES. The estimated overfeeding EI was then compared with the actual EI consumed in the metabolic chamber during the last week of overfeeding.ResultsIn inpatient individuals, calculated EI during overfeeding determined from ΔES in FM and FFM was (mean ± SD) 3461 ± 848 kcal/d, which was not significantly (-29 ± 273 kcal/d or 0.8%; limits of agreement: -564, 505 kcal/d; P = 0.78) different from the actual EI provided (3490 ± 729 kcal/d). Estimated EI determined from ΔES in weight closely estimated actual intake (-7 ± 193 kcal/d or 0.2%; limits of agreement: -386, 370 kcal/d; P = 0.9). In free-living individuals, estimated EI during overfeeding determined from ΔES in FM and FFM was 4123 ± 500 kcal/d and underestimated actual EI (4286 ± 488 kcal/d; -162 ± 301 kcal or 3.8%; limits of agreement: -751, 427 kcal/d; P = 0.003). Estimated EI determined from ΔES in weight also underestimated actual intake (-159 ± 270 kcal/d or 3.7%; limits of agreement: -688, 370 kcal/d; P = 0.001).ConclusionThe intake-balance method can be used to estimate EI during a period of weight gain as a result of 40% overfeeding in individuals who are inpatients or free-living with only a slight underestimate of actual EI by 0.2-3.8%.
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Project description:The classic rule stating that restricting intake by 3500 kcal/wk will lead to a 1-lb/wk rate of weight loss has come under intense scrutiny. Generally not a component of most weight loss prediction models, the "early" rapid weight loss phase may represent a period during which the energy content of weight change (?EC/?W) is low and thus does not follow the classic "rule." The current study tested this hypothesis. Dynamic ?EC/?W changes were examined in 23 Comprehensive Assessment of Long-term Effects of Reducing Intake of Energy Study overweight men and women evaluated by dual-energy x-ray absorptiometry during weight loss at treatment weeks 4 to 24. Changes from baseline in body energy content were estimated from fat and fat-free mass. Repeated-measures analysis of variance was used to determine if ?EC/?W changed significantly over time. The evaluation was expanded with addition of the Kiel 13-week weight loss study of 75 obese men and women to test with adequate power if there are sex differences in ?EC/?W. The analysis of variance CALERIE time effect was significant (P < .001), with post hoc tests indicating that ?EC/?W (kilocalories per kilogram) increased significantly from week 4 (X ± SEM; 4, 858 ± 388) to 6 (6, 041 ± 376, P < .01) and changed insignificantly thereafter; ?EC/?W was significantly larger for Kiel women (6, 804 ± 226) vs men (6, 119 ± 240, P < .05). Sex-specific dynamic relative changes in body composition and related ?EC/?W occur with weight loss initiation that extend for 1 month or more. These observations provide new information for developing energy balance models and further define limitations of the 3500-kcal energy deficit ? 1-lb weight loss rule.
| S-EPMC3810417 | biostudies-literature
Project description:ContextReduced energy expenditure following weight loss is thought to contribute to weight gain. However, the effect of dietary composition on energy expenditure during weight-loss maintenance has not been studied.ObjectiveTo examine the effects of 3 diets differing widely in macronutrient composition and glycemic load on energy expenditure following weight loss.Design, setting, and participantsA controlled 3-way crossover design involving 21 overweight and obese young adults conducted at Children's Hospital Boston and Brigham and Women's Hospital, Boston, Massachusetts, between June 16, 2006, and June 21, 2010, with recruitment by newspaper advertisements and postings.InterventionAfter achieving 10% to 15% weight loss while consuming a run-in diet, participants consumed an isocaloric low-fat diet (60% of energy from carbohydrate, 20% from fat, 20% from protein; high glycemic load), low-glycemic index diet (40% from carbohydrate, 40% from fat, and 20% from protein; moderate glycemic load), and very low-carbohydrate diet (10% from carbohydrate, 60% from fat, and 30% from protein; low glycemic load) in random order, each for 4 weeks.Main outcome measuresPrimary outcome was resting energy expenditure (REE), with secondary outcomes of total energy expenditure (TEE), hormone levels, and metabolic syndrome components.ResultsCompared with the pre-weight-loss baseline, the decrease in REE was greatest with the low-fat diet (mean [95% CI], -205 [-265 to -144] kcal/d), intermediate with the low-glycemic index diet (-166 [-227 to -106] kcal/d), and least with the very low-carbohydrate diet (-138 [-198 to -77] kcal/d; overall P = .03; P for trend by glycemic load = .009). The decrease in TEE showed a similar pattern (mean [95% CI], -423 [-606 to -239] kcal/d; -297 [-479 to -115] kcal/d; and -97 [-281 to 86] kcal/d, respectively; overall P = .003; P for trend by glycemic load < .001). Hormone levels and metabolic syndrome components also varied during weight maintenance by diet (leptin, P < .001; 24-hour urinary cortisol, P = .005; indexes of peripheral [P = .02] and hepatic [P = .03] insulin sensitivity; high-density lipoprotein [HDL] cholesterol, P < .001; non-HDL cholesterol, P < .001; triglycerides, P < .001; plasminogen activator inhibitor 1, P for trend = .04; and C-reactive protein, P for trend = .05), but no consistent favorable pattern emerged.ConclusionAmong overweight and obese young adults compared with pre-weight-loss energy expenditure, isocaloric feeding following 10% to 15% weight loss resulted in decreases in REE and TEE that were greatest with the low-fat diet, intermediate with the low-glycemic index diet, and least with the very low-carbohydrate diet.Trial registrationclinicaltrials.gov Identifier: NCT00315354.
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Project description:High-protein (HP) intake during weight loss (WL) therapy is often recommended because it reduces the loss of lean tissue mass. However, HP intake could have adverse effects on metabolic function, because protein ingestion reduces postprandial insulin sensitivity. In this study, we compared the effects of ?10% WL with a hypocaloric diet containing 0.8 g protein/kg/day and a hypocaloric diet containing 1.2 g protein/kg/day on muscle insulin action in postmenopausal women with obesity. We found that HP intake reduced the WL-induced decline in lean tissue mass by ?45%. However, HP intake also prevented the WL-induced improvements in muscle insulin signaling and insulin-stimulated glucose uptake, as well as the WL-induced adaptations in oxidative stress and cell structural biology pathways. Our data demonstrate that the protein content of a WL diet can have profound effects on metabolic function and underscore the importance of considering dietary macronutrient composition during WL therapy for people with obesity.
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