The Accuracy of Stated Energy Contents of Reduced-Energy, Commercially Prepared Foods

doi:10.1016/j.jada.2009.10.003

Journal of the American Dietetic Association

Volume 110, Issue 1, January 2010, Pages 116-123

https://doi.org/10.1016/j.jada.2009.10.003 Get rights and content

Abstract

The accuracy of stated energy contents of reduced-energy restaurant foods and frozen meals purchased from supermarkets was evaluated. Measured energy values of 29 quick-serve and sit-down restaurant foods averaged 18% more than stated values, and measured energy values of 10 frozen meals purchased from supermarkets averaged 8% more than originally stated. These differences substantially exceeded laboratory measurement error but did not achieve statistical significance due to considerable variability in the degree of underreporting. Some individual restaurant items contained up to 200% of stated values and, in addition, free side dishes increased provided energy to an average of 245% of stated values for the entrees they accompanied. These findings suggest that stated energy contents of reduced-energy meals obtained from restaurants and supermarkets are not consistently accurate, and in this study averaged more than measured values, especially when free side dishes were taken into account. If widespread, this phenomenon could hamper efforts to self-monitor energy intake to control weight, and could also reduce the potential benefit of recent policy initiatives to disseminate information on food energy content at the point of purchase.

Section snippets

Methods

This study involved measurement of the energy content of 39 commercially prepared restaurant foods and supermarket frozen convenience meals obtained in the Boston, MA, area, and comparison of measured values with nutrition information stated by the vendor or manufacturer. The restaurant chains included in the study were selected as a convenience sample of quick-serve and sit-down restaurant chains with broad distribution throughout the United States who provided information on nutrient contents

Statistical Methods

Although formal statistical methods do not apply to convenience samples, standard statistical tests were employed to summarize the data for exploratory purposes and to suggest directions for future study. Differences in energy content (measured vs stated) were therefore compared by using two-sided t tests of whether the observed mean was within sampling variability of zero. Multifactor analysis of variance was used to examine potential predictors of the percent difference between stated and

Results and Discussion

The energy contents of individual foods are given in the Table, and Figure 1 illustrates percent differences between measured and stated values. On average, restaurant foods contained 18% more energy than stated; however, there was substantial variability in the difference between measured and stated values, and some foods contained twice as much energy as stated. The measured energy content of supermarket-purchased meals was also greater than stated values, by 8%. There was no statistically

Conclusions

Mean measured energy contents of reduced-energy restaurant and supermarket meals in this pilot study exceeded vendor-stated amounts by substantially more than could be accounted for by laboratory measurement error. Although the discrepancies were within acceptable limits based on federal regulations for most packaged and restaurant foods (which are not subject to these federal regulations) some restaurant foods did have measured energy contents that were double those stated by the restaurant,

L. E. Urban is a doctoral degree student, Gerald J. and Dorothy R. Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA.

References (43)

T.A. Wadden et al.
Behavioral treatment of obesity
Endocrinol Metab Clin North Am
(2003)
A.K. Kant et al.
Eating out in America, 1987–2000: Trends and nutritional correlates
Prev Med
(2004)
S. Paeratakul et al.
Fast-food consumption among US adults and children: Dietary and nutrient intake profile
J Am Diet Assoc
(2003)
L.H. Eck Clemens et al.
The effect of eating out on quality of diet in premenopausal women
J Am Diet Assoc
(1999)
J.F. Guthrie et al.
Role of food prepared away from home in the American diet, 1977-78 versus 1994-96: Changes and consequences
J Nutr Educ Behav
(2002)
C.L. Ogden et al.
Prevalence of overweight and obesity in the United States, 1999-2004
JAMA
(2006)
Average daily per capita calories from the US food availability, adjusted for spoilage and other waste
Health, United States, 2007
(2007)
J.M. Jakicic et al.
American College of Sports Medicine position standAppropriate intervention strategies for weight loss and prevention of weight regain for adults
Med Sci Sports Exerc
(2001)
T.A. Wadden et al.
The treatment of obesity: An overview

R.R. Wing et al.

Successful weight loss maintenance

Annu Rev Nutr

(2001)

B. Lin et al.

Away-from-home foods increasingly important to quality of American diet

(1999)

S.A. Bowman et al.

Fast food consumption of US adults: Impact on energy and nutrient intakes and overweight status

J Am Coll Nutr

(2004)

B.H. Lin et al.

Nutritional quality of foods at and away from home

Food Rev

(1997)

Nutrition Labeling of Restaurant Foods, 21 CFR §101.10

(1996)

Guidance for industry: A labeling guide for restaurants and other retail establishments selling away-from-home foods

I. Wolf

Restaurant menu promises buried in fat

Scripps Howard News Service

(May 21, 2008)

J. Hurley et al.

Restaurant confidential Italian restaurant food: Belly-ssimo!

Nutrition Action Healthletter

(2007)

A.D. Root et al.

Meals identified as healthy choices on restaurant menus: An evaluation of accuracy

Int J Food Sci Nutr

(2004)

S. Woo

Push for calories on menus gains

The Wall Street Journal

(June 11, 2008)

Menu Education and Labeling Act (MEAL act), HR 3895, 110th Congress, 2nd Session

(2007)

Cited by (47)

Determination of the chemical compositions of Mexican antojitos and dishes in Mexico City
2023, Journal of Food Composition and Analysis
The gastronomy of Mexico is characterized by its great variety of dishes, some of which are marketed in informal establishments. These foods do not have a nutrition information label because they are not prepackaged, and their chemical composition is unknown. The objective of this study was to determine the chemical composition of Mexican antojitos and comida corrida dishes. A total of 320 samples of 22 Mexican antojitos and 10 comida corrida dishes were collected from 2 neighborhoods from each of 5 municipalities (in the 4 cardinal directions and center) of Mexico City. Each sample was collected and analyzed in duplicate. The analysis included the determination of moisture content, sodium, ash, protein, total fat, crude fiber, and energy value. The carbohydrates content was determined by difference calculations. The mean (standard deviation) of each parameter per serving and per 100 g were estimated. Most of the Mexican antojitos and comida corrida dishes analyzed were shown to be an important source of energy, protein and total fat. The Mexican antojito with the highest average energy (802 ± 314 kcal/portion) and fat value (31.2 ± 13.6 g/portion) was milanesa torta and the highest in sodium was ham torta (1591 ± 792 mg/portion). Most of the Mexican antojitos and comida corrida dishes analyzed provided more than 25 % of the daily sodium intake recommended by the World Health Organization (WHO). Results suggest that a complete comida corrida may provide close to 100 % of the recommended amount of sodium.
Reliability and Validity of Digital Images to Assess Child Dietary Intake in a Quick-Service Restaurant Setting
2023, Journal of the Academy of Nutrition and Dietetics
Citation Excerpt :
In line with previous research,7 the formula was: ([Pre-weight (g) from the QSR − Average weight of leftovers (g)] × kcal/g from the QSR) Energy (kcal) of the leftover food was determined by BC, which is accurate to a mean ± standard deviation (SD) of −1.9 ± 0.3%19,23 and has been used to measure kilocalorie content of QSR leftovers.22 Data came from a separate sub-study within the larger trial.22
Development of methods to accurately measure dietary intake in free-living situations—restaurants or otherwise—is critically needed to understand overall dietary patterns.
This study aimed to develop and test reliability and validity of digital images (DI) for measuring children’s dietary intake in quick-service restaurants (QSRs), validating against weighed plate waste (PW) and bomb calorimetry (BC).
In 2016, cross-sectional data were collected at two time points within a randomized controlled trial assessing children’s leftovers in QSRs from parents of 4- to 12-year-old children.
Parents (n = 640; mean age = 35.9 y; 70.8% female) consented and agreed to provide their child’s PW for digital imaging, across 11 QSRs in Massachusetts in areas with low socioeconomic status and ethnically diverse populations.
Outcome measures were interrater reliability for DIs, correspondence between methods for energy consumed and left over, and correspondence between methods across varying quantities of PW.
Intraclass correlations, percent agreement, Spearman correlations, Wilcoxon signed rank tests, and Bland-Altman plots were used.
Interrater reliability ratings for DIs had substantial intraclass correlations (ICC = 0.94) but not acceptable exact percent agreement (80.2%); DI and PW energy consumed were significantly correlated (r = 0.96, P < 0.001); DI slightly underestimated energy consumed compared with PW (Mdiff = −1.61 kcals, P < 0.001). Bland-Altman plots showed high DI–PW correspondence across various energy amounts and revealed few outliers. Energy left over by BC was highly correlated with DI (r = 0.87, P < 0.001) and PW (r = 0.90, P < 0.001); and mean differences were not significantly different from DI (Mdiff = 9.77 kcal, P = 0.06) or PW (Mdiff = −2.84 kcal, P = 0.20).
Correspondence was high between PW and DI assessments of energy consumed, and high with BC energy left over. Results demonstrate reliability and practical validity of digital images for assessing child meal consumption in QSR settings.
Dietary Energy
2022, Advances in Nutrition
Trends in the Nutrition Profile of Menu Items at Large Burger Chain Restaurants
2020, American Journal of Preventive Medicine
Fast food restaurants, including top burger chains, have reduced calorie content of some menu items in recent years. However, the extent to which the nutrition profile of restaurant menus is changing over time is unknown.
Data from 2,472 food items on the menus of 14 top-earning burger fast food chain restaurants in the U.S., available from 2012 to 2016, were obtained from the MenuStat project and analyzed in 2019. Nutrition Profile Index scores were estimated and used to categorize foods as healthy (≥64 of 100). Generalized linear models examined mean scores and the proportion of healthy menu items among items offered in all years (2012–2016) and items offered in 2012 only compared with items newly introduced in subsequent years.
Overall, <20% of menu items were classified as healthy with no change from 2012 to 2016 (p=0.91). Mean Nutrition Profile Index score was relatively constant across the study period among all food items (≈50 points, p=0.58) and children's menu items (≈56 points, p=0.73). The only notable change in Nutrition Profile Index score or in proportion of healthy items was in the direction of menu items becoming less healthy.
At large chain burger restaurants, most items were unhealthy, and the overall nutrition profile of menus remained unchanged from 2012 to 2016. Future research should examine the nutrition profile of restaurant menus in a larger, more diverse sample of restaurants over a longer timeframe and examine whether results are robust when other measures of nutritional quality are used.
Comparison of Label and Laboratory Sodium Values in Popular Sodium-Contributing Foods in the United States
2019, Journal of the Academy of Nutrition and Dietetics
Citation Excerpt :
Urban and colleagues22 reported 8% to 18% higher mean stated energy in 39 low-energy prepared items in restaurants and supermarkets in Boston, MA, in 2010, but found no statistically significant differences between mean stated and measured energy in 269 restaurant items across three states in 2010. As observed in NDL’s analyses for sodium and related nutrients, Urban and colleagues22 reported considerable variability in discrepancies between declared and laboratory energy values for restaurant foods, although they found that labels tended to underdeclare energy content.22,23 In this study, about one-fifth of the major sodium-contributing foods had absolute differences >20% for sodium content, but it is encouraging that the proportion of foods with ratios >120% for sodium were lower in the present study than in earlier reports or in other countries.38-40
Nutrition labels are important tools for consumers and for supporting public health strategies. Recent, published comparison of label and laboratory sodium values for US foods, and differences by brand type (national or private-label) or source (store or restaurant [fast-food and sit-down]) is unavailable.
The objective was to compare label and laboratory values for sodium and related nutrients (ie, total sugars, total fat, and saturated fat) in popular, sodium-contributing foods, and examine whether there are differences by brand type, and source.
During 2010 to 2014, the Nutrient Data Laboratory of the US Department of Agriculture collected 3,432 samples nationwide of 125 foods, combined one or more samples of the same food (henceforth referred to as composites), and chemically analyzed them. For this comparative post hoc analysis, the Nutrient Data Laboratory linked laboratory values for 1,390 composites (consisting of one or more samples of the same food) of 114 foods to corresponding label or website (restaurant) nutrient values.
Label and laboratory values and their ratio for each composite, for each of the four nutrients (sodium, total fat, total sugars, and saturated fat).
Nutrient Data Laboratory analysis determined the ratio of laboratory to label value for each composite, and categorized them into six groups: ≥141%, 121% to 140%, 101% to 120%, 81% to 100%, 61% to 80%, and ≤60%. For sodium, the Nutrient Data Laboratory analysis determined the distribution of the ratios by food, food category, brand type, and source.
For sodium, 5% of the composites had ratios of laboratory to label values >120% and 14% had ratios ≤80%. Twenty-two percent of private-label brand composites had ratios ≤80%, compared with 12% of national brands. Only 3% of store composites had ratios >120% compared with 11% of restaurant composites. Ratios ≤80% were more prevalent among sit-down restaurants (37%) compared with fast-food restaurants (9%).
This study shows that a majority of label and laboratory values sampled agree and underdeclaration of label values is limited. However, there is some disagreement. Periodic monitoring of the nutrient content of foods through laboratory analyses establishes validity of the food labels and helps identify foods and food categories where the label and laboratory values do not compare well, and hence may need laboratory analyses to support accuracy of food composition data.
Effective National Menu Labeling Requires Accuracy and Enforcement
2018, Journal of the Academy of Nutrition and Dietetics
Citation Excerpt :
Using bomb calorimeters to test the actual energy content in restaurant dishes, Urban and colleagues9 found that 20% of tested samples contained at least 100 calories per portion more than stated, and 10% contained an average of 250 calories more than stated. These researchers also found that low-calorie foods were particularly prone to labeling error, containing on average 18% more calories than stated, with some dishes containing twice the stated calories.8 In a university with contracted food services, Feldman and colleagues13 found >10% average discrepancy between measured and labeled nutrients.

View all citing articles on Scopus

L. E. Urban is a doctoral degree student, Gerald J. and Dorothy R. Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA.

E. Saltzman is chair, Department of Nutritional Sciences, Gerald J. and Dorothy R. Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA.

L. M. Ausman is Saqr bin Mohammed Al Qasimi Professor in International Nutrition, Gerald J. and Dorothy R. Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA.

G. E. Dallal is director, Biostatistics Unit, Energy Metabolism Laboratory, Jean Mayer US Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, Boston, MA.

L. M. Robinson is a research dietitian, Energy Metabolism Laboratory, Jean Mayer US Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, Boston, MA.

S. B. Roberts is director, Energy Metabolism Laboratory, Jean Mayer US Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, Boston, MA.

View full text

ResearchResearch and Professional BriefThe Accuracy of Stated Energy Contents of Reduced-Energy, Commercially Prepared Foods

Abstract

Section snippets

Methods

Statistical Methods

Results and Discussion

Conclusions

Endocrinol Metab Clin North Am

Prev Med

J Am Diet Assoc

J Am Diet Assoc

J Nutr Educ Behav

Prevalence of overweight and obesity in the United States, 1999-2004

JAMA

Average daily per capita calories from the US food availability, adjusted for spoilage and other waste

Health, United States, 2007

American College of Sports Medicine position standAppropriate intervention strategies for weight loss and prevention of weight regain for adults

Med Sci Sports Exerc

The treatment of obesity: An overview