Monitor Energy Intake Research Articles

Study protocol: prevalence of low energy availability and its relation to health and performance among female football players

Enduring low energy availability (LEA) is associated with several potentially serious physiological and mental conditions. LEA has been found highly prevalent among female elite athletes within endurance sports, thus hampering...

Citrus Flavonoid Effects on Obesity

The increased prevalence of obesity in recent decades has sparked tremendous concern worldwide. Obesity, a chronic disease that increases the risk for a myriad of diseases including diabetes, hypertension, cardiovascular diseases, as well as certain types of cancers, results from a persistent excess of energy intake versus energy expenditure and is characterized by an increase in both adipose cell size and number. Treatments to date consist of medications that cause various adverse side effects. This has led to the recent shift in focus towards investigating natural alternatives to treat obesity. The use of phytochemicals as a safe and natural alternative to treat obesity is under current investigation as citrus flavonoids haven been shown to monitor energy intake versus expenditure, regulate lipid metabolism and adipose tissue, and inhibit amylase function.

Are you Committed Cathy, Reluctant Rita or Negative Nancy? Defining User Personas for a Technology-Based Wrist-Worn Eating Monitor

Self-monitoring of energy intake is a critical element of a successful weight loss plan. However, current methods to monitor energy intake are cumbersome and prone to under reporting. The present study examined how individuals used a new energy intake monitoring tool, the Bite Counter to adjust their eating behavior to a targeted bite limit. Data were collected from 30 female participants examining their compliance with using the device as well as their adherence to eating limits based on bite count. Three distinct compliance personas were developed based on the shared behaviors and traits of device users: Committed Cathy (the rapid adopter, seldom misses tracking eating activities), Reluctant Rita (often forgets device, always has an excuse) and Negative Nancy (will not wear or use the device). These personas will inform future experimenters on how to improve usage instructions in order to increase participant compliance with using technology-based eating behavior monitoring tools.

Detecting Periods of Eating During Free-Living by Tracking Wrist Motion

This paper is motivated by the growing prevalence of obesity, a health problem affecting over 500 million people. Measurements of energy intake are commonly used for the study and treatment of obesity. However, the most widely used tools rely upon self-report and require a considerable manual effort, leading to underreporting of consumption, noncompliance, and discontinued use over the long term. The purpose of this paper is to describe a new method that uses a watch-like configuration of sensors to continuously track wrist motion throughout the day and automatically detect periods of eating. Our method uses the novel idea that meals tend to be preceded and succeeded by the periods of vigorous wrist motion. We describe an algorithm that segments and classifies such periods as eating or noneating activities. We also evaluate our method on a large dataset (43 subjects, 449 total h of data, containing 116 periods of eating) collected during free-living. Our results show an accuracy of 81% for detecting eating at 1-s resolution in comparison to manually marked event logs of periods eating. These results indicate that vigorous wrist motion is a useful indicator for identifying the boundaries of eating activities, and that our method should prove useful in the continued development of body-worn sensor tools for monitoring energy intake.

A New Method for Measuring Meal Intake in Humans via Automated Wrist Motion Tracking

Measuring the energy intake (kcal) of a person in day-to-day life is difficult. The best laboratory tool achieves 95% accuracy on average, while tools used in daily living typically achieve 60-80% accuracy. This paper describes a new method for measuring intake via automated tracking of wrist motion. Our method uses a watch-like device with a micro-electro-mechanical gyroscope to detect and record when an individual has taken a bite of food. Two tests of the accuracy of our device in counting bites found that our method has 94% sensitivity in a controlled meal setting and 86% sensitivity in an uncontrolled meal setting, with one false positive per every 5bites in both settings. Preliminary data from daily living indicates that bites measured by the device are positively related to caloric intake illustrating the potential of the device to monitor energy intake. Future research should seek to further explore the relationship between bites taken and kilocalories consumed to validate the device as an automated measure of energy intake.

Adoption of diet-related self-monitoring behaviors varies by race/ethnicity, education, and baseline binge eating score among overweight-to-obese postmenopausal women in a 12-month dietary weight loss intervention

Recent research has identified self-monitoring behaviors as important strategies for both initial weight loss and weight loss maintenance, but relatively little is known about adopters and nonadopters of these behaviors. To test our hypothesis that key characteristics distinguish adopters from nonadopters, we examined the demographic characteristics and eating behaviors (eg, restrained, uncontrolled, emotional, and binge eating) associated with more frequent compared with less frequent use of these behaviors. Baseline demographic characteristics and eating behaviors as well as 12-month self-monitoring behaviors (ie, self-weighing, food journaling, monitoring energy intake) were assessed in 123 postmenopausal women enrolled in a dietary weight loss intervention. Logistic regression models were used to test associations of self-monitoring use with demographic characteristics and eating behaviors. Nonwhites, compared with non-Hispanic whites, were less likely to monitor energy intake regularly (adjusted odds ratio [OR], 0.36; 95% confidence interval [CI], 0.13-0.97; P < .05), controlling for intervention arm and baseline body mass index. Participants with a college degree or higher education were less likely to self-weigh daily (adjusted OR, 0.30; 95% CI, 0.13-0.67; P < .01) compared with individuals who attended some college or less. Those with higher baseline binge eating scores were less likely to monitor energy intake (adjusted OR, 0.84; 95% CI, 0.73-0.97; P < .01) compared with participants with lower binge eating scores. In summary, use of diet-related self-monitoring behaviors varied by race/ethnicity, education, and binge eating score in postmenopausal women who completed a year-long dietary weight loss intervention. Improved recognition of groups less likely to self-monitor may be helpful in promoting these behaviors in future interventions.

The Comparison of a Technology‐Based System and an In‐Person Behavioral Weight Loss Intervention

The purpose of this study was to compare a technology-based system, an in-person behavioral weight loss intervention, and a combination of both over a 6-month period in overweight adults. Fifty-one subjects (age: 44.2 ± 8.7 years, BMI: 33.7 ± 3.6kg/m(2)) participated in a 6-month behavioral weight loss program and were randomized to one of three groups: standard behavioral weight loss (SBWL), SBWL plus technology-based system (SBWL+TECH), or technology-based system only (TECH). All groups reduced caloric intake and progressively increased moderate intensity physical activity. SBWL and SBWL+TECH attended weekly meetings. SBWL+TECH also received a TECH that included an energy monitoring armband and website to monitor energy intake and expenditure. TECH used the technology system and received monthly telephone calls. Body weight and physical activity were assessed at 0 and 6 months. Retention at 6 months was significantly different (P = 0.005) between groups (SBWL: 53%, SBWL+TECH: 100%, and TECH: 77%). Intent-to-treat (ITT) analysis revealed significant weight losses at 6 months in SBWL+TECH (-8.8 ± 5.0kg, -8.7 ± 4.7%), SBWL (-3.7 ± 5.7kg, -4.1 ± 6.3%), and TECH (-5.8 ± 6.6kg, -6.3 ± 7.1%) (P < 0.001). Self-report physical activity increased significantly in SBWL (473.9 ± 800.7kcal/week), SBWL+TECH (713.9 ± 1,278.8kcal/week), and TECH (1,066.2 ± 1,371kcal/week) (P < 0.001), with no differences between groups (P = 0.25). The TECH used in conjunction with monthly telephone calls, produced similar, if not greater weight losses and changes in physical activity than the standard in-person behavioral program at 6 months. The use of this technology may provide an effective short-term clinical alternative to standard in-person behavioral weight loss interventions, with the longer term effects warranting investigation.

Effects Of Adding A Technology-based System To An In-Person Behavioral Weight Loss Program

With the intention of improving weight outcomes, more behavioral weight loss interventions have added the use of technology. The commercially available GoWear Fit® System (BodyMedia Inc.) includes a multi-sensor armband and display to measure and provide real-time feedback on energy expenditure, and a website to monitor energy intake and daily energy balance. PURPOSE: To examine the influence of adding the GoWear Fit® System to an in-person behavioral program on weight loss in overweight and obese adults. METHODS: Thirty-four overweight and obese (BMI: 33.8 ± 3.6 kg·m-2) adults (age: 43.6 ± 9.2 kg·m-2) participated in a behavioral weight loss intervention and were randomized to one of two groups: standard behavioral weight loss (SBWL) or standard behavioral weight loss plus technology (SBWL+GoWearFit). Energy intake was reduced to 1200-1800 kcal/day based on baseline weight. Exercise was progressed from 100 to 150 min/week. Body weight was measured at 0 and 6 weeks. RESULTS: At 6 weeks, percent weight loss was -2.9±2.2% in SBWL+GoWearFit and -1.5±2.0% in SBWL (p =.07). In SBWL+GoWearFit, the multisensory armband was worn for 16.9±4.7 hours per day. SBWL+GoWearFit logged meals online significantly more days per week (6.5±1.3 days/week) than SBWL tracked meals in paper diaries (5.1±2.8 days/ week) (p <.001). SBWL+GoWearFit also reported more days per week of moderate intensity physical activity of at least 10 minutes per bout (5.1±2.1 days/week) than SBWL (3.2±2.3 days/week) (p <.001). CONCLUSION: The trend for percent weight loss to improve over the initial 6 weeks of a behavioral weight loss program with the addition of the GoWear Fit® System is a promising finding. Moreover, it appears that individuals are willing to wear the multi-sensor armband and use the website provided with the GoWear Fit® System, and this appears to have promising effects on exercise participation and self-monitoring of eating behaviors when compared to the SBWL group during this 6 week period. Long-term evaluation of the GoWear Fit® System is necessary to determine feasibility and effectiveness of this system to improve weight loss in overweight and obese adults. Supported by the University of Pittsburgh Obesity and Nutrition Research Center (NIH P30 DK46204)

The Energetics of Obesity: A Review: Monitoring Energy Intake and Energy Expenditure in Humans

Writing about obesity research is a challenging task. While the rising obesity epidemic drastically raised public awareness of the problem, the causes behind the epidemic are still poorly understood. The etiology of obesity is a subject of ongoing scientific debate with widely varying views and strong opinions. Is it mostly genetic or environmental in nature? Is obesity caused by changes in our diet or changes in lifestyle and physical activity or both? Modern research literature quite often offers conflicting findings. Publications in popular media like the one in Time magazine add to the controversy by making quick and strongly worded summaries of academic research. Although the root causes of obesity remains a topic of active research, this review concentrates on the fundamental components of weight regulation in humans and their relative contribution to the energy equation. A better understanding of the energetics of obesity may provide some insight into the etiology of the obesity epidemic. The energetics of obesity also showcases an engineering challenge: development of techniques to accurately measure individual components of the energy equation.

Monitoring Energy Intake: A Hand-Held Personal Digital Assistant Provides Accuracy Comparable to Written Records

New approaches to assess energy intake (EI) may have advantages over traditional written methods, but validity of these emerging methodologies must be demonstrated. This exploratory study compared EI obtained using a hand-held personal digital assistant (PDA) and traditional written records with total energy expenditure measured by doubly labeled water (TEE DLW). Twenty-six volunteers (aged 23±4 years, body mass index [calculated as kg/m 2] 24±2) participated in a randomized (either PDA or written record group) and matched (for sex, age, and body mass index) study for 7 consecutive days between June 2005 and April 2006 to record EI. Group comparisons were made with t and Mann-Whitney U tests. Bland-Altman plots were used to compare limits of agreement between methods. Volunteers remained weight stable during the study period (0.2±0.8 kg; P>0.05). Reported EI by written record and PDA were similar to TEE DLW; 105% vs 92% of TEE DLW, respectively ( P>0.05). There was a significant relationship between reported EI by PDA and TEE DLW ( r=0.60, P<0.05), but not for written record ( r=0.45, P>0.05). Limits of agreement indicated both written record and PDA had large variability (range 1,394 to −1,472 kcal/day). Findings suggest the bias in using a PDA is similar to that observed when using a written record for estimation of EI in weight-stable volunteers.

Nutrient intakes and physical growth of children with phenylketonuria undergoing nutrition therapy

Objective To evaluate nutrient intakes, plasma phenylalanine (PHE) and tyrosine (TYR) concentrations, and physical growth of children with phenylketonuria undergoing nutrition management. Design Children were fed three different medical foods during a one-year study. Subjects/setting Children were evaluated at baseline and every three months in metabolic clinics. Children’s diets were managed at home. Statistical analyses Intakes of medical foods and nutrients, number of diaries with nutrients <67% and <100% of Recommended Dietary Intakes (RDI), and mean plasma PHE and TYR concentrations were compared among groups using two-way ANOVA. χ-squared test compared the percentage of plasma PHE and TYR concentrations in each group in specific categories. Height and body mass index were plotted against National Center for Health Statistics reference data; means were compared among groups. Tukey’s test compared groups with significant treatment effects. Results Mean intakes of nutrients, except energy by all groups and vitamin B-12 by the Periflex-fed group, met or exceeded RDIs. The oldest children tended to have the highest PHE intakes and plasma PHE concentrations. Mean length or height z score indicated normal linear growth. Mean body mass index z scores at study end suggested many children were overweight. Applications Dietitians should prescribe adequate medical food and encourage children with phenylketonuria to ingest all prescribed daily. Linear growth of children, where mean protein equivalent intakes ranged from 113% to 129% of RDI, was normal, demonstrating the need for a protein intake greater than RDIs when an elemental diet is the primary protein source. Dietitians should prescribe and carefully monitor energy intake, physical activity, and weight.

Energy and water balance during torpor and hydropenia in the pigmy gerbil,Gerbillus pusillus

Under ad lib. food conditions,G. pusillus used 107% of the predicted daily energy expenditure. This increased significantly with water deprivation to 116% of the allometric expected value, thereby reflecting an increase in activity in search of food with high moisture content, a shift to metabolic water for meeting the animal's water requirements and a change in the state of hydration of the animal. Economic water expenditure through efficient kidney concentrating ability, reduced pulmocutaneous evaporation, reduced faecal water loss, and tolerance to haemoconcentration, was sufficient to impart virtual independence of exogenous water. Gerbillus pusillus responded to food shortage by abandoning homeothermy. In doing so, it was able to maintain a fairly stable body mass by monitoring energy intake and ensuring that energy expenditure did not exceed intake. There was no significant difference in energy expenditure between gerbils on a restricted energy intake and ad lib. water and those gerbils on a restricted energy intake and no water. Both these experimental groups were able to maintain a positive water balance, for whilst less metabolic water was available, water loss primarily through evaporation decreased concomittantly with reduced body temperature. In addition, the volume of urine excreted when torpid accounted for approximately 5% of the volume excreted by coenothermic rodents deprived of free water. Urine, although less concentrated than that of non-torpid gerbils deprived of water, was ten times more concentrated than the plasma. Daily torpor, although uniquely suited to energy conservation, is not without cost. A reduced body temperature resulted in a decline in ‘apparent assimilation efficiency’ (AE). It seems therefore that the cost of maintaining an elevated body temperature for the full duration of digestion is impractical. The cost of employing torpor as calculated from the reduced AE of food (0.5 kJ·day−1), was however insignificant in comparison to the savings accured (32.25 kJ·day−1) by the use of torpor.